Dynamics of a small population of endangered huemul deer (Hippocamelus bisulcus) in Chilean Patagonia
Bibliographic record
Abstract
Conservation of huemul (Hippocamelus bisulcus), an endangered South American deer, is hindered by a lack of quantitative information on its population dynamics. We conducted a 3-year study in Chilean Patagonia to assess the dynamics of huemul by monitoring known individuals. We fitted 55 deer of all sexage classes with either radiocollars, radio ear tags, or conventional ear tags, and identified 33 additional deer through natural marks. KaplanMeier estimates revealed that annual survival of adult females was high and stable (0•94 ± 0•07 SD), but survival of female fawns was low and variable (0•13 ± 0•18). Predation was the predominant cause of mortality for deer of all age classes. Fertility rates were lower (0•72 ± 0•20) than in other cervids of similar size. Simulations of the finite rate of increase (λ) suggest that the population is currently stable. Sensitivity analysis showed that any decrease in adult female survival would have drastic effects on λ. Consequently, management should maintain high adult survival and improve recruitment. Continued monitoring of individuals is required to provide baseline data for comparison with other populations and to inform recovery strategies of small and fragmented populations. © 2010 American Society of Mammalogists.
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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 | 0.000 |
| 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 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".