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Why do Californian striders fly?

2008· article· en· W2062982348 on OpenAlexfundno aff
Daphne J. Fairbairn, Elizabeth G. King

Bibliographic record

VenueJournal of Evolutionary Biology · 2008
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of California, DavisNational Oceanic and Atmospheric Administration
KeywordsBiologyEcologyHabitatAdaptation (eye)STREAMS

Abstract

fetched live from OpenAlex

Discerning the adaptive significance of migratory strategies poses significant challenges, not the least of which is measuring migratory capability in natural populations. We take advantage of a visible migratory dimorphism to study variation in migratory capability in the stream-dwelling water strider, Aquarius remigis. Theory predicts loss of migratory capability in this species because streams have been viewed as stable and persistent habitats. As expected, A. remigis lack wings throughout most of North America. However, Californian populations are noted for unexpectedly high frequencies of winged, migratory morphs. To deduce the adaptive significance of this anomalous regional variation, we compare proportion winged among 37 Californian populations. We discover a strong, positive correlation with altitude, but no correlations with latitude, rainfall or stream size. A common garden experiment reveals that both proportion winged and its reaction norm to temperature differ genetically among populations, and a half-sibling experiment demonstrates that wing morph has high heritability, moderate genetic correlations across environments and a significant genotype by environment interaction. These results support the hypothesis that proportion winged and its reaction norm to temperature have diverged genetically in California. We conclude that high migratory capability is an evolutionary adaptation to the unusual harshness and instability of Californian stream habitats, and particularly to the high elevational gradients and extreme seasonal variation characteristic of montane streams.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.149
Threshold uncertainty score0.998

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)0.0030.000

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 head0.012
GPT teacher head0.217
Teacher spread0.206 · 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

Citations42
Published2008
Admission routes1
Has abstractyes

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