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Record W149591681

Investigating the conservation genetics small population paradigm using the brook trout (Salvelinus fontinalis): do small populations have less adaptive potential?

2014· dissertation· en· W149591681 on OpenAlexfundaboutno aff
Jacquelyn L. A. Wood

Bibliographic record

VenueSpectrum Research Repository (Concordia University) · 2014
Typedissertation
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic and phenotypic traits in livestock
Canadian institutionsnot available
FundersFisheries and Oceans CanadaNatural Sciences and Engineering Research Council of CanadaDalhousie UniversityConcordia University
KeywordsSalvelinusBiologyTroutPopulationEcologyHabitat fragmentationLocal adaptationPopulation sizeConservation geneticsPopulation fragmentationFontinalisHabitatPopulation geneticsEvolutionary biologyGenetic variationGene flowDemographyGeneticsFisheryAllele
DOInot available

Abstract

fetched live from OpenAlex

The conservation genetics small population paradigm predicts reduced quantitative genetic variation and consequently, adaptive potential, for populations which have become small and isolated due to habitat fragmentation. While these expectations are supported by laboratory studies, their generality in wild populations remain unresolved. In actuality, the evolutionary consequences of fragmentation may depend on whether environmental characteristics– and by extension, selective regimes are (1) shifted in a consistent directional manner as is widely assumed (Directional hypothesis), or (2) become more variable as population and fragment size decrease (Variable hypothesis); this latter possibility has so far received little empirical attention.
\nImplementing field techniques, I explore these two competing hypotheses by relating variability in habitat characteristics to population size in a series of differentially abundant brook trout (Salvelinus fontinalis) populations located at Cape Race, Newfoundland. I furthermore use these hypotheses as a foundation to test the assumptions of the conservation genetic small population paradigm by investigating the relationships of population size at Cape Race to additive genetic variation (VA), trait differentiation (QST), and phenotypic plasticity in common garden analyses, and to the extent of natural selection in a meta-analysis using a large number of natural populations and species.
\nAcross two years and in relation to two population size metrics, patterns of habitat characteristics among small versus large Cape Race populations supported the Variable hypothesis. However, small brook trout populations did not significantly differ from large populations in either the magnitude or variability of VA, QST, or phenotypic plasticity. Results of the meta-analysis similarly revealed little support for differences in the strength, direction, and form of selection among wild populations differing in population size. The lack of differences might be explained by long term fluctuating environmental conditions which resulted in fluctuating selective pressures and similar outcomes among small compared to large Cape Race populations, and among the species included in the meta-analysis.
\nOverall, the results of this research contradict the assumption that small populations generally inhabit marginal environments and also dispute the major tenets of the conservation genetics small population paradigm. Taken together, they suggest that even very small populations of some species may retain the adaptive potential necessary to cope with future environmental change.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.397
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
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 head0.065
GPT teacher head0.288
Teacher spread0.223 · 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

Citations0
Published2014
Admission routes2
Has abstractyes

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