Investigation of North American vegetation variability under recent climate – A study using the SSiB4/TRIFFID biophysical/dynamic vegetation model

Monday, 15 December 2014
Zhengqiu Zhang, CAMS Chinese Academy of Meteorological Sciences, Beijing, China, Yongkang Xue, University of California Los Angeles, Department of Atmospheric and Oceanic Sciences, Los Angeles, CA, United States, Glen M MacDonald, University of California Los Angeles, Los Angeles, CA, United States, Peter Michael Cox, University of Exeter, Exeter, United Kingdom and George James Collatz, NASA Goddard SFC, Greenbelt, MD, United States
This study applies a 2-D biophysical model/dynamic vegetation model (SSiB4/TRIFFID) to investigate the dominant factors affecting vegetation equilibrium conditions, to assess the model’s ability to simulate seasonal to decadal variability for the past 60 years (from 1948 through 2008), to analyze vegetation spatiotemporal characteristics over North America (NA), and to identify the relationships between vegetation and climate. Satellite data are employed as constraints for this study. 

The optimum temperature for photosynthesis, leaf drop threshold temperatures, and competition coefficients in the Lotka-Volterra equation have major impact on the vegetation spatial distribution and reach to equilibrium status in SSiB4/TRIFFID.  The phenomenon that vegetation competition coefficients affect equilibrium suggests the importance of including biotic effects in dynamical vegetation modeling. SSiB4/TRIFFID can reproduce the features of NA distributions of dominant vegetation types, the vegetation fraction, and LAI, including its seasonal, interannual, and decadal variability, well compared with satellite-derived products. The NA LAI shows an increasing trend after the 1970s in responding to warming. Meanwhile, both simulation and satellite observations reveal LAI increased in the southeastern U.S. starting from the 1980s. The effects of the severe drought during 1987-1992 and the last decade in the southwestern U.S.on vegetation are also evident from the simulated and satellite-derived LAIs.

Both simulated and satellite-derived LAIs have the strongest correlations with air temperature at northern middle to high latitudes in spring through their effect on photosynthesis and phenological processes. During the summer, the areas with positive correlations retreat northward. Meanwhile, in southwestern dry lands, the negative correlations appear due to the heat stress there during the summer. Furthermore, there are also positive correlations between soil wetness and LAI, which increases from spring to summer.