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Record W4388689197 · doi:10.1111/nrm.12390

Maximum sustainable yield as a reference point in the presence of fishing effort that follows an ideal free distribution

2023· article· en· W4388689197 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueNatural Resource Modeling · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine and fisheries research
Canadian institutionsUniversity of Manitoba
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMaximum sustainable yieldFishingIdeal (ethics)Fisheries managementFisheryIdeal pointSustainable yieldComputer scienceMathematicsMathematical economicsEnvironmental scienceEcologyBiologyPolitical science

Abstract

fetched live from OpenAlex

Abstract The concept of maximum sustainable yield (MSY), and the underlying Schaefer model, remain relevant in fisheries management today in spite of past difficulties. However, this model is often applied without the consideration of the spatial structure or dynamics of fishing activities. We expand the Schaefer model to account for multiple fishing sites and fishing activities (effort) that follow an ideal free distribution (IFD, a form of Nash equilibrium) driven by exploitation. We explore this conceptual model using both analytical and numerical solutions. MSY across the fishery is unaffected by the spatial structure when fishing is allocated independently within sites. However, in other cases IFD effort dynamics depress MSY and modify the values of associated reference points. The game theoretic aspect of fleet dynamics should be considered in the use of MSY as a management reference point or during the application of the Schaefer model to data‐limited 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.

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)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.496
Threshold uncertainty score0.986

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
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 head0.035
GPT teacher head0.275
Teacher spread0.240 · 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