Changing patterns and determinants of natural capital in the Yangtze River Delta of China 2000-2010

Natural capital (NC) is crucial to human existence and human well-being. Evaluating ecosystem services on a regional scale has presented tremendous theoretical, methodological and policy challenges. This study addresses the challenges by developing an interdisciplinary methodology, based on expert knowledge, and by focusing on the Yangtze River Delta of China. It evaluates the stock of NC, analyzes the characteristics of, and identifies the key drivers for, spatial and temporal change in NC in the deltaic region from 2000 to 2010. A main contribution is the novel incorporation of remote sensing data that explains the dynamics of the spatio-temporal change in land use and a set of ecosystem service indicators derived from it. The study focuses on key indicators for key ecosystem services related to carbon sequestration, grain production and water supply. The indictors reflect the spatial heterogeneity of NC across diverse ecosystems in the region. Each indicator builds on land use configuration and land use composition information derived from 250 m 16-day MODIS and Landsat TM remote sensing data for 2000 and 2010, with adjustment parameters being constructed. The regional evaluation shows an overall degradation of ecosystem services, reducing total NC by 10.4% (or 8.44 billion yuan) in 2000-2010. The spatial distribution of NC exhibits a declining pattern from the south to the north of the delta. At the city level, 15 out of 16 major cities in the region have experienced dramatic loss of NC, and this pattern is significantly correlated with rapid urbanization, population growth and industrialization. Land use/land cover change and deteriorating water quality are dominant factors causing NC depletion, while increased grain productivity and environmental policies help offset the NC losses. Outcomes of this research are useful to policy makers to mitigate the declines in NC through balancing the growth between economy and population.