Coccolithophore calcification is independent of carbonate chemistry in the tropical ocean

Marañón, Emilio ... et al.-- 13 pages, 7 figures, 1 table, supporting information https://dx.doi.org/10.1002/lno.10295Short-term experiments indicate that seawater acidification can cause a decrease in the rate of calcification by coccolithophores, but the relationship between carbonate chemistry and coccolithophore calcification rate in natural assemblages is still unclear. During the Malaspina 2010 circumnavigation, we measured primary production, calcification, coccolithophore abundance, particulate inorganic carbon (PIC) concentration, and the parameters of the carbonate system, along basin-scale transects in the tropical Atlantic, Indian and Pacific oceans. Euphotic layer-integrated calcification and mean cell-specific calcification in the euphotic layer ranged between 2–10 mgC m−2 d−1 and 5–20 pgC cell−1 d−1, respectively. We found a significant relationship between primary production and calcification, such that the calcification to primary production (CP/PP) ratio was relatively invariant among ocean basins, with an overall mean value of 0.05 ± 0.04. Extrapolating this value to the entire ocean would result in a global pelagic calcification rate of 2.4 PtC yr−1. The mean PIC concentration in surface waters was 1.8 ± 1.6 mgC m−3 and its turnover time averaged 20 d. We combined our data of calcification, primary production, and carbonate chemistry from Malaspina 2010 with those obtained during two previous cruises in the northern Arabian Sea. Both the CP/PP ratio and cell-specific calcification were largely constant across a wide range of calcite saturation state (1.5–6.5), [ inline image]/[H+] (0.08–0.24; mol: μmol), and pH (7.6–8.1), which indicates that calcification by natural coccolithophore assemblages was independent of carbonate chemistry. Our results suggest that coccolithophore calcification, at least in tropical regions, may not be decreasing in the currently acidifying oceanFunding for this study was provided by the Spanish Ministry of Science and Innovation through research projects Malaspina 2010 (grant no. CSD2008-00077), PERSEO (CTM2007-28925-E/MAR), MANIFEST (CTM2012-32017) and TERRIFIC (CTM2014-53582-R). Funding for W.M.B. came from the NSF (OCE-0961660; OCE1220068), NASA (NNX11AO72G; NNX11AL93G; NNX14AQ41G; NNX14AQ43A; NNX14AL92G; NNX14AM77G) and NOAA (NA11OAR4310055).Peer Reviewe

Multi-model remote sensing assessment of primary production in the subtropical gyres

The subtropical gyres occupy about 70% of the ocean surface. While primary production (PP) within these oligotrophic regions is relatively low, their extension makes their total contribution to ocean productivity significant. Monitoring marine pelagic primary production across broad spatial scales, particularly across the subtropical gyre regions, is challenging but essential to evaluate the oceanic carbon budget. PP in the ocean can be derived from remote sensing however in situ depth-integrated PP (IPPis) measurements required for validation are scarce from the subtropical gyres. In this study, we collected >120 IPPis measurements from both northern and southern subtropical gyres that we compared to commonly used primary productivity models (the Vertically Generalized Production Model, VGPM and six variants; the Eppley-Square-Root model, ESQRT; the Howard–Yoder–Ryan model, HYR; the model of MARRA, MARRA; and the Carbon-based Production Model, CbPM) to predict remote PP (PPr) in the subtropical regions and explored possibilities for improving PP prediction. Our results showed that satellite-derived PP (IPPsat) estimates obtained from the VGPM1, MARRA and ESQRT provided closer values to the IPPis (i.e., the difference between the mean of the IPPsat and IPPis was closer to 0; |Bias| ~ 0.09). Model performance varied due to differences in satellite predictions of in situ parameters such as chlorophyll a (chl-a) concentration or the optimal assimilation efficiency of the productivity profile (PBopt) in the subtropical region. In general, model performance was better for areas showing higher IPPis, highlighting the challenge of PP prediction in the most oligotrophic areas (i.e. PP < 300 mg C m−2 d−1). The use of in situ chl-a data, and PBopt as a function of sea surface temperature (SST) and the mixed layer depth (MLD) from gliders and floats in PPr models would improve their IPP predictions considerably in oligotrophic oceanic regions such as the subtropical gyres where MLD is relatively low (<60 m) and cloudiness may bias satellite input data