Exploring the influence of lake water chemistry on chlorophyll a: A   multivariate statistical model analysis

doi:10.1016/j.ecolmodel.2009.03.010

CORC > 北京大学 > 环境科学与工程学院

	Exploring the influence of lake water chemistry on chlorophyll a: A multivariate statistical model analysis
	Liu, Yong ; Guo, Huaicheng ; Yang, Pingjian
刊名	ecological modelling
	2010
关键词	Absolute principal component score (APCS) Multivariate linear regression (MLR) Structural equation modeling (SEM) Chlorophyll a Lake Qilu SOURCE APPORTIONMENT MANAGEMENT POLLUTION PATTERNS RIVER DYNAMICS NUTRIENT CHINA USA
DOI	10.1016/j.ecolmodel.2009.03.010
英文摘要	A multivariate statistical approach integrating the absolute principal components score (APCS) and multivariate linear regression (APCS-MLR), along with structural equation modeling (SEM), was used to model the influence of water chemistry variables on chlorophyll a (Chl a) in Lake Qilu, a severely polluted lake in southwestern China. Water quality was surveyed monthly from 2000 to 2005. APCS-MLR was used to identify key water chemistry variables, mine data for SEM, and predict Chl a. Seven principal components (PCs) were determined as eigenvalues > 1, which explained 68.67% of the original variance. Four PCs were selected to predict Chl a using APCS-MLR. The results showed a good fit between the observed data and modeled values. with R(2) = 0.80. For SEM, Chl a and eight variables were used: NH(4)-N (ammonia-nitrogen), total phosphorus (TP), Secchi disc depth (SD), cyanide (CN), arsenic (As), cadmium (Cd), fluoride (F), and temperature (T). A conceptual model was established to describe the relationships among the water chemistry variables and Chl a. Four latent variables were also introduced: physical factors, nutrients, toxic substances, and phytoplankton. In general, the SEM demonstrated good agreement between the sample covariance matrix of observed variables and the model-implied covariance matrix. Among the water chemistry factors, T and TP had the greatest positive influence on Chl a, whereas SD had the largest negative influence. These results will help researchers and decision-makers to better understand the influence of water chemistry on phytoplankton and to manage eutrophication adaptively in Lake Qilu. (C) 2009 Elsevier B.V. All rights reserved.; http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000274844500013&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=8e1609b174ce4e31116a60747a720701 ; Ecology; SCI(E); EI; 17; ARTICLE; 4; 681-688; 221
语种	英语
内容类型	期刊论文
源URL	[http://ir.pku.edu.cn/handle/20.500.11897/158499]
专题	环境科学与工程学院
推荐引用方式 GB/T 7714	Liu, Yong,Guo, Huaicheng,Yang, Pingjian. Exploring the influence of lake water chemistry on chlorophyll a: A multivariate statistical model analysis[J]. ecological modelling,2010.
APA	Liu, Yong,Guo, Huaicheng,&Yang, Pingjian.(2010).Exploring the influence of lake water chemistry on chlorophyll a: A multivariate statistical model analysis.ecological modelling.
MLA	Liu, Yong,et al."Exploring the influence of lake water chemistry on chlorophyll a: A multivariate statistical model analysis".ecological modelling (2010).