992 resultados para variable sampling interval


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While the Cluster spacecraft were located near the high-latitude magnetopause, between 10:10 and 10:40 UT on 16 January 2004, three typical flux transfer event (FTE) signatures were observed. During this interval, simultaneous and conjugated all-sky camera measurements, recorded at Yellow River Station, Svalbard, are available at 630.0 and 557.7nm that show poleward-moving auroral forms (PMAFs), consistent with magnetic reconnection at dayside magnetopause. Simultaneous FTEs seen at the magnetopause mainly move northward, but having duskward (eastward) and tailward velocity components, roughly consistent with the observed direction of motion of the PMAFs in all-sky images. Between the PMAFs meridional keograms, extracted from the all-sky images, show intervals of lower intensity aurora which migrate equatorward just before the PMAFs intensify. This is strong evidence for an equatorward eroding and poleward moving open-closed boundary (OCB) associated with a variable magnetopause reconnection rate under variable IMF conditions. From the durations of the PMAFs we infer that the evolution time of FTEs is 5-11 minutes from its origin on magnetopause to its addition to the polar cap.

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We consider boundary value problems posed on an interval [0,L] for an arbitrary linear evolution equation in one space dimension with spatial derivatives of order n. We characterize a class of such problems that admit a unique solution and are well posed in this sense. Such well-posed boundary value problems are obtained by prescribing N conditions at x=0 and n–N conditions at x=L, where N depends on n and on the sign of the highest-degree coefficient n in the dispersion relation of the equation. For the problems in this class, we give a spectrally decomposed integral representation of the solution; moreover, we show that these are the only problems that admit such a representation. These results can be used to establish the well-posedness, at least locally in time, of some physically relevant nonlinear evolution equations in one space dimension.

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1. Suction sampling is a popular method for the collection of quantitative data on grassland invertebrate populations, although there have been no detailed studies into the effectiveness of the method. 2. We investigate the effect of effort (duration and number of suction samples) and sward height on the efficiency of suction sampling of grassland beetle, true bug, planthopper and spider Populations. We also compare Suction sampling with an absolute sampling method based on the destructive removal of turfs. 3. Sampling for durations of 16 seconds was sufficient to collect 90% of all individuals and species of grassland beetles, with less time required for the true bugs, spiders and planthoppers. The number of samples required to collect 90% of the species was more variable, although in general 55 sub-samples was sufficient for all groups, except the true bugs. Increasing sward height had a negative effect on the capture efficiency of suction sampling. 4. The assemblage structure of beetles, planthoppers and spiders was independent of the sampling method (suction or absolute) used. 5. Synthesis and applications. In contrast to other sampling methods used in grassland habitats (e.g. sweep netting or pitfall trapping), suction sampling is an effective quantitative tool for the measurement of invertebrate diversity and assemblage structure providing sward height is included as a covariate. The effective sampling of beetles, true bugs, planthoppers and spiders altogether requires a minimum sampling effort of 110 sub-samples of duration of 16 seconds. Such sampling intensities can be adjusted depending on the taxa sampled, and we provide information to minimize sampling problems associated with this versatile technique. Suction sampling should remain an important component in the toolbox of experimental techniques used during both experimental and management sampling regimes within agroecosystems, grasslands or other low-lying vegetation types.

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Methodology used to measure in vitro gas production is reviewed to determine impacts of sources of variation on resultant gas production profiles (GPP). Current methods include measurement of gas production at constant pressure (e.g., use of gas tight syringes), a system that is inexpensive, but may be less sensitive than others thereby affecting its suitability in some situations. Automated systems that measure gas production at constant volume allow pressure to accumulate in the bottle, which is recorded at different times to produce a GPP, and may result in sufficiently high pressure that solubility of evolved gases in the medium is affected, thereby resulting in a recorded volume of gas that is lower than that predicted from stoichiometric calculations. Several other methods measure gas production at constant pressure and volume with either pressure transducers or sensors, and these may be manual, semi-automated or fully automated in operation. In these systems, gas is released as pressure increases, and vented gas is recorded. Agitating the medium does not consistently produce more gas with automated systems, and little or no effect of agitation was observed with manual systems. The apparatus affects GPP, but mathematical manipulation may enable effects of apparatus to be removed. The amount of substrate affects the volume of gas produced, but not rate of gas production, provided there is sufficient buffering capacity in the medium. Systems that use a very small amount of substrate are prone to experimental error in sample weighing. Effect of sample preparation on GPP has been found to be important, but further research is required to determine the optimum preparation that mimics animal chewing. Inoculum is the single largest source of variation in measuring GPP, as rumen fluid is variable and sampling schedules, diets fed to donor animals and ratios of rumen fluid/medium must be selected such that microbial activity is sufficiently high that it does not affect rate and extent of fermentation. Species of donor animal may also cause differences in GPP. End point measures can be mathematically manipulated to account for species differences, but rates of fermentation are not related. Other sources of inocula that have been used include caecal fluid (primarily for investigating hindgut fermentation in monogastrics), effluent from simulated rumen fermentation (e.g., 'Rusitec', which was as variable as rumen fluid), faeces, and frozen or freeze-dried rumen fluid (which were both less active than fresh rumen fluid). Use of mixtures of cell-free enzymes, or pure cultures of bacteria, may be a way of increasing GPP reproducibility, while reducing reliance on surgically modified animals. However, more research is required to develop these inocula. A number of media have been developed which buffer the incubation and provide relevant micro-nutrients to the microorganisms. To date, little research has been completed on relationships between the composition of the medium and measured GPP. However, comparing GPP from media either rich in N or N-free, allows assessment of contributions of N containing compounds in the sample. (c) 2005 Published by Elsevier B.V.

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The soil fauna is often a neglected group in many large-scale studies of farmland biodiversity due to difficulties in extracting organisms efficiently from the soil. This study assesses the relative efficiency of the simple and cheap sampling method of handsorting against Berlese-Tullgren funnel and Winkler apparatus extraction. Soil cores were taken from grassy arable field margins and wheat fields in Cambridgeshire, UK, and the efficiencies of the three methods in assessing the abundances and species densities of soil macroinver-tebrates were compared. Handsorting in most cases was as efficient at extracting the majority of the soil macrofauna as the Berlese-Tullgren funnel and Winkler bag methods, although it underestimated the species densities of the woodlice and adult beetles. There were no obvious biases among the three methods for the particular vegetation types sampled and no significant differences in the size distributions of the earthworms and beetles. Proportionally fewer damaged earthworms were recorded in larger (25 x 25 cm) soil cores when compared with smaller ones (15 x 15 cm). Handsorting has many benefits, including targeted extraction, minimum disturbance to the habitat and shorter sampling periods and may be the most appropriate method for studies of farmland biodiversity when a high number of soil cores need to be sampled. (C) 2008 Elsevier Masson SAS. All rights reserved.

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Bee pollinators are currently recorded with many different sampling methods. However, the relative performances of these methods have not been systematically evaluated and compared. In response to the strong need to record ongoing shifts in pollinator diversity and abundance, global and regional pollinator initiatives must adopt standardized sampling protocols when developing large-scale and long-term monitoring schemes. We systematically evaluated the performance of six sampling methods (observation plots, pan traps, standardized and variable transect walks, trap nests with reed internodes or paper tubes) that are commonly used across a wide range of geographical regions in Europe and in two habitat types (agricultural and seminatural). We focused on bees since they represent the most important pollinator group worldwide. Several characteristics of the methods were considered in order to evaluate their performance in assessing bee diversity: sample coverage, observed species richness, species richness estimators, collector biases (identified by subunit-based rarefaction curves), species composition of the samples, and the indication of overall bee species richness (estimated from combined total samples). The most efficient method in all geographical regions, in both the agricultural and seminatural habitats, was the pan trap method. It had the highest sample coverage, collected the highest number of species, showed negligible collector bias, detected similar species as the transect methods, and was the best indicator of overall bee species richness. The transect methods were also relatively efficient, but they had a significant collector bias. The observation plots showed poor performance. As trap nests are restricted to cavity-nesting bee species, they had a naturally low sample coverage. However, both trap nest types detected additional species that were not recorded by any of the other methods. For large-scale and long-term monitoring schemes with surveyors with different experience levels, we recommend pan traps as the most efficient, unbiased, and cost-effective method for sampling bee diversity. Trap nests with reed internodes could be used as a complementary sampling method to maximize the numbers of collected species. Transect walks are the principal method for detailed studies focusing on plant-pollinator associations. Moreover, they can be used in monitoring schemes after training the surveyors to standardize their collection skills.

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The jackknife method is often used for variance estimation in sample surveys but has only been developed for a limited class of sampling designs.We propose a jackknife variance estimator which is defined for any without-replacement unequal probability sampling design. We demonstrate design consistency of this estimator for a broad class of point estimators. A Monte Carlo study shows how the proposed estimator may improve on existing estimators.

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It is common practice to design a survey with a large number of strata. However, in this case the usual techniques for variance estimation can be inaccurate. This paper proposes a variance estimator for estimators of totals. The method proposed can be implemented with standard statistical packages without any specific programming, as it involves simple techniques of estimation, such as regression fitting.

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The systematic sampling (SYS) design (Madow and Madow, 1944) is widely used by statistical offices due to its simplicity and efficiency (e.g., Iachan, 1982). But it suffers from a serious defect, namely, that it is impossible to unbiasedly estimate the sampling variance (Iachan, 1982) and usual variance estimators (Yates and Grundy, 1953) are inadequate and can overestimate the variance significantly (Särndal et al., 1992). We propose a novel variance estimator which is less biased and that can be implemented with any given population order. We will justify this estimator theoretically and with a Monte Carlo simulation study.

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We show that the Hájek (Ann. Math Statist. (1964) 1491) variance estimator can be used to estimate the variance of the Horvitz–Thompson estimator when the Chao sampling scheme (Chao, Biometrika 69 (1982) 653) is implemented. This estimator is simple and can be implemented with any statistical packages. We consider a numerical and an analytic method to show that this estimator can be used. A series of simulations supports our findings.

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