| Autor: |
Miller TR; Joseph J. Zilber School of Public Health , University of Wisconsin-Milwaukee , Milwaukee , Wisconsin 53211 , United States., Bartlett SL; Joseph J. Zilber School of Public Health , University of Wisconsin-Milwaukee , Milwaukee , Wisconsin 53211 , United States.; School of Freshwater Sciences , University of Wisconsin-Milwaukee , Milwaukee , Wisconsin 53204 , United States., Weirich CA; Joseph J. Zilber School of Public Health , University of Wisconsin-Milwaukee , Milwaukee , Wisconsin 53211 , United States., Hernandez J; Joseph J. Zilber School of Public Health , University of Wisconsin-Milwaukee , Milwaukee , Wisconsin 53211 , United States. |
| Abstrakt: |
Temporal variability of toxins produced by cyanobacteria in lakes is relatively unknown at time scales relevant to public health (i.e., hourly). In this study, a water quality monitoring buoy was outfitted with an automated water sampler taking preserved samples every 6 h for 68.75 days over a drinking water intake. A total of 251 samples were analyzed by tandem mass spectrometry for 21 cyanotoxin congeners in 5 classes producing 5020 data points. Microcystins (MCs) were the most abundant toxins measured (mean ± sd = 3.9 ± 3.3 μg/L) followed by cyanopeptolins (CPs) (1.1 ± 1.5 μg/L), anabaenopeptins (APs) (1.0 ± 0.6 μg/L), anatoxin-a (AT-A) (0.03 ± 0.06 μg/L), and microginin-690 (MG-690) (0.002 ± 0.01 μg/L). Advanced time series analyses uncovered patterns in cyanotoxin production. The velocity of cyanotoxin concentration varied from -0.7 to 0.9 μg/L/h with a maximum positive velocity just prior to peak toxin concentration during nonbloom periods. A backward-looking moving window of variance analysis detected major increases in cyanotoxin concentration and predicted the two greatest increases in MC. A wavelet analysis identified a significant ( p < 0.01) 2.8-4.2 day periodicity in toxin concentration over a ∼25 day period during peak toxin production, which is partially explained by easterly wind velocity ( R = -0.2, p < 0.05). Diversity in congener profiles was explored with principle component analysis showing that cyanotoxin dynamics followed a seasonal trajectory where toxin profiles were significantly clustered (ANOSIM R = 0.7, p < 0.05) on a daily basis. Variability in toxin profiles was strongly correlated with time ( R = -0.8, p < 0.001) as well as the C:N ratio of the toxin pool ( R = 0.17, p < 0.05). The methods employed here should be useful for uncovering patterns in cyanotoxin dynamics in other systems. |
