Fluctuations in harvest of native and introduced crayfish are driven by temperature and population density in previous years
Bibliographic record
Abstract
The effects of temperature and density on annual fluctuations in catches of large adult crayfish are evaluated using time series analysis. We tested if temperature during different stages of the crayfish life cycle influenced observed catches from 1946 to 2007 in Lake Bunn (Sweden). From 1946 to 1974, native noble crayfish ( Astacus astacus ) inhabited the lake, but then, crayfish plague wiped out the whole population. In 1985, the exotic signal crayfish ( Pacifastacus leniusculus ) was introduced and is still present. This made it possible to model the two species separately and compare how temperature and density influence the abundance of large adult crayfish. The best models indicate that both climatic- and density-dependent factors influence the observed fluctuations and there was a time lag for most factors included in the best models. Winter temperature had the strongest influence on fluctuations of both species. Also, density dependence was included in the best model for both species. Growth season for noble crayfish and temperature during the mating season for signal crayfish were also present in the most parsimonious model. Based on our findings, it is difficult to predict how further climate warming will affect crayfish population dynamics in freshwaters.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".