Article
Environmental Sciences
Reza Valipour, Luis F. Leon, Todd Howell, Alice Dove, Yerubandi R. Rao
Summary: The study examines the nearshore-offshore exchange of hypoxic waters in northern Lake Erie during episodic coastal upwelling events, finding that wind-induced upwelling events play a dominant role in transporting low-oxygen waters to offshore regions. These events lead to temporal and spatial variations in oxygen levels and pH in nearshore waters, impacting oxygen levels near the lake bed.
JOURNAL OF GREAT LAKES RESEARCH
(2021)
Article
Environmental Sciences
Rene S. Shahmohamadloo, Satyendra P. Bhavsar, Xavier Ortiz Almirall, Stephen A. C. Marklevitz, Seth M. Rudman, Paul K. Sibley
Summary: Toxic harmful algal blooms (HABs) are a pervasive threat to fish populations, with substantial risks to fish health and recruitment. Although microcystins pose low risks to human health from fish consumption, the unresolved toxicological impacts on wildlife species raise uncertainties about the biodiversity and functioning of aquatic ecosystems. This field study conducted in Lake Erie highlights the need to acknowledge and address the significant threats posed by HABs.
SCIENCE OF THE TOTAL ENVIRONMENT
(2023)
Article
Marine & Freshwater Biology
Alexander Y. Karatayev, Lyubov E. Burlakova, Knut Mehler, Elizabeth K. Hinchey, Molly Wick, Martyna Bakowska, Natalia Mrozinska
Summary: A novel method was developed and tested on Lake Erie to assess Dreissenid distribution and density in large waterbodies in near real-time using video analysis. The rapid assessment method proved to be accurate and cost-effective in monitoring Dreissenid populations across large areas.
Article
Environmental Sciences
Mukul Tewari, Chandra M. Kishtawal, Vincent W. Moriarty, Pallav Ray, Tarkeshwar Singh, Lei Zhang, Lloyd Treinish, Kushagra Tewari
Summary: A machine learning approach using nutrient loading observations and physical large scale climate indices improves early seasonal prediction of harmful algal bloom activity in Lake Erie between July and October, which can assist in local fisheries management.
COMMUNICATIONS EARTH & ENVIRONMENT
(2022)
Article
Geosciences, Multidisciplinary
Shuqi Lin, Leon Boegman, Shiliang Shan, Ryan Mulligan
Summary: For enhanced public safety and water resource management, a three-dimensional operational lake hydrodynamic forecasting system, COASTLINES, was developed. The system accurately predicts lake water levels, temperatures, and other variables, with real-time visualization available on a website. Validation against observation data and satellite images confirms the accuracy of the forecasts. This forecasting system has applications in coastal flooding and water resource management.
GEOSCIENTIFIC MODEL DEVELOPMENT
(2022)
Article
Environmental Sciences
Cecilia E. Heuvel, Kenneth G. Drouillard, G. Douglas Haffner, Yingming Zhao, Aaron T. Fisk
Summary: This study found that POP concentrations were similar among different species of freshwater fish in Lake Erie, but varied significantly with ecological characteristics such as age and trophic level within individuals, illustrating the complexity of contaminant dynamics in freshwater fish.
ENVIRONMENTAL TOXICOLOGY AND CHEMISTRY
(2021)
Article
Environmental Sciences
Mark D. Rowe, Reza Valipour, Todd M. Redder
Summary: By comparing multiple Lake Erie hypoxia models, this study found that differences in model constructs can lead to variations in hypoxia predictions, emphasizing the importance of comparing different models before generating ensemble modeling load-response curves.
JOURNAL OF GREAT LAKES RESEARCH
(2023)
Article
Geosciences, Multidisciplinary
G. C. Wiles, K. Devereux, B. V. Gaglioti, R. D. D'Arrigo
Summary: We present a 420-year-long winter lake level reconstruction for Lake Erie based on temperature-sensitive tree-ring chronologies from Alaska, Oregon, and California. The model explains over 51% of the variance in winter lake levels and shows decadal fluctuations related to changes in sea surface temperatures in the North Pacific and the North Atlantic. The fluctuations in Lake Erie water levels greatly impact the region's infrastructure and ecosystems.
GEOPHYSICAL RESEARCH LETTERS
(2023)
Article
Engineering, Environmental
Peter L. Lenaker, Steven R. Corsi, Sherri A. Mason
Summary: The spatial distribution, concentration, particle size, and polymer compositions of microplastics in Lake Michigan and Lake Erie sediment were investigated. Fibers/lines were the most abundant of the five particle types characterized. Microplastic particles were observed in all samples with mean concentrations for particles greater than 0.355 mm of 65.2 p kg(-1) in Lake Michigan samples (n = 20) and 431 p kg(-1) in Lake Erie samples (n = 12).
ENVIRONMENTAL SCIENCE & TECHNOLOGY
(2021)
Article
Environmental Sciences
Junda Ren, Adam D. Point, Sadjad Fakouri Baygi, Sujan Fernando, Philip K. Hopke, Thomas M. Holsen, Bernard S. Crimmins
Summary: The bioaccumulation and biomagnification of PFAS in the Lake Erie food web were investigated using surface water and biological samples. PFOS was the dominant PFAS in the samples, followed by C9-C11 PFCAs. Apex piscivorous fish showed biomagnification of C8-C14 PFAS, while planktivorous fish exhibited biodilution. PFAS concentrations in surface water ranged from 2.1-2.8 ng/L, with PFBA being the highest. The bioaccumulation factor generally increased with log Kow for C6, 8, and 9 PFAS in all selected species.
ENVIRONMENTAL POLLUTION
(2023)
Article
Fisheries
Jerom R. Stocks, Iain M. Ellis, Dylan E. van der Meulen, Jonathon Doyle, Katherine J. M. Cheshire
Summary: Understanding the impacts of extreme events on fish populations is crucial for fisheries management. A study in Australia found that millions of native fish died in the Lower Darling-Baaka River due to hypoxia triggered by climatic events. The research also showed that the fish community in the affected area continued to experience stress, with different species responding differently to the initial fish kills over an 18-month period. Ongoing monitoring will be essential for guiding recovery management interventions in the region.
MARINE AND FRESHWATER RESEARCH
(2022)
Article
Environmental Sciences
Donald Scavia, Yu-Chen Wang, Daniel R. Obenour
Summary: Ecological models are important for predicting ecosystem responses to stresses, and their reliability depends on long records, skill assessments, and quantifying uncertainty. This study focuses on Lake Erie harmful algal blooms and enhances a Bayesian model using new information and a larger dataset. The model explains a significant portion of the variability in bloom size and performs better than previous forecasts.
SCIENCE OF THE TOTAL ENVIRONMENT
(2023)
Article
Multidisciplinary Sciences
Ferdi L. Hellweger, Robbie M. Martin, Falk Eigemann, Derek J. Smith, Gregory J. Dick, Steven W. Wilhelm
Summary: This study conducted a large-scale meta-analysis and found that the succession of harmful cyanobacteria strains is mainly influenced by cellular oxidative stress mitigation strategies and nitrogen limitation. The simulation results showed that reducing phosphorus load can decrease the biomass of cyanobacteria, but increase toxin production and concentration.
Article
Marine & Freshwater Biology
Ryan K. Walter, Stephen A. Huie, Jon Christian P. Abraham, Alexis Pasulka, Kristen A. Davis, Thomas P. Connolly, Piero L. F. Mazzini, Ian Robbins
Summary: Declining dissolved oxygen (DO) in nearshore ecosystems is a growing concern. This study reveals the dynamics and hypoxia risk in this highly variable environment. The study finds that nearshore DO is influenced by low-frequency synoptic variability, with higher variance near the surface and inside the bay. Two nearshore hypoxic regimes are identified, one driven by advection and exchange of low DO waters from the shelf during strong upwelling, and the other driven by localized respiration and stratification inside the bay during weaker upwelling.
ESTUARINE COASTAL AND SHELF SCIENCE
(2022)
Article
Engineering, Environmental
Haiping Ai, Kai Zhang, Jiachun Sun, Huichun Zhang
Summary: In order to improve control and management, the recent outbreaks of harmful algal blooms in the western Lake Erie Basin have received significant attention. A comprehensive literature review was conducted to address the limitations of existing models. A large dataset was compiled, and machine learning-based classification and regression models were built for 10-day scale bloom predictions. By analyzing feature importance, 8 key features for HAB control were identified. The models achieved high accuracy and the LSTM model provided short-term forecasts even without feature values.