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Record W2131574267 · doi:10.1890/07-1701.1

Development and application of DNA techniques for validating and improving pinniped diet estimates

2009· article· en· W2131574267 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueEcological Applications · 2009
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicIdentification and Quantification in Food
Canadian institutionsCanadian Sport Centre PacificFisheries and Oceans CanadaUniversity of British Columbia
FundersUniversity of VictoriaNational Science Foundation
KeywordsBiologyPredationCottidaeZoologyForage fishFisheryEcologySculpinFish <Actinopterygii>

Abstract

fetched live from OpenAlex

Polymerase chain reaction techniques were developed and applied to identify DNA from >40 species of prey contained in fecal (scat) soft-part matrix collected at terrestrial sites used by Steller sea lions (Eumetopias jubatus) in British Columbia and the eastern Aleutian Islands, Alaska. Sixty percent more fish and cephalopod prey were identified by morphological analyses of hard parts compared with DNA analysis of soft parts (hard parts identified higher relative proportions of Ammodytes sp., Cottidae, and certain Gadidae). DNA identified 213 prey occurrences, of which 75 (35%) were undetected by hard parts (mainly Salmonidae, Pleuronectidae, Elasmobranchii, and Cephalopoda), and thereby increased species occurrences by 22% overall and species richness in 44% of cases (when comparing 110 scats that amplified prey DNA). Prey composition was identical within only 20% of scats. Overall, diet composition derived from both identification techniques combined did not differ significantly from hard-part identification alone, suggesting that past scat-based diet studies have not missed major dietary components. However, significant differences in relative diet contributions across scats (as identified using the two techniques separately) reflect passage rate differences between hard and soft digesta material and highlight certain hypothesized limitations in conventional morphological-based methods (e.g., differences in resistance to digestion, hard part regurgitation, partial and secondary prey consumption), as well as potential technical issues (e.g., resolution of primer efficiency and sensitivity and scat subsampling protocols). DNA analysis of salmon occurrence (from scat soft-part matrix and 238 archived salmon hard parts) provided species-level taxonomic resolution that could not be obtained by morphological identification and showed that Steller sea lions were primarily consuming pink (Oncorhynchus gorbuscha) and chum (Oncorhynchus keta) salmon. Notably, DNA from Atlantic salmon (Salmo salar) that likely originated from a distant fish farm was also detected in two scats from one site in the eastern Aleutian Islands. Overall, molecular techniques are valuable for identifying prey in the fecal remains of marine predators. Combining DNA and hard-part identification will effectively alleviate certain predicted biases and will ultimately enhance measures of diet richness, fisheries interactions (especially salmon-related ones), and the ecological role of pinnipeds and other marine predators, to the benefit of marine wildlife conservationists and fisheries managers.

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.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.399
Threshold uncertainty score0.306

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.018
GPT teacher head0.293
Teacher spread0.274 · 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