Wildlife conservation and animal temperament: causes and consequences of evolutionary change for captive, reintroduced, and wild populations
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract We argue that animal temperament is an important concept for wildlife conservation science and review causes and consequences of evolutionary changes in temperament traits that may occur in captive‐breeding programmes. An evolutionary perspective is valid because temperament traits are heritable, linked to fitness and potentially subject to intense selection in captivity. Natural, sexual and artificial selection can cause permanent shifts in temperament, reducing the diversity of temperament traits, diversity that may be critical to reintroduction success. Breeding programmes that ignore temperament risk leading the captive population towards domestication. Furthermore, shifts in temperament may involve alterations in linked morphological and physiological traits, and selection may even change functional relationships between traits. Captive‐breeding programmes can reduce changes in temperaments by closely monitoring temperament traits, equalizing reproductive success between temperament morphs and using environmental enrichment to reduce captive stress. Under certain circumstances, knowledge about temperament may also provide a useful tool to optimize captive reproduction and to increase reintroduction success. Outside reintroduction programmes, temperament can mediate responses to human contact, hunting, exploitation, habitat fragmentation and disease transmission. Consideration of temperaments could strengthen both captive and wild conservation efforts.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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 it