Chlorophyll a as an indicator of microcystin: Short-term forecasting and risk assessment in Lake Erie

Chlorophyll a as an indicator of microcystin: Short-term forecasting and risk assessment in Lake Erie

We developed a Bayesian hierarchical modeling framework to establish a short-term forecasting model of particulate cyanobacterial toxin concentrations in Western Lake Erie using chlorophyll a concentration as the predictor. The model evolves over time with additional data to reflect the changing dyn...

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Bibliographic Details
Main Authors: Anderson, E.J (Author), Johengen, T.H (Author), Liu, Q. (Author), Qian, S.S (Author), Rowe, M.D (Author), Rowland, F.E (Author), Stow, C.A (Author), Stumpf, R.P (Author)
Format: Article
Language:English
Published: Elsevier B.V. 2021
Subjects:
Algae control
Bayesian hierarchical model
Bayesian networks
bioindicator
Chlorophyll
chlorophyll a
concentration (composition)
Cyanobacteria
Cyanobacterial toxins
cyanobacterium
ecological modeling
Forecasting
forecasting method
Great Lakes [North America]
harmful algal blooms
Harmful algal blooms
Hierarchical systems
Indicator indicator
informative priors
Informative Priors
Lake Erie
Lakes
Microcystins
predictive model
Predictive models
risk assessment
Risk assessment
Risks assessments
sequential updating
Sequential updating
Short-term forecasting
Toxic materials
toxin
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