Spider assemblage structure and functional diversity patterns in clear-cut, logged, and undisturbed areas in a large Atlantic Forest remnant
Bibliographic record
Abstract
Habitat loss is one of the main consequences of landscape transformation by humans. Monitoring biodiversity changes in areas under different management strategies is fundamental for species conservation. Our study is the first to assess the role of forest disturbance history on spider (Araneae) biodiversity in the westernmost portion of the Atlantic Forest. We analyzed taxonomic and functional aspects of spider assemblages in understories in a large forest fragment in southwestern Brazil. Spiders were sampled in five 30 m × 5 m plots over three seasons in three areas with different management histories: clear-cutting, selective logging, or native plots. We also characterized tree basal area, tree density, and canopy openness. The clear-cut plots showed more canopy openness and low habitat heterogeneity due to the high density of one pioneer native tree species. Forest structure in selective logging and native plots was similar. Spider richness, abundance, and functional richness were affected only by the season. Species composition also differed among the areas depending on the season. The abundance of web-building species was mainly associated with clear-cut areas in winter and spring. These results highlight the importance of natural regeneration in the Atlantic Forest after disturbance for the conservation of regional spider biodiversity.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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".