Alexandra Veremeeva

Dr. Alexandra Veremeeva

orcid

Research Focus & Metrics

Academic Career Length

18Years (2009-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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26 February 2021 in Science Advances
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UMUmakant Mishra
Umakant Mishra
GHGustaf Hugelius
Gustaf Hugelius
ESEitan Shelef
Eitan Shelef
YYYuanhe Yang
Yuanhe Yang
JSJens Strauss
Jens Strauss
AOAndrew Orr
Andrew Orr
Large stocks of soil organic carbon (SOC) have accumulated in the Northern Hemisphere permafrost region, but their current amounts and future fate remain uncertain. By analyzing dataset combining >2700 soil profiles with environmental variables in a geospatial framework, we generated spatially explicit estimates of permafrost-region SOC stocks, quantified spatial heterogeneity, and identified key environmental predictors. We estimated that 1014−175+194 Pg C are stored in the top 3 m of permafrost region soils. The greatest uncertainties occurred in circumpolar toe-slope positions and in flat areas of the Tibetan region. We found that soil wetness index and elevation are the dominant topographic controllers and surface air temperature (circumpolar region) and precipitation (Tibetan region) are significant climatic controllers of SOC stocks. Our results provide first high-resolution geospatial assessment of permafrost region SOC stocks and their relationships with environmental factors, which are crucial for modeling the response of permafrost affected soils to changing climate.

1 September 2017 in Earth-Science Reviews
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Journal Article
Open access
JSJens Strauss
Jens Strauss
LSLutz Schirrmeister
Lutz Schirrmeister
GGGuido Grosse
Guido Grosse
DFDaniel Fortier
Daniel Fortier
GHGustaf Hugelius
Gustaf Hugelius
AVAlexandra Veremeeva
Alexandra Veremeeva
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

27 June 2017 in Remote Sensing
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Journal Article
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INIngmar Nitze
Ingmar Nitze
GGGuido Grosse
Guido Grosse
Benjamin JonesBenjamin Jones
Benjamin Jones
CAChristopher Arp
Christopher Arp
MUMathias Ulrich
Mathias Ulrich
AVAlexandra Veremeeva
Alexandra Veremeeva
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.

6 June 2017 in Earth System Science Data
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Journal Article
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SMSina Muster
Sina Muster
KRKurt Roth
Kurt Roth
MLMoritz Langer
Moritz Langer
SLStephan Lange
Stephan Lange
FAFabio Cresto Aleina
Fabio Cresto Aleina
JBJulia Boike
Julia Boike
Ponds and lakes are abundant in Arctic permafrost lowlands. They play an important role in Arctic wetland ecosystems by regulating carbon, water, and energy fluxes and providing freshwater habitats. However, ponds, i.e., waterbodies with surface areas smaller than 1. 0 × 104 m2, have not been inventoried on global and regional scales. The Permafrost Region Pond and Lake (PeRL) database presents the results of a circum-Arctic effort to map ponds and lakes from modern (2002–2013) high-resolution aerial and satellite imagery with a resolution of 5 m or better. The database also includes historical imagery from 1948 to 1965 with a resolution of 6 m or better. PeRL includes 69 maps covering a wide range of environmental conditions from tundra to boreal regions and from continuous to discontinuous permafrost zones. Waterbody maps are linked to regional permafrost landscape maps which provide information on permafrost extent, ground ice volume, geology, and lithology. This paper describes waterbody classification and accuracy, and presents statistics of waterbody distribution for each site. Maps of permafrost landscapes in Alaska, Canada, and Russia are used to extrapolate waterbody statistics from the site level to regional landscape units. PeRL presents pond and lake estimates for a total area of 1. 4 × 106 km2 across the Arctic, about 17 % of the Arctic lowland ( < 300 m a.s.l.) land surface area. PeRL waterbodies with sizes of 1. 0 × 106 m2 down to 1. 0 × 102 m2 contributed up to 21 % to the total water fraction. Waterbody density ranged from 1. 0 × 10 to 9. 4 × 101 km−2. Ponds are the dominant waterbody type by number in all landscapes representing 45–99 % of the total waterbody number. The implementation of PeRL size distributions in land surface models will greatly improve the investigation and projection of surface inundation and carbon fluxes in permafrost lowlands. Waterbody maps, study area boundaries, and maps of regional permafrost landscapes including detailed metadata are available at https://doi.pangaea.de/10.1594/PANGAEA.868349.

6 January 2021 in Remote Sensing
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Journal Article
Open access
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AVAlexandra Veremeeva
Alexandra Veremeeva
INIngmar Nitze
Ingmar Nitze
FGFrank Günther
Frank Günther
GGGuido Grosse
Guido Grosse
Elizaveta RivkinaElizaveta Rivkina
Elizaveta Rivkina
Thermokarst lakes are widespread in Arctic lowlands. Under a warming climate, landscapes with highly ice-rich Yedoma Ice Complex (IC) deposits are particularly vulnerable, and thermokarst lake area dynamics serve as an indicator for their response to climate change. We conducted lake change trend analysis for a 44,500 km2 region of the Kolyma Lowland using Landsat imagery in conjunction with TanDEM-X digital elevation model and Quaternary Geology map data. We delineated yedoma–alas relief types with different yedoma fractions, serving as a base for geospatial analysis of lake area dynamics. We quantified lake changes over the 1999–2018 period using machine-learning-based classification of robust trends of multi-spectral indices of Landsat data and object-based long-term lake detection. We analyzed the lake area dynamics separately for 1999–2013 and 1999–2018 periods, including the most recent five years that were characterized by very high precipitation. Comparison of drained lake basin area with thermokarst lake extents reveal the overall limnicity decrease by 80% during the Holocene. Current climate warming and wetting in the region led to a lake area increase by 0.89% for the 1999–2013 period and an increase by 4.15% for the 1999–2018 period. We analyzed geomorphological factors impacting modern lake area changes for both periods such as lake size, elevation, and yedoma–alas relief type. We detected a lake area expansion trend in high yedoma fraction areas indicating ongoing Yedoma IC degradation by lake thermokarst. Our concept of differentiating yedoma–alas relief types helps to characterize landscape-scale lake area changes and could potentially be applied for refined assessments of greenhouse gas emissions in Yedoma regions. Comprehensive geomorphological inventories of Yedoma regions using geospatial data provide a better understanding of the extent of thermokarst processes during the Holocene and the pre-conditioning of modern thermokarst lake area dynamics.

23 October 2024 in The Cryosphere
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Journal Article
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NNNina Nesterova
Nina Nesterova
MLMarina Leibman
Marina Leibman
AKAlexander Kizyakov
Alexander Kizyakov
Hugues LantuitHugues Lantuit
Hugues Lantuit
ITIlya Tarasevich
Ilya Tarasevich
GGGuido Grosse
Guido Grosse
Retrogressive thaw slumps (RTSs) are spectacular landforms that occur due to the thawing of ice-rich permafrost or melting of massive ground ice, often in hillslope terrain. RTSs occur in the Arctic, the subarctic, and high mountain (Qinghai–Tibet Plateau) permafrost regions and are observed to expand in size and number due to climate warming. As the observation of RTSs is receiving more and more attention due to their important role in permafrost thaw; impacts on topography; mobilization of sediment, carbon, nutrients, and contaminants; and their effects on downstream hydrology and water quality, the thematic breadth of studies increases and scientists from different scientific backgrounds and perspectives contribute to new RTS research. At this point, a wide range of terminologies originating from different scientific schools is used, and we identified the need to provide an overview of variable characteristics of RTSs to clarify terminologies and ease the understanding of the literature related to RTS processes, dynamics, and feedbacks. We review the theoretical geomorphological background of RTS formation and landform characteristics to provide an up-to-date understanding of the current views on terminology and underlying processes. The presented overview can be used not only by the international permafrost community but also by scientists working on ecological, hydrological, and biogeochemical consequences of RTS occurrence and by remote-sensing specialists developing automated methods for mapping RTS dynamics. The review will foster a better understanding of the nature and diversity of RTS phenomena and provide a useful base for experts in the field but also ease the introduction to the topic of RTSs for scientists who are new to it.