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Simulating Landfast Ice in Lake Superior. JOURNAL OF MARINE SCIENCE AND ENGINEERING 2022. [DOI: 10.3390/jmse10070932] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
Landfast ice plays an important role in the nearshore hydrodynamics of large lakes, such as the dampening of surface waves and currents. In this study, previously developed landfast ice basal stress parameterizations were added to an unstructured grid hydrodynamic ice model to represent the effects of grounded ice keels and tensile strength of ice cover. Numerical experiments using this model were conducted to evaluate the development of coastal landfast ice in Lake Superior. A sensitivity study of the free parameters was conducted from December 2018 to May 2021 to cover both high and low ice cover winters in Lake Superior and was compared against observations from the United States National Ice Center. The model reproduces the annual variation in coastal landfast ice in Lake Superior, particularly in shallow nearshore areas and the semi-enclosed bays in the northern regions of the lake. Experiments also show that the growth of landfast ice is mainly controlled by the free parameter that controls the critical ice thickness for the activation of basal stress. Overall, the model tends to underestimate the extent of coastal landfast against observations.
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Physiographic Controls on Landfast Ice Variability from 20 Years of Maximum Extents across the Northwest Canadian Arctic. REMOTE SENSING 2022. [DOI: 10.3390/rs14092175] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/10/2022]
Abstract
Landfast ice is a defining feature among Arctic coasts, providing a critical transport route for communities and exerting control over the exposure of Arctic coasts to marine erosion processes. Despite its significance, there remains a paucity of data on the spatial variability of landfast ice and limited understanding of the environmental processes’ controls since the beginning of the 21st century. We present a new high spatiotemporal record (2000–2019) across the Northwest Canadian Arctic, using MODIS Terra satellite imagery to determine maximum landfast ice extent (MLIE) at the start of each melt season. Average MLIE across the Northwest Canadian Arctic declined by 73% in a direct comparison between the first and last year of the study period, but this was highly variable across regional to community scales, ranging from 14% around North Banks Island to 81% in the Amundsen Gulf. The variability was largely a reflection of 5–8-year cycles between landfast ice rich and poor periods with no discernible trend in MLIE. Interannual variability over the 20-year record of MLIE extent was more constrained across open, relatively uniform, and shallower sloping coastlines such as West Banks Island, in contrast with a more varied pattern across the numerous bays, headlands, and straits enclosed within the deep Amundsen Gulf. Static physiographic controls (namely, topography and bathymetry) were found to influence MLIE change across regional sites, but no association was found with dynamic environmental controls (storm duration, mean air temperature, and freezing and thawing degree day occurrence). For example, despite an exponential increase in storm duration from 2014 to 2019 (from 30 h to 140 h or a 350% increase) across the Mackenzie Delta, MLIE extents remained relatively consistent. Mean air temperatures and freezing and thawing degree day occurrences (over 1, 3, and 12-month periods) also reflected progressive northwards warming influences over the last two decades, but none showed a statistically significant relationship with MLIE interannual variability. These results indicate inferences of landfast ice variations commonly taken from wider sea ice trends may misrepresent more complex and variable sensitivity to process controls. The influences of different physiographic coastal settings need to be considered at process level scales to adequately account for community impacts and decision making or coastal erosion exposure.
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Biomolecular Composition of Sea Ice Microalgae and Its Influence on Marine Biogeochemical Cycling and Carbon Transfer through Polar Marine Food Webs. GEOSCIENCES 2022. [DOI: 10.3390/geosciences12010038] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Microalgae growing on the underside of sea ice are key primary producers in polar marine environments. Their nutritional status, determined by their macromolecular composition, contributes to the region’s biochemistry and the unique temporal and spatial characteristics of their growth makes them essential for sustaining polar marine food webs. Here, we review the plasticity and taxonomic diversity of sea ice microalgae macromolecular composition, with a focus on how different environmental conditions influence macromolecular production and partitioning within cells and communities. The advantages and disadvantages of methodologies for assessing macromolecular composition are presented, including techniques that provide high throughput, whole macromolecular profile and/or species-specific resolution, which are particularly recommended for future studies. The directions of environmentally driven macromolecular changes are discussed, alongside anticipated consequences on nutrients supplied to the polar marine ecosystem. Given that polar regions are facing accelerated rates of environmental change, it is argued that a climate change signature will become evident in the biochemical composition of sea ice microalgal communities, highlighting the need for further research to understand the synergistic effects of multiple environmental stressors. The importance of sea ice microalgae as primary producers in polar marine ecosystems means that ongoing research into climate-change driven macromolecular phenotyping is critical to understanding the implications for the regions biochemical cycling and carbon transfer.
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