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Record W4206902663 · doi:10.1101/2022.01.18.476846

Bergmann’s rule in <i>Microlophus</i> lizards: testing for latitudinal and climatic gradients of body size

2022· preprint· en· W4206902663 on OpenAlexaff
Ken S. Toyama, Christopher K. Boccia

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2022
Typepreprint
Languageen
FieldEnvironmental Science
TopicSpecies Distribution and Climate Change
Canadian institutionsQueen's UniversityUniversity of Toronto
Fundersnot available
KeywordsBergmann's ruleEctothermLatitudeBiologyEcologySexual dimorphismNatural selectionZoologyGeographyPopulationDemography

Abstract

fetched live from OpenAlex

ABSTRACT Broadscale environmental gradients exert selection pressures that can result in macroevolutionary patterns of phenotypic diversity. Bergmann’s rule, one of the most studied ecogeographical patterns, states that among related species or populations, larger body sizes should occur at higher latitudes or colder climates given the efficacy of larger sizes to conserve heat. However, there is still much debate regarding the mechanisms that underlie the rule and whether they should be different between endotherms and ectotherms. Here we test for Bergmann’s rule in Microlophus lizards, a genus distributed in western South America and the Galápagos Islands, and test for associations between body size and climatic variables. Our results indicate that mainland Microlophus species follow Bergmann’s rule, meaning that larger species are found towards the southernmost latitudes encompassed by the genus’ distribution. This relationship was similar for males and females, suggesting that patterns of sexual size dimorphism are not driven by differing latitudinal gradients of body size between the sexes. We identified negative associations between body size and temperature, precipitation, and isothermality, meaning that larger species are found in colder, drier, and more thermally variable environments. We discuss the possible mechanisms behind this pattern, the implications of insularity and ecology for the evolution of body size in this genus, and emphasize the need for additional natural history information to allow for the elucidation of the mechanisms behind the patterns presented in this work.

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)0.002
metaresearch head score (Gemma)0.007
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
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 head0.023
GPT teacher head0.235
Teacher spread0.212 · 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

Citations1
Published2022
Admission routes1
Has abstractyes

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