Citation:

Banerji, A., M. Bagley, J. Shoemaker, Dan Tettenhorst, C. Nietch, Joel Allen, AND J. Santodomingo. Evaluating putative ecological drivers of microcystin spatiotemporal dynamics using metabarcoding and environmental data. Harmful Algae. Elsevier B.V., Amsterdam, Netherlands, 86:84-95, (2019). https://doi.org/10.1016/j.hal.2019.05.004

Impact/Purpose:

We performed random forest regression analyses on metagenomic (16S and 18S rRNA genes) and environmental time series data for a freshwater reservoir to determine which biotic and abiotic factors were most closely associated with the dynamics of total microcystin and several specific congeners. The cyanotoxin microcystin is a global health concern. Understanding the environmental drivers of microcystin production is crucial for establishing best management practices to reduce harmful exposures. Numerous hypotheses regarding ecological functions of microcystin have been proposed, but evidence in favor of these hypotheses has not been definitive. We performed random forest regression analyses on metagenomic (16S and 18S rRNA genes) and environmental time series data for a freshwater reservoir to determine which biotic and abiotic factors were most closely associated with the dynamics of total microcystin and several specific congeners. Model performance was highest for prediction of MC-LR concentrations, with ca. 90% of spatial and temporal variance explained. Toxic cyanobacteria such as Microcystis and Cylindrospermopsis explained most of the variance. Assessment of the model predictors’ relative importance within the model and temporal dynamics revealed evidence of MC-LR having roles in defense, interference competition, nutrient processing, and homeostasis. Surprisingly, however, factors long thought to be important drivers of microcystin production, such as temperature and arthropod grazers, were not predictive of microcystin dynamics in our system. Instead, the main drivers appeared to be protozoans, non-microcystin-producing cyanobacteria, total reactive P, and pH.

Description:

The cyanotoxin microcystin is a global health concern. Understanding the environmental drivers of microcystin production is crucial for establishing best management practices to reduce harmful exposures. Numerous hypotheses regarding ecological functions of microcystin have been proposed, but evidence in favor of these hypotheses has not been definitive. We performed random forest regression analyses on metagenomic (16S and 18S rRNA genes) and environmental time series data for a freshwater reservoir to determine which biotic and abiotic factors were most closely associated with the dynamics of total microcystin and several specific congeners. Model performance was highest for prediction of MC-LR concentrations, with ca. 90% of spatial and temporal variance explained. Toxic cyanobacteria such as Microcystis and Cylindrospermopsis explained most of the variance. Assessment of the model predictors’ relative importance within the model and temporal dynamics revealed evidence of MC-LR having roles in defense, interference competition, nutrient processing, and homeostasis. Surprisingly, however, factors long thought to be important drivers of microcystin production, such as temperature and arthropod grazers, were not predictive of microcystin dynamics in our system. Instead, the main drivers appeared to be protozoans, non-microcystin-producing cyanobacteria, total reactive P, and pH.

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