32 resultados para Landscape indicators : assessing and monitoring landscape quality
Resumo:
The dataset is based on samples collected in the summer of 1998 in the Western Black Sea in front of Bulgaria coast. The whole dataset is composed of 69 samples (from 22 stations of National Monitoring Grid) with data of mesozooplankton 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 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 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 Lyudmila Kamburska using the relevant taxonomic literature (Mordukhay-Boltovskoy, F.D. (Ed.). 1968, 1969,1972).
Resumo:
The dataset is based on samples collected in the summer of 2001 in the Western Black Sea in front of Bulgaria coast (transects at c. Kaliakra and c. Galata). The whole dataset is composed of 26 samples (from 10 stations of National Monitoring Grid) with data of mesozooplankton species composition abundance and biomass. Samples were collected in discrete layers 0-10, 10-20, 10-25, 25-50, 50-75, 75-90. 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 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 Lyudmila Kamburska and Kremena Stefanova 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 Lyudmila Kamburska and Kremena Stefanova using the relevant taxonomic literature (Mordukhay-Boltovskoy, F.D. (Ed.). 1968, 1969,1972).
Resumo:
The dataset is based on samples collected in the summer of 2000 in the Western Black Sea in front of Bulgaria coast. The whole dataset is composed of 84 samples (from 31 stations of National Monitoring Grid) with data of mesozooplankton 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. 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 Lyudmila Kamburska using the relevant taxonomic literature (Mordukhay-Boltovskoy, F.D. (Ed.). 1968, 1969,1972). 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 Lyudmila Kamburska using the relevant taxonomic literature (Mordukhay-Boltovskoy, F.D. (Ed.). 1968, 1969,1972).
Resumo:
Analytical challenges in obtaining high quality measurements of rare earth elements (REEs) from small pore fluid volumes have limited the application of REEs as deep fluid geochemical tracers. Using a recently developed analytical technique, we analyzed REEs from pore fluids collected from Sites U1325 and U1329, drilled on the northern Cascadia margin during the Integrated Ocean Drilling Program (IODP) Expedition 311, to investigate the REE behavior during diagenesis and their utility as tracers of deep fluid migration. These sites were selected because they represent contrasting settings on an accretionary margin: a ponded basin at the toe of the margin, and the landward Tofino Basin near the shelf's edge. REE concentrations of pore fluid in the methanogenic zone at Sites U1325 and U1329 correlate positively with concentrations of dissolved organic carbon (DOC) and alkalinity. Fractionations across the REE series are driven by preferential complexation of the heavy REEs. Simultaneous enrichment of diagenetic indicators (DOC and alkalinity) and of REEs (in particular the heavy elements Ho to Lu), suggests that the heavy REEs are released during particulate organic carbon (POC) degradation and are subsequently chelated by DOC. REE concentrations are greater at Site U1325, a site where shorter residence times of POC in sulfate-bearing redox zones may enhance REE burial efficiency within sulfidic and methanogenic sediment zones where REE release ensues. Cross-plots of La concentrations versus Cl, Li and Sr delineate a distinct field for the deep fluids (z > 75 mbsf) at Site U1329, and indicate the presence of a fluid not observed at the other sites drilled on the Cascadia margin. Changes in REE patterns, the presence of a positive Eu anomaly, and other available geochemical data for this site suggest a complex hydrology and possible interaction with the igneous Crescent Terrane, located east of the drilled transect.
Resumo:
The spatial and temporal dynamics of seagrasses have been well studied at the leaf to patch scales, however, the link to large spatial extent landscape and population dynamics is still unresolved in seagrass ecology. Traditional remote sensing approaches have lacked the temporal resolution and consistency to appropriately address this issue. This study uses two high temporal resolution time-series of thematic seagrass cover maps to examine the spatial and temporal dynamics of seagrass at both an inter- and intra-annual time scales, one of the first globally to do so at this scale. Previous work by the authors developed an object-based approach to map seagrass cover level distribution from a long term archive of Landsat TM and ETM+ images on the Eastern Banks (~200 km**2), Moreton Bay, Australia. In this work a range of trend and time-series analysis methods are demonstrated for a time-series of 23 annual maps from 1988 to 2010 and a time-series of 16 monthly maps during 2008-2010. Significant new insight was presented regarding the inter- and intra-annual dynamics of seagrass persistence over time, seagrass cover level variability, seagrass cover level trajectory, and change in area of seagrass and cover levels over time. Overall we found that there was no significant decline in total seagrass area on the Eastern Banks, but there was a significant decline in seagrass cover level condition. A case study of two smaller communities within the Eastern Banks that experienced a decline in both overall seagrass area and condition are examined in detail, highlighting possible differences in environmental and process drivers. We demonstrate how trend and time-series analysis enabled seagrass distribution to be appropriately assessed in context of its spatial and temporal history and provides the ability to not only quantify change, but also describe the type of change. We also demonstrate the potential use of time-series analysis products to investigate seagrass growth and decline as well as the processes that drive it. This study demonstrates clear benefits over traditional seagrass mapping and monitoring approaches, and provides a proof of concept for the use of trend and time-series analysis of remotely sensed seagrass products to benefit current endeavours in seagrass ecology.
Resumo:
The dataset is based on samples collected in the summer of 2002 in the Western Black Sea in front of Bulgaria coast. The whole dataset is composed of 47 samples (from 19 stations of National Monitoring Grid) with data of mesozooplankton species composition abundance and biomass. Sampling for zooplankton was performed 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 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 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 Lyudmila Kamburska using the relevant taxonomic literature (Mordukhay-Boltovskoy, F.D. (Ed.). 1968, 1969,1972).