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Lakes cover large parts of the climatically sensitive Arctic landscape and respond rapidly to environmental change. Arctic lakes have different origins and include the predominant thermokarst lakes, which are small, young and highly dynamic, as well as large, old and stable glacial lakes. Freshwater diatoms dominate the primary producer community in these lakes and can be used to detect biotic responses to climate and environmental change. We used specific diatom metabarcoding on sedimentary DNA, combined with next-generation sequencing and diatom morphology, to assess diatom diversity in five glacial and 15 thermokarst lakes within the easternmost expanse of the Siberian treeline ecotone in Chukotka, Russia. We obtained 163 verified diatom sequence types and identified 176 diatom species morphologically. Although there were large differences in taxonomic assignment using the two approaches, they showed similar high abundances and diversity of Fragilariceae and Aulacoseiraceae. In particular, the genetic approach detected hidden within-lake variations of fragilarioids in glacial lakes and dominance of centric Aulacoseira species, whereas Lindavia ocellata was predominant using morphology. In thermokarst lakes, sequence types and valve counts also detected high diversity of Fragilariaceae, which followed the vegetation gradient along the treeline. Ordination analyses of the genetic data from glacial and thermokarst lakes suggest that concentrations of sulfate (SO42-), an indicator of the activity of sulfate-reducing microbes under anoxic conditions, and bicarbonate (HCO3-), which relates to surrounding vegetation, have a significant influence on diatom community composition. For thermokarst lakes, we also identified lake depth as an important variable, but SO42- best explains diatom diversity derived from genetic data, whereas HCO3- best explains the data from valve counts. Higher diatom diversity was detected in glacial lakes, most likely related to greater lake age and different edaphic settings, which gave rise to diversification and endemism. In contrast, small, dynamic thermokarst lakes are inhabited by stress-tolerant fragilarioids and are related to different vegetation types along the treeline ecotone. Our study demonstrated that genetic investigations of lake sediments can be used to interpret climate and environmental responses of diatoms. It also showed how lake type affects diatom diversity, and that such genetic analyses can be used to track diatom community changes under ongoing warming in the Arctic.
Thermokarst lakes are prevalent in Arctic coastal lowland regions and sublake permafrost degradation and talik development contributes to greenhouse gas emissions by tapping the large permafrost carbon pool. Whereas lateral thermokarst lake expansion is readily apparent through remote sensing and shoreline measurements, sublake thawed sediment conditions and talik growth are difficult to measure. Here we combine transient electromagnetic surveys with thermal modeling, backed up by measured permafrost properties and radiocarbon ages, to reveal closed-talik geometry associated with a thermokarst lake in continuous permafrost. To improve access to talik geometry data, we conducted surveys along three transient electromagnetic transects perpendicular to lakeshores with different decadal-scale expansion rates of 0.16, 0.38, and 0.58m/year. We modeled thermal development of the talik using boundary conditions based on field data from the lake, surrounding permafrost and a borehole, independent of the transient electromagnetics. A talik depth of 91m was determined from analysis of the transient electromagnetic surveys. Using a lake initiation age of 1400years before present and available subsurface properties the results from thermal modeling of the lake center arrived at a best estimate talk depth of 80m, which is on the same order of magnitude as the results from the transient electromagnetic survey. Our approach has provided a noninvasive estimate of talik geometry suitable for comparable settings throughout circum-Arctic coastal lowland regions.
Arctic lowlands are characterized by large numbers of small waterbodies, which are known to affect surface energy budgets and the global carbon cycle. Statistical analysis of their size distributions has been hindered by the shortage of observations at sufficiently high spatial resolutions. This situation has now changed with the high-resolution (<5 m) circum-Arctic Permafrost Region Pond and Lake (PeRL) database recently becoming available. We have used this database to make the first consistent, high-resolution estimation of Arctic waterbody size distributions, with surface areas ranging from 0.0001 km(2) (100 m(2)) to 1 km(2). We found that the size distributions varied greatly across the thirty study regions investigated and that there was no single universal size distribution function (including power-law distribution functions) appropriate across all of the study regions. We did, however, find close relationships between the statistical moments (mean, variance, and skewness) of the waterbody size distributions from different study regions. Specifically, we found that the spatial variance increased linearly with mean waterbody size (R-2 = 0.97, p < 2.2e-16) and that the skewness decreased approximately hyperbolically. We have demonstrated that these relationships (1) hold across the 30 Arctic study regions covering a variety of (bio)climatic and permafrost zones, (2) hold over time in two of these study regions for which multi-decadal satellite imagery is available, and (3) can be reproduced by simulating rising water levels in a high-resolution digital elevation model. The consistent spatial and temporal relationships between the statistical moments of the waterbody size distributions underscore the dominance of topographic controls in lowland permafrost areas. These results provide motivation for further analyses of the factors involved in waterbody development and spatial distribution and for investigations into the possibility of using statistical moments to predict future hydrologic dynamics in the Arctic.
Subsea permafrost is perennially cryotic earth material that lies offshore. Most submarine permafrost is relict terrestrial permafrost beneath the Arctic shelf seas, was inundated after the last glaciation, and has been warming and thawing ever since. It is a reservoir and confining layer for gas hydrates and has the potential to release greenhouse gases and affect global climate change. Furthermore, subsea permafrost thaw destabilizes coastal infrastructure. While numerous studies focus on its distribution and rate of thaw over glacial timescales, these studies have not been brought together and examined in their entirety to assess rates of thaw beneath the Arctic Ocean. In addition, there is still a large gap in our understanding of sub-aquatic permafrost processes on finer spatial and temporal scales. The degradation rate of subsea permafrost is influenced by the initial conditions upon submergence. Terrestrial permafrost that has already undergone warming, partial thawing or loss of ground ice may react differently to inundation by seawater compared to previously undisturbed ice-rich permafrost. Heat conduction models are sufficient to model the thaw of thick subsea permafrost from the bottom, but few studies have included salt diffusion for top-down chemical degradation in shallow waters characterized by mean annual cryotic conditions on the seabed. Simulating salt transport is critical for assessing degradation rates for recently inundated permafrost, which may accelerate in response to warming shelf waters, a lengthening open water season, and faster coastal erosion rates. In the nearshore zone, degradation rates are also controlled by seasonal processes like bedfast ice, brine injection, seasonal freezing under floating ice conditions and warm freshwater discharge from large rivers. The interplay of all these variables is complex and needs further research. To fill this knowledge gap, this thesis investigates sub-aquatic permafrost along the southern coast of the Bykovsky Peninsula in eastern Siberia. Sediment cores and ground temperature profiles were collected at a freshwater thermokarst lake and two thermokarst lagoons in 2017. At this site, the coastline is retreating, and seawater is inundating various types of permafrost: sections of ice-rich Pleistocene permafrost (Yedoma) cliffs at the coastline alternate with lagoons and lower elevation previously thawed and refrozen permafrost basins (Alases). Electrical resistivity surveys with floating electrodes were carried out to map ice-bearing permafrost and taliks (unfrozen zones in the permafrost, usually formed beneath lakes) along the diverse coastline and in the lagoons. Combined with the borehole data, the electrical resistivity results permit estimation of contemporary ice-bearing permafrost characteristics, distribution, and occasionally, thickness. To conceptualize possible geomorphological and marine evolutionary pathways to the formation of the observed layering, numerical models were applied. The developed model incorporates salt diffusion and seasonal dynamics at the seabed, including bedfast ice. Even along coastlines with mean annual non-cryotic boundary conditions like the Bykovsky Peninsula, the modelling results show that salt diffusion minimizes seasonal freezing of the seabed, leading to faster degradation rates compared to models without salt diffusion. Seasonal processes are also important for thermokarst lake to lagoon transitions because lagoons can generate cold hypersaline conditions underneath the ice cover. My research suggests that ice-bearing permafrost can form in a coastal lagoon environment, even under floating ice. Alas basins, however, may degrade more than twice as fast as Yedoma permafrost in the first several decades of inundation. In addition to a lower ice content compared to Yedoma permafrost, Alas basins may be pre-conditioned with salt from adjacent lagoons. Considering the widespread distribution of thermokarst in the Arctic, its integration into geophysical models and offshore surveys is important to quantify and understand subsea permafrost degradation and aggradation. Through numerical modelling, fieldwork, and a circum-Arctic review of subsea permafrost literature, this thesis provides new insights into sub-aquatic permafrost evolution in saline coastal environments.
Lakes are a ubiquitous landscape feature in northern permafrost regions. They have a strong impact on carbon, energy and water fluxes and can be quite responsive to climate change. The monitoring of lake change in northern high latitudes, at a sufficiently accurate spatial and temporal resolution, is crucial for understanding the underlying processes driving lake change. To date, lake change studies in permafrost regions were based on a variety of different sources, image acquisition periods and single snapshots, and localized analysis, which hinders the comparison of different regions. Here, we present a methodology based on machine-learning based classification of robust trends of multi-spectral indices of Landsat data (TM, ETM+, OLI) and object-based lake detection, to analyze and compare the individual, local and regional lake dynamics of four different study sites (Alaska North Slope, Western Alaska, Central Yakutia, Kolyma Lowland) in the northern permafrost zone from 1999 to 2014. Regional patterns of lake area change on the Alaska North Slope (-0.69%), Western Alaska (-2.82%), and Kolyma Lowland (-0.51%) largely include increases due to thermokarst lake expansion, but more dominant lake area losses due to catastrophic lake drainage events. In contrast, Central Yakutia showed a remarkable increase in lake area of 48.48%, likely resulting from warmer and wetter climate conditions over the latter half of the study period. Within all study regions, variability in lake dynamics was associated with differences in permafrost characteristics, landscape position (i.e., upland vs. lowland), and surface geology. With the global availability of Landsat data and a consistent methodology for processing the input data derived from robust trends of multi-spectral indices, we demonstrate a transferability, scalability and consistency of lake change analysis within the northern permafrost region.