Abstract

The in vivo fluorescence of chlorophyll-a is commonly used as a proxy for phytoplankton biomass. Measurement of in vivo fluorescence in the field is attractive because it can be made at high spatial temporal, and vertical resolution relative to discrete sampling and pigment extraction. Fluorometers installed on ships of opportunity provide a cost-effective alternative to many of the traditional sampling methods. However, fluorescence-based estimates of chlorophyll-a can be impacted by sensor calibration and biofouling, variations in phytoplankton taxonomy and physiology (such as non-photochemical quenching) and the influence of other fluorescing matters in the water. Several methods have been proposed to address these issues separately, but few studies have addressed the interaction of multiple sources of error in the in vivo Chl-a fluorescence signal. Here, we demonstrate a method to improve the accuracy of chlorophyll-a concentration retrieved from a coastal ferry system, operating in a dynamic estuarine system. First, we used HPLC chlorophyll-a measurements acquired in low-light conditions to correct sensor level bias. Next, we tested three methods to correct the effect of non-photochemical quenching and evaluated the accuracy of each method using HPLC. As our study area is in highly dynamic coastal waters, we also evaluated the accuracy of our correction procedure across a range of irradiance and biogeochemical conditions. We found that sensor bias accounted for a significant portion of error in the fluorescence signal. The NPQ correction developed by Davis et al. (2008) best improved correspondence between in vivo Chl-a fluorescence and HPLC-based measurement of extracted Chl-a. We suggest the use of this correction for in vivo Chl-a measurements along with pre-processing steps to correct potential sensor biofouling and bias.

Highlights

  • The biomass and distribution of phytoplankton in the ocean can vary at fine spatial and temporal scales due to interactions between physical and biological processes (Margalef, 1997; McCarthy, 2002; Cloern and Jassby, 2008)

  • Halverson and Pawlowicz (2013) corrected fluorescence derived Chl-a concentration obtained by a similar ferry system in the Strait of Georgia for the effect of non-photochemical quenching (NPQ) using a function originally derived by Cullen and Lewis (1995)

  • (3) Correct potential sensor bias by comparing HPLC to fluorescence based estimates of Chl-a acquired in low-irradiance conditions

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Summary

Introduction

The biomass and distribution of phytoplankton in the ocean can vary at fine spatial and temporal scales due to interactions between physical and biological processes (Margalef, 1997; McCarthy, 2002; Cloern and Jassby, 2008). Monitoring phytoplankton at an appr opriate scale is important given its foundational role within aquatic ecosystems and biogeochemical cycles (Falkowski et al, 1998). Chlorophyll-a (Chl-a) is commonly used as a proxy for phytoplankton biomass (Lorenzen, 1966; Kiefer, 1973; Cullen, 1982), and monitoring programs typically rely on deriving Chl-a concentration from discrete water samples (Lorenzen, 1967; Welshmeyer, 1994; Hooker et al, 2010)

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