999 resultados para Biomass, wet mass per volume
Resumo:
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).
Resumo:
The present study analysed the megabenthic diversity in subtidal soft bottoms and assessed the main environmental drivers of megabenthic community organisation along the Algarve coast (southern Portugal). We tested the hypothesis that megabenthic communities respond to the same environmental drivers than macrofauna. We found that similar to macrofauna, megafaunal communities were organised in relation to the depth of closure, light reaching the bottom, and the hydrodynamic conditions related with exposure within the shallower areas. The influence of the main river outflow prevailed over other drivers, but only up to 9 m depth. We found that seven different spatial units should be considered, each characterised by different indicator species. Additionally, among a total of 412 taxa collected between 4 and 50 m depth, we provide the characteristics of the 64 commonest species in terms of occurrence, frequency, distribution, abundance, bathymetric and sedimentary preferences, which constitutes most valuable information for ecosystem modelling. Megabenthic alpha diversity decreased with depth, contrary to evenness and was higher in the proximity of the river Guadiana and in highly exposed shores. We conclude that the megafauna, which is significantly quicker to collect and analyse, can provide an accurate alternative to macrofauna sampling, as their communities are shaped by the same drivers.