Population Ecology in Practice (eBook)

Dennis L. Murray, Brett K. Sandercock (Herausgeber)

eBook Download: EPUB

2019
John Wiley & Sons (Verlag)
978-1-119-57462-0 (ISBN)

Infos

A synthesis of contemporary analytical and modeling approaches in population ecology

The book provides an overview of the key analytical approaches that are currently used in demographic, genetic, and spatial analyses in population ecology. The chapters present current problems, introduce advances in analytical methods and models, and demonstrate the applications of quantitative methods to ecological data. The book covers new tools for designing robust field studies; estimation of abundance and demographic rates; matrix population models and analyses of population dynamics; and current approaches for genetic and spatial analysis. Each chapter is illustrated by empirical examples based on real datasets, with a companion website that offers online exercises and examples of computer code in the R statistical software platform. 

• Fills a niche for a book that emphasizes applied aspects of population analysis
• Covers many of the current methods being used to analyse population dynamics and structure
• Illustrates the application of specific analytical methods through worked examples based on real datasets
• Offers readers the opportunity to work through examples or adapt the routines to their own datasets using computer code in the R statistical platform

Population Ecology in Practice is an excellent book for upper-level undergraduate and graduate students taking courses in population ecology or ecological statistics, as well as established researchers needing a desktop reference for contemporary methods used to develop robust population assessments.

DENNIS L. MURRAY, PHD, is Professor of Biology at Trent University and holds the position of Canada Research Chair in Integrative Wildlife Conservation, Bioinformatics, and Ecological Modeling.

BRETT K. SANDERCOCK, PHD, is a Senior Research Scientist in the Department of Terrestrial Ecology at the Norwegian Institute for Nature Research.

Textauszug

Preface

Our motivation as editors for assembling a book on current methods in population ecology arose from our ongoing interactions with graduate students and professionals in the fields of ecology, conservation biology, and wildlife management. Over the past several decades, research in population ecology has developed at a rapid pace, from a largely descriptive field dominated by observation and description, to a mature discipline that emphasizes innovative and robust analyses of ecological patterns and processes. Many recent advances have been driven by persistent knowledge gaps, not the least of which are urgent questions about the key drivers of population dynamics and their ecological relevance in the face of ongoing global environmental change. Increasingly, population ecologists have recognized that key questions in ecology and evolutionary biology must be investigated using the data and analytical methods that allow researchers to make robust inferences about causality. At the same time, advances in satellite or GPS‐based telemetry, noninvasive genetic sampling, automated field photography, and other new technologies have revolutionized our ability to collect new data on the occurrence, abundance, and distributions of rare or elusive organisms under natural conditions. Emerging technologies have opened up new possibilities for data collection, but many have also required development of innovative approaches for data analysis. In some cases, new quantitative approaches have been adopted directly from other fields of research but some types of data have required the development of entirely novel analytical tools. Improvements in the capacity of personal and cloud‐based computing, availability of Program R and other freeware statistical packages, and online resources for learning and troubleshooting new statistical procedures have led to tremendous improvements in the potential capacity for data analysis in population ecology. Developments in population ecology have paralleled improvements in data quality and analysis in genomics, data sciences, and other scientific disciplines. Still, population ecology has been transformed in recent decades so that our current ability to answer longstanding and elusive questions greatly surpasses what could have been imaginable even a short time ago.

Development of new tools for ecological analysis has been exciting to witness but presents a challenge for both new and seasoned ecologists who would like to stay current with available technologies and analytical approaches. During our own formative years as graduate students a few decades ago, the prevailing quantitative methods for data analysis consisted mainly of statistical tests in a frequentist framework that were originally designed for analysis of data from controlled experiments and balanced study designs. Basic tests like analysis of variance and regression were familiar because of their extensive coverage in undergraduate courses, or else they were readily adopted following focused reading or trial and error. Even specialized techniques like population estimation or habitat selection analysis were mostly accessible using off‐the‐shelf analytical approaches. Accordingly, at the time most ecologists were not unduly challenged to conduct data analysis that met contemporary standards. However, ecological systems are rarely governed by factors that conform to controlled conditions, and therefore ecological research rarely yields field data that truly fits standard assumptions of independence, normality, and lack of bias. Moreover, the sheer volume, structure, and complexity of ecological data collected in many field studies preclude standard statistical approaches. New quantitative methods in ecology often deviate substantially from the standard approaches that form the basis of undergraduate training in statistics, and ecologists may be left scrambling to correctly identify and implement an appropriate analytical technique. The correct application of contemporary methods for data analysis is increasingly a prerequisite for publication and for implementation of effective management policy in ecology.

Our edited volume is primarily aimed at graduate students and early career professionals who may be embarking on their first attempt to analyze ecological data using contemporary methods. We aimed to assemble a series of chapters that review the state of knowledge in the core areas of population ecology, and our selection of topics and authors was purposeful to cover the main areas by experts in the field. Our final submissions included 16 manuscripts from 39 contributors working in 8 different countries. Our aim was for every chapter to serve as a stand‐alone assessment for different topics in population ecology, including pros and cons of related quantitative methods, basic assumptions and limitations when deriving inference from a given approach, and some of the potential pitfalls in the application of available techniques. Perhaps unavoidably, the chapters include some bias toward methods that are especially relevant for use with wildlife species and for using data that have been collected through newer monitoring technologies. Nevertheless, many of the general concepts and approaches covered in our contributed chapters have broad relevance to a diversity of research questions and study systems.

The 16 chapters of our book are organized into five sections. The first section begins with two chapters that provide a framework for asking relevant questions in ecology, including how research studies can be best designed to derive robust inference. The second section assembles five chapters covering a variety of analytical approaches in population demography and population time series analysis; these topics normally form the requisite basis of most investigations into population status and trend. The analytical approaches differ in whether they are based on closed or open population models, use encounter histories from marked or unmarked individuals, or control for situations where detection may be perfect or imperfect. The third section highlights population‐level analysis, including newer approaches that use integrative and individual‐based models to understand population drivers and forecast their potential change. The fourth section includes five chapters that address genetic and spatial approaches in population analysis, covering topics like home range and resource selection analysis and species distribution modeling.

This volume is intended to provide an overview for researchers using a variety of analytical tools and platforms. Importantly, the R statistical software platform has been transformative to data analysis in ecology, and to that end the final chapter provides an ecologically focused overview of basic nomenclature and data management using R software. Chapters are supported by a compendium of online exercises in R that provide worked through examples that reinforce topics covered in individual chapters. The intent is for exercises to provide readers with both the necessary background to implement more common analytical approaches, as well as sample code in R that can be adapted to start their own data analysis. All online exercises can be accessed from the publisher's website (www.wiley.com/go/MurrayPopulationEcology).

Our edited book would not have seen the light of day without the significant efforts of a number of people to whom we are indebted. We thank Guillaume Chapron, who began this journey with us and helped start the editorial process of selecting topics for the different chapters and inviting contributors. We thank all of the contributors who contributed their work to this volume for sharing with us a vision for the book, mostly adhering to our editorial requests, peer‐reviewing each other's chapters, and for working hard to improve the quality of their chapters. Working on an edited volume can provide new appreciation of the old adage that a caravan is only as fast as the slowest camel. We thank the contributors for their sustained efforts and commitment, but especially for their patience in graciously accepting delays that arose while two slow camels worked to keep the editorial process on track. Special thanks to all of the external reviewers who provided anonymous reviews of chapters, including the many graduate students who served as test groups for the chapters and the online exercises. The students provided many useful comments that helped calibrate the volume for its intended audience. We also highlight the valuable contribution by Pat Heney, who standardized and tested all the online exercises prior to their release. Likewise, a debt of gratitude is owed to Sam Sonnega for help with indexing the complete volume. The staff at Wiley‐Blackwell, especially Anupama Sreekanth, Kavitha Chandrasekar and Emma Cole, provided valuable assistance in support of our vision for the book. Last, we thank H. Dean Cluff for being an initial source of inspiration and for an exploding can of sardines.

Our hope is that our edited book will contribute to a growing body of literature that guides researchers in the rigorous analysis of ecological data. The current state of our planet, and of the species and ecosystems that have captivated the fascination of population ecologists for decades, are under grave peril. The quantitative methods described in this volume provide a valuable set of tools for addressing some of the current and emerging environmental problems that will command humanity's attention for the foreseeable future. Our book will be a success if it provides a new generation of early career researchers with the necessary tools to tackle some of these problems.

In recognition of the daunting environmental...

Produkt-Details

• Erscheint lt. Verlag: 27.12.2019
• Sprache: englisch
• Themenwelt: Naturwissenschaften ► Biologie ► Ökologie / Naturschutz
• Schlagworte: Bevölkerungsökologie • Biowissenschaften • conservation biology • Demography • Ecological Analysis • ecological statistics • Ecology • Life Sciences • <p>assessment • Movement • Ökologie • Ökologie / Populationen u. Lebensgemeinschaften • Population & Community Ecology • population dynamics • Population Genetics • Quantitative ecology • spatial ecology • Statistics • wildlife management</p>
• ISBN-10: 1-119-57462-5 / 1119574625
• ISBN-13: 978-1-119-57462-0 / 9781119574620