MANAGEMENT STRATEGIES, YIELD AND POPULATION DEVELOPMENT OF THE NOBLE CRAYFISH ASTACUS ASTACUS IN LAKE STEINSFJORDEN
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".