Contrasting demographic responses to size‐selective harvesting among neighbouring wild fish populations
Bibliographic record
Abstract
Abstract Sustainable harvesting of wild populations relies on evidence‐based knowledge to predict harvesting outcomes for species and the ecosystems they inhabit. Although harvesting may elicit compensatory density‐dependence, it is generally size‐selective, which induces additional pressures that are challenging to forecast. Furthermore, responses to harvest may be population‐specific and whether generalizable patterns exist remains unclear. Taking advantage of Parks Canada's mandate to remove introduced brook trout Salvelinus fontinalis to restore alpine lakes in Canadian parks, we experimentally applied standardized size‐selective harvesting rates (the largest ~64% annually) for three consecutive summers in five populations with different initial size structures. Four unharvested populations were used as controls. At reduced densities, harvested and control populations exhibited similar density‐dependent increases in specific growth, juvenile survival and earlier maturation. However, size‐selective harvesting simultaneously induced changes to size and age structure that contrasted among harvested populations. Average body length decreased in three of five harvested populations, whereas it tended to increase in control populations over the 3 years. We also detected contrasting, population‐specific changes in body length variability and ultimately in length‐ and age‐at‐harvest in harvested populations but not controls. Overall, populations with smaller, more homogeneous body sizes, and living at high densities were most resilient to size‐selective harvesting, exhibiting the smallest change in size‐at‐age. In contrast, large‐bodied populations exhibited more substantial size‐structure changes following selective harvesting: large‐bodied populations experienced either stabilizing or disruptive pressures, when initial length variability was high or low, respectively. Synthesis and application . Our results show that within species, size‐selective harvesting inherently leads to more risk and uncertainty when harvesting populations with larger and more varied body sizes than smaller‐bodied populations with less range in body size. Our study supports prioritizing regulations that protect harvested populations with larger and more varied body sizes. Such a management strategy would reduce the likelihood of eliciting unpredictable or undesirable demographic changes to fish populations with these attributes.
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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 | 0.001 | 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) | 0.000 | 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".