Lu Tan

Phytoplankton development and ecological status during a cyanobacterial bloom in a tributary bay of the Three Gorges Reservoir, China.

Reservoirs can provide suitable conditions for cyanobacterial bloom development, which may impact on water quality and biological communities. Weekly surveys in a cyanobacterial bloom process were carried out in the mainstream and Xiangxi Bay of the Three Gorges Reservoir (China), from June 6 to July 18 in 2008. By application of the phytoplankton functional group approach, the spatiotemporal pattern, impact factors, and the ecological status based on Q index (assemblage index) were analyzed. The depth of euphotic layer was apparently the key factor driving the phytoplankton functional group variations. Longitudinal patterns of phytoplankton distribution were detected during this bloom: in the beginning phase, groups D (mainly Stephanodiscus hantzschii) and B (Cyclotella stelligera) dominated in the mainstream of the Three Gorges Reservoir and the mouth area of Xiangxi Bay, group Y (Cryptomonas species) dominated in the upper area, while groups J (mainly Pediastrum duplex), F (mainly Sphaerocystis schroeteri) and G (Pandorina morum and Eudorina elegans) were important in other areas; in the mid phase, group M became absolutely dominant in the whole region; and in the ending phase, besides groups M and Y, groups X2 (Chroomonas acuta, Pyramimonas nanella, etc.) and Lo (Ceratium hirundinella) became more important in the lower and upper area respectively. Generally the ecological status was bad, temporally varied with the bloom process. No spatial difference of ecological status was found in the mainstream, while longitudinal patterns in Xiangxi Bay were detected for different phases: firstly a few sites had relatively better status than the others, then nearly all the sites were in the bad condition, and at last the status in the downstream was better than that in the upstream. The longitudinal patterns of ecological status were related to phytoplankton distribution, disturbed by jacking from the downstream and flood from the upstream of Xiangxi Bay.

Real-time observation, early warning and forecasting phytoplankton blooms by integrating in situ automated online sondes and hybrid evolutionary algorithms

Phytoplankton bloom is one of the most serious threats to water resource, and remains a global challenge in environmental management Real-time monitoring and forecasting the dynamics of phytoplankton and early warning the risks are critical steps in an effective environmental management. Automated online sondes have been widely used for in situ real-time monitoring of water quality due to their high reliability and low cost. However, the knowledge of using real-time data from those sondes to forecast phytoplankton blooms has been seldom addressed. Here we present an integrated system for real-time observation, early warning and forecasting of phytoplankton blooms by integrating automated online sondes and the ecological model. Specifically, based on the high-frequency data from automated online sondes in Xiangxi Bay of Three Gorges Reservoir, we successfully developed 1-4 days ahead forecasting models for chlorophyll a (chl a) concentration with hybrid evolutionary algorithms (HEM). With the predicted concentration of chl a, we achieved a high precision in 1-7 days ahead early warning of good (chl a = 25 mu g/L). Our study shows that the optimized HEM achieved an acceptable performance in real-time short-term forecasting and early warning of phytoplankton blooms with the data from the automated in situ sondes. This system provides an efficient way in real-time monitoring and early warning of phytoplankton blooms, and may have a wide application in eutrophication monitoring and management

Ecosystem metabolism and the driving factors in Xiangxi Bay of Three Gorges Reservoir, China

Ecosystem metabolism determines organic matter cycling and trophic structure in aquatic ecosystems. Ecosystem metabolism is well studied in ponds, lakes, estuaries, streams, and rivers, but it is seldom investigated in large reservoirs. Here, we report daily ecosystem metabolism (26 January–10 May 2009), measured with the free-water technique, in the surface layer of Xiangxi Bay, Three Gorges Reservoir. Further, we investigated the potential factors influencing variation in metabolic processes by systematically testing 4 hypotheses based on phytoplankton biomass, water temperature, nutrient concentration, and light availability. Daily dynamics of respiration (R), gross primary production (GPP), and net ecosystem production (NEP) had high variability during the spring phytoplankton blooms in Xiangxi Bay. GPP ranged from 0.57 to 9.79 mg O2 L−1 d−1; R ranged from 0.27 to 7.80 mg O2 L−1 d−1; and NEP ranged from −4.24 to 1.96 mg O2 L−1 d−1 (mean = −0.26 mg O2 L−1 d−1). Further analysis showed that: 1) GPP is determined by phytoplankton biomass and maximum daily photosynthetically active radiation (PAR); 2) R is determined by phytoplankton biomass and water temperature; and 3) NEP has a significant positive correlation with soluble reactive P. However, the potential mechanism explaining the relationship between NEP and P requires further research. Our study reveals that the metabolic processes in Xiangxi Bay are determined mainly by phytoplankton biomass, water temperature, and maximum daily PAR. This work improves our understanding of ecosystem metabolism in Three Gorges Reservoir.