Impact of <scp>H</scp>urricane <scp>D</scp>ean (2007) on Game Species of the <scp>S</scp>elva <scp>M</scp>aya, <scp>M</scp>exico
Bibliographic record
Abstract
Abstract We assessed the effects of a high‐intensity hurricane on the abundance of nine game species in the Yucatan Peninsula, Mexico. We sampled 370 km of linear transects in the 3 yr before the hurricane (i.e., 2003–2005), and 315 km in 3 yr after the hurricane (2008–2010). Relative track abundances of all species declined by two‐thirds of their prehurricane values. Abundances of Central American agouti Dasyprocta punctata, white‐tailed deer Odocoileus virginianus, paca Cuniculus paca, and Great Curassow Crax rubra declined significantly after the hurricane swept the area. Relative track abundances showed a negative, but nonsignificant trend for Ocellated Turkey Meleagris ocellata, white‐nosed coati Nasua narica, brocket deer Mazama sp., and collared peccary Pecari tajacu. Only nine‐banded armadillo Dasypus novemcinctus showed a significant increase in abundance. Strictly frugivore and habitat specialist species were more affected than omnivores and habitat generalist species. These latter characteristics, or their combination, seemed advantageous to withstand the stress of habitat disturbance. The trend of posthurricane recovery was incipient for affected species, and it was significant for five species after the impact. Overall, most frugivores and habitat specialists did not reach their prehurricane relative track abundances, and Great Curassow showed no recovery trend. The future expectation of increased frequency and intensity of hurricanes might have severe effects on such species.
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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 | 0.000 | 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) | 0.001 | 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".