{"product_id":"ecological-modeling-isbn-9781405161688","title":"Ecological Modeling","description":"\u003ci\u003eEcological Modeling:A Commonsense Approach to Theory and Practice\u003c\/i\u003e explores how simulation modeling and its new ecological applications can offer solutions to complex natural resource management problems. This is a practical guide for students, teachers, and professional ecologists.  \u003cul\u003e \u003cli\u003eExamines four phases of the modeling process: conceptual model formulation, quantitative model specification, model evaluation, and model use\u003c\/li\u003e \u003cli\u003eProvides useful building blocks for constructing systems simulation models\u003c\/li\u003e \u003cli\u003eIncludes a format for reporting the development and use of simulation models\u003c\/li\u003e \u003cli\u003eOffers an integrated systems perspective for students, faculty, and professionals\u003c\/li\u003e \u003cli\u003eFeatures helpful insights from the author, gained over 30 years of university teaching\u003c\/li\u003e \u003c\/ul\u003e \u003cp\u003e\"I can strongly recommend the book as textbook for all courses in population dynamic modeling particularly when the course is planned for the second or third year of a bachelor study in ecology, environmental science or ecological engineering. It uncovers very clearly for the readers the scientific idea and thinking behind modeling and all the necessary steps in the development of models.\"\u003cbr\u003e \u003ci\u003e\u003cb\u003eEcological Modeling Journal, 2009\u003c\/b\u003e\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003ePreface xi\u003c\/p\u003e \u003cp\u003eAcknowledgments xiii\u003c\/p\u003e \u003cp\u003e\u003cb\u003e1 Introduction \u003c\/b\u003e1\u003c\/p\u003e \u003cp\u003e1.1 Common-sense solutions: three exercises 1\u003c\/p\u003e \u003cp\u003e1.2 Modeling theory 2\u003c\/p\u003e \u003cp\u003e1.3 Modeling practice 2\u003c\/p\u003e \u003cp\u003e1.4 Theory, practice, and common sense 3\u003c\/p\u003e \u003cp\u003e1.5 Intended use of this book 3\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePart 1 Common-sense solutions: three exercises\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e2 Common-sense solutions \u003c\/b\u003e\u003cb\u003e5\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e2.1 Three problems 6\u003c\/p\u003e \u003cp\u003e2.1.1 Harvesting food for the winter 6\u003c\/p\u003e \u003cp\u003e2.1.2 Estimating the probability of population extinction 12\u003c\/p\u003e \u003cp\u003e2.1.3 Managing the Commons 20\u003c\/p\u003e \u003cp\u003e2.2 The systems approach to problem solving 49\u003c\/p\u003e \u003cp\u003e2.2.1 The conceptual model (Phase I) 50\u003c\/p\u003e \u003cp\u003e2.2.2 The quantitative model (Phase II) 51\u003c\/p\u003e \u003cp\u003e2.2.3 Model evaluation (Phase III) 51\u003c\/p\u003e \u003cp\u003e2.2.4 Model application (Phase IV) 51\u003c\/p\u003e \u003cp\u003e2.3 The three problems revisited: the systems approach in theory and practice 51\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePart 2 Modeling theory\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e3 Theory I: the conceptual model \u003c\/b\u003e\u003cb\u003e53\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e3.1 State the model objectives (I\u003csub\u003ea\u003c\/sub\u003e) 54\u003c\/p\u003e \u003cp\u003e3.2 Bound the system-of-interest (I\u003csub\u003eb\u003c\/sub\u003e) 55\u003c\/p\u003e \u003cp\u003e3.3 Categorize the components within the system-of-interest (I\u003csub\u003ec\u003c\/sub\u003e) 57\u003c\/p\u003e \u003cp\u003e3.3.1 State variables 57\u003c\/p\u003e \u003cp\u003e3.3.2 Material transfers 59\u003c\/p\u003e \u003cp\u003e3.3.3 Sources and sinks 61\u003c\/p\u003e \u003cp\u003e3.3.4 Information transfers 61\u003c\/p\u003e \u003cp\u003e3.3.5 Driving variables 62\u003c\/p\u003e \u003cp\u003e3.3.6 Constants 62\u003c\/p\u003e \u003cp\u003e3.3.7 Auxiliary variables 62\u003c\/p\u003e \u003cp\u003e3.4 Identify the relationships among the components that are of interest (I\u003csub\u003ed\u003c\/sub\u003e) 63\u003c\/p\u003e \u003cp\u003e3.4.1 Submodels 63\u003c\/p\u003e \u003cp\u003e3.5 Represent the conceptual model (I\u003csub\u003ee\u003c\/sub\u003e) 65\u003c\/p\u003e \u003cp\u003e3.5.1 Conceptual-model diagrams 65\u003c\/p\u003e \u003cp\u003e3.6 Describe the expected patterns of model behavior (I\u003csub\u003ef\u003c\/sub\u003e) 66\u003c\/p\u003e \u003cp\u003e\u003cb\u003e4 Theory II: the quantitative model \u003c\/b\u003e\u003cb\u003e67\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e4.1 Select the general quantitative structure for the model (II\u003csub\u003ea\u003c\/sub\u003e) 68\u003c\/p\u003e \u003cp\u003e4.2 Choose the basic time unit for the simulations (II\u003csub\u003eb\u003c\/sub\u003e) 72\u003c\/p\u003e \u003cp\u003e4.3 Identify the functional forms of the model equations (II\u003csub\u003ec\u003c\/sub\u003e) 72\u003c\/p\u003e \u003cp\u003e4.3.1 Information on which to base the choice of functional forms 73\u003c\/p\u003e \u003cp\u003e4.3.2 Selecting types of equations to represent the chosen functional forms 73\u003c\/p\u003e \u003cp\u003e4.4 Estimate the parameters of the model equations (II\u003csub\u003ed\u003c\/sub\u003e) 75\u003c\/p\u003e \u003cp\u003e4.4.1 Statistical analyses within the context of simulation model parameterization 75\u003c\/p\u003e \u003cp\u003e4.4.2 Quantifying qualitative information 76\u003c\/p\u003e \u003cp\u003e4.4.3 Deterministic- versus stochastic-model parameterization 76\u003c\/p\u003e \u003cp\u003e4.5 Execute the baseline simulation (II\u003csub\u003ee\u003c\/sub\u003e) 77\u003c\/p\u003e \u003cp\u003e4.5.1 Baseline simulations for stochastic models 78\u003c\/p\u003e \u003cp\u003e\u003cb\u003e5 Theory III: model evaluation \u003c\/b\u003e\u003cb\u003e79\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e5.1 Assess the reasonableness of the model structure and the interpretability of functional relationships within the model (III\u003csub\u003ea\u003c\/sub\u003e) 81\u003c\/p\u003e \u003cp\u003e5.2 Evaluate the correspondence between model behavior and the expected patterns of model behavior (III\u003csub\u003eb\u003c\/sub\u003e) 82\u003c\/p\u003e \u003cp\u003e5.3 Examine the correspondence between model projections and the data from the real system (III\u003csub\u003ec\u003c\/sub\u003e) 84\u003c\/p\u003e \u003cp\u003e5.3.1 Quantitative versus qualitative model evaluation 86\u003c\/p\u003e \u003cp\u003e5.4 Determine the sensitivity of model projections to changes in the values of important parameters (III\u003csub\u003ed\u003c\/sub\u003e) 86\u003c\/p\u003e \u003cp\u003e5.4.1 Interpreting sensitivity analysis within a model evaluation framework 87\u003c\/p\u003e \u003cp\u003e\u003cb\u003e6 Theory IV: model application \u003c\/b\u003e\u003cb\u003e89\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e6.1 Develop and execute the experimental design for the simulations (IV\u003csub\u003ea\u003c\/sub\u003e) 89\u003c\/p\u003e \u003cp\u003e6.2 Analyze and interpret the simulation results (IV\u003csub\u003eb\u003c\/sub\u003e) 91\u003c\/p\u003e \u003cp\u003e6.3 Communicate the simulation results (IV\u003csub\u003ec\u003c\/sub\u003e) 91\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePart 3 Modeling practice\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e7 Some common pitfalls \u003c\/b\u003e\u003cb\u003e93\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e7.1 Phase I pitfalls: the conceptual model 93\u003c\/p\u003e \u003cp\u003e7.2 Phase II pitfalls: the quantitative model 97\u003c\/p\u003e \u003cp\u003e7.3 Phase III pitfalls: model evaluation 100\u003c\/p\u003e \u003cp\u003e7.4 Phase IV pitfalls: model application 102\u003c\/p\u003e \u003cp\u003e\u003cb\u003e8 The modeling process in practice \u003c\/b\u003e\u003cb\u003e105\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e8.1 Preliminary conceptual model (CM) 106\u003c\/p\u003e \u003cp\u003e8.1.1 How to begin 106\u003c\/p\u003e \u003cp\u003e8.1.2 Adding new components to the model 108\u003c\/p\u003e \u003cp\u003e8.1.3 Describing expected patterns 108\u003c\/p\u003e \u003cp\u003e8.1.4 Describing the plan of attack 108\u003c\/p\u003e \u003cp\u003e8.2 Intermediate developmental models (IDM\u003csub\u003ei\u003c\/sub\u003e) 109\u003c\/p\u003e \u003cp\u003e8.2.1 Evaluate–adjust cycle for each developmental model 110\u003c\/p\u003e \u003cp\u003e8.2.2 Sensitivity analysis of the last developmental model 112\u003c\/p\u003e \u003cp\u003e8.3 Final model (FM) 112\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePart 4 Theory, practice, and common sense\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e9 The common-sense problems revisted \u003c\/b\u003e\u003cb\u003e115\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e9.1 Harvesting food for the winter 115\u003c\/p\u003e \u003cp\u003e9.1.1 The preliminary conceptual model (CM) 115\u003c\/p\u003e \u003cp\u003e9.1.2 The last (only) intermediate development model (IDM\u003csub\u003elast\u003c\/sub\u003e) 116\u003c\/p\u003e \u003cp\u003e9.1.3 The final model (FM) 117\u003c\/p\u003e \u003cp\u003e9.2 Estimating the probability of population extinction 117\u003c\/p\u003e \u003cp\u003e9.2.1 The preliminary conceptual model (CM) 117\u003c\/p\u003e \u003cp\u003e9.2.2 The intermediate development models (IDM\u003csub\u003ei\u003c\/sub\u003e) 118\u003c\/p\u003e \u003cp\u003e9.2.3 The final model (FM) 118\u003c\/p\u003e \u003cp\u003e9.3 Managing the Commons 118\u003c\/p\u003e \u003cp\u003e9.3.1 The preliminary conceptual model (CM) 118\u003c\/p\u003e \u003cp\u003e9.3.2 The intermediate development models (IDM\u003csub\u003ei\u003c\/sub\u003e) 120\u003c\/p\u003e \u003cp\u003e9.3.3 The final model (FM) 121\u003c\/p\u003e \u003cp\u003e\u003cb\u003e10 Reflections \u003c\/b\u003e\u003cb\u003e123\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e10.1 The systems approach as a complement to other methods of problem solving 123\u003c\/p\u003e \u003cp\u003e10.2 Ecological modeling as a problem-solving process 126\u003c\/p\u003e \u003cp\u003e10.3 Expectations for ecological models 127\u003c\/p\u003e \u003cp\u003e10.4 A final thought 129\u003c\/p\u003e \u003cp\u003eReferences 131\u003c\/p\u003e \u003cp\u003e\u003cb\u003eAppendix A: Introduction to the ecological modeling literature \u003c\/b\u003e\u003cb\u003e133\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003eAppendix B: Scientific reports for the examples in Chapter 2 \u003c\/b\u003e\u003cb\u003e139\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eB.1 Effect of deforestation on rate of food harvest 139\u003c\/p\u003e \u003cp\u003eB.2 Effect of hurricane frequency on probability of population extinction 141\u003c\/p\u003e \u003cp\u003eB.3 Effect of stocking rate on forage and animal production 143\u003c\/p\u003e \u003cp\u003eIndex 149 \u003c\/p\u003e \"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)  \u003cp\u003e 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.\" (\u003ci\u003eAustral Ecology\u003c\/i\u003e, May 2009)\u003c\/p\u003e  \u003cp\u003e \"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.\" (\u003ci\u003eEcological Modelling\u003c\/i\u003e, January 2009)\u003c\/p\u003e  \u003cp\u003e \"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.\" (\u003ci\u003eCHOICE\u003c\/i\u003e, January 2009)\u003c\/p\u003e  \u003cp\u003e \"A key feature of the book is the use of case studies which are based on straightforward ecological questions with a practical interest.\" (\u003ci\u003eEnvironmental Conservation\u003c\/i\u003e, September 2008)\u003c\/p\u003e  \u003cb\u003eBill Grant\u003c\/b\u003e has taught ecological modeling in the Department of Wildlife and Fisheries Sciences (WFSC) at Texas A\u0026amp;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 \u003ci\u003eEcological Modelling\u003c\/i\u003e since 1997.  \u003cp\u003e\u003cb\u003eTodd Swannack\u003c\/b\u003e also has taught ecological modeling in WFSC at Texas A\u0026amp;M University, and has been modeling the population dynamics of endangered species since 2002.\u003c\/p\u003e  \u003ci\u003eEcological Modeling: A Common-Sense Approach to Theory and Practice\u003c\/i\u003e is a down-to-earth guide for students, teachers, and professional ecologists.  \u003cp\u003eThe text candidly addresses the question \"What do I really need to know to begin building and using ecological models in a responsible manner?\" In addition to providing a common-sense introduction to the basic principles of systems modeling, the authors suggest a practical strategy for dealing with pitfalls commonly encountered during model development. The ties between theory and practice, which beginning modelers often find so elusive, are demystified via the step-by-step development of three models representing ecological systems of increasing complexity.\u003c\/p\u003e \u003cp\u003eThe coauthors infuse the text with complimentary perspectives from the first (Grant) and most recent (Swannack) generations of ecological modelers.\u003c\/p\u003e","brand":"Wiley-Blackwell","offers":[{"title":"Default Title","offer_id":47989099856101,"sku":"NP9781405161688","price":76.95,"currency_code":"USD","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/1842\/7735\/files\/9781405161688.jpg?v=1761782794","url":"https:\/\/k12savings.com\/es\/products\/ecological-modeling-isbn-9781405161688","provider":"K12savings","version":"1.0","type":"link"}