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A system may be studied by distinguishing its major components, characterizing the changes in them by differential equations that form their simplified representa tions, and then interconnecting these representations to obtain a model of the original system. Developing the model is the systems synthesis phase. The behaviour of the model may now be studied and compared with experimental results obtained from the system. This research method is called systems analysis and simulation. Systems analysis and simulation can serve to make predictions, to improve the insight in systems, and to test knowledge on consistency and completeness. Predictive models are rare in ecology, simply because the underlying processes which form the basis of the models are seldom well known. A successful example of a predictive model was the work of van Keulen (1975). He showed that under semi arid conditions, where water is the main factor controlling primary production, the simulation technique could predict the production of natural grasslands. Fair predicti ons could also be made for the Sahelian pastures (Penning de Vries & Djiteye, 1982). Predictive models of populations of different pest and disease organisms are being used in biological control systems (Zadoks et aI., 1984).
This book explores the theory and methods of systems analysis and computer modeling as applied to problems in ecology and natural resource management. It reflects the problems and conflicts between competing uses of limited space and the need for quantitative predictors of the outcome of various management strategies.
Systems Analysis and Simulation in Ecology, Volume III, and its companion, Volume IV, grew out of a symposium, Modeling and Analysis of Ecosystems, held at the University of Georgia, 1-3 March 1973. The purposes of the meeting were to (i) review the status of ecosystem modeling, simulation, and analysis; (ii) provide a forum for interaction between U.S. International Biological Program (IBP) Biome modeling programs and selected non-IBP investigations involving systems approaches to ecosystem analysis; and (iii) identify and promote dialogue on key issues in macrosystem modeling. The volume is organized into two parts. Part I treats ecosystem modeling in the U.S. IBP. The introductory chapter is followed by five chapters describing grassland, deciduous forest, desert, tundra, and coniferous forest biome modeling. The concluding chapter is one of critique and evaluation. Part II is devoted mainly to freshwater ecosystems, grading into the estuarine system in the last chapter. The five chapters of this section encompass a simple thermal ecosystem, small woodland streams, a reservoir, one of the Great Lakes, a lake reclaimed from eutrophication, and a major estuary under stress of human impact.
The world's boreal forests, which lie to the south of the Arctic, are considered to be the Earth's most significant terrestrial ecosystems. A panel of ecologists here provide a synthesis of the important patterns and processes which occur in boreal forests and review the principal mechanisms which control the forest's patterns.
Physiolophy and terminology. Basic elements of dynamic simulation. A simulation language: Continuous system modeling program III. The growth of yeast. Additional exercises I. Numerical intergration and error analysis. Aspects of structured programming using CSMP and Fortran. Modelling of ageing, developmemt, delays and dispersion. Mass flow, numeral dispersion and diffusion. Simulation using Fortran. Additional exercises.
This book presents an overview of modeling and simulation of environmental systems via diverse research problems and pertinent case studies. It is divided into four parts covering sustainable water resources modeling, air pollution modeling, Internet of Things (IoT) based applications in environmental systems, and future algorithms and conceptual frameworks in environmental systems. Each of the chapters demonstrate how the models, indicators, and ecological processes could be applied directly in the environmental sub-disciplines. It includes range of concepts and case studies focusing on a holistic management approach at the global level for environmental practitioners. Features: Covers computational approaches as applied to problems of air and water pollution domain. Delivers generic methods of modeling with spatio-temporal analyses using soft computation and programming paradigms. Includes theoretical aspects of environmental processes with their complexity and programmable mathematical approaches. Adopts a realistic approach involving formulas, algorithms, and techniques to establish mathematical models/computations. Provides a pathway for real-time implementation of complex modeling problem formulations including case studies. This book is aimed at researchers, professionals and graduate students in Environmental Engineering, Computational Engineering/Computer Science, Modeling/Simulation, Environmental Management, Environmental Modeling and Operations Research.
During recent decades, large-scale effects of pollution on marine estuaries and even entire enclosed coastal seas have become apparent. One of the first regions where this was observed is the Baltic Sea, whereby the appearance of anoxic deep basins, extensive algal blooms and elimination of top predators like eagles and seals indicated effects of both increased nutrient inputs and toxic substances. This book describes the physical, biochemical and ecological processes that govern inputs, distribution and ecological effects of nutrients and toxic substances in the Baltic Sea. Extensive reviews are supplemented by budgets and dynamic simulation models. This book is highly interdisciplinary and uses a systems approach for analyzing and describing a marine ecosystem. It gives an overview of the Baltic Sea, but is useful for any marine scientist studying large marine ecosystems.
The present volume contains the papers which were accepted for presentation at the 3rd International Symposium for Systems Analysis and Simulation held in Berlin (GDR), September 12-:-16, 1988. It is already a tradition to meet a broad international community of experts in systems analysis, modelling and simulation at this symposium. This fact shows the requirements for a forum of presentation and discussion of new developments and applications of modelling and simulation in systems analysis. To realize the great interest in this field one has to take into consideration the developed role of computer simulation as a powerful tool of problem solving. More and more areas in sciences and production have been investigated by mathematical models and computer' simulation. Biological sciences and social sciences are even by now influenced by this trend. The model use on the computer has been very much improved in decision support systems. Parallel simulation will provide drastic shortening of computing time. Parallel simulation and model based decision support systems are brought in the focus of international activities. Numerical mathematics, systems theory and control sciences provide with algorithms supporting the modelling process itself based on simulation or analytic methods. Such simulation systems equipped with tools for modelling and graphics for representing results are real model support systems. A new important impact comes from artificial intelligence by knowledge processing. Expert systems may help decision making in case of missing mathematical models. Expert systems may also support teaching and using simulation systems.