Science Summary: Greenland Ice Sheet (GrIS) melting is increasing. The associated runoff to the adjacent oceans may have important impacts on marine ecosystems. Meltwater characteristics, such as iron, sulfate and carbon content, are not well known and depend on the extent and activity of weathering reactions beneath the ice sheet. Microbes in these critical subglacial environments are important contributors of chemical weathering processes, yet, to date, direct molecular evidence of such processes remains to be obtained from GrIS subglacial environments. Here, the principal investigators will optimize methods to analyze samples obtained previously from GrIS subglacial meltwaters and to identify evidence of microbial activity in GrIS’ subglacial meltwaters. This is necessary background information required to develop models of the potential impact of increasing meltwater discharge from GrIS on local and downstream commercial fisheries.
This project will contribute to STEM manpower development by offering research experience to an undergraduate student and mentoring to a female postdoctoral researcher. Its public K-12 focused outreach efforts include workshops and exhibits at three annual Science Weekend experiences for the museum-going public at Seattle’s Pacific Science Center (Polar Science, Life Science Research, and UW PAWS on Science). Each event provides the possibility of one-on-one interactions with over 9000 students from diverse socio-economic backgrounds, allowing time to excite students during explanation of the ‘Greenland ice microbes’ exhibit and presentation of a hands-on mass spectrometry model.
This work will ultimately provide the first direct molecular evidence for enzymatic microbe-mediated nutrient cycling and remineralization (e.g., iron, sulfate, carbon release) underneath the GrIS. It constitutes the critical first step towards improving conceptual models of microbial GrIS weathering and its resulting impact on nutrient fluxes to future polar oceans. Specifically, the principal investigator anticipates that it will:
1. Optimize protein extraction and environmental proteomics techniques for subglacial meltwater samples;
2. Identify enzymes involved in microbial weathering and nutrient release to the ocean;
3. Decipher molecular protective mechanisms that help microbes in the subglacial environment survive;
4. Identify protein/peptide biomarkers to identify and quantify key metabolic processes in future subglacial studies; and
5. Promote further discovery of novel cold-adaptive enzymes of significant interest to
environmental ecologists and industrial scientists.
Through these efforts, the PIs will demonstrate the ability to detect enzyme-controlled weathering, a prerequisite to quantify and track these processes in detail in the field (e.g., by combining geochemical measurements with targeted quantitative proteomics and 13C-isotopic tracer studies). The success of this project has the potential to fundamentally change the way in which science views the effects of ice sheet melting. Identification and quantification of the microbial processes controlling weathering and nutrient availability is critical to the next generation of conceptual models ice sheet-ocean interaction.
Logistics Summary: Changes in freshwater input from the Greenland Ice Sheet (GrIS) has substantial impacts on marine ecosystems and global biogeochemical cycling, but the role of microbes in chemical weathering in the subglacial environments is poorly understood. This project will increase our understanding of microbial enzymes active in GrIS subglacial waters using state-of-the-art proteomics techniques.
Researchers will analyze samples of subglacial sediments, basal ice, and glacial meltwater obtained during previous field efforts in Greenland near Thule and Kangerlussuaq. This study will be the first to map out the proteins expressed by a subglacial microbial community and correlate protein function with geochemical datasets.
No fieldwork is conducted.
Parameters used to generate this report:, Grant# = "1603276", IPY = "ALL"
Number of projects returned based on your query parameters = 1