Development of a spatially explicit approach for mapping ecosystem services in the Brazilian Savanna – MapES

Abstract

The objective of the presented study is the development of a spatially explicit approach for mapping ecosystem services (MapES) by using specific knowledge about the Cerrado biome (Brazilian Savanna). This biome covers an area of about 2 million km2, i.e. nearly 24% of the total area of Brazil, and has come under substantial pressure during the last 50 years caused by strong land-use/land-cover change, mostly due to agricultural expansion and urbanization. Because of its fast transformation rate, there is an enormous demand for knowledge, and its application, about the effects of land-use/land-cover on the capacity of providing or maintaining ecosystem services. The MapES approach was developed using a vast existing knowledge base. After analyzing and structuring this knowledge the relationships between land-use/land-cover and the potential to provide or maintain eight ecosystem services (Erosion Control, Runoff Control, Water Supply, Water Quality Maintenance, Soil Quality Maintenance, Biodiversity Maintenance, Food Production and Energy Production) were parametrized. In addition, the approach was developed as spatially explicit by including landscape properties (soil, slope and distance to river network) in the cell based system. A reference map of potential natural vegetation and a land use map for 2013 for a meso-scale experimental catchment (32.7km2) were produced. The catchment was used as an example to apply the approach, i.e. assessing and visualizing changes from before human interference to the current land use situation. Finally, a procedure for assessing the potential impacts of land-use/land-cover on ecosystem services considering the methodological limitations of the respective monitoring. The presented approach is easy to understand, to modify and to adapt to other situations and might be therefore used in other context of decision support. It might also help to fill the gap between land use planning and numeric modeling using very complex tools.