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Subject: grazing × WGL Institute: PIK ×

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    Challenges and opportunities in mapping land use intensity globally
    (Amsterdam : Elsevier, 2013) Kuemmerle, Tobias; Erb, Karlheinz; Meyfroidt, Patrick; Müller, Daniel; Verburg, Peter H.; Estel, Stephan; Haberl, Helmut; Hostert, Patrick; Jepsen, Martin R.; Kastner, Thomas; Levers, Christian; Lindner, Marcus; Plutzar, Christoph; Verkerk, Pieter Johannes; van der Zanden, Emma H.; Reenberg, Anette
    Future increases in land-based production will need to focus more on sustainably intensifying existing production systems. Unfortunately, our understanding of the global patterns of land use intensity is weak, partly because land use intensity is a complex, multidimensional term, and partly because we lack appropriate datasets to assess land use intensity across broad geographic extents. Here, we review the state of the art regarding approaches for mapping land use intensity and provide a comprehensive overview of available global-scale datasets on land use intensity. We also outline major challenges and opportunities for mapping land use intensity for cropland, grazing, and forestry systems, and identify key issues for future research.
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    Modelling the role of livestock grazing in C and N cycling in grasslands with LPJmL5.0-grazing
    (Katlenburg-Lindau : Copernicus, 2023) Heinke, Jens; Rolinski, Susanne; Müller, Christoph
    To represent the impact of grazing livestock on carbon (C) and nitrogen (N) dynamics in grasslands, we implement a livestock module into LPJmL5.0-tillage, a global vegetation and crop model with explicit representation of managed grasslands and pastures, forming LPJmL5.0-grazing. The livestock module uses lactating dairy cows as a generic representation of grazing livestock. The new module explicitly accounts for forage quality in terms of dry-matter intake and digestibility using relationships derived from compositional analyses for different forages. Partitioning of N into milk, feces, and urine as simulated by the new livestock module shows very good agreement with observation-based relationships reported in the literature. Modelled C and N dynamics depend on forage quality (C:N ratios in grazed biomass), forage quantity, livestock densities, manure or fertilizer inputs, soil, atmospheric CO2 concentrations, and climate conditions. Due to the many interacting relationships, C sequestration, GHG emissions, N losses, and livestock productivity show substantial variation in space and across livestock densities. The improved LPJmL5.0-grazing model can now assess the effects of livestock grazing on C and N stocks and fluxes in grasslands. It can also provide insights about the spatio-temporal variability of grassland productivity and about the trade-offs between livestock production and environmental impacts.