Lizard assemblages on sandy coastal plains in southeastern Brazil: An analysis of occurrence and composition, and the role of habitat structure
Bibliographic record
Abstract
Data on the structure of lizard communities in the different biomes and ecosystems of Brazil are still limited. In this study, we related the species richness, abundance and the spatial occurrence of lizards to the structure of the vegetation found on the coast of the state of Espírito Santo, southeastern Brazil, to determine whether habitat influences the structure of lizard communities. We conducted fieldwork in 2012, 2013 and 2014, collecting data in standardized samples. We analyze whether variables of vegetation structure influenced species richness and abundance, using Generalized Linear Models (GLMs). We recorded 12 lizard species from eight families. In general, species richness and abundance were similar among sites. Locally, we recorded the highest species richness in shrubby vegetation, open Clusia vegetation, and the restinga forest zone. Bromeliads explained the occurrence of teiids, although there was no systematic relationship between species richness and vegetation structure. Our results provide important insights into the characteristics of the lizard communities found on sandy coastal plains and contribute to the conservation of these species in these ecosystems.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".