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Data and model archive for multiple linear regression models for prediction of weighted cyanotoxin mixture concentrations and microcystin concentrations at three recurring bloom sites in Kabetogama Lake in Minnesota

Dates

Publication Date
Start Date
2016-06-02
End Date
2017-09-19

Citation

Christensen, V.G., Stelzer, E.A., and Haserodt, M.H., 2021, Data and model archive for multiple linear regression models for prediction of weighted cyanotoxin mixture concentrations and microcystin concentrations at three recurring bloom sites in Kabetogama Lake in Minnesota: U.S. Geological Survey data release, https://doi.org/10.5066/P9X7EO1K.

Summary

Multiple linear regression models were developed using data collected in 2016 and 2017 from three recurring bloom sites in Kabetogama Lake in northern Minnesota. These models were developed to predict concentrations of cyanotoxins (anatoxin-a, microcystin, and saxitoxin) that occur within the blooms. Virtual Beach software (version 3.0.6) was used to develop four models: two cyanotoxin mixture (MIX) models and two microcystin (MC) models. Models include those using readily available environmental variables (for example, wind speed and specific conductance) and those using additional comprehensive variables (based on laboratory analyses). Many of the independent variables were averages over a certain time period prior to a sample date, [...]

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Attached Files

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MC comprehensive_final_data.csv 3.01 KB text/csv
MC_environmental_final_dataset.csv 2.46 KB text/csv
MIX_comprehensive_final_dataset.csv 3.08 KB text/csv
MIX_environmental_final_dataset.csv 2.51 KB text/csv
Model equations.docx 31.63 KB application/vnd.openxmlformats-officedocument.wordprocessingml.document

Purpose

Purpose: Models to be considered for management decisions to predict toxin concentration to evaluate exceedance of a weighted toxin or microcystin threshold values at Kabetogama Lake. In addition, data used to develop the models are provided for each model. All measured and calculated variables initially considered in developing the models are provided in the model archive.

Additional Information

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DOI https://www.sciencebase.gov/vocab/category/item/identifier doi:10.5066/P9X7EO1K

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