982 resultados para LINE-DATA-BASE


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Oceanographic data collected by ocean research organisations in Russia, the USA, the United Kingdom, Germany, Norway, and Poland for the Barents, Kara and White Seas region are presented in this atlas. Recently declassified naval data from Norway, the USA, and the UK are also included. More than 1,000,000 oceanographic stations containing temperature and/or sea-water salinity data were originally selected. After correcting errors and eliminating duplicates, data from 206,300 checked stations were placed on CD-ROM, together with many figures describing the characteristics of both the single-input and combined data set. In addition, temperature and salinity measurements were interpolated to the following standard horizons: 0, 25, 50, 100, 150, 200, 250, 300 m, and bottom. This atlas covers the 100-year period 1898 to 1998 and is, to date, the most complete oceanographic data collection for these Arctic shelf seas. This data set is complemented by more than 9,000 measurements of sea surface temperature, which were recently digitized from ships' logbooks. They cover the same geographical area within the time period 1867-1912.

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It is widely recognized that climate change poses significant challenges to the conservation of biodiversity. The need of dealing with relatively rapid and uncertain environmental change calls for the enhancement of adaptive capacity of both biodiversity and conservation management systems. Under the hypothesis that most of the conventional biodiversity conservation tools do not sufficiently stimulate a dynamic protected area management, which takes rapid environmental change into account, we evaluated almost 900 of The Nature Conservancy's site-based conservation action plans. These were elaborated before a so-called climate clinic in 2009, an intensive revision of existing plans and a climate change training of the planning teams. We also compare these results with plans elaborated after the climate clinic. Before 2009, 20% of the CAPs employed the term "climate change" in their description of the site viability, and 45% identified key ecological attributes that are related to climate. 8% of the conservation strategies were directly or indirectly related to climate change adaptation. After 2009, a significantly higher percentage of plans took climate change into account. Our data show that many planning teams face difficulties in integrating climate change in their management and planning. However, technical guidance and concrete training can facilitate management teams learning processes. Arising new tools of adaptive conservation management that explicitly incorporate options for handling future scenarios, vulnerability analyses and risk management into the management process have the potential of further making protected area management more proactive and robust against change.

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This database (Leemans & Cramer 1991) contains monthly averages of mean temperature, temperature range, precipitation, rain days and sunshine hours for the terrestrial surface of the globe, gridded at 0.5 degree longitude/latitude resolution. All grd-files contain the same 62483 pixels in the same order, with 30' latitude and longitude resolution. The coordinates are in degree-decimals and indicate the SW corner of each pixel. Topography is from ETOPO5 and indicates modal elevation. Data were generated from a large data base, using the partial thin-plate splining algorithm (Hutchinson & Bischof 1983). This version is widely used around the globe, notably by all groups participating in the IGBP NPP model intercomparison.

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Microzooplankton (the 20 to 200 µm size class of zooplankton) is recognised as an important part of marine pelagic ecosystems. In terms of biomass and abundance heterotrophic dinoflagellates are one of the important groups of organism in microzooplankton. However, their rates - grazing and growth - , feeding behaviour and prey preferences are poorly known and understood. A set of data was assembled in order to derive a better understanding of heterotrophic dinoflagellates rates, in response to parameters such as prey concentration, prey type (size and species), temperature and their own size. With these objectives, literature was searched for laboratory experiments with information on one or more of these parameters effect studied. The criteria for selection and inclusion in the database included: (i) controlled laboratory experiment with a known dinoflagellate feeding on a known prey; (ii) presence of ancillary information about experimental conditions, used organisms - cell volume, cell dimensions, and carbon content. Rates and ancillary information were measured in units that meet the experimenter need, creating a need to harmonize the data units after collection. In addition different units can link to different mechanisms (carbon to nutritive quality of the prey, volume to size limits). As a result, grazing rates are thus available as pg C dinoflagellate-1 h-1, µm3 dinoflagellate-1 h-1 and prey cell dinoflagellate-1 h-1; clearance rate was calculated if not given and growth rate is expressed as the growth rate per day.

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I developed a new model for estimating annual production-to-biomass ratio P/B and production P of macrobenthic populations in marine and freshwater habitats. Self-learning artificial neural networks (ANN) were used to model the relationships between P/B and twenty easy-to-measure abiotic and biotic parameters in 1252 data sets of population production. Based on log-transformed data, the final predictive model estimates log(P/B) with reasonable accuracy and precision (r2 = 0.801; residual mean square RMS = 0.083). Body mass and water temperature contributed most to the explanatory power of the model. However, as with all least squares models using nonlinearly transformed data, back-transformation to natural scale introduces a bias in the model predictions, i.e., an underestimation of P/B (and P). When estimating production of assemblages of populations by adding up population estimates, accuracy decreases but precision increases with the number of populations in the assemblage.

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Microzooplankton (the 20 to 200 µm size class of zooplankton) is recognised as an important part of marine pelagic ecosystems. In terms of biomass and abundance pelagic ciliates are one of the important groups of organism in microzooplankton. However, their rates - grazing and growth - , feeding behaviour and prey preferences are poorly known and understood. A set of data was assembled in order to derive a better understanding of pelagic ciliates rates, in response to parameters such as prey concentration, prey type (size and species), temperature and their own size. With these objectives, literature was searched for laboratory experiments with information on one or more of these parameters effect studied. The criteria for selection and inclusion in the database included: (i) controlled laboratory experiment with a known ciliates feeding on a known prey; (ii) presence of ancillary information about experimental conditions, used organisms - cell volume, cell dimensions, and carbon content. Rates and ancillary information were measured in units that meet the experimenter need, creating a need to harmonize the data units after collection. In addition different units can link to different mechanisms (carbon to nutritive quality of the prey, volume to size limits). As a result, grazing rates are thus available as pg C/(ciliate*h), µm**3/(ciliate*h) and prey cell/(ciliate*h); clearance rate was calculated if not given and growth rate is expressed as the growth rate per day.

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Aims: Familial hypercholesterolemia (FH) is an autosomal dominant disorder with increased cardiovascular risk, caused by mutations in LDLR, APOB and PCSK 9 genes. Although it is described that over 1700 variants have been found, none of the existing databases are completely updated. The aim of this work is to construct a FH database in order to provide a unique source of verified information about variants associated with FH for a more accurate genetic diagnosis.

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Mode of access: Internet.

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Mode of access: Internet.

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National Highway Traffic Safety Administration, Office of Research and Development, Washington, D.C.

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National Highway Traffic Safety Administration, Office of Research and Development, Washington, D.C.

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National Highway Traffic Safety Administration, Office of Research and Development, Washington, D.C.

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National Highway Traffic Safety Administration, Office of Research and Development, Washington, D.C.

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Transportation Systems Center, Cambridge, Mass.