Position Descriptions

Changing atmospheric conditions exert direct control on downstream ecosystem processes, including lake surface temperatures, ice cover, water quality, and fisheries habitat. Although Global Climate Models (GCMs) provide future climate projections in the Great Lakes region, the spatial scales inherent to GCMs (~50 – 200km) are too large for many modeling applications. One potential solution for this is the so-called pseudo-global-warming (PGW) approach, where predicted changes in GCMs are used to scale higher resolution atmospheric reanalysis products, like ERA5 or HRRR. This approach preserves the resolution of the reanalysis products while significantly reducing computational costs associated with more traditional regional climate model (RCM) techniques. This project will focus on developing a PGW product for the Great Lakes, with potential applications in downstream lake and ecosystem modeling.

Research Questions:

• 1. Can PGW approaches generate physically consistent global warming scenarios for the Great Lakes region?

Project Activities:

The main focus of this project is to develop PGW products for the Great Lakes region under several potential warming scenarios, as informed by GCM scenarios. Specific activities include:

• • Download variables from several scenarios of the GFDL-CM4 CMIP6 model (SSP126, SSP245, SSP585) and use data analysis to evaluate expected changes between 2015 and 2100.
  • Download atmospheric reanalysis product variables and apply PGW techniques (using available Python software packages) to generate forcing products for each CMIP6 scenario. We will focus on high-resolution reanalysis products that include explicit representation of the Great Lakes (e.g. HRRR) in order to facilitate comparisons with other PGW datasets developed for the region, including work from the DOE COMPASS team.
  • Evaluate PGW forcing over the period from 2015-2025 to ensure that they replicate the weather and climate patterns unique and important to the Great Lakes region. Special attention will be paid to winter months, which provide unique challenges for PGW approaches (i.e. missing lake-ice-atmosphere interactions).

Required Skills:

The ideal candidate will be interested in atmospheric science and have or be working toward a degree in a related discipline. Some experience or relevant coursework involving programming (Python, Matlab, R, or similar program) and familiarity with gridded and observational atmospheric datasets (e.g., netCDF) would be useful. The mentor team will offer training on these skills as needed.

Location: NOAA Great Lakes Environmental Research Laboratory in Ann Arbor, MI, remote, or hybrid. 

The rapid expansion of data centers threatens local water security in the Great Lakes region by placing massive, unanalyzed demands on municipal water and wastewater infrastructure. Communities lack clear data and a planning framework to assess the localized water stress, infrastructure capacity, and indirect energy-water tradeoffs associated with these high-volume users. This project will address this gap by working towards an open-source assessment framework and a practical guide for municipal managers.

Research Questions:

How can advanced water impact metrics be adapted to create a proxy-powered framework that assesses a community’s localized water stress and infrastructure capacity headroom against data center demands?

Project Activities: 

The Fellow will design and prototype a multi-dimensional risk assessment framework and translate it into a Community Strategy Guide. Activities include:

• Conducting a targeted literature review of water footprint metrics and municipal planning standards;
• Adapting the Adjusted Water Impact (AWI) metric to separate local adjusted water impact (hydrologic stress) from infrastructure capacity headroom (reserve margin) and developing a supplementary methodology for indirect water impact from electricity generation;
• Developing and validating a public-data proxy methodology using case studies applied to 1-2 illustrative Great Lakes scenarios; and
• Writing a draft Community Strategy Guide outlining siting guardrails, negotiation terms, and a data request checklist.
• Develop a Dissemination & Outreach Plan in coordination with CIGLR Research Engagement staff: Identify key municipal stakeholders (e.g. Great Lakes and St. Lawrence Cities Initiative) and draft a plan for sharing the Community Strategy Guide, which may include a webinar outline, a policy brief, or a presentation for a regional water management conference.

Required Skills:

Quantitative analysis skills (e.g., in Python, R, or spreadsheet modeling) and the ability to synthesize technical information into clear written communications are critical. Familiarity with GIS or publicly available water data sources (e.g. USGS, state water withdrawal programs) would be very helpful.

Location: University of Michigan central campus and NOAA Great Lakes Environmental Research Laboratory, Ann Arbor, MI, remote, or hybrid.

Fish recruitment success is often shaped by ecological and habitat-specific processes influencing early growth and survival. Along the eastern shoreline of Lake Michigan, drowned river-mouths (DRM) provide highly productive nursery habitats compared to open-lake areas. For yellow perch, DRM and open-lake nearshore populations exhibit distinct genetic structure (Chorak et al. 2019) and early life traits that may influence how invasive dreissenid veligers affect growth and survival during critical developmental periods. By directly comparing larval recruitment dynamics across well-connected but genetically isolated populations, this project will (a) expand sampling during the CSMI field season into DRM to investigate habitat-specific differences in recruitment dynamics, and (b) contribute to 2025-2026 CSMI research priorities by evaluating how nearshore zooplankton communities, particularly dreissenid veliger abundance, affect fish early-life growth and survival.

Research Questions: 

We hypothesize that yellow perch in DRM will emerge earlier and at larger sizes than fish in nearshore Lake Michigan. As a result, yellow perch in DRM will encounter fewer gape limitations with the encountered prey field and as a result, will consume a lower proportion of energetically deficient dreissenid veligers than their nearshore neighbors.

Project Activities:

The summer fellow will help expand the CSMI 2025–2026 field season by assisting with the collection, processing, and analysis of larval yellow perch from both nearshore Lake Michigan and Muskegon Lake (a drowned river-mouth lake). The fellow will participate in field surveys, conduct laboratory diet analyses, and synthesize historical datasets to compare early-life dynamics across these two connected but genetically distinct habitats. The fellow will:

1. Coordinate and assist field sampling in Muskegon Lake and nearshore Lake Michigan.Field work will be an extension of CSMI nearshore sampling, during which the fellow will support NOAA ecologists in the collection and organization of abiotic and biotic data. Additional sampling gear (trawl or seines) may be employed to target specific life stages.
2. Process samples collected during field work at NOAA–GLERL laboratory. The fellow will work under direct supervision of a CIGLR ecologist to identify target species in ichthyoplankton and zooplankton samples. A subset of yellow perch collected will be dissected to remove otoliths for age estimation, stomach content for diet analysis, and cataloged for potential future genetic verification. The fellow will estimate the relative proportion of veligers present in zooplankton samples to assess yellow perch selectivity. The student will become familiar with broader lab workflows (zooplankton processing, sample archiving, microscopy techniques, etc.).
3. Analyze and synthesize current and historical yellow perch datasets collected by NOAA GLERL to support habitat comparisons. The fellow will (a) summarize existing yellow perch data, including larval size distributions, prey fields, and environmental conditions, and (b) compare larval diets between habitats to evaluate differences in dreissenid veliger consumption and prey energy density.

Required Skills:

Candidates should have a strong background in fisheries, limnology/oceanography, or a related field, and have taken introductory coursework in biostatistics. The successful candidate will participate in a lakewide sampling program supported by multiple federal, state, and local agencies, as well as academic partners. To ensure data integrity, the candidate should have experience or familiarity working in a laboratory environment (strong organization and equipment skills) and on boats in variable weather conditions.

Location: In Person Only – NOAA Great Lakes Environmental Research Laboratory in Ann Arbor, MI. Field work will be based out of GLERL’s Lake Michigan Field Station at 1431 Beach Street, Muskegon, MI 49441.

Acidification of large freshwater systems due to increases in atmospheric pCO2 are understudied compared to marine systems where changes to the lower food web have been identified. At the same time these ecosystems are also experiencing a number of biological threats, including invasive species and harmful algal blooms, which have had a large impact on the ecosystem’s structure and function. Previous studies have indicated that key species to food web dynamics, such as mussels and phytoplankton, will be altered by freshwater acidification. Our aim is to examine how freshwater acidification impacts the feeding behavior of invasive quagga mussels.

Research Questions: 

1. Are the growth rates of phytoplankton cultures (Microcystis aeruginosa and Chlamydomonas oblonga) impacted by pCO2 (acidification) concentrations and temperature?
2. Do quagga mussels change their feeding and clearance rates based on acidification or temperature conditions?

Project Activities:

Conduct phytoplankton growth experiments

• Establish and maintain phytoplankton cultures under 2 different pCO2 conditions and two temperature conditions.
• Conduct growth rate experiments and determine growth rate.

Conduct quagga mussel feeding experiments

• Learn how to run and analyze pigment and fluoroprobe data.
• Conduct a mussel feeding experiment with the maintained phytoplankton cultures. This will include assisting with collection of an array of water quality parameters.

Evaluate impact of freshwater acidification on phytoplankton and mussels.

• Analyze difference in phytoplankton growth rates under the different growth conditions.
• Calculate clearance rate, capture rate and ingestion rate from mussel feeding experiments.

Required Skills:  

The fellow should have a general understanding of laboratory techniques, such as working with live organisms and using general technical equipment. General understanding and experience with statistics and programs, such as Excel, R or Python. Experience with data management and note taking skills.

Location: In Person Only – NOAA Great Lakes Environmental Research Laboratory in Ann Arbor, MI.