Compilation of scientific results of the OASIS project

Seamounts are of great interest to science, industry and conservation because of their potential role as 'stirring rods' of the oceans, their enhanced productivity, their high local biodiversity, and the growing exploitation of their natural resources. This is accompanied by rising concern about the threats to seamount ecosystems, e.g. through over-fishing and the impact of trawling. OASIS described the functioning characteristics of seamount ecosystems. OASIS' integrated hydrographic, biogeochemical and biological information. Based on two case studies. The scientific results, condensed in conceptual and mass balanced ecosystem models, were applied to outline a model management plan as well as site-specific management plans for the seamounts investigated. OASIS addressed five main objectives: Objective 1: To identify and describe the physical forcing mechanisms effecting seamount systems Objective 2: To assess the origin, quality and dynamics of particulate organic material within the water column and surface sediment at seamounts. Objective 3: To describe aspects of the biodiversity and the ecology of seamount biota, to assess their dynamics and the maintenance of their production. Objective 4: Modelling the trophic ecology of seamount ecosystems. Objective 5: Application of scientific knowledge to practical conservation.

Biogenic and lithogenic silica, silicic acid, production of biogenic silica, and irradiance measurements during the Ross Sea Bloom Project 1994-1996

The development of the seasonal phytoplankton bloom in the Ross Sea was studied during two cruises. The first, conducted in November-December 1994, investigated the initiation and rapid growth of the bloom, whereas the second (December 1995-January 1996) concentrated on the bloom's maximum biomass period and the subsequent decline in biomass. Central to the understanding of the controls of growth and the summer decline of the bloom is a quantitative assessment of the growth rate of phytoplankton. Growth rates were estimated over two time scales with different methods. The first estimated daily growth rates from isotropic incorporation under simulated in situ conditions, including 14C, 15N and 32Si uptake measurements combined with estimates of standing stocks of particulate organic carbon, nitrogen and biogenic silica. The second method used daily to weekly changes in biomass at selected locations, with net growth rates being estimated from changes in standing stocks of phytoplankton. In addition, growth rates were estimated in large-volume experiments under optimal irradiances. Growth rates showed distinct temporal patterns. Early in the growing season, short-term estimates suggested that growth rates of in situ assemblages were less than maximum (relative to the temperature-limited maximum) and were likely reduced due to low irradiance regimes encountered under the ice. Growth rates increased thereafter and appeared to reach their maximum as biomass approached the seasonal peak, but decreased markedly in late December. Differences between the major taxonomic groups present were also noted, especially from the isotopic tracer experiments. The haplophyte Phaeocystic antarctica was dominant in 1994 throughout the growing season, and it exhibited the greatest growth rates (mean 0.41/day) during spring. Diatom standing stocks were low early in the growing season, and growth rates averaged 0.100/day. In summer diatoms were more abundant, but their growth rates remained much lower (mean of 0.08/day) than the potential maximum. Understanding growth rate controls is essential to the development of predictive models of the carbon cycle and food webs in Antarctic waters.

Abundance of mesozooplankton in the western part of the Black Sea in summer 2005 during Phase 2: Leg1 from the GEF Project

The sampling area was extended to the Western-South area off the Black Sea coast from Kaliakra cape toward the Bosforous. Samples were collected along four transects. The whole dataset is composed of 17 samples (from 10 stations) with data of mesozooplankton species composition abundance and biomass. Sampling for zooplankton was performed from bottom up to the surface at depths depending on water column stratification and the thermocline depth. These data are organized in the "Control of eutrophication, hazardous substances and related measures for rehabilitating the Black Sea ecosystem: Phase 2: Leg I: PIMS 3065". Data Report is not published. Zooplankton samples were collected with vertical closing Juday net,diameter - 36cm, mesh size 150 µm. Tows were performed from surface down to bottom meters depths in discrete layers. Samples were preserved by a 4% formaldehyde sea water buffered solution. Sampling volume was estimated by multiplying the mouth area with the wire length. Mesozooplankton abundance: The collected material was analysed using the method of Domov (1959). Samples were brought to volume of 25-30 ml depending upon zooplankton density and mixed intensively until all organisms were distributed randomly in the sample volume. After that 5 ml of sample was taken and poured in the counting chamber which is a rectangle form for taxomomic identification and count. Large (> 1 mm body length) and not abundant species were calculated in whole sample. Counting and measuring of organisms were made in the Dimov chamber under the stereomicroscope to the lowest taxon possible. Taxonomic identification was done at the Institute of Oceanology by Kremena Stefanova using the relevant taxonomic literature (Mordukhay-Boltovskoy, F.D. (Ed.). 1968, 1969,1972). Taxon-specific abundance: The collected material was analysed using the method of Domov (1959). Samples were brought to volume of 25-30 ml depending upon zooplankton density and mixed intensively until all organisms were distributed randomly in the sample volume. After that 5 ml of sample was taken and poured in the counting chamber which is a rectangle form for taxomomic identification and count. Copepods and Cladoceras were identified and enumerated; the other mesozooplankters were identified and enumerated at higher taxonomic level (commonly named as mesozooplankton groups). Large (> 1 mm body length) and not abundant species were calculated in whole sample. Counting and measuring of organisms were made in the Dimov chamber under the stereomicroscope to the lowest taxon possible. Taxonomic identification was done at the Institute of Oceanology by Kremena Stefanova using the relevant taxonomic literature (Mordukhay-Boltovskoy, F.D. (Ed.). 1968, 1969,1972).

Determination of absolute coccolith abundances in deep-sea sediments by spiking with microbeads and spraying - SMS-method (Table 1)

A quick new method is described for the quantification of absolute nannofossil proportions in deep-sea sediments. This method (SMS) is the combination of Spiking a sample with Microbeads and Spraying it on a cover slide. It is suitable for scanning electron microscope (SEM) analyses and for light microscope (LM) analyses. Repeated preparation and counting of the same sample (30 times) revealed a standard deviation of 10.5%. The application of tracer microbeads with different diameters and densities revealed no statistically significant differences between counts. The SMS-method yielded coccolith numbers that are statistically not significantly different from values obtained from the filtration-method. However, coccolith counts obtained by the random settling method are three times higher than the values obtained by the SMS- and the filtration-method.

Sea surface and the sea floor regionalization of the Southern Ocean by multivariate cluster analysis, links to ArcGIS project files

This study subdivides the Weddell Sea, Antarctica, into seafloor regions using multivariate statistical methods. These regions are categories used for comparing, contrasting and quantifying biogeochemical processes and biodiversity between ocean regions geographically but also regions under development within the scope of global change. The division obtained is characterized by the dominating components and interpreted in terms of ruling environmental conditions. The analysis uses 28 environmental variables for the sea surface, 25 variables for the seabed and 9 variables for the analysis between surface and bottom variables. The data were taken during the years 1983-2013. Some data were interpolated. The statistical errors of several interpolation methods (e.g. IDW, Indicator, Ordinary and Co-Kriging) with changing settings have been compared for the identification of the most reasonable method. The multivariate mathematical procedures used are regionalized classification via k means cluster analysis, canonical-correlation analysis and multidimensional scaling. Canonical-correlation analysis identifies the influencing factors in the different parts of the cove. Several methods for the identification of the optimum number of clusters have been tested. For the seabed 8 and 12 clusters were identified as reasonable numbers for clustering the Weddell Sea. For the sea surface the numbers 8 and 13 and for the top/bottom analysis 8 and 3 were identified, respectively. Additionally, the results of 20 clusters are presented for the three alternatives offering the first small scale environmental regionalization of the Weddell Sea. Especially the results of 12 clusters identify marine-influenced regions which can be clearly separated from those determined by the geological catchment area and the ones dominated by river discharge.