DIVERSITY AND DISTRIBUTION OF ANURANS FROM MATA DAS FLORES STATE PARK, ESPÍRITO SANTO, SOUTHEASTERN BRAZIL
Bibliographic record
Abstract
The scarcity of information on anurans to many areas makes it difficult to delimit new conservation areas with higher relevance to the taxa, and therefore, knowledge of community composition and the study of ecological specialties are of fundamental importance for the conservation of the biodiversity. We studied the anuran community of Mata das Flores State Park (MFSP), located in the municipality of Castelo, Espírito Santo state, Southeastern Brazil, evaluating the richness, composition, abundance, and distribution of anurans species. We sampled the MFSP from March/2017 to January/2018, with four occasions during this time period. We performed sampling at night in six plots of 250 meters distributed along the MFSP area, three plots in flooded environments and three plots in forest environments. We sampled the anurans using the active search method, with visual and auditory sampling. During each transect, the plot was surveyed by two observers. We recorded 226 individuals from 18 species of anurans, distributed in six families. The composition and abundance of the anuran species differed between the plots located near the flooded areas and those located in forest areas of the MFSP. Our study is the first to provide data from the MFSP anuran community and our results point to a worrying scenario for the biodiversity of the area, due to the diverse anthropic impacts and presence of the exotic species Lithobates catesbeianus . The Park is an important forest fragment, being continuous to the ecological corridor Pedra Azul - Forno Grande, but it is the conservation unit that suffers the most impacts due to its proximity to urban areas. Thus, long-term studies are necessary, mainly to quantify and evaluate the effects of these impacts on local fauna.
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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".