Beyond canaries in coal mines: Co-occurrence of Andean mining concessions and migratory birds
Bibliographic record
Abstract
Spatial planning and decision-support tools facilitate the consideration of socioecological tradeoffs associated with extractive activities, but insufficient data resources often limit their application. Focusing on birds and mining concessions in the Northern Andes, we illustrate how publicly-available data can be used in spatial prioritization tools to identify where concessions have the potential to impact 22 species of Neotropical migratory birds. Concessions covered 11% of the land area of Colombia, Ecuador, and Peru, and disproportionately occurred within important areas for migratory birds in Colombia and Ecuador, but not Peru. eBird data showed that one-quarter of avian species, including the Olive-sided Flycatcher, Cerulean Warbler, and Canada Warbler, had >10% of their global populations on concession land during the non-breeding season. More worrisome, species of greater conservation importance and with larger population declines (1974–2014) were most likely to co-occur with mining. Our approach highlights how public biodiversity data can be used to predict, avoid, or mitigate potential ecological impacts from extractive activities.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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".