Quantifying agricultural land-use intensity for spatial biodiversity modelling: implications of different metrics and spatial aggregation methods

Abstract

Context Agricultural intensification is a major driver of farmland biodiversity declines. However, the relationship between land-use intensity (LUI) and biodiversity is complex and difficult to characterise, not least because of the difficulties in accurately quantifying LUI across heterogeneous agricultural regions. Objectives We investigated how the use of different LUI metrics and spatial aggregation methods can lead to large variations in LUI estimation across space and thus affect biodiversity modelling. Methods We used three spatial aggregation methods (square, hexagonal, and voronoi grids) to calculate ten commonly used LUI metrics describing three LUI dimensions: land use, land management and landscape structure. Using a virtual species approach, we compared how LUI values sampled at biodiversity monitoring sites vary across different metrics and grids. We modelled the distribution of three virtual species using Generalised Additive Models to test how omitting certain LUI dimensions from the models affected the model results. Results The density distributions of LUI values at the presence points of the virtual species were significantly different across metrics and grids. The predefined species-environment relationships characterising the environmental niches of two out of three virtual species remained undetected in models that omitted certain LUI dimensions. Conclusions We encourage researchers to consider the implications of using alternative grid types in biodiversity models, and to account for multiple LUI dimensions, for a more complete representation of LUI. Advances in remote sensing-derived products and increased accessibility to datasets on farm structure, land-use and management can greatly advance our understanding of LUI effects on biodiversity.