We are focusing on theoretical concepts in ecological and biological processes, transferring these concepts into mathematical models and predicting these processes under different scenarios.
One of our main research interests is the development of eco-biological models in estuarine ecosystem for management purposes. We have developed a complex multiscale model for simulation of mangrove development under interactions of different factors. This model is used for testing alternative management schemes and assess their effects on the ecosystem quality through forest health and dynamics. This study provides a review of the current modeling practice and discusses several guidelines towards a more rational model development. In this direction, we focus on single optimal parameter selection to a distribution of parameter sets that provide acceptable (behavioral) model performance.
Our plan is to test several methods of uncertainty analysis and Bayesian parameter estimation (e.g., Generalized Likelihood Uncertainty Estimation, Markov Chain Monte Carlo) and provide a comparative description of the strengths and weaknesses, advantages and disadvantages regarding their efficiency as surrogates of the posterior parameter distributions.
We investigate the effects of climate variability (climate change) on the estuarine ecosystem phenology. Estuaries are particularly sensitive to the ecological impacts of climate forcing, and several long time-series have shown a close coupling between climate, hydro-properties and ecosystem physiology, population abundance, community structure, and food-web dynamics. Thus, understanding the complex interplay between meteorological forcing, hydrological variability, and ecosystem functioning is essential basic knowledge for assisting risk assessment and resource management.
We developed the mangrove dynamics model which incorporates stochastic initial seedling spacing, propagule dispersal, recruitment, and mortality. This model is capable of simulating and forecasting different mangrove species responding to plausible scenarios of temperature, rainfall, and sea level rise. Scenarios-based modeling is a primary tool for decision- making under uncertainty.
In coastal wetlands, pollution from untreated domestic, hospital, and industrial wastewater, poor urban drainage, and so on, are the problems which have seriously caused harmful eﬀects on environmental quality and ecosystem health. In addition to efforts to improve the production processes with respect to pollutant emission, phytoremediation techniques may constitute a suitable way to mitigate the impact of pollutants to the environment by utilizing natural plant processes to enhance the removal of contaminants in soil and water. This technique has been employed at sites with soils contaminated with lead, uranium, and other heavy metals. Mangrove trees can serve as a natural water and wastewater treatment system. They do not require frequent harvesting and annual planting, which is not only labor-intensive and time- consuming.
We, in collaboration with colleagues at the Institute of Geoecology – Technical University Braunschweig (Professor Otto Richter and Mr. Klaus- Jürgen Schmalstieg), developed modeling tools (statistical and dynamic models) for predicting the perfomance of a phytoremediation system. We simulated an operation of such a system with different factors: load of pollutants, number of plants, age of plants or initial biomass, volume of the wastewater, nutrient level and the mass of the soil.
We investigate the transport and transfer of fungicides in the pepper cultivated soil. The fate of a substance in the environment is determined by physical, chemical and biological processes. Environmental fate modelling demands an interdisciplinary approach. The understanding of the structures of mathematical models to apply to the dynamical systems theory and on numerical methods will help to create models for simulation of fate of pesticides in the environment, for example, the coupling of kinetics with transport leads to systems of partial differential equations. These processes can be embedded into a random environment.
The mathematical model for the simulation of a HOLNAD waste water treatment system was calibrated and validated by the data from an empirical model and was applied to evaluate the effectiveness of this type of wastewater treatment system under different regimes of dissolved oxygen. This mathematical model consists of a system of differential equations which describe: the oxidation of ammonium to nitrite by AOB bacteria, the process of NO2 to NO3 by NOB bacteria, the conversion of NH4 and NO2 into N2 gas by anammox bacteria, the decline of NH4, NO2, NO3 and COD caused by AOB, NOB, Anammox and other exotic strains…