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Oceanography | Vol. 38, No. 2

78

fluorometers, we will focus here only on the discrete under­

way Chl-a data. Before collection, the date and time of sam­

pling were recorded along with the current fluorometer read­

ings. Fifteen to 20 samples were collected on a random timeline

during the cruise, while ensuring collection of half the samples

during the day and about half during the night, to capture the

effects of nonphotochemical quenching (Marra, 1998; Holm-

Hansen et al., 2000). Additional effort was devoted to maximiz­

ing the dynamic range of fluorescence and corresponding Chl-a

concentrations, based on real-time observations of the under­

way fluorescence signals (e.g., during periods of unusually low

or high fluorescence). A collection container with a volume

between 500 mL and 1 L was rinsed three times with underway

water, then filled. Three plastic 152 mL bottles were then filled to

the top with the underway water in triplicates. Immediately after

collection, the entire volume of each triplicate was filtered onto

Whatman GF/F 25 mm filters using gentle vacuum (not exceed­

ing 150 mm Hg) in a light-limited environment to avoid any

degradation of the Chl-a pigments. The filters were then each

placed in glass tubes containing 6 mL of 95% ethanol, capped,

and stored in the dark at room temperature to extract the Chl-a

for approximately 12 hours (±2 hours). After the extraction

period, the fluorescence of the samples was recorded with a

Turner 10AU fluorometer first as is, and then with the addition

of acid to correct for phaeopigments (Wasmund et al., 2006).

The discrete underway sample data were digitized and orga­

nized, then Chl-a concentration, in mg m–3 (= μg L–1), was cal­

culated using coefficients obtained from the in-lab fluorometer’s

calibration; this was performed before each cruise based on pure

Chl-a standards (Sigma-Aldrich, from Anacystis nidulans algae).

Each data point was then given a quality flag based on the IODE

(International Oceanographic Data and Information Exchange)

quality flag scheme (IOC, 2013) so that only the highest quality

data would be included in the post-calibration. Discrete under­

way Chl-a data from six NES-LTER cruises are available on the

EDI data portal (Menden-Deuer et al., 2022).

SECTION 2. USING DISCRETE CHL-a TO

POST-CALIBRATE SENSOR-BASED FLUORESCENCE

(1.5 hours)

There can be substantial differences between manufacturer-​

calibrated continuous fluorescence data and discrete Chl-a con­

centrations. Manufacturer-calibrated fluorescence values con­

verted to Chl-a concentrations (mg m–³) should be interpreted

with caution because the calibration is typically performed

using either pure Chl-a extracts or single-species phytoplank­

ton cultures that may not accurately reflect the local phyto­

plankton community, environmental conditions (e.g., tempera­

ture), or optical properties encountered in the field. Factors

such as species composition, physiological state, light his­

tory, and colored dissolved organic matter (CDOM) can all

influence the fluorescence signal independent of actual Chl-a

concentration. The optical components of the fluorescence sen­

sor may also be biofouled during deployment. Although this

is minimized by cleaning the sensors before and after each

deployment and by maintaining a high flow rate, any biofoul­

ing can still alter the recorded optical signal. As a result, with­

out cross-validation, these manufacturer-derived values can be

substantially different from in situ Chl-a. Therefore, it is crucial

to acknowledge, correct for, and interpret the uncertainty and

imprecision in in vivo fluorescence data to interpret the fluo­

rescence signal (Cullen, 1982; Falkowski and Kiefer, 1985; Xing

et al., 2017). To obtain reliable, accurate, high-resolution Chl-a

data from in vivo fluorescence, the continuous fluorometer data

must undergo post-​calibration against discrete Chl-a values.

The steps required for this data management are the subject of

this hands-on exercise.

PART 1. PLOTTING SENSOR-BASED CHL-a FLUORESCENCE

VS. EXTRACTED CHL-A CONCENTRATIONS

Goals. Linking sensor-based underway chlorophyll-a (Chl-a)

fluorescence and discrete Chl-a data. Introduce methods required

for post-calibrating sensor-based Chl-a fluorescence data.

Expected Outcomes. Develop familiarity with linear regres­

sion, including the concepts of slope, intercept, and coefficient

of determination. Understand the significance of linear regres­

sion results and their application in post-calibrating underway

Chl-a fluorescence data.

Narrative. It is now time to compare the discrete Chl-a concen­

trations with the corresponding underway fluorescence values

observed when sampling (Figures 3 and 4). The goal here is to

identify whether both fluorometers are equally well suited to use

for the post-calibration and to identify the coefficients that will

FIGURE 3. Raw underway fluorescence (mg Chl-a m–3) during the EN661

NES-LTER transect cruise (February 3 to February 7, 2021, winter in the

Northern Hemisphere) from the WetStar (dark green) and the ECO-Fl (light

green) fluorometers. The discrete Chl-a concentrations collected in tripli­

cate during the cruise are represented by black dots. Only discrete Chl-a

data with an IODE Quality Flag = 1 (good) are shown. Note the change in

fluorescence from the WetStar fluorometers on 02/05/2021, which cor­

responds to the change observed after the cleaning of the instruments.

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