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Thermokarst lake landscapes are permafrost regions, which are prone to rapid (on seasonal to decadal time scales) changes, affecting carbon and nitrogen cycles. However, there is a high degree of uncertainty related to the balance between carbon and nitrogen cycling and storage. We collected 12 permafrost soil cores from six drained thermokarst lake basins (DTLBs) along a chronosequence north of Teshekpuk Lake in northern Alaska and analyzed them for carbon and nitrogen contents. For comparison, we included three lacustrine cores from an adjacent thermokarst lake and one soil core from a non thermokarst affected remnant upland. This allowed to calculate the carbon and nitrogen stocks of the three primary landscape units (DTLB, lake, and upland), to reconstruct the landscape history, and to analyze the effect of thermokarst lake formation and drainage on carbon and nitrogen stocks. We show that carbon and nitrogen contents and the carbon-nitrogen ratio are considerably lower in sediments of extant lakes than in the DTLB or upland cores indicating degradation of carbon during thermokarst lake formation. However, we found similar amounts of total carbon and nitrogen stocks due to the higher density of lacustrine sediments caused by the lack of ground ice compared to DTLB sediments. In addition, the radiocarbon-based landscape chronology for the past 7,000years reveals five successive lake stages of partially, spatially overlapping DTLBs in the study region, reflecting the dynamic nature of ice-rich permafrost deposits. With this study, we highlight the importance to include these dynamic landscapes in future permafrost carbon feedback models. Plain Language Summary When permanently frozen soils (permafrost) contain ice-rich sediments, the thawing of this permafrost causes the surface to sink, which may result in lake formation. This process, the thaw of ice-rich permafrost and melting of ground ice leads to characteristic landforms-known as thermokarst. Once such a thaw process is initiated in ice-rich sediments, a thaw lake forms and grows by shoreline erosion, eventually expanding until a drainage pathway is encountered and the lake eventually drains, resulting in a drained thermokarst lake basin. In our study, we show that such a thermokarst-affected landscape north of Teshekpuk Lake in northern Alaska is shaped by repeated thaw lake formation and lake drainage events during the past 7,000years, highlighting the dynamic nature of these landscapes. These landscape-scale processes have a big effect on the carbon and nitrogen stored in permafrost soils. We show that large amounts of carbon (>45kg C/m(2)) and nitrogen (>2.6kg N/m(2)) are stored in unfrozen lake sediments and in frozen soil sediments. The findings are important when considering the potential effect that permafrost thaw has for the global climate through releasing carbon and nitrogen, which was frozen and therefore locked away for millennia, from the active carbon cycle.
Climatic and limnological changes at Lake Karakul (Tajikistan) during the last similar to 29 cal ka
(2017)
We present results of analyses on a sediment core from Lake Karakul, located in the eastern Pamir Mountains, Tajikistan. The core spans the last similar to 29 cal ka. We investigated and assessed processes internal and external to the lake to infer changes in past moisture availability. Among the variables used to infer lake-external processes, high values of grain-size end-member (EM) 3 (wide grain-size distribution that reflects fluvial input) and high Sr/Rb and Zr/Rb ratios (coinciding with coarse grain sizes), are indicative of moister conditions. High values in EM1, EM2 (peaks of small grain sizes that reflect long-distance dust transport or fine, glacially derived clastic input) and TiO2 (terrigenous input) are thought to reflect greater influence of dry air masses, most likely of Westerly origin. High input of dust from distant sources, beginning before the Last Glacial Maximum (LGM) and continuing to the late glacial, reflects the influence of dry Westerlies, whereas peaks in fluvial input suggest increased moisture availability. The early to early-middle Holocene is characterised by coarse mean grain sizes, indicating constant, high fluvial input and moister conditions in the region. A steady increase in terrigenous dust and a decrease in fluvial input from 6.6 cal ka BP onwards points to the Westerlies as the predominant atmospheric circulation through to present, and marks a return to drier and even arid conditions in the area. Proxies for productivity (TOC, TOC/TN, TOCBr), redox potential (Fe/Mn) and changes in the endogenic carbonate precipitation (TIC, delta(18) OCarb) indicate changes within the lake. Low productivity characterised the lake from the late Pleistocene until 6.6 cal ka BP, and increased rapidly afterwards. Lake level remained low until the LGM, but water depth increased to a maximum during the late glacial and remained high into the early Holocene. Subsequently, the water level decreased to its present stage. Today the lake system is mainly climatically controlled, but the depositional regime is also driven by internal limnogeological processes.
Arctic lakes located in permafrost regions are susceptible to catastrophic drainage. In this study, we reconstructed historical lake drainage events on the western Arctic Coastal Plain of Alaska between 1955 and 2017 using USGS topographic maps, historical aerial photography (1955), and Landsat Imagery (ca. 1975, ca. 2000, and annually since 2000). We identified 98 lakes larger than 10 ha that partially (>25% of area) or completely drained during the 62-year period. Decadal-scale lake drainage rates progressively declined from 2.0 lakes/yr (1955-1975), to 1.6 lakes/yr (1975-2000), and to 1.2 lakes/yr (2000-2017) in the ~30,000-km(2) study area. Detailed Landsat trend analysis between 2000 and 2017 identified two years, 2004 and 2006, with a cluster (five or more) of lake drainages probably associated with bank overtopping or headward erosion. To identify future potential lake drainages, we combined the historical lake drainage observations with a geospatial dataset describing lake elevation, hydrologic connectivity, and adjacent lake margin topographic gradients developed with a 5-m-resolution digital surface model. We identified ~1900 lakes likely to be prone to drainage in the future. Of the 20 lakes that drained in the most recent study period, 85% were identified in this future lake drainage potential dataset. Our assessment of historical lake drainage magnitude, mechanisms and pathways, and identification of potential future lake drainages provides insights into how arctic lowland landscapes may change and evolve in the coming decades to centuries.
Arctic lakes located in permafrost regions are susceptible to catastrophic drainage. In this study, we reconstructed historical lake drainage events on the western Arctic Coastal Plain of Alaska between 1955 and 2017 using USGS topographic maps, historical aerial photography (1955), and Landsat Imagery (ca. 1975, ca. 2000, and annually since 2000). We identified 98 lakes larger than 10 ha that partially (>25% of area) or completely drained during the 62-year period. Decadal-scale lake drainage rates progressively declined from 2.0 lakes/yr (1955-1975), to 1.6 lakes/yr (1975-2000), and to 1.2 lakes/yr (2000-2017) in the ~30,000-km(2) study area. Detailed Landsat trend analysis between 2000 and 2017 identified two years, 2004 and 2006, with a cluster (five or more) of lake drainages probably associated with bank overtopping or headward erosion. To identify future potential lake drainages, we combined the historical lake drainage observations with a geospatial dataset describing lake elevation, hydrologic connectivity, and adjacent lake margin topographic gradients developed with a 5-m-resolution digital surface model. We identified ~1900 lakes likely to be prone to drainage in the future. Of the 20 lakes that drained in the most recent study period, 85% were identified in this future lake drainage potential dataset. Our assessment of historical lake drainage magnitude, mechanisms and pathways, and identification of potential future lake drainages provides insights into how arctic lowland landscapes may change and evolve in the coming decades to centuries.
Lakes are dominant and diverse landscape features in the Arctic, but conventional land cover classification schemes typically map them as a single uniform class. Here, we present a detailed lake-centric geospatial database for an Arctic watershed in northern Alaska. We developed a GIS dataset consisting of 4362 lakes that provides information on lake morphometry, hydrologic connectivity, surface area dynamics, surrounding terrestrial ecotypes, and other important conditions describing Arctic lakes. Analyzing the geospatial database relative to fish and bird survey data shows relations to lake depth and hydrologic connectivity, which are being used to guide research and aid in the management of aquatic resources in the National Petroleum Reserve in Alaska. Further development of similar geospatial databases is needed to better understand and plan for the impacts of ongoing climate and land-use changes occurring across lake-rich landscapes in the Arctic.
The Arctic is greatly impacted by climate change. The increase in air temperature drives the thawing of permafrost and an increase in coastal erosion and river discharge. This leads to a greater input of sediment and organic matter into coastal waters, which substantially impacts the ecosystems by reducing light transmission through the water column and altering the biogeochemistry, but also the subsistence economy of local people, and changes in climate because of the transformation of organic matter into greenhouse gases. Yet, the quantification of suspended sediment in Arctic coastal and nearshore waters remains unsatisfactory due to the absence of dedicated algorithms to resolve the high loads occurring in the close vicinity of the shoreline. In this study we present the Arctic Nearshore Turbidity Algorithm (ANTA), the first reflectance-turbidity relationship specifically targeted towards Arctic nearshore waters that is tuned with in-situ measurements from the nearshore waters of Herschel Island Qikiqtaruk in the western Canadian Arctic. A semi-empirical model was calibrated for several relevant sensors in ocean color remote sensing, including MODIS, Sentinel 3 (OLCI), Landsat 8 (OLI), and Sentinel 2 (MSI), as well as the older Landsat sensors TM and ETM+. The ANTA performed better with Landsat 8 than with Sentinel 2 and Sentinel 3. The application of the ANTA to Sentinel 2 imagery that matches in-situ turbidity samples taken in Adventfjorden, Svalbard, shows transferability to nearshore areas beyond Herschel Island Qikiqtaruk.
The Arctic is greatly impacted by climate change. The increase in air temperature drives the thawing of permafrost and an increase in coastal erosion and river discharge. This leads to a greater input of sediment and organic matter into coastal waters, which substantially impacts the ecosystems by reducing light transmission through the water column and altering the biogeochemistry, but also the subsistence economy of local people, and changes in climate because of the transformation of organic matter into greenhouse gases. Yet, the quantification of suspended sediment in Arctic coastal and nearshore waters remains unsatisfactory due to the absence of dedicated algorithms to resolve the high loads occurring in the close vicinity of the shoreline. In this study we present the Arctic Nearshore Turbidity Algorithm (ANTA), the first reflectance-turbidity relationship specifically targeted towards Arctic nearshore waters that is tuned with in-situ measurements from the nearshore waters of Herschel Island Qikiqtaruk in the western Canadian Arctic. A semi-empirical model was calibrated for several relevant sensors in ocean color remote sensing, including MODIS, Sentinel 3 (OLCI), Landsat 8 (OLI), and Sentinel 2 (MSI), as well as the older Landsat sensors TM and ETM+. The ANTA performed better with Landsat 8 than with Sentinel 2 and Sentinel 3. The application of the ANTA to Sentinel 2 imagery that matches in-situ turbidity samples taken in Adventfjorden, Svalbard, shows transferability to nearshore areas beyond Herschel Island Qikiqtaruk.
Arctic tundra ecosystems have experienced unprecedented change associated with climate warming over recent decades. Across the Pan-Arctic, vegetation productivity and surface greenness have trended positively over the period of satellite observation. However, since 2011 these trends have slowed considerably, showing signs of browning in many regions. It is unclear what factors are driving this change and which regions/landforms will be most sensitive to future browning. Here we provide evidence linking decadal patterns in arctic greening and browning with regional climate change and local permafrost-driven landscape heterogeneity. We analyzed the spatial variability of decadal-scale trends in surface greenness across the Arctic Coastal Plain of northern Alaska (similar to 60,000 km(2)) using the Landsat archive (1999-2014), in combination with novel 30 m classifications of polygonal tundra and regional watersheds, finding landscape heterogeneity and regional climate change to be the most important factors controlling historical greenness trends. Browning was linked to increased temperature and precipitation, with the exception of young landforms (developed following lake drainage), which will likely continue to green. Spatiotemporal model forecasting suggests carbon uptake potential to be reduced in response to warmer and/or wetter climatic conditions, potentially increasing the net loss of carbon to the atmosphere, at a greater degree than previously expected.
Arctic tundra ecosystems have experienced unprecedented change associated with climate warming over recent decades. Across the Pan-Arctic, vegetation productivity and surface greenness have trended positively over the period of satellite observation. However, since 2011 these trends have slowed considerably, showing signs of browning in many regions. It is unclear what factors are driving this change and which regions/landforms will be most sensitive to future browning. Here we provide evidence linking decadal patterns in arctic greening and browning with regional climate change and local permafrost-driven landscape heterogeneity. We analyzed the spatial variability of decadal-scale trends in surface greenness across the Arctic Coastal Plain of northern Alaska (similar to 60,000 km(2)) using the Landsat archive (1999-2014), in combination with novel 30 m classifications of polygonal tundra and regional watersheds, finding landscape heterogeneity and regional climate change to be the most important factors controlling historical greenness trends. Browning was linked to increased temperature and precipitation, with the exception of young landforms (developed following lake drainage), which will likely continue to green. Spatiotemporal model forecasting suggests carbon uptake potential to be reduced in response to warmer and/or wetter climatic conditions, potentially increasing the net loss of carbon to the atmosphere, at a greater degree than previously expected.
Arctic tundra landscapes are composed of a complex mosaic of patterned ground features, varying in soil moisture, vegetation composition, and surface hydrology over small spatial scales (10-100 m). The importance of microtopography and associated geomorphic landforms in influencing ecosystem structure and function is well founded, however, spatial data products describing local to regional scale distribution of patterned ground or polygonal tundra geomorphology are largely unavailable. Thus, our understanding of local impacts on regional scale processes (e.g., carbon dynamics) may be limited. We produced two key spatiotemporal datasets spanning the Arctic Coastal Plain of northern Alaska (similar to 60,000 km(2)) to evaluate climate-geomorphological controls on arctic tundra productivity change, using (1) a novel 30m classification of polygonal tundra geomorphology and (2) decadal-trends in surface greenness using the Landsat archive (1999-2014). These datasets can be easily integrated and adapted in an array of local to regional applications such as (1) upscaling plot-level measurements (e.g., carbon/energy fluxes), (2) mapping of soils, vegetation, or permafrost, and/or (3) initializing ecosystem biogeochemistry, hydrology, and/or habitat modeling.