Spatial and Temporal Variability of Cyanobacteria Recruitment From Hypereutrophic Reservoir Sediments

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About Me

Purpose

Methods

Results

Career Readiness Skills Gained Through Research

Acknowledgements

Research Citations

About Me

Hi, I'm Preston

I am a senior Biology student co-majoring in Environmental Science along with pursuing the GIS Certificate here at Miami. My interest in aquatic ecology began when back in 2022 when I joined Dr. Lesley Knoll's lab as a sophomore. At the time, I wasn't sure where to focus my interests within ecology, but I quickly discovered that limnology and broader aquatic ecology were the areas that most captivated me. Through the GIS Certificate, I was also introduced to geospatial science and landscape ecology. In designing this project, my goal was to merge these research interests and bring a new perspective to ongoing work related to Acton Lake.

Satellite view of Acton Lake

Credit: Google Maps

Research Question

How do cyanobacteria recruitment rates vary spatially and temporally from the sediments of a hypereutrophic reservoir?

Purpose

Cyanobacteria are a major contributor to water quality degradation in agriculturally dominated landscapes. Harmful algal blooms (HABs), often driven by excess nutrient inputs from agricultural runoff, can release toxins that negatively impact lake ecosystems (Hamilton, 2016; Rengefors, 2004). Understanding the spatial and temporal distribution of cyanobacterial blooms is essential for both preventing their occurrence and managing lakes where they are already present. One approach to studying bloom dynamics is by observing cyanobacterial spore recruitment from lake sediments. While much is known about the general process of recruitment, key questions remain such as whether spore accumulation is greater in pelagic or littoral zones, and how recruitment rates differ between these areas (Rengefors, 2004). This project aimed to explore the relationships between sediment spore recruitment rates and their spatial distribution within Acton Lake, located in Southwestern Ohio.

A satellite view of a 2017 harmful algal bloom (HAB) in Lake Erie.

Credit: NASA Earth Observatory

Study Site

Acton Lake is a man-made reservoir located within Hueston Woods State Park, north of Oxford, Ohio. It was constructed in 1955 by the U.S. Army Corps of Engineers through the damming of Four Mile Creek and is characterized by its shallow bathymetry (Knoll, 2024). The surrounding watershed is primarily agricultural(~80%), contributing to elevated inputs of fertilizer-derived nutrients.

Land use map of Acton Lake’s watershed, highlighting agricultural dominance in the watershed

Methods

Study Design

Three transects were selected at the north end of Acton Lake along a longitudinal gradient for sediment coring. Along each transect, three sediment cores were collected, one for the western and eastern shore lines and one in the lakes center. The 3rd transects western collection point was removed and replaced with a collection point near Acton’s inflow due to limitations with an old stream bed making sediment collection unattainable.

Map inset showing study site transects used for project

Data Collection

Surface sediment (top 2 cm of sediment cores) was collected along with water grab samples (besides experiment 1) at collection sites. Additionally, at each site, profiles for light, dissolved oxygen, and temperature were collected, along with surface water samples. For each site, location and time data for each sediment core was collected using Esri’s Field Maps application. Sediment cores were then taken back to the lab, where 5mL of sediment was placed in glass tubes with 20mL of sterile lake water. Sterile lake water was added slowly with a syringe and small tube to avoid disturbing the sediment. The samples were then placed in an environmental chamber under conditions of high light and ambient lake temperature in order to induce cyanobacteria recruitment. Grab samples analyzed for algae content using an Algae Lab Analyzer (ALA) on the day of collection. Water was removed and replaced every two days during the 6 day experiment and immediately ran through the ALA to measure photosynthetic activity for four major algal taxonomic groups (i.e. greens, diatoms, cryptophytes, and cyanobacteria) to determine recruitment rates.

Analysis

After sample collection, it was determined that recruitment peaked on Day 3 of incubation across all sites. Using this information, peak recruitment data from the Algae Lab Analyzer (ALA) was imported into ArcGIS Pro and joined to the corresponding GPS point data. The concentration values reflected cumulative recruitment over the three-day incubation period (Day 0 to Day 3) within the 40 mL test tubes. Once imported, Inverse Distance Weighting (IDW) interpolation was performed to visualize spatial patterns in recruitment across sampling sites for each collection period. This process was also repeated using ALA data from grab samples to identify any compositional patterns that may have occurred throughout the entire water column.

Photos from the Field and Lab

Results

Inverse Distance Weighting (IDW) was used to interpolate between sites to highlight spatial trends for peak recrutiment (Day 3 Recrutiment). These concentrations reflect recruitment over a 3 day period (day 0 to day 3) in the 40 mL test tubes.

Time series graph of cyanobacteria concentrations throughout each experimental trial. There was an overall trend of Day 3 recrutiment concentrations being the highest with recrutiment rates crashing by Day 6

In summary, no significant spatial patterns were found during the study.

Throughout the experiment recruitment spatial distribution varied greatly between sites. There were relatively consistent medium to high recruitment rates on the east shore of Acton (sites 5 & 8). While there were no significant trends here, we speculate that with west winds being dominant in the region, this may have played some role. There is also an interesting relation of substantially lower recruitment and grab sample cyanobacteria concentrations for week 2 data which are believed to be due to strong mixing and flushing caused by a large storm three days prior to sampling

While there are no clear patterns with the sites samples, a greater number of sampling sites may help reveal patterns not seen through interpolation. Overall, the results of this study demonstrate that cyanobacterial recruitment is highly variable, especially across space, challenging our previous assumptions of more uniform behavior. This emphasizes the importance of sampling a greater number of sites to better understand these more nuanced dynamics.

Inverse Distance Weighted (IDW) maps comparing chlorophyll-a concentrations from grab sample ALA data (top row) with experimental Day 3 recruitment data (bottom row).

Note: Legend values differ between maps for appropriate scaling. Trial 1 is not included due to the absence of grab sample data.

Career Readiness Skills Gained Through Research

Critical Thinking - Through designing and conducting my research, I've learned to approach complex ecological questions with a critical eye. Interpreting recruitment spatial patterns and troubleshoot lab and field methods (especially when results weren't as expected) helped me develop adaptive thinking and evidence based decision making.
Leadership & Teamwork - This being my first time leading a research project, I gained valuable experience making decisions about methodology and field techniques. Taking initiative in both the planning and execution phases gave me a deeper understanding of the research process and what it means to lead in a scientific setting. Additionally, stepping into a leadership role helped me learn how to effectively coordinate with others and clearly communicate my research objectives when being assisted in the field and lab.
Technology - This project was a great opportunity to apply and further develop my skills in ArcGIS Pro and RStudio. While I had prior experience with both programs from coursework, using them in an independent research setting allowed me to make more personalized decisions about how to visualize and manipulate my data. Being able to take ownership of those choices deepened my understanding of both tools and gave me more confidence in applying them to real-world scientific questions.

Acknowledgements

I’d like to thank Miami University for the opportunity to work on this project under the Hughes Internship. This project would also be not of been possible without the help from my mentor Dr. Lesley Knoll along with Robbyn Abbitt for helping me navigate my GIS analysis. I’d also like to thank Maggie Voyles, Kloe Atwood, Constance Kammerer, and John Castro for their help with the planning, field work, and analysis for this project.

Research Citations

1. Hamilton, David P., Nico Salmaso, and Hans W. Paerl. “Mitigating Harmful Cyanobacterial Blooms: Strategies for Control of Nitrogen and Phosphorus Loads.” Aquatic Ecology 50, no. 3 (August 23, 2016): 351–66. https://doi.org/10.1007/s10452-016-9594-z.

2. Rengefors K, Gustafsson S, Ståhl-Delbanco A. 2004. Factors regulating the recruitment of cyanobacterial and eukaryotic phytoplankton from littoral and profundal sediments. Aquatic Microbial Ecology. 36:213–226. doi:https://doi.org/10.3354/ame036213.

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