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Using R for Modelling and Quantitative Methods in Fisheries has evolved and been adapted from an earlier book by the same author and provides a detailed introduction to analytical methods commonly used by fishery scientists, ecologists, and advanced students using the open-source software R as a programming tool. Some knowledge of R is assumed, as this is a book about using R, but an introduction to the development and working of functions, and how one can explore the contents of R functions and packages, is provided. The example analyses proceed step-by-step using code listed in the book and from the book’s companion R package, MQMF, available from GitHub and the standard archive, CRAN. The examples are designed to be simple to modify so the reader can quickly adapt the methods described to use with their own data. A primary aim of the book is to be a useful resource to natural resource practitioners and students. Featured Chapters: Model Parameter Estimation provides a detailed explanation of the requirements and steps involved in fitting models to data, using R and, mainly, maximum likelihood methods. On Uncertainty uses R to implement bootstrapping, likelihood profiles, asymptotic errors, and Bayesian posteriors to characterize any uncertainty in an analysis. The use of the Monte Carlo Markov Chain methodology is examined in some detail. Surplus Production Models applies all the methods examined in the earlier parts of the book to conducting a stock assessment. This included fitting alternative models to the available data, characterizing the uncertainty in different ways, and projecting the optimum models forward in time as the basis for providing useful management advice.
Quantitative methods and mathematical modelling are of critical importance to fishery science and management but, until now, there has been no book that offers the sharp focus, methodological detail, and practical examples needed by non-specialist fishery scientists and managers, and ecologists. Modelling and Quantitative Methods in Fisheries fills that void. To date, methodology books in fisheries science have been limited to cookbook approach to problems; simple compilations; or expositions in which either too much theory or insufficient methodological detail is given. The text is organized into three sections: an introduction to modelling in fisheries and ecology, a straight methodology section covering a range of methods, and a section focusing on specific fields in fisheries science. This book is timely as it addresses a topic of recent debate in fisheries and ecology, describing and comparing the uses of Least Squares, Maximum Likelihood, and Bayesian quantitative methods. Designed as stand-alone units, each chapter provides examples from both classic and recent literature and comes with dedicated Excel spreadsheets that permit you to delve into every detail of the analysis. All of these spreadsheets serve as active examples, which can easily be modified and customized and can be used as templates for analyzing your own data. The spreadsheets permit you to learn at your own speed and cover the simplest linear regression to the more complex non-linear modelling using maximum likelihood. Data analysis and modelling are best learned by doing and not just by reading. This book illustrates, step by step, the analyses it covers. More detailed in terms of introductory quantitative methods and modelling as applied to fisheries than any other book available, Modelling and Quantitative Methods in Fisheries gives you the advantage by supplying the full details of the analysis so that understanding the material is a matter of following the book.
This book really began in 1980 with our first microcomputer, an Apple II +. The great value of the Apple II + was that we could take the computer programs we had been building on mainframe and mini-computers, and make them available to the many fisheries biologists who also had Apple II + 's. About 6 months after we got our first Apple, John Glaister came through Vancouver and saw what we were doing and realized that his agency (New South Wales State Fisheries) had the same equipment and could run the same programs. John organized a training course in Australia where we showed about 25 Australian fisheries biologists how to use microcomputers to do many standard fisheries analyses. In the process of organizing this and sub sequent courses we developed a series of lecture notes. Over the last 10 years these notes have evolved into the chapters of this book.
A How-To Guide for Conducting Common Fisheries-Related Analyses in R Introductory Fisheries Analyses with R provides detailed instructions on performing basic fisheries stock assessment analyses in the R environment. Accessible to practicing fisheries scientists as well as advanced undergraduate and graduate students, the book demonstrates the flexibility and power of R, offers insight into the reproducibility of script-based analyses, and shows how the use of R leads to more efficient and productive work in fisheries science. The first three chapters present a minimal introduction to the R environment that builds a foundation for the fisheries-specific analyses in the remainder of the book. These chapters help you become familiar with R for basic fisheries analyses and graphics. Subsequent chapters focus on methods to analyze age comparisons, age-length keys, size structure, weight-length relationships, condition, abundance (from capture-recapture and depletion data), mortality rates, individual growth, and the stock-recruit relationship. The fundamental statistical methods of linear regression, analysis of variance (ANOVA), and nonlinear regression are demonstrated within the contexts of these common fisheries analyses. For each analysis, the author completely explains the R functions and provides sufficient background information so that you can confidently implement each method. Web Resource The author’s website at http://derekogle.com/IFAR/ includes the data files and R code for each chapter, enabling you to reproduce the results in the book as well as create your own scripts. The site also offers supplemental code for more advanced analyses and practice exercises for every chapter.
With numerous real-world examples, Modelling and Quantitative Methods in Fisheries, Second Edition provides an introduction to the analytical methods used by fisheries' scientists and ecologists. By following the examples using Excel, readers see the nuts and bolts of how the methods work and better understand the underlying principles. Excel workb
With numerous real-world examples, Modelling and Quantitative Methods in Fisheries, Second Edition provides an introduction to the analytical methods used by fisheries’ scientists and ecologists. By following the examples using Excel, readers see the nuts and bolts of how the methods work and better understand the underlying principles. Excel workbooks are available for download from CRC Press website. In this second edition, the author has revised all chapters and improved a number of the examples. This edition also includes two entirely new chapters: Characterization of Uncertainty covers asymptotic errors and likelihood profiles and develops a generalized Gibbs sampler to run a Markov chain Monte Carlo analysis that can be used to generate Bayesian posteriors Sized-Based Models implements a fully functional size-based stock assessment model using abalone as an example This book continues to cover a broad range of topics related to quantitative methods and modelling. It offers a solid foundation in the skills required for the quantitative study of marine populations. Explaining important and relatively complex ideas and methods in a clear manner, the author presents full, step-by-step derivations of equations as much as possible to enable a thorough understanding of the models and methods.
Biology of Sharks and Their Relatives is an award-winning and groundbreaking exploration of the fundamental elements of the taxonomy, systematics, physiology, and ecology of sharks, skates, rays, and chimera. This edition presents current research as well as traditional models, to provide future researchers with solid historical foundations in shark research as well as presenting current trends from which to develop new frontiers in their own work. Traditional areas of study such as age and growth, reproduction, taxonomy and systematics, sensory biology, and ecology are updated with contemporary research that incorporates emerging techniques including molecular genetics, exploratory techniques in artificial insemination, and the rapidly expanding fields of satellite tracking, remote sensing, accelerometry, and imaging. With two new editors and 90 contributors from the US, UK, South Africa, Portugal, France, Canada, New Zealand, Australia, India, Palau, United Arab Emirates, Micronesia, Sweden, Argentina, Indonesia, Cameroon, and the Netherlands, this third edition is the most global and comprehensive yet. It adds six new chapters representing extensive studies of health, stress, disease and pathology, and social structure, and continues to explore elasmobranch ecological roles and interactions with their habitats. The book concludes with a comprehensive review of conservation policies, management, and strategies, as well as consideration of the potential effects of impending climate change. Presenting cohesive and integrated coverage of key topics and discussing technological advances used in modern shark research, this revised edition offers a well-rounded picture for students and researchers.
A key goal of fisheries management is to regulate extractive pressure on a resource so as to ensure social, economic and ecological sustainability. This text provides an accessible entry point for students and professionals to management science as developed in fisheries, in order to facilitate uptake of the latest ideas and methods. Traditional management approaches have relied upon a stock assessment based on existing understanding of resource status and dynamics, and a prediction of the likely future response to a static management proposal. However all such predictions include an inherent degree of uncertainty, and the last few decades have seen the emergence of an adaptive approach that uses feedback control to account for unknown future behaviour. Feedback is achieved via a control rule, which defines a relationship between perceived status of the resource and a management action. Evaluations of such rules usually include computer simulation testing across a broad range of uncertainties, so that an appropriate and robust rule can be selected by stakeholders and managers. The book focuses on this approach, which is usually referred to as Management Strategy Evaluation. The book is enriched by case study examples from different parts of the world, as well as insights into the theory and practice from those actively involved in the science of fisheries management.
The fields of fish population dynamics and stock assessment have seen major advances in the 1980s and 1990s, creating the need for a new synthesis. This text attempts that synthesis by presenting a contemporary approach for quantitative fisheries science that incorporates modern statistical and mathematical techniques. It emphasizes the link between biology and theory by explaining the assumptions inherent in the quantitative methods and models. The book covers key topics that are often overlooked in other texts, such as optimal harvesting, migratory stocks, and complex age and size-structured models. Quantitative Fish Dynamics is an ideal textbook for graduate and undergraduate courses in fish population dynamics and stock assessment. It is an indispensable reference work for fisheries scientists and others interested in conservation biology, fish and wildlife management, population ecology, and statistical applications.
The second edition of a bestselling textbook, Using R for Introductory Statistics guides students through the basics of R, helping them overcome the sometimes steep learning curve. The author does this by breaking the material down into small, task-oriented steps. The second edition maintains the features that made the first edition so popular, while updating data, examples, and changes to R in line with the current version. See What’s New in the Second Edition: Increased emphasis on more idiomatic R provides a grounding in the functionality of base R. Discussions of the use of RStudio helps new R users avoid as many pitfalls as possible. Use of knitr package makes code easier to read and therefore easier to reason about. Additional information on computer-intensive approaches motivates the traditional approach. Updated examples and data make the information current and topical. The book has an accompanying package, UsingR, available from CRAN, R’s repository of user-contributed packages. The package contains the data sets mentioned in the text (data(package="UsingR")), answers to selected problems (answers()), a few demonstrations (demo()), the errata (errata()), and sample code from the text. The topics of this text line up closely with traditional teaching progression; however, the book also highlights computer-intensive approaches to motivate the more traditional approach. The authors emphasize realistic data and examples and rely on visualization techniques to gather insight. They introduce statistics and R seamlessly, giving students the tools they need to use R and the information they need to navigate the sometimes complex world of statistical computing.