Abstract
Abstract. Predicting water-column phytoplankton biomass from near-surface measurements is a common approach in biological oceanography, particularly since the advent of satellite remote sensing of ocean color (OC). In the Arctic Ocean, deep subsurface chlorophyll maxima (SCMs) that significantly contribute to primary production (PP) are often observed. These are neither detected by ocean color sensors nor accounted for in the primary production models applied to the Arctic Ocean. Here, we assemble a large database of pan-Arctic observations (i.e., 5206 stations) and develop an empirical model to estimate vertical chlorophyll a (Chl a) according to (1) the shelf–offshore gradient delimited by the 50 m isobath, (2) seasonal variability along pre-bloom, post-bloom, and winter periods, and (3) regional differences across ten sub-Arctic and Arctic seas. Our detailed analysis of the dataset shows that, for the pre-bloom and winter periods, as well as for high surface Chl a concentration (Chl asurf; 0.7–30 mg m−3) throughout the open water period, the Chl a maximum is mainly located at or near the surface. Deep SCMs occur chiefly during the post-bloom period when Chl asurf is low (0–0.5 mg m−3). By applying our empirical model to annual Chl asurf time series, instead of the conventional method assuming vertically homogenous Chl a, we produce novel pan-Arctic PP estimates and associated uncertainties. Our results show that vertical variations in Chl a have a limited impact on annual depth-integrated PP. Small overestimates found when SCMs are shallow (i.e., pre-bloom, post-bloom > 0.7 mg m−3, and the winter period) somehow compensate for the underestimates found when SCMs are deep (i.e., post-bloom < 0.5 mg m−3). SCMs are, however, important seasonal features with a substantial impact on depth-integrated PP estimates, especially when surface nitrate is exhausted in the Arctic Ocean and where highly stratified and oligotrophic conditions prevail.
Highlights
Arctic phytoplankton commuSniotielisdarEe caurrrtehntly exposed to major environmental change (Wassmann et al, 2011; Tremblay et al, 2012)
These empirical relationships at low (i.e., ≤ 0.7 mg m−3; prebloom and winter periods) and high (i.e., > 0.7 mg m−3; all the open period) chlorophyll a (Chl a) concentrations are relatively similar, which could be explained by the same pattern in vertical Chl a distribution (Fig. 5)
Empirical models developed for temperate and tropical oceans have proven to be useful for estimating vertical Chl a profiles and for improving primary production (PP) estimates based on ocean color (OC) (Morel and Berthon, 1989; Uitz et al, 2006; Platt et al, 2008)
Summary
Arctic phytoplankton commuSniotielisdarEe caurrrtehntly exposed to major environmental change (Wassmann et al, 2011; Tremblay et al, 2012). Several in situ studies have highlighted the inability of satellites OC sensors to detect subsurface peaks of phytoplankton biomass, the socalled subsurface chlorophyll maxima (SCMs), and stressed that the contribution of SCM to areal PP in the Arctic Ocean is omitted from PP estimates based on OC remote sensing (Hill et al, 2005; Weston et al, 2005; Martin et al, 2010). The increase in satellite-derived PP is in disagreement with other in situ, experimental, and modeling studies, showing contrasting responses of phytoplankton production and community structure to environmental forcing (Li et al, 2009; Cai et al, 2011; Wassmann and Reigstad, 2011). At the pan-Arctic scale, these studies reveal that the importance of the SCM in annual PP estimates is still a subject of discussion
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