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Record W4367173643 · doi:10.1126/science.abn5856

The contribution of historical processes to contemporary extinction risk in placental mammals

2023· article· en· W4367173643 on OpenAlexaff
Aryn P. Wilder, Megan A. Supple, Ayshwarya Subramanian, Anish Mudide, Ross Swofford, Aitor Serres‐Armero, Cynthia Steiner, Klaus‐Peter Koepfli, Diane P. Genereux, Elinor K. Karlsson, Kerstin Lindblad‐Toh, Tomàs Marquès‐Bonet, Violeta Muñoz‐Fuentes, Kathleen Foley, Wynn K. Meyer, Oliver A. Ryder, Beth Shapiro, Gregory Andrews, Joel Armstrong, Matteo Bianchi, Susan J. Birren, Kevin R. Bredemeyer, Ana M. Breit, Matthew J. Christmas, Hiram Clawson, Joana Damas, Federica Di Palma, Mark Diekhans, Michael X. Dong, Eduardo Eizirik, Kaili Fan, Cornelia Fanter, Nicole M. Foley, Karin Forsberg‐Nilsson, Carlos J. Garcia, John Gatesy, Steven Gazal, Linda Goodman, Jenna Grimshaw, Michaela K. Halsey, Andrew J. Harris, Glenn Hickey, Michael Hiller, Allyson G. Hindle, Robert Hubley, Graham M. Hughes, Jeremy Johnson, David Juan, Irene M. Kaplow, Kathleen C. Keough, Bogdan Kirilenko, Jennifer M. Korstian, Amanda Kowalczyk, Sergey V. Kozyrev, Alyssa J. Lawler, Colleen Lawless, Thomas Lehmann, Danielle L. Levesque, Harris A. Lewin, Xue Li, Abigail Lind, Ava Mackay-Smith, Voichita D. Marinescu, Victor C. Mason, Jennifer R. S. Meadows, Jill E. Moore, Lucas R. Moreira, Diana D. Moreno-Santillán, Kathleen M. Morrill, Gerard Muntané, William J. Murphy, Arcadi Navarro, Martin Nweeia, Sylvia Ortmann, Austin Osmanski, Benedict Paten, Nicole S. Paulat, Andreas R. Pfenning, BaDoi N. Phan, Katherine S. Pollard, Henry Pratt, David A. Ray, Steven K. Reilly, Jeb Rosen, Irina Ruf, Louise Ryan, Pardis C. Sabeti, Daniel E. Schäffer, Aitor Serres, Arian F. A. Smit, Mark S. Springer, Chaitanya Srinivasan, Jessica M. Storer, Kevin A. Sullivan, Patrick F. Sullivan, Elisabeth Sundström, Joy-El Talbot, Emma C. Teeling, Jason Turner-Maier, Alejandro Valenzuela, Franziska Wagner, Ola Wallerman, Chao Wang, Juehan Wang, Zhiping Weng, Morgan Wirthlin, James R. Xue, Xiaomeng Zhang

Bibliographic record

VenueScience · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicWildlife Ecology and Conservation
Canadian institutionsCanadian Museum of NatureGenome British Columbia
FundersNational Human Genome Research InstituteNational Cancer InstituteNational Institutes of HealthVetenskapsrådetGeneralitat de CatalunyaBroad InstituteEuropean CommissionCentres de Recerca de CatalunyaAgencia Estatal de InvestigaciónHoward Hughes Medical Institute
KeywordsExtinction (optical mineralogy)BiologyGeographyPaleontology

Abstract

fetched live from OpenAlex

Species persistence can be influenced by the amount, type, and distribution of diversity across the genome, suggesting a potential relationship between historical demography and resilience. In this study, we surveyed genetic variation across single genomes of 240 mammals that compose the Zoonomia alignment to evaluate how historical effective population size ( N e ) affects heterozygosity and deleterious genetic load and how these factors may contribute to extinction risk. We find that species with smaller historical N e carry a proportionally larger burden of deleterious alleles owing to long-term accumulation and fixation of genetic load and have a higher risk of extinction. This suggests that historical demography can inform contemporary resilience. Models that included genomic data were predictive of species’ conservation status, suggesting that, in the absence of adequate census or ecological data, genomic information may provide an initial risk assessment.

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)0.001
metaresearch head score (Gemma)0.005
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 score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
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 head0.014
GPT teacher head0.239
Teacher spread0.225 · 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

Citations104
Published2023
Admission routes1
Has abstractyes

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