The potential of high-frequency profiling to assess vertical and seasonal patterns of phytoplankton dynamics in lakes: an extension of the Plankton Ecology Group (PEG) model. Issue 4 (1st January 2016)

• Record Type: Journal Article
• Authors: Brentrup, Jennifer A.; Williamson, Craig E.; Colom-Montero, William; Eckert, Werner; de Eyto, Elvira; Grossart, Hans-Peter; Huot, Yannick; Isles, Peter D. F.; Knoll, Lesley B.; Leach, Taylor H.; McBride, Chris G.; Pierson, Don; Pomati, Francesco; Read, Jordan S.; Rose, Kevin C.; Samal, Nihar R.; Staehr, Peter A.; Winslow, Luke A.
• Is Part Of: Inland waters. Volume 6:Issue 4(2016)
• Page Start: 565
• Page End: 580
• Publication Date: 2016-01-01
• Subjects: chlorophyll fluorescence -- Global Lake Ecological Observatory Network (GLEON) -- high-frequency sensors -- PEG model -- phytoplankton -- profiling buoys -- subsurface chlorophyll maximum; Limnology -- Periodicals; Hydrology -- Periodicals; Aquatic biology -- Periodicals; Lake ecology -- Periodicals; Lakes -- Environmental aspects -- Periodicals; 551.48205
• DOI: 10.5268/IW-6.4.890
• Languages: English
• ISSNs: 2044-2041

Abstract

Abstract: The use of high-frequency sensors on profiling buoys to investigate physical, chemical, and biological processes in lakes is increasing rapidly. Profiling buoys with automated winches and sensors that collect high-frequency chlorophyll fluorescence (ChlF) profiles in 11 lakes in the Global Lake Ecological Observatory Network (GLEON) allowed the study of the vertical and temporal distribution of ChlF, including the formation of subsurface chlorophyll maxima (SSCM). The effectiveness of 3 methods for sampling phytoplankton distributions in lakes, including (1) manual profiles, (2) single-depth buoys, and (3) profiling buoys were assessed. High frequency ChlF surface data and profiles were compared to predictions from the Plankton Ecology Group (PEG) model. The depth-integrated ChlF dynamics measured by the profiling buoy data revealed a greater complexity that neither conventional sampling nor the generalized PEG model captured. Conventional sampling techniques would have missed the SSCM in 7 of 11 study lakes. Although surface-only ChlF data underestimated average water column ChlF, at times by nearly 2-fold in 4 of the lakes, overall there was a remarkable similarity between surface and mean water column data. Contrary to the PEG model's proposed negligible role for physical control of phytoplankton during the growing season, thermal structure and light availability were closely associated with ChlF seasonal depth distribution. Thus, an extension of the PEG model is proposed, with a new conceptual framework that explicitly includes physical metrics to better predict SSCM formation in lakes and highlight when profiling buoys are especially informative.