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The role of temperature in the capture and release of fish

2011· article· en· W2152895060 on OpenAlexafffund
Marika Kirstin Gale, Scott G. Hinch, Michael Donaldson

Bibliographic record

VenueFish and Fisheries · 2011
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsUniversity of British Columbia
FundersUniversity of British Columbia
KeywordsPerciformesLimitingFish <Actinopterygii>Context (archaeology)FisheryBiologyFisheries managementClimate changeEcologyFishing

Abstract

fetched live from OpenAlex

Abstract We searched major electronic databases to identify peer‐reviewed literature investigating the role of temperature on the stress response and mortality of captured and released fish. We identified 83 studies that fit these criteria, the majority of which were conducted in North America (81%) on freshwater fish (76%) in the orders Perciformes (52%) and Salmoniformes (28%). We found that hook‐and‐line fisheries (65% of all studies) were more commonly studied than all net fisheries combined (24%). Despite the wide recognition for many species that high water temperatures exacerbate the effects of capture on released fish, this review is the first to quantitatively investigate this problem, finding that warming contributed to both mortality and indices of stress in 70% of articles that measured each of those endpoints. However, more than half (58%) of the articles failed to place the experimental temperatures into a biological context, therefore limiting their broad applicability to management. Integration of survival and sublethal effects to investigate mechanisms of fish mortality was relatively rare (28%). Collectively, the results suggest that capture–release mortality increases at temperatures within, rather than above, species‐specific thermal preferenda. We illustrate how knowledge of ecologically relevant high temperatures in the capture and release of fish can be incorporated into management, which will become increasingly important as climate change exerts additional pressure on fish and fisheries.

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)0.013
metaresearch head score (Gemma)0.098
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.019
Threshold uncertainty score0.069

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0130.098
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.003
Bibliometrics0.0190.024
Science and technology studies0.0000.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.006
GPT teacher head0.162
Teacher spread0.156 · 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

Citations179
Published2011
Admission routes2
Has abstractyes

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