(Table 3) Growth rates of the juvenile polychaete Scolelepis squamata obtained from ice cores under varying conditions

In spring, Arctic coastal fast ice is inhabited by high densities of sea ice algae and, among other fauna, juveniles of benthic polychaetes. This paper investigates the hypothesis that growth rates of juveniles of the common sympagic polychaete, Scolelepis squamata (Polychaeta: Spionidae), are significantly faster at sea ice algal bloom concentrations compared to concurrent phytoplankton concentrations. Juvenile S. squamata from fast ice off Barrow, Alaska, were fed with different algal concentrations at 0 and 5 °C, simulating ambient high sea ice algal concentrations, concurrent low phytoplankton concentrations, and an intermediate concentration. Growth rates, calculated using a simple linear regression equation, were significantly higher (up to 115 times) at the highest algal concentration compared to the lowest. At the highest algal concentration, juveniles grew faster at 5 °C compared to those feeding at 0 °C with a Q10 of 2.0. We conclude that highly concentrated sea ice algae can sustain faster growth rates of polychaete juveniles compared to the less dense spring phytoplankton concentrations. The earlier melt of Arctic sea ice predicted with climate change might cause a mismatch between occurrence of polychaete juveniles and food availability in the near future. Our data indicate that this reduction in food availability might counteract any faster growth of a pelagic juvenile stage based on forecasted increased water temperatures.

Abundance and biomass of mesozooplankton collected in front of the Danube Delta in May and September 1980

The Gurile Dunarii 1980 dataset contains zooplankton data collected in May and September 1980 in 14 station allong 3 transect in front of the Danube Delta (45°05' - 44°45'N, 30°02'- 29°27'E). Zooplankton sampling was undertaken at 14 stations where samples were collected using a Juday closing net in the 0-10, 10-25 and 25-50m layer (depending also on the water masses). The dataset includes samples analysed for mesozooplankton species composition and abundance. Sampling volume was estimated by multiplying the mouth area with the wire length. Taxon-specific mesozooplankton abundance was count under microscope. Total abundance is the sum of the counted individuals. Total biomass Fodder, Rotifera , Ctenophora and Noctiluca was estimated using a tabel with wet weight for each species an stage.