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Record W2889164000 · doi:10.3160/3712.1

The Evolution of the Thermal Niche Across Locally Adapted Populations of the Copepod <i>Tigriopus californicus</i>

2018· article· en· W2889164000 on OpenAlexaboutno aff
Christopher S. Willett, Christine Son

Bibliographic record

VenueBulletin Southern California Academy of Sciences · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicPhysiological and biochemical adaptations
Canadian institutionsnot available
Fundersnot available
KeywordsCopepodNicheBiologyEcologyZoologyCrustacean

Abstract

fetched live from OpenAlex

Thermal performance is a key component of fitness particularly for ectotherms living in thermally variable environments.Local adaptation can occur within populations of a species that inhabit regions with divergent thermal conditions, but this adaptation may result in trade-offs in other measures of fitness.If these trade-offs affect other aspects of thermal performance, several different patterns are possible (Huey and Kingsolver 1993).One potential pattern from a trade-off is a shift in the thermal niche, meaning that an or¬ ganism that can handle a new range of higher temperatures can no longer handle colder temperatures as well.A second type of pattern is a generalist/specialist trade-off whereby populations may have broader thermal niches but lower fitness at optimal temperatures [i.e."a jack-of-all-trades is a master of none" (Huey and Hertz 1984)].Another possibility is that increased investment associated with local thermal adaptation (i.e.high tempera¬ ture tolerance) may result in trade-offs in non-thermally dependent traits (Angilletta et al. 2003).The nature and structure of these trade-offs could determine the degree to which organisms will be able to respond to a changing climate.The copepod Tigriopus californicus (Baker, 1912) has become an important system in which to study the evolution of local adaptation to the thermal environment.Geographi¬ cally distinct populations of this copepod occur in upper intertidal pools along the Pacific coast from central Baja Mexico to Alaska.These populations often show high degrees of genetic divergence from one another indicating that levels of gene flow between popula¬ tions can be very limited over long periods of time (Burton 1997;Edmands 2001; Willett and Ladner 2009).There is also a clear latitudinal gradient in high temperature survival that is suggestive of local thermal adaptation for this species (Willett 2010;Kelly et al. 2012;Leong et al. 2018).This latitudinal gradient for high temperature tolerance has been seen for nauplii and copepodids as well as adults (Tangwancharoen and Burton 2014).Local thermal adaptation in T. californicus is also suggested by studies of fitness com¬ ponents and competitive fitness under non-extreme temperatures.Hong and Shurin (2015) examined 15 populations of T. californicus from Vancouver Island, BC, Canada, to south¬ ern California (CA) for a set of life history traits that contribute to fitness under four different temperature conditions (from 15°C to 30°C).They estimated the net fitness ef¬ fect of these traits by calculating an intrinsic population growth rate (r) and found a con¬ sistent shift in the thermal niche from south to north and also higher r in the northern populations.Willett (2010) also found that for comparisons across a set of moderate tem¬ peratures there was a flip in competitive fitness between pairs of southern and central CA T. californicus populations.Central CA populations outcompeted southern populations at 16°C while the opposite pattern was observed in a fluctuating environment with an aver¬ age temperature of 24°C (a 20°C to 28°C daily cycle).Combined these results suggest that

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.009
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.022
GPT teacher head0.251
Teacher spread0.229 · 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 source (direct Gemma or distilled Codex), 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

Citations7
Published2018
Admission routes1
Has abstractyes

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