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Handbook of Ecological Modellingand Informatics

Handbook of Ecological Modellingand Informatics

Editors:

S.E. JørgensenThe University of Pharmaceutical Science, Denmark

T-S. ChonPusan National University, Korea

F. RecknagelUniversity of Adelaide, Australia

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ISBN: 978-1-84564-207-5

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Editors:S.E. JørgensenThe University of Pharmaceutical Science, Denmark

T-S. ChonPusan National University, Korea

F. RecknagelUniversity of Adelaide, Australia

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 ......... 1 S.E. Jørgensen 1 History of the ecological sub-disciplines ......................................................................... 1 2 The development of ecological modeling ........................................................................ 5

Chapter 2 Overview of the model types available for ecological modeling ..................................... 9 S.E. Jørgensen & T.-S. Chon 1 Issues in model development ........................................................................................... 9

1.1 Presentation of spatial distribution ........................................................................... 11 1.2 Computational realization of biological properties ................................................. 15 1.3 Revealing environmental factors ............................................................................. 17 1.4 Data handling and model construction .................................................................... 18

2 Increasing number of model types ................................................................................... 19 3 Characteristics of the model types available today ......................................................... 21

3.1 Dynamic models: Chapters 5 and 11 ...................................................................... 22 3.2 Static models: Chapters 5 and 11 ........................................................................... 23 3.3 Population dynamic model: Chapter 12 ................................................................ 24 3.4 Structurally dynamic models: Chapter 13 ............................................................. 25 3.5 Fuzzy models: Chapter 8 ........................................................................................ 26 3.6 Models in ecological informatics: Chapter 9 ......................................................... 27 3.7 Individual-based models and cellular automata: Chapters 7 and 16 ..................... 28 3.8 Spatial models: Chapters 6 and 20 ......................................................................... 30 3.9 Ecotoxicological models: Chapters 14 and 15 ....................................................... 31 3.10 Stochastic models: Chapter 12 ............................................................................... 33 3.11 Rule-based models: Chapter 17 ............................................................................. 34 3.12 Hybrid models: Chapter 10 .................................................................................... 35

3.13 Mediated/institutionalized models: Chapters 4 and 19 .......................................... 35 3.14 Network analyses and calculations: Chapter 18 .................................................... 37

4 Applicability of the model types ...................................................................................... 37 Chapter 3 Ecological informatics: current scope and feature areas ................................................ 41 F. Recknagel 1 Introduction ...................................................................................................................... 41 2 Feature areas ..................................................................................................................... 43 3 Future directions ............................................................................................................... 44

Chapter 4 Model making ....................................................................................................................... 49 S.E. Jørgensen 1 Modelling procedure ......................................................................................................... 49 2 Institutionalized modeling ................................................................................................ 51

2.1 The institutionalized modelling process .................................................................. 52 3 When to apply IMM? ........................................................................................................ 53

Chapter 5 Ecopath with Ecosim: linking fisheries and ecology ........................................................ 55 V. Christensen 1 Why ecosystem modeling in fisheries? ............................................................................ 55 2 The Ecopath with Ecosim (EwE) modeling approach .................................................... 56

2.1 Model overview......................................................................................................... 56 2.2 Mass-balance ............................................................................................................ 56 2.3 The foraging arena .................................................................................................... 58 2.4 Ecosim ...................................................................................................................... 59

3 EwE modules and applications ........................................................................................ 60 5 EwE applications .............................................................................................................. 61 6 Getting hold of the EwE software .................................................................................... 62 7 Exercise: trawling cultivates the ocean bottom for squid ................................................ 63

Chapter 6 Surface modelling of population distribution ................................................................... 71 T.-X. Yue, Y.-A. Wang & Z.-M. Fan 1 Introduction ...................................................................................................................... 71 2 YUE-SMPD ...................................................................................................................... 72

2.1 Approaches to population distribution analyses ...................................................... 72 2.2 YUE-SMPD formulation .......................................................................................... 73

3 An application of YUE-SMPD ........................................................................................ 74 3.1 Major data layers ...................................................................................................... 74 3.2 YUE-SMPD operation ............................................................................................. 86 3.3 Change trend of population distribution in China ................................................... 87 3.4 Scenarios of population distribution in China ......................................................... 90

4 Discussion ......................................................................................................................... 92

Chapter 7 Individual-based models ...................................................................................................... 99 T.-S. Chon, Sang Hee Lee, C. Jeoung, H.K. Cho, Seung Ho Lee & Y.-J. Chung 1 Introduction ...................................................................................................................... 99 2 Properties of individuals .................................................................................................. 100 3 Model construction ........................................................................................................... 101

3.1 Program outline and system environment ............................................................... 101 3.2 Variables ................................................................................................................... 102 3.3 Model structure and interaction ............................................................................... 102 3.4 Parameters and input data ........................................................................................ 102 3.5 Output and model results .......................................................................................... 102

4 Case study 1: flocking behavior ....................................................................................... 103 4.1 Program outline and system environment ............................................................... 103 4.2 Variables ................................................................................................................... 103 4.3 Model structure and interaction ............................................................................... 105 4.4 Parameters and input data ........................................................................................ 107 4.5 Output and results ..................................................................................................... 107

5 Case study 2: population dispersal ................................................................................... 109 5.1 Program outline and system environment ............................................................... 109 5.2 Variables ................................................................................................................... 111 5.3 Model structure and interaction ............................................................................... 113 5.4 Parameters and input data ........................................................................................ 113 5.5 Output and results ..................................................................................................... 114

Chapter 8 A fuzzy approach to ecological modelling and data analysis .......................................... 125 A. Salski, B. Holsten & M. Trepel 1 Imprecision, uncertainty and heterogeneity of environmental data ................................ 125 2 Fuzzy sets and fuzzy logic in ecological applications ..................................................... 126

2.1 Fuzzy classification and spatial data analysis .......................................................... 126 2.2 Fuzzy modelling, decision making and ecosystem management ............................ 127 2.3 Hybrid approaches to data analysis and ecological modelling ................................ 127

3 Fuzzy classification: a fuzzy clustering approach ........................................................... 127 3.1 An application example: fuzzy classification of wetlands for determination

of water quality improvement potentials ................................................................. 129 4 Fuzzy modelling ............................................................................................................... 132

4.1 An application example: a fuzzy and neuro-fuzzy approach to modelling cattle grazing in Western Europe ............................................................................. 134

5 Final remarks .................................................................................................................... 138

Chapter 9 Ecological informatics by means of neural, evolutionary and object-oriented computation ............................................................................................... 141 F. Recknagel & H. Cao 1 Introduction ...................................................................................................................... 141 2 Artificial neural networks ................................................................................................. 141

2.1 Supervised feedforward ANN .................................................................................. 143 2.2 Supervised feedback ANN ....................................................................................... 144 2.3 Non-supervised ANN ............................................................................................... 145

2.4 Evolutionary algorithms ........................................................................................... 150 2.5 Object-oriented programming .................................................................................. 153

3 Conclusions ...................................................................................................................... 160 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 .......................................................................... 169 H. Cao & F. Recknagel 1 Introduction ...................................................................................................................... 169 2 Evolutionary algorithm for the optimisation

of process representations and parameters ...................................................................... 170 2.1 Encoding ................................................................................................................... 171 2.2 Fitness evaluation ..................................................................................................... 171 2.3 Genetic operators ...................................................................................................... 172

3 Optimisation of process representations in SALMO-OO by means of EA .................... 172 3.1 Experimental settings and measures ........................................................................ 172 3.2 Results and discussion .............................................................................................. 175

4 Case study of parameter optimisation in SALMO-OO ................................................... 176 4.1 Experimental settings and measures ........................................................................ 176 4.2 Results and discussion .............................................................................................. 178

5 Conclusions and future work ........................................................................................... 184

Chapter 11 Biogeochemical models ........................................................................................................ 187 S.E. Jørgensen

1 The characteristics of biogeochemical models ................................................................ 187 2 The application of biogeochemical models ..................................................................... 188 3 Biogeochemical models ................................................................................................... 190 4 Model of sub-surface wetland........................................................................................... 190

4.1 The state variables .................................................................................................... 191 4.2 Forcing functions ...................................................................................................... 193 4.3 Process equations ...................................................................................................... 194 4.4 Parameters ................................................................................................................ 195 4.5 Differential equations ............................................................................................... 195 4.6 Model results ............................................................................................................ 197 4.7 Additional results ...................................................................................................... 197 4.8 Comparison of simulated and measured values ....................................................... 197 4.9 Practical information about forcing functions and parameters ............................... 198

Chapter 12 Stochastic population dynamic models as probability networks .................................... 199 M.E. Borsuk & D.C. Lee

1 Introduction ...................................................................................................................... 199 1.1 Population dynamic models ..................................................................................... 199 1.2 Stochasticity .............................................................................................................. 199 1.3 Stochastic models ..................................................................................................... 200 1.4 Probability networks ................................................................................................. 201

2 Methods ............................................................................................................................ 201

2.1 Model construction.................................................................................................... 201 2.2 Communicating results ............................................................................................. 202 2.3 Use of probability networks ..................................................................................... 202

3 Example models and their applications ........................................................................... 203 3.1 BayVAM and westslope cutthroat trout

in the Upper Missouri River Basin, USA ................................................................ 203 3.2 CATCH-Net and brown trout in the Rhine River Basin, Switzerland .................... 210

4 Availability of models and software ................................................................................ 217 4.1 BayVAM/Netica ....................................................................................................... 217 4.2 CATCH-Net/Analytica ............................................................................................. 217

Chapter 13 Structurally dynamic models .............................................................................................. 221 S.E. Jørgensen 1 Introduction: why structurally dynamic models? ............................................................. 221 2 Ecosystem characteristics ................................................................................................. 221 3 Structurally dynamic models ........................................................................................... 226 4 Development of SDM for Darwin’s finches..................................................................... 233 5 Model of the ectoparasite–bird interactions .................................................................... 234

Chapter 14 Ecotoxicological models ....................................................................................................... 241 S.E. Jørgensen 1 Introduction: characteristics of ecotoxicological models ................................................ 241 2 Classification of ecotoxicological models ....................................................................... 242

2.1 Food chain or food web dynamic models ................................................................ 242 2.2 Static models of the mass flows of toxic substances ............................................... 242 2.3 A dynamic model of a toxic substance in one trophic level .................................... 243 2.4 Ecotoxicological models in population dynamics ................................................... 245 2.5 Ecotoxicological models with effect components ................................................... 245

3 The application of parameter estimation methods in ecotoxicological modelling ......... 247 4 Biogeochemical and ecotoxicological models: tylosine ................................................. 250

4.1 The equations ............................................................................................................ 251 4.2 State variables ........................................................................................................... 251 4.3 Differential equations and initial values: (process abbreviations, see below) ......... 251 4.4 Site-specific parameter ............................................................................................. 251 4.5 Climatic forcing functions as graphs ....................................................................... 251 4.6 Processes ................................................................................................................... 251

Chapter 15 Behavioral methods in ecotoxicology ................................................................................. 255 T.-S. Chon, C.W. Ji1, Y.-S. Park & S.E. Jørgensen 1 Why behavioral methods in ecotoxicology?..................................................................... 255

1.1 Behavioral monitoring .............................................................................................. 255 1.2 Behaviors linked with genes and populations ......................................................... 256

2 Monitoring at the individual level .................................................................................... 257 2.1 Monitoring processes ............................................................................................... 257 2.2 Data preparation ....................................................................................................... 258 2.3 Statistical description ............................................................................................... 259 2.4 Analysis of data structure ......................................................................................... 262

2.5 Pattern detection by learning method ...................................................................... 264 3 Modeling the gene–individual–population relationships ................................................ 270

3.1 Program outline and system environment ............................................................... 271 Chapter 16 Cellular automata ................................................................................................................. 283 Q. Chen 1 Introduction to cellular automata ..................................................................................... 283

1.1 Definition of cellular automata ................................................................................ 283 1.2 Neighbourhood schemes .......................................................................................... 284 1.3 Local evolution rules ................................................................................................ 284 1.4 Initial conditions ....................................................................................................... 285 1.5 Boundary conditions ................................................................................................. 285 1.6 Development of cellular automata ........................................................................... 286

2 Development and application of EcoCA ......................................................................... 286 2.1 Development of EcoCA ........................................................................................... 286 2.2 Application of EcoCA .............................................................................................. 288 2.3 User guide for EcoCA .............................................................................................. 293

3 Development and application of LYC ............................................................................. 295 3.1 Description of study area .......................................................................................... 296 3.2 Model development .................................................................................................. 297 3.3 Results and discussion .............................................................................................. 299 3.4 User guide for LYC .................................................................................................. 302

4 Discussion ......................................................................................................................... 303

Chapter 17 Rule-based ecological model ............................................................................................... 307 Q. Chen & A. Mynett 1 Introduction to rule-based technique ............................................................................... 307

1.1 Feature reasoning ...................................................................................................... 307 1.2 Case reasoning .......................................................................................................... 309 1.3 Decision tree ............................................................................................................. 309

2 Rule-based modelling of algal biomass in Dutch coastal waters .................................... 311 2.1 Description of study area .......................................................................................... 311 2.2 Model development .................................................................................................. 312 2.3 Model testing ............................................................................................................ 313

3 Integrated numerical and rule-based technique ............................................................... 313 3.1 Description of study area .......................................................................................... 314 3.2 Model development .................................................................................................. 314 3.2 Results ....................................................................................................................... 318

4 Discussion ......................................................................................................................... 319 5 User guide for FuzzHab ................................................................................................... 320

5.1 Factor selection ......................................................................................................... 320 5.2 Rule generation ......................................................................................................... 320 5.3 Modelling .................................................................................................................. 321

Chapter 18 Network calculations II: a user’s manual for EcoNet ...................................................... 325 C. Kazanci 1 Introduction ...................................................................................................................... 325 2 How to create an EcoNet model ...................................................................................... 327

2.1 EcoNet model structure ............................................................................................ 327 2.2 EcoNet model flexibility .......................................................................................... 328 2.3 A few rules about EcoNet models ............................................................................ 329

3 How to run an EcoNet model ........................................................................................... 330 3.1 Fourth-order Runge–Kutta method .......................................................................... 331 3.2 Numerical solution methods .................................................................................... 332 3.3 Stochastic method ..................................................................................................... 333 3.4 From model to differential equation ........................................................................ 334

4 Simulation and analysis results ........................................................................................ 335 4.1 Network diagram ...................................................................................................... 335 4.2 Time-course plot and data of compartment storage values ..................................... 336 4.3 Model information .................................................................................................... 338 4.4 Adjacency matrix ...................................................................................................... 338 4.5 Flow coefficient matrix ............................................................................................ 338 4.6 Flow matrix ............................................................................................................... 340 4.7 Network analysis ...................................................................................................... 341 4.8 Storage analysis ........................................................................................................ 341 4.9 Throughflow analysis ............................................................................................... 342 4.10 Utility analysis .......................................................................................................... 344

5 Study of an EcoNet model ............................................................................................... 345 5.1 Model description ..................................................................................................... 345 5.2 Flow analysis ............................................................................................................ 346 5.3 Storage and utility analysis ...................................................................................... 348 5.4 Further analysis ........................................................................................................ 349

Chapter 19 Mediating conceptual knowledge using qualitative reasoning ....................................... 351 B. Bredeweg & P. Salles 1 Introduction ...................................................................................................................... 351 2 Background and principles ............................................................................................... 352

2.1 How does it work?..................................................................................................... 352 2.2 Model ingredients ..................................................................................................... 353 2.3 Qualitativeness ......................................................................................................... 354 2.4 Causality ................................................................................................................... 355 2.5 Inequality reasoning ................................................................................................. 356 2.6 Correspondences ....................................................................................................... 357 2.7 Model fragments: reusing partial models ................................................................ 357 2.8 Generating a state-graph ........................................................................................... 358

3 Garp3: QR workbench ..................................................................................................... 359 3.1 Build environment .................................................................................................... 361 3.2 Simulate environment .............................................................................................. 365 3.3 Special features and support ..................................................................................... 368 3.4 Support and getting started ....................................................................................... 373

4 Examples of QR models ................................................................................................... 373 4.1 Binary population interactions ................................................................................. 373

4.2 The Ants’ Garden ..................................................................................................... 381 4.3 Towards the Millennium Development Goals ......................................................... 386

5 Assignments ..................................................................................................................... 390 5.1 Two and three populations ....................................................................................... 390 5.2 Deforestation and vegetation growth ....................................................................... 390 5.3 Challenges with the population models ................................................................... 392

6 Evaluating QR models ..................................................................................................... 392 7 Conclusion and discussion ............................................................................................... 394

Chapter 20 Models of flow pattern and mass distribution .................................................................. 399 R. Miranda & R. Neves 1 Introduction ...................................................................................................................... 399 2 Mohid overview ............................................................................................................... 399 3 Finite volumes .................................................................................................................. 400 4 Boundaries ........................................................................................................................ 400 5 Hydrodynamic model ....................................................................................................... 400

5.1 Turbulence ................................................................................................................ 401 6 Transport models .............................................................................................................. 401

6.1 Lagrangian transport model ..................................................................................... 402 6.2 Eulerian transport model .......................................................................................... 403

7 Numerical modelling of water properties ........................................................................ 403 7.1 Water quality model ................................................................................................. 404

8 Mohid’s results ................................................................................................................. 404 8.1 Tagus operational model .......................................................................................... 404 8.2 Sediment transport .................................................................................................... 405

9 Conclusions ...................................................................................................................... 405

Chapter 21 Applications of data mining in ecological modelling ........................................................ 409 M. Debeljak & S. Džeroski 1 Introduction ...................................................................................................................... 409 2 Data mining ...................................................................................................................... 410

2.1 Data ........................................................................................................................... 410 2.2 Patterns ..................................................................................................................... 411 2.3 Algorithms ................................................................................................................ 412

3 Applications ...................................................................................................................... 415 3.1 Equations .................................................................................................................. 415 3.2 Decision trees ........................................................................................................... 417 3.3 Predictive rules for regression .................................................................................. 420

4 Conclusions ...................................................................................................................... 421

Index ...................................................................................................................................... 425

During the last two decades the development in computer technology has been enormous. Twodecades ago, we were probably working with our first personal computers, which may have hada memory of 512 kb or 1024 kb and storage capacity was 30 or 50 Mb. The laptops of today have1000 or 2000 times as much memory and capacity and the price of computers is 25-50 timeslower, when we consider the level of incomes. This development has of course also influencedthe development of ecological models. The models of today are much larger. For instance 3D-models that were hardly used twenty years ago due to the required computer time are generally inuse to day. Models considering the spatial distribution are now regularly used whenever a spatialdistribution is of importance for the modelling results; it was impossible to run most spatialdistribution models on personal computers twenty years ago. As a result, several new modeltypes 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 yearsago, The more comprehensive tool box has made it easier to achieve good model results, but ithas also made it more difficult to select the right tool or combination of tools to solve a specificproblem. We have therefore found that there was a need for a “Handbook in Ecological Model-ling” with the scope to present to the readers all the available model tools of today. To facilitatethe selection of the right model type for a specific problem, we have included on a CD a typicalexample of all the available model types. Such an easy-to-go test of a model example, will dem-onstrate the advantages and disadvantages of the model type for the readers and thereby give abetter basis for the right model type selection.

The development of the computer technology has offered two other advantages for theecological modellers, namely that it is more easy to have access to and to apply big data bases and

Preface

that an enormous amount of ecologically relevant information including genetic information isavailable on internet. Due to this development a new ecological sub-discipline called ecologicalinformatics was born in Adelaide in year 2000, when it was agreed at a conference in ecologicalinformatics to launch ISEI, International Society of Ecological Informatics. We found it there-fore of interest for the readers to include also this development of applied ecology in the hand-book and we have therefore decided to use the title “Handbook of Ecological Modelling andInformatics”. What ecological informatics covers is presented in details in Chapter 3 and also theminor overlap it has with ecological modelling, while the field of ecological modelling is pre-sented in Chapter 2. The chapters 4-20 present the up-to-date tool box of ecological modellingand informatics. In the last chapter, we attempt to predict in which direction these two rapidgrowing sub-disciplines of ecology will develop.

Ecological modelling and informatics are two very recent sub-disciplines of ecology. Theyhave opened-up a number of new possibilities for synthesizing and quantifying knowledge inecology, which is urgently needed in modern environmental management. With the ecologicalcrisis that can be foreseen in the 21st century due to a rapidly expanding population in manycountries, rapidly decreasing natural resources in all countries and significant global climatechanges, there will be a growing need for ecological modelling and informatics. This handbookwill contribute to wider development and application of quantitative ecological approaches.

The Editors, 2008