Handbook of Ecological Modelling and Informatics WITPRESS

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1 Handbook of Ecological Modelling and Informatics WITPRESS WIT Press publishes leading books in Science and Technology. Visit our website for the current list of titles. WITeLibrary Home of the Transactions of the Wessex Institute, the WIT electronic-library provides the international scientific community with immediate and permanent access to individual papers presented at WIT conferences. Visit the WIT elibrary at

2 Handbook of Ecological Modelling and Informatics Editors: The University of Pharmaceutical Science, Denmark T-S. Chon Pusan National University, Korea F. Recknagel University of Adelaide, Australia

3 Editors: The University of Pharmaceutical Science, Denmark T-S. Chon Pusan National University, Korea F. Recknagel University of Adelaide, Australia Published by WIT Press Ashurst Lodge, Ashurst, Southampton, SO40 7AA, UK Tel: 44 (0) ; Fax: 44 (0) For USA, Canada and Mexico WIT Press 25 Bridge Street, Billerica, MA 01821, USA Tel: ; Fax: British Library Cataloguing-in-Publication Data A Catalogue record for this book is available from the British Library ISBN: Library of Congress Catalog Card Number: The texts of the papers in this volume were set individually by the authors or under their supervision. No responsibility is assumed by the Publisher, the Editors and Authors for any injury and/or damage to persons or property as a matter of products liability, negligence or otherwise, or from any use or operation of any methods, products, instructions or ideas contained in the material herein. The Publisher does not necessarily endorse the ideas held, or views expressed by the Editors or Authors of the material contained in its publications. WIT Press 2009 Printed in Great Britain by Athenaeum Press Ltd. All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, electronic, mechanical, photocopying, recording, or otherwise, without the prior written permission of the Publisher.

4 Contents Preface... xiii Model examples, software, homepages and contact person for the various model types... xv Chapter 1 Introduction: sub-disciplines of ecology and the history of ecological modeling History of the ecological sub-disciplines The development of ecological modeling... 5 Chapter 2 Overview of the model types available for ecological modeling... 9 & T.-S. Chon 1 Issues in model development Presentation of spatial distribution Computational realization of biological properties Revealing environmental factors Data handling and model construction Increasing number of model types Characteristics of the model types available today Dynamic models: Chapters 5 and Static models: Chapters 5 and Population dynamic model: Chapter Structurally dynamic models: Chapter Fuzzy models: Chapter Models in ecological informatics: Chapter Individual-based models and cellular automata: Chapters 7 and Spatial models: Chapters 6 and Ecotoxicological models: Chapters 14 and Stochastic models: Chapter Rule-based models: Chapter Hybrid models: Chapter

5 3.13 Mediated/institutionalized models: Chapters 4 and Network analyses and calculations: Chapter Applicability of the model types Chapter 3 Ecological informatics: current scope and feature areas F. Recknagel 1 Introduction Feature areas Future directions Chapter 4 Model making Modelling procedure Institutionalized modeling The institutionalized modelling process When to apply IMM? Chapter 5 Ecopath with Ecosim: linking fisheries and ecology V. Christensen 1 Why ecosystem modeling in fisheries? The Ecopath with Ecosim (EwE) modeling approach Model overview Mass-balance The foraging arena Ecosim EwE modules and applications EwE applications Getting hold of the EwE software Exercise: trawling cultivates the ocean bottom for squid Chapter 6 Surface modelling of population distribution T.-X. Yue, Y.-A. Wang & Z.-M. Fan 1 Introduction YUE-SMPD Approaches to population distribution analyses YUE-SMPD formulation An application of YUE-SMPD Major data layers YUE-SMPD operation Change trend of population distribution in China Scenarios of population distribution in China Discussion... 92

6 Chapter 7 Individual-based models T.-S. Chon, Sang Hee Lee, C. Jeoung, H.K. Cho, Seung Ho Lee & Y.-J. Chung 1 Introduction Properties of individuals Model construction Program outline and system environment Variables Model structure and interaction Parameters and input data Output and model results Case study 1: flocking behavior Program outline and system environment Variables Model structure and interaction Parameters and input data Output and results Case study 2: population dispersal Program outline and system environment Variables Model structure and interaction Parameters and input data Output and results Chapter 8 A fuzzy approach to ecological modelling and data analysis A. Salski, B. Holsten & M. Trepel 1 Imprecision, uncertainty and heterogeneity of environmental data Fuzzy sets and fuzzy logic in ecological applications Fuzzy classification and spatial data analysis Fuzzy modelling, decision making and ecosystem management Hybrid approaches to data analysis and ecological modelling Fuzzy classification: a fuzzy clustering approach An application example: fuzzy classification of wetlands for determination of water quality improvement potentials Fuzzy modelling An application example: a fuzzy and neuro-fuzzy approach to modelling cattle grazing in Western Europe Final remarks Chapter 9 Ecological informatics by means of neural, evolutionary and object-oriented computation F. Recknagel & H. Cao 1 Introduction Artificial neural networks Supervised feedforward ANN Supervised feedback ANN Non-supervised ANN

7 2.4 Evolutionary algorithms Object-oriented programming Conclusions Chapter 10 Hybridisation of process-based ecosystem models with evolutionary algorithms: multi-objective optimisation of process and parameter representations of the lake simulation library SALMO-OO H. Cao & F. Recknagel 1 Introduction Evolutionary algorithm for the optimisation of process representations and parameters Encoding Fitness evaluation Genetic operators Optimisation of process representations in SALMO-OO by means of EA Experimental settings and measures Results and discussion Case study of parameter optimisation in SALMO-OO Experimental settings and measures Results and discussion Conclusions and future work Chapter 11 Biogeochemical models The characteristics of biogeochemical models The application of biogeochemical models Biogeochemical models Model of sub-surface wetland The state variables Forcing functions Process equations Parameters Differential equations Model results Additional results Comparison of simulated and measured values Practical information about forcing functions and parameters Chapter 12 Stochastic population dynamic models as probability networks M.E. Borsuk & D.C. Lee 1 Introduction Population dynamic models Stochasticity Stochastic models Probability networks Methods

8 2.1 Model construction Communicating results Use of probability networks Example models and their applications BayVAM and westslope cutthroat trout in the Upper Missouri River Basin, USA CATCH-Net and brown trout in the Rhine River Basin, Switzerland Availability of models and software BayVAM/Netica CATCH-Net/Analytica Chapter 13 Structurally dynamic models Introduction: why structurally dynamic models? Ecosystem characteristics Structurally dynamic models Development of SDM for Darwin s finches Model of the ectoparasite bird interactions Chapter 14 Ecotoxicological models Introduction: characteristics of ecotoxicological models Classification of ecotoxicological models Food chain or food web dynamic models Static models of the mass flows of toxic substances A dynamic model of a toxic substance in one trophic level Ecotoxicological models in population dynamics Ecotoxicological models with effect components The application of parameter estimation methods in ecotoxicological modelling Biogeochemical and ecotoxicological models: tylosine The equations State variables Differential equations and initial values: (process abbreviations, see below) Site-specific parameter Climatic forcing functions as graphs Processes Chapter 15 Behavioral methods in ecotoxicology T.-S. Chon, C.W. Ji1, Y.-S. Park & 1 Why behavioral methods in ecotoxicology? Behavioral monitoring Behaviors linked with genes and populations Monitoring at the individual level Monitoring processes Data preparation Statistical description Analysis of data structure

9 2.5 Pattern detection by learning method Modeling the gene individual population relationships Program outline and system environment Chapter 16 Cellular automata Q. Chen 1 Introduction to cellular automata Definition of cellular automata Neighbourhood schemes Local evolution rules Initial conditions Boundary conditions Development of cellular automata Development and application of EcoCA Development of EcoCA Application of EcoCA User guide for EcoCA Development and application of LYC Description of study area Model development Results and discussion User guide for LYC Discussion Chapter 17 Rule-based ecological model Q. Chen & A. Mynett 1 Introduction to rule-based technique Feature reasoning Case reasoning Decision tree Rule-based modelling of algal biomass in Dutch coastal waters Description of study area Model development Model testing Integrated numerical and rule-based technique Description of study area Model development Results Discussion User guide for FuzzHab Factor selection Rule generation Modelling

10 Chapter 18 Network calculations II: a user s manual for EcoNet C. Kazanci 1 Introduction How to create an EcoNet model EcoNet model structure EcoNet model flexibility A few rules about EcoNet models How to run an EcoNet model Fourth-order Runge Kutta method Numerical solution methods Stochastic method From model to differential equation Simulation and analysis results Network diagram Time-course plot and data of compartment storage values Model information Adjacency matrix Flow coefficient matrix Flow matrix Network analysis Storage analysis Throughflow analysis Utility analysis Study of an EcoNet model Model description Flow analysis Storage and utility analysis Further analysis Chapter 19 Mediating conceptual knowledge using qualitative reasoning B. Bredeweg & P. Salles 1 Introduction Background and principles How does it work? Model ingredients Qualitativeness Causality Inequality reasoning Correspondences Model fragments: reusing partial models Generating a state-graph Garp3: QR workbench Build environment Simulate environment Special features and support Support and getting started Examples of QR models Binary population interactions

11 4.2 The Ants Garden Towards the Millennium Development Goals Assignments Two and three populations Deforestation and vegetation growth Challenges with the population models Evaluating QR models Conclusion and discussion Chapter 20 Models of flow pattern and mass distribution R. Miranda & R. Neves 1 Introduction Mohid overview Finite volumes Boundaries Hydrodynamic model Turbulence Transport models Lagrangian transport model Eulerian transport model Numerical modelling of water properties Water quality model Mohid s results Tagus operational model Sediment transport Conclusions Chapter 21 Applications of data mining in ecological modelling M. Debeljak & S. Džeroski 1 Introduction Data mining Data Patterns Algorithms Applications Equations Decision trees Predictive rules for regression Conclusions Index

12 Preface During the last two decades the development in computer technology has been enormous. Two decades ago, we were probably working with our first personal computers, which may have had a memory of 512 kb or 1024 kb and storage capacity was 30 or 50 Mb. The laptops of today have 1000 or 2000 times as much memory and capacity and the price of computers is times lower, when we consider the level of incomes. This development has of course also influenced the development of ecological models. The models of today are much larger. For instance 3Dmodels that were hardly used twenty years ago due to the required computer time are generally in use to day. Models considering the spatial distribution are now regularly used whenever a spatial distribution is of importance for the modelling results; it was impossible to run most spatial distribution models on personal computers twenty years ago. As a result, several new model types have emerged, and they are able to solve modeling problems formulated in the 1970s. How do we deal with the individuality of the organisms? How do we consider the change in properties of the organisms due to adaptation? How do we consider a shift in the species composition, which we know may take place? How can we build a model based on a very heterogeneous data base? How can we develop a model, when our data base is fuzzy? How can we describe the spatial distribution? How can we ensure that we get the best model description based on our data? Can we combine several ecosystem models to a landscape model? The modelling tool box available to day, year 2008, contains many more tools than twenty years ago, The more comprehensive tool box has made it easier to achieve good model results, but it has also made it more difficult to select the right tool or combination of tools to solve a specific problem. We have therefore found that there was a need for a Handbook in Ecological Modelling with the scope to present to the readers all the available model tools of today. To facilitate the selection of the right model type for a specific problem, we have included on a CD a typical example of all the available model types. Such an easy-to-go test of a model example, will demonstrate the advantages and disadvantages of the model type for the readers and thereby give a better basis for the right model type selection. The development of the computer technology has offered two other advantages for the ecological modellers, namely that it is more easy to have access to and to apply big data bases and

13 that an enormous amount of ecologically relevant information including genetic information is available on internet. Due to this development a new ecological sub-discipline called ecological informatics was born in Adelaide in year 2000, when it was agreed at a conference in ecological informatics to launch ISEI, International Society of Ecological Informatics. We found it therefore of interest for the readers to include also this development of applied ecology in the handbook and we have therefore decided to use the title Handbook of Ecological Modelling and Informatics. What ecological informatics covers is presented in details in Chapter 3 and also the minor overlap it has with ecological modelling, while the field of ecological modelling is presented in Chapter 2. The chapters 4-20 present the up-to-date tool box of ecological modelling and informatics. In the last chapter, we attempt to predict in which direction these two rapid growing sub-disciplines of ecology will develop. Ecological modelling and informatics are two very recent sub-disciplines of ecology. They have opened-up a number of new possibilities for synthesizing and quantifying knowledge in ecology, which is urgently needed in modern environmental management. With the ecological crisis that can be foreseen in the 21 st century due to a rapidly expanding population in many countries, rapidly decreasing natural resources in all countries and significant global climate changes, there will be a growing need for ecological modelling and informatics. This handbook will contribute to wider development and application of quantitative ecological approaches. The Editors, 2008