Biodiversity-based cropping systems: A long-term perspective is necessary

Abstract

Biodiversity-based cropping systems are an interesting option to address the many challenges that agriculture faces. However, benefits of these systems should not obscure the fact that creating biodiversity-based cropping systems represents a major change for farmers. To address this challenge, we argue that designing biodiversity-based cropping systems requires transforming ecological concepts into technical opportunities. Indeed, integrating ecological concepts such as plant-soil feedback and plant functional traits more strongly into cropping system design offers promising opportunities for the provision of ecosystem services, such as pest and disease control, crop production (including crop yield stability), climate regulation and regulation of soil quality. Accordingly, we demonstrate that designing biodiversity-based cropping systems requires considering not only the short term but also the long term. This would ensure that the expected ecosystem services have enough time to build up and provide their full effects, that the cropping systems are resilient and that they avoid the limitations of short-term assessments, which do not sufficiently consider multi-year effects. Considering long-term consequences of system change - induced by biodiversity - is essential to identify potential trade-offs between ecosystem services, as well as agricultural obstacles to and mechanisms of change. Including farmers and other food-chain actors in cropping system design would help find acceptable compromises that consider not only the provision of ecosystem services, but also other dimensions related to economic viability, workload or the technical feasibility of crops, which are identified as major obstacles to crop diversification. This strategy represents an exciting research front for the development of agroecological cropping systems.

Keywords: Conceptual modelling; Multicriteria assessment; Participatory design; Plant functional trait; Plant–soil feedback; Process-based modelling.