985 resultados para ABUNDANCE ANALYSIS


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Glacial cooling (~1-5°C) in the eastern equatorial Pacific (EEP) cold tongue is often attributed to increased equatorial upwelling, stronger advection from the Peru-Chile Current (PCC), and to the more remote subpolar southeastern Pacific water mass. However, evidence is scarce for identifying unambiguously which process plays a more important role in driving the large glacial cooling in the EEP. To address this question, here we adopt a faunal calibration approach using planktic foraminifers with a new compilation of coretop data from the eastern Pacific, and present new downcore variation data of fauna assemblage and estimated sea surface temperatures (SSTs) for the past 160 ka (Marine Isotope Stage (MIS) 6) from ODP Site 1240 in the EEP. With significant improvement achieved by adding more coretop data from the eastern boundary current, our downcore calibration results indicate that most of the glacial cooling episodes over the past 160 ka in the EEP are attributable to increased influence from the subpolar water mass from high latitudes of the southern Pacific. By applying this new calibration of the fauna SST transfer function to a latitudinal transect of eastern Pacific (EP) cores, we find that the subpolar water mass has been a major dynamic contributor to EEP cold tongue cooling since MIS 6.

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The HCMR_SES_LAGRANGIAN_GR2_ MICROBIAL PARAMETERS dataset is based on samples collected in the framework of the project SESAME, in the North Aegean Sea during October 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 0.6?m 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 bacteria: 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).

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The dataset is composed of 50 years of approximately monthly mesozooplankton sampling at station Stoncica. The volume of filtered water was estimated assuming 70% efficiency of the Hensen 330 micrometer mesh size net according to Laevastu (1958). Subsamples amounting to 1/20 of the catch were counted for the most representative groups. The whole catch was examined for rare species.The results in the datatables are recalculated to (#/m**3).

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In temperate, subpolar and polar marine systems, the classical perception that bacteria are carbon limited by end of winter and respond in activity and abundance to the production of new carbon during the diatom spring bloom and post bloom. Contrary to this view, we here document an strong increase in bacterial abundance and activity (latter measured by increasing high nuclei acid (HNA) to low nuclei acid (LNA) bacteria ratio) during the winter-spring transition, where phytoplankton smaller than 10 µm dominate. Further DNA-virus were enumerated and revealed the virus to bacteria ratio (VBR) to be decreasing during winter-spring transition, indicating that the virus did not increase in number accordingly to bacteria. During repeated visits to stations in the deep Icelandic and the Norwegian Basins and the shallow Shetland Shelf (26 March to 29 April 2012), we investigated the abundance of bacteria and the succession of HNA:LNA bacteria and VBR. Water samples were collected from CTD rosette .10 L Niskin bottles and fixed in glutaraldehyde (final conc. 5%), flash frozen in liquid Nitrogen and stored at -80°C until analysis.

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Data on zooplankton abundance and biovolume were collected in concert with data on the biophysical environment during the development of the phytoplankton spring bloom at 4 stations in the North Atlantic. Station 1 in the Icelandic Basin was visited four times (26 March, 8 April, 18 April, 27 April), Station 2 in the southern Norwegian Sea was visited three times (30 March, 13 April, 23 April), Station 3 in the North Sea was visited twice (2 April, 15 April) and one intermediate station was visited once. The data were sampled by a Laser Optical Plankton Counter (LOPC, Rolls Royce Canada Ltd.) that was mounted on a carousel water sampler together with a Conductivity-Temperature-Depth sensor (CTD, SBE19plusV2, Seabird Electronics, Inc., USA). Based on the LOPC data, abundance (individuals/m**3) and biovolume (mm3/m**3) were calculated as described in the LOPC Software Operation Manual [(Anonymous, 2006), http://www.brooke-ocean.com/index.html]. LOPC data were regrouped into 49 size groups of equal log10 (body volume) increments (Edvardsen et al., 2002, doi:10.3354/meps227205). LOPC data quality was checked as described in Basedow et al. (2013, doi:10.1016/j.pocean.2012.10.005). CTD data were screened for erroneous (out of range) values and then averaged to the same frequency as the LOPC data (2 Hz). All data were processed using especially developed scripts in the python programming language. The LOPC is an optical instrument designed to count and measure particles (0.1 to 30 mm equivalent spherical diameter) in the water column (Herman et al., 2004; doi:10.1093/plankt/fbh095). The size of particles as equivalent spherical diameter (ESD) was computed as described in the manual (Anonymous, 2006), and in more detail in Checkley et al. (2008, doi:10.4319/lo.2008.53.5_part_2.2123) and Gaardsted et al. (2010, doi:10.1111/j.1365-2419.2010.00558.x).

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Data on zooplankton abundance and biovolume were collected in concert with data on the biophysical environment during the development of the phytoplankton spring bloom at 4 stations in the North Atlantic. Station 1 in the Icelandic Basin was visited four times (26 March, 8 April, 18 April, 27 April), Station 2 in the southern Norwegian Sea was visited three times (30 March, 13 April, 23 April), Station 3 in the North Sea was visited twice (2 April, 15 April) and one intermediate station was visited once. The data were sampled by a Laser Optical Plankton Counter (LOPC, Rolls Royce Canada Ltd.) that was mounted on a carousel water sampler together with a Conductivity-Temperature-Depth sensor (CTD, SBE19plusV2, Seabird Electronics, Inc., USA). Based on the LOPC data, abundance (individuals/m**3) and biovolume (mm3/m**3) were calculated as described in the LOPC Software Operation Manual [(Anonymous, 2006), http://www.brooke-ocean.com/index.html]. LOPC data were regrouped into 49 size groups of equal log10 (body volume) increments (Edvardsen et al., 2002, doi:10.3354/meps227205). LOPC data quality was checked as described in Basedow et al. (2013, doi:10.1016/j.pocean.2012.10.005). CTD data were screened for erroneous (out of range) values and then averaged to the same frequency as the LOPC data (2 Hz). All data were processed using especially developed scripts in the python programming language. The LOPC is an optical instrument designed to count and measure particles (0.1 to 30 mm equivalent spherical diameter) in the water column (Herman et al., 2004; doi:10.1093/plankt/fbh095). The size of particles as equivalent spherical diameter (ESD) was computed as described in the manual (Anonymous, 2006), and in more detail in Checkley et al. (2008, doi:10.4319/lo.2008.53.5_part_2.2123) and Gaardsted et al. (2010, doi:10.1111/j.1365-2419.2010.00558.x).

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Species diversity is the most common variable reported in recent ecological research articles. Ecological processes, however, are driven by individuals. High abundances make arthropods, despite their small body sizes, important actors in food webs. We sampled arthropod assemblages in disturbed and undisturbed vegetation types along an elevation gradient of from 800 to 4550 m a.s.l. on the southern slopes of Mt. Kilimanjaro, Tanzania. In our analysis, we focused on 13 different lineages of arthropods that represented three major functional groups: predators, herbivores and decomposers. The samples were collected with pitfall traps on 59 (of 60) study sites within the framework of the KiLi-project (https://www.kilimanjaro.biozentrum.uni-wuerzburg.de/). In each of twelve vegetation types five sampling sites of 50 m x 50 m were established with a minimum distance of 300 m between the individual sites. On each of the 59 sites, ten pitfall traps were evenly spaced along two 50 m transects, with a distance of 10 m between individual traps and 20 m between the parallel transects. Pitfall traps were filled with 100-200 ml of a mixture of ethylenglycol and water (1:1) with a drop of liquid soap to break surface tension. Traps were exposed at 2 to 5 sampling events for seven days in both the dry and wet seasons between May 2011 and October 2012. The reported abundances per lineage were averaged twice: first over all samples per site for each sampling event (3-10 analyzed samples per site and sampling event), and then averaged over all sampling events for each site.

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In this study, we present a unique high-resolution Holocene record of oceanographic and climatic change based on analyses of diatom assemblages combined with biomarker data from a sediment core collected from the Vega Drift, eastern Antarctic Peninsula (EAP). These data add to the climate framework already established by high-resolution marine sedimentary records from the Palmer Deep, western Antarctic Peninsula (WAP). Heavy sea ice conditions and reduced primary productivity were observed prior to 7.4 ka B.P. in relation with the proximity of the glacial ice melt and calving. Subsequent Holocene oceanographic conditions were controlled by the interactions between the Westerlies-Antarctic Circumpolar Current (ACC)-Weddell Gyre dynamics. A warm period characterized by short seasonal sea ice duration associated with a southern shift of both ACC and Westerlies field persisted until 5 ka B.P. This warm episode was then followed by climate deterioration during the middle-to-late Holocene (5 to 1.9 ka B.P.) with a gradual increase in annual sea ice duration triggered by the expansion of the Weddell Gyre and a strong oceanic connection from the EAP to the WAP. Increase of benthic diatom species during this period was indicative of more summer/autumn storms, which was consistent with changes in synoptic atmospheric circulation and the establishment of low- to high-latitude teleconnections. Finally, the multicentennial scale variability of the Weddell Gyre intensity and storm frequency during the late Holocene appeared to be associated with the increased El Niño-Southern Oscillation frequency.

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In temperate, subpolar and polar marine systems, the classical perception is that diatoms initiate the spring bloom and thereby mark the beginning of the productive season. Contrary to this view, here we document an pre-bloom of pico- and nanophytoplankton prior to the diatom bloom; a period with excess nutrients and deep convection of the water column. During repeated visits to stations in the deep Icelandic and the Norwegian Basins and the shallow Shetland Shelf (26 March to 29 April 2012), we investigated the succession and dynamics of <10 µm phytoplankton. Water samples were collected from CTD rosette 10 L Niskin bottles and fixed in glutaraldehyde (final conc. 5%), flash frozen in liquid Nitrogen and stored at -80°C until analysis.

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Data on zooplankton abundance and biovolume were collected in concert with data on the biophysical environment during the development of the phytoplankton spring bloom at 4 stations in the North Atlantic. Station 1 in the Icelandic Basin was visited four times (26 March, 8 April, 18 April, 27 April), Station 2 in the southern Norwegian Sea was visited three times (30 March, 13 April, 23 April), Station 3 in the North Sea was visited twice (2 April, 15 April) and one intermediate station was visited once. The data were sampled by a Laser Optical Plankton Counter (LOPC, Rolls Royce Canada Ltd.) that was mounted on a carousel water sampler together with a Conductivity-Temperature-Depth sensor (CTD, SBE19plusV2, Seabird Electronics, Inc., USA). Based on the LOPC data, abundance (individuals/m**3) and biovolume (mm3/m**3) were calculated as described in the LOPC Software Operation Manual [(Anonymous, 2006), http://www.brooke-ocean.com/index.html]. LOPC data were regrouped into 49 size groups of equal log10 (body volume) increments (Edvardsen et al., 2002, doi:10.3354/meps227205). LOPC data quality was checked as described in Basedow et al. (2013, doi:10.1016/j.pocean.2012.10.005). CTD data were screened for erroneous (out of range) values and then averaged to the same frequency as the LOPC data (2 Hz). All data were processed using especially developed scripts in the python programming language. The LOPC is an optical instrument designed to count and measure particles (0.1 to 30 mm equivalent spherical diameter) in the water column (Herman et al., 2004; doi:10.1093/plankt/fbh095). The size of particles as equivalent spherical diameter (ESD) was computed as described in the manual (Anonymous, 2006), and in more detail in Checkley et al. (2008, doi:10.4319/lo.2008.53.5_part_2.2123) and Gaardsted et al. (2010, doi:10.1111/j.1365-2419.2010.00558.x).

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Data on zooplankton abundance and biovolume were collected in concert with data on the biophysical environment during the development of the phytoplankton spring bloom at 4 stations in the North Atlantic. Station 1 in the Icelandic Basin was visited four times (26 March, 8 April, 18 April, 27 April), Station 2 in the southern Norwegian Sea was visited three times (30 March, 13 April, 23 April), Station 3 in the North Sea was visited twice (2 April, 15 April) and one intermediate station was visited once. The data were sampled by a Laser Optical Plankton Counter (LOPC, Rolls Royce Canada Ltd.) that was mounted on a carousel water sampler together with a Conductivity-Temperature-Depth sensor (CTD, SBE19plusV2, Seabird Electronics, Inc., USA). Based on the LOPC data, abundance (individuals/m**3) and biovolume (mm3/m**3) were calculated as described in the LOPC Software Operation Manual [(Anonymous, 2006), http://www.brooke-ocean.com/index.html]. LOPC data were regrouped into 49 size groups of equal log10 (body volume) increments (Edvardsen et al., 2002, doi:10.3354/meps227205). LOPC data quality was checked as described in Basedow et al. (2013, doi:10.1016/j.pocean.2012.10.005). CTD data were screened for erroneous (out of range) values and then averaged to the same frequency as the LOPC data (2 Hz). All data were processed using especially developed scripts in the python programming language. The LOPC is an optical instrument designed to count and measure particles (0.1 to 30 mm equivalent spherical diameter) in the water column (Herman et al., 2004; doi:10.1093/plankt/fbh095). The size of particles as equivalent spherical diameter (ESD) was computed as described in the manual (Anonymous, 2006), and in more detail in Checkley et al. (2008, doi:10.4319/lo.2008.53.5_part_2.2123) and Gaardsted et al. (2010, doi:10.1111/j.1365-2419.2010.00558.x).

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Data on zooplankton abundance and biovolume were collected in concert with data on the biophysical environment during the development of the phytoplankton spring bloom at 4 stations in the North Atlantic. Station 1 in the Icelandic Basin was visited four times (26 March, 8 April, 18 April, 27 April), Station 2 in the southern Norwegian Sea was visited three times (30 March, 13 April, 23 April), Station 3 in the North Sea was visited twice (2 April, 15 April) and one intermediate station was visited once. The data were sampled by a Laser Optical Plankton Counter (LOPC, Rolls Royce Canada Ltd.) that was mounted on a carousel water sampler together with a Conductivity-Temperature-Depth sensor (CTD, SBE19plusV2, Seabird Electronics, Inc., USA). Based on the LOPC data, abundance (individuals/m**3) and biovolume (mm3/m**3) were calculated as described in the LOPC Software Operation Manual [(Anonymous, 2006), http://www.brooke-ocean.com/index.html]. LOPC data were regrouped into 49 size groups of equal log10 (body volume) increments (Edvardsen et al., 2002, doi:10.3354/meps227205). LOPC data quality was checked as described in Basedow et al. (2013, doi:10.1016/j.pocean.2012.10.005). CTD data were screened for erroneous (out of range) values and then averaged to the same frequency as the LOPC data (2 Hz). All data were processed using especially developed scripts in the python programming language. The LOPC is an optical instrument designed to count and measure particles (0.1 to 30 mm equivalent spherical diameter) in the water column (Herman et al., 2004; doi:10.1093/plankt/fbh095). The size of particles as equivalent spherical diameter (ESD) was computed as described in the manual (Anonymous, 2006), and in more detail in Checkley et al. (2008, doi:10.4319/lo.2008.53.5_part_2.2123) and Gaardsted et al. (2010, doi:10.1111/j.1365-2419.2010.00558.x).

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Zooplankton samples were taken in five depth strata using a Multinet type Midi, with 50 µm nets. The samples were taken during the second leg only, three times at station 1, two times at station 2 and once at station 3. Zooplankton were identified to species / genus and life-stage, and at least 300 individuals were counted per sample. 10 individuals of each stage / species were measured and the numbers of eggs counted.

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The continuously influence of human impacts on the seafloor and benthic habitats demands the knowledge of clearly defined habitats to assess recent conditions and to monitor future changes. In this study, a benthic habitat dominated by sorted bedforms was mapped in 2010 using biological, sedimentological and acoustic data. This approach reveals the first interdisciplinary analysis of macrofauna communities in sorted bedforms in the German Bight. The study area covered 4 km², and was located ca. 3.5 km west of island of Sylt. Sorted bedforms formed as sinuous depressions with an east west orientation. Inside these depressions coarse sand covers the seafloor, while outside predominantly fine to medium sand was found. Based on the hydroacoustic data, two seafloor classes were identified. Acoustic class 1 was linked to coarse sand (type A) found inside these sorted bedforms, whereas acoustic class 2 was related to mainly fine to medium sands (type B). The two acoustic classes and sediment types corresponded with the macrofauna communities 1 and 2. The Aoinides paucibranchiata-Goniadella bobretzkii community on coarse sand and the Spiophanes bombyx - Magelona johnstonii community on fine sand. A transitional community 3 (Scoloplos armiger - Ophelia community), with species found in communities 1 and 2, could not be detected by hydroacoustic methods. This study showed the limits of the used acoustic methods, which were unable to detect insignificant differences in the fauna composition of sandy areas.