improvingremotesensingbasednetprimaryproductionestimationinthegrazedlandwithdefoliationformulationmodel

	improvingremotesensingbasednetprimaryproductionestimationinthegrazedlandwithdefoliationformulationmodel
	Ye Hui 2; Huang Xiaotao 3; Luo Geping 2; Wang Junbang 4; Zhang Miao 1; Wang Xinxin 5
刊名	journalofmountainscience
	2019
卷号	16 期号:2 页码:323
ISSN号	1672-6316
英文摘要	Remote sensing (RS) technologies provide robust techniques for quantifying net primary productivity (NPP) which is a key component of ecosystem production management. Applying RS, the confounding effects of carbon consumed by livestock grazing were neglected by previous studies, which created uncertainties and underestimation of NPP for the grazed lands. The grasslands in Xinjiang were selected as a case study to improve the RS based NPP estimation. A defoliation formulation model (DFM) based on RS is developed to evaluate the extent of underestimated NPP between 1982 and 2011. The estimates were then used to examine the spatiotemporal patterns of the calculated NPP. Results show that average annual underestimated NPP was 55.74 gC.m(-2)yr(-1) over the time period understudied, accounting for 29.06% of the total NPP for the Xinjiang grasslands. The spatial distribution of underestimated NPP is related to both grazing intensity and time. Data for the Xinjiang grasslands show that the average annual NPP was 179.41 gC.m(-2)yr(-1), the annual NPP with an increasing trend was observed at a rate of 1.04 gC.m(-2)yr(-1) between 1982 and 2011. The spatial distribution of NPP reveals distinct variations from high to low encompassing the geolocations of the Tianshan Mountains, northern and southern Xinjiang Province and corresponding with mid-mountain meadow, typical grassland, desert grassland, alpine meadow, and saline meadow grassland types. This study contributes to improving RS-based NPP estimations for grazed land and provides a more accurate data to support the scientific management of fragile grassland ecosystems in Xinjiang.
资助项目	[international Partnership Program of the Chinese Academy of Science] ; [National Natural Science Foundation of China] ; [Network Plan of the Science and Technology Service, Chinese Academy of Sciences (STS Plan)] ; [Qinghai innovation platform construction project]
语种	英语
内容类型	期刊论文
源URL	[http://ir.igsnrr.ac.cn/handle/311030/76995]
专题	中国科学院地理科学与资源研究所
作者单位	1.陕西师范大学 2.中国科学院新疆生态与地理研究所 3.中国科学院西北高原生物研究所 4.中国科学院地理科学与资源研究所 5.复旦大学
推荐引用方式 GB/T 7714	Ye Hui,Huang Xiaotao,Luo Geping,et al. improvingremotesensingbasednetprimaryproductionestimationinthegrazedlandwithdefoliationformulationmodel[J]. journalofmountainscience,2019,16(2):323.
APA	Ye Hui,Huang Xiaotao,Luo Geping,Wang Junbang,Zhang Miao,&Wang Xinxin.(2019).improvingremotesensingbasednetprimaryproductionestimationinthegrazedlandwithdefoliationformulationmodel.journalofmountainscience,16(2),323.
MLA	Ye Hui,et al."improvingremotesensingbasednetprimaryproductionestimationinthegrazedlandwithdefoliationformulationmodel".journalofmountainscience 16.2(2019):323.