Description: ABSTRACT Time-domain electromagnetic data are conveniently inverted by using smoothly varying 1D models with fixed vertical discretization. The vertical smoothness of the obtained models stems from the application of Occam-type regularization constraints, which are meant to address the ill-posedness of the problem. An important side effect of such regularization, however, is that horizontal layer boundaries can no longer be accurately reproduced as the model is required to be smooth. This issue can be overcome by inverting for fewer layers with variable thicknesses; nevertheless, to decide on a particular and constant number of layers for the parameterization of a large survey inversion can be equally problematic. Here, we present a focusing regularization technique to obtain the best of both methodologies. The new focusing approach allows for accurate reconstruction of resistivity distributions using a fixed vertical discretization while preserving the capability to reproduce horizontal boundaries. The formulation is flexible and can be coupled with traditional lateral/spatial smoothness constraints in order to resolve interfaces in stratified soils with no additional hypothesis about the number of layers. The method relies on minimizing the number of layers of non-vanishing resistivity gradient, instead of minimizing the norm of the model variation itself. This approach ensures that the results are consistent with the measured data while favouring, at the same time, the retrieval of horizontal abrupt changes. In addition, the focusing regularization can also be applied in the horizontal direction in order to promote the reconstruction of lateral boundaries such as faults. We present the theoretical framework of our regularization methodology and illustrate its capabilities by means of both synthetic and field data sets. We further demonstrate how the concept has been integrated in our existing spatially constrained inversion formalism and show its application to large-scale time-domain electromagnetic data inversions.

Description: Soils are warming as air temperatures rise across the Arctic and Boreal region concurrent with the expansion of tall-statured shrubs and trees in the tundra. Changes in vegetation structure and function are expected to alter soil thermal regimes, thereby modifying climate feedbacks related to permafrost thaw and carbon cycling. However, current understanding of vegetation impacts on soil temperature is limited to local or regional scales and lacks the generality necessary to predict soil warming and permafrost stability on a pan-Arctic scale. Here we synthesize shallow soil and air temperature observations with broad spatial and temporal coverage collected across 106 sites representing nine different vegetation types in the permafrost region. We showed ecosystems with tall-statured shrubs and trees (〉 40 cm) have warmer shallow soils than those with short-statured tundra vegetation when normalized to a constant air temperature. In tree and tall shrub vegetation types, cooler temperatures in the warm season do not lead to cooler mean annual soil temperature indicating that ground thermal regimes in the cold-season rather than the warm-season are most critical for predicting soil warming in ecosystems underlain by permafrost. Our results suggest that the expansion of tall shrubs and trees into tundra regions can amplify shallow soil warming, and could increase the potential for increased seasonal thaw depth and increase soil carbon cycling rates and lead to increased carbon dioxide loss and further permafrost thaw.

Description: © The Author(s), 2021. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Kropp, H., Loranty, M. M., Natali, S. M., Kholodov, A. L., Rocha, A., V., Myers-Smith, I., Abbot, B. W., Abermann, J., Blanc-Betes, E., Blok, D., Blume-Werry, G., Boike, J., Breen, A. L., Cahoon, S. M. P., Christiansen, C. T., Douglas, T. A., Epstein, H. E., Frost, G., V., Goeckede, M., Hoye, T. T., Mamet, S. D., O'Donnell, J. A., Olefeldt, D., Phoenix, G. K., Salmon, V. G., Sannel, A. B. K., Smith, S. L., Sonnentag, O., Vaughn, L. S., Williams, M., Elberling, B., Gough, L., Hjort, J., Lafleur, P. M., Euskirchen, E. S., Heijmans, M. M. P. D., Humphreys, E. R., Iwata, H., Jones, B. M., Jorgenson, M. T., Gruenberg, I., Kim, Y., Laundre, J., Mauritz, M., Michelsen, A., Schaepman-Strub, G., Tape, K. D., Ueyama, M., Lee, B., Langley, K., & Lund, M. Shallow soils are warmer under trees and tall shrubs across arctic and boreal ecosystems. Environmental Research Letters, 16(1), (2021): 015001. doi:10.1088/1748-9326/abc994.

Description: Soils are warming as air temperatures rise across the Arctic and Boreal region concurrent with the expansion of tall-statured shrubs and trees in the tundra. Changes in vegetation structure and function are expected to alter soil thermal regimes, thereby modifying climate feedbacks related to permafrost thaw and carbon cycling. However, current understanding of vegetation impacts on soil temperature is limited to local or regional scales and lacks the generality necessary to predict soil warming and permafrost stability on a pan-Arctic scale. Here we synthesize shallow soil and air temperature observations with broad spatial and temporal coverage collected across 106 sites representing nine different vegetation types in the permafrost region. We showed ecosystems with tall-statured shrubs and trees (〉40 cm) have warmer shallow soils than those with short-statured tundra vegetation when normalized to a constant air temperature. In tree and tall shrub vegetation types, cooler temperatures in the warm season do not lead to cooler mean annual soil temperature indicating that ground thermal regimes in the cold-season rather than the warm-season are most critical for predicting soil warming in ecosystems underlain by permafrost. Our results suggest that the expansion of tall shrubs and trees into tundra regions can amplify shallow soil warming, and could increase the potential for increased seasonal thaw depth and increase soil carbon cycling rates and lead to increased carbon dioxide loss and further permafrost thaw.

Description: We thank G Peter Kershaw, LeeAnn Fishback, Cathy Wilson, and Coleen Iversen for assistance in collection of data. We thank the Permafrost Carbon Network for support and organization of the data synthesis. We thank Vladimir Romanovsky for his feedback and contribution of publicly available data. This project was supported by the National Science Foundation (Grant No. 1417745 to M L, Grant No. 1417700 to S M N, Grant No. 1417908 to A K, Grant No. 1556772 to A R, Grant No. 1637459 to L G, Grant No. 1636476 and Grant No. 1503912 to E S E, Grant No. 1806213 to B M J, Grant No. 1833056 to K D T), UK Natural Environment Research Council (Grant No. NE/M016323/1 to I H M S, Grant No. NE/K00025X/1 to G K P, Grant No. NE/K000292/1 to M W), Natural Sciences and Engineering Research (to P L, I H M S, Grant No. RGPIN-2016-04688 to D O), Council of Canada, Canadian Graduate Scholarship to (I H M -S), Greenland Ecosystem Monitoring Programme: ClimateBasis (to J A and K A), The Next-Generation Ecosystem Experiments (NGEE Arctic) project is supported by the Office of Biological and Environmental Research in the DOE Office of Science (to A L B), Engineer Research and Development Center Army Direct (6.1) Research Program and the Strategic Environmental Research and Development Program (projects RC-2110 and 18-1170 to T A D), United States Geological Survey (to E E S), Arctic Challenge for Sustainability (ArCS; Grant No. JPMXD1300000000) and ArCS II (Grant No. JPMXD1420318865) (to M U and H I), the Danish National Research Foundation (Grant No. CENPERM DNRF100 to B E), the Academy of Finland (Grant No. 315519), the National Research Foundation of Korea (Grant Nos. NRF-2016M1A5A1901769; KOPRI-PN20081 to K Y and B Y L), Research Network for Geosciences in Berlin and Potsdam (to I G), the Swiss National Science Foundation (Grant No. 140631 to G S S), the URPP Global Change and Biodiversity, University of Zurich (to G S S), the University of Alberta Northern Research Awards (to D O), and the Northern Scientific Training Program (to D O), and UT-Battelle, LLC, under contract DE-AC05-00OR22725 with the US Department of Energy (DOE) Office of Science, Biological and Environmental Research (to V G S). S M has been supported by grants and/or in-kind from Natural Sciences and Engineering Research Council of Canada, AMAX Northwest Mining, Co. (North American Tungsten Corp., Ltd), Imperial Oil, Ltd, University of Alberta, Earthwatch International (EI), The Garfield Weston Foundation, Wapusk National Park, Churchill Northern Studies Centre, and the Northern Scientific Training Program. All code for this project are archived (DOI: 10.5281/zenodo.4041165). The data that support the findings of this study are openly available through the Arctic Data Center (Heather Kropp, Michael Loranty, Britta Sannel, Jonathan O'Donnell, Elena Blanc-Betes, et al 2020. Synthesis of soil-air temperature and vegetation measurements in the pan-Arctic. 1990-2016. Arctic Data Center. doi:10.18739/A2736M31X).

Description: Microtopography can be a key driver of heterogeneity in the ground thermal and hydrological regime of permafrost landscapes. In turn, this heterogeneity can influence plant communities, methane fluxes, and the initiation of abrupt thaw processes. Here we have implemented a two-tile representation of microtopography in JULES (the Joint UK Land Environment Simulator), where tiles are representative of repeating patterns of elevation difference. Tiles are coupled by lateral flows of water, heat, and redistribution of snow, and a surface water store is added to represent ponding. Simulations are performed of two Siberian polygon sites, (Samoylov and Kytalyk) and two Scandinavian palsa sites (Stordalen and Iškoras). The model represents the observed differences between greater snow depth in hollows vs. raised areas well. The model also improves soil moisture for hollows vs. the non-tiled configuration (“standard JULES”) though the raised tile remains drier than observed. The modelled differences in snow depths and soil moisture between tiles result in the lower tile soil temperatures being warmer for palsa sites, as in reality. However, when comparing the soil temperatures for July at 20 cm depth, the difference in temperature between tiles, or “temperature splitting”, is smaller than observed (3.2 vs. 5.5 ∘C). Polygons display small (0.2 ∘C) to zero temperature splitting, in agreement with observations. Consequently, methane fluxes are near identical (+0 % to 9 %) to those for standard JULES for polygons, although they can be greater than standard JULES for palsa sites (+10 % to 49 %). Through a sensitivity analysis we quantify the relative importance of model processes with respect to soil moisture and temperatures, identifying which parameters result in the greatest uncertainty in modelled temperature. Varying the palsa elevation between 0.5 and 3 m has little effect on modelled soil temperatures, showing that using only two tiles can still be a valid representation of sites with a range of palsa elevations. Mire saturation is heavily dependent on landscape-scale drainage. Lateral conductive fluxes, while small, reduce the temperature splitting by ∼ 1 ∘C and correspond to the order of observed lateral degradation rates in peat plateau regions, indicating possible application in an area-based thaw model.

Description: Snow is an important driver of ecosystem processes in cold biomes. Snow accumulation determines ground temperature, light conditions and moisture availability during winter. It also affects the growing season’s start and end, and plant access to moisture and nutrients. Here, we review the current knowledge of the snow cover’s role for vegetation, plant-animal interactions, permafrost conditions, microbial processes and biogeochemical cycling. We also compare studies of natural snow gradients with snow manipulation studies, altering snow depth and duration, to assess time scale difference of these approaches. The number of studies on snow in tundra ecosystems has increased considerably in recent years, yet we still lack a comprehensive overview of how altered snow conditions will affect these ecosystems. In specific, we found a mismatch in the timing of snowmelt when comparing studies of natural snow gradients with snow manipulations. We found that snowmelt timing achieved by manipulative studies (average 7.9 days advance, 5.5 days delay) were substantially lower than those observed over spatial gradients (mean range of 56 days) or due to interannual variation (mean range of 32 days). Differences between snow study approaches need to be accounted for when projecting snow dynamics and their impact on ecosystems in future climates.