Life-cycle analysis of an endangered migratory goose to assess the impact of conservation actions on population recovery
Bibliographic record
Abstract
Evaluating the effectiveness of conservation actions is challenging for migratory species because a population can be impacted anywhere along its route. Conservation actions for the critically endangered Fennoscandian lesser white-fronted goose population include culling of red foxes in the breeding area and habitat improvements and reduction of illegal hunting in the non-breeding areas. One goal of the predator control strategy is to prevent adult birds from using an autumn migration route through western Asia, where mortality is believed to be higher than on the migration route through eastern Europe. We used 23 years of count data obtained at different staging areas to parameterize a seasonal state-space model describing the full-annual cycle dynamics of this population and evaluate whether the recent population recovery was linked to these conservation efforts. The results did not provide evidence that predator control influenced population recovery, as survival on the European route did not appear higher than on the allegedly riskier Asian route. However, adult survival at staging areas on both routes and at wintering sites may have improved in the last decade, suggesting a positive effect of the other conservation initiatives. These results emphasize the importance of including the non-breeding dynamics in population assessments of migratory species and highlight the challenge of evaluating the efficacy of separate conservation actions when a proper experimental design is unfeasible. Our study, which is a unique case of cross-national, coordinated conservation efforts, exemplifies how to model complex population dynamics to assess the influence of costly conservation initiatives.
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How this classification was reachedexpand
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 teacher head, 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".