Changes in arthropod communities mediate the effects of landscape composition and farm management on pest control ecosystem services in organically managed strawberry crops
Bibliographic record
Abstract
Abstract Landscape composition and local diversification practices such as polyculture, cover cropping and hedgerows may promote natural pest control by benefiting natural enemy communities on farms. Our study employs piecewise structural equation modelling (PSEM) to test causal hypotheses regarding the effects of landscape composition and local diversification practices on arthropod communities and pest control ecosystem services. We sampled 27 organic strawberry fields in California's Central Coast region in 2015 and 2016 (17 repeated between years) for a total of 37 distinct sites across years. The sites were selected along orthogonal gradients of landscape composition and local diversification practices. We also investigated the effects of two common pest management practices. At each site, we sampled arthropod communities using a handheld vacuum and performed sentinel prey experiments using the pest species Lygus hesperus to estimate pest control levels. At the landscape scale, proportion of woody habitat increased natural enemy abundance; at the local scale, on‐farm diversification practices increased natural enemy diversity. Insecticides and tractor vacuuming, aimed at controlling pests, were indirectly detrimental to pest control services. Both practices decreased natural enemy abundance, and while insecticides also decreased pest abundance, vacuuming did not. Natural enemy abundance and diversity increased pest control levels, while pest abundance had the opposite effect. The PSEM results confirmed our hypotheses that landscape and local effects on pest control are mediated through changes in arthropod communities. Synthesis and applications . At the landscape scale, higher proportions of woody habitat are associated with greater natural enemy abundance, which increases pest control levels in organic strawberry crops. When promoting pest control ecosystem services is a policy goal, regional planners should prioritize the conservation and restoration of woodlands in agricultural landscapes. At the local scale, actions by individual growers can impact pest control services. For many growers, adopting practices that promote on‐farm plant diversity may be a feasible solution for increasing pest control levels while avoiding the environmental and economic costs imposed by insecticide application and tractor vacuuming.
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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) | 0.000 | 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".