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Record W4213166058 · doi:10.1111/geb.13461

Tree diversity effects on soil microbial biomass and respiration are context dependent across forest diversity experiments

2022· article· en· W4213166058 on OpenAlexaff
Simone Cesarz, Dylan Craven, Harald Auge, Helge Bruelheide, Bastien Castagneyrol, Jessica Gutknecht, Andy Hector, Hervé Jactel, Julia Koricheva, Christian Messier, Bart Muys, Michael J. O’Brien, Alain Paquette, Quentin Ponette, Catherine Potvin, Peter B. Reich, Michael Scherer‐Lorenzen, Andrew R. Smith, Kris Verheyen, Nico Eisenhauer

Bibliographic record

VenueGlobal Ecology and Biogeography · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicEcology and Vegetation Dynamics Studies
Canadian institutionsMcGill UniversityUniversité du Québec en OutaouaisUniversité du Québec à Montréal
FundersAgencia Nacional de Investigación y DesarrolloDeutsche ForschungsgemeinschaftDeutsches Zentrum für integrative Biodiversitätsforschung Halle-Jena-LeipzigNational Science Foundation
KeywordsEnvironmental scienceBiomass (ecology)EcologyAbiotic componentContext (archaeology)Soil carbonSoil ecologySoil biologySoil waterSoil organic matterBiologySoil biodiversity

Abstract

fetched live from OpenAlex

Abstract Aim Soil microorganisms are essential for the functioning of terrestrial ecosystems. Although soil microbial communities and functions are linked to tree species composition and diversity, there has been no comprehensive study of the generality or context dependence of these relationships. Here, we examine tree diversity–soil microbial biomass and respiration relationships across environmental gradients using a global network of tree diversity experiments. Location Boreal, temperate, subtropical and tropical forests. Time period 2013. Major taxa studied Soil microorganisms. Methods Soil samples collected from 11 tree diversity experiments were used to measure microbial respiration, biomass and respiratory quotient using the substrate‐induced respiration method. All samples were measured using the same analytical device, method and procedure to reduce measurement bias. We used linear mixed‐effects models and principal components analysis (PCA) to examine the effects of tree diversity (taxonomic and phylogenetic), environmental conditions and interactions on soil microbial properties. Results Abiotic drivers, mainly soil water content, but also soil carbon and soil pH, significantly increased soil microbial biomass and respiration. High soil water content reduced the importance of other abiotic drivers. Tree diversity had no effect on the soil microbial properties, but interactions with phylogenetic diversity indicated that the effects of diversity were context dependent and stronger in drier soils. Similar results were found for soil carbon and soil pH. Main conclusions Our results indicate the importance of abiotic variables, especially soil water content, for maintaining high levels of soil microbial functions and modulating the effects of other environmental drivers. Planting tree species with diverse water‐use strategies and structurally complex canopies and high leaf area might be crucial for maintaining high soil microbial biomass and respiration. Given that greater phylogenetic distance alleviated unfavourable soil water conditions, reforestation efforts that account for traits improving soil water content or select more phylogenetically distant species might assist in increasing soil microbial functions.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.033
Threshold uncertainty score0.998

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 studies0.0040.000
Scholarly communication0.0000.000
Open science0.0000.003
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 head0.008
GPT teacher head0.220
Teacher spread0.211 · 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.

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

Citations52
Published2022
Admission routes1
Has abstractyes

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