Abstract

Higher crop diversity can enhance biodiversity and ecosystem services; however, it remains unclear to what extent and where crop diversity can be increased. We use spatially explicit multiscale optimization to determine potential and attainable crop diversity with field-level land use data for case studies in Brandenburg, Germany. Our model maximizes crop diversity at the landscape scale while reassigning crop types over multiple years to existing arable fields. The model implements field-level crop sequence rules and maintains the crop composition of each farm and for each year. We found that a 10% higher crop diversity can be attained on average compared to currently observed diversity; minor changes in crop composition would close this gap. Improved crop allocation can contribute to closing the gap between observed and attainable crop diversity, which in turn can increase biodiversity, improve pollination services, and support pest control.

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