Restored marginal farmland benefits arthropod diversity at multiple scales
Bibliographic record
Abstract
The loss of resource‐rich non‐crop habitat is a hypothesized driver of arthropod decline on farms, implying recovery with restoration. Alternatively, chronic arthropod loss may limit colonization to abundant taxa, especially crop pests. Here, we test the impact of restoring marginal farmland on agriculturally important arthropods on 13 conventional farms across a 10,000 km2 region of central North America with approximately 92% crop cover. We examined local richness by habitat (crops, restored prairie, remnant forest), spatial turnover among habitat and farms, and regional comparisons between farm and non‐farms using iNaturalist data. Sampling approximately 13,000 individuals identified to family or lower, restored prairie had twice the abundance of arthropods compared to crop and forest, with 44% of all families detected, 66% of beneficial families, and 94 unique taxa despite their recent construction (<10 years) and small size (~9.6% of farm area). There was some compositional overlap between crop and prairie, while farm forest had mostly unique taxa. Larger restored areas supported more diverse and taxonomically uniform arthropod assemblages, while crop fields were family‐depauperate with primarily herbivorous taxa. Unexpectedly, the abundance and richness of arthropods between farms with restored habitat and non‐farm areas regionally were similar, although farms possessed more herbivorous species and fewer butterflies and aquatics. The extensive and rapid colonization of restored habitat by beneficial arthropods implies that conventional farms may be habitat limited for many taxa. Our work supports calls for farm redesign that includes habitat reconstruction, which can support arthropods with known benefits to food production.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.002 | 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".