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Record W3098807819 · doi:10.1002/lol2.10176

Arctic seals as tracers of environmental and ecological change

2020· article· en· W3098807819 on OpenAlexaff
Camille de la Vega, Claire Mahaffey, Robyn E. Tuerena, David J. Yurkowski, Steven H. Ferguson, Garry B. Stenson, Erling S. Nordøy, Tore Haug, Martin Biuw, Sophie Smout, Jo Hopkins, Alessandro Tagliabue, Rachel M. Jeffreys

Bibliographic record

VenueLimnology and Oceanography Letters · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicIsotope Analysis in Ecology
Canadian institutionsFisheries and Oceans Canada
FundersNatural Environment Research CouncilSight Research UKUK Research and Innovation
KeywordsTrophic levelArcticFood webEcosystemEcologyEnvironmental scienceδ15NPredationMarine ecosystemApex predatorBayStable isotope ratioOceanographyBiologyGeologyδ13C

Abstract

fetched live from OpenAlex

Abstract Knowledge of species trophic position (TP) is an essential component of ecosystem management. Determining TP from stable nitrogen isotopes (δ 15 N) in predators requires understanding how these tracers vary across environments and how they relate to predator isotope composition. We used two seal species as a model for determining TP across large spatial scales in the Arctic. δ 15 N in seawater nitrate (δ 15 N NO3 ) and seal muscle amino acids (δ 15 N AA ) were determined to independently characterize the base of the food web and the TP of harp and ringed seals, demonstrating a direct link between δ 15 N NO3 and δ 15 N AA . Our results show that the spatial variation in δ 15 N AA in seals reflects the δ 15 N NO3 end members in Pacific vs. Atlantic waters. This study provides a reference for best practice on accurate comparison of TP in predators and as such, provides a framework to assess the impact of environmental and human‐induced changes on ecosystems at pan‐Arctic scales.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.016
Threshold uncertainty score0.917

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 studies0.0000.001
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 head0.011
GPT teacher head0.196
Teacher spread0.184 · 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

Citations19
Published2020
Admission routes1
Has abstractyes

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