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Record W1918319460

Seasonal biological cycles in Atlantic cod (Gadus morhua) and implications for fisheries and management: a simulation approach with application to the Placentia Bay cod fishery (NAFO subdivision 3Ps)

2005· dissertation· en· W1918319460 on OpenAlexfundaboutno aff

Bibliographic record

VenueMemorial University Research Repository (Memorial University) · 2005
Typedissertation
Languageen
FieldEnvironmental Science
TopicMarine and fisheries research
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaMemorial University of NewfoundlandEli Lilly and Company
KeywordsGadusAtlantic codFisheryBayCapelinDemersal fishCod fisheriesGadidaeDemersal zoneStock assessmentFishingEnvironmental scienceOceanographyBiologyGeographyFish <Actinopterygii>
DOInot available

Abstract

fetched live from OpenAlex

Atlantic cod (Gadus morhua) is a demersal fish found across the North Atlantic Ocean in a variety of habitats from the shoreline to the continental shelf slope. Throughout its range of distribution, cod experience a great variety of biotic and abiotic conditions, particularly in relation to thermal and feeding regimes. Such variations affect life history characteristics such as growth, physiological condition, distribution and migration patterns at a variety of scales including decadal, annual and seasonal. In this study I investigate how these processes vary on a seasonal scale level and affect fisheries, stock assessment and management of cod from Placentia Bay, Newfoundland (Northwest Atlantic Fisheries Organization Subdivision 3Ps). The results of this study show that cod have marked seasonal variability in traits such as weight, physiological condition, growth, distribution and aggregations patterns, in addition to the commercial yield and quality of fish products. These changes were related to changes in thermal and feeding regimes through the year, in addition to spawning, migration and intermixing of cod from different geographic regions. Cod ages 4-9 experienced a rapid increase in weight and condition during late spring and summer when capelin (Mallotus villosus) comprised an important component of the diet, despite of cold water temperatures and moderate to high spawning activity and peaked in the fall. Seasonal variations of biological cycles, distribution and mixing of different groups of cod resulted in large within-year variations in stock abundance, age and size composition, impacted fishing levels and harvest rates of putative stock components and affected precision of abundance index estimates. Simulation results suggest that stock performance and productivity are impacted by the way fishing mortality is distributed across age groups and that stock growth and catch yield are driven by the survival of younger fish and by allowing age diversity in the stock, which appears to facilitate good recruitment, particularly when abundance is high. The simulations show that a weight-based fishery in the fall when cod are heavier and in good physiological condition would harvest fewer fish and result in better yield and product quality. However, a fall fishery would concentrate exploitation on the resident component of the stock. The largest sustainable catches were observed in summer when the most abundant non-resident fish are found in the bay. Overall, the results and conclusions of this thesis suggest that seasonal biological patterns in cod may be used to develop fishing and management strategies that minimize the impact of harvesting on productivity while optimizing economic benefits and conservation of stock components. The results from this study are likely relevant to other cod stocks and perhaps to other species (e.g., invertebrates, marine mammals) as seasonality is a common feature of reproduction and growth of many temperate and high latitude aquatic species, which are normally synchronised with periods when organisms benefit from favourable thermal conditions and high forage status.

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.835
Threshold uncertainty score0.329

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.255
Teacher spread0.233 · 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 designSimulation or modeling
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

Citations1
Published2005
Admission routes2
Has abstractyes

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