Abundance of mesozooplankton in the western part of the Black Sea in 1995 during the Cooperative Marine Science Program for the Black Sea (CoMSBlack)

The "CoMSBlack-95" dataset is based on samples collected in the summer of 1995. The whole dataset is composed of 81 samples (28 stations) with data of zooplankton species composition, abundance and biomass. Samples were collected in discrete layers 0-10, 0-20, 0-50, 10-25, 25-50, 50-100 and from bottom up to the surface at depths depending on water column stratification and the thermocline depth. Zooplankton samples were collected with vertical closing Juday net,diameter - 36 cm, 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 Asen Konsulov and Lyudmila Kamburska 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 Asen Konsulov and Lyudmila Kamburska using the relevant taxonomic literature (Mordukhay-Boltovskoy, F.D. (Ed.). 1968, 1969,1972).

Abundance and biomass of zooplankton from 1981-1985 collected in front of Constanta city, Black Sea

The Est Constanta 1981-1985 dataset contains zooplankton data collected allong a 5 station transect in front of the city Constanta (44°10'N, 28°41.5'E - EC1; 44°10'N, 28°47'E - EC2; 44°10'N, 28°54'E - EC3; 44°10'N, 29°08'E - EC4; 44°10'N, 29°22'E - EC5). Zooplankton sampling was undertaken at 5 stations where samples were collected using a Juday closing net in the 0-10, 10-25, 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.

Abundance and biomass of zooplankton from the Romanian littoral collected in April, May and June 1997

The SHELF 1997 dataset contains zooplankton data collected in April, May and June 1997 5 transect in front of the Romanian littoral . Zooplankton sampling was undertaken 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.

Meroplankton in the Kara Sea

Meroplankton was sampled at 11 stations in the southern Kara Sea and the Yenisei Estuary in September 2000. Larvae of 29 benthic taxa representing 10 higher groups were identified. Meroplankton was present at almost all stations and most depth levels. The two most abundant groups were Echinodermata (68%) and Polychaeta (26%). Echinoderms dominated total meroplankton locally due to mass occurrences of Ophiopluteus larvae. The relative group composition was highly variable and seemed to depend mainly on the local hydrographic pattern. Comparison of meroplanktonic data with the distribution of the adults revealed for Spionida and Bivalvia a 'downstream' transport of the larvae whereas for other polychaete species and Ophiuroida 'upstream' transport into the estuary occurred. The distribution and concentration of the larvae within the estuary is explained by physical barriers established by hydrographic gradients, the prevailing mixing processes and the presence of a near-bottom counter current.

Abundance and biomass of zooplankton collected in front of the Danube Delta in May and September 1979

The Gurile Dunarii 1979 dataset contains zooplankton data collected in May and September 1979 in 13 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 13 stations where samples were collected using a Juday closing net in the 0-10, 10-20, 20-30, 30-40 and 40-50m 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.

Macroinvertebrate abundance and proportion of trait categories in river biotopes across England and Wales

There is a long tradition of river monitoring using macroinvertebrate communities to assess environmental quality in Europe. A promising alternative is the use of species life-history traits. Both methods, however, have relied on the time-consuming identification of taxa. River biotopes, 1-100 m**2 'habitats' with associated species assemblages, have long been seen as a useful and meaningful way of linking the ecology of macroinvertebrates and river hydro-morphology and can be used to assess hydro-morphological degradation in rivers. Taxonomic differences, however, between different rivers had prevented a general test of this concept until now. The species trait approach may overcome this obstacle across broad geographical areas, using biotopes as the hydro-morphological units which have characteristic species trait assemblages. We collected macroinvertebrate data from 512 discrete patches, comprising 13 river biotopes, from seven rivers in England and Wales. The aim was to test whether river biotopes were better predictors of macroinvertebrate trait profiles than taxonomic composition (genera, families, orders) in rivers, independently of the phylogenetic effects and catchment scale characteristics (i.e. hydrology, geography and land cover). We also tested whether species richness and diversity were better related to biotopes than to rivers. River biotopes explained 40% of the variance in macroinvertebrate trait profiles across the rivers, largely independently of catchment characteristics. There was a strong phylogenetic signature, however. River biotopes were about 50% better at predicting macroinvertebrate trait profiles than taxonomic composition across rivers, no matter which taxonomic resolution was used. River biotopes were better than river identity at explaining the variability in taxonomic richness and diversity (40% and <=10%, respectively). Detailed trait-biotope associations agreed with independent a priori predictions relating trait categories to near river bed flows. Hence, species traits provided a much needed mechanistic understanding and predictive ability across a broad geographical area. We show that integration of the multiple biological trait approach with river biotopes at the interface between ecology and hydro-morphology provides a wealth of new information and potential applications for river science and management.