From the abstract of one of the papers: Oxygen microelectrodes were used to measure the photosynthetic rates of Antarctic fast ice algal mats. Using the oxygen flux across the diffusive boundary layer below the fast ice at Davis, a productivity range of 0-1.78mg C per square metre per hour was measured. This is at the lower end of fast ice productivity estimates and suggests that conventional carbon 14 techniques may overestimate sea ice algal mat productivity. Photosynthetic capacity (P max) approached 0.05 mg per C.(mg chlorophyl a) per hr. Onset of photosynthesis saturation, E k, was found at about 14 micromol photons per square metre per second. The irradiance of photoinhibition onset, E inh, was about 20 micromol photons per square metre per second and the irradiance at the compensation point, E c, was 4 micromol photons per square metre per second.

The productivity of Antarctic waters may be controlled by the amount of iron. Experiments have shown that this is probably the case for phytoplankton but as yet we do not know if iron limits the growth of sea ice algae. This study will assess whether iron limits sea ice algae production and will conduct experiments to work out how these algae use iron. Measurements have been made to determine whether sea ice algae are limited by Fe. Sea ice samples were taken and this spreadsheet refers to those ice cores Columns A-G are self explanatory Column G is the depth in the ice core from the bottom Column H is the chlorophyll concentration in mg Chl m-2 Column I is the phaeophytin concentration in mg m-2 J is the total amount of protein in the sample ng m-2 K is the total amount of the protein flavodoxin ng m-2 L is the total amount of ferrodoxin ng m-2 These last two enable the Fe limitation status to calculated (not completed).

Metadata record for data from ASAC Project 102 See the link below for public details on this project. From the abstracts of some of the referenced papers: Six species of marine microalgae, namely Phaeodactylum tricornutum Bohlin, Dunaliella tertiolecta Butcher, Isochrysis galbana Parke, Porphyridium purpureum (Bory) Ross, Chroomonas sp., and Oscillatoria woronichinii Anis., have been examined with respect to their gas exchange characteristics and the inorganic carbon species taken up by the cells from the bulk medium. All species showed a high affinity, in photosynthesis, for inorganic carbon and low CO2 compensation concentrations. Such data are suggestive of operation of a 'CO2-concentrating mechanism' in these microalgae. Direct measurements of internal organic carbon pools in four of the species studied confirm this (O. woronichinii and Chroomonas were not tested). By comparison of achieved photosynthetic rates with calculated rates of CO2 supply from the dehydration of bicarbonate, it was shown that Phaeodactylum, Porphyridium and Dunaliella could utilise the bicarbonate present in the medium. Data for the other species were inconclusive although the pH dependence of K 1/2CO2 for photosynthesis by Oscillatoria indicated that this species too could utilise bicarbonate. Such observations could, however, not be used as evidence that, at least in the eucaryotic algae examined, bicarbonate was the inorganic carbon species crossing the plasmalemma as Phaeodactylum, Porphyridium and Dunaliella, and Isochrysis all showed the presence of carbonic anhydrase activity in intact cells as well as in crude extracts. 'External' carbonic anhydrase activity represented from 1/4 to 1/2 of the total activity in the cells of these algae. It is concluded that, as a consequence of a CO2-concentrating mechanism, photorespiration was suppressed in the marine microalgae examined although the data obtained did not allow any firm conclusions to be drawn regarding the species of inorganic carbon transported into the cell. Analysis of the age composition of a given species within a community is fundamental to any study of population dynamics and to the subsequent analyses of community interactions such as competition, succession and productivity. A problem exists in that calendar age often provides little information on the role played by any given individual plant within a population. For many populations the most useful definition of population structure is obtained from an analysis of both the functional age and the vitality of the component plants. Data from such studies on populations of marine macroalgae are lacking mainly because of the lack of suitable methods. This paper provides a review of the methods which have ben applied to such analyses in both terrestrial and marine communities, discusses these methods in the context of marine algae and presents the results of a case study on the analysis of population structure in the large brown alga Durvillaea potatorum. Evidence is presented for the occurrence of sexual reproduction including plasmogamy and meiosis, events previously undescribed in the life history of Ascoseira mirabilis. Ascoseira is monoecious. Gametangia are formed in chains within conceptacles. Synaptonemal complexes, structures concerned with chromosome pairing in meiosis, have been observed in the nucleus of gametangial initials. Mature male and female gametes have the same size and appearance, and resemble typical brown algal zoids. Sexual interaction begins after the female gamete settles down, and both zygotes and unfused gametes develop into sporophytes. It is concluded that Ascoseira has the same basic pattern of life history that characterises the order Fucales, and it is argued that this is probably the result of convergent evolution rather than being indicative of close phylogenetic relationship. Life histories are of central importance in understanding evolution and phylogeny of brown algae. Like other hereditary

Peter Sedwick collected water column samples (6 depths, less than 350m) and measured dissolved iron in these samples, using specialised trace-metal clean techniques, at 9 stations along the SR3 transect between 47 deg S and 66 deg S. These are the first such data for this oceanographic sector during spring. The dissolved iron levels were generally very low (less than 0.2 nM nM) in the upper water column, particularly south of the Subantarctic Front, and surprisingly there was no evidence of significant iron inputs from melting sea ice in our study region. Ongoing work quantified various size fractions of dissolved iron as well as total acid soluble iron. In addition, Jack DiTullio collected water samples for measurements of five biogenic sulfur pools at most shallow water CTD casts. The sulfur pools measured include: dimethylsulfide (DMS), particulate and dissolved dimethylsulfoniopropionate (DMSP) and particulate and dissolved pools of dimethylsulfoxide (DMSO). Taken from the referenced paper: A shipboard-deployable, flow-injection (FI) based instrument for monitoring iron(II) in surface marine waters is described. It incorporates a miniature, low-power photoncounting head for measuring the light emitted from the iron-(II)-catalyzed chemiluminescence (CL) luminol reaction. System control, signal acquisition, and data processing are performed in a graphical programming environment. The limit of detection for iron(II) is in the range 8-12 pmol L-1(based on 3s of the blank), and the precision over the range 8-1000 pmol L-1 varies between 0.9 and 7.6% (n )4). Results from a day-night deployment during a north to-south transect of the Atlantic Ocean and a daytime transect in the Sub-Antarctic Front are presented together with ancillary temperature, salinity, and irradiance data. The generic nature of the components used to assemble the instrument make the technology readily transferable to other laboratories and the modular construction makes it easy to adapt the system for use with other CL chemistries.

Public Description of the Project This project will assess the importance of the trace micro-nutrient element iron to Antarctic sea-ice algal communities during the International Polar Year (2007-2009). We will investigate the biogeochemistry of iron, including a comprehensive examination of its distribution, speciation, cycling and role in fuelling ice-edge phytoplankton blooms. A significant part of this research will concentrate on the the influence of organic exopolysaccharides on iron solubility, complexation and bioavailability, both within the ice and in surrounding snow and surface seawater. This innovative research will improve our understanding of key processes that control the productivity of the climatically-important Antarctic sea-ice zone. Project objectives: This project will assess the importance of the trace element iron (Fe) as a micro-nutrient to seasonal sea-ice algal communities in the Australian sector of Antarctica during the International Polar Year (2007-09). We will investigate the biogeochemistry of Fe, including a comprehensive examination of its distribution, speciation, cycling and role in fuelling ice-edge phytoplankton blooms. A significant part of this research will concentrate on the influence of organic exopolysaccharides (EPS) on Fe solubility and complexation (and hence bioavailability), both within the ice and in surrounding surface waters. This innovative research will improve our understanding of key processes that control the productivity of the climatically-important Antarctic sea-ice zone. This metadata record describes data collected at Casey Station as part of project 3026. Collected data from the time series experiment in sea ice near Casey station Antarctica (66 degrees 13 minutes 07 seconds S, 110 degrees 39 minutes 02 seconds E). Measurements were made at the same location during seven consecutive study days between 10 November and 2 December 2009. Variables measured were pFe (particulate Fe), TDFe (total dissolvable Fe), dFe (dissolved Fe), plFe (particulate leachable Fe), PON (particulate organic nitrogen), POC (particulate organic carbon), Chl a (Chlorophyll a), salinity, ice temperature, vb/v (brine volume fraction), mean daily air temperature, and max daily air temperature. Measurements were taken on each study day of the snow directly overlying the sea ice (SNOW), a shallow and a deep brine (B- and B+, respectively), three sections of the sea ice core at median depths 3, 33, and 73 centimeters (SI1, SI2, and SI3, respectively) as well as two consecutive sections in the lower most basal ice (SI4 and SI5). Finally, four samples were taken of the underlying seawater at 0, 5, 10 and 15 m (SW0, SW5, SW10 and SW15, respectively).

From the abstract of one of the papers: Phytoplankton biomass and speciation were monitored at an inshore site near Davis Station, East Antarctica during three consecutive summer seasons (December-February, 1992-5). Four distinct phytoplankton assemblages were identified in which the dominant species were: Phaeocystis sp., an undescribed Cryptomonas species, Thalassiosira dichotomica, and a mixed assemblage containing Fragilariopsis spp. and Nitzschia spp. Little interannual consistency was found in either the timing of the appearance or disappearance of the various assemblages. Similarly, the seasonal trends in biomass varied dramatically from year to year. Variations in the phytoplankton community can be ascribed, to some extent, to the random variation in a number of factors, including the date of fast ice break out, water column stratification, temperature and salinity, zooplankton grazing and strong winds. Periods of strong wind result in the introduction of offshore or deeper water masses into the shallow inshore environment, where the physical and chemical conditions allow blooms to develop. A number of the papers listed in the reference section are available as pdf's in the download section.

Chlorophyll data was used to measure growth rates of sea ice algae in CO2 incubations. Sea ice brine microalgae was collected from sackholes. Replicate samples were incubated in ambient air (~0.04% CO2), 0.1% CO2, 1.0% CO2 and 2.0% CO2 concentrations. Three incubation experiments were carried out at SIPEX stations 4 (expt 1) 7 (expt 3) and 8 (expt 4). Growth rate calcualtions followed a standard exponential growth model, i.e Bf = Bi x e(rt) Where Bf equals final biomass, Bi equals initial biomass, r = growth rate and t = time (in days).