To be updated

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Evaluation of an in situ culturing approach on the Greenland Ice Sheet

The Greenland Ice Sheet (GrIS) is a biome that supports growth of a range of microbes (Anesio et al., 2017). The study of these under-investigated microbes, a major goal of the Deep Purple ERCSy project, is however hampered by the problem known as microbial dark matter, meaning that the majority of microbial life has never been cultured in the lab so far. A way to increase cultivability of microbes from the environment is in situ culturing. Here, microbial isolates are first incubated in their natural environment before being brought back to the lab. It is found that this increases the number of isolates that can be successfully brought into culture (Berdy et al., 2017). A device that makes use of the same principle was for the first time applied on the Greenland Ice Sheet during fieldwork in 2021. These “culture chips” will be applied again during fieldwork coming summer. This student project involves the follow up work that is connected to this culturing method, back in the lab.

Main objectives:

The goal of the project is to create a culture collection of axenic cultures of microbes coming from the Greenland Ice Sheet. It involves isolating bacteria and fungi from the culture chips, and culturing them followed by identification through sequencing. The resulting data will be used to compare this method to earlier application (fieldwork 2021) as well as to conventional culturing methods.

Techniques used:

• Culturing of microbial isolates from an extreme environment; bacteria and fungi
• DNA extraction
• PCR
• Various sequencing methods; Sanger, amplicon, whole genome sequencing

Project setup:

The project is quite flexible, and can take shape as a BSc/MSc project/internship. In principle, it should take place in the entire autumn semester of 2022, (starting September) but this can be negotiated. Candidates are welcome to bring their own ideas to the table for this project. A background in microbiology/molecular biology is ideal, and previous lab experience is valuable. You will be part of an international and interdisciplinary research group studying microbial processes of the Greenland Ice Sheet. Supervision by Alexandre Anesio, daily supervision by Ate Jaarsma (contact person). Work takes place at the department of Environmental Sciences of Aarhus University, campus Roskilde.

ahj@envs.au.dk

Department of Environmental Sciences, Frederiksborgvej 399, 4000 Roskilde

https://www.deeppurple-ercsyg.eu/home

Anesio, A. M., Lutz, S., Chrismas, N. A. M., & Benning, L. G. (2017). The microbiome of glaciers and ice sheets. Npj Biofilms and Microbiomes, 3(1), 0–1. doi.org/10.1038/s41522-017-0019-0

Berdy, B., Spoering, A. L., Ling, L. L., & Epstein, S. S. (2017). In situ cultivation of previously uncultivable microorganisms using the ichip. Nature Protocols, 12(10), 2232–2242. doi.org/10.1038/nprot.2017.074

9 March 2022

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Remote sensing of surface ice albedo in the Arctic: Validation

Albedo is a critical factor affecting the melt rates of glaciers and ice sheets. A novel algorithm for converting multispectral data from satellites into broadband albedo values required for melt modelling has been developed as part of the Deep Purple project (https://www.deeppurple-ercsyg.eu/home). The albedo derived by applying this algorithm to harmonized Landsat and Sentinel 2 imagery agrees well with in-situ automatic weather station (AWS) albedo measurements on the Greenland Ice Sheet. However, we now wish to recruit a student to help us validate the algorithm for other areas in the Arctic.

The supervisors will assist the student to learn and apply remote sensing techniques, data processing and analysis. Tasks include:

1. Collecting AWS albedo records in other Arctic areas (e.g. Svalbard, Scandinavian glaciers, Alaska etc.).
2. Apply the narrow to broadband conversion algorithm to multispectral images from various sources (drone, airborne, and satellite platforms such as Landsat, Sentinel-2, ASTER etc.).
3. Validate the remote sensing derived albedo with the collected in-situ albedo measurements.

Prospective students should be self-motivated and new ideas are highly encouraged. Basic coding skills in data analysis using one of high-level programming languages (Python, MATLAB, R, Javascript etc.) is necessary. Experience with Google Earth Engine is welcomed.

The project is expected to be finished in one semester and the final report/thesis should be written in English. Please note this is a thesis idea proposal and we are not offering funding for this project as it is intended to be part of your existing study. Necessary data will be provided by supervisors and on campus work is acceptable if prospective students are self-funded with scholarship themselves.

Supervisors:

Aarhus University: Shunan Feng, Martyn Tranter, Joseph Cook

Uppsala University: Rickard Pettersson

Contact person: Shunan Feng (shunan.feng@envs.au.dk)

Department of Environmental Sciences

Aarhus University

Frederiksborgvej 399

DK-4000 Roskilde

Denmark

https://www.deeppurple-ercsyg.eu/home

11 January 2022

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Developing a dual camera remote sensing imaging system and LiDAR on UAV.

The Unmanned Aerial Vehicle (UAV) is becoming more and more important in acquiring remote sensing images. The student project will be focusing on developing a dual camera system to mount both a hyperspectral and a multispectral camera and installing a lightweight LiDAR on a drone (DJI M600 Pro). This is part of the Deep Purple project (https://www.deeppurple-ercsyg.eu/home). The scope of the project is simply to install and test the two additional sensors.

The drone, cameras, LiDAR sensor and gimbal are all available. The purchase of necessary components will be supported by the project. The delivery of the final product is expected to be by the end of March or Early April 2022. Prospective students should be self-motivated and new ideas are highly encouraged. Experience in electrical engineering and/or control systems is necessary.

Please note this is a student project call to students who could work on campus in Roskilde or other university campus in Denmark. Travel and living expenses will not be covered by the project. 

Supervisors:

Aarhus University: Shunan Feng, Martyn Tranter, Joseph Mitchell Cook

Contact person: Shunan Feng (shunan.feng@envs.au.dk)

Department of Environmental Sciences

Aarhus University

Frederiksborgvej 399

DK-4000 Roskilde

Denmark

https://www.deeppurple-ercsyg.eu/home

11 January 2022

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Klimaændringers indvirkning på den Arktiske forurening med POPer