MétaCan
Menu
Back to cohort
Record W3203150004 · doi:10.3389/fgene.2021.708871

Location and Species Matters: Variable Influence of the Environment on the Gene Flow of Imperiled, Native and Invasive Cottontails

2021· article· en· W3203150004 on OpenAlexaff
Thomas J. McGreevy, Sozos Michaelides, Mihajla Djan, Mary Sullivan, Diana M. Beltrán, Bill Buffum, Thomas P. Husband

Bibliographic record

VenueFrontiers in Genetics · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic diversity and population structure
Canadian institutionsConcordia University
FundersYale University
KeywordsSympatric speciationGeneralist and specialist speciesGene flowBiologyEcologyGenetic diversityPopulationHabitatGenetic variationGeographyGeneDemographyGenetics

Abstract

fetched live from OpenAlex

The environment plays an important role in the movement of individuals and their associated genes among populations, which facilitates gene flow. Gene flow can help maintain the genetic diversity both within and between populations and counter the negative impact of genetic drift, which can decrease the fitness of individuals. Sympatric species can have different habitat preferences, and thus can exhibit different patterns of genetic variability and population structure. The specialist-generalist variation hypothesis (SGVH) predicts that specialists will have lower genetic diversity, lower effective population sizes (Ne), and less gene flow among populations. In this study, we used spatially explicit, individual-based comparative approaches to test SGVH predictions in two sympatric cottontail species and identify environmental variables that influence their gene flow. New England cottontail (Sylvilagus transitionalis) is the only native cottontail in the Northeast US, an early successional habitat specialist, and a species of conservation concern. Eastern cottontail (S. floridanus) is an invasive species in the Northeast US and a habitat generalist. We characterized each species’ genomic variation by developing double-digest Restriction-site Associated DNA sequence single nucleotide polymorphism markers, quantified their habitat with Geographic Information System environmental variables, and conducted our analyses at multiple scales. Surprisingly, both species had similar levels of genetic diversity and eastern cottontail’s Ne was only higher than New England cottontail in one of three subregions. At a regional level, the population clusters of New England cottontail were more distinct than eastern cottontail, but the subregional levels showed more geographic areas of restricted gene flow for eastern cottontail than New England cottontail. In general, the environmental variables had the predicted effect on each species’ gene flow. However, the most important environmental variable varied by subregion and species, which shows that location and species matter. Our results provide partial support for the SGVH and the identification of environmental variables that facilitate or impede gene flow can be used to help inform management decisions to conserve New England cottontail.

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 score0.014
Threshold uncertainty score0.028

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 head0.005
GPT teacher head0.175
Teacher spread0.170 · 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

Citations5
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueFrontiers in GeneticsSame topicGenetic diversity and population structureFrench-language works237,207