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Decoding the Past: Evolutionary History of North American Deer Mouse Populations on the Gulf Islands

2024· dissertation· en· W4399778154 on OpenAlexaboutno aff
Rachel Ann Berg

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldEnvironmental Science
TopicAnimal Ecology and Behavior Studies
Canadian institutionsnot available
Fundersnot available
KeywordsBiologyPeromyscusEcologyGigantismMainlandPopulationMicroevolutionInsular biogeographyHabitatSubfossilZoologyGeographyDemography

Abstract

fetched live from OpenAlex

Anthropogenic habitat fragmentation is increasing the number of small and isolated organismal populations, and the long-term effects of these recent isolations are not well understood. Small populations are at increased risk of extinction thus it is essential to identify populations that have been isolated over long time periods to use as model systems to study consequences of isolation. Besides understanding genetic consequences, isolated populations may also serve as natural systems to study morphological changes in populations that have independent evolutionary trajectories. Investigating island populations may help in the discovery of long-term isolated populations that may be experiencing morphological changes as well. Island populations of small land vertebrates frequently exhibit insular gigantism, presenting with larger body sizes in comparison to mainland counterparts. I studied historic population isolation and presence of insular gigantism of North American Deer Mice (Peromyscus maniculatus) in the Gulf Islands of British Columbia, Canada. These islands were isolated after sea-level rise following the Pleistocene ice age. I hypothesized that the order and timeline of island separation, due to a rise in local sea level, affected the phylogenetic relationship of island populations, through genetic isolation. Furthermore, I expected to find evidence of island gigantism in these isolated island populations. I live trapped Deer Mice on nine of the Gulf Islands, as well as the mainland and took tissue samples for DNA extraction and recorded body mass. Samples were sequenced at low depth (2x, n=160) and high depth (20x, n=10). Analyses indicate genetic isolation of the smaller island populations as well as mainland populations. Furthermore, evidence from high depth samples indicate population divergence of several thousand years. I also found presence of insular gigantism in the Gulf Islands system. Examining the evolution of island body size is becoming increasingly imperative as populations experiencing gigantism and dwarfism are under greater extinction threat. Island populations with these morphological extremes may be under even greater threat if they are also small and isolated. Understanding the evolutionary history of these populations will provide insight into future work regarding the evolution of small, isolated populations and how some have persisted through time.

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 score0.967
Threshold uncertainty score0.067

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 communication0.0000.000
Open science0.0000.000
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 head0.026
GPT teacher head0.262
Teacher spread0.236 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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