Biodiversity Models Need To Represent Land-Use Intensity More Comprehensively

GLOBAL ECOLOGY AND BIOGEOGRAPHY(2021)

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Abstract
Background Land use is the major driver of the current biodiversity crisis. However, its impact is not yet adequately reflected in biodiversity scenarios. In particular, effects of land-use intensity are often neglected although natural limits to land conversion will likely enforce further land-use intensification in the future.Aims and innovation We argue that integration of land-use intensity into biodiversity models should ideally be based on a proper conceptualization of the land-use intensity phenomenon. We, therefore, present terminological distinctions and a conceptual framework developed in land system science. The framework distinguishes three dimensions of land-use intensity: input intensity, output intensity, and alterations of system properties. We discuss nonlinearities and intricacies of the relationships among these dimensions as well as their direct and indirect relationships to biodiversity. In an explorative literature assessment we demonstrate that the multi-dimensional nature of land-use intensity appears insufficiently reflected in biodiversity research. Finally, we discuss issues of data availability that limit integration of land-use intensity into spatially and temporally explicit biodiversity modelling.Conclusion Research on the relationship between land use and biodiversity would profit from a more systematic and comprehensive consideration of land-use intensity. While there is no standard recipe for combining indicators of land-use intensity in biodiversity studies the input-output-system distinction is a useful conceptual basis for study designs. More generally, better integration of biodiversity and land system science would foster understanding and predicting the consequences of land-use intensification on biodiversity.
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Key words
biodiversity loss, ecosystem properties, input intensity, land&#8208, use change, land&#8208, use intensification, output intensity, predictive model
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