分析净生态系统生产力(NEP)的空间分布特点和变化趋势,对科学评估中国生态系统的固碳能力和制定气候变化应对政策/措施具有重要意义,然而目前这方面的研究较为缺乏。该文借助多源空间数据,对2000-2015年中国的NEP进行估算并分析其空间...分析净生态系统生产力(NEP)的空间分布特点和变化趋势,对科学评估中国生态系统的固碳能力和制定气候变化应对政策/措施具有重要意义,然而目前这方面的研究较为缺乏。该文借助多源空间数据,对2000-2015年中国的NEP进行估算并分析其空间分布特点和变化趋势。结果表明:2000-2015年,中国陆地NEP约为0.134 Pg C a^-1,表现为碳汇,碳汇高值区主要分布在云南、四川等省域,而碳源高值区主要分布在西部的西藏和青海等区域;从时间变化趋势看,中国生态系统的碳汇能力总体呈增强趋势,特别是西藏南部、四川南部以及云南、陕西、安徽和江苏等省的部分区域;NEP呈上升、基本不变和下降趋势的省级区域数量占比分别为55%、29%和16%;NEP的空间分布和年际变化主要受NPP、气温和降水的影响。展开更多
Spatial and temporal monitoring of soil properties in smelting regions requires collection of a large number of sam- ples followed by laboratory cumbersome and time-consuming measurements. Visible and near-infrared di...Spatial and temporal monitoring of soil properties in smelting regions requires collection of a large number of sam- ples followed by laboratory cumbersome and time-consuming measurements. Visible and near-infrared diffuse reflectance spectroscopy （VNIR-DRS） provides a rapid and inexpensive tool to predict various soil properties simultaneously. This study evaluated the suitability of VNIR-DRS for predicting soil properties, including organic matter （OM）, pH, and heavy metals （Cu, Pb, Zn, Cd, and Fe）, using a total of 254 samples collected in soil profiles near a large copper smelter in China. Partial least square regression （PLSR） with cross-validation was used to relate soil property data to the reflectance spectral data by applying different preprocessing strategies. The performance of VNIR-DRS calibration models was evaluated using the coefficient of determination in cross-validation （R^2cv） and the ratio of standard deviation to the root mean standard error of cross-validation （SD/RMSEcv）. The models provided fairly accurate predictions for OM and Fe （R2v 〉 0.80, SD/RMSEcv 〉 2.00）, less accurate but acceptable for screening purposes for pH, Cu, Pb, and Cd （0.50 〈 Rcv 〈 0.80, 1.40 〈 SD/RMSEcv 〈 2.00）, and poor accuracy for Zn （R2v 〈 0.50, SD/RMSEcv 〈 1.40）. Because soil properties in conta- minated areas generally show large variation, a comparative large number of calibrating samples, which are variable enough and uniformly distributed, are necessary to create more accurate and robust VNIR-DRS calibration models. This study indicated that VNIR-DRS technique combined with continuously enriched soil spectral library could be a nondestructive alternative for soil environment monitoring.展开更多
文摘分析净生态系统生产力(NEP)的空间分布特点和变化趋势,对科学评估中国生态系统的固碳能力和制定气候变化应对政策/措施具有重要意义,然而目前这方面的研究较为缺乏。该文借助多源空间数据,对2000-2015年中国的NEP进行估算并分析其空间分布特点和变化趋势。结果表明:2000-2015年,中国陆地NEP约为0.134 Pg C a^-1,表现为碳汇,碳汇高值区主要分布在云南、四川等省域,而碳源高值区主要分布在西部的西藏和青海等区域;从时间变化趋势看,中国生态系统的碳汇能力总体呈增强趋势,特别是西藏南部、四川南部以及云南、陕西、安徽和江苏等省的部分区域;NEP呈上升、基本不变和下降趋势的省级区域数量占比分别为55%、29%和16%;NEP的空间分布和年际变化主要受NPP、气温和降水的影响。
基金Supported by the National Natural Science Foundation of China (Nos. 40801081 and 40271104)the open fund from the Key Laboratory of Virtual Geographic Environment of the Ministry of Education,China (No. NS207002)
文摘Spatial and temporal monitoring of soil properties in smelting regions requires collection of a large number of sam- ples followed by laboratory cumbersome and time-consuming measurements. Visible and near-infrared diffuse reflectance spectroscopy （VNIR-DRS） provides a rapid and inexpensive tool to predict various soil properties simultaneously. This study evaluated the suitability of VNIR-DRS for predicting soil properties, including organic matter （OM）, pH, and heavy metals （Cu, Pb, Zn, Cd, and Fe）, using a total of 254 samples collected in soil profiles near a large copper smelter in China. Partial least square regression （PLSR） with cross-validation was used to relate soil property data to the reflectance spectral data by applying different preprocessing strategies. The performance of VNIR-DRS calibration models was evaluated using the coefficient of determination in cross-validation （R^2cv） and the ratio of standard deviation to the root mean standard error of cross-validation （SD/RMSEcv）. The models provided fairly accurate predictions for OM and Fe （R2v 〉 0.80, SD/RMSEcv 〉 2.00）, less accurate but acceptable for screening purposes for pH, Cu, Pb, and Cd （0.50 〈 Rcv 〈 0.80, 1.40 〈 SD/RMSEcv 〈 2.00）, and poor accuracy for Zn （R2v 〈 0.50, SD/RMSEcv 〈 1.40）. Because soil properties in conta- minated areas generally show large variation, a comparative large number of calibrating samples, which are variable enough and uniformly distributed, are necessary to create more accurate and robust VNIR-DRS calibration models. This study indicated that VNIR-DRS technique combined with continuously enriched soil spectral library could be a nondestructive alternative for soil environment monitoring.
