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Record W2798468864 · doi:10.1101/310714

Anthropogenic habitat alteration leads to rapid loss of adaptive variation and restoration potential in wild salmon populations

2018· preprint· en· W2798468864 on OpenAlexaff
Tasha Q. Thompson, Renee M. Bellinger, Sean O’Rourke, Daniel J. Prince, Alexander E. Stevenson, Antonia Rodrigues, Matthew R. Sloat, Camilla Speller, Dongya Yang, Virginia L. Butler, Michael A. Banks, Michael R. Miller

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2018
Typepreprint
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsSimon Fraser University
FundersNational Oceanic and Atmospheric AdministrationGordon and Betty Moore Foundation
KeywordsPhenotypic plasticityBiologyHabitatAlleleLocus (genetics)EcologyGenetic variationPhenotypeEvolutionary biologyGeneticsGene

Abstract

fetched live from OpenAlex

Abstract Phenotypic variation is critical for the long-term persistence of species and populations. Anthropogenic activities have caused substantial shifts and reductions in phenotypic variation across diverse taxa, but the underlying mechanism (i.e., phenotypic plasticity and/or genetic evolution) and potential to recover previous phenotypic characteristics are unclear. Here we investigate changes in adult migration characteristics of wild salmon populations caused by dam construction and other anthropogenic habitat modifications. Strikingly, we find that dramatic allele frequency change (i.e., genetic evolution) from strong selection at a single locus explains the rapid phenotypic shift observed after recent dam construction. Furthermore, ancient DNA analysis confirms the abundance of a specific allele associated with adult migration type in historical habitat that will soon become accessible through a large restoration (i.e., dam removal) project. However, analysis of contemporary samples suggests the restoration will be challenged by loss of the allele from potential source populations. These results highlight the need to conserve and restore critical adaptive variation before the potential for recovery is lost.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.117
Threshold uncertainty score1.000

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 science0.0000.001
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 head0.015
GPT teacher head0.227
Teacher spread0.212 · 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.

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

Citations45
Published2018
Admission routes1
Has abstractyes

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