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Record W4408162245 · doi:10.1002/ece3.71024

Climate but Not Land Use Influences Body Size of Fowler's Toad (<i>Anaxyrus fowleri</i>)

2025· article· en· W4408162245 on OpenAlexaff
Paradyse E. Blackwood, Amanda K. Martin, Jennifer A. Sheridan

Bibliographic record

VenueEcology and Evolution · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicPhysiological and biochemical adaptations
Canadian institutionsUniversity of British Columbia
FundersNational Science Foundation Graduate Research Fellowship Program
KeywordsToadEnvironmental scienceEcologyGeographyPhysical geographyBiology

Abstract

fetched live from OpenAlex

ABSTRACT Anthropogenic changes to the environment have been associated with changes in body size of multiple organisms. However, although climate and land use influences on body size have been examined separately, the simultaneous effects and potential interactions of these two factors on body size have rarely been studied. We examined the size and mass of a common North American toad (Fowler's toad, Anaxyrus fowleri) using museum specimens from 1931 to 1998 to quantify the potential interactive effects of climate change (temperature and precipitation) and land use change (forested area) on body size. We found that snout–vent length (SVL) and mass declined over time, and that size was negatively related to both temperature and precipitation (smaller size at higher values of temperature and precipitation). We did not find evidence of an effect of forest cover on size or mass. Our results suggest that Fowler's toad body size is affected by climate but not land use, and we encourage further examination of additional species and land cover variables (such as urbanization) to determine whether our results are representative of ectotherms more broadly. This work highlights the strength of climate in determining anuran body size and contrasts with existing studies showing interactive effects of climate and land use on animal body size.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.010
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

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)0.0020.000

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 head0.010
GPT teacher head0.224
Teacher spread0.214 · 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

Citations2
Published2025
Admission routes1
Has abstractyes

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