ALBERT

Note: Table of Contents Abstract Zusammenfassung List of Figures List of Tables 1. Introduction 1.1 Scientific Background 1.1.1 Arctic Climate Change 1.1.2 Permafrost Degradation 1.1.3 The Arctic Freshwater System and its Biogeochemistry 1.2 Objectives 1.3 Study Region and Methods 1.3.1 Study Area 1.3.2 Field Sampling and Measurements 1.3.3 Geochemical Analyses 1.3.4 Data Processing 1.4 Thesis Structure 1.5 Author Contributions 2. Spatial Variability of Dissolved Organic Carbon, Solutes and Suspended Sediment in Disturbed Low Arctic Coastal Watersheds 2.1 Abstract 2.2 Introduction 2.3 Study Site 2.4 Methods 2.4.1 Stream Monitoring 2.4.2 Mapping of Disturbances 2.4.3 Flux Estimates and Statistics 2.5 Results 2.5.1 Catchment Disturbance 2.5.2 Runoff and Hydrochemistry 2.5.3 Lateral Transport of Stream Water 2.5.4 Hydrochemical Composition and Fluxes in Nearby Streams 2.6 Discussion 2.6.1 Total Runoff and Water Quality 2.6.2 Water Quality Changes from Headwaters to Downstream 2.6.3 Changes in Hydrochemistry and Isotopic Composition over Time 2.6.4 Importance of Disturbances for Hydrochemistry 2.7 Conclusions 2.8 Supplementary Material 3. Terrestrial Colored Dissolved Organic Matter (cDOM) in Arctic Catchments - Characterizing Organic Matter Composition Across the Arctic 3.1 Introduction 3.2 Study Area 3.3 Methods 3.3.1 Field Methods and Hydrochemistry 3.3.2 Statistical Analyses 3.4 Results 3.4.1 Meteorological Conditions and General Hydrochemistry 3.4.2 DOC and cDOM Absorption Characteristics 3.4.3 Downstream Patterns of DOC and cDOM Along Longitudinal Transects 3.4.4 Temporal Trends ofDOC and cDOM with Changing Meteorological Conditions 3.5 Discussion 3.5.1 Limitations of cDOM Measurements from Terrestrial Sources 3.5.2 Catchment Processes and Biogeochemical Cycling 3.5.2.1 Regional Catchment Properties 3.5.2.2 Rainfall Events 3.5.2.3 Downstream Patterns and Impact of Permafrost Disturbance 3.5.3 Nature of cDOM-DOC Across the Terrestrial Arctic 3.6 Conclusion 3.7 Supplementary Material 4. Summer Rainfall DOC, Solute and Sediment Fluxes in a Small Arctic Coastal Catchment on Herschel Island (Yukon Territory, Canada) 4.1 Abstract 4.2 Introduction 4.3 Study Site 4.4 Methodology 4.4.1 Weather data 4.4.2 Hydrology 4.4.3 Suspended Sediment and Hydrochemistry 4.4.4 Flux Estimates and Statistics 4.5 Results 4.5.1 Meteorological Conditions 4.5.2 Streamflow and Electrical Conductivity 4.5.3 Transport of Suspended Sediment and Organic Matter 4.5.4 Solute Transport 4.5.5 Alluvial Fan Sampling 4.6 Discussion 4.6.1 Hydrological Response 4.6.2 Water Quality and Fluxes 4.6.3 Rainfall Response and Flow Pathways 4.7 Conclusions 4.8 Supplementary Material 5. Synthesis 5.1 Impacts of Permafrost Degradation on Stream Biogeochemistry 5.2 Controls on DOM Quality across the Arctic 5.3 Biogeochemical Fluxes from Small Coastal Catchments to the Arctic Ocean 5.4 Challenges 5.5 Outlook Acronyms Bibliography Acknowledgements Eidesstattliche Erklärung

Note: Dissertation, Universität Potsdam, 2019 , Table of contents Abstract Zusammenfassung Abbreviations 1 Introduction 1.1 Scientific background 1.1.1 Permafrost in the Northern Hemisphere 1.1.2 The permafrost carbon climate feedback 1.1.3 Rapidly changing, deep permafrost environments 1.2 Aims of this dissertation 1.3 Investigated study areas 1.4 Basic method overview 1.4.1 Field work in the Arctic 1.4.2 Laboratory procedure 1.4.3 Analysis ofl andscape-scale carbon and nitrogen stocks 1.5 Thesis organization 1.6 Overview of publications 1.6.1 Publication#1 - Yedoma landscape publication 1.6.2 Publication#2 - Thermokarst lake sequence publication 1.6.3 Publication#3 - North Alaska Arctic river delta publication 1.6.4 Extended Abstract - Western Alaska river delta study 1.6.5 Appendices - Supplementary material and paper in preparation II Carbon and nitrogen pools in thermokarst-affected permafrost landscapes in Arctic Siberia 2.1 Abstract 2.2 Introduction 2.3 Material and methods 2.3.1 Study area 2.3.2 Field Work 2.3.3 Laboratory analysis 2.3.4 Landform classification and upscaling C and N pools 2.4 Results 2.4.1 Sedimentological results 2.4.2 Sampling site SOC and N stocks 2.4.3 Upscaling: Landscape SOC and N stocks 2.4.4 Radiocarbon dates 2.5 Discussion 2.5.1 Site specific soil organic C and N stock characteristics 2.5.2 Upscaling of C and N pools 2.5.3 Sediment and organic C accumulation rates 2.5.4 Characterizing soil organic carbon 2.5.5 The fate of organic carbon in thermokarst-affected yedoma in Siberia 2.6 Conclusions III Impacts of successive thermokarst lake stages on soil organic matter, Arctic Alaska 3.1 Abstract 3.2 Plain language summary 3.3 Introduction 3.4 Study site 3.5 Methods 3.5.1 Core collection 3.5.2 Biogeochemical analyses 3.5.3 Study area OC and N calculation 3.6 Results 3.6.1 Biogeochemistry 3.6.2 Sediment organic carbon and nitrogen stocks 3.6.3 Radiocarbon dates and carbon accumulation rates 3.6.4 Landscape C and N budget 3.7 Discussion 3.7.1 Impact of thermokarst lake dynamics on organic matter storage 3.7.2 High organic C and N stocks on the ACP 3.7.3 Landscape chronology 3.7.4 Organic matter accumulation 3.7.5 Future development 3.8 Conclusions IV Sedimentary and geochemical characteristics of two small permafrost-dominated Arctic river deltas in northern Alaska 4.1 Abstract 4.2 Introduction 4.3 Study area 4.4 Material and Methods 4.4.1 Soil organic carbon and soil nitrogen storage 4.4.2 Radiocarbon dating and organic carbon accumulation rates 4.4.3 Grain size distribution 4.4.4 Scaling carbon and nitrogen contents to landscape level 4.5 Results 4.5.1 Carbon and nitrogen contents 4.5.2 Radiocarbon dates and accumulation rates 4.5.3 Grain size distribution 4.5.4 Arctic river delta carbon and nitrogen storage 4.6. Discussion 4.6.1 Significance of carbon and nitrogen stocks in Arctic river deltas 4.6.2 SOC and SN distribution with depth 4.6.3 Sedimentary characteristics 4.6.3.1 Accumulation rates 4.6.3.2 Sediment distribution 4.6.4 Impacts of future changes 4.6.5 Significance of remotely sensed upscaling results 4.7 Conclusions V Soil carbon and nitrogen stocks in Arctic river deltas - New data for three Western Alaskan deltas 5.1 Abstract 5.2 Introduction 5.3 Study sites 5.4 Methods 5.5 Results and discussion 5.5 Conclusions VI Discussion 6.1 Interregional comparison 6.2 Changing thermokarst landscapes and their global impact 6.3 A growing C and N data base 6.4 Outlook - potential follow-up projects VII Synthesis VIII References Appendix A Synthesis of SOC and N inventories Appendix B Supplementary material to Chapter II Appendix C Supplementary material to Chapter III Appendix D Supplementary material to Chapter IV Appendix E Supplementary material to Chapter V Appendix F Arctic river delta data set - Version 1.0 Acknowledgements - Danksagung

Note: Contents: 1 General introduction. - 1.1 Challenges of isotope-based temperature reconstructions. - 1.2 Thesis overview. - 1.3 Author contributions. - 2 Theoretical background. - 2.1 The isotopic composition of firn and ice. - 2.1.1 Fractionation of water isotopologues. - 2.1.2 Relationship with temperature. - 2.1.3 Measuring of the isotopic composition. - 2.2 Processes within the firn column. - 2.2.1 The firn column of polar ice sheets. - 2.2.2 The density of firn. - 2.2.3 The temperature profile of firn. - 2.2.4 Vapour diffusion in firn. - 2.3 Internal climate variability. - 3 Regional climate signal vs.local noise: a two-dimensional view of water isotopes. - 3.1 Introduction. - 3.2 Data and methods. - 3.3 Results. - 3.3.1 Trench isotope records. - 3.3.2 Single-profile representativity. - 3.3.3 Mean trench profiles. - 3.3.4 Spatial correlation structure. - 3.3.5 Statistical noise model. - 3.4 Discussion. - 3.4.1 Local noise vs. regional climate signal. - 3.4.2 Representativity of isotope signals. - 3.4.3 Implications. - 3.5 Conclusions. - 3.6 Appendix A: Derivation of noise model. - 3.6.1 Definitions. - 3.6.2 Derivation of model correlations. - 3.6.3 Estimation of parameters. - 3.7 Appendix B: Noise level after diffusion. - 4 Constraints on post-depositional isotope modifications in east antarctic firn. - 4.1 Introduction. - 4.2 Data and methods. - 4.2.1 Sampling and measurements. - 4.2.2 Trench depth scale. - 4.2.3 Spatial variability of trench profiles. - 4.2.4 Quantification of downward advection, densification and diffusion. - 4.2.5 Statistical tests. - 4.3 Results. - 4.3.1 Comparison of T15 and T13 isotope data. - 4.3.2 Expected isotope profile changes. - 4.3.3 Temporal vs. spatial variability. - 4.4 Discussion. - 4.4.1 Densification, diffusion and stratigraphic noise. - 4.4.2 Additional post-depositional modifications. - 4.5 Conclusions. - 5 On the similarity and apparent cycles of isotope variations. - 5.1 Introduction. - 5.2 Data and Methods. - 5.2.1 Data. - 5.2.2 Spectral analysis. - 5.2.3 Rice’s formula. - 5.2.4 Cycle length and amplitude estimation. - 5.2.5 Model for vertical isotope profiles. - 5.3 Results. - 5.3.1 Spectral analysis of isotope profiles. - 5.3.2 Theoretical and observed cycle length. - 5.3.3 Illustrative examples. - 5.3.4 Depth dependency of cycle length. - 5.3.5 Simulated vs. observed isotope variations. - 5.4 Discussion and summary. - 5.5 Conclusions. - 5.6 Appendix A: Input sensitivity. - 5.7 Appendix B: Additional results. - 5.8 Appendix C: Spectral significance testing. - 6 Timescale-dependency of antarctic isotope variations. - 6.1 Introduction. - 6.2 Data and methods. - 6.2.1 DML and WAIS isotope records. - 6.2.2 Spectral model. - 6.2.3 Timescale-dependent signal-to-noise ratio. - 6.2.4 Effects of diffusion and time uncertainty. - 6.2.5 Present-day temperature decorrelation. - 6.3 Results. - 6.3.1 Illustration of model approach. - 6.3.2 DML and WAIS isotope variability. - 6.4 Discussion. - 6.4.1 Interpretation of noise spectra. - 6.4.2 Interpretation of signal spectra. - 6.4.3 Signal-to-noise ratios. - 6.4.4 Differences between DML and WAIS. - 6.5 Conclusions. - 7 Declining temperature variability from LGM to holocene. - 8 General discussion and conclusions. - 8.1 Short-scale spatial and temporal isotope variability. - 8.1.1 Local spatial variability. - 8.1.2 Seasonal to interannual variability. - 8.1.3 Spatial vs. temporal variability. - 8.2 Extension to longer scales. - 8.2.1 Spatial vs. temporal variability on interannual timescales. - 8.2.2 Holocene and longer timescales. - 8.3 Concluding remarks and outlook. - Bibliography. - A Methods to: declining temperature variability from lgm to holocene. - A.1 Temperature proxy data. - A.2 Model-based temperature and variability change. - A.3 Temperature recalibration of proxy records. - A.3.1 Recalibration of ice-core records. - A.3.2 Recalibration of marine records. - A.4 Variance and variance ratio estimation. - A.5 Noise correction. - A.5.1 Testing effect of noise correction. - A.6 Effect of ecological adaption and bioturbation. - A.7 Effect of proxy sampling locations. - B Layering of surface snow and firn: noise or seasonal signal?. - B.1 Introduction. - B.2 Materials and methods. - B.2.1 Firn-core density profiles. - B.2.2 Trench density profiles. - B.2.3 Dielectric profiling and density estimates. - B.2.4 Comparison of DEP and CT density. - B.2.5 Ion measurements. - B.3 Results. - B.3.1 2-D trench density data. - B.3.2 Spatial correlation structure. - B.3.3 Comparison of mean density, isotope and impurity profiles. - B.3.4 Spectral analysis of vertical density data. - B.4 Discussion. - B.4.1 Spatial variability. - B.4.2 Representativeness of single profiles. - B.4.3 Seasonal cycle in snow density. - B.4.4 Density layering in firn and impurities. - B.5 Conclusions. - Acknowledgements - Danksagung.

Note: Inhaltsverzeichnis 1 Einleitung 1.1Wissenschaftliche Zielsetzung 2 Grundlagen 2.1 Grundgleichungen 2.2 Potentielle Vorticity 2.3 Planetare Wellen 2.4 Atmosphärische Instabilität 2.5 Grenzschicht 2.6 Kopplung von Tropo- und Stratosphäre 3 Daten und Methoden 3.1 N-ICE2015 3.1.1 Expeditionsbeschreibung 3.1.2 Ziele der Expedition 3.2 Daten 3.2.1 Beobachtungsdaten 3.2.2 ERA-Interim Reanalyse 3.2.3 Das HIRHAM5 Modell 3.3 Analysemethoden 3.3.1 Temperaturinversionen 3.3.2 Vertikale Stabilität 3.3.3 Grenzschichthöhe 3.3.4 Eady Growth Rate 3.3.5 2d-Skalenfilterung und -Pattern-Korrelation 3.3.6 Nudging Experiment 4 Analyse der N-ICE2015 Radiosonden 4.1 Blick auf die Troposphäre 4.2 Fallstudie zum M2-Sturm: A 4.3 Zyklonencharakteristika 4.4 Temperaturinversionen und Stabilität 4.5 Vergleich mit ERA-Interim, SHEBA und Ny-Ålesund 4.6 Résumé der Expeditionsdaten 5 Nudging Studien mit HIRHAM5 5.1 Vergleich mit ERA-Interim 5.2 Vergleich der Simulationen 5.3 Fallstudie zum M2-Sturm: B 5.3.1 Synoptische Aktivität 5.4 Statistischer Vergleich 6 Einfluss der Stratosphäre 6.1 Stratosphäre im Winter 2014/2015 6.2 Fallstudie zum M2-Sturm: C 6.3 PV als Ladung 6.4 Résumé der Beobachtungen 7 Zusammenfassung und Ausblick A Zusätztliche Abbildungen B Literaturverzeichnis

Note: Contents Summary 1. Introduction 1.1 Background 1.1.1 Precipitation changes 1.1.2 Large-scale atmospheric patterns 1.2 Objectives and research questions 1.3 Thesis outline and author contribution High spatial and temporal organization of changes inprecipitation over Germany for 1951–2006 2.1 Introduction 2.2 Data 2.3 Methods 2.3.1 Threshold between wet and dry days 2.3.2 Derivation of time series of precipitation characteristics 2.3.3 Trend analyses under consideration of temporal and spatial correlation 2.3.4 Visualization of results 2.4 Results and discussion 2.4.1 Changes in total precipitation 2.4.2 Changes in mean, variability, and heavy precipitation indicators 2.4.3 Transition probabilities 2.4.4 Seven-day precipitation amount with return period 100 years 2.5 Conclusions Can local climate variability be explained by weatherpatterns? A multi-station evaluation for the Rhine basin 3.1 Introduction 3.2 Data 3.3 Methods 3.3.1 Weather pattern classification 3.3.2 Finding optimal classification parameters 3.3.3 Evaluation of classifications 3.4 Results 3.4.1 Stratification of local climate variables 3.4.2 Performance of GCMs 3.5 Discussion 3.5.1 On the optimal classification 3.5.2 On the skill of GCMs 3.6 Conclusions 3.7 Data availability 3.A Appendix Do changing weather types explain observed climatictrends in the Rhine basin? An analysis of within andbetween-type changes 4.1 Introduction 4.2 Data and weather pattern classification 4.3 Methods 4.3.1 Relationship of WPs and large-scale circulation modes 4.3.2 Trend detection methods 4.3.3 Relative share of between- and within-type changes 4.4 Results 4.4.1 Attribution of WPs to large-scale circulation modes 4.4. 2Between-Type Changes 4.4.3 Within-Type Changes 4.4.4 Relative share of between- and within-type changes 4.5 Discussion and conclusions 4.A Appendix 4.S Supplementary Discussion and conclusions 5.1 Main results 5.2 Discussion and directions for further research 5.2.1 Weather pattern classification for downscaling 5.2.2 Limitations for downscaling 5.3 Concluding remarks Bibliography

Note: Dissertation, Universität Potsdam, 2017 , Table of Contents I. Abstract II. Deutsche Zusammenfassung 0 Challenge 1 Introduction 1.1 The treeline ecotone 1.2 Stand structure drivers in the treeline ecotone 1.3 Climate change and recent treeline changes 1.4 Methods for treeline studies 1.4.1 Overview 1.4.2 Field-based treeline studies 1.4.3 Modelling treeline dynamics 1.5 Study Area 1.6 The Siberian treeline ecotone 1.7 Larix as study Species 1.8 Objectives of this thesis 1.9 Thesis outline 1.10 Contribution of the authors 1.10.1 Manuscript!- published 1.10.2 Manuscript II - submitted 1.10.3 Manuscript III-in preparation 1.10.4 Manuscript IV-submitted 2 Manuscript I Treeline dynamics in Siberia under changing climates as inferred from an individual-based model for Larix 2.1 Abstract 2.2 Introduction 2.3 Materials and Methods 2.3.1 Reference sites 2.3.2 Description of the model LAVESI 2.3.3 The ODD-Protocol for LAVESI 2.3.4 Parameterization 2.3.5 Khatanga climate time-series 2.3.6 Sensitivity analysis 2.3.7 Model experiments 2.4 Results 2.4.1 Sensitivity analysis 2.4.2 Taymyr treeline application 2.4.3 Temperature experiments 2.5 Discussion 2.5.1 Assessment of LAVESI sensitivity 2.5.2 Larix stand simulation under the Taymyr Peninsula weather 2.5.3 Transient Larix response to hypothetical future temperature changes 2.5.4 Conclusions 2.6 Acknowledgements 3 Manuscript II Dissimilar responses of larch stands in northern Siberia to increasing temperatures - a field and simulation based study 3.1 Abstract 3.2 Introduction 3.3 Methods 3.3.1 Study area 3.3.2 Field-based approach 3.3.3 Age analyses 3.3.4 Stand structure analyses 3.3.5 Seed analyses 3.3.6 Establishment history 3.3.7 Modelling approach 3.4 Results 3.4.1 Field data 3.4.2 Simulation study 3.5 Discussion 3.5.1 Data acquisition 3.5.2 Larch-stand patterns across the Siberian treeline ecotone 3.5.3 Warming causes densification in the forest-tundra 3.5.4 Intra-specific competition inhibits densification in the closed forest 3.5.5 Recruitment limitation decelerates densification and northward expansion ofthe single-tree tundra 3.6 Conclusions 3.7 Acknowledgements 4 Manuscript III Spatial patterns and growth sensitivity of larch stands in the Taimyr Depression 4.1 Abstract 4.2 Introduction 4.3 Methods 4.3.1 Study Area 4.3.2 Field data collection 4.3.3 Spatial point patterns 4.3.4 Dendrological approach 4.4 Results 4.4.1 Spatial patterns 4.4.2 Tree growth 4.5 Discussion 4.5.1 Spatial patterns 4.5.2 Tree chronology characteristics 4.6 Conclusion 5 Manuscript IV Patterns of larch stands under different disturbance regimes in the lower Kolyma River area (Russian Far East) 5.1 Abstract 5.2 Introduction 5.3 Methods 5.3.1 Study area and field data collection 5.3.2 Site description 5.3.3 Dendrochronological approach 5.3.4 Statistical analyses 5.4 Results 5.4.1 General stand characteristics and age structure 5.4.2 Spatial patterns 5.5 Discussion 5.5.1 Fire related disturbances 5.5.2 Water-related disturbances: lake drainage, flooding, polygon development 5.5.3 Implications and conclusion 6 Synthesis and Discussion 6.1 Assessment of applied methods 6.1.1 Field-based observations: 6.1.2 Modelling 6.2 Overview of larch stand structures and spatial pattern on different spatial scales 6.2.1 Recent stand structures 6.2.2 Spatial Patterns 6.3 Stand structure drivers and treeline changes 6.3.1 Climate change 6.3.2 Disturbances 6.3.3 Autecology 6.4 Conclusion 6.5 Outlook 7 Appendix 7.1 Supplementary information for Manuscript I 7.2 Supplementary information for Manuscript II 7.2.1 Manuscript II: Appendix 1. Climatic information for the study region 7.2.2 Manuscript II: Appendix 2. Plot-specific values and krummholz appearance 7.2.3 Manuscript II: Appendix 3. Regression analysis for age data 7.2.4 Manuscript II: Appendix 4. Model description 7.3 Supplementary information for Manuscript III 7.4 Supplementary information for Manuscript IV 7.5 Supplementary information 8 References Danksagung Eidesstattliche Erklärung

Note: Table of contents Abstract Zusammenfassung Abbreviations and Nomenclature 1. Introduction 1.1 Scientific Background 1.1.1 Climate and Permafrost 1.1.2 Remote Sensing 1.1.3 Research Questions 1.2 General Approach 1.3 Thesis Structure 1.4 Author’ s contributions 1.4.1 Chapter 2 1.4.2 Chapter 3 1.4.3 Chapter 4 1.4.4 Chapter 5 1.4.5 Appendix Paper 1 2. Detection of landscape dynamics in the Arctic Lena Delta withtemporally dense Landsat time-series Stacks 2.1 Abstract 2.2 Introduction 2.3 Study Area and Data 2.3.1 Study Area 2.3.2 Data 2.3.3 Methods/processing 2.4 Results 2.4.1 Regional Scale changes 2.4.2 Local scale changes 2.5 Discussion 2.5.1 Regional scale changes 2.5.2 Local scale changes 2.5.3 Data quality 2.5.4 Data usage and outlook 2.6 Conclusion 2.7 Data Archive 2.8 Acknowledgements 2.9 Appendix A. Supplementary Data 3. Landsat-Based Trend Analysis of Lake Dynamics across NorthernPermafrost Regions 3.1 Abstract 3.2 Introduction 3.3 Study Sites 3.3.1 Alaska North Slope (NSL) 3.3.2 Alaska Kobuk-Selawik Lowlands (AKS) 3.3.3 Central Yakutia (CYA) 3.3.4 Kolyma Lowland (KOL) 3.4 Data and Methods 3.4.1 Data and Trend Analysis 3.4.2 Pixel-Based Machine-Leaming Classification 3.4.3 Object-Based Image Analysis 3.4.4 Data Quality and Post-Processing 3.4.5 Calculation of Lake Change Statistics 3.5 Results 3.5.1 NSL (Alaska North Slope) 3.5.2 AKS (Alaska Kobuk-Selawik Lowlands) 3.5.3 CYA (Central Yakutia) 3.5.4 KOL (Kolyma Lowland) 3.6 Discussion 3.6.1 Data Analysis 3.6.2 Comparison of Sites and Prior Studies 3.7 Conclusions 3.8 Supplementary Materials 3.9 Acknowledgements 3.10 Appendix A 4. Remotely sensing recent permafrost region disturbances across Arcticto Subarctic transects 4.1 Abstract 4.2 Introduction 4.3 Results 4.3.1 Lakes 4.3.2 Retrogressive Thaw Slumps 4.3.3 Wildfire 4.4 Discussion 4.5 Methods 4.5.1 Remote Sensing Data Processing 4.5.2 Auxiliary Data Sources 5. Tundra landform and Vegetation productivity trend maps for theArctic Coastal Plain of northern Alaska 5.1 Abstract 5.2 Background & Summary 5.3 Methods 5.3.1 Polygonal tundra geomorphology mapping 5.3.2 Image processing 5.3.3 Image Classification 5.3.4 Decadal scale NDVI trend analysis 5.4 Data Records 5.5 Technical Validation 5.5.1 Tundra Geomorphology Map 5.5.2 NDVI Trend Map 5.6 Data Citation 6. Discussion/Synthesis 6.1 Landsat-based trend analysis 6.1.1 Spatial Scale 6.1.2 Time series analysis 6.1.3 Model complexity 6.2 Mapping of permafrost landscape dynamics 6.2.1 Lake dynamics 6.2.2 Wildfire 6.2.3 Retrogressive Thaw Slumps 6.3 Pan-arctic scale distribution and consequences of changes inpermafrost 6.4 Outlook Bibliography A-1. Appendix: Reduced arctic tundra productivity linked with landform and climate change interactions A-1.1 Abstract A-1.2 Introduction A-1.3 Methods A-1.4 Results A-1.5 Discussion Danksagung/Acknowledgements Eidesstattliche Erklärung

Note: Table of contents Abstract Zusammenfassung Abbreviations and nomenclatureI 1. Introduction 1.1 Scientific background 1.1.1 Permafrost and ground ice 1.1.2 Organic carbon pools and fluxes into the Arctic Ocean 1.1.3 Climate warming and permafrost thaw 1.1.4 Permafrost degradation and coastal erosion 1.1.5 Study area Yukon coast and Qikiqtaruk 1.2 Knowledge gaps 1.3 Aims and objectives 1.4 Thesis structure and author's contribution 2. Eroding permafrost coasts release low amounts of dissolved organic carbon (DOC) from ground ice into the nearshore zone of the Arctic Ocean 2.1 Abstract 2.2 Introduction 2.3 Study area 2.4 Methods 2.4.1 Field work 2.4.2 DOC concentration 2.4.3 DOC flux estimation 2.5 Results 2.5.1 Segmentation of the coast - literature synthesis 2.5.2 DOC concentration 2.5.3 DOC stocks and fluxes 2.6 Discussion 2.6.1 DOC concentrations in ground ice 2.6.2 DOC fluxes from the YC 2.6.3 DOC fluxes and the Arctic carbon budget 2.7 Conclusion and Outlook 2.8 Acknowledgements 3.Transformation of terrestrial organic matter along thermokarst-affected permafrost coasts in the Arctic 3.1 Abstract 3.2 Introduction 3.3 Study area 3.3 Methods 3.3.1 Field work 3.3.2 Sedimentology, stratigraphy, and vegetation 3.3.3 Organic matter 3.3.4 Statistics 3.3.5 Transformation of organic matter 3.3.6 Fate of organic matter in the nearshore zone 3.4 Results 3.4.1 Sedimentology, stratigraphy, and vegetation 3.4.2 Organic matter 3.4.3 C/N-ratios and δ13C 3.4.4 Biomarkers 3.5 Discussion 3.5.1 Transformation of organic matter in the disturbed zone 3.5.2 Fate of organic matter in the nearshore zone 3.5.3 Environmental impact of the RTS 3.6 Conclusion 3.7 Acknowledgements 4. Rapid greenhouse gas release from eroding permafrost coasts 4.1 Summary 4.2 Background 4.3 Study site 4.4 Sampling and incubation setup 4.5 Findings and discussion 4.6 Conclusion 4.7 Methods 4.7.1 Incubation conditions 4.7.2 Gas measurements 4.7.3 Geo- and hydrochemical analysis 4.8 Acknowledgements 5. Synthesis 5.1 Mobilization of permafrost OC pools by coastal erosion 5.2 Transformation of permafrost OM on transit from land to sea 5.3 Fate and pathways of permafrost OC in the nearshore zone 5.4 Conclusion and outlook References Appendix I: Dissolved organic carbon (DOC) in Arctic ground ice I-1 Abstract I-2 Introduction I-3 Study area and study sites I-4 Material and methods I-4-1 Laboratory analyses I-4-2 Statistical methods I-5 Results I-5-1 DOC and DIC concentrations I-5-2 Correlation matrix I-5-3 Principal components I-5-4 Univariate Tree Model (UTM) I-6 Discussion I-6-1 DOC stocks in ground ice and relevance to carbon cycling I-6-2 Carbon sequestration and origin in relation to inorganic geochemistry I-6-3 DOC mobility and quality upon permafrost degradation I-7 Conclusions and outlook I-8 Acknowledgements Appendix II: Supplementary material for Chapter 2 II-1 Supplementary table - Ground ice and geochemical data II-2 Supplementary table - Coastal segments and DOC flux Appendix III: Supplementary material for Chapter 3 III-1 Normalized Differenced Vegetation Index map III-2 Photograph of a massive ice bed in a RTS III-3 Calculation of biomarker proxies III-4 Supplementary table - Summary of geochemical data III-5 Supplementary table - Summary of statistical analysis AppendixI V: Supplementary material for Chapter 4 IV-1 Design of the incubation experiment IV-2 Photograph of a standard incubation setup IV-3 Conversion of gas amounts into mass IV-4 Total and daily aerobic CH4 production IV-5 Histogram summarizing OC losses and CO2 emissions IV-6 Supplementary table - Summary of TOC, DOC, and pH data IV-7 Supplementary table - Summary of TN, TOC/TN, and δ13C-TOC data IV-8 Supplementary table - Summary of total CO2 and CH4 production data IV-9 Supplementary table - Comparison of incubation setups IV-10 Supplementary table - Summary of daily CO2 production data IV-11 Supplementary table - Summary of daily CH4 production data Acknowledgements-Danksagung

Note: Table of contents Abstract Zusammenfassung 1 Motivation 2 Introduction 2.1 Arctic climate changes and their impacts on Coastal processes 2.2 Shoreline retreat along Arctic coasts 2.3 Impacts of Coastal erosion 2.3.1 Material fluxes 2.3.2 Retrogressive thaw slumps 2.3.3 Socio-economic impacts 2.4 Objectives 2.5 Study area 2.6 Thesis structure 2.7 Authors’ contributions 3 Variability in rates of Coastal change along the Yukon coast, 1951 to 2015 3.1 Introduction 3.2 Study Area 3.3 Data and Methods 3.3.1 Remote sensing data 3.3.2 Field survey data 3.3.3 Classification of shoreline 3.3.4 Transect-wise analyses of shoreline movements through time 3.4 Results 3.4.1 Temporal variations in shoreline change rates 3.4.2 Alongshore rates of change 3.4.3 Shoreline dynamics along field sites 3.4.4 Dynamics of lagoons, barrier Islands and spits (gravel features) 3.4.5 Yukon Territory land loss 3.5 Discussion 3.5.1 Temporal variations in shoreline change rates 3.5.2 Alongshore rates of change 3.5.3 Dynamics of lagoons, barrier Islands, and spits (gravel features) 3.5.4 Expected shoreline changes as a consequence of future climate warming 3.6 Conclusions Context 4 Coastal erosion of permafrost Solls along the Yukon Coastal Plain and Kuxes oforganic carbon to the Canadian Beaufort Sea 4.1 Introduction 4.2 Study Area 4.3 Methods 4.3.1 Sample collection and laboratory analyses 4.3.2 Soll organic carbon determinations 4.3.3 Flux of organic soil carbon and Sediments 4.3.4 Fate of the eroded soil organic carbon 4.4 Results 4.4.1 Ground lce 4.4.2 Organic carbon contents 4.4.3 Material fluxes 4.5 Discussion 4.5.1 Ground lce 4.5.2 Organic carbon contents 4.5.3 Material fluxes 4.5.4 Organic carbon in nearshore Sediments 4.6 Conclusion Context 5 Terrain Controls on the occurrence of Coastal retrogressive thaw slumpsalong the Yukon Coast, Canada 5.1 Introduction 5.2 Study Area 5.3 Methods 5.3.1 Mapping of RTSs and landform Classification 5.3.2 Environmental variables 5.3.3 Univariate regression trees 5.4 Results 5.4.1 Characteristics of RTS along the coast 5.4.2 Density and areal coverage od RTSs along the Yukon Coast 5.5 Discussion 5.5.1 Characteristics and distribution of RTSs along the Yukon Coast 5.5.2 Terrain factors explaining RTS occurrence 5.5.3 Coastal processes 5.6 Conclusions Context 6 Impacts of past and fiiture Coastal changes on the Yukon coast - threats forcultural sites, infrastructure and travel routes 6.1 Introduction 6.2 Study Area 6.3 Methods 6.3.1 Data for shoreline projections 6.3.2 Shoreline projection for the conservative scenario (S1) 6.3.3 Shoreline Projection for the dynamic scenario (S2) 6.3.4 Positioning and characterizing of cultural sites 6.3.5 Calculation of losses under the S1 and S2 scenarios 6.3.6 Estimation of future dynamics in very dynamic areas 6.4 Results and discussion 6.4.1 Past and future shoreline change rates 6.4.2 Cultural sites 6.4.3 Infrastructure and travel routes 6.5 Conclusions 7 Discussion 7.1 The importance of understanding climatic drivers of Coastal changes 7.2 The influence of shoreline change rates on retrogressive thaw slump activity 7.3 On the calculation of carbon fluxes from Coastal erosion along the Yukon coast 7.4 Impacts of present and future Coastal erosion on the natural and human environment 7.5 Synthesis 8 Summary and Conclusions Bibliography Supporting Material Data Set ds01 Table S1 Table S3 Abbreviations and Nomendature Acknowledgements

Note: Table of Contents Abstract Kurzfassung Abbreviations and nomenclature 1. Introduction 2. Scientific Background 2.1. Permafrost 2.2.Retrogressive Thaw Slumps 2.3. Inputs of Freshwater, Sediment and Carbon into the Canadian Beaufort Sea 3. Study Area 3.1. Regional Setting: Yukon Coast and Herschel Island 3.2. Retrogressive Thaw Slumps 4. Material and Methods 4.1. Field Work 4.1.1. Terrain Photography 4.1.2. Differential Global Positioning System (DGPS) 4.1.3. Light Detection And Ranging (LiDAR) and Digital Elevation Model (DEM) 4.1.4. Micrometeorology 4.1.5. Discharge Measurement 4.1.6. Multiple Regression-Statistical Relationships between Micrometeorological Variables and Discharge 4.1.7. Sampling 4.2. Laboratory Analyses 4.2.1. Sedimentological Analyses 4.2.2. Hydrochemical Analyses 4.3. Fluxes of Sediment and (In-) Organic Matter 5. Results 5.1. Field Work 5.1.1. Terrain Photography 5.1.2. Differential Global Positioning System (DGPS) 5.1.3. Light Detecting And Ranging (LiDAR) and Digital Elevation Model (DEM) 5.1.4. Micrometeorology 5.1.5. Discharge 5.1.6. Multiple Regression - Statistical Relationships between Micrometeorology and Discharge 5.2. Laboratory Analyses 5.2.1. Sedimentological Analyses 5.2.2. Hydrochemical Analyses 5.3. Fluxes of Sediment-meltwater 6. Discussion 6.1. Microclimatological and Geomorphological Factors Controlling Discharge 6.1.1. Diurnal Variations 6.1.2. Seasonal Variations 6.2. Contribution of Retrogressive Thaw Slumps to the Sediment Budget of the Yukon Coast 6.2.1. Origin of Outflow Material 6.2.2. Slump D in the Regional Context 6.2.3. Seasonal Sediment Budget Compilation for Slump D 6.2.4. Retrogressive Thaw Slump Occurrence along the Yukon Coast 6.2.5. Input to the Beaufort Sea 6.3. Projected Climatic Change and its Impact on Retrogressive Thaw Slump Outflow 6.4. Uncertainties and Limitations 6.5. Future Research 7. Conclusion 8. Appendix 8.1. Field Work 8.1.1. Slump D's northern headwall profile 8.1.2. Collinson Head slump 8.1.3. Herschel Island West Coast slump 8.1.4. Roland Bay slump 8.1.5. Kay Point slump 8.2. Laboratory Work 8.2.1. Volumetric Ice Content 8.2.2. Grain Size 8.3. Evolution of Slump D 8.3.1. Geo Eye satellite of Slump D 8.3.2. Aerial Oblique Photography of Slump D 8.3.3. LiDAR of Slump D 8.3.4. Time Lapse Photography of Slump D's Headwall 9. References 10. Financial and technical support 11. Acknowledgement - Danksagung

Note: Contents Contributors 1 Introduction 1.1 Part 1: Applied statistical theory 1.2 Part 2: The case studies 1.3 Data, software and flowcharts 2 Data management and software 2.1 Introduction 2.2 Data management 2.3 Data preparation 2.4 Statistical software 3 Advice for teachers 3.1 Introduction 4 Exploration 4.1 The first steps 4.2 Outliers, transformations and standardisations 4.3 A final thought on data exploration 5 Linear regression 5.1 Bivariate linear regression 5.2 Multiple linear regression 5.3 Partial linear regression 6 Generalised linear modelling 6.1 Poisson regression 6.2 Logistic regression 7 Additive and generalised additive modelling 7.1 Introduction 7.2 The additive model 7.3 Example of an additive model 7.4 Estimate the smoother and amount of smoothing 7.5 Additive models with multiple explanatory variables 7.6 Choosing the amount of smoothing 7.7 Model selection and validation 7.8 Generalised additive modelling 7.9 Where to go from here 8 Introduction to mixed modelling 8.1 Introduction 8.2 The random intercept and slope model 8.3 Model selection and validation 8.4 A bit of theory 8.5 Another mixed modelling example 8.6 Additive mixed modelling 9 Univariate tree models 9.1 Introduction 9.2 Pruning the tree 9.3 Classification trees 9.4 A detailed example: Ditch data 10 Measures of association 10.1 Introduction 10.2 Association between sites: Q analysis 10.3 Association among species: R analysis 10.4 Q and R analysis: Concluding remarks 10.5 Hypothesis testing with measures of association 11 Ordination — First encounter 11.1 Bray-Curtis ordination 12 Principal component analysis and redundancy analysis 12.1 The underlying principle of PCA 12.2 PCA: Two easy explanations 12.3 PCA: Two technical explanations 12.4 Example of PCA 12.5 The biplot 12.6 General remarks 12.7 Chord and Hellinger transformations 12.8 Explanatory variables 12.9 Redundancy analysis 12.10 Partial RDA and variance partitioning 12.11 PCA regression to deal with collinearity 13 Correspondence analysis and canonical correspondence analysis 13.1 Gaussian regression and extensions 13.2 Three rationales for correspondence analysis 13.3 From RGR to CCA13.4 Understanding the CCA triplot 13.5 When to use PCA, CA, RDA or CCA 13.6 Problems with CA and CCA 14 Introduction to discriminant analysis 14.1 Introduction 14.2 Assumptions 14.3 Example 14.4 The mathematics 14.5 The numerical output for the sparrow data 15 Principal coordinate analysis and non-metric multidimensional scaling 15.1 Principal coordinate analysis 15.2 Non-metric multidimensional scaling 16 Time series analysis — Introduction 16.1 Using what we have already seen before 16.2 Auto-regressive integrated moving average models with exogenous variables 17 Common trends and sudden changes 17.1 Repeated LOESS smoothing 17.2 Identifying the seasonal component 17.3 Common trends: MAFA 17.4 Common trends: Dynamic factor analysis 17.5 Sudden changes: Chronological clustering 18 Analysis and modelling of lattice data 18.1 Lattice data 18.2 Numerical representation of the lattice structure 18.3 Spatial correlation 18.4 Modelling lattice data 18.5 More exotic models 18.6 Summary 19 Spatially continuous data analysis and modelling 19.1 Spatially continuous data 19.2 Geostatistical functions and assumptions 19.3 Exploratory variography analysis 19.4 Geostatistical modelling: Kriging 19.5 A full spatial analysis of the bird radar data 20 Univariate methods to analyse abundance of decapod larvae 20.1 Introduction 20.2 The data 20.3 Data exploration 20.4 Linear regression results 20.5 Additive modelling results 20.6 How many samples to take? 20.7 Discussion 21 Analysing presence and absence data for flatfish distribution in the Tagus estuary, Portugal 21.1 Introduction 21.2 Data and materials 21.3 Data exploration 21.4 Classification trees 21.5 Generalised additive modelling 21.6 Generalised linear modelling 21.7 Discussion 22 Crop pollination by honeybees in Argentina using additive mixed modelling 22.1 Introduction 22.2 Experimental setup 22.3 Abstracting the information 22.4 First steps of the analyses: Data exploration 22.5 Additive mixed modelling 22.6 Discussion and conclusions 23 Investigating the effects of rice farming on aquatic birds with mixed modelling 23.1 Introduction 23.2 The data 23.3 Getting familiar with the data: Exploration 23.4 Building a mixed model 23.5 The optimal model in terms of random components 23.6 Validating the optimal linear mixed model 23.7 More numerical output for the optimal model 23.8 Discussion 24 Classification trees and radar detection of birds for North Sea wind farms 24.1 Introduction 24.2 From radars to data 24.3 Classification trees 24.4 A tree for the birds 24.5 A tree for birds, clutter and more clutter 24.6 Discussion and conclusions 25 Fish stock identification through neural network analysis of parasite fauna 25.1 Introduction 25.2 Horse mackerel in the northeast Atlantic 25.3 Neural networks 25.4 Collection of data 25.5 Data exploration 25.6 Neural network results 25.7 Discussion 26 Monitoring for change: Using generalised least squares, non-metric multidimensional scaling, and the Mantel test on western Montana grasslands 26.1 Introduction 26.2 The data 26.3 Data exploration 26.4 Linear regression results 26.5 Generalised least squares results 26.6 Multivariate analysis results 26.7 Discussion 27 Univariate and multivariate analysis applied on a Dutch sandy beach community 27.1 Introduction 27.2 The variables 27.3 Analysing the data using univariate methods 27.4 Analysing the data using multivariate methods 27.5 Discussion and conclusions 28 Multivariate analyses of South-American zoobenthic species — spoilt for choice 28.1 Introduction and the underlying questions 28.2 Study site and sample collection 28.3 Data exploration 28.4 The Mantel test approach 28.5 The transformation plus RDA approach 28.6 Discussion and conclusions 29 Principal component analysis applied to harbour porpoise fatty acid data 29.1 Introduction 29.2 The data 29.3 Principal component analysis 29.4 Data exploration 29.5 Principal component analysis results 29.6 Simpler alternatives to PCA 29.7 Discussion 30 Multivariate analyses of morphometric turtle data — size and shape 30.1 Introduction 30.2 The turtle data 30.3 Data exploration 30.4 Overview of classic approaches related to PCA 30.5 Applying PCA to the original turtle data 30.6 Classic morphometric data analysis approaches 30.7 A geometric morphometric approach 31 Redundancy analysis and additive modelling applied on savanna tree data 31.1 Introduction 31.2 Study area 31.3 Methods 31.4 Results 31.5 Discussion 32 Canonical correspondence analysis of lowland pasture vegetation in the humid tropics of Mexico 32.1 Introduction 32.2 The study area 32.3 The data 32.4 Data exploration 32.5 Canonical correspondence analysis results 32.6 African star grass 32.7 Discussion and conclusion 33 Estimating common trends in Portuguese fisheries landings 33.1 Introduction 33.2 The time series data 33.3 MAFA and DFA 33.4 MAFA results 33.5 DFA results 33.6 Discussion 34 Common trends in demersal communities on the Newfoundland-Labrador Shelf 34.1 Introduction 34.2 Data 34.3 Time series analysis 34.4 Discussion 35 Sea level change and salt marshes in the Wadden Sea: A time series analysis 35.1 Interaction between hydrodynamical and biological factors 35.2 The data 35.3 Data exploration 35.4 Additive mixed modelling 35.5 Additive mixed modelling results 35.6 Discussion 36 Time series analysis of Hawaiian waterbirds 36.1 Introduction 36.2 Endangered Hawaiian waterbirds 36.3 Data exploration 36.4 Three ways to estimate trends 36.5 Additive mixed modelling 36.6 Sudden breakpoints 36.7 Discussion 37 Spatial modelling of forest community features in the Volzhsko-Kamsky reserve 37.1 Introduction 37.2 Study area 37.3 Data exploration 37.4 Models of boreality without spatial auto-correlation 37.5 Models of boreality with spatial auto-correlation 37.6 Conclusion References Index