870 resultados para Time varying coefficients


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Ocean Drilling Program (ODP) Hole 735B was drilled to a depth of 1.5 km in a tectonic window of gabbroic lower oceanic crust created at the Southwest Indian Ridge. The gabbros have a very stable natural remanent magnetization (NRM) of reversed polarity with most unblocking temperatures slightly below the Curie temperature of magnetite. The NRM includes a drilling-induced overprint but its intensity decays strongly towards the interior of the drill core. The demagnetization data yield no or only a very small secondary magnetization component acquired during the present Brunhes chron or an earlier normal chron, suggesting cooling through most of the blocking temperature range during chron C5r and a strong resistance against the acquisition of thermoviscous magnetization. A novel furnace has been designed to measure magnetizations and their time dependences at high temperatures (up to 580 deg C) inside a commercial SQUID magnetometer. Magnetic viscosity experiments have been conducted on the gabbros at temperatures up to 550 deg C to determine the time and temperature stability of remanent magnetization. Viscosities are generally small and increase little with temperature below the main blocking temperature, where the increase becomes almost an order of magnitude. Extrapolations to geological times infer viscous acquisitions that would be 5-25% of a thermoremanence in 100 kyr and at temperatures of 200-500 deg C. At ocean bottom temperature the predicted magnetization of one sample acquired in the present Brunhes chron should be 10% of the NRM. However, this is not recognized during NRM demagnetization and partial thermoremanent magnetization (pTRM) acquisitions at 250 deg C are also much smaller than predicted. It thus appears that the NRMs are generally magnetically harder than magnetizations acquired after heating to 570 deg C in the laboratory. Susceptibility changes during heating are small (<5%) indicating a seemingly stable magneto-mineralogy, but conspicuous minima occur after heating to 520 deg C. Also, quasi paleointensity experiments reveal characteristic patterns in the NRM/pTRM ratios and also large increases in pTRM capacity after heating to 570 deg C. Moreover, anhysteretic remanent magnetization acquisition in the low field range (<=10 mT) is strongly enhanced after heating by factors up to three. The alteration of the magneto-mineralogy is interpreted to result from the annealing of defects in magnetite that originate from tectonically induced strain. The oceanic gabbros of Hole 735B are thus ideal source layer material for marine magnetic anomalies, and secondary thermoviscous acquisition, as a possible cause for anomalous skewness, is essentially absent.

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This data set comprises a time series of aboveground community plant biomass (Sown plant community, Weed plant community, Dead plant material, and Unidentified plant material; all measured in biomass as dry weight) and species-specific biomass from the sown species of the dominance experiment plots of a large grassland biodiversity experiment (the Jena Experiment; see further details below). In the dominance experiment, 206 grassland plots of 3.5 x 3.5 m were established from a pool of 9 species that can be dominant in semi-natural grassland communities of the study region. In May 2002, varying numbers of plant species from this species pool were sown into the plots to create a gradient of plant species richness (1, 2, 3, 4, 6, and 9 species). Plots were maintained by bi-annual weeding and mowing. Aboveground community biomass was harvested twice a year, generally in May and August (in 2002 only once in September) on all experimental plots of the dominance experiment. This was done by clipping the vegetation at 3 cm above ground in two rectangles of 0.2 x 0.5 m per experimental plot. The location of these rectangles was assigned by random selection of new coordinates every year within the central area of the plots (excluding an outer edge of 50cm). The positions of the rectangles within plots were identical for all plots. The harvested biomass was sorted into categories: individual species for the sown plant species, weed plant species (species not sown at the particular plot), detached dead plant material, and remaining plant material that could not be assigned to any category. Biomass was dried to constant weight (70°C, >= 48 h) and weighed. Sown plant community biomass was calculated as the sum of the biomass of the individual sown species. The mean of both samples per plot and the individual measurements are provided in the data file. Overall, analyses of the community biomass data have identified species richness and the presence of particular species as an important driver of a positive biodiversity-productivity relationship.

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ZooScan with ZooProcess and Plankton Identifier (PkID) software is an integrated analysis system for acquisition and classification of digital zooplankton images from preserved zooplankton samples. Zooplankton samples are digitized by the ZooScan and processed by ZooProcess and PkID in order to detect, enumerate, measure and classify the digitized objects. Here we present a semi-automatic approach that entails automated classification of images followed by manual validation, which allows rapid and accurate classification of zooplankton and abiotic objects. We demonstrate this approach with a biweekly zooplankton time series from the Bay of Villefranche-sur-mer, France. The classification approach proposed here provides a practical compromise between a fully automatic method with varying degrees of bias and a manual but accurate classification of zooplankton. We also evaluate the appropriate number of images to include in digital learning sets and compare the accuracy of six classification algorithms. We evaluate the accuracy of the ZooScan for automated measurements of body size and present relationships between machine measures of size and C and N content of selected zooplankton taxa. We demonstrate that the ZooScan system can produce useful measures of zooplankton abundance, biomass and size spectra, for a variety of ecological studies.

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In spring, Arctic coastal fast ice is inhabited by high densities of sea ice algae and, among other fauna, juveniles of benthic polychaetes. This paper investigates the hypothesis that growth rates of juveniles of the common sympagic polychaete, Scolelepis squamata (Polychaeta: Spionidae), are significantly faster at sea ice algal bloom concentrations compared to concurrent phytoplankton concentrations. Juvenile S. squamata from fast ice off Barrow, Alaska, were fed with different algal concentrations at 0 and 5 °C, simulating ambient high sea ice algal concentrations, concurrent low phytoplankton concentrations, and an intermediate concentration. Growth rates, calculated using a simple linear regression equation, were significantly higher (up to 115 times) at the highest algal concentration compared to the lowest. At the highest algal concentration, juveniles grew faster at 5 °C compared to those feeding at 0 °C with a Q10 of 2.0. We conclude that highly concentrated sea ice algae can sustain faster growth rates of polychaete juveniles compared to the less dense spring phytoplankton concentrations. The earlier melt of Arctic sea ice predicted with climate change might cause a mismatch between occurrence of polychaete juveniles and food availability in the near future. Our data indicate that this reduction in food availability might counteract any faster growth of a pelagic juvenile stage based on forecasted increased water temperatures.

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This data set contains four time series of particulate and dissolved soil nitrogen measurements from the main experiment plots of a large grassland biodiversity experiment (the Jena Experiment; see further details below). In the main experiment, 82 grassland plots of 20 x 20 m were established from a pool of 60 species belonging to four functional groups (grasses, legumes, tall and small herbs). In May 2002, varying numbers of plant species from this species pool were sown into the plots to create a gradient of plant species richness (1, 2, 4, 8, 16 and 60 species) and functional richness (1, 2, 3, 4 functional groups). Plots were maintained by bi-annual weeding and mowing. 1. Total nitrogen from solid phase: Stratified soil sampling was performed every two years since before sowing in April 2002 and was repeated in April 2004, 2006 and 2008 to a depth of 30 cm segmented to a depth resolution of 5 cm giving six depth subsamples per core. In 2002 five samples per plot were taken and analyzed independently. Averaged values per depth layer are reported. In later years, three samples per plot were taken, pooled in the field, and measured as a combined sample. Sampling locations were less than 30 cm apart from sampling locations in other years. All soil samples were passed through a sieve with a mesh size of 2 mm in 2002. In later years samples were further sieved to 1 mm. No additional mineral particles were removed by this procedure. Total nitrogen concentration was analyzed on ball-milled subsamples (time 4 min, frequency 30 s-1) by an elemental analyzer at 1150°C (Elementaranalysator vario Max CN; Elementar Analysensysteme GmbH, Hanau, Germany). 2. Total nitrogen from solid phase (high intensity sampling): In block 2 of the Jena Experiment, soil samples were taken to a depth of 1m (segmented to a depth resolution of 5 cm giving 20 depth subsamples per core) with three replicates per block ever 5 years starting before sowing in April 2002. Samples were processed as for the more frequent sampling but were always analyzed independently and never pooled. 3. Mineral nitrogen from KCl extractions: Five soil cores (diameter 0.01 m) were taken at a depth of 0 to 0.15 m (and between 2002 and 2004 also at a depth of 0.15 to 0.3 m) of the mineral soil from each of the experimental plots at various times over the years. In addition also plots of the management experiment, that altered mowing frequency and fertilized subplots (see further details below) were sampled in some later years. Samples of the soil cores per plot (subplots in case of the management experiment) were pooled during each sampling campaign. NO3-N and NH4-N concentrations were determined by extraction of soil samples with 1 M KCl solution and were measured in the soil extract with a Continuous Flow Analyzer (CFA, 2003-2005: Skalar, Breda, Netherlands; 2006-2007: AutoAnalyzer, Seal, Burgess Hill, United Kingdom). 4. Dissolved nitrogen in soil solution: Glass suction plates with a diameter of 12 cm, 1 cm thickness and a pore size of 1-1.6 µm (UMS GmbH, Munich, Germany) were installed in April 2002 in depths of 10, 20, 30 and 60 cm to collect soil solution. The sampling bottles were continuously evacuated to a negative pressure between 50 and 350 mbar, such that the suction pressure was about 50 mbar above the actual soil water tension. Thus, only the soil leachate was collected. Cumulative soil solution was sampled biweekly and analyzed for nitrate (NO3-), ammonium (NH4+) and total dissolved nitrogen concentrations with a continuous flow analyzer (CFA, Skalar, Breda, The Netherlands). Nitrate was analyzed photometrically after reduction to NO2- and reaction with sulfanilamide and naphthylethylenediamine-dihydrochloride to an azo-dye. Our NO3- concentrations contained an unknown contribution of NO2- that is expected to be small. Simultaneously to the NO3- analysis, NH4+ was determined photometrically as 5-aminosalicylate after a modified Berthelot reaction. The detection limits of NO3- and NH4+ were 0.02 and 0.03 mg N L-1, respectively. Total dissolved N in soil solution was analyzed by oxidation with K2S2O8 followed by reduction to NO2- as described above for NO3-. Dissolved organic N (DON) concentrations in soil solution were calculated as the difference between TDN and the sum of mineral N (NO3- + NH4+).

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Parameters in the photosynthesis-irradiance (P-E) relationship of phytoplankton were measured at weekly to bi-weekly intervals for 20 yr at 6 stations on the Rhode River, Maryland (USA). Variability in the light-saturated photosynthetic rate, PBmax, was partitioned into interannual, seasonal, and spatial components. The seasonal component of the variance was greatest, followed by interannual and then spatial. Physiological models of PBmax based on balanced growth or photoacclimation predicted the overall mean and most of the range, but not individual observations, and failed to capture important features of the seasonal and interannual variability. PBmax correlated most strongly with temperature and the concentration of dissolved inorganic carbon (IC), with lesser correlations with chlorophyll a, diffuse attenuation coefficient, and a principal component of the species composition. In statistical models, temperature and IC correlated best with the seasonal pattern, but temperature peaked in late July, out of phase with PBmax, which peaked in September, coincident with the maximum in monthly averaged IC concentration. In contrast with the seasonal pattern, temperature did not contribute to interannual variation, which instead was governed by IC and the additional lesser correlates. Spatial variation was relatively weak and uncorrelated with ancillary measurements. The results demonstrate that both the overall distribution of PBmax and its relationship with environmental correlates may vary from year to year. Coefficients in empirical statistical models became stable after including 7 to 10 yr of data. The main correlates of PBmax are amenable to automated monitoring, so that future estimates of primary production might be made without labor-intensive incubations.