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Table of contents
CHAPTER 1 GENERAL INTRODUCTION
1 PERMAFROST DEFINITION AND DISTRIBUTION
2 COMMON FEATURES OF PERMAFROST LANDSCAPES
3 ANTHROPOGENIC CLIMATE CHANGE IN THE ARCTIC AND SUB-ARCTIC
4 PERMAFROST AND LOCAL AND GLOBAL CARBON CYCLES
5 REFERENCES
CHAPTER 2 14,000-YEAR CARBON ACCUMULATION DYNAMICS IN A SIBERIAN LAKE REVEAL CATCHMENT AND LAKE PRODUCTIVITY CHANGES
1 INTRODUCTION
2 STUDY SITE
3 METHODS
3.1 Field Sampling
3.2 Sediment core subsampling and dating
3.3 X-ray fluorescence (XRF) analysis
3.4 Grain size analysis
3.5 Dry bulk density, sedimentation and organic carbon accumulation calculations
3.6 Biogeochemical analysis
3.7 Statistical Analysis
4 RESULTS
4.1 Chronology and sedimentation rates
4.2 General Stratigraphy
4.3 Grain-size distribution
4.4 Biogeochemistry
4.5 Inorganic elemental composition
4.6 PCA Analysis
5 DISCUSSION
5.1 Multiproxy-inferred paleolimnological history
5.2 Lake Malaya Chabyda carbon accumulation rates
5.3 Connections between the lake environment, permafrost dynamics, and climatic conditions
6 CONCLUSIONS
7 REFERENCES
8 ACKNOWLEDGEMENTS
CHAPTER 3 SEASONAL PATTERNS IN GREENHOUSE GAS EMISSIONS FROM THERMOKARST LAKES IN CENTRAL YAKUTIA (EASTERN SIBERIA)
1 INTRODUCTION
2 STUDY SITE
2.1 Lake types
3 METHODS
3.1 Physicochemical characteristics of lake water
3.2 Dissolved greenhouse gas measurements
3.3 Statistical analysis
4 RESULTS
4.1 Seasonal conditions
4.2 Physicochemical characterization of lake water
4.2.1 Broad trends and seasonal averages.
4.2.2 Seasonal Profiles.
4.2.3 Dissolved greenhouse gas concentrations
4.2.4 Diffusive greenhouse gas fluxes
5 DISCUSSION
5.1 Developmental stage as a driving factor on lake greenhouse gas concentrations and fluxes
5.2 Seasonal variations in greenhouse gas concentrations
5.3 Diffusive greenhouse gas fluxes: comparison across high-latitude regions
6 CONCLUSIONS
7 REFERENCES
8 ACKNOWLEDGMENTS
CHAPTER 4 AUTOMATED IDENTIFICATION OF THERMOKARST LAKES USING MACHINE LEARNING IN THE PERMAFROST LANDSCAPE OF CENTRAL YAKUTIA (EASTERN SIBERIA)
1 INTRODUCTION
2 STUDY SITE
3 METHODS
3.1. Image Data
3.2. Defining lake boundaries and lake types
3.3. General Workflow
3.3.1. Machine learning model
3.3.2. Fine tuning and training
3.3.3. Accuracy assessment of initial model
3.3.4. Ensembling
3.3.5. Comparison of total surface area for prediction and corrected shapefiles
3.4. Surface area change analysis
3.4.1. South study site
3.4.2. Center study site
3.7. Temperature and precipitation
4 RESULTS AND DISCUSSION
4.1. Changes in temperature and precipitation since 1900
4.2. Spatial distribution of lake types
4.3. Lake surface area change: South study site
4.4. Lake surface area change: Center study site
5 CONCLUSIONS
6 REFERENCES
