@article{JonesArpGrosseetal.2020, author = {Jones, Benjamin M. and Arp, Christopher D. and Grosse, Guido and Nitze, Ingmar and Lara, Mark J. and Whitman, Matthew S. and Farquharson, Louise M. and Kanevskiy, Mikhail and Parsekian, Andrew D. and Breen, Amy L. and Ohara, Nori and Rangel, Rodrigo Correa and Hinkel, Kenneth M.}, title = {Identifying historical and future potential lake drainage events on the western Arctic coastal plain of Alaska}, series = {Permafrost and Periglacial Processes}, volume = {31}, journal = {Permafrost and Periglacial Processes}, number = {1}, publisher = {Wiley}, address = {New York}, doi = {10.1002/ppp.2038}, pages = {110 -- 127}, year = {2020}, abstract = {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.}, language = {en} } @misc{JonesArpGrosseetal.2020, author = {Jones, Benjamin M. and Arp, Christopher D. and Grosse, Guido and Nitze, Ingmar and Lara, Mark J. and Whitman, Matthew S. and Farquharson, Louise M. and Kanevskiy, Mikhail and Parsekian, Andrew D. and Breen, Amy L. and Ohara, Nori and Rangel, Rodrigo Correa and Hinkel, Kenneth M.}, title = {Identifying historical and future potential lake drainage events on the western Arctic coastal plain of Alaska}, series = {Zweitver{\"o}ffentlichungen der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe}, journal = {Zweitver{\"o}ffentlichungen der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe}, number = {1}, issn = {1866-8372}, doi = {10.25932/publishup-61043}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-610435}, pages = {20}, year = {2020}, abstract = {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.}, language = {en} } @article{RungeNitzeGrosse2021, author = {Runge, Alexandra and Nitze, Ingmar and Grosse, Guido}, title = {Remote sensing annual dynamics of rapid permafrost thaw disturbances with LandTrendr}, series = {Remote sensing of environment : an interdisciplinary journal}, volume = {268}, journal = {Remote sensing of environment : an interdisciplinary journal}, publisher = {Elsevier}, address = {New York}, issn = {0034-4257}, doi = {10.1016/j.rse.2021.112752}, pages = {18}, year = {2021}, abstract = {Permafrost is warming globally which leads to widespread permafrost thaw. Particularly ice-rich permafrost is vulnerable to rapid thaw and erosion, impacting whole landscapes and ecosystems. Retrogressive thaw slumps (RTS) are abrupt permafrost disturbances that expand by several meters each year and lead to an increased soil organic carbon release. Local Remote Sensing studies identified increasing RTS activity in the last two decades by increasing number of RTS or heightened RTS growth rates. However, a large-scale assessment across diverse permafrost regions and at high temporal resolution allowing to further determine RTS thaw dynamics and its main drivers is still lacking. In this study we apply the disturbance detection algorithm LandTrendr for automated large-scale RTS mapping and high temporal thaw dynamic assessment to North Siberia (8.1 x 106km2). We adapted and parametrised the temporal segmentation algorithm for abrupt disturbance detection to incorporate Landsat+Sentinel-2 mosaics, conducted spectral filtering, spatial masking and filtering, and a binary machine-learning object classification of the disturbance output to separate between RTS and false positives (F1 score: 0.609). Ground truth data for calibration and validation of the workflow was collected from 9 known RTS cluster sites using very highresolution RapidEye and PlanetScope imagery. Our study presents the first automated detection and assessment of RTS and their temporal dynamics at largescale for 2001-2019. We identified 50,895 RTS and a steady increase in RTS-affected area from 2001 to 2019 across North Siberia, with a more abrupt increase from 2016 onward. Overall the RTS-affected area increased by 331\% compared to 2000 (2000: 20,158 ha, 2001-2019: 66,699 ha). Contrary to this, 5 focus sites show spatiotemporal variability in their annual RTS dynamics, with alternating periods of increased and decreased RTS development, indicating a close relationship to thaw drivers. The majority of identified RTS was active from 2000 onward and only a small proportion initiated during the assessment period, indicating that the increase in RTS-affected area was mainly caused by enlarging existing RTS and not by new RTS. The detected increase in RTS dynamics suggests advancing permafrost thaw and underlines the importance of assessing abrupt permafrost disturbances with high spatial and temporal resolution at large-scales. Obtaining such consistent disturbance products will help to parametrise regional and global climate change models.}, language = {en} } @article{WieczorekKolmogorovKruseetal.2017, author = {Wieczorek, Mareike and Kolmogorov, Alexei and Kruse, Stefan and Jacobsen, Inga and Nitze, Ingmar and Nikolaev, Anatoly N. and Heinrich, Ingo and Pestryakova, Luidmila Agafyevna and Herzschuh, Ulrike}, title = {Disturbance-effects on treeline larch-stands in the lower Kolyma River area (NE Siberia)}, series = {Silva Fennica : a quarterly journal for forest science}, volume = {51}, journal = {Silva Fennica : a quarterly journal for forest science}, number = {3}, publisher = {The Finnish Society of Forest Science}, address = {Helsinki}, issn = {0037-5330}, doi = {10.14214/sf.1666}, pages = {20}, year = {2017}, abstract = {Tree stands in the boreal treeline ecotone are, in addition to climate change, impacted by disturbances such as fire, water-related disturbances and logging. We aim to understand how these disturbances affect growth, age structure, and spatial patterns of larch stands in the north-eastern Siberian treeline ecotone (lower Kolyma River region), an insufficiently researched region. Stand structure of Larix cajanderi Mayr was studied at seven sites impacted by disturbances. Maximum tree age ranged from 44 to 300 years. Young to medium-aged stands had, independent of disturbance type, the highest stand densities with over 4000 larch trees per ha. These sites also had the highest growth rates for tree height and stem diameter. Overall lowest stand densities were found in a polygonal field at the northern end of the study area, with larches growing in distinct " tree islands". At all sites, saplings are significantly clustered. Differences in fire severity led to contrasting stand structures with respect to tree, recruit, and overall stand densities. While a low severity fire resulted in low-density stands with high proportions of small and young larches, high severity fires resulted in high-density stands with high proportions of big trees. At waterdisturbed sites, stand structure varied between waterlogged and drained sites and latitude. These mixed effects of climate and disturbance make it difficult to predict future stand characteristics and the treeline position.}, language = {en} } @article{KleinLantuitHeimetal.2021, author = {Klein, Konstantin P. and Lantuit, Hugues and Heim, Birgit and Doxaran, David and Juhls, Bennet and Nitze, Ingmar and Walch, Daniela and Poste, Amanda and S{\o}reide, Janne E.}, title = {The Arctic Nearshore Turbidity Algorithm (ANTA)}, series = {Science of remote sensing}, volume = {4}, journal = {Science of remote sensing}, publisher = {Elsevier}, address = {Amsterdam}, issn = {2666-0172}, doi = {10.1016/j.srs.2021.100036}, pages = {11}, year = {2021}, abstract = {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.}, language = {en} } @misc{KleinLantuitHeimetal.2021, author = {Klein, Konstantin P. and Lantuit, Hugues and Heim, Birgit and Doxaran, David and Juhls, Bennet and Nitze, Ingmar and Walch, Daniela and Poste, Amanda and S{\o}reide, Janne E.}, title = {The Arctic Nearshore Turbidity Algorithm (ANTA)}, series = {Zweitver{\"o}ffentlichungen der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe}, journal = {Zweitver{\"o}ffentlichungen der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe}, number = {1250}, issn = {1866-8372}, doi = {10.25932/publishup-55369}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-553692}, pages = {11}, year = {2021}, abstract = {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.}, language = {en} } @article{LaraNitzeGrosseetal.2018, author = {Lara, Mark J. and Nitze, Ingmar and Grosse, Guido and Martin, Philip and McGuire, A. David}, title = {Reduced arctic tundra productivity linked with landform and climate change interactions}, series = {Scientific reports}, volume = {8}, journal = {Scientific reports}, publisher = {Nature Publ. Group}, address = {London}, issn = {2045-2322}, doi = {10.1038/s41598-018-20692-8}, pages = {10}, year = {2018}, abstract = {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.}, language = {en} } @article{JonesArpWhitmanetal.2017, author = {Jones, Benjamin M. and Arp, Christopher D. and Whitman, Matthew S. and Nigro, Debora and Nitze, Ingmar and Beaver, John and Gadeke, Anne and Zuck, Callie and Liljedahl, Anna and Daanen, Ronald and Torvinen, Eric and Fritz, Stacey and Grosse, Guido}, title = {A lake-centric geospatial database to guide research and inform management decisions in an Arctic watershed in northern Alaska experiencing climate and land-use changes}, series = {AMBIO}, volume = {46}, journal = {AMBIO}, publisher = {Springer}, address = {Dordrecht}, issn = {0044-7447}, doi = {10.1007/s13280-017-0915-9}, pages = {769 -- 786}, year = {2017}, abstract = {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.}, language = {en} } @article{TapeJonesArpetal.2018, author = {Tape, Ken D. and Jones, Benjamin M. and Arp, Christopher D. and Nitze, Ingmar and Grosse, Guido}, title = {Tundra be dammed}, series = {Global change biology}, volume = {24}, journal = {Global change biology}, number = {10}, publisher = {Wiley}, address = {Hoboken}, issn = {1354-1013}, doi = {10.1111/gcb.14332}, pages = {4478 -- 4488}, year = {2018}, abstract = {Increasing air temperatures are changing the arctic tundra biome. Permafrost is thawing, snow duration is decreasing, shrub vegetation is proliferating, and boreal wildlife is encroaching. Here we present evidence of the recent range expansion of North American beaver (Castor canadensis) into the Arctic, and consider how this ecosystem engineer might reshape the landscape, biodiversity, and ecosystem processes. We developed a remote sensing approach that maps formation and disappearance of ponds associated with beaver activity. Since 1999, 56 new beaver pond complexes were identified, indicating that beavers are colonizing a predominantly tundra region (18,293km(2)) of northwest Alaska. It is unclear how improved tundra stream habitat, population rebound following overtrapping for furs, or other factors are contributing to beaver range expansion. We discuss rates and likely routes of tundra beaver colonization, as well as effects on permafrost, stream ice regimes, and freshwater and riparian habitat. Beaver ponds and associated hydrologic changes are thawing permafrost. Pond formation increases winter water temperatures in the pond and downstream, likely creating new and more varied aquatic habitat, but specific biological implications are unknown. Beavers create dynamic wetlands and are agents of disturbance that may enhance ecosystem responses to warming in the Arctic.}, language = {en} } @article{NitzeGrosseJonesetal.2018, author = {Nitze, Ingmar and Grosse, Guido and Jones, Benjamin M. and Romanovsky, Vladimir E. and Boike, Julia}, title = {Remote sensing quantifies widespread abundance of permafrost region disturbances across the Arctic and Subarctic}, series = {Nature Communications}, volume = {9}, journal = {Nature Communications}, publisher = {Nature Publ. Group}, address = {London}, issn = {2041-1723}, doi = {10.1038/s41467-018-07663-3}, pages = {11}, year = {2018}, abstract = {Local observations indicate that climate change and shifting disturbance regimes are causing permafrost degradation. However, the occurrence and distribution of permafrost region disturbances (PRDs) remain poorly resolved across the Arctic and Subarctic. Here we quantify the abundance and distribution of three primary PRDs using time-series analysis of 30-m resolution Landsat imagery from 1999 to 2014. Our dataset spans four continental-scale transects in North America and Eurasia, covering similar to 10\% of the permafrost region. Lake area loss (-1.45\%) dominated the study domain with enhanced losses occurring at the boundary between discontinuous and continuous permafrost regions. Fires were the most extensive PRD across boreal regions (6.59\%), but in tundra regions (0.63\%) limited to Alaska. Retrogressive thaw slumps were abundant but highly localized (< 10(-5)\%). Our analysis synergizes the global-scale importance of PRDs. The findings highlight the need to include PRDs in next-generation land surface models to project the permafrost carbon feedback.}, language = {en} } @misc{NitzeGrosseJonesetal.2019, author = {Nitze, Ingmar and Grosse, Guido and Jones, B. M. and Romanovsky, Vladimir E. and Boike, Julia}, title = {Author Correction: Nitze, I; Grosse, G; Jones, B.M.; Romanovsky, V.E.; Boike, J.: Remote sensing quantifies widespread abundance of permafrost region disturbances across the Arctic and Subarctic. - Nature Communications. - 9 (2018), 5423}, series = {Nature Communications}, volume = {10}, journal = {Nature Communications}, publisher = {Nature Publ. Group}, address = {London}, issn = {2041-1723}, doi = {10.1038/s41467-019-08375-y}, pages = {1}, year = {2019}, language = {en} } @article{FuchsLenzJocketal.2019, author = {Fuchs, Matthias and Lenz, Josefine and Jock, Suzanne and Nitze, Ingmar and Jones, Benjamin M. and Strauss, Jens and G{\"u}nther, Frank and Grosse, Guido}, title = {Organic carbon and nitrogen stocks along a thermokarst lake sequence in Arctic Alaska}, series = {Journal of geophysical research : Biogeosciences}, volume = {124}, journal = {Journal of geophysical research : Biogeosciences}, number = {5}, publisher = {American Geophysical Union}, address = {Washington}, issn = {2169-8953}, doi = {10.1029/2018JG004591}, pages = {1230 -- 1247}, year = {2019}, abstract = {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.}, language = {en} } @misc{LaraNitzeGrosseetal.2018, author = {Lara, Mark J. and Nitze, Ingmar and Große, Guido and McGuire, David}, title = {Tundra landform and vegetation productivity trend maps for the Arctic Coastal Plain of northern Alaska}, series = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe}, journal = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe}, number = {1035}, issn = {1866-8372}, doi = {10.25932/publishup-45987}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-459875}, pages = {12}, year = {2018}, abstract = {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.}, language = {en} } @article{NitzeGrosseJonesetal.2017, author = {Nitze, Ingmar and Grosse, Guido and Jones, Benjamin M. and Arp, Christopher D. and Ulrich, Mathias and Fedorov, Alexander and Veremeeva, Alexandra}, title = {Landsat-Based Trend Analysis of Lake Dynamics across Northern Permafrost Regions}, series = {Remote sensing}, volume = {9}, journal = {Remote sensing}, publisher = {MDPI}, address = {Basel}, issn = {2072-4292}, doi = {10.3390/rs9070640}, pages = {28}, year = {2017}, abstract = {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.}, language = {en} } @article{HeineckeMischkeAdleretal.2017, author = {Heinecke, Liv and Mischke, Steffen and Adler, Karsten and Barth, Anja and Biskaborn, Boris and Plessen, Birgit and Nitze, Ingmar and Kuhn, Gerhard and Rajabov, Ilhomjon and Herzschuh, Ulrike}, title = {Climatic and limnological changes at Lake Karakul (Tajikistan) during the last similar to 29 cal ka}, series = {Journal of paleolimnolog}, volume = {58}, journal = {Journal of paleolimnolog}, publisher = {Springer}, address = {Dordrecht}, issn = {0921-2728}, doi = {10.1007/s10933-017-9980-0}, pages = {317 -- 334}, year = {2017}, abstract = {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.}, language = {en} } @article{LaraNitzeGrosseetal.2018, author = {Lara, Mark J. and Nitze, Ingmar and Große, Guido and McGuire, A. David}, title = {Tundra landform and vegetation productivity trend maps for the Arctic Coastal Plain of northern Alaska}, series = {Scientific Data}, volume = {5}, journal = {Scientific Data}, publisher = {Nature Publ. Group}, address = {London}, issn = {2052-4463}, doi = {10.1038/sdata.2018.58}, pages = {10}, year = {2018}, abstract = {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.}, language = {en} } @article{NitzeGrosse2016, author = {Nitze, Ingmar and Grosse, Guido}, title = {Detection of landscape dynamics in the Arctic Lena Delta with temporally dense Landsat time-series stacks}, series = {Remote sensing of environment : an interdisciplinary journal}, volume = {181}, journal = {Remote sensing of environment : an interdisciplinary journal}, publisher = {Elsevier}, address = {New York}, issn = {0034-4257}, doi = {10.1016/j.rse.2016.03.038}, pages = {27 -- 41}, year = {2016}, abstract = {Arctic permafrost landscapes are among the most vulnerable and dynamic landscapes globally, but due to their extent and remoteness most of the landscape changes remain unnoticed. In order to detect disturbances in these areas we developed an automated processing chain for the calculation and analysis of robust trends of key land surface indicators based on the full record of available Landsat TM, ETM +, and OLI data. The methodology was applied to the similar to 29,000 km(2) Lena Delta in Northeast Siberia, where robust trend parameters (slope, confidence intervals of the slope, and intercept) were calculated for Tasseled Cap Greenness, Wetness and Brightness, NDVI, and NDWI, and NDMI based on 204 Landsat scenes for the observation period between 1999 and 2014. The resulting datasets revealed regional greening trends within the Lena Delta with several localized hot-spots of change, particularly in the vicinity of the main river channels. With a 30-m spatial resolution various permafrost-thaw related processes and disturbances, such as thermokarst lake expansion and drainage, fluvial erosion, and coastal changes were detected within the Lena Delta region, many of which have not been noticed or described before. Such hotspots of permafrost change exhibit significantly different trend parameters compared to non-disturbed areas. The processed dataset, which is made freely available through the data archive PANGAEA, will be a useful resource for further process specific analysis by researchers and land managers. With the high level of automation and the use of the freely available Landsat archive data, the workflow is scalable and transferrable to other regions, which should enable the comparison of land surface changes in different permafrost affected regions and help to understand and quantify permafrost landscape dynamics. (C) 2016 Elsevier Inc. All rights reserved.}, language = {en} } @misc{NitzeGrosseJonesetal.2019, author = {Nitze, Ingmar and Grosse, Guido and Jones, Benjamin M. and Romanovsky, Vladimir E. and Boike, Julia}, title = {Remote sensing quantifies widespread abundance of permafrost region disturbances across the Arctic and Subarctic}, series = {Postprints der Universit{\"a}t Potsdam Mathematisch-Naturwissenschaftliche Reihe}, journal = {Postprints der Universit{\"a}t Potsdam Mathematisch-Naturwissenschaftliche Reihe}, number = {799}, issn = {1866-8372}, doi = {10.25932/publishup-42617}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-426171}, pages = {11}, year = {2019}, abstract = {Local observations indicate that climate change and shifting disturbance regimes are causing permafrost degradation. However, the occurrence and distribution of permafrost region disturbances (PRDs) remain poorly resolved across the Arctic and Subarctic. Here we quantify the abundance and distribution of three primary PRDs using time-series analysis of 30-m resolution Landsat imagery from 1999 to 2014. Our dataset spans four continental-scale transects in North America and Eurasia, covering ~10\% of the permafrost region. Lake area loss (-1.45\%) dominated the study domain with enhanced losses occurring at the boundary between discontinuous and continuous permafrost regions. Fires were the most extensive PRD across boreal regions (6.59\%), but in tundra regions (0.63\%) limited to Alaska. Retrogressive thaw slumps were abundant but highly localized (<10-5\%). Our analysis synergizes the global-scale importance of PRDs. The findings highlight the need to include PRDs in next-generation land surface models to project the permafrost carbon feedback.}, language = {en} } @misc{LaraNitzeGrosseetal.2018, author = {Lara, Mark J. and Nitze, Ingmar and Grosse, Guido and Martin, Philip and McGuire, A. David}, title = {Reduced arctic tundra productivity linked with landform and climate change interactions}, series = {Postprints der Universit{\"a}t Potsdam Mathematisch-Naturwissenschaftliche Reihe}, journal = {Postprints der Universit{\"a}t Potsdam Mathematisch-Naturwissenschaftliche Reihe}, number = {550}, issn = {1866-8372}, doi = {10.25932/publishup-42313}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-423132}, pages = {10}, year = {2018}, abstract = {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.}, language = {en} } @phdthesis{Nitze2017, author = {Nitze, Ingmar}, title = {Remote sensing of rapid permafrost landscape dynamics}, school = {Universit{\"a}t Potsdam}, pages = {151}, year = {2017}, language = {en} }