Life‐history plasticity and sustainable exploitation: a theory of growth compensation applied to walleye management
Bibliographic record
Abstract
A simple population model was developed to evaluate the role of plastic and evolutionary life-history changes on sustainable exploitation rates. Plastic changes are embodied in density-dependent compensatory adjustments to somatic growth rate and larval/juvenile survival, which can compensate for the reductions in reproductive lifetime and mean population fecundity that accompany the higher adult mortality imposed by exploitation. Evolutionary changes are embodied in the selective pressures that higher adult mortality imposes on age at maturity, length at maturity, and reproductive investment. Analytical development, based on a biphasic growth model, led to simple equations that show explicitly how sustainable exploitation rates are bounded by each of these effects. We show that density-dependent growth combined with a fixed length at maturity and fixed reproductive investment can support exploitation-driven mortality that is 80% of the level supported by evolutionary changes in maturation and reproductive investment. Sustainable fishing mortality is proportional to natural mortality (M) times the degree of density-dependent growth, as modified by both the degree of density-dependent early survival and the minimum harvestable length. We applied this model to estimate sustainable exploitation rates for North American walleye populations (Sander vitreus). Our analysis of demographic data from walleye populations spread across a broad latitudinal range indicates that density-dependent variation in growth rate can vary by a factor of 2. Implications of this growth response are generally consistent with empirical studies suggesting that optimal fishing mortality is approximately 0.75M for teleosts. This approach can be adapted to the management of other species, particularly when significant exploitation is imposed on many, widely distributed, but geographically isolated populations.
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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) | 0.017 | 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".