Sources of Variability in the Column Photosynthetic Cross Section for Antarctic Coastal Waters

Using a highly resolved Long Term Ecological Research (LTER) database collected near Palmer Station, Antarctica, from 1991 to 1994, the variability in the column photosynthetic cross section (ψ*, m 2 g Chl a ) was analyzed. The relationship between the daily integrated primary production rates versus the product of surface irradiance (QPAR(0*)) and the integrated chlorophyll content (down to 0.1% QPAR(0*)) gave a ψ* value of 0.0695 m 2 g Chl a -1 (r = 0.85, p <0.001, n= 151) which is similar to those determined for temperate and tropical seas. However, the average value of single ψ* estimates is higher (0.109 ± 0.075 m 2 g Chl a ) with extreme values extending over a fiftyfold range (0.009-0.488 m 2 g Chl a ). The possible drivers of this variability are analyzed in detail, considering variables which are presently used in biooptical models (e.g., surface irradiance and chlorophyll content) and those which are not (taxonomic composition). A sixfold variation in ψ* was observed with time of year and strongly associated with the high seasonality in incident irradiance characteristic of these polar sampling sites. Variability in daily incident irradiance as influenced by cloudiness and variation in chlorophyll content were responsible for an additional twofold variation in ψ*. Finally, the taxonomic dependency of ψ* was demonstrated for the first time. For identical chlorophyll content and surface irradiance, mean ψ* values of 0.114 ± 0.051 m 2 g Chl a were recorded for diatom blooms and 0.053 ± 0.011 m 2 g Chl a for cryptophyte-dominated populations. Results illustrate the validity of ψ* -based approaches for estimating primary production for the Southern Ocean but emphasize the need to address taxonspecific photophysiology to better estimate primary production on smaller spatio-temporal scales. Introduction Today, attempts to estimate primary production from space utilize algorithms which incorporate phytoplankton photophysiology [Lewis, 1992]. These algorithms are generally based upon a mechanistic understanding of the photosynthesis-irradiance (P-I) relationship [Morel, 1991; Bidigare et al,1992]. However, first attempts to derive primary production rates from variables which are determinable by remote sensing, namely surface irradiance and chlorophyll content, have relied on empirical relationships [e.g., Morel, 1978]. Falkowski [1981] postulated that daily integrated rates of primary production could be modeled as a direct function of the product of surface irradiance QPAR(0*)) (mol quanta m d) and an estimate of areal chlorophyll a (g Chl a ), through an efficiency factor called the column light utilization index ψ (g C (g Chl a) m (mol quanta) ) (see Table 1 for notation) :ψ= ρ/ QPAR(0*)(Chl) By expressing surface irradiance and primary production in energy equivalent, Morel [1978, 1991] proposed a similar index, ψ* (m 2 g Chl a ), the column photosynthetic cross section: ψ* = 39P/ QPAR(0*)(Chl) where the constant value of 39 corresponds to the kilojoules of chemical energy stored by the photosynthetic fixation of 1 g C and QPAR(0*) is expressed as energy (kJ m d). The conversion from ψ to ψ* is achieved with a nondimensionless conversion factor, such that ψ= 6.174 ψ* [Morel, 1991]. Morel [1978] and Piatt [1986] reviewed various trophic situations in temperate and tropical oceans and observed that ψ* varies by ± 50 % (at 1 standard deviation) around a central value of 0.07 m 2 g Chl a . Such an a priori consistency and stability for this biogeochemical index are of great hope in view of mapping primary production at a global scale. Recently, Prasad et al. [1995] estimated similar values for coastal waters of the Gulf of Mexico and Claustre and Marty [1995] have found comparable results for the tropical North Atlantic. However, higher and more variable values for ψ* were reported by Campbell and O'Reilly [1988] for the northwest Atlantic continental shelf, by Siegel et al. [1995] for the Bermuda Atlantic Time-Series study (BATS) and by Balch and Byrne [1994] for an analysis at a global scale. While experimental or analytical differences may explain the discrepancies in different estimates of ψ* [Campbell and O'Reilly,1988; Siegel et al., 1995], it is equally possible that systematic variations in ψ* do occur in nature. Understanding these sources of variability will lead to future development of more accurate remote-sensing algorithms. Morel [1991], using a modeling approach, addressed potential sources of variability in ψ* by documenting the effect of incident irradiance changes (mostly driven by latitude, seasonality, and cloudiness) as well as the effect of chlorophyll a variations (driven by trophic conditions). Table 1. List of Symbols Symbol Definition Units ā * Mean, reconstructed specific absportion coefficient m 2 g Chl a -1 ā * ACT Same as ā *, but for photosynthetic (active) pigments only m 2 g Chl a -1 α Mean, Chl-normalized α (z) (mg C mg a b)(μmol quanta m s) -1 Chl (z) Chlorophyll a concentration at depth z mg Chl a m Chl * Mean Chl concentration mg Chl a m Integrated Chl concentration mg Chl a m P* Integrated daily primary production rates g C m d -1 *P* Integrated daily primary production rates performed at g C m d -1 light saturation PMAX(z) Maximum photosynthetic rate at depth z mg C m h α (z) Slope of the photosynthesis-light curve at depth z (mg C m h ) (μmol quanta m s) -1 PMAX * Mean, Chl-normalized PMAX(z) mg C mg Chl a -1 h QPAR(z) Photosynthetic available radiation at depth z μmol quanta m s QPAR(0) photosynthetic available radiation at the sea surface μmol quanta m s Ze Depth of 1% isolume (euphotic zone) m Zt Depth of the 0.1% isolume m Φ ** Mean time-averaged quantum yield dimensionless Ψ Column light utilization index g C (g Chl a ) m 2 (mol quanta) -1 Ψ* Column photosynthetic cross section m 2 g Chl a -3 *Unless explicitly specified in the text, the integrated or mean quantities refer to the layer between surface and Zt. The variations in these input variables account for part of the variability of ψ* recorded in the field studies, with the remainder of this variability likely resulting from biological sources, namely from the photophysiological parameters typical of the algal assemblages [Morel et al.,1996]. Reconciling empirical estimates of primary production with a mechanistic understanding of phytoplankton photophysiology has been the focus of many studies [e.g., Piatt, 1986; Campbell and O'Reilly, 1988]. In particular, the biooptical model of Morel [1991] explicitly combines the P-I formulation and phytoplankton absorption properties to quantify ψ*. Using some simplifications, essentially ψ * can be expressed as