Global relationship of wood and leaf litter decomposability: the role of functional traits within and across plant organs
Bibliographic record
Abstract
Abstract Aim 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. Location Global. Methods 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 *. Results 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. Main conclusions 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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".