Taxonomic and functional diversity of foliage‐dwelling ants in conventional and organic agroecosystems in southern <scp>Brazil</scp> : A landscape perspective
Bibliographic record
Abstract
Abstract In modern landscapes, understanding how land use and land cover, specifically agriculture, affect biodiversity and ecological functions is essential for conservation. According to Brazilian law, agroecosystems must include areas designated for biodiversity conservation called Legal Reserves. We evaluated the taxonomic and functional diversity of foliage‐dwelling ants in Legal Reserves of agroecosystems in the south of Rio Grande do Sul, Brazil. We aimed to understand how land use and land cover at different landscape scales affect the ant fauna. We sampled ant communities in organic and conventional agroecosystems using passive and active sampling methods (arboreal pitfall traps and active sample, respectively). For the analysis of functional diversity, we measured morphological attributes related to the ecological strategies of ants, such as perception of visual cues, foraging and resource acquisition. We characterized the landscape by visual interpretation of high‐resolution satellite imagery within a 100 m, 500 m and 1 km radius of the sampling areas. We did not identify any effects of cultivation systems on ant fauna. However, we found that landscape characteristics, such as the proportion of natural forest within 100 m, positively affected functional richness. Additionally, within 500 m, natural forest coverage, along with the proportion of cultivation, positively influenced ant incidence. We emphasize the function of Legal Reserves around farms, of serving as support to maintain the presence of ants and the diversity of ecological functions performed by these organisms. We also emphasize that new studies in the region should investigate how a higher homogenization of cultures and cultivation systems, including other phyto‐physiognomies, influence the myrmecofauna of these environments.
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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 | 0.001 |
| Scholarly communication | 0.001 | 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".