Spatial-temporal variability of in situ cyanobacteria vertical structure in Western Lake Erie: Implications for remote sensing observations

Details

• Journal Title:
  Journal of Great Lakes Research
• Personal Author:
  Bosse, Karl R. ; Sayers, Michael J. ; Shuchman, Robert A. ; Fahnenstiel, Gary L. ; Ruberg, Steven A. ; Fanslow, David L. ; Stuart, Dack G. ; Johengen, Thomas H. ; Burtner, Ashley M.
• NOAA Program & Office:
  OAR (Oceanic and Atmospheric Research) ; CIGLR (Cooperative Institute for Great Lakes Research) ; GLERL (Great Lakes Environmental Research Laboratory)
• Description:
  Remote sensing has provided expanded temporal and spatial range to the study of harmful algal blooms (cyanoHABs) in western Lake Erie, allowing for a greater understanding of bloom dynamics than is possible through in situ sampling. However, satellites are limited in their ability to specifically target cyanobacteria and can only observe the water within the first optical depth. This limits the ability of remote sensing to make conclusions about full water column cyanoHAB biomass if cyanobacteria are vertically stratified. FluoroProbe data were collected at nine stations across western Lake Erie in 2015 and 2016 and analyzed to characterize spatiotemporal variability in cyanobacteria vertical structure. Cyanobacteria were generally homogenously distributed during the growing season except under certain conditions. As water depth increased and high surface layer concentrations were observed, cyanobacteria were found to be more vertically stratified and the assumption of homogeneity was less supported. Cyanobacteria vertical distribution was related to wind speed and wave height, with increased stratification at low wind speeds (<4.9 m/s) and wave heights (<027 m). Once wind speed and wave height exceeded these thresholds the assumption of vertically uniform cyanobacteria populations was justified. These findings suggest that remote sensing can provide adequate estimates of water column cyanoHAB biomass in most conditions; however, the incorporation of bathymetry and environmental conditions could lead to improved biomass estimates. Additionally, cyanobacteria contributions to total chlorophyll-a were shown to change throughout the season and across depth, suggesting the need for remote sensing algorithms to specifically identify cyanobacteria. (C) 2019 The Authors. Published by Elsevier B.V. on behalf of International Association for Great Lakes Research.
• Source:
  Journal of Great Lakes Research, 45(3), 480-489.
• DOI:
  https://doi.org/10.1016/j.jglr.2019.02.003
• Document Type:
  Journal Article
• Rights Information:
  CC BY
• Compliance:
  Submitted
• Download URL:
  https://repository.library.noaa.gov/view/noaa/22099/noaa_22099_DS1.pdf
• File Type:
  [PDF - 1.34 MB]
• Collection(s):
  Office of Oceanic and Atmospheric Research (OAR) ; NOAA Cooperative Institutes
• Main Document Checksum:
  urn:sha-512:62ca2f07b18c25ac7244a6f8d2405f45d0ce3fadefa9212978ee94e45167f4699b230203ea11a82adc34908479e94a4a2e08bc76308db67cf5a89b9480469c62