Nonlinear variations of forest leaf area index over China during 1982-2010 based on EEMD method.

Variations in leaf area index (LAI) are critical to research on forest ecosystem structure and function, especially carbon and water cycle, and their responses to climate change. Using the ensemble empirical mode decomposition (EEMD) method and global inventory modeling and mapping studies (GIMMS) LAI3g dataset from 1982 to 2010, we analyzed the nonlinear feature and spatial difference of forest LAI variability over China for the past 29 years in this paper. Results indicated that the national-averaged forest LAI was characterized by quasi-3- and quasi-7-year oscillations, which generally exhibited a rising trend with an increasing rate. When compared with 1982, forest LAI change by 2010 was more evident than that by 1990 and 2000. The largest increment of forest LAI occurred in Central and South China, while along the southeastern coastal areas LAI increased at the fastest pace. During the study period, forest LAI experienced from decrease to increase or vice versa across much of China and varied monotonically for only a few areas. Focusing on regional-averaged trend processes, almost all eco-geographical regions showed continuously increasing trends in forest LAI with different magnitudes and speeds, other than tropical humid region and temperate humid/subhumid region, where LAI decreased initially and increased afterwards.