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Record W3088738889 · doi:10.1111/geb.13181

Functional and phylogenetic diversity promote litter decomposition across terrestrial ecosystems

2020· article· en· W3088738889 on OpenAlexafffund
Wenya Xiao, Chen Chen, Xinli Chen, Zhiqun Huang, Han Y. H. Chen

Bibliographic record

VenueGlobal Ecology and Biogeography · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicEcology and Vegetation Dynamics Studies
Canadian institutionsLakehead University
FundersNatural Sciences and Engineering Research Council of CanadaNational Natural Science Foundation of China
KeywordsDecomposerLitterPlant litterEcosystemSpecies richnessEcologyAbundance (ecology)Nutrient cycleBiologyPhylogenetic diversityBiomass (ecology)Terrestrial ecosystemMonoculturePhylogenetics

Abstract

fetched live from OpenAlex

Abstract Aim Litter decomposition is a vital process of carbon and nutrient cycling in terrestrial ecosystems. Despite rapid declines in plant diversity worldwide, the effects of plant diversity on litter decomposition, along with the factors driving their directions and magnitudes, remain uncertain. Location Global. Time period 1985–2018. Major taxa studied Plants. Methods By synthesizing 492 paired observations of leaf litter mixtures and monocultures from 110 studies, we conducted a global meta‐analysis of the effects of litter mixtures on litter decomposition rates, which were calculated as k coefficients from m t / m 0 = e − kt , where m t was the remaining mass of leaf litter at year t and m 0 was the initial litter mass at the beginning of experiments. Results Litter mixtures on average increased litter decomposition rates by 5.6% (95% confidence intervals, 3.0–8.1%), and the effects of litter mixtures increased with litter species richness, the functional diversity of chemical traits (leaf C, N, P contents and C : N ratio) and phylogenetic diversity consistently across terrestrial ecosystems. The decomposer abundance and function, including soil fauna abundance, microbial biomass, and extracellular enzyme activities, were positively associated with litter mixture effects on decomposition rates. The structural equation models accounted for 48.6% of the global variation in litter decomposition rates and revealed that the positive effects of litter functional diversity on decomposer abundance and function led to increased litter decomposition rates, while litter phylogenetic diversity had a positive direct effect on litter decomposition rates. Main conclusions As indicators for complementarity effects, functional diversity of the chemical traits and phylogenetic diversity lead to more positive litter mixture effects on decomposition. The positive litter diversity effects on decomposition rates are mechanistically linked with soil fauna abundance, microbial biomass, and extracellular enzyme activities. Our results suggest that plant diversity, especially functional and phylogenetic diversity, increases decomposer abundance and function, and thus plays a key role in carbon and nutrient cycling across terrestrial ecosystems.

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How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.484

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.010
GPT teacher head0.224
Teacher spread0.215 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations64
Published2020
Admission routes2
Has abstractyes

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