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Record W3094674137 · doi:10.1111/eva.13159

Selection on individuals of introduced species starts before the actual introduction

2020· article· en· W3094674137 on OpenAlexaff
Adrián Baños‐Villalba, Martina Carrete, José L. Tella, Julio Blas, Jaime Potti, Carlos Camacho, Moussa Diop, Tracy A. Marchant, Sonia Cabezas, Pim Edelaar

Bibliographic record

VenueEvolutionary Applications · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicWildlife Ecology and Conservation
Canadian institutionsUniversity of Saskatchewan
FundersMinisterio de Ciencia e Innovación
KeywordsBiologySelection (genetic algorithm)EcologyRange (aeronautics)Invasive species

Abstract

fetched live from OpenAlex

Abstract Biological invasion is a global problem with large negative impacts on ecosystems and human societies. When a species is introduced, individuals will first have to pass through the invasion stages of uptake and transport, before actual introduction in a non‐native range. Selection is predicted to act during these earliest stages of biological invasion, potentially influencing the invasiveness and/or impact of introduced populations. Despite this potential impact of pre‐introduction selection, empirical tests are virtually lacking. To test the hypothesis of pre‐introduction selection, we followed the fate of individuals during capture, initial acclimation, and captivity in two bird species with several invasive populations originating from the international trade in wild‐caught pets (the weavers Ploceus melanocephalus and Euplectes afer ). We confirm that pre‐introduction selection acts on a wide range of physiological, morphological, behavioral, and demographic traits (incl. sex, age, size of body/brain/bill, bill shape, body mass, corticosterone levels, and escape behavior); these are all traits which likely affect invasion success. Our study thus comprehensively demonstrates the existence of hitherto ignored selection acting before the actual introduction into non‐native ranges. This could ultimately change the composition and functioning of introduced populations, and therefore warrants greater attention. More knowledge on pre‐introduction selection also might provide novel targets for the management of invasive species, if pre‐introduction filters can be adjusted to change the quality and/or quantity of individuals passing through such that invasion probability and/or impacts are reduced.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.232
Threshold uncertainty score0.999

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)0.0020.001

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 head0.011
GPT teacher head0.206
Teacher spread0.195 · 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

Citations13
Published2020
Admission routes1
Has abstractyes

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