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Biota

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  • Description: Spatial distribution of selected demersal fish species in the German Bight. Data source: Data from environmental impact assessments (EIA) under the permit procedures of the Federal Maritime and Hydrographic Agency (BSH) in the North Sea EEZ and research data of the Alfred Wegener Institute (AWI), Helmholtz Centre for Polar and Marine Research; time period: 2000 to 2014, mainly spring and autumn data (EIA data), but also summer and winder data (AWI data) Sampling standards: Data of EIAs follow the standard investigation concept StUK 1-3 (BSH 2007), AWI data mainly collected in accordance with the ICES sampling standard (Rumohr 1999). Sampling gears: EIA-data with 7-8 m (partly 6 m) beam trawl (haul: 15 min), AWI-data with a 2-3 m beam trawl (haul: 5-15 min); trawling speed 3-4 kn, codend mesh size 10 mm Sampling: 1 haul per station and sampling date, data were recorded on board or subsamples were stored frozen for further analysis, analysis of abundance and biomass (kg wet weight) per species Data analysis: science information system of demersal fish data, examination of quality and plausibility, data harmonisation, product computation by AWI Product description: Grid: 10x10 km²; available selectable parameter: number of stations, minimum, maximum, mean, median and standard deviation of density (km-²) per species; classification method: natural jenks (Jenks Caspall algorithm); Note: The products contain a different classification of species density! Note: Please regard different value ranges! Note: Data refer exclusively to demersal fish species spectrum! Cited literature Rumohr, H. (1999). "Soft bottom macrofauna: Collection, treatment, and quality assurance of samples." ICES Techniques in Environmental Sciences, No. 27: 1-19. BSH (2007): Standard Investigation of the Impacts of Offshore Wind Turbines on the Marine Environment (StUK 3), Hamburg.

  • The density classes of harbour porpoises are shown seasonally in a grid of 6 minutes of latitude x 10 minutes of longitude.

  • Description: Spatial distribution of selected macrozoobenthic species in the German Bight. Data source: Data from environmental impact assessments (EIA) under the permit procedures of the Federal Maritime and Hydrographic Agency (BSH) in the North Sea EEZ and research data of the Alfred Wegener Institute (AWI), Helmholtz Centre for Polar and Marine Research; time period: 1997 to 2011, mainly spring and autumn data (EIA data), but also summer and winter data (AWI data) Sampling standards: Data of EIAs follow the standard investigation concept StUK 1-3 (BSH 2007), AWI data collected in accordance with the ICES sampling standard (Rumohr 1999). Sampling gears: mainly van Veen grabs (0.1 m², 30-95 kg), few stations by box corer (0.1 m², 160 kg), Nephrops norvegicus and Goneplax rhomboides sampled by beam trawl and dredge (1-3 m width) Sampling: 1-3 replicates per station, fixation in 4 % buffered formalin seawater solution, dredge and beam-trawl data recorded on board or subsamples frozen stored, abundance and biomass (g wet weight) per species Data analysis: science information system of benthic invertebrate data, examination of quality and plausibility, data harmonisation, product computation by AWI Product description: Grid: 5x5 km² for grab data, 10x10 km² for data on N. norvegicus and G. rhomboides from beam trawl and dredge hauls; available selectable parameter: number of stations, minimum, maximum, mean, median and standard deviation of density (m-²) per species; classification method: natural jenks (Jenks Caspall algorithm), Note: The products contain a different classification of species density! Note: Please regard different value ranges! Rumohr, H. (1999). "Soft bottom macrofauna: Collection, treatment, and quality assurance of samples." ICES Techniques in Environmental Sciences, No. 27: 1-19. BSH (2007): Standard "Investigation of the Impacts of Offshore Wind Turbines on the Marine Environment (StUK 3)", Hamburg.

  • In this service, information on underwater obstacles is presented, which is stored in the "Deutsches Unterwasserhindernisauskunftssystem" (DUWHAS) of the BSH. The data are displayed according to the symbolisation of CONTIS.

  • In this service, information on underwater obstacles is presented, which is available in the "Deutsches Unterwasserhindernisauskunftssystem" (DUWHAS) of the BSH. The data are displayed according to the symbolisation of the international nautical charts (INT 1).

  • This product consists of global gap free Leaf area index (LAI) time series, based on MERIS full resolution Level 1B data. It is produced as a series of 10-day composites in geographic projection at 300m spatial resolution. The processing chain comprises geometric correction, radiometric correction and pixel identification, LAI calculation with the BEAM MERIS vegetation processor, re-projection to a global grid, and temporal aggregation selecting the measurement closest to the mean value. After the LAI pre-processing we applied time series analysis to fill data gaps and filter outliers using the technique of harmonic analysis in combination with mean annual and multiannual phenological data. Data gaps are caused by clouds, sensor limitations due to the solar zenith angle (less than 10 degrees), topography and intermittent data reception. We applied our technique for the whole period of observation (Jul 2002 - Mar 2012). Validation, was performed using VALERI and BigFoot data.

  • Knowledge of the optical properties of the components of the forest canopy is important to the understanding of how plants interact with their environment and how this information may be used to determine vegetation characteristics using remote sensing. During the summers of 1983 and 1984, samples of the major components of the boreal forest canopy (needles, leaves, branches, moss, litter) were collected in the Superior National Forest (SNF) of Minnesota and sent to the Johnson Space Center (JSC). At JSC, the spectral reflectance and transmittance characteristics of the samples were determined for wavelengths between .35 and 2.1 micrometers using the Cary-14 radiometer. This report presents plots of these data as well as averages to the Thematic Mapper Simulator (TMS) bands. There were two main thrusts to the SNF optical properties study. The first was to collect the optical properties of many of the components of the boreal forest canopy. The second goal of the study was to investigate the variability of optical properties within a species. The results of these studies allow a comparison of the optical properties of a variety of different species and a measure of the variability within species. These data provide basic information necessary to model canopy reflectance patterns. [ This document was provided by NASA's Global Change Master Directory. For more information on the source of this metadata please visit http://gcmd.nasa.gov/r/geoss/[GCMD]SNF_LEAFCARY ]

  • Productivity of a steppe grassland was determined at the Tumentsogt Research Station in Mongolia, between 1982 and 1990. Measurements were made of seasonal dynamics of above-ground live biomass for each year. The Mongolian steppe occupies a major part of eastern Mongolia and northern China, characterised by an arid continental climate with most rain falling between June and August. Land use is dominated by grazing, historically by nomadic pastoralists and more recently for cooperative livestock production. Private livestock grazing has been increasing since 1990. Climate data for this site are also available: see Any Other Relevant Information in section 11 of this document. More information on the entire Net Primary Production Project can be found at the NPP homepage. [ This document was provided by NASA's Global Change Master Directory. For more information on the source of this metadata please visit http://gcmd.nasa.gov/r/geoss/[GCMD]NPP_TMN ]

  • Productivity of a steppe grassland was determined from 1980 to 1989 at the Inner Mongolia Grassland Research Station of the Chinese Academy of Sciences, within the Xilingol Biosphere Reserve. Measurements of above-ground live biomass, standing dead matter and litter were made bi-weekly from the beginning of May to early October for each year. Above-ground net primary production was estimated by summing peak live biomass of each of 5 species categories. Steppe grasslands of Leymus chinense and Stipa grandis are the dominant vegetation types, respectively, in the Eastern Eurasian steppe zone (semi-arid and sub-humid) and the middle Eurasian steppe zone (semi-arid). Both species provide good livestock forage and are used mainly as natural grazing lands, and both occur within the Xilingol reserve. More information on the entire Net Primary Production Project can be found at the NPP homepage. [ This document was provided by NASA's Global Change Master Directory. For more information on the source of this metadata please visit http://gcmd.nasa.gov/r/geoss/[GCMD]NPP_XLN ]

  • The Vegetation Species and Cover Abundance Data Set documents the species present at the FIFE staff data measurement sites. Percent cover is estimated for each species at approximately the time of the IFC's. Disturbances occur over a variety of spatial and temporal scales in North American grasslands, and interactions of these different disturbances affect community structure. Two types of disturbance commonly occur over large spatial scales in grasslands, namely, fire and grazing. Analysis of percent cover of dominant species indicated that composition and heterogeneity was significantly affected by grazing intensity and burning. The effects of disturbances on community structure are not additive, and may not be extrapolated from studies of single factors. The interpretation of patterns in natural communities is clearly scale dependent, and processes may act differently when viewed from different spatial or temporal scales. The effects of scale may not always be predictable; therefore, an understanding of pattern and process at one hierarchical level may not provide useful information about pattern and process at a different hierarchical level. [ This document was provided by NASA's Global Change Master Directory. For more information on the source of this metadata please visit http://gcmd.nasa.gov/r/geoss/[GCMD]FIFE_VEG_SPEC ]

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