中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
Spatial sampling design optimization of monitoring network for terrestrial ecosystem in China

文献类型:期刊论文

作者Wu Xiaojing1,2; He Honglin1,2,3; Zhang Li1,2,3; Feng Lili1,2; Ren Xiaoli1,2; Liu Weihua1,2; Zou Changxin4; Lin Naifeng4
刊名SCIENCE OF THE TOTAL ENVIRONMENT
出版日期2022-11-15
卷号847页码:12
ISSN号0048-9697
关键词Forest Grassland and desert Spatial representativeness Spatial sampling method Data-driven approach
DOI10.1016/j.scitotenv.2022.157397
通讯作者He Honglin(hehl@igsnrr.ac.cn) ; Zhang Li(li.zhang@igsnrr.ac.cn)
英文摘要The rapid socioeconomic development leads to the deterioration of ecological environment. Ecosystem assessment has been conducted worldwide, e.g. the Millennium Ecosystem Assessment to assess consequences of ecosystem change for human well-being. To enhance ecosystem assessment in China, this study proposes the design of a monitoring network for the terrestrial ecosystem consisting of core stations and localized points. With focus on ecosystem services of NPP, water conservation, soil retention and sandstorm prevention, core stations of the monitoring network for observ-ing all four services are first selected by assessing and improving spatial representativeness in ecoregions of forest, grassland and desert ecosystems. Then a spatial sampling method is applied to choose localized points for observing each specific service. Eventually expert's knowledge is used to make final decisions of added stations and points by utilizing existing networks and considering factors such as topography, spatial coverage. Combining both aforementioned approaches and experts knowledge, 60 core stations and 176 localized points are finally determined for the monitoring network. For the forest ecosystem, 39 core stations are decided with 31 selected from existing networks and eight newly added core stations improve spatial representativeness by 51.58 %, 68.11 % and 75.55 % in Temper-ate grasslands, Temperate desert and Alpine vegetation in Tibet Plateau respectively. For the grassland and desert eco-system, 21 core stations are chosen with 18 from existing networks and three newly added core stations improve the representativeness by 21.60 % and 44.88 % in Tibet alpine grassland and Grassland in southern mountain areas respectively. Priorities in the implementation phase should be given to instruments installation for monitoring all four services in core stations from existing networks and setting up new stations in regions where representativeness are significantly improved.
WOS关键词REPRESENTATIVENESS ASSESSMENT ; SERVICES ; BIODIVERSITY ; BASIN
资助项目National Natural Science Foundation of China[42030509] ; Ministry of Ecology and Environment Budget Project of Supervision and Management of Ecological Conservation Redline
WOS研究方向Environmental Sciences & Ecology
语种英语
出版者ELSEVIER
WOS记录号WOS:000911741700003
资助机构National Natural Science Foundation of China ; Ministry of Ecology and Environment Budget Project of Supervision and Management of Ecological Conservation Redline
源URL[http://ir.igsnrr.ac.cn/handle/311030/189271]  
专题中国科学院地理科学与资源研究所
通讯作者He Honglin; Zhang Li
作者单位1.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Ecosyst Network Observat & Modeling, Beijing 100101, Peoples R China
2.Chinese Acad Sci, Natl Ecosyst Sci Data Ctr, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China
3.Univ Chinese Acad Sci, Coll Resource & Environm, Beijing 100049, Peoples R China
4.Minist Ecol & Environm, Nanjing Inst Environm Sci, Nanjing 210042, Peoples R China
推荐引用方式
GB/T 7714
Wu Xiaojing,He Honglin,Zhang Li,et al. Spatial sampling design optimization of monitoring network for terrestrial ecosystem in China[J]. SCIENCE OF THE TOTAL ENVIRONMENT,2022,847:12.
APA Wu Xiaojing.,He Honglin.,Zhang Li.,Feng Lili.,Ren Xiaoli.,...&Lin Naifeng.(2022).Spatial sampling design optimization of monitoring network for terrestrial ecosystem in China.SCIENCE OF THE TOTAL ENVIRONMENT,847,12.
MLA Wu Xiaojing,et al."Spatial sampling design optimization of monitoring network for terrestrial ecosystem in China".SCIENCE OF THE TOTAL ENVIRONMENT 847(2022):12.

入库方式: OAI收割

来源:地理科学与资源研究所

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