An Introduction Into Ecological Modelling for Students, Teachers & Scientists

Modelling Complex Ecological Dynamics . Fred Jopp l Hauke Reuter l Broder Breckling Editors Modelling Complex Ecological Dynamics An Introduction into Ecological Modelling for Students, Teachers & Scientists Title Drawings by Melanie Trexler Foreword by Sven Erik Jørgensen & Donald L. DeAngelis Editors Dr. Fred Jopp Dr. Hauke Reuter Department of Biology Department of Ecological Modelling University of Miami Leibniz Center for Tropical Marine Ecology P.O. Box 249118 GmbH (ZMT) Coral Gables, FL 33124 Fahrenheitstraße 6 USA 28359 Bremen [email protected] Germany [email protected] Dr. Broder Breckling General and Theoretical Ecology Center for Environmental Research and Sustainable Technology (UFT) University of Bremen Leobener St. 28359 Bremen Germany [email protected] ISBN 978-3-642-05028-2 e-ISBN 978-3-642-05029-9 DOI 10.1007/978-3-642-05029-9 Springer Heidelberg Dordrecht London New York Library of Congress Control Number: 2011921703 # Springer-Verlag Berlin Heidelberg 2011 This work is subject to copyright. All rights are reserved, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilm or in any other way, and storage in data banks. Duplication of this publication or parts thereof is permitted only under the provisions of the German Copyright Law of September 9, 1965, in its current version, and permission for use must always be obtained from Springer. Violations are liable to prosecution under the German Copyright Law. The use of general descriptive names, registered names, trademarks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protec- tive laws and regulations and therefore free for general use. Cover design: F. Jopp and WMXDesign GmbH, Heidelberg, Germany Printed on acid-free paper Springer is part of Springer Science+Business Media (www.springer.com) Foreword Natural systems are complex, heterogeneous and diverse. If we look in detail, in fact, we see that each system is unique, differing from all others in various characteristics. Scientific investigation is largely a process of simplifying and selecting from such systems a small set of key components, governing factors, and relationships that are sufficient to describe how the system works. From these, ecologists try to develop generalizations across many systems. By this process, they improve their understanding of nature. This knowledge may also help where guidance in management is necessary. There is no one “right” way to perform the simplifications used in the study of natural systems. This text is about the quantitative modelling of natural systems, but makes the point that a number of different approaches to such modelling have evolved and may be valid. Thus, ecologists have at their disposal alternative ways of specifying the aspects that are needed for describing of how an ecological system works and which aspects can be left out of consideration. Ecological modelling today plays an increasingly important part in facilitating insights into how organisms interact with their environment and each other, and how this creates the properties of ecological systems. The general use of quantitative models in studying nature developed historically as a specific part of the advancement of science. Where one locates the starting point of modelling depends on one’s particular perspective. Some of the methods we use today – differential equations – were developed during the seventeenth century. One prediction of such equations, exponential growth, representing an important component today in many ecological models, became well known through the famous work of Malthus in the late eighteenth century in an economical context. Verhulst’s formula of logistic growth was formulated in the nineteenth century. With the equations for a predator–prey interaction by Lotka and Volterra in the early twentieth century, quantitative ecology started to use models of successively increasing complexity. In the early stages of development, ecological modelling was largely based on differential equations, which were fundamental primarily for the development of classical mechanics. This may have contributed to the notion that modelling in ecology was merely an application of differential equations or other mathematical formalisms. However, if this were actually true, it would not be reasonable to v vi Foreword consider ecological modelling as a distinct discipline. Ecological modelling would in that case be more properly viewed as a subdiscipline of applied physics or mathematics. The point of view taken in this book is a different one. It presents the modelling of complex ecological dynamics as a part of ecology, thus a subdiscipline of biology. It makes use of a wide variety of techniques imported from various sources, among which there are numerous mathematical methods, but also techniques from computer science and operations research. In addition, systems theory, quantitative methods from geography, and methods from a variety of other fields have helped supply formal methods to solving ecological problems. It is the understanding of the organizers of this text that modelling should start with the specific ecological questions at hand and then the most appropriate ways of representation and formalisation should be selected. That is, ecological modelling should not be primarily steered by knowledge of applied mathematics, but should start from the foundations of ecological and biological knowledge and insight. Then the quantitative methods that are most suitable can be chosen and applied. Using and adapting methods from outside biology for ecological purposes requires a broad overview of the methodological repertoire that is applicable for representing and understanding patterns and processes arising from the interaction of organisms with their environment. The spectrum of what can be applied in this field of science has indeed grown considerably – quantitatively as well as structurally. Ecological modelling has grown very rapidly during the last 35 years. When the journal Ecological Modelling was launched in 1975, only 300 pages were published per year – around 20 papers. Today, the journal publishes 4,000 pages of a larger format and about 400 papers per year. Ecological models are used much more widely today and are indispens- able tools in ecological research and environmental management. Models are also able today to solve a wider range of problems, because we have a wider range of different model types available. Thirty-five years ago most of the published models were either biogeochemical models or population dynamic models. We have today many more types of models that can account for the spatial distribution, the shifts in structure, adaptation, individuality and the quality of the available data sets. This textbook presents both the quantitative and qualitative progress in ecological modelling and draws a clear up-to-date image of the field of ecological modelling. The progress of the last few decades results not only in ecological modellers now being able to make use of an enormous range of mathematical tools and specialised software. It also results in a great expansion in the different ways of looking at ecological systems. Therefore, an overview of ecological modelling cannot be given today simply by introducing a single approach or technique. An overview of how to model complex ecological dynamics is a task that by its nature can only be addressed by bringing together experts on different methods. This is similar to the approach used in large-scale modelling efforts, where scientists specialised in different fields work together with other collaborators who have statistical, geographical, or computer science expertise. Accordingly, the editors of this textbook did not attempt to summarise second- hand information from literature, but instead asked leading specialists in the most Foreword vii relevant domains of modelling to contribute chapters, starting from the level of elementary introductions and leading up to summaries of more advanced topics and studies. This required structuring criteria on how to guide the reader through the field. The editors decided on a historical and conceptual introduction, followed by an ordering of topics, based on increasing complexity, introducing a range of different modelling techniques in 11 subsequent chapters. The main part of the book presents the most relevant modern approaches, starting with equilibrium methods of ecosystem mass transfer balances and ending with object-oriented systems approaches allowing for time variation, as well as structurally varying self-organizing networks. To illustrate applications of these methods, the final section of the book describes a number of selected prominent case studies, which also emphasise the necessity of cooperation in the application of different techniques to solve complex tasks. Producing a coherent text through the efforts of many collaborators was only possible through productive interaction. In this respect, this collaboration reflects in miniature the way ecological modelling is usually done in the world. It is not a field for “lone wolves”, but requires considerable team spirit. This book creates a proper ambience for such spirit, by going beyond just the compilation of facts and how-to’s, to demonstrate concrete examples of cooperation in this field. Reading the lines

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