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Record W2138364485 · doi:10.1111/mec.13014

Foundations of invasion genetics: the Baker and Stebbins legacy

2014· article· en· W2138364485 on OpenAlexafffund
Spencer C. H. Barrett

Bibliographic record

VenueMolecular Ecology · 2014
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and animal studies
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsBiologyEcological geneticsHuman evolutionary geneticsPopulation geneticsEvolutionary biologyQuantitative geneticsEcologyPhenotypic plasticityEvolutionary ecologyGenetic variationVariation (astronomy)GeneticsPopulationPhylogeneticsDemographySociologyGene

Abstract

fetched live from OpenAlex

Invasion genetics is a relatively new discipline that investigates patterns of genetic variation in populations of invasive species and their ecological and evolutionary consequences. Evolutionary biologists have a long-standing interest in colonizing species, owing to their short life cycles and widespread distributions, but not until publication of The Genetics of Colonizing Species (1965), edited by H.G. Baker and G.L. Stebbins, was a synthesis on the genetics and evolution of colonizers available. Here, I make the case that the Baker and Stebbins volume is the foundational document for invasion genetics, and in conjunction with the increased use of genetic markers and development of invasion biology, resulted in the birth of this new field over the past two decades. I consider the historical origins and legacy of the Baker and Stebbins volume and review some of the key issues that were addressed. I provide biographical sketches of the two editors, emphasizing their contrasting backgrounds and personalities. I review examples from my own work on plant invasions that are relevant to issues discussed by contributors to the volume. These include the following: determinants of invasion success, life history trade-offs, generalist vs. specialist strategies, general-purpose genotypes, adaptive phenotypic plasticity, mating systems and the influence of bottlenecks on genetic variation. I conclude by posing several key questions in invasion genetics and argue that one of the main challenges that the area faces is to integrate experimental field studies of the ecology and demography of populations with the largely descriptive approaches that have tended to dominate most research to date.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.860
Threshold uncertainty score0.129

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)0.0000.000

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 head0.028
GPT teacher head0.210
Teacher spread0.181 · 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

Citations129
Published2014
Admission routes2
Has abstractyes

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