Opportunities for the conservation of migratory birds to benefit threatened resident vertebrates in the Neotropics
Bibliographic record
Abstract
Abstract Neotropical countries receive financing and effort from temperate nations to aid the conservation of migratory species that move between temperate and tropical regions. If allocated strategically, these resources could simultaneously contribute to other conservation initiatives. In this study, we use novel distribution maps to show how those resources could aid planning for the recovery of threatened resident vertebrates. Using eBird‐based relative abundance estimates, we first identified areas with high richness of Neotropical migrant landbirds of conservation concern (23 species) during the stationary non‐breeding period. Within these areas, we then identified threatened species richness, projected forest loss and conducted a prioritization for 1,261 red‐listed vertebrates using Terrestrial Area‐of‐Habitat maps. Richness for migrants was greatest along a corridor from the Yucatan peninsula south to the northern Andes but also included south‐west Mexico and Hispaniola. Protected areas account for 22% of this region while 21% is at risk of forest loss. Within this focal region for migrants, all four vertebrate groups showed hotspots of threatened species richness along the west and east Andean slopes. Taxa‐specific hotspots included montane areas of southern Mexico and central Guatemala (amphibians/reptiles) and the entire east slope of the Colombian East Andes (mammals). Our prioritization highlighted several areas of importance for conservation due to high threatened species richness and projected forest loss including (a) the Pacific dry forests of south‐west Mexico, (b) montane regions of northern Central America and (c) the west Andean slope of Colombia and Ecuador. At a landscape scale in southern Colombia, we show how conservation efforts for six Neotropical migrants could benefit 56 threatened residents that share a similar elevational range. Synthesis and applications . Funding and effort for migratory bird conservation also has potential to benefit threatened resident vertebrates in the Neotropics. Our study highlights how novel, high‐resolution information on species distributions and risk of forest loss can be integrated to identify priority areas for the two groups at regional and landscape scales. The approach and data can be further modified for more specific goals, such as within‐country 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 | 0.001 | 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 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".