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作 者:杨淑霞[1] 冯琦胜[1] 孟宝平[1] 高金龙[1] 葛静[1] 梁天刚[1] Yang Shu xia;Feng Qi-sheng;Meng Bao ping;Gao Jin long;GeJing;I.iang Tian gang(State Key Laboratory of Grassland Agro ecosystems, College of Pastoral Agriculture Science and Fechnology, Lanzhou University, Lanzhou 730020, Gansu, Chin)
机构地区:[1]兰州大学草地农业生态系统国家重点实验室兰州大学草地农业科技学院,甘肃兰州730020
出 处:《草业科学》2018年第5期956-968,共13页Pratacultural Science
基 金:国家自然科学基金项目(31372367;3167130274;31702175);长江学者和创新团队发展计划(IRT13019)
摘 要:三江源区位于青藏高原腹地,作为长江、黄河和澜沧江的发源地,是我国重要的水源涵养和生态功能保护区。为了分析三江源区草地生物量的动态变化,本研究采用了人工神经网络方法(back propagation artificial neural network,BP ANN)模拟了草地地上生物量(above ground biomass,AGB),估算了2001-2016年草地AGB,从草地类型和流域两方面对草地AGB时空变化特征进行分析。结果表明:1)基于BP ANN的CXYN模型适用于研究区生物量的高精度反演,该模型的R2为0.77,RMSE为429.06kg·hm-2;2)16年间,三江源区草地生物量的变化趋势主要以稳定和恢复为主;3)草地生物量在空间分布上表现出明显的地域差异,呈现出由东南向西北逐渐减少的趋势。东南部部分区域AGB可达3 000kg·hm-2,而西北部的部分区域AGB小于500kg·hm-2。The Three-River Headwaters Region,located in the hinterland of the Qinghai-Tibet Plateau,contains the headstreams of the Yangtze River,Yellow River,and Lancang River.It is an important area for water conservation and protection of ecological functions in China.To analyze the dynamics of the Three-River Headwaters Region,a back propagation artificial neural network(BP-ANN)was used to simulate the grassland aboveground biomass(AGB).The grassland AGB was estimated from 2001 to 2016,and the characteristics of the temporal and spatial changes of the grassland AGB from different grassland types and river basins were analyzed.The results showed that:1)The CXYN model based on BP-ANN is suitable for grassland biomass inversion(R2=0.769 9,RMSE=429.1 kg·ha-1);2)In the past 16 years,the grassland AGB,overall,tended to be stable and restored;3)The spatial distribution of AGB included significant regional differences,with a decreasing trend from the southeast to the northwest.The AGB was up to 3 000 kg·ha-1 in some parts of the southeast,but was very low(less than 500 kg·ha-1)in some parts of the northwest.
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