Tracking data and retrospective analyses of diet reveal the consequences of loss of marine subsidies for an obligate scavenger, the Andean condor
Bibliographic record
Abstract
Over the last century, marine mammals have been dramatically reduced in the world's oceans. We examined evidence that this change caused dietary and foraging pattern shifts of the Andean condor ( Vultur gryphus ) in Patagonia. We hypothesized that, after the decrease in marine mammals and the increase in human use of coastlines, condor diet changed to a more terrestrial diet, which in turn influenced their foraging patterns. We evaluated the diet by means of stable isotope analysis ( δ 13 C, δ 15 N and δ 34 S) of current (last decade) and historical (1841–1933) feathers. We further evaluated the movement patterns of 23 condors using satellite tracking of individuals. Condors reduced their use of marine-derived prey in recent compared with historical times from 33 ± 13% to less than 8 ± 3% respectively; however, they still breed close to the coast. The average distance between the coast and nests was 62.5 km, but some nests were located close to the sea (less than 5 km). Therefore, some birds must travel up to 86 km from nesting sites, crossing over the mountain range to find food. The worldwide reduction in marine mammal carcasses, especially whales, may have major consequences on the foraging ecology of scavengers, as well as on the flux of marine inputs within terrestrial ecosystems.
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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 | 0.002 |
| 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 | 0.000 |
| 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 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".