Causes, Prevention, and Mitigation Workgroup Report

Perovich, Gina; Dortch, Quay; Goodrich, James Tait; Berger, Paul S.; Brooks, J. C.; Evens, Terence J.; Gobler, Christopher J.; Graham, Jennifer L.; Hyde, James B.; Karner, Dawn A.; O'Shea, Dennis; Paul, Valerie J.; Paerl, Hans W.; Piehler, Michael F.; Rosen, Barry H.; Santelmann, Mary V.; Tester, Pat; Westrick, Judy A.

doi:10.1007/978-0-387-75865-7_9

Cited by 14 publications

(10 citation statements)

References 32 publications

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“…However, limiting nutrient inputs often does not control FHABs in the near term. The implementation of nutrient input-reduction strategies is usually a long-term undertaking, and nutrient loads already in sediment frequently stimulate FHABs when resuspended into the water column (Paerl, 2008;Perovich et al, 2008;Pieler, 2008).…”

Section: Introductionmentioning

confidence: 98%

Freshwater harmful algal bloom (FHAB) suppression with solar powered circulation (SPC)

Hudnell

Jones

Labisi³

et al. 2010

Harmful Algae

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Section: Introductionmentioning

confidence: 98%

Freshwater harmful algal bloom (FHAB) suppression with solar powered circulation (SPC)

Hudnell

Jones

Labisi³

et al. 2010

Harmful Algae

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“…Estimating the nutrient load reductions necessary to achieve target bloom sizes requires models capable of quantifying the relationshipbetween load and bloom severity. Accurate quantification of the uncertainty associated with the load-bloom relationship is also critical to provide policy makers with defensible ranges of likely future bloom sizes corresponding to different P load scenarios.Quantified uncertainty should be recognized as essential information in the decision process (Reckhow, 1994;Reckhow and Chapra, 1999)and is particularly important when modeling a phenomenon like cyanobacteria blooms, where substantial limitations and uncertainties are known to affect the methods used to measure bloom size (Ho and Michalak, 2015;Reinart and Kutser, 2006;Srivastava et al, 2013), as well as our knowledge of the multiple interacting processes that influence bloom formation (Perovich et al, 2008). Failure to account for these sources of variance could lead to models that do not accurately reflect our actual knowledge of the system`s behavior.…”

Section: Introductionmentioning

confidence: 99%

Probabilistically assessing the role of nutrient loading in harmful algal bloom formation in western Lake Erie

Bertani

Obenour

Steger

et al. 2016

Journal of Great Lakes Research

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Harmful algal blooms (HABs) have increased in frequency and magnitude in western Lake Erie and spring phosphorus (P) load was shown to be a key driver of bloom intensity. A recently developed Bayesian hierarchical model that predicts peak bloom size as a function of Maumee River phosphorus load suggested an apparent increased susceptibility of the lake to HABs. We applied that model to develop load-response curves to inform revision of Lake Erie phosphorus load targets under the 2012 Great Lakes Water Quality Agreement. In this application, the model was modified to estimate the fraction of the particulate P (PP) load that becomes bioavailable, and it was re-calibrated with additionalbloom observations. Although the uncertainty surrounding the estimate of the bioavailable PP fraction is large, inclusion in the model improves prediction of bloom variability compared to dissolved reactive P (DRP) alone. The ability to characterize model and measurement uncertainty through hierarchical modeling allowed us to show that inconsistencies in bloom measurement represent a considerable portion of the overall uncertainty associated with load-response curves. The updated calibration also lends support to the system`s apparent enhanced susceptibility to blooms. The temporal trend estimated by the model results in an upward shift of the load-response curve over time such that a larger load reduction is required to achieve a target bloom size today compared to earlier years. More research is needed to further test the hypothesis of ashift in the lake`s response to stressors over time and, if confirmed, to explore underlying mechanisms.

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“…Macrophytes are able to improve water quality by adsorbing nutrients through their roots, adsorbing microbes and floating matter through their leaves and stems and precipitating suspended particulates [86]. Macrophytes and their roots can be used to stabilize sediment so that it is less likely to be suspended by wind-induced waves and release additional nutrients that can be utilized by phytoplankton [81,86]. Planting of macrophytes is one technique that can be used to help maintain the sediment and keep nutrients from becoming resuspended in the water column.…”

Section: Biological Methodsmentioning

confidence: 99%

Sustainable Management of Eutrophic Lakes and Reservoirs

Wagner¹,

Erickson²

2017

JEP

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Eutrophication of lakes and reservoirs is a major water quality problem that poses significant environmental, economic and social threats around the world. Monitoring and managing lakes and reservoirs to prevent or limit eutrophication, therefore, has significant value. The literature has been reviewed to study ecological engineering and management methods that have been and can be applied to improve water quality. Ecological engineering has the potential to be utilized to improve the design and operation of lakes and reservoirs through monitoring and active management of biological, chemical and physical components. Phosphorus concentrations can be reduced by effective and sustainable management practices to improve water quality.

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Causes, Prevention, and Mitigation Workgroup Report

Cited by 14 publications

References 32 publications

Freshwater harmful algal bloom (FHAB) suppression with solar powered circulation (SPC)

Freshwater harmful algal bloom (FHAB) suppression with solar powered circulation (SPC)

Probabilistically assessing the role of nutrient loading in harmful algal bloom formation in western Lake Erie

Sustainable Management of Eutrophic Lakes and Reservoirs

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