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Assessing the Variability of Phytoplankton Assemblages in Old Woman Creek, Ohio

Bonini, Nick
http://rave.ohiolink.edu/etdc/view?acc_num=kent1469959717

Abstract Details

2016, PHD, Kent State University, College of Arts and Sciences / Department of Earth Sciences.
Various techniques for assessing, monitoring, and predicting algal blooms in an estuarine ecosystem are analyzed. In one section, routine water samples are collected at previously established monitoring sites in Old Woman Creek, filtered onto a 47 mm, 0.7 µm glass-fiber filter (GF/F), and then measured using a visible/near-infrared spectrophotometer. Varimax-rotated principal component analysis (VPCA) is applied to reflectance data and then used to quantify and identify pigments, phytoplankton taxa, and sediments by comparing the measured spectral signatures to known standards. Common assemblages that are reported throughout the three-year study include: bacillariophyceae (diatoms), chlorophyta (green algae), cyanobacteria (blue-green algae), and illite. A similar approach is taken in the next section by applying multivariate statistics to Landsat 8 satellite imagery in order to determine the distribution of in-water constituents at a high spatial resolution. Only four bands in the visible range are available for this analysis, but it is possible to identify several of the same groups of algae and sediments, providing a useful complement to the hyperspectral work. Finally, a bloom prediction model based on springtime discharge is created by applying VPCA to in-water sonde data from one of the monitoring sites at Old Woman Creek during a recent 11-year time period. In this model, a proxy for net community production (NCP) is determined using oxygen and pH dynamics and then compared to daily rates of streamflow. Possible monthly sequences between January and June are considered in order to determine which timeframe is the best indicator of the average annual NCP. Time of day (daytime versus nighttime) and mouth bar conditions (barrier beach present versus absent) are important factors in determining production in the estuary. Based on the results, the best predictor for NCP is stream discharge from March through May, which produces correlations that are significant at even the 1% level. A positive relationship is found between NCP and discharge when flow from Old Woman Creek into Lake Erie is permitted. When flow is blocked by the barrier beach, however, the relationship is reversed.
Joseph Ortiz (Advisor)
Anne Jefferson (Committee Member)
Alison Smith (Committee Member)
Darren Bade (Committee Member)
192 p.
Aquatic Sciences; Biological Oceanography; Environmental Geology; Environmental Science; Geology; Limnology; Water Resource Management
Old Woman Creek; Lake Erie; algal blooms; phytoplankton; water quality; estuary; barrier beach; VNIR derivative spectroscopy; VPCA; principal component analysis; remote sensing; prediction model; net community production; streamflow

Recommended Citations

Citations

  • Bonini, N. (2016). Assessing the Variability of Phytoplankton Assemblages in Old Woman Creek, Ohio [Doctoral dissertation, Kent State University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=kent1469959717

    APA Style (7th edition)

  • Bonini, Nick. Assessing the Variability of Phytoplankton Assemblages in Old Woman Creek, Ohio. 2016. Kent State University, Doctoral dissertation. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=kent1469959717.

    MLA Style (8th edition)

  • Bonini, Nick. "Assessing the Variability of Phytoplankton Assemblages in Old Woman Creek, Ohio." Doctoral dissertation, Kent State University, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=kent1469959717

    Chicago Manual of Style (17th edition)

kent1469959717
609
© 2016, all rights reserved.
This open access ETD is published by Kent State University and OhioLINK.