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Record W2909996064 · doi:10.1111/gcb.14567

Plant diversity loss reduces soil respiration across terrestrial ecosystems

2019· article· en· W2909996064 on OpenAlexafffund
Xinli Chen, Han Y. H. Chen

Bibliographic record

VenueGlobal Change Biology · 2019
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSoil Carbon and Nitrogen Dynamics
Canadian institutionsLakehead University
FundersNatural Sciences and Engineering Research Council of CanadaGovernment of Ontario
KeywordsTerrestrial ecosystemEcosystemEnvironmental scienceSoil respirationDiversity (politics)Plant diversityRespirationEcologyBiodiversityAgroforestryBiology

Abstract

fetched live from OpenAlex

The rapid global biodiversity loss has led to the decline in ecosystem function. Despite the critical importance of soil respiration (Rs) in the global carbon and nutrient cycles, how plant diversity loss affects Rs remains uncertain. Here we present a meta-analysis using 446 paired observations from 95 published studies to evaluate the effects of plant and litter mixtures on Rs and its components. We found that total Rs and heterotrophic respiration (Rh) were, on average, greater in plant mixtures than expected from those of monocultures. These mixture effects increased with increasing species richness (SR) in both plant and litter mixtures. While the positive effects of species mixtures remained similar over time for total Rs, they increased over time for Rh in plant mixtures but decreased in litter mixtures. Despite the wide range of variations in mean annual temperature, annual aridity index, and ecosystem types, the plant mixture effects on total Rs and Rh did not change geographically, except for a more pronounced increase of total Rs in species mixtures with reduced water availability. Our structural equation models suggested that the positive effects of SR and stand age on total and Rh were driven by increased plant inputs and soil microbial biomass. Our results suggest that plant diversity loss has ubiquitous negative impacts on Rs, one of the fundamental carbon-cycle processes sustaining terrestrial element cycling and ecosystem function.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

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 score0.037
Threshold uncertainty score0.999

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 studies0.0000.000
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 head0.054
GPT teacher head0.264
Teacher spread0.210 · 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

Citations109
Published2019
Admission routes2
Has abstractyes

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