While understanding the kinetics of algae growth plays an important role in improving algae cultivation technology, none of the existing kinetic models are able to describe algae growth when more than three growth limiting factors are involved. A model was developed in this study to describe algae growth in a photobioreactor. Two expressions were proposed based on the Monod model to relate the specific growth rate of algae to the concentration of nitrogen, phosphorus, inorganic carbon and light intensity in the culture media. Algal biomass concentration as a function of time was calculated by solving mass and energy balances around the photobioreactor. Model simulations were compared with the experimental data from the cultivation of wild type algae in a semi-continuous culture of a completely mixed photobioreactor. There were minor differences between the model results from using the two proposed expressions of the specific growth rate of algae. Biomass concentration simulated by the model followed the same pattern as the measured concentration. However, there was discrepancy between the model output and the experimental results, because of variability from environmental conditions during the experiment and some environmental factors such as temperature were not considered in the model. Also, most of the model's parameters were either derived theoretically or obtained from literature instead of being measured directly. It was found through sensitivity analysis that the maximum biomass density predicted by the model is very sensitive to the maximum specific growth rate for carbon, maximum growth yield and higher heating value of algae. Results from running the model for a continuous culture of the same photobioreactor, showed that the minimum hydraulic retention time for the growth of algae will be 30 days. Further investigations are needed to get more accurate data for sensitive parameters so algae growth can be predicted more accurately. Future work towards integrating other factors including temperature, pH, inhibition factors and decay rate in the kinetic expression, will lead to a better prediction of algae growth

In light of increasing harmful algal blooms and the need to protect human health and aquatic resources, proactive management approaches merit further study. For this purpose I conducted field samplings to characterize plankton community composition and laboratory experiments to test some approaches to new management schemes in the lower Rincon Delta. On site measurements and microscopic analysis showed that environmental parameters and plankton community composition varied considerably among sampling stations and sampling dates. A recent modeling study suggested that manipulation of freshwater inflow to estuaries might prevent phytoplankton blooms and enhance secondary productivity. To test this theory I conducted three semi-continuous design and flow-through incubation design experiments using natural plankton assemblages. I investigated the effect of two different pulsing regimes of inflow and nutrient loading on zooplankton densities, and phytoplankton biomass and diversity. Despite differences in zooplankton structure and phytoplankton community composition between the two experiment designs, the results confirmed that pulsed inflows might alter plankton dynamics. My findings showed that 3-day pulse treatments consistently supported greater zooplankton densities and higher phytoplankton species diversity when compared to 1-day pulse treatments. In addition, accumulation of phytoplankton biovolume remained low during 3-day pulse treatments. Differences in zooplankton performance between 3-day pulse and 1-day pulse inflow treatments were likely due to the ability of phytoplankton to uptake and store greater amounts of nutrients under conditions of 3-day pulse inflow. This resulted in food of higher quality for zooplankton, and might have supported greater zooplankton population growth rates. Additionally, in an attempt to understand the mechanisms leading to high biodiversity in aquatic ecosystems, I built a resource-storage model and studied the effects of resource-storage on competition of multiple phytoplankton species on multiple abiotic resources. I compared this model with a well-established multi-species competition model. My results showed that for certain species combinations a resource-storage-based model can generate dissimilar outcomes when compared to a model without resource-storage.

In light of increasing harmful algal blooms and the need to protect human health and aquatic resources, proactive management approaches merit further study. For this purpose I conducted field samplings to characterize plankton community composition and laboratory experiments to test some approaches to new management schemes in the lower Rincon Delta. On site measurements and microscopic analysis showed that environmental parameters and plankton community composition varied considerably among sampling stations and sampling dates. A recent modeling study suggested that manipulation of freshwater inflow to estuaries might prevent phytoplankton blooms and enhance secondary productivity. To test this theory I conducted three semi-continuous design and flow-through incubation design experiments using natural plankton assemblages. I investigated the effect of two different pulsing regimes of inflow and nutrient loading on zooplankton densities, and phytoplankton biomass and diversity. Despite differences in zooplankton structure and phytoplankton community composition between the two experiment designs, the results confirmed that pulsed inflows might alter plankton dynamics. My findings showed that 3-day pulse treatments consistently supported greater zooplankton densities and higher phytoplankton species diversity when compared to 1-day pulse treatments. In addition, accumulation of phytoplankton biovolume remained low during 3-day pulse treatments. Differences in zooplankton performance between 3-day pulse and 1-day pulse inflow treatments were likely due to the ability of phytoplankton to uptake and store greater amounts of nutrients under conditions of 3-day pulse inflow. This resulted in food of higher quality for zooplankton, and might have supported greater zooplankton population growth rates. Additionally, in an attempt to understand the mechanisms leading to high biodiversity in aquatic ecosystems, I built a resource-storage model and studied the effects of resource-storage on competition of multiple phytoplankton species on multiple abiotic resources. I compared this model with a well-established multi-species competition model. My results showed that for certain species combinations a resource-storage-based model can generate dissimilar outcomes when compared to a model without resource-storage.

Phytoplanktonarten unterscheiden sich in ihren Ansprüchen hinsichtlich Ressourcen wie Nährstoffe, Licht und andere physikalische Faktoren. Wechselwirkungen zwischen Nährstoffen und physikalischen Faktoren beeinflussen daher die Artenzusammensetzung einer Phytoplanktongemeinschaft. In der vorliegenden Arbeit wurde der Einfluss von Temperatur und Photoperiode auf das Phytoplanktonwachstum in Abhängigkeit vom Lichtregime und dem Angebot an Phosphor (P) und Silizium (Si) untersucht. Hierfür wurden Wachstums- und Konkurrenzexperimente unter Laborverhältnissen mit Stephanodiscus minutulus, Nitzschia acicularis (beides Bacillariophyceae) und Limnothrix redekei (Cyanophyceae) durchgeführt, ein Modell der Faktorinteraktionen entwickelt sowie ökologische Langzeitdaten des Müggelsees (Berlin) statistisch ausgewertet. Die Effekte von Temperatur und Photoperiode auf die Wachstumsraten unterschieden sich nicht zwischen konstantem und fluktuierendem Licht. Die Auswirkungen der Photoperiode und der Lichtfluktuationen auf die Wachstumsraten waren hierbei additiv. Der Grad der Limitation der Wachstumsraten durch P oder Si wurde durch die Photoperiode nicht signifikant beeinflusst. Wechselwirkungen zwischen Temperatur und P oder Si waren hingegen komplex und artspezifisch. Unabhängig davon, ob die Wachstumsraten durch P, Si oder fluktuierendes Licht gesteuert wurden, war S. minutulus konkurrenzstärker bei niedrigeren Temperaturen und N. acicularis bei höheren Temperaturen. Zusammenfassend zeigen die Ergebnisse, dass die Faktorinteraktionstypen artspezifisch sind, die Adaptation der Arten widerspiegeln und so zur Nischen-Differenzierung beitragen. Kenntnisse dieser Wechselwirkungen fördern deshalb unser Verständnis der Phytoplanktondiversität und ermöglichen es, Reaktionen des Phytoplanktons auf Klimaerwärmung und Trophieveränderung, die mit einer Verschiebung der Verhältnisse zwischen Nährstoffen, Temperatur und Licht einhergehen, besser vorherzusagen. / Phytoplankton species have different resource requirements and different sensitivities to important growth factors. Interactions between nutrients and physical factors, such as temperature and light should therefore influence the species composition. Because these interactions are poorly understood, this study investigated the interactive effects of temperature and photoperiod on phytoplankton growth controlled by fluctuating light, phosphorus (P) and silicon (Si). Growth and competition experiments were performed in the laboratory on Stephanodiscus minutulus, Nitzschia acicularis (both Bacillariophyceae) and Limnothrix redekei (Cyanophyceae). A model of factor interactions was developed and long-term field data from Lake Müggelsee (Berlin) were statistically analysed. Temperature and photoperiod had the same influence on growth under fluctuating light as they did under constant light. The photoperiod and short term light fluctuations caused by mixing had additive effects on growth. P and Si interacted strongly with temperature with respect to growth, but less with the photoperiod. The Droop relation fitted to S. minutulus but not N. acicularis. The Monod equation could not sufficiently account for non-steady dynamics of diatom growth under Si limitation, underestimating uptake rates and overestimating uptake affinity. Estimates based on the Monod model may therefore considerably underestimate the degree of Si limitation. The types of factor interactions were generally species-specific, reflected niche adaptation and enhanced niche differentiation. Interactions between nutrients and physical factors are relevant to growth during spring and contribute to the phytoplankton composition. Understanding the interactions should improve our knowledge of phytoplankton diversity and increase our ability to predict phytoplankton response to climate and trophic change, which shift the relationship between nutrients, temperature and light.