Double-stranded RNAs (dsRNAs) represent a promising class of biosafe insecticidal compounds. We examined the ability to induce RNA interference (RNAi) in the pollen beetle Brassicogethes aeneus via anther feeding, and compared short-term (3 d) to chronic (17 d) feeding of various concentrations of dsRNA targeting αCOP (dsαCOP). In short-term dsαCOP feeding, only the highest concentration resulted in significant reductions in B. aeneus survival; whereas in chronic dsαCOP feeding, all three concentrations resulted in significant mortality. Chronic dsαCOP feeding also resulted in significantly greater mortality compared to short-term feeding of equivalent dsαCOP concentrations. Our results have implications for the economics and development of dsRNA spray approaches for managing crop pests, in that multiple lower-concentration dsRNA spray treatments across crop growth stages may result in greater pest management efficacy, compared to single treatments using higher dsRNA concentrations. Furthermore, our results highlight the need for research into the development of RNAi cultivars for oilseed rape protection, given the enhanced RNAi efficacy resulting from chronic, compared to short-term, dsRNA feeding in B. aeneus.

Spray-induced gene silencing (SIGS) is a potential strategy for agricultural pest management, whereby nucleotide sequence-specific double-stranded RNA (dsRNA) can be sprayed onto a crop; the desired effect being a consumption of dsRNA by the target pest, and subsequent gene silencing-induced mortality. Nucleotide sequence-specificity is the basis for dsRNA’s perceived biosafety. A biosafe approach to pollen beetle (Brassicogethes aeneus) management in oilseed rape (Brassica napus) agroecosystems is needed. We examined the potential for SIGS in B. aeneus, via bud feeding, a field-relevant dsRNA exposure route. Oilseed rape buds were uniformly treated with dsRNA designed to target αCOP in B. aeneus. Our model control dsRNA (dsGFP) remained detectable on buds throughout the entire 3 d exposure period. When applied at 5 µg/µL, dsαCOP induced significant αCOP silencing 3 d after dietary exposure to buds treated with this dsαCOP concentration. We also observed a trend of increased αCOP silencing with increasing concentrations of dsαCOP at both 3 and 6 d. Furthermore, we observed a marginally significant and significant reduction in B. aeneus survival at 10 and 15 d, respectively. Our results suggest potential for developing a SIGS approach to B. aeneus management—though further experiments are needed to more fully understand this potential.

Pesticide use and habitat loss are major anthropogenic drivers of bee decline, raising global concerns about impaired crop pollination. However, the relative importance of these stressors and their combined impact on bee assemblages comprising species with different traits, such as body size or nesting strategy, remains unknown. Here we addressed these key knowledge gaps in a global quantitative synthesis analysing bee assemblage data from 681 crop fields across three continents. We found that both local pesticide hazards and decreasing proportions of semi-natural habitats in surrounding landscapes negatively affected wild bee abundance and species richness in crop fields, while pesticides additionally reduced functional and phylogenetic diversity. Semi-natural habitat availability did not buffer against these negative pesticide effects, nor did we identify any specific traits rending bees more vulnerable to one of the two drivers. Our findings highlight the pressing need to reduce non-target effects of pesticide use and emphasize that conservation and restoration of semi-natural habitats successfully promote wild bees, but are insufficient strategies to mitigate pesticide-driven losses of wild bee pollinators from crop fields.

BACKGROUND: Agricultural landscapes provide resources for arthropod pests as well as their natural enemies. To develop integrated pest management (IPM) practices, it is important to understand how spatiotemporal location influences crop colonization and damage severity. We performed a 3‐year (2016–2018) field experiment in winter oilseed rape (OSR, Brassica napus) fields in Estonia, where half of the fields were within 500 m of the location of the previous year's winter OSR field and half were outside this zone. We investigated how distance from the previous year's OSR crop influences the infestation and parasitism rates of two of its most important pests: the pollen beetle (Brassicogethes aeneus) and the cabbage seed weevil (Ceutorhynchus obstrictus).RESULTS: When the distance from the previous year's OSR crop was >500 m, we recorded significantly reduced pest pressure by both B. aeneus and C. obstrictus in the study fields. Biocontrol of both pests, provided by parasitic wasps, was high in each study year and commonly not affected by distance. Mean parasitism rates of B. aeneus were >31%, occasionally reaching >70%; for C. obstrictus, mean parasitism was >46%, reaching up to 79%, thereby providing effective biocontrol for both pest species.CONCLUSION: Spatiotemporal separation of OSR fields can reduce pest pressure without resulting in reduced parasitism of OSR pests. This supports a spatiotemporal field separation concept as an effective and sustainable technique for IPM in OSR. © 2023 The Authors. Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

The pollen beetle Brassicogethes viridescens has become an invasive pest to rapeseed crops in North America, especially Canada, the world’s most prolific grower of rapeseed. The use of conventional insecticides to control Brassicogethes spp. can lead to substantial insecticide resistance development in target pest populations and detrimental effects on non-target organisms in and around rapeseed crops. Therefore, economically and ecologically sustainable alternatives to conventional insecticides must be explored. Given the continued increases in production efficacy- and the nucleotide sequence-specific mode of action of dsRNA pesticide products, RNA pesticides represent a potential tool for use within the management of B. viridescens. We examined the insecticidal efficacy of dsRNA against B. viridescens, using transcripts of its intragenus relative Brassicogethes aeneus as a template for dsRNA design. In B. viridescens, we observed similar sensitivities to dsRNA compared to B. aeneus. Furthermore, survival assays using three model non-target species suggest highly selective insecticidal activity of the dsRNAs. Finally, we generated the first transcriptome draft for B. viridescens, which provides valuable information for future management needs against this pest species. Given these first insights towards sustainable RNAi-based management of B. viridescens, further work (different exposure methods, semi-field larval studies) is needed to develop RNAi-based approaches to managing B. viridescens in both European and North American rapeseed systems.

Soil fauna is crucial for carbon cycling, controlling organic matter decomposition and contributing to ecosystem services ^1–7 . Soil microarthropods are top-down regulators in the decomposer food web and serve as fundamental indicators of soil health. Yet, routine field-level monitoring remains restricted to resource-intensive research, leaving a critical gap in arable land management and policy. To address this, we developed Edapholog ^® extractor, a fully automated laboratory device that detects and identifies live soil microarthropods via real-time, AI-based image analysis, enabling taxonomic identification. Here, we demonstrate its accuracy across 319 arable fields spanning ten European countries. We show that computer vision can support ecological interpretation in arable systems and long-term studies on conservation tillage and cover cropping, offering a scalable tool for integrating soil biodiversity metrics into regenerative agriculture and carbon farming. We validated the system against classical taxonomy and found that across ∼35,000 microarthropod individuals, the device achieved an overall accuracy of 86%, sensitivity of 75%, and specificity of 99% compared to manual identifications. Community composition analyses revealed high similarities (83%), with minimal richness differences (7%) and low species replacement (13%) across countries, indicating that the AI does not introduce taxonomic bias. When applied in a long-term field experiment, the system detected significant taxon-specific responses to conservation tillage, with effect sizes ranging from 0.5 to 4. Total abundance, richness, and a soil biological health index were 39%, 47%, and 150% higher, respectively, under conservation tillage compared to conventional ploughing. These effects were statistically consistent between the automated and classical methods. However, while manual microscopy required several hours per sample, the AI-based system delivered immediate results without the need for taxonomic expertise. Edapholog ^® extractor offers exciting opportunities for rapid, scalable soil biodiversity monitoring for future sustainable land management.