Linking crop availability, forest elephant visitation and perceptions of human–elephant interactions in villages bordering Ivindo National Park, Gabon
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Feeding by Critically Endangered forest elephants Loxodonta cyclotis in rural plantations is a conservation issue in Gabon, but studies characterizing drivers of spatiotemporal patterns of human–elephant interactions remain sparse, hindering mitigation. In this study, we use GPS tracking data from two elephants to characterize temporal patterns of village visitation, and surveys of 101 local farmers across seven villages to determine local patterns of crop planting and harvesting and of human–elephant interactions. Local farmers' perceptions of elephant visitations and empirical data on such visits were positively correlated with local crop availability. However, considering the two elephants separately revealed that the correlations were driven by just one individual, with the second elephant showing weak links between crop availability and visitation, highlighting the challenges in reliably predicting human–wildlife interactions. The most popular local perceptions of the drivers of elephant visitation were the presence of crops (53% of responses) and logging (39%). The most popular proposed interventions were letting the government find a solution (32%), killing problem elephants (30%) and providing compensation for lost crops (22%). We discuss the potential feasibility and efficacy of the proposed solutions in the context of human–elephant interactions. Future research efforts should focus on collaring elephants in zones with high potential for negative human–elephant interaction and expanding perception surveys to villages with contrasting ecological contexts (e.g. with and without logging in their surrounding forests), as these could influence local perceptions of conflicts and conservation initiatives.
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.
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 | 0.000 | 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 it