Surface Ocean CO2 Atlas (SOCAT) gridded data products

As a response to public demand for a well-documented, quality controlled, publically available, global surface ocean carbon dioxide (CO2) data set, the international marine carbon science community developed the Surface Ocean CO2 Atlas (SOCAT). The first SOCAT product is a collection of 6.3 million quality controlled surface CO2 data from the global oceans and coastal seas, spanning four decades (1968–2007). The SOCAT gridded data presented here is the second data product to come from the SOCAT project. Recognizing that some groups may have trouble working with millions of measurements, the SOCAT gridded product was generated to provide a robust, regularly spaced CO2 fugacity (fCO2) product with minimal spatial and temporal interpolation, which should be easier to work with for many applications. Gridded SOCAT is rich with information that has not been fully explored yet (e.g., regional differences in the seasonal cycles), but also contains biases and limitations that the user needs to recognize and address (e.g., local influences on values in some coastal regions).

European Project on Ocean Acidification (EPOCA): Objectives, products and scientific highlights

The European Project on Ocean Acidification (EPOCA) is Europe's first large-scale research initiative devoted to studying the impacts and consequences of ocean acidification. More than 100 scientists from 27 institutes and nine countries bring their expertise to the project, resulting in a multidisciplinary and versatile consortium. The project is funded for four years (2008 to 2012) by the European Commission within its Seventh Framework Programme. This article describes EPOCA and explains its different aspects, objectives, and products. Following a general introduction, six boxes highlight outcomes, techniques, and scientific results from each of the project's core themes.

Southern Ocean biogeography and taxonomic resolution: what's in the name?

We examined the taxonomic resolution of zooplankton data required to identify ocean basin scale biogeographic zonation in the Southern Ocean. A 2,154 km transect was completed south of Australia. Sea surface temperature (SST) measured at 1 min intervals showed that seven physical zones were sampled. Zooplankton were collected at a spatial resolution of similar to 9.2 km with a continuous plankton recorder, identified to the highest possible taxonomic resolution and enumerated. Zooplankton assemblage similarity between samples was calculated using the Bray-Curtis index for the taxonomic levels of species, genus, family, order and class after first log(10)(x + 1) (LA) and then presence/absence (PA) transformation of abundance data. Although within and between zone sample similarity increased with decreasing taxonomic resolution, for both data transformations, cluster analysis demonstrated that the biogeographic separation of zones remained at all taxonomic levels when using LA data. ANOSIM confirmed this, detecting significant differences in zooplankton assemblage structure between all seven a priori determined physical zones for all taxonomic levels when using the LA data. In the case of the PA data for the complete data set, and both LA and PA data for a crustacean only data set, no significant differences were detected between zooplankton assemblages in the Polar frontal zone (PFZ) and inter-PFZ at any taxonomic level. Loss of information at resolutions below the species level, particularly in the PA data, prevented the separation of some zones. However, the majority of physical zones were biogeographically distinct from species level to class using both LA and PA transformations. Significant relationships between SST and zooplankton community structure, summarised as NMDS scores, at all taxonomic levels, for both LA and PA transformations, and complete and crustacean only data sets, highlighted the biogeographic relevance of low resolution taxonomic data. The retention of biogeographic information in low taxonomic resolution data shows that data sets collected with different taxonomic resolutions may be meaningfully merged for the post hoc generation of Southern Ocean time series.

On the temporal consistency of chlorophyll products derived from three ocean-colour sensors

Satellite ocean-colour sensors have life spans lasting typically five-to-ten years. Detection of long-term trends in chlorophyll-a concentration (Chl-a) using satellite ocean colour thus requires the combination of different ocean-colour missions with sufficient overlap to allow for cross-calibration. A further requirement is that the different sensors perform at a sufficient standard to capture seasonal and inter-annual fluctuations in ocean colour. For over eight years, the SeaWiFS, MODIS-Aqua and MERIS ocean-colour sensors operated in parallel. In this paper, we evaluate the temporal consistency in the monthly Chl-a time-series and in monthly inter-annual variations in Chl-a among these three sensors over the 2002–2010 time period. By subsampling the monthly Chl-a data from the three sensors consistently, we found that the Chl-a time-series and Chl-a anomalies among sensors were significantly correlated for >90% of the global ocean. These correlations were also relatively insensitive to the choice of three Chl-a algorithms and two atmospheric-correction algorithms. Furthermore, on the subsampled time-series, correlations between Chl-a and time, and correlations between Chl-a and physical variables (sea-surface temperature and sea-surface height) were not significantly different for >92% of the global ocean. The correlations in Chl-a and physical variables observed for all three sensors also reflect previous theories on coupling between physical processes and phytoplankton biomass. The results support the combining of Chl-a data from SeaWiFS, MODIS-Aqua and MERIS sensors, for use in long-term Chl-a trend analysis, and highlight the importance of accounting for differences in spatial sampling among sensors when combining ocean-colour observations.

The CO2 microalgae biorefinery: high value products and biofuels using halophilic microalgae in the “D-Factory”

Fuel-only algal systems are not economically feasible because yields are too low and costs too high for producing microalgal biomass compared to using agricultural residues e.g. straw. Biorefineries which integrate biomass conversion processes and equipment to produce fuels, power and chemicals from biomass, offer a solution. The CO2 microalgae biorefinery (D-Factory) is a 10 million Euro FP7-funded project which will cultivate the microalga Dunaliella in highly saline non-potable waters in photobioreactors and open raceways and apply biorefinery concepts and European innovations in biomass processing technologies to develop a basket of compounds from Dunaliella biomass, including the high value nutraceutical, β-carotene, and glycerol. Glycerol now finds markets both as a green chemical intermediate and as a biofuel in CHP applications as a result of novel combustion technology. Driving down costs by recovering the entire biomass of Dunaliella cells from saline cultivation water poses one of the many challenges for the D-Factory because Dunaliella cells are both motile, and do not possess an external cell wall, making them highly susceptible to cell rupture. Controlling expression of desired metabolic pathways to deliver the desired portfolio of compounds flexibly and sustainably to meet market demand is another. The first prototype D-Factory in Europe will be operational in 48 months, and will serve as a robust manifestation of the business case for global investment in algae biorefineries and in large-scale production of microalgae.