Position Descriptions

Research Question: The Meaningful Watershed Educational Experience (MWEE) is a learner-centered framework that focuses on investigations into local environmental issues and leads to informed action. What are the most effective uses of the MWEE framework to achieve K-12 stewardship action projects, as demonstrated in the Great Lakes region’s B-WET funded projects? 

Project Activities: The summer fellow will assist the Great Lakes B-WET Program Manager in the following activities, as well as attending national and regional B-WET networking opportunities:

• Analyze recipient projects by reviewing reports and comparing to MWEE framework
• Evaluate effective uses of MWEE framework that achieved stewardship action projects 
• Make recommendations of successful project examples to form case studies
• Create content for general audience based on successful project examples / case study templates
• Participate in Great Lakes regional grantee events and trainings as representative of B-WET team
• Support trainings and meetings for grantees hosted by Great Lakes B-WET region 

Required & Desired Skills: Desired skills include experience in using Google Suite, and good communication skills, including strong writing ability, and general organizational skills.

Location: If conditions permit in-person work, this position will be housed at the NOAA Thunder Bay National Marine Sanctuary in Alpena, Michigan. Remote work is possible for this position even if an in-person fellowship is offered.

Research Questions:

• What is the seasonal progression of phytoplankton in the western basin of Lake Erie from April – Oct, as determined based on FluoroProbe (bbe moldaenke©) readings and  photopigment analysis; and are the methods comparable?
• Is there a relationship between FluoroProbe or photopigments to microcystin concentrations?

Project Activities:

1. Assess phytoplankton group dynamics from 2015 – 2021 using FluoroProbe readings.
2. Determine bulk community composition from photopigements analysis using CHEMTAX.  
3. Identify periods when phytoplankton assemblage composition varies based on the method used.
4. Determine if a relationship is present between cyanobacteria concentrations and microcystin toxin concentrations.
5. Complete dilution experiments using Lake Erie-based cultures to determine threshold conditions for FluoroProbe*.      

*Requires onsite laboratory access in Ann Arbor, MI, which is to be determined based on local pandemic conditions and restrictions during the fellowship period. In the event of a virtual fellowship, this activity will not be included in the project.

Required & Desired Skills:  An understanding of aquatic ecology, with a basic understanding of phytoplankton groups and factors influencing growth characteristics and population dynamics. Use of Excel or other spreadsheets to manipulate data sets.  General understanding of statistics and experience with statistical programs (such as R, or Python).

Location: If conditions permit in-person work, this position will be housed at the NOAA Great Lakes Environmental Research Laboratory in Ann Arbor, Michigan. Remote work is possible for this position even if an in-person fellowship is offered.

Research Questions:

• Do buoyancy-related genes (gvp gene cluster) or other gene clusters vary during the peak of a cHAB? 
• Does the presence of the gvp gene cluster vary between a small cHAB bloom (2018) and a large bloom (2019)?
• Is there a relationship between the chosen gene cluster and other environmental parameters?   

Project Activities:

• Explore metagenomic data collected during the 2018 and 2019 Lake Erie cHAB from the 3G ESP and annotate the chosen gene clusters.  
• Explore associated environmental data and correlate environmental factors (spatially) to gene cluster presence.   
• Annotate gene cluster data from other Great Lakes systems (such as Lake Huron).  

Required & Desired Skills:

• Strong interest in Microcystis aeruginosa blooms research. 
• General understanding of statistics and experience with programs (such as R or Python).
• General understanding of genetic pipelines (such as QIIME2, mothur, etc.).

Location: If conditions permit in-person work, this position will be housed at the NOAA Great Lakes Environmental Research Laboratory in Ann Arbor, Michigan. Remote work is possible for this position even if an in-person fellowship is offered.

Research Questions:

• Are the frequency of ecologically important events such as episodic hypoxia and harmful algal blooms changing over time in Saginaw Bay?
• What are the long-term trends in the physical, chemical, and biological properties of Saginaw Bay?
• The fellow will be encouraged to articulate and address additional questions that arise as the project proceeds.

Project Activities: The fellow will assemble the data into a common database, plot and analyze the data using common statistical techniques and write a short report describing the main findings and conclusions. The project requires the student to become familiar with Saginaw Bay buoy, benthic, and lab processed data.

• Analysis of buoy time-series data over the period 2010-2021
• Assess relationship of buoy time-series data to satellite remote sensing, benthic, and lab data for the period

Required & Desired Skills: Proficiency using R software, familiarity with basic graphing and statistical techniques and technical writing capability is needed. Candidates should have a strong background in freshwater or marine science and have taken an introductory statistics course. However, a fellow with a strong background in statistical analysis using the R analysis package (e.g.: formal model-selection and multiple linear regression; partial least squares regression; ordinary least squares regression; generalized additive models and other statistical tools) to analyze the fine-scale data will be a preferred candidate.

Location: If conditions permit in-person work, this position will be housed at the NOAA Great Lakes Environmental Research Laboratory in Ann Arbor, Michigan. Remote work is possible for this position even if an in-person fellowship is offered.

Research Question: How has the frequency and intensity of winter storms over the Great Lakes region changed during the past decades?

Project Activities: The fellow will conduct meteorological data analysis using existing storm detection algorithms to examine the winter mesoscale storm frequency/intensity over the Great Lakes region.

• Conduct literature review on existing storm detection algorithms, as well as on relevant research
• Download atmospheric re-analysis dataset with select variables (e.g., air pressure, wind speed) over the target period
• Apply an existing storm detection algorithm(s) to the obtained atmospheric re-analysis dataset for select storm cases and verify the results by comparing with the storm reports from National Weather Service.
• If time allows, expand the analysis to the longer period, calculate the statistics (e.g., frequency, maximum wind speed), and evaluate the trend over the past decades

Required & desired skills: Required qualifications are strong interest in pursuing a career in earth science, such as atmospheric science and physical oceanography, experience with gridded data analysis, and familiarity with one or more programming languages such as Python, R, and Fortran.  

Location: If conditions permit in-person work, this position will be housed at the NOAA Great Lakes Environmental Research Laboratory in Ann Arbor, Michigan. Remote work is possible for this position even if an in-person fellowship is offered.

Research Questions: For each species, the selected fellow will answer the research questions:

• Is this species already established (overwintering and reproducing) in the Great Lakes?
• If so, what are its distribution as well as realized and potential impacts? 
• If not, does this species pose a significant risk to the Great Lakes for introduction, establishment, and impact? 

Project Activities: The summer fellow will conduct a mini-review of the available literature for 5-10 species (candidate species include: Akebia quinata, Oenanthe javanica, Barbarea stricta, Barbarea verna, Filipendula ulmaria, Impatiens balfourii, Petasites hybridus, Robinia pseudoacacia, Salix atrocinerea, Silphium perfoliatum, Valeriana officinalis, Egeria najas, Hydrocotyle ranunculoides, Lythrum virgatum, and Sagittaria subulata).  For each species this includes organizing all literature into the database (including abstracts, pdfs, keyword tags, etc); extracting and organizing the distribution, impact, and ecological information into database formats; conducting a standardized risk assessment; and writing a species profile if the species is determined to meet listing criteria. To the extent time allows, the fellow will help to shepherd assessments and profiles through the internal, external, and NOAA review processes.  All assessments are published as part of the NOAA Tech Memo Series and the fellow will have the opportunity to be listed as a contributing author.  Profiles are also considered to be citable NOAA publications.

Required & Desired Skills:

• Excellent technical writing and organizational skills.
• Familiarity with Excel, Word, Google sheets, etc.
• Interest in invasion biology and/or botany

Location: If conditions permit in-person work, this position will be housed at the NOAA Great Lakes Environmental Research Laboratory in Ann Arbor, Michigan. Remote work is possible for this position even if an in-person fellowship is offered.

Research Question: How do biomass and toxin concentration differ between the surface and bottom and do those differences, if any, correspond to known drivers of vertical distribution? 

Project Activities: This fellow will use our ongoing monitoring dataset and available environmental data in a retrospective statistical analysis to address this research question. That analysis will involve:

• Identifying and assimilating available data, with guidance from mentors
• Performing initial data exploration and visualization tasks
• Building multiple statistical models using different approaches or assumptions, then comparing these models in terms of performance and interpretation

Required & Desired Skills:

• Required: Experience building statistical models in R
• Desired: Experience working with sparse environmental data, limnological profiles of water quality parameters, and familiarity with HABs

Location: If conditions permit in-person work, this position will be housed at the NOAA Great Lakes Environmental Research Laboratory in Ann Arbor, Michigan. Remote work is not possible for this position if an in-person fellowship is offered.

Research Questions:

• In addition to water temperature and wind forcing, is Great Lakes ice cover correlated to Arctic sea ice cover in response to the same teleconnection forcing?  If so, how strong are these correlations and are they linear or non-linear?
• Can we hindcast and predict Great Lakes and Arctic ice cover using physical forcings? Furthermore, can we estimate/hindcast ice thickness using satellite measurements and thermodynamic equations?

Project Activities: The research includes the development of regression models using the statistical program R for predicting ice cover using climate teleconnection indices and physical forcings. For example, atmospheric teleconnection pattern indices are used to formulate statistical regression models to hindcast lake/sea ice cover, which should be able to explain the connection of lake/sea ice with atmospheric teleconnection patterns. R data analysis tools that will be used include time series analysis, correlation, and/or empirical orthogonal function analysis and regression analysis. 

Required & Desired Skills: Minimum qualifications include programming in Fortran, Python, C, or R, or  willingness to learn these programming skills.

Location: If conditions permit in-person work, this position will be housed at the NOAA Great Lakes Environmental Research Laboratory in Ann Arbor, Michigan. Remote work may be possible for this position if an in-person fellowship is offered.