Ecological fragmentation effects in mouse lemurs and small mammals in northwestern Madagascar
Bibliographic record
Abstract
Habitat loss and fragmentation are major ecological forces threatening animal communities across the globe. These issues are especially true in Madagascar, where forest loss is ongoing. We examined the effects of forest fragmentation on the distribution and abundance of sympatric, endemic gray, and golden-brown mouse lemurs (Microcebus murinus and Microcebus ravelobensis), the endemic western tuft-tailed rat (Eliurus myoxinus), and the invasive black rat (Rattus rattus) in two regions in northwestern Madagascar. We used systematic capture procedures in 40 forest fragments and four continuous forest sites which differed in size, shape, and degree of isolation. With a trapping effort of 11,567 trap nights during two dry seasons (2017-2018), we captured 929 individuals (432 M. ravelobensis, 196 M. murinus, 116 E. myoxinus, and 185 R. rattus). We examined the influence of study region, forest type (fragment vs. continuous), forest size, forest shape, the proportion of 50-m forest edge and distance to continuous forest on the abundance and interaction of the four species. Responses to fragmentation differed strongly between species, but no interaction could be detected between the abundance of the different species. Thus competition within and between native and invasive species may not be regulating abundances in these regions. On the contrary, the abundance of M. ravelobensis and E. myoxinus differed significantly between study regions and was negatively affected by fragmentation. In contrast, there was no evidence of an impact of fragmentation on the abundance of M. murinus. Finally, the invasive R. rattus responded positively to the increasing distance to the continuous forest. In conclusion, the response of small Malagasy mammals to forest fragmentation varies largely between species, and fragmentation effects need to be examined at a species-specific level to fully understand their ecological dynamics and complexity.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 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".