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Record W2790741128 · doi:10.1111/1365-2435.13064

Land‐use intensity indirectly affects ecosystem services mainly through plant functional identity in a temperate forest

2018· article· en· W2790741128 on OpenAlexaff
Verónica Chillo, Diego P. Vázquez, Mariano M. Amoroso, Elena M. Bennett

Bibliographic record

VenueFunctional Ecology · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicEcology and Vegetation Dynamics Studies
Canadian institutionsMcGill University
FundersFundación Bunge y BornUniversidad Nacional de Río NegroRufford Foundation
KeywordsEcosystem servicesBiodiversityEcosystemProvisioningEcologyBiomass (ecology)Complementarity (molecular biology)Land useEnvironmental resource managementBiologyAgroforestryEnvironmental science

Abstract

fetched live from OpenAlex

Abstract Land‐use change is known to affect biodiversity, and there is increasing concern regarding how these changes may impact the provision of ecosystem services. Although functional composition (diversity and identity) could influence ecosystem properties and services at the community level, there is little quantitative understanding of these relationships in the field. Here, we evaluate the direct and indirect effects (through ecosystem properties) of biodiversity on the provision of multiple ecosystem services in native mixed forest in north‐west Patagonia, and how land‐use intensity influences these relationships. We used structural equation modelling to test hypotheses regarding the relationship between understorey plant functional composition, two ecosystem properties, four ecosystem services and silvopastoral use intensity (SUI). We also evaluated two alternative models to assess the mechanism behind biodiversity and ecosystem properties relationships (biomass ratio and niche complementarity). Finally, we performed pairwise correlations to identify synergies and trade‐offs between ecosystem services. SUI affected functional composition, and the provision of three out of four ecosystem services was indirectly affected by land‐use intensity through changes in ecosystem properties. We found that this indirect effect of biodiversity on ecosystem services happens mainly through changes in functional identity rather than functional diversity. Under increasing land‐use intensity, functional composition changed towards a community characterized by a resource acquisition strategy. Trade‐offs between ecosystem services (provisioning vs. regulating) were enhanced under high SUI, while synergies where enhanced under low SUI (provisioning vs. cultural). Thus, although the strength of these relationships varied between SUI, its nature (trade‐off or synergy) stayed the same. Our results expand on previous studies by simultaneously considering the effect of land‐use intensification directly on functional composition and on the ecosystem processes underpinning ecosystem services, as well as on the relationship among them. We provide evidence of an indirect effect of land‐use intensification on multiple ecosystem services through biodiversity. Moreover, we found that functional identity is more important than diversity for ecosystem functionality. Land‐use intensification affects biodiversity, and thus, ecosystem properties, but does not change the relationship among ecosystem services. A plain language summary is available for this article.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.020
Threshold uncertainty score0.040

Distilled classifier scores by category (both heads)

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 communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.014
GPT teacher head0.223
Teacher spread0.209 · 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 source (direct Gemma or distilled Codex), 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

Citations72
Published2018
Admission routes1
Has abstractyes

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