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Record W4396917462 · doi:10.1098/rsbl.2023.0509

Is competitive ability the key adaptation to benign environments? Revisiting experiments on closely related species of tidal plants

2024· article· en· W4396917462 on OpenAlexafffund
Paul R. Martin, Cameron K. Ghalambor

Bibliographic record

VenueBiology Letters · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicEcology and Vegetation Dynamics Studies
Canadian institutionsKingston Health Sciences CentreQueen's University
FundersNatural Sciences and Engineering Research Council of CanadaNational Science Foundation
KeywordsBiologyAdaptation (eye)Local adaptationEcologyCompetition (biology)Divergence (linguistics)Evolutionary biologyTaxonReciprocalContrast (vision)Neuroscience

Abstract

fetched live from OpenAlex

A central goal in biology is to understand which traits underlie adaptation to different environments. Yet, few studies have examined the relative contribution of competitive ability towards adaptive divergence among species occupying distinct environments. Here, we test the relative importance of competitive ability as an adaptation to relatively benign versus challenging environments, using previously published studies of closely related species pairs of primarily tidal plants subjected to reciprocal removal with transplant experiments in nature. Subordinate species typically occupy more challenging environments and showed consistent evidence for adaptation to challenging conditions, with no significant competitive effect on non-local, dominant species. In contrast, dominant species typically occupy relatively benign environments and performed significantly better than non-local, subordinate species that faced competition from the dominant species. Surprisingly, when the two species were not allowed to compete, the subordinate species performed as well as the dominant species in the benign environments where the subordinate species do not occur. These results suggest that competitive ability is the most important adaptation distinguishing the species that occupy relatively benign environments. The limited scope and number of suitable experimental studies encourage future work to test if these results are generalizable across taxa and environments.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.002
Scholarly communication0.0000.001
Open science0.0010.002
Research integrity0.0000.001
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 head0.021
GPT teacher head0.254
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 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

Citations5
Published2024
Admission routes2
Has abstractyes

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