3 resultados para Complex network analysis. Time varying graph mine (TVG). Slow-wave sleep (SWS). Fault tolerance

em Publishing Network for Geoscientific


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Large-scale studies of ocean biogeochemistry and carbon cycling have often partitioned the ocean into regions along lines of latitude and longitude despite the fact that spatially more complex boundaries would be closer to the true biogeography of the ocean. Herein, we define 17 open-ocean biomes classified from four observational data sets: sea surface temperature (SST), spring/summer chlorophyll a concentrations (Chl a), ice fraction, and maximum mixed layer depth (maxMLD) on a 1° × 1° grid. By considering interannual variability for each input, we create dynamic ocean biome boundaries that shift annually between 1998 and 2010. Additionally we create a core biome map, which includes only the grid cells that do not change biome assignment across the 13 years of the time-varying biomes. These biomes can be used in future studies to distinguish large-scale ocean regions based on biogeochemical function.

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Ecological network analysis (ENA) was used to study the effects of Pomatoschistus microps on energy transport through the food web, its impact on other compartments and its possible role as a keystone species in the trophic webs of an Arenicola tidal flat ecosystem and a sparse Zostera noltii bed ecosystem. Three ENA models were constructed: (a) model 1 contains data of the original food web from prior research in the investigated area by Baird et al. (2007), (b) an updated model 2 which included biomass and diet data of P. microps from recent sampling, and (c) model 3 simulating a food web without P. microps. A comparison of energy transport between the different models revealed that more energy is transported from lower trophic levels up the food chain, in the presence of P. microps (models 1 and 2) than in its absence (model 3). Calculations of the keystone index (KSi) revealed the high overall impact (measured as eps_i) of this fish species on food webs. In model 1, P. microps was assigned a low KSi in the Arenicola flat and in the sparse Z. noltii bed. Calculations in model 2 ranked P. microps first for keystoneness and eps_i in both communities, the Arenicola flat and the sparse Z. noltii bed. Taken together, our results give insight into the role of P. microps when considering a whole food web and reveal direct and indirect trophic interactions of this small-sized fish species. These results might illustrate the impact and importance of abundant, widespread species in food webs and facilitate further investigations.

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In the frame of the transnational ALPS-GPSQUAKENET project, a component of the Alpine Space Programme of the European Community Initiative Programme (CIP) INTERREG III B, the Deutsches Geodätisches Forschungsinstitut (DGFI) in Munich, Germany, installed in 2005 five continuously operating permanent GPS stations located along the northern Alps boundary in Bavaria. The main objective of the ALPS-GPSQUAKENET project was to build-up a high-performance transnational space geodetic network of Global Positioning System (GPS) receivers in the Alpine region (the so-called Geodetic Alpine Integrated Network, GAIN). Data from this network allows for studying crustal deformations in near real-time to monitor Earthquake hazard and improve natural disaster prevention. The five GPS stations operatied by DGFI are mounted on concrete pillars attached to solid rock. The names of the stations are (from west to east) Hochgrat (HGRA), Breitenberg (BREI), Fahrenberg (FAHR), Hochries (HRIE) and Wartsteinkopf (WART). The provided data series start from October 7, 2005. Data are stored with a temporal spacing of 15 seconds in daily RINEX files.