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Record W2979295304 · doi:10.1139/cjz-2019-0108

Seasonal differences in foraging and isotopic niche width related to body size in Gulf of Alaska harbor seals

2019· article· en· W2979295304 on OpenAlexvenueno aff
Justin S. Smith, Shawna Karpovich, Lara Horstmann, Julie McIntyre, Diane M. O’Brien

Bibliographic record

VenueCanadian Journal of Zoology · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine animal studies overview
Canadian institutionsnot available
FundersU.S. Fish and Wildlife ServiceNational Marine Fisheries ServiceNational Fish and Wildlife Foundation
KeywordsPhocaForagingBiologyIsotope analysisEcologyHarbor sealGlacial periodPopulationStable isotope ratioHabitatδ13C

Abstract

fetched live from OpenAlex

Harbor seals (Phoca vitulina Linnaeus, 1758) use different foraging strategies based on body size and sex, but this difference can be difficult to evaluate across seasons. We used stable isotope analysis of harbor seal whiskers from 32 individuals to assess seasonal foraging of seals inhabiting tidewater glacial habitat in Southeast Alaska. We analyzed stable isotope ratios from serial sections of whiskers, estimated deposition date for each section, and used mixed models to determine if sex and body size influence stable isotope ratios. Seals were grouped by size (>1.4 m or ≤1.4 m curvilinear length) as a proxy for sexual maturity to describe isotopic differences between groups using standard ellipse corrected area. Mean carbon and nitrogen isotope ratios differed significantly between size classes (p < 0.005), with no effect of sex. Larger seals exhibited a broader isotopic niche in the fall, winter, and spring relative to smaller seals, but not in the summer. Our results suggest that seals using tidewater glacial habitat share common foraging behavior in the summer, while larger seals exhibit more diverse foraging throughout the rest of the year. These results highlight the importance of tidewater glacial habitat for this population of harbor seals during the summer.

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 score0.015
Threshold uncertainty score0.030

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)0.0010.000

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 head0.009
GPT teacher head0.213
Teacher spread0.204 · 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

Citations8
Published2019
Admission routes1
Has abstractyes

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