Exploring the regional differences of ecosystem health and its driving factors in China

Spatial heterogeneity of estuarine wetland ecosystem health influenced by complex natural and anthropogenic factors

Geographically weighted regression (GWR) is a classic and widely used approach to model spatial non-stationarity. However, the approach makes no precise expressions of its weighting kernels and is ...

Geographically neural network weighted regression for the accurate estimation of spatial non-stationarity

How human activities influence the island ecosystem through damaging the natural ecosystem and supporting the social ecosystem

Assessing the dynamic landscape ecological risk and its driving forces in an island city based on optimal spatial scales: Haitan Island, China

In this research, factors that influence ecosystem health assessment (EHA) in coastal waters were grouped into three categories: natural causes, direct human causes, and indirect human causes. Statistical analysis based on previous researches was utilized to determine EHA indicators of the first two categories. For the third category, spatio-temporal patterns of potential EHA indicators are prevalent due to the variations of anthropogenic activities in their spatial and temporal distribution across seascape and over timescales. Various Geographic Information System (GIS) analysis methods were hence incorporated to translate and visualize anthropogenic activities into ecosystem-specific impacts. The most adequate indexes were identified to establish a holistic EHA framework. Case study in the northern coastal waters of Zhejiang Province from 2005 to 2014 excellently highlighted ecosystem health changes over the years and revealed the advantage of visualization efficiency and the superiority of considering intense human disturbance of our EHA method over traditional ones.

Congjiao Zhao

Papers

Ecosystem health assessment in coastal waters by considering spatio-temporal variations with intense anthropogenic disturbance