Population correlates of rapid captive‐induced maladaptation in a wild fish
Bibliographic record
Abstract
Abstract Understanding the extent to which captivity generates maladaptation in wild species can inform species recovery programs and elucidate wild population responses to novel environmental change. Although rarely quantified, effective population size (Ne) and genetic diversity should influence the magnitude of plastic and genetic changes manifested in captivity that reduce wild fitness. Sexually dimorphic traits might also mediate consequences of captivity. To evaluate these relationships, we generated >600 full‐ and half‐sibling families from nine wild brook trout populations, reared them for one generation under common, captive environmental conditions and contrasted several fitness‐related traits in wild versus captive lines. We found substantial variation in lifetime success (lifetime survival and reproductive success) and life history traits among wild populations after just one captive generation (fourteen‐ and threefold ranges across populations, respectively). Populations with lower heterozygosity showed lower captive lifetime success, suggesting that captivity generates maladaptation within one generation. Greater male‐biased mortality in captivity occurred in populations having disproportionately higher growth rates in males than females. Wild population Ne and allelic diversity had little or no influence on captive trait expression and lifetime success. Our results have four conservation implications: (i) Trait values and lifetime success were highly variable across populations following one generation of captivity. (ii) Maladaptation induced by captive breeding might be particularly intense for the very populations practitioners are most interested in conserving, such as those with low heterozygosity. (iii) Maladaptive sex differences in captivity might be associated with population‐dependent growth costs of reproduction. (iv) Heterozygosity can be a good indicator of short‐term, intraspecific responses to novel environmental change.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".