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Record W2005983199 · doi:10.1051/kmae:2002072

MANAGEMENT STRATEGIES, YIELD AND POPULATION DEVELOPMENT OF THE NOBLE CRAYFISH ASTACUS ASTACUS IN LAKE STEINSFJORDEN

2002· article· en· W2005983199 on OpenAlexaboutno aff
Jostein Skurdal, Erik Garnås, Trond Taugbøl

Bibliographic record

VenueBulletin Français de la Pêche et de la Pisciculture · 2002
Typearticle
Languageen
FieldEnvironmental Science
TopicCrustacean biology and ecology
Canadian institutionsnot available
FundersNature
KeywordsCrayfishAstacusBiologyPopulationAnimal scienceFisheryEcology

Abstract

fetched live from OpenAlex

Lake Steinsfjorden is the most important noble crayfish locality in Norway. The crayfish population has been monitored annually since 1979 including data on total trapping effort, yield and population composition before and after the catching season. The harvest has ranged from 0.7-4.7 kg.ha-1. The catch per trap night decreased prior to 1991 and the yield was reduced by some 50% over the years 1987-1992 as compared to 1979-1986. This was due to removal of small crayfish, high exploitation and the establishment of dense stands of Canadian pondweed (Elodea canadensis). Baited traps catch a large fraction of crayfish < 95 mm total length minimum size. These should according to the regulations immediately be released into the lake. However, it is apparent from the size composition that release of these small crayfish was rather incomplete. In 1983, trap mesh size was increased from 17.5 mm to 21 mm to reduce the fraction of undersized crayfish in the trap catches, yet no effects of this increased mesh size on crayfish size distribution were observed. The legal season has been reduced three times during the study period. In 1983, the closing date was changed from 31 December to 15 September. In 1989 the legal season was further reduced to two weeks and finally in 1995 to 10 days. This reduced total trap effort by 45%. The shorter season allow many crayfish to moult twice instead of once between seasons and the fraction of large crayfish has thus increased and so has the catch per trap night. Canadian pondweed has established dense annual stands and thus has made large parts of the shallow areas unsuitable for crayfish, causing an overall decrease in crayfish population size and production.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.213
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.211
Teacher spread0.205 · 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

Citations13
Published2002
Admission routes1
Has abstractyes

Explore more

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