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A Practical Guide to Ecological Modelling

A Practical Guide to Ecological Modelling PDF Author: Karline Soetaert
Publisher: Springer Science & Business Media
ISBN: 1402086245
Category : Science
Languages : en
Pages : 372

Book Description
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.

A Practical Guide to Ecological Modelling

A Practical Guide to Ecological Modelling PDF Author: Karline Soetaert
Publisher: Springer Science & Business Media
ISBN: 1402086245
Category : Science
Languages : en
Pages : 372

Book Description
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 Models and Data in R

Ecological Models and Data in R PDF Author: Benjamin M. Bolker
Publisher: Princeton University Press
ISBN: 0691125228
Category : Computers
Languages : en
Pages : 408

Book Description
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.

Ecological Modeling

Ecological Modeling PDF Author: William E. Grant
Publisher: John Wiley & Sons
ISBN: 1444359932
Category : Science
Languages : en
Pages : 178

Book Description
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

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

A Biologist's Guide to Mathematical Modeling in Ecology and Evolution PDF Author: Sarah P. Otto
Publisher: Princeton University Press
ISBN: 1400840910
Category : Science
Languages : en
Pages : 745

Book Description
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

Ecological Modelling and Ecophysics

Ecological Modelling and Ecophysics PDF Author: FORT
Publisher: IOP Publishing Limited
ISBN: 9780750324304
Category : Ecology
Languages : en
Pages : 300

Book Description
This book focuses on use-inspired basic science by connecting theoretical methods and mathematical developments in ecology with practical real-world problems, either in production or conservation. The text aims to increase the reader's confidence to rely on partial aspects and relations of systems to which we only have an incomplete understanding. By abstracting and simplifying problems, Ecological Modelling and Ecophysics seeks to expand the reader's understanding and ability to solve practical issues with rigorous quantitative methods. The first part of this book is devoted to classical methods in population and community ecology. The second part aims to introduce the reader to certain tools and techniques from different branches of physics, such as thermodynamics, statistical mechanics and complex systems, and their applications in ecology and environmental sciences. Connecting ecological problems with well-studied phenomena in physics allows the exploiting of analogies to gain deeper insight into these problems, to identify novel questions and problems, and to get access to alternative quantitative methods and tools from physics. This is an essential text for quantitative ecologists and environmental scientists with an interest in novel mathematical approaches, and also applied physicists and mathematicians with an interest in ecological systems. Key Features Focuses on the practical applications of quantitative ecological models Practical challenges are drawn from agriculture and environmental science Applies methods and theories from physics to gain deeper insight into ecological challenges Covers key quantitative models in ecology including niche theory, mutualism, and game theory Will be of interest to environmental scientists and biophysicists as well as ecologists

Modelling Complex Ecological Dynamics

Modelling Complex Ecological Dynamics PDF Author: Fred Jopp
Publisher: Springer Science & Business Media
ISBN: 3642050298
Category : Science
Languages : en
Pages : 397

Book Description
Model development is of vital importance for understanding and management of ecological processes. Identifying the complex relationships between ecological patterns and processes is a crucial task. Ecological modelling—both qualitatively and quantitatively—plays a vital role in analysing ecological phenomena and for ecological theory. This textbook provides a unique overview of modelling approaches. Representing the state-of-the-art in modern ecology, it shows how to construct and work with various different model types. It introduces the background of each approach and its application in ecology. Differential equations, matrix approaches, individual-based models and many other relevant modelling techniques are explained and demonstrated with their use. The authors provide links to software tools and course materials. With chapters written by leading specialists, “Modelling Complex Ecological Dynamics” is an essential contribution to expand the qualification of students, teachers and scientists alike.

Climate Change and Terrestrial Ecosystem Modeling

Climate Change and Terrestrial Ecosystem Modeling PDF Author: Gordon Bonan
Publisher: Cambridge University Press
ISBN: 1107043786
Category : Mathematics
Languages : en
Pages : 459

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

Systems Science and Modeling for Ecological Economics

Systems Science and Modeling for Ecological Economics PDF Author: Alexey A. Voinov
Publisher: Academic Press
ISBN: 9780080886176
Category : Science
Languages : en
Pages : 432

Book Description
Modeling is a key component to sciences from mathematics to life science, including environmental and ecological studies. By looking at the underlying concepts of the software, we can make sure that we build mathematically feasible models and that we get the most out of the data and information that we have. Systems Science and Modeling for Ecological Economics shows how models can be analyzed using simple math and software to generate meaningful qualitative descriptions of system dynamics. This book shows that even without a full analytical, mathematically rigorous analysis of the equations, there may be ways to derive some qualitative understanding of the general behavior of a system. By relating some of the modeling approaches and systems theory to real-world examples the book illustrates how these approaches can help understand concepts such as sustainability, peak oil, adaptive management, optimal harvest and other practical applications. Relates modeling approaches and systems theory to real-world examples Teaches students to build mathematically feasible models and get the most out of the data and information available Wide range of applications in hydrology, population dynamics, market cycles, sustainability theory, management, and more

Ecological Modeling in Risk Assessment

Ecological Modeling in Risk Assessment PDF Author: Robert A. Pastorok
Publisher: CRC Press
ISBN: 1420032321
Category : Technology & Engineering
Languages : en
Pages : 328

Book Description
Toxic chemicals can exert effects on all levels of the biological hierarchy, from cells to organs to organisms to populations to entire ecosystems. However, most risk assessment models express their results in terms of effects on individual organisms, without corresponding information on how populations, groups of species, or whole ecosystems may respond to chemical stressors. Ecological Modeling in Risk Assessment: Chemical Effects on Populations, Ecosystems, and Landscapes takes a new approach by compiling and evaluating models that can be used in assessing risk at the population, ecosystem, and landscape levels. The authors give an overview of the current process of ecological risk assessment for toxic chemicals and of how modeling of populations, ecosystems, and landscapes could improve the status quo. They present a classification of ecological models and explain the differences between population, ecosystem, landscape, and toxicity-extrapolation models. The authors describe the model evaluation process and define evaluation criteria. Finally, the results of the model evaluations are presented in a concise format with recommendations on modeling approaches to use now and develop further. The authors present and evaluate various models on the basis of their realism and complexity, prediction of relevant assessment endpoints, treatment of uncertainty, regulatory acceptance, resource efficiency, and other criteria. They provide models that will improve the ecological relevance of risk assessments and make data collection more cost-effective. Ecological Modeling in Risk Assessment serves as a reference for selecting and applying the best models when performing a risk assessment.

Hierarchical Modeling and Inference in Ecology

Hierarchical Modeling and Inference in Ecology PDF Author: J. Andrew Royle
Publisher: Elsevier
ISBN: 0080559255
Category : Science
Languages : en
Pages : 464

Book Description
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