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Record W1601698169 · doi:10.1111/bij.12556

Biometrical analysis reveals major differences between the two subspecies of the European rabbit

2015· article· en· W1601698169 on OpenAlexaff
Catarina Ferreira, Francisca Castro, Vicente Piorno, Isabel C. Barrio, Miguel Delibes‐Mateos, Carlos Rouco, Luis Alberto Mínguez-Mínguez, Fernando Aparicio, José Blanco, Esther Ramírez, Candelaria Iriarte, Carlos Antonio Ríos‐Saldaña, Jesús Cañadilla, Luis Arias de Reyna, Pablo Ferreras, Paulo C. Alves, Rafael Villafuerte

Bibliographic record

VenueBiological Journal of the Linnean Society · 2015
Typearticle
Languageen
FieldEnvironmental Science
TopicAnimal Ecology and Behavior Studies
Canadian institutionsUniversity of AlbertaTrent University
FundersEuropean Regional Development FundFundação Luso-Americana para o Desenvolvimento
KeywordsSubspeciesBiologyRange (aeronautics)PeninsulaEcologyZoologyBiometricsPhylogeographyHabitatPhylogenetics

Abstract

fetched live from OpenAlex

The climatic oscillations that have occurred in the last few million years have strongly affected species distribution ranges. Highly divergent genetic lineages arose, some of which correspond to recognized subspecies that currently occupy small geographical areas. Understanding the implications of the genetic differences between these subspecies is crucial for proper conservation of Evolutionarily Significant Units. We use the two European rabbit subspecies, Oryctolagus cuniculus cuniculus and O. c. algirus, in the Iberian Peninsula as a model to investigate the repercussions at the biometric level of their largely recognized genetic differentiation. To accomplish this we analysed the ear and hind foot length, and the body mass of 999 adult rabbits from 27 locations across the distribution range of both subspecies in their native range, the Iberian Peninsula. Our results show biometric differences between the two subspecies, also explained by geographical location and sex, O. c. algirus being lighter and having shorter ear and hind foot lengths. We examine these findings under an evolutionary framework, and discuss their implications for current conservation efforts. Future research should focus on the ecological implications of these biometric differences, namely potential different habitat use and anti-predatory strategies in the species' native range.

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)0.002
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 score0.003
Threshold uncertainty score0.647

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.001
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.096
GPT teacher head0.290
Teacher spread0.194 · 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

Citations22
Published2015
Admission routes1
Has abstractyes

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