Field-Based Estimation of Net Primary Productivity and Its Above- and Belowground Partitioning in Global Grasslands

doi:10.1029/2021JG006472

	Field-Based Estimation of Net Primary Productivity and Its Above- and Belowground Partitioning in Global Grasslands
	Sun, Yuanfeng ; Feng, Yuhao ; Wang, Yupin ; Zhao, Xia 1; Yang, Yuanhe1 ; Tang, Zhiyao ; Wang, Shaopeng ; Su, Haojie ; Zhu, Jiangling ; Chang, Jinfeng 2; Fang, Jingyun
	2021
发表期刊	JOURNAL OF GEOPHYSICAL RESEARCH-BIOGEOSCIENCES
ISSN	2169-8953
卷号	126 期号:11
摘要	Net primary productivity (NPP) in global grasslands is a critical component of terrestrial carbon cycling and the primary source of food for herbivores. However, the size and spatial distribution of NPP across global grasslands remain unclear, especially for belowground NPP (BNPP), which limits our understanding of above- and belowground carbon cycling and the assessments of herbivore food security. Here, we compiled a comprehensive grassland NPP database with 1,467 field measurements to estimate the spatial distributions of aboveground NPP (ANPP), BNPP, total NPP (TNPP), and the fraction of BNPP (f(BNPP)) using the random forest (RF) model. The global mean grassland ANPP, BNPP, TNPP, and f(BNPP) were 433 +/- 31 g m(-2) yr(-1), 593 +/- 47 g m(-2) yr(-1), 979 +/- 78 g m(-2) yr(-1), and 0.54 +/- 0.02, respectively. The total ANPP, BNPP, and TNPP over global grasslands were 6.84 +/- 0.49, 9.36 +/- 0.74, and 15.46 +/- 1.23 Pg C yr(-1), respectively. ANPP, BNPP, and TNPP exhibited decreasing trends from low latitudes toward the poles. The spatial pattern of f(BNPP) was almost opposite to that of ANPP. Climate was a major determinant in shaping the spatial distribution of ANPP and TNPP, while soil and vegetation had significant impacts on that of BNPP and f(BNPP). Our findings suggest that field data-driven estimation of NPP using the RF model could be a useful approach for obtaining spatially explicit NPP of grasslands, particularly BNPP products, and that more attention should be paid on belowground and non-climatic factors to better assess the carbon cycle in global grasslands.
关键词	net primary productivity field data global grasslands random forest model spatial product driving factors
学科领域	Environmental Sciences ; Geosciences, Multidisciplinary
DOI	10.1029/2021JG006472
收录类别	SCI
语种	英语
WOS关键词	ABOVEGROUND PRIMARY PRODUCTIVITY ; NORTH-AMERICAN GRASSLANDS ; AFFECT ROOT PRODUCTION ; RAIN-USE EFFICIENCY ; INNER-MONGOLIA ; ALPINE MEADOW ; GRAZING INTENSITY ; TALLGRASS PRAIRIE ; SOIL CARBON ; LAND-USE
WOS研究方向	Science Citation Index Expanded (SCI-EXPANDED)
WOS记录号	WOS:000722469900013
出版者	AMER GEOPHYSICAL UNION
文献子类	Article
出版地	WASHINGTON
EISSN	2169-8961
资助机构	National Key Research and Development Program of China [2017YFC0503906] ; National Natural Science Foundation of China [31988102] ; Fundamental Research Funds for the Central Universities [2021QNA6005]
作者邮箱	changjf@zju.edu.cn ; jyfang@urban.pku.edu.cn
引用统计	被引频次：18[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ibcas.ac.cn/handle/2S10CLM1/26737
专题	植被与环境变化国家重点实验室
作者单位	1.Peking Univ, Coll Urban & Environm Sci, Key Lab Earth Surface Proc, Inst Ecol,Minist Educ, Beijing, Peoples R China 2.Chinese Acad Sci, Inst Bot, State Key Lab Vegetat & Environm Change, Beijing, Peoples R China 3.Zhejiang Univ, Coll Environm & Resource Sci, Hangzhou, Peoples R China
推荐引用方式 GB/T 7714	Sun, Yuanfeng,Feng, Yuhao,Wang, Yupin,et al. Field-Based Estimation of Net Primary Productivity and Its Above- and Belowground Partitioning in Global Grasslands[J]. JOURNAL OF GEOPHYSICAL RESEARCH-BIOGEOSCIENCES,2021,126(11).
APA	Sun, Yuanfeng.,Feng, Yuhao.,Wang, Yupin.,Zhao, Xia.,Yang, Yuanhe.,...&Fang, Jingyun.(2021).Field-Based Estimation of Net Primary Productivity and Its Above- and Belowground Partitioning in Global Grasslands.JOURNAL OF GEOPHYSICAL RESEARCH-BIOGEOSCIENCES,126(11).
MLA	Sun, Yuanfeng,et al."Field-Based Estimation of Net Primary Productivity and Its Above- and Belowground Partitioning in Global Grasslands".JOURNAL OF GEOPHYSICAL RESEARCH-BIOGEOSCIENCES 126.11(2021).

条目包含的文件
文件名称/大小	文献类型	版本类型	开放类型	使用许可
Field_Based_Estimati（2535KB）	期刊论文	出版稿	开放获取	CC BY-NC-SA	浏览请求全文