Dynamic internal drivers of a historically severe cyanobacteria bloom in Lake Champlain revealed through comprehensive monitoring

Isles, Peter D. F.; Giles, Courtney D.; Gearhart, Trevor; Xu, Yaoyang; Druschel, Greg K.; Schroth, Andrew W.

doi:10.1016/j.jglr.2015.06.006

Cited by 51 publications

(44 citation statements)

References 67 publications

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“…For example, cyanobacterial growth is optimal at higher temperatures, between 15 and 30°C (Konopka and Brock, 1978). We confirmed that cyanobacterial blooms are correlated with and likely respond to nutrient concentrations, as previously described (Fogg, 1969;Jacoby et al, 2000;Paerl and Huisman, 2008;Paerl and Huisman, 2009;Fortin et al 2015;Isles et al, 2015). Dissolved nitrogen and temperature were negatively correlated, which could be explained by the fact that the lake becomes enriched in nitrates during spring, when temperatures are lower and rain and drainage bring nutrients into the lake (Shade et al, 2007;Fortin et al, 2015).…”

Section: Discussionsupporting

confidence: 89%

Characterising and predicting cyanobacterial blooms in an 8-year amplicon sequencing time course

et al. 2017

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Cyanobacterial blooms occur in lakes worldwide, producing toxins that pose a serious public health threat. Eutrophication caused by human activities and warmer temperatures both contribute to blooms, but it is still difficult to predict precisely when and where blooms will occur. One reason that prediction is so difficult is that blooms can be caused by different species or genera of cyanobacteria, which may interact with other bacteria and respond to a variety of environmental cues. Here we used a deep 16S amplicon sequencing approach to profile the bacterial community in eutrophic Lake Champlain over time, to characterise the composition and repeatability of cyanobacterial blooms, and to determine the potential for blooms to be predicted based on time course sequence data. Our analysis, based on 135 samples between 2006 and 2013, spans multiple bloom events. We found that bloom events significantly alter the bacterial community without reducing overall diversity, suggesting that a distinct microbial community-including non-cyanobacteria-prospers during the bloom. We also observed that the community changes cyclically over the course of a year, with a repeatable pattern from year to year. This suggests that, in principle, bloom events are predictable. We used probabilistic assemblages of OTUs to characterise the bloom-associated community, and to classify samples into bloom or non-bloom categories, achieving up to 92% classification accuracy (86% after excluding cyanobacterial sequences). Finally, using symbolic regression, we were able to predict the start date of a bloom with 78-92% accuracy (depending on the data used for model training), and found that sequence data was a better predictor than environmental variables.

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Section: Discussionsupporting

confidence: 89%

Characterising and predicting cyanobacterial blooms in an 8-year amplicon sequencing time course

et al. 2017

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“…Expansion and persistence of low DO conditions due to lack of physical mixing and oxygen diffusion from the atmosphere allowed Mn concentrations to increase in the bottom water over time and expand vertically as winter progressed. In comparison to the 2014 winter, as well as multiple field campaigns during summer blooms (Smith et al ; Isles et al ; Giles et al ), the continuous suboxic conditions of bottom water DO during the Cold Period were the most persistent ever measured at MB. This indicates that particularly cold winters that limit physical mixing and SWI re‐oxygenation can expose shallow sediments to prolonged periods of reducing conditions, the duration of which (months) is simply not feasible in other seasons due to more active mixing and surficial oxygen diffusion.…”

Section: Discussionmentioning

confidence: 89%

“…Global climate change has and will continue to cause a reduction in the frequency and duration of ice cover during winter (IPCC 2007;Weyhenmeyer et al 2008Weyhenmeyer et al , 2011Dibike et al 2012;Shuter et al 2013). Many seasonally ice covered lakes ranging from small ponds to the Laurentian Great Lakes have experienced delayed ice-onset and early ice break-up (Magnuson et al 2000;Hodgkins et al 2002;Vincent 2010).…”

mentioning

confidence: 99%

Winter weather and lake‐watershed physical configuration drive phosphorus, iron, and manganese dynamics in water and sediment of ice‐covered lakes

Joung

Leduc²,

Ramcharitar

et al. 2017

Limnology & Oceanography

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While decreasing occurrence and duration of lake ice cover is well-documented, biogeochemical dynamics in frozen lakes remain poorly understood. Here, we interpret winter physical and biogeochemical time series from eutrophic Missisquoi Bay (MB) and hyper-eutrophic Shelburne Pond (SP) to describe variable drivers of under ice biogeochemistry in systems of fundamentally different lake-watershed physical configurations (lake area, lake : watershed area). The continuous cold of the 2015 winter drove the MB sediment-water interface to the most severe and persistent suboxic state ever documented at this site, promoting the depletion of redoxsensitive phases in sediments, and an expanding zone of bottom water enriched in reactive species of Mn, Fe, and P. In this context, lake sediment and water column inventories of reactive chemical species were sensitive to the severity and persistence of subfreezing temperatures. During thaws, event provenance and severity impact lake thermal structure and mixing, water column enrichment in P and Fe, and thaw capability to suppress redox front position and internal chemical loading. Nearly identical winter weather manifest differently in nearby SP, where the small surface and watershed areas promoted a warmer, less stratified water column and active phytoplankton populations, impacting biogeochemical dynamics. In SP, Fe and P behavior under ice were decoupled due to active biological cycling, and thaw impacts were different in distribution and composition due to SP's physical structure and related antecedent conditions. We find that under ice biogeochemistry is highly dynamic in both time and space and sensitive to a variety of drivers impacted by climate change.

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“…With the high P addition, we aimed to ensure N limitation of the phytoplankton. P release from the sediment resulting in a high availability of P is a common process in many shallow polymictic lakes in summer (e.g., Isles et al, ; Köhler et al, ).…”

Section: Methodsmentioning

confidence: 99%

The response of nitrogen fixing cyanobacteria to a reduction in nitrogen loading

Kolzau

Dolman

Voß

et al. 2018

Internat Rev Hydrobiol

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Due to their competitive advantage when inorganic nitrogen (N) sources are scarce, it is widely assumed that the abundance and N2‐fixation rate of N2‐fixing cyanobacteria (Nostocales) would increase in response to reduced N loading. If realized, this response would render efforts to improve water quality by N reduction ineffective. To assess this, we performed a microcosm experiment using water from an N limited lake, Langer See, in which phosphorus loading was held constant, while a gradient of decreasing N loading was simulated. Nostocales biovolume increased over time in all microcosms, regardless of the N addition rate, so that no difference in Nostocales biovolume developed between high and low N microcosms. In contrast, the biovolumes of other taxa (especially non‐fixing cyanobacteria) were lower at low N addition rates. N2‐fixation increased in low N microcosms, compensating for 36% of the difference in N addition by day 6. However, this compensation rate was achieved at Nostocales biovolumes far higher than those typical in the studied lake. At biovolumes typical for summer the compensation rate would only account for 7% of the omitted N. If these results were to hold over longer time scales, in shallow polymictic lakes like Langer See, reduced N loading may lower both in‐lake N concentrations and biovolumes of non‐fixing phytoplankton without significantly impacting Nostocales biovolume.

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Dynamic internal drivers of a historically severe cyanobacteria bloom in Lake Champlain revealed through comprehensive monitoring

Cited by 51 publications

References 67 publications

Characterising and predicting cyanobacterial blooms in an 8-year amplicon sequencing time course

Characterising and predicting cyanobacterial blooms in an 8-year amplicon sequencing time course

Winter weather and lake‐watershed physical configuration drive phosphorus, iron, and manganese dynamics in water and sediment of ice‐covered lakes

The response of nitrogen fixing cyanobacteria to a reduction in nitrogen loading

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