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Landscape Heterogeneity

How does landscape organization control permafrost evolution and associated C and nutrient fluxes in a changing environment?

Landscape heterogeneity considers how vegetation, biogeochemistry, and hydrology are influenced by regional landforms such as ridges, valleys, and drainage basins. Variation in landscape form and function are simplified for input into models while still retaining fine-scale features with the strongest influence on climate feedbacks.

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Publications

2024

  • Fiolleau, Sylvain, et al. “Insights on Seasonal Solifluction Processes in Warm Permafrost Arctic Landscape Using a Dense Monitoring Approach across Adjacent Hillslopes”. Environmental Research Letters, vol. 19, 2024, https://doi.org/10.1088/1748-9326/ad28dc.
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  • Wang, Chen, et al. “Local-Scale Heterogeneity of Soil Thermal Dynamics and Controlling Factors in a Discontinuous Permafrost Region”. Environmental Research Letters, vol. 19, 2024, https://doi.org/10.1088/1748-9326/ad27bb .
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2023

  • Painter, Scott L., et al. “Drying of Tundra Landscapes Will Limit Subsidence-Induced Acceleration of Permafrost Thaw”. Proceedings of the National Academy of Sciences, vol. 120, no. 8, 2023, https://doi.org/10.1073/pnas.2212171120.
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  • Uhlemann, Sebastian, et al. “Estimating Permafrost Distribution Using Co-Located Temperature and Electrical Resistivity Measurements”. Geophysical Research Letters, vol. 50, 2023, https://doi.org/10.1029/2023GL103987.
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  • Thaler, Evan A., et al. “High-Resolution Maps of Near-Surface Permafrost for Three Watersheds on the Seward Peninsula, Alaska Derived From Machine Learning”. Earth and Space Science, vol. 10, 2023, https://doi.org/10.1029/2023EA003015.
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  • Wielandt, Stijn, et al. “TDD LoRa and Delta Encoding in Low-Power Networks of Environmental Sensor Arrays for Temperature and Deformation Monitoring”. Journal of Signal Processing Systems, 2023, https://doi.org/10.1007/s11265-023-01834-2.
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2022

  • Shirley, Ian A., et al. “Near‐Surface Hydrology and Soil Properties Drive Heterogeneity in Permafrost Distribution, Vegetation Dynamics, and Carbon Cycling in a Sub‐Arctic Watershed”. Journal of Geophysical Research: Biogeosciences, vol. 127, no. 9, 2022, https://doi.org/10.1029/2022jg006864.
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  • Brunetti, Carlotta, et al. “Probabilistic Estimation of Depth-Resolved Profiles of Soil Thermal Diffusivity from Temperature Time Series”. Earth Surface Dynamics, vol. 10, no. 4, 2022, pp. 687-04, https://doi.org/10.5194/esurf-10-687-2022.
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2021

  • Debolskiy, Matvey V., et al. “Water Balance Response of Permafrost-Affected Watersheds to Changes in Air Temperatures”. Environmental Research Letters, vol. 16, no. 8, 2021, p. 084054, https://doi.org/10.1088/1748-9326/ac12f3.
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2020

  • Abolt, Charles J., et al. “Feedbacks Between Surface Deformation and Permafrost Degradation in Ice Wedge Polygons, Arctic Coastal Plain, Alaska”. Journal of Geophysical Research: Earth Surface, vol. 125, no. 3, 2020, https://doi.org/10.1029/2019jf005349.
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2017

  • Liljedahl, Anna K., et al. “Tundra Water Budget and Implications of Precipitation Underestimation”. Water Resources Research, vol. 53, no. 8, 2017, pp. 6472-86, https://doi.org/10.1002/2016wr020001.
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