Effects of law enforcement and community outreach on mammal diversity in a biodiversity hotspot
Bibliographic record
Abstract
Management activities such as law enforcement and community outreach are thought to affect conservation outcomes in protected areas, but their importance relative to intrinsic environmental characteristics of the parks and extrinsic human pressures surrounding the parks have not been explored. Furthermore, it is not clear which is more related to conservation outcomes-the management itself or local people's perceptions of the management. We measured objective (reports by park staff) and subjective (reports by local people) levels of community outreach and law enforcement based on responses to 374 questionnaires. We estimated mammal abundance and diversity of 6 protected areas based on data from 115 camera traps in Xishuangbanna, southwest China, a biodiversity hotspot with high hunting and land-conversion pressures. We then examined correlations among them and found that local people's perception of law enforcement was positively related to the local abundance of 2 large, hunted species, wild boar (Sus scrofa) (β = 15.22) and muntjac (Muntiacus vaginalis) (β = 14.82), but not related to the abundance of smaller mammals or to objective levels of enforcement. The subjective frequency of outreach by park staff to local communities (β = 3.42) and park size (β = 3.28) were significantly and positively related to mammal species richness, whereas elevation, human population density, and subjective frequency of law enforcement were not. We could not conclude that community outreach and law enforcement were directly causing increased mammal abundance and diversity. Nevertheless, the patterns we detected are some of the first empirical evidence consistent with the idea that biodiversity in protected areas may be more positively and strongly related to local perceptions of the intensity of park management than to either intrinsic (e.g., elevation, park size) or extrinsic (e.g., human population density) environmental factors.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".