The effects of a national highway on the Endangered golden-brown mouse lemur<i>Microcebus ravelobensis</i>in Ankarafantsika National Park, Madagascar
Bibliographic record
Abstract
Abstract Although roads are often assumed to be barriers to the dispersal of arboreal species, there has been little empirical testing of this assumption. If arboreal animals are unable to cross roads, population subdivision may occur, or resources may become inaccessible. We tested the hypothesis that Route Nationale 4 (RN4), a paved highway, was a barrier to movement and dispersal of the Endangered golden-brown mouse lemur Microcebus ravelobensis in Ankarafantsika National Park, in north-west Madagascar. During June–August 2015 we conducted a capture–mark–recapture study at three sites: two adjacent to RN4 and one within intact forest without a potential barrier. During 2,294 trap nights we captured 120 golden-brown mouse lemurs 1,032 times. In roadside habitats we captured significantly more males than females, whereas the opposite was the case in interior forest habitat. We detected eighteen crossings of highway transects by nine individuals; however, all potential dispersal events involved males. In roadside habitat, movement was significantly inhibited in both males and females. We present some of the first data on the effects of roads on movement patterns in arboreal Malagasy mammals, showing species- and sex-biased effects of roads as dispersal barriers. Our findings indicate that roads may not be complete barriers to dispersal in lemurs. We recommend that conservation managers and scientists examine explicitly the effects of roads and natural arboreal bridges in Madagascar in future studies.
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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 | 0.001 |
| 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 | 0.001 | 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 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".