Rotation/Succession Systems Affects Springtails (Hexapoda: Collembola) Abundance in Cash Crops Under No Tillage Cultivation
Bibliographic record
Abstract
Acknowledging the bio indicator importance of springtails (Hexapoda: Collembola) for soil quality, this study aimed to determine the abundance of these arthropods in different systems of rotation/succession with commercial and cover crops, while also verifying the agricultural factor associated to these arthropods’ population. In the Instituto de Desenvolvimento Rural do Paraná (IAPAR-EMATER), during six years, areas with differing crops in rotation/succession adopting the no-tillage system were studied. For each system, chemical analyses of the soil were conducted and the number of captured springtails in pitfall traps was counted. The phytosanitary products applied during the evaluations and the quantity of vegetal cover remaining after harvest were considered as well. No difference was found between the rotation/succession systems in relation to chemical soil attributes, however the largest number of springtails was found in crop covers from corn, Brachiaria sp., and canola. These crop covers, including wheat, resulted in the highest straw dry mass. When removing the system in which the predecessor crop had the highest quantities of fungicide application, a positive correlation (r = 0.63; p < 0.01) was found, between springtail abundance and highest amount of straw after the harvest. If no fungicide applications occur, the crops with the largest amount of vegetal cover favor springtail populations.
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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 | 0.000 | 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".