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Do biotic interactions shape both sides of the humped‐back model of species richness in plant communities?

2006· article· en· W1974820063 on OpenAlexaff
Richard Michalet, Robin W. Brooker, Lohengrin A. Cavieres, Zaal Kikvidze, Christopher J. Lortie, Francisco I. Pugnaire, Alfonso Valiente‐Banuet, Ragan M. Callaway

Bibliographic record

VenueEcology Letters · 2006
Typearticle
Languageen
FieldEnvironmental Science
TopicEcology and Vegetation Dynamics Studies
Canadian institutionsYork University
FundersNatural Environment Research Council
KeywordsSpecies richnessNicheEcologyFacilitationBiomass (ecology)Competition (biology)Plant communityStructuringCommunity structureProductivityBiologyEconomics

Abstract

fetched live from OpenAlex

A humped-back relationship between species richness and community biomass has frequently been observed in plant communities, at both local and regional scales, although often improperly called a productivity-diversity relationship. Explanations for this relationship have emphasized the role of competitive exclusion, probably because at the time when the relationship was first examined, competition was considered to be the significant biotic filter structuring plant communities. However, over the last 15 years there has been a renewed interest in facilitation and this research has shown a clear link between the role of facilitation in structuring communities and both community biomass and the severity of the environment. Although facilitation may enlarge the realized niche of species and increase community richness in stressful environments, there has only been one previous attempt to revisit the humped-back model of species richness and to include facilitative processes. However, to date, no model has explored whether biotic interactions can potentially shape both sides of the humped-back model for species richness commonly detected in plant communities. Here, we propose a revision of Grime's original model that incorporates a new understanding of the role of facilitative interactions in plant communities. In this revised model, facilitation promotes diversity at medium to high environmental severity levels, by expanding the realized niche of stress-intolerant competitive species into harsh physical conditions. However, when environmental conditions become extremely severe the positive effects of the benefactors wane (as supported by recent research on facilitative interactions in extremely severe environments) and diversity is reduced. Conversely, with decreasing stress along the biomass gradient, facilitation decreases because stress-intolerant species become able to exist away from the canopy of the stress-tolerant species (as proposed by facilitation theory). At the same time competition increases for stress-tolerant species, reducing diversity in the most benign conditions (as proposed by models of competition theory). In this way our inclusion of facilitation into the classic model of plant species diversity and community biomass generates a more powerful and richer predictive framework for understanding the role of plant interactions in changing diversity. We then use our revised model to explain both the observed discrepancies between natural patterns of species richness and community biomass and the results of experimental studies of the impact of biodiversity on the productivity of herbaceous communities. It is clear that explicit consideration of concurrent changes in stress-tolerant and competitive species enhances our capacity to explain and interpret patterns in plant community diversity with respect to environmental severity.

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)0.004
metaresearch head score (Gemma)0.013
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.013
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0010.001
Science and technology studies0.0010.006
Scholarly communication0.0020.005
Open science0.0030.002
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.018
GPT teacher head0.221
Teacher spread0.203 · 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

Citations633
Published2006
Admission routes1
Has abstractyes

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