Diversity of Coleoptera in Maize Crops (Zea mays L.) and a Secondary Succession Area in Paraíba, Brazil
Bibliographic record
Abstract
This work compares the diversity of beetles (Coleoptera) in areas of maize cultivation with fertilization (NPK) and without fertilization, and a field in secondary succession (capoeira) aiming to understand the relation of these organisms in the different systems. The study was carried out in a farm belonging to EMEPA-PB, in the city of Alagoinha, Paraíba state, Brazil, from July to August 2018. Insects were captured in Provid traps and collected every seven days during the vegetative period of the crop. The screenings were carried out at the Zoology Laboratory of the Universidade Federal da Paraiba and the specimens identified at the family level. Data were analyzed using the ANAFAU program. Ten families of beetles were found: Alleculidae, Cecindelidae, Coccinellidae, Carabidae, Scarabaeidae, Cleridae, Staphylinidae, Erotylidae, Chrysomelidae, and Tenebrionidae. Five families were common in all studied areas except for Staphylinidae that was absent in the fertilized area. Beetle families classified as predatory insects were more abundant in the non-fertilized maize system and secondary succession area, except the Coccinellidae family. The families considered as maize crop pests (Scarabaeidae, Chrysomelidae, and Tenebrionidae) had higher abundance in the fertilized maize system. The Erotylidae family also showed predominance in the non-fertilized area. We conclude that there is a greater diversity of beetle in the non-fertilized maize crop when compared to the other studied 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 | 0.000 |
| 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".