Agricultural ecology has been transformed by intensification, with the expansion of monocultures, simplification of landscapes, and removal of non-crop habitats reducing plant and insect diversity. These changes can disrupt pollination, natural enemy communities, and other ecosystem functions, while contributing to pest outbreaks and increasing dependence on synthetic pesticides. Although ecosystem diversification - including crop mixtures, rotations, cover crops, hedgerows, flower strips, agroforestry, and habitat restoration - has been promoted as a basis for conservation biological control, its effects are often context dependent. Recent studies indicate that diversification can increase the abundance and effectiveness of predators and parasitoids, strengthen trophic interactions, and improve several ecosystem services, but outcomes vary according to crop type, spatial scale, landscape context, management intensity, and climatic conditions. Important questions remain regarding the mechanisms underlying these effects, potential trade-offs with crop production, the stability of pest suppression over time, and the conditions required for diversification to deliver reliable benefits. A more integrated assessment of bottom-up and top-down processes, multi-trophic interactions, and landscape-scale management is therefore needed to support the transition from chemically dependent monocultures to resilient agricultural systems.
This Research Topic aims to advance understanding of the ecological, behavioral, and landscape mechanisms through which ecosystem diversification enhances biological pest control. It will examine how manipulating plant, insect, and habitat diversity influences the abundance, movement, interactions, and effectiveness of natural enemies, as well as pest population dynamics and crop performance. Contributions may address whether diversified agroecosystems provide consistent long-term pest suppression, how local management interacts with surrounding landscapes, and which strategies best balance biological control, yield, profitability, biodiversity conservation, and climate resilience. The Research Topic also seeks to identify knowledge gaps and develop practical, evidence-based approaches for reducing reliance on synthetic pesticides.
To gather further insights into ecosystem diversification strategies across local, farm, and landscape scales, this Research Topic welcomes studies focused on agricultural systems and their ecological, agronomic, and socioeconomic outcomes, including but not limited to:
• Plant diversification through intercropping, crop rotation, cover crops, varietal mixtures, and agroforestry; • Habitat diversification using hedgerows, flower strips, field margins, prairie strips, and semi-natural habitats; • Effects of diversification on predators, parasitoids, pollinators, herbivores, and other beneficial insects; • Bottom-up effects of plant diversity on herbivore performance, pest pressure, and crop resistance; • Top-down regulation and multi-trophic interactions in biological control networks; • Behavioral ecology, movement, dispersal, and habitat selection of natural enemies; • Local- and landscape-scale drivers of biological control effectiveness; • Synergies and trade-offs between diversification, crop yield, farm profitability, and pesticide reduction; • Long-term, multi-season, and multi-scale evaluations of ecosystem diversification; • Climate resilience, environmental variability, and the stability of pest suppression; • Modelling, monitoring, and decision-support tools for diversified agricultural landscapes; • Farmer adoption, management feasibility, and the socioeconomic implementation of conservation biological control.
Article types and fees
This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:
Brief Research Report
Data Report
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FAIR² Data
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Hypothesis and Theory
Methods
Mini Review
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Article types
This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:
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