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青藏高原草地承载力空间演变特征及其预警
引用本文:王立景,肖燚,孔令桥,吴炳方,欧阳志云.青藏高原草地承载力空间演变特征及其预警[J].生态学报,2022,42(16):6684-6694.
作者姓名:王立景  肖燚  孔令桥  吴炳方  欧阳志云
作者单位:中国科学院生态环境研究中心, 城市与区域生态国家重点实验室, 北京 100085;中国科学院大学, 北京 100049;中国科学院空天信息研究院, 北京 100094
基金项目:第二次青藏高原科学考察研究"生态脆弱性与生态安全"专题(2019QZKK0308)
摘    要:为研究青藏高原草地承载力的空间演变特征并对其进行预警,以已有的青藏高原净初级生产力数据为基础,核算了该地区的草地理论载畜量及演变趋势,并结合县域实际存栏量,划定了草地承载力的预警等级。结果表明:(1)青藏高原草地承载力整体呈东高西低的格局,其中高寒草原和高寒草甸是该地区草地承载力的主要组成部分;(2)2000-2015年,青藏高原理论载畜量由8614.89万羊单位增至9451.53万羊单位;(3)青藏高原整体处于超载状态,2000-2010年超载状况加剧,至2015年超载状况稍有缓解,草畜平衡指数由67.88%增至79.90%,再降至67.91%。目前亟需优先控制72个红色预警县(超载状态正在加剧)的牲畜存栏量,避免超载状况进一步恶化。未来需要通过控制牲畜存栏量、调整畜牧区发展布局和提高草地生产力等多项措施的结合来改善青藏高原地区的草地承载状况,维持草地生态系统的可持续发展。

关 键 词:草地生态系统  承载力  预警  青藏高原
收稿时间:2021/2/3 0:00:00
修稿时间:2022/2/23 0:00:00

Spatiotemporal patterns and early-warning of grassland carrying capacity in the Qinghai-Tibet Plateau
WANG Lijing,XIAO Yi,KONG Lingqiao,WU Bingfang,OUYANG Zhiyun.Spatiotemporal patterns and early-warning of grassland carrying capacity in the Qinghai-Tibet Plateau[J].Acta Ecologica Sinica,2022,42(16):6684-6694.
Authors:WANG Lijing  XIAO Yi  KONG Lingqiao  WU Bingfang  OUYANG Zhiyun
Institution:State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China;University of Chinese Academy of Sciences, Beijing 100049, China;Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China
Abstract:Grassland ecosystem carrying capacity (GCC) is directly related to herdsmen''s livelihood, and the implementation of ecosystem conservation and restoration programs. It is particularly concerned widely in the Qinghai-Tibet Plateau (QTP) due to its unique location conditions and important ecosystem services. To investigate the spatiotemporal patterns and early-warning of GCC in the QTP, we calculated the theoretical livestock carrying capacity, and defined the early-warning level of GCC based on the net primary productivity (NPP) in the QTP and livestock inventory in 236 counties from 2000 to 2015. The results showed as follows:(1) the GCC in the east was higher than that in the west in the QTP. The theoretical livestock carrying capacity of alpine grassland and alpine meadow accounted for 64.99% of the total, and they were the main components of theoretical livestock carrying capacity. (2) The theoretical livestock carrying capacity increased from 86.15 million sheep units (SU) to 91.18 million SU from 2000 to 2010, and then increased to 94.52 million SU from 2010 to 2015. The theoretical livestock carrying capacity increased by 9.71% in the past 15 years. And the theoretical livestock carrying capacity in the northeast increased the most, but the theoretical livestock carrying capacity in the west was basically stable in the QTP. (3) The GCC had always been overgrazed in the QTP. The livestock inventory increased from 144.90 million SU to 163.85 million SU from 2000 to 2010, and then decreased to 158.46 million SU from 2010 to 2015. The livestock inventory increased by 9.36% in the past 15 years. The Balance of Grassland and Livestock Index (BGLI) increased from 67.88% to 79.90% before 2010, and then slightly eased in 2015 (67.91%). The spatial pattern of GCC was consistent with the early-warning pattern. The numbers of green no early-warning zone, blue early-warning zone, yellow early-warning zone, orange early-warning zone and red early-warning zone were 32, 9, 4, 119 and 72, respectively. The green no early-warning zone was located in the west and north, meanwhile, they were always the pastoral and semipastoral areas in the QTP. At present, we should give priority to control the livestock in the red early-warning area since they were overgrazed and their BGLI were still increasing. In the future, it is necessary to improve the GCC and maintain the sustainable development of grassland ecosystem by controlling the livestock inventory, adjusting the development pattern of animal husbandry and enhancing grassland productivity in the QTP.
Keywords:grassland ecosystem  carrying capacity  early-warning  Qinghai-Tibet Plateau
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