Ecological Modeling

Bill Grant has taught ecological modeling in the Department of Wildlife and Fisheries Sciences (WFSC) at Texas A&M University since 1976, has served on the Board of Governors and as President of the International Society for Ecological Modeling, and has been Associate Editor of the international journal Ecological Modelling since 1997. Todd Swannack also has taught ecological modeling in WFSC at Texas A&M University, and has been modeling the population dynamics of endangered species since 2002.

• Preface xiAcknowledgments xiii1 Introduction 11.1 Common-sense solutions: three exercises 11.2 Modeling theory 21.3 Modeling practice 21.4 Theory, practice, and common sense 31.5 Intended use of this book 3Part 1 Common-sense solutions: three exercises2 Common-sense solutions 52.1 Three problems 62.1.1 Harvesting food for the winter 62.1.2 Estimating the probability of population extinction 122.1.3 Managing the Commons 202.2 The systems approach to problem solving 492.2.1 The conceptual model (Phase I) 502.2.2 The quantitative model (Phase II) 512.2.3 Model evaluation (Phase III) 512.2.4 Model application (Phase IV) 512.3 The three problems revisited: the systems approach in theory and practice 51Part 2 Modeling theory3 Theory I: the conceptual model 533.1 State the model objectives (Ia) 543.2 Bound the system-of-interest (Ib) 553.3 Categorize the components within the system-of-interest (Ic) 573.3.1 State variables 573.3.2 Material transfers 593.3.3 Sources and sinks 613.3.4 Information transfers 613.3.5 Driving variables 623.3.6 Constants 623.3.7 Auxiliary variables 623.4 Identify the relationships among the components that are of interest (Id) 633.4.1 Submodels 633.5 Represent the conceptual model (Ie) 653.5.1 Conceptual-model diagrams 653.6 Describe the expected patterns of model behavior (If) 664 Theory II: the quantitative model 674.1 Select the general quantitative structure for the model (IIa) 684.2 Choose the basic time unit for the simulations (IIb) 724.3 Identify the functional forms of the model equations (IIc) 724.3.1 Information on which to base the choice of functional forms 734.3.2 Selecting types of equations to represent the chosen functional forms 734.4 Estimate the parameters of the model equations (IId) 754.4.1 Statistical analyses within the context of simulation model parameterization 754.4.2 Quantifying qualitative information 764.4.3 Deterministic- versus stochastic-model parameterization 764.5 Execute the baseline simulation (IIe) 774.5.1 Baseline simulations for stochastic models 785 Theory III: model evaluation 795.1 Assess the reasonableness of the model structure and the interpretability of functional relationships within the model (IIIa) 815.2 Evaluate the correspondence between model behavior and the expected patterns of model behavior (IIIb) 825.3 Examine the correspondence between model projections and the data from the real system (IIIc) 845.3.1 Quantitative versus qualitative model evaluation 865.4 Determine the sensitivity of model projections to changes in the values of important parameters (IIId) 865.4.1 Interpreting sensitivity analysis within a model evaluation framework 876 Theory IV: model application 896.1 Develop and execute the experimental design for the simulations (IVa) 896.2 Analyze and interpret the simulation results (IVb) 916.3 Communicate the simulation results (IVc) 91Part 3 Modeling practice7 Some common pitfalls 937.1 Phase I pitfalls: the conceptual model 937.2 Phase II pitfalls: the quantitative model 977.3 Phase III pitfalls: model evaluation 1007.4 Phase IV pitfalls: model application 1028 The modeling process in practice 1058.1 Preliminary conceptual model (CM) 1068.1.1 How to begin 1068.1.2 Adding new components to the model 1088.1.3 Describing expected patterns 1088.1.4 Describing the plan of attack 1088.2 Intermediate developmental models (IDMi) 1098.2.1 Evaluate–adjust cycle for each developmental model 1108.2.2 Sensitivity analysis of the last developmental model 1128.3 Final model (FM) 112Part 4 Theory, practice, and common sense9 The common-sense problems revisted 1159.1 Harvesting food for the winter 1159.1.1 The preliminary conceptual model (CM) 1159.1.2 The last (only) intermediate development model (IDMlast) 1169.1.3 The final model (FM) 1179.2 Estimating the probability of population extinction 1179.2.1 The preliminary conceptual model (CM) 1179.2.2 The intermediate development models (IDMi) 1189.2.3 The final model (FM) 1189.3 Managing the Commons 1189.3.1 The preliminary conceptual model (CM) 1189.3.2 The intermediate development models (IDMi) 1209.3.3 The final model (FM) 12110 Reflections 12310.1 The systems approach as a complement to other methods of problem solving 12310.2 Ecological modeling as a problem-solving process 12610.3 Expectations for ecological models 12710.4 A final thought 129References 131Appendix A: Introduction to the ecological modeling literature 133Appendix B: Scientific reports for the examples in Chapter 2 139B.1 Effect of deforestation on rate of food harvest 139B.2 Effect of hurricane frequency on probability of population extinction 141B.3 Effect of stocking rate on forage and animal production 143Index 149

"In addition, it has the advantage that it is draws heavily on the knowledge of one of the world's most experienced ecological modellers, Bill Grant, a former President of the International Society for Ecological Modeling, and an editor of the journal Ecological Modelling." (Biodivers Conserv, 2011) Grant and Swannack are to be commended for their attempt to strip ecological modelling of its complexities and present the bare bones for beginners.... I found the book to be very well written, clear and inclusive of all basic theory for deterministic ecological modelling. The book is admirably concise, which will appeal to many." (Austral Ecology, May 2009)"This is an excellent textbook in population dynamic modeling. The very core of the system approach and system thinking is explained very clearly and in a way that encourages the readers to go modeling." (Ecological Modelling, January 2009)"This book is valuable for its listing of 39 common pitfalls of model development; the 60 citations dividing into four categories of models that can serve as the starting point for most ecological modeling approaches; and the fractal beauty of it all." (CHOICE, January 2009)"A key feature of the book is the use of case studies which are based on straightforward ecological questions with a practical interest." (Environmental Conservation, September 2008)