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Can more carbon be captured by grasslands? A case study of Inner Mongolia, China
Sha, Zongyao; Bai, Yongfei1; Lan, Hai2; Liu, Xuefeng3; Li, Ruren4; Xie, Yichun5
AbstractGrasslands cover a large part of the Earth's surface and play an important role in the global carbon cycle. Previous studies have indicated that nearly half of the grassland vegetation cover has experienced degradation on a global scale; if this degradation is reversed, grasslands can act as potential carbon sinks. However, the question of how much more carbon (carbon gap) could be sequestrated by grassland vegetation by regulating human activities remains unanswered. Here, we present an innovative approach to assess the achievable carbon gap through focal analysis of long-term Moderate Resolution Imaging Spectroradiometer (MODIS) Net Primary Production (NPP) dataset or observed NPP (ONPP). In focal analysis, region segmentation was done to produce spatially homogeneous patches of the same types of soil, topography, and vegetation, referred to as S-T-V units, to minimize the variation in environmental conditions and their impacts on the NPP. Then, the ONPP within each S-T-V unit was rectified by offsetting the variations in potential NPP determined by the climate-oriented Miami NPP model. Hence, spatial variations in the climate-rectified ONPP (ONPPCR) in an S-T-V unit were solely determined by different human activities across locations. In a case study of the Inner Mongolia grassland of China, three focal statistics, namely mean (Mean), 95% percentile threshold (95%PCT), and maximum (Max) within each S-T-V unit were computed for ONPPCR for each year from 2000 to 2014 to assess the annual carbon uptake that was achievable by updating grassland management practices. The carbon gaps were assessed to be 11.8, 58.9, and 74.6 gC/m(2) per year based on Mean, 95%PCT, and Max, respectively, compared to 65.0 gC/m(2) per year based on the traditional pixel-based approach. We conclude that the carbon gap patterns identified from focal analysis are practically achievable and are more valuable in formulating policy-related decisions for grassland management. Implementing sustainable management practices that are currently being practiced at locations with high ONPPCR in neighboring degraded areas is expected to increase the carbon sequestration by grassland vegetation by one-third. (C) 2020 Elsevier B.V. All rights reserved.
KeywordFocal analysis Grassland Carbon sink Carbon source Geoinformatics
Subject AreaEnvironmental Sciences
Indexed BySCI
WOS Research AreaEnvironmental Sciences & Ecology
WOS IDWOS:000535897200006
Publication PlaceAMSTERDAM
Funding OrganizationNational Natural Science Foundation of ChinaNational Natural Science Foundation of China (NSFC) [41871296, 51774204] ; Guangdong Innovative and Entrepreneurial Research Team Program [2016ZT06D336] ; GDAS' Special Project of Science and Technology Development [2017GDASCX-0101]
Corresponding Author Emailzongyaosha@whu.edu.cn ; yfbai@ibcas.ac.cn ; hlan@terpmail.umd.edu ; lxf02@shu.edu.cn ; yxie@emich.edu
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Cited Times:9[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Affiliation1.Wuhan Univ, Sch Remote Sensing & Informat Engn, Wuhan 430079, Peoples R China
2.Chinese Acad Sci, Inst Bot, Beijing 100093, Peoples R China
3.Univ Maryland, Dept Geog Sci, College Pk, MD 20742 USA
4.Shanghai Univ, Sch Commun & Informat Engn, Shanghai 200072, Peoples R China
5.Shenyang Jianzhu Univ, Sch Transportat Engn, Shenyang 110044, Liaoning, Peoples R China
6.Eastern Michigan Univ, Dept Geog & Geol, Ypsilanti, MI 48197 USA
Recommended Citation
GB/T 7714
Sha, Zongyao,Bai, Yongfei,Lan, Hai,et al. Can more carbon be captured by grasslands? A case study of Inner Mongolia, China[J]. SCIENCE OF THE TOTAL ENVIRONMENT,2020,723.
APA Sha, Zongyao,Bai, Yongfei,Lan, Hai,Liu, Xuefeng,Li, Ruren,&Xie, Yichun.(2020).Can more carbon be captured by grasslands? A case study of Inner Mongolia, China.SCIENCE OF THE TOTAL ENVIRONMENT,723.
MLA Sha, Zongyao,et al."Can more carbon be captured by grasslands? A case study of Inner Mongolia, China".SCIENCE OF THE TOTAL ENVIRONMENT 723(2020).
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