EXECUTIVE SUMMARYCoastal environments are an important component of the global carbon cycle, and probably more vulnerable than the open ocean to anthropogenic forcings. Due to strong spatial heterogeneity and temporal variability, carbon flows in coastal environments are poorly constrained. Hence, an integrated, international, and interdisciplinary program of ship-based hydrography, Voluntary Observing Ship (VOS) lines, time-series moorings, floats, gliders, and autonomous surface vessels with sensors for pCO 2 and ancillary variables are recommended to better understand present day carbon cycle dynamics, quantify air-sea CO 2 fluxes, and determine future long-term trends of CO 2 in response to global change forcings (changes in river inputs, in the hydrological cycle, in circulation, sea-ice retreat, expanding oxygen minimum zones, ocean acidification, …) in the coastal oceans. Integration at the international level is also required for data archiving, management, and synthesis that will require multi-scale approaches including the development of biogeochemical models and use of remotely sensed parameters. The total cost of these observational efforts is estimated at about 50 million US dollars per year.
Article history:Available online xxxx a b s t r a c tHere we present more than 21,000 observations of carbon dioxide fugacity in air and seawater (fCO 2 ) along the Atlantic Meridional Transect (AMT) programme for the period 1995-2013. Our dataset consists of 11 southbound and 2 northbound cruises in boreal autumn and spring respectively. Our paper is primarily focused on change in the surface-ocean carbonate system during southbound cruises. We used observed fCO 2 and total alkalinity (TA), derived from salinity and temperature, to estimate dissolved inorganic carbon (DIC) and pH (total scale). Using this approach, estimated pH was consistent with spectrophotometric measurements carried out on 3 of our cruises. The AMT cruises transect a range of biogeographic provinces where surface Chlorophyll-a spans two orders of magnitude (mesotrophic high latitudes to oligotrophic subtropical gyres). We found that surface Chlorophyll-a was negatively correlated with fCO 2 , but that the deep chlorophyll maximum was not a controlling variable for fCO 2 . Our data show clear evidence of ocean acidification across 100°of latitude in the Atlantic Ocean. Over the period 1995-2013 we estimated annual rates of change in: (a) sea surface temperature of 0.01 ± 0.05°C, (b) seawater fCO 2 of 1.44 ± 0.84 latm, (c) DIC of 0.87 ± 1.02 lmol per kg and (d) pH of À0.0013 ± 0.0009 units.Monte Carlo simulations propagating the respective analytical uncertainties showed that the latter were < 5% of the observed trends. Seawater fCO 2 increased at the same rate as atmospheric CO 2 .
[1] The concept of ocean biogeochemical provinces is based on the observation that large ocean regions are characterized by coherent physical forcing and environmental conditions, which are eventually representative of macroscale ocean ecosystems. Biogeochemical models of the global ocean focus on simulating the coupling between prevalent physical conditions and the biogeochemical processes with the assumption that biological properties respond coherently to physics and therefore should produce such provinces as an emergent property. In this paper, we quantitatively assess the emergence of a reference set of predefined biogeochemical provinces in the available global data sets and propose a province-based approach to the evaluation of one of the most comprehensive models of ocean biogeochemistry. Multivariate statistical tools were applied to model and observation data, verifying the existence, distinctiveness and reliability of the predefined provinces and quantifying the correlation of model results with observations at the global scale. The analysis of similarity between provinces shows that they are statistically separable in data and model output and therefore can be used as reliable metrics. The analyses indicate that provinces can be more easily distinguished in terms of their environmental features rather than using chlorophyll concentration. The characterization of provinces by means of chlorophyll values shows a significant overlap in both the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) data and the model. It is likely this is related to the choice of province boundaries based on coarse-resolution mapped data, which are not necessarily the same as those derivable from high-resolution satellite data. We also demonstrated through cluster analysis that the long-term time series data collected at Joint Global Ocean Flux Study (JGOFS) stations are representative of environmental conditions of the respective province and can thus be used to evaluate model results extracted from that province. The method shows promise for helping to overcome problems with model verification due to under sampling of most ocean biogeochemical variables but also gives indications that unsupervised clustering may be required when more spatially resolved data and models are available.Citation: Vichi, M., J. I. Allen, S. Masina, and N. J. Hardman-Mountford (2011), The emergence of ocean biogeochemical provinces: A quantitative assessment and a diagnostic for model evaluation, Global Biogeochem. Cycles, 25, GB2005,
Hardman-Mountford, N. J., Moore, G., Bakker, D. C. E., Watson, A. J., Schuster, U., Barciela, R., Hines, A., Moncoiffé, G., Brown, J., Dye, S., Blackford, J., Somerfield, P. J., Holt, J., Hydes, D. J., and Aiken, J. 2008. An operational monitoring system to provide indicators of CO2-related variables in the ocean. – ICES Journal of Marine Science, 65: 1498–1503. Demand by governments and scientists is increasing for indicators of CO2-related variables for the ocean. We describe a recent project, CARBON-OPS, during which a “supply chain” was developed for automated measurement of pCO2 in the surface of the ocean, data processing, and its use in providing information for research and policy development. Data are gathered by new pCO2 measurement systems on five UK research ships in the Southern Ocean, Atlantic Ocean, and northwestern European shelf seas. These send data in near-real-time, via satellite communication systems, to the British Oceanographic Data Centre, where they are automatically processed, quality controlled, and archived. The data are then delivered to the UK Met Office and others for use in testing predictions from operational ocean models. These models will generate indicator products and assist government through the Marine Climate Change Impact Partnership, a partnership of scientists, government, its agencies, and NGOs, by providing information on ocean CO2 uptake, changes in ocean pH, and potential impacts on global climate and marine ecosystems.
Error-quantified, synoptic-scale relationships between chlorophyll-a (Chla) and phytoplankton pigment groups at the sea surface are presented. A total of nine pigment groups were considered to represent nine phytoplankton functional types (PFTs) including microplankton, nanoplankton, picoplankton, diatoms, dinoflagellates, green algae, picoeukaryotes, prokaryotes and Prochlorococcus sp. The observed relationships between Chla and pigment groups were well-defined at the global scale to show that Chla can be used as an index of not only phytoplankton abundance but also community structure; large (micro) phytoplankton monotonically increase as Chla increases, whereas the small (pico) phytoplankton community generally decreases. Within these relationships, we also found non-monotonic variations with Chla for certain pico-plankton (pico-eukaryotes, Prokaryotes and Prochlorococcus sp.) and for Green Algae and nano-sized phytoplankton. The relationships were quantified with a least-square fitting approach in order to estimate the PFTs from Chla alone. The estimated uncertainty of the relationships quantified depends on both phytoplankton types and Chla concentration. Maximum uncertainty over all groups (34.7% Chla) was found from diatom at approximately Chla = 1.07 mg m−3. However, the mean uncertainty of the relationships over all groups was 5.8 [% Chla] over the entire Chla range observed (0.02 < Chla < 6.84 mg m−3). The relationships were applied to SeaWiFS satellite Chla data from 1998 to 2009 to show the global climatological fields of the surface distribution of PFTs. Results show that microplankton are present in the mid and high latitudes, constituting ~9.0 [% Chla] of the phytoplankton community at the global surface, in which diatoms explain ~6.0 [% Chla]. Nanoplankton are ubiquious throught much of the global surface oceans except subtropical gyres, acting as a background population, constituting ~44.2 [% Chla]. Picoplankton are mostly limited in subtropical gyres, constituting ~46.8 [% Chla] globally, in which prokaryotes are the major species explaining 32.3 [% Chla] (prochlorococcus sp. explaining 21.5 [% Chla]), while pico-eukaryotes are notably abundant in the Southern Pacific explaining ~14.5 [% Chla]. These results may be used to constrain or validate global marine ecosystem models
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