Demography and viability analyses of a diamondback terrapin population
Why this work is in the frame
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Bibliographic record
Abstract
The diamondback terrapin, Malaclemys terrapin, is a long-lived species with special management requirements but quantitative analyses to support management are lacking. I analyzed markrecapture data and constructed an age-classified matrix population model to determine the status and viability of the only known diamondback terrapin population in Rhode Island. Female diamondback terrapins were captured, marked, and recaptured while nesting during 19902001. Population growth rate (λ) was 1.034 (95% confidence interval = 1.0121.056). For the preceding 5 years, however, abundance had been stable at about 188 breeding females. Adult apparent survival was high but declined slightly by 0.14% per year from 0.959 in 1990 to 0.944 in 2000. Recruitment of breeding females also decreased during the study period; therefore, survival was increasingly a greater component of population growth rate. Juvenile survival was 0.565 at λ = 1.034 and 0.446 at λ = 1. Both retrospective (markrecapture) and prospective (matrix population model) analyses showed a greater influence of survival versus reproduction on population growth. Population- model projections showed that capping nests to improve reproductive success could increase population growth rate, but the magnitude of increase was positively related to pre-reproductive survival, therefore negating nest capping as a remedy for declining populations or poor survival. Extinction attributable to demographic stochasticity is unlikely.
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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) | 0.000 | 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