Capturing the effects of flower strips on natural pest control in agronomic land use models

Abstract

ContextGiven policy objectives for pesticide reduction, functional biodiversity is increasingly important for agricultural production. However, economic land use optimisation models rarely account for the interplay between agricultural production and functional biodiversity, like natural pest control (NPC). ObjectiveWe present and discuss an approach to consider feedback effects between NPC and agricultural production in a geodata-based farm economic land use model. MethodsThe geodata-based land use model PALUD was extended to incorporate interactions between NPC and crop yields. This included linking a generic NPC model, based on semi-natural habitats, with an econometric approach to estimate yield gaps as a function of NPC potential. As a case study, the model was then applied to the German state Brandenburg, using permanent flower strips as example to promote NPC. Here, we analysed the impacts of enhancing NPC potential on food production and gross margins from arable land use. Results and conclusionsOur analysis revealed that a higher level of NPC through flower strips improved gross margins. by up to 6.4 % and crop production by up to 1.2 % within a pesticide-free environment in Brandenburg. Despite inherent limitations and uncertainties of the approach, our study provides a pivotal advancement in integrating NPC into economic land use models. Future refinements incorporating more detailed knowledge on context-specific interactions between crops, pests and predators will improve model robustness. Our approach and case study results provide valuable insights for policy-making on tailored sustainable landscape development and serve as a foundation for future modelling efforts. SignificanceTo our knowledge the interaction between NPC and crop yields has not yet been integrated into any geospatially based economic land use model before. Incorparating these interactions is vital for guiding policies towards sustainable agricultural systems. In this respect it is important to develop and discuss further methodological approaches.