Biomass of mesozooplankton in the western part of the Black Sea in 1992 during the Cooperative Marine Science Program for the Black Sea (CoMSBlack)

The "CoMSBlack92" dataset is based on samples collected in the summer of 1992 along the Bulgarian coast including coastal and open sea areas. The whole dataset is composed of 79 samples (28 stations) with data of zooplankton species composition, abundance and biomass. Sampling for zooplankton was performed from bottom up to the surface at standard depths depending on water column stratification and the thermocline depth. Zooplankton samples were collected with vertical closing Juday net,diameter - 36cm, mesh size 150 ?m. 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. Sampling volume was estimated by multiplying the mouth area with the wire length. 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 using the relevant taxonomic literature (Mordukhay-Boltovskoy, F.D. (Ed.). 1968, 1969,1972 ). The biomass was estimated as wet weight by Petipa, 1959 (based on species specific wet weight). Wet weight values were transformed to dry weight using the equation DW=0.16*WW as suggested by Vinogradov & Shushkina, 1987. 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. The biomass was estimated as wet weight by Petipa, 1959 ussing standard average weight of each species in mg/m**3.

Biomass of mesozooplankton in the western part of the Black Sea in summer 1991 during the NATO Programme Hydroblack

The "Hydroblack91" dataset is based on samples collected in the summer of 1991 and covers part of North-Western in front of Romanian coast and Western Black Sea (Bulgarian coasts) (between 43°30' - 42°10' N latitude and 28°40'- 31°45' E longitude). Mesozooplankton sampling was undertaken at 20 stations. The whole dataset is composed of 72 samples 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 - 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 materia 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 using the relevant taxonomic literature (Mordukhay-Boltovskoy, F.D. (Ed.). 1968, 1969,1972). The biomass was estimated as wet weight by Petipa, 1959 (based on species specific wet weight). Wet weight values were transformed to dry weight using the equation DW=0.16*WW as suggested by Vinogradov & Shushkina, 1987. 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 using the relevant taxonomic literature (Mordukhay-Boltovskoy, F.D. (Ed.). 1968, 1969,1972). The biomass was estimated as wet weight by Petipa, 1959 ussing standard average weight of each species in mg/m3. WW were converted to DW by equation DW=0.16*WW (Vinogradov ME, Sushkina EA, 1987).

Body condition indices of Asian green mussels, Perna viridis, from Indonesia

While part of a single country, the Indonesian archipelago covers several biogeographic regions, and the high levels of national shipping likely facilitate transfer of non-native organisms between the different regions. Two vessels of a domestic shipping line appear to have served as a transport vector for the Asian green mussel Perna viridis (Linnaeus, 1758) between regions. This species is indigenous in the western but not in the eastern part of the archipelago, separated historically by the Sunda Shelf. The green mussels collected from the hulls of the ferries when in eastern Indonesia showed a significantly lower body condition index than similar-sized individuals from three different western-Indonesian mussel populations. This was presumably due to reduced food supply during the ships' voyages. Although this transportinduced food shortage may initially limit the invasive potential (through reduced reproductive rates) of the translocated individuals, the risk that the species will extend its distributional range further into eastern Indonesia is high. If the species becomes widely established in eastern Indonesia, there will then be an increased risk of incursions to Australia, where the mussel is listed as a high-priority pest species.

Seawater carbonate chemistry and Strongylocentrotus purpuratus body length and gene expression pattern changes during experiments, 2011

Extensive use of fossil fuels is leading to increasing CO2 concentrations in the atmosphere and causes changes in the carbonate chemistry of the oceans which represents a major sink for anthropogenic CO2. As a result, the oceans' surface pH is expected to decrease by ca. 0.4 units by the year 2100, a major change with potentially negative consequences for some marine species. Because of their carbonate skeleton, sea urchins and their larval stages are regarded as likely to be one of the more sensitive taxa. In order to investigate sensitivity of pre-feeding (2 days post-fertilization) and feeding (4 and 7 days post-fertilization) pluteus larvae, we raised Strongylocentrotus purpuratus embryos in control (pH 8.1 and pCO2 41 Pa e.g. 399 µatm) and CO2 acidified seawater with pH of 7.7 (pCO2 134 Pa e.g. 1318 µatm) and investigated growth, calcification and survival. At three time points (day 2, day 4 and day 7 post-fertilization), we measured the expression of 26 representative genes important for metabolism, calcification and ion regulation using RT-qPCR. After one week of development, we observed a significant difference in growth. Maximum differences in size were detected at day 4 (ca. 10 % reduction in body length). A comparison of gene expression patterns using PCA and ANOSIM clearly distinguished between the different age groups (Two way ANOSIM: Global R = 1) while acidification effects were less pronounced (Global R = 0.518). Significant differences in gene expression patterns (ANOSIM R = 0.938, SIMPER: 4.3% difference) were also detected at day 4 leading to the hypothesis that differences between CO2 treatments could reflect patterns of expression seen in control experiments of a younger larva and thus a developmental artifact rather than a direct CO2 effect. We found an up regulation of metabolic genes (between 10 to 20% in ATP-synthase, citrate synthase, pyruvate kinase and thiolase at day 4) and down regulation of calcification related genes (between 23 and 36% in msp130, SM30B, SM50 at day 4). Ion regulation was mainly impacted by up regulation of Na+/K+-ATPase at day 4 (15%) and down regulation of NHE3 at day 4 (45%). We conclude that in studies in which a stressor induces an alteration in the speed of development, it is crucial to employ experimental designs with a high time resolution in order to correct for developmental artifacts. This helps prevent misinterpretation of stressor effects on organism physiology.