Historical signatures in the alpha and beta diversity patterns of Atlantic Forest harvestman communities (Arachnida: Opiliones)
Bibliographic record
Abstract
The integration of ecology and historical biogeography is fostering the investigation of diversity patterns. We studied alpha and beta diversity patterns of Brazilian Atlantic Forest harvestman (Arachnida: Opiliones) communities and related them to environmental and historical factors. Our data bank contains 508 species from 63 sites, encompassing almost the entire latitudinal range of Atlantic Forest. Alpha diversity was higher in coastal sites in the south and southeast regions and decreased in sites inland, as well as in sites in the coastal northeast region, especially in northern Bahia state. Alpha diversity was positively influenced by precipitation and altitudinal range, but the low number of species in northeastern coastal sites seems to be more related to the historical distribution of Neotropical harvestman lineages than to recent environmental factors. Geographic distance was the most influential factor for beta diversity. Compositional changes were also remarkably congruent with areas of endemism delimited for Atlantic Forest harvestmen. The percentage of protected areas for each area of endemism was very unbalanced, and Espírito Santo and Pernambuco states were the least protected areas. The turnover process observed in the compositional changes indicates that conservation strategies should include as many reserves as possible because every community presents a unique set of species.
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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".