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Record W2900500182 · doi:10.1038/s41467-018-06695-z

Demographic histories and genetic diversity across pinnipeds are shaped by human exploitation, ecology and life-history

2018· article· en· W2900500182 on OpenAlexaff
Martin A. Stoffel, Emily Humble, A.J. Paijmans, Karina Acevedo‐Whitehouse, B. Louise Chilvers, Bobette R. Dickerson, Filippo Galimberti, Neil J. Gemmell, Simon Goldsworthy, Hazel J. Nichols, Oliver Krüger, Sandra S. Negro, Amy J. Osborne, Teresa Pastor, Bruce C. Robertson, Simona Sanvito, Jennifer K. Schultz, Aaron B. A. Shafer, Jochen B. W. Wolf, Joseph I. Hoffman

Bibliographic record

VenueNature Communications · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine animal studies overview
Canadian institutionsTrent University
FundersDeutsche ForschungsgemeinschaftNatural Environment Research CouncilSight Research UK
KeywordsEcologyBiodiversityPopulation bottleneckGenetic diversityConservation biologyBiologyPopulationDemographic historyEndangered speciesIUCN Red ListPopulation sizeConservation geneticsEffective population sizeHabitat destructionHabitatDemography

Abstract

fetched live from OpenAlex

A central paradigm in conservation biology is that population bottlenecks reduce genetic diversity and population viability. In an era of biodiversity loss and climate change, understanding the determinants and consequences of bottlenecks is therefore an important challenge. However, as most studies focus on single species, the multitude of potential drivers and the consequences of bottlenecks remain elusive. Here, we combined genetic data from over 11,000 individuals of 30 pinniped species with demographic, ecological and life history data to evaluate the consequences of commercial exploitation by 18th and 19th century sealers. We show that around one third of these species exhibit strong signatures of recent population declines. Bottleneck strength is associated with breeding habitat and mating system variation, and together with global abundance explains much of the variation in genetic diversity across species. Overall, bottleneck intensity is unrelated to IUCN status, although the three most heavily bottlenecked species are endangered. Our study reveals an unforeseen interplay between human exploitation, animal biology, demographic declines and genetic diversity.

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)0.001
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 score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
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 head0.032
GPT teacher head0.273
Teacher spread0.241 · 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

Citations108
Published2018
Admission routes1
Has abstractyes

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