Exploring Spatiotemporal Pattern of Grassland Cover in Western China from 1661 to 1996
文献类型:期刊论文
作者 | Yang, Fan1,2; He, Fanneng2; Li, Shicheng3; Li, Meijiao1,2 |
刊名 | INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH
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出版日期 | 2019-09-01 |
卷号 | 16期号:17页码:17 |
关键词 | grasslands reconstruction land use and land cover land reclamation immigration western China |
DOI | 10.3390/ijerph16173160 |
通讯作者 | He, Fanneng(hefn@igsnrr.ac.cn) |
英文摘要 | Historical grassland cover change is vital for global and regional environmental change modeling; however, in China, estimates of this are rare, and therefore, we propose a method to reconstruct grassland cover over the past 300 years. By synthesizing remote sensing-derived Chinese land use and land cover change (LULCC) data (1980-2015) and potential natural vegetation data simulated by the relationship between vegetation and environment, we first determined the potential extent of natural grassland vegetation (PENG) in the absence of human activities. Then we reconstructed grassland cover across western China between 1661 and 1996 at 10 km resolution by overlaying the Chinese historical cropland dataset (CHCD) over the PENG. As this land cover type has been significantly influenced by anthropogenic factors, the data show that the proportion of grassland in western China continuously decreased from 304.84 x 10(6) ha in 1661 to 277.69 x 10(6) ha in 1996. This reduction can be divided into four phases, comprising a rapid decrease between 1661 and 1724, a slow decrease between 1724 and 1873, a sharp decrease between 1873 and 1980, and a gradual increase since 1980. These reductions correspond to annual loss rates of 7.32 x 10(4) ha, 2.90 x 10(4) ha, 17.04 x 10(4) ha, and -2.37 x 10(4) ha, respectively. The data reconstructed here show that the decrease in grassland area between 1661 and 1724 was mainly limited to the Gan-Ning region (Gansu and Ningxia) and was driven by the early agricultural development policies of the Qing Dynasty. Grassland was extensively cultivated in northeastern China (Heilongjiang, Jilin, and Liaoning) and in the Xinjiang region between 1724 and 1980, a process which resulted from an exponential increase in immigrants to these provinces. The reconstruction results enable provide crucial data that can be used for modeling long-term climate change and carbon emissions. |
WOS关键词 | LAND-USE CHANGE ; PAST 300 YEARS ; NORTHEAST CHINA ; SPATIAL-PATTERN ; CARBON ; VEGETATION ; HOLOCENE ; RECONSTRUCTION ; DATASETS ; MAPS |
资助项目 | National Key Research and Development Program of China[2017YFA0603304] ; National Natural Science Foundation of China[41671149] ; Chinese Academy of Sciences Strategic Priority Research Program[XDA19040101] |
WOS研究方向 | Environmental Sciences & Ecology ; Public, Environmental & Occupational Health |
语种 | 英语 |
WOS记录号 | WOS:000487037500155 |
出版者 | MDPI |
资助机构 | National Key Research and Development Program of China ; National Natural Science Foundation of China ; Chinese Academy of Sciences Strategic Priority Research Program |
源URL | [http://ir.igsnrr.ac.cn/handle/311030/69511] ![]() |
专题 | 中国科学院地理科学与资源研究所 |
通讯作者 | He, Fanneng |
作者单位 | 1.Univ Chinese Acad Sci, Beijing 100049, Peoples R China 2.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Land Surface Pattern & Simulat, Beijing 100101, Peoples R China 3.China Univ Geosci, Sch Publ Adm, Wuhan 430074, Hubei, Peoples R China |
推荐引用方式 GB/T 7714 | Yang, Fan,He, Fanneng,Li, Shicheng,et al. Exploring Spatiotemporal Pattern of Grassland Cover in Western China from 1661 to 1996[J]. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH,2019,16(17):17. |
APA | Yang, Fan,He, Fanneng,Li, Shicheng,&Li, Meijiao.(2019).Exploring Spatiotemporal Pattern of Grassland Cover in Western China from 1661 to 1996.INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH,16(17),17. |
MLA | Yang, Fan,et al."Exploring Spatiotemporal Pattern of Grassland Cover in Western China from 1661 to 1996".INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 16.17(2019):17. |
入库方式: OAI收割
来源:地理科学与资源研究所
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