Absorption properties of phytoplankton in the Lower Estuary and Gulf of St. Lawrence (Canada)

Abstract

Models of ocean colour rely on information about phytoplankton absorption, which varies according to community composition and photoacclimation. Here we show that pigment packaging, which is strongly determined by the size structure of local algal populations, represents a dominant factor in the Estuary and Gulf of St. Lawrence, accounting for ~50%–80% of the reduction in phytoplankton absorption at 440 nm during the spring bloom periods and for 24%–48% before and after the blooms. This is consistent with the importance of diatoms in this environment. Comparison between three methods of estimating packaging gave average values within less than 20% of each other during the blooms. Changes in pigment composition, which also affect phytoplankton absorption, were more important outside bloom periods (particularly in the Gulf), although this influence was relatively modest (11%–13%). This was accompanied by an increase in photoprotective pigments and an absorption peak in the ultraviolet range (~330 nm). Regional variations in phytoplankton absorption reflected bloom conditions, whereas detrital particulate material was highest in the upstream Saguenay region (often more than 60% of the absorption of total particulate material at 440 nm (ap(440))) and was at least 20%–30% elsewhere. This information is a first step towards the development of regional models of ocean colour.

Variability of phytoplankton light absorption in Canadian Arctic seas

“…The depth interval for these calculations is 1 m. Interquartile ranges, extents and medians of a ϕ *( λ ) samples were calculated at eight SeaWiFS wavelengths (Figure 3). The outliers (i.e., values that are more than 1.5 times the interquartile range away from the interquartile range itself) that do not correspond to observed values of literature [ Bricaud et al , 1995, 1998; Babin et al , 1996; Allali et al , 1997; Matsuoka et al , 2007; Roy et al , 2008] were removed. The relationships between a ϕ ( λ ) and TChl a were calculated according to the following equation: a ϕ ( λ ) = A ϕ ( λ ) (TChl a ) B ϕ ( λ ) (m −1 ) [ Bricaud et al , 1998], where A ϕ and B ϕ are regression's constants.…”

“…Nowadays, most of the natural variability in the spectral shape of a ϕ *( λ ) between 400 and 700 nm can be explained by the dominant phytoplankton group and cell size [ Ciotti et al , 2002; Bricaud et al , 2004; Roy et al , 2008]. However, small phytoplankton cells photoadapted to low light could experience an important package effect [ Morel , 1991].…”

A Comparison between Local and Global Spaceborne Chlorophyll Indices in the St. Lawrence Estuary

“…With reference to the second factor, nFLH is expected to change in a direct way with respect ΦF and a ph * (Equation (2) in [27]). Previous investigations have shown that the magnitude of a ph * during April-May 2000 and 2001 cruises in the SLE varied between 2.8 and 6.4-fold, respectively [45]. Therefore, in our study area, the impact of this variability for satellite chlorophyll fluorescence should be secondary.…”

Light absorption properties of the New York/New Jersey Harbor Estuary

“…The a NAP for the NY/NJ Harbor Estuary is observed comparable to the global coastal water (Table 1), while the exponential slope of NAP absorption spectra, S NAP , is slightly greater than many coastal waters (Table 1), but comparable to the Lower Estuary and Gulf of St. Lawrence, Canada (0.013 ± 0.002, 0.014 ± 0.002 nm -1 ) (Roy et al, 2008). When the absorption coefficient of NAP at 440 nm, a NAP (440), was plotted as a function of salinity for the entire estuary, the lack of correlation (R 2 = 0.0001, P [ 0.5) between a NAP (440) and salinity might deny the dilution of terrestrial NAP by marine water.…”

“…As such, measuring in situ light absorption properties is one of the requisites to build and refine these models (IOCCG, 2000;Bricaud et al, 2010). In situ absorption measurements have been conducted in many estuaries to better understand the local characteristics of the water (Hu et al, 2004;Sasaki et al, 2005;Gilerson et al, 2007;Roy et al, 2008;Aurin et al, 2010), develop and improve the localized algorithms and models, and finally improve space-based estimates of biomass, CDOM, and NAP (Magnuson et al, 2004;Xie et al, 2012).…”