Characterizing the Impact of Cyanobacterial Blooms on the Photoreactivity of Surface Waters from New York Lakes: A Combined Statewide Survey and Laboratory Investigation

Article

Author: Wasswa, Joseph ; Matthews, David A ; Perkins, MaryGail ; Zeng, Teng

Cyanobacterial blooms introduce autochthonous dissolved organic matter (DOM) into aquatic environments, but their impact on surface water photoreactivity has not been investigated through collaborative field sampling with comparative laboratory assessments. In this work, we quantified the apparent quantum yields (Φ_app,RI) of reactive intermediates (RIs), including excited triplet states of dissolved organic matter (³DOM*), singlet oxygen (¹O₂), and hydroxyl radicals (^•OH), for whole water samples collected by citizen volunteers from more than 100 New York lakes. Multiple comparisons tests and orthogonal partial least-squares analysis identified the level of cyanobacterial chlorophyll a as a key factor in explaining the enhanced photoreactivity of whole water samples sourced from bloom-impacted lakes. Laboratory recultivation of bloom samples in bloom-free lake water demonstrated that apparent increases in Φ_app,RI during cyanobacterial growth were likely driven by the production of photoreactive moieties through the heterotrophic transformation of freshly produced labile bloom exudates. Cyanobacterial proliferation also altered the energy distribution of ³DOM* and contributed to the accelerated transformation of protriptyline, a model organic micropollutant susceptible to photosensitized reactions, under simulated sunlight conditions. Overall, our study provides insights into the relationship between the photoreactivity of surface waters and the limnological characteristics and trophic state of lakes and highlights the relevance of cyanobacterial abundance in predicting the photoreactivity of bloom-impacted surface waters.

01 Aug 2017·Journal of Paleolimnology

Pairing paleolimnological inference models with mechanistic water column models enhances assessment of lake water quality

Author: Charles T. Driscoll ; Donald F. Charles ; Jay A. Bloomfield ; Steven W. Effler ; H. Chandler Rowell

Reconciliation of paleolimnology inference models with hindcasts from mechanistic water column models aided the reconstruction of past relationships for total phosphorus/dissolved oxygen and acid neutralizing capacity/pH in highly polluted lake ecosystems in New York State. Pre-disturbance Onondaga Lake, Syracuse, NY, was shown to have experienced seasonal hypolimnetic anoxia even under oligotrophic (<10 ug l−1) phosphorus levels. In the Adirondack Mountains of New York State the paired modeling confirmed that, while many lakes have the potential to eventually recover from acidification by atmospheric deposition, approximately 30% likely experienced naturally acidic conditions (pH < 6) prior to increases in industrial emissions. Comparison between the model results illuminated areas of individual model inadequacy, improved understanding of lake ecology, and increased confidence in the ability of predictive water column models to accurately develop restoration scenarios representing improved conditions. The work presented here is the first such comparison modeling for total phosphorus, dissolved oxygen, and acid neutralizing capacity. The technique remains to be more widely applied geographically and extended to less heavily stressed lake systems. Because a fossil inference and mechanistic hindcast should independently lead to similar results, comparison modeling is a potentially powerful tool for examining past interactions between ecosystem structure and ecosystem functioning.

01 Apr 2017·Water, Air, & Soil Pollution

A Mechanistic Model for Secchi Disk Depth, Driven by Light Scattering Constituents

Author: MaryGail Perkins ; Feng Peng ; Steven W. Effler ; Steve C. Chapra ; Adam J.P. Effler ; David M. O’Donnell ; Anthony R. Prestigiacomo ; Christopher Strait ; Susan M. O’Donnell

An optics theory-based mechanistic model for Secchi disk depth (Z_SD) is advanced, tested, and applied for Cayuga Lake, NY.Robust data sets supported the initiative, including for (1) Z_SD, (2) multiple light attenuation metrics, most importantly the beam attenuation (c) and particulate scattering (b_p) coefficients, and (3) measures of constituents responsible for contributions to b_p by phytoplankton (b_o) and minerogenic particles (b_m).The model features two serially connected links.The first link supports predictions of b_p from those for b_o and b_m.The second link provides predictions of Z_SD based on those for b_p, utilizing an earlier optical theory radiative transfer equation.Recent advancements in mechanistically strong estimates of b_m, empirical estimates of b_o, and more widely available bulk measurements of c and b_p have enabled a transformation from a theory-based conceptual to this implementable Z_SD model for lacustrine waters.The successfully tested model was applied to quantify the contributions of phytoplankton biomass, and minerogenic particle groups, such as terrigenous clay minerals and autochthonously produced calcite, to recent b_p and Z_SD levels and dynamics.Moreover, it has utility for integration as a submodel into larger water quality models to upgrade their predictive capabilities for Z_SD.

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