Restoration Provides Hope for Faunal Recovery: Changes in Primate Abundance Over 45 Years in Kibale National Park, Uganda
Bibliographic record
Abstract
In much of the tropics, the proportion of the land covered by regenerating forest surpasses than in primary forest, thus protecting regenerating forest could offer a valuable conservation opportunity, but only if those lands promote faunal recovery. Chapman et al. documented the recovery of populations of six primate species over up to 45 years in Kibale National Park, Uganda and discovered that in preexisting forest, populations of all species grew, except blue monkeys. Populations (except blue monkeys) also increased by colonizing regenerating forests at previously cleared sites. In many cases, populations in these regenerating areas were of comparable size to those in old-growth forest, and there was little evidence that this population increase corresponded with a decline in neighboring old-growth forests. This research demonstrates the potential for management of regenerating forest to be an effective conservation tool and illustrates the importance of conducting and funding long-term monitoring.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".