Distribution of the critically endangered Coquerel's sifaka (<i>Propithecus coquereli</i>) across a fragmented landscape in NW Madagascar
Bibliographic record
Abstract
Abstract Habitat loss and fragmentation affect species occurrence and distribution in rapidly changing ecosystems. These issues are especially relevant on the Island of Madagascar where modern deforestation has been widespread and is ongoing. We investigated the occurrence of the critically endangered Coquerel's sifaka (Propithecus coquereli) in an anthropogenically modified landscape: the Mariarano region of north‐western Madagascar. We surveyed four large forest sites from 500 to 5,000 ha and 16 forest fragments ranging from 1.5 to 19.2 ha in size. We recorded various attributes of the visited sites such as area, distance to nearest large forest and anthropogenic disturbance. We encountered sifakas in 10 of 16 fragments and in all large forest sites, with the majority of encounters occurring in habitat edge zones. Furthermore, we encountered 19 sifakas in the matrix such as in villages and fields. We found that neither human disturbance, area nor distance to a large forest predicts the presence of sifakas in the Mariarano region. Our results suggest that Coquerel's sifakas are able to persist in highly degraded and small forests fragments, but further research is needed on their long‐term viability in anthropogenically modified landscapes.
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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 | 0.000 | 0.000 |
| 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 | 0.000 |
| 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 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".