Table of Contents
List of Contributors ix
Website xi
Acknowledgments xiii
Glossary xv
1 Introduction to Landscape Genetics – Concepts Methods Applications 1 Niko Balkenhol Samuel A. Cushman Andrew Storfer and Lisette P. Waits
1.1 Introduction 1
1.2 Defining landscape genetics 2
1.3 The three analytical steps of landscape genetics 3
1.4 The interdisciplinary challenge of landscape genetics 3
1.5 Structure of this book – concepts methods applications 5
References 6
Part 1: Concepts 2 Basics of Landscape Ecology: An Introduction to Landscapes and Population Processes for Landscape Geneticists 11 Samuel A. Cushman Brad H. McRae and Kevin McGarigal
2.1 Introduction 11
2.2 How landscapes affect population genetic processes 12
2.3 Defining the landscape for landscape genetic research 16
2.4 Defining populations and characterizing dispersal processes 21
2.5 Putting it together: combinations of landscape and population models 24
2.6 Frameworks for delineating landscapes and populations for landscape genetics 26
2.7 Current challenges and future opportunities 30
References 30
3 Basics of Population Genetics: Quantifying Neutral and Adaptive Genetic Variation for Landscape Genetic Studies 35 Lisette P. Waits and Andrew Storfer
3.1 Introduction 35
3.2 Overview of landscape influences on genetic variation 36
3.3 Overview of DNA types and molecular methods 38
3.4 Important population genetic models 41
3.5 Measuring genetic diversity 45
3.6 Evaluating genetic structure and detecting barriers 46
3.7 Estimating gene flow using indirect and direct methods 50
3.8 Conclusion and future directions 52
References 53
4 Basics of Study Design: Sampling Landscape Heterogeneity and Genetic Variation for Landscape Genetic Studies 58 Niko Balkenhol and Marie-Josée Fortin
4.1 Introduction 58
4.2 Study design terminology used in this Chapter 59
4.3 General study design considerations 60
4.4 Considerations for landscape genetic study design 61
4.5 Current knowledge about study design effects in landscape genetics 66
4.6 Recommendations for optimal sampling strategies in landscape genetics 71
4.7 Conclusions and future directions 73
References 74
5 Basics of Spatial Data Analysis: Linking Landscape and Genetic Data for Landscape Genetic Studies 77 Helene H. Wagner and Marie-Josée Fortin
5.1 Introduction 77
5.2 How to model landscape effects on genetic variation 84
5.3 How to model isolation-by-distance 93
5.4 Future directions 95
Acknowledgments 96
References 96
Part 2: Methods 6 Simulation Modeling in Landscape Genetics 101 Erin Landguth Samuel A. Cushman and Niko Balkenhol
6.1 Introduction 101
6.2 A brief overview of models and simulations 101
6.3 General benefits of simulation modeling 102
6.4 Landscape genetic simulation modeling 103
6.5 Examples of simulation modeling in landscape genetics 104
6.6 Designing and choosing landscape genetic simulation models 108
6.7 The future of landscape genetic simulation modeling 111
References 111
7 Clustering and Assignment Methods In Landscape Genetics 114 Olivier François and Lisette P. Waits
7.1 Introduction 114
7.2 Exploratory data analysis and model-based clustering for population structure analysis 115
7.3 Spatially explicit methods in landscape genetics 119
7.4 Spatial EDA methods: spatial PCA and spatial factor analysis 119
7.5 Spatial MBC methods 120
7.6 Habitat and environmental heterogeneity models 121
7.7 Discussion 123
References 125
8 Resistance Surface Modeling in Landscape Genetics 129 Stephen F. Spear Samuel A. Cushman and Brad H. McRae
8.1 Introduction 129
8.2 Techniques for parameterizing resistance surfaces 133
8.3 Estimating connectivity from resistance surfaces 137
8.4 Statistical validation of resistance surfaces 139
8.5 The future of the resistance surface in landscape genetics 142
8.6 Conclusions 144
References 144
9 Genomic Approaches in Landscape Genetics 149 Andrew Storfer Michael F. Antolin Stéphanie Manel Bryan K. Epperson and Kim T. Scribner
9.1 Introduction 149
9.2 Current landscape genomics methods 150
9.3 General challenges in landscape genomics 157
9.4 Spatial autocorrelation 157
9.5 Applications of landscape genomics to climate change 159
References 160
10 Graph Theory and Network Models In Landscape Genetics 165 Melanie Murphy Rodney Dyer and Samuel A. Cushman
10.1 Introduction 165
10.2 Background on graph theory 167
10.3 Landscape genetic applications 170
10.4 Recommendations for using graph approaches in landscape genetics 175
10.5 Current research needs 176
10.6 Conclusion – potential for application of graphs for conservation 176
References 177
Part 3: Applications 11 Landscapes and Plant Population Genetics 183 Rodney J. Dyer
11.1 Introduction 183
11.2 Contemporary population genetic processes 186
11.3 Historical population genetic processes 190
11.4 Future research 192
References 194
12 Applications of Landscape Genetics to Connectivity Research In Terrestrial Animals 199 Lisette P. Waits Samuel A. Cushman and Steve F. Spear
12.1 Introduction 199
12.2 General overview of terrestrial animal study systems and research challenges 199
12.3 Detecting barriers and defining corridors 202
12.4 Evaluating population dynamics 205
12.5 Detecting and predicting the response to landscape change 206
12.6 Common limitations of landscape genetic studies involving terrestrial animals 208
12.7 Testing ecological hypotheses about gene flow in heterogeneous landscapes 208
12.8 Knowledge gaps and future directions 213
References 214
13 Waterscape Genetics – Applications of Landscape Genetics To Rivers Lakes and Seas 220 Kimberly A. Selkoe Kim T. Scribner and Heather M. Galindo
13.1 Introduction 220
13.2 Understanding marine and freshwater environments 223
13.3 Typical research questions and approaches 229
13.4 Applications of landscape genetic approaches 234
13.5 Future directions: knowledge gaps research challenges and limitations 237
Acknowledgments 238
References 238
14 Current Status Future Opportunities and Remaining Challenges in Landscape Genetics 247 Niko Balkenhol Samuel A. Cushman Lisette P. Waits and Andrew Storfer
14.1 Introduction 247
14.2 Conclusion 1: issues of scale need to be considered 248
14.3 Conclusion 2: sampling needs to specifically target landscape genetic questions 248
14.4 Conclusion 3: choice of appropriate statistical methods remains challenging 249
14.5 Conclusion 4: simulations play a key role in landscape genetics 249
14.6 Conclusion 5: measures of genetic variation are rarely developed specifically for landscape genetics 249
14.7 Conclusion 6: landscape resistance is just one of the possible landscape–genetic relationships 250
14.8 Conclusion 7: genomics provides novel opportunities but also creates new challenges 250
14.9 Conclusion 8: the scope of landscape genetics needs to expand 251
14.10 Conclusion 9: specific hypotheses are rarely stated in current landscape genetic studies 251
14.11 Conclusion 10: a comprehensive theory for landscape genetics is currently missing 252
14.12 The future of landscape genetics 252
References 253
Index 257
