Evolution in agriculture: the application of evolutionary approaches to the management of biotic interactions in agro‐ecosystems

TLDR

Anthropogenic changes drive ecological and evolutionary processes in agro‑ecosystems, where expanding production and reducing environmental impacts create conflicting pressures that will reshape agriculture over the next 30–40 years. The study aims to demonstrate how integrating agronomic, ecological, and evolutionary perspectives on pest and pathogen interactions can provide practical management insights. The authors propose using predictive evolutionary models as pre‑emptive management tools and outline specific research opportunities to support this approach.

Abstract

Anthropogenic impacts increasingly drive ecological and evolutionary processes at many spatio-temporal scales, demanding greater capacity to predict and manage their consequences. This is particularly true for agro-ecosystems, which not only comprise a significant proportion of land use, but which also involve conflicting imperatives to expand or intensify production while simultaneously reducing environmental impacts. These imperatives reinforce the likelihood of further major changes in agriculture over the next 30-40 years. Key transformations include genetic technologies as well as changes in land use. The use of evolutionary principles is not new in agriculture (e.g. crop breeding, domestication of animals, management of selection for pest resistance ), but given land-use trends and other transformative processes in production landscapes, ecological and evolutionary research in agro-ecosystems must consider such issues in a broader systems context. Here, we focus on biotic interactions involving pests and pathogens as exemplars of situations where integration of agronomic, ecological and evolutionary perspectives has practical value. Although their presence in agro-ecosystems may be new, many traits involved in these associations evolved in natural settings. We advocate the use of predictive frameworks based on evolutionary models as pre-emptive management tools and identify some specific research opportunities to facilitate this. We conclude with a brief discussion of multidisciplinary approaches in applied evolutionary problems.