干旱区生态环境知识资源中心(Arid): Modeling the Underlying Drivers of Natural Vegetation Occurrence in West Africa with Binary Logistic Regression Method

Arid

DOI	10.3390/su13094673
	Modeling the Underlying Drivers of Natural Vegetation Occurrence in West Africa with Binary Logistic Regression Method
	Asenso Barnieh, Beatrice; Jia, Li; Menenti, Massimo; Jiang, Min; Zhou, Jie; Zeng, Yelong; Bennour, Ali
通讯作者	Jia, L (corresponding author), Chinese Acad Sci, Aerosp Informat Res Inst, State Key Lab Remote Sensing Sci, Beijing 100101, Peoples R China.
来源期刊	SUSTAINABILITY
EISSN	2071-1050
出版年	2021
卷号	13 期号:9
英文摘要	The occurrence of natural vegetation at a given time is determined by interplay of multiple drivers. The effects of several drivers, e.g., geomorphology, topography, climate variability, accessibility, demographic indicators, and changes in human activities on the occurrence of natural vegetation in the severe drought periods and, prior to the year 2000, have been analyzed in West Africa. A binary logistic regression (BLR) model was developed to better understand whether the variability in these drivers over the past years was statistically significant in explaining the occurrence of natural vegetation in the year 2000. Our results showed that multiple drivers explained the occurrence of natural vegetation in West Africa at p < 0.05. The dominant drivers, however, were site-specific. Overall, human influence indicators were the dominant drivers in explaining the occurrence of natural vegetation in the selected hotspots. Human appropriation of net primary productivity (HANPP), which is an indicator of human socio-economic activities, explained the decreased likelihood of natural vegetation occurrence at all the study sites. However, the impacts of the remaining significant drivers on natural vegetation were either positive (increased the probability of occurrence) or negative (decreased the probability of occurrence), depending on the unique environmental and socio-economic conditions of the areas under consideration. The study highlights the significant role human activities play in altering the normal functioning of the ecosystem by means of a statistical model. The research contributes to a better understanding of the relationships and the interactions between multiple drivers and the response of natural vegetation in West Africa. The results are likely to be useful for planning climate change adaptation and sustainable development programs in West Africa.
英文关键词	West Africa natural vegetation underlying drivers climate human activities binary logistic regression
类型	Article
语种	英语
开放获取类型	Green Published, gold
收录类别	SCI-E ; SSCI
WOS记录号	WOS:000650892000001
WOS关键词	LAND-COVER CHANGE ; GREAT GREEN WALL ; DRIVING FORCES ; DYNAMICS ; SAHEL ; SELECTION ; CLIMATE ; TRENDS ; DESERTIFICATION ; VALIDATION
WOS类目	Green & Sustainable Science & Technology ; Environmental Sciences ; Environmental Studies
WOS研究方向	Science & Technology - Other Topics ; Environmental Sciences & Ecology
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/351847
作者单位	[Asenso Barnieh, Beatrice; Jia, Li; Menenti, Massimo; Jiang, Min; Zeng, Yelong; Bennour, Ali] Chinese Acad Sci, Aerosp Informat Res Inst, State Key Lab Remote Sensing Sci, Beijing 100101, Peoples R China; [Asenso Barnieh, Beatrice; Zeng, Yelong; Bennour, Ali] Univ Chinese Acad Sci, Olymp Campus, Beijing 100101, Peoples R China; [Menenti, Massimo] Delft Univ Technol, Fac Civil Engn & Geosci, Stevin Weg 1, NL-2825 CN Delft, Netherlands; [Zhou, Jie] Cent China Normal Univ, Coll Urban & Environm Sci, Key Lab Geog Proc Anal & Simulat Hubei Prov, Wuhan 430079, Peoples R China
推荐引用方式 GB/T 7714	Asenso Barnieh, Beatrice,Jia, Li,Menenti, Massimo,et al. Modeling the Underlying Drivers of Natural Vegetation Occurrence in West Africa with Binary Logistic Regression Method[J],2021,13(9).
APA	Asenso Barnieh, Beatrice.,Jia, Li.,Menenti, Massimo.,Jiang, Min.,Zhou, Jie.,...&Bennour, Ali.(2021).Modeling the Underlying Drivers of Natural Vegetation Occurrence in West Africa with Binary Logistic Regression Method.SUSTAINABILITY,13(9).
MLA	Asenso Barnieh, Beatrice,et al."Modeling the Underlying Drivers of Natural Vegetation Occurrence in West Africa with Binary Logistic Regression Method".SUSTAINABILITY 13.9(2021).