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Record W2968443814 · doi:10.1002/ecs2.2840

Evidence of limiting similarity revealed using a conservative assessment of coexistence

2019· article· en· W2968443814 on OpenAlexafffund
Brandon S. Schamp, Ashley M. Jensen

Bibliographic record

VenueEcosphere · 2019
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and animal studies
Canadian institutionsAlgoma University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsSimilarity (geometry)LimitingEcologyNicheNull hypothesisNull modelEmpirical evidenceBiologyPredictive powerEvolutionary biologyComputer scienceEconometricsMathematicsArtificial intelligenceEpistemologyEngineering

Abstract

fetched live from OpenAlex

Abstract The concept of limiting similarity is important in ecology because it encapsulates the expectation under niche theory that differences among species are fundamental to coexistence. A growing body of research has tested for evidence of limiting similarity, but only a small number of studies have produced support. Here, using relevant field data, we highlight one possible explanation for the paucity of support for limiting similarity. We test whether coexisting plant species that share bees as pollinators flower asynchronously, a form of temporal niche separation consistent with limiting similarity. Our results provide evidence of limiting similarity, adding to the small collection of null modeling studies that have thus far done so. Our work also provides evidence that temporal niche variation may be an important niche axis that broadly contributes to species coexistence. Finally, we demonstrate that a more conservative assessment of coexistence that includes only individual plants that have achieved reproduction, is consequential in whether we find evidence of significant flowering asynchrony in this study. We conclude that the conservative approach to assessing coexistence that we present here can reduce noise in coexistence data, improving our power to test for evidence consistent with limiting similarity. Using this approach may or may not result in an increase in evidence supporting limiting similarity; however, it will certainly give researchers more confidence that they have not missed existing evidence of limiting similarity.

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 score0.487
Threshold uncertainty score0.470

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 head0.179
GPT teacher head0.303
Teacher spread0.124 · 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

Citations12
Published2019
Admission routes2
Has abstractyes

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