The grassland in the Hindu Kush Himalayan(HKH) region is one of the large st and most biodiverse mountain grassland types in the world,and its ecosystem service functions have profound impacts on the sustainable devel...The grassland in the Hindu Kush Himalayan(HKH) region is one of the large st and most biodiverse mountain grassland types in the world,and its ecosystem service functions have profound impacts on the sustainable development of the HKH region.Monitoring the spatiotemporal distribution of grassland aboveground biomass(AGB) accurately and quantifying its response to climate change are indispensable sources of information for sustainably managing grassland ecosystems in the HKH region.In this study,a pure vegetation index model(PVIM) was applied to estimate the long-term dynamics of grassland AGB in the HKH region during 2000-2018.We further quantified the response of grassland AGB to climate change(temperature and precipitation) by partial correlation and variance partitioning analyses and then compared their differences with elevation.Our results demonstrated that the grassland AGB predicted by the PVIM had a good linear relationship with the ground sampling data.The grassland AGB distribution pattern showed a decreasing trend from east to west across the HKH region except in the southern Himalayas.From 2000 to 2018,the mean AGB of the HKH region increased at a rate of 1.57 g/(m~2·yr) and ranged from 252.9(2000) to 307.8 g/m~2(2018).AGB had a positive correlation with precipitation in more than 80% of the grassland,and temperature was positively correlated with AGB in approximately half of the region.The change in grassland AGB was more responsive to the cumulative effect of annual precipitation,while it was more sensitive to the change in temperature in the growing season;in addition,the influence of climate varied at different elevations.Moreover,compared with that of temperature,the contribution of precipitation to grassland AGB change was greater in approximately 60% of the grassland,but the differences in the contribution for each climate factor were small between the two temporal scales at elevations over 2000 m.An accurate assessment of the temporal and spatial distributions of grassland AGB and the quantification of its response to climate change are of great significance for grassland management and sustainable development in the HKH region.展开更多
ZERO HUNGER has been recognized as a core sustainable development goal (UN 2015).To this end,efforts should be made to increase productivity and production,strengthen capacity for adaptation to climate change,extreme ...ZERO HUNGER has been recognized as a core sustainable development goal (UN 2015).To this end,efforts should be made to increase productivity and production,strengthen capacity for adaptation to climate change,extreme weather and disasters with sustainable food production systems and resilient agricultural practices,and promote food market information transparency to ensure the proper functioning of food commodity markets and to limit extreme food price volatility.展开更多
基金Under the auspices of the Strategic Priority Research Program of the Chinese Academy of Sciences (No.XDA19030202)National Key Research and Development Program of China (No. 2020YFE0200800)+1 种基金International Cooperation and Exchange of National Natural Science Foundation of China (No. 31761143018)National Natural Science Foundation of China (No.42071344)。
文摘The grassland in the Hindu Kush Himalayan(HKH) region is one of the large st and most biodiverse mountain grassland types in the world,and its ecosystem service functions have profound impacts on the sustainable development of the HKH region.Monitoring the spatiotemporal distribution of grassland aboveground biomass(AGB) accurately and quantifying its response to climate change are indispensable sources of information for sustainably managing grassland ecosystems in the HKH region.In this study,a pure vegetation index model(PVIM) was applied to estimate the long-term dynamics of grassland AGB in the HKH region during 2000-2018.We further quantified the response of grassland AGB to climate change(temperature and precipitation) by partial correlation and variance partitioning analyses and then compared their differences with elevation.Our results demonstrated that the grassland AGB predicted by the PVIM had a good linear relationship with the ground sampling data.The grassland AGB distribution pattern showed a decreasing trend from east to west across the HKH region except in the southern Himalayas.From 2000 to 2018,the mean AGB of the HKH region increased at a rate of 1.57 g/(m~2·yr) and ranged from 252.9(2000) to 307.8 g/m~2(2018).AGB had a positive correlation with precipitation in more than 80% of the grassland,and temperature was positively correlated with AGB in approximately half of the region.The change in grassland AGB was more responsive to the cumulative effect of annual precipitation,while it was more sensitive to the change in temperature in the growing season;in addition,the influence of climate varied at different elevations.Moreover,compared with that of temperature,the contribution of precipitation to grassland AGB change was greater in approximately 60% of the grassland,but the differences in the contribution for each climate factor were small between the two temporal scales at elevations over 2000 m.An accurate assessment of the temporal and spatial distributions of grassland AGB and the quantification of its response to climate change are of great significance for grassland management and sustainable development in the HKH region.
基金the financial support from the Strategic Priority Research Program of the Chinese Academy of Sciences (Grant No. XDA19030201)National Natural Science Foundation of China (41561144013)International Partnership Program of Chinese Academy of Sciences (131C11KYSB20160061).
文摘ZERO HUNGER has been recognized as a core sustainable development goal (UN 2015).To this end,efforts should be made to increase productivity and production,strengthen capacity for adaptation to climate change,extreme weather and disasters with sustainable food production systems and resilient agricultural practices,and promote food market information transparency to ensure the proper functioning of food commodity markets and to limit extreme food price volatility.
