Coupling paraecology and hunter GPS self‐follows to quantify village bushmeat hunting dynamics across the landscape scale
Bibliographic record
Abstract
Abstract Hunting for bushmeat represents a complex social–ecological system ill‐suited to top‐down management. Community participatory management is an alternative approach with increasing support for both ethical and pragmatic reasons. Key to a community approach is long‐term monitoring: this can both catalyse local ownership of and cohesion around management and is necessary to assess the effects of interventions and make changes as needed through adaptive management. Yet community‐driven methods to monitor hunting remain underdeveloped: they often fail to account for sampling bias and do not incorporate space in a thorough way, and data are not communally analysed to simulate effects of potential management decisions. We created a novel community bushmeat monitoring programme to address these gaps across 20 villages in north‐eastern Gabon. Paraecologists conducted standardised monitoring of bushmeat, and hundreds of hunters conducted GPS self‐follows mapping village hunting catchments. We integrated these data to estimate the proportion of bushmeat sampled and make robust extrapolations of total offtake across space and time, estimating an annual offtake of ~30,000 animals of >56 species across all villages. Here, we present our approach and data—and apply them through a case study of six sympatric duiker species—to inform new directions for social–ecological bushmeat research and management.
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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 | 0.001 | 0.000 |
| 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 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".