Correlation of cyanobacterial harmful bloom monitoring parameters: A case study on western Lake Erie

Hesam Zamankhan Malayeri; Mike Twardowski; James Sullivan; Timothy Moore; Hyeok Choi; Hesam Zamankhan Malayeri; Mike Twardowski; James Sullivan; Timothy Moore; Hyeok Choi

doi:10.3934/environsci.2018.1.24

AIMS Environmental Science

2018, Volume 5, Issue 1: 24-34. doi: 10.3934/environsci.2018.1.24

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Research article

Correlation of cyanobacterial harmful bloom monitoring parameters: A case study on western Lake Erie

1.
Department of Civil Engineering, The University of Texas at Arlington, Arlington, TX 76019-0308, USA
2.
Harbor Branch Oceanographic Institute, Florida Atlantic University, Fort Pierce, FL 34946, USA
3.
Institute for the Study of Earth, Oceans, and Space, University of New Hampshire, Durham, NH, 03824-3525, USA

Received: 01 September 2017 Accepted: 26 January 2018 Published: 06 February 2018

Occurrence of cyanobacterial harmful blooms (CHBs) in water has caused serious concern to environmental and health authorities because of their potential to produce and release lethal biological toxins. Among many toxins, microcystins (MCs) are of particular interest. There have been significant efforts to observe the harmful algal bloom events and cyanotoxin levels, including: (i) manual field sampling followed by lab analysis to directly measure MCs, (ii) remote sensing based on satellite image analysis to estimate cyanobacterial index (CI), and (iii) in-situ sensing of proxy parameters to cyanobacterial blooms such as phycocyanin. This study compared the observation systems in western Lake Erie to find any potential correlations among these CHB monitoring parameters based on the Pearson Product-Moment equation. We found the relationships among the parameters to be site-specific and so we compared geographical, ecological, meteorological, and analytical factors specific to the locations to explain the observed correlations and variations. The CHB observing parameters (MCs, CI, and phycocyanin) were generally well correlated because they inherently represented the same phenomenon. In particular, we found the measured biological toxin concentration (MCs) to be strongly correlated with the cyanobacterial bloom activity (CI) estimated by satellite image analysis. The phycocyanin concentration also had a strong correlation with CI, implying that measuring an easy-to-detect proxy parameter in-situ and in real-time is effective for monitoring CHBs. The results support the notion that key environmental management parameters such as CHB toxicity can be inferred from remotely-sensed ocean color through proxy variables such as CI.
- cyanobacterial harmful blooms,
- harmful algal blooms,
- Lake Erie,
- microcystins,
- cyanobacterial index,
- phycocyanin,
- monitoring and observation
Citation: Hesam Zamankhan Malayeri, Mike Twardowski, James Sullivan, Timothy Moore, Hyeok Choi. Correlation of cyanobacterial harmful bloom monitoring parameters: A case study on western Lake Erie[J]. AIMS Environmental Science, 2018, 5(1): 24-34. doi: 10.3934/environsci.2018.1.24

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Abstract

Occurrence of cyanobacterial harmful blooms (CHBs) in water has caused serious concern to environmental and health authorities because of their potential to produce and release lethal biological toxins. Among many toxins, microcystins (MCs) are of particular interest. There have been significant efforts to observe the harmful algal bloom events and cyanotoxin levels, including: (i) manual field sampling followed by lab analysis to directly measure MCs, (ii) remote sensing based on satellite image analysis to estimate cyanobacterial index (CI), and (iii) in-situ sensing of proxy parameters to cyanobacterial blooms such as phycocyanin. This study compared the observation systems in western Lake Erie to find any potential correlations among these CHB monitoring parameters based on the Pearson Product-Moment equation. We found the relationships among the parameters to be site-specific and so we compared geographical, ecological, meteorological, and analytical factors specific to the locations to explain the observed correlations and variations. The CHB observing parameters (MCs, CI, and phycocyanin) were generally well correlated because they inherently represented the same phenomenon. In particular, we found the measured biological toxin concentration (MCs) to be strongly correlated with the cyanobacterial bloom activity (CI) estimated by satellite image analysis. The phycocyanin concentration also had a strong correlation with CI, implying that measuring an easy-to-detect proxy parameter in-situ and in real-time is effective for monitoring CHBs. The results support the notion that key environmental management parameters such as CHB toxicity can be inferred from remotely-sensed ocean color through proxy variables such as CI.

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