Range-wide declines of a key Neotropical ecosystem architect, the Near Threatened white-lipped peccary<i>Tayassu pecari</i>
Bibliographic record
Abstract
Abstract We report a range-wide status assessment of a key Neotropical ecosystem architect, the white-lipped peccaryTayassu pecari, categorized as Near Threatened on the IUCN Red List, using published information and unpublished data from 41 scientists in 15 range countries. We estimate that the white-lipped peccary has been extirpated in 21% of its historical range over the last 100 years, with reduced abundance and a low to medium probability of long-term survival in another 48% of its current range. We found major range declines in Argentina, Paraguay, southern Brazil, Colombia, Venezuela, north-east Brazil, Mexico and Costa Rica. This species is particularly at risk in more xeric ecosystems, especially the caatinga, cerrado and pampas. Hunting and habitat destruction are the most severe threats, although there are also unexplained sudden die-offs suggestive of disease. We evaluate our results in light of this species’ important interspecific interactions and its role as an ecosystem architect. One of our recommendations is that conservation efforts should focus on landscape conservation of large, continuous and ecologically intact areas containing a mosaic of different habitat types.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".