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Record W2114685860 · doi:10.1111/nph.12908

The context dependence of beneficiary feedback effects on benefactors in plant facilitation

2014· article· en· W2114685860 on OpenAlexaff
Christian Schöb, Ragan M. Callaway, Fabien Anthelme, Rob W. Brooker, Lohengrin A. Cavieres, Zaal Kikvidze, Christopher J. Lortie, Richard Michalet, Francisco I. Pugnaire, Sa Xiao, Brittany H. Cranston, Nicole Hupp, Luis D. Llambí, Emanuele Lingua, Anya Reid, Liang Zhao, Bradley J. Butterfield

Bibliographic record

VenueNew Phytologist · 2014
Typearticle
Languageen
FieldEnvironmental Science
TopicEcology and Vegetation Dynamics Studies
Canadian institutionsUniversity of British ColumbiaYork University
FundersProgram for New Century Excellent Talents in UniversityComisión Nacional de Investigación Científica y TecnológicaUniversité de BordeauxNational Natural Science Foundation of ChinaSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungAgence Nationale de la RechercheNational Science Foundation
KeywordsBeneficiaryFacilitationContext (archaeology)ProductivityBiodiversityScale (ratio)PsychologyEcologyBusinessBiologyEconomicsGeographyNeuroscienceEconomic growth

Abstract

fetched live from OpenAlex

Facilitative effects of some species on others are a major driver of biodiversity. These positive effects of a benefactor on its beneficiary can result in negative feedback effects of the beneficiary on the benefactor and reduced fitness of the benefactor. However, in contrast to the wealth of studies on facilitative effects in different environments, we know little about whether the feedback effects show predictable patterns of context dependence. We reanalyzed a global data set on alpine cushion plants, previously used to assess their positive effects on biodiversity and the nature of the beneficiary feedback effects, to specifically assess the context dependence of how small- and large-scale drivers alter the feedback effects of cushion-associated (beneficiary) species on their cushion benefactors using structural equation modelling. The effect of beneficiaries on cushions became negative when beneficiary diversity increased and facilitation was more intense. Local-scale biotic and climatic conditions mediated these community-scale processes, having indirect effects on the feedback effect. High-productivity sites demonstrated weaker negative feedback effects of beneficiaries on the benefactor. Our results indicate a limited impact of the beneficiary feedback effects on benefactor cushions, but strong context dependence. This context dependence may help to explain the ecological and evolutionary persistence of this widespread facilitative system.

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 score0.061
Threshold uncertainty score0.988

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 head0.011
GPT teacher head0.231
Teacher spread0.220 · 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

Citations48
Published2014
Admission routes1
Has abstractyes

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