Publications

<span>The temperature dependence of global photosynthesis and respiration determine land carbon sink strength. While the land sink currently mitigates ~30% of anthropogenic carbon emissions, it is unclear whether this ecosystem service will persist and, more specifically, what hard temperature limits, if any, regulate carbon uptake. Here, we use the largest continuous carbon flux monitoring network to construct the first observationally derived temperature response curves for global land carbon uptake. We show that the mean temperature of the warmest quarter (3-month period) passed the thermal maximum for photosynthesis during the past decade. At higher temperatures, respiration rates continue to rise in contrast to sharply declining rates of photosynthesis. Under business-as-usual emissions, this divergence elicits a near halving of the land sink strength by as early as 2040.</span>

<span>The challenges of restoration in dryland ecosystems are growing due to a rise in anthropogenic disturbance and increasing aridity. Plant functional traits are often used to predict plant performance and can offer a window into potential outcomes of restoration efforts across environmental gradients. We analyzed a database including 15 yr of seeding outcomes across 150 sites on the Colorado Plateau, a cold desert ecoregion in the western United States, and analyzed the independent and interactive effects of functional traits (seed mass, height, and specific leaf area) and local biologically relevant climate variables on seeding success. We predicted that the best models would include an interaction between plant traits and climate, indicating a need to match the right trait value to the right climate conditions to maximize seeding success. Indeed, we found that both plant height and seed size significantly interacted with temperature seasonality, with larger seeds and taller plants performing better in more seasonal environments. We also determined that these trait?environment patterns are not influenced by whether a species is native or nonnative. Our results inform the selection of seed mixes for restoring areas with specific climatic conditions, while also demonstrating the strong influence of temperature seasonality on seeding success in the Colorado Plateau region.</span>

<span>Microbial activity increases after rewetting dry soil, resulting in a pulse of carbon mineralization and nutrient availability. The biogeochemical responses to wet-up are reasonably well understood and known to be microbially mediated. Yet, the population level dynamics, and the resulting changes in microbial community patterns, are not well understood as ecological phenomena. Here, we used sequencing of 16S rRNA genes coupled with heavy water (H218O) DNA quantitative stable isotope probing to estimate population-specific rates of growth and mortality in response to a simulated wet-up event in a California annual grassland soil. Bacterial growth and mortality responded rapidly to wet-up, within 3 h, and continued throughout the 168 h incubation, with patterns of sequential growth observed at the phylum level. Of the 37 phyla detected in the prewet community, growth was found in 18 phyla while mortality was measured in 26 phyla. Rapid growth and mortality rates were measurable within 3 h of wet-up but had contrasting characteristics; growth at 3 h was dominated by select taxa within the Proteobacteria and Firmicutes, whereas mortality was taxonomically widespread. Furthermore, across the community, mortality exhibited density-independence, consistent with the indiscriminate shock resulting from dry-down and wet-up, whereas growth was density-dependent, consistent with control by competition or predation. Total aggregated growth across the community was highly correlated with total soil CO2 production. Together, these results illustrate how previously “invisible” population responses can translate quantitatively to emergent observations of ecosystem-scale biogeochemistry.</span>

<span>Forests absorb a large fraction of anthropogenic CO2 emission, but their ability to continue to act as a sink under climate change depends in part on plant species undergoing rapid adaptation. Yet models of forest response to climate change currently ignore local adaptation as a response mechanism. Thus, considering the evolution of intraspecific trait variation is necessary for reliable, long-term species and climate projections. Here, we combine ecophysiology and predictive climate modeling with analyses of genomic variation to determine whether sugar and starch storage, energy reserves for trees under extreme conditions, have the heritable variation and genetic diversity necessary to evolve in response to climate change within populations of black cottonwood (Populus trichocarpa). Despite current patterns of local adaptation and extensive range-wide heritable variation in storage, we demonstrate that adaptive evolution in response to climate change will be limited by a lack of heritable variation within northern populations and by a need for extreme genetic changes in southern populations. Our method can help design more targeted species management interventions and highlights the power of using genomic tools in ecological prediction to scale from molecular to regional processes to determine the ability of a species to respond to future climates.</span>

<span>Globally, soils store two to three times as much carbon as currently resides in the atmosphere, and it is critical to understand how soil greenhouse gas (GHG) emissions and uptake will respond to ongoing climate change. In particular, the soil-to-atmosphere CO2 flux, commonly though imprecisely termed soil respiration (RS), is one of the largest carbon fluxes in the Earth system. An increasing number of high-frequency RS measurements (typically, from an automated system with hourly sampling) have been made over the last two decades; an increasing number of methane measurements are being made with such systems as well. Such high frequency data are an invaluable resource for understanding GHG fluxes, but lack a central database or repository. Here we describe the lightweight, open-source COSORE (COntinuous SOil REspiration) database and software, that focuses on automated, continuous and long-term GHG flux datasets, and is intended to serve as a community resource for earth sciences, climate change syntheses and model evaluation. Contributed datasets are mapped to a single, consistent standard, with metadata on contributors, geographic location, measurement conditions and ancillary data. The design emphasizes the importance of reproducibility, scientific transparency and open access to data. While being oriented towards continuously measured RS, the database design accommodates other soil-atmosphere measurements (e.g. ecosystem respiration, chamber-measured net ecosystem exchange, methane fluxes) as well as experimental treatments (heterotrophic only, etc.). We give brief examples of the types of analyses possible using this new community resource and describe its accompanying R software package.</span>

<span>Effects of riparian vegetation on fluvial sediment dynamics depend on morphological traits of the constituent species. Determining the effects of different morphological guilds on sedimentation rates, as influenced by multiple aspects of dam operations, can help identify viable strategies for streamflow and vegetation management to achieve riparian resource goals. Plants of increasing size and branching density or complexity have been found to have greater effects on sedimentation in free-flowing systems; however, this relationship could differ in regulated rivers. We tested the hypothesis that plant guilds of increasing height and branching complexity would be positively associated with sedimentation rates on 23 sandbars deposited in zones of recirculating flow (eddies) along the Colorado River in Grand Canyon. We used an image-based vegetation classification and digital elevation models from annual topographic surveys to track associations between six plant morphological guilds and topographic change over 5?years. Vegetation had significant associations with deposition after accounting for geomorphic setting, but the ordinal guild scale was not positively correlated with deposition magnitude. Instead, low-statured rhizomatous and herbaceous guilds were particularly effective at capturing sediment in the separation zone of sandbars, whereas tall herbs and large shrubs were most effective at capturing sediment in reattachment zones. These nuanced interactions between geomorphic position and morphological guild may be a direct consequence of flow regulation through modifications to physical deposition and erosion processes. Flow regulation may also select for a narrow subset of morphological guilds, reducing the diversity of vegetation feedbacks on sedimentation and emphasizing geomorphic drivers.</span>

<span>Climate warming is widely expected to affect rice yields, but results are equivocal and variation in rice cropping systems and climatic conditions complicates country-scale yield assessments. Here we show, through meta–analysis of field warming experiments, that yield responses to warming differ strongly between China's rice cropping systems. Whereas warming increases yields in “single rice” systems, it decreases yields in “middle rice” systems and has contrasting effects for early and late rice in “double rice” systems. We further show that the contribution of these cropping systems to China's total rice production has shifted dramatically over recent decades. We estimate that if the present structure of rice cropping systems persists, warming will reduce China's total rice production by 5.0% in 2060. However, if the recent decline in the area of double rice systems continues, China's rice production may decrease by 13.5%. Our results underline the need for maintaining the current area of China's “double rice” cropping system and for technological innovations in multiple rice cropping systems to ensure food security in a warming climate.</span>

<span>Climate warming affects soil carbon (C) dynamics, with possible serious consequences for soil C stocks and atmospheric CO2 concentrations. However, the mechanisms underlying changes in soil C storage are not well understood, hampering long-term predictions of climate C-feedbacks. The activity of the extracellular enzymes ligninase and cellulase can be used to track changes in the predominant C sources of soil microbes and can thus provide mechanistic insights into soil C loss pathways. Here we show, using meta-analysis, that reductions in soil C stocks with warming are associated with increased ratios of ligninase to cellulase activity. Furthermore, whereas long-term (≥5 years) warming reduced the soil recalcitrant C pool by 14%, short-term warming had no significant effect. Together, these results suggest that warming stimulates microbial utilization of recalcitrant C pools, possibly exacerbating long-term climate-C feedbacks.</span>

<span>Increased human-derived nitrogen (N) deposition to terrestrial ecosystems has resulted in widespread phosphorus (P) limitation of net primary productivity. However, it remains unclear if and how N-induced P limitation varies over time. Soil extracellular phosphatases catalyze the hydrolysis of P from soil organic matter, an important adaptive mechanism for ecosystems to cope with N-induced P limitation. Here we show, using a meta-analysis of 140 studies and 668 observations worldwide, that N stimulation of soil phosphatase activity diminishes over time. Whereas short-term N loading (≤5 years) significantly increased soil phosphatase activity by 28%, long-term N loading had no significant effect. Nitrogen loading did not affect soil available P and total P content in either short- or long-term studies. Together, these results suggest that N-induced P limitation in ecosystems is alleviated in the long-term through the initial stimulation of soil phosphatase activity, thereby securing P supply to support plant growth. Our results suggest that increases in terrestrial carbon uptake due to ongoing anthropogenic N loading may be greater than previously thought.</span>

<span>The addition of glucose to soil has long been used to study the metabolic activity of microbes in soil; however, the response of the microbial ecophysiology remains poorly characterized. To address this, we sequenced the metagenomes and metatranscriptomes of glucose-amended soil microbial communities in a laboratory incubation.</span>

<span>Multiple lines of evidence have demonstrated the persistence of global land carbon (C) sink during the past several decades. However, both annual net ecosystem productivity (NEP) and its inter-annual variation (IAV</span><span class="inline-formula">_NEP</span><span>) keep varying over space. Thus, identifying local indicators for the spatially varying NEP and IAV</span><span class="inline-formula">_NEP</span><span> is critical for locating the major and sustainable C sinks on land. Here, based on daily NEP observations from FLUXNET sites and large-scale estimates from an atmospheric-inversion product, we found a robust logarithmic correlation between annual NEP and seasonal carbon uptake–release ratio (i.e. </span><span class="inline-formula"><i>U</i> ∕ <i>R</i></span><span>). The cross-site variation in mean annual NEP could be logarithmically indicated by </span><span class="inline-formula"><i>U</i> ∕ <i>R</i></span><span>, while the spatial distribution of IAV</span><span class="inline-formula">_NEP</span><span> was associated with the slope (i.e. </span><span class="inline-formula"><i>β</i></span><span>) of the logarithmic correlation between annual NEP and </span><span class="inline-formula"><i>U</i> ∕ <i>R</i></span><span>. Among biomes, for example, forests and croplands had the largest </span><span class="inline-formula"><i>U</i> ∕ <i>R</i></span><span> ratio (1.06 </span><span class="inline-formula">±</span><span> 0.83) and </span><span class="inline-formula"><i>β</i></span><span> (473 </span><span class="inline-formula">±</span><span> 112 g C m</span><span class="inline-formula">⁻²</span><span> yr</span><span class="inline-formula">⁻¹</span><span>), indicating the highest NEP and IAV</span><span class="inline-formula">_NEP</span><span> in forests and croplands, respectively. We further showed that these two simple indicators could directly infer the spatial variations in NEP and IAV</span><span class="inline-formula">_NEP</span><span> in global gridded NEP products. Overall, this study provides two simple local indicators for the intricate spatial variations in the strength and stability of land C sinks. These indicators could be helpful for locating the persistent terrestrial C sinks and provide valuable constraints for improving the simulation of land–atmospheric C exchanges.</span>

<span>Climate change is altering disturbance regimes outside historical norms, which can impact biodiversity by selecting for plants with particular traits. The relative impact of disturbance characteristics on plant traits and community structure may be mediated by environmental gradients. We aimed to understand how wildfire impacted understory plant communities and plant regeneration strategies along gradients of environmental conditions and wildfire characteristics in boreal forests. We established 207 plots (60?m2) in recently burned stands and 133 plots in mature stands with no recent fire history in comparable gradients of stand type, site moisture (drainage) and soil organic layer (SOL) depth in two ecozones in Canada's Northwest Territories. At each plot, we recorded all vascular plant taxa in the understory and measured the regeneration strategy (seeder, resprouter, survivor) in burned plots, along with seedbed conditions (mineral soil and bryophyte cover). Dispersal, longevity and growth form traits were determined for each taxon. Fire characteristics measured included proportion of pre-fire SOL combusted (fire severity), date of burn (fire seasonality) and pre-fire stand age (time following fire). Results showed understory community composition was altered by fire. However, burned and mature stands had similar plant communities in wet sites with deep SOL. In the burned plots, regeneration strategies were determined by fire severity, drainage and pre- and post-fire SOL depth. Resprouters were more common in wet sites with deeper SOL and lower fire severity, while seeders were associated with drier sites with thinner SOL and greater fire severity. This led to drier burned stands being compositionally different from their mature counterparts and seedbed conditions were important. Our study highlights the importance of environment?wildfire interactions in shaping plant regeneration strategies and patterns of understory plant community structure across landscapes, and the overriding importance of SOL depth and site drainage in mediating fire severity, plant regeneration and community structure.</span>

<span>Boreal wildfires are increasing in intensity, extent, and frequency, potentially intensifying carbon emissions and transitioning the region from a globally significant carbon sink to a source. The productive southern boreal forests of central Canada already experience relatively high frequencies of fire, and as such may serve as an analog of future carbon dynamics for more northern forests. Fire?carbon dynamics in southern boreal systems are relatively understudied, with limited investigation into the drivers of pre-fire carbon stocks or subsequent combustion. As part of NASA's Arctic-Boreal Vulnerability Experiment, we sampled 79 stands (47 burned, 32 unburned) throughout central Saskatchewan to characterize above- and belowground carbon stocks and combustion rates in relation to historical land use, vegetation characteristics, and geophysical attributes. We found southern boreal forests emitted an average of 3.3 ± 1.1 kg C/m2 from field sites. The emissions from southern boreal stands varied as a function of stand age, fire weather conditions, ecozone, and soil moisture class. Sites affected by historical timber harvesting had greater combustion rates due to faster carbon stock recovery rates than sites recovering from wildfire events, indicating that different boreal forest land use practices can generate divergent carbon legacy effects. We estimate the 2015 fire season in Saskatchewan emitted a total of 36.3 ± 15.0 Tg C, emphasizing the importance of southern boreal fires for regional carbon budgets. Using the southern boreal as an analog, the northern boreal may undergo fundamental shifts in forest structure and carbon dynamics, becoming dominated by stands &lt;70 years old that hold 2?7 kg C/m2 less than current mature northern boreal stands. Our latitudinal approach reinforces previous studies showing that northern boreal stands are at a high risk of holding less carbon under changing disturbance conditions.</span>

<span>It is well-known that global warming has effects on high-latitude tundra underlain with permafrost. This leads to a severe concern that decomposition of soil organic carbon (SOC) previously stored in this region, which accounts for about 50% of the world’s SOC storage, will cause positive feedback that accelerates climate warming. We have previously shown that short-term warming (1.5 years) stimulates rapid, microbe-mediated decomposition of tundra soil carbon without affecting the composition of the soil microbial community (based on the depth of 42684 sequence reads of 16S rRNA gene amplicons per 3 g of soil sample).</span>

<span>One major source of uncertainties in the estimation of soil organic carbon (SOC) dynamics is carbon (C) residence time, an important parameter in terrestrial ecosystem C cycling models. To better predict terrestrial dynamics, C residence time and its controlling factors need to be well quantified and investigated. In this study, we applied a data assimilation approach to quantify the residence times of different soil C pools on the Tibetan Plateau, based on incubated soil carbon dioxide (CO2) efflux data. We also assessed the effects of soil properties on C residence times. Our results showed that the residence times of active (RTA) and slow (RTS) C pools were well estimated through data assimilation. Soil physical, chemical, and microbial properties significantly regulated RTA and RTS. The RTA was higher in soils with high clay contents (R2 = 0.52, p &lt; 0.01) and low microbial quotients (qMB) (R2 = 0.55, p &lt; 0.01), whereas, the RTS was higher in soils with high clay contents (R2 = 0.76, p &lt; 0.01), high C:N ratios (R2 = 0.44, p &lt; 0.05), low qMBvalues (R2 = 0.50, p &lt; 0.05), and low soil pH values (R2 = 0.80, p &lt; 0.01). Structural equation modeling (SEM) analyses indicated that the model could explain 55% and 91% of the variations in the RTA and RTS, respectively. The qMB was the key factor in regulating the RTA, while soil pH was the crucial variable in controlling the RTS. These results demonstrated that the major controlling factors on the RTA and RTS were different. Considering these variables and their different controls on residence times of different soil C pools could provide more accurate estimation of terrestrial C cycles, and prediction of future C-climate feedbacks.</span>

<span>Non-structural carbohydrates (NSCs) are necessary for plant growth and affected by plant water status, but the temporal dynamics of water stress impacts on NSC are not well understood. We evaluated how seasonal NSC concentrations varied with plant water status (predawn xylem water potential, ) and air temperature (T) in the evergreen desert shrub Larrea tridentata. Aboveground sugar and starch concentrations were measured weekly or monthly for ~1.5 years on 6 -12 shrubs simultaneously instrumented with automated stem psychrometers; leaf photosynthesis (Anet) was measured monthly for 1 year. Leaf sugar increased during the dry, premonsoon period, associated with lower  (greater water stress) and high T. Leaf sugar accumulation coincided with declines in leaf starch and stem sugar, suggesting the prioritization of leaf sugar during low photosynthetic uptake. Leaf starch was strongly correlated with Anet and peaked during the spring and monsoon seasons, while stem starch remained relatively constant except for depletion during the monsoon. Recent photosynthate appeared sufficient to support spring growth, while monsoon growth required the remobilization of stem starch reserves. The coordinated responses of different NSC fractions to water status, photosynthesis, and growth demands suggest that NSCs serve multiple functions under extreme environmental conditions, including severe drought.</span>

Plant species are characterized along a spectrum of isohydry to anisohydry depending on their regulation of water potential (?), but the plasticity of hydraulic strategies is largely unknown. The role of environmental drivers was evaluated in the hydraulic behavior of Larrea tridentata, a drought-tolerant desert shrub that withstands a wide range of environmental conditions. With a 1.5 yr time-series of 2324 in situ measurements of daily predawn and midday ?, the temporal variability of hydraulic behavior was explored in relation to soil water supply, atmospheric demand and temperature. Hydraulic behavior in Larrea was highly dynamic, ranging from partial isohydry to extreme anisohydry. Larrea exhibited extreme anisohydry under wet soil conditions corresponding to periods of high productivity, whereas partial isohydry was exhibited after prolonged dry or cold conditions, when productivity was low. Environmental conditions can strongly influence plant hydraulic behavior at relatively fast timescales, which enhances our understanding of plant drought responses. Although species may exhibit a dominant hydraulic behavior, variable environmental conditions can prompt plasticity in ? regulation, particularly for species in seasonally dry climates.

Pinyon-juniper (PJ) plant communities cover a large area across North America and provide critical habitat for wildlife, biodiversity and ecosystem functions, and rich cultural resources. These communities occur across a variety of environmental gradients, disturbance regimes, structural conditions and species compositions, including three species of juniper and two species of pinyon. PJ communities have experienced substantial changes in recent decades and identifying appropriate management strategies for these diverse communities is a growing challenge. Here, we surveyed the literature and compiled 441 studies to characterize patterns in research on PJ communities through time, across geographic space and climatic conditions, and among focal species. We evaluate the state of knowledge for three focal topics: 1) historical stand dynamics and responses to disturbance, 2) land management actions and their effects, and 3) potential future responses to changing climate. We identified large and potentially important gaps in our understanding of pinyon-juniper communities both geographically and topically. The effect of drought on Pinus edulis, the pinyon pine species in eastern PJ communities was frequently addressed, while few studies focused on drought effects on Pinus monophylla, which occurs in western PJ communities. The largest proportion of studies that examined land management actions only measured their effects for one year. Grazing was a common land-use across the geographic range of PJ communities yet was rarely studied. We found only 39 studies that had information on the impacts of anthropogenic climate change and most were concentrated on Pinus edulis. These results provide a synthetic perspective on PJ communities that can help natural resource managers identify relevant knowledge needed for decision-making and researchers design new studies to fill important knowledge gaps.

<span>We conducted a large-scale, multiple-year study in harvested areas of Douglas-fir (Pseudotsuga menziesii [Mirbel] Franco) forests in western Washington, examining the effectiveness of control methods on the widespread invasive shrub Scotch broom [Cytisus scoparius (L.) Link]. We tested both chemical and physical control methods, using three different approaches that are management relevant: (1) triclopyr, a POST herbicide, at different times of year and on different-sized plants; (2) cutting (or brushcutting) of mature individuals; and (3) scarification of soil surface to remove seedlings once versus multiple times. We measured initial mortality, seed germination, and percent cover of C. scoparius in plots for 3 yr following treatments. Triclopyr treatment resulted in greater mortality and reduced percent cover compared with all other treatments with the effect persisting for 2 yr after spraying. Further, triclopyr had the same effect on C. scoparius cover and mortality irrespective of time of year applied. Similar to soil scarification, triclopyr treatments resulted in a flush of seedlings, suggesting that removal of conspecific competitors and not soil disturbance per se promotes seed germination. Brushcutting was generally effective in reducing C. scoparius cover in the short term, but effects did not persist as long as triclopyr treatments, in part due to large differences in stump resprouting rates across sites. Soil scarification to remove seedlings, even over multiple years, did not result in reduced C. scoparius cover. Triclopyr is an effective approach for controlling both emerging and established stands of C. scoparius.</span>

<span>Our aim is to use elevational gradients to quantify the relationship between temperature and ecosystem functioning. Ecosystem functions such as decomposition, nutrient cycling and carbon storage are linked with the amount of microbial biomass in the soil. Previous studies have shown variable relationships between elevation and soil microbial biomass (SMB). Understanding the biological mechanisms linking SMB with elevational gradients will shed light on the environmental impacts of global warming. Location Global. Time period 2002?2018. Major taxa studied Soil microbes. Method We performed a global meta-analysis of the relationships between SMB and elevation. Data were collected from 59 studies of 73 elevational transects from around the world. Results We found no consistent global relationship between SMB and elevation. SMB increased significantly with elevation in the tropics and subtropics, but not in other climate zones. However, we found consistent positive relationships between SMB, soil organic carbon and total nitrogen concentrations. Main conclusions Our results suggest that global warming will impact tropical and subtropical ecosystems more severely than colder regions. Tropical ecosystems, already at risk from species extinctions, will likely experience declines in SMB as the climate warms, resulting in losses of fundamental ecosystem functions such as nutrient cycling and carbon storage.</span>

<span>As Arctic soils warm, thawed permafrost releases nitrogen (N) that could stimulate plant productivity and thus offset soil carbon losses from tundra ecosystems. Although mycorrhizal fungi could facilitate plant access to permafrost-derived N, their exploration capacity beyond host plant root systems into deep, cold active layer soils adjacent to the permafrost table is unknown. We characterized root-associated fungi (RAF) that colonized ericoid (ERM) and ectomycorrhizal (ECM) shrub roots and occurred below the maximum rooting depth in permafrost thaw-front soil in tussock and shrub tundra communities. We explored the relationships between root and thaw front fungal composition and plant uptake of a 15N tracer applied at the permafrost boundary. We show that ERM and ECM shrubs associate with RAF at the thaw front providing evidence for potential mycelial connectivity between roots and the permafrost boundary. Among shrubs and tundra communities, RAF connectivity to the thaw boundary was ubiquitous. The occurrence of particular RAF in both roots and thaw front soil was positively correlated with 15N recovered in shrub biomass Taxon-specific RAF associations could be a mechanism for the vertical redistribution of deep, permafrost-derived nutrients, which may alleviate N limitation and stimulate productivity in warming tundra.</span>

<span>Phosphorus (P) limitation of aboveground plant production is usually assumed to occur in tropical regions but rarely elsewhere. Here we report that such P limitation is more widespread and much stronger than previously estimated. In our global meta-analysis, almost half (46.2%) of 652 P-addition field experiments reveal a significant P limitation on aboveground plant production. Globally, P additions increase aboveground plant production by 34.9% in natural terrestrial ecosystems, which is 7.0–15.9% higher than previously suggested. In croplands, by contrast, P additions increase aboveground plant production by only 13.9%, probably because of historical fertilizations. The magnitude of P limitation also differs among climate zones and regions, and is driven by climate, ecosystem properties, and fertilization regimes. In addition to confirming that P limitation is widespread in tropical regions, our study demonstrates that P limitation often occurs in other regions. This suggests that previous studies have underestimated the importance of altered P supply on aboveground plant production in natural terrestrial ecosystems.</span>

Plants are thought to be limited by phosphorus (P) especially in tropical regions. Here, Hou et al. report a meta-analysis of P fertilization experiments to show widespread P limitation on plant growth across terrestrial ecosystems modulated by climate, ecosystem properties, and fertilization regimes

<span>Through agriculture and industry, humans are increasing the deposition and availability of nitrogen (N) in ecosystems worldwide. Carbon (C) isotope tracers provide useful insights into soil C dynamics, as they allow to study soil C pools of different ages. We evaluated to what extent N enrichment affects soil C dynamics in experiments that applied C isotope tracers.</span>

<span>Nitrogen (N2)-fixing moss microbial communities play key roles in nitrogen cycling of boreal forests. Forest type and leaf litter inputs regulate moss abundance, but how they control moss microbiomes and N2-fixation remains understudied. We examined the impacts of forest type and broadleaf litter on microbial community composition and N2-fixation rates of Hylocomium splendens and Pleurozium schreberi. We conducted a moss transplant and leaf litter manipulation experiment at three sites with paired paper birch (Betula neoalaskana) and black spruce (Picea mariana) stands in Alaska. We characterized bacterial communities using marker gene sequencing, determined N2-fixation rates using stable isotopes (15N2) and measured environmental covariates. Mosses native to and transplanted into spruce stands supported generally higher N2-fixation and distinct microbial communities compared to similar treatments in birch stands. High leaf litter inputs shifted microbial community composition for both moss species and reduced N2-fixation rates for H. splendens, which had the highest rates. N2-fixation was positively associated with several bacterial taxa, including cyanobacteria. The moss microbiome and environmental conditions controlled N2-fixation at the stand and transplant scales. Predicted shifts from spruce- to deciduous-dominated stands will interact with the relative abundances of mosses supporting different microbiomes and N2-fixation rates, which could affect stand-level N inputs.</span>

<span>Organic matter input to soils can accelerate the decomposition of native soil carbon (C), a process called the priming effect. Priming is ubiquitous and exhibits some consistent patterns, but a general explanation remains elusive, in part because of variation in the response across different ecosystems, and because of a diversity of proposed mechanisms, including microbial activation, stoichiometry, and community shifts. Here, we conducted five-week incubations of four soils (grassland, piñon-juniper, ponderosa pine, mixed conifer), varying the amount of substrate added (as 13C-glucose, either 350 or 1000 μg C g−1 week−1) and either with no added nitrogen (N), or with sufficient N (as NH4NO3) to bring the C-to-N ratio of the added substrate to 10. Using four different ecosystems enabled testing the generality of mechanisms underlying the priming effect. The responses of priming to the amount and C-to-N ratio of the added substrate were consistent across ecosystems: priming increased with the rate of substrate addition and declined when the C-to-N ratio of the substrate was reduced. However, structural equation models failed to confirm intermediate responses postulated to mediate the priming effect, including responses postulated to be mediated by stoichiometry and microbial activation. Specifically, priming was not clearly associated with changes in microbial biomass or turnover, nor with extracellular enzyme activities or the microbial C-to-N ratio. The strongest explanatory pathways in the structural equation models were the substrate, soil, and C-to-N ratio treatments themselves, with no intermediates, suggesting that either these measurements lacked sufficient sensitivity to reveal causal relationships, or the actual drivers for priming were not included in the ancillary measurements. While we observed consistent changes in priming caused by the amount and C-to-N ratio of the added substrate across a wide array of soils, our findings did not clearly conform to common models offered for the priming effect. Because priming is a residual flux involving diverse substrates of varying chemical composition, a simple and generalizable explanation of the phenomenon may be elusive.</span>

<span>Large-scale primary native broadleaf forests (BF) have been converted to secondary forests (SF) and plantation forests (PF) in subtropical China over the past decades. However, how and what magnitude of plant and soil carbon (C), nitrogen (N), and phosphorus (P) stocks and stoichiometry are affected by forest conversion is still vague. Here, we addressed this issue by systematically measuring tree biomass and the C, N, and P concentrations in tree organs and soils (0–100 cm) collected from 300 plots in Fujian province. With forest conversion of BF to PF, the tree C, N, and P stocks declined by 43.8, 47.9, and 63.1%, respectively, and the soil C and N stocks across whole soil depth decreased by 19.1% and 13.0%, respectively, and these decreases were more evident after conversion of BF to PF than SF. However, soil P stock showed a tendency of decreasing at 0–20 cm soil depth but increasing at 20–100 cm soil depth following conversion of BF to SF and PF. This unconformity of the vertical pattern of P stock in contrast to C and N stocks, was perhaps due to higher C and N inputs and greater P uptake from the subsoil and its redistribution to the topsoil in BF than in SF and PF. The tree and soil C, N, and P stoichiometry was strongly related to tree biomass, indicating that tree biomass was a vital factor driving soil inputs and retention of nutrients, and thus affecting their stoichiometry. The leaf N:P ratios ranging from 16.7 to 17.2 at our study sites suggested that co-limitations of N and P for forest growth could occur in the studied region. Our results provided insights into the C, N, and P linkages between soils and trees as affected by forest conversion, and advised that predicting these linkages could be an effective approach to identify the impacts of forest conversion, thereby implementing targeted conservation and rehabilitation actions.</span>

<span>The dynamic equilibrium of mass and energy movement in ecosystems is an important basis for the Earth system to nurture and maintain biodiversity. Since the Industrial Revolution, human activities have caused the carbon exchange between terrestrial ecosystems and the atmosphere to be at dynamic disequilibrium. This paper examines a dynamic disequilibrium hypothesis for the carbon cycle of terrestrial ecosystems. The hypothesis suggests that the dynamic disequilibrium is caused by interactions of four basic properties of internal processes of the terrestrial carbon cycle with five types of external drivers. Based on these internal properties and external drivers, this paper summarizes the expression phenomena of the dynamic disequilibrium of terrestrial carbon cycle at different time and space scales, and discusses its detection methods from the perspective of observations, experiments and models. The dynamic disequilibrium hypothesis for terrestrial carbon cycle not only helps us understand the complex terrestrial carbon-cycle phenomenon, but also provides a new theoretical framework for predicting the future terrestrial carbon sink dynamics.</span>

<span>Will mature forests absorb enough carbon from the atmosphere to mitigate climate change as levels of carbon dioxide increase? An experiment in a eucalyptus forest provides fresh evidence.</span>

<span>Cities and their associated urban heat islands are ideal natural laboratories for evaluating the response of plant phenology to warming conditions. In this study, we demonstrate that the satellite-derived start of season for plants occurred earlier but showed less covariation with temperature in most of the large 85 cities across the conterminous United States for the period 2001–2014. The results show a reduction in the response of urban phenology to temperature and imply that, in nonurban environments, the onset of spring phenology will likely advance but will slow down as the general trend toward warming continues.Urbanization has caused environmental changes, such as urban heat islands (UHIs), that affect terrestrial ecosystems. However, how and to what extent urbanization affects plant phenology remains relatively unexplored. Here, we investigated the changes in the satellite-derived start of season (SOS) and the covariation between SOS and temperature (RT) in 85 large cities across the conterminous United States for the period 2001–2014. We found that 1) the SOS came significantly earlier (6.1 ± 6.3 d) in 74 cities and RT was significantly weaker (0.03 ± 0.07) in 43 cities when compared with their surrounding rural areas (P &amp;amp;lt; 0.05); 2) the decreased magnitude in RT mainly occurred in cities in relatively cold regions with an annual mean temperature &amp;amp;lt;17.3 °C (e.g., Minnesota, Michigan, and Pennsylvania); and 3) the magnitude of urban−rural difference in both SOS and RT was primarily correlated with the intensity of UHI. Simulations of two phenology models further suggested that more and faster heat accumulation contributed to the earlier SOS, while a decrease in required chilling led to a decline in RT magnitude in urban areas. These findings provide observational evidence of a reduced covariation between temperature and SOS in major US cities, implying the response of spring phenology to warming conditions in nonurban environments may decline in the warming future.</span>

<span>Growth of soil microorganisms is often described as carbon limited, and adding labile carbon to soil often results in a transient and large increase in respiration. In contrast, soil microbial biomass changes little, suggesting that growth and respiration are decoupled in response to a carbon pulse. Alternatively, measuring bulk responses of the entire community (total respiration and biomass) could mask ecologically important variation among taxa in response to the added carbon. Here, we assessed taxon-specific variation in cellular growth (measured as DNA synthesis) and metabolic activity (measured as rRNA synthesis) following glucose addition to soil using quantitative stable isotope probing with H218O. We found that glucose addition altered rates of DNA and rRNA synthesis, but the effects were strongly taxon specific: glucose stimulated growth and rRNA transcription for some taxa, and suppressed these for others. These contrasting taxon-specific responses could explain the small and transient changes in total soil microbial biomass. Responses to glucose were not well predicted by a priori assignments of taxa into copiotrophic or oligotrophic categories. Across all taxa, rates of DNA and rRNA synthesis changed in parallel, indicating that growth and activity were coupled, and the degree of coupling was unaffected by glucose addition. This pattern argues against the idea that labile carbon addition causes a large reduction in metabolic growth efficiency; rather, the large pulse of respiration observed with labile substrate addition is more likely to be the result of rapid turnover of microbial biomass, possibly due to trophic interactions. Our results support a strong connection between rRNA synthesis and bacterial growth, and indicate that taxon-specific responses among soil bacteria can buffer responses at the scale of the whole community.</span>

<span>Despite the wide application of meta-analysis in ecology, some of the traditional methods used for meta-analysis may not perform well given the type of data characteristic of ecological meta-analyses. We reviewed published meta-analyses on the ecological impacts of global climate change, evaluating the number of replicates used in the primary studies (ni) and the number of studies or records (k) that were aggregated to calculate a mean effect size. We used the results of the review in a simulation experiment to assess the performance of conventional frequentist and Bayesian meta-analysis methods for estimating a mean effect size and its uncertainty interval. Our literature review showed that ni and k were highly variable, distributions were right-skewed and were generally small (median ni = 5, median k = 44). Our simulations show that the choice of method for calculating uncertainty intervals was critical for obtaining appropriate coverage (close to the nominal value of 0.95). When k was low (&lt;40), 95% coverage was achieved by a confidence interval (CI) based on the t distribution that uses an adjusted standard error (the Hartung?Knapp?Sidik?Jonkman, HKSJ), or by a Bayesian credible interval, whereas bootstrap or z distribution CIs had lower coverage. Despite the importance of the method to calculate the uncertainty interval, 39% of the meta-analyses reviewed did not report the method used, and of the 61% that did, 94% used a potentially problematic method, which may be a consequence of software defaults. In general, for a simple random-effects meta-analysis, the performance of the best frequentist and Bayesian methods was similar for the same combinations of factors (k and mean replication), though the Bayesian approach had higher than nominal (&gt;95%) coverage for the mean effect when k was very low (k &lt; 15). Our literature review suggests that many meta-analyses that used z distribution or bootstrapping CIs may have overestimated the statistical significance of their results when the number of studies was low; more appropriate methods need to be adopted in ecological meta-analyses.</span>

<span>Fire activity is changing dramatically across the globe, with uncertain effects on ecosystem processes, especially below-ground. Fire-driven losses of soil carbon (C) are often assumed to occur primarily in the upper soil layers because the repeated combustion of above-ground biomass limits organic matter inputs into surface soil. However, C losses from deeper soil may occur if frequent burning reduces root biomass inputs of C into deep soil layers or stimulates losses of C via leaching and priming. To assess the effects of fire on soil C, we sampled 12 plots in a 51-year-long fire frequency manipulation experiment in a temperate oak savanna, where variation in prescribed burning frequency has created a gradient in vegetation structure from closed-canopy forest in unburned plots to open-canopy savanna in frequently burned plots. Soil C stocks were nonlinearly related to fire frequency, with soil C peaking in savanna plots burned at an intermediate fire frequency and declining in the most frequently burned plots. Losses from deep soil pools were significant, with the absolute difference between intermediately burned plots versus most frequently burned plots more than doubling when the full 1 m sample was considered rather than the top 0?20 cm alone (losses of 98.5 Mg C/ha [?76%] and 42.3 Mg C/ha [?68%] in the full 1 m and 0?20 cm layers respectively). Compared to unburned forested plots, the most frequently burned plots had 65.8 Mg C/ha (?58%) less C in the full 1 m sample. Root biomass below the top 20 cm also declined by 39% with more frequent burning. Concurrent fire-driven losses of nitrogen and gains in calcium and phosphorus suggest that burning may increase nitrogen limitation and play a key role in the calcium and phosphorus cycles in temperate savannas. Synthesis. Our results illustrate that fire-driven losses in soil C and root biomass in deep soil layers may be critical factors regulating the net effect of shifting fire regimes on ecosystem C in forest-savanna transitions. Projected changes in soil C with shifting fire frequencies in savannas may be 50% too low if they only consider changes in the topsoil.</span>

<span>In trees, large uncertainties remain in how nonstructural carbohydrates (NSCs) respond to variation in water availability in natural, intact ecosystems. Variation in NSC pools reflects temporal fluctuations in supply and demand, as well as physiological coordination across tree organs in ways that differ across species and NSC fractions (e.g., soluble sugars vs starch). Using landscape-scale crown (leaves and twigs) NSC concentration measurements in three foundation tree species (Populus tremuloides, Pinus edulis, Juniperus osteosperma), we evaluated in situ, seasonal variation in NSC responses to moisture stress on three timescales: short-term (via predawn water potential), seasonal (via leaf δ13C) and annual (via current year’s ring width index). Crown NSC responses to moisture stress appeared to depend on hydraulic strategy, where J. osteosperma appears to regulate osmotic potentials (via higher sugar concentrations), P. edulis NSC responses suggest respiratory depletion and P. tremuloides responses were consistent with direct sink limitations. We also show that overly simplistic models can mask seasonal and tissue variation in NSC responses, as well as strong interactions among moisture stress at different timescales. In general, our results suggest large seasonal variation in crown NSC concentrations reflecting the multiple cofunctions of NSCs in plant tissues, including storage, growth and osmotic regulation of hydraulically vulnerable leaves. We emphasize that crown NSC pool size cannot be viewed as a simple physiological metric of stress; in situ NSC dynamics are complex, varying temporally, across species, among NSC fractions and among tissue types.</span>

<span>The diversity patterns of macroorganisms (i.e., plants) among different habitats have been well documented, however, those of microorganisms (i.e., fungi) as well as the relationships between them are still unclear. Here, we tested whether and to what degree fungal diversity was related to habitat types and compared diversity patterns of woody plants and soil fungi. We carried out field investigations on soil fungi in different habitat types (i.e., valleys, foothills, hillsides, and hilltops) in a 25-ha karst broadleaf forest in Southwest China. The tree richness, Shannon index, and Simpson index significantly increased from valleys to hilltops. While the soil fungal N1 diversity (the exponential Shannon index) marginally increased toward valleys, fungal N0 (richness) and N2 (the inverse Simpson index) diversity exhibited significantly reduced and increased patterns, respectively, from valleys to hilltops. The major fungal functional groups (i.e., EcM, AM, saprotrophic, and pathogenic fungi) showed similar increasing richness patterns in valleys. Moreover, woody plant alpha diversity was an important indicator of fungal functional groups except for EcM and AM fungi. In addition, woody plants increased in species turnover rate (βSIM) from valleys to hilltops, while fungal species had a concave distribution. The patterns of nestedness (βSNE) for tree species decreased from valleys to hilltops, while the opposite was true for soil fungal species. Our findings indicated that the diversity patterns of woody plants and fungi were inconsistent among habitat types, and the relationships between fungal and woody plant communities depended on habitat types in the karst forest.</span>

<span>Elevated atmospheric CO2 (eCO2) generally increases carbon input in rice paddy soils and stimulates the growth of methane-producing microorganisms. Therefore, eCO2 is widely expected to increase methane (CH4) emissions from rice agriculture, a major source of anthropogenic CH4. Agricultural practices strongly affect CH4 emissions from rice paddies as well, but whether these practices modulate effects of eCO2 is unclear. Here we show, by combining a series of experiments and meta-analyses, that whereas eCO2 strongly increased CH4 emissions from paddies without straw incorporation, it tended to reduce CH4 emissions from paddy soils with straw incorporation. Our experiments also identified the microbial processes underlying these results: eCO2 increased methane-consuming microorganisms more strongly in soils with straw incorporation than in soils without straw, with the opposite pattern for methane-producing microorganisms. Accounting for the interaction between CO2 and straw management, we estimate that eCO2 increases global CH4 emissions from rice paddies by 3.7%, an order of magnitude lower than previous estimates. Our results suggest that the effect of eCO2 on CH4 emissions from rice paddies is smaller than previously thought and underline the need for judicious agricultural management to curb future CH4 emissions.</span>

<span>The impacts of climate change and extreme weather events (e.g. frost-, heat-, drought-, and heavy rainfall events) on the continuous phenological development over the entire seasonal cycle remained poorly understood. Previous studies mainly focused on modeling key phenological transition dates (e.g. discrete timing of spring bud-break and fall senescence) based on aggregated climate variables (e.g. mean temperature, growing-degree days). We developed and evaluated a Bayesian Hierarchical Space-Time model for Land Surface Phenology (BHST-LSP) to synthesize remotely sensed vegetation greenness with climate covariates at a daily temporal scale from 1981 to 2014 across the entire conterminous United States. The BHST-LSP model incorporated both temporal and spatial information and exhibited high predictive power in simulating daily phenological development with an overall out-of-sample R2 of 0.80 ± 0.17 and 0.72 ± 0.20 for spring and fall phenology, respectively. The overall out-of-sample normalized root mean square errors were 9.3% ± 6.1% and 9.9% ± 5.2% between the observed and predicted vegetation greenness for spring and fall phenology, respectively. We found that a fast increase of temperature can accelerate the speed of spring green-up while a slow decrease of temperature can lead to a decelerated fall brown-down. Increasing accumulated precipitation can benefit daily phenological development over an entire growing season, while extreme rainfall events can have the opposite effects. More frequent frost events could slow spring leaf expansion and accelerate fall leaf senescence. Impacts of extreme heat events were complex and depended on water availability. Cropland in the Midwest as well as evergreen needleleaf forest along the coastal regions showed relatively strong resistance to drought events compared to other land cover types. The BHST-LSP model can be used to forecast vegetation phenology given future climate projection, thus providing valuable information for adopting climate change adaptation and mitigation measures.</span>

<span>Permafrost thaw is typically measured with active layer thickness, or the maximum seasonal thaw measured from the ground surface. However, previous work has shown that this measurement alone fails to account for ground subsidence and therefore underestimates permafrost thaw. To determine the impact of subsidence on observed permafrost thaw and thawed soil carbon stocks, we quantified subsidence using high-accuracy GPS and identified its environmental drivers in a permafrost warming experiment near the southern limit of permafrost in Alaska. With permafrost temperatures near 0°C, 10.8 cm of subsidence was observed in control plots over 9 years. Experimental air and soil warming increased subsidence by five times and created inundated microsites. Across treatments, ice and soil loss drove 85?91% and 9?15% of subsidence, respectively. Accounting for subsidence, permafrost thawed between 19% (control) and 49% (warming) deeper than active layer thickness indicated, and the amount of newly thawed carbon within the active layer was between 37% (control) and 113% (warming) greater. As additional carbon thaws as the active layer deepens, carbon fluxes to the atmosphere and lateral transport of carbon in groundwater could increase. The magnitude of this impact is uncertain at the landscape scale, though, due to limited subsidence measurements. Therefore, to determine the full extent of permafrost thaw across the circumpolar region and its feedback on the carbon cycle, it is necessary to quantify subsidence more broadly across the circumpolar region.</span>

<span>Root endophytes are a promising tool for increasing plant growth, but it is unclear whether they perform consistently across plant hosts. We characterized the blue grama (Bouteloua gracilis) root microbiome using two sequencing methods, quantified the effects of root endophytes in the original host (blue grama) and an agricultural recipient, corn (Zea mays), under drought and well-watered conditions and examined in vitro mechanisms for plant growth promotion. 16S rRNA amplicon sequencing revealed that the blue grama root microbiome was similar across an elevation gradient, with the exception of four genera. Culturing and Sanger sequencing revealed eight unique endophytes belonging to the genera Bacillus, Lysinibacillus and Pseudomonas. All eight endophytes colonized corn roots, but had opposing effects on aboveground and belowground biomass in each plant species: they increased blue grama shoot mass by 45% (19) (mean +/− SE) while decreasing corn shoot mass by 10% (19), and increased corn root:shoot by 44% (7), while decreasing blue grama root:shoot by 17% (7). Furthermore, contrary to our expectations, endophytes had stronger effects on plant growth under well-watered conditions rather than drought conditions. Collectively, these results suggest that ecological features, including host identity, bacterial traits, climate conditions and morphological outcomes, should be carefully considered in the design and implementation of agricultural inocula.</span>

<span>Water and CO2 flux responses (e.g., evapotranspiration [ET] and net ecosystem exchange [NEE]) to environmental conditions can provide insights into how climate change will affect the terrestrial water and carbon budgets, especially in sensitive semiarid ecosystems. Here, we evaluated sensitivity of daily ET and NEE to current and antecedent (past) environment conditions, including atmospheric (vapor pressure deficit [VPD] and air temperature [Tair]) and moisture (precipitation and soil water) drivers. We focused on two common southwestern U.S. (?Southwest?) biomes: pinyon-juniper woodland (Pinus edulis, Juniperus monosperma) and ponderosa pine forest (Pinus ponderosa). Due to differences in aridity, rooting patterns, and plant physiological strategies (stomatal and hydraulic traits), we expected ET and NEE in these ecosystems to respond differently to atmospheric and moisture drivers, with longer response timescales in the drier pinyon-juniper woodland. Net sensitivity to drivers varied temporally in both ecosystems, reflecting the integrated influence of interacting drivers and antecedent precipitation patterns. NEE sensitivity to VPD and soil moisture (and ET sensitivity to deep soil moisture [Sdeep]) was higher in the ponderosa forest. ET and NEE in both ecosystems responded almost instantaneously to Tair, VPD, and shallow soil moisture (Sshall), and increases in any of these drivers weakened the carbon sink and enhanced water loss. Conversely, Sdeep and precipitation influenced ET and NEE over longer timescales (days to months, respectively), and higher Sdeep enhanced the carbon sink. As climate changes, these results suggest hotter and drier conditions will weaken the carbon sink and exacerbate water loss from Southwest pinyon-juniper and ponderosa ecosystems.</span>

<span>The magnitude of carbon (C) loss to the atmosphere via microbial decomposition is a function of the amount of C stored in soils, the quality of the organic matter, and physical, chemical, and biological factors that comprise the environment for decomposition. The decomposability of C is commonly assessed by laboratory soil incubation studies that measure greenhouse gases mineralized from soils under controlled conditions. Here, we introduce the Soil Incubation Database (SIDb) version 1.0, a compilation of time series data from incubations, structured into a new, publicly available, open-access database of C flux (carbon dioxide, </span><span class="inline-formula">CO₂</span><span>, or methane, </span><span class="inline-formula">CH₄</span><span>). In addition, the SIDb project also provides a platform for the development of tools for reading and analysis of incubation data as well as documentation for future use and development. In addition to introducing SIDb, we provide reporting guidance for database entry and the required variables that incubation studies need at minimum to be included in SIDb. A key application of this synthesis effort is to better characterize soil C processes in Earth system models, which will in turn reduce our uncertainty in predicting the response of soil C decomposition to a changing climate. We demonstrate a framework to fit curves to a number of incubation studies from diverse ecosystems, depths, and organic matter content using a built-in model development module that integrates SIDb with the existing SoilR package to estimate soil C pools from time series data. The database will help bridge the gap between point location measurements, which are commonly used in incubation studies, and global remote-sensed data or data products derived from models aimed at assessing global-scale rates of decomposition and C turnover. The SIDb version 1.0 is archived and publicly available at </span><a href="https://doi.org/10.5281/zenodo.3871263">https://doi.org/10.5281/zenodo.3871263</a><span> (Sierra et al., 2020), and the database is managed under a version-controlled system and centrally stored in GitHub (</span><span class="uri"><a href="https://github.com/SoilBGC-Datashare/sidb" target="_blank" rel="noopener noreferrer">https://github.com/SoilBGC-Datashare/sidb</a></span><span>, last access: 26 June 2020).</span>

<span>Terrestrial vegetation removes CO2 from the atmosphere; an important climate regulation service that slows global warming. This 119 Pg C per annum transfer of CO2 into plants—gross primary productivity (GPP)—is the largest land carbon flux globally. While understanding past and anticipated future GPP changes is necessary to support carbon management, the factors driving long-term changes in GPP are largely unknown. Here we show that 1901 to 2010 changes in GPP have been dominated by anthropogenic activity. Our dual constraint attribution approach provides three insights into the spatiotemporal patterns of GPP change. First, anthropogenic controls on GPP change have increased from 57% (1901 decade) to 94% (2001 decade) of the vegetated land surface. Second, CO2 fertilization and nitro  gen deposition are the most important drivers of change, 19.8 and 11.1 Pg C per annum (2001 decade) respectively, especially in the tropics and industrialized areas since the 1970’s. Third, changes in climate have functioned as fertilization to enhance GPP (1.4 Pg C per annum in the 2001 decade). These findings suggest that, from a land carbon balance perspective, the Anthropocene began over 100 years ago and that global change drivers have allowed GPP uptake to keep pace with anthropogenic emissions.</span>

<span>Evergreen conifer forests are the most prevalent land cover type in North America. Seasonal changes in the color of evergreen forest canopies have been documented with near-surface remote sensing, but the physiological mechanisms underlying these changes, and the implications for photosynthetic uptake, have not been fully elucidated. Here, we integrate on-the-ground phenological observations, leaf-level physiological measurements, near surface hyperspectral remote sensing and digital camera imagery, tower-based CO2 flux measurements, and a predictive model to simulate seasonal canopy color dynamics. We show that seasonal changes in canopy color occur independently of new leaf production, but track changes in chlorophyll fluorescence, the photochemical reflectance index, and leaf pigmentation. We demonstrate that at winter-dormant sites, seasonal changes in canopy color can be used to predict the onset of canopy-level photosynthesis in spring, and its cessation in autumn. Finally, we parameterize a simple temperature-based model to predict the seasonal cycle of canopy greenness, and we show that the model successfully simulates interannual variation in the timing of changes in canopy color. These results provide mechanistic insight into the factors driving seasonal changes in evergreen canopy color and provide opportunities to monitor and model seasonal variation in photosynthetic activity using color-based vegetation indices.</span>

<span>Rising temperatures with increased drought pose two challenges for management of future biodiversity. First, are the most vulnerable species concentrated in specific regions and habitats? Second, where can landscape heterogeneity potentially mitigate impacts? We conducted a comprehensive trait analysis of forest plots spanning the eastern United States to quantify how resource-acquisitive species respond to moisture-soil-climate interactions. We found that resource-acquisitive species, including nutrient-acquisitive and moisture-acquisitive species, respond disproportionately to environmental gradients, and their response is largely explained by soil variation. We showed that the strong boundary of resource-acquisitive species occurs near the last glacial limit, highlighting one of the clearest indicators of soil controls. Although local soil moisture may reduce drought-induced stress for moisture-acquisitive species, nutrient-acquisitive species remain vulnerable on wet soils in dry climates. The results suggest that theories explaining species distributions should devote close attention to the combination of local drainage and soil type.</span>

<span>Despite abounding evidence that leaf litter traits can predict decomposition rate, the way these traits influence trophic efficiency and element transfer to higher trophic levels is not resolved. Here, we used litter labeled with 13C and 15N stable isotopes to trace fluxes of litter C and N from four leaf types to freshwater invertebrate communities. We measured absolute (mg C or N) and relative assimilation (percentage of litter C or N incorporated into invertebrate biomass relative to C and N lost during decomposition). Four patterns emerged: (1) Invertebrate communities assimilated more C and N from slowly decomposing litter than communities feeding on rapidly decomposing litter; (2) absolute assimilation of both C and N in leaf packs was positively correlated with the relative biomass of invertebrate taxa in leaf packs; (3) Chironomidae larvae, which colonize packs in the early decomposition stages, assimilated the most C and N by the end of the 35-day experiment; and (4) most taxa, spanning five functional feeding groups (collector–gatherers, shredders, collector–filterers, scrapers, and predators), showed similar patterns in both absolute and relative assimilation across leaf types. These results challenge traditional views of litter quality by demonstrating that trophic efficiency is negatively associated with decomposition rate across these four leaf types.</span>

<span>Quantitative stable isotope probing (qSIP) estimates the degree of incorporation of an isotope tracer into nucleic acids of metabolically active organisms and can be applied to microorganisms growing in complex communities, such as the microbiomes of soil or water. As such, qSIP has the potential to link microbial biodiversity and biogeochemistry. As with any technique involving quantitative estimation, qSIP involves measurement error; a more complete understanding of error, precision and statistical power will aid in the design of qSIP experiments and interpretation of qSIP data. We used several existing qSIP datasets of microbial communities found in soil and water to evaluate how variance in the estimate of isotope incorporation depends on organism abundance and on the resolution of the density fractionation scheme. We also assessed statistical power for replicated qSIP studies, and sensitivity and specificity for unreplicated designs. We found that variance declines as taxon abundance increases. Increasing the number of density fractions reduces variance, although the benefit of added fractions declines as the number of fractions increases. Specifically, nine fractions appear to be a reasonable tradeoff between cost and precision for most qSIP applications. Increasing replication improves power and reduces the minimum detectable threshold for inferring isotope uptake to 5 atom%. Finally, we provide evidence for the importance of internal standards to calibrate the %GC to mean weighted density regression per sample. These results should benefit those designing future SIP experiments, and provide a reference for metagenomic SIP applications where financial and computational limitations constrain experimental scope.Importance One of the biggest challenges in microbial ecology is correlating the identity of microorganisms with the roles they fulfill in natural environmental systems. Studies of microbes in pure culture reveal much about genomic content and potential functions, but may not reflect an organism’s activity within its natural community. Culture-independent studies supply a community-wide view of composition and function in the context of community interactions, but fail to link the two. Quantitative stable isotope probing (qSIP) is a method that can link the identity and function of specific microbes within a naturally occurring community. Here we explore how the resolution of density-gradient fractionation affects the error and precision of qSIP results, how they may be improved via additional replication, and cost-benefit balanced scenarios for SIP experimental design.</span>

<span>The amount of reactive nitrogen has more than doubled in terrestrial ecosystems due to human activities such fertiliser application that is predicted to increase dramatically in coming decades. We conducted a 3-year experiment in a Neotropical savanna in which we determined the effects of increased N deposition on litter decomposition in plots subjected to different levels of N addition (50 kg N ha?1 year?2, 20 kg N ha?1 year?2, or no N addition). For this, we compared the litter decomposition from the bunchgrass Tristachya leiostachya using litter collected from plots with different N addition treatments. Five randomly selected bags of litter from each N addition treatment (origin) were distributed to each plot (destination). We also compared litter nitrogen (N) concentration and indicators of microbial activity (basal respiration, carbon of microbial biomass, metabolic quotient, enzyme activity) in all plots. We found that nitrogen addition influences litter decay, but in idiosyncratic ways that differ between years. In year 1, litter decomposed faster in high-N addition plots than in low-N and control plots, regardless of its origin. In contrast, litter from high-N addition plots decomposing fastest in year 2, regardless of its destination. Finally, there was no effect of either litter origin or destination on the rate of decomposition in year 3. Litter collected in high-N addition plots had a concentration of N 12?17% higher than litter collected in other plots and higher in 2009 than in other years. Four years after the beginning of the fertilisation experiment, concentration and the microbial activity in the soil did not differ between the treatments. Our findings suggest that the levels of N addition predicted for Neotropical savannas can alter litter N concentrations and the process of litter decomposition, but that the direction and magnitude of these changes may be challenging to predict since that precipitation can influence the mechanisms regulating decomposition in the Cerrado.</span>

<span>Moss-associated N2 fixation provides a substantial but heterogeneous input of new N to nutrient-limited ecosystems at high latitudes. In spite of the broad diversity of mosses found in boreal and Arctic ecosystems, the extent to which host moss identity drives variation in N2 fixation rates remains largely undetermined. We used 15N2 incubations to quantify the fixation rates associated with 34 moss species from 24 sites ranging from 60° to 68° N in Alaska, USA. Remarkably, all sampled moss genera fixed N2, including well-studied feather and peat mosses and genera such as Tomentypnum, Dicranum, and Polytrichum. The total moss-associated N2 fixation rates ranged from almost zero to 3.2 mg N m−2 d−1, with an average of 0.8 mg N m−2 d−1, based on abundance-weighted averages of all mosses summed for each site. Random forest models indicated that moss taxonomic family was a better predictor of rate variation across Alaska than any of the measured environmental factors, including site, pH, tree density, and mean annual precipitation and temperature. Consistent with this finding, mixed models showed that trends in N2 fixation rates among moss genera were consistent across biomes. We also found “hotspots” of high fixation rates in one-fourth of sampled sites. Our results demonstrated the importance of moss identity in influencing N2 fixation rates. This in turn indicates the potential utility of moss identity when making ecosystem N input predictions and exploring other sources of process rate variation.</span>

<span>In a warmer world, microbial decomposition of previously frozen organic carbon (C) is one of the most likely positive climate feedbacks of permafrost regions to the atmosphere. However, mechanistic understanding of microbial mediation on chemically recalcitrant C instability is limited; thus, it is crucial to identify and evaluate active decomposers of chemically recalcitrant C, which is essential for predicting C-cycle feedbacks and their relative strength of influence on climate change. Using stable isotope probing of the active layer of Arctic tundra soils after depleting soil labile C through a 975-day laboratory incubation, the identity of microbial decomposers of lignin and, their responses to warming were revealed.</span>

<span>An amendment to this paper has been published and can be accessed via a link at the top of the paper.</span>

<span>The permafrost zone is expected to be a substantial carbon source to the atmosphere, yet large-scale models currently only simulate gradual changes in seasonally thawed soil. Abrupt thaw will probably occur in &lt;20% of the permafrost zone but could affect half of permafrost carbon through collapsing ground, rapid erosion and landslides. Here, we synthesize the best available information and develop inventory models to simulate abrupt thaw impacts on permafrost carbon balance. Emissions across 2.5 million km2 of abrupt thaw could provide a similar climate feedback as gradual thaw emissions from the entire 18 million km2 permafrost region under the warming projection of Representative Concentration Pathway 8.5. While models forecast that gradual thaw may lead to net ecosystem carbon uptake under projections of Representative Concentration Pathway 4.5, abrupt thaw emissions are likely to offset this potential carbon sink. Active hillslope erosional features will occupy 3% of abrupt thaw terrain by 2300 but emit one-third of abrupt thaw carbon losses. Thaw lakes and wetlands are methane hot spots but their carbon release is partially offset by slowly regrowing vegetation. After considering abrupt thaw stabilization, lake drainage and soil carbon uptake by vegetation regrowth, we conclude that models considering only gradual permafrost thaw are substantially underestimating carbon emissions from thawing permafrost.</span>

<span>Terrestrial animal communities are largely shaped by vegetation and climate. With climate also shaping vegetation, can we attribute animal patterns solely to climate? Our study observes ant community changes along climatic gradients (i.e., elevational gradients) within different habitat types (i.e., open and forest) on the Colorado Plateau in the southwestern United States. We sampled ants and vegetation along two elevational gradients spanning 1,132 m with average annual temperature and precipitation differences of 5.7°C and 645mm, respectively. We used regression analyses and structural equation modeling to compare the explanatory powers and effect sizes of climate and vegetation variables on ants. Climate variables had the strongest correlations and the largest effect sizes on ant communities, while vegetation composition, richness, and primary productivity had relatively small effects. Precipitation was the strongest predictor for most ant community metrics. Ant richness and abundance had a negative relationship with precipitation in forested habitats, and positive in open habitats. Our results show strong direct climate effects on ants with little or no effects of vegetation composition or primary productivity, but contrasting patterns between vegetation type (i.e., forested vs. open) with precipitation. This indicates vegetation structure can modulate climate responses of ant communities. Our study demonstrates climate-animal relationships may vary among vegetation types which can impact both findings from elevational studies and how communities will react to changes in climate.</span>

<span>In this work we define a spatial concordance coefficient for second-order stationary processes. This problem has been widely addressed in a non-spatial context, but here we consider a coefficient that for a fixed spatial lag allows one to compare two spatial sequences along a 45°line. The proposed coefficient was explored for the bivariate Matérn and Wendland covariance functions. The asymptotic normality of a sample version of the spatial concordance coefficient for an increasing domain sampling framework was established for the Wendland covariance function. To work with large digital images, we developed a local approach for estimating the concordance that uses local spatial models on non-overlapping windows. Monte Carlo simulations were used to gain additional insights into the asymptotic properties for finite sample sizes. As an illustrative example, we applied this methodology to two similar images of a deciduous forest canopy. The images were recorded with different cameras but similar fields-of-view and within minutes of each other. Our analysis showed that the local approach helped to explain a percentage of the non-spatial concordance and provided additional information about its decay as a function of the spatial lag.</span>

<span>Atmospheric carbon dioxide concentration ([CO2]) is increasing, which increases leaf-scale photosynthesis and intrinsic water-use efficiency. These direct responses have the potential to increase plant growth, vegetation biomass, and soil organic matter; transferring carbon from the atmosphere into terrestrial ecosystems (a carbon sink). A substantial global terrestrial carbon sink would slow the rate of [CO2] increase and thus climate change. However, ecosystem CO2-responses are complex or confounded by concurrent changes in multiple agents of global change and evidence for a [CO2]-driven terrestrial carbon sink can appear contradictory. Here we synthesise theory and broad, multi-disciplinary evidence for the effects of increasing [CO2] (iCO2) on the global terrestrial carbon sink. Evidence suggests a substantial increase in global photosynthesis since pre-industry. Established theory, supported by experiments, indicates that iCO2 is likely responsible for about half of the increase. Global carbon budgeting, atmospheric data, and forest inventories indicate a historical carbon sink, and these apparent iCO2-responses are high in comparison with experiments and theory. Plant mortality and soil carbon iCO2-responses are highly uncertain. In conclusion, a range of evidence supports a positive terrestrial carbon sink in response to iCO2, albeit with uncertain magnitude and strong suggestion of a role for additional agents of global change.</span>

<span>Increases in fire frequency, extent, and severity are expected to strongly impact the structure and function of boreal forest ecosystems. An important function of the boreal forest is its ability to sequester and store carbon (C). Increasing disturbance from wildfires, emitting large amounts of C to the atmosphere, may create a positive feedback to climate warming. Variation in ecosystem structure and function throughout the boreal forest is important for predicting the effects of climate warming and changing fire regimes on C dynamics. In this study, we compiled data on soil characteristics, stand structure, pre-fire C pools, C loss from fire, and the potential drivers of these C metrics from 527 sites distributed across six ecoregions of North America’s western boreal forests. We assessed structural and functional differences between these fire-prone ecoregions using data from 417 recently burned sites (2004–2015) and estimated ecoregion-specific relationships between soil characteristics and depth from 167 of these sites plus an additional 110 sites (27 burned, 83 unburned). We found that northern boreal ecoregions were generally older, stored and emitted proportionally more belowground than aboveground C, and exhibited lower rates of C accumulation over time than southern ecoregions. We present ecoregion-specific estimates of depth-wise soil characteristics that are important for predicting C combustion from fire. As climate continues to warm and disturbance from wildfires increases, the C dynamics of these fire-prone ecoregions are likely to change with significant implications for the global C cycle and its feedbacks to climate change.</span>

<span>Carbon (C) emissions from wildfires are a key terrestrial–atmosphere interaction that influences global atmospheric composition and climate. Positive feedbacks between climate warming and boreal wildfires are predicted based on top-down controls of fire weather and climate, but C emissions from boreal fires may also depend on bottom-up controls of fuel availability related to edaphic controls and overstory tree composition. Here we synthesized data from 417 field sites spanning six ecoregions in the northwestern North American boreal forest and assessed the network of interactions among potential bottom-up and top-down drivers of C emissions. Our results indicate that C emissions are more strongly driven by fuel availability than by fire weather, highlighting the importance of fine-scale drainage conditions, overstory tree species composition and fuel accumulation rates for predicting total C emissions. By implication, climate change-induced modification of fuels needs to be considered for accurately predicting future C emissions from boreal wildfires.</span>

<span>When multiple metabolic pathways lead to the same product, compound-specific isotope analysis may not provide enough information to quantify the activities of the contributing pathways. Instead, identification of where in the molecule the 13C is incorporated is required. Here we show how knowledge of position-specific 13C incorporation in fatty acids (FA) and FA fragments can be used to quantitatively estimate the fluxes through the central C metabolic network. We developed a method to measure 13C enrichment of FA and FA fragments (ethanoate, propionate) using electron impact GC–MS. We tested the accuracy and repeatability of the measurements using natural abundance and position-specific 13C labelled standards and FA extracted from Bacillus licheniformis and Pseudomonas fluorescens grown with labelled and unlabelled glucose. The molecular ions of FA generally reflected theoretical predictions of mass isotopomer distributions for natural abundance values, but that of the associated FA fragments deviated from expected values, likely associated with McLafferty rearrangements of hydrogen. After correction for naturally occurring isotopes, 13C enrichments of FA and FA fragments showed good agreement with expected isotope composition of FA standards (root mean square error &lt; 0.044 at%; δ13C of ∼ 40‰), natural abundance and labelled glucose. The unsaturated FA extracted from P. fluorescens deviated from expected values likely associated with problems of co-elution and ion suppression and were excluded from analysis. The ratio of glucose-1-13C to glucose-3-13C incorporation into FA fragments was high for B. licheniformis, but low for P. fluorescens. Metabolic flux modelling based on the 13C enrichment of ethanoate and propionate fragments showed that B. licheniformis used Embden-Meyerhof-Parnas and pentose phosphate pathway (66% and 30%, respectively), whereas P. fluorescens utilized Entner-Doudoroff and pentose phosphate pathway (72% and 27%, respectively). FA fragment analysis is therefore a promising tool to study central C metabolic network activities of co-occurring groups of microbes in intact and complex environmental communities.</span>

<span>The effects of invasive plants on soil carbon (C) and nitrogen (N) cycling are widely documented, while the mechanisms of their influences on the microbial ecology of soil remain unknown. Therefore, the objective of this study was to explore variations in soil bacterial communities following plant invasion, and the mechanisms that drive these changes.</span>

<span>Unique soil properties in rhizosphere can affect plant growth and biogeochemical cycles of ecosystems. While rhizosphere has been widely investigated, little is known about differences in the rhizosphere effect (RE) between co-existing overstory trees and understory shrubs and herbs in forest ecosystems. In this study, we investigated REs on soil chemical properties of overstory trees and understory shrubs and herbs in forest plantations of southern China. Bulk soil and rhizospheres were sampled in April, July and December 2017. Soil pH, nitrate and ammonium nitrogen, dissolved organic carbon, available phosphorus, total carbon, total nitrogen, and total phosphorus were tested. The REs were defined as the ratios of the chemical properties of the rhizospheres to those of the bulk soil. Our results showed that pH was lower and nutrient contents were higher in the plant rhizospheres than the bulk soil. REs were generally larger in trees than understory plants. The REs were larger in July than April and December. Our findings indicated that the RE varied among plant life forms, species and sampling times, emphasizing the functional role of the RE of understory vegetation in subtropical forests.</span>

<span>Rubber powdery mildew caused by the foliar fungi Oidium heveae is one of the main diseases affecting rubber plantations (Hevea brasiliensis) worldwide. It is particularly serious in sub-optimal growing areas, such as Xishuangbanna in SW China. To prevent and control this disease, fungicides causing serious environmental problems are widely used. Strong correlations between the infection level and the temperature variables were reported previously, but they were related to monthly data that did not allow unraveling the patterns during the entire sensitive period. We correlated the infection level of powdery mildew of rubber trees recorded over 2003–2011 with antecedent 365 days daily temperature variables using partial least squares (PLS) regression. Our PLS regression results showed that the infection level of powdery mildew responded differently to the temperature variables of the defoliation and refoliation periods. Further analysis with Kriging interpolation showed that the infection level increased by 20% and 11%, respectively, per 1 °C rise of the daily maximum and mean temperature in the defoliation season, while it decreased by 8% and 10%, respectively, per 1 °C rise of the daily maximum and temperature difference in the refoliation season. This pattern was likely linked to the effects of temperature on leaf phenology. It seems highly possible that the infection level of powdery mildew increases, as increasing trends of maximum temperature and mean temperature during the defoliation continue.</span>

<span>Plant functional traits can be used to predict ecosystem responses to climate gradients, yet precipitation explains very little variation for most traits. Soil water availability directly influences plant water uptake and thus may assist with the improvement of plant trait–water relationships. However, this promise remains poorly realized due to rare tests. Here, we provide the first study that attempts to link climate factors, vertical soil water availability, and community composition at a regional scale. Our study paired field-measured vertical soil available water (0–300 cm) and community functional composition at 46 herbaceous grassland sites along a steep hydrothermal gradient in the Loess Plateau of Central China. Community functional composition was expressed via community-weighted means of eight traits. Structural equation modeling was employed to evaluate the role of vertical soil available water content, controlled by precipitation and air temperature, in affecting plant community-weighted traits. We found that soil available water content at depths of 20–100 cm was typically responsible for mediating the effects of precipitation and air temperature on plant community composition. This emerged as the predominant factor to explain variations in grassland response traits, including leaf area, specific leaf area, and leaf dry matter content. These traits exhibited clear drought-induced shifts along soil desiccation gradients and responded to drier conditions by reducing leaf area/specific leaf area and increasing leaf dry matter content. Our findings rehighlighted soil water availability as the core driver that needs to be considered in the restoration and management of dryland ecosystems.</span>

<span>Large-scale vegetation restoration projects pose threats to water resource security in water-limited regions. Thus, the quantification of how vegetation cover affects soil moisture is of key importance to support effective restoration schemes in drylands. However, the current understanding of such effects remains poor. For this study, an in-situ vegetation-removal experiment was conducted at 36 herbaceous grassland sites having different community compositions and topographical conditions in two adjacent loess watersheds of the Loess Plateau, China. The effects of vegetation cover (vegetation effects) on soil moisture were analyzed across soil profiles (0–180 cm) and two growing seasons. Overall, 13 plant traits and 7 topographic and soil properties were employed to evaluate how community compositions modulated vegetation effects on soil moisture. The results showed that vegetation cover increased soil moisture in the surface layer (0–20 cm) by 6.81% during wet periods (semi-monthly rainfall &gt;30 mm) relative to an in-situ unvegetated control, but primarily induced a decline of soil moisture in the deep soil layer (20–180 cm) by 19.44% across two growing seasons. Redundancy analysis (RDA) and structural equation modeling (SEM) suggested that these vegetation effects on soil moisture were significantly correlated with vegetative height, leaf area, shallow root allocation, and slope gradient. Our study revealed that tall, small-leaved, and shallow-rooted plants on flat topographies were beneficial to soil water retention and replenishment. This implied that current restoration strategies may be significantly improved through the development of optimal communities and diverse terracing measures. Our findings are anticipated to provide effective guidance for soil water conservation, as well as ecosystem rehabilitation in dry and degraded regions.</span>

<span>The traditional view holds that biological nitrogen (N) fixation often peaks in early- or mid-successional ecosystems and declines throughout succession based on the hypothesis that soil N richness and/or phosphorus (P) depletion become disadvantageous to N fixers. This view, however, fails to support the observation that N fixers can remain active in many old-growth forests despite the presence of N-rich and/or P-limiting soils. Here, we found unexpected increases in N fixation rates in the soil, forest floor, and moss throughout three successional forests and along six age-gradient forests in southern China. We further found that the variation in N fixation was controlled by substrate carbon(C) : N and C : (N : P) stoichiometry rather than by substrate N or P. Our findings highlight the utility of ecological stoichiometry in illuminating the mechanisms that couple forest succession and N cycling.</span>

<span>Biological nitrogen (N) fixation plays an important role in terrestrial N cycling and represents a key driver of terrestrial net primary productivity (NPP). Despite the importance of N fixation in terrestrial ecosystems, our knowledge regarding the controls on terrestrial N fixation remains poor. Here, we conducted a meta-analysis (based on 852 observations from 158 studies) of N fixation across three types of ecosystems with different status of disturbance (no management, restoration [previously disturbed], and disturbance [currently disturbed]) and in response to multiple environmental change factors (warming, elevated carbon dioxide [CO2], increased precipitation, increased drought, increased N deposition, and their combinations). We explored the mechanisms underlying the changes in N fixation by examining the variations in soil physicochemical properties (bulk density, texture, moisture, and pH), plant and microbial characteristics (dominant plant species numbers, plant coverage, and soil microbial biomass), and soil resources (total carbon, total N, total phosphorus (P), inorganic N, and inorganic P). Human disturbance inhibited non-symbiotic N fixation but not symbiotic N fixation. Terrestrial N fixation was stimulated by warming (+152.7%), elevated CO2 (+19.6%), and increased precipitation (+73.1%) but inhibited by increased drought (?30.4%), N deposition (?31.0%), and combinations of available multiple environmental change factors (?14.5%), the extents of which varied among biomes and ecosystem compartments. Human disturbance reduced the N fixation responses to environmental change factors, which was associated with the changes in soil physicochemical properties (2%?56%, p &lt; .001) and the declines in plant and microbial characteristics (3%?49%, p ≤ .003) and soil resources (6%?48%, p ≤ .03). Overall, our findings reveal for the first time the effects of multiple environmental change factors on terrestrial N fixation and indicate the role of human disturbance activities in inhibiting N fixation, which can improve our understanding, modeling, and prediction of terrestrial N budgets, NPP, and ecosystem feedbacks under global change scenarios.</span>

<span>Biodiversity on the Earth is changing at an unprecedented rate due to a variety of global change factors (GCFs). However, the effects of GCFs on microbial diversity is unclear despite that soil microorganisms play a critical role in biogeochemical cycling. Here, we synthesize 1235 GCF observations worldwide and show that microbial rare species are more sensitive to GCFs than common species, while GCFs do not always lead to a reduction in microbial diversity. GCFs-induced shifts in microbial alpha diversity can be predominately explained by the changed soil pH. In addition, GCF impacts on soil functionality are explained by microbial community structure and biomass rather than the alpha diversity. Altogether, our findings of GCF impacts on microbial diversity are fundamentally different from previous knowledge for well-studied plant and animal communities, and are crucial to policy-making for the conservation of microbial diversity hotspots under global changes.</span>

Soil fauna is critical for maintaining ecosystem functioning, and its community could be significantly impacted by nitrogen (N) deposition. However, our knowledge of how soil-faunal community composition responds to N addition is still limited. In this study, we simulated N deposition (0, 50, 100, 150, and 300 kg N ha-1 year-1) to explore the effects of N addition on the total and the phytophagous soil fauna along the soil profile (0-10, 10-25, and 25-40 cm) in poplar plantations (Populus deltoids) on the east coast of China. Ammonium nitrate (NH4NO3) was dissolved in water and sprayed evenly under the canopy with a backpack sprayer to simulate N deposition. Our results showed that N addition either significantly increased or decreased the density (D) of both the total and the phytophagous soil fauna (Dtotal and Dp) at low or high N addition rates, respectively, indicating the existence of threshold effects over the range of N addition. However, N addition had no significant impacts on the number of groups (G) and diversity (H) of either the total or the phytophagous soil fauna (Gtotal, Gp and Htotal, Hp). With increasing soil depth, Dtotal, Dp, Gtotal, and Gp largely decreased, showing that the soil fauna have a propensity to aggregate at the soil surface. Htotal and Hp did not significantly vary along the soil profile. Importantly, the threshold effects of N addition on Dtotal and Dp increased from 50 and 100 to 150 kg N ha-1 year-1 along the soil profile. Fine root biomass was the dominant factor mediating variations in Dtotal and Dp. Our results suggested that N addition may drive changes in soil-faunal community composition by altering belowground food resources in poplar plantations.

Climate change is impacting forested ecosystems worldwide, particularly in the Northern Hemisphere where warming has increased at a faster rate than the rest of the globe. As climate warms, trembling aspen (Populus tremuloides) is expected to become more successful in northern boreal forests because of its current presence in drier areas of North America. However, large-scale productivity decline of aspen has recently been documented throughout the United States and Canada as a result of drought and insect outbreaks. We used tree ring measurements (basal area increment (BAI) and stable carbon isotopes (δ13C)) and remote sensing indices of vegetation productivity (NDVI) to study the impact of climate and damage by the aspen epidermal leaf miner (Phyllocnistis populiella) on aspen productivity and physiology in interior Alaska. We found that productivity decreased with greater leaf mining and was not sensitive to growing season moisture availability. Although productivity decreased during high leaf mining years, it recovered to pre-outbreak levels during years of low insect damage, suggesting a degree of resilience to P. populiella mining. Climate and leaf mining interacted to influence tree ring δ13C, with greater leaf mining resulting in decreased δ13C when growing season moisture availability was low. We also found that NDVI was negatively associated with leaf mining, and positively correlated with BAI and the δ13C decrease corresponding to mining. This suggests that NDVI is capturing not only variations in productivity, but also changes in physiology associated with P. populiella. Overall, these findings indicate that the indirect effects of P. populiella mining have a larger impact on aspen productivity and physiology than climate under current conditions, and is essential to consider when assessing growth, physiology and NDVI trends in interior Alaska.

Plant communities typically exhibit lagged responses to climate change due to poorly understood effects of colonization and local extinction. Here, we quantify rates of change in mean cold tolerances, and contributions of colonization and local extinction to those rates, recorded in plant macrofossil assemblages from North American hot deserts over the last 30,000 years. Location: Mojave, Sonoran and Chihuahuan Deserts. Time period 30-0 thousand years before present (kybp). Major taxa studied: Vascular plants. Methods: Colonization and local extinction dates for 269 plant species were approximated from macrofossils in 15 packrat (Neotoma) midden series. Cold tolerances estimated from contemporary climate were used to quantify assemblage-mean cold tolerances through time. Rates of colonization and local extinction, and their effects on rates of change in assemblage-mean cold tolerances, were estimated for 30-20 kybp (Late Pleistocene, no directional warming), 20-10 kybp (deglaciation, rapid warming) and 10-0 kybp (Holocene, no directional warming). Results: Rates of change in all metrics were negligible during the Late Pleistocene. Rates of change in assemblage-mean cold tolerances (mean 1.0°C x 10-4/yr) lagged behind warming during deglaciation, and continued at similar rates (1.2°C x 10-4/yr) throughout the Holocene. Colonization and local extinction contributed equally to delayed responses to warming, but their dynamics differed through time: Colonization by warm-adapted species predominated during deglaciation, while the most heat-adapted species exhibited long delays in colonization. Only the most cold-adapted species went locally extinct during deglaciation, followed by slow repayment of the extinction debt of cool-adapted species during the Holocene. Main conclusions Responses to rapid warming can persist for millennia, even after cessation of warming. Consistent patterns from different midden series across the region support a metacommunity model in which dispersal interacts with environmental filters and buffers against local extinction to drive community?climate disequilibrium during and after periods of warming.

Variation in life-history strategies can affect metapopulation dynamics and consequently the composition and diversity of communities. However, data sets that allow for the full range of species turnover from colonization to extinction over relevant time periods are limited. The late Quaternary record provides unique opportunities to explore the traits that may have influenced interspecific variation in responses to past climate warming, in particular the rate at which species colonized newly suitable habitat or went locally extinct from degrading habitat. We controlled for differences in species climate niches in order to predict expected colonization and extinction sequences recorded in packrat middens from 15 localities in the Mohave, Sonoran, and Chihuahuan deserts of North America. After accounting for temperature niche differences, we tested the hypotheses that dispersal syndrome (none, wind, vertebrate), growth form (herb, shrub, tree) and seed mass mediated variation in postglacial colonization lags among species, whereas clonality (clonal, non-clonal), growth form, and seed mass affected extinction lags. Growth form and dispersal syndrome interactively affected colonization lags, where herbaceous species lacking long-distance dispersal mechanisms exhibited lags that exceeded those of woody, wind or vertebrate-dispersed species by an average of 2,000-5,000 yr. Growth form and seed mass interactively affected extinction lags, with very small-seeded shrubs persisting for 4,000-8,000 yr longer than other functional groups. Taller, vertebrate-dispersed plants have been shown in other studies to disperse farther than shorter plants without specialized dispersal mechanisms. We found that variation along this axis of dispersal syndromes resulted in dramatic differences in colonization rates in response to past climate change. Very small seeded shrubs may have a unique combination of long vegetative and seed bank lifetimes that may allow them to persist for long periods despite declines in habitat condition. This study indicates that readily measurable traits may help predict which species will be more or less sensitive to future climate change, and inform interventions that can stabilize and promote at-risk populations.

<div class="fixed-element fixedToolbar"><nav aria-label="Article navigation and tools" class="coolBar stickybar"> <div class="stickybar__wrapper coolBar__wrapper clearfix"> <div class="rlist coolBar__zone"> <div class="coolBar__section">The feedback between plant, soil and climate is partly determined by plant litter turnover time, which is influenced by climate, litter quality and soil properties. However, the spatial patterns of litter turnover time and its interrelation with these variables are rarely quantified. With a database of 1,378 litter turnover times and key associated climate, litter quality and soil properties (total of 20 variables), this study investigated the driving factors and spatial patterns of litter turnover time across Chinese terrestrial ecosystems. The mean litter turnover time was the longest in forest ecosystems, followed by that in grassland and cropland ecosystems. The litter turnover time varied significantly depending on the litter quality and climate zone, and increased exponentially as latitude increased. Mean annual temperature (MAT) and mean annual precipitation (MAP) could accurately predict litter turnover time via negative exponential equations. Among these variables, MAT had the greatest influence on litter turnover time, which accounted for 37.4% of the variation, followed by litter quality (ecosystem types, litter types, C:N of litter and lignin content; 33.4%) and soil properties (sand content, soil pH and soil organic carbon (SOC); 29.2%) based on a boosted regression tree (BRT) model. Path analysis identified that MAT negatively affected litter turnover time both directly and indirectly through regulating soil properties and litter quality, which positively and directly affected litter turnover time. Finally, the spatial patterns of litter turnover time were obtained with a regional dataset of ecosystem types, MAT, sand content, soil pH and SOC as BRT model drivers. Overall, our results suggest that climate variables have contrasting effects on litter turnover time and could mediate the impact on litter turnover time by litter quality and soil properties. These results highlight important implications for climate‐smart soil management and can be used to create reliable model predictions.</div> </div> </div> </nav></div>

Fertilization is an important management strategy for crop yields by mediating soil fertility. However, rare studies quantitatively assessed the interactions among fertilization, crop yields, and soil fertility. Here, data from a 25-year fertilization experiment in the humid subtropical region of Southern China were used to evaluate and quantify the effect of fertilization on crop yields via soil fertility. Seven treatments were chosen: CK (non-fertilizer); N (synthetic nitrogen); NP (synthetic N and phosphorus); NPK (synthetic N, P and potassium); NPKM1 (synthetic NPK with manure); 1.5NPKM1 (1.5 times of NPKM1); and M2 (manure alone). Overall, the crop yields of wheat and maize under manure (1.36–1.58 and 3.85-5.82 Mg ha−1) were higher than those under CK (0.34 and 0.25 Mg ha−1) and synthetic fertilized treatments (0.27–0.97 and 0.48–2.65 Mg ha−1), as the averaged of 1991–2015. Higher SOC stocks were found under the NPKM1, 1.5NPKM1, and M2 treatments with a pronounced increase in SOC over the first 10 years and stable over the last 15 years. By the boosted regression trees, manure, synthetic fertilizer and soil properties (SOC storage, soil pH, and soil nutrients) accounted for 39%, 21%, and 40% of the variation of the relative yield, respectively. Path analysis identified a network of inter-relations of manure, synthetic fertilizer, and soil properties in the relative yields. Compared to synthetic fertilized treatments, manure application strongly and positively affected the relative yield by increasing SOC storage, soil nutrients, and soil pH (path coefficients: 0.90, 0.88, and 0.76). These factors explained 72% of the crop yields' variance. These results suggest that manure application is a viable strategy for regulating crop yields due to its improvement in soil fertility.

Manual chamber-based measurements of CO2 (and H2O) fluxes are important for understanding ecosystem carbon metabolism. Small opaque chambers can be used to measure leaf, stem and soil respiration. Larger transparent chambers can be used to measure net ecosystem exchange of CO2, and small jars often serve this purpose for laboratory incubations of soil and plant material. We developed an Android application (app), called Flux Puppy, to facilitate chamber-based flux measurements in the field and laboratory. The app is designed to run on an inexpensive handheld Android device, such as a tablet or phone, and it has a graphical user interface that communicates with a LI-COR LI-820 and LI-830 (CO2) or LI-840 and LI-850 (CO2/H2O) infrared gas analyzer. The app logs concentrations of CO2 and H2O, cell temperature and pressure at 1 Hz, displays the output graphically, and calculates the linear regression slope, R-squared, and standard error of the CO2 time series. A metadata screen allows users to enter operator, site, and plot information, as well as take a photograph using the Android device’s built-in camera, and log measurement location using the device GPS. Additionally, there is a notes field, which can be revised after the measurements are taken. Data files (the 1 s raw data, photograph, and metadata including statistics calculated from the raw data) are then transmitted off the device through file sharing options (Gmail, Outlook, Google Drive, Dropbox etc.). Because Flux Puppy code is open-source (available on GitHub) and the flux measurement system we describe is relatively inexpensive and straightforward to assemble, it should be of broad interest to the carbon cycling community.

Wildfire is an important ecological disturbance that can have cascading effects on ecosystem carbon (C) fluxes. Ecosystem respiration (ER) and soil respiration (SR) account for two of the largest terrestrial C fluxes to the atmosphere, and they play critical roles in regulating C?climate feedbacks. Here, the responses of ER, SR and their source components to experimental burning in a meadow grassland on the Tibetan Plateau were investigated. Fire treatment increased ER by 9% but decreased SR by 15%. The contrasting post-fire responses of SR and ER can be explained by the behaviour of their source components; that is, fire increased aboveground plant respiration (Ragb) by 37%, but decreased heterotrophic respiration (HR) by 21%. Increases in ER and Ragb were mainly related to enhanced plant productivity, whereas smaller SR and HR were associated with reductions in microbial biomass and soil moisture. Accounting for the responses of ER, SR and their intrinsic components has advanced our understanding of how fire affects ecosystem C fluxes. Highlights Fire treatment increased ecosystem respiration (ER) and aboveground plant respiration. Fire treatment decreased soil respiration (SR) and heterotrophic respiration (HR). Increases in ER and aboveground plant respiration were related to plant productivity. Reductions in SR and HR were caused by the suppressed microbial activity.

Soil microorganisms participate in almost all soil organic carbon (SOC) transformations, but they are not represented explicitly in the current generation of earth system models. This study used a data-driven approach to incorporate extracellular enzyme activity into the Terrestrial ECOsystem (TECO) model, and the updated version was named the Data-driven ENZYme (DENZY) model. DENZY is based on results from an extensive data synthesis, which show that the CN ratio is positively correlated with ligninase activity (R2 = 0.50). The latter is inversely correlated to soil organic carbon storage. The DENZY model was parameterized using the revise database to information from a recent meta-analysis and tested for its ability to simulate SOC dynamics at Duke Forest (North Carolina, USA) from 1996 to 2007. DENZY can well simulate the observed negative relationship between ligninase activity and SOC under N deposition conditions (R2 ranges from 0.61 to 0.89). Moreover, outputs from DENZY better matched the observed SOC than its prototype model with the same parameterization. This study provides a simple and straightforward approach to effectively use real-world observations to improve SOC projections in terrestrial biogeochemical models.

Land managers frequently apply vegetation removal and seeding treatments to restore ecosystem function following woody plant encroachment, invasive species spread, and wildfire. However, the long-term outcome of these treatments is unclear due to a lack of widespread monitoring. We quantified how vegetation removal (via wildfire or management) with or without seeding and environmental conditions related to plant community composition change over time in 491 sites across the intermountain western United States. Most community metrics took over 10 years to reach baseline conditions posttreatment, with the slowest recovery observed for native perennial cover. Total cover was initially higher in sites with seeding after vegetation removal than sites with vegetation removal alone, but increased faster in sites with vegetation removal only. Seeding after vegetation removal was associated with rapidly increasing non-native perennial cover and decreasing non-native annual cover. Native perennial cover increased in vegetation removal sites irrespective of seeding and was suppressed by increasing non-native perennial cover. Seeding was associated with higher non-native richness across the monitoring period as well as initially higher, then declining, total and native species richness. Several cover and richness recovery metrics were positively associated with mean annual precipitation and negatively associated with mean annual temperature, whereas relationships with weather extremes depended on the lag time and season. Our results suggest that key plant groups, such as native perennials and non-native annuals, respond to restoration treatments at divergent timescales and with different sensitivities to climate and weather variation.

Wildfire is the dominant disturbance in boreal forests and fire activity is increasing in these regions. Soil fungal communities are important for plant growth and nutrient cycling postfire but there is little understanding of how fires impact fungal communities across landscapes, fire severity gradients, and stand types in boreal forests. Understanding relationships between fungal community composition, particularly mycorrhizas, and understory plant composition is therefore important in predicting how future fire regimes may affect vegetation. We used an extreme wildfire event in boreal forests of Canada's Northwest Territories to test drivers of fungal communities and assess relationships with plant communities. We sampled soils from 39 plots 1 year after fire and 8 unburned plots. High-throughput sequencing (MiSeq, ITS) revealed 2,034 fungal operational taxonomic units. We found soil pH and fire severity (proportion soil organic layer combusted), and interactions between these drivers were important for fungal community structure (composition, richness, diversity, functional groups). Where fire severity was low, samples with low pH had higher total fungal, mycorrhizal, and saprotroph richness compared to where severity was high. Increased fire severity caused declines in richness of total fungi, mycorrhizas, and saprotrophs, and declines in diversity of total fungi and mycorrhizas. The importance of stand age (a surrogate for fire return interval) for fungal composition suggests we could detect long-term successional patterns even after fire. Mycorrhizal and plant community composition, richness, and diversity were weakly but significantly correlated. These weak relationships and the distribution of fungi across plots suggest that the underlying driver of fungal community structure is pH, which is modified by fire severity. This study shows the importance of edaphic factors in determining fungal community structure at large scales, but suggests these patterns are mediated by interactions between fire and forest stand composition.

The continuous increase of nitrogen (N) deposition may exacerbate phosphorus (P) deficiency, which affects soil organic carbon (SOC) decomposition by changing microbial community characteristics in subtropical forests with highly weathered soils. However, there is currently little information about the role of P and the N × P interaction in SOC dynamics. Here, a field nutrient manipulation experiment was established in a subtropical plantation forest in China. Soils collected from simulated N deposition and P addition treatments for 5 years were incubated at 25 °C for 130 days. Soil microbial composition was measured using the phospholipid fatty acid method and the enzyme activities related to SOC hydrolysis were measured. The SOC concentration and δ13C in bulk soil and three particle-size fracfractions were also determined. The cumulative CO2 respired over 9 days, representing the utilization of carbon sources under field conditions, increased with N deposition levels under the without-P treatment, while no significant differences were found among the three N deposition levels in the with-P treatment. Meanwhile, P addition generally suppressed the SOC decomposition during 130 days incubation. Similarly, P addition decreased the potential organic carbon decomposition (C0) and C0/SOC ratio. In contrast, C0 increased with N deposition in the without-P treatment, while was unaffected by N deposition under the with-P treatment, suggesting the response of SOC decomposition to N deposition was affected following P addition by alteration of SOC quality. Moreover, N deposition tended to deplete the δ13C of the SOC and P addition enriched the δ13C of the macro-particulate organic carbon. Addition of P increased total microbial, fungal and bacterial biomass values by 41.6%, 90.0% and 46.9%, respectively, whereas N deposition had no significant effect. Soil fungi/bacteria ratio significantly increased by N deposition and P addition, which partly explained the reduction of SOC decomposition after P addition. The cellobioside activity significantly decreased by 48.3% after P addition, while cellobioside and β-xylosidase activities increased with N deposition, suggesting that N deposition and P addition had opposite roles in the SOC stability. These results indicate that the positive effect of N deposition on SOC decomposition was suppressed when P was added by changing microbial community and enzyme activity and enhanced P availability may result in increased SOC accumulation under N deposition scenarios in subtropical forests.

Tundra ecosystems are typically carbon (C) rich but nitrogen (N) limited. Since biological N2 fixation is the major source of biologically available N, the soil N2-fixing (i.e., diazotrophic) community serves as an essential N supplier to the tundra ecosystem. Recent climate warming has induced deeper permafrost thaw and adversely affected C sequestration, which is modulated by N availability. Therefore, it is crucial to examine the responses of diazotrophic communities to warming across the depths of tundra soils. Herein, we carried out one of the deepest sequencing efforts of nitrogenase gene (nifH) to investigate how 5 years of experimental winter warming affects Alaskan soil diazotrophic community composition and abundance spanning both the organic and mineral layers. Although soil depth had a stronger influence on diazotrophic community composition than warming, warming significantly (P &amp;amp;lt; 0.05) enhanced diazotrophic abundance by 86.3% and aboveground plant biomass by 25.2%. Diazotrophic composition in the middle and lower organic layers, detected by nifH sequencing and a microarray-based tool (GeoChip), was markedly altered, with an increase of α-diversity. Changes in diazotrophic abundance and composition significantly correlated with soil moisture, soil thaw duration, and plant biomass, as shown by structural equation modeling analyses. Therefore, more abundant diazotrophic communities induced by warming may potentially serve as an important mechanism for supplementing biologically available N in this tundra ecosystem.IMPORTANCE With the likelihood that changes in global climate will adversely affect the soil C reservoir in the northern circumpolar permafrost zone, an understanding of the potential role of diazotrophic communities in enhancing biological N2 fixation, which constrains both plant production and microbial decomposition in tundra soils, is important in elucidating the responses of soil microbial communities to global climate change. A recent study showed that the composition of the diazotrophic community in a tundra soil exhibited no change under a short-term (1.5-year) winter warming experiment. However, it remains crucial to examine whether the lack of diazotrophic community responses to warming is persistent over a longer time period as a possibly important mechanism in stabilizing tundra soil C. Through a detailed characterization of the effects of winter warming on diazotrophic communities, we showed that a long-term (5-year) winter warming substantially enhanced diazotrophic abundance and altered community composition, though soil depth had a stronger influence on diazotrophic community composition than warming. These changes were best explained by changes in soil moisture, soil thaw duration, and plant biomass. These results provide crucial insights into the potential factors that may impact future C and N availability in tundra regions.

The boreal zone of Alaska is dominated by interactions between disturbances, vegetation, and soils. These interactions are likely to change in the future through increasing permafrost thaw, more frequent and intense wildfires, and vegetation change from drought and competition. We utilize an individual tree-based vegetation model, the University of Virginia Forest Model Enhanced (UVAFME), to estimate current and future forest conditions across sites within interior Alaska. We updated UVAFME for application within interior Alaska, including improved simulation of permafrost dynamics, litter decay, nutrient dynamics, fire mortality, and post-fire regrowth. Following these updates, UVAFME output on species-specific biomass and stem density was comparable to inventory measurements at various forest types within interior Alaska. We then simulated forest response to climate change at specific inventory locations and across the Tanana Valley River Basin on a 2 × 2 km2 grid. We derived projected temperature and precipitation from a five-model average taken from the CMIP5 archive under the RCP 4.5 and 8.5 scenarios. Results suggest that climate change and the concomitant impacts on wildfire and permafrost dynamics will result in overall decreases in biomass (particularly for spruce (Picea spp.)) within the interior Tanana Valley, despite increases in quaking aspen (Populus tremuloides) biomass, and a resulting shift towards higher deciduous fraction. Simulation results also predict increases in biomass at cold, wet locations and at high elevations, and decreases in biomass in dry locations, under both moderate (RCP 4.5) and extreme (RCP 8.5) climate change scenarios. These simulations demonstrate that a highly detailed, species interactive model can be used across a large region within Alaska to investigate interactions between vegetation, climate, wildfire, and permafrost. The vegetation changes predicted here have the capacity to feed back to broader scale climate-forest interactions in the North American boreal forest, a region which contributes significantly to the global carbon and energy budgets.

Dynamic global vegetation models are key tools for interpreting and forecasting the responses of terrestrial ecosystems to climatic variation and other drivers. They estimate plant growth as the outcome of the supply of carbon through photosynthesis. However, growth is itself under direct control, and not simply controlled by the amount of available carbon. Therefore predictions by current photosynthesis-driven models of large increases in future vegetation biomass due to increasing concentrations of atmospheric CO2may be significant over-estimations. We describe how current understanding of wood formation can be used to reformulate global vegetation models, with potentially major implications for their behaviour.

Dynamic global vegetation models are key tools for interpreting and forecasting the responses of terrestrial ecosystems to climatic variation and other drivers. They estimate plant growth as the outcome of the supply of carbon through photosynthesis. However, growth is itself under direct control, and not simply controlled by the amount of available carbon. Therefore predictions by current photosynthesis-driven models of large increases in future vegetation biomass due to increasing concentrations of atmospheric CO2may be significant over-estimations. We describe how current understanding of wood formation can be used to reformulate global vegetation models, with potentially major implications for their behaviour.

It is critical to accurately estimate carbon (C) turnover time as it dominates the uncertainty in ecosystem C sinks and their response to future climate change. In the absence of direct observations of ecosystem C losses, C turnover times are commonly estimated under the steady state assumption (SSA), which has been applied across a large range of temporal and spatial scales including many at which the validity of the assumption is likely to be violated. However, the errors associated with improperly applying SSA to estimate C turnover time and its covariance with climate as well as ecosystem C sequestrations have yet to be fully quantified. Here, we developed a novel model-data fusion framework and systematically analyzed the SSA-induced biases using time-series data collected from 10 permanent forest plots in the eastern China monsoon region. The results showed that (a) the SSA significantly underestimated mean turnover times (MTTs) by 29%, thereby leading to a 4.83-fold underestimation of the net ecosystem productivity (NEP) in these forest ecosystems, a major C sink globally; (b) the SSA-induced bias in MTT and NEP correlates negatively with forest age, which provides a significant caveat for applying the SSA to young-aged ecosystems; and (c) the sensitivity of MTT to temperature and precipitation was 22% and 42% lower, respectively, under the SSA. Thus, under the expected climate change, spatiotemporal changes in MTT are likely to be underestimated, thereby resulting in large errors in the variability of predicted global NEP. With the development of observation technology and the accumulation of spatiotemporal data, we suggest estimating MTTs at the disequilibrium state via long-term data assimilation, thereby effectively reducing the uncertainty in ecosystem C sequestration estimations and providing a better understanding of regional or global C cycle dynamics and C-climate feedback.

Accurate estimates of microbial carbon use efficiency (CUE) are required to predict how global change will impact microbially-mediated ecosystem functions such as organic matter decomposition. Multiple approaches are currently used to quantify CUE but the extent to which estimates reflect methodological variability is unknown. This limits our ability to apply or cross-compare published CUE values. Here we evaluated the performance of five methods in a single soil under standard conditions. The microbial response to three substrate amendment rates (0.0, 0.05, and 2.0 mg glucose-C g−1 soil) was examined using: 13C and 18O isotope tracing approaches which estimate CUE based on substrate uptake and growth dynamics; calorespirometry which infers growth and CUE from metabolic heat and respiration rates; metabolic flux analysis where CUE is determined as the balance between biosynthesis and respiration using position-specific 13CO2 production of labeled glucose; and stoichiometric modeling which derives CUE from elemental ratios of microbial biomass, substrate, and exoenzyme activity. The CUE estimates we obtained differed by method and substrate concentration, ranging under in situ conditions from &lt;0.4 for the substrate-nonspecific methods that do not use C tracers (18O, stoichiometric modeling) to &gt;0.6 for the substrate-specific methods that trace glucose use (13C method, calorespirometry, metabolic flux analysis). We explore the different aspects of microbial metabolism that each method captures and how this affects the interpretation of CUE estimates. We recommend that users consider the strengths and weaknesses of each method when choosing the technique that will best address their research needs.

Reforestation is challenging when timber harvested areas have been degraded, invaded by nonnative species, or are of marginal suitability to begin with. Conifers form mutualistic partnerships with ectomycorrhizal fungi (EMF) to obtain greater access to soil resources, and these partnerships may be especially important in degraded areas. However, timber harvest can impact mycorrhizal fungi by removing or compacting topsoil, removing host plants, and warming and drying the soil. We used a field experiment to evaluate the role of EMF in Douglas-fir reforestation in clearcuts invaded by Cytisus scoparius (Scotch broom) where traditional reforestation approaches have repeatedly failed. We tested how planting distance from intact Douglas-fir forest edges influenced reforestation success and whether inoculation with forest soils can be used to restore EMF relationships. We used an Illumina DNA sequencing approach to measure the abundance, richness and composition of ectomycorrhizal fungi on Douglas-fir roots, and assessed differences in Douglas-fir seedling survival and growth near to and far from forest edges with and without forest soil inoculum. Planting Douglas-fir seedlings near forest edges increased seedling survival, growth, and EMF root colonization. Edge proximity had no effect on EMF richness but did change fungal community composition. Inoculations with forest soil did not increase EMF abundance or richness or change community composition, nor did it improve seedling establishment. With Illumina sequencing, we identified two to three times greater species richness than described in previous edge effects studies. Of the 95 EMF species we identified, 40% of the species occurred on less than 5% of the seedlings. The ability to detect fungi at low abundance may explain why we did not detect differences in EMF richness with distance to hosts as previous studies. Our findings suggest that forest edges are suitable for reforestation, even when the interiors of deforested areas are not. We advocate for timber harvest designs that maximize edge habitat where ectomycorrhizal fungi contribute to tree establishment. However, this study does not support the use of inoculation with forest soil as a simple method to enhance EMF and seedling survival.

Forests remove about 30% of anthropogenic CO2 emissions through photosynthesis and return almost 40% of incident precipitation back to the atmosphere via transpiration. The trade-off between photosynthesis and transpiration through stomata, the water-use efficiency (WUE), is an important driver of plant evolution and ecosystem functioning, and has profound effects on climate. Using stable carbon and oxygen isotope ratios in tree rings, we found that WUE has increased by a magnitude consistent with estimates from atmospheric measurements and model predictions. Enhanced photosynthesis was widespread, while reductions in stomatal conductance were modest and restricted to moisture-limited forests. This result points to smaller reductions in transpiration in response to increasing atmospheric CO2, with important implications for forest–climate interactions, which remain to be explored.Multiple lines of evidence suggest that plant water-use efficiency (WUE)—the ratio of carbon assimilation to water loss—has increased in recent decades. Although rising atmospheric CO2 has been proposed as the principal cause, the underlying physiological mechanisms are still being debated, and implications for the global water cycle remain uncertain. Here, we addressed this gap using 30-y tree ring records of carbon and oxygen isotope measurements and basal area increment from 12 species in 8 North American mature temperate forests. Our goal was to separate the contributions of enhanced photosynthesis and reduced stomatal conductance to WUE trends and to assess consistency between multiple commonly used methods for estimating WUE. Our results show that tree ring-derived estimates of increases in WUE are consistent with estimates from atmospheric measurements and predictions based on an optimal balancing of carbon gains and water costs, but are lower than those based on ecosystem-scale flux observations. Although both physiological mechanisms contributed to rising WUE, enhanced photosynthesis was widespread, while reductions in stomatal conductance were modest and restricted to species that experienced moisture limitations. This finding challenges the hypothesis that rising WUE in forests is primarily the result of widespread, CO2-induced reductions in stomatal conductance.

Plant water potential Ψ is regulated by stomatal responses to atmospheric moisture demand D and soil water availability W, but the timescales of influence and interactions between these drivers of plant Ψ are poorly understood. Here, we quantify the effects of antecedent D and W on plant Ψ in the desert shrub Larrea tridentata. Repeated measurements of plant baseline water potential ΨB and diurnal water potential ΨD were analyzed in a Bayesian framework to evaluate the influence of antecedent D and W at daily and subdaily timescales. Both ΨB and ΨD exhibited negative, 2- to 4-d lagged responses to daily-scale D; conversely, plant ΨD responded almost instantaneously to subdaily D, though the direction of this response depended on antecedent moisture conditions. Plant ΨB and ΨD responded positively and immediately (no lag) to shallow W, which contrasts the negative, lagged (6-7 d) response to deep W. The changing sensitivity of ΨD to subdaily D highlights shifting modes of plant Ψ regulation: D effects on ΨD range from negative to neutral to positive depending on past conditions and time of day. Explicit consideration of antecedent conditions across multiple timescales can reveal important complexities in plant responses.

Determining the temporal scaling of biodiversity, typically described as species–time relationships (STRs), in the face of global climate change is a central issue in ecology because it is fundamental to biodiversity preservation and ecosystem management. However, whether and how climate change affects microbial STRs remains unclear, mainly due to the scarcity of long-term experimental data. Here, we examine the STRs and phylogenetic–time relationships (PTRs) of soil bacteria and fungi in a long-term multifactorial global change experiment with warming (+3 °C), half precipitation (−50%), double precipitation (+100%) and clipping (annual plant biomass removal). Soil bacteria and fungi all exhibited strong STRs and PTRs across the 12 experimental conditions. Strikingly, warming accelerated the bacterial and fungal STR and PTR exponents (that is, the w values), yielding significantly (P &lt; 0.001) higher temporal scaling rates. While the STRs and PTRs were significantly shifted by altered precipitation, clipping and their combinations, warming played the predominant role. In addition, comparison with the previous literature revealed that soil bacteria and fungi had considerably higher overall temporal scaling rates (w = 0.39–0.64) than those of plants and animals (w = 0.21–0.38). Our results on warming-enhanced temporal scaling of microbial biodiversity suggest that the strategies of soil biodiversity preservation and ecosystem management may need to be adjusted in a warmer world.

The susceptibility of soil organic carbon (SOC) in tundra to microbial decomposition under warmer climate scenarios potentially threatens a massive positive feedback to climate change, but the underlying mechanisms of stable SOC decomposition remain elusive. Herein, Alaskan tundra soils from three depths (a fibric O horizon with litter and course roots, an O horizon with decomposing litter and roots, and a mineral-organic mix, laying just above the permafrost) were incubated. Resulting respiration data were assimilated into a 3-pool model to derive decomposition kinetic parameters for fast, slow, and passive SOC pools. Bacterial, archaeal, and fungal taxa and microbial functional genes were profiled throughout the 3-year incubation. Correlation analyses and a Random Forest approach revealed associations between model parameters and microbial community profiles, taxa, and traits. There were more associations between the microbial community data and the SOC decomposition parameters of slow and passive SOC pools than those of the fast SOC pool. Also, microbial community profiles were better predictors of model parameters in deeper soils, which had higher mineral contents and relatively greater quantities of old SOC than in surface soils. Overall, our analyses revealed the functional potential of microbial communities to decompose tundra SOC through a suite of specialized genes and taxa. These results portray divergent strategies by which microbial communities access SOC pools across varying depths, lending mechanistic insights into the vulnerability of what is considered stable SOC in tundra regions.

The ratio of CO efflux to influx (ARQ, apparent respiratory quotient) in tree stems is expected to be 1.0 for carbohydrates, the main substrate supporting stem respiration. In previous studies of stem fluxes, ARQ values below 1.0 were observed and hypothesized to indicate retention of respired carbon within the stem. Here, we demonstrate that stem ARQ 1.0 values are common across 85 tropical, temperate, and Mediterranean forest trees from nine different species. Mean ARQ values per species per site ranged from 0.39 to 0.78, with an overall mean of 0.59. Assuming that uptake provides a measure of in situ stem respiration (due to the low solubility of O2), the overall mean indicates that on average 41% of CO2 respired in stems is not emitted from the local stem surface. The instantaneous ARQ did not vary with sap flow. ARQ values of incubated stem cores were similar to those measured in stem chambers on intact trees. We therefore conclude that dissolution of CO2 in the xylem sap and transport away from the site of respiration cannot explain the low ARQ values. We suggest refixation of respired CO2 in biosynthesis reactions as possible mechanism for low ARQ values.

The dynamics of soil phosphorus (P) control its bioavailability. Yet it remains a challenge to quantify soil P dynamics. Here we developed a soil P dynamics (SPD) model. We then assimilated eight data sets of 426-day changes in Hedley P fractions into the SPD model, to quantify the dynamics of six major P pools in eight soil samples that are representative of a wide type of soils. The performance of our SPD model was better for labile P, secondary mineral P, and occluded P than for nonoccluded organic P (Po) and primary mineral P. All parameters describing soil P dynamics were approximately constrained by the data sets. The average turnover rates were labile P 0.040 g g?1 day?1, nonoccluded Po 0.051 g g?1 day?1, secondary mineral P 0.023 g g?1 day?1, primary mineral P 0.00088 g g?1 day?1, occluded Po 0.0066 g g?1 day?1, and occluded inorganic P 0.0065 g g?1 day?1, in the greenhouse environment studied. Labile P was transferred on average more to nonoccluded Po (transfer coefficient of 0.42) and secondary mineral P (0.38) than to plants (0.20). Soil pH and organic C concentration were the key soil properties regulating the competition for P between plants and soil secondary minerals. The turnover rate of labile P was positively correlated with that of nonoccluded Po and secondary mineral P. The pool size of labile P was most sensitive to its turnover rate. Overall, we suggest data assimilation can contribute significantly to an improved understanding of soil P dynamics.

<p id="d1e248">Predicting future changes in ecosystem services is not only highly desirable but is also becoming feasible as several forces (e.g., available big data, developed data assimilation (DA) techniques, and advanced cyber-infrastructure) are converging to transform ecological research into quantitative forecasting. To realize ecological forecasting, we have developed an Ecological Platform for Assimilating Data (EcoPAD, v1.0) into models. EcoPAD (v1.0) is a web-based software system that automates data transfer and processing from sensor networks to ecological forecasting through data management, model simulation, data assimilation, forecasting, and visualization. It facilitates interactive data–model integration from which the model is recursively improved through updated data while data are systematically refined under the guidance of model. EcoPAD (v1.0) relies on data from observations, process-oriented models, DA techniques, and the web-based workflow.</p> <p id="d1e251">We applied EcoPAD (v1.0) to the Spruce and Peatland Responses Under Climatic and Environmental change (SPRUCE) experiment in northern Minnesota. The EcoPAD-SPRUCE realizes fully automated data transfer, feeds meteorological data to drive model simulations, assimilates both manually measured and automated sensor data into the Terrestrial ECOsystem (TECO) model, and recursively forecasts the responses of various biophysical and biogeochemical processes to five temperature and two <span class="inline-formula">CO₂</span> treatments in near-real time (weekly). Forecasting with EcoPAD-SPRUCE has revealed that mismatches in forecasting carbon pool dynamics are more related to model (e.g., model structure, parameter, and initial value) than forcing variables, opposite to forecasting flux variables. EcoPAD-SPRUCE quantified acclimations of methane production in response to warming treatments through shifted posterior distributions of the <span class="inline-formula">CH₄:CO₂</span> ratio and the temperature sensitivity (<span class="inline-formula"><i>Q</i>₁₀</span>) of methane production towards lower values. Different case studies indicated that realistic forecasting of carbon dynamics relies on appropriate model structure, correct parameterization, and accurate external forcing. Moreover, EcoPAD-SPRUCE stimulated active feedbacks between experimenters and modelers to identify model components to be improved<span id="page1120"></span> and additional measurements to be taken. It has become an interactive model–experiment (ModEx) system and opens a novel avenue for interactive dialogue between modelers and experimenters. Altogether, EcoPAD (v1.0) acts to integrate multiple sources of information and knowledge to best inform ecological forecasting.</p>

Forest ecosystems sequester approximately 12% of anthropogenic carbon emissions, and efforts to increase forest carbon uptake are central to climate change mitigation policy. Managing forests to store carbon has focused on increasing forested area, decreasing area lost to logging and clearing, and increasing forest carbon density. Warming, drought, and wildfires challenge the stability of carbon stored in forests. By contrast, natural cycles of low-intensity fires in dry forests can, over the long term, promote forest carbon storage by protecting carbon in soil and in large, old trees. The conundrum is how to balance immediate, disturbance-driven carbon loss with long-term, stable carbon storage and account for these risks in policies for forest carbon management.

Organic carbon stored in high-latitude permafrost represents a potential positive feedback to climate warming as well as a valuable store of paleoenvironmental information. The below-freezing conditions have effectively removed permafrost organic material from the modern carbon cycle and preserved its pre-freezing bulk and molecular states. The conditions that lead to efficient burial of organic carbon (OC) within permafrost were investigated by measuring OC stocks, past accumulation rates, and biogeochemical composition of a permafrost core taken from Interior Alaska dating back to 40 ka. The post-glacial Marine Isotope Stage 1 is represented by the top 1.2 m of the core and contains 64.7 kg OC/m2 with an accumulation rate of 4.3 g OC/m2/yr. The sediments that accumulated around the Last Glacial Maximum contain 9.9 kg OC/m2 with an accumulation rate of 0.5 g OC/m2/yr. Carbon storage (144.7 kg OC/m2) and accumulation (26.1 g OC/m2/yr) are both observed to be greatest between 35 and 40 ka, late during the Marine Isotope Stage 3 global interstadial. The extent of OC degradation was assessed using lignin and amino acid biomarkers with both approaches indicating well-preserved contemporary active layer and interstadial OC, whereas stadial OC was highly degraded. Lignin compositional indices throughout the core appear altered by sorptive processes that confounded some expected trends in the overall organic matter composition, while amino acids provided a more integrated pattern of change. Significant correlations between carbon-normalized hydroxyproline and total lignin concentrations further support the usefulness of hydroxyproline as an indicator for the abundance of plant organic matter. A novel amino acid plant-microbial index of the ratio of microbial-specific muramic acid and diaminopimelic acid biomarkers to the plant-specific hydroxyproline biomarker, indicate a transition from plant-dominated organic matter in fresh organic soils (index values of 0.01–0.20) to more microbial-dominated organic matter in degraded mineral soils (index values of 0.50–2.50). The branched glycerol dialkyl glycerol tetraether composition is complex and is not immediately compatible with existing temperature transfer functions. Residence time within the active layer is interpreted to integrate key factors such as primary productivity, inorganic sediment delivery, and other climate factors that control soil organic matter degradation. The Marine Isotope Stage 3, mid-Wisconsin interstadial period at this locality was forest-dominated and suggests the currently prevailing tundra ecotone is sensitive to environmental change. The majority of buried permafrost OC is high in degradability and if thawed, would be expected to be highly vulnerable to microbial decomposition.

The effect of rain on the phyllosphere community has not been extensively explored, especially in the context of spatial variation on the impact of rain throughout the tree canopy. We characterized the response of the phyllosphere bacterial community removed from leaf surfaces of the Southern Magnolia (Magnolia grandiflora) to rain across different spatial locations of the canopy. We hypothesized that: (1) rain would lead to an initial decrease in phyllosphere bacterial diversity, followed by an increase in diversity on subsequent days, but that this effect would be minimized in the lower and interior portion of the canopy, and that (2) community beta dispersion of phyllosphere microorganisms would be lower following rain, and similarly contingent on canopy position. We used targeted next-generation sequencing of the V4 region of the bacterial 16S rRNA gene to characterize bacterial composition. We found higher bacterial richness in interior canopy and distinct composition across canopy positions. Further, the effect of rain on beta dispersion was contingent on canopy position: rain lowered dispersion in the upper canopy but increased it in the lower and interior canopy. Our results demonstrate that canopy structure should be considered when looking at the impact of rain on the collective phyllosphere community.

Nutrient resorption from senescing leaves is one of the plants&amp;rsquo; essential nutrient conservation strategies. Parameters associated with resorption are important nutrient-cycling constraints for accurate predictions of long-term primary productivity in forest ecosystems. However, we know little about the spatial patterns and drivers of leaf nutrient resorption in planted forests worldwide. By synthesizing results of 146 studies, we explored nitrogen (N) and phosphorus (P) resorption efficiency (NRE and PRE) among climate zones and tree functional types, as well as the factors that play dominant roles in nutrient resorption in plantations globally. Our results showed that the mean NRE and PRE were 58.98% &amp;plusmn; 0.53% and 60.21% &amp;plusmn; 0.77%, respectively. NRE significantly increased from tropical to boreal zones, while PRE did not significantly differ among climate zones, suggesting differential impacts of climates on NRE and PRE. Plant functional types exert a strong influence on nutrient resorption. Conifer trees had higher PRE than broadleaf trees, reflecting the adaptation of the coniferous trees to oligotrophic habitats. Deciduous trees had lower PRE than evergreen trees that are commonly planted in P-limited low latitudes and have long leaf longevity with high nutrient use efficiency. While non-N-fixing trees had higher NRE than N-fixing trees, the PRE of non-N-fixing trees was lower than that of N-fixing trees, indicating significant impact of the N-fixing ability on the resorption of N and P. Our multivariate regression analyses showed that variations in NRE were mainly regulated by climates (mean annual precipitation and latitude), while variations in PRE were dominantly controlled by green leaf nutrient concentrations (N and P). Our results, in general, suggest that the predicted global warming and changed precipitation regimes may profoundly affect N cycling in planted forests. In addition, green leaf nutrient concentrations may be good indicators for PRE in planted forests.

Rice is a staple food for nearly half of the world's population, but rice paddies constitute a major source of anthropogenic CH4 emissions. Root exudates from growing rice plants are an important substrate for methane-producing microorganisms. Therefore, breeding efforts optimizing rice plant photosynthate allocation to grains, i.e., increasing harvest index (HI), are widely expected to reduce CH4 emissions with higher yield. Here we show, by combining a series of experiments, meta-analyses and an expert survey, that the potential of CH4 mitigation from rice paddies through HI improvement is in fact small. Whereas HI improvement reduced CH4 emissions under continuously flooded (CF) irrigation, it did not affect CH4 emissions in systems with intermittent irrigation (II). We estimate that future plant breeding efforts aimed at HI improvement to the theoretical maximum value will reduce CH4 emissions in CF systems by 4.4%. However, CF systems currently make up only a small fraction of the total rice growing area (i.e., 27% of the Chinese rice paddy area). Thus, to achieve substantial CH4 mitigation from rice agriculture, alternative plant breeding strategies may be needed, along with alternative management.

Ongoing permafrost thaw is expected to stimulate microbial release of greenhouse gases, threatening to further exacerbate climate change (cause positive feedback). In this study, a unique field warming experiment was conducted in Interior Alaska to promote surface permafrost degradation while maintaining uniform hydraulic conditions. After 5 winters of experimental warming by ∼1 °C, microbial community shifts were observed at the receded permafrost/active layer boundary, which reflected more reduced conditions, including increased methanogenesis. In contrast, increased carbohydrate utilization (respiration) was observed at the surface layer. These shifts were relatable to observed increases in CO2 and CH4 release from this study site and the surrounding ecosystem. Collectively, our results demonstrate that microbial responses to warming are rapid and identify potential biomarkers that could be important in modeling.Northern-latitude tundra soils harbor substantial carbon (C) stocks that are highly susceptible to microbial degradation with rising global temperatures. Understanding the magnitude and direction (e.g., C release or sequestration) of the microbial responses to warming is necessary to accurately model climate change. In this study, Alaskan tundra soils were subjected to experimental in situ warming by ∼1.1 °C above ambient temperature, and the microbial communities were evaluated using metagenomics after 4.5 years, at 2 depths: 15 to 25 cm (active layer at outset of the experiment) and 45 to 55 cm (transition zone at the permafrost/active layer boundary at the outset of the experiment). In contrast to small or insignificant shifts after 1.5 years of warming, 4.5 years of warming resulted in significant changes to the abundances of functional traits and the corresponding taxa relative to control plots (no warming), and microbial shifts differed qualitatively between the two soil depths. At 15 to 25 cm, increased abundances of carbohydrate utilization genes were observed that correlated with (increased) measured ecosystem carbon respiration. At the 45- to 55-cm layer, increased methanogenesis potential was observed, which corresponded with a 3-fold increase in abundance of a single archaeal clade of the Methanosarcinales order, increased annual thaw duration (45.3 vs. 79.3 days), and increased CH4 emissions. Collectively, these data demonstrate that the microbial responses to warming in tundra soil are rapid and markedly different between the 2 critical soil layers evaluated, and identify potential biomarkers for the corresponding microbial processes that could be important in modeling.

Climate warming is leading to greater precipitation variability, resulting in increased frequency and intensity of both drought and wet extremes. However, how these extreme events interact with climate warming and hay-harvest in grasslands to impact ecosystem functions has not yet been well explored. In this study, we took advantage of a long-term experiment to examine how climate warming and clipping (i.e., mimicking hay harvest) regulated impacts of naturally occurring drought and wet extremes on ecosystem CO2 fluxes of a tallgrass prairie in the Great Plains, USA. Warming resulted in net ecosystem carbon release (i.e., positive net ecosystem CO2 exchange, NEE) in the extreme drought year of 2011, but significantly enhanced net carbon uptake in the extremely wet year of 2015 in comparison with NEE in normal years. Warming-induced carbon release in the drought year was due to significantly enhanced ecosystem respiration (ER) from mid-summer to early-autumn, whereas warming-enhanced NEE in the wet year was due to an increase in aboveground net primary production (ANPP) compared to those in normal years. Drought diminished warming-induced increases in ANPP to about one sixth of that in the wet year in the unclipped plots. Interestingly, clipping offset the drought-mediated ecosystem carbon loss by increasing GPP and weakened the wet-enhanced ANPP. Overall, our results suggest that a future, warmer climate may exacerbate carbon losses in terrestrial ecosystems during drought extremes but stimulate the ecosystem carbon sink under wet extremes.

Accurate prediction of community responses to global change drivers (GCDs) is critical given the effects of biodiversity on ecosystem services. There is consensus that human activities are driving species extinctions at the global scale, but debate remains over whether GCDs are systematically altering local communities worldwide. Across 105 experiments that included over 400 experimental manipulations, we found evidence for a lagged response of herbaceous plant communities to GCDs caused by shifts in the identities and relative abundances of species, often without a corresponding difference in species richness. These results provide evidence that community responses are pervasive across a wide variety of GCDs on long-term temporal scales and that these responses increase in strength when multiple GCDs are simultaneously imposed.Global change drivers (GCDs) are expected to alter community structure and consequently, the services that ecosystems provide. Yet, few experimental investigations have examined effects of GCDs on plant community structure across multiple ecosystem types, and those that do exist present conflicting patterns. In an unprecedented global synthesis of over 100 experiments that manipulated factors linked to GCDs, we show that herbaceous plant community responses depend on experimental manipulation length and number of factors manipulated. We found that plant communities are fairly resistant to experimentally manipulated GCDs in the short term (&amp;amp;lt;10 y). In contrast, long-term (≥10 y) experiments show increasing community divergence of treatments from control conditions. Surprisingly, these community responses occurred with similar frequency across the GCD types manipulated in our database. However, community responses were more common when 3 or more GCDs were simultaneously manipulated, suggesting the emergence of additive or synergistic effects of multiple drivers, particularly over long time periods. In half of the cases, GCD manipulations caused a difference in community composition without a corresponding species richness difference, indicating that species reordering or replacement is an important mechanism of community responses to GCDs and should be given greater consideration when examining consequences of GCDs for the biodiversity–ecosystem function relationship. Human activities are currently driving unparalleled global changes worldwide. Our analyses provide the most comprehensive evidence to date that these human activities may have widespread impacts on plant community composition globally, which will increase in frequency over time and be greater in areas where communities face multiple GCDs simultaneously.

Warming temperatures are likely to accelerate permafrost thaw in the Arctic, potentially leading to the release of old carbon previously stored in deep frozen soil layers. Deeper thaw depths in combination with geomorphological changes due to the loss of ice structures in permafrost, may modify soil water distribution, creating wetter or drier soil conditions. Previous studies revealed higher ecosystem respiration rates under drier conditions, and this study investigated the cause of the increased ecosystem respiration rates using radiocarbon signatures of respired CO2 from two drying manipulation experiments: one in moist and the other in wet tundra. We demonstrate that higher contributions of CO2 from shallow soil layers (0?15 cm; modern soil carbon) drive the increased ecosystem respiration rates, while contributions from deeper soil (below 15 cm from surface and down to the permafrost table; old soil carbon) decreased. These changes can be attributed to more aerobic conditions in shallow soil layers, but also the soil temperature increases in shallow layers but decreases in deep layers, due to the altered thermal properties of organic soils. Decreased abundance of aerenchymatous plant species following drainage in wet tundra reduced old carbon release but increased aboveground plant biomass elevated contributions of autotrophic respiration to ecosystem respiration. The results of this study suggest that drier soils following drainage may accelerate decomposition of modern soil carbon in shallow layers but slow down decomposition of old soil carbon in deep layers, which may offset some of the old soil carbon loss from thawing permafrost. This article is protected by copyright. All rights reserved.

Shifts in the extent of the boreal forest during past warm intervals and correlations between climate and the position of the forest–tundra ecotone suggest that recent temperature increases will facilitate forest expansion into tundra ecosystems. In this study, we used a unique set of high-resolution repeat photographs to characterize white spruce (<i>Picea glauca</i> (Moench) Voss) populations in 1980 and 2015 at 52 sites across the forest–tundra transition in the Northwest Territories, Canada. We also conducted field inventories at eight sites to examine mapping accuracy, construct age distributions, and assess cone production and seed viability. Our analysis shows that stand density in the forest–tundra has increased significantly since 1980 but that the density of spruce at sites in the tundra has not changed. Age distributions constructed from field sampling also indicate that recent recruitment has occurred in the forest–tundra but not at tundra sites. The nonlinear relationship between summer temperature and seed viability suggests that recent warming has facilitated recruitment in the northern Subarctic but that cold temperatures still limit recruitment at higher latitude tundra sites. Additional research to determine the extent of changes in forest density across the northern Subarctic should be conducted to determine if similar changes are occurring across this ecotone.

Relationships between microbial genes and performance are often evaluated in the laboratory in pure cultures, with little validation in nature. Here, we show that genomic traits related to laboratory measurements of maximum growth potential failed to predict the growth rates of bacteria in unamended soil, but successfully predicted growth responses to resource pulses: growth increased with 16S rRNA gene copy number and declined with genome size after substrate addition to soils, responses that were repeated in four different ecosystems. Genome size best predicted growth rate in response to addition of glucose alone; adding ammonium with glucose weakened the relationship, and the relationship was absent in nutrient-replete pure cultures, consistent with the idea that reduced genome size is a mechanism of nutrient conservation. Our findings demonstrate that genomic traits of soil bacteria can map to their ecological performance in nature, but the mapping is poor under native soil conditions, where genomic traits related to stress tolerance may prove more predictive. These results remind that phenotype depends on environmental context, underscoring the importance of verifying proposed schemes of trait-based strategies through direct measurement of performance in nature, an important and currently missing foundation for translating microbial processes from genes to ecosystems.

Global soil carbon (C) stocks are expected to decline with warming, and changes in microbial processes are key to this projection. However, warming responses of critical microbial parameters such as carbon use efficiency (CUE) and biomass turnover (rB) are not well understood. Here, we determine these parameters using a probabilistic inversion approach that integrates a microbial-enzyme model with 22 years of carbon cycling measurements at Harvard Forest. We find that increasing temperature reduces CUE but increases rB, and that two decades of soil warming increases the temperature sensitivities of CUE and rB. These temperature sensitivities, which are derived from decades-long field observations, contrast with values obtained from short-term laboratory experiments. We also show that long-term soil C flux and pool changes in response to warming are more dependent on the temperature sensitivity of CUE than that of rB. Using the inversion-derived parameters, we project that chronic soil warming at Harvard Forest over six decades will result in soil C gain of 1.0% on average (1st and 3rd quartiles: 3.0% loss and 10.5% gain) in the surface mineral horizon. Our results demonstrate that estimates of temperature sensitivity of microbial CUE and rB can be obtained and evaluated rigorously by integrating multidecadal datasets. This approach can potentially be applied in broader spatiotemporal scales to improve long-term projections of soil C feedbacks to climate warming.

An increasing number of studies showed that coverage of existing protected areas is not enough to protect biodiversity. However, to what extent and how human population density influence the geographical pattern of protected areas are not clear. Based on 2644 terrestrial nature reserves (NRs) in mainland China in 2015, correlation analysis showed that there was a significantly negative relationship between human density and area (R = −0.52, P &lt; 0.001) and coverage of NRs (R = −0.21, P &lt; 0.001), and a positive one between human density and density of NRs at county level (R = 0.64, P &lt; 0.001) (all sample size n = 1171). These relationships could also be observed at provincial level. Counties with NRs had significantly lower human density (mean = 95 persons km−2) than those without (mean = 289 persons km−2) (P &lt; 0.001, n = 31) across China. Both percentage of agricultural land and road density significantly and negatively correlated with area and coverage of NRs, and positively with human density and density of NRs at provincial level (all P &lt; 0.01, n = 31). The relationships between human and NRs varied among 31 provinces, three conservation objectives of ecosystems, species and others, three hierarchical managements of national, provincial, and city-county levels, and two jurisdictional departments of forestry and non-forestry. But the general pattern of such relationships did not change. In addition, human density and density of NRs significantly positively, and area and coverage of NRs negatively correlated with density of IUCN red-list high plants and vertebrates excluding fishes at provincial level (all P &lt; 0.05, n = 31). These results suggested that human density had substantial impacts on the geographical distribution of NRs when their sites were designated, elucidating the mechanism responsible for the low effectiveness of NRs in representing biodiversity.

Organic matter input to soils can accelerate the decomposition of native soil carbon (C), a process called the priming effect. Priming is ubiquitous and exhibits some consistent patterns, but a general explanation remains elusive, in part because of variation in the response across different ecosystems, and because of a diversity of proposed mechanisms, including microbial activation, stoichiometry, and community shifts. Here, we conducted five-week incubations of four soils (grassland, piñon-juniper, ponderosa pine, mixed conifer), varying the amount of substrate added (as 13C-glucose, either 350 or 1000 μg C g−1 week−1) and either with no added nitrogen (N), or with sufficient N (as NH4NO3) to bring the C-to-N ratio of the added substrate to 10. Using four different ecosystems enabled testing the generality of mechanisms underlying the priming effect. The responses of priming to the amount and C-to-N ratio of the added substrate were consistent across ecosystems: priming increased with the rate of substrate addition and declined when the C-to-N ratio of the substrate was reduced. However, structural equation models failed to confirm intermediate responses postulated to mediate the priming effect, including responses postulated to be mediated by stoichiometry and microbial activation. Specifically, priming was not clearly associated with changes in microbial biomass or turnover, nor with extracellular enzyme activities or the microbial C-to-N ratio. The strongest explanatory pathways in the structural equation models were the substrate, soil, and C-to-N ratio treatments themselves, with no intermediates, suggesting that either these measurements lacked sufficient sensitivity to reveal causal relationships, or the actual drivers for priming were not included in the ancillary measurements. While we observed consistent changes in priming caused by the amount and C-to-N ratio of the added substrate across a wide array of soils, our findings did not clearly conform to common models offered for the priming effect. Because priming is a residual flux involving diverse substrates of varying chemical composition, a simple and generalizable explanation of the phenomenon may be elusive.

Clarifying how increased atmospheric CO2 concentration (eCO2) contributes to accelerated land carbon sequestration remains important since this process is the largest negative feedback in the coupled carbon–climate system. Here, we constrain the sensitivity of the terrestrial carbon sink to eCO2 over the temperate Northern Hemisphere for the past five decades, using 12 terrestrial ecosystem models and data from seven CO2 enrichment experiments. This constraint uses the heuristic finding that the northern temperate carbon sink sensitivity to eCO2 is linearly related to the site-scale sensitivity across the models. The emerging data-constrained eCO2 sensitivity is 0.64 ± 0.28 PgC yr−1 per hundred ppm of eCO2. Extrapolating worldwide, this northern temperate sensitivity projects the global terrestrial carbon sink to increase by 3.5 ± 1.9 PgC yr−1 for an increase in CO2 of 100 ppm. This value suggests that CO2 fertilization alone explains most of the observed increase in global land carbon sink since the 1960s. More CO2 enrichment experiments, particularly in boreal, arctic and tropical ecosystems, are required to explain further the responsible processes.

How do antecedent (past) conditions influence land-carbon dynamics after those conditions no longer persist? In particular, quantifying such memory effects associated with the influence of past environmental (exogenous) and biological (endogenous) conditions is crucial for understanding and predicting the carbon cycle. Here we show, using data from 42 eddy covariance sites across six major biomes, that ecological memory?decomposed into environmental and biological memory components?of daily net carbon exchange (NEE) is critical for understanding the land-carbon metabolism, especially in drylands for which memory explains ~ 32% of the variation in NEE. The strong environmental memory in drylands was primarily driven by short- and long-term moisture status. Moreover, the strength of environmental memory scales with increasing water stress. This universal scaling relationship, emerging within and among major biomes, suggests a potential adaptive response to water limitation. Our findings underscore the necessity of considering ecological memory in experiments, observations and modelling.

As terrestrial leaf litter decomposes in rivers, its constituent elements follow multiple pathways. Carbon leached as dissolved organic matter can be quickly taken up by microbes, then respired before it can be transferred to the macroscopic food web. Alternatively, this detrital carbon can be ingested and assimilated by aquatic invertebrates, so it is retained longer in the stream and transferred to higher trophic levels. Microbial growth on litter can affect invertebrates through three pathways, which are not mutually exclusive. First, microbes can facilitate invertebrate feeding, improving food quality by conditioning leaves and making them more palatable for invertebrates. Second, microbes can be prey for invertebrates. Third, microbes can compete with invertebrates for resources bound within litter and may produce compounds that retard carbon and nitrogen fluxes to invertebrates. As litter is broken down into smaller particles, there are many opportunities for its elements to reenter the stream food web. Here, I describe a conceptual framework for evaluating how traits of leaf litter will affect its fate in food webs and ecosystems that is useful for predicting how global change will alter carbon fluxes into and out of streams.

Arctic land ice is melting, sea ice is decreasing, and permafrost is thawing. Changes in these Arctic elements are interconnected, and most interactions accelerate the rate of change. The changes affect infrastructure, economics, and cultures of people inside and outside of the Arctic, including in temperate and tropical regions, through sea level rise, worsening storm and hurricane impacts, and enhanced warming. Coastal communities worldwide are already experiencing more regular flooding, drinking water contamination, and coastal erosion. We describe and summarize the nature of change for Arctic permafrost, land ice, and sea ice, and its influences on lower latitudes, particularly the United States. We emphasize that impacts will worsen in the future unless individuals, businesses, communities, and policy makers proactively engage in mitigation and adaptation activities to reduce the effects of Arctic changes and safeguard people and society.

Organisms influence ecosystems, from element cycling to disturbance regimes, to trophic interactions and to energy partitioning. Microorganisms are part of this influence, and understanding their ecology in nature requires studying the traits of these organisms quantitatively in their natural habitats—a challenging task, but one which new approaches now make possible. Here, we show that growth rate and carbon assimilation rate of soil microorganisms are influenced more by evolutionary history than by climate, even across a broad climatic gradient spanning major temperate life zones, from mixed conifer forest to high-desert grassland. Most of the explained variation (~50% to ~90%) in growth rate and carbon assimilation rate was attributable to differences among taxonomic groups, indicating a strong influence of evolutionary history, and taxonomic groupings were more predictive for organisms responding to resource addition. With added carbon and nitrogen substrates, differences among taxonomic groups explained approximately eightfold more variance in growth rate than did differences in ecosystem type. Taxon-specific growth and carbon assimilation rates were highly intercorrelated across the four ecosystems, constrained by the taxonomic identity of the organisms, such that plasticity driven by environment was limited across ecosystems varying in temperature, precipitation and dominant vegetation. Taken together, our results suggest that, similar to multicellular life, the traits of prokaryotes in their natural habitats are constrained by evolutionary history to a greater degree than environmental variation.

Recent warming in the Arctic, which has been amplified during the winter1–3, greatly enhances microbial decomposition of soil organic matter and subsequent release of carbon dioxide (CO2)4. However, the amount of CO2 released in winter is not known and has not been well represented by ecosystem models or empirically based estimates5,6. Here we synthesize regional in situ observations of CO2 flux from Arctic and boreal soils to assess current and future winter carbon losses from the northern permafrost domain. We estimate a contemporary loss of 1,662 TgC per year from the permafrost region during the winter season (October–April). This loss is greater than the average growing season carbon uptake for this region estimated from process models (−1,032 TgC per year). Extending model predictions to warmer conditions up to 2100 indicates that winter CO2 emissions will increase 17% under a moderate mitigation scenario—Representative Concentration Pathway 4.5—and 41% under business-as-usual emissions scenario—Representative Concentration Pathway 8.5. Our results provide a baseline for winter CO2 emissions from northern terrestrial regions and indicate that enhanced soil CO2 loss due to winter warming may offset growing season carbon uptake under future climatic conditions.

Chinese milk vetch (Astragalus sinicus L., vetch), a leguminous winter cover crop, has been widely adopted by farmers in southern China to boost yield of the succeeding rice crop. However, the effects of vetch on rice grain yield and nitrogen (N) use efficiency have not yet been well studied in the intensive double-cropped rice cropping systems. To fill this gap, we conducted a three-year field experiment to evaluate the impacts of the vetch crop on yields and N use efficiency in the subsequent early and late rice seasons. With moderate N input (100 kg N ha&amp;minus;1 for each rice crop), vetch cover significantly increased grain yields by 7.3&amp;ndash;13.4% for early rice, by 8.2&amp;ndash;10.4% for late rice, and by 8.6&amp;ndash;11.5% for total annual rice production when compared with winter fallow. When rice crops received an N input of 200 kg N ha&amp;minus;1, vetch cover increased grain yields by 5.9&amp;ndash;18.4% for early rice, by 3.8&amp;ndash;10.1% for late rice, and by 6.2&amp;ndash;11.3% for annual rice production. Moreover, comparable grain yields (11.9 vs. 12.0 Mg ha&amp;minus;1 for annual rice production) were observed between vetch cover with moderate N and fallow with added N fertilizer. Yield components analysis indicated that the increased tillering number was the main factor for the enhanced grain yields by vetch cover. Vetch cover with moderate and higher N input resulted in higher agronomic N use efficiency and applied N recovery efficiency compared with the fallow treatments. Here, our results showed that vetch as a winter cover crop can be combined with reduced N fertilizer input while maintaining high grain yields, thus gaining a more sustainable rice production system.

Ecologists increasingly use hierarchical Bayesian (HB) models to estimate group-level parameters that vary by, for example, species, treatment level, habitat type or other factors. Group-level parameters may be compared to infer differences among levels. We would conclude a non-zero pairwise difference, separately, for each pair in the group, when the respective 95% credible interval excludes zero. Classical procedures suggest that the rejection procedure should be adjusted to control the family-wise error rate (FWER) for a family of differences. Adjustments for FWER have been considered unnecessary in HB models due to partial pooling whereby increased pooling strength - group-level parameters become more alike - could lead to decreased rejection rates (Type I error, FWER, or Power) and increased false acceptance rates (Type 2 error and its family-wise analogue). To address this, we conducted a simulation experiment with factors of sample size, group size, balance (missingness), overall mean and ratio of within- to between-group variances, resulting in 2016 factor-level combinations (scenarios), replicated 100 times, producing 201,600 pseudo datasets analysed in a Bayesian framework. We evaluated the results in the context of a new partial pooling index (PPI), which we show is also applicable to more complex model structures based on four real-data examples. Simulation results confirm intuition that rejection rates (false and true) decrease and false acceptance rates increase with increasing PPI or pooling strength (scenario-level R2 = 0.81-0.97). The relationship with PPI differed greatly for balanced versus unbalanced designs and was affected by group size, especially for family-wise errors. Critically, an HB model does not guarantee that the FWER will follow a set significance level (α); for example, even minor imbalance can lead to FWER &gt; α for weak to moderate pooling. These results are confirmed by the real-data examples, suggesting that ecologists need to consider FWER when applying HB models, especially for large group sizes or incomplete datasets. Contrary to current thought, HB models are not immune to issues of multiplicity, and our proposed PPI offers a method for evaluating if a particular HB analysis is likely to produce FWER ≤ α (no adjustment or alternative solution required).

RNA is considered to be a short-lived molecule, indicative of cellular metabolic activity, whereas DNA is thought to turn over more slowly because living cells do not always grow and divide. To explore differences in the rates of synthesis of these nucleic acids, we used H218O quantitative stable isotope probing (qSIP) to measure the incorporation of 18O into 16S rRNA, the 16S rDNA, amoA mRNA and the amoA gene of soil Thaumarchaeota. Incorporation of 18O into the thaumarchaeal amoA mRNA pool was faster than into the 16S rRNA pool, suggesting that Thaumarchaea were metabolically active while using rRNA molecules that were likely synthetized prior to H218O addition. Assimilation rates of 18O into 16S rDNA and amoA genes were similar, which was expected because both genes are present in the same thaumarchaeal genome. The Thaumarchaea had significantly higher rRNA to rDNA ratios than bacteria, though the 18O isotopic signature of thaumarchaeal rRNA was lower than that of bacterial rRNA, further suggesting preservation of old non-labeled rRNA. Through qSIP of soil with H218O, we showed that 18O incorporation into thaumarchaeal nucleic acids was generally low, indicating slower turnover rates compared to bacteria, and potentially suggesting thaumarchaeal capability for preservation and efficient reuse of biomolecules.

Growth of soil microorganisms is often described as carbon limited, and adding labile carbon to soil often results in a transient and large increase in respiration. In contrast, soil microbial biomass changes little, suggesting that growth and respiration are decoupled in response to a carbon pulse. Alternatively, measuring bulk responses of the entire community (total respiration and biomass) could mask ecologically important variation among taxa in response to the added carbon. Here, we assessed taxon-specific variation in cellular growth (measured as DNA synthesis) and metabolic activity (measured as rRNA synthesis) following glucose addition to soil using quantitative stable isotope probing with H218O. We found that glucose addition altered rates of DNA and rRNA synthesis, but the effects were strongly taxon specific: glucose stimulated growth and rRNA transcription for some taxa, and suppressed these for others. These contrasting taxon-specific responses could explain the small and transient changes in total soil microbial biomass. Responses to glucose were not well predicted by a priori assignments of taxa into copiotrophic or oligotrophic categories. Across all taxa, rates of DNA and rRNA synthesis changed in parallel, indicating that growth and activity were coupled, and the degree of coupling was unaffected by glucose addition. This pattern argues against the idea that labile carbon addition causes a large reduction in metabolic growth efficiency; rather, the large pulse of respiration observed with labile substrate addition is more likely to be the result of rapid turnover of microbial biomass, possibly due to trophic interactions. Our results support a strong connection between rRNA synthesis and bacterial growth, and indicate that taxon-specific responses among soil bacteria can buffer responses at the scale of the whole community.

Higher temperatures in northern latitudes will increase permafrost thaw and stimulate above- and belowground plant biomass growth in tundra ecosystems. Higher plant productivity increases the input of easily decomposable carbon (C) to soil, which can stimulate microbial activity and increase soil organic matter decomposition rates. This phenomenon, known as the priming effect, is particularly interesting in permafrost because an increase in C supply to deep, previously frozen soil may accelerate decomposition of C stored for hundreds to thousands of years. The sensitivity of old permafrost C to priming is not well known; most incubation studies last less than one year, and so focus on fast-cycling C pools. Furthermore, the age of respired soil C is rarely measured, even though old C may be vulnerable to labile C inputs. We incubated soil from a moist acidic tundra site in Eight Mile Lake, Alaska for 409 days at 15 °C. Soil from surface (0–25 cm), transition (45–55 cm), and permafrost (65–85 cm) layers were amended with three pulses of uniformly 13C-labeled glucose or cellulose every 152 days. Glucose addition resulted in positive priming in the permafrost layer 7 days after each substrate addition, eliciting a two-fold increase in cumulative soil C loss relative to unamended soils with consistent effects across all three pulses. In the transition and permafrost layers, glucose addition significantly decreased the age of soil-respired CO2-C with Δ14C values that were 115‰ higher. Previous field studies that measured the age of respired C in permafrost regions have attributed younger Δ14C ecosystem respiration values to higher plant contributions. However, the results from this study suggest that positive priming, due to an increase in fresh C supply to deeply thawed soil layers, can also explain the respiration of younger C observed at the ecosystem scale. We must consider priming effects to fully understand permafrost C dynamics, or we risk underestimating the contribution of soil C to ecosystem respiration.

While we often assume tree growth?climate relationships are time-invariant, impacts of climate phenomena such as the El Niño Southern Oscillation (ENSO) and the North American Monsoon (NAM) may challenge this assumption. To test this assumption, we grouped ring widths (1900-present) in three southwestern US conifers into La Niña periods (LNP) and other years (OY). The 4 years following each La Niña year are included in LNP, and despite 1-2 year growth declines, compensatory adjustments in tree growth responses result in essentially equal mean growth in LNP and OY, as average growth exceeds OY means 2-4 years after La Niña events. We found this arises because growth responses in the two periods are not interchangeable: Due to differences in growth?climate sensitivities and climatic memory, parameters representing LNP growth fail to predict OY growth and vice versa (decreases in R2 up to 0.63; lowest R2 = 0.06). Temporal relationships between growth and antecedent climate (memory) show warmer springs and longer growing seasons negatively impact growth following dry La Niña winters, but that NAM moisture can rescue trees after these events. Increased importance of monsoonal precipitation during LNP is key, as the largest La Niña-related precipitation deficits and monsoonal precipitation contributions both occur in the southern part of the region. Decreases in first order autocorrelation during LNP were largest in the heart of the monsoon region, reflecting both the greatest initial growth declines and the largest recovery. Understanding the unique climatic controls on growth in Southwest conifers requires consideration of both the influences and interactions of drought, ENSO, and NAM, each of which is likely to change with continued warming. While plasticity of growth sensitivity and memory has allowed relatively quick recovery in the tree-ring record, recent widespread mortality events suggest conditions may soon exceed the capacity for adjustment in current populations.

Evidence suggests that 5–15% of the vast pool of soil carbon stored in northern permafrost ecosystems could be emitted as greenhouse gases by 2100 under the current path of global warming. However, direct measurements of changes in soil carbon remain scarce, largely because ground subsidence that occurs as the permafrost soils begin to thaw confounds the traditional quantification of carbon pools based on fixed depths or soil horizons. This issue is overcome when carbon is quantified in relation to a fixed ash content, which uses the relatively stable mineral component of soil as a metric for pool comparisons through time. We applied this approach to directly measure soil carbon pool changes over five years in experimentally warmed and ambient tundra ecosystems at a site in Alaska where permafrost is degrading due to climate change. We show a loss of soil carbon of 5.4% per year (95% confidence interval: 1.0, 9.5) across the site. Our results point to lateral hydrological export as a potential pathway for these surprisingly large losses. This research highlights the potential to make repeat soil carbon pool measurements at sentinel sites across the permafrost region, as this feedback to climate change may be occurring faster than previously thought.

Fire is a primary disturbance in boreal forests and generates both positive and negative climate forcings. The influence of fire on surface albedo is a predominantly negative forcing in boreal forests, and one of the strongest overall, due to increased snow exposure in the winter and spring months. Albedo forcings are spatially and temporally heterogeneous and depend on a variety of factors related to soils, topography, climate, land cover/vegetation type, successional dynamics, time since fire, season, and fire severity. However, how these variables interact to influence albedo is not well understood, and quantifying these relationships and predicting postfire albedo becomes increasingly important as the climate changes and management frameworks evolve to consider climate impacts. Here we developed a MODIS-derived ?blue sky? albedo product and a novel machine learning modeling framework to predict fire-driven changes in albedo under historical and future climate scenarios across boreal North America. Converted to radiative forcing (RF), we estimated that fires generate an annual mean cooling of ?1.77 ± 1.35 W/m2 from albedo under historical climate conditions (1971?2000) integrated over 70 years postfire. Increasing postfire albedo along a south?north climatic gradient was offset by a nearly opposite gradient in solar insolation, such that large-scale spatial patterns in RF were minimal. Our models suggest that climate change will lead to decreases in mean annual postfire albedo, and hence a decreasing strength of the negative RF, a trend dominated by decreased snow cover in spring months. Considering the range of future climate scenarios and model uncertainties, we estimate that for fires burning in the current era (2016) the cooling effect from long-term postfire albedo will be reduced by 15%?28% due to climate change.

Advancing phenology is one of the most visible effects of climate change on plant communities, and has been especially pronounced in temperature-limited tundra ecosystems. However, phenological responses have been shown to differ greatly between species, with some species shifting phenology more than others. We analysed a database of 42,689 tundra plant phenological observations to show that warmer temperatures are leading to a contraction of community-level flowering seasons in tundra ecosystems due to a greater advancement in the flowering times of late-flowering species than early-flowering species. Shorter flowering seasons with a changing climate have the potential to alter trophic interactions in tundra ecosystems. Interestingly, these findings differ from those of warmer ecosystems, where early-flowering species have been found to be more sensitive to temperature change, suggesting that community-level phenological responses to warming can vary greatly between biomes.

Microorganisms in soil assimilate, transform, and mineralize soil C to support growth. There are an estimated 2.6 × 1029 microbial cells containing 26 Pg C in soils worldwide. Consequently, quantifying microbial growth in soil is critical for determining the degree to which microorganisms contribute to the global C cycle. Measuring taxon-specific microbial growth enables understanding of the contribution of microbial taxa to elemental transformations across ecosystems and their susceptibility to environmental perturbations. These measurements in soil have largely been lacking due to inadequate methods. Quantitative stable isotope probing (qSIP) with H218O is used to measure taxon-specific growth of microbial taxa in soil, an improvement compared with traditional stable isotope probing (SIP). In qSIP, DNA extracted from both a labeled (18O-enriched water) and an unlabeled treatment is separated into numerous density fractions by isopycnic centrifugation, and target genes are quantified and sequenced in each fraction. The taxon-specific DNA density shift and ultimately the isotopic composition (18O enrichment) is calculated for each taxon. Here we discuss methods and illustrate the procedure for quantifying microbial taxon-specific growth in soil with qSIP using heavy isotope enriched H218O.

Soil microbial carbon-use efficiency (CUE), which is defined as the ratio of growth over C uptake, is commonly assumed as a constant or estimated by a temperature-dependent function in current microbial-explicit soil carbon (C) models. The temperature-dependent function (i.e., CUE = CUE0 + m × (T − 20)) simulates the dynamic CUE based on the specific CUE at a given reference temperature (i.e., CUE0) and a temperature response coefficient (i.e., m). Here, based on 780 observations from 98 sites, we showed a divergent spatial distribution of the soil microbial CUE (0.5 ± 0.25; mean ± SD) at the global scale. Then, the key parameters CUE0 and m in the above equation were estimated as 0.475 and −0.016, respectively, based on the observations with the Markov chain Monte Carlo technique. We also found a strong dependence of microbial CUE on the type of C substrate. The multiple regression analysis showed that glucose influences the variation of measured CUE associated with the environmental factors. Overall, this study confirms the global divergence of soil microbial CUE and calls for the incorporation of C substrate beside temperature in estimating the microbial CUE in different biomes.

It has been well established by field experiments that warming stimulates either net ecosystem carbon uptake or release, leading to negative or positive carbon cycle–climate change feedback, respectively. This variation in carbon-climate feedback has been partially attributed to water availability. However, it remains unclear under what conditions water availability enhances or weakens carbon-climate feedback or even changes its direction. Combining a field experiment with a global synthesis, we show that warming stimulates net carbon uptake (negative feedback) under wet conditions, but depresses it (positive feedback) under very dry conditions. This switch in carbon-climate feedback direction arises mainly from scaling effects of warming-induced decreases in soil water content on net ecosystem productivity. This water scaling of warming effects offers generalizable mechanisms not only to help explain varying magnitudes and directions of observed carbon-climate feedback but also to improve model prediction of ecosystem carbon dynamics in response to climate change.

Carbon dynamics within trees are intrinsically important for physiological functioning, in particular growth and survival, as well as ecological interactions on multiple timescales. Thus, these internal dynamics play a key role in the global carbon cycle by determining the residence time of carbon in forests via allocation to different tissues and pools, such as leaves, wood, storage, and exudates. Despite the importance of tree internal carbon dynamics, our understanding of how carbon is used in trees, once assimilated, has major gaps. The primary tissue that transports carbon from sources to sinks within a tree is the phloem. Therefore, direct phloem transport manipulation techniques have the potential to improve understanding of numerous aspects of internal carbon dynamics. These include relationships between carbon assimilation, nonstructural carbon availability, respiration for growth and tissue maintenance, allocation to, and remobilization from, storage reserves, and long-term sequestration in lignified structural tissues. This review aims to: (1) introduce the topic of direct phloem transport manipulations, (2) describe the three most common methods of direct phloem transport manipulation and review their mechanisms, namely (i) girdling, (ii) compression and (iii) chilling; (3) summarize the known impacts of these manipulations on carbon dynamics and use in forest trees; (4) discuss potential collateral effects and compare the methods; and finally (5) highlight outstanding key questions that relate to tree carbon dynamics and use, and propose ways to address them using direct phloem transport manipulation.

Monitoring drought in real-time using minimal field data is a challenge for ecosystem management and conservation. Most methods require extensive data collection and in-situ calibration and accuracy is difficult to evaluate. Here, we demonstrated how the space-borne canopy “thermal stress”, defined as surface-air temperature difference, provides a reliable surrogate for drought-induced water stress in vegetation. Using physics-based relationships that accommodate uncertainties, we showed how changes in canopy water flux from ground-based measurements relate to both the surface energy balance and remotely-sensed thermal stress. Field measurements of evapotranspiration in the southeastern and northwestern US verify this approach based on sensitivity of evapotranspiration to thermal stress in a large range of atmospheric and climate conditions. We found that a 1 °C change in the thermal stress is comparable to 1–1.2 mm day−1 of evapotranspiration, depending on site and climate conditions. We quantified temporal and spatial sensitivity of evapotranspiration to the thermal stress and showed that it has the strongest relationship with evapotranspiration during warm and dry seasons, when monitoring drought is essential. Using only air and surface temperatures, we predicted the inter-annual anomaly in thermal stress across the contiguous United States over the course of 15 years and compared it with conventional drought indices. Among drought metrics that were considered in this study, the thermal stress had the highest correlation values. Our sensitivity results demonstrated that the thermal stress is a particularly strong indicator of water-use in warm seasons and regions. This simple metric can be used at varying time-scales to monitor surface evapotranspiration and drought in large spatial extents in near real-time.

Digital repeat photography and near-surface remote sensing have been used by environmental scientists to study environmental change for nearly a decade. However, a user-friendly, reliable, and robust platform to extract color-based statistics and time series from a large stack of images is still lacking. Here, we present an interactive open-source toolkit, called xROI, that facilitates the process of time series extraction and improves the quality of the final data. xROI provides a responsive environment for scientists to interactively (a) delineate regions of interest (ROI), (b) handle field of view (FOV) shifts, and (c) extract and export time series data characterizing color-based metrics. The software gives user the opportunity to adjust mask files or draw new masks, every time an FOV shift occurs. Utilizing xROI can significantly facilitate data extraction from digital repeat photography and enhance the accuracy and continuity of extracted data.

Direct quantification of terrestrial biosphere responses to global change is crucial for projections of future climate change in Earth system models. Here, we synthesized ecosystem carbon-cycling data from 1,119 experiments performed over the past four decades concerning changes in temperature, precipitation, CO2 and nitrogen across major terrestrial vegetation types of the world. Most experiments manipulated single rather than multiple global change drivers in temperate ecosystems of the USA, Europe and China. The magnitudes of warming and elevated CO2 treatments were consistent with the ranges of future projections, whereas those of precipitation changes and nitrogen inputs often exceeded the projected ranges. Increases in global change drivers consistently accelerated, but decreased precipitation slowed down carbon-cycle processes. Nonlinear (including synergistic and antagonistic) effects among global change drivers were rare. Belowground carbon allocation responded negatively to increased precipitation and nitrogen addition and positively to decreased precipitation and elevated CO2. The sensitivities of carbon variables to multiple global change drivers depended on the background climate and ecosystem condition, suggesting that Earth system models should be evaluated using site-specific conditions for best uses of this large dataset. Together, this synthesis underscores an urgent need to explore the interactions among multiple global change drivers in underrepresented regions such as semi-arid ecosystems, forests in the tropics and subtropics, and Arctic tundra when forecasting future terrestrial carbon-climate feedback.

Temperature is a primary environmental control on ecological systems and processes at a range of spatial and temporal scales. The surface temperature of organisms is often more relevant for ecological processes than air temperature, which is much more commonly measured. Surface temperature influences?and is influenced by?a range of biological, physical, and chemical processes, providing a unique view of temperature effects on ecosystem function. Furthermore, surface temperatures vary markedly over a range of temporal and spatial scales and may diverge from air temperature by 40°C or more. Surface temperature measurements have been challenging due to sensor and computational limitations but are now feasible at high spatial and temporal resolutions using thermal imaging. Thus, significant advances in our understanding of plant and ecosystem thermal regimes and their functional consequences are now possible. Thermal measurements may be used to address many ecological questions, such as the thermal controls on plant and ecosystem metabolism and the impact of heat waves and drought. Further advances in this area will require interdisciplinary collaborations among practitioners in fields ranging from physiology to ecosystem ecology to remote sensing and geospatial analysis. In this overview, we demonstrate the feasibility, utility, and potential of thermal imaging for measuring vegetation surface temperatures across a range of scales and from measurement, analysis, and synthesis perspectives.

Warming is altering the way soils function in ecosystems both directly by changing microbial physiology and indirectly by causing shifts in microbial community composition. Some of these warming-driven changes are short term, but others may persist over time. Here, we took advantage of a long-term (14 yr) warming experiment in a tallgrass prairie to tease apart the influence of short- and long-term warming on litter decomposition. We collected soils originating from warmed and control plots and incubated them with a common litter substrate in a reciprocal design under elevated and ambient growth chamber temperatures. Litter decomposition was 40% higher in soils that were warmed in the field for 14 yr (long-term warming) relative to soils derived from ambient plots. Short-term warming in the laboratory had less of an impact on decomposition-decomposition increased by 12% under laboratory warming. Using a two-pool soil carbon model to explore how different carbon pools may be responding, we found that long-term warming accelerated the turnover of labile, not recalcitrant, carbon in these prairie soils-a result that is likely due to shifts in soil community activity/composition. Taken together, our results offer experimental evidence that warming-induced changes in the soil community that occur over 14 yr of warming have long-lasting effects on carbon turnover.

Elevated CO2 (eCO2) experiments provide critical information to quantify the effects of rising CO2 on vegetation1–6. Many eCO2 experiments suggest that nutrient limitations modulate the local magnitude of the eCO2 effect on plant biomass1,3,5, but the global extent of these limitations has not been empirically quantified, complicating projections of the capacity of plants to take up CO27,8. Here, we present a data-driven global quantification of the eCO2 effect on biomass based on 138 eCO2 experiments. The strength of CO2 fertilization is primarily driven by nitrogen (N) in ~65% of global vegetation and by phosphorus (P) in ~25% of global vegetation, with N- or P-limitation modulated by mycorrhizal association. Our approach suggests that CO2 levels expected by 2100 can potentially enhance plant biomass by 12 ± 3% above current values, equivalent to 59 ± 13 PgC. The global-scale response to eCO2 we derive from experiments is similar to past changes in greenness9 and biomass10 with rising CO2, suggesting that CO2 will continue to stimulate plant biomass in the future despite the constraining effect of soil nutrients. Our research reconciles conflicting evidence on CO2 fertilization across scales and provides an empirical estimate of the biomass sensitivity to eCO2 that may help to constrain climate projections.

Temperature is a primary driver of microbial community composition and taxonomic diversity; however, it is unclear to what extent temperature affects characteristics of central carbon metabolic pathways (CCMPs). In this study, 16S rRNA gene amplicon and metagenome sequencing were combined with 13C-labeled metabolite probing of the CCMPs to assess community carbon metabolism along a temperature gradient (60-95 °C) in Great Boiling Spring, NV. 16S rRNA gene amplicon diversity was inversely proportional to temperature, and Archaea were dominant at higher temperatures. Metagenomes spanning the temperature gradient hosted abundant CCMPs genes and many individual metagenome-assembled genomes had complete pathways. In contrast, genes encoding cellulosomes and some others involved in plant matter degradation and most for photosynthesis and were absent at higher temperatures. In situ 13C-CO2 production from labeled isotopomer pairs of glucose, pyruvate, and acetate suggested lower relative oxidative pentose phosphate pathway activity and/or fermentation at 60°C, and a stable or decreased maintenance energy demand at higher temperatures. Catabolism of 13C-labeled citrate, succinate, L-alanine, L-serine, and L-cysteine was observed at 85°C, demonstrating broad heterotrophic activity. Together, these results suggest that temperature-driven losses in biodiversity in geothermal systems may not alter CCMP function or maintenance energy demands at a community level.

Increasing atmospheric CO2 stimulates photosynthesis which can increase net primary production (NPP), but at longer timescales may not necessarily increase plant biomass. Here we analyse the four decade-long CO2-enrichment experiments in woody ecosystems that measured total NPP and biomass. CO2 enrichment increased biomass increment by 1.05 ± 0.26 kg C m−2 over a full decade, a 29.1 ± 11.7% stimulation of biomass gain in these early-secondary-succession temperate ecosystems. This response is predictable by combining the CO2 response of NPP (0.16 ± 0.03 kg C m−2 y−1) and the CO2-independent, linear slope between biomass increment and cumulative NPP (0.55 ± 0.17). An ensemble of terrestrial ecosystem models fail to predict both terms correctly. Allocation to wood was a driver of across-site, and across-model, response variability and together with CO2-independence of biomass retention highlights the value of understanding drivers of wood allocation under ambient conditions to correctly interpret and predict CO2 responses.

Boreal forest fires emit large amounts of carbon into the atmosphere primarily through the combustion of soil organic matter1–3. During each fire, a portion of this soil beneath the burned layer can escape combustion, leading to a net accumulation of carbon in forests over multiple fire events4. Climate warming and drying has led to more severe and frequent forest fires5–7, which threaten to shift the carbon balance of the boreal ecosystem from net accumulation to net loss1, resulting in a positive climate feedback8. This feedback will occur if organic-soil carbon that escaped burning in previous fires, termed ‘legacy carbon’, combusts. Here we use soil radiocarbon dating to quantitatively assess legacy carbon loss in the 2014 wildfires in the Northwest Territories of Canada2. We found no evidence for the combustion of legacy carbon in forests that were older than the historic fire-return interval of northwestern boreal forests9. In forests that were in dry landscapes and less than 60 years old at the time of the fire, legacy carbon that had escaped burning in the previous fire cycle was combusted. We estimate that 0.34 million hectares of young forests (&lt;60 years) that burned in the 2014 fires could have experienced legacy carbon combustion. This implies a shift to a domain of carbon cycling in which these forests become a net source—instead of a sink—of carbon to the atmosphere over consecutive fires. As boreal wildfires continue to increase in size, frequency and intensity7, the area of young forests that experience legacy carbon combustion will probably increase and have a key role in shifting the boreal carbon balance.

Crop straw management plays important roles in sustainable agriculture and environmental protection. Straw incorporation has multiple influences on soil organic carbon (SOC) sequestration, greenhouse gas (GHG) emissions, and crop yields, but these influences have rarely been studied simultaneously in a single cropping system. This study was conducted to examine the influence of long-term straw incorporation on the SOC sequestration rate, methane (CH4) and nitrous oxide (N2O) emissions and crop yields in a Chinese rice (Oryza sativa L.) –wheat (Triticum aestivum L.) cropping system in Hydragric Anthrosols under a subtropical monsoon climate. Four straw incorporation treatments were applied: wheat straw incorporation only (WS), rice straw incorporation only (RS), both wheat and rice straw incorporation (WSRS), and no straw incorporation (as a control). The SOC sequestration rate was estimated from the changes in SOC stock in the topsoil (0–20 cm) from 2007 to 2016. The emissions of CH4 and N2O were measured every 7 d when possible using a static chamber method from the 2013 rice season to the 2016 wheat season. Our results showed that the straw incorporation treatments significantly influenced the seasonal CH4 and N2O emissions and rice yield but had no influence on wheat yield. Straw incorporation significantly increased the annual topsoil SOC sequestration rate by 0.24–0.43 t C ha−1 yr−1 and the annual CH4 and N2O emissions by 44–138 kg CH4-C ha−1 yr−1 and 0.68–1.49 kg N2O-N ha−1 yr−1, respectively. Relative to the RS treatment, the WS and WSRS treatments significantly increased annual CH4 emissions by 38% and 61%, respectively. Relative to the RS treatment, the WSRS treatment significantly increased the annual N2O emissions, by 35%. The average annual yields were significantly higher in the WSRS (16.8 t ha−1 yr−1) and RS (16.7 t ha−1 yr−1) treatments than in the WS (15.7 t ha−1 yr−1) and control (15.2 t ha−1 yr−1) treatments. Across the three rotation cycles, the annual net global warming potential and greenhouse gas intensity were similar between the control and RS treatments but were significantly lower in these treatments than in the WSRS and WS treatments. These findings suggest that the RS treatment can simultaneously increase crop yields and environmental sustainability in rice–wheat cropping systems.

One known bias in current Earth system models (ESMs) is the underestimation of global mean soil carbon (C) transit time (<span class="inline-formula"><i>τ</i>_soil</span>), which quantifies the age of the C atoms at the time they leave the soil. However, it remains unclear where such underestimations are located globally. Here, we constructed a global database of measured <span class="inline-formula"><i>τ</i>_soil</span> across 187 sites to evaluate results from 12 ESMs. The observations showed that the estimated <span class="inline-formula"><i>τ</i>_soil</span> was dramatically shorter from the soil incubation studies in the laboratory environment (median <span class="inline-formula">=</span> 4 years; interquartile range <span class="inline-formula">=</span> 1 to 25 years) than that derived from field in situ measurements (31; 5 to 84 years) with shifts in stable isotopic C (<span class="inline-formula">¹³C</span>) or the <i>stock-over-flux</i> approach. In comparison with the field observations, the multi-model ensemble simulated a shorter median (19 years) and a smaller spatial variation (6 to 29 years) of <span class="inline-formula"><i>τ</i>_soil</span> across the same site locations. We then found a significant and negative linear correlation between the in situ measured <span class="inline-formula"><i>τ</i>_soil</span> and mean annual air temperature. The underestimations of modeled <span class="inline-formula"><i>τ</i>_soil</span> are mainly located in cold and dry biomes, especially tundra and desert. Furthermore, we showed that one ESM (i.e., CESM) has improved its <span class="inline-formula"><i>τ</i>_soil</span> estimate by incorporation of the soil vertical profile. These findings indicate that the spatial variation of <span class="inline-formula"><i>τ</i>_soil</span> is a useful benchmark for ESMs, and we recommend more observations and modeling efforts on soil C dynamics in regions limited by temperature and moisture.

Hydraulic limitations to tree height can be mitigated by widening the conducting elements toward a tree’s base. However, size limits of tracheid and vessel dimensions may constrain this compensation mechanism as the water transport pathway elongates. Moreover, variation in conduit size is poorly described in tall trees even though their long transport paths have high potential for hydraulic resistance. Here, we evaluated whether axial variation in conduit diameter was uniquely structured, or matched theoretical predictions in <em class="EmphasisTypeItalic ">Sequoia sempervirens</em>, <em class="EmphasisTypeItalic ">Sequoiadendron giganteum,</em> and <em class="EmphasisTypeItalic ">Eucalyptus regnans</em> that were 86–105 m tall and exceeded 85% of the maximum height for each species. Across <em class="EmphasisTypeItalic ">Sequoia</em> and <em class="EmphasisTypeItalic ">Sequoiadendron</em>, tree top tracheids maintained constant width, whereas tree base tracheids in the outermost ring were 20% wider in taller trees, suggesting maintenance of basipetal conduit widening with height growth. In all trees, the observed widening decreased at a rate per unit path length that fitted well to a power function with an exponent consistent with hydraulic compensation. However, below about 60 m from the tree tops, conduit diameters approached an asymptote beneath the power function, indicating a limit to maximum conduit size. Quantifying the distribution of base-to-top hydraulic resistance suggested that the minimal hydraulic benefit gained with increasingly wider conduits near the tree base may trade off with other factors such as maintaining mechanical strength or reducing fluid volume. We summarize these results into an anatomical model of height growth that includes limits to axial variation in conduit diameter and is supported by many physiological and anatomical observations.

Piling and burning is widely used to dispose of unmerchantable debris resulting from thinning in forests throughout the western United States. Quite often more piles are created than are burned in a given year, however, causing piles to persist, accumulate, and age on the landscape. The effects of burning piles of increasing age has not been studied. We examined the effects of time since construction (i.e., pile age, in roughly six month increments for two years) and burn season (fall and spring) on fuelbed properties, combustion dynamics, fuel consumption, and charcoal formation for hand-constructed piles in thinned ponderosa pine-dominated sites in New Mexico (n = 50 piles) and Washington (n = 49 piles). Piles compacted over time similarly for both study sites, losing approximately 15% of their height annually for the first two years following piling. Peak flame height decreased and the duration of flaming combustion increased with increasing pile age for both burn seasons in New Mexico, yet depended on burn season in Washington. Increasing fuel moisture and compaction reduced peak flame height and increased flaming duration modestly for both sites. Peak flame height was reduced 6–7 cm and flaming duration increased 0.9–2.3 min for every percentage increase in small fuel moisture. Similarly, peak flame height was reduced 4–5 cm and flaming duration increased 0.6–0.8 min for every percentage reduction in pile height. Fuel consumption was high, averaging 90% in New Mexico and 95% in Washington. Fuel consumption patterns differed between locations, however; fuel consumption decreased with age and was slightly higher for spring than fall burns in New Mexico, whereas, neither pile age nor burn season affected fuel consumption in Washington. Charcoal formation as a fraction of pre-burn pile weight averaged 2.8% in New Mexico and 1.2% in Washington, and was not affected by pile age or burn season. Fuel consumption and charcoal production were unaffected by fuel moisture or compaction levels at either site. Findings from this study will inform fuel and fire managers about the potential effects on fire behavior, fuel consumption, and charcoal formation of burning piles of different age in different seasons under different environmental conditions.

Carbon storage dynamics in vegetation and soil are determined by the balance of carbon influx and turnover. Estimates of these opposing fluxes differ markedly among different empirical datasets and models leading to uncertainty and divergent trends. To trace the origin of such discrepancies through time and across major biomes and climatic regions, we used a model-data fusion framework. The framework emulates carbon cycling and its component processes in a global dynamic ecosystem model, LPJ-GUESS, and preserves the model-simulated pools and fluxes in space and time. Thus, it allows us to replace simulated carbon influx and turnover with estimates derived from empirical data, bringing together the strength of the model in representing processes, with the richness of observational data informing the estimations. The resulting vegetation and soil carbon storage and global land carbon fluxes were compared to independent empirical datasets. Results show model-data agreement comparable to, or even better than, the agreement between independent empirical datasets. This suggests that only marginal improvement in land carbon cycle simulations can be gained from comparisons of models with current-generation datasets on vegetation and soil carbon. Consequently, we recommend that model skill should be assessed relative to reference data uncertainty in future model evaluation studies.

Tree architecture is crucial to maximizing light capture, determined by carbon allocation of individual trees, and consequently characterizes species-specific growth strategies. Its variation and associated life-history strategies have been examined in tropical and temperate forests, but not in subtropical forests. Moreover, a similar architectural pattern was found using a hierarchical Bayesian model in a tropical forest, which differed from most of previous studies. Here, we employed a hierarchical Bayesian model to examine tree architecture differences and associations with adult stature and light requirement among 59 subtropical co-occurring species. Architectural variations among tree species with different seed dispersal and leaf phenology types were analyzed. Most species showed similar architecture in the height of the lowest foliage-tree height relationships (F-H) and the long side of crown- tree height relationships (W1-H), but some species showed interspecific variations in tree height-stem diameter relationships (H-D) among the 59 co-occurring species in the subtropical montane forest. Trees developed deeper and larger crowns at mid-elevation compared to the tropical and temperate forests. Parameters of H-D relationship differed in leaf phenology and dispersal types, and intercepts of F-H relationship and W1-H relationship differed in leaf phenology. Large-statured species had more slender stems, and shallower and narrower crowns at small sizes, but similar crowns at large sizes. Light-demanding species showed weak correlations between architectural variables and light requirement but exhibited wide crowns at the intermediate sizes. In general, size-dependent architectural differentiation was driven mainly by adult stature and light requirement in subtropical forest. Coexistence species showed different life-history strategies in light capture, which may help provide options in forest thinning and harvesting in subtropical forest. Species-specific tree architectural models of 59 co-occurring species represent three-dimensional (3D) structure of this subtropical forest accurately, but also support for future terrestrial laser scanning (TLS) data analysis.

Mulching techniques have been widely used in dryland regions in northern China. It is necessary to develop water-saving cultivation techniques in irrigation regions in northern China to relieve water scarcity. Planting and mulching on separate rows has been widely used to improve wheat yield and involves a pattern of a double row of planting and a blank row of mulching. However, whether the mulching pattern during the wheat season can be applied to the wheat-maize system to increase the yield of both crops and to reduce the use of irrigation water remains unclear. Three mulching practices (conventional planting (CP), conventional planting with mulching (CPM) and double-blank planting with mulching (DPM)) during the wheat season were conducted to verify the potential roles of DPM in increasing wheat and maize yields, improving soil temperature and enhancing water storage under the DPM practice. The results show that the DPM practice significantly increased the efficiency spike number, aboveground biomass and grain yield (7.8% higher than CP and 11.3% higher than CPM) of wheat. The heat conservation effect of the DPM practice was stronger in the early stage of growth and was more effective in minimizing fluctuations in soil temperature in the wheat season compared with CPM. The development and yield of maize that was sowed in the mulching lines of DPM were less improved, although the amount of aboveground biomass at the maturity stage was higher. Additionally, the soil temperature of the maize season under DPM showed a narrowing trend of changes during the early stage with slight effects in the middle stage and a resumption of heat conservation in the late stage. Compared with CP, both mulching patterns decreased soil evaporation during the two crops’ seasons by an average 5.3% in CPM and 7.8% in DPM, which is particularly evident when the crops’ leaf area index was low. Therefore, the DPM pattern could more effectively optimize soil temperature and water storage. Furthermore, this pattern may have positive effects on the yields of winter wheat and on reducing the soil water requirement of the maize season.

The continuously increasing concentration of atmospheric CO2 has considerably altered ecosystem functioning. However, few studies have examined the long-term (i.e. over a decade) effect of elevated CO2 on soil microbial communities. Using 16S rRNA gene amplicons and a GeoChip microarray, we investigated soil microbial communities from a Californian annual grassland after 14 years of experimentally elevated CO2 (275 ppm higher than ambient). Both taxonomic and functional gene compositions of the soil microbial community were modified by elevated CO2. There was decrease in relative abundance for taxa with higher ribosomal RNA operon (rrn) copy number under elevated CO2, which is a functional trait that responds positively to resource availability in culture. In contrast, taxa with lower rrn copy number were increased by elevated CO2. As a consequence, the abundance-weighted average rrn copy number of significantly changed OTUs declined from 2.27 at ambient CO2 to 2.01 at elevated CO2. The nitrogen (N) fixation gene nifH and the ammonium-oxidizing gene amoA significantly decreased under elevated CO2 by 12.6% and 6.1%, respectively. Concomitantly, nitrifying enzyme activity decreased by 48.3% under elevated CO2, albeit this change was not significant. There was also a substantial but insignificant decrease in available soil N, with both nitrate (NO3−) (−27.4%) and ammonium (NH4+) (−15.4%) declining. Further, a large number of microbial genes related to carbon (C) degradation were also affected by elevated CO2, whereas those related to C fixation remained largely unchanged. The overall changes in microbial communities and soil N pools induced by long-term elevated CO2 suggest constrained microbial N decomposition, thereby slowing the potential maximum growth rate of the microbial community.

Soil fungal communities play a critical role in ecosystem carbon (C) and nitrogen (N) cycling. Although the effect of plant invasions on ecosystem C and N cycling is well established, its impact on soil fungal communities is not fully understood. The objective of this study was therefore to understand the variations in soil fungal communities as affected by plant invasion, and the mechanisms that drive these changes.

In order to better understand the variations in soil bacterial community and associated drivers following plant invasion, we investigated changes in soil bacterial community along with 9-, 13-, 20- and 23-year-old Spartina alterniflora Loisel. (SA) invasion in comparison with bare flat (BF) in the eastern Chinese coastal wetlands, based on analyses of quantitative polymerase chain reaction (qPCR) and Illumina MiSeq DNA sequencing of 16S rRNA gene. The SA invasion significantly elevated soil bacterial abundance and diversity relative to BF, with the highest levels in 9-year-old SA soil, which gradually decreased with SA invasion from 9 to 23 years. The abundance of copiotrophic Proteobacteria, β-proteobacteria, and Bacteroidetes generally diminished along with SA invasion chronosequence. While, changes in abundance of oligotrophic Chloroflexi, Acidobacteria, Nitrospirae and Planctomycetes exhibited opposite trends. Our data suggest that soil nutrient substrates, and physiochemical properties (soil pH and/or moisture) primarily drive the shifts in soil bacterial abundance, diversity, and community composition along with SA invasion chronosequence in the costal wetlands of eastern China. Overall, soil bacterial abundance and diversity peaked in 9-year-old SA community, with soil bacterial community composition changing from copiotrophic to oligotrophic groups along with SA invasion chronosequence.

Plant invasion typically alters the microbial communities of soils, which affects ecosystem carbon (C) and nitrogen (N) cycles. The responses of the soil fungal communities to plant invasion along its chronosequence remain poorly understood. For this study, we investigated variations in soil fungal communities through Illumina MiSeq sequencing analyses of the fungal internal transcribed spacer (ITS) region, and quantitative polymerase chain reaction (qPCR), along a chronosequence (i.e., 9-, 13-, 20- and 23-year-old) of invasive Spartina alterniflora. We compared these variations with those of bare flat in a Chinese Yellow Sea coastal wetland. Our results highlighted that the abundance of soil fungi, the number of operational taxonomic units (OTUs), species richness, and Shannon diversity indices for soil fungal communities were highest in 9-year-old S. alterniflora soil, which gradually declined along the invasion chronosequence. The relative abundance of copiotrophic Basidiomycota revealed significant decreasing trend, while the relative abundance of oligotrophic Ascomycota gradually increased along the S. alterniflora invasion chronosequence. The relative abundance of soil saprotrophic fungi (e.g., undefined saprotrophs) was gradually reduced while symbiotic fungi (e.g., ectomycorrhizal fungi) and pathotrophic fungi (e.g., plant and animal pathogens) progressively increased along the S. alterniflora invasion chronosequence. Our results suggested that S. alterniflora invasion significantly altered soil fungal abundance and diversity, community composition, trophic modes, and functional groups along a chronosequence, via substantially reduced soil litter inputs, and gradually decreased soil pH, moisture, and soil nutrient substrates along the invasion chronosequence, from 9 to 23 years. These changes in soil fungal communities, particularly their trophic modes and functional groups along the S. alterniflora invasion chronosequence could well impact the decomposition and accumulation of soil C and N, while potentially altering ecosystem C and N sinks in a Chinese Yellow Sea coastal wetland.

Aim Leaf litter decomposition in freshwater ecosystems is a vital process linking ecosystem nutrient cycling, energy transfer and trophic interactions. In comparison to terrestrial ecosystems, in which researchers find that litter traits predominantly regulate litter decomposition worldwide, the dominant factors controlling its decomposition in aquatic ecosystems are still debated, with global patterns not well documented. Here, we aimed to explore general patterns and key drivers (e.g., litter traits, climate and water characteristics) of leaf litter decomposition in streams worldwide. Location Global. Time period 1977?2018. Major taxa studied Leaf litter. Methods We synthesized 1,707 records of litter decomposition in streams from 275 studies. We explored variations in decomposition rates among climate zones and tree functional types and between mesh size groups. Regressions were performed to identify the factors that played dominant roles in litter decomposition globally. Results Litter decomposition rates did not differ among tropical, temperate and cold climate zones. Decomposition rates of litter from evergreen conifer trees were much lower than those of deciduous and evergreen broadleaf trees, attributed to the low quality of litter from evergreen conifers. No significant differences were found between decomposition rates of litter from deciduous and evergreen broadleaf trees. Additionally, litter decomposition rates were much higher in coarse- than in fine-mesh bags, which controled the entrance of decomposers of different body sizes. Multiple regressions showed that litter traits (including lignin, C:N ratio) and elevation were the most important factors in regulating leaf litter decomposition. Main conclusions Litter traits predominantly control leaf litter decomposition in streams worldwide. Although further analyses are necessary to explore whether commonalities of the predominant role of litter traits in decomposition exist in both aquatic and terrestrial ecosystems, our findings could contribute to the use of trait-based approaches in modelling the decomposition of litter in streams globally and exploring mechanisms of land?water?atmosphere carbon fluxes.

Plant functional traits can be used to predict ecosystem responses to climate gradients, yet precipitation explains very little variation for most traits. Soil water availability directly influences plant water uptake and thus may assist with the improvement of plant trait–water relationships. However, this promise remains poorly realized due to rare tests. Here, we provide the first study that attempts to link climate factors, vertical soil water availability, and community composition at a regional scale. Our study paired field-measured vertical soil available water (0–300 cm) and community functional composition at 46 herbaceous grassland sites along a steep hydrothermal gradient in the Loess Plateau of Central China. Community functional composition was expressed via community-weighted means of eight traits. Structural equation modeling was employed to evaluate the role of vertical soil available water content, controlled by precipitation and air temperature, in affecting plant community-weighted traits. We found that soil available water content at depths of 20–100 cm was typically responsible for mediating the effects of precipitation and air temperature on plant community composition. This emerged as the predominant factor to explain variations in grassland response traits, including leaf area, specific leaf area, and leaf dry matter content. These traits exhibited clear drought-induced shifts along soil desiccation gradients and responded to drier conditions by reducing leaf area/specific leaf area and increasing leaf dry matter content. Our findings rehighlighted soil water availability as the core driver that needs to be considered in the restoration and management of dryland ecosystems.

Boreal forests are facing profound changes in their growth environment, including warming-induced water deficits, extended growing seasons, accelerated snowmelt, and permafrost thaw. The influence of warming on trees varies regionally, but in most boreal forests studied to date, tree growth has been found to be negatively affected by increasing temperatures. Here, we used a network of Pinus sylvestris tree-ring collections spanning a wide climate gradient the southern end of the boreal forest in Asia to assess their response to climate change for the period 1958?2014. Contrary to findings in other boreal regions, we found that previously negative effects of temperature on tree growth turned positive in the northern portion of the study network after the onset of rapid warming. Trees in the drier portion did not show this reversal in their climatic response during the period of rapid warming. Abundant water availability during the growing season, particularly in the early to mid-growing season (May?July), is key to the reversal of tree sensitivity to climate. Advancement in the onset of growth appears to allow trees to take advantage of snowmelt water, such that tree growth increases with increasing temperatures during the rapidly warming period. The region's monsoonal climate delivers limited precipitation during the early growing season, and thus snowmelt likely covers the water deficit so trees are less stressed from the onset of earlier growth. Our results indicate that the growth response of P. sylvestris to increasing temperatures strongly related to increased early season water availability. Hence, boreal forests with sufficient water available during crucial parts of the growing season might be more able to withstand or even increase growth during periods of rising temperatures. We suspect that other regions of the boreal forest may be affected by similar dynamics.

Boreal forests are facing profound changes in their growth environment, including warming-induced water deficits, extended growing seasons, accelerated snowmelt, and permafrost thaw. The influence of warming on trees varies regionally, but in most boreal forests studied to date, tree growth has been found to be negatively affected by increasing temperatures. Here, we used a network of Pinus sylvestris tree-ring collections spanning a wide climate gradient the southern end of the boreal forest in Asia to assess their response to climate change for the period 1958?2014. Contrary to findings in other boreal regions, we found that previously negative effects of temperature on tree growth turned positive in the northern portion of the study network after the onset of rapid warming. Trees in the drier portion did not show this reversal in their climatic response during the period of rapid warming. Abundant water availability during the growing season, particularly in the early to mid-growing season (May?July), is key to the reversal of tree sensitivity to climate. Advancement in the onset of growth appears to allow trees to take advantage of snowmelt water, such that tree growth increases with increasing temperatures during the rapidly warming period. The region's monsoonal climate delivers limited precipitation during the early growing season, and thus snowmelt likely covers the water deficit so trees are less stressed from the onset of earlier growth. Our results indicate that the growth response of P. sylvestris to increasing temperatures strongly related to increased early season water availability. Hence, boreal forests with sufficient water available during crucial parts of the growing season might be more able to withstand or even increase growth during periods of rising temperatures. We suspect that other regions of the boreal forest may be affected by similar dynamics.

The traditional view holds that biological nitrogen (N) fixation often peaks in early- or mid-successional ecosystems and declines throughout succession based on the hypothesis that soil N richness and/or phosphorus (P) depletion become disadvantageous to N fixers. This view, however, fails to support the observation that N fixers can remain active in many old-growth forests despite the presence of N-rich and/or P-limiting soils. Here, we found unexpected increases in N fixation rates in the soil, forest floor, and moss throughout three successional forests and along six age-gradient forests in southern China. We further found that the variation in N fixation was controlled by substrate carbon(C) : N and C : (N : P) stoichiometry rather than by substrate N or P. Our findings highlight the utility of ecological stoichiometry in illuminating the mechanisms that couple forest succession and N cycling.

Asymbiotic nitrogen (N) fixation (ANF) is an important source of N in pristine forests and is predicted to decrease with N deposition. Previous studies revealing N fixation in response to N deposition have mostly applied understory N addition approaches, neglecting the key processes (for example, N retention and uptake) occurring in forest canopy. This study evaluated the effects of N deposition on N fixation in the soil, forest floor, mosses, and canopy leaves in a temperate forest (in central China) and a tropical forest (in southern China) with different treatments: control, understory N addition, and canopy N addition. Results showed that total ANF rates were higher in the temperate forest (2.57 ± 0.19 mg N m−2 d−1) than in the tropical forest (1.34 ± 0.09 mg N m−2 d−1). N addition inhibited the soil, forest floor, moss, and foliar N fixation in the temperate forest, whereas it inhibited only the soil N fixation in the tropical forest. Compared to canopy N addition, understory N addition overestimated the inhibitory effects of N deposition on total ANF slightly in the tropical forest (by 35%) but severely in the temperate forest (by 375–472%) due to neglecting canopy retention of N. In summary, our findings indicate that ANF has different rates and sensitivities to N addition between tropical and temperate forests and that understory N addition overestimates the N deposition effects on ANF in forests, particularly in the temperate forest. These findings are important for our accurate understanding and estimate of terrestrial N fixation under N deposition scenarios.

Biological nitrogen (N) fixation (BNF), an important source of N in terrestrial ecosystems, plays a critical role in terrestrial nutrient cycling and net primary productivity. Currently, large uncertainty exists regarding how nutrient availability regulates terrestrial BNF and the drivers responsible for this process. We conducted a global meta-analysis of terrestrial BNF in response to N, phosphorus (P), and micronutrient (Micro) addition across different biomes (i.e., tropical/subtropical forest, savanna, temperate forest, grassland, boreal forest, and tundra) and explored whether the BNF responses were affected by fertilization regimes (nutrient-addition rates, duration, and total load) and environmental factors (mean annual temperature (MAT), mean annual precipitation (MAP), and N deposition). The results showed that N addition inhibited terrestrial BNF (by 19.0% [95% confidence interval (CI): 17.7?20.3%]; hereafter), Micro addition stimulated terrestrial BNF (30.4% [25.7?35.3%]), and P addition had an inconsistent effect on terrestrial BNF (i.e., inhibiting free-living N fixation (7.5% [4.4?10.6%]) and stimulating symbiotic N fixation (85.5% [25.8?158.7%])). Furthermore, the response ratios (i.e., effect sizes) of BNF to nutrient addition were smaller in low-latitude (&lt;30°) biomes (8.5?36.9%) than in mid-/high-latitude (≥30°) biomes (32.9?61.3%), and the sensitivity (defined as the absolute value of response ratios) of BNF to nutrients in mid-/high-latitude biomes decreased with decreasing latitude (p≤0.009; linear/logarithmic regression models). Fertilization regimes did not affect this phenomenon (p&gt;0.05), but environmental factors did affect it (p&lt;0.001) because MAT, MAP, and N deposition accounted for 5?14%, 10?32%, and 7?18% of the variance in the BNF response ratios in cold (MAT&lt;15°C), low-rainfall (MAP&lt;2500 mm), and low-N-deposition (&lt;7 kg ha?1 yr?1) biomes, respectively. Overall, our meta-analysis depicts a global pattern of nutrient impacts on terrestrial BNF and indicates that certain types of global change (i.e., warming, elevated precipitation and N deposition) may reduce the sensitivity of BNF in response to nutrient enrichment in mid-/high-latitude biomes. This article is protected by copyright.

Estimating soil erosion and nutrient losses from surface runoff in paddy fields is essential for the assessment of sustainable rice (Oryza sativa L.) production and water quality protection. Different rice establishment methods have been used in the last three decades in Asia; however, it is still unclear how these methods influence sustainable agriculture and environmental protection in humid areas. The aim of this study was to evaluate the impacts of rice establishment method on soil erosion and phosphorus (P) losses from surface runoff in Hydragric Anthrosols under a subtropical monsoon climate. Total suspended solids (TSS), total P (TP), dissolved P (DP), and particulate P (PP) runoff losses were measured under four rice establishment treatments in 2013 and 2014, including traditional manual transplanting (TT), mechanical transplanting (MT), dry direct seeding (DD), and wet direct seeding (WD). The results showed that the seasonal TSS in the runoff varied from 59.9 to 829.8 kg ha−1 in the two years. Compared with TT, the DD significantly increased the TSS by 481% in 2013 and by 349% in 2014, while the WD significantly increased TSS by 783% in 2013 and by 571% in 2014. In the 2013 and 2014 rice seasons, the field-observed TP runoff losses were from 0.18 to 1.51 kg ha−1. Compared with TT, the DD significantly increased the TP lost by 222% in 2013 and by 197% in 2014, whereas the WD significantly increased the TP lost by 483% in 2013 and by 387% in 2014. However, the TSS and P losses from the MT and TT were similar in both years. The PP runoff losses accounted for 58–77% of the seasonal TP lost. These findings demonstrate that the conversion of traditional manual transplanting to direct seeding increased soil erosion and P runoff losses in subtropical China.

Plant diversity can increase biomass production in plot-scale studies, but applying these results to ecosystem carbon (C) storage at larger spatial and temporal scales remains problematic. Other ecosystem controls interact with diversity and plant production, and may influence soil pools differently from plant pools. We integrated diversity with the state-factor framework, which identifies key controls, or ?state factors?, over ecosystem properties and services such as C storage. We used this framework to assess the effects of diversity, plant traits and state factors (climate, topography, time) on live tree, standing dead, organic horizon and total C in Québec forests. Four patterns emerged: (1) while state factors were usually the most important model predictors, models with both state and biotic factors (mean plant traits and diversity) better predicted C pools; (2) mean plant traits were better predictors than diversity; (3) diversity increased live tree C but reduced organic horizon C; (4) different C pools responded to different traits and diversity metrics. These results suggest that, where ecosystem properties result from multiple processes, no simple relationship may exist with any one organismal factor. Integrating biodiversity into ecosystem ecology and assessing both traits and diversity improves our mechanistic understanding of biotic effects on ecosystems.

Fire severity is increasing across the boreal forest biome as climate warms, and initial post-fire changes in tree demographic processes could be important determinants of long-term forest structure and carbon dynamics. To examine soil burn severity impacts on tree regeneration, we conducted experimental burns in summer 2012 that created a gradient of residual post-fire soil organic layer (SOL) depth within a mature, sparse-canopy Cajander larch (Larix cajanderi Mayr.) forest in the Eastern Siberian Arctic. Each fall from 2012 to 2016, we added larch seeds to plots along the burn severity gradient. We tracked density of new larch germinants and established seedlings (alive ≥ 1 year) during subsequent growing seasons, along with changes in seedbed conditions (permafrost thaw depth, moisture, and temperature). Over the study, a cumulative total of 17 and 18 new germinants m−2 occurred in high and moderate severity treatments, respectively, while germinants were rare in unburned and low severity treatments (< 0.5 germinants m−2). Most seedlings (> 50%) germinated in summer 2017, following a mast event in fall 2016, suggesting safe sites for germination were not fully occupied in previous years despite seed additions. By 2017, established seedling density was ∼5 times higher on moderate and high severity treatments compared to other treatments. Cumulative total density of new germinants and established seedlings increased linearly with decreasing residual SOL depth, as did thaw depth, soil moisture, and soil temperature. Our findings suggest that increased soil burn severity could improve seedbed conditions and increase larch recruitment, assuming seed sources are available. If these demographic changes persist as stands mature, a climate-driven increase in soil burn severity could shift forest structure from sparse-canopy stands, which dominate this region of the Siberian Arctic, to high density stands, with potential implications for carbon, energy, and water cycling.

The Tundra Trait Team (TTT) database includes field-based measurements of key traits related to plant form and function at multiple sites across the tundra biome. This dataset can be used to address theoretical questions about plant strategy and trade-offs, trait?environment relationships and environmental filtering, and trait variation across spatial scales, to validate satellite data, and to inform Earth system model parameters. Main types of variable contained The database contains 91,970 measurements of 18 plant traits. The most frequently measured traits (&gt;1,000 observations each) include plant height, leaf area, specific leaf area, leaf fresh and dry mass, leaf dry matter content, leaf nitrogen, carbon and phosphorus content, leaf C:N and N:P, seed mass, and stem specific density. Spatial location and grain Measurements were collected in tundra habitats in both the Northern and Southern Hemispheres, including Arctic sites in Alaska, Canada, Greenland, Fennoscandia and Siberia, alpine sites in the European Alps, Colorado Rockies, Caucasus, Ural Mountains, Pyrenees, Australian Alps, and Central Otago Mountains (New Zealand), and sub-Antarctic Marion Island. More than 99% of observations are georeferenced. Time period and grain All data were collected between 1964 and 2018. A small number of sites have repeated trait measurements at two or more time periods. Major taxa and level of measurement Trait measurements were made on 978 terrestrial vascular plant species growing in tundra habitats. Most observations are on individuals (86%), while the remainder represent plot or site means or maximums per species. Software format csv file and GitHub repository with data cleaning scripts in R; contribution to TRY plant trait database (www.try-db.org) to be included in the next version release.

Soil organic matter (SOM) turnover increasingly is conceptualized as a tension between accessibility to microorganisms and protection from decomposition via physical and chemical association with minerals in emerging soil biogeochemical theory. Yet, these components are missing from the original mathematical models of belowground carbon dynamics and remain underrepresented in more recent compartmental models that separate SOM into discrete pools with differing turnover times. Thus, a gap currently exists between the emergent understanding of SOM dynamics and our ability to improve terrestrial biogeochemical projections that rely on the existing models. In this opinion paper, we portray the SOM paradigm as a triangle composed of three nodes: conceptual theory, analytical measurement, and numerical models. In successful approaches, we contend that the nodes are connected—models capture the essential features of dominant theories while measurement tools generate data adequate to parameterize and evaluate the models—and balanced—models can inspire new theories via emergent behaviors, pushing empiricists to devise new measurements. Many exciting advances recently pushed the boundaries on one or more nodes. However, newly integrated triangles have yet to coalesce. We conclude that our ability to incorporate mechanisms of microbial decomposition and physicochemical protection into predictions of SOM change is limited by current disconnections and imbalances among theory, measurement, and modeling. Opportunities to reintegrate the three components of the SOM paradigm exist by carefully considering their linkages and feedbacks at specific scales of observation.

The fundamental niche of many species is shifting with climate change, especially in sub-arctic ecosystems with pronounced recent warming. Ongoing warming in sub-arctic regions should lessen environmental constraints on tree growth and reproduction, leading to increased success of trees colonising tundra. Nevertheless, variable responses of treeline ecotones have been documented in association with warming temperatures. One explanation for time lags between increasingly favourable environmental conditions and treeline ecotone movement is reproductive limitations caused by low seed availability. Our objective was to assess the reproductive constraints of the dominant tree species at the treeline ecotone in the circumpolar north. We sampled reproductive structures of trees (cones and catkins) and stand attributes across circumarctic treeline ecotones. We used generalized linear mixed models to estimate the sensitivity of seed production and the availability of viable seed to regional climate, stand structure, and species-specific characteristics. Both seed production and viability of available seed were strongly driven by specific, sequential seasonal climatic conditions, but in different ways. Seed production was greatest when growing seasons with more growing degree days coincided with years with high precipitation. Two consecutive years with more growing degree days and low precipitation resulted in low seed production. Seasonal climate effects on the viability of available seed depended on the physical characteristics of the reproductive structures. Large-coned and -seeded species take more time to develop mature embryos and were therefore more sensitive to increases in growing degree days in the year of flowering and embryo development. Our findings suggest that both moisture stress and abbreviated growing seasons can have a notable negative influence on the production and viability of available seed at treeline. Our synthesis revealed that constraints on predispersal reproduction within the treeline ecotone might create a considerable time lag for range expansion of tree populations into tundra ecosystems.

Climate change is shifting the phenological cycles of plants1, thereby altering the functioning of ecosystems, which in turn induces feedbacks to the climate system2. In northern (north of 30° N) ecosystems, warmer springs lead generally to an earlier onset of the growing season3,4 and increased ecosystem productivity early in the season5. In situ6 and regional7–9 studies also provide evidence for lagged effects of spring warmth on plant productivity during the subsequent summer and autumn. However, our current understanding of these lagged effects, including their direction (beneficial or adverse) and geographic distribution, is still very limited. Here we analyse satellite, field-based and modelled data for the period 1982–2011 and show that there are widespread and contrasting lagged productivity responses to spring warmth across northern ecosystems. On the basis of the observational data, we find that roughly 15 per cent of the total study area of about 41 million square kilometres exhibits adverse lagged effects and that roughly 5 per cent of the total study area exhibits beneficial lagged effects. By contrast, current-generation terrestrial carbon-cycle models predict much lower areal fractions of adverse lagged effects (ranging from 1 to 14 per cent) and much higher areal fractions of beneficial lagged effects (ranging from 9 to 54 per cent). We find that elevation and seasonal precipitation patterns largely dictate the geographic pattern and direction of the lagged effects. Inadequate consideration in current models of the effects of the seasonal build-up of water stress on seasonal vegetation growth may therefore be able to explain the differences that we found between our observation-constrained estimates and the model-constrained estimates of lagged effects associated with spring warming. Overall, our results suggest that for many northern ecosystems the benefits of warmer springs on growing-season ecosystem productivity are effectively compensated for by the accumulation of seasonal water deficits, despite the fact that northern ecosystems are thought to be largely temperature- and radiation-limited10.

Understanding drivers of straw decomposition is essential for adopting appropriate management practice to improve soil fertility and promote carbon (C) sequestration in agricultural systems. However, predicting straw decomposition and characteristics is difficult because of the interactions between many factors related to straw properties, soil properties, and climate, especially under future climate change conditions. This study investigated the driving factors of straw decomposition of six types of crop straw including wheat, maize, rice, soybean, rape, and other straw by synthesizing 1642 paired data from 98 published papers at spatial and temporal scales across China. All the data derived from the field experiments using little bags over twelve years. Overall, despite large differences in climatic and soil properties, the remaining straw carbon (C, %) could be accurately represented by a three-exponent equation with thermal time (accumulative temperature). The lignin/nitrogen and lignin/phosphorus ratios of straw can be used to define the size of labile, intermediate, and recalcitrant C pool. The remaining C for an individual type of straw in the mild-temperature zone was higher than that in the warm-temperature and subtropical zone within one calendar year. The remaining straw C after one thermal year was 40.28%, 37.97%, 37.77%, 34.71%, 30.87%, and 27.99% for rice, soybean, rape, wheat, maize, and other straw, respectively. Soil available nitrogen and phosphorus influenced the remaining straw C at different decomposition stages. For one calendar year, the total amount of remaining straw C was estimated to be 29.41 Tg and future temperature increase of 2 °C could reduce the remaining straw C by 1.78 Tg. These findings confirmed the long-term straw decomposition could be mainly driven by temperature and straw quality, and quantitatively predicted by thermal time with the three-exponent equation for a wide array of straw types at spatial and temporal scales in agro-ecosystems of China.

The global carbon cycle is strongly controlled by the source/sink strength of vegetation as well as the capacity of terrestrial ecosystems to retain this carbon. These dynamics, as well as processes such as the mixing of old and newly fixed carbon, have been studied using ecosystem models, but different assumptions regarding the carbon allocation strategies and other model structures may result in highly divergent model predictions. We assessed the influence of three different carbon allocation schemes on the C cycling in vegetation. First, we described each model with a set of ordinary differential equations. Second, we used published measurements of ecosystem C compartments from the Harvard Forest Environmental Measurement Site to find suitable parameters for the different model structures. And third, we calculated C stocks, release fluxes, radiocarbon values (based on the bomb spike), ages, and transit times. We obtained model simulations in accordance with the available data, but the time series of C in foliage and wood need to be complemented with other ecosystem compartments in order to reduce the high parameter collinearity that we observed, and reduce model equifinality. Although the simulated C stocks in ecosystem compartments were similar, the different model structures resulted in very different predictions of age and transit time distributions. In particular, the inclusion of two storage compartments resulted in the prediction of a system mean age that was 12–20 years older than in the models with one or no storage compartments. The age of carbon in the wood compartment of this model was also distributed towards older ages, whereas fast cycling compartments had an age distribution that did not exceed 5 years. As expected, models with C distributed towards older ages also had longer transit times. These results suggest that ages and transit times, which can be indirectly measured using isotope tracers, serve as important diagnostics of model structure and could largely help to reduce uncertainties in model predictions. Furthermore, by considering age and transit times of C in vegetation compartments as distributions, not only their mean values, we obtain additional insights into the temporal dynamics of carbon use, storage, and allocation to plant parts, which not only depends on the rate at which this C is transferred in and out of the compartments but also on the stochastic nature of the process itself.

Extracellular enzymes catalyze rate-limiting steps in soil organic matter decomposition, and their activities (EEAs) play a key role in determining soil respiration (SR). Both EEAs and SR are highly sensitive to temperature, but their responses to climate warming remain poorly understood. Here, we present a meta-analysis on the response of soil cellulase and ligninase activities and SR to warming, synthesizing data from 56 studies. We found that warming significantly enhanced ligninase activity by 21.4% but had no effect on cellulase activity. Increases in ligninase activity were positively correlated with changes in SR, while no such relationship was found for cellulase. The warming response of ligninase activity was more closely related to the responses of SR than a wide range of environmental and experimental methodological factors. Furthermore, warming effects on ligninase activity increased with experiment duration. These results suggest that soil microorganisms sustain long-term increases in SR with warming by gradually increasing the degradation of the recalcitrant carbon pool.

Agricultural and industrial activities have increased atmospheric nitrogen (N) deposition to ecosystems worldwide. N deposition can stimulate plant growth and soil carbon (C) input, enhancing soil C storage. Changes in microbial decomposition could also influence soil C storage, yet this influence has been difficult to discern, partly because of the variable effects of added N on the microbial enzymes involved. We show, using meta-analysis, that added N reduced the activity of lignin-modifying enzymes (LMEs), and that this N-induced enzyme suppression was associated with increases in soil C. In contrast, N-induced changes in cellulase activity were unrelated to changes in soil C. Moreover, the effects of added soil N on LME activity accounted for more of the variation in responses of soil C than a wide range of other environmental and experimental factors. Our results suggest that, through responses of a single enzyme system to added N, soil microorganisms drive long-term changes in soil C accumulation. Incorporating this microbial influence on ecosystem biogeochemistry into Earth system models could improve predictions of ecosystem C dynamics.

Grazing exclusion (GE) is an effective method for protecting degraded grasslands, and it can profoundly affect ecosystem carbon (C) cycles. Ecosystem respiration (ER), which includes both autotrophic and heterotrophic respiration (HR), accounts for the largest land-to-atmosphere C fluxes. How ER responds to GE is still unclear, however, and to investigate this, a controlled GE experiment was conducted at a meadow grassland near Qinghai Lake, China. Animal exclusion enhanced ER and aboveground plant respiration (Ragb) by 10.5% and 40.1%, respectively, but it suppressed soil respiration by 12.4% and HR by 17.6%. Positive responses of ER and Ragb were linked to increased aboveground biomass, particularly graminoids biomass. Negative responses of soil respiration and HR were associated with GE-induced changes in microbial biomass C and nitrogen. These results show that grassland responded in complex ways to GE and that ER and its components were regulated by both abiotic and biotic factors. Moreover, the divergent responses of respiration components have important implications for models of terrestrial C cycles and climate under enhanced human activities and changes in land use.

Partitioning of evapotranspiration (ET) into biological component transpiration (T) and non-biological component evaporation (E) is crucial in understanding the impact of environmental change on ecosystems and water resources. However, direct measurement of transpiration is still challenging. In this paper, an optimality-based ecohydrological model named Vegetation Optimality Model (VOM) is applied for ET partitioning. The results show that VOM model can reasonably simulate ET and ET components in a semiarid shrubland. Overall, the ratio of transpiration to evapotranspiration is 49% for the whole period. Evaporation and plant transpiration mainly occur in monsoon following the precipitation events. Evaporation responds immediately to precipitation events, while transpiration shows a lagged response of several days to those events. Different years demonstrate different patterns of T/ET ratio dynamic in monsoon. Some of the years show a low T/ET ratio at the beginning of monsoon and slowly increased T/ET ratio. Other years show a high level of T/ET ratio for the whole monsoon. We find out that spring precipitation, especially the size of the precipitation, has a significant influence on the T/ET ratio in monsoon.

Many Low Arctic tundra regions are currently undergoing a vegetation shift towards increasing growth and groundcover of tall deciduous shrubs due to recent climate warming. Vegetation change directly affects ecosystem carbon balance, but it can also affect soil biogeochemical cycling through physical and biological feedback mechanisms. Recent studies indicate that enhanced snow accumulation around relatively tall shrubs has negligible physical effect on litter decomposition rates. However, these investigations were no more than 3 years, and therefore may be insufficient to detect differences in inherently slow biogeochemical processes. Here, we report a 5-year study near Daring Lake, Canada, comparing Betula neoalaskana foliar litter decay rates within unmanipulated and snowfenced low-stature birch (height: ~ 0.3 m) plots to test the physical effect of experimentally deepened snow, and within tall birch (height: ~ 0.8 m) plots to test the combined physical and biological effects, that is, deepened snow plus strong birch dominance. Having corrected for carbon gain by the colonizing decomposers, actual litter carbon loss increased by approximately 25% in the tall birch relative to both low birch sites. Decay of lignin-like acid unhydrolizable litter residues also accelerated in the tall birch site, and a similar but lower magnitude response in the snowfenced low birch site indicated that physical effects of deepened snow were at least partially responsible. In contrast, deepened snow alone did not affect litter carbon loss. Our findings suggest that a combination of greater litter inputs, altered soil microbial community, enhanced soil nutrient pools, and warmer winter soils together promote relatively fast decomposition of recalcitrant litter carbon in tall birch shrub environments.

Leaf litter provides an important nutrient subsidy to headwater streams, but little is known about how tree genetics influences energy pathways from litter to higher trophic levels. Despite the charge to quantify carbon (C) and nitrogen (N) pathways from decomposing litter, the relationship between litter decomposition and aquatic consumers remains unresolved. We measured litter preference (attachments to litter), C and N assimilation rates, and growth rates of a shredding caddisfly (Hesperophylax magnus, Limnephilidae) in response to leaf litter of different chemical and physical phenotypes using Populus cross types (P. fremontii, P. angustifolia, and F1 hybrids) and genotypes within P. angustifolia. We combined laboratory mesocosm studies using litter from a common garden with a field study using doubly labeled litter (13 C and 15 N) grown in a greenhouse and incubated in Oak Creek, AZ. We found that, in the lab, shredders initially chose relatively labile (low lignin and condensed tannin concentrations, rapidly decomposing) cross type litter, but preference changed within four days to relatively recalcitrant (high lignin and condensed tannin concentrations, slowly decomposing) litter types. Additionally, in the lab, shredder growth rates were higher on relatively recalcitrant compared to labile cross type litter. Over the course of a three-week field experiment, shredders also assimilated more C and N from relatively recalcitrant compared to labile cross type litter. Finally, among P. angustifolia genotypes, N assimilation by shredders was positively related to litter lignin and C:N, but negatively related to condensed tannins and decomposition rate. C assimilation was likewise positively related to litter C:N, and also to litter %N. C assimilation was not associated with condensed tannins or lignin. Collectively, these findings suggest that relatively recalcitrant litter of Populus cross types provides more nutritional benefit, in terms of N fluxes and growth, than labile litter, but among P. angustifolia genotypes the specific trait of litter recalcitrance (lignin or tannins) determines effects on C or N assimilation. As shredders provide nutrients and energy to higher trophic levels, the influence of these genetically based plant decomposition pathways on shredder preference and performance may affect community and food web structure.

We sought to determine if the prevalence of antibiotic-resistant Escherichia coli differed across retail poultry products and among major production categories, including organic, “raised without antibiotics”, and conventional.

Quantifying the ecological patterns of loss of ecosystem function in extreme drought is important to understand the carbon exchange between the land and atmosphere. Rain-use efficiency [RUE; gross primary production (GPP)/precipitation] acts as a typical indicator of ecosystem function. In this study, a novel method based on maximum rain-use efficiency (RUEmax) was developed to detect losses of ecosystem function globally. Three global GPP datasets from the MODIS remote sensing data (MOD17), ground upscaling FLUXNET observations (MPI-BGC), and process-based model simulations (BESS), and a global gridded precipitation product (CRU) were used to develop annual global RUE datasets for 2001-2011. Large, well-known extreme drought events were detected, e.g. 2003 drought in Europe, 2002 and 2011 drought in the U.S., and 2010 drought in Russia. Our results show that extreme drought-induced loss of ecosystem function could impact 0.9% ± 0.1% of earth's vegetated land per year and was mainly distributed in semi-arid regions. The reduced carbon uptake caused by functional loss (0.14 ± 0.03 PgC/yr) could explain &gt;70% of the interannual variation in GPP in drought-affected areas (p ≤ 0.001). Our results highlight the impact of ecosystem function loss in semi-arid regions with increasing precipitation variability and dry land expansion expected in the future. Copyright © 2018 Elsevier B.V. All rights reserved.

The interaction between terrestrial carbon (C) and nitrogen (N) cycles has been incorporated into more and more land surface models. However, the scheme of C–N coupling differs greatly among models, and how these diverse representations of C–N interactions will affect C-cycle modeling remains unclear. In this study, we explored how the simulated ecosystem C storage capacity in the terrestrial ecosystem (TECO) model varied with three different commonly used schemes of C–N coupling. The three schemes (SM1, SM2, and SM3) have been used in three different coupled C–N models (i.e., TECO-CN, CLM 4.5, and O-CN, respectively). They differ mainly in the stoichiometry of C and N in vegetation and soils, plant N uptake strategies, downregulation of photosynthesis, and the pathways of N import. We incorporated the three C–N coupling schemes into the C-only version of the TECO model and evaluated their impacts on the C cycle with a traceability framework. Our results showed that all three of the C–N schemes caused significant reductions in steady-state C storage capacity compared with the C-only version with magnitudes of <span class="inline-formula">−23</span> %, <span class="inline-formula">−30</span> %, and <span class="inline-formula">−54</span> % for SM1, SM2, and SM3, respectively. This reduced C storage capacity was mainly derived from the combined effects of decreases in net primary productivity (NPP; <span class="inline-formula">−29</span> %, <span class="inline-formula">−15</span> %, and <span class="inline-formula">−</span>45 %) and changes in mean C residence time (MRT; 9 %, <span class="inline-formula">−17</span> %, and <span class="inline-formula">−17</span> %) for SM1, SM2, and SM3, respectively. The differences in NPP are mainly attributed to the different assumptions on plant N uptake, plant tissue <span class="inline-formula">C</span> <span class="inline-formula">:</span> <span class="inline-formula">N</span> ratio, downregulation of photosynthesis, and biological N fixation. In comparison, the alternative representations of the plant vs. microbe competition strategy and the plant N uptake, combined with the flexible <span class="inline-formula">C</span> <span class="inline-formula">:</span> <span class="inline-formula">N</span> ratio in vegetation and soils, led to a notable spread in MRT. These results highlight the fact that the diverse assumptions on N processes represented by different C–N coupled models could cause additional uncertainty for land surface models. Understanding their difference can help us improve the capability of models to predict future biogeochemical cycles of terrestrial ecosystems.

Roads are a main threat to biodiversity conservation in the Amazon, in part, because roads increase access for hunters. We examine how increased landscape access by hunters may lead to cascading effects that influence the prey community and abundance of the jaguar (Panthera onca), the top Amazonian terrestrial predator. Understanding such ecological effects originating from anthropogenic actions is essential for conservation and management of wildlife populations in areas undergoing infrastructure development. Our study was conducted in Yasuní Biosphere Reserve, the protected area with highest potential for jaguar conservation in Ecuador, and an area both threatened by road development and inhabited by indigenous groups dependent upon bushmeat. We surveyed prey and jaguar abundance with camera traps in four sites that differed in accessibility to hunters and used site occupancy and spatially explicit capture-recapture analyses to evaluate prey occurrence and estimate jaguar density, respectively. Higher landscape accessibility to hunters was linked with lower occurrence and biomass of game, particularly white-lipped peccary (Tayassu pecari) and collared peccary (Pecari tajacu), the primary game for hunters and prey for jaguars. Jaguar density was up to 18 times higher in the most remote site compared to the most accessible site. Our results provide a strong case for the need to: 1) consider conservation of large carnivores and other wildlife in policies about road construction in protected areas, 2) coordinate conservation initiatives with local governments so that development activities do not conflict with conservation objectives, and 3) promote development of community-based strategies for wildlife management that account for the needs of large carnivores.

Plant functional traits research has revealed many interesting and important patterns among morphological, physiological, and life-history traits and the environment. These are exemplified in trade-offs between groups of traits such as those embodied in the leaf and wood economics spectra. Inferences from empirical studies are often constrained by the correlative nature of the analyses, availability of trait data, and a focus on easily measured traits. However, empirical studies have been fundamental to modeling endeavors aiming to enhance our understanding of how functional traits scale up to affect, for example, community dynamics and ecosystem productivity. Here, we take a complementary approach utilizing an individual-based model of tree growth and mortality (the allometrically constrained growth and carbon allocation [ACGCA] model) to investigate the theoretical trait space (TTS) of North American trees. The model includes 32 parameters representing allometric, physiological, and anatomical traits, some overlapping leaf and wood economics spectra traits. Using a Bayesian approach, we fit the ACGCA model to individual tree heights and diameters from the USFS Forest Inventory and Analysis (FIA) dataset, with further constraints by literature-based priors. Fitting the model to 1.3 million FIA records?aggregated across individuals, species, and sites?produced a posterior distribution of traits leading to realistic growth. We explored this multidimensional posterior distribution (the TTS) to evaluate trait?trait relationships emerging from the ACGCA model, and compare these against empirical patterns reported in the literature. Only three notable bivariate correlations, among 496 possible trait pairs, were contained in the TTS. However, stepwise regressions uncovered a complicated structure; only a subset of traits?related to photosynthesis (e.g., radiation-use efficiency and maintenance respiration)?exhibited strong multivariate trade-offs with each other, while half of the traits?mostly related to allometries and construction costs?varied independently of other traits. Interestingly, specific leaf area was related to several rarely measured root traits. The trade-offs contained in the TTS generally reflect mass-balance (related to carbon allocation) and engineering (mostly related to allometries) trade-offs represented in the ACGCA model and point to potentially important traits that are under-explored in field studies (e.g., root traits and branch senescence rates).

We refer to a theoretical trait space (TTS) as an n-dimensional hypervolume (hypercube) characterizing the range of values and covariations among multiple functional traits, in the absence of explicit filtering mechanisms. We previously constructed a 32-dimensional TTS for North American trees by fitting the Allometrically Constrained Growth and Carbon Allocation (ACGCA) model to USFS Forest Inventory and Analysis (FIA) data. Here, we sampled traits from this TTS, representing different individual ?trees,? and subjected these trees to a series of gap dynamics simulations resulting in different annual light levels to explore the impact of environmental filtering (light stress) on the trait space. Variation in light limitation led to non-random mortality and a refinement of the TTS. We investigated potential mechanisms underlying such filtering processes by exploring how traits and the environment relate to mortality rates at the tree, phenotype (a specific set of trait values), and stand (a specific gap scenario) levels. The average light level at the forest floor explained 42% of the stand-level mortality, while phenotype- and tree-level mortality were best explained by six functional traits, especially radiation-use efficiency, maximum tree height, and xylem conducting area to sapwood area ratio (?X). These six ?mortality? traits and six traits related to the leaf and wood economics spectra were used to construct trait hypercubes represented by trees that died or survived each gap scenario. For trees that survived, the volume of their refined trait space decreased linearly with increasing stand-level mortality (up to ~50% mortality); the location also shifted, as indicated by non-zero distances between the hypercube centroids of surviving trees compared to dead trees and the original TTS. Overall, the patterns were consistent with empirical studies of functional traits, in terms of which traits predict mortality and the direction of the relationships. This work, however, also identified potentially important functional traits that are not commonly measured in empirical studies, such as ?X and senescence rates of relatively long-lived tissues.

Data-model integration plays a critical role in assessing and improving our capacity to predict ecosystem dynamics. Similarly, the ability to attach quantitative statements of uncertainty around model forecasts is crucial for model assessment and interpretation and for setting field research priorities. Bayesian methods provide a rigorous data assimilation framework for these applications, especially for problems with multiple data constraints. However, the Markov chain Monte Carlo (MCMC) techniques underlying most Bayesian calibration can be prohibitive for computationally demanding models and large datasets. We employ an alternative method, Bayesian model emulation of sufficient statistics, that can approximate the full joint posterior density, is more amenable to parallelization, and provides an estimate of parameter sensitivity. Analysis involved informative priors constructed from a meta-analysis of the primary literature and specification of both model and data uncertainties, and it introduced novel approaches to autocorrelation corrections on multiple data streams and emulating the sufficient statistics surface. We report the integration of this method within an ecological workflow management software, Predictive Ecosystem Analyzer (PEcAn), and its application and validation with two process-based terrestrial ecosystem models: SIPNET and ED2. In a test against a synthetic dataset, the emulator was able to retrieve the true parameter values. A comparison of the emulator approach to standard <q>brute-force</q> MCMC involving multiple data constraints showed that the emulator method was able to constrain the faster and simpler SIPNET model's parameters with comparable performance to the brute-force approach but reduced computation time by more than 2 orders of magnitude. The emulator was then applied to calibration of the ED2 model, whose complexity precludes standard (brute-force) Bayesian data assimilation techniques. Both models are constrained after assimilation of the observational data with the emulator method, reducing the uncertainty around their predictions. Performance metrics showed increased agreement between model predictions and data. Our study furthers efforts toward reducing model uncertainties, showing that the emulator method makes it possible to efficiently calibrate complex models.

Native soil organic carbon (SOC) decomposition rates may be altered through increased carbon (C) input, a phenomenon known as SOC priming (Blagodatskaya et al., 2011). Quantifying priming is important because it may modulate long-term SOC storage in ecosystems and therefore C biogeochemical cycling. Priming is positive when more SOC is decomposed or, conversely, negative when less native SOC is decomposed after C amendment (Kuzyakov et al., 2000; Kuzyakov, 2002; Bader and Cheng, 2007). Yet, controls over the direction and magnitude of the priming effect and the consequences for soil C balance remain uncertain (Dijkstra et al., 2013; Liu et al., 2017).

Runoff in the United States is changing, and this study finds that the measured change is dependent on the geographic region and varies seasonally. Specifically, observed annual total runoff had an insignificant increasing trend in the US between 1950 and 2010, but this insignificance was due to regional heterogeneity with both significant and insignificant increases in the eastern, northern, and southern US, and a greater significant decrease in the western US. Trends for seasonal mean runoff also differed across regions. By region, the season with the largest observed trend was autumn for the east (positive), spring for the north (positive), winter for the south (positive), winter for the west (negative), and autumn for the US as a whole (positive). Based on the detection and attribution analysis using gridded WaterWatch runoff observations along with semi-factorial land surface model simulations from the Multi-scale Synthesis and Terrestrial Model Intercomparison Project (MsTMIP), we found that while the roles of CO 2 concentration, nitrogen deposition, and land use and land cover were inconsistent regionally and seasonally, the effect of climatic variations was detected for all regions and seasons, and the change in runoff could be attributed to climate change in summer and autumn in the south and in autumn in the west. We also found that the climate-only and historical transient simulations consistently underestimated the runoff trends, possibly due to precipitation bias in the MsTMIP driver or within the models themselves.

Despite the importance of nonstructural carbohydrates (NSC) for growth and survival in woody plants, we know little about whole-tree NSC storage. The conventional theory suggests that NSC reserves will increase over the growing season and decrease over the dormant season. Here, we compare storage in five temperate tree species to determine the size and seasonal fluctuation of whole-tree total NSC pools as well as the contribution of individual organs. NSC concentrations in the branches, stemwood, and roots of 24 trees were measured across 12 months. We then scaled up concentrations to the whole-tree and ecosystem levels using allometric equations and forest stand inventory data. While whole-tree total NSC pools followed the conventional theory, sugar pools peaked in the dormant season and starch pools in the growing season. Seasonal depletion of total NSCs was minimal at the whole-tree level, but substantial at the organ level, particularly in branches. Surprisingly, roots were not the major storage organ as branches stored comparable amounts of starch throughout the year, and root reserves were not used to support springtime growth. Scaling up NSC concentrations to the ecosystem level, we find that commonly used, process-based ecosystem and land surface models all overpredict NSC storage.

Plants store nonstructural carbohydrates (NSCs), such as sugars and starch, to use as carbon and energy sources for daily maintenance and growth needs as well as during times of stress. Allocation of NSCs to storage provides an important physiological strategy associated with future growth and survival, and thus understanding the seasonal patterns of NSC reserves provides insight into how species with different traits (e.g., growth form, leaf habit, wood anatomy) may respond to stress. We characterized the seasonal patterns of NSCs in four woody boreal plant species in Minnesota, USA. Sugar and starch concentrations were measured across the year in the roots and branches of two conifer trees, black spruce (Picea mariana (Mill.) B.S.P.) and eastern tamarack (Larix laricina (Du Roi) K. Koch), as well as in the leaves and branches of two evergreen broadleaf shrubs, bog Labrador tea (Rhododendron groenlandicum (Oeder) Kron & Judd) and leatherleaf (Chamaedaphne calyculata (L.) Moench). In general, seasonal variation was dominated by changes in starch across all organs and species. While similar seasonal patterns of NSCs were observed in the shrubs, different seasonal patterns were observed between the trees, particularly in the roots. Our results suggest that species-specific traits likely have consequences for organ-level storage dynamics, which may influence whole-plant growth and survival under global change.

Disruptions of natural flow impair rivers and streams worldwide. Those conducting restoration efforts have rarely explored how and when stream ecosystems can recover after reinstating natural flows. We quantified responses of ecosystem metabolism and N dynamics to the decommissioning and removal of a 100-y-old diversion dam in a desert stream, Fossil Creek, Arizona. Fossil Creek is a travertine river, meaning that CaCO3 concentrations in water in the springs that feed Fossil Creek are high enough to precipitate out of the water to form travertine terraces and deep pools. The majority of flow was diverted for power generation, so travertine deposition rates were significantly reduced and travertine terraces were smaller and less frequent compared to pre-dam historical records. Flow restoration enabled the recovery of the geochemical process of travertine deposition and increased gross primary production and N uptake to rates comparable to those measured in an upstream, reference reach. Reinstating a river’s natural flow regime can result in rapid and near-complete recovery of fundamental ecosystem processes that reshape the aquatic food web.

Rain-fed peatlands are dominated by peat mosses (Sphagnum sp.), which for their growth depend on nutrients, water and CO2 uptake from the atmosphere. As the isotopic composition of carbon (12,13C) and oxygen (16,18O) of these Sphagnum mosses are affected by environmental conditions, Sphagnum tissue accumulated in peat constitutes a potential long-term archive that can be used for climate reconstruction. However, there is inadequate understanding of how isotope values are influenced by environmental conditions, which restricts their current use as environmental and palaeoenvironmental indicators. Here we tested (i) to what extent C and O isotopic variation in living tissue of Sphagnum is species-specific and associated with local hydrological gradients, climatic gradients (evapotranspiration, temperature, precipitation) and elevation; (ii) whether the C isotopic signature can be a proxy for net primary productivity (NPP) of Sphagnum; and (iii) to what extent Sphagnum tissue δ18O tracks the δ18O isotope signature of precipitation. In total, we analysed 337 samples from 93 sites across North America and Eurasia using two important peat-forming Sphagnum species (S. magellanicum, S. fuscum) common to the Holarctic realm. There were differences in δ13C values between species. For S. magellanicum δ13C decreased with increasing height above the water table (HWT, R2 = 17%) and was positively correlated to productivity (R2 = 7%). Together these two variables explained 46% of the between-site variation in δ13C values. For S. fuscum, productivity was the only significant predictor of δ13C but had low explanatory power (total R2 = 6%). For δ18O values, approximately 90% of the variation was found between sites. Globally modelled annual δ18O values in precipitation explained 69% of the between-site variation in tissue δ18O. S. magellanicum showed lower δ18O enrichment than S. fuscum (−0.83‰ lower). Elevation and climatic variables were weak predictors of tissue δ18O values after controlling for δ18O values of the precipitation. To summarize, our study provides evidence for (a) good predictability of tissue δ18O values from modelled annual δ18O values in precipitation, and (b) the possibility of relating tissue δ13C values to HWT and NPP, but this appears to be species-dependent. These results suggest that isotope composition can be used on a large scale for climatic reconstructions but that such models should be species-specific.

Classical niche partitioning theory posits increased competition for and partitioning of the most limiting resource among coexisting species. Coexisting plant species may vary in rooting depth, reflecting niche partitioning in water source use. Our goal was to assess the soil water partitioning of woody plant communities across northern Arizona along an elevational moisture gradient using stem and soil water isotopes from two sampling periods to estimate the use of different water sources. We hypothesized that niche overlap of water sources would be higher and monsoon precipitation uptake would be lower at sites with higher moisture availability. Pairwise niche overlap of coexisting species was calculated using mixing model estimates of proportional water use for three sources. Across the moisture gradient, niche overlap increased with site moisture index (precipitation/potential evapotranspiration) across seasons, and site moisture index explained 37% of the variation in niche overlap of intermediate and deeper sources of water. Desert trees utilized more winter source water than desert shrubs, suggesting the partitioning of water sources between functional groups. However, seasonal differences in surface water use were primarily found at intermediate levels of site moisture availability. Our findings support classical niche partitioning theory in that plants exhibit higher overlap of water sources when water is not a limiting resource.

Accurate climate projections require an understanding of the effects of warming on ecological communities and the underlying mechanisms that drive them1–3. However, little is known about the effects of climate warming on the succession of microbial communities4,5. Here we examined the temporal succession of soil microbes in a long-term climate change experiment at a tall-grass prairie ecosystem. Experimental warming was found to significantly alter the community structure of bacteria and fungi. By determining the time-decay relationships and the paired differences of microbial communities under warming and ambient conditions, experimental warming was shown to lead to increasingly divergent succession of the soil microbial communities, with possibly higher impacts on fungi than bacteria. Variation partition- and null model-based analyses indicate that stochastic processes played larger roles than deterministic ones in explaining microbial community taxonomic and phylogenetic compositions. However, in warmed soils, the relative importance of stochastic processes decreased over time, indicating a potential deterministic environmental filtering elicited by warming. Although successional trajectories of microbial communities are difficult to predict under future climate change scenarios, their composition and structure are projected to be less variable due to warming-driven selection.

Recently, severe droughts that occurred in North America are likely to have impacted its terrestrial carbon sink. However, process-based understanding of how meteorological conditions prior to the onset of drought, for instance warm or cold springs, affect drought-induced carbon cycle effects remains scarce. Here we assess and compare the response of terrestrial carbon fluxes to summer droughts in 2011 and 2012 characterized by contrasting spring conditions. The analysis is based on a comprehensive ensemble of carbon cycle models, including FLUXCOM, TRENDY v5, SiBCASA, CarbonTracker Europe, and CarbonTracker, and emerging Earth observations. In 2011, large reductions of net ecosystem production (NEP; ?0.24 ± 0.17 Pg C/year) are due to decreased gross primary production (?0.17 ± 0.18 Pg C/year) and slightly increased ecosystem respiration (+0.07 ± 0.17 Pg C/year). Conversely, in 2012, NEP reductions (?0.17 ± 0.25 Pg C/year) are attributed to a larger increase of ecosystem respiration (+0.48 ± 0.27 Pg C/year) than gross primary production (+0.31 ± 0.29 Pg C/year), induced predominantly by an extra warmer spring prior to summer drought. Two temperate ecoregions crops/agriculture and the grass/shrubs contribute largest to these reductions and also dominate the interannual variations of NEP during 2007?2014. Moreover, the warming spring compensated largely the negative carbon anomaly due to summer drought, consistent with earlier studies; however, the compensation occurred only in some specific ecoregions. Overall, our analysis offers a refined view on recent carbon cycle variability and extremes in North America. It corroborates earlier results but also highlights differences with respect to ecoregion-specific carbon cycle responses to drought and heat.

Phenology is the study of recurring events in nature and their relationships with climate. The word derives from the Greek phaínō ‘appear’ and logos ‘reason’, emphasizing the focus on observing events and understanding why they occur (Demarée and Rutishauser 2009). Phenological recording has a history that dates back many centuries (Linneaus and Bark 1753; Aono and Kazui 2008). More recently, advances in monitoring technologies have enabled automated and remotely sensed observations, complemented by increasing citizen science participation in monitoring efforts. Phenological information can also be derived from widespread environmental monitoring stations around the globe. Phenological records clearly demonstrate the biological effects of year-to-year variability in climate, as well as longer-term trends associated with environmental change. Phenological monitoring thus plays an important role in understanding how our planet is changing. Changes in the growing season, for example, are more tangible and more readily conveyed to the general public than seemingly small changes in mean annual temperature. Here, we describe just a fraction of the phenological information currently available, highlighting northern hemisphere records of phenology of primary producers across a range of spatial and temporal scales.

The release of permafrost-derived nitrogen (N) has the potential to fertilize tundra vegetation, which in turn may stimulate productivity and thus offset carbon (C) losses from thawing permafrost. Below-ground plant traits may mediate ecosystem response to permafrost thaw and associated feedbacks to the atmosphere by differentially conferring access to deep, newly thawed permafrost N. Yet, identifying roots and quantifying root N uptake from deep, cold soils in complex plant communities has proved challenging to date. We investigated plant acquisition of experimentally added 15N isotope tracer applied at the permafrost boundary in graminoid- and shrub-dominated tundra at Eight Mile Lake, Alaska, when the thaw front was close to its maximum depth, simulating the release of newly thawed permafrost N. We used molecular tools to verify species and estimate biomass, nitrogen, and isotope pools. Root biomass depth distributions follow an asymptotic relationship with depth, typical of other ecosystems. Few species had roots occurring close to the thaw front. Rubus chamaemorus, a short-statured non-mycorrhizal forb, and Carex bigelowii, a sedge, consistently had the deepest roots. Twenty-four hours after isotope addition, we observed that deep-rooted, non-mycorrhizal species had the highest 15N enrichment values in their fine root tissue indicating that they access deep N late in the growing season when the thaw front is deepest. Deep-rooted plants are therefore able to immediately take up newly thawed permafrost-derived N. During the following growing season, herbaceous, non-mycorrhizal plants allocated tracer above-ground before woody, mycorrhizal plants. Ectomycorrhizal deciduous and ericoid mycorrhizal evergreen shrubs, by contrast, did not have immediate access to the deep N tracer and assimilated it into new foliar tissue gradually over the following growing season. Synthesis. Graminoids and forbs that have immediate access to deep N represent a modest C sink compared to C emissions from thawing permafrost. However, the effects of deep N fertilization on shrubs over longer time-scales may stimulate productivity and account for a more considerable N and C sink, thus constraining the permafrost C-climate feedback.

A significant fraction of the terrestrial biosphere comprises biomes containing tree–grass mixtures. Forecasting vegetation dynamics in these environments requires a thorough understanding of how trees and grasses use and compete for key belowground resources. There is disagreement about the extent to which tree–grass vertical root separation occurs in these ecosystems, how this overlap varies across large-scale environmental gradients, and what these rooting differences imply for water resource availability and tree–grass competition and coexistence. To assess the extent of tree–grass rooting overlap and how tree and grass rooting patterns vary across resource gradients, we examined landscape-level patterns of tree and grass functional rooting depth along a mean annual precipitation (MAP) gradient extending from ~ 450 to ~ 750 mm year−1 in Kruger National Park, South Africa. We used stable isotopes from soil and stem water to make inferences about relative differences in rooting depth between these two functional groups. We found clear differences in rooting depth between grasses and trees across the MAP gradient, with grasses generally exhibiting shallower rooting profiles than trees. We also found that trees tended to become more shallow-rooted as a function of MAP, to the point that trees and grasses largely overlapped in terms of rooting depth at the wettest sites. Our results reconcile previously conflicting evidence for rooting overlap in this system, and have important implications for understanding tree–grass dynamics under altered precipitation scenarios.

Mosses are critical components of boreal ecosystems where they typically account for a large proportion of net primary productivity and harbour diverse bacterial communities that can be the major source of biologically-fixed nitrogen in these ecosystems. Despite their ecological importance, we have limited understanding of how microbial communities vary across boreal moss species and the extent to which local site conditions may influence the composition of these bacterial communities. We used marker gene sequencing to analyze bacterial communities associated with seven boreal moss species collected near Fairbanks, AK, USA. We found that host identity was more important than site in determining bacterial community composition and that mosses harbour diverse lineages of potential N2-fixers as well as an abundance of novel taxa assigned to understudied bacterial phyla (including candidate phylum WPS-2). We performed shotgun metagenomic sequencing to assemble genomes from the WPS-2 candidate phylum and found that these moss-associated bacteria are likely anoxygenic phototrophs capable of carbon fixation via RuBisCo with an ability to utilize byproducts of photorespiration from hosts via a glyoxylate shunt. These results give new insights into the metabolic capabilities of understudied bacterial lineages that associate with mosses and the importance of plant hosts in shaping their microbiomes.

Climate is predicted to change over the 21st century. However, little is known about how climate change can affect soil phosphorus (P) cycle and availability in global terrestrial ecosystems, where P is a key limiting nutrient. With a global database of Hedley P fractions and key‐associated physiochemical properties of 760 (seminatural) natural soils compiled from 96 published studies, this study evaluated how climate pattern affected soil P cycle and availability in global terrestrial ecosystems. Overall, soil available P, indexed by Hedley labile inorganic P fraction, significantly decreased with increasing mean annual temperature (MAT) and precipitation (MAP). Hypothesis‐oriented path model analysis suggests that MAT negatively affected soil available P mainly by decreasing soil organic P and primary mineral P and increasing soil sand content. MAP negatively affected soil available P both directly and indirectly through decreasing soil primary mineral P; however, these negative effects were offset by the positive effects of MAP on soil organic P and fine soil particles, resulting in a relatively minor total MAP effect on soil available P. As aridity degree was mainly determined by MAP, aridity also had a relatively minor total effect on soil available P. These global patterns generally hold true irrespective of soil depth (less than or equal to 10 cm or greater than 10 cm) or site aridity index (less than or equal to 1.0 or greater than 1.0), and were also true for the low‐sand (less than or equal to 50%) soils. In contrast, available P of the high‐sand (greater than 50%) soils was positively affected by MAT and aridity and negatively affected by MAP. Our results suggest that temperature and precipitation have contrasting effects on soil P availability and can interact with soil particle size to control soil P availability.

The annual peak growth of vegetation is critical in characterizing the capacity of terrestrial ecosystem productivity and shaping the seasonality of atmospheric CO2 concentrations. The recent greening of global lands suggests an increasing trend of terrestrial vegetation growth, but whether or not the peak growth has been globally enhanced still remains unclear. Here, we use two global datasets of gross primary productivity (GPP) and a satellite-derived Normalized Difference Vegetation Index (NDVI) to characterize recent changes in annual peak vegetation growth (that is, GPPmax and NDVImax). We demonstrate that the peak in the growth of global vegetation has been linearly increasing during the past three decades. About 65% of the NDVImax variation is evenly explained by expanding croplands (21%), rising CO2 (22%) and intensifying nitrogen deposition (22%). The contribution of expanding croplands to the peak growth trend is substantiated by measurements from eddy-flux towers, sun-induced chlorophyll fluorescence and a global database of plant traits, all of which demonstrate that croplands have a higher photosynthetic capacity than other vegetation types. The large contribution of CO2 is also supported by a meta-analysis of 466 manipulative experiments and 15 terrestrial biosphere models. Furthermore, we show that the contribution of GPPmax to the change in annual GPP is less in the tropics than in other regions. These multiple lines of evidence reveal an increasing trend in the peak growth of global vegetation. The findings highlight the important roles of agricultural intensification and atmospheric changes in reshaping the seasonality of global vegetation growth.

The terrestrial carbon (C) cycle has been commonly represented by a series of C balance equations to track C influxes into and effluxes out of individual pools in earth system models (ESMs). This representation matches our understanding of C cycle processes well but makes it difficult to track model behaviors. It is also computationally expensive, limiting the ability to conduct comprehensive parametric sensitivity analyses. To overcome these challenges, we have developed a matrix approach, which reorganizes the C balance equations in the original ESM into one matrix equation without changing any modeled C cycle processes and mechanisms. We applied the matrix approach to the Community Land Model (CLM4.5) with vertically‐resolved biogeochemistry. The matrix equation exactly reproduces litter and soil organic carbon (SOC) dynamics of the standard CLM4.5 across different spatial‐temporal scales. The matrix approach enables effective diagnosis of system properties such as C residence time and attribution of global change impacts to relevant processes. We illustrated, for example, the impacts of CO2 fertilization on litter and SOC dynamics can be easily decomposed into the relative contributions from C input, allocation of external C into different C pools, nitrogen regulation, altered soil environmental conditions, and vertical mixing along the soil profile. In addition, the matrix tool can accelerate model spin‐up, permit thorough parametric sensitivity tests, enable pool‐based data assimilation, and facilitate tracking and benchmarking of model behaviors. Overall, the matrix approach can make a broad range of future modeling activities more efficient and effective.

Abstract Phenology is a first-order control on productivity and mediates the biophysical environment by altering albedo, surface roughness length and evapotranspiration. Accurate and transparent modelling of vegetation phenology is therefore key in understanding feedbacks between the biosphere and the climate system. Here, we present the PHENOR R package and modelling framework. The framework leverages measurements of vegetation phenology from four common phenology observation datasets, the PhenoCam network, the USA National Phenology Network (USA-NPN), the Pan European Phenology Project (PEP725), MODIS phenology (MCD12Q2) combined with (global) retrospective and projected climate data. We show an example analysis, using the phenor modelling framework, which quickly and easily compares 20 included spring phenology models for three plant functional types. An analysis of model skill using the root mean squared (RMSE) error shows little or no difference regardless of model structure, corroborating previous studies. We argue that addressing this issue will require novel model development combined with easy data assimilation as facilitated by our framework. In conclusion, we hope the phenor phenology modelling framework in the r language and environment for statistical computing will facilitate reproducibility and community driven phenology model development, in order to increase their overall predictive power, and leverage an ever growing number of phenology data products.

Dominant canopy tree species have strong effects on the composition and function of understory species, particularly bryophytes. In boreal forests, bryophytes and their associated microbes are a primary source of ecosystem nitrogen (N) inputs, and an important process regulating ecosystem productivity. We investigated how feather moss-associated N₂-fixation rates and contribution to N budgets vary in time and space among coniferous and broadleaf deciduous forests. We measured N₂-fixation rates using stable isotope (¹⁵N₂) labeling in two moss species (<em class="EmphasisTypeItalic ">Pleurozium schreberi</em> and <em class="EmphasisTypeItalic ">Hylocomium splendens</em>) in broadleaf deciduous (Alaska paper birch—<em class="EmphasisTypeItalic ">Betula neoalaskana</em>) and coniferous (black spruce—<em class="EmphasisTypeItalic ">Picea mariana</em>) stands near Fairbanks, interior Alaska, from 2013 to 2015. N₂-fixation rates showed substantial inter-annual variation among the 3 years. High N₂-fixation was more strongly associated with high precipitation than air temperature or light availability. Overall, contribution of N₂-fixation to N budgets was greater in spruce than in birch stands. Our results enhance the knowledge of the processes that drive N₂-fixation in boreal forests, which is important for predicting ecosystem consequences of changing forest composition.

The contemporary Arctic carbon balance is uncertain, and the potential for a permafrost carbon feedback of anywhere from 50 to 200 petagrams of carbon (Schuur et al., 2015) compromises accurate 21st-century global climate system projections. The 42-year record of atmospheric CO2 measurements at Barrow, Alaska (71.29 N, 156.79 W), reveals significant trends in regional land-surface CO2 anomalies (ΔCO2), indicating long-term changes in seasonal carbon uptake and respiration. Using a carbon balance model constrained by ΔCO2, we find a 13.4% decrease in mean carbon residence time (50% confidence range = 9.2 to 17.6%) in North Slope tundra ecosystems during the past four decades, suggesting a transition toward a boreal carbon cycling regime. Temperature dependencies of respiration and carbon uptake suggest that increases in cold season Arctic labile carbon release will likely continue to exceed increases in net growing season carbon uptake under continued warming trends.

The ability to forecast ecological carbon cycling is imperative to land management in a world where past carbon fluxes are no longer a clear guide in the Anthropocene. However, carbon‐flux forecasting has not been practiced routinely like numerical weather prediction. This study explored (1) the relative contributions of model forcing data and parameters to uncertainty in forecasting flux‐ versus pool‐based carbon cycle variables and (2) the time points when temperature and CO2 treatments may cause statistically detectable differences in those variables. We developed an online forecasting workflow (Ecological Platform for Assimilation of Data (EcoPAD)), which facilitates iterative data‐model integration. EcoPAD automates data transfer from sensor networks, data assimilation, and ecological forecasting. We used the Spruce and Peatland Responses Under Changing Experiments data collected from 2011 to 2014 to constrain the parameters in the Terrestrial Ecosystem Model, forecast carbon cycle responses to elevated CO2 and a gradient of warming from 2015 to 2024, and specify uncertainties in the model output. Our results showed that data assimilation substantially reduces forecasting uncertainties. Interestingly, we found that the stochasticity of future external forcing contributed more to the uncertainty of forecasting future dynamics of C flux‐related variables than model parameters. However, the parameter uncertainty primarily contributes to the uncertainty in forecasting C pool‐related response variables. Given the uncertainties in forecasting carbon fluxes and pools, our analysis showed that statistically different responses of fast‐turnover pools to various CO2 and warming treatments were observed sooner than slow‐turnover pools. Our study has identified the sources of uncertainties in model prediction and thus leads to improve ecological carbon cycling forecasts in the future.

In deciduous forests, spring leaf phenology controls the onset of numerous ecosystem functions. While most studies have focused on a single annual spring event, such as budburst, ecosystem functions like photosynthesis and transpiration increase gradually after budburst, as leaves grow to their mature size. Here, we examine the “velocity of green-up,” or duration between budburst and leaf maturity, in deciduous forest ecosystems of eastern North America. We use a diverse data set that includes 301 site-years of phenocam data across a range of sites, as well as 22 years of direct ground observations of individual trees and 3 years of fine-scale high-frequency aerial photography, both from Harvard Forest. We find a significant association between later start of spring and faster green-up: − 0.47 ± 0.04 (slope ± 1 SE) days change in length of green-up for every day later start of spring within phenocam sites, − 0.31 ± 0.06 days/day for trees under direct observation, and − 1.61 ± 0.08 days/day spatially across fine-scale landscape units. To explore the climatic drivers of spring leaf development, we fit degree-day models to the observational data from Harvard Forest. We find that the default phenology parameters of the ecosystem model PnET make biased predictions of leaf initiation (39 days early) and maturity (13 days late) for red oak, while the optimized model has biases of 1 day or less. Springtime productivity predictions using optimized parameters are closer to results driven by observational data (within 1%) than those of the default parameterization (17% difference). Our study advances empirical understanding of the link between early and late spring phenophases and demonstrates that accurately modeling these transitions is important for simulating seasonal variation in ecosystem productivity.

Forest phenology is a multi-scale phenomenon, arising from processes in leaves and trees, with effects on the ecology of plant communities and landscapes. Because phenology controls carbon and water cycles, which are commonly observed at the ecosystem scale (e.g. eddy flux measurements), it is important to characterize the relation between phenophase transition events at different spatial scales. We use aerial photography recorded from an unmanned aerial vehicle (UAV) to observe plant phenology over a large area (5.4 ha) and across diverse communities, with spatial and temporal resolution at the scale of individual tree crowns and their phenophase transition events (10 m spatial resolution, ∼5 day temporal resolution in spring, weekly in autumn). We validate UAV-derived phenophase transition dates through comparison with direct observations of tree phenology, PhenoCam image analysis, and satellite remote sensing. We then examine the biological correlates of spatial variance in phenology using a detailed species inventory and land cover classification. Our results show that species distribution is the dominant factor in spatial variability of ecosystem phenology. We also explore statistical relations governing the scaling of phenology from an organismic scale (10 m) to forested landscapes (1 km) by analyzing UAV photography alongside Landsat and MODIS data. From this analysis we find that spatial standard deviation in transition dates decreases linearly with the logarithm of increasing pixel size. We also find that fine-scale phenology aggregates to a coarser scale as the median and not the mean date in autumn, indicating coarser scale phenology is less sensitive to the tails of the distribution of sub-pixel transitions in the study area. Our study is the first to observe forest phenology in a spatially comprehensive, whole-ecosystem way, yet with fine enough spatial resolution to describe organism-level correlates and scaling phenomena.

Understanding how population-level dynamics contribute to ecosystem-level processes is a primary focus of ecological research and has led to important breakthroughs in the ecology of macroscopic organisms. However, the inability to measure population-specific rates, such as growth, for microbial taxa within natural assemblages has limited ecologists’ understanding of how microbial populations interact to regulate ecosystem processes. Here, we use isotope incorporation within DNA molecules to model taxon-specific population growth in the presence of 18O-labeled water. By applying this model to phylogenetic marker sequencing data collected from stable-isotope probing studies, we estimate rates of growth, mortality, and turnover for individual microbial populations within soil assemblages. When summed across the entire bacterial community, our taxon-specific estimates are within the range of other whole-assemblage measurements of bacterial turnover. Because it can be applied to environmental samples, the approach we present is broadly applicable to measuring population growth, mortality, and associated biogeochemical process rates of microbial taxa for a wide range of ecosystems and can help reveal how individual microbial populations drive biogeochemical fluxes.

Snow is important for local to global climate and surface hydrology, but spatial and temporal heterogeneity in the extent of snow cover make accurate, fine-scale mapping and monitoring of snow an enormous challenge. We took 184,453 daily near-surface images acquired by 133 automated cameras and processed them using crowdsourcing and deep learning to determine whether snow was present or absent in each image. We found that the crowdsourced data had an accuracy of 99.1% when compared with expert evaluation of the same imagery. We then used the image classification to train a deep convolutional neural network via transfer learning, with accuracies of 92% to 98%, depending on the image set and training method. The majority of neural network errors were due to snow that was present not being detected. We used the results of the neural networks to validate the presence or absence of snow inferred from the MODIS satellite sensor and obtained similar results to those from other validation studies. This method of using automated sensors, crowdsourcing, and deep learning in combination produced an accurate high temporal dataset of snow presence across a continent. It holds broad potential for real-time large-scale acquisition and processing of ecological and environmental data in support of monitoring, management, and research objectives.

Non-structural carbohydrates (NSCs), the stored products of photosynthesis, building blocks for growth and fuel for respiration, are central to plant metabolism, but their measurement is challenging. Differences in methods and procedures among laboratories can cause results to vary widely, limiting our ability to integrate and generalize patterns in plant carbon balance among studies. A recent assessment found that NSC concentrations measured for a common set of samples can vary by an order of magnitude, but sources for this variability were unclear. We measured a common set of nine plant material types, and two synthetic samples with known NSC concentrations, using a common protocol for sugar extraction and starch digestion, and three different sugar quantification methods (ion chromatography, enzyme, acid) in six laboratories. We also tested how sample handling, extraction solvent and centralizing parts of the procedure in one laboratory affected results. Non-structural carbohydrate concentrations measured for synthetic samples were within about 11.5% of known values for all three methods. However, differences among quantification methods were the largest source of variation in NSC measurements for natural plant samples because the three methods quantify different NSCs. The enzyme method quantified only glucose, fructose and sucrose, with ion chromatography we additionally quantified galactose, while the acid method quantified a large range of mono- and oligosaccharides. For some natural samples, sugars quantified with the acid method were two to five times higher than with other methods, demonstrating that trees allocate carbon to a range of sugar molecules. Sample handling had little effect on measurements, while ethanol sugar extraction improved accuracy over water extraction. Our results demonstrate that reasonable accuracy of NSC measurements can be achieved when different methods are used, as long as protocols are robust and standardized. Thus, we provide detailed protocols for the extraction, digestion and quantification of NSCs in plant samples, which should improve the comparability of NSC measurements among laboratories.

Clouds and aerosols increase the fraction of global solar irradiance that is diffuse light. This phenomenon is known to increase the photosynthetic light use efficiency (LUE) of closed-canopy vegetation by redistributing photosynthetic photon flux density (400–700 nm) from saturated, sunlit leaves at the top of the canopy, to shaded leaves deeper in the canopy. We combined a process-based carbon cycle model with 10 years of eddy covariance carbon flux measurements and other ancillary data sets to assess 1) how this LUE enhancement influences interannual variation in carbon uptake, and 2) how errors in modeling diffuse fraction affect predictions of carbon uptake. Modeled annual gross primary productivity (GPP) increased by ≈0.94% when observed levels of diffuse fraction were increased by 0.01 (holding total irradiance constant). The sensitivity of GPP to increases in diffuse fraction was highest when the diffuse fraction was low to begin with, and lowest when the diffuse fraction was already high. Diffuse fraction also explained significantly more of the interannual variability of modeled net ecosystem exchange (NEE), than did total irradiance. Two tested radiation partitioning models yielded over- and underestimates of diffuse fraction at our site, which propagated to over- and underestimates of annual NEE, respectively. Our findings highlight the importance of incorporating LUE enhancement under diffuse light into models of global primary production, and improving models of diffuse fraction.

Recent evidences show that terrestrial biogeochemical models have large uncertainty in estimating climate-change effect on grassland net ecosystem productivity (NEP), which is defined as the difference between gross ecosystem photosynthesis (GEP) and respiration (ER). It remains unclear that whether GEP or ER limits the model capability to simulate NEP responses to climate change in semiarid grasslands. Given the surrogate CENTURY-type model is widely used for Earth system modeling, we investigated two of them (i.e., DAYCENT and TECO models) and examined which processes dominate their ability to capture the responses of NEP to experimental climate changes in a temperate steppe of northern China. During the simulation from 2006 to 2008, the two models captured the observed mean annual NEP in the control plots when they were validated by the observations from an adjacent eddy-flux tower. However, they failed to capture the treatment effects of experimental warming and increased precipitation on NEP because of the poor estimations of ER responses. DAYCENT model simulated a higher precipitation effect on ER (37.83%) and TECO model overestimated the warming effect on ER by 8.18%. The simulation of treatment effects on ER and therefore NEP can be improved by an optimized parameterization of the water-related decay functions for soil organic carbon (C). The simulated cumulative loss of total ecosystem C stock during 2010–2100 were decreased when the TECO model used experiment-fitted parameters (0.72 kg C m−2) instead of using the initial validation with eddy-flux data (0.96 kg C m−2). The ecosystem shifted from C sink to source at threshold of 435 mm of annual total precipitation. Our findings indicate that future projection of C cycle in semiarid grasslands could be improved by better understanding of water response of ecosystem respiratory processes.

Remote sensing of radiative indices must balance spatially and temporally coarse satellite measurements with finer-scale, but geographically limited, in-situ surface measurements. Instruments mounted upon an Unmanned Aerial Vehicle (UAV) can provide small-scale, mobile remote measurements that fill this resolution gap. Here we present and validate a novel method of obtaining albedo values using an unmodified quadcopter at a deciduous northern hardwood forest. We validate this method by comparing simultaneous albedo estimates by UAV and a fixed tower at the same site. We found that UAV provided stable albedo measurements across multiple flights, with results that were well within the range of tower-estimated albedo at similar forested sites. Our results indicate that in-situ albedo measurements (tower and UAV) capture more site-to-site variation in albedo than satellite measurements. Overall, we show that UAVs produce reliable, consistent albedo measurements that can capture crucial surface heterogeneity, clearly distinguishing between different land uses. Future application of this approach can provide detailed measurements of albedo and potentially other vegetation indices to enhance global research and modeling efforts.

The concentration–carbon feedback (β), also called the CO2 fertilization effect, is a key unknown in climate–carbon-cycle projections. A better understanding of model mechanisms that govern terrestrial ecosystem responses to elevated CO2 is urgently needed to enable a more accurate prediction of future terrestrial carbon sink. We conducted C-only, carbon–nitrogen (C–N) and carbon–nitrogen–phosphorus (C–N–P) simulations of the Community Atmosphere Biosphere Land Exchange model (CABLE) from 1901 to 2100 with fixed climate to identify the most critical model process that causes divergence in β. We calculated CO2 fertilization effects at various hierarchical levels from leaf biochemical reaction and leaf photosynthesis to canopy gross primary production (GPP), net primary production (NPP), and ecosystem carbon storage (cpool) for seven C3 plant functional types (PFTs) in response to increasing CO2 under the RCP 8.5 scenario. Our results show that β values at biochemical and leaf photosynthesis levels vary little across the seven PFTs, but greatly diverge at canopy and ecosystem levels in all simulations. The low variation of the leaf-level β is consistent with a theoretical analysis that leaf photosynthetic sensitivity to increasing CO2 concentration is almost an invariant function. In the CABLE model, the major jump in variation of β values from leaf levels to canopy and ecosystem levels results from divergence in modeled leaf area index (LAI) within and among PFTs. The correlation of βGPP, βNPP, or βcpool each with βLAI is very high in all simulations. Overall, our results indicate that modeled LAI is a key factor causing the divergence in β in the CABLE model. It is therefore urgent to constrain processes that regulate LAI dynamics in order to better represent the response of ecosystem productivity to increasing CO2 in Earth system models.

Soil respiration (RS), which is the second largest carbon flux between the atmosphere and terrestrial ecosystems, has significant impact on atmospheric CO2 concentration and climatic dynamics. Nitrogen (N) fertilizer has been heavily applied in agroecosystems at the global scale for high crop yields, and plays a major role in regulating RS. Although the respective response of soil biochemical property and RS to N addition has been widely studied, the contributions of soil biochemical parameters especially in the rhizosphere to changes in RS and its components (soil heterotrophic (RH) and autotrophic (RA) respiration) under N application remain poorly understood. The present study aimed to examine whether the rhizosphere effect alters the relationship between soil biochemical properties and RS under N addition in croplands.

Climate warming can result in both abiotic (e.g., permafrost thaw) and biotic (e.g., microbial functional genes) changes in Arctic tundra. Recent research has incorporated dynamic permafrost thaw in Earth system models (ESMs) and indicates that Arctic tundra could be a significant future carbon (C) source due to the enhanced decomposition of thawed deep soil C. However, warming‐induced biotic changes may influence biologically related parameters and the consequent projections in ESMs. How model parameters associated with biotic responses will change under warming and to what extent these changes affect projected C budgets have not been carefully examined. In this study, we synthesized six data sets over 5 years from a soil warming experiment at the Eight Mile Lake, Alaska, into the Terrestrial ECOsystem (TECO) model with a probabilistic inversion approach. The TECO model used multiple soil layers to track dynamics of thawed soil under different treatments. Our results show that warming increased light use efficiency of vegetation photosynthesis but decreased baseline (i.e., environment‐corrected) turnover rates of SOC in both the fast and slow pools in comparison with those under control. Moreover, the parameter changes generally amplified over time, suggesting processes of gradual physiological acclimation and functional gene shifts of both plants and microbes. The TECO model predicted that field warming from 2009 to 2013 resulted in cumulative C losses of 224 or 87 g/m², respectively, without or with changes in those parameters. Thus, warming‐induced parameter changes reduced predicted soil C loss by 61%. Our study suggests that it is critical to incorporate biotic changes in ESMs to improve the model performance in predicting C dynamics in permafrost regions.

Increases in carbon (C) inputs to soil can replenish soil organic C (SOC) through various mechanisms. However, recent studies have suggested that the increased C input can also stimulate the decomposition of old SOC via priming. Whether the loss of old SOC by priming can override C replenishment has not been rigorously examined. Here we show, through data–model synthesis, that the magnitude of replenishment is greater than that of priming, resulting in a net increase in SOC by a mean of 32% of the added new C. The magnitude of the net increase in SOC is positively correlated with the nitrogen-to-C ratio of the added substrates. Additionally, model evaluation indicates that a two-pool interactive model is a parsimonious model to represent the SOC decomposition with priming and replenishment. Our findings suggest that increasing C input to soils likely promote SOC accumulation despite the enhanced decomposition of old C via priming.

Boreal forests are changing in response to climate, with potentially important feedbacks to regional and global climate through altered carbon cycle and albedo dynamics. These feedback processes will be affected by vegetation changes, and feedback strengths will largely rely on the spatial extent and timing of vegetation change. Satellite remote sensing is widely used to monitor vegetation dynamics, and vegetation indices (VIs) are frequently used to characterize spatial and temporal trends in vegetation productivity. In this study we combine field observations of larch forest cover across a 25 km2 upland landscape in northeastern Siberia with high-resolution satellite observations to determine how the Normalized Difference Vegetation Index (NDVI) and the Enhanced Vegetation Index (EVI) are related to forest cover. Across 46 forest stands ranging from 0% to 90% larch canopy cover, we find either no change, or declines in NDVI and EVI derived from PlanetScope CubeSat and Landsat data with increasing forest cover. In conjunction with field observations of NDVI, these results indicate that understory vegetation likely exerts a strong influence on vegetation indices in these ecosystems. This suggests that positive decadal trends in NDVI in Siberian larch forests may correspond primarily to increases in understory productivity, or even to declines in forest cover. Consequently, positive NDVI trends may be associated with declines in terrestrial carbon storage and increases in albedo, rather than increases in carbon storage and decreases in albedo that are commonly assumed. Moreover, it is also likely that important ecological changes such as large changes in forest density or variable forest regrowth after fire are not captured by long-term NDVI trends.

Elevated atmospheric N deposition threatens ecosystem health through eutrophication in terrestrial ecosystems, but little is known about consequences of N deposition in N-rich tropical ecosystems. We added several levels of N to an N-rich tropical forest and monitored plant growth dynamics, forest nutrient status, plant water use, and water losses from the ecosystem for a decade. We found that plants can acclimate and maintain nutrient balance by altering hydrological cycling. These results demonstrate that while elevated N deposition to already N-rich tropical forests may have minor effects on forest growth, it can exert a detectable influence on hydrological dynamics. Reduced runoff may threaten water supply in rapidly developing tropical regions.Anthropogenic nitrogen (N) deposition has accelerated terrestrial N cycling at regional and global scales, causing nutrient imbalance in many natural and seminatural ecosystems. How added N affects ecosystems where N is already abundant, and how plants acclimate to chronic N deposition in such circumstances, remains poorly understood. Here, we conducted an experiment employing a decade of N additions to examine ecosystem responses and plant acclimation to added N in an N-rich tropical forest. We found that N additions accelerated soil acidification and reduced biologically available cations (especially Ca and Mg) in soils, but plants maintained foliar nutrient supply at least in part by increasing transpiration while decreasing soil water leaching below the rooting zone. We suggest a hypothesis that cation-deficient plants can adjust to elevated N deposition by increasing transpiration and thereby maintaining nutrient balance. This result suggests that long-term elevated N deposition can alter hydrological cycling in N-rich forest ecosystems.

Ecosystem carbon (C) transit time is a critical diagnostic parameter to characterize land C sequestration. This parameter has different variants in the literature, including a commonly used turnover time. However, we know little about how different transit time and turnover time are in representing carbon cycling through multiple compartments under a non-steady state. In this study, we estimate both C turnover time as defined by the conventional stock over flux and mean C transit time as defined by the mean age of C mass leaving the system. We incorporate them into the Community Atmosphere Biosphere Land Exchange (CABLE) model to estimate C turnover time and transit time in response to climate warming and rising atmospheric [CO₂]. Modelling analysis shows that both C turnover time and transit time increase with climate warming but decrease with rising atmospheric [CO₂]. Warming increases C turnover time by 2.4 years and transit time by 11.8 years in 2100 relative to that at steady state in 1901. During the same period, rising atmospheric [CO₂] decreases C turnover time by 3.8 years and transit time by 5.5 years. Our analysis shows that 65% of the increase in global mean C transit time with climate warming results from the depletion of fast-turnover C pool. The remaining 35% increase results from accompanied changes in compartment C age structures. Similarly, the decrease in mean C transit time with rising atmospheric [CO₂] results approximately equally from replenishment of C into fast-turnover C pool and subsequent decrease in compartment C age structure. Greatly different from the transit time, the turnover time, which does not account for changes in either C age structure or composition of respired C, underestimated impacts of warming and rising atmospheric [CO₂] on C diagnostic time and potentially led to deviations in estimating land C sequestration in multi-compartmental ecosystems.

Tree-grass ecosystems are widely distributed. However, their phenology has not yet been fully characterized. The technique of repeated digital photographs for plant phenology monitoring (hereafter referred as PhenoCam) provide opportunities for long-term monitoring of plant phenology, and extracting phenological transition dates (PTDs, e.g., start of the growing season). Here, we aim to evaluate the utility of near-infrared-enabled PhenoCam for monitoring the phenology of structure (i.e., greenness) and physiology (i.e., gross primary productivity-GPP) at four tree-grass Mediterranean sites. We computed four vegetation indexes (VIs) from PhenoCams: (1) green chromatic coordinates (GCC), (2) normalized difference vegetation index (CamNDVI), (3) near-infrared reflectance of vegetation index (CamNIRv), and (4) ratio vegetation index (CamRVI). GPP is derived from eddy covariance flux tower measurement. Then, we extracted PTDs and their uncertainty from different VIs and GPP. The consistency between structural (VIs) and physiological (GPP) phenology was then evaluated. CamNIRv is best at representing the PTDs of GPP during the Green-up period, while CamNDVI is best during the Dry-down period. Moreover, CamNIRv outperforms the other VIs in tracking growing season length of GPP. In summary, the results show it is promising to track structural and physiology phenology of seasonally dry Mediterranean ecosystem using near-infrared-enabled PhenoCam. We suggest using multiple VIs to better represent the variation of GPP.

Soil contains the largest terrestrial pool of carbon (C), but how this pool will be affected by global change remains unknown. Warmer temperatures generally increase soil respiration, while additional C inputs from plants to soil can increase or decrease soil C decomposition rates through a phenomenon known as priming. Priming occurs when soil organic matter (SOM) decomposition rates change in response to a fresh substrate, though the mechanisms underlying priming are poorly understood. Here, we measured priming in four ecosystems during a seven-week incubation with weekly glucose additions. Soil was collected from field warming experiments in the four ecosystems, so our experiment assessed the influence of long-term warming on priming. All treatments exhibited negative priming (reduced SOM decomposition) after the first substrate pulse. Subsequent substrate pulses elicited variable responses, and the effect of long-term warming on priming was ecosystem-dependent. Priming was correlated with changes in soil C and N in response to warming: ecosystems that lost soil C and N over nine years of experimental warming exhibited low rates of priming (decreased SOM decomposition), while ecosystems that gained soil C and N in response to warming had high priming. Consequently, priming may accelerate C losses in ecosystems that exhibit warming-induced C increases, and vice versa, thus partially buffering soil C content against change.

High latitude warming and permafrost thaw will expose vast stores of deep soil organic carbon (SOC) to decomposition. Thaw also changes water movement causing either wetter or drier soil. The fate of deep SOC under different thaw and moisture conditions is unclear. We measured weekly growing-season δ13C of ecosystem respiration (Recoδ13C) across thaw and moisture conditions (Shallow-Dry; Deep-Dry; Deep-Wet) in a soil warming manipulation. Deep SOC loss was inferred from known δ13C signatures of plant shoot, root, surface soil, and deep soil respiration. In addition, a 2-year-old vegetation removal treatment (No Veg) was used to isolate surface and deep SOC decomposition contributions to Reco. In No Veg, seasonal Recoδ13C indicated that deep SOC loss increased as the soil column thawed, while in vegetated areas, root contributions appeared to dominate Reco. The Recoδ13C differences between Shallow-Dry and Deep-Dry were significant but surprisingly small. This most likely suggests that, under dry conditions, soil warming stimulates root and surface SOC respiration with a negative 13C signature that opposes the more positive 13C signal from increased deep SOC respiration. In Deep-Wet conditions, Recoδ13C suggests reduced deep SOC loss but could also reflect altered diffusion or methane (CH4) dynamics. Together, these results demonstrate that frequent Recoδ13C measurements can detect deep SOC loss and that plants confound the signal. In future studies, soil profile δ13C measurements, vegetation removal across thaw gradients, and isotopic effects of CH4 dynamics could further deconvolute deep SOC loss via surface Reco.

We conducted a model-based assessment of changes in permafrost area and carbon storage for simulations driven by RCP4.5 and RCP8.5 projections between 2010 and 2299 for the northern permafrost region. All models simulating carbon represented soil with depth, a critical structural feature needed to represent the permafrost carbon–climate feedback, but that is not a universal feature of all climate models. Between 2010 and 2299, simulations indicated losses of permafrost between 3 and 5 million km^2 for the RCP4.5 climate and between 6 and 16 million km^2 for the RCP8.5 climate. For the RCP4.5 projection, cumulative change in soil carbon varied between 66-Pg C (10^15-g carbon) loss to 70-Pg C gain. For the RCP8.5 projection, losses in soil carbon varied between 74 and 652 Pg C (mean loss, 341 Pg C). For the RCP4.5 projection, gains in vegetation carbon were largely responsible for the overall projected net gains in ecosystem carbon by 2299 (8- to 244-Pg C gains). In contrast, for the RCP8.5 projection, gains in vegetation carbon were not great enough to compensate for the losses of carbon projected by four of the five models; changes in ecosystem carbon ranged from a 641-Pg C loss to a 167-Pg C gain (mean, 208-Pg C loss). The models indicate that substantial net losses of ecosystem carbon would not occur until after 2100. This assessment suggests that effective mitigation efforts during the remainder of this century could attenuate the negative consequences of the permafrost carbon–climate feedback.

Increasing wildfire activity in Alaska’s boreal forests has led to greater fuel reduction management. Management has been implemented to reduce wildfire spread, but the ecological impacts of these practices are poorly known. We quantified the effects of handthinning and shearblading on above- and belowground stand characteristics, plant species composition, carbon (C) and nitrogen (N) pools, and soil thaw across 19 sites dominated by black spruce (Picea mariana) in interior Alaska treated 2–12 years prior to sampling. The density of deciduous tree seedlings was significantly higher in shearbladed areas compared to unmanaged forest (6.4 vs. 0.1 stems/m2), and unmanaged stands exhibited the highest mean density of conifer seedlings and layers (1.4 stems/m2). Understory plant community composition was most similar between unmanaged and thinned stands. Shearblading resulted in a near complete loss of aboveground tree biomass C pools while thinning approximately halved the C pool size (1.2 kg C/m2 compared to 3.1 kg C/m2 in unmanaged forest). Significantly smaller soil organic layer (SOL) C and N pools were observed in shearbladed stands (3.2 kg C/m2 and 116.8 g N/m2) relative to thinned (6.0 kg C/m2 and 192.2 g N/m2) and unmanaged (5.9 kg C/m2 and 178.7 g N/m2) stands. No difference in C and N pool sizes in the uppermost 10 cm of mineral soil was observed among stand types. Total C stocks for measured pools was 2.6 kg C/m2 smaller in thinned stands and 5.8 kg C/m2 smaller in shearbladed stands when compared to unmanaged forest. Soil thaw depth averaged 13 cm deeper in thinned areas and 46 cm deeper in shearbladed areas relative to adjacent unmanaged stands, although variability was high across sites. Deeper soil thaw was linked to shallower SOL depth for unmanaged stands and both management types, however for any given SOL depth, thaw tended to be deeper in shearbladed areas compared to unmanaged forest. These findings indicate that fuel-reduction management alters plant community composition, C and N pools, and soil thaw depth, with consequences for ecosystem structure and function beyond those intended for fire management.

Nitrogen (N) is frequently a limiting nutrient in soil; its availability can govern ecosystem functions such as primary production and decomposition. Assimilation of N by microorganisms impacts the availability of N in soil. Despite its established ecological significance, the contributions of microbial taxa to N assimilation are unknown. Here we measure N uptake and use by microbial phylotypes and taxonomic groups within a diverse assemblage of soil microbes through quantitative stable isotope probing (qSIP) with 15N. Following incubation with 15NH+4, distinct patterns of 15N assimilation among taxonomic groups were observed. For instance, glucose addition stimulated 15N assimilation in most members of Actinobacteria and Proteobacteria but generally decreased 15N use by Firmicutes and Bacteriodetes. While NH+4 is considered a preferred and universal source of N to prokaryotes, the majority (Greater than 80%) of N assimilation in our soils could be attributed to a handful of active orders. Characterizing N assimilation of taxonomic groups with 15N qSIP may provide a basis for understanding how microbial community composition influences N availability in the environment.

Functional traits, which usually develop over evolutionary time‐scales to maximize plant survivorship and functional performances in changing environment, are important indices to explore how ecosystems respond and adapt to a changing environment. Many ecologists have argued that identifying regional to global‐scale patterns in functional traits, at organismal to ecosystem scales, in combination with responses to environmental changes, is necessary to increase our ability to predict how ecosystems will function in the future (Katja &amp; Jeanfrançois, 2009; Reich, Walters, &amp; Ellsworth, 1997; Wright et al., 2017). Global models that have been used to simulate changes in ecosystem function primarily incorporate biogeochemical and ecophysiological processes (Bonan, 2008; Taylor, Stouffer, &amp; Meehl, 2012). These models, however, could not well predict community compositional change (Fisher et al., 2017). Traditionally, plant functional types have been used to represent community composition changes in dynamic global vegetation models (DGVM). That scheme remains poor at predicting ecosystem functions and their responses to climatic change (Sitch et al., 2008). Recently, trait‐based modelling has emerged as one of the most promising approach to simulation of community dynamics under global changes (Markus, Michael, Mahecha, Jens, &amp; Baldocchi, 2014; van Bodegom, Douma, &amp; Verheijen, 2014; Van Bodegom et al., 2012; Violle, Reich, Pacala, Enquist, &amp; Kattge, 2014). To support this trait‐based modelling, it is urgent to compile empirical evidence, develop comprehensive datasets, and reveal the large‐scale patterns and controlling factors of functional traits and their variations along environmental gradients.

1. Dryland vegetation is characterized by discrete plant patches that accumulate and capture soil resources under their canopies. These “fertile islands” are major drivers of dryland ecosystem structure and functioning, yet we lack an integrated understanding of the factors controlling their magnitude and variability at the global scale. 2. We conducted a standardized field survey across 236 drylands from five continents. At each site, we measured the composition, diversity and cover of perennial plants. Fertile island effects were estimated at each site by comparing composite soil samples obtained under the canopy of the dominant plants and in open areas devoid of perennial vegetation. For each sample, we measured 15 soil variables (functions) associated with carbon, nitrogen and phosphorus cycling and used the relative interaction index to quantify the magnitude of the fertile island effect for each function. In 80 sites, we also measured fungal and bacterial abundance (quantitative PCR) and diversity (Illumina MiSeq). 3. The most fertile islands, i.e. those where a higher number of functions were simultaneously enhanced, were found at lower elevation sites with greater soil pH values and sand content under semiarid climates, particularly at locations where the presence of tall woody species with a low‐specific leaf area increased fungal abundance beneath plant canopies, the main direct biotic controller of the fertile island effect in the drylands studied. Positive effects of fungal abundance were particularly associated with greater nutrient contents and microbial activity (soil extracellular enzymes) under plant canopies. 4. Synthesis. Our results show that the formation of fertile islands in global drylands largely depends on: (1) local climatic, topographic and edaphic characteristics, (2) the structure and traits of local plant communities and (3) soil microbial communities. Our study also has broad implications for the management and restoration of dryland ecosystems worldwide, where woody plants are commonly used as nurse plants to enhance the establishment and survival of beneficiary species. Finally, our results suggest that forecasted increases in aridity may enhance the formation of fertile islands in drylands worldwide.

Growing bacteria have a high concentration of ribosomes to ensure sufficient protein synthesis, which is necessary for genome replication and cellular division. To elucidate whether metabolic activity of soil microorganisms is coupled with growth, we investigated the relationship between rRNA and DNA synthesis in a soil bacterial community using quantitative stable isotope probing (qSIP) with H2 18O. Most soil bacterial taxa were metabolically active and grew, and there was no significant difference between the isotopic composition of DNA and RNA extracted from soil incubated with H2 18O. The positive correlation between 18O content of DNA and rRNA of taxa, with a slope statistically indistinguishable from 1 (slope = 0.96; 95% confidence interval [CI], 0.90 to 1.02), indicated that few taxa made new rRNA without synthesizing new DNA. There was no correlation between rRNA-to-DNA ratios obtained from sequencing libraries and the atom percent excess (APE) 18O values of DNA or rRNA, suggesting that the ratio of rRNA to DNA is a poor indicator of microbial growth or rRNA synthesis. Our results support the notion that metabolic activity is strongly coupled to cellular division and suggest that nondividing taxa do not dominate soil metabolic activity. IMPORTANCE Using quantitative stable isotope probing of microbial RNA and DNA with H2 18O, we show that most soil taxa are metabolically active and grow because their nucleic acids are significantly labeled with 18O. A majority of the populations that make new rRNA also grow, which argues against the common paradigm that most soil taxa are dormant. Additionally, our results indicate that relative sequence abundance-based RNA-to-DNA ratios, which are frequently used for identifying active microbial populations in the environment, underestimate the number of metabolically active taxa within soil microbial communities.

Most soil bacterial taxa are thought to be dormant, or inactive, yet the extent to which they synthetize new rRNA is poorly understood. We analyzed 18O composition of RNA extracted from soil incubated with H218O and used quantitative stable isotope probing to characterize rRNA synthesis among microbial taxa. RNA was not fully labeled with 18O, peaking at a mean of 23.6 ± 6.8 atom percent excess (APE) 18O after eight days of incubation, suggesting some ribonucleotides in soil were more than eight days old. Microbial taxa varied in the degree they incorporated 18O into their rRNA over time and there was no correlation between the APE 18O of bacterial rRNA and their rRNA to DNA ratios, suggesting that the ratios were not appropriate to measure ribonucleotide synthesis. Our study indicates that, on average, 94% of soil taxa produced new rRNA and therefore were metabolically active.

Higher temperatures in northern latitudes will increase permafrost thaw and stimulate above-and belowground plant biomass growth in tundra ecosystems. Higher plant productivity increases the input of easily decomposable carbon (C) to soil, which can stimulate microbial activity and increase soil organic matter decomposition rates. This phenomenon, known as the priming effect, is particularly interesting in permafrost because an increase in C supply to deep, previously frozen soil may accelerate decomposition of C stored for hundreds to thousands of years. The sensitivity of old permafrost C to priming is not well known; most incubation studies last less than one year, and so focus on fast-cycling C pools. Furthermore, the age of respired soil C is rarely measured, even though old C may be vulnerable to labile C inputs. We incubated soil from a moist acidic tundra site in Eight Mile Lake, Alaska for 409 days at 15 °C. Soil from surface (0–25 cm), transition (45–55 cm), and permafrost (65–85 cm) layers were amended with three pulses of uniformly 13C labeled glucose or cellulose, every 152 days. Glucose addition resulted in positive priming in the permafrost layer 7 days after each substrate addition, eliciting a two-fold increase in cumulative soil C loss relative to unamended soils with consistent effects across all three pulses. In the transition and permafrost layers, glucose addition significantly decreased the age of soil-respired CO2C with Δ14C values that were 115‰ higher. Previous field studies that measured the age of respired C in permafrost regions have attributed younger Δ14C ecosystem respiration values to higher plant contributions. However, the results from this study suggest that positive priming, due to an increase in fresh C supply to deeply thawed soil layers, can also explain the respiration of younger C observed at the ecosystem scale. We must consider priming effects to fully understand permafrost C dynamics, or we risk underestimating the contribution of soil C to ecosystem respiration.

Drylands (hyperarid, arid, semiarid, and dry subhumid ecosystems) cover almost half of Earth’s land surface and are highly vulnerable to environmental pressures. Here we provide an inventory of soil properties including carbon (C), nitrogen (N), and phosphorus (P) stocks within the current boundaries of drylands, aimed at serving as a benchmark in the face of future challenges including increased population, food security, desertification, and climate change. Aridity limits plant production and results in poorly developed soils, with coarse texture, low C:N and C:P, scarce organic matter, and high vulnerability to erosion. Dryland soils store 646 Pg of organic C to 2 m, the equivalent of 32% of the global soil organic C pool. The magnitude of the historic loss of C from dryland soils due to human land use and cover change and their typically low C:N and C:P suggest high potential to build up soil organic matter, but coarse soil textures may limit protection and stabilization processes. Restoring, preserving, and increasing soil organic matter in drylands may help slow down rising levels of atmospheric carbon dioxide by sequestering C, and is strongly needed to enhance food security and reduce the risk of land degradation and desertification.

Improved quantification of the factors controlling soil organic matter (SOM) stabilization at continental to global scales is needed to inform projections of the largest actively cycling terrestrial carbon pool on Earth, and its response to environmental change. Biogeochemical models rely almost exclusively on clay content to modify rates of SOM turnover and fluxes of climate-active CO2 to the atmosphere. Emerging conceptual understanding, however, suggests other soil physicochemical properties may predict SOM stabilization better than clay content. We addressed this discrepancy by synthesizing data from over 5,500 soil profiles spanning continental scale environmental gradients. Here, we demonstrate that other physicochemical parameters are much stronger predictors of SOM content, with clay content having relatively little explanatory power. We show that exchangeable calcium strongly predicted SOM content in water-limited, alkaline soils, whereas with increasing moisture availability and acidity, iron- and aluminum-oxyhydroxides emerged as better predictors, demonstrating that the relative importance of SOM stabilization mechanisms scales with climate and acidity. These results highlight the urgent need to modify biogeochemical models to better reflect the role of soil physicochemical properties in SOM cycling.

Global change is shifting the seasonality of vegetation in ecosystems around the globe. High-frequency digital camera imagery, and vegetation indices derived from that imagery, is facilitating better tracking of phenological responses to environmental variation. This method, commonly referred to as the “phenocam” approach, is well-suited to several specific applications, including: close-up observation of individual organisms; long-term canopy-level monitoring at individual sites; automated regional-to-continental scale observatory networks; and tracking responses to experimental treatments. Several camera networks are already well-established, and some camera records are a more than a decade long. These data can be used to identify the environmental controls on phenology in different ecosystems, which will contribute to the development of improved prognostic phenology models. This article is protected by copyright. All rights reserved.

Vegetation phenology controls the seasonality of many ecosystem processes, as well as numerous biosphere-atmosphere feedbacks. Phenology is also highly sensitive to climate change and variability. Here we present a series of datasets, together consisting of almost 750 years of observations, characterizing vegetation phenology in diverse ecosystems across North America. Our data are derived from conventional, visible-wavelength, automated digital camera imagery collected through the PhenoCam network. For each archived image, we extracted RGB (red, green, blue) colour channel information, with means and other statistics calculated across a region-of-interest (ROI) delineating a specific vegetation type. From the high-frequency (typically, 30 min) imagery, we derived time series characterizing vegetation colour, including “canopy greenness”, processed to 1- and 3-day intervals. For ecosystems with one or more annual cycles of vegetation activity, we provide estimates, with uncertainties, for the start of the “greenness rising” and end of the “greenness falling” stages. The database can be used for phenological model validation and development, evaluation of satellite remote sensing data products, benchmarking earth system models, and studies of climate change impacts on terrestrial ecosystems.

Shifts in vegetation phenology are a key example of the biological effects of climate change. However, there is substantial uncertainty about whether these temperature-driven trends will continue, or whether other factors—for example, photoperiod—will become more important as warming exceeds the bounds of historical variability. Here we use phenological transition dates derived from digital repeat photography to show that experimental whole-ecosystem warming treatments of up to +9 °C linearly correlate with a delayed autumn green-down and advanced spring green-up of the dominant woody species in a boreal <i>Picea</i>–<i>Sphagnum</i> bog. Results were confirmed by direct observation of both vegetative and reproductive phenology of these and other bog plant species, and by multiple years of observations. There was little evidence that the observed responses were constrained by photoperiod. Our results indicate a likely extension of the period of vegetation activity by 1–2 weeks under a ‘CO₂ stabilization’ climate scenario (+2.6 ± 0.7 °C), and 3–6 weeks under a ‘high-CO₂ emission’ scenario (+5.9 ± 1.1 °C), by the end of the twenty-first century. We also observed severe tissue mortality in the warmest enclosures after a severe spring frost event. Failure to cue to photoperiod resulted in precocious green-up and a premature loss of frost hardiness, which suggests that vulnerability to spring frost damage will increase in a warmer world. Vegetation strategies that have evolved to balance tradeoffs associated with phenological temperature tracking may be optimal under historical climates, but these strategies may not be optimized for future climate regimes. These in situ experimental results are of particular importance because boreal forests have both a circumpolar distribution and a key role in the global carbon cycle.

Phenology is a valuable diagnostic of ecosystem health, and has applications to environmental monitoring and management. Here, we conduct an intercomparison analysis using phenological transition dates derived from near-surface PhenoCam imagery and MODIS satellite remote sensing. We used approximately 600 site-years of data, from 128 camera sites covering a wide range of vegetation types and climate zones. During both “greenness rising” and “greenness falling” transition phases, we found generally good agreement between PhenoCam and MODIS transition dates for agricultural, deciduous forest, and grassland sites, provided that the vegetation in the camera field of view was representative of the broader landscape. The correlation between PhenoCam and MODIS transition dates was poor for evergreen forest sites. We discuss potential reasons (including sub-pixel spatial heterogeneity, flexibility of the transition date extraction method, vegetation index sensitivity in evergreen systems, and PhenoCam geolocation uncertainty) for varying agreement between time series of vegetation indices derived from PhenoCam and MODIS imagery. This analysis increases our confidence in the ability of satellite remote sensing to accurately characterize seasonal dynamics in a range of ecosystems, and provides a basis for interpreting those dynamics in the context of tangible phenological changes occurring on the ground.

Mechanical cutting and mastication of juniper trees aims to restore grassland habitat by reducing the density of encroaching woody species. However, the associated soil disturbance may also create conduits for invasive species, a risk that must be mitigated by land managers. We characterized herbaceous communities in treated and adjacent untreated areas in a piñon-juniper (Pinus edulis and Juniper monosperma) woodland in northern Arizona 2.5 years after treatment. Untreated plots had 4× the herbaceous cover (82%) than treated plots (21%). Within treated plots, native species cover (19%) was 10× higher than invasive species cover (2%). Furthermore, treated plots exhibited greater plant community variability and diversity than untreated plots, driven by an increase in the diversity of native grasses and non-native forbs. No new recruits were Arizona listed noxious weeds, indicating that, at least in the short term, mastication is not producing invasive species hot spots in this piñon-juniper woodland.

Heat waves are increasing in frequency and intensity, presenting a challenge for the already difficult practice of ecological restoration. We investigated whether pre-heating locally sourced rhizosphere soil (inoculum) could acclimatize plants to a field-imposed heat wave in a restoration setting. Soil heating in the laboratory caused a marked shift in rhizosphere bacterial community composition, accompanied by an increase in species evenness. Furthermore, pre-heated rhizosphere soil reduced plant height, number of leaves, and shoot mass of the C4 grass, blue grama (Bouteloua gracilis), and it reduced the shoot mass of the C3 grass, Arizona fescue (Festuca arizonica) in the glasshouse. Following transplantation and the application of a field heat wave, pre-heated inoculum did not influence heat wave survival for either plant species. However, there were strong species-level responses to the field heat wave. For instance, heat wave survivorship was over four times higher in blue grama (92%) than in Arizona fescue (22%). These results suggest that the use of C4 seeds may be preferable for sites exhibiting high heat wave risk. Further research is needed to understand whether inocula are more effective in highly degraded soil in comparison with partially degraded soils.

The flux of CO₂ from the soil to the atmosphere (soil respiration, <i>R</i>_soil) is a major component of the global carbon (C) cycle. Methods to measure and model <i>R</i>_soil, or partition it into different components, often rely on the assumption that soil CO₂ concentrations and fluxes are in steady state, implying that <i>R</i>_soil is equal to the rate at which CO₂ is produced by soil microbial and root respiration. Recent research, however, questions the validity of this assumption. Thus, the aim of this work was two-fold: (1) to describe a non-steady state (NSS) soil CO₂ transport and production model, DETECT, and (2) to use this model to evaluate the environmental conditions under which <i>R</i>_soiland CO₂ production are likely in NSS. The backbone of DETECT is a non-homogeneous, partial differential equation (PDE) that describes production and transport of soil CO₂, which we solve numerically at fine spatial and temporal resolution (e.g., 0.01m increments down to 1m, every 6h). Production of soil CO₂ is simulated for every depth and time increment as the sum of root respiration and microbial decomposition of soil organic matter. Both of these factors can be driven by current and antecedent soil water content and temperature, which can also vary by time and depth. We also analytically solved the ordinary differential equation (ODE) corresponding to the steady-state (SS) solution to the PDE model. We applied the DETECT NSS and SS models to the six-month growing season period representative of a native grassland in Wyoming. Simulation experiments were conducted with both model versions to evaluate factors that could affect departure from SS, such as (1) varying soil texture; (2) shifting the timing or frequency of precipitation; and (3) with and without the environmental antecedent drivers. For a coarse-textured soil, <i>R</i>_soil from the SS model closely matched that of the NSS model. However, in a fine-textured (clay) soil, growing season <i>R</i>_soil was  ∼ 3% higher under the assumption of NSS (versus SS). These differences were exaggerated in clay soil at daily time scales whereby <i>R</i>_soil under the SS assumption deviated from NSS by up to 35% on average in the 10 days following a major precipitation event. Incorporation of antecedent drivers increased the magnitude of <i>R</i>_soil by 15 to 37% for coarse- and fine-textured soils, respectively. However, the responses of <i>R</i>_soil to the timing of precipitation and antecedent drivers did not differ between SS and NSS assumptions. In summary, the assumption of SS conditions can be violated depending on soil type and soil moisture status, as affected by precipitation inputs. The DETECT model provides a framework for accommodating NSS conditions to better predict <i>R</i>_soil and associated soil carbon cycling processes.

1.Dams disrupt the river continuum, altering hydrology, biodiversity and energy flow. Although research indicates that tributary inputs have the potential to dilute these effects, knowledge at the food‐web level is still scarce. 2.Here, we examined the riverine food‐web structure of the Colorado River below Glen Canyon Dam, focusing on organic matter sources, trophic diversity and food chain length. We asked how these components respond to pulsed flows from tributaries following monsoon thunderstorms that seasonally increase streamflow in the American Southwest. 3.Tributaries increased the relative importance of terrestrial organic matter, particularly during the wet season below junctures of key tributaries. This contrasted with the algal‐based food‐web present immediately below Glen Canyon Dam. 4.Tributary inputs during the monsoon also increased trophic diversity and food chain length: food chain length peaked below the confluence with the largest tributary (by discharge) in Grand Canyon, increasing by greater than 1 trophic level over a 4–5 km reach possibly due to aquatic prey being flushed into the mainstem during heavy rain events. 5.Our results illustrate that large tributaries can create seasonal discontinuities, influencing riverine food‐web structure in terms of allochthony, food‐web diversity and food chain length. 6.Synthesis and applications. Pulsed flows from unregulated tributaries following seasonal monsoon rains increase the importance of terrestrially derived organic matter in large, regulated river food webs, increasing food chain length and trophic diversity downstream of tributary inputs. Protecting unregulated tributaries within hydropower cascades may be important if we are to mitigate food‐web structure alteration due to flow regulation by large dams. This is critical in the light of global hydropower development, especially in megadiverse, developing countries where dam placement (including completed and planned structures) is in tributaries.

Losses of C from decomposing permafrost may be offset by increased productivity of tundra plants, but nitrogen availability partially limits plant growth in tundra ecosystems. In this soil incubation experiment carbon (C) and nitrogen (N) cycling dynamics were examined from the soil surface down through upper permafrost. We found that losses of CO2 were negatively correlated to net N mineralization because C-rich surface soils mineralized little N, while deep soils had low rates of C respiration but high rates of net N mineralization. Permafrost soils released a large flush of inorganic N when initially thawed. Depth-specific rates of N mineralization from the incubation were combined with thaw depths and soil temperatures from a nearby manipulative warming experiment to simulate the potential magnitude, timing, and depth of inorganic N release during the process of permafrost thaw. Our calculations show that inorganic N released from newly thawed permafrost may be similar in magnitude to the increase in N mineralized by warmed soils in the middle of the profile. The total release of inorganic N from the soil profile during the simulated thaw process was twice the size of the observed increase in the foliar N pool observed at the manipulative experiment. Our findings suggest that increases in N availability are likely to outpace the N demand of tundra plants during the first 5 years of permafrost thaw and may increase C losses from surface soils as well as induce denitrification and leaching of N from these ecosystems.

Inferences about subsurface CO2 fluxes often rely on surface soil respiration (Rsoil) estimates because directly measuring subsurface microbial and root respiration (collectively, CO2 production, STotal) is difficult. To evaluate how well Rsoil serves as a proxy for STotal, we applied the nonsteady state DEconvolution of Temporally varying Ecosystem Carbon componenTs model (0.01-m vertical resolution), using 6-hourly data from a Wyoming grassland, in six simulations that cross three soil types (clay, sandy loam, and sandy) with two depth distributions of subsurface biota. We used cross-wavelet coherence analysis to examine temporal coherence (localized linear correlation) and offsets (lags) between STotal and Rsoil and fluxes and drivers (e.g., soil temperature and moisture). Cross-wavelet coherence revealed higher coherence between fluxes and drivers than linear regressions between concurrent variables. Soil texture and moisture exerted the strongest controls over coherence between CO2 fluxes. Coherence between CO2 fluxes in all soil types was strong at short (~1 day) and long periods (&gt;8 days), but soil type controlled lags, and rainfall events decoupled the fluxes at periods of 1?8 days for several days in sandy soil, up to 1 week in sandy loam, and for a month or more in clay soil. Concentrating root and microbial biomass nearer the surface decreased lags in all soil types and increased coherence up to 10% in clay soil. The assumption of high temporal coherence between Rsoil and STotal is likely valid in dry, sandy soil, but may lead to underestimates of short-term STotal in semiarid grasslands with fine-grained and/or wet soil.

In the last few decades, temperatures in the Arctic have increased twice as much as the rest of the globe. As permafrost thaws in response to this warming, large amounts of soil organic matter may become vulnerable to decomposition. Microbial decomposition will release carbon (C) from permafrost soils, however, warmer conditions could also lead to enhanced plant growth and C uptake. Field and modeling studies show high uncertainty in soil and plant responses to climate change but there have been few studies that reconcile field and model data to understand differences and reduce uncertainty. Here, we evaluate gross primary productivity (GPP), ecosystem respiration (R eco ), and net ecosystem C exchange (NEE) from eight years of experimental soil warming in moist acidic tundra against equivalent fluxes from the Community Land Model during simulations parameterized to reflect the field conditions associated with this manipulative field experiment. Over the eight-year experimental period, soil temperatures and thaw depths increased with warming in field observations and model simulations. However, the field and model results do not agree on warming effects on water table depth; warming created wetter soils in the field and drier soils in the models. In the field, initial increases in growing season GPP, R eco , and NEE to experimentally-induced permafrost thaw created a higher C sink capacity in the first years followed by a stronger C source in years six through eight. In contrast, both models predicted linear increases in GPP, R eco , and NEE with warming. The divergence of model results from field experiments reveals the role subsidence, hydrology, and nutrient cycling play in influencing the C flux responses to permafrost thaw, a complexity that the models are not structurally able to predict, and highlight challenges associated with projecting C cycle dynamics across the Arctic.

Differences in the biogeochemistry of nitrogen (N) and phosphorus (P) lead to differential losses and inputs during and over time after fire such that fire may affect nutrient limitation of primary productivity. We conducted a nutrient addition experiment in scrubby flatwoods, a Florida scrub community type, to test the hypothesis that nutrient limitation of primary productivity shifts from N limitation in recently burned sites to P limitation in longer unburned sites. We added three levels of N, P, and N and P together to sites 6 weeks, 8 years, and 20 years postfire and assessed the effects of nutrient addition on above- and belowground productivity and nutrient concentrations. At the community level, nutrient addition did not affect aboveground biomass, but root productivity increased with high N + P addition in sites 8 and 20 years after fire. At the species level, N addition increased leaf biomass of saw palmetto (Serenoa repens) in sites 6 weeks and 20 years postfire, while P addition increased foliar %P and apical shoot growth of scrub oak (Quercus inopina) in sites 8 and 20 years postfire, respectively. Contrary to our hypothesis, nutrient limitation does not appear to shift with time after fire; recently burned sites show little evidence of nutrient limitation, while increased belowground productivity indicates that scrubby flatwoods are co-limited by N and P at intermediate and longer times after fire.

The Arctic may seem remote, but the unprecedented environmental changes occurring there have important consequences for global society. Of all Arctic system components, changes in permafrost (perennially frozen ground) are one of the least documented. Permafrost is degrading as a result of climate warming, and evidence is mounting that changing permafrost will have significant impacts within and outside the region. This review asks: What are key structural and functional properties of ecosystems that interact with changing permafrost, and how do these ecosystem changes affect local and global society? Here, we look beyond the classic definition of permafrost to include a broadened focus on the composition of frozen ground, including the ice and the soil organic carbon content, and how it is changing. This ecological perspective of permafrost serves to identify areas of both vulnerability and resilience as climate, ecological disturbance regimes, and the human footprint all continue to change in this sensitive and critical region of Earth.

Large model uncertainty in projected future soil carbon (C) dynamics has been well documented. However, our understanding of the sources of this uncertainty is limited. Here we quantify the uncertainties arising from model parameters, structures and their interactions, and how those uncertainties propagate through different models to projections of future soil carbon stocks. Both the vertically resolved model and the microbial explicit model project much greater uncertainties to climate change than the conventional soil C model, with both positive and negative C-climate feedbacks, whereas the conventional model consistently predicts positive soil C-climate feedback. Our findings suggest that diverse model structures are necessary to increase confidence in soil C projection. However, the larger uncertainty in the complex models also suggests that we need to strike a balance between model complexity and the need to include diverse model structures in order to forecast soil C dynamics with high confidence and low uncertainty.

Succession theory predicts altered sensitivity of ecosystem functions to disturbance (i.e., climate change) due to the temporal shift in plant community composition. However, empirical evidence in global change experiments is lacking to support this prediction. Here, we present findings from an 8-year long-term global change experiment with warming and altered precipitation manipulation (double and halved amount). First, we observed a temporal shift in species composition over 8 years, resulting in a transition from an annual C3-dominant plant community to a perennial C4-dominant plant community. This successional transition was independent of any experimental treatments. During the successional transition, the response of aboveground net primary productivity (ANPP) to precipitation addition magnified from neutral to +45.3%, while the response to halved precipitation attenuated substantially from ?17.6% to neutral. However, warming did not affect ANPP in either state. The findings further reveal that the time-dependent climate sensitivity may be regulated by successional change in species composition, highlighting the importance of vegetation dynamics in regulating the response of ecosystem productivity to precipitation change.

Understanding what drives the interannual variability (IAV) of the land carbon sink is crucial for improving future predictions of this important, yet uncertain, component of the climate system. While drivers of global and hemispheric-scale net ecosystem exchange (NEE) IAV have been investigated, our understanding of the drivers of NEE IAV at regional scales (e.g. sub-continental, biome-level) is quite poor. Here we explore the biome-level attribution and drivers of North American NEE using inverse estimates derived from a dense network of atmospheric CO 2 observations. We find that deciduous broadleaf and mixed forests are the primary regions responsible for North American NEE IAV, which differs from the ecoregions identified for the globe and Northern Hemisphere. We also find that a suite of terrestrial biosphere models (TBMs) do not agree on the dominant biome contributing to NEE IAV, with TBMs falling along an apparent spectrum ranging between those with IAV dominated primarily by forested ecosystems to those with IAV dominated by non-forested ecosystems. Furthermore, this regional trade-off in TBM NEE IAV is found to be linked to differing regional responses to environmental drivers among TBMs. This work displays the importance of extra-tropical forests in driving continental NEE IAV and also highlights the challenges and limitations of using TBMs to inform regional-scale carbon flux dynamics.

Ecologists often equate litter quality with decomposition rate. In soil and sediments, litter that is rapidly decomposed by microbes often has low concentrations of tannin and lignin and low C:N ratios. Do these same traits also favor element transfer to higher trophic levels in streams, where many insects depend on litter as their primary food source? We test the hypothesis that slow decomposition rates promote element transfer from litter to insects, whereas rapid decomposition favors microbes. We measured carbon and nitrogen fluxes from four plant species to a leaf-shredding caddisfly using isotopically labeled litter. Caddisflies assimilated a higher percentage of litter carbon and nitrogen lost from slowly decomposing litters (Platanus wrightii and Quercus gambelii). In contrast, rapidly decomposing litters (Fraxinus velutina and Populus fremontii) supported higher microbial biomass. These results challenge the view that rapidly decomposing litter is higher quality by demonstrating that slowly decomposing litters provide a critical resource for insects.

Insect outbreaks can significantly influence carbon (C) and water balances of forests. Forest tent caterpillars (FTC) (Malacosoma disstria Hübner) are one of the most prominent insects found in aspen forests in Canada and have the potential to considerably influence regional C and water fluxes. In the summer of 2016, an FTC infestation occurred in a ca. 100 -year-old trembling aspen (Populus tremuloides) stand in the southern boreal forest where the longterm research site known as Old Aspen (OA) is located. The infestation led to nearly complete defoliation of the canopy during the leafing out period when photosynthesis, and thus C uptake, is progressing towards maximum levels. We used 21 years of eddy-covariance (EC) and climate measurements covering pre-infestation and infestation periods to estimate the impact of the FTC infestation on net ecosystem production (NEP), gross ecosystem production (GEP) and evapotranspiration (E). Defoliation in 2016 reduced annual NEP to −130 g C m−2 y−1 and GEP to 798 g C m−2 y−1, respectively, which were much less than their 20-year means (NEP = 118 ± 53 g C m−2 y−1, GEP = 1057 ± 74 g C m−2 y−1), and resulted in the most negative annual NEP value of the 21 years of measurements at the OA site. NEP for 2016 was even lower than values observed during three drought years (2001–2003). However, FTC infestation caused little effect on annual E. FTC infestation reduced the near-surface remotely-measured greenness index, green chromatic coordinate (GCC), to ∼0.32 on June 10 in comparison to ∼0.40 in other years. The defoliation, observable from space as reductions in normalized difference vegetation index (NDVI) values, also showed a negligible effect on E but a large effect on the C fluxes.

Soils contain more carbon than plants or the atmosphere, and sensitivities of soil organic carbon (SOC) stocks to changing climate and plant productivity are a major uncertainty in global carbon cycle projections. Despite a consensus that microbial degradation and mineral stabilization processes control SOC cycling, no systematic synthesis of long-term warming and litter addition experiments has been used to test process-based microbe-mineral SOC models. We explored SOC responses to warming and increased carbon inputs using a synthesis of 147 field manipulation experiments and five SOC models with different representations of microbial and mineral processes. Model projections diverged but encompassed a similar range of variability as the experimental results. Experimental measurements were insufficient to eliminate or validate individual model outcomes. While all models projected that CO2 efflux would increase and SOC stocks would decline under warming, nearly one-third of experiments observed decreases in CO2 flux and nearly half of experiments observed increases in SOC stocks under warming. Long-term measurements of C inputs to soil and their changes under warming are needed to reconcile modeled and observed patterns. Measurements separating the responses of mineral-protected and unprotected SOC fractions in manipulation experiments are needed to address key uncertainties in microbial degradation and mineral stabilization mechanisms. Integrating models with experimental design will allow targeting of these uncertainties and help to reconcile divergence among models to produce more confident projections of SOC responses to global changes.

Greenhouse gas emissions from thawing permafrost in arctic ecosystems may amplify global warming, yet estimates of the rate of carbon release, and the proportion of carbon released as methane (CH4) or carbon dioxide (CO2), have a high degree of uncertainty. There are many areas where no measurements exist, and few year-round or long-term records. Existing year-round eddy covariance measurements of arctic CH4 fluxes suggest that nongrowing season emissions make up a significant proportion of tundra systems emissions on an annual basis. Here we present continuous CH4 flux measurements made at Eight Mile Lake, an upland tundra ecosystem undergoing permafrost degradation in Interior Alaska. We found net CH4 emissions throughout the year (1.2 ? 0.011 g C-CH4 m2/yr) that made up 61% of total radiative forcing from annual C emissions (CO2 and CH4; 32.3 g C m2/yr) when taking into account the greenhouse warming potential of CH4 relative to CO2. Nongrowing season emissions accounted for 50% of the annual CH4 budget, characterized by large pulse emissions. These were related to abrupt increases in air and shallow soil temperatures rather than consistent emissions during the zero curtain?a period of the fall/early winter season when subsurface soil temperatures remain near the 0 °C freezing point. Weekly growing season CH4 emissions in 2016 and 2017 were significantly related with thaw depth, and the magnitude of CH4 emissions between these seasons was proportional to the rate of active layer thaw throughout the season.

Land ecosystems sequester on average about a quarter of anthropogenic CO2 emissions. It has been proposed that nitrogen (N) availability will exert an increasingly limiting effect on plants’ ability to store additional carbon (C) under rising CO2, but these mechanisms are not well understood. Here, we review findings from elevated CO2 experiments using a plant economics framework, highlighting how ecosystem responses to elevated CO@ may depend on the costs and benefits of plant interactions with mycorrhizal fungi and symbiotic N‐fixing microbes. We found that N‐acquisition efficiency is positively correlated with leaf‐level photosynthetic capacity and plant growth, and negatively with soil C storage. Plants that associate with ectomycorrhizal fungi and N‐fixers may acquire N at a lower cost than plants associated with arbuscular mycorrhizal fungi. However, the additional growth in ectomycorrhizal plants is partly offset by decreases in soil C pools via priming. Collectively, our results indicate that predictive models aimed at quantifying C cycle feedbacks to global change may be improved by treating N as a resource that can be acquired by plants in exchange for energy, with different costs depending on plant interactions with microbial symbionts.

At the global scale, the uptake of atmospheric carbon dioxide by terrestrial ecosystems through photosynthesis is commonly estimated through vegetation indices or biophysical properties derived from optical remote sensing data. Microwave observations of vegetated areas are sensitive to different components of the vegetation layer than observations in the optical domain and may therefore provide complementary information on the vegetation state, which may be used in the estimation of Gross Primary Production (GPP). However, the relation between GPP and Vegetation Optical Depth (VOD), a biophysical quantity derived from microwave observations, is not yet known. This study aims to explore the relationship between VOD and GPP. VOD data were taken from different frequencies (L-, C-, and X-band) and from both active and passive microwave sensors, including the Advanced Scatterometer (ASCAT), the Soil Moisture Ocean Salinity (SMOS) mission, the Advanced Microwave Scanning Radiometer for Earth Observation System (AMSR-E) and a merged VOD data set from various passive microwave sensors. VOD data were compared against FLUXCOM GPP and Solar-Induced chlorophyll Fluorescence (SIF) from the Global Ozone Monitoring Experiment-2 (GOME-2). FLUXCOM GPP estimates are based on the upscaling of flux tower GPP observations using optical satellite data, while SIF observations present a measure of photosynthetic activity and are often used as a proxy for GPP. For relating VOD to GPP, three variables were analyzed: original VOD time series, temporal changes in VOD (ΔVOD), and positive changes in VOD (ΔVOD≥0). Results show widespread positive correlations between VOD and GPP with some negative correlations mainly occurring in dry and wet regions for active and passive VOD, respectively. Correlations between VOD and GPP were similar or higher than between VOD and SIF. When comparing the three variables for relating VOD to GPP, correlations with GPP were higher for the original VOD time series than for ΔVOD or ΔVOD≥0 in case of sparsely to moderately vegetated areas and evergreen forests, while the opposite was true for deciduous forests. Results suggest that original VOD time series should be used jointly with changes in VOD for the estimation of GPP across biomes, which may further benefit from combining active and passive VOD data.

Long-term, continuous digital camera imagery and tower-based radiometric monitoring were conducted at a representative hardwood forest site in the Northeastern United States, part of the AmeriFlux network. In this study, the phenological metrics of the leaf area index (LAI), plant area index (PAI) and associated transition dates (e.g., timing of the onset of leaf expansion and the cessation of leaf fall) were compared using 4-year of data from Bartlett Experimental Forest. We used digital repeat photography (DRP) imagery collected using two different methods (“canopy cover” and “phenocam” approaches), together with above- and below-canopy measurements of photosynthetically active radiation (PAR). The growth-period LAI estimated from canopy cover images (LAICANOPY) and the above and below canopy PAR measurements (LAIfPARt) were within approximately the same range, in term of magnitude, as previous results for multiple comparative methods, although growing-season LAICANOPY was slightly lower (3.11 m2 m−2 to 3.35 m2 m−2) than LAIfPARt (3.19 m2 m−2 to 3.67 m2 m−2). In addition, we derived phenological transition dates from PAICANOPY, PAIfPARt, and color-based metrics calculated from the phenocam imagery (green (GCC) and red (RCC) chromatic coordinates). The transition dates in both spring and autumn differed somewhat according to method, presumably due to the vegetation status detection abilities of each vegetation metric. We found that LAI estimation from canopy cover images may be influenced by automatic exposure settings, which limits the ability to detect subtle changes in phenology during the transition phases in both spring and autumn. Particularly in autumn, the color-based metrics calculated from the phenocam imagery are decoupled from leaf area dynamics and thus PAI. While above and below canopy PAR measurements could yield the better indicators for estimating LAI, its seasonal dynamics, and associated phenological transition dates in long-term monitoring, we argue that there are obvious benefits to the multi-sensor approach used here.

Afforestation and reforestation projects in the karst regions of southwest China aim to combat desertification and improve the ecological environment. However, it remains unclear at what scale conservation efforts have impacted on carbon stocks and if vegetation regrowth occurs at a large spatial scale as intended. Here we use satellite time series data and show a widespread increase in leaf area index (a proxy for green vegetation cover), and aboveground biomass carbon, which contrasted negative trends found in the absence of anthropogenic influence as simulated by an ecosystem model. In spite of drought conditions, aboveground biomass carbon increased by 9% (+0.05 Pg C y−1), mainly in areas of high conservation effort. We conclude that large scale conservation projects can contribute to a greening Earth with positive effects on carbon sequestration to mitigate climate change. At the regional scale, such ecological engineering projects may reduce risks of desertification by increasing the vegetation cover and reducing the ecosystem sensitivity to climate perturbations.

Future droughts are expected to become more severe and frequent under future climate change scenarios, likely causing widespread tree mortality in the western USA. Coping with an uncertain future requires an understanding of long-term ecosystem responses in areas where prolonged drought is projected to increase. Tree-ring records are ideally suited for this task. We developed 24 tree-ring chronologies from 20 U.S. Forest Service Forest Inventory and Analysis (FIA) plots in the southwestern USA. Climate variables were derived from the PRISM climate dataset (800-m grid cells) to capture the bimodal precipitation regime of winter snow and summer monsoonal rainfall, as well as warm-season vapor-pressure deficit (VPD) and winter minimum temperature. Based on mixed linear models, radial growth from 1948 to 2013 for four conifer species (Pinus edulis, Juniperus osteosperma, Pinus ponderosa, and Picea engelmannii) responded negatively to warm-season VPD and positively to cold-season precipitation. Pinus spp. benefited from warm-season precipitation linked to the North American monsoon, and Pinus spp. and J. osteosperma radial growth increased with warmer cold-season minimum temperature. However, warmer cold-season minimum temperatures countered the beneficial influence of cold-season precipitation for radial growth in Pinus spp. and J. osteosperma, while P. engelmannii was unaffected. Also, enhanced drying effects of warm-season VPD associated with decreased cold-season precipitation negatively affected radial growth of Pinus spp. and P. engelmannii. Of the four conifer species studied, Pinus spp. are most affected by droughts since 1948, while P. engelmanniiand J. osteosperma appear to be more resilient. Investigating seasonal climate responses and interaction effects on radial growth in areas impacted by severe drought helps identify species that may be particularly at risk from climate change impacts in the Anthropocene.

The mechanisms governing tree drought mortality and recovery remain a subject of inquiry and active debate given their role in the terrestrial carbon cycle and their concomitant impact on climate change. Counter-intuitively, many trees do not die during the drought itself. Indeed, observations globally have documented that trees often grow for several years after drought before mortality. A combination of meta-analysis and tree physiological models demonstrate that optimal carbon allocation after drought explains observed patterns of delayed tree mortality and provides a predictive recovery framework. Specifically, post-drought, trees attempt to repair water transport tissue and achieve positive carbon balance through regrowing drought-damaged xylem. Furthermore, the number of years of xylem regrowth required to recover function increases with tree size, explaining why drought mortality increases with size. These results indicate that tree resilience to drought-kill may increase in the future, provided that CO2 fertilisation facilitates more rapid xylem regrowth.

Crowther et al. Reported that the best predictor of surface soil carbon (top 10 cm) losses in response to warming is the size of the surface carbon stock in the soil (that is, carbon stocks in plots that have not been warmed), finding that soils that are high in soil carbon also lose more carbon under warming conditions. This relationship was based on a linear regression of soil carbon losses and soil carbon stocks in field warming studies, which was then used to project carbon losses over time and to generate a map of soil carbon vulnerability. However, a few extreme data points (high-leverage points) can strongly influence the slope of a regression line. Only 5 of the 49 sites analysed by Crowther et al. are in the upper half of the carbon stock range, which raises the possibility that the relationship they observed could be substantially altered by introducing data from sites with relatively high surface soil carbon stocks.

Increased fire frequency, extent and severity are expected to strongly affect the structure and function of boreal forest ecosystems. In this study, we examined 213 plots in boreal forests dominated by black spruce (Picea mariana) or jack pine (Pinus banksiana) of the Northwest Territories, Canada, after an unprecedentedly large area burned in 2014. Large fire size is associated with high fire intensity and severity, which would manifest as areas with deep burning of the soil organic layer (SOL). Our primary objectives were to estimate burn depth in these fires and then to characterise landscapes vulnerable to deep burning throughout this region. Here we quantify burn depth in black spruce stands using the position of adventitious roots within the soil column, and in jack pine stands using measurements of burned and unburned SOL depths. Using these estimates, we then evaluate how burn depth and the proportion of SOL combusted varies among forest type, ecozone, plot-level moisture and stand density. Our results suggest that most of the SOL was combusted in jack pine stands regardless of plot moisture class, but that black spruce forests experience complete combustion of the SOL only in dry and moderately well-drained landscape positions. The models and calibrations we present in this study should allow future research to more accurately estimate burn depth in Canadian boreal forests.

Climate warming and drying is associated with increased wildfire disturbance and the emergence of megafires in North American boreal forests. Changes to the fire regime are expected to strongly increase combustion emissions of carbon (C) which could alter regional C balance and positively feedback to climate warming. In order to accurately estimate C emissions and thereby better predict future climate feedbacks, there is a need to understand the major sources of heterogeneity that impact C emissions at different scales. Here, we examined 211 field plots in boreal forests dominated by black spruce (Picea mariana) or jack pine (Pinus banksiana) of the Northwest Territories (NWT), Canada after an unprecedentedly large area burned in 2014. We assessed both aboveground and soil organic layer (SOL) combustion, with the goal of determining the major drivers in total C emissions, as well as to develop a high spatial resolution model to scale emissions in a relatively understudied region of the boreal forest. On average, 3.35 kg C m−2 was combusted and almost 90% of this was from SOL combustion. Our results indicate that black spruce stands located at landscape positions with intermediate drainage contribute the most to C emissions. Indices associated with fire weather and date of burn did not impact emissions, which we attribute to the extreme fire weather over a short period of time. Using these results, we estimated a total of 94.3 Tg C emitted from 2.85 Mha of burned area across the entire 2014 NWT fire complex, which offsets almost 50% of mean annual net ecosystem production in terrestrial ecosystems of Canada. Our study also highlights the need for fine‐scale estimates of burned area that represent small water bodies and regionally specific calibrations of combustion that account for spatial heterogeneity in order to accurately model emissions at the continental scale.

Global terrestrial nitrogen (N) and phosphorus (P) cycles are coupled to the global carbon (C) cycle for net primary production (NPP), plant C allocation, and decomposition of soil organic matter, but N and P have distinct pathways of inputs and losses. Current C-nutrient models exhibit large uncertainties in their estimates of pool sizes, fluxes, and turnover rates of nutrients, due to a lack of consistent global data for evaluating the models. In this study, we present a new model–data fusion framework called the Global Observation-based Land-ecosystems Utilization Model of Carbon, Nitrogen and Phosphorus (GOLUM-CNP) that combines the CARbon DAta MOdel fraMework (CARDAMOM) data-constrained C-cycle analysis with spatially explicit data-driven estimates of N and P inputs and losses and with observed stoichiometric ratios. We calculated the steady-state N- and P-pool sizes and fluxes globally for large biomes. Our study showed that new N inputs from biological fixation and deposition supplied <span class="inline-formula">&gt;20</span>&thinsp;% of total plant uptake in most forest ecosystems but accounted for smaller fractions in boreal forests and grasslands. New P inputs from atmospheric deposition and rock weathering supplied a much smaller fraction of total plant uptake than new N inputs, indicating the importance of internal P recycling within ecosystems to support plant growth. Nutrient-use efficiency, defined as the ratio of gross primary production (GPP) to plant nutrient uptake, were diagnosed from our model results and compared between biomes. Tropical forests had the lowest N-use efficiency and the highest P-use efficiency of the forest biomes. An analysis of sensitivity and uncertainty indicated that the NPP-allocation fractions to leaves, roots,<span id="page3904"/> and wood contributed the most to the uncertainties in the estimates of nutrient-use efficiencies. Correcting for biases in NPP-allocation fractions produced more plausible gradients of N- and P-use efficiencies from tropical to boreal ecosystems and highlighted the critical role of accurate measurements of C allocation for understanding the N and P cycles.

Leaf litter provides an important resource to forested stream ecosystems. During leaf fall a significant amount of dissolved organic carbon (DOC) enters streams as leaf leachate. We compared the effects of plant species and leaf leachate bioavailability on the composition of stream bacterial communities and rates of DOC decomposition. We used four common riparian tree species that varied in foliar chemistry, leachate optical properties, and litter decomposition rate. We used laboratory microcosms from two streams and amended with a standard concentration of DOC derived from leaf leachate of the four tree species. After 24 h, we measured rates of DOC biodegradation and determined the composition of the bacterial communities via bar-coded pyrosequencing of the 16S rRNA gene. The composition, diversity, and abundance of the bacterial community differed significantly among plant species from both streams. The phylogenetic distance of the different bacterial communities correlated with species-specific leachate optical properties and rates of DOC biodegradation. Highest rates of DOC decomposition were associated with high tannin and lignin leaf types. Results demonstrate that riparian plant species strongly influences stream bacterial communities via their leachate suggesting that alterations to the presence or abundance of riparian plant taxa may influence these communities and associated ecosystem processes.

As leaves are the basic elements of plants that conduct photosynthesis and transpiration, vegetation leaf dynamics controls canopy physical and biogeochemical processes and hence largely influences the interactive exchanges of energy and materials between the land surface and the atmosphere. Given that the processes of plant leaf allocation is highly sensitive to climatological and environmental conditions, developing robust models that simulate leaf dynamics via climate variables contributes a key component to land surface models and coupled land-atmosphere models. Here we propose a new method to simulate seasonal leaf dynamics based on the idea of applying vegetation productivity as a synthesized metric to track and assess the climate suitability to plant growth over time. The method first solves two closed simultaneous equations of leaf phenology and canopy photosynthesis as modeled using the Growing Production-Day model iteratively for deriving the time series of steady-state leaf area index (LAI), and then applies the method of simple moving average to account for the time lagging of leaf allocation behind steady-state LAI. The seasonal LAI simulated using the developed method agree with field measurements from a selection of AmeriFlux sites as indicated by high coefficient of determination (R2 = 0.801) and low root mean square error (RMSE = 0.924 m2/m2) and with satellite-derived data (R2 = 0.929 and RMSE = 0.650 m2/m2) for the studied flux tower sites. Moreover, the proposed method is able to simulate seasonal LAI of deciduous broadleaf forests that match with satellite-derived LAI time series across the entire eastern United States. Comparative modeling studies suggest that the proposed method produces more accurate results than the method based on Growing Season Index in terms of correlation coefficients and error metrics. The developed method provides a complete solution to modeling seasonal leaf dynamics as well as canopy productivity solely using climate variables.

Soil organic carbon (SOC) has a significant effect on carbon emissions and climate change. However, the current SOC prediction accuracy of most models is very low. Most evaluation studies indicate that the prediction error mainly comes from parameter uncertainties, which can be improved by parameter calibration. Data assimilation techniques have been successfully employed for the parameter calibration of SOC models. However, data assimilation algorithms, such as the sampling-based Bayesian Markov chain Monte Carlo (MCMC), generally have high computation costs and are not appropriate for complex global land models. This study proposes a new parameter calibration method based on surrogate optimization techniques to improve the prediction accuracy of SOC. Experiments on three types of soil carbon cycle models, including the Community Land Model with the Carnegie–Ames–Stanford Approach biogeochemistry submodel (CLM-CASA') and two microbial models show that the surrogate-based optimization method is effective and efficient in terms of both accuracy and cost. Compared to predictions using the tuned parameter values through Bayesian MCMC, the root mean squared errors (RMSEs) between the predictions using the calibrated parameter values with surrogate-base optimization and the observations could be reduced by up to 12% for different SOC models. Meanwhile, the corresponding computational cost is lower than other global optimization algorithms.

Permafrost soil in high latitude tundra is one of the largest terrestrial carbon (C) stocks and is highly sensitive to climate warming. Understanding microbial responses to warming‐induced environmental changes is critical to evaluating their influences on soil biogeochemical cycles. In this study, a functional gene array (i.e., geochip 4.2) was used to analyze the functional capacities of soil microbial communities collected from a naturally degrading permafrost region in Central Alaska. Varied thaw history was reported to be the main driver of soil and plant differences across a gradient of minimally, moderately, and extensively thawed sites. Compared with the minimally thawed site, the number of detected functional gene probes across the 15–65 cm depth profile at the moderately and extensively thawed sites decreased by 25% and 5%, while the community functional gene β‐diversity increased by 34% and 45%, respectively, revealing decreased functional gene richness but increased community heterogeneity along the thaw progression. Particularly, the moderately thawed site contained microbial communities with the highest abundances of many genes involved in prokaryotic C degradation, ammonification, and nitrification processes, but lower abundances of fungal C decomposition and anaerobic‐related genes. Significant correlations were observed between functional gene abundance and vascular plant primary productivity, suggesting that plant growth and species composition could be co‐evolving traits together with microbial community composition. Altogether, this study reveals the complex responses of microbial functional potentials to thaw‐related soil and plant changes and provides information on potential microbially mediated biogeochemical cycles in tundra ecosystems.

As atmospheric nitrogen (N) concentrations increase, it can wreak havoc on the entire planet, as well as the fragile ecosystems, once it exceeds the demand of ecosystems. Chronically elevated N deposition affects litter decomposition, which is a crucial process that controls nutrient cycling, soil fertility, and primary productivity. Nevertheless, the responses of litter decomposition and nutrient release to N addition remain elusive. Here we conduct a meta-analysis using 3434 paired observations from 55 publications to evaluate these responses. We found that although litter decomposition rate did not change significantly under N addition when averaged across all studies, it decreased with N application rate and experimental duration, showing that it was stimulated at low levels but suppressed at high levels of N application and duration. Phosphorus released more slowly under N enrichment, and this response became greater with longer duration. Moreover, the decomposition of lignin was depressed under N addition, and this effect was more pronounced with the increase of N application rate and experimental duration. Importantly, in terms of different ecosystems, the decomposition of litter was significantly inhibited by N addition in plantations, but was promoted in secondary forests, and there were no significant changes in primary forests, grasslands and wetlands. The responses of litter mass loss, along with the release of nutrients to N fertilization, changed with mean annual temperature and mean annual precipitation of the study sites. Our results provided a synthetic understanding of the effects of N addition on the decomposition of litter and nutrient release under climate change scenarios.

Land surface phenology (LSP) has been widely retrieved from time series of various satellite instruments in order to monitor climate change and ecosystem dynamics. However, any evaluation of the quality of LSP data sets is quite challenging because the in situ observations on a limited number of individual trees, shrubs, or other plants are rarely representative of the landscape sampled in a single satellite pixel. Moreover, vegetation indices detecting biophysical features of vegetation seasonality are different from (but related to) the specific plant life history stages observed by humans at ground level. This study is the first comprehensive evaluation of the LSP product derived from Visible Infrared Imaging Radiometer Suite (VIIRS) data using both MODIS LSP products and observations from the PhenoCam network across the Contiguous United States during 2013 and 2014. PhenoCam observes vegetation canopy over a landscape at very high frequency, providing nearly continuous canopy status and enabling the estimate of discrete phenophase using vegetation indices that are conceptually similar to satellite data. Six phenological dates (greenup onset, mid-greenup phase, maturity onset, senescence onset, mid-senescence phase, and dormancy onset) were retrieved separately from daily VIIRS NDVI (normalized difference vegetative index) and EVI2 (two-band enhanced vegetation index) time series. Similarly, the six phenological dates were also extracted from the 30-min time series of PhenoCam data using GCC (green chromatic coordinate) and VCI (vegetation contrast index) separately. Phenological dates derived from VIIRS NDVI and EVI2 and PhenoCam GCC and VCI were generally comparable for the vegetation greenup phase, but differed considerably for the senescence phase. Although all indices captured green leaf development effectively, performance discrepancies arose due to their ability to track the mixture of senescing leaf colors. PhenoCam GCC and VCI phenological observations were in better agreement with the phenological dates from VIIRS EVI2 than from VIIRS NDVI. Further, the VIIRS EVI2 phenological metrics were more similar to those from PhenoCam VCI than from PhenoCam GCC time series. Overall, the average absolute difference between the VIIRS EVI2 and PhenoCam VCI phenological dates was 7–11 days in the greenup phase and 10–13 days in the senescence phase. The difference was smaller in forests, followed by grasslands and croplands, and then savannas. Finally, the phenological dates derived from VIIRS EVI2 were compared with MODIS detections, which showed a good agreement with an average absolute difference less than a week except for the senescence onset. These results for the first time demonstrate the upper boundary of uncertainty in VIIRS LSP detections and the continuity to MODIS LSP product.

Terrestrial carbon cycle models have incorporated increasingly more processes as a means to achieve more-realistic representations of ecosystem carbon cycling. Despite this, there are large across-model variations in the simulation and projection of carbon cycling. Several model intercomparison projects (MIPs), for example, the fifth phase of the Coupled Model Intercomparison Project (CMIP5) (historical simulations), Trends in Net Land?Atmosphere Carbon Exchange (TRENDY), and Multiscale Synthesis and Terrestrial Model Intercomparison Project (MsTMIP), have sought to understand intermodel differences. In this study, the authors developed a suite of new techniques to conduct post-MIP analysis to gain insights into uncertainty sources across 25 models in the three MIPs. First, terrestrial carbon storage dynamics were characterized by a three-dimensional (3D) model output space with coordinates of carbon residence time, net primary productivity (NPP), and carbon storage potential. The latter represents the potential of an ecosystem to lose or gain carbon. This space can be used to measure how and why model output differs. Models with a nitrogen cycle generally exhibit lower annual NPP in comparison with other models, and mostly negative carbon storage potential. Second, a transient traceability framework was used to decompose any given carbon cycle model into traceable components and identify the sources of model differences. The carbon residence time (or NPP) was traced to baseline carbon residence time (or baseline NPP related to the maximum carbon input), environmental scalars, and climate forcing. Third, by applying a variance decomposition method, the authors show that the intermodel differences in carbon storage can be mainly attributed to the baseline carbon residence time and baseline NPP (&gt;90% in the three MIPs). The three techniques developed in this study offer a novel approach to gain more insight from existing MIPs and can point out directions for future MIPs. Since this study is conducted at the global scale for an overview on intermodel differences, future studies should focus more on regional analysis to identify the sources of uncertainties and improve models at the specified mechanism level.

Temperature sensitivity of soil organic carbon (SOC) decomposition is one of the major uncertainties in predicting climate‐carbon (C) cycle feedback. Results from previous studies are highly contradictory with old soil C decomposition being more, similarly, or less sensitive to temperature than decomposition of young fractions. The contradictory results are partly from difficulties in distinguishing old from young SOC and their changes over time in the experiments with or without isotopic techniques. In this study, we have conducted a long‐term field incubation experiment with deep soil collars (0–70 cm in depth, 10 cm in diameter of PVC tubes) for excluding root C input to examine apparent temperature sensitivity of SOC decomposition under ambient and warming treatments from 2002 to 2008. The data from the experiment were infused into a multi‐pool soil C model to estimate intrinsic temperature sensitivity of SOC decomposition and C residence times of three SOC fractions (i.e., active, slow, and passive) using a data assimilation (DA) technique. As active SOC with the short C residence time was progressively depleted in the deep soil collars under both ambient and warming treatments, the residences times of the whole SOC became longer over time. Concomitantly, the estimated apparent and intrinsic temperature sensitivity of SOC decomposition also became gradually higher over time as more than 50% of active SOC was depleted. Thus, the temperature sensitivity of soil C decomposition in deep soil collars was positively correlated with the mean C residence times. However, the regression slope of the temperature sensitivity against the residence time was lower under the warming treatment than under ambient temperature, indicating that other processes also regulated temperature sensitivity of SOC decomposition. These results indicate that old SOC decomposition is more sensitive to temperature than young components, making the old C more vulnerable to future warmer climate.

Climate change intensifies the hydrological cycle and consequently alters precipitation regimes. Accurately assessing future carbon (C) budgets depends on understanding the influence of altered precipitation on both aboveground C cycling and belowground processes. Our goal was to explore generalities and mechanisms of responses of soil microbial communities to altered precipitation and implications for C cycling in terrestrial ecosystems. Location Global. Time period 2001?2017. Major taxa studied Soil microbes. Methods We used the meta-analytical technique to synthesize data of 41 increased (IPPT) and 53 decreased precipitation (DPPT) studies from 65 publications worldwide. The data covered broad variations in climate, percentage of precipitation change, experimental duration and soil properties. Results The fungi to bacteria ratio did not show a water-tolerant shift, but the community compositions within the bacteria did. Microbial biomass showed a higher response to moderate IPPT than moderate DPPT, whereas it was more sensitive to extreme DPPT than extreme IPPT, suggesting that the responses of microbial biomass to altered precipitation are double asymmetric. However, such asymmetric responses of microbial biomass varied with climate humidity and soil texture: microbial biomass was more sensitive to IPPT at xeric sites than at mesic sites, whereas it was more responsive to DPPT in humid areas; microbial biomass in coarse-textured soils was more sensitive to altered precipitation than that in fine-textured soils. In addition, microbial response was positively correlated with the responses of aboveground/belowground plant biomass, soil respiration and organic C content. Main conclusions Our meta-analysis provides the first evidence that the asymmetric response of microbial biomass to altered precipitation varies with climate humidity and soil texture. Given the coordinated responses in the plant?soil?microorganism C continuum, our synthesis extends the double asymmetric model and provides a framework for understanding and modelling responses of ecosystem C cycling to global precipitation change.

The recovery of North American forests is likely to impact their capacity as a carbon sink. Here, Zhu et al. show a growth in aboveground biomass in various climate change scenarios, with these forests expected to sequester no more than 22% more carbon than current levels by the 2080s.

Land-use conversions and elevated temperature can impact on carbon dioxide (CO2) and nitrous oxide (N2O) emissions, both of which are important greenhouse gasses (GHGs). Afforestation activity has increased significantly over the last century with a significant focus in recent years directed at offsetting GHG emissions, as forests have a large capacity to store carbon (C) and nitrogen (N) as well as affecting CO2 and N2O emissions. However, the impact of warming on GHG offsetting is unclear. This study was conducted in a forest and a grassland to investigate the effect of afforestation and warming, using infrared heaters, on soil fluxes of CO2 and N2O. Warming significantly increased the daily mean soil temperatures at a depth of 5 cm by 1.7 °C and reduced the soil moisture by ∼5% in the forest from March 2014 to February 2016. In the grassland, there were no significant increases in temperature and moisture with warming and no impact on the soil fluxes of CO2 and N2O. In the forest, elevated soil temperature enhanced the average soil CO2 efflux by 23% but had no effect on soil N2O fluxes. Warming decreased the temperature sensitivity by 13% and 23% at the forest and grassland, respectively. The soil fluxes of CO2 increased exponentially with temperature and decreased linearly with the reduction in soil moisture, and were much larger in the grassland compared to the forest. However the grassland proved to be a larger sink for N2O than the forest. Irrespective of warming treatments, all measured pools were significantly larger in the grassland compared to the forest. Our results imply that afforestation may have a bigger effect than warming on soil CO2 and N2O fluxes within the range of temperatures used and that afforestation dramatically lowers the inorganic, organic and microbial C and N pools, that could, in turn, impact on the responses of forest soils to future global warming.

Future climate change is expected to alter the terrestrial carbon cycle through its impact on soil respiration. In this study, we determined the responses of soil respiration and its components to experimental warming with or without water addition. A replicated <em>in situ</em> heating (∼2 °C above ambient soil temperatures) and water addition (170 mm in total each year) experiment was carried out for the first time in a temperate plantation forest of Sitka spruce over the period 2014–2016. R_hwas measured inside deep collars (35 cm deep) that excluded root growth, while R_swas measured using the static chamber approach and near-surface collars (5 cm deep) and R_a calculated by subtracting R_h from total soil respiration (R_s). Experimental warming significantly increased R_s, R_h and R_h/R_s, but had no effect on R_a. In contrast, none of the respiration components were affected by water addition. Warming increased annual R_h by 62% but had no effect on R_a. Overall, warming did not significantly increase annual R_s. Warming showed a stronger impact on R_s in the non-growing season but had a smaller impact in the growing season. Warming increased R_a in the non-growing season but decreased it in the growing season. The effects of warming on R_h were similar for the two periods. Our results highlight the differential response of R_a and R_h to warming, which was mediated by water addition or season. For this and other similar forest sites that don’t experience water limitation, global warming may have a positive feedback on atmospheric CO₂concentrations through enhanced soil respiration.

Increased fire severity in boreal forests of Interior Alaska is shifting forest canopy composition from black spruce (Picea mariana) to deciduous species, including trembling aspen (Populus tremuloides) and Alaska paper birch (Betula neoalaskana). Because deciduous trees are less flammable than black spruce, the dominant disturbance regime in deciduous forests could move away from fire to one of gap disturbances. In this study, we quantified forest gap characteristics and vegetation within eight mature (62-119-yr-old) deciduous stands in Interior Alaska. Canopy gaps were generally small (true gap area &lt;50 m(2)), formed by the mortality of 4-16 gap makers (which were always deciduous trees), and occupied similar to 17-29% of the forest except in the oldest stand, where gap fraction exceeded 45%, and in one anomalous 84-yr old stand, where gaps were absent. Canopy openness increased linearly with gap area, but density of both deciduous and evergreen tree recruits was generally low and insufficient to create future stands with densities similar to those currently found in mature stands across the landscape. Canopy openness was instead correlated with decreased leaf litter cover and increased cover of moss, lichen, and evergreen shrubs. Given the low recruitment of trees with canopy gaps and the decreased probability of fire, deciduous stands will likely "transition to non-forested areas or low density stands once overstory trees reach maturity and die. This could have numerous implications for ecosystem function, including carbon (C), water, and energy balance, and potential feedbacks to future fire occurrence and regional climate. (C) 2017 Elsevier B.V. All rights reserved. &nbsp;

Over the last two decades, satellite-derived estimates of biophysical variables have been increasingly used in operational services, requiring quantification of their accuracy and uncertainty. Evaluating satellite-derived vegetation products is challenging due to their moderate spatial resolution, the heterogeneity of the terrestrial landscape, and difficulties in adequately characterising spatial and temporal vegetation dynamics. In recent years, near-surface remote sensing has emerged as a potential source of data against which satellite-derived vegetation products can be evaluated. Several studies have focussed on the evaluation of satellite-derived phenological transition dates, however in most cases the shape and magnitude of the underlying time-series are neglected. In this paper, we investigated the relationship between the green chromatic coordinate (GCC) derived using near-surface remote sensing and a range of vegetation products derived from the Medium Resolution Imaging Spectrometer (MERIS) throughout the growing season. Moderate to strong relationships between the GCC and vegetation products derived from MERIS were observed at deciduous forest sites. Weak relationships were observed over evergreen forest sites as a result of their subtle seasonality, which is likely masked by atmospheric, bidirectional reflectance distribution function (BRDF), and shadowing effects. Temporal inconsistencies were attributed to the oblique viewing geometry of the digital cameras and differences in the incorporated spectral bands. In addition, the commonly observed summer decline in GCC values was found to be primarily associated with seasonal variations in brown pigment concentration, and to a lesser extent illumination geometry. At deciduous sites, increased sensitivity to initial increases in canopy greenness was demonstrated by the GCC, making it particularly well-suited to identifying the start of season when compared to satellite-derived vegetation products. Nevertheless, in some cases, the relationship between the GCC and vegetation products derived from MERIS was found to saturate asymptotically. This limits the potential of the approach for evaluation of the vegetation products that underlie satellite-derived phenological transition dates, and for the continuous monitoring of vegetation during the growing season, particularly at medium to high biomass study sites.

Current and future warming of high latitude ecosystems will play an important role in climate change through feedbacks to the global carbon cycle. This study compares six years of CO2 flux measurements in moist acidic tundra using autochambers and eddy covariance (Tower) approaches. We found that the tundra was an annual source of CO2 to the atmosphere as indicated by net ecosystem exchange using both methods with a combined mean of 105 +/- 17 g CO2 - C m-2 y-1 across methods and years (Tower 87 +/- 17 and Autochamber 123 +/- 14). The difference between methods was largest early in the observation period, with Autochambers indicated a greater CO2 source to the atmosphere. This discrepancy diminished through time and in the final year the Autochambers measured a greater sink strength than tower. Active layer thickness (ALT) was a significant driver of NEE, GPP, and R eco and could account for differences between Autochamber and Tower. The stronger source initially was attributed lower summer season gross primary production (GPP) during the first three years, coupled with lower ecosystem respiration (R eco) during the first year. The combined suppression of GPP and R eco in the first year of Autochamber measurements could be the result of the experimental setup. Root damage associated with Autochamber soil collar installation may have lowered the plant community's capacity to fix C, but recovered within three years. While this ecosystem was a consistent CO2 sink during the summer, CO2 emissions during the non-summer months offset summer CO2 uptake each year.

Despite a large body of research documenting invasive plant impacts, few studies have followed individual invaded sites over decades to observe how they change, and none have contrasted how compositional impacts from invasion compare to ecosystem-process impacts over a multi-decadal time-scale. Using direct measurements of plant density and composition and of ecosystems processes, we evaluate how ecosystem structure, above-ground net primary production (ANPP), and above-ground and soil nutrient pools compare over 25 years since fire and C4 grass invasions disrupted seasonally dry Hawaiian woodlands. We compare structure and function between primary woodland that has never burned and is largely native species-dominated, with sites that had been the same woodland type but burned in alien-grass-fuelled fires in the 1970s and 1980s. The sites have not experienced fires since 1987. We report here that woody plant composition and structure continue to be dramatically changed by the initial invasions and fires that occurred 25 years ago and invaders continue to dominate in burned sites. This is reflected in continued low plant carbon pools in burned compared to unburned sites. Yet ANPP and N storage, which were dramatically lower in the initial decade after invasive-grass fuelled fires, have increased and are now indistinguishable from values measured in intact woodlands. Soil carbon pools were resilient to both invasion and fire initially and over time. Above-ground net primary production has recovered because of invasion of burned sites by a non-native N-fixing tree rather than because of recovery of native species. This invasive N-fixing tree is unlikely to return C storage of the invaded sites to those of unburned woodland because of its tissue and growth characteristics and its interactions with invasive grasses. It does not facilitate native species but rather promotes a persistent invasive grass/N-fixer savanna. Synthesis. We conclude that fire, an unusual disturbance in this system, has perpetuated the dominance of these sites by invasive species and that despite the dramatic recovery of above-ground net primary production and N pools, the ecosystem continues to be in a distinctly different state than the pre-fire, pre-Melinis community. Thus, despite the absence of further disturbance (fire), there is no evidence that succession towards the original ecosystem is occurring. The fact that N pools and above-ground net primary production recover because of a new invader (Morella faya), highlights the unpredictability of ecosystem trajectories in the face of altered regional species pools.

Climate variability associated with the El Niño-Southern Oscillation (ENSO) and its consequent impacts on land carbon sink interannual variability have been used as a basis for investigating carbon cycle responses to climate variability more broadly, and to inform the sensitivity of the tropical carbon budget to climate change. Past studies have presented opposing views about whether temperature or precipitation is the primary factor driving the response of the land carbon sink to ENSO. Here, we show that the dominant driver varies with ENSO phase. Whereas tropical temperature explains sink dynamics following El Niño conditions (r TG,P = 0.59, p &lt; 0.01), the post La Niña sink is driven largely by tropical precipitation (r PG,T = −0.46, p = 0.04). This finding points to an ENSO-phase-dependent interplay between water availability and temperature in controlling the carbon uptake response to climate variations in tropical ecosystems. We further find that none of a suite of ten contemporary terrestrial biosphere models captures these ENSO-phase-dependent responses, highlighting a key uncertainty in modeling climate impacts on the future of the global land carbon sink.

Quantifying soil organic carbon (SOC) decomposition under warming is critical to predict carbon–climate feedbacks. According to the substrate regulating principle, SOC decomposition would decrease as labile SOC declines under field warming, but observations of SOC decomposition under warming do not always support this prediction. This discrepancy could result from varying changes in SOC components and soil microbial communities under warming. This study aimed to determine the decomposition of SOC components with different turnover times after subjected to long‐term field warming and/or root exclusion to limit C input, and to test whether SOC decomposition is driven by substrate lability under warming. Taking advantage of a 12‐year field warming experiment in a prairie, we assessed the decomposition of SOC components by incubating soils from control and warmed plots, with and without root exclusion for 3 years. We assayed SOC decomposition from these incubations by combining inverse modeling and microbial functional genes during decomposition with a metagenomic technique (GeoChip). The decomposition of SOC components with turnover times of years and decades, which contributed to 95% of total cumulative CO2 respiration, was greater in soils from warmed plots. But the decomposition of labile SOC was similar in warmed plots compared to the control. The diversity of C‐degradation microbial genes generally declined with time during the incubation in all treatments, suggesting shifts of microbial functional groups as substrate composition was changing. Compared to the control, soils from warmed plots showed significant increase in the signal intensities of microbial genes involved in degrading complex organic compounds, implying enhanced potential abilities of microbial catabolism. These are likely responsible for accelerated decomposition of SOC components with slow turnover rates. Overall, the shifted microbial community induced by long‐term warming accelerates the decomposition of SOC components with slow turnover rates and thus amplify the positive feedback to climate change.

Carbon storage by ecosystems is valuable for climate protection. Biodiversity conservation may help increase carbon storage, but the value of this influence has been difficult to assess. We use plant, soil, and ecosystem carbon storage data from two grassland biodiversity experiments to show that greater species richness increases economic value: Increasing species richness from 1 to 10 had twice the economic value of increasing species richness from 1 to 2. The marginal value of each additional species declined as species accumulated, reflecting the nonlinear relationship between species richness and plant biomass production. Our demonstration of the economic value of biodiversity for enhancing carbon storage provides a foundation for assessing the value of biodiversity for decisions about land management. Combining carbon storage with other ecosystem services affected by biodiversity may well enhance the economic arguments for conservation even further.

Bryophytes are dominant components of boreal forest understories and play a large role in regulating soil microclimate and nutrient cycling. Therefore, shifts in bryophyte communities have the potential to affect boreal forests’ ecosystem processes. We investigated how bryophyte communities varied in 83 forest stands in interior Alaska that ranged in age (since fire) from 8 to 163 years and had canopies dominated by deciduous broadleaf (Populus tremuloides Michx. or Betula neoalaskana Sarg.) or coniferous trees (Picea mariana Mill B.S.P.). In each stand, we measured bryophyte community composition, along with environmental variables (e.g., organic layer depth, leaf litter cover, moisture). Bryophyte communities were initially similar in deciduous vs. coniferous forests but diverged in older stands in association with changes in organic layer depth and leaf litter cover. Our data suggest two tipping points in bryophyte succession: one at the disappearance of early colonizing taxa 20 years after fire and another at 40 years after fire, which corresponds to canopy closure and differential leaf litter inputs in mature deciduous and coniferous canopies. Our results enhance understanding of the processes that shape compositional patterns and ecosystem services of bryophytes in relation to stand age, canopy composition, and changing disturbances such as fire that may trigger changes in canopy composition.

Applying biochar to soil is thought to have multiple benefits, from helping mitigate climate change [1, 2], to managing waste [3] to conserving soil [4]. Biochar is also widely assumed to boost crop yield [5, 6], but there is controversy regarding the extent and cause of any yield benefit [7]. Here we use a global-scale meta-analysis to show that biochar has, on average, no effect on crop yield in temperate latitudes, yet elicits a 25% average increase in yield in the tropics. In the tropics, biochar increased yield through liming and fertilization, consistent with the low soil pH, low fertility, and low fertilizer inputs typical of arable tropical soils. We also found that, in tropical soils, high-nutrient biochar inputs stimulated yield substantially more than low-nutrient biochar, further supporting the role of nutrient fertilization in the observed yield stimulation. In contrast, arable soils in temperate regions are moderate in pH, higher in fertility, and generally receive higher fertilizer inputs, leaving little room for additional benefits from biochar. Our findings demonstrate that the yield-stimulating effects of biochar are not universal, but may especially benefit agriculture in low-nutrient, acidic soils in the tropics. Biochar management in temperate zones should focus on potential non-yield benefits such as lime and fertilizer cost savings, greenhouse gas emissions control, and other ecosystem services.

Uptake of anthropogenically emitted carbon (C) dioxide by terrestrial ecosystem is critical for determining future climate. However, Earth system models project large uncertainties in future C storage. To help identify sources of uncertainties in model predictions, this study develops a transient traceability framework to trace components of C storage dynamics. Transient C storage (X) can be decomposed into two components, C storage capacity (Xc) and C storage potential (Xp). Xc is the maximum C amount that an ecosystem can potentially store and Xp represents the internal capacity of an ecosystem to equilibrate C input and output for a network of pools. Xc is codetermined by net primary production (NPP) and residence time (τN), with the latter being determined by allocation coefficients, transfer coefficients, environmental scalar, and exit rate. Xp is the product of redistribution matrix (τch) and net ecosystem exchange. We applied this framework to two contrasting ecosystems, Duke Forest and Harvard Forest with an ecosystem model. This framework helps identify the mechanisms underlying the responses of carbon cycling in the two forests to climate change. The temporal trajectories of X are similar between the two ecosystems. Using this framework, we found that different mechanisms lead to a similar trajectory between the two ecosystems. This framework has potential to reveal mechanisms behind transient C storage in response to various global change factors. It can also identify sources of uncertainties in predicted transient C storage across models and can therefore be useful for model intercomparison.

Breeding high‐yielding rice cultivars through increasing biomass is a key strategy to meet rising global food demands. Yet, increasing rice growth can stimulate methane (CH4) emissions, exacerbating global climate change, as rice cultivation is a major source of this powerful greenhouse gas. Here, we show in a series of experiments that high‐yielding rice cultivars actually reduce CH4 emissions from typical paddy soils. Averaged across 33 rice cultivars, a biomass increase of 10% resulted in a 10.3% decrease in CH4 emissions in a soil with a high carbon (C) content. Compared to a low‐yielding cultivar, a high‐yielding cultivar significantly increased root porosity and the abundance of methane‐consuming microorganisms, suggesting that the larger and more porous root systems of high‐yielding cultivars facilitated CH4 oxidation by promoting O2 transport to soils. Our results were further supported by a meta‐analysis, showing that high‐yielding rice cultivars strongly decrease CH4 emissions from paddy soils with high organic C contents. Based on our results, increasing rice biomass by 10% could reduce annual CH4 emissions from Chinese rice agriculture by 7.1%. Our findings suggest that modern rice breeding strategies for high‐yielding cultivars can substantially mitigate paddy CH4 emission in China and other rice growing regions.

Large interannual variations in the measured growth rate of atmospheric carbon dioxide (CO2) originate primarily from fluctuations in carbon uptake by land ecosystems. It remains uncertain, however, to what extent temperature and water availability control the carbon balance of land ecosystems across spatial and temporal scales. Here we use empirical models based on eddy covariance data and process-based models to investigate the effect of changes in temperature and water availability on gross primary productivity (GPP), terrestrial ecosystem respiration (TER) and net ecosystem exchange (NEE) at local and global scales. We find that water availability is the dominant driver of the local interannual variability in GPP and TER. To a lesser extent this is true also for NEE at the local scale, but when integrated globally, temporal NEE variability is mostly driven by temperature fluctuations. We suggest that this apparent paradox can be explained by two compensatory water effects. Temporal water-driven GPP and TER variations compensate locally, dampening water-driven NEE variability. Spatial water availability anomalies also compensate, leaving a dominant temperature signal in the year-to-year fluctuations of the land carbon sink. These findings help to reconcile seemingly contradictory reports regarding the importance of temperature and water in controlling the interannual variability of the terrestrial carbon balance. Our study indicates that spatial climate covariation drives the global carbon cycle response.

The North American Monsoon delivers warm season precipitation to much of the southwestern United States, yet the importance of this water source for forested ecosystems in the region is not well understood. While it is widely accepted that trees in southwestern forests use winter precipitation for earlywood production, the extent to which summer (monsoon season) precipitation supports latewood production is unclear. We used tree ring records, local climate data, and stable isotope analyses (δ¹⁸O) of water and cellulose to examine the importance of monsoon precipitation for latewood production in mature ponderosa pine (<i>Pinus ponderosa</i> Dougl.) in northern Arizona. Our analyses identified monsoon season vapor pressure deficit (VPD) and Palmer Drought Severity Index (PDSI) as significant effects on latewood growth, together explaining 39% of latewood ring width variation. Stem water and cellulose δ¹⁸O analyses suggest that monsoon precipitation was not directly used for latewood growth. Our findings suggest that mature ponderosa pines in this region utilize winter precipitation for growth throughout the entire year. The influence of monsoon precipitation on growth is indirect and mediated by its effect on atmospheric moisture stress (VPD). Together, summer VPD and antecedent soil moisture conditions have a strong influence on latewood growth.

Warming temperatures in the Northern Hemisphere have enhanced terrestrial productivity. Despite the warming trend, North America has experienced more frequent and more intense cold weather events during winters and springs. These events have been linked to anomalous Arctic warming since 1990, and may affect terrestrial processes. Here we analyse multiple observation data sets and numerical model simulations to evaluate links between Arctic temperatures and primary productivity in North America. We find that positive springtime temperature anomalies in the Arctic have led to negative anomalies in gross primary productivity over most of North America during the last three decades, which amount to a net productivity decline of 0.31 PgC yr−1across the continent. This decline is mainly explained by two factors: severe cold conditions in northern North America and lower precipitation in the South Central United States. In addition, United States crop-yield data reveal that during years experiencing anomalous warming in the Arctic, yields declined by approximately 1 to 4% on average, with individual states experiencing declines of up to 20%. We conclude that the strengthening of Arctic warming anomalies in the past decades has remotely reduced productivity over North America.

Plant phenology is a sensitive indicator of the effects of global change on terrestrial ecosystems and controls the timing of key ecosystem functions including photosynthesis and transpiration. Aerial drone imagery and photogrammetric techniques promise to advance the study of phenology by enabling the creation of distortion-free orthomosaics of plant canopies at the landscape scale, but with branch-level image resolution. The main goal of this study is to determine the leaf life cycle events corresponding to phenological metrics derived from automated analyses based on color indices calculated from drone imagery. For an oak-dominated, temperate deciduous forest in the northeastern USA, we find that plant area index (PAI) correlates with a canopy greenness index during spring green-up, and a canopy redness index during autumn senescence. Additionally, greenness and redness metrics are significantly correlated with the timing of budburst and leaf expansion on individual trees in spring. However, we note that the specific color index for individual trees must be carefully chosen if new foliage in spring appears red, rather than green—which we observed for some oak trees. In autumn, both decreasing greenness and increasing redness correlate with leaf senescence. Maximum redness indicates the beginning of leaf fall, and the progression of leaf fall correlates with decreasing redness. We also find that cooler air temperature microclimates near a forest edge bordering a wetland advance the onset of senescence. These results demonstrate the use of drones for characterizing the organismic-level variability of phenology in a forested landscape and advance our understanding of which phenophase transitions correspond to color-based metrics derived from digital image analysis.

Antibiotic‐resistant pathogens increasingly threaten human health. Widespread application of antibiotics to animal populations raised for food, including chickens, cattle, and pigs, selects for resistance and contributes to the evolution of those pathogens. Despite a half century of research establishing the mechanisms and pathways by which antibiotic‐resistant bacteria spread from food animals to people, scientists lack the appropriate data and models to estimate the public health burden of antibiotic‐resistant human infections attributable to antibiotic use in food‐animal production. Genomic technologies are enabling researchers to track the bidirectional transmissions of specific bacterial strains from livestock to people – and from people to livestock – that can amplify resistance traits. Concepts in ecology, which were developed to understand resource subsidies, metapopulations, and biological invasions, provide insight into the epidemiology of antibiotic resistance from genomic data. By applying ecological principles to highly resolved phylogenetic data, researchers can improve strategies for controlling antibiotic resistance.

Groundwater is an integral component of the water cycle, and it also influences the carbon cycle by supplying moisture to ecosystems. However, the extent and determinants of groundwater-vegetation interactions are poorly understood at the global scale. Using several high-resolution data products, we show that the spatial patterns of ecosystem gross primary productivity and groundwater table depth are correlated during at least one season in more than two thirds of the global vegetated area. Positive relationships, i.e., larger productivity under shallower groundwater table, predominate in moisture-limited dry to mesic conditions with herbaceous and shrub vegetation. Negative relationships, i.e., larger productivity under deeper groundwater, predominate in humid climates with forests, possibly indicating a drawdown of groundwater table due to substantial ecosystem water use. Interestingly, these opposite groundwater-vegetation interactions are primarily associated with differences in vegetation than with climate and surface characteristics. These findings put forth the first evidence, and a need for better representation, of extensive and non-negligible groundwater-vegetation interactions at the global scale.

Labile carbon (C) input to soil can accelerate or slow the decomposition of soil organic matter, a phenomenon called priming. However, priming is difficult to predict, making its relationship with C input elusive. To assess this relationship, we added ¹³C-glucose at five levels (8 to 1606 μg C g⁻¹ week⁻¹) to the soil from four different ecosystems for seven weeks. We observed a positive linear relationship between C input and priming in all soils: priming increased from negative or no priming at low C input to strong positive priming at high C input. However, the sensitivity of priming to C input varied among soils and between ways of expressing C input, and decreased with elevation. Positive substrate thresholds were detected in three soils (56 to 242 μg C g⁻¹ week⁻¹), suggesting the minimum C input required to trigger positive priming. Carbon input expressed as a fraction of microbial biomass explained 16.5% less variation in priming than did C input expressed as a fraction of dry soil mass, indicating that priming is not strongly related to the size of the soil microbial biomass. We conclude that priming increases with the rate of labile C input, once that rate exceeds a threshold, but the magnitude of increase varies among soils. Further research on mechanisms causing the variation of priming sensitivity to increasing labile C input might help promote a quantitative understanding of how such phenomenon impacts soil C cycling, offering the potential to improve earth system models.

Fertilizer inputs affect plant uptake of native soil nitrogen (N), yet the underlying mechanisms remain elusive. To increase mechanistic insight into this phenomenon, we evaluated the effect of fertilizer addition on mineralization (in the absence of plants) and plant uptake of native soil N. We synthesized 43 isotope tracer (¹⁵N) studies and estimated the effects of fertilizer addition using <em>meta</em>-analysis. We found that organic fertilizer tended to reduce native soil N mineralization (−99 kg ha⁻¹ year⁻¹; p = 0.09) while inorganic fertilizer tended to increase N priming (58 kg ha⁻¹ year⁻¹; p = 0.17). In contrast, both organic and inorganic fertilizers significantly increased plant uptake of native soil N (179 and 107 kg ha⁻¹ year⁻¹). Organic fertilizer had greater effect on plant uptake than on mineralization of native soil N (p &lt; 0.001), but inorganic fertilizer had similar effects. Fertilizer effects on mineralization and plant uptake of native soil N were not influenced by study location (laboratory or field) and duration, soil texture, carbon and N content, and pH. Fertilizer addition variably affected native soil N mineralization but consistently increased plant uptake of native soil N. The positive effect of organic fertilizer on plant uptake of native soil N can not be explained by its negative effect on native soil N mineralization, suggesting that increased plant uptake of native soil N was caused mostly by plant-mediated mechanisms (e.g., increased root growth, rhizosphere N priming) rather than by soil microbe-mediated mechanisms.

Large uncertainties exist in predicting responses of wetland methane (CH4) fluxes to future climate change. However, sources of the uncertainty have not been clearly identified despite the fact that methane production and emission processes have been extensively explored. In this study, we took advantage of manual CH4 flux measurements under ambient environment from 2011 to 2014 at the Spruce and Peatland Responses Under Changing Environments (SPRUCE) experimental site and developed a data‐informed process‐based methane module. The module was incorporated into the Terrestrial ECOsystem (TECO) model before its parameters were constrained with multiple years of methane flux data for forecasting CH4 emission under five warming and two elevated CO2 treatments at SPRUCE. We found that 9°C warming treatments significantly increased methane emission by approximately 400%, and elevated CO2 treatments stimulated methane emission by 10.4%–23.6% in comparison with ambient conditions. The relative contribution of plant‐mediated transport to methane emission decreased from 96% at the control to 92% at the 9°C warming, largely to compensate for an increase in ebullition. The uncertainty in plant‐mediated transportation and ebullition increased with warming and contributed to the overall changes of emissions uncertainties. At the same time, our modeling results indicated a significant increase in the emitted CH4:CO2 ratio. This result, together with the larger warming potential of CH4, will lead to a strong positive feedback from terrestrial ecosystems to climate warming. The model‐data fusion approach used in this study enabled parameter estimation and uncertainty quantification for forecasting methane fluxes.

Rapid Arctic warming is expected to increase global greenhouse gas concentrations as permafrost thaw exposes immense stores of frozen carbon (C) to microbial decomposition. Permafrost thaw also stimulates plant growth, which could offset C loss.Using data from seven years of experimental Air and Soil warming in moist acidic tundra, we show that Soil warming had a much stronger effect on CO2 flux than Air warming. Soil warming caused rapid permafrost thaw and increased ecosystem respiration (Reco), gross primary productivity (GPP), and net summer CO2 storage (NEE). Over seven years Reco, GPP, and NEE also increased in Control (i.e., ambient plots), but this change could be explained by slow thaw in Control areas. In the initial stages of thaw, Reco, GPP, and NEE increased linearly with thaw across all treatments, despite different rates of thaw. As thaw in Soil warming continued to increase linearly, ground surface subsidence created saturated micro-sites, and suppressed Reco, GPP, and NEE. However Reco and GPP remained high in areas with large Eriophorum vaginatum biomass. In general NEE increased with thaw, but was more strongly correlated with plant biomass than thaw, indicating that higher Reco in deeply thawed areas during summer months was balanced by GPP. Summer CO2 flux across treatments fit a single quadratic relationship that captured the functional response of CO₂ flux to thaw, water table depth, and plant biomass. These results demonstrate the importance of indirect thaw effects on CO2 flux: plant growth and water table dynamics. Non-summer Reco models estimated that the area was an annual CO2 source during all years of observation. Non-summer CO2 loss in warmer, more deeply thawed soils exceeded the increases in summer GPP, and thawed tundra was a net annual CO2 source.

Aridisols are the dominant soil type in drylands, which occupy one-third of Earth's terrestrial surface. We examined controls on biogeographical patterns of Aridisol prokaryotic (bacterial and archaeal) communities at a regional scale by comparing communities from 100 Aridisols throughout the southwestern United States using high-throughput sequencing of the 16S rRNA gene. We found that microbial communities differed among global biomes and deserts of the Southwest. Differences among biomes were driven by differences in taxonomic identities, whereas differences among deserts of the Southwest were driven by differences in relative sequence abundance. Desert communities were dominated by Actinobacteria, Proteobacteria and Crenarchaeota, supporting the notion of a core set of abundant taxa in desert soils. Our findings contrast with studies showing little taxonomic overlap at the OTU level (97% sequence similarity) across large spatial scales, as we found ∼90% of taxa in at least two of the three deserts. Geographic distance structured prokaryotic communities indirectly through the influence of climate and soil properties. Structural equation modeling suggests that climate exerts a stronger influence than soil properties in shaping the composition of Aridisol microbial communities, with annual heat moisture index (an aridity metric) being the strongest climate driver. Annual heat moisture index was associated with decreased microbial diversity and richness. If the Desert Southwest becomes hotter and drier as predicted, these findings suggest that prokaryotic diversity and richness in Aridisols will decline.

Forests cover 30% of the terrestrial Earth surface and are a major component of the global carbon (C) cycle. Humans have doubled the amount of global reactive nitrogen (N), increasing deposition of N onto forests worldwide. However, other global changes—especially climate change and elevated atmospheric carbon dioxide concentrations—are increasing demand for N, the element limiting primary productivity in temperate forests, which could be reducing N availability. To determine the long-term, integrated effects of global changes on forest N cycling, we measured stable N isotopes in wood, a proxy for N supply relative to demand, on large spatial and temporal scales across the continental U.S.A. Here, we show that forest N availability has generally decl