An empirical evaluation of spatial value transfer methods for identifying cultural ecosystem services. (October 2016) - Brown, Greg; Pullar, David; Hausner, Vera Helene
Highlights: Identifies spatial associations between cultural ecosystem services (CES) and land cover. Examines key variables that can influence spatial value transfer outcomes for CES. Compares spatial value transfer maps generated from primary data in two different regions. Value transfer maps strongly correlated with maps generated from primary data. Describes conditions for using spatial value transfer of CES. Abstract: A significant barrier to the assessment of ecosystem services is a lack of primary data, especially for cultural ecosystem services. Spatial value transfer, also known as benefits transfer, is a method to identify the probable locations of ecosystem services based on empirical spatial associations found in other geographic locations. To date, there has been no systematic evaluation of spatial value transfer methods for cultural ecosystem services identified through participatory mapping methods. This research paper addresses this knowledge gap by examining key variables that influence value transfer for cultural ecosystem services: (1) the geographic setting, (2) the type of ecosystem services, and (3) the land cover data selected for value-transfer. Spatial data from public participation GIS (PPGIS) processes in two regions in Norway were used to evaluate spatial value transfer where the actual mapped distribution of cultural ecosystem values were compared to maps generated using value transfer coefficients. Six cultural ecosystem values were evaluated using two different land cover classification systems GlobCover (300 m resolution) and CORINE (100 m resolution). Value transfer maps based on the distribution of mapped ecosystem values produced strongly correlated results to primary data in both regions. Value transfer for cultural ecosystems appear valid under conditions where the primary data and value transfer regions have similar physical landscapes, the social and cultural values of the human populations are similar, and the primary data sample sizes are large and unbiased. We suggest the use of non-economic value transfer coefficients derived from participatory mapping as the current best approach for estimating the importance and spatial distribution of cultural ecosystem services.