Contrasting the Performance of Eight Satellite-Based GPP Models in Water-Limited and Temperature-Limited Grassland Ecosystems

doi:10.3390/rs11111333

	Contrasting the Performance of Eight Satellite-Based GPP Models in Water-Limited and Temperature-Limited Grassland Ecosystems
	Zhang, Liangxia 1; Zhou, Decheng 1; Fan, Jiangwen 2; Guo, Qun 2; Chen, Shiping3 ; Wang, Ranghui 1; Li, Yuzhe 2
	2019
发表期刊	REMOTE SENSING
卷号	11 期号:11
摘要	Models constitute the primary approaches for predicting terrestrial ecosystem gross primary production (GPP) at regional and global scales. Many satellite-based GPP models have been developed due to the simple algorithms and the low requirements of model inputs. The performances of these models are well documented at the biome level. However, their performances among vegetation subtypes limited by different environmental stresses within a biome remains largely unexplored. Taking grasslands in northern China as an example, we compared the performance of eight satellite-based GPP models, including three light-use efficiency (LUE) models (vegetation photosynthesis model (VPM), modified VPM (MVPM), and moderate resolution imaging spectroradiometer GPP algorithm (MODIS-GPP)) and five statistical models (temperature and greenness model (TG), greenness and radiation model (GR), vegetation index model (VI), alpine vegetation model (AVM), and photosynthetic capacity model (PCM)), between the water-limited temperate steppe and the temperature-limited alpine meadow based on 16 site-year GPP estimates at four eddy covariance (EC) flux towers. The results showed that all the GPP models performed better in the alpine meadow, particularly in the alpine shrub meadow (R-2 0.84), than in the temperate steppe (R-2 0.68). The performance varied greatly among the models in the temperate steppe, while slight intermodel differences existed in the alpine meadow. Overall, MVPM (of the LUE models) and VI (of the statistical models) were the two best-performing models in the temperate steppe due to their better representation of the effect of water stress on vegetation productivity. Additionally, we found that the relatively worse model performances in the temperate steppe were seriously exaggerated by drought events, which may occur more frequently in the future. This study highlights the varying performances of satellite-based GPP models among vegetation subtypes of a biome in different precipitation years and suggests priorities for improving the water stress variables of these models in future efforts.
关键词	gross primary productivity light use efficiency model satellite remote sensing MODIS EVI eddy covariance grassland ecosystem temperate steppe alpine meadow
学科领域	Environmental Sciences ; Geosciences, Multidisciplinary ; Remote Sensing ; Imaging Science & Photographic Technology
DOI	10.3390/rs11111333
收录类别	SCI
语种	英语
WOS关键词	GROSS PRIMARY PRODUCTION ; LIGHT USE EFFICIENCY ; NET PRIMARY PRODUCTIVITY ; LEYMUS-CHINENSIS STEPPE ; COMPARING GLOBAL-MODELS ; ALPINE SWAMP MEADOW ; TERRESTRIAL ECOSYSTEMS ; NORTHERN CHINA ; INTERANNUAL VARIABILITY ; TIBETAN PLATEAU
WOS研究方向	Environmental Sciences & Ecology ; Geology ; Remote Sensing ; Imaging Science & Photographic Technology
WOS记录号	WOS:000472648000076
出版者	MDPI
文献子类	Article
出版地	BASEL
EISSN	2072-4292
资助机构	National Natural Science Foundation of ChinaNational Natural Science Foundation of China (NSFC) [31870413] ; National Key R&D Program of China [2017YFA0604804] ; Chinese Academy of Sciences Technology Service Plan [KFJ_STS-ZDTP-013-02] ; Qinglan Project of Jiangsu Province of China
作者邮箱	zhanglx@nuist.edu.cn ; zhoudc@nuist.edu.cn ; fanjw@igsnrr.ac.cn ; guoq@igsnrr.ac.cn ; spchen@ibcas.ac.cn ; rhwang@nuist.edu.cn ; liyuzhe@igsnrr.ac.cn
作品OA属性	Green Submitted, gold
引用统计	被引频次：26[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/2S10CLM1/19854
专题	植被与环境变化国家重点实验室
作者单位	1.Nanjing Univ Informat Sci & Technol, Jiangsu Key Lab Agr Meteorol, Nanjing 210044, Jiangsu, Peoples R China 2.Nanjing Univ Informat Sci & Technol, Collaborat Innovat Ctr Forecast & Evaluat Meteoro, Nanjing 210044, Jiangsu, Peoples R China 3.Chinese Acad Sci, Key Lab Land Surface Pattern & Simulat, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China 4.Chinese Acad Sci, State Key Lab Vegetat & Environm Change, Inst Bot, 20 Nanxincun, Beijing 100093, Peoples R China
推荐引用方式 GB/T 7714	Zhang, Liangxia,Zhou, Decheng,Fan, Jiangwen,et al. Contrasting the Performance of Eight Satellite-Based GPP Models in Water-Limited and Temperature-Limited Grassland Ecosystems[J]. REMOTE SENSING,2019,11(11).
APA	Zhang, Liangxia.,Zhou, Decheng.,Fan, Jiangwen.,Guo, Qun.,Chen, Shiping.,...&Li, Yuzhe.(2019).Contrasting the Performance of Eight Satellite-Based GPP Models in Water-Limited and Temperature-Limited Grassland Ecosystems.REMOTE SENSING,11(11).
MLA	Zhang, Liangxia,et al."Contrasting the Performance of Eight Satellite-Based GPP Models in Water-Limited and Temperature-Limited Grassland Ecosystems".REMOTE SENSING 11.11(2019).

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
Zhang-2019-Contrasti（5477KB）	期刊论文	出版稿	开放获取	CC BY-NC-SA	浏览请求全文