Invertebrate community composition in dominant agroecosystems of Saskatchewan, Manitoba, and North Dakota
Bibliographic record
Abstract
Agriculture currently occupies the majority of the former prairie ecosystem of North America, and farm management decisions affect the abundance and diversity of life in this region. Over 3 yr, we collected and identified the aboveground and soil insect communities from 159 agricultural fields representing 16 different food systems. A total of 107,320 specimens representing 990 operational taxonomic units were collected and identified. The invertebrate community was represented by 24 Orders, 189 Families, and 477 identified Genera. Herbivores were the most abundant (26,112 specimens; 59% of the non-Collembola/mite specimens) and taxonomically rich (308 species; 31%) functional group. Parasitoids, predators, omnivores, and detritivores were each represented by 8% to 10% of specimens collected. Perennial grassland habitats had the most abundant and diverse invertebrate communities (528 insects from 79 species per field); which was approximately twice that of any monocropped system. Including a second cash crop (ie intercropping) often doubled the insect community abundance and richness (380 specimens, 64 species) relative to the component monocrops. This research suggests that conservation and promotion of invertebrate biodiversity within agricultural landscapes may be fostered by supporting perennial grazing lands and intercropping as an alternative to monocrop farming.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".