Publications

As the permafrost region warms, its large organic carbon pool will be increasingly vulnerable to decomposition, combustion, and hydrologic export. Models predict that some portion of this release will be offset by increased production of Arctic and boreal biomass; however, the lack of robust estimates of net carbon balance increases the risk of further overshooting international emissions targets. Precise empirical or model-based assessments of the critical factors driving carbon balance are unlikely in the near future, so to address this gap, we present estimates from 98 permafrost-region experts of the response of biomass, wildfire, and hydrologic carbon flux to climate change. Results suggest that contrary to model projections, total permafrost-region biomass could decrease due to water stress and disturbance, factors that are not adequately incorporated in current models. Assessments indicate that end-of-the-century organic carbon release from Arctic rivers and collapsing coastlines could increase by 75% while carbon loss via burning could increase four-fold. Experts identified water balance, shifts in vegetation community, and permafrost degradation as the key sources of uncertainty in predicting future system response. In combination with previous findings, results suggest the permafrost region will become a carbon source to the atmosphere by 2100 regardless of warming scenario but that 65%–85% of permafrost carbon release can still be avoided if human emissions are actively reduced.

Global change models predict that high-latitude boreal forests will become increasingly susceptible to fire activity as climate warms, possibly causing a positive feedback to warming through fire-driven emissions of CO₂ into the atmosphere. However, fire-climate feedbacks depend on forest regrowth and carbon (C) accumulation over the post-fire successional interval, which is influenced by nitrogen (N) availability. To improve our understanding of post-fire C and N accumulation patterns in boreal forests, we evaluated above- and belowground C and N pools within 70 stands throughout interior Alaska, a region predicted to undergo a shift in canopy dominance as fire severity increases. Stands represented gradients in age and successional trajectory, from black spruce (<em class="EmphasisTypeItalic ">Picea mariana</em>) self-replacement to species replacement by deciduous species of trembling aspen (<em class="EmphasisTypeItalic ">Populus tremuloides</em>) and Alaska paper birch (<em class="EmphasisTypeItalic ">Betula neoalaskana</em>). Stands undergoing deciduous trajectories stored proportionally more of their C and N in aboveground stemwood and had 5–7 times faster rates of aboveground net primary productivity of trees compared to stands undergoing a black spruce trajectory, which stored more of their C and N in the soil organic layer (SOL), a thick layer of mostly undecomposed mosses. Thus, as successional trajectories shift, total C and N pool sizes will remain relatively unchanged, but there will be a trade-off in pool location and a potential increase in C and N longevity due to decreased flammability and decomposition rates of deciduous stemwood. Despite often warmer, drier conditions in deciduous compared to black spruce stands, deciduous stemwood has a C:N around 10 times higher than the black spruce SOL and often remains standing for many years with reduced exposure to fungal decomposers. Thus, a fire-driven shift in successional trajectories could cause a negative feedback to climate warming because of increased pool longevity in deciduous trajectories.

Optimality theory states that whole-tree carbon gain is maximized when leaf N and photosynthetic capacity profiles are distributed along vertical light gradients such that the marginal gain of nitrogen investment is identical among leaves. However, observed photosynthetic N gradients in trees do not follow this prediction, and the causes for this apparent discrepancy remain uncertain. Our objective was to evaluate how hydraulic limitations potentially modify crown-level optimization in Sequoiadendron giganteum (giant sequoia) trees up to 90 m tall. Leaf water potential (Ψ l ) and branch sap flow closely followed diurnal patterns of solar radiation throughout each tree crown. Minimum leaf water potential correlated negatively with height above ground, while leaf mass per area (LMA), shoot mass per area (SMA), leaf nitrogen content (%N), and bulk leaf stable carbon isotope ratios (δ13C) correlated positively with height. We found no significant vertical trends in maximum leaf photosynthesis (A), stomatal conductance (g s), and intrinsic water-use efficiency (A/g s), nor in branch-averaged transpiration (<em>E</em>L), stomatal conductance (<i><span style="font-weight: 400;">G</span></i><span style="font-weight: 400;">S</span>), and hydraulic conductance (<em>K</em>L). Adjustments in hydraulic architecture appear to partially compensate for increasing hydraulic limitations with height in giant sequoia, allowing them to sustain global maximum summer water use rates exceeding 2000 kg day−1. However, we found that leaf N and photosynthetic capacity do not follow the vertical light gradient, supporting the hypothesis that increasing limitations on water transport capacity with height modify photosynthetic optimization in tall trees.

Carbon (C) buried deep in soil (below 1 m) is often hundreds to thousands of years old, though the stability and sensitivity of this deep C to environmental change are not well understood. We examined the C dynamics in three soil horizons and their responses to changes in substrate availability in a coarse-textured sandy spodosol (0.0–0.1, 1.0–1.3, and 2.7–3.0 m deep). Substrate additions were intended to mimic an increase in root exudates and available inorganic nitrogen (N) that would follow an increase of belowground biomass at depth, as previously found in a long-term CO₂ enrichment experiment at this site. We incubated these soils for 60 days with glucose, alanine, and leaf litter, crossed with an inorganic N amendment equivalent to three times ambient concentrations. The organic substrates were isotopically labeled (¹³C), allowing us to determine the source of mineralized C and assess the priming effect. Enzyme activity increased as much as 13 times in the two deeper horizons (1.0–1.3, and 2.7–3.0 m) after the addition of the organic substrates, even though the deepest horizon had microbial biomass and microbial phospholipid fatty acids below the level of detection before the experiment. The deepest horizon (2.7–3.0 m) yielded the largest priming response under alanine, indicating that microorganisms in these soil horizons can become active in response to input of organic substrates. Inorganic N amendments significantly decreased the priming effect, suggesting that decomposition may not be N limited. However, alanine (organic N) yielded the highest priming effect at every soil depth, indicating the importance of differentiating effect of organic and inorganic N on decomposition. Distinct priming effects with depth suggest that portions of the soil profile can respond differently to organic inputs. Our findings indicate that the deep soil C pools might be more vulnerable to environmental or anthropogenic change than previously thought, potentially influencing net CO₂ exchange estimates between the land and the atmosphere.

Permafrost soils contain more than 1300 Pg of carbon (C), twice the amount of C in the atmosphere. Temperatures in higher latitudes are increasing, inducing permafrost thaw and subsequent microbial decomposition of previously frozen C, which will most likely feed back to climate warming through release of the greenhouse gases CO2 and CH4. Understanding the temperature sensitivity (Q10) and dynamics of soil organic matter (SOM) decomposition under warming is essential to predict the future state of the climate system. Alaskan tundra soils from the discontinuous permafrost zone were exposed to in situ experimental warming for two consecutive winters, increasing soil temperature by 2.3 °C down to 40 cm in the soil profile. Soils obtained at three depths (0–15, 15–25 and 45–55 cm) from the experimental warming site were incubated under aerobic conditions at 15 °C and 25 °C over 365 days in the laboratory. Carbon fluxes were measured periodically and dynamics of SOM decomposition, C pool sizes, and decay rates were estimated. Q10 was estimated using both a short-term temperature manipulation (Q10-ST) performed at 14, 100 and 280 days of incubation and via the equal C method (Q10-EC, ratio of time taken for a soil to respire a given amount of C), calculated continuously. At the same time points, functional diversities of the soil microbial communities were monitored for all incubation samples using a microbial functional gene array, GeoChip 5.0. Each array contains over 80,000 probes targeting microbial functional genes involved in biogeochemical cycling of major nutrients, remediation strategies, pathogenicity and other important environmental functions. Of these, over 20,000 probes target genes involved in the degradation of varying C substrates and can be used to quantify the relative gene abundances and functional gene diversities related to soil organic matter turnover. The slow decomposing C pool (CS), which represented close to 95% of total C in the top 25 cm soils, had a higher Q10 than the fast decomposing C pool (CF) and also dominated the total amount of C released by the end of the incubation. Overall, CS had temperature sensitivities of Q10-ST = 2.55 ± 0.03 and Q10-EC = 2.19 ± 0.13, while the CF had a temperature sensitivity of Q10-EC = 1.16 ± 0.30. In contrast to the 15 °C incubations, the 25 °C microbial communities showed reduced diversities of C-degradation functional genes in the early stage of the incubations. However, as the incubations continued the 25 °C communities more closely paralleled the 15 °C communities with respect to the detection of microbial genes utilized in the degradation of labile to recalcitrant C substrates. Two winter seasons of experimental warming did not affect the dynamics and temperature sensitivity of SOM decomposition or the microbial C-degradation genes during incubation. However, under the projected sustained warming attributable to climate change, we might expect increased contribution of CS to organic matter decomposition. Because of the higher Q10 and the large pool size of CS, increased soil organic matter release under warmer temperatures will contribute towards accelerating climate change.

<span id="yui_3_14_1_1_1470075850807_2152" class="foldable-text" data-reactid="143"><span class="text-with-line-breaks">The soils of the McMurdo Dry Valleys, Antarctica are an extreme polar desert, inhabited exclusively by microscopic taxa. This region is on the threshold of anticipated climate change, with glacial melt, permafrost thaw, and the melting of massive buried ice increasing liquid water availability and mobilizing soil nutrients. Experimental water and organic matter (OM) amendments were applied to investigate how these climate change effects may impact the soil communities. To identify active taxa and their functions, total community RNA transcripts were sequenced and annotated, and amended soils were compared with unamended control soils using differential abundance and expression analyses. Overall, taxonomic diversity declined with amendments of water and organic matter. The domain Bacteria increased with both amendments while Eukaryota declined from 38% of all taxa in control soils to 8% and 11% in water and OM amended soils, respectively. Among bacterial phyla, Actinobacteria (59%) dominated water-amended soils and Firmicutes (45%) dominated OM amended soils. Three bacterial phyla (Actinobacteria, Proteobacteria, and Firmicutes) were primarily responsible for the observed positive functional responses, while eukaryotic taxa experienced the majority (27 of 34) of significant transcript losses. These results indicated that as climate changes in this region, a replacement of endemic taxa adapted to dry, oligotrophic conditions by generalist, copiotrophic taxa is likely.</span></span>

<span id="yui_3_14_1_1_1461966615416_1099" class="foldable-text" data-reactid=".5aqlq823uo.1.0.0.0.4.1.0"><span id="yui_3_14_1_1_1461966615416_1253" class="text-with-line-breaks" data-reactid=".5aqlq823uo.1.0.0.0.4.1.0.0"><span id="yui_3_14_1_1_1461966615416_1252" data-reactid=".5aqlq823uo.1.0.0.0.4.1.0.0.$1">Balancing the joint production of multiple ecosystem services, also referred to as the ‘multifunctionality’ of an ecosystem or landscape, requires understanding of the ecological processes that produce and economic processes that evaluate those services. Here, we review the ecological tradeoffs and compatibilities among ecosystem processes that influence ecosystem multifunctionality with respect to ecosystem services, including variation in functional strategies, constraints on community assembly and direct effects of the abiotic environment. We then review how different valuation methods may alter the magnitude of tradeoffs and compatibilities in monetary terms. Among communities, functional diversity increases ecosystem multifunctionality, but community-average trait values are emerging as important drivers of ecosystem services with greater potential to produce tradeoffs when compared to functional diversity. However, research that links organismal functional strategies to community assembly rules in real, heterogeneous landscapes demonstrate that predictable tradeoffs among species do not consistently scale up to the community level, necessitating further research on trait-based community assembly in order to develop general predictive models of biotic effects on ecosystem multifunctionality. Abiotic factors are frequently incorporated into mapping assessments of multifunctionality, but the emergent tradeoffs and compatibilities in ecosystem services driven by those factors are rarely assessed, despite a number of studies that have demonstrated their clear importance in ecosystem multifunctionality. Finally, while a variety of valuation methods are used to quantify the joint production of ecosystem services, only provisioning services are typically directly valued and assumed to have fixed correlations with other ecosystem services that can lead to inaccurate valuation, and potentially inappropriate prioritisation, of multiple ecosystem services.</span></span></span>

DataONE is a federated data network focusing on earth and environmental science data. We present the provenance and search features of DataONE by means of an example involving three earth scientists who interact through a DataONE Member Node. DataONE provenance systems enable reproducible research and facilitate proper attribution of scientific results transitively across generations of derived data products.

Terrestrial leaf litter provides aquatic insects with an energy source and habitat structure, and species differences in litter can influence aquatic insect emergence. Emerging insects also provide energy to riparian predators. We hypothesized that plant genetics would influence the composition and timing of emerging insect communities among individual genotypes of Populus angustifolia varying in litter traits. We also compared the composition and timing of emerging insect communities on litter from mixed genotypes of three cross types of a hybridizing cottonwood complex: P. angustifolia, P. fremontii, and their F1 hybrids. Using litter harvested from an experimental common garden, we measured emerging insect community composition, abundance, and production for 12 weeks in large litter packs affixed with emergence traps. Five major findings emerged. (1) In support of the genetic similarity hypothesis, we found that, among P. angustifolia tree genotypes, litter from more closely related genotypes had more similar litter thickness, nitrogen concentrations, decomposition rates, and emerging insect communities. (2) Genetic similarity was not correlated with other litter traits, although the litter fungal community was a strong predictor of emerging insect communities. (3) Litter decomposition rate, which was the strongest predictor of emerging aquatic insect communities, was influenced by litter thickness, litter N, and the litter fungal community. (4) In contrast to strong community composition differences among P. angustifolia genotypes, differences in community composition between P. fremontii and P. angustifolia were only marginally significant, and communities on F1 hybrids were indistinguishable from P. angustifolia despitegenetic and litter trait differences. (5) Mixed litter packs muted the genetic effects observed in litter packs consisting of single genotypes. These results demonstrate that the genetic structure of riparian forests can affect the composition and timing of aquatic insect emergence. Because many riparian trees are clonal, including P. angustifolia, large clone size is likely to result in patches of genetically structured leaf litter that may influence the timing and composition of insect emergence within watersheds. Riparian restoration efforts incorporating different tree genotypes could also influence the biodiversity of emerging aquatic insects. Our work illustrates the importance of plant genes for community and ecosystem processes in riparian corridors.

Annual-based arable agroecosystems experience among the greatest frequency, extent and magnitude of disturbance regimes of all terrestrial ecosystems. In order to control non-crop vegetation, farmers implement tillage practices and/or utilize herbicides. These practices effectively shift the farmed ecosystems to early stages of secondary succession where they remain as long as annual crops are grown. Humanity’s long-standing dependence on a disturbance-based food and fiber producing ecosystem has resulted in degraded soil structure, unsustainable levels of soil erosion, losses of soil organic matter, low nutrient and water retention, severe weed challenges, and a less-diverse or functional soil microbiome. While no-till cropping systems have reduced some hazards like soil erosion, they remain compromised with respect to ecosystem functions like water and nutrient uptake, and carbon sequestration compared to many later successional ecosystems. Recent advances in the development of perennial grain crop species invite consideration of the ecological implications of farming grains further down the successional gradient than ever before possible. In this review, we specifically explore how the nitrogen (N) economy of a mid-successional agroecosystem might differ from early-successional annual grain ecosystems as well as native mid-successional grassland ecosystems. We present a conceptual model that compares changes in soil organic matter, net ecosystem productivity, N availability, and N retention through ecosystem succession. Research from the agronomic and ecological literatures suggest that mid-successional grain agriculture should feature several ecological functions that could greatly improve synchrony between soil N supply and crop demands; these include larger active soil organic matter pools, a more trophically complex and stable soil microbiome that facilitates higher turnover rates of available N, greater N retention due to greater assimilation and seasonal translocation by deeply rooted perennial species as well as greater microbial immobilization. Compared to native mid-successional grasslands that cycle the majority of N required to maintain productivity within the ecosystem, a mid-successional agriculture would require greater external N inputs to balance N exports in food. Synthetic N fertilizer could make up this deficit, but in the interest of maximizing ecological intensification in order to minimize inputs and associated environmental consequences, we explore making up the N deficit with biological N₂ fixation. The dominant approach to addressing problems in agriculture is to target specific shortcomings such as nutrient retention or weed invasion. Moving agriculture down the successional gradient promises to change the nature of the ecosystem itself, shifting attention from symptom to cause, such that ecological intensification and provision of a broader suite of ecosystem services happen not in spite of, but as a consequence of agriculture.

Both geomorphic setting and dynamic environmental variables influence riverine wetland vegetation distributions. Most studies of species distributions in riverine systems emphasize either hydrological variability or geomorphic controls, but rarely consider the interaction between the two. It is unknown whether and to what extent the relationship between the geomorphic template and species distribution is modified by fluctuating environmental conditions. This study examines how spatial patterns of riverine wetlands in a desert stream change in response to environmental shifts brought about by interannual variability in the hydrologic regime. We surveyed wetland spatial distribution and measured its abundance every June over 5 years (2009–2013) by recording patch size and presence/absence of five wetland plant species along the 12-km main stem of Sycamore Creek, Arizona, U.S.A. The study period encompassed a very large flood in January 2010, a wet year (2010), two average years (2009 and 2013) and two extremely dry years (2011 and 2012). We used a Bayesian statistical approach to analyse the relationship between geomorphic variables and wetland distribution under different hydrological conditions. The geomorphic variables provided much greater explanatory power in dry years than in average to wet years. Hydrological conditions modified the interactions between geomorphic template and species distribution. Annual hydrological conditions affected the direction (i.e. positive or negative effect) and magnitude (i.e. the size and significance level of an effect) of these interactions, both of which gave rise to spatial patterns of wetlands. Ecosystem temporal variability, such as inter-annual and multi-year hydrological variability and longer-term ecosystem state changes, triggered complex species responses. Synthesis. The effect of geomorphic setting on stream wetland plant distribution in this desert system is conditioned on the temporal variability in hydrology among years. Temporal transferability of the relationship between geomorphology and species distributions is therefore questionable.

Increasing rates of permafrost thaw in boreal peatlands are converting conifer forests to waterlogged open wetlands. Permafrost thaw increases soil nitrogen (N) availability, but it is unclear whether such changes are due solely to changes in surface soil N mineralization or N mobilization from thawing permafrost soils at depth. We examined plant species composition and N availability along triplicate permafrost thaw gradients in Alaskan peatlands. Each gradient comprised four community types including: 1) a permafrost peatland with intact permafrost; 2) a drunken forest experiencing active thaw; 3) a moat representing initial complete thaw; and 4) a collapse scar bog representing several decades of post-thaw succession. Concentrations of dissolved organic (DON) and inorganic N (DIN) in the upper 60 cm of soil increased along the permafrost thaw gradients. The drunken forest had the greatest mean concentrations of total dissolved N relative to the other community types, primarily due to greater concentrations of large molecular DON. The moat and collapse bog had significantly greater inorganic N concentrations than the permafrost or drunken forest, suggesting that changes in N availability are not a short-term effect, but can be sustained for decades or centuries. Across all plant community types, DIN and DON concentrations increased with soil depth during maximum seasonal ice thaw (September), suggesting that deeper soil horizons are important reservoirs of N post-thaw. Vegetation responses to permafrost thaw included changes in plant community composition shifting from upland forest species to hydrophilic vegetation with deeper rooting profiles in the collapse scar bogs, and changes in foliar N and δ15N values. N concentrations in plant foliage and litterfall increased with concentrations of DIN during collapse bog succession, suggesting that plants are utilizing additional mineralized N. Synthesis: Our results suggest that the conversion of forest to wetlands associated with permafrost thaw in boreal lowlands increases N availability, at least in part by increasing turnover of deep soil organic matter. Plants appear to utilize these additional deeper N sources over timescales of years to centuries following permafrost thaw.

The land surface provides a boundary condition to atmospheric forward and flux inversion models. These models require prior estimates of CO₂ fluxes at relatively high temporal resolutions (e.g., 3-hourly) because of the high frequency of atmospheric mixing and wind heterogeneity. However, land surface model CO₂ fluxes are often provided at monthly time steps, typically because the land surface modeling community focuses more on time steps associated with plant phenology (e.g., seasonal) than on sub-daily phenomena. Here, we describe a new dataset created from 15 global land surface models and 4 ensemble products in the Multi-scale Synthesis and Terrestrial Model Intercomparison Project (MsTMIP), temporally downscaled from monthly to 3-hourly output. We provide 3-hourly output for each individual model over 7 years (2004–2010), as well as an ensemble mean, a weighted ensemble mean, and the multi-model standard deviation. Output is provided in three different spatial resolutions for user preferences: 0.5°  ×  0.5°, 2.0°  ×  2.5°, and 4.0°  ×  5.0° (latitude  ×  longitude).

Invasive, non-native plant species can alter soil microbial communities in ways that contribute to their persistence. While most studies emphasize mycorrhizal fungi, invasive plants also may influence communities of dark septate fungi (DSF), common root endophytes that can function like mycorrhizas. We tested the hypothesis that a widespread invasive plant in the western United States, cheatgrass (Bromus tectorum), influenced the abundance and community composition of DSF by examining the roots and rhizosphere soils of cheatgrass and two native plant species in cheatgrass invaded and non-invaded areas of sagebrush steppe. We focused on cheatgrass because it is negatively affected by mycorrhizal fungi and colonized by DSF. We found that DSF root colonization and operational taxonomic (OTU) richness were significantly higher in sagebrush (Artemisia tridentata) and rice grass (Achnatherum hymenoides) from invaded areas than non-invaded areas. Cheatgrass roots had similar levels of DSF colonization and OTU richness as native plants. The community composition of DSF varied with invasion in the roots and soils of native species and among the roots of the three plant species in invaded areas. The substantial changes in DSF we observed following cheatgrass invasion argue for comparative studies of DSF function in native and non-native plant species.

<span id="yui_3_14_1_1_1461105258100_1608" class="foldable-text" data-reactid=".qoiwja49og.1.0.0.0.4.1.0"><span id="yui_3_14_1_1_1461105258100_1773" class="text-with-line-breaks" data-reactid=".qoiwja49og.1.0.0.0.4.1.0.0"><span id="yui_3_14_1_1_1461105258100_1772" data-reactid=".qoiwja49og.1.0.0.0.4.1.0.0.$1">The permafrost component of the cryosphere is changing dramatically, but the permafrost region is not well monitored and the consequences of change are not well understood. Changing permafrost interacts with ecosystems and climate on various spatial and temporal scales. The feedbacks resulting from these interactions range from local impacts on topography, hydrology, and biology to complex influences on global scale biogeochemical cycling. This review contributes to this focus issue by synthesizing its 28 multidisciplinary studies which provide field evidence, remote sensing observations, and modeling results on various scales. We synthesize study results from a diverse range of permafrost landscapes and ecosystems by reporting key observations and modeling outcomes for permafrost thaw dynamics, identifying feedbacks between permafrost and ecosystem processes, and highlighting biogeochemical feedbacks from permafrost thaw. We complete our synthesis by discussing the progress made, stressing remaining challenges and knowledge gaps, and providing an outlook on future needs and research opportunities in the study of permafrost–ecosystem–climate interactions.</span></span></span>

<div id="sec-1" class="subsection"> <p id="p-1"><strong>PREMISE OF THE STUDY:</strong> The aboveground tissues of plants host numerous, ecologically important fungi, yet patterns in the spatial distribution of these fungi remain little known. Forest canopies in particular are vast reservoirs of fungal diversity, but intracrown variation in fungal communities has rarely been explored. Knowledge of how fungi are distributed throughout tree crowns will contribute to our understanding of interactions between fungi and their host trees and is a first step toward investigating drivers of community assembly for plant-associated fungi. Here we describe spatial patterns in fungal diversity within crowns of the world’s tallest trees, coast redwoods (<em>Sequoia sempervirens</em>).</p> </div> <div id="sec-2" class="subsection"> <p id="p-2"><strong>METHODS:</strong> We took a culture-independent approach, using the Illumina MiSeq platform, to characterize the fungal assemblage at multiple heights within the crown across the geographical range of the coast redwood.</p> </div> <div id="sec-3" class="subsection"> <p id="p-3"><strong>KEY RESULTS:</strong> Within each tree surveyed, we uncovered evidence for vertical stratification in the fungal community; different portions of the tree crown harbored different assemblages of fungi. We also report between-tree variation in the fungal community within redwoods.</p> </div> <div id="sec-4" class="subsection"> <p id="p-4"><strong>CONCLUSIONS:</strong> Our results suggest the potential for vertical stratification of fungal communities in the crowns of other tall tree species and should prompt future study of the factors giving rise to this stratification.</p> </div>

Identification of microorganisms that facilitate the cycling of nutrients in freshwater is paramount to understanding how these ecosystems function. Here, we identify growing aquatic bacteria using <span class="math-equation-construct" data-equation-construct="true"><span class="math-equation-image" data-equation-image="true"><img class="inlineGraphic" src="http://onlinelibrary.wiley.com/store/10.1111/1758-2229.12475/asset/equation/emi412475-math-0002.png?v=1&amp;s=800650689e2f28b7ca342149c1b25838931bf5b9" alt="math formula" /></span></span> quantitative stable isotope probing. During 8 day incubations in 97 atom %<span class="math-equation-construct" data-equation-construct="true"><span class="math-equation-image" data-equation-image="true"><img class="inlineGraphic" src="http://onlinelibrary.wiley.com/store/10.1111/1758-2229.12475/asset/equation/emi412475-math-0003.png?v=1&amp;s=b511335828cf868c20f2f0a4a86a7b4b83a09dc9" alt="math formula" /></span></span>, 54% of the taxa grew. The most abundant phyla among growing taxa were <em>Proteobacteria</em> (45%), <em>Bacteroidetes</em> (30%) and <em>Firmicutes</em> (10%). Taxa differed in isotopic enrichment, reflecting variation in DNA replication of bacterial populations. At the class level, the highest atom fraction excess was observed for OPB41 and δ-<em>Proteobacteria</em>. There was no linear relationship between ¹⁸O incorporation and abundance of taxa. δ-<em>Proteobacteria</em> and OPB41 were not abundant, yet the DNA of both taxa was highly enriched in ¹⁸O. <em>Bacteriodetes</em>, in contrast, were abundant but not highly enriched. Our study shows that a large proportion of the bacterial taxa found on decomposing leaf litter grew slowly, and several low abundance taxa were highly enriched. These findings indicating that rare organisms may be important for the decomposition of leaf litter in streams, and that quantitative stable isotope probing with <span class="math-equation-construct" data-equation-construct="true"><span class="math-equation-image" data-equation-image="true"><img class="inlineGraphic" src="http://onlinelibrary.wiley.com/store/10.1111/1758-2229.12475/asset/equation/emi412475-math-0004.png?v=1&amp;s=1fde9faebe8b6460b636559f2fe2464644157799" alt="math formula" /></span></span> can be used to advance our understanding of microorganisms in freshwater by identifying species that are growing in complex communities.

<div id="yui_3_14_1_1_1463605085348_1720" class="selectable" data-canvas-width="91.9909420168124"><strong>Background:</strong> Vegetation change in high latitude tundra ecosystems is expected to accelerate due to increased wild-fire activity. High-severity fires increase the availability of mineral soil seedbeds, which facilitates recruitment, yet fire also alters soil microbial composition, which could significantly impact seedling establishment.</div> <div id="yui_3_14_1_1_1463605085348_1733" class="selectable" data-canvas-width="56.02443236414706"><strong>Results:</strong> We investigated the effects of fire severity on soil biota and associated effects on plant performance for two plant species predicted to expand into Arctic tundra. We inoculated seedlings in a growth chamber experiment with soils collected from the largest tundra fire recorded in the Arctic and used molecular tools to characterize root-associated fungal communities. Seedling biomass was significantly related to the composition of fungal inoculum. Biomass decreased as fire severity increased and the proportion of pathogenic fungi increased.</div> <div class="selectable" data-canvas-width="91.47017517924458"><strong>Conclusions:</strong> Our results suggest that effects of fire severity on soil biota reduces seedling performance and thus we hypothesize that in certain ecological contexts fire-severity effects on plant–fungal interactions may dampen the expected increases in tree and shrub establishment after tundra fire.</div> <div class="selectable" data-canvas-width="75.30960428439917"><strong>Keywords:</strong> Alnus viridis, Arctic tundra, ARISA, Climate change, Fire severity, Fungal internal transcribed spacer (ITS), Picea mariana, Shrub expansion, Treeline</div> &nbsp;

<div id="ASec1" class="AbstractSection"> <h3 class="Heading">Context</h3> <p id="Par1" class="Para">Forecasting the expansion of forest into Alaska tundra is critical to predicting regional ecosystem services, including climate feedbacks such as carbon storage. Controls over seedling establishment govern forest development and migration potential. Ectomycorrhizal fungi (EMF), obligate symbionts of all Alaskan tree species, are particularly important to seedling establishment, yet their significance to landscape vegetation change is largely unknown.</p> </div> <div id="ASec2" class="AbstractSection"> <h3 class="Heading">Objective</h3> <p id="Par2" class="Para">We used ALFRESCO, a landscape model of wildfire and vegetation dynamics, to explore whether EMF inoculum potential influences patterns of tundra afforestation and associated flammability.</p> </div> <div id="ASec3" class="AbstractSection"> <h3 class="Heading">Methods</h3> <p id="Par3" class="Para">Using two downscaled CMIP3 general circulation models (ECHAM5 and CCCMA) and a mid-range emissions scenario (A1B) at a 1 km² resolution, we compared simulated tundra afforestation rates and flammability from four parameterizations of EMF effects on seedling establishment and growth from 2000 to 2100.</p> </div> <div id="ASec4" class="AbstractSection"> <h3 class="Heading">Results</h3> <p id="Par4" class="Para">Modeling predicted an 8.8–18.2 % increase in forest cover from 2000 to 2100. Simulations that explicitly represented landscape variability in EMF inoculum potential showed a reduced percent change afforestation of up to a 2.8 % due to low inoculum potential limiting seedling growth. This reduction limited fuel availability and thus, cumulative area burned. Regardless of inclusion of EMF effects in simulations, landscape flammability was lower for simulations driven by the wetter and cooler CCCMA model than the warmer and drier ECHAM5 model, while tundra afforestation was greater.</p> </div> <div id="ASec5" class="AbstractSection"> <h3 class="Heading">Conclusions</h3> <p id="Par5" class="Para">Results suggest abiotic factors are the primary driver of tree migration. Simulations including EMF effects, a biotic factor, yielded more conservative estimates of land cover change across Alaska that better-matched empirical estimates from the previous century.</p> </div>

Human impacts on biogeochemical cycles are evident around the world, from changes to forest structure and function due to atmospheric deposition, to eutrophication of surface waters from agricultural effluent, and increasing concentrations of carbon dioxide (CO₂) in the atmosphere. The National Ecological Observatory Network (NEON) will contribute to understanding human effects on biogeochemical cycles from local to continental scales. The broad NEON biogeochemistry measurement design focuses on measuring atmospheric deposition of reactive mineral compounds and CO₂ fluxes, ecosystem carbon (C) and nutrient stocks, and surface water chemistry across 20 eco-climatic domains within the United States for 30 yr. Herein, we present the rationale and plan for the ground-based measurements of C and nutrients in soils and plants based on overarching or “high-level” requirements agreed upon by the National Science Foundation and NEON. The resulting design incorporates early recommendations by expert review teams, as well as recent input from the larger natural sciences community that went into the formation and interpretation of the requirements, respectively. NEON's efforts will focus on a suite of data streams that will enable end-users to study and predict changes to biogeochemical cycling and transfers within and across air, land, and water systems at regional to continental scales. At each NEON site, there will be an initial, one-time effort to survey soil properties to 1 m (including soil texture, bulk density, pH, baseline chemistry) and vegetation community structure and diversity. A sampling program will follow, focused on capturing long-term trends in soil C, nitrogen (N), and sulfur stocks, isotopic composition (of C and N), soil N transformation rates, phosphorus pools, and plant tissue chemistry and isotopic composition (of C and N). To this end, NEON will conduct extensive measurements of soils and plants within stratified random plots distributed across each site. The resulting data will be a new resource for members of the scientific community interested in addressing questions about long-term changes in continental-scale biogeochemical cycles, and is predicted to inspire further process-based research.

Invasive species alter ecosystems, threaten native and endangered species, and have negative economic impacts. Knowing where invading individuals are from and when they arrive to a new site can guide management. Here, we evaluated how well the stable hydrogen isotope composition (δ2H) records the recent origin and time since arrival of specimens of the invasive Japanese beetle (Popillia japonica Newman) captured near the Portland International Airport (Oregon, U.S.A.). The δ2H of Japanese beetle specimens collected from sites across the contiguous U.S.A. reflected the δ2H of local precipitation, a relationship similar to that documented for other organisms, and one confirming the utility of δ2H as a geographic fingerprint. Within weeks after experimental relocation to a new isotopic environment, the δ2H of beetles changed linearly with time, demonstrating the potential for δ2H to also mark the timing of arrival to a new location. We used a hierarchical Bayesian model to estimate the recent geographical origin and timing of arrival of each specimen based on its δ2H value. The geographic resolution was broad, with values consistent with multiple regions of origin in the eastern U.S.A., slightly favoring the southeastern U.S.A. as the more likely source. Beetles trapped from 2007–2010 had arrived 30 or more days prior to trapping, whereas the median time since arrival declined to 3–7 days for beetles trapped from 2012–2014. This reduction in the time between arrival and trapping at the Portland International Airport supports the efficacy of trapping and spraying to prevent establishment. More generally, our analysis shows how stable isotopes can serve as sentinels of biological invasions, verifying the efficacy of control measures, or, alternatively, indicating when those measures show signs of failure.

Changing climate and a legacy of fire-exclusion have increased the probability of high-severity wildfire, leading to an increased risk of forest carbon loss in ponderosa pine forests in the southwestern USA. Efforts to reduce high-severity fire risk through forest thinning and prescribed burning require both the removal and emission of carbon from these forests, and any potential carbon benefits from treatment may depend on the occurrence of wildfire. We sought to determine how forest treatments alter the effects of stochastic wildfire events on the forest carbon balance. We modeled three treatments (control, thin-only, and thin and burn) with and without the occurrence of wildfire. We evaluated how two different probabilities of wildfire occurrence, 1% and 2% per year, might alter the carbon balance of treatments. In the absence of wildfire, we found that thinning and burning treatments initially reduced total ecosystem carbon (TEC) and increased net ecosystem carbon balance (NECB). In the presence of wildfire, the thin and burn treatment TEC surpassed that of the control in year 40 at 2%/yr wildfire probability, and in year 51 at 1%/yr wildfire probability. NECB in the presence of wildfire showed a similar response to the no-wildfire scenarios: both thin-only and thin and burn treatments increased the C sink. Treatments increased TEC by reducing both mean wildfire severity and its variability. While the carbon balance of treatments may differ in more productive forest types, the carbon balance benefits from restoring forest structure and fire in southwestern ponderosa pine forests are clear.

The seasonal-cycle amplitude (SCA) of the atmosphere–ecosystem carbon dioxide (CO₂) exchange rate is a useful metric of the responsiveness of the terrestrial biosphere to environmental variations. It is unclear, however, what underlying mechanisms are responsible for the observed increasing trend of SCA in atmospheric CO₂ concentration. Using output data from the Multi-scale Terrestrial Model Intercomparison Project (MsTMIP), we investigated how well the SCA of atmosphere–ecosystem CO₂ exchange was simulated with 15 contemporary terrestrial ecosystem models during the period 1901–2010. Also, we made attempt to evaluate the contributions of potential mechanisms such as atmospheric CO₂, climate, land-use, and nitrogen deposition, through factorial experiments using different combinations of forcing data. Under contemporary conditions, the simulated global-scale SCA of the cumulative net ecosystem carbon flux of most models was comparable in magnitude with the SCA of atmospheric CO₂ concentrations. Results from factorial simulation experiments showed that elevated atmospheric CO₂ exerted a strong influence on the seasonality amplification. When the model considered not only climate change but also land-use and atmospheric CO₂changes, the majority of the models showed amplification trends of the SCAs of photosynthesis, respiration, and net ecosystem production (+0.19 % to +0.50 % yr⁻¹). In the case of land-use change, it was difficult to separate the contribution of agricultural management to SCA because of inadequacies in both the data and models. The simulated amplification of SCA was approximately consistent with the observational evidence of the SCA in atmospheric CO₂ concentrations. Large inter-model differences remained, however, in the simulated global tendencies and spatial patterns of CO₂ exchanges. Further studies are required to identify a consistent explanation for the simulated and observed amplification trends, including their underlying mechanisms. Nevertheless, this study implied that monitoring of ecosystem seasonality would provide useful insights concerning ecosystem dynamics.

<div id="yui_3_14_1_1_1461088040208_3844" class="selectable" data-canvas-width="886.7532679738565">How soil microbial communities contrast with respect to taxonomic and functional composition within and between ecosystems remains an unresolved question that is central to predicting how global anthropogenic change will affect soil functioning and services. In particular, it remains unclear how small-scale observations of soil communities based on the typical volume sampled (1-2 grams) are generalizable to ecosystem- scale responses and processes. This is especially relevant for remote, northern latitude soils, which are challenging to sample and are also thought to be more vulnerable to climate change compared to temperate soils. Here, we employed well replicated shotgun metagenome and 16S rRNA gene amplicon sequencing to characterize community composition and metabolic potential in Alaskan tundra soils, combining our own datasets with those publically available from distant tundra and temperate grassland and agriculture habitats. We found that the abundance of many taxa and metabolic functions differed substantially between tundra soil metagenomes relative to those from temperate soils, and that a high degree of OTU-sharing exists between tundra locations. Tundra soils were an order of magnitude less complex than their temperate counterparts, allowing for near- complete coverage of microbial community richness (~92% breadth) by sequencing, and the recovery of twenty-seven high-quality, almost complete (&gt;80% completeness) population bins. These population bins, collectively, made up to ~10% of the metagenomic datasets, and represented diverse taxonomic groups and metabolic lifestyles tuned toward sulfur cycling, hydrogen metabolism, methanotrophy, and organic matter oxidation. Several population bins, including members of Acidobacteria, Actinobacteria, and Proteobacteria, were also present in geographically distant (~100-530 km apart) tundra habitats  (full genome representation and up to 99.6% genome-derived average nucleotide identity). Collectively, our results revealed that Alaska tundra microbial communities are less diverse and more homogenous across spa tial scales than previously anticipated, and provided DNA sequencesof abundant populations and genes that would be relevant for future studies of the effects of environmental change on tundra ecosystems.</div> &nbsp;

Dams impound the majority of rivers and provide important societal benefits, especially daily water releases that enable on-peak hydroelectricity generation. Such “hydropeaking” is common worldwide, but its downstream impacts remain unclear. We evaluated the response of aquatic insects, a cornerstone of river food webs, to hydropeaking using a life history–hydrodynamic model. Our model predicts that aquatic-insect abundance will depend on a basic life-history trait—adult egg-laying behavior—such that open-water layers will be unaffected by hydropeaking, whereas ecologically important and widespread river-edge layers, such as mayflies, will be extirpated. These predictions are supported by a more-than-2500-sample, citizen-science data set of aquatic insects from the Colorado River in the Grand Canyon and by a survey of insect diversity and hydropeaking intensity across dammed rivers of the Western United States. Our study reveals a hydropeaking-related life history bottleneck that precludes viable populations of many aquatic insects from inhabiting regulated rivers.

Disturbances affect almost all terrestrial ecosystems, but it has been difficult to identify general principles regarding these influences. To improve our understanding of the long-term consequences of disturbance on terrestrial ecosystems, we present a conceptual framework that analyzes disturbances by their biogeochemical impacts. We posit that the ratio of soil and plant nutrient stocks in mature ecosystems represents a characteristic site property. Focusing on nitrogen (N), we hypothesize that this partitioning ratio (soil N: plant N) will undergo a predictable trajectory after disturbance. We investigate the nature of this partitioning ratio with three approaches: (1) nutrient stock data from forested ecosystems in North America, (2) a process-based ecosystem model, and (3) conceptual shifts in site nutrient availability with altered disturbance frequency. Partitioning ratios could be applied to a variety of ecosystems and successional states, allowing for improved temporal scaling of disturbance events. The generally short-term empirical evidence for recovery trajectories of nutrient stocks and partitioning ratios suggests two areas for future research. First, we need to recognize and quantify how disturbance effects can be accreting or depleting, depending on whether their net effect is to increase or decrease ecosystem nutrient stocks. Second, we need to test how altered disturbance frequencies from the present state may be constructive or destructive in their effects on biogeochemical cycling and nutrient availability. Long-term studies, with repeated sampling of soils and vegetation, will be essential in further developing this framework of biogeochemical response to disturbance.

<section id="jvs12377-sec-0001" class="article-section article-body-section"> <h3>Aim</h3> Vertical root distributions (‘profiles’) influence plant water use and productivity, and the differentiation of root profiles between neighbouring species can indicate the degree of plant interactions and niche partitioning. However, quantifying multiple species' root distributions in the field can be labour intensive and highly destructive to the soil and plants. We describe a method for partitioning multiple species roots using minimally destructive methods to determine if neighbour interactions alter the root profile of a common desert shrub, <em>Larrea tridentata</em>(creosote bush). </section><section id="jvs12377-sec-0002" class="article-section article-body-section"> <h3>Location</h3> Sonoran Desert, central Arizona, USA. </section><section id="jvs12377-sec-0003" class="article-section article-body-section"> <h3>Methods</h3> We obtained root and soil samples from soil cores collected around <em>Larrea</em> growing alone and next to three different neighbouring species. Bulk root mass was measured for each soil sample, and <em>Larrea</em> and neighbouring species root presence was determined with molecular identification methods. Water extracted from the soil and paired stem samples was analysed for its stable isotope composition (D and ¹⁸O). Species-specific (i.e. <em>Larrea</em> and neighbouring species) root biomass and fractional active root area were estimated through a hierarchical statistical modelling approach that combined all three data sets and accounted for detection errors. </section><section id="jvs12377-sec-0004" class="article-section article-body-section"> <h3>Results</h3> The combined data model successfully partitioned <em>Larrea</em> root biomass from neighbouring plants and provided biologically relevant estimates of rooting profiles with greater certainty than individual analyses of each data source. The data model results indicate that plant neighbours alter <em>Larrea</em>'s root profile; <em>Larrea</em> growing under tree species had significantly higher root biomass in shallow soil layers than <em>Larre</em>a growing alone. </section><section id="jvs12377-sec-0005" class="article-section article-body-section"> <h3>Conclusions</h3> Our framework requires minimally destructive sampling methods, and accounts for sampling errors associated with different methods. We demonstrate the utility of our approach with a common desert shrub species, which illustrated that plant neighbours can alter the <em>Larrea</em>vertical root profile. Our approach is useful in problematic study systems fraught with sample collection issues or supporting species with inhibitory compounds that prohibit the use of more sophisticated molecular methods to identify the presence of other species' roots. </section>

<span id="yui_3_14_1_1_1470075122251_2130" class="foldable-text" data-reactid="113"><span class="text-with-line-breaks">With increasing air temperatures and changing precipitation patterns forecast for the Arctic over the coming decades, the thawing of ice-rich permafrost is expected to increasingly alter hydrological conditions by creating mosaics of wetter and drier areas. The objective of this study is to investigate how 10 years of lowered water table depths of wet floodplain ecosystems would affect CO2 fluxes measured using a closed chamber system, focusing on the role of long-term changes in soil thermal characteristics and vegetation community structure. Drainage diminishes the heat capacity and thermal conductivity of organic soil, leading to warmer soil temperatures in shallow layers during the daytime and colder soil temperatures in deeper layers, resulting in a reduction in thaw depths. These soil temperature changes can intensify growing-season heterotrophic respiration by up to 95 %. With decreased autotrophic respiration due to reduced gross primary production under these dry conditions, the differences in ecosystem respiration rates in the present study were 25%. We also found that a decade-long drainage installation significantly increased shrub abundance, while decreasing Eriophorum angustifolium abundance resulted in Carex sp. dominance. These two changes had opposing influences on gross primary production during the growing season: while the increased abundance of shrubs slightly increased gross primary production, the replacement of E. angustifolium by Carex sp. significantly decreased it. With the effects of ecosystem respiration and gross primary production combined, net CO2 uptake rates varied between the two years, which can be attributed to Carex-dominated plots' sensitivity to climate. However, underlying processes showed consistent patterns: 10 years of drainage increased soil temperatures in shallow layers and replaced E. angustifolium by Carex sp., which increased CO2 emission and reduced CO2 uptake rates. During the non-growing season, drainage resulted in 4 times more CO2 emissions, with high sporadic fluxes; these fluxes were induced by soil temperatures, E. angustifolium abundance, and air pressure.</span></span>

Projecting the response of forests to changing climate requires understanding how biotic and abiotic controls on tree growth will change over time. As temperature and interannual precipitation variability increase, the overall forest response is likely to be influenced by species-specific responses to changing climate. Management actions that alter composition and density may help buffer forests against the effects of changing climate, but may require tradeoffs in ecosystem services. We sought to quantify how projected changes in climate and different management regimes would alter the composition and productivity of Puget Lowland forests in Washington State, USA. We modeled forest responses to four treatments (control, burn-only, thin-only, thin-and-burn) under five different climate scenarios: baseline climate (historical) and projections from two climate models (CCSM4 and CNRM-CM5), driven by moderate (RCP 4.5) and high (RCP 8.5) emission scenarios. We also simulated the effects of intensive management to restore Oregon white oak woodlands (Quercus garryana) for the western gray squirrel (Sciurus griseus) and quantified the effects of these treatments on the probability of oak occurrence and carbon sequestration. At the landscape scale we found little difference in carbon dynamics between baseline and moderate emission scenarios. However, by late-century under the high emission scenario, climate change reduced forest productivity and decreased species richness across a large proportion of the study area. Regardless of the climate scenario, we found that thinning and burning treatments increased the carbon sequestration rate because of decreased resource competition. However, increased productivity with management was not sufficient to prevent an overall decline in productivity under the high emission scenario. We also found that intensive oak restoration treatments were effective at increasing the probability of oak presence and that the limited extent of the treatments resulted in small declines in total ecosystem carbon across the landscape as compared to the thin-and-burn treatment. Our research suggests that carbon dynamics in this system under the moderate emission scenario may be fairly consistent with the carbon dynamics under historical climate, but that the high emission scenario may alter the successional trajectory of these forests.

Soil microbial diversity is huge and a few grams of soil contain more bacterial taxa than there are bird species on Earth. This high diversity often makes predicting the responses of soil bacteria to environmental change intractable and restricts our capacity to predict the responses of soil functions to global change. Here, using a long-term field experiment in a California grassland, we studied the main and interactive effects of three global change factors (increased atmospheric CO2 concentration, precipitation and nitrogen addition, and all their factorial combinations, based on global change scenarios for central California) on the potential activity, abundance and dominant taxa of soil nitrite-oxidizing bacteria (NOB). Using a trait-based model, we then tested whether categorizing NOB into a few functional groups unified by physiological traits enables understanding and predicting how soil NOB respond to global environmental change. Contrasted responses to global change treatments were observed between three main NOB functional types. In particular, putatively mixotrophic <i>Nitrobacter</i>, rare under most treatments, became dominant under the ‘High CO2CNitrogenCPrecipitation’ treatment. The mechanistic trait-based model, which simulated ecological niches of NOB types consistent with previous ecophysiological reports, helped predicting the observed effects of global change on NOB and elucidating the underlying biotic and abiotic controls. Our results are a starting point for representing the overwhelming diversity of soil bacteria by a few functional types that can be incorporated into models of terrestrial ecosystems and biogeochemical processes.

<section id="abstract" class="article-section article-section--abstract"> <div class="article-section__content mainAbstract"> Soil carbon (C) is a critical component of Earth system models (ESMs), and its diverse representations are a major source of the large spread across models in the terrestrial C sink from the third to fifth assessment reports of the Intergovernmental Panel on Climate Change (IPCC). Improving soil C projections is of a high priority for Earth system modeling in the future IPCC and other assessments. To achieve this goal, we suggest that (1) model structures should reflect real-world processes, (2) parameters should be calibrated to match model outputs with observations, and (3) external forcing variables should accurately prescribe the environmental conditions that soils experience. First, most soil C cycle models simulate C input from litter production and C release through decomposition. The latter process has traditionally been represented by first-order decay functions, regulated primarily by temperature, moisture, litter quality, and soil texture. While this formulation well captures macroscopic soil organic C (SOC) dynamics, better understanding is needed of their underlying mechanisms as related to microbial processes, depth-dependent environmental controls, and other processes that strongly affect soil C dynamics. Second, incomplete use of observations in model parameterization is a major cause of bias in soil C projections from ESMs. Optimal parameter calibration with both pool- and flux-based data sets through data assimilation is among the highest priorities for near-term research to reduce biases among ESMs. Third, external variables are represented inconsistently among ESMs, leading to differences in modeled soil C dynamics. We recommend the implementation of traceability analyses to identify how external variables and model parameterizations influence SOC dynamics in different ESMs. Overall, projections of the terrestrial C sink can be substantially improved when reliable data sets are available to select the most representative model structure, constrain parameters, and prescribe forcing fields. </div> </section>&nbsp; <section class="article-section align-center"></section>

A significant portion of the large amount of carbon (C) currently stored in soils of the permafrost region in the Northern Hemisphere has the potential to be emitted as the greenhouse gases CO2 and CH4 under a warmer climate. In this study we evaluated the variability in the sensitivity of permafrost and C in recent decades among land surface model simulations over the permafrost region between 1960 and 2009. The 15 model simulations all predict a loss of near-surface permafrost (within 3 m) area over the region, but there are large differences in the magnitude of the simulated rates of loss among the models (0.2 to 58.8 × 103 km2 yr−1). Sensitivity simulations indicated that changes in air temperature largely explained changes in permafrost area, although interactions among changes in other environmental variables also played a role. All of the models indicate that both vegetation and soil C storage together have increased by 156 to 954 Tg C yr−1 between 1960 and 2009 over the permafrost region even though model analyses indicate that warming alone would decrease soil C storage. Increases in gross primary production (GPP) largely explain the simulated increases in vegetation and soil C. The sensitivity of GPP to increases in atmospheric CO2 was the dominant cause of increases in GPP across the models, but comparison of simulated GPP trends across the 1982–2009 period with that of a global GPP data set indicates that all of the models overestimate the trend in GPP. Disturbance also appears to be an important factor affecting C storage, as models that consider disturbance had lower increases in C storage than models that did not consider disturbance. To improve the modeling of C in the permafrost region, there is the need for the modeling community to standardize structural representation of permafrost and carbon dynamics among models that are used to evaluate the permafrost C feedback and for the modeling and observational communities to jointly develop data sets and methodologies to more effectively benchmark models.

Monsoon precipitation in the arid southwestern United States is an important driver of ecosystem productivity, delivering up to 50% of annual precipitation during the summer months. These sporadic rainfall events typify drying-rewetting cycles and impose a physiological stress on the soil microbial communities responsible for carbon and nutrient cycling. As one aspect of climate change is an intensification of the hydrologic cycle, understanding how soil microbial communities and the processes they mediate are impacted by moisture fluctuations is increasingly important. We performed a month-long watering manipulation in the field and characterized bacterial and fungal communities across five time points using high-throughput sequencing. Watering treatment had a significant impact on fungal community composition, and there was a trend toward decreased fungal diversity and OTU richness in watered plots. In contrast, no significant differences were observed in bacterial communities between watered and control plots nor among sampling times. These findings suggest that fungi are more sensitive than bacteria to changes in soil moisture.

Ecosystem responses to the increasing warming in recent decades across North America (NA) are spatially heterogeneous and partly uncertain. Here we examined the spatial and temporal variability of warming across different eco-regions of NA using long-term (1979–2010) climate data (North America Regional Reanalysis (NARR)) with 3-hourly time-step and 0.25° × 0.25° spatial resolution and run a comprehensive mathematical process model, <em>ecosys</em> to study the impacts of this variability in warming on gross primary productivity (GPP). In a site scale test of model results, annual GPP modeled for pixels which corresponded to the locations of 20 eddy covariance flux towers correlated well (<em>R</em>² = 0.76) with annual GPP derived from the towers in 2005. At continental scale, long-term annual average modeled GPP correlated well (geographically weighed regression <em>R</em>² = 0.8) with MODIS GPP. GPP modeled in eastern temperate forests and most areas with lower mean annual air temperature (<em>T</em>_a), such as those in northern forests and Taiga, increased due to early spring and late autumn warming observed in NARR and these eco-regions contributed 92% of the increases in NA GPP over the last three decades. However, modeled GPP declined in most southwestern regions of NA (accounting &gt;50% of the ecosystems with declining GPP), due to water stress from rising <em>T</em>_a and declining precipitation, implying that further warming and projected dryness in this region could further reduce NA carbon uptake. Overall, NA modeled GPP increased by 5.8% in the last 30 years, with a positive trend of +0.012 ± 0.01 Pg C yr⁻¹ and a range of −1.16 to +0.87 Pg C yr⁻¹ caused by interannual variability of GPP from the long-term (1980–2010) mean. This variability was the greatest in southwest of US and part of the Great Plains, which could be as a result of frequent El Niño–Southern Oscillation’ events that led to major droughts.

We investigated the phenology of adult angel lichen moths (<i>Cisthene angelus</i>) along a 364-km long segment of the Colorado River in Grand Canyon, Arizona, USA, using a unique data set of 2,437 light-trap samples collected by citizen scientists. We found that adults of <i>C. angelus</i> were bivoltine from 2012 to 2014. We quantified plasticity in wing lengths and sex ratios among the two generations and across a 545-m elevation gradient. We found that abundance, but not wing length, increased at lower elevations and that the two generations differed in size and sex distributions. Our results shed light on the life history and morphology of a common, but poorly known, species of moth endemic to the southwestern United States and Mexico.

Phylogeny is an ecologically meaningful way to classify plants and animals, as closely related taxa frequently have similar ecological characteristics, functional traits and effects on ecosystem processes. For bacteria, however, phylogeny has been argued to be an unreliable indicator of an organism’s ecology owing to evolutionary processes more common to microbes such as gene loss and lateral gene transfer, as well as convergent evolution. Here we use advanced stable isotope probing with 13C and 18O to show that evolutionary history has ecological significance for in situ bacterial activity. Phylogenetic organization in the activity of bacteria sets the stage for characterizing the functional attributes of bacterial taxonomic groups. Connecting identity with function in this way will allow scientists to begin building a mechanistic understanding of how bacterial community composition regulates critical ecosystem functions.

Vessel  length  is  an  important  but  understudied  dimension  of  variation  in  angiosperm  vascular  anatomy. Among other traits, vessel length mediates an important tradeoff between hydraulic efficiency and safety that could  influence  how  plants  respond  to  extreme  weather  with  climate  change.  However,  the  functional significance  of vessel length variation within individual stems is poorly known, in part because existing data analysis methods handle uncertainty in a way that makes vessel length distributions difficult to compare. We provide a solution to this problem through a hierarchical Bayesian framework for estimating vessel lengths and we demonstrate the flexibility of this method by applying it to data from serial cross sections of dye injected stems. Our approach can accelerate data collection and accommodate  associated uncertainties by statistically correcting for bias and error that result from subsampling images. We illustrate our analytical framework by estimating and comparing vessel length distributions for 21 woody species characteristic of a North American forest.  The best-fit  model  corrected  for both bias due to secondary  growth  and sampling  error  within  and among  species.  Vessel  length  estimates  from  this  model  varied  by  almost  an  order  of  magnitude  and parameters  of these  distributions  correlated  with  point  estimates  derived  from  a different,  commonly  used method. Furthermore, we show how key contrasts can be estimated with the Bayesian framework, and in doing so, we show that the shape of the vessel length distribution differed between ring- and diffuse-porous species, suggesting that within-stem vessel length variation corresponds to water stress seasonality and contributes to landscape-level  habitat segregation. Our analysis method revealed the importance of within-stem variation in vessel length, and our results complement work on between-species variation in average vessel length, further illuminating how vascular anatomy can influence woody plants’ responses to water stress.

Of course plants do not have brains and, thus, cannot actually remember what happened to them in the past. Although plants cannot remember, however, we use “memory” as a metaphor to refer to the effect of the past on current and future plant and ecosystem functioning. Such memory effects have been repeatedly shown in ecosystems (such as deserts) that are often defined by highly variable environmental conditions, where air temperatures, humidity, and soil water availability can differ greatly from one day to the next, week to week, among seasons, and year to year.

Nonsteady state chambers are often employed to measure soil CO₂ fluxes. CO₂ concentrations (<em>C</em>) in the headspace are sampled at different times (<em>t</em>), and fluxes (<em>f</em>) are calculated from regressions of <em>C</em> versus <em>t</em> based on a limited number of observations. Variability in the data can lead to poor fits and unreliable <em>f</em> estimates; groups with too few observations or poor fits are often discarded, resulting in “missing” <em>f</em> values. We solve these problems by fitting linear (steady state) and nonlinear (nonsteady state, diffusion based) models of <em>C</em> versus <em>t</em>, within a hierarchical Bayesian framework. Data are from the Prairie Heating and CO₂ Enrichment study that manipulated atmospheric CO₂, temperature, soil moisture, and vegetation. CO₂ was collected from static chambers biweekly during five growing seasons, resulting in &gt;12,000 samples and &gt;3100 groups and associated fluxes. We compare <em>f</em> estimates based on nonhierarchical and hierarchical Bayesian (B versus HB) versions of the linear and diffusion-based (L versus D) models, resulting in four different models (BL, BD, HBL, and HBD). Three models fit the data exceptionally well (<em>R</em>² ≥ 0.98), but the BD model was inferior (<em>R</em>² = 0.87). The nonhierarchical models (BL and BD) produced highly uncertain <em>f</em> estimates (wide 95% credible intervals), whereas the hierarchical models (HBL and HBD) produced very precise estimates. Of the hierarchical versions, the linear model (HBL) underestimated <em>f</em> by ~33% relative to the nonsteady state model (HBD). The hierarchical models offer improvements upon traditional nonhierarchical approaches to estimating <em>f</em>, and we provide example code for the models.

Thermokarst is the process whereby the thawing of ice-rich permafrost ground causes land subsidence, resulting in development of distinctive landforms. Accelerated thermokarst due to climate change will damage infrastructure, but also impact hydrology, ecology and biogeochemistry. Here, we present a circumpolar assessment of the distribution of thermokarst landscapes, defined as landscapes comprised of current thermokarst landforms and areas susceptible to future thermokarst development. At 3.6 × 10⁶ km², thermokarst landscapes are estimated to cover <span class="stix">∼</span>20% of the northern permafrost region, with approximately equal contributions from three landscape types where characteristic wetland, lake and hillslope thermokarst landforms occur. We estimate that approximately half of the below-ground organic carbon within the study region is stored in thermokarst landscapes. Our results highlight the importance of explicitly considering thermokarst when assessing impacts of climate change, including future landscape greenhouse gas emissions, and provide a means for assessing such impacts at the circumpolar scale.

Sub-arctic birch forests (<em class="EmphasisTypeItalic ">Betula pubescens</em> Ehrh. ssp. <em class="EmphasisTypeItalic ">czerepanovii</em>) periodically suffer large-scale defoliation events caused by the caterpillars of the geometrid moths <em class="EmphasisTypeItalic ">Epirrita autumnata</em> and <em class="EmphasisTypeItalic ">Operophtera brumata</em>. Despite their obvious influence on ecosystem primary productivity, little is known about how the associated reduction in belowground C allocation affects soil processes. We quantified the soil response following a natural defoliation event in sub-arctic Sweden by measuring soil respiration, nitrogen availability and ectomycorrhizal fungi (EMF) hyphal production and root tip community composition. There was a reduction in soil respiration and an accumulation of soil inorganic N in defoliated plots, symptomatic of a slowdown of soil processes. This coincided with a reduction of EMF hyphal production and a shift in the EMF community to lower autotrophic C-demanding lineages (for example, /russula-lactarius). We show that microbial and nutrient cycling processes shift to a slower, less C-demanding state in response to canopy defoliation. We speculate that, amongst other factors, a reduction in the potential of EMF biomass to immobilise excess mineral nitrogen resulted in its build-up in the soil. These defoliation events are becoming more geographically widespread with climate warming, and could result in a fundamental shift in sub-arctic ecosystem processes and properties. EMF fungi may be important in mediating the response of soil cycles to defoliation and their role merits further investigation.

Understanding impacts of drought on tree growth and forest health is of major concern given projected climate change. Droughts may become more common in the Southwest due to extreme temperatures that will drive increased evapotranspiration and lower soil moisture, in combination with uncertain precipitation changes. Utilizing ~1.3 million tree-ring widths from the International Tree Ring Data Bank representing 10 species (eight conifers, two oaks) in the Southwest, we evaluated the effects of drought on tree growth. We categorized ring widths by formation year in relation to drought (pre-drought, drought year, and post-drought), and we used a mixed-effects model to estimate the effects of current and antecedent precipitation and temperature on tree growth during the post-drought recovery period. This allowed us to assess changes in sensitivity of tree growth to precipitation and temperature at multiple timescales following multiple droughts, and to evaluate drought resistance and recovery in these species. The effects of precipitation and temperature on ring widths following drought varied among species and time since drought. Across species, 16% of the climate effects (i.e., “sensitivities”) were significantly different from their pre-drought values. Species differed, with some showing increased sensitivities to precipitation and temperature following drought, and others showing decreased sensitivities. Furthermore, some species (e.g., <em>Abies concolor</em> and <em>Pinus ponderosa</em>) showed low resistance and slow recovery, with changes in growth sensitivities persisting up to 5 yr; others (e.g., <em>Juniper</em> spp.) showed high resistance, such that their climatic sensitivities did not change. Among species, the importance of different antecedent climate variables changed with time since drought. Though a majority of species responded positively to same-year precipitation pre-drought, all 10 species were positively affected by same-year precipitation the second year after drought. Our results demonstrate tree growth sensitivities vary among species and with time since drought, raising questions about physiological mechanisms and implications for forest health under future drought.

Perennially frozen soil in high latitude ecosystems (permafrost) currently stores 1330-1580 Pg of carbon (C). As these ecosystems warm, the thaw and decomposition of permafrost is expected to release large amounts of C to the atmosphere. Fortunately, losses from the permafrost C pool will be partially offset by increased plant productivity. The degree to which plants are able to sequester C, however, will be determined by changing nitrogen (N) availability in these thawing soil profiles. N availability currently limits plant productivity in tundra ecosystems but plant access to N is expected improve as decomposition increases in speed and extends to deeper soil horizons. In order to evaluate the relationship between permafrost thaw and N availability, we monitored N cycling during five years of experimentally induced permafrost thaw at the Carbon in Permafrost Experimental Heating Research project (CiPEHR). Inorganic N availability increased significantly in response to deeper thaw and greater soil moisture induced by Soil warming. This treatment also prompted a 23% increase in aboveground biomass and a 49% increase in foliar N pools. The sedge Eriophorum vaginatum responded most strongly to warming: this species explained 91% of the change in aboveground biomass during the five year period. Air warming had little impact when applied alone, but when applied in combination with Soil warming, growing season soil inorganic N availability was significantly reduced. These results demonstrate that there is a strong positive relationship between the depth of permafrost thaw and N availability in tundra ecosystems but that this relationship can be diminished by interactions between increased thaw, warmer air temperatures and higher levels of soil moisture. Within five years of permafrost thaw, plants actively incorporate newly available N into biomass but C storage in live vascular plant biomass is unlikely to be greater than losses from deep soil C pools. This article is protected by copyright. All rights reserved.

Increasing temperatures in northern high latitudes are causing permafrost to thaw, making large amounts of previously frozen organic matter vulnerable to microbial decomposition. Permafrost thaw also creates a fragmented landscape of drier and wetter soil conditions that determine the amount and form (carbon dioxide (CO₂), or methane (CH₄)) of carbon (C) released to the atmosphere. The rate and form of C release control the magnitude of the permafrost C feedback, so their relative contribution with a warming climate remains unclear. We quantified the effect of increasing temperature and changes from aerobic to anaerobic soil conditions using 25 soil incubation studies from the permafrost zone. Here we show, using two separate meta-analyses, that a 10<span class="mb"><span class="mb"> </span></span>°C increase in incubation temperature increased C release by a factor of 2.0 (95% confidence interval (CI), 1.8 to 2.2). Under aerobic incubation conditions, soils released 3.4 (95% CI, 2.2 to 5.2) times more C than under anaerobic conditions. Even when accounting for the higher heat trapping capacity of CH₄, soils released 2.3 (95% CI, 1.5 to 3.4) times more C under aerobic conditions. These results imply that permafrost ecosystems thawing under aerobic conditions and releasing CO₂ will strengthen the permafrost C feedback more than waterlogged systems releasing CO₂ and CH₄ for a given amount of C.

The Arctic continues to warm at a rate that is currently twice as fast as the global average (see essay on <em><a href="http://www.arctic.noaa.gov/Report-Card/Report-Card-2016/ArtMID/5022/ArticleID/271/Surface-Air-Temperature">Surface Air Temperature</a></em>). Warming is causing normally frozen ground (permafrost) to thaw, exposing significant quantities of organic soil carbon to decomposition by soil microbes (Romanovsky et al. 2010, Romanovsky et al. 2012). This <strong>permafrost carbon</strong> is the remnants of plants, animals, and microbes accumulated in frozen soil over hundreds to thousands of years (Schuur et al. 2008). The northern permafrost zone holds twice as much carbon as currently in the atmosphere (Schuur et al. 2015, Hugelius et al. 2014, Tarnocai et al. 2009, Zimov et al. 2006). Release of just a fraction of this frozen carbon pool, as the greenhouse gases carbon dioxide and methane, into the atmosphere would dramatically increase the rate of future global climate warming (Schuur et al. 2013). This report details recent advances in quantifying the amount of organic carbon stored in permafrost zone soils and recent trends (1970-2010) in the exchange of carbon between tundra ecosystems and the atmosphere. These data are the most recent comprehensive data synthesis across individual sites.

Growth and mortality of microorganisms have been characterized through DNA stable isotope probing (SIP) with ¹⁸O-water in soils from a range of ecosystems. Conventional SIP has been improved by sequencing a marker gene in all fractions retrieved from an ultracentrifuge tube to produce taxon density curves, which allow estimating the atom percent isotope composition of each microbial taxon's genome. Very recent advances in SIP with ¹⁸O-water include expansion of the technique to aquatic samples, investigations of microbial turnover in soil, and the first use of ¹⁸O-water in RNA-SIP studies.

Soil bacteria play a key role in regulating terrestrial biogeochemical cycling and greenhouse gas fluxes across the soil-atmosphere continuum. Despite their importance to ecosystem functioning, we lack a general understanding of how bacterial communities respond to climate change, especially in relatively understudied ecosystems like tropical montane wet forests. We used a well-studied and highly constrained 5.2°C mean annual temperature (MAT) gradient in tropical montane wet forests on the Island of Hawaii to test the hypothesis that long-term, whole-ecosystem warming and the accompanying increase in belowground carbon flux increase the diversity and alter the composition of soil bacterial communities. Across this MAT gradient, dominant vegetation, substrate type and age, soil moisture, and disturbance history are constant, allowing us to effectively isolate the influence of rising MAT on soil bacterial community structure. Contrary to our hypothesis, we found that the richness, evenness, and phylogenetic diversity of the soil bacterial community remained remarkably stable with MAT and that MAT did not predict variation in bacterial community composition despite a substantial increase in belowground soil carbon fluxes across the gradient. Our results suggest that other factors that are constant across this gradient—such as soil pH, water availability and plant species composition—may be more important than warming in influencing soil bacterial community composition and diversity, at least within the temperature range studied here (~13–18°C MAT). Ours is the first study to demonstrate stability of soil bacterial community structure with rising MAT and increased belowground carbon flux in a tropical wet forest ecosystem. Moreover, our results add to growing evidence that the diversity and composition of soil bacterial communities dominated by Proteobacteria and Acidobacteria in low-pH forest soils may be insensitive to the direct effect of climate warming.

Despite the importance of net primary productivity (NPP) and net biome productivity (NBP), estimates of NPP and NBP for China are highly uncertain. To investigate the main sources of uncertainty, we synthesized model estimates of NPP and NBP for China from published literature and the Multi-scale Synthesis and Terrestrial Model Intercomparison Project (MsTMIP). The literature-based results showed that total NPP and NBP in China were 3.35 ± 1.25 and 0.14 ± 0.094 Pg C yr⁻¹, respectively. Classification and regression tree analysis based on literature data showed that model type was the primary source of the uncertainty, explaining 36% and 64% of the variance in NPP and NBP, respectively. Spatiotemporal scales, land cover conditions, inclusion of the N cycle, and effects of N addition also contributed to the overall uncertainty. Results based on the MsTMIP data suggested that model structures were overwhelmingly important (&gt;90%) for the overall uncertainty compared to simulations with different combinations of time-varying global change factors. The interannual pattern of NPP was similar among diverse studies and increased by 0.012 Pg C yr⁻¹ during 1981–2000. In addition, high uncertainty in China's NPP occurred in areas with high productivity, whereas NBP showed the opposite pattern. Our results suggest that to significantly reduce uncertainty in estimated NPP and NBP, model structures should be substantially tested on the basis of empirical results. To this end, coordinated distributed experiments with multiple global change factors might be a practical approach that can validate specific structures of different models.

Plants buffer increasing atmospheric carbon dioxide (CO₂) concentrations through enhanced growth, but the question whether nitrogen availability constrains the magnitude of this ecosystem service remains unresolved. Synthesizing experiments from around the world, we show that CO₂ fertilization is best explained by a simple interaction between nitrogen availability and mycorrhizal association. Plant species that associate with ectomycorrhizal fungi show a strong biomass increase (30 ± 3%, <em>P</em> &lt; 0.001) in response to elevated CO₂ regardless of nitrogen availability, whereas low nitrogen availability limits CO₂ fertilization (0 ± 5%, <em>P</em> = 0.946) in plants that associate with arbuscular mycorrhizal fungi. The incorporation of mycorrhizae in global carbon cycle models is feasible, and crucial if we are to accurately project ecosystem responses and feedbacks to climate change.

Observations show an increasing amplitude in the seasonal cycle of CO₂ (ASC) north of 45°N of 56 ± 9.8% over the last 50 years and an increase in vegetation greenness of 7.5–15% in high northern latitudes since the 1980s. However, the causes of these changes remain uncertain. Historical simulations from terrestrial biosphere models in the Multiscale Synthesis and Terrestrial Model Intercomparison Project are compared to the ASC and greenness observations, using the TM3 atmospheric transport model to translate surface fluxes into CO₂concentrations. We find that the modeled change in ASC is too small but the mean greening trend is generally captured. Modeled increases in greenness are primarily driven by warming, whereas ASC changes are primarily driven by increasing CO₂. We suggest that increases in ecosystem-scale light use efficiency (LUE) have contributed to the observed ASC increase but are underestimated by current models. We highlight potential mechanisms that could increase modeled LUE.

The terrestrial biosphere can release or absorb the greenhouse gases, carbon dioxide (CO₂), methane (CH₄) and nitrous oxide (N₂O), and therefore has an important role in regulating atmospheric composition and climate^{<a id="ref-link-1" title="Lovelock, J. E. &amp; Margulis, L. Atmospheric homeostasis by and for the biosphere: the gaia hypothesis. Tellus A 26, http://dx.doi.org/10.3402/tellusa.v26i1-2.9731 (1974)" href="http://www.nature.com/nature/journal/v531/n7593/full/nature16946.html#ref1">1</a>}. Anthropogenic activities such as land-use change, agriculture and waste management have altered terrestrial biogenic greenhouse gas fluxes, and the resulting increases in methane and nitrous oxide emissions in particular can contribute to climate change^{<a id="ref-link-2" title="Vitousek, P. M., Mooney, H. A., Lubchenco, J. &amp; Melillo, J. M. Human domination of Earth’s ecosystems. Science 277, 494–499 (1997)" href="http://www.nature.com/nature/journal/v531/n7593/full/nature16946.html#ref2">2</a>, <a id="ref-link-3" title="Ciais, P. et al. in Climate Change 2013: The Physical Science Basis (eds Stocker, T. F. et al. ) Ch. 6 (Cambridge Univ. Press, 2013)" href="http://www.nature.com/nature/journal/v531/n7593/full/nature16946.html#ref3">3</a>}. The terrestrial biogenic fluxes of individual greenhouse gases have been studied extensively^{<a id="ref-link-4" title="Le Quéré, C. et al. Global carbon budget 2013. Earth Syst. Sci. Data 6, 235–263 (2014)" href="http://www.nature.com/nature/journal/v531/n7593/full/nature16946.html#ref4">4</a>, <a id="ref-link-5" title="Kirschke, S. et al. Three decades of global methane sources and sinks. Nature Geosci . 6, 813–823 (2013)" href="http://www.nature.com/nature/journal/v531/n7593/full/nature16946.html#ref5">5</a>, <a id="ref-link-6" title="Davidson, E. A. &amp; Kanter, D. Inventories and scenarios of nitrous oxide emissions. Environ. Res. Lett. 9, 105012 (2014)" href="http://www.nature.com/nature/journal/v531/n7593/full/nature16946.html#ref6">6</a>}, but the net biogenic greenhouse gas balance resulting from anthropogenic activities and its effect on the climate system remains uncertain. Here we use bottom-up (inventory, statistical extrapolation of local flux measurements, and process-based modelling) and top-down (atmospheric inversions) approaches to quantify the global net biogenic greenhouse gas balance between 1981 and 2010 resulting from anthropogenic activities and its effect on the climate system. We find that the cumulative warming capacity of concurrent biogenic methane and nitrous oxide emissions is a factor of about two larger than the cooling effect resulting from the global land carbon dioxide uptake from 2001 to 2010. This results in a net positive cumulative impact of the three greenhouse gases on the planetary energy budget, with a best estimate (in petagrams of CO₂ equivalent per year) of 3.9 ± 3.8 (top down) and 5.4 ± 4.8 (bottom up) based on the GWP100 metric (global warming potential on a 100-year time horizon). Our findings suggest that a reduction in agricultural methane and nitrous oxide emissions, particularly in Southern Asia, may help mitigate climate change.

Spatio-temporal fields of land–atmosphere fluxes derived from data-driven models can complement simulations by process-based land surface models. While a number of strategies for empirical models with eddy-covariance flux data have been applied, a systematic intercomparison of these methods has been missing so far. In this study, we performed a cross-validation experiment for predicting carbon dioxide, latent heat, sensible heat and net radiation fluxes across different ecosystem types with 11 machine learning (ML) methods from four different classes (kernel methods, neural networks, tree methods, and regression splines). We applied two complementary setups: (1) 8-day average fluxes based on remotely sensed data and (2) daily mean fluxes based on meteorological data and a mean seasonal cycle of remotely sensed variables. The patterns of predictions from different ML and experimental setups were highly consistent. There were systematic differences in performance among the fluxes, with the following ascending order: net ecosystem exchange (R 2 &lt; 0.5), ecosystem respiration (R 2 &gt; 0.6), gross primary production (R 2&gt; 0.7), latent heat (R 2 &gt; 0.7), sensible heat (R 2 &gt; 0.7), and net radiation (R 2 &gt; 0.8). The ML methods predicted the across-site variability and the mean seasonal cycle of the observed fluxes very well (R 2 &gt; 0.7), while the 8-day deviations from the mean seasonal cycle were not well predicted (R 2 &lt; 0.5). Fluxes were better predicted at forested and temperate climate sites than at sites in extreme climates or less represented by training data (e.g., the tropics). The evaluated large ensemble of ML-based models will be the basis of new global flux products.

In sagebrush steppe, snowpack may govern soil respiration through its effect on multiple abiotic and biotic factors. Across the Intermountain West of the United States, snowpack has been declining for decades and is projected to decline further over the next century, making the response of soil respiration to snowpack a potentially important factor in the ecosystem carbon cycle. In this study, we evaluated the direct and indirect roles of the snowpack in driving soil respiration in sagebrush steppe ecosystems by taking advantage of highway snowfences in Wyoming to manipulate snowpack. An important contribution of this study is the use of Bayesian modeling to quantify the effects of soil moisture and temperature on soil respiration across a wide range of conditions from frozen to hot and dry, while simultaneously accounting for biotic factors (e.g., vegetation cover, root density, and microbial biomass and substrate-use diversity) affected by snowpack. Elevated snow depth increased soil temperature (in the winter) and moisture (winter and spring), and was associated with reduced vegetation cover and microbial biomass carbon. Soil respiration showed an exponential increase with temperature, with a temperature sensitivity that decreased with increasing seasonal temperature (<em>Q</em>₁₀ = 4.3 [winter], 2.3 [spring], and 1.7 [summer]); frozen soils were associated with unrealistic <em>Q</em>₁₀ ≈ 7989 due to the liquid-to-ice transition of soil water. Soil respiration was sensitive to soil water content; predicted respiration under very dry conditions was less than 10% of respiration under moist conditions. While higher vegetation cover increased soil respiration, this was not due to increased root density, and may reflect differences in litter inputs. Microbial substrate-use diversity was negatively related to reference respiration (i.e., respiration rate at a reference temperature and optimal soil moisture), although the mechanism remains unclear. This study indicates that soil respiration is inhibited by shallow snowpack through multiple mechanisms; thus, future decreases in snowpack across the sagebrush steppe have the potential to reduce losses of soil C, potentially affecting regional carbon balance.

High daily temperature range of soil (DTRsoil) negatively affects soil microbial biomass and activity, but its interaction with seasonal soil moisture in regulating ecosystem function remains unclear. For our 5-year field study in the Chihuahuan Desert, we suspended shade cloth 15 cm above the soil surface to reduce daytime temperature and increase nighttime soil temperature compared to unshaded plots, thereby reducing DTRsoil (by 5 ºC at 0.2 cm depth) without altering mean temperatures. Microbial biomass production was primarily regulated by seasonal precipitation with the magnitude of the response dependent on DTRsoil. Reduced DTRsoil more consistently increased microbial biomass nitrogen (MBN; +38 %) than microbial biomass carbon (MBC) with treatment responses being similar in spring and summer. Soil respiration depended primarily on soil moisture with responses to reduced DTRsoil evident only in wetter summer soils (+53 %) and not in dry spring soils. Reduced DTRsoil had no effect on concentrations of dissolved organic C, soil organic matter (SOM), nor soil inorganic N (extractable NO3 −–N + NH4 +–N). Higher MBN without changes in soil inorganic N suggests faster N cycling rates or alternate sources of N. If N cycling rates increased without a change to external N inputs (atmospheric N deposition or N fixation), then productivity in this desert system, which is N-poor and low in SOM, could be negatively impacted with continued decreases in daily temperature range. Thus, the future N balance in arid ecosystems, under conditions of lower DTR, seems linked to future precipitation regimes through N deposition and regulation of soil heat load dynamics.

Climate change has increased the occurrence, severity, and impact of disturbances on forested ecosystems worldwide, resulting in a need to identify factors that contribute to an ecosystem’s resilience or capacity to recover from disturbance. Forest resilience to disturbance may decline with climate change if mature trees are able to persist under stressful environmental conditions that do not permit successful recruitment and survival after a disturbance. In this study, we used the change in proportional representation of black spruce pre- to post-fire as a surrogate for resilience. We explored links between patterns of resilience and tree ring signals of drought stress across topographic moisture gradients within the boreal forest. We sampled 72 recently (2004) burned stands of black spruce in interior Alaska (USA); the relative dominance of black spruce after fire ranged from almost no change (high resilience) to a 90% decrease (low resilience). Variance partitioning analysis indicated that resilience was related to site environmental characteristics and climate–growth responses, with no unique contribution of pre-fire stand composition. The largest shifts in post-fire species composition occurred in sites that experienced the compounding effects of pre-fire drought stress and shallow post-fire organic layer thickness. These sites were generally located at warmer and drier landscape positions, suggesting they are less resilient to disturbance than sites in cool and moist locations. Climate–growth responses can provide an estimate of stand environmental stress to climate change and as such are a valuable tool for predicting landscape variations in forest ecosystem resilience.

Permafrost soils currently store approximately 1672 Pg of carbon (C), but as high latitudes warm, this temperature-protected C reservoir will become vulnerable to higher rates of decomposition. In recent decades, air temperatures in the high latitudes have warmed more than any other region globally, particularly during the winter. Over the coming century, the arctic winter is also expected to experience the most warming of any region or season, yet it is notably understudied. Here we present nonsummer season (NSS) CO2 flux data from the Carbon in Permafrost Experimental Heating Research project, an ecosystem warming experiment of moist acidic tussock tundra in interior Alaska. Our goals were to quantify the relationship between environmental variables and winter CO2 production, account for subnivean photosynthesis and late fall plant C uptake in our estimate of NSS CO2 exchange, constrain NSS CO2 loss estimates using multiple methods of measuring winter CO2 flux, and quantify the effect of winter soil warming on total NSS CO2 balance. We measured CO2 flux using four methods: two chamber techniques (the snow pit method and one where a chamber is left under the snow for the entire season), eddy covariance, and soda lime adsorption, and found that NSS CO2 loss varied up to fourfold, depending on the method used. CO2 production was dependent on soil temperature and day of season but atmospheric pressure and air temperature were also important in explaining CO2 diffusion out of the soil. Warming stimulated both ecosystem respiration and productivity during the NSS and increased overall CO2 loss during this period by 14% (this effect varied by year, ranging from 7 to 24%). When combined with the summertime CO2 fluxes from the same site, our results suggest that this subarctic tundra ecosystem is shifting away from its historical function as a C sink to a C source.

Foliar chemistry influences leaf decomposition, but little is known about how litter chemistry affects the assemblage of bacterial communities during decomposition. Here we examined relationships between initial litter chemistry and the composition of the bacterial community in a stream ecosystem. We incubated replicated genotypes of <em class="EmphasisTypeItalic ">Populus fremontii</em> and <em class="EmphasisTypeItalic ">P. angustifolia</em> leaf litter that differ in percent tannin and lignin, then followed changes in bacterial community composition during 28 days of decomposition using 16S rRNA gene-based pyrosequencing. Using a nested experimental design, the majority of variation in bacterial community composition was explained by time (i.e., harvest day) (<em class="EmphasisTypeItalic ">R</em> <em class="EmphasisTypeItalic ">2</em>  = 0.50). Plant species, nested within harvest date, explained a significant but smaller proportion of the variation (<em class="EmphasisTypeItalic ">R</em> <em class="EmphasisTypeItalic ">2</em>  = 0.03). Significant differences in community composition between leaf species were apparent at day 14, but no significant differences existed among genotypes. Foliar chemistry correlated significantly with community composition at day 14 (<em class="EmphasisTypeItalic ">r</em> = 0.46) indicating that leaf litter with more similar phytochemistry harbor bacterial communities that are alike. Bacteroidetes and β-proteobacteria dominated the bacterial assemblage on decomposing leaves, and Verrucomicrobia and α- and δ-proteobacteria became more abundant over time. After 14 days, bacterial diversity diverged significantly between leaf litter types with fast-decomposing <em class="EmphasisTypeItalic ">P. fremontii</em> hosting greater richness than slowly decomposing <em class="EmphasisTypeItalic ">P. angustifolia</em>; however, differences were no longer present after 28 days in the stream. Leaf litter tannin, lignin, and lignin: N ratios all correlated negatively with diversity. This work shows that the bacterial community on decomposing leaves in streams changes rapidly over time, influenced by leaf species via differences in genotype-level foliar chemistry.

Microbial decomposition of soil carbon in high-latitude tundra underlain with permafrost is one of the most important, but poorly understood, potential positive feedbacks of greenhouse gas emissions from terrestrial ecosystems into the atmosphere in a warmer world^{<a title="Schuur, E. A. G. et al. Vulnerability of permafrost carbon to climate change: implications for the global carbon cycle. BioScience 58, 701-714 (2008)." href="http://www.nature.com/nclimate/journal/vaop/ncurrent/full/nclimate2940.html#ref1">1</a>, <a id="ref-link-5" title="Schuur, E. et al. Expert assessment of vulnerability of permafrost carbon to climate change. Climatic Change 119, 359-374 (2013)." href="http://www.nature.com/nclimate/journal/vaop/ncurrent/full/nclimate2940.html#ref2">2</a>, <a id="ref-link-6" title="Zhou, J. et al. Microbial mediation of carbon-cycle feedbacks to climate warming. Nature Clim. Change 2, 106-110 (2012)." href="http://www.nature.com/nclimate/journal/vaop/ncurrent/full/nclimate2940.html#ref3">3</a>, <a id="ref-link-7" title="Graham, D. E. et al. Microbes in thawing permafrost: the unknown variable in the climate change equation. ISME J. 6, 709-712 (2012)." href="http://www.nature.com/nclimate/journal/vaop/ncurrent/full/nclimate2940.html#ref4">4</a>}. Using integrated metagenomic technologies, we showed that the microbial functional community structure in the active layer of tundra soil was significantly altered after only 1.5 years of warming, a rapid response demonstrating the high sensitivity of this ecosystem to warming. The abundances of microbial functional genes involved in both aerobic and anaerobic carbon decomposition were also markedly increased by this short-term warming. Consistent with this, ecosystem respiration (<i>R</i>_eco) increased up to 38%. In addition, warming enhanced genes involved in nutrient cycling, which very likely contributed to an observed increase (30%) in gross primary productivity (GPP). However, the GPP increase did not offset the extra <i>R</i>_eco, resulting in significantly more net carbon loss in warmed plots compared with control plots. Altogether, our results demonstrate the vulnerability of active-layer soil carbon in this permafrost-based tundra ecosystem to climate warming and the importance of microbial communities in mediating such vulnerability.

Understanding the global carbon (C) cycle is of crucial importance to map current and future climate dynamics relative to global environmental change. A full characterization of C cycling requires detailed information on spatiotemporal patterns of surface-atmosphere fluxes. However, relevant C cycle observations are highly variable in their coverage and reporting standards. Especially problematic is the lack of integration of vertical oceanic, inland freshwaters and terrestrial carbon dioxide (CO₂) exchange. Here we adopt a data-driven approach to synthesize a wide range of observation-based spatially explicit surface-atmosphere CO₂ fluxes from 2001 and 2010, to identify the state of today’s observational opportunities and data limitation. The considered fluxes include vertical net exchange of open oceans, continental shelves, estuaries, rivers, and lakes, as well as CO₂ fluxes related to gross primary productivity, terrestrial ecosystem respiration, fire emissions, loss of tropical aboveground C, harvested wood and crops, as well as fossil fuel and cement emissions. Spatially explicit CO₂ fluxes are obtained through geostatistical and/or remote sensing-based upscaling; minimizing biophysical or biogeochemical assumptions encoded in process-based models. We estimate a global bottom-up net C exchange (NCE) between the surface (land, ocean, and coastal areas) and the atmosphere. Uncertainties for NCE and its components are derived using resampling. In most continental regions our NCE estimates agree well with independent estimates from other sources. This holds for Europe (mean ±1 SD: 0.80 ± 0.16 PgC/yr, positive numbers are sources to the atmosphere), Russia (−0.02 ± 0.49 PgC/yr), East Asia (1.76 ± 0.38 PgC/yr), South Asia (0.25 ± 0.16 PgC/yr), and Australia (0.22 ± 0.47 PgC/yr). Our NCE estimates also suggest large C sink in tropical areas. The global NCE estimate is −6.07 ± 3.38 PgC/yr. This global bottom-up value is the opposite direction of what is expected from the atmospheric growth rate of CO₂, and would require an offsetting surface C source of 4.27±0.10 PgC/yr. This mismatch highlights large knowledge and observational gaps in tropical areas, particularly in South America, Africa, and Southeast Asia, but also in North America. Our uncertainty assessment provides the basis for designing new observation campaigns. In particular, we lack seasonal monitoring of shelf, estuary and inland water-atmosphere C exchange. Also, extensive pCO₂measurements are missing in the Southern Ocean. Most importantly, tropical land C fluxes suffer from a lack of in-situ observations. The consistent derivation of data uncertainties could serve as prior knowledge in multi-criteria optimization such as the Carbon Cycle Data Assimilation System (CCDAS) without overstating data credibility. Furthermore, the spatially explicit flux estimates may be used as a starting point to assess the validity of countries’ claims of reducing net C emissions in climate change negotiations.