Empirical modelling of submersed macrophytes in Yangtze lakes

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	Empirical modelling of submersed macrophytes in Yangtze lakes
	Wang, HZ ; Wang, HJ ; Liang, XM ; Ni, LY ; Liu, XQ ; Cui, YD
刊名	ECOLOGICAL MODELLING
	2005-11-10
卷号	188 期号:2-4 页码:483-491
关键词	key-time models submersed macrophytes Yangtze shallow lakes biomass transparency thresholds
ISSN号	0304-3800
通讯作者	Wang, HZ, Chinese Acad Sci, Inst Hydrobiol, State Key Lab Freshwater Ecol & Biotechnol, Wuhan 430072, Peoples R China
中文摘要	Submersed macrophytes in Yangtze lakes have experienced large-scale declines due to the increasing human activities during past decades. To seek the key factor that affects their growth, monthly investigations of submersed macrophytes were conducted in 20 regions of four Yangtze lakes during December, 2001-March, 2003. Analyses based on annual values show that the ratio of Secchi depth to mean depth is the key factor (50% of macrophyte biomass variability among these lakes is statistically explained). Further analyses also demonstrate that the months from March to June are not only the actively growing season for most macrophytes, but the key time the factor acts. Five key-time models yielding higher predictive power (r(2) reaches 0.75,0.76,0.77,0.69 and 0.81) are generated. A comparison between key-time models and traditional synchronic ones indicates that key-time models have higher predictive power. Analyses of transparency thresholds during macrophyte growing season and the limitations of the models are presented. The models and other results may benefit the work concerning submersed macrophyte recovery in Yangtze lakes. (c) 2005 Elsevier B.V. All rights reserved.
英文摘要	Submersed macrophytes in Yangtze lakes have experienced large-scale declines due to the increasing human activities during past decades. To seek the key factor that affects their growth, monthly investigations of submersed macrophytes were conducted in 20 regions of four Yangtze lakes during December, 2001-March, 2003. Analyses based on annual values show that the ratio of Secchi depth to mean depth is the key factor (50% of macrophyte biomass variability among these lakes is statistically explained). Further analyses also demonstrate that the months from March to June are not only the actively growing season for most macrophytes, but the key time the factor acts. Five key-time models yielding higher predictive power (r(2) reaches 0.75,0.76,0.77,0.69 and 0.81) are generated. A comparison between key-time models and traditional synchronic ones indicates that key-time models have higher predictive power. Analyses of transparency thresholds during macrophyte growing season and the limitations of the models are presented. The models and other results may benefit the work concerning submersed macrophyte recovery in Yangtze lakes. (c) 2005 Elsevier B.V. All rights reserved.
学科主题	Ecology
WOS标题词	Science & Technology ; Life Sciences & Biomedicine
类目[WOS]	Ecology
研究领域[WOS]	Environmental Sciences & Ecology
关键词[WOS]	WATER TRANSPARENCY ; SIMULATION-MODEL ; BIOMASS ; COMMUNITIES ; VEGETATION ; DYNAMICS ; PATTERNS ; COVER ; DEPTH ; STATE
收录类别	SCI
语种	英语
WOS记录号	WOS:000233188700019
公开日期	2010-10-13
内容类型	期刊论文
源URL	[http://ir.ihb.ac.cn/handle/152342/9110]
专题	水生生物研究所_中科院水生所知识产出（2009年前）_期刊论文
作者单位	1.Chinese Acad Sci, Inst Hydrobiol, State Key Lab Freshwater Ecol & Biotechnol, Wuhan 430072, Peoples R China 2.Chinese Acad Sci, Grad Sch, Beijing, Peoples R China
推荐引用方式 GB/T 7714	Wang, HZ,Wang, HJ,Liang, XM,et al. Empirical modelling of submersed macrophytes in Yangtze lakes[J]. ECOLOGICAL MODELLING,2005,188(2-4):483-491.
APA	Wang, HZ,Wang, HJ,Liang, XM,Ni, LY,Liu, XQ,&Cui, YD.(2005).Empirical modelling of submersed macrophytes in Yangtze lakes.ECOLOGICAL MODELLING,188(2-4),483-491.
MLA	Wang, HZ,et al."Empirical modelling of submersed macrophytes in Yangtze lakes".ECOLOGICAL MODELLING 188.2-4(2005):483-491.