Abstract
This study analyzes spatial variability of grassland vegetation growth in response to climate change in the central section of Inner Mongolian Autonomous Region of China. The study area consists of twelve types of plant communities and their spatial distributions reflect an east-to-west water-temperature gradient, transforming from moist meadow-type, to typical steppe-type and then to arid desert-type communities. The enhanced vegetation index (EVI), derived from MODIS at a 250 m resolution and 16-day intervals from May 8 to September 28 during 2000–2010, was adopted as a proxy for vegetation growth. The inter-annual and intra-annual changes of seven climate factors (barometric pressure, humidity, precipitation, sunlight hours, temperature, vapor pressure and wind speed) during the same period were synchronized with the EVI observations and over the twelve types of plant communities, creating a time-series panel dataset. Two panel regression models (the composite and the individual) were developed to explore causal relationships between climatic variables and vegetation growth across distinct plant communities and over time. Both panel regression models confirm that vegetation growth responses to regional climate changes are shaped by the unique characteristics of the study area, and that the interactions between vegetation growth and climate are dependent on a variety of spatially and temporally varying contextual factors.
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