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Record W2548873777

Factors Affecting Catch and Release (CAR) Mortality in Fish: Insight into CAR Mortality in Red Snapper and the Influence of Catastrophic Decompression

2007· book-chapter· en· W2548873777 on OpenAlexaff
Jodie L. Rummer

Bibliographic record

VenueResearchOnline at James Cook University (James Cook University) · 2007
Typebook-chapter
Languageen
FieldEnvironmental Science
TopicMarine and fisheries research
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsOverfishingFisheryFishingCatch and releasePopulationMortality rateBycatchGeographyFish mortalityFish <Actinopterygii>BiologyMedicineEnvironmental healthSurgeryRecreational fishing
DOInot available

Abstract

fetched live from OpenAlex

The red snapper Lutanus campechanus fishery is arguably one of the most important in the Gulf of Mexico, but habitat destruction, climate change, and serial overfishing has resulted in significant population declines in red snapper and other high-profile fisheries species. The red snapper fishery may be one of the best examples where management strategies that promote catch and release (CAR) have failed. Populations have not recovered despite CAR management strategies, likely because CAR mortality is high; however, the basis for CAR mortality is unclear. Numerous studies associated with fishing-induced mortality were reviewed in an attempt to make generalizations as to how red snapper and other high-profile fisheries species respond to CAR. A framework for understanding CAR mortality in red snapper and other species was constructed based on four pillars: retrieval conditions, species and size relationships, handling, and release conditions. Each of these fishing factors was examined as to relative impact toward CAR. A predictive model was generated from all available data on CAR mortality. For a deep-water fish like red snapper, the underlying problem is directly related to capture depth, particularly injuries related to rapid swim bladder (SB) overinflation and catastrophic decompression syndrome (CDS). If not immediately lethal, depth-related injuries may have long term effects on growth and immune function that could go unnoticed and are unaccounted for in traditional field studies; all other fishing factors will only intensify this baseline impairment. Management plans are typically built under the assumption that CAR mortality is below 20%, but it is widely accepted that this is a gross underestimate. Modeling from this review suggests that, in red snapper, mortality may be as low as 20% but only if fish are caught between 0 and 20 m depths. This is not the case, and CAR mortality may reach 100% if fish are retrieved from deeper than 110 m. Current CAR management strategies are ineffective, and not enough information exists to impose maximum fishing depths. Given these limitations, a logical approach would be to restrict particular areas such that fish populations can be protected from all fishing and CAR activity, therefore protecting age, size, and sex classes and ratios. For fish species like red snapper, where overfishing is widespread and CAR mortality is high, or other species where CAR is unclear and a thorough investigation as to depth-related CAR mortality has not been performed, strategies based on space (i.e., marine protected areas and no-take reserves), rather than time or numbers (i.e., season closures, size limits, bag limits, etc.), have the greatest potential for overall conservation and sustainability and should be strongly considered.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.272
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.004
Scholarly communication0.0000.001
Open science0.0010.004
Research integrity0.0010.002
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 head0.030
GPT teacher head0.258
Teacher spread0.228 · 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

Citations18
Published2007
Admission routes1
Has abstractyes

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