Lemur responses to edge effects in the Vohibola III classified forest, Madagascar
Bibliographic record
Abstract
Forest edges are dynamic zones characterized by the penetration (to varying depths and intensities) of conditions from the surrounding environment (matrix) into the forest interior. Although edge effects influence many tropical organisms, they have not been studied directly in primates. Edge effects are particularly relevant to lemurs because of the highly fragmented forest landscapes found in Madagascar. In this study, data are presented regarding how the densities of six lemur species (Avahi laniger, Cheirogaleus major, Eulemur rubriventer, Hapalemur griseus griseus, Microcebus rufus, and Propithecus diadema edwardsi) varied between six 500-m interior transects and six 500-m edge transects in the Vohibola III Classified Forest in SE Madagascar. Diurnal (n = 433) and nocturnal (n = 128) lemur surveys were conducted during June-October 2003 and May-November 2004. A. laniger, E. rubriventer, and H. g. griseus exhibited a neutral edge response (no differences in densities between habitats). M. rufus and P. d. edwardsi had a positive edge response (higher densities in edge habitats), which may be related to edge-related variations in food abundance and quality. Positive edge responses by M. rufus and P. d. edwardsi may ultimately be detrimental due to edge-related anthropogenic factors (e.g., hunting by local people). The negative edge response exhibited by C. major (lower densities in edge habitats) may result from heightened ambient temperatures that inhibit torpor in edge habitats.
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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 | 0.000 | 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) | 0.001 | 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".