06 April 2017 - 07 April 2017
Land use choices affect five critical areas of sustainable development: (i) food production, (ii) greenhouse gas emissions, (iii) biodiversity conservation including forest conservation, (iv) freshwater availability, and (v) air and water pollution. Under current land-use patterns, none of these is sustainable. Food production is threatened by climate change, freshwater stress, loss of biodiversity, and land degradation. Greenhouse gas management is undermined by deforestation, land degradation, and agricultural and livestock practices. Forests and other biodiversity are being lost as habitats are destroyed for agriculture, urbanization, and other purposes. Freshwater is being utilized faster than recharge, for example through the overuse of groundwater. Land use patterns are contributing to air and water pollution through nitrogen and phosphorus fluxes, peat burning, slash-and-burn agriculture, pesticides, and other farm practices. Land use directly impacts almost every planetary boundary: climate change, ocean acidification, nitrogen and phosphorus cycles, freshwater use, changes in land use, biodiversity loss, atmospheric aerosol loading, and chemical pollution. The challenge of achieving sustainable land use is therefore highly complex, and filled with tradeoffs.
Initiated by IIASA and the UN Sustainable Development Solutions Network (SDSN) and implemented with partners around the world under the umbrella of The World in 2050 Initiative, Food, Agriculture, Biodiversity, Land, and Energy (FABLE) project aims to address the following challenges:
Last edited: 05 September 2018
Di Fulvio F, Forsell N, Korosuo A, Obersteiner M, & Hellweg S (2019). Spatially explicit LCA analysis of biodiversity losses due to different bioenergy policies in the European Union. Science of the Total Environment 651: 1505-1516. DOI:10.1016/j.scitotenv.2018.08.419.
Folberth C, Baklanov A, Balkovic J, Skalsky R, Khabarov N, & Obersteiner M (2019). Spatio-temporal downscaling of gridded crop model yield estimates based on machine learning. Agricultural and Forest Meteorology 264: 1-15. DOI:10.1016/j.agrformet.2018.09.021.
Fernández-Martínez M, Sardans J, Chevallier F, Ciais P, Obersteiner M, Vicca S, Canadell J G, Bastos A, et al. (2018). Global trends in carbon sinks and their relationships with CO2 and temperature. Nature Climate Change DOI:10.1038/s41558-018-0367-7. (In Press)
International Institute for Applied Systems Analysis (IIASA)
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