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最后间冰期至未来2070s中国潜在自然植被时空分布格局及其对气候变化的响应
引用本文:任正超,朱华忠,史华,柳小妮.最后间冰期至未来2070s中国潜在自然植被时空分布格局及其对气候变化的响应[J].自然资源学报,2020,35(6):1484-1498.
作者姓名:任正超  朱华忠  史华  柳小妮
作者单位:1. 甘肃农业大学财经学院,兰州 730070;2. 甘肃省生态建设与环境保护研究中心,兰州 730070;3. 中国科学院地理科学与资源研究所,北京 100101;4. 美国地质调查局地球资源观测与科学研究中心,苏福尔斯 57198;5. 甘肃农业大学草业学院,兰州 730070
基金项目:国家自然科学基金项目(30960264,31160475); 甘肃农业大学校派青年出国留学访问学者项目
摘    要:潜在自然植被(PNV)对生态环境的修复与重建、自然保护区的规划与建设和农牧业的生产与发展均有着重要的指导作用。研究基于综合顺序分类系统(CSCS),利用最后间冰期至未来2070s六个时期的温度和降水量数据,模拟中国PNV的时空分布格局及其对气候变化的响应。研究结果表明:(1)CSCS将六个时期中国PNV分别划分为39、37、38、40、40和40类以及10个类组。(2)寒冷干旱型类组主要分布在西北,温暖湿润型和炎热潮湿型则分布在中东部和南方。除冻原和高山草地、冷荒漠、半荒漠和温带森林草地4个类组呈现下降趋势外,其余均为上升趋势。(3)温带森林草地转变为亚热带森林草地的面积最大,占总变化面积的35.4%。(4)CSCS既未包含人类活动影响因素,又能模拟长时间序列的PNV演替。(5)最后间冰期至未来2070s,森林类组向纬度和海拔高度更高的北方及青藏高原移动。研究结果进一步明确了PNV概念的界限,揭示了气候变化对PNV演替的作用机理。

关 键 词:PNV  CSCS  时空格局  植被分类体系  气候变化  
收稿时间:2019-04-18
修稿时间:2019-06-10

Spatio-temporal distribution pattern of potential natural vegetation and its response to climate change from Last Interglacial to future 2070s in China
REN Zheng-chao,ZHU Hua-zhong,SHI Hua,LIU Xiao-ni.Spatio-temporal distribution pattern of potential natural vegetation and its response to climate change from Last Interglacial to future 2070s in China[J].Journal of Natural Resources,2020,35(6):1484-1498.
Authors:REN Zheng-chao  ZHU Hua-zhong  SHI Hua  LIU Xiao-ni
Abstract:Regarded as the final evolutionary status with its standing environment, potential natural vegetation plays a key role in ecological reconstruction, design of natural reserve, and development of agriculture and livestock farming. Based on the Comprehensive and Sequential Classification System model, in combination of climatic datasets containing temperature and precipitation in periods of Last Interglacial, Last Glacial Maximum, Mid Holocene, Present-Day, and project climate in the 2050s and 2070s, the spatio-temporal distribution pattern of potential natural vegetation in China and its response to climate change during the six periods were analyzed. The results showed that: (1) 39, 37, 38, 40, 40, 40 and 40 classes, and 10 super-classes were classified for potential natural vegetation by CSCS model from Last Inter-Glacial to future 2070s in China. (2) The frigid-arid super-classes were mainly distributed in northwest China, but warm-humid super-classes and tropical-perhumid super-classes appeared in the central-east China and southern China, respectively. The area was following a descending order: temperate zonal forest steppe, tundra and alpine steppe, sub-tropical zonal forest steppe, frigid desert, semi desert, steppe, temperate zonal humid grassland, tropical zonal forest steppe, warm desert and savanna during the six periods. Tundra and alpine steppe, frigid desert, semi desert, and temperate zonal forest steppe presented a decreasing trend, but the other super-classes showed an increasing trend. (3) The conversion of temperate zonal forest steppe to sub-tropical zonal forest steppe had the biggest area, accounting for 35.4% of total changed area, which meant that the climate shifted sharply and the response of terrestrial vegetation to climate change was sensitive during the period from Last Glacial Maximum to Mid Holocene. (4) CSCS, with more detailed features for classifying grassland vegetation than other models such as RT, excluding the human activity from its classification system, could simulate the long-time series succession of potential natural vegetation. (5) With the global warming, forest shifted to northern China and Tibet with much higher latitude and elevation. The geometrical center, shifting direction and distance of super-classes revealed more offset with more serious impact of climate change. The results further clarified the concept of potential natural vegetation, explored the impact mechanism of climatic change on succession of potential natural vegetation, and enriched the research contents of potential natural vegetation, which could be taken as a reference for construction of regional natural reserve, ecological reconstruction and promotion for agriculture and animal husbandry.
Keywords:CSCS  climate change  vegetation classification system  potential natural vegetation  spatio-temporal pattern  
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