Recent decline in suitable large mammal habitats within the Dzanga Sangha Protected Areas, Central African Republic
Bibliographic record
Abstract
The forests of the Congo Basin are an important home to some of the world’s most critically endangered species, including the central chimpanzee (Pan troglodytes troglodytes), the western lowland gorilla (Gorilla gorilla gorilla) and the forest elephant (Loxodanta cyclotis). To contribute to the long-term sustainability of these species and their habitats within the Dzanga Sangha Protected Areas (DSPA) in the Central African Republic, the World Wide Fund for Nature (WWF) developed an ecological monitoring program to assess the spatial drivers of species' habitat changes. Here, we assess and quantify chimpanzee, gorilla and elephant habitat suitability within the DSPA using data from two survey years (2015 and 2020), to identify priority habitat areas and recommend conservation measures to mitigate ongoing habitat changes. We found that priority chimpanzee habitats covered about 1383 km2 (30 %) of the entire DSPA in the year 2015, while priority gorilla and elephant habitats covered approximately 2569 km2 (56 %) and 3075 km2 (67 %) respectively. Priority habitat area for the three species declined by 4, 4.5 % and 9.8 % points respectively between 2015 and 2020, mostly due to increased human pressures. We further provide evidence that the Dzanga National Park represents a region of higher priority habitat for all three species owing to the reduced human pressure that has resulted from higher eco-guard patrol efforts. Based on our analysis, we recommend maintaining a nonviolent patrol presence to mitigate human pressures within remaining priority habitat areas, recognizing also the importance of collaboration with local communities to support long-term conservation goals.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".