Estimating the Net Primary Production of Chinese Forest Ecosystem with Spatial Statistical Methods
Tonglin Zhang
Statistics, Purdue University, West Lafayette, IN, United States

Forest ecosystems play an important role in global carbon cycle and quantification of forest net primary production (NPP) in a spatial context remains an important challenge at landscape, regional and continental scales. Previous studies have revealed that the spatial correlation is present in forest NPP distributions. By using spatial statistical methods, this study first investigated the local relationship between Chinese forest NPP density and many climate variables, and then derived prediction of the national forest NPP total. The results showed that the geostatistical modeling method made significantly better prediction than multiple regression method, and it was more robust than the remote sensing or process-based methods.

Keywords: Net primary production; Spatial statistics; Kriging prediction; Correlation function

Biography: Dr. Zhang received his Ph.D. in statistics from the University of Michigan. He is an associate professor of statistic, Purdue University, West Lafayette, Indiana, USA. His research interest is spatial statistics for public health and environment.