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Record W2146877652 · doi:10.1577/m01-232am

Active Management of Walleye Fisheries in Alberta: Dilemmas of Managing Recovering Fisheries

2003· article· en· W2146877652 on OpenAlexafffundabout
Michael G. Sullivan

Bibliographic record

VenueNorth American Journal of Fisheries Management · 2003
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsAlberta Environment and Protected Areas
FundersAlberta Conservation Association
KeywordsFisheryStizostedionFishingRecreational fishingFisheries managementCoregonus clupeaformisRecreationCatch and releaseBycatchFish stockFish <Actinopterygii>BiologyEcology

Abstract

fetched live from OpenAlex

Abstract Managers of the recreational fishery for walleyes Sander vitreus (formerly Stizostedion vitreum) in Alberta, Canada, face an unusual combination of very low productivity (related to the northern climate) and high fishing pressure. Passive management of the large recreational fishery and active management of the smaller commercial fishery failed to prevent declines and collapses of walleye stocks. During the 1990s, extensive consultations with the public resulted in the development of an active recreational fishery management system using set points to classify stocks. Catch and release and large, highly restrictive length limits were used to regulate the harvest. These restrictions on the recreational harvest resulted in a dramatic increase in the catch rates of growth-overfished stocks. Paradoxically, this recovery has created dilemmas and controversies in both the recreational and commercial fisheries. Anglers are now dissatisfied with the low harvest rates and absence of large fish attending the high catch rates of small fish. The total allowable catch, however, is being taken by hooking mortality and illegal harvest of undersize walleyes in the recreational harvest. In commercial gill-net fisheries for lake whitefish Coregonus clupeaformis, increasing bycatch of walleyes restricts the harvest of lake whitefish and has created uneconomical fisheries. Resolving these dilemmas will require dramatic changes to fisheries management techniques in Alberta.

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)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.152
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.001
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 head0.007
GPT teacher head0.196
Teacher spread0.189 · 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

Citations128
Published2003
Admission routes3
Has abstractyes

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