Macroecological approach for scorpions (Arachnida, Scorpiones): β-diversity in Brazilian montane forests
Bibliographic record
Abstract
The montane forests of northeastern Brazil are patches of rainforests, surrounded by xeric vegetation, that originated during the expansion of rainforests in the Pleistocene epoch. Their historical processes make these areas ideal for biogeographical investigations of organisms, particularly in groups with low dispersion and habitat specificity, such as scorpions. We perform a macroecological investigation of the community assembly process of scorpions, disentangling the pattern of β-diversity to test the hypothesis that the similarity in the composition of scorpion fauna in areas of montane forests and coastal rainforests is greater when these localities are geographically close. We also investigated if larger patches of montane forests exhibit a positive species–area relationship. Our results state that species replacement accounts for 71% of the total scorpion β-diversity in montane forest remnants. Additionally, scorpion assemblages were influenced by the spatial arrangement, with a higher similarity between the fauna of montane forests and coastal forests when these areas were geographically close. We did not find a species–area relationship in montane forest patches. The expressive contribution of species replacement to the overall β-diversity may reflect both the high environmental heterogeneity and the historical and independent colonization events that took place in these areas.
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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 | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 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".