Impact of farming systems on agricultural landscapes and biodiversity: From plot to farm and landscape scales

Abstract

Green-way policies in agricultural landscapes focus on ecological continuity between semi-natural elements (hedgerows, permanent grasslands, woods) and landscape heterogeneity. These policies suggest annual crops and temporary grasslands exhibit a negative or neutral impact on biodiversity. However, recent studies indicated the spatial continuities between different crops (spring vs. winter) showed positive impacts on biodiversity. These landscape patterns were directly related to farmers' decisions regarding the crops cultivated and where the crops were distributed spatially on the farm. The aim of the present study was to evaluate the impacts of different livestock farming system management types on crop patterns and associated biodiversity (carabid beetles) in agricultural landscapes. We combined empirical analyses of farmers' decision making and ecological data to develop a modeling framework simulating crop allocation and abundance of two different carabid beetle species groups (maize and woody species). Modeling included field, farm, and landscape levels. We simulated different scenarios, where two livestock farming systems, swine and dairy, were combined in different proportions (i.e. number of swine vs. dairy farms) in two agricultural landscapes with varied hedgerow densities. Simulations showed maize carabid species abundance was higher in swine production landscapes due to more frequent spatial continuities between spring and winter crops. In contrast, woody carabid species were more abundant in mixed landscapes (dairy and swine) under high crop diversity. For a given combination of livestock farming systems, simulated landscapes were highly variable in crop acreages and spatial continuities between crops. Our results emphasized the need to manage landscape at a collective level, where crop allocation decisions create more interfaces without modifying livestock farming system combinations.