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Permafrost is a distinct feature of the terrestrial Arctic and is vulnerable to climate warming. Permafrost degrades in different ways, including deepening of a seasonally unfrozen surface and localized but rapid development of deep thaw features. Pleistocene ice-rich permafrost with syngenetic ice-wedges, termed Yedoma deposits, are widespread in Siberia, Alaska, and Yukon, Canada and may be especially prone to rapid-thaw processes. Freeze-locked organic matter in such deposits can be re-mobilized on short time-scales and contribute to a carbon-cycle climate feedback. Here we synthesize the characteristics and vulnerability of Yedoma deposits by synthesizing studies on the Yedoma origin and the associated organic carbon pool. We suggest that Yedoma deposits accumulated under periglacial weathering, transport, and deposition dynamics in non-glaciated regions during the late Pleistocene until the beginning of late glacial warming. The deposits formed due to a combination of aeolian, colluvial, nival, and alluvial deposition and simultaneous ground ice accumulation. We found up to 130 gigatons organic carbon in Yedoma, parts of which are well-preserved and available for fast decomposition after thaw. Based on incubation experiments, up to 10% of the Yedoma carbon is considered especially decomposable and may be released upon thaw. The substantial amount of ground ice in Yedoma makes it highly vulnerable to disturbances such as thermokarst and thermo-erosion processes. Mobilization of permafrost carbon is expected to increase under future climate warming. Our synthesis results underline the need of accounting for Yedoma carbon stocks in next generation Earth-System-Models for a more complete representation of the permafrost-carbon feedback.
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.
Thermokarst lakes are assumed to develop cyclically, driven by processes that are triggered by climate and maintained by internal feedbacks that may trigger lake drainage. However, the duration of these cycles remains uncertain, as well as whether or not they affect the stabilization of lake ecosystems in permafrost regions over millennial time scales. Our research has combined investigations into modern lake-to-lake variability with a study of the long-term development of individual lakes. We have investigated the physico-chemical and diatom compositions of a set of 101 lakes with a variety of different origins in central Yakutia (Eastern Siberia), including thermokarst lakes, fluvial-erosion thermokarst lakes, fluvial-erosion lakes, and dune lakes. We found a significant relationship between lake genesis and the present-day variability in environmental and diatom characteristics, as revealed by multi-response permutation procedures, indicator species analyses, and redundancy analyses. Environmental parameters also exhibit a significant correlation with variations in the diatom data, for which they may have been to a substantial extent responsible. Mg and SO4 concentrations, together with pH and water depth, were identified as the most important parameters, influencing the variations in the diatom data almost as much as the entire environmental parameter set. We were therefore able to establish a robust Mg-diatom transfer function, which was then applied to three Holocene lake records. From these reconstructions, together with a general interpretation of the diatom record (including, e.g., the ratio between benthic/epiphytic and planktonic taxa), we have been able to infer that all three of these lakes show (1) a continuous record with no desiccation events, (2) high lake water-levels during the early Holocene, (3) centennial to millennial scale variability, and (4) high levels of variability during the early Holocene but rather stable conditions during the late Holocene (a feature that is also known from other sites around the world). We therefore concluded that the development of these three lakes was mainly driven directly by the climate, rather than by thaw lake cycling.