Prioritizing options of plant diversification across scales to control multiple pests: insights from a theoretical approach

Abstract: Designing agroecological farming systems and landscapes that effectively reduce
pest emergence, spread and damage has become crucial for sustainable crop production. Plant diversification is a solid pathway to enhance agroecosystem resistance and resilience, and encompasses multiple management options, including within-field diversification strategies (e. g., cultivar mixture) and landscape-level strategies (e. g., crop diversity). However, managing crop health in a systemic way is challenging as multiple mechanisms to control multiple pests operate across spatial and temporal scales. The theoretical framework we propose aims to improve our understanding about the efficiency of combinations of plant diversification options to limit risks related to pests. We suggest a trait-based framework linking pest functional traits to the ecological processes that influence their dynamics, including resource use, dispersal, and host specialization. This mechanistic approach seeks to move beyond taxonomic descriptions toward a predictive understanding of pest responses to plant diversification options. Building on this framework, we developed a computational tool that allows users to produce a prioritized list of relevant plant diversification options based on simple pest traits through logical rules grounded in a mechanistic understanding of pest control. This innovative, integrated approach aims to connect ecological theory and applied pest management, fostering predictive strategies for sustainable agroecosystems.