Do Power Lines and Protected Areas Present a Catch-22 Situation for Cape Vultures (Gyps coprotheres)?
Bibliographic record
Abstract
Cape vulture Gyps coprotheres populations have declined across their range due to multiple anthropogenic threats. Their susceptibility to fatal collisions with the expanding power line network and the prevalence of carcasses contaminated with illegal poisons and other threats outside protected areas are thought to be the primary drivers of declines in southern Africa. We used GPS-GSM units to track the movements and delineate the home ranges of five adult (mean ±SD minimum convex polygon area = 121,655±90,845 km(2)) and four immature (mean ±SD minimum convex polygon area = 492,300±259,427 km(2)) Cape vultures to investigate the influence of power lines and their use of protected areas. The vultures travelled more than 1,000 km from the capture site and collectively entered five different countries in southern Africa. Their movement patterns and core foraging ranges were closely associated with the spatial distribution of transmission power lines and we present evidence that the construction of power lines has allowed the species to extend its range to areas previously devoid of suitable perches. The distribution of locations of known Cape vulture mortalities caused by interactions with power lines corresponded to the core ranges of the tracked vultures. Although some of the vultures regularly roosted at breeding colonies located inside protected areas the majority of foraging activity took place on unprotected farmland. Their ability to travel vast distances very quickly and the high proportion of time they spend in the vicinity of power lines and outside protected areas make Cape vultures especially vulnerable to negative interactions with the expanding power line network and the full range of threats across the region. Co-ordinated cross-border conservation strategies beyond the protected area network will therefore be necessary to ensure the future survival of threatened vultures in Africa.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".