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Bertilsson, Stefan ; Burgin, Amy ; Carey, Cayelan C. ; Fey, Samuel B. ; Grossart, Hans-Peter ; Grubisic, Lorena M. ; Jones, Ian D. ; Kirillin, Georgiy ; Lennon, Jay T. ; Shade, Ashley ; Smyth, Robyn L.
Compared to the well-studied open water of the "growing" season, under-ice conditions in lakes are characterized by low and rather constant temperature, slow water movements, limited light availability, and reduced exchange with the surrounding landscape. These conditions interact with ice-cover duration to shape microbial processes in temperate lakes and ultimately influence the phenology of community and ecosystem processes. We review the current knowledge on microorganisms in seasonally frozen lakes. Specifically, we highlight how under-ice conditions alter lake physics and the ways that this can affect the distribution and metabolism of auto-and heterotrophic microorganisms. We identify functional traits that we hypothesize are important for understanding under-ice dynamics and discuss how these traits influence species interactions. As ice coverage duration has already been seen to reduce as air temperatures have warmed, the dynamics of the under-ice microbiome are important for understanding and predicting the dynamics and functioning of seasonally frozen lakes in the near future.
Buratti, Bonnie J. ; Thomas, P. C. ; Roussos, Elias ; Howett, Carly ; Seiss, Martin ; Hendrix, A. R. ; Helfenstein, Paul ; Brown, R. H. ; Clark, R. N. ; Denk, Tilmann ; Filacchione, Gianrico ; Hoffmann, Holger ; Jones, Geraint H. ; Khawaja, N. ; Kollmann, Peter ; Krupp, Norbert ; Lunine, Jonathan ; Momary, T. W. ; Paranicas, Christopher ; Postberg, Frank ; Sachse, Manuel ; Spahn, Frank ; Spencer, John ; Srama, Ralf ; Albin, T. ; Baines, K. H. ; Ciarniello, Mauro ; Economou, Thanasis ; Hsu, Hsiang-Wen ; Kempf, Sascha ; Krimigis, Stamatios M. ; Mitchell, Donald ; Moragas-Klostermeyer, Georg ; Nicholson, Philip D. ; Porco, C. C. ; Rosenberg, Heike ; Simolka, Jonas ; Soderblom, Laurence A.
Saturn’s main ring system is associated with a set of small moons that either are embedded within it or interact with the rings to alter their shape and composition. Five close flybys of the moons Pan, Daphnis, Atlas, Pandora, and Epimetheus were performed between December 2016 and April 2017 during the ring-grazing orbits of the Cassini mission. Data on the moons’ morphology, structure, particle environment, and composition were returned, along with images in the ultraviolet and thermal infrared. We find that the optical properties of the moons’ surfaces are determined by two competing processes: contamination by a red material formed in Saturn’s main ring system and accretion of bright icy particles or water vapor from volcanic plumes originating on the moon Enceladus.
Arboleda-Zapata, Mauricio ; Angelopoulos, Michael ; Overduin, Pier Paul ; Grosse, Guido ; Jones, Benjamin M. ; Tronicke, Jens
Sea level rise and coastal erosion have inundated large areas of Arctic permafrost. Submergence by warm and saline waters increases the rate of inundated permafrost thaw compared to sub-aerial thawing on land. Studying the contact between the unfrozen and frozen sediments below the seabed, also known as the ice-bearing permafrost table (IBPT), provides valuable information to understand the evolution of sub-aquatic permafrost, which is key to improving and understanding coastal erosion prediction models and potential greenhouse gas emissions. In this study, we use data from 2D electrical resistivity tomography (ERT) collected in the nearshore coastal zone of two Arctic regions that differ in their environmental conditions (e.g., seawater depth and resistivity) to image and study the subsea permafrost. The inversion of 2D ERT data sets is commonly performed using deterministic approaches that favor smoothed solutions, which are typically interpreted using a user-specified resistivity threshold to identify the IBPT position. In contrast, to target the IBPT position directly during inversion, we use a layer-based model parameterization and a global optimization approach to invert our ERT data. This approach results in ensembles of layered 2D model solutions, which we use to identify the IBPT and estimate the resistivity of the unfrozen and frozen sediments, including estimates of uncertainties. Additionally, we globally invert 1D synthetic resistivity data and perform sensitivity analyses to study, in a simpler way, the correlations and influences of our model parameters. The set of methods provided in this study may help to further exploit ERT data collected in such permafrost environments as well as for the design of future field experiments.
Arboleda-Zapata, Mauricio ; Angelopoulos, Michael ; Overduin, Pier Paul ; Grosse, Guido ; Jones, Benjamin M. ; Tronicke, Jens
Sea level rise and coastal erosion have inundated large areas of Arctic permafrost. Submergence by warm and saline waters increases the rate of inundated permafrost thaw compared to sub-aerial thawing on land. Studying the contact between the unfrozen and frozen sediments below the seabed, also known as the ice-bearing permafrost table (IBPT), provides valuable information to understand the evolution of sub-aquatic permafrost, which is key to improving and understanding coastal erosion prediction models and potential greenhouse gas emissions. In this study, we use data from 2D electrical resistivity tomography (ERT) collected in the nearshore coastal zone of two Arctic regions that differ in their environmental conditions (e.g., seawater depth and resistivity) to image and study the subsea permafrost. The inversion of 2D ERT data sets is commonly performed using deterministic approaches that favor smoothed solutions, which are typically interpreted using a user-specified resistivity threshold to identify the IBPT position. In contrast, to target the IBPT position directly during inversion, we use a layer-based model parameterization and a global optimization approach to invert our ERT data. This approach results in ensembles of layered 2D model solutions, which we use to identify the IBPT and estimate the resistivity of the unfrozen and frozen sediments, including estimates of uncertainties. Additionally, we globally invert 1D synthetic resistivity data and perform sensitivity analyses to study, in a simpler way, the correlations and influences of our model parameters. The set of methods provided in this study may help to further exploit ERT data collected in such permafrost environments as well as for the design of future field experiments.