The influence of eutrophication and population biomass on common whitefish (<i>Coregonus lavaretus</i>) growth — the Lake Constance example revisited
Bibliographic record
Abstract
Accelerated growth of freshwater fish during anthropogenic eutrophication has been attributed almost exclusively to the increased nutrient content, while density-dependent effects have been largely neglected. We evaluated the relative importance of these factors by studying the growth of 43 consecutive year classes of common whitefish (Coregonus lavaretus) from Upper Lake Constance. This prealpine lake underwent eutrophication from the 1950s to 1970s, followed by reoligotrophication. Because whitefish are harvested with gill nets in a strongly size-selective way, we used back-calculated lengths of average fast-growing fish to compare growth among cohorts. Standing stock biomass was estimated based upon virtual year-class strengths. Multiple linear regression analysis revealed that growth of whitefish during their second year was most strongly related to standing stock biomass followed by PO4-P content during spring turnover and by calendar year, which was incorporated as a third independent variable (adjusted R2 = 0.84). The negative correlation between whitefish growth rate and calendar year is interpreted as evidence of an evolutionary response to the highly size-selective fishery during at least four decades. We conclude that density-dependent effects on whitefish growth are more important than had been realized previously and that the impact of eutrophication on growth of whitefish needs to be reconsidered.
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 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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".