Mapping regulating ecosystem service deprivation in urban areas: a transferable high-spatial resolution uncertainty aware approach

Baker, Fraser, Smith, Graham, Marsden, Stuart and Cavan, Gina ORCID: https://orcid.org/0000-0002-8429-870X (2021) Mapping regulating ecosystem service deprivation in urban areas: a transferable high-spatial resolution uncertainty aware approach. Ecological Indicators, 121. p. 107058. ISSN 1470-160X

Preview

Accepted Version Available under License Creative Commons Attribution Non-commercial No Derivatives. Download (7MB) | Preview

Abstract

Maps of regulating urban ecosystem services (UES) aid identification of priority areas for green–blue infrastructure investment to improve urban resilience to environmental hazards. Current mapping approaches however may present coarse spatial resolutions, and often fail to consider how UES flows serve resident demand at the appropriate micro-scale. In addition, prohibitive costs involved in collecting primary data to validate UES model parameters to local conditions may enforce the use of proxy methods, thereby inferring ambiguity in parameterisation and uncertainty in mapping outputs. This study examines both issues through the implementation of a high-spatial resolution approach to map multiple urban regulating ecosystem service (temperature regulation, stormwater absorption, and carbon storage) deprivation in Manchester, UK. Poorly performing UES areas are defined as the lowest 10% combined ecosystem service indicator values (‘coldspots’) at 100m grid resolution. Coldspots are compared to population demand levels, disaggregated from weighted population estimates, indicating neighbourhoods deprived of UES. Ambiguity in proxy method implementation is examined using combinations of UES parameter settings (n = 16) within various demand measures (n = 3) to measure changes in relationships between UES, and variation in final map outputs across the study area. Uncertainty is therefore quantified as an interactive process, whereby input parameter ambiguity affects local uncertainty in map outputs, due to varying landcover composition. As explicit sensitivity analysis in current UES mapping studies is limited, the study demonstrates how ambiguity in method parameterisation may impact UES mapping exercises. Complex interactions governing spatial variance in map uncertainty may therefore be addressed through identification of consistent areas of interest (e.g. hotspots, coldspots) by contrasting outputs realised from different parameterisations. As such, the study demonstrates the mapping approach as a transferable city-wide visualisation tool, using accessible data and methods, to investigate regulating UES deprivation at practical scales required to retrofit existing urban infrastructure with green-blue infrastructure investment.