Post‐catastrophe patterns of abundance and survival reveal no evidence of population recovery in a long‐lived animal
Why this work is in the frame
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Bibliographic record
Abstract
Abstract Population catastrophes are widespread, unpredictable phenomena occurring in natural populations that have important, yet frequently underappreciated, consequences for persistence. As human impacts on ecosystems increase globally, the frequency of catastrophes is likely to rise as increasingly fragmented and depleted populations become more vulnerable. Species with slow life histories are expected to recover slowly from catastrophes because of their longer generation times, and assessing their population recovery requires data spanning long periods. We report results from a long‐term mark–recapture study of snapping turtles ( Chelydra serpentina ) in Algonquin Provincial Park, Ontario, that experienced a major mortality event from winter predation by river otters. We estimated abundance and survival of nesting females before, during, and 23 yr following the catastrophe. We built multistate mark–recapture models incorporating movement between sites, temporary emigration, and observation effects. We found that during the 3‐yr mortality event, abundance of nesting females declined by 39% overall, and by 49% at our focal nesting area. Apparent survivorship of nesting females during these three years fell from 0.94 before the mortality event to 0.76 at the focal site and 0.86 at adjacent nest sites. Survivorship over the following 23‐yr period averaged 0.972 and 0.940 at the two sampling areas. Despite high post‐catastrophe survivorship and connectivity with other populations, the population failed to recover, displaying consistently reduced abundances across 23 post‐catastrophe years. We discuss the relationship between life‐history attributes and the causes and consequences of local catastrophes and their conservation implications.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it