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Record W4221078397 · doi:10.1002/ecy.3675

Competitive size asymmetry, not intensity, is linked to species loss and gain in a native grassland community

2022· article· en· W4221078397 on OpenAlexafffund
Charlotte Brown, James F. Cahill

Bibliographic record

VenueEcology · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicEcology and Vegetation Dynamics Studies
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaAlberta Conservation Association
KeywordsCompetition (biology)GrasslandCoexistence theoryEcologyAsymmetryBiologyPlant communityBiodiversitySpecies richnessPhysics

Abstract

fetched live from OpenAlex

Competition is often highlighted as a major force influencing plant species diversity. However, there are multiple facets of competition (e.g., strength, intransitivity, and size asymmetry) that may have independent and differential impacts on diversity, making understanding the degree to which competition structures communities difficult. Unfortunately, field-based experiments that decouple multiple facets of competition are lacking, limiting our ability to test theoretical frameworks and reducing understanding of the actual linkages among competition and coexistence. Here, we experimentally manipulate the size structure of local grassland communities to examine the relative impacts of competitive size asymmetry (i.e., competitive advantage based on relative size) and intensity (i.e., mean effect of neighbors on plant growth) on species loss and gain. Increased competitive size asymmetry was associated with increased species loss and decreased species gain, while no relationship was found between competitive intensity and species loss and gain. Furthermore, the probability of loss was not dependent on a species initial size, suggesting that small species may not always be the losers of size-asymmetric interactions. Instead, loss was dependent on species rarity, where loss was higher for rare species. Overall, these results suggest that competitive size asymmetry may be more important for species loss than intensity in some plant communities and demonstrates the importance of decoupling different aspects of competition to better understand their drivers and ecological consequences.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.048
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.016
GPT teacher head0.249
Teacher spread0.233 · 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

Citations19
Published2022
Admission routes2
Has abstractyes

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