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  • Dissertation by Jan O. Engler

    From occurrence to

    Assessing connectivity in a changing world through modelling and landscape genetics

    eco-evolutionary dynamics

  • FROM OCCURRENCE TO ECO-EVOLUTIONARYDYNAMICS: ASSESSING CONNECTIVITY IN A

    CHANGING WORLD THROUGH MODELING AND

    LANDSCAPE GENETICS

    Dissertation

    zur Erlangung des Doktorgrades (Dr. rer. nat.)

    der

    Mathematisch-Naturwissenschaftlichen Fakultt

    der

    Rheinischen Friedrich-Wilhelms-Universitt Bonn

    vorgelegt von

    Jan Oliver Engler

    aus

    Oberhausen

    Bonn, November 2015

  • THESIS COMMITTEE Prof. Dr. J. WOLFGANG WGELE (Erstgutachter)Director ZFMK Zoological Research Museum Alexander Koenig

    Prof. Dr. BERNHARD MISOF (Zweitgutachter)Director ZMB Zoological Research Museum Alexander Koenig

    Prof. Dr. NIKO BALKENHOL (Fachnahes Mitglied)Head of Department of Wildlife Sciences Bsgen Institut, University of Gttingen

    Prof. Dr. GABRIELE M. KNIG (Fachfernes Mitglied)Professor of Pharmaceutical Biology Institute of Pharmaceutical Biology, University of Bonn

  • Angefertigt mit Genemigung der Mathematisch-Naturwissenschaftlichen Fakultt der Rheinischen Friedrich-Wilhelms-Universitt Bonn.

    Die Arbeit wurde am Zoologischen Forschungsmuseum Alexander Koenig in Bonn durchgefhrt

    Tag der mndlichen Prfung: 25.05.2016

  • Erklrung

    Hiermit versichere ich, Jan O. Engler, dass ich diese Arbeit selbstndig verfasst, keine

    anderen Quellen und Hilfsmittel als die angegebenen verwendet, und die Stellen der Arbeit,

    die anderen Werken dem Wortlaut oder dem Sinn nach entnommen sind, unter Angabe der

    Quelle kenntlich gemacht habe. Ich versichere auerdem, dass ich die beigefgte Dissertation

    nur in diesem und keinem anderen Promotionsverfahren eingereicht habe und, dass diesem

    Promotionsverfahren keine endgltig gescheiterten Promotionsverfahren vorausgegangen

    sind.

    Bonn, den 18.11.2015

  • Jan O. Engler

    From occurrence to eco-evolutionary dynamics: assessing connectivity in a changing world through modeling and landscape genetics

    Date of defense: 25.05.2016

    Thesis, University of Bonn, Bonn, Germany (2016)

    With references, with summaries in Englisch and German

  • Contents

    List of Figures

    List of Tables

    Aims & Scope 1

    Chapter 1: General Introduction 7

    What is connectivity? 9

    Connectivity in Conservation and Environmental Planning 11

    Connectivity in Landscape Genetics 13

    Chapter 2: Conception of Potential Connectivity Models 17

    Environmental Information 19

    Occurrence Information 21

    The SDM 21

    The Connectivity Model 23

    Linking genetic information with PCMs 23

    PART A PCMS IN CONSERVATION & ENVIRONMENTALPLANNING 27

    Chapter 3: Accounting for the network in the Natura 2000 network: A response to Hochkirch et al. 2013 29

    Commentary 31

    Chapter 4: Missing the target? A critical view on butterfly conservation efforts on calcareous grasslands in south-western Germany 35

  • Introduction 37

    Material and methods 39 Study sites 39

    Field sampling design 41

    Classification of butterfly species 42

    Statistical analysis 45

    Resistance surface modeling 46

    Results 49 Species decline 49

    Degradation of functional groups 50

    Changes in relative trait diversity 51

    Connectivity modeling 52

    Discussion 53

    Chapter 5: Coupling satellite data with species distribution and connectivity models as a tool for environmental management and planning in matrix-sensitive species 59

    Introduction 61

    Material and methods 65 Study area and data sampling 65

    Satellite data 67

    Potential Connectivity Model 68

    Results 72 Estimated condition status of Colognes sand lizard populations basedon field

    observations 72

    Distribution of potential habitats 72

    Predicted connectivity between populations 73

    Discussion 74 Applicability of the approach 74

    Data requirements and limitation for further applications 78

    Conclusion 79

  • PART B PCMS IN LANDSCAPE GENETICS 83

    Chapter 6: Comparative landscape genetics of three closely related sympatric Hesperid butterflies with diverging ecological traits 85

    Introduction 87

    Material and methods 89 Ethics statement 89

    Study area and species 89

    Molecular data and genetic cluster analysis 90

    Modelling landscape effects on genetic differentiation 92

    Comparing connectivity estimates with genetic data 95

    Results 96 Genetic structures 96

    Genetic clustering results 97

    Species Distribution Models 97

    Landscape effects of genetic differentiation 98

    Discussion 102 Diverging responses to identical landscape conditions 103

    Accounting for FST and Dest in landscape genetic studies 106

    Conclusion 107

    Supplementary material 109

    Chapter 7: A statistical learning approach to improve ecological inferences in landscape genetics by accounting for spatial nonstationarity of genetic differentiation 117

    Introduction 119

    Material and methods 122 The statistical learning approach 122

    Empirical examples 123

    Results 125

    Discussion 126

  • Supplementary material 131

    PART C IMPROVING SDMS USING CONTEMPORARY GENETIC INFORMATION 135

    Chapter 8: Genes to the niche! How contemporary DNA can help to refine niche theory for predicting range dynamics in the Anthropocene 137

    Niche models, theory, and the recent integration of genetic

    information 139

    Why do we need to consider genetic information in the ENM

    concept? 140

    Integrating genetic information to understand the processes behind

    range dynamic patterns 141 Gene flow and functional connectivity 141

    Spatial genetic structure 142

    Density blocking 143

    Hybridization 144

    Source-sink dynamics 145

    Using genetic data to enhance the ENM concept 146

    Concluding remarks 149

    Box 1: Integration of niche theory and genetic information 150

    Box 2: What can genetic information add to our understanding of the

    realized niche? 151

    Box 3: What can genetic information add to our understanding of the

    niche dynamics during colonization? 153

    GENERAL DISCUSSION 159

    The necessity to include standart connectivity assessments in conservation management and policy 161

    Benefits and caveats of PCMs in landscape genetics 163

  • From genes to ranges and back: is niche theory ready for the Anthropocene? 166

    Personal outlook 167

    SUMMARIES 169

    Summary 171

    Zusammenfassung 175

    ACKNOWLEDGEMENTS 181

    REFERENCES 187

    CURRICULUM VITAE 225

  • List of Figures

    Figure 1.1: Illustration of the differences between structural connectivity and functional connectivity for mobile and matrix-sensitive species 10

    Figure 2.1: The potential connectivity model (PCM) framework 19

    Figure 4.1: Location of the study area near Trier in south-western Germany as well as habitat suitability and potential connectivity maps from the same region. 53

    Figure 4.2: Trait space spanned by the first two principal components for either vineyard fallows and calcareous grasslands. 54

    Figure 5.1: Two-step conceptional framework for performing potential connectivity models. 64

    Figure 5.2: Potential distribution and connectivity of the sand lizard in the city of Cologne. 76

    Figure 6.1: Locations of populations studied for all three Thymelicus species in southwestern Germany and adjoining areas in France and Luxemburg. 92

    Figure 6.2: SDM output for Thymelicus lineola and T. sylvestris as well as T. acteon. 98

    Figure 6.3: Schematic illustration about the gradual effects forcing the three Thymelicus species. 102

    Material 6.S1 Figure 1: Consensus tree inferred by using the Neighbor-Joining method accounting for the 50% majority rule. 110

    Figure 6.S1: Estimation of the number of panmictic clusters for each species. 113

    Figure 6.S2: Scatterplots showing the difference of isolation by distance patterns with isolation by resistance patterns in the two species that show a spatial genetic structure. 114

    Figure 7.1: A fictive study area that comprises seven localities where genetic information from a species was obtained but where relationships to landscape elements are unknown. 121

    Figure 7.2: Spatial composition of regions where one of the three landscape elements is locally driving gene flow in the study region. 122

  • Figure 7.3: Linear relationships between genetic distance with effective distances from land use, topography, and climate together with the optimized solution for the Hesperid butterfly Thymelicus sylvestris. 126

    Figure 7.4: The optimized solution plotted as a network of comparisons across the study area from T. sylvestris. 127

    Figure 7.5: Linear relationships between genetic distance with effective distances from range shape and climate together with the optimized for the wolverine. 128

    Figure 7.6: The optimized solution plotted as a network of comparisons across the North American range of the wolverine. 129

    Figure 8.1: The fraction of the BAM plot where species occur. 140

    Figure 8.2: Expanding the ENM concept with genetic information. 147

    Figure 8.B1.1: The BAM diagram as an abstract visualization of the ENM concept in geographic space. Biological and ecological aspects than can be quantified with g