Edge effects and their influence on lemur density and distribution in Southeast Madagascar
Bibliographic record
Abstract
Edge effects are caused by the penetration of abiotic and biotic conditions from the matrix into forest interiors. Although edge effects influence the biogeography of many tropical organisms, they have not been studied directly in primates. Edge effects are particularly relevant to lemurs due to the loss of 80-90% of forests in Madagascar. In this study, data are presented on how biotic edge effects influenced the distribution and density of lemurs in the Vohibola III Classified Forest in southeastern Madagascar. In total, 415 lemur surveys were conducted during June-October 2003 and May-September 2004 along six 1,250-m transects that ran perpendicular to the forest edge. Data were also collected on lemur food trees along the six transects (density, height, diameter at breast height, area, volume, and distance to forest edge). Four nocturnal species (Avahi laniger, Cheirogaleus major, Lepilemur microdon, and Microcebus rufus) and four diurnal species (Eulemur rubriventer, Eulemur fulvus rufus, Hapalemur grisesus griseus, and Propithecus diadema edwardsi) were sighted during surveys. Regression analyses of lemur densities as a function of distance to forest edge provided edge tolerances for A. laniger (edge-tolerant), M. rufus (edge-tolerant), E. rubriventer (edge-tolerant or omnipresent), and H. g. griseus (omnipresent). The density and distribution of M. rufus and their foods trees were correlated. Edge-related variations in food quality and predation pressures may also be influencing lemurs in Vohibola III. Tolerance for edge effects may explain, in part, how lemurs have survived extreme habitat loss and forest fragmentation in southeastern Madagascar.
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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".