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A Practical Guide to Ecological Modelling

A Practical Guide to Ecological Modelling
Author: Karline Soetaert
Publisher: Springer Science & Business Media
Total Pages: 376
Release: 2008-10-14
Genre: Science
ISBN: 1402086245

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Mathematical modelling is an essential tool in present-day ecological research. Yet for many ecologists it is still problematic to apply modelling in their research. In our experience, the major problem is at the conceptual level: proper understanding of what a model is, how ecological relations can be translated consistently into mathematical equations, how models are solved, steady states calculated and interpreted. Many textbooks jump over these conceptual hurdles to dive into detailed formulations or the mathematics of solution. This book attempts to fill that gap. It introduces essential concepts for mathematical modelling, explains the mathematics behind the methods, and helps readers to implement models and obtain hands-on experience. Throughout the book, emphasis is laid on how to translate ecological questions into interpretable models in a practical way. The book aims to be an introductory textbook at the undergraduate-graduate level, but will also be useful to seduce experienced ecologists into the world of modelling. The range of ecological models treated is wide, from Lotka-Volterra type of principle-seeking models to environmental or ecosystem models, and including matrix models, lattice models and sequential decision models. All chapters contain a concise introduction into the theory, worked-out examples and exercises. All examples are implemented in the open-source package R, thus taking away problems of software availability for use of the book. All code used in the book is available on a dedicated website.


Ecological Modeling

Ecological Modeling
Author: William E. Grant
Publisher: John Wiley & Sons
Total Pages: 178
Release: 2011-08-26
Genre: Science
ISBN: 1444359932

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Ecological Modeling:A Commonsense Approach to Theory and Practice 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. Examines four phases of the modeling process: conceptual model formulation, quantitative model specification, model evaluation, and model use Provides useful building blocks for constructing systems simulation models Includes a format for reporting the development and use of simulation models Offers an integrated systems perspective for students, faculty, and professionals Features helpful insights from the author, gained over 30 years of university teaching "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." Ecological Modeling Journal, 2009


Ecological Models and Data in R

Ecological Models and Data in R
Author: Benjamin M. Bolker
Publisher: Princeton University Press
Total Pages: 408
Release: 2008-07-21
Genre: Computers
ISBN: 0691125228

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Introduction and background; Exploratory data analysis and graphics; Deterministic functions for ecological modeling; Probability and stochastic distributions for ecological modeling; Stochatsic simulation and power analysis; Likelihood and all that; Optimization and all that; Likelihood examples; Standar statistics revisited; Modeling variance; Dynamic models.


A Biologist's Guide to Mathematical Modeling in Ecology and Evolution

A Biologist's Guide to Mathematical Modeling in Ecology and Evolution
Author: Sarah P. Otto
Publisher: Princeton University Press
Total Pages: 745
Release: 2011-09-19
Genre: Science
ISBN: 1400840910

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Thirty years ago, biologists could get by with a rudimentary grasp of mathematics and modeling. Not so today. In seeking to answer fundamental questions about how biological systems function and change over time, the modern biologist is as likely to rely on sophisticated mathematical and computer-based models as traditional fieldwork. In this book, Sarah Otto and Troy Day provide biology students with the tools necessary to both interpret models and to build their own. The book starts at an elementary level of mathematical modeling, assuming that the reader has had high school mathematics and first-year calculus. Otto and Day then gradually build in depth and complexity, from classic models in ecology and evolution to more intricate class-structured and probabilistic models. The authors provide primers with instructive exercises to introduce readers to the more advanced subjects of linear algebra and probability theory. Through examples, they describe how models have been used to understand such topics as the spread of HIV, chaos, the age structure of a country, speciation, and extinction. Ecologists and evolutionary biologists today need enough mathematical training to be able to assess the power and limits of biological models and to develop theories and models themselves. This innovative book will be an indispensable guide to the world of mathematical models for the next generation of biologists. A how-to guide for developing new mathematical models in biology Provides step-by-step recipes for constructing and analyzing models Interesting biological applications Explores classical models in ecology and evolution Questions at the end of every chapter Primers cover important mathematical topics Exercises with answers Appendixes summarize useful rules Labs and advanced material available


Spatial Ecology and Conservation Modeling

Spatial Ecology and Conservation Modeling
Author: Robert Fletcher
Publisher: Springer
Total Pages: 523
Release: 2019-02-15
Genre: Science
ISBN: 3030019896

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This book provides a foundation for modern applied ecology. Much of current ecology research and conservation addresses problems across landscapes and regions, focusing on spatial patterns and processes. This book is aimed at teaching fundamental concepts and focuses on learning-by-doing through the use of examples with the software R. It is intended to provide an entry-level, easily accessible foundation for students and practitioners interested in spatial ecology and conservation.


Ecological Modeling

Ecological Modeling
Author: Hsiao-Hsuan Wang
Publisher: Elsevier
Total Pages: 306
Release: 2019-08-14
Genre: Science
ISBN: 0444641645

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Ecological Modeling: An Introduction to the Art and Science of Modeling Ecological Systems, Volume 31, presents the skills needed to appropriately evaluate and use ecological models. Illustrated throughout with practical examples, the book discusses ecological modeling as both an art and a science, balancing the qualitative (artistic) side, with its foundations in common sense and modeling practice, against the quantitative (scientific) aspects of the modeling process. This book draws on the authors’ extensive experience in both teaching and using these techniques to provide readers with a practical, user-friendly guide that supports and encourages the appropriate, effective use of these tools. Provides readers with a commonsense understanding of the systems perspective and its foundations in general system theory Highlights the importance of a solid understanding of the qualitative aspects of the modeling process Facilitates the ability to appropriately evaluate and use ecological models Supports learning with a variety of simple examples to instill the desire and confidence to embark upon the modeling experience


Climate Change and Terrestrial Ecosystem Modeling

Climate Change and Terrestrial Ecosystem Modeling
Author: Gordon Bonan
Publisher: Cambridge University Press
Total Pages: 459
Release: 2019-02-21
Genre: Mathematics
ISBN: 1107043786

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Provides an essential introduction to modeling terrestrial ecosystems in Earth system models for graduate students and researchers.


Ecological Modeling

Ecological Modeling
Author: Clifford S. Russell
Publisher: Routledge
Total Pages: 248
Release: 2015-09-25
Genre: Nature
ISBN: 1317327160

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This volume, originally published in 1975, grew out of Resources for the Future’s involvement as a consultant to the Marine Ecosystem Analysis programme management within the National Oceanic and Atmospheric Agency. Here, researchers look at the state of the art in aquatic ecological modelling in a resource management context. Although the aim of the research in this volume is specific, the models used can be applied in broader contexts and provide conceptual frameworks for regional residuals-environmental quality management and other ecological modelling. This title is suitable for students interested in Environmental Studies.


Hierarchical Modeling and Inference in Ecology

Hierarchical Modeling and Inference in Ecology
Author: J. Andrew Royle
Publisher: Elsevier
Total Pages: 463
Release: 2008-10-15
Genre: Science
ISBN: 0080559255

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A guide to data collection, modeling and inference strategies for biological survey data using Bayesian and classical statistical methods. This book describes a general and flexible framework for modeling and inference in ecological systems based on hierarchical models, with a strict focus on the use of probability models and parametric inference. Hierarchical models represent a paradigm shift in the application of statistics to ecological inference problems because they combine explicit models of ecological system structure or dynamics with models of how ecological systems are observed. The principles of hierarchical modeling are developed and applied to problems in population, metapopulation, community, and metacommunity systems. The book provides the first synthetic treatment of many recent methodological advances in ecological modeling and unifies disparate methods and procedures. The authors apply principles of hierarchical modeling to ecological problems, including * occurrence or occupancy models for estimating species distribution * abundance models based on many sampling protocols, including distance sampling * capture-recapture models with individual effects * spatial capture-recapture models based on camera trapping and related methods * population and metapopulation dynamic models * models of biodiversity, community structure and dynamics Wide variety of examples involving many taxa (birds, amphibians, mammals, insects, plants) Development of classical, likelihood-based procedures for inference, as well as Bayesian methods of analysis Detailed explanations describing the implementation of hierarchical models using freely available software such as R and WinBUGS Computing support in technical appendices in an online companion web site