422 resultados para TOTAL ABOVEGROUND BIOMASS
Resumo:
Vertical distribution of common zooplankton species is examined on the base of two series of layer-by-layer net catches down to depth of 3400 m. Differences between the series are significant for most species only near the surface, whereas in deeper layers character of distribution remains the same. Great depths in the Sea of Japan are populated most actively by species performing intensive daily migrations, and less actively by species continuously confined to a definite depth range. Different character of nutrition of the animals apparently determines extent of utilization of deep layers, which are usual for the species.
Resumo:
According to results of Cruise 22 of R/V Akademik Mstislav Keldysh in the Northwest Pacific in July-August 1990, picophytoplankton represented mainly by cyanobacteria (up to 90%) comprised from 70 to 99% of total phytoplankton. Nanophytoplankton constituted substantial part of total biomass (22-37%) and consisted mainly of small phytoflagellates (2-4 ?m), cryptomonades, and coccolithophorids Emiliania huxleyi. Summer species such as Neodenticula seminae prevailed among large phytoplankton. Horizontal and vertical distribution of phytoplankton groups and species was described. Taxonomy and vertical distribution were related to nutrient concentrations in the upper mixed layer.
Resumo:
Distribution of mesoplankton in the Burgas Bay in 53 bottle samples taken in October-November 1982 is discussed. Decrease in total biomass of zooplankton from north to south can be traced at the northern meridional section (Cape Krotiriya to Cape Kaliakra), probably resulting from decrease in eutrophicating effect of the Danube River in this direction. Plankton off the Bulgarian coast was in typical autumn condition. In the southern part of the Burgas Bay, where there is discharge current carrying eutrophicated sewage from the city of Burgas, various stages in development of the community, from a young community in the inner end of the bay to a mature one at its outlet, were observed.
Resumo:
Ichthyoplankton density (fish eggs and larvae) and bulk zooplankton biomass in September 2010 were determined for 10 stations in the northern Benguela upwelling system, based on oblique Multinet hauls during the RRS Discovery D356 cruise. A HYDROBIOS Multinet, type Midi (0.25 m**2 mouth area) was equipped with five nets of 500 µm-mesh size, temperature and oxygen probes, and an inner and outer flow meter to monitor the net's trajectory (for volume filtered calculations) as well as net clogging. The Multinet was handled over the side, towed horizontally at 2 knots. Winch speed when fearing was 0.5 or 0.3 m/s, heaving velocity 0.2 - 0.3 m/s. The Multinet was towed obliquely at 10 stations sampling the upper 200 m of the water column, which were divided into five different depth strata after inspection of temperature and oxygen concentration depth profiles. Ichthyoplankton densities and zooplankton biomass were calculated for each depth stratum (=single net) from total abundance and the volume of water filtered [individuals per m**3 and g wet weight per m**3, respectively]. In addition, densities and biomass were integrated over the area for each station [individuals per m**2], as sum of calculations for each net: Sum ([individuals per m**3]*Delta(depth bot[m]-depth top [m]).
Resumo:
IIchthyoplankton density (fish eggs and larvae) and bulk zooplankton biomass in December 2009 were determined for 22 stations in the Benguela upwelling system, based on oblique Multinet hauls during the FRS Africana cruise AFR258. A HYDROBIOS Multinet, type Midi (0.25 m**2 mouth area) was equipped with five nets of 500 µm-mesh size, temperature and oxygen probes, and an inner and outer flow meter to monitor the net's trajectory (for volume filtered calculations) as well as net clogging. The Multinet was handled over the side, towed horizontally at 2 knots. Winch speed when fearing was 0.5 or 0.3 m/s, heaving velocity 0.2 - 0.3 m/s. The Multinet was towed obliquely at 22 stations sampling the upper 200 m of the water column, which were divided into five different depth strata after inspection of temperature and oxygen concentration depth profiles. Ichthyoplankton densities and zooplankton biomass were calculated for each depth stratum (=single net) from total abundance and the volume of water filtered [individuals per m**3 and g wet weight per m**3, respectively]. Densities and biomass were integrated over the area for each station [individuals per m**2], as sum of calculations for each net: Sum ([individuals per m**3]*Delta (depth bot[m]-depth top [m]).
Resumo:
The HCMR_SES_LAGRANGIAN_GR1_ MICROBIAL PARAMETERS dataset is based on samples collected in the framework of the project SESAME, in the North Aegean Sea during April 2008. The objectives were to measure the standing stocks and calculate the production of the microbial compartment of the food web, describe the vertical distribution pattern and characterize its structure and function through the water column as influenced by the BSW. Heterotrophic bacteria, Synechococcus, Prochlorococcus and Virus abundance: Subsamples for virus, heterotrophic bacteria and cyanobacteria (Synechococcus spp. and Prochlorococcus spp.) counting were analyzed using a FACSCalibur (Becton Dickinson) flow cytometer equipped with a standard laser (488 nm) and filter set and using deionized water as sheath fluid. Fluorescent beads with a diameter of 0.97 µm (Polysciences) were added to each sample as an internal standard, and all parameters were normalized to the beads and expressed as relative units. SYBRGreen I stain (Molecular Probe) was used to stain viral and heterotrophic bacterial DNA. Viruses were counted according to (Brussaard 1984). In order to avoid bulk consentrations of viruses samples we dilluted to Tris-EDTA (pH=8,0) buffer to a final sollution of 1/5 to 1/100. Total abundance and nucleid content classes were calculated using the Paint-A-Gate software (Becton Dickinson). Heterotrophic Nanoflagellate abundance: Subsamples (30-150 ml) were concentrated on 25mm black polycarbonate filters of porosity 0.6µm and stained with DAPI for 10 min (Porter and Feig 1980). Under epifluorescence microscopy heterotrophic nanoflagellates (HNAN) were distinguished using UV and blue excitation and enumerated. Nanoflagellates were classified in size categories and the biovolume was calculated. Ciliate abundance: For ciliate identification and enumeration, 100-3000 ml samples were left for 24h-4d for sedimentation and then observed under an inverted microscope. Ciliates were counted, distinguished into size-classes and major taxonomic groups and identified down to genus or species level where possible (Pitta et al. 2005). Heterotrophic bacteria, Synechococcus, Prochlorococcus biomass: Subsamples for virus, heterotrophic bacteria and cyanobacteria (Synechococcus spp. and Prochlorococcus spp.) counting were analyzed using a FACSCalibur (Becton Dickinson) flow cytometer equipped with a standard laser (488 nm) and filter set and using deionized water as sheath fluid. Fluorescent beads with a diameter of 0.97 µm (Polysciences) were added to each sample as an internal standard, and all parameters were normalized to the beads and expressed as relative units. SYBRGreen I stain (Molecular Probe) was used to stain viral and heterotrophic bacterial DNA. Viruses were counted according to (Brussaard 1984). In order to avoid bulk consentrations of viruses samples we dilluted to Tris-EDTA (pH=8,0) buffer to a final sollution of 1/5 to 1/100. Total abundance and nucleid content classes were calculated using the Paint-A-Gate software (Becton Dickinson). Abundance data were converted into C biomass using 250 fgC cell-1 (Kana & Glibert 1987) for Synechococcus, 50 fgC cell-1 (Campbell et al. 1994) for Prochlorococcus and 20fgC cell-1 (Lee & Fuhrman 1987) for heterotrophic bacteria. Heterotrophic Nanoflagellate biomass: Subsamples (30-150 ml) were concentrated on 25mm black polycarbonate filters of porosity 0.6µm and stained with DAPI for 10 min (Porter and Feig 1980). Under epifluorescence microscopy heterotrophic nanoflagellates (HNAN) were distinguished using UV and blue excitation and enumerated. Nanoflagellates were classified in size categories and the biovolume was calculated. Abundance data were converted into C biomass using 183 fgC µm**3 (Caron et al. 1995). Ciliate biomass: For ciliate identification and enumeration, 100-3000 ml samples were left for 24h-4d for sedimentation and then observed under an inverted microscope. Ciliates were counted, distinguished into size-classes and major taxonomic groups and identified down to genus or species level where possible (Pitta et al. 2005). Ciliate cell sizes were measured and converted into cell volumes using appropriate geometric formulae using image analysis. For biomass estimation, the conversion factor 190 fgC µm**3 was used (Putt and Stoecker 1989).
Resumo:
The Danubs 2001 dataset contains zooplankton data collected in March, June, September and October 2001 in 11 station allong 5 transect in front of the Romanian littoral. Zooplankton sampling was undertaken at 11 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.
Resumo:
Ichthyoplankton density (fish eggs and larvae) and bulk zooplankton biomass in March 2008 were determined for 32 stations in the northern Benguela upwelling system, based on oblique Multinet hauls during the FS Maria S. Merian MSM07/3 cruise. A HYDROBIOS Multinet, type Midi (0.25 m**2 mouth area) was equipped with five nets of 500 µm-mesh size, temperature and oxygen probes, and an inner and outer flow meter to monitor the net's trajectory (for volume filtered calculations) as well as net clogging. The Multinet was handled over the side, towed horizontally at 2 knots. Winch speed when fearing was 0.5 or 0.3 m/s, heaving velocity 0.2 - 0.3 m/s. The Multinet was towed obliquely at 32 stations sampling the upper 200 m of the water column, which were divided into five different depth strata after inspection of temperature and oxygen concentration depth profiles. Ichthyoplankton densities and zooplankton biomass were calculated for each depth stratum (=single net) from total abundance and the volume of water filtered [individuals per m**3 and g wet weight per m**3, respectively]. In addition, densities and biomass were integrated over the area for each station [individuals per m**2], as sum of calculations for each net: Sum ([individuals per m**3]*Delta (depth bot[m]-depth top [m]).
Resumo:
Ichthyoplankton density (fish eggs and larvae) and bulk zooplankton biomass in September 2010 were determined for 10 stations in the northern Benguela upwelling system, based on oblique Multinet hauls during the RRS Discovery D356 cruise. A HYDROBIOS Multinet, type Midi (0.25 m**2 mouth area) was equipped with five nets of 500 µm-mesh size, temperature and oxygen probes, and an inner and outer flow meter to monitor the net's trajectory (for volume filtered calculations) as well as net clogging. The Multinet was handled over the side, towed horizontally at 2 knots. Winch speed when fearing was 0.5 or 0.3 m/s, heaving velocity 0.2 - 0.3 m/s. The Multinet was towed obliquely at 10 stations sampling the upper 200 m of the water column, which were divided into five different depth strata after inspection of temperature and oxygen concentration depth profiles. Ichthyoplankton densities and zooplankton biomass were calculated for each depth stratum (=single net) from total abundance and the volume of water filtered [individuals per m**3 and g wet weight per m**3, respectively]. In addition, densities and biomass were integrated over the area for each station [individuals per m**2], as sum of calculations for each net: Sum ([individuals per m**3]*Delta(depth bot[m]-depth top [m]).