Abundance, density and activity of<i>Salvator merianae</i>(Reptilia: Teiidae) and the effect of poaching on the site occupancy by the lizard in an Atlantic Forest Reserve, Brazil
Why this work is in the frame
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Bibliographic record
Abstract
Abstract We aimed to estimate the density, occupancy and detectability of Salvator merianae (Tegu) in one of the largest Atlantic rainforest remnants in Espírito Santo, Brazil, the VNR . Species patch occupancy was modelled and used to predict the response direction of six covariates based on prior knowledge of the Tegu's ecology. A priori , we expected that the covariates measured should represent key habitat features for the species (i.e. temperature, forest edge, open habitats) or elements possibly avoided by the species, based on the hypothesis that poaching would have a negative effect on patch occupancy. We used line‐transect surveys to estimate density and abundance. Camera‐traps were used to estimate patch occupancy by the Tegu. Estimated density for S. merianae was 0.21 ± 0.02 Tegus/ha and estimated population size was 4990 ± 521 individuals. Patch occupancy was best described by two covariates: poaching intensity and distance to the forest edge. Detectability was affected by three covariates: poaching intensity, tree density and temperature. Our study presents robust information on abundance and density, habitat use, and activity of S. merianae in the VNR and is the first study providing data on the effects that poaching has on patch occupancy of this lizard. The data indicated that the occupancy and detectability of this species were influenced by a set of factors, providing information that can be useful in management plans in areas where this species can potentially decline and in areas where it may be introduced.
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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 | 0.000 |
| 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 | 0.002 |
| 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 it