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Record W2343594205 · doi:10.1101/050773

Urbanization drives parallel adaptive clines in plant populations

2016· preprint· en· W2343594205 on OpenAlexaff
Ken Thompson, Marie Renaudin, Marc T. J. Johnson

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2016
Typepreprint
Languageen
FieldAgricultural and Biological Sciences
TopicCassava research and cyanide
Canadian institutionsAmgen (Canada)University of Toronto
Fundersnot available
KeywordsUrbanizationHerbivoreEcologyTrifolium repensBiologyAdaptive evolutionAbundance (ecology)BiodiversityPollinatorGeographyPollination

Abstract

fetched live from OpenAlex

Abstract Urban areas are a new and increasingly dominant feature of terrestrial landscapes that dramatically alter environments. It is unclear whether wild populations can adapt to the unique challenges presented by urbanization. To address this problem, we sampled the frequency of a Mendelian-inherited trait—cyanogenesis—in white clover ( Trifolium repens L.) plants along urbanization gradients in four large cities. Cyanogenesis protects plants from herbivores, but also reduces freezing tolerance. Plants evolved reduced cyanogenesis with increasing proximity to the urban center in three of the four cities. In an experiment, we demonstrate that gradients in herbivore pressure do not cause these clines. Instead, urban areas experience relatively cold minimum winter ground temperatures because of reduced snow cover within cities, which selects against cyanogenesis. Together, our study demonstrates that wild populations exhibit parallel adaptive evolution in response to urbanization, which likely facilitates the persistence of these plants and promotes pollinator abundance and diversity.

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 score0.841
Threshold uncertainty score0.601

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 head0.041
GPT teacher head0.241
Teacher spread0.200 · 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

Citations4
Published2016
Admission routes1
Has abstractyes

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