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Carotenoids; a unique biomarker for monitoring Peridinium dinoflagellate blooms in freshwaters
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Abstract
Peridinium is a rare but, toxic bloom-forming dinoflagellate in freshwaters. Its toxic effects were reported from several countries including Sri Lanka although not-much attened. In this study, we developed a remote sensing-based empirical model to quantify Peridinium using Maussakelle Reservoir in Sri Lanka as the model. Since carotenoids are the major light-harvesting accessary pigments of Peridinium and many other dinoflagellates, it serves as a unique biomarker. Thus, spectral signatures of carotenoids allowed us to distinguish Peridinium in the background of chlorophyll-dominated mix population of phytoplankton. Ground data and Sentinel-2 satellite images were collected when a high density of Peridinium and carotenoid pigment levels were present and a set of linear regression models were developed. Among the models, that developed with B2 and B3 bands of Sentinel-2 better regressed with measured carotenoid (R2 = 0.93, p < 0.001). The relationship between measured and model-predicted carotenoid concentrations displayed a correlation (R2) of 0.86 and root mean squared error (RMSE) of 2.82. Further, a second regression model was developed to predict Peridinium cell density using carotenoid as a proxy. The established relationship was strong and significant (R2 = 0.85, p < 0.001). Then a final empirical model was derived by coupling the two regression models to quantify Peridinium cell density (R2 = 0.71, p < 0.001). We highlight that this method would be a novel approach that directs reliable and accurate prediction and quantification of carotenoid pigments and Peridinium cell density in freshwaters.
Title: Carotenoids; a unique biomarker for monitoring Peridinium dinoflagellate blooms in freshwaters
Description:
Abstract
Peridinium is a rare but, toxic bloom-forming dinoflagellate in freshwaters.
Its toxic effects were reported from several countries including Sri Lanka although not-much attened.
In this study, we developed a remote sensing-based empirical model to quantify Peridinium using Maussakelle Reservoir in Sri Lanka as the model.
Since carotenoids are the major light-harvesting accessary pigments of Peridinium and many other dinoflagellates, it serves as a unique biomarker.
Thus, spectral signatures of carotenoids allowed us to distinguish Peridinium in the background of chlorophyll-dominated mix population of phytoplankton.
Ground data and Sentinel-2 satellite images were collected when a high density of Peridinium and carotenoid pigment levels were present and a set of linear regression models were developed.
Among the models, that developed with B2 and B3 bands of Sentinel-2 better regressed with measured carotenoid (R2 = 0.
93, p < 0.
001).
The relationship between measured and model-predicted carotenoid concentrations displayed a correlation (R2) of 0.
86 and root mean squared error (RMSE) of 2.
82.
Further, a second regression model was developed to predict Peridinium cell density using carotenoid as a proxy.
The established relationship was strong and significant (R2 = 0.
85, p < 0.
001).
Then a final empirical model was derived by coupling the two regression models to quantify Peridinium cell density (R2 = 0.
71, p < 0.
001).
We highlight that this method would be a novel approach that directs reliable and accurate prediction and quantification of carotenoid pigments and Peridinium cell density in freshwaters.
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