Matthew Russell - Statistics in Natural Resources: Applications with R

To manage our environment sustainably, professionals must understand the quality and quantity of our natural resources. Statistical analysis provides information that supports management decisions and is universally used across scientific disciplines. Statistics in Natural Resources: Applications with R focuses on the application of statistical analyses in the environmental, agricultural, and natural resources disciplines. This is a book well suited for current or aspiring natural resource professionals who are required to analyze data and perform statistical analyses in their daily work. More seasoned professionals that have previously had a course or two in statistics will also find the content familiar. This text can also serve as a bridge between professionals who understand statistics and want to learn how to perform analyses on natural resources data in R.

The primary goal of this book is to learn and apply common statistical methods used in natural resources by using the R programming language. If you dedicate considerable time to this book, you will:

• Develop analytical and visualization skills for investigating the behavior of agricultural and natural resources data.

• Become competent in importing, analyzing, and visualizing complex data sets in the R environment.

• Recode, combine, and restructure data sets for statistical analysis and visualization.

• Appreciate probability concepts as they apply to environmental problems.

• Understand common distributions used in statistical applications and inference.

• Summarize data effectively and efficiently for reporting purposes.

• Learn the tasks required to perform a variety of statistical hypothesis tests and interpret their results.

• Understand which modeling frameworks are appropriate for your data and how to interpret predictions.

• Includes over 130 exercises in R, with solutions available on the book's website.

Matthew Russell is a forest analytics consultant at Arbor Custom Analytics LLC where he uses data to solve natural resources problems. He is the author/co-author of more than 75 peer-reviewed publications focused on applied forestry research. He has conducted extensive research and teaching on topics related to forest modeling and statistics. He regularly offers short courses and workshops on data science and R for natural resources and environmental professionals.

First edition published 2023

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2023 Matthew Russell

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Library of Congress Cataloging-in-Publication Data

Names: Russell, Matthew B. (Computer scientist) author.

Title: Statistics in natural resources: applications with R / Matthew Russell.

Description: 1 Edition. | Boca Raton, FL: CRC Press, 2023. | Includes bibliographical references and index.

Identifiers: LCCN 2022009570 (print) | LCCN 2022009571 (ebook) | ISBN 9781032258782 (hardback) | ISBN 9781032259543 (paperback) | ISBN 9781003285809 (ebook)

Subjects: LCSH: Natural resourcesStatistical methods. | R (Computer program language) | Data mining.

Classification: LCC HC59.3. R87 2023 (print) | LCC HC59.3 (ebook) | DDC 330.01/5195dc23/eng/20220401

LC record available at https://lccn.loc.gov/2022009570

LC ebook record available at https://lccn.loc.gov/2022009571

ISBN: 978-1-032-25878-2 (hbk)

ISBN: 978-1-032-25954-3 (pbk)

ISBN: 978-1-003-28580-9 (ebk)

DOI: 10.1201/9781003285809

Typeset in Latin modern

by KnowledgeWorks Global Ltd.

Publisher's note: This book has been prepared from camera-ready copy provided by the authors.

To natural resources students. Past, present, and future.

The primary goal of this book is to learn and apply common statistical methods used in natural resources by using the R programming language. This book encompasses applied and theoretical techniques commonly used in these disciplines. A key component of the book is learning how to make inference with diverse data sources using R.

To manage our environment sustainably, professionals must understand the quality and quantity of our natural resources. Statistical analysis provides information that supports management decisions and is universally used across scientific disciplines. This book focuses on the application of statistical analyses in the environmental, agricultural, and natural resources disciplines.

could also be included in an introductory statistics class for graduate students that moves at an accelerated pace.

If you dedicate considerable time to this book, you do the following:

• Develop analytical and visualization skills for investigating the behavior of agricultural and natural resources data.

• Become competent in importing, analyzing, and visualizing complex data sets in the R environment.

• Recode, combine, and restructure data sets for statistical analysis and visualization.

• Appreciate probability concepts as they apply to environmental problems.

• Understand common distributions used in statistical applications and inference.

• Summarize data effectively and efficiently for reporting purposes.

• Learn the tasks required to perform a variety of statistical hypothesis tests and interpret their results.

• Understand which modeling frameworks are appropriate for your data and how to interpret predictions.

This book does not cover how natural resources data are collected and/or sampled. For the purposes of learning, we will mostly work with tidy data sets that have been collected by others. Many other texts in the disciplines of environmental sampling and experimental design are available that cover these topics in more depth. You would do well to have one of these courses as a part of your quantitative expertise.

The discipline of data science describe, the field of data science differs from statistics in many ways, but also has some similarities.