Global relationship of wood and leaf litter decomposability: the role of functional traits within and across plant organs
Recent meta-analyses have revealed that plant traits and their phylogenetic history influence decay rates of dead wood and leaf litter, but it remains unknown if decay rates of wood and litter covary over a wide range of tree species and across ecosystems. We evaluated the relationships between species-specific wood and leaf litter decomposability, as well as between wood and leaf traits that control their respective decomposability.
We compiled data on rates of wood and leaf litter decomposition for 324 and 635 tree species, respectively, and data on six functional traits for both organs. We used hierarchical Bayesian meta-analysis to estimate, for the first time, species-specific values for wood and leaf litter decomposability standardized to reference conditions (k*wood and k*leaf) across the globe. With these data, we evaluated the relationships: (1) between wood and leaf traits, (2) between each k* and the selected traits within and across organs, and (3) between wood and leaf k*.
Across all species k*wood and k*leaf were positively correlated, phylogenetically clustered and correlated with plant functional traits within and across organs. k* of both organs was usually better described as a function of within- and cross-organ traits, than of within-organ traits alone. When analysed for angiosperms and gymnosperms separately, wood and leaf k* were no longer significantly correlated, but each k* was still significantly correlated to the functional traits.
We demonstrate important relationships among wood and leaf litter decomposability as after-life effects of traits from the living plants. These functional traits influence the decomposability of senesced tissue which could potentially lead to alterations in the rates of biogeochemical cycling, depending on the phylogenetic structure of the species pool. These results provide crucial information for a better representation of decomposition rates in dynamic global vegetation models.