Model-based design of crop diversification through new field arrangements in spatially heterogeneous landscapes. A review

Abstract

AbstractIntensive agriculture in Germany is not only highly productive but has also led to detrimental effects in the environment. Crop diversification together with new field arrangements considering soil heterogeneities can be an alternative to improve resource use efficiency (RUE), ecosystem services (ESS), and biodiversity. Agroecosystem models are tools that help us to understand and design diversified new field arrangements. The main goal of this study was to review the extent to which agroecosystem models have been used for crop diversification design at field and landscape scale by considering soil heterogeneities and to understand the model requirements for this purpose. We found several agroecosystem models available for simulating spatiotemporal crop diversification at the field scale. For spatial crop diversification, simplified modelling approaches consider crop interactions for light, water, and nutrients, but they offer restricted crop combinations. For temporal crop diversification, agroecosystem models include the major crops (e.g., cereals, legumes, and tuber crops). However, crop parameterization is limited for marginal crops and soil carbon and nitrogen (N). At the landscape scale, decision-making frameworks are commonly used to design diversified cropping systems. Within-field soil heterogeneities are rarely considered in field or landscape design studies. Combining static frameworks with dynamic agroecosystems models can be useful for the design and evaluation of trade-offs for ESS delivery and biodiversity. To enhance modeling capabilities to simulate diversified cropping systems in new field arrangements, it will be necessary to improve the representation of crop interactions, the inclusion of more crop species options, soil legacy effects, and biodiversity estimations. Newly diversified field arrangement design also requires higher data resolution, which can be generated via remote sensing and field sensors. We propose the implementation of a framework that combines static approaches and process-based models for new optimized field arrangement design and propose respective experiments for testing the combined framework.