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Record W2800929656 · doi:10.1002/ecy.2346

Effects of intraspecific phenotypic variation on species coexistence

2018· article· en· W2800929656 on OpenAlexafffund
Stephen Hausch, Steven M. Vamosi, Jeremy W. Fox

Bibliographic record

VenueEcology · 2018
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and animal studies
Canadian institutionsUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsIntraspecific competitionBiologyInterspecific competitionEcologyCoexistence theoryStorage effectEvolutionary biology

Abstract

fetched live from OpenAlex

Intraspecific variation can promote or inhibit species coexistence, both by increasing species' competitive abilities, and by altering the relative strengths of intraspecific and interspecific competition. Effects of intraspecific variation on coexistence can occur via complementarity of different variants, and via a selection effect: initially-variable populations are more likely to contain highly competitive variants that might determine the ability of the population as a whole to both invade and resist invasion. We tested the effects of intraspecific variation and composition on coexistence by assaying the mutual invasibility of populations of two competing bean weevil species (Callosobruchus maculatus and C. chinensis) when each was initiated with one, three, or five genetically- and phenotypically-distinct lineages. Our results reveal that intraspecific variation is a double-edged sword for species coexistence. Increasing intraspecific variation increased species' abilities to invade, and to resist invasion, via selection effects and intraspecific niche complementarity among conspecific lineages, thereby creating the potential for exclusion among mismatched competitors. But intraspecific variation also increased the scope for resource partitioning, creating the potential for stable coexistence. Stable coexistence occurred only when intraspecific variation caused species to exhibit both relatively evenly-matched competitive abilities and sufficiently-strong resource partitioning. Our work explains the conflicting results of previous studies.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.964
Threshold uncertainty score0.379

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 head0.029
GPT teacher head0.203
Teacher spread0.173 · 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

Citations54
Published2018
Admission routes2
Has abstractyes

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