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Spatiotemporal Variation in Gross Primary Productivity and Their Responses to Climate in the Great Lakes Region of Sub-Saharan Africa during 2001-2020

文献类型：期刊论文

作者Kayiranga, Alphonse2,3; Chen, Baozhang2,3,4,5,6; Wang, Fei2,3; Nthangeni, Winny7; Dilawar, Adil2,3; Hategekimana, Yves1,3,8; Zhang, Huifang2,3; Guo, Lifeng5
刊名SUSTAINABILITY
出版日期2022-03-01
卷号14期号:5页码:23
关键词gross primary productivity light-use efficiency Carnegie-Ames-Stanford Approaches (CASA) model vegetation photosynthesis model (VPM) Sub-Saharan African tropics Great Lakes
DOI10.3390/su14052610
通讯作者Chen, Baozhang(baozhang.chen@igsnrr.ac.cm)
英文摘要The impacts of climate on spatiotemporal variations of eco-physiological and bio-physical factors have been widely explored in previous research, especially in dry areas. However, the understanding of gross primary productivity (GPP) variations and its interactions with climate in humid and semi-humid areas remains unclear. Based on hyperspectral satellite remotely sensed vegetation phenology processes and related indices and the re-analysed climate datasets, we investigated the seasonal and inter-annual variability of GPP by using different light-use efficiency (LUE) models including the Carnegie-Ames-Stanford Approaches (CASA) model, vegetation photosynthesis models (VPMChl and VPMCanopy) and Moderate Resolution Imaging Spectroradiometer (MODIS) GPP products (MOD17A2H) during 2001-2020 over the Great Lakes region of Sub-Saharan Africa (GLR-SSA). The models' validation against the in situ GPP-based upscaled observations (GPP-EC) indicated that these three models can explain 82%, 79% and 80% of GPP variations with root mean square error (RMSE) values of 5.7, 8.82 and 10.12 g C center dot m(-2)center dot yr(-1), respectively. The spatiotemporal variations of GPP showed that the GLR-SSA experienced: (i) high GPP values during December-May; (ii) high annual GPP increase during 2002-2003, 2011-2013 and 2015-2016 and annual decreasing with a marked alternation in other years; (iii) evergreen broadleaf forests having the highest GPP values while grasslands and croplands showing lower GPP values. The spatial correlation between GPP and climate factors indicated 60% relative correlation between precipitation and GPP and 65% correction between surface air temperature and GPP. The results also showed high GPP values under wet conditions (in rainy seasons and humid areas) that significantly fell by the rise of dry conditions (in long dry season and arid areas). Therefore, these results showed that climate factors have potential impact on GPP variability in this region. However, these findings may provide a better understanding of climate implications on GPP variability in the GLR-SSA and other tropical climate zones.
WOS关键词CARBON USE EFFICIENCY ; WATER-USE EFFICIENCY ; LIGHT-USE EFFICIENCY ; FOREST PHOTOSYNTHESIS ; GLOBAL PATTERNS ; MODIS ; ECOSYSTEM ; MODELS ; EXCHANGE ; VARIABILITY
资助项目National Natural Science Foundation of China[42141018] ; National Natural Science Foundation of China[41977404] ; National Key R&D Program of China[2018YFA0606001] ; National Key R&D Program of China[2017YFA0604301] ; National Key R&D Program of China[2017YFA0604302] ; Strategic Priority Research Program of Chinese Academy of Sciences[XDA 20030302]
WOS研究方向Science & Technology - Other Topics ; Environmental Sciences & Ecology
语种英语
WOS记录号WOS:000775768800001
出版者MDPI
资助机构National Natural Science Foundation of China ; National Key R&D Program of China ; Strategic Priority Research Program of Chinese Academy of Sciences
源URL[http://ir.igsnrr.ac.cn/handle/311030/173304]  
专题中国科学院地理科学与资源研究所
通讯作者Chen, Baozhang
作者单位1.Rwanda Space Agcy, Telecom House Kacyiru,POB 6205, Kigali, Rwanda
2.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resource & Environm Informat Syst, Beijing 100101, Peoples R China
3.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
4.Nanjing Univ Informat Sci & Technol, Sch Remote Sensing & Geomat Engn, Nanjing 210044, Peoples R China
5.Chinese Acad Meteorol Sci, Inst Atmospher Composit & Environm Meteorol, Beijing 100081, Peoples R China
6.Jiangsu Ctr Collaborat Innovat Geog Informat Reso, Nanjing 210023, Peoples R China
7.Univ Johannesburg, Fac Sustainable Urban Planning & Dev, POB 17011, ZA-2028 Johannesburg, South Africa
8.Chinese Acad Sci, Aerosp Informat Res Inst, Beijing 100101, Peoples R China
推荐引用方式
GB/T 7714		 Kayiranga, Alphonse,Chen, Baozhang,Wang, Fei,et al. Spatiotemporal Variation in Gross Primary Productivity and Their Responses to Climate in the Great Lakes Region of Sub-Saharan Africa during 2001-2020[J]. SUSTAINABILITY,2022,14(5):23.
APA Kayiranga, Alphonse.,Chen, Baozhang.,Wang, Fei.,Nthangeni, Winny.,Dilawar, Adil.,...&Guo, Lifeng.(2022).Spatiotemporal Variation in Gross Primary Productivity and Their Responses to Climate in the Great Lakes Region of Sub-Saharan Africa during 2001-2020.SUSTAINABILITY,14(5),23.
MLA Kayiranga, Alphonse,et al."Spatiotemporal Variation in Gross Primary Productivity and Their Responses to Climate in the Great Lakes Region of Sub-Saharan Africa during 2001-2020".SUSTAINABILITY 14.5(2022):23.

入库方式： OAI收割

来源：地理科学与资源研究所

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