Optimizing the conservation of migratory species over their full annual cycle
Bibliographic record
Abstract
Abstract Limited knowledge of the distribution, abundance, and habitat associations of migratory species introduces uncertainty about the most effective conservation actions. We used Neotropical migratory birds as a model group to evaluate contrasting approaches to land prioritization to support ≥30% of the global abundances of 117 species throughout the annual cycle in the Western hemisphere. Conservation targets were achieved in 43% less land area in plans based on annual vs. weekly optimizations. Plans agnostic to population structure required comparatively less land area to meet targets, but at the expense of representation. Less land area was also needed to meet conservation targets when human-dominated lands were included rather than excluded from solutions. Our results point to key trade-offs between efforts minimizing the opportunity costs of conservation vs. those ensuring spatiotemporal representation of populations, and demonstrate a novel approach to the conservation of migratory species based on leading-edge abundance models and linear programming to identify portfolios of priority landscapes and inform conservation planners.
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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 | 0.001 | 0.001 |
| 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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".