Grassland covers approximately one-third of the area of China and plays an important role in the global terrestrial carbon(C) cycle.However,little is known about biomass C stocks and dynamics in these grasslands.Durin...Grassland covers approximately one-third of the area of China and plays an important role in the global terrestrial carbon(C) cycle.However,little is known about biomass C stocks and dynamics in these grasslands.During 2001-2005,we conducted five consecutive field sampling campaigns to investigate above-and below-ground biomass for northern China's grasslands.Using measurements obtained from 341 sampling sites,together with a NDVI(normalized difference vegetation index) time series dataset over 1982-2006,we examined changes in biomass C stock during the past 25 years.Our results showed that biomass C stock in northern China's grasslands was estimated at 557.5 Tg C(1 Tg=1012 g),with a mean density of 39.5 g C m-2 for above-ground biomass and 244.6 g C m-2 for below-ground biomass.An increasing rate of 0.2 Tg C yr-1 has been observed over the past 25 years,but grassland biomass has not experienced a significant change since the late 1980s.Seasonal rainfall(January-July) was the dominant factor driving temporal dynamics in biomass C stock;however,the responses of grassland biomass to climate variables differed among various grassland types.Biomass in arid grasslands(i.e.,desert steppe and typical steppe) was significantly associated with precipitation,while biomass in humid grasslands(i.e.,alpine meadow) was positively correlated with mean January-July temperatures.These results suggest that different grassland ecosystems in China may show diverse responses to future climate changes.展开更多
为了推进高光谱遥感在草地生理生化参数定量化方面的研究与应用,从冠层尺度上估算草地生物量,该文选用美国A SD公司的A SD F ie ldSpec P ro FRTM光谱仪,对内蒙古自治区锡林郭勒盟的天然草地进行高光谱遥感地面观测。在进行天然草地地...为了推进高光谱遥感在草地生理生化参数定量化方面的研究与应用,从冠层尺度上估算草地生物量,该文选用美国A SD公司的A SD F ie ldSpec P ro FRTM光谱仪,对内蒙古自治区锡林郭勒盟的天然草地进行高光谱遥感地面观测。在进行天然草地地上生物量与原始光谱和高光谱特征变量相关分析的基础上,将观测数据分成两组:一组观测数据作为训练样本,运用单变量线性、非线性和逐步回归分析方法,建立生物量高光谱遥感估算模型;另一组观测数据作为检验样本,进行精度检验。结果表明:生物量与高光谱吸收特征参数变量的分析中,以840、1132、1579、1769和2012 nm等5个原始高光谱波段反射率为变量的逐步回归估算方程为最佳模型,模型标准差为0.404 kg/m2,估算精度为91.6%,说明可以利用高光谱反射率数据,从冠层上对草地生物量进行量化。展开更多
基金supported by the National Natural Science Foundation of China (Grant Nos. 90711002 and 90211016)
文摘Grassland covers approximately one-third of the area of China and plays an important role in the global terrestrial carbon(C) cycle.However,little is known about biomass C stocks and dynamics in these grasslands.During 2001-2005,we conducted five consecutive field sampling campaigns to investigate above-and below-ground biomass for northern China's grasslands.Using measurements obtained from 341 sampling sites,together with a NDVI(normalized difference vegetation index) time series dataset over 1982-2006,we examined changes in biomass C stock during the past 25 years.Our results showed that biomass C stock in northern China's grasslands was estimated at 557.5 Tg C(1 Tg=1012 g),with a mean density of 39.5 g C m-2 for above-ground biomass and 244.6 g C m-2 for below-ground biomass.An increasing rate of 0.2 Tg C yr-1 has been observed over the past 25 years,but grassland biomass has not experienced a significant change since the late 1980s.Seasonal rainfall(January-July) was the dominant factor driving temporal dynamics in biomass C stock;however,the responses of grassland biomass to climate variables differed among various grassland types.Biomass in arid grasslands(i.e.,desert steppe and typical steppe) was significantly associated with precipitation,while biomass in humid grasslands(i.e.,alpine meadow) was positively correlated with mean January-July temperatures.These results suggest that different grassland ecosystems in China may show diverse responses to future climate changes.
