Grantee Research Project Results
Final Report: A systems approach for understanding, predicting, and managing harmful algal blooms in Midwestern lakes
EPA Grant Number: R839270Title: A systems approach for understanding, predicting, and managing harmful algal blooms in Midwestern lakes
Investigators: Howe, Adina , Ikuma, Kaoru , Swanner, Elizabeth , Lee, Jaejin
Institution: Iowa State University
EPA Project Officer: Ludwig-Monty, Sarah
Project Period: January 1, 2018 through December 31, 2020 (Extended to December 31, 2021)
Project Amount: $760,000
RFA: Freshwater Harmful Algal Blooms (2017) RFA Text | Recipients Lists
Research Category: Water , Watersheds , Water Quality
Objective:
The objective of the study was to use a systems approach to identify genetic and environmental factors controlling the occurrence and fate of harmful algal blooms (HABs) in Iowa’s recreational lakes. We hypothesized that HAB ecology and cyanotoxin production are the predictable result of environmental factors (e.g., high nutrient conditions); that the underlying genetic markers for cyanotoxin production are taxonomically controlled; and that incipient cyanotoxin-degrading microbes are present during HABs. We tested these hypotheses in conjunction with the development of novel predictive tools to target future cyanotoxin monitoring and mitigation to the highest-risk recreational waters. In this study, we conducted an integrated meta-analysis of physicochemical parameters and microbiome analyses of Iowa’s HAB-impacted recreational waters to develop a predictive model of HAB occurrence; developed scalable tools that can be used to rapidly monitor HABs and identify when additional cyanotoxin monitoring is necessary; identified emerging cyanotoxins within Iowa's lakes and determine the freshwater HAB species linked to these toxins and the genetic systems that control toxin production; and identified and evaluated novel toxin-degraders for the mitigation of HAB cyanotoxins. The output of this work will promote the implementation of early warning and closures of HAB-associated recreational waters that threaten public health.
Summary/Accomplishments (Outputs/Outcomes):
Throughout four years of sampling, 1,792 freshwater lake samples were collected. Across the state of Iowa, 36 lakes were sampled for 15-week periods over 2 years to monitor microbiome community changes over time, as well as observations of nutrient and weather data. Findings of microcystin levels correlated with dissolved organic carbon, pH, and nitrogen, with negative correlations to chlorine levels and nitrous oxide. Microcystin levels were seen to correlate with temperature, dew point, and wind speed. Co-occurrences within the microbiome at the genera level revealed evidence of relationships between Microcystis and three other Cyanobacteria, Snowella, Dolichospermum, and Pseudanabaena, with negative co-occurrences observed for many genera of Actinobacteriota and Proteobacteria, such as Limnohabitans
Establishing a machine learning-based predictive model for one-week ahead prediction of cyanobacterial harmful algal blooms in Iowa lakes was completed. Although more than 1,500 samples were collected from 2018 to 2020, additional sampling (i.e., 120 samples) was conducted in 2021 to compensate the imbalance between hazardous and non-hazardous cases. Microcystin concentrations were categorized into two classes according to EPA’s guidelines (i.e., over the advisory threshold: ³ 8 mg/L and below threshold: < 8 mg/L). The predictive model we used was based on using the XGBoost machine learning algorithm and can be directly used to forecast the occurrence of cyanobacterial harmful algal blooms one-week ahead.
We demonstrated that it is feasible for agencies to monitor the development of Cyanobacterial blooms in multiple lakes simultaneously in real-time using multi-wavelength fluorescence instruments. Verification of Chlorophyll a data from multi-wavelength fluorescence with lab-based extractions is recommended a subset of samples as a quality check, and dilutions are recommended for samples with >200 µg L-1 chlorophyll. The multi-wavelength technique was most accurate for Cyanobacteria and diatoms/dinoflagellates.
We targeted lakes in the last 8 weeks of IDNR beach sampling, when toxin concentrations are generally higher for analysis of saxitoxin and anatoxin and targeted these lakes and dates for enrichments. We found that saxitoxin and anatoxin were detectable in numerous lakes, with anatoxin detection increasing in the late season. There are currently no EPA regulations regarding exposure to anatoxin and saxitoxin. We also detected the presence of microcystin-degrading bacteria in Iowa lake, which are previously rarely reported in US lakes. We also showed that the lake water microbial communities and their metabolic activities can be strongly influenced by the presence of cyanotoxins.
Journal Articles on this Report : 1 Displayed | Download in RIS Format
Other project views: | All 11 publications | 1 publications in selected types | All 1 journal articles |
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Lee J, Choi J, Fatka M, Swanner E, Ikuma K, Liang X, Leung T, Howe A. Improved detection of mcyA genes and their phylogenetic origins in harmful algal blooms. Water Research 2020;19:115730. |
R839270 (2019) R839270 (Final) |
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Progress and Final Reports:
Original AbstractThe perspectives, information and conclusions conveyed in research project abstracts, progress reports, final reports, journal abstracts and journal publications convey the viewpoints of the principal investigator and may not represent the views and policies of ORD and EPA. Conclusions drawn by the principal investigators have not been reviewed by the Agency.