Exploration of relationships between phytoplankton biomass and related environmental variables using multivariate statistic analysis in a eutrophic shallow lake: a 5-year study.
Understanding the process of the changing phytoplankton patterns can be particularly useful in water quality improvement and management decisions. However, it is generally not easy to illustrate the interactions between phytoplankton biomass and related environmental variables given their high spatial and temporal heterogeneity. To elucidate relationships between them, in a eutrophic shallow lake, Taihu Lake, relative long-term data set of biotic and abiotic parameters of water quality in the lake were conducted using multivariate statistical analysis within seasonal periodicity. The results indicate that water temperature and total phosphorus (TP) played governing roles in phytoplankton dynamics in most seasons (i.e. temperature in winter, spring and summer; TP in spring, summer and autumn); COD (chemical oxygen demand) and BOD (biological oxygen demand) presented significant positive relationships with phytoplankton biomass in spring, summer and autumn. However, a complex interplay was found between phytoplankton biomass and nitrogen considering significant positive relationships occurring between them in spring and autumn, and conversely negative ones in summer. As the predatory factor, zooplankton presented significant grazing-pressure on phytoplankton biomass during summer in view of negative relationship between them in the season. Significant feedback effects of phytoplankton development were identified in summer and autumn in view that significant relationships were observed between phytoplankton biomass and pH, Trans (transparency of water) and DO. The results indicate that interactions between phytoplankton biomass and related environmental variables are highly sensitive to seasonal periodicity, which improves understanding of different roles of biotic and abiotic variables upon phytoplankton variability, and hence, advances management methods for eutrophic lakes.
Wang
Xiao-long
XL
State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China. wangjie78eo@yahoo.com.cn
Lu
Yong-long
YL
He
Gui-zhen
GZ
Han
Jing-yi
JY
Wang
Tie-yu
TY
D000818:Animals; D018533:Biomass; D002681:China; D002734:Chlorophyll / Q000032:analysis; D000077194:Chlorophyll A; D005068:Eutrophication; D005163:Factor Analysis, Statistical; D005618:Fresh Water; D006863:Hydrogen-Ion Concentration; D015999:Multivariate Analysis; D009584:Nitrogen / Q000032:analysis; D010100:Oxygen / Q000032:analysis; D010710:Phosphates / Q000032:analysis; D010839:Phytoplankton; D000644:Quaternary Ammonium Compounds / Q000032:analysis; D012621:Seasons; D014874:Water Pollutants, Chemical / Q000032:analysis; D015048:Zooplankton
D010710:Phosphates; D000644:Quaternary Ammonium Compounds; D014874:Water Pollutants, Chemical; D002734:Chlorophyll; D009584:Nitrogen; D010100:Oxygen; D000077194:Chlorophyll A