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Climate change reduces genetic diversity of Canada lynx at the trailing range edge

2014· article· en· W2047169728 on OpenAlexafffundabout
Erin L. Koen, Jeff Bowman, Dennis L. Murray, Paul J. Wilson

Bibliographic record

VenueEcography · 2014
Typearticle
Languageen
FieldEnvironmental Science
TopicWildlife Ecology and Conservation
Canadian institutionsMinistry of Natural Resources and ForestryTrent University
FundersNatural Sciences and Engineering Research Council of CanadaU.S. Fish and Wildlife ServiceCanada Research ChairsMinistry of Natural Resources
KeywordsRange (aeronautics)Climate changeEcologyGeographyGenetic diversityDiversity (politics)Trailing edgeBiologyDemographyPopulation

Abstract

fetched live from OpenAlex

Shifts in species distributions due to environmental change may affect the spatial pattern of genetic structure within a species' range, including possible changes to the adaptive potential of populations. We investigated spatial patterns of neutral genetic diversity and differentiation at the southern edge of the Canada lynx Lynx canadensis distribution in Ontario, Canada. We analyzed provincial fur harvest records (1972–2010) and collected and genotyped lynx pelt samples (2007–2009) from 702 lynx at 14 microsatellite loci. We show that the southern range boundary of lynx in central Canada has contracted northward by > 175 km since the 1970s, and that high winter temperature, low snow depth, and low proportion of suitable habitat are strongly correlated with low neutral genetic diversity and high genetic differentiation at the trailing range edge. Our work tests fundamental ideas about species range limits and demonstrates that environmental conditions can have a marked influence on neutral genetic structure. Our results suggest that changes in environmental conditions will result in further loss of genetic diversity and possibly reduce adaptive potential in southern peripheral lynx populations.

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 score0.388
Threshold uncertainty score0.965

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)0.0010.000

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 head0.012
GPT teacher head0.178
Teacher spread0.165 · 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

Citations41
Published2014
Admission routes3
Has abstractyes

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