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Record W4406428536 · doi:10.1093/molbev/msae270

Rapid Parallel Adaptation in Distinct Invasions of <i>Ambrosia Artemisiifolia</i> Is Driven by Large-Effect Structural Variants

2025· article· en· W4406428536 on OpenAlexaff
Paul Battlay, Sam Craig, Andhika R. Putra, Keyne Monro, Nissanka P De Silva, Jonathan Wilson, Vanessa C. Bieker, Saila Kabir, Nawar Shamaya, Lotte A. van Boheemen, Loren H. Rieseberg, John R. Stinchcombe, Alexandre Fournier‐Level, Michael D. Martin, Kathryn A. Hodgins

Bibliographic record

VenueMolecular Biology and Evolution · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicEcology and Vegetation Dynamics Studies
Canadian institutionsUniversity of TorontoUniversity of British Columbia
Fundersnot available
KeywordsBiologyAmbrosia artemisiifoliaAdaptation (eye)Evolutionary biologyAmbrosiaGeneticsBotanyRagweedNeuroscience

Abstract

fetched live from OpenAlex

When introduced to multiple distinct ranges, invasive species provide a compelling natural experiment for understanding the repeatability of adaptation. Ambrosia artemisiifolia is an invasive, noxious weed, and chief cause of hay fever. Leveraging over 400 whole-genome sequences spanning the native-range in North America and 2 invasions in Europe and Australia, we inferred demographically distinct invasion histories on each continent. Despite substantial differences in genetic source and effective population size changes during introduction, scans of both local climate adaptation and divergence from the native-range revealed genomic signatures of parallel adaptation between invasions. Disproportionately represented among these parallel signatures are 37 large haploblocks-indicators of structural variation-that cover almost 20% of the genome and exist as standing genetic variation in the native-range. Many of these haploblocks are associated with traits important for adaptation to local climate, like size and the timing of flowering, and have rapidly reformed native-range clines in invaded ranges. Others show extreme frequency divergence between ranges, consistent with a response to divergent selection on different continents. Our results demonstrate the key role of large-effect standing variants in rapid adaptation during range expansion, a pattern that is robust to diverse invasion histories.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.074
Threshold uncertainty score0.320

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 head0.005
GPT teacher head0.236
Teacher spread0.231 · 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

Citations16
Published2025
Admission routes1
Has abstractyes

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