Effects of protected area coverage and research on conservation status of primates globally
Bibliographic record
Abstract
Conducting conservation research and establishing protected areas (PAs) based on research results are critical to biodiversity conservation. However, the effect of research and PAs on conservation of threatened species has rarely been evaluated simultaneously. We collected data on PAs from 2000 for 2021 and determined the number of publications on global primates (published from 1950 to 2021) to assess the effect of PAs, research, and biological and socioeconomic factors on the current International Union for Conservation of Nature endangered status and change in status. We used the MCMCglmm package to conduct a phylogenetic comparative analysis to control the phylogenetic relationship of primate species. The status of 24.6% (82 of 333) of species assessed at least twice declined. Only the black lion tamarin (Leontopithecus chrysopygus) had an improved status. Species with status declines mostly occurred on the south coast of West Africa and in Madagascar. PAs covered 22.1% of each species' range. Forest loss in PAs (5.5%) was significantly lower than forest loss within 5 km outside PAs (13.8%), suggesting PAs effectively mitigated forest loss. Both the median number of total publications and conservation publications on critically endangered species were higher than those of other categories. Models showed that PA coverage and number of publications or conservation-focused publications were not related to current status or change in status over time. A decline in status was not related to creation of PAs or increase of research since the last assessment. Our results suggest that current PAs and research are not reversing the extinction crisis of global primates. Doing more conservation-oriented research, strengthening management of current PAs, and expanding PAs will be needed to protect primates globally.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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) | 0.000 | 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 teacher head, 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".