Adjacent habitat type affects the movement of predators suppressing soybean aphids
Bibliographic record
Abstract
Landscape complexity influences soybean aphid suppression by generalist predators in North America, but the role of adjacent habitats as sources of these predators has not been studied directly. We quantified movement of aphidophagous predators between soybean and five adjacent habitats common in Manitoba using bi-directional Malaise traps. To test the contribution of predators from neighboring habitats to soybean aphid suppression, we performed experimental manipulations in adjacent soybean and alfalfa fields and monitored the movement of sevenspotted lady beetles, Coccinella septempunctata, using mark-release-recapture experiments. The identity of adjacent habitats affected the net movement of predators into soybean. The most abundant predators were hover flies (Diptera: Syrphidae), moving from woodlands to soybean. Similar (but non-significant) trends were found for lady beetles, minute pirate bugs, and green and brown lacewings. There was also a net movement of hover flies and green lacewings from soybean to canola. Lady beetles showed higher bidirectional movement in alfalfa and wheat borders than in woodland and canola borders in a high lady beetle abundance year. Soybean aphid populations in predator exclusion cages were 21- to 122- fold higher than populations exposed to predators, both in alfalfa and soybean fields. Aerial predators provide similar levels of aphid suppression as aerial and epigeal predators combined. Mark-release-recapture experiments showed high dispersal of C. septempunctata between soybean and alfalfa, with a net movement towards alfalfa, probably due to the lack of aphids in soybean. These results demonstrate that predator assemblages from both soybeans and alfalfa can suppress soybean aphids. Our findings indicate that the type of adjacent habitat and predator identity affect the directionality of predator movement into soybean. This study suggests that information on predator movement can be used to design the distribution of crops and natural habitats in agricultural landscapes that maximize pest control services.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".