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Record W2167885187 · doi:10.1093/conphys/cou041

Interpopulational variation in the cold tolerance of a broadly distributed marine copepod

2014· article· en· W2167885187 on OpenAlexaff
Gemma T. Wallace, Tohyun Kim, Christopher J. Neufeld

Bibliographic record

VenueConservation Physiology · 2014
Typearticle
Languageen
FieldEnvironmental Science
TopicPhysiological and biochemical adaptations
Canadian institutionsQuest University Canada
FundersUniversity of Washington
KeywordsBiologyEctothermCopepodLocal adaptationEcologyLatitudeAdaptation (eye)Intertidal zoneTemperate climateCrustaceanPopulationDemography

Abstract

fetched live from OpenAlex

Latitudinal trends in cold tolerance have been observed in many terrestrial ectotherms, but few studies have investigated interpopulational variation in the cold physiology of marine invertebrates. Here, the intertidal copepod Tigriopus californicus was used as a model system to study how local adaptation influences the cold tolerance of a broadly distributed marine crustacean. Among five populations spanning 18° in latitude, the following three metrics were used to compare cold tolerance: the temperature of chill-coma onset, the chill-coma recovery time and post-freezing recovery. In comparison to copepods from warmer southern latitudes, animals from northern populations exhibited lower chill-coma onset temperatures, shorter chill-coma recovery times and faster post-freezing recovery rates. Importantly, all three metrics showed a consistent latitudinal trend, suggesting that any single metric could be used equivalently in future studies investigating latitudinal variation in cold tolerance. Our results agree with previous studies showing that populations within a single species can display strong local adaptation to spatially varying climatic conditions. Thus, accounting for local adaptation in bioclimate models will be useful for understanding how broadly distributed species like T. californicus will respond to anthropogenic climate change.

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 score0.962
Threshold uncertainty score0.329

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 head0.014
GPT teacher head0.219
Teacher spread0.205 · 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

Citations17
Published2014
Admission routes1
Has abstractyes

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