Landscape Genetics

Concepts, Methods, Applications

Niko Balkenhol, Samuel Cushman, Andrew Storfer, Lisette Waits

• Publisher: Wiley-Blackwell
• Year: 2015
• ISBN:
  9781118525234
• Edition: 1
• Topic: Biological Sciences
• Subtopic: Ecology
• Index: Biological Sciences

LANDSCAPE GENETICS: CONCEPTS, METHODS, APPLICATIONS

LANDSCAPE GENETICS: CONCEPTS, METHODS, APPLICATIONS

Edited by Niko Balkenhol, Samuel A. Cushman, Andrew T. Storfer, Lisette P. Waits

Landscape genetics is an exciting and rapidly growing field, melding methods and theory from landscape ecology and population genetics to address some of the most challenging and urgent ecological and evolutionary topics of our time. Landscape genetic approaches now enable researchers to study in detail how environmental complexity in space and time affect gene flow, genetic drift, and local adaptation. However, learning about the concepts and methods underlying the field remains challenging due to the highly interdisciplinary nature of the field, which relies on topics that have traditionally been treated separately in classes and textbooks.

In this edited volume, some of the leading experts in landscape genetics provide the first comprehensive introduction to underlying concepts, commonly used methods, and current and future applications of landscape genetics. Consistent with the interdisciplinary nature of the field, the book includes textbook-like chapters that synthesize fundamental concepts and methods underlying landscape genetics (Part 1), chapters on advanced topics that deserve a more in-depth treatment (Part 2), and chapters illustrating the use of concepts and methods in empirical applications (Part 3).

Aimed at beginning landscape geneticists and experienced researchers alike, this book will be helpful for all scientists and practitioners interested in learning, teaching, and applying landscape genetics.

Chapter 1
Introduction To Landscape Genetics – Concepts, Methods, Applications

NikoBalkenhol¹, Samuel A.Cushman², AndrewStorfer³ and Lisette P.Waits⁴

¹Department of Wildlife Sciences, University of Göttingen, Germany

²Forest and Woodlands Ecosystems Program, Rocky Mountain Research Station, United States Forest Service, USA

³School of Biological Sciences, Washington State University, USA

⁴Fish and Wildlife Sciences, University of Idaho, USA

1.1 Introduction

Genetic variation is considered the most basic level of biological diversity and a prerequisite for the variability of species, populations, and ecosystems (Primack 2014). Diversity at the genetic level is also crucial for the fitness and survival of individuals, the viability of populations, and the ability of species to adapt to environmental change (Allendorf et al. 2012; Frankham et al. 2010). Thus, conserving genetic diversity is important in itself, and researchers in many disciplines, including ecology, evolution, and conservation, are interested in understanding the factors that shape patterns of genetic variation in nature. The foundations for understanding genetic diversity were laid more than 100 years ago (e.g., Hardy 1908; Weinberg 1908; Wright 1917), at which time time, laboratory techniques did not yet allow the actual quantification of genes or DNA (deoxyribonucleic acid, see Chapter 3). Consequently, much of the early work of population geneticists was theoretical and conceptual. This changed after the discovery of the structure of DNA in 1953 by Francis Crick, James Watson, and Maurice Wilkins, and even more so after the development of PCR (polymerase chain reaction) by Kary Mullis in 1983. PCR made it possible to obtain large quantities of DNA even from minuscule samples, and the technique revolutionized many research disciplines, including medicine, forensics, genetic engineering, and population genetics.

Due to these technological advancements, genetic data also became more readily available to ecologists and conservationists, who increasingly realized the tremendous impact of human activities on biological diversity. In the 1970s and 1980s, genetic factors were recognized to be of fundamental importance for successful conservation strategies (e.g., Frankel 1970, 1974) and genetic diversity was explicitly considered in two of the earliest books on conservation biology (Soulé & Wilcox 1980; Frankel & Soulé 1981). Furthermore, human-caused loss and fragmentation of habitats were determined to be major drivers (e.g., Wilcove et al. 1986) and the ability to move among remaining habitat patches was identified as a key for the long-term conservation of populations and species in fragmented landscapes (e.g., Levins 1969; Hanski 1998). The consequences of changing environments also became a central topic of landscape ecology, which emerged as a scientific discipline in the 1980s (e.g., Naveh & Lieberman 1984; Forman & Godron 1986). Given these almost simultaneous developments in several research areas, it is not surprising that scientists began to combine concepts and methods from population genetics and landscape ecology to assess the influence of environmental heterogeneity on gene flow and genetic diversity (e.g., Pamilo 1988; Merriam et al. 1989; Manicacci et al. 1992; Gaines et al. 1997). Nevertheless, “landscape genetics” did not exist as a research area until it was formally defined in a seminal paper by Manel et al. (2003). This paper stimulated a tremendous interest in the scientific community, so that many novel methods for analyzing landscape genetic data were introduced (e.g., Guillot et al. 2005; Murphy et al. 2008) and the number of published landscape genetic studies grew quickly (reviewed in Holderegger & Wagner 2006; Storfer et al. 2010). Just ten years after its first formal definition, landscape genetics had already contributed substantially to research in ecology, evolution, and conservation (see Manel & Holderegger 2013). Currently, landscape genetics still presents itself as a highly dynamic and rapidly advancing field. New methods are frequently suggested and novel research questions are identified as a result of both conceptual and technological improvements. The rapid growth of landscape genetics is both exciting and motivating, but it is also accompanied by tremendous challenges.

In this introductory chapter, we highlight some of these challenges and explain the rationale for this book and its particular structure. Before doing so, we provide a definition of what we feel constitutes landscape genetics. Furthermore, we provide a simple conceptual framework for landscape genetic analyses, which can be particularly useful for the novice landscape geneticist.

1.2 Defining Landscape Genetics

Most readers of this book will already know that landscape genetics combines landscape ecology and population genetics. This is certainly correct, but is also not very specific or precise. To better understand landscape genetics, it is worthwhile to define the field more clearly. Three commonly used definitions of landscape genetics are shown in Table 1.1.

Table 1.1 Overview of definitions of landscape genetics.

Reference	Definition of landscape genetics^*	Analytical consequence
Manel et al. (2003), page 189	[Landscape genetics…] aims to provide information about the interaction between landscape features and microevolutionary processes, such as gene flow, genetic drift and selection.	Need to quantify mircoevolutionary processes
Holderegger and Wagner (2006), page 793	[…] landscape genetics endorses those studies that combine population genetic data, adaptive or neutral, with data on landscape composition and configuration, including matrix quality.	Need to quantify landscape heterogeneity
Storfer et al. (2007), page 131	[…] research that explicitly quantifies the effects of landscape composition, configuration and [or] matrix quality on gene flow and [or] spatial variation.	Need to explicitly test for landscape-genetic relationships
*Bold emphases are ours.

In the original definition of Manel et al. (2003) the focus was on “microrevolutionary processes”, which can be measured using genetic data. Thus, the emphasis of this definition lies on the population genetic aspects of landscape genetics, but was not very specific about the ‘landscape features’ to be included in the analyses. The definition was extended by Holderegger and Wagner (2006) who clarified that landscape heterogeneity can be measured in terms of landscape composition, configuration and/or matrix quality (see Chapter 2 for explanations of these terms). Holderegger and Wagner (2006) also noted that landscape genetics can be conducted using different types of genetic data and that appropriate analyses and correct inferences depend strongly on whether the data is adaptive (i.e., under selection) or not (i.e., neutral; see also Holderegger et al. 2006). Finally, Storfer et al. (2007) highlighted that landscape genetics needs to quantitatively link landscape and genetic data to explicitly test for landscape-genetic relationships. This aspect is particularly important, because it allows landscape genetics to move beyond descriptive studies that visually assess spatially coinciding patterns in genetic and landscape data, towards quantitative models that make it possible to predict the genetic consequences of environmental change (e.g., Jay et al. 2012, Wasserman et al. 2012).

Putting these three definitions together, we can define landscape genetics as research that combines population genetics, landscape ecology, and spatial analytical techniques to explicitly quantify the effects of landscape composition, configuration, and matrix quality on microevolutionary processes, such as gene flow, drift, and selection, using neutral and adaptive genetic data.

1.3 The Three Analytical Steps of Landscape Genetics

The definitions provided above lead to a simple conceptual framework for landscape genetic data analysis. Specifically, three general steps are necessary to reach the goals of landscape genetics (see last column in Table 1.1). First, we have to measure genetic variation so that we can quantify the miroevolutionary processes we are interested in. This step relies heavily on population genetic approaches and involves the description of the genetic composition of individuals or populations sampled across space – see Chapters 3, 7, and 9 for details.

Second, we have to quantify landscape heterogeneity so that we can capture the composition, configuration, and/or matrix quality of the study landscape – see Chapters 2 and 8. Third, we have to statistically link landscape heterogeneity and genetic variation, so that we can explicitly and quantitativel...

Table of contents

• Cover
• Title Page
• Copyright
• List of Contributors
• Website
• Acknowledgments
• Glossary
• Chapter 1: Introduction To Landscape Genetics – Concepts, Methods, Applications
• Part 1: Concepts
• Part 2: Methods
• Part 3: Applications
• Index
• End User License Agreement