Roles of Nutrient Limitation on Western Lake Erie CyanoHAB Toxin Production

Barnard, Malcolm A.; Chaffin, Justin D.; Plaas, Haley E.; Boyer, Gregory L.; Wei, Bofan; Wilhelm, Steven W.; Rossignol, Karen L.; Braddy, Jeremy S.; Bullerjahn, George S.; Bridgeman, Thomas B.; Davis, Timothy W.; Jin, Weiqing; Bu, Minsheng; Paerl, Hans W.

doi:10.3390/toxins13010047

Cited by 27 publications

(16 citation statements)

References 104 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Of the factors to consider in HCBs development, the concentrations of N and P are critical for HCB development, e.g., in [ 18 ], and measuring these nutrients is essential for modeling and predicting HCB development [ 13 , 19 ]. However, it is unclear if nutrient load affects the interaction between C. cladosporioides and M. aeruginosa .…”

Section: Discussionmentioning

confidence: 99%

Possible Antagonism between Cladosporium cladosporioides and Microcystis aeruginosa in a Freshwater Lake during Bloom Seasons

Wymer

Vesper

Struewing

et al. 2022

Life

View full text Add to dashboard Cite

To ensure drinking-water safety, it is necessary to understand the factors that regulate harmful cyanobacterial blooms (HCBs) and the toxins they produce. One controlling factor might be any relationship between fungi and the cyanobacteria. To test this possibility, water samples were obtained from Harsha Lake in southwestern Ohio during the 2015, 2016, and 2017 bloom seasons, i.e., late May through September. In each water sample, the concentration of the filamentous fungus Cladosporium cladosporioides was determined by quantitative PCR (qPCR) assay, and Microcystis aeruginosa microcystin-gene transcript copy number (McyG TCN) was quantified by reverse-transcriptase qPCR (RT-qPCR) analyses. The results showed that during each bloom season, the C. cladosporioides concentration and McyG TCN appeared to be interrelated. Therefore, C. cladosporioides concentrations were statistically evaluated via regression on McyG TCN in the water samples for lag times of 1 to 7 days. The regression equation developed to model the relationship demonstrated that a change in the C. cladosporioides concentration resulted in an opposing change in McyG TCN over an approximately 7-day interval. Although the interaction between C. cladosporioides and McyG TCN was observed in each bloom season, the magnitude of each component varied yearly. To better understand this possible interaction, outdoor Cladosporium spore-count data for the Harsha Lake region were obtained for late May through September of each year from the South West Ohio Air Quality Agency. The average Cladosporium spore count in the outdoor air samples was significantly greater in 2016 than in either 2015 or 2017, and the M. aeruginosa McyG TCN was significantly lower in Harsha Lake water samples in 2016 compared to 2015 or 2017. These results suggest that there might be a “balanced antagonism” between C. cladosporioides and M. aeruginosa during the bloom season.

show abstract

Section: Discussionmentioning

confidence: 99%

Possible Antagonism between Cladosporium cladosporioides and Microcystis aeruginosa in a Freshwater Lake during Bloom Seasons

Wymer

Vesper

Struewing

et al. 2022

Life

View full text Add to dashboard Cite

show abstract

“…We are aware that when blooms reemerge, it is important to look at additional factors beyond those that previously drove the prior blooms. In multiple systems where the blooms were traditionally P-limited, anthropogenic loading of nutrients has led to eutrophication and N-limitation and N and P co-limitation arising (e.g., Barnard et al, 2021;Paerl et al, 2011Paerl et al, , 2016Jansson et al, 2001). However, nitrogen concentrations in the pelagic zone and river inputs did not change dramatically and did not seem to have a significant impact on the resurgence of P. rubescens.…”

Section: Discussionmentioning

confidence: 99%

Die hard in Lake Bourget! The case of Planktothrix rubescens reborn

Rimet

Girel³

et al. 2021

Ann. Limnol. - Int. J. Lim.

View full text Add to dashboard Cite

Blooms of Planktothrix rubescens have been recorded for 15 years in Lake Bourget (France), from 1995 to 2009. Then, the presence of this filamentous and toxic cyanobacterium became anecdotic between 2010 and 2015 and it was thought that its proliferation was over. However, blooms occurred again in 2016 and 2017 despite apparent low phosphorus concentrations in surface waters of the lake. We have attempted to explain the reasons for this come back in order to develop scenarios helpful to stakeholders who are concerned such proliferations may occur in the future. We show that phosphorus input, both from the main tributaries to the lake and possibly from the sediments, were likely the triggers of the new development of the cyanobacterium provided a minimum autumn/winter inoculum of P. rubescens was detected the year before. The subsequent bloom was observed deeper than previous years and associated with a conjunction of factors known to favour the development of this species (i.e., mild winter temperature, water column stability, available light at depth, surface water transparency, low predation, etc.). Although many factors and processes could account for the occurrence and bloom of the cyanobacterium, a plausible scenario is proposed. One thing remains unclear: where does this cyanobacterium “hide” when it is not observed during the routine monitoring surveys and from which place it could initiate its development (nearshore, the pelagic zone, or from the sediment?).

show abstract

“…Under future climate change and nutrient management scenarios, the predicted average annual Chl-a concentrations were in the range of 15-16 µg L −1 . CYANO is the major component of total Chl-a [68], with the optimal temperature for growth above 25 • C [69]. In the future climate scenario, the temperature is 0.27-7.84 • C, which is much lower than the 25 • C that occurred in the summer during 2002 and 2015, so the predicted Chl-a concentrations are lower than the peak values during 2002 and 2015 in Figure 4.…”

Section: Prediction Of Future Water Qualitymentioning

confidence: 93%

A Predictive Model of Chlorophyll a in Western Lake Erie Based on Artificial Neural Network

Wang

2021

Applied Sciences

View full text Add to dashboard Cite

The reoccurrence of algal blooms in western Lake Erie (WLE) since the mid-1990s, under increased system stress from climate change and excessive nutrients, has shown the need for developing management tools to predict water quality. In this study, process-based model GLM-AED (General Lake Model-Aquatic Ecosystem Dynamics) and statistical model ANN (artificial neural network) were developed with meteorological forcing derived from surface buoys, airports, and land-based stations and historical monitoring nutrients, to predict water quality in WLE from 2002 to 2015. GLM-AED was calibrated with observed water temperature and chlorophyll a (Chl-a) from 2002 to 2015. For ANN, during the training period (2002–2010), the inputs included meteorological forcing and nutrient concentrations, and the target was Chl-a simulated by calibrated GLM-AED due to the lack of continuously daily measured Chl-a concentrations. During the testing period (2011–2015), the predicted Chl-a concentrations were compared with the observations. The results showed that the ANN model has higher accuracy with lower Chl-a RMSE and MAE values than GLM-AED during 2011 and 2015. Lastly, we applied the established ANN model to predict the future 10-year water quality of WLE, which showed that the probability of adverse health effects would be moderate, so more intense water resources management should be implemented.

show abstract

Roles of Nutrient Limitation on Western Lake Erie CyanoHAB Toxin Production

Cited by 27 publications

References 104 publications

Possible Antagonism between Cladosporium cladosporioides and Microcystis aeruginosa in a Freshwater Lake during Bloom Seasons

Possible Antagonism between Cladosporium cladosporioides and Microcystis aeruginosa in a Freshwater Lake during Bloom Seasons

Die hard in Lake Bourget! The case of Planktothrix rubescens reborn

A Predictive Model of Chlorophyll a in Western Lake Erie Based on Artificial Neural Network

Contact Info

Product

Resources

About