Disturbance impacts on large rain-forest vertebrates differ with edge type and regional context in Sulawesi, Indonesia
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: Anthropogenic edge effects, whereby disturbance strength increases in proximity to ecotone boundaries, are known to strongly affect individual species but we lack a general understanding of how they vary by species, disturbance type and regional context. We deployed 46 camera-trap stations for a total of 3545 trap-days at two sites in Sulawesi, Indonesia, obtaining 937 detections of five vertebrate species. Anoa ( Bubalus spp.) were more abundant near edges, booted macaque ( Macaca ochreata ) and red jungle fowl ( Gallus gallus ) were less abundant near edges, and edges did not impact Sulawesi warty pig ( Sus celebensis ) or Malay civet ( Viverra tangalunga ). But the relative importance of habitat disturbance from agriculture, roads and villages differed for each species, and edge-induced disturbances varied not only in magnitude but also in direction between the study areas. In the strongest instance, macaque local abundance was 3.5 times higher near villages than it was 3 km into the forest in one reserve, but 2.8 times higher 3 km into the forest than near villages in the other reserve. Our results suggest that responses to habitat edges among species and edge types are idiosyncratic, and that landscape-level context can strongly alter the influence of local disturbance on biodiversity.
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) | 0.000 | 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 it