Exploration of relationships between phytoplankton biomass and relatedenvironmental variables using multivariate statistic analysisin a eutrophic shallow lake: A 5-year study
WANG Xiao-long , LU Yong-long , HE Gui-zhen , HAN Jing-yi , WANG Tie-yu
DOI:
Received October 11, 2006,Revised January 29, 2007, Accepted , Available online
Volume 19,2007,Pages 920-927
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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 e ects 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 di erent roles of biotic and abiotic variables upon phytoplankton
variability, and hence, advances management methods for eutrophic lakes.
