The ecological basis for simulating phytoplankton responses to environmental change (PROTECH)

The theory and mathematical development of a model, called PROTECH, are presented. The model simulates the dynamic responses of up to eight species of phytoplankton to environmental variability in lakes and reservoirs. PROTECH models were developed originally to fulfil a commercial, decision-support role in the management of industrial water quality, where plankton growth is an issue. The progressive refinements to the model nevertheless have a robust ecological basis. This makes PROTECH a promising tool for researching plankton community ecology. The model calculates exponents describing growth and attrition, from a base of the maximum growth rates of algal species in culture. Subject to defined thresholds, growth integrates variability in the fluxes of light and nutrients. The paper develops this philosophy and its embodiment into the structure of the model. Examples of its authenticated, validated and sensitivity-tested outputs are presented.     

A vertical-compressed three-dimensional ecological model in Lake Taihu, China

A three-dimensional ecological model on the basis of the analyses of environmental characteristics is set up for Lake Taihu, one of the largest shallow lakes in China. The hydrodynamic processes, nutrient cycling, chemical processes and biological processes are integrated in the model. Model state variables include: water current, surface displacement, nutrients of nitrogen and phosphorus, as well as their different forms such as ammonia nitrogen, nitrate nitrogen, phosphate phosphorus, etc., biomasses of macroplankton, phytoplankton, zooplankton and fish, and also the nutrient levels of macroplankton and phytoplankton. A nutrient budget and sediment transformation are also coupled in the model. The data from January 17, 1997 to January 18, 1998 are use to calibrate the model. The model results have shown good agreement with the observations. It implies that the model could be used for the lake environmental management and research for examining the processes and determining the water quality. The reasons of deviations between the modelled results and the observed values are also discussed. There are six factors that explain the deviations of the modelled results from the observed values and they can be grouped into two sets. One set of problems is associated with the standard deviation introduced by sampling and analyses. The second set of problems can be solved by introduction of processes lacking in the present model (resuspension, phytoplankton transportation mode under the wind with low speed, shifts in species composition and varied size of phytoplankton and zooplankton). The latter two processes should be included in the model at a later stage by integration of a structurally dynamic approach into the three-dimensional model.     

Alkaline phosphatase activity in the phosphorus-limited southern Chinese coastal waters

Three fractions of alkaline phosphatase activity(APA), including phytoplankton APA(phyto-APA), bacterial APA(bact-APA), and free-APA, were examined in the sea surface microlayer(SML) and the subsurface water(SSW) from Daya Bay, Guishan Island, and Guanghai Bay of southern China. Relationships between APA and environmental parameters were analyzed. The growth of phytoplankton was significantly limited by dissolved inorganic phosphorus(DIP) in the three sea areas, especially in Daya Bay. TotalAPA ranged between 1.41 and 35.26 nmol/L/hr, and the highest value was found in Daya Bay. The increased APA in Daya Bay was the result of the increase of phytoplankton biomass and the response of phytoplankton to P limitation. Phyto-APA was the main contributor in Daya Bay, while phyto-and free-APA co-dominated in Guishan Island and Guanghai Bay. Bact-, phyto-, and total-APA showed a significant inverse power function relationship with DIP, and 0.2 μmol/L was the threshold for DIP on particulates and totalAPA. Pearson correlation analysis suggested that DIP limitation together with high N levels enhanced APA. High water temperature and freshwater input accelerated APA as well.Principal component analysis clearly separated samples from the three sea areas, as well as from the SML and the SSW, which indicated the differences in environmental parameters and APA levels. Our results highlight the influence of phosphorus limitation and environmental parameters on APA.