全球变化知识资源中心

Change in precipitation in tropics would have a severe consequence on soil CO2 flux and on its major determinants like soil temperature and soil moisture. Variation in climatic condition also supports the establishment of invasive species in the area. In this communication an attempt is made to assess the impact of change in precipitation regime on soil CO2 flux in a constructed tropical grassland with and without an invasive plant, Hyptis suaveolens. Three rainout shelters with manipulated precipitation doses (i) of 800 mm (20% the below average), (ii) 1100 mm (average) and (iii) 1600 mm (60% above the average) were established, along with one unsheltered plot (open C) receiving ambient precipitation. Each rain-out shelter containing three sub-treatments viz. (i) bare plots with no vegetation, (ii) uninvaded indigenous grassland plots (NIG), and (iii) grassland plots invaded with H. suaveolens (IG). Significant high soil CO2 flux was found in plots receiving maximum precipitation (1600 mm) and low in plots receiving minimum precipitation (800 mm). Furthermore, vegetated plots (NIG and IG) exhibited higher soil CO2 flux than the non-vegetated plots. Among the vegetated plots, IG plots receiving maximum precipitation (1600 mm) had highest soil CO2 flux, followed by IG plots receiving 1100 mm, and 800 mm precipitation. Seasonal and monthly observations showed that maximum soil CO2 flux occurred in rainy season, (in July), and minimum in winter season (in January). The important controlling factors for soil CO2 flux were soil moisture, root biomass and soil temperature. In this study soil moisture explained 61% variability in the soil CO2 flux. A linear combination of moisture and root biomass explained 74% variability in soil CO2 flux, and when temperature was added in the multiple regression a total of 79% variability in soil CO2 flux was accounted for. These findings would help us to understand the biological thresholds of tropical ecosystem related to precipitation regime. It will encourage researchers around the globe to develop ecosystem models, which would enable to forecast the impact of climate change on nutrient cycling.