957 resultados para Schreuder, Hans T.: Sampling methods for multiresource forest inventory


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Captan and folpet are two fungicides largely used in agriculture, but biomonitoring data are mostly limited to measurements of captan metabolite concentrations in spot urine samples of workers, which complicate interpretation of results in terms of internal dose estimation, daily variations according to tasks performed, and most plausible routes of exposure. This study aimed at performing repeated biological measurements of exposure to captan and folpet in field workers (i) to better assess internal dose along with main routes-of-entry according to tasks and (ii) to establish most appropriate sampling and analysis strategies. The detailed urinary excretion time courses of specific and non-specific biomarkers of exposure to captan and folpet were established in tree farmers (n = 2) and grape growers (n = 3) over a typical workweek (seven consecutive days), including spraying and harvest activities. The impact of the expression of urinary measurements [excretion rate values adjusted or not for creatinine or cumulative amounts over given time periods (8, 12, and 24 h)] was evaluated. Absorbed doses and main routes-of-entry were then estimated from the 24-h cumulative urinary amounts through the use of a kinetic model. The time courses showed that exposure levels were higher during spraying than harvest activities. Model simulations also suggest a limited absorption in the studied workers and an exposure mostly through the dermal route. It further pointed out the advantage of expressing biomarker values in terms of body weight-adjusted amounts in repeated 24-h urine collections as compared to concentrations or excretion rates in spot samples, without the necessity for creatinine corrections.

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Hematocrit (Hct) is one of the most critical issues associated with the bioanalytical methods used for dried blood spot (DBS) sample analysis. Because Hct determines the viscosity of blood, it may affect the spreading of blood onto the filter paper. Hence, accurate quantitative data can only be obtained if the size of the paper filter extracted contains a fixed blood volume. We describe for the first time a microfluidic-based sampling procedure to enable accurate blood volume collection on commercially available DBS cards. The system allows the collection of a controlled volume of blood (e.g., 5 or 10 μL) within several seconds. Reproducibility of the sampling volume was examined in vivo on capillary blood by quantifying caffeine and paraxanthine on 5 different extracted DBS spots at two different time points and in vitro with a test compound, Mavoglurant, on 10 different spots at two Hct levels. Entire spots were extracted. In addition, the accuracy and precision (n = 3) data for the Mavoglurant quantitation in blood with Hct levels between 26% and 62% were evaluated. The interspot precision data were below 9.0%, which was equivalent to that of a manually spotted volume with a pipet. No Hct effect was observed in the quantitative results obtained for Hct levels from 26% to 62%. These data indicate that our microfluidic-based sampling procedure is accurate and precise and that the analysis of Mavoglurant is not affected by the Hct values. This provides a simple procedure for DBS sampling with a fixed volume of capillary blood, which could eliminate the recurrent Hct issue linked to DBS sample analysis.

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OBJECTIVE: Accuracy studies of Patient Safety Indicators (PSIs) are critical but limited by the large samples required due to low occurrence of most events. We tested a sampling design based on test results (verification-biased sampling [VBS]) that minimizes the number of subjects to be verified. METHODS: We considered 3 real PSIs, whose rates were calculated using 3 years of discharge data from a university hospital and a hypothetical screen of very rare events. Sample size estimates, based on the expected sensitivity and precision, were compared across 4 study designs: random and VBS, with and without constraints on the size of the population to be screened. RESULTS: Over sensitivities ranging from 0.3 to 0.7 and PSI prevalence levels ranging from 0.02 to 0.2, the optimal VBS strategy makes it possible to reduce sample size by up to 60% in comparison with simple random sampling. For PSI prevalence levels below 1%, the minimal sample size required was still over 5000. CONCLUSIONS: Verification-biased sampling permits substantial savings in the required sample size for PSI validation studies. However, sample sizes still need to be very large for many of the rarer PSIs.

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OBJECTIVE: The objective of our study was to investigate the impact of radial k-space sampling and steady-state free precession (SSFP) imaging on image quality in MRI of coronary vessel walls. SUBJECTS AND METHODS: Eleven subjects were examined on a 1.5-T MR system using three high-resolution navigator-gated and cardiac-triggered 3D black blood sequences (cartesian gradient-echo [GRE], radial GRE, and radial SSFP) with identical spatial resolution (0.9 x 0.9 x 2.4 mm3). The signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), vessel wall sharpness, and motion artifacts were analyzed. RESULTS: The mean SNR and CNR of the coronary vessel wall were improved using radial imaging and were best using radial k-space sampling combined with SSFP imaging. Vessel border definition was similar for all three sequences. Radial k-space sampling was found to be less sensitive to motion. Consistently good image quality was seen with the radial GRE sequence. CONCLUSION: Radial k-space sampling in MRI of coronary vessel walls resulted in fewer motion artifacts and improved SNR and CNR. The use of SSFP imaging, however, did not result in improved coronary vessel wall visualization.

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Identifying the geographic distribution of populations is a basic, yet crucial step in many fundamental and applied ecological projects, as it provides key information on which many subsequent analyses depend. However, this task is often costly and time consuming, especially where rare species are concerned and where most sampling designs generally prove inefficient. At the same time, rare species are those for which distribution data are most needed for their conservation to be effective. To enhance fieldwork sampling, model-based sampling (MBS) uses predictions from species distribution models: when looking for the species in areas of high habitat suitability, chances should be higher to find them. We thoroughly tested the efficiency of MBS by conducting an important survey in the Swiss Alps, assessing the detection rate of three rare and five common plant species. For each species, habitat suitability maps were produced following an ensemble modeling framework combining two spatial resolutions and two modeling techniques. We tested the efficiency of MBS and the accuracy of our models by sampling 240 sites in the field (30 sitesx8 species). Across all species, the MBS approach proved to be effective. In particular, the MBS design strictly led to the discovery of six sites of presence of one rare plant, increasing chances to find this species from 0 to 50%. For common species, MBS doubled the new population discovery rates as compared to random sampling. Habitat suitability maps coming from the combination of four individual modeling methods predicted well the species' distribution and more accurately than the individual models. As a conclusion, using MBS for fieldwork could efficiently help in increasing our knowledge of rare species distribution. More generally, we recommend using habitat suitability models to support conservation plans.

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This paper investigates the use of ensemble of predictors in order to improve the performance of spatial prediction methods. Support vector regression (SVR), a popular method from the field of statistical machine learning, is used. Several instances of SVR are combined using different data sampling schemes (bagging and boosting). Bagging shows good performance, and proves to be more computationally efficient than training a single SVR model while reducing error. Boosting, however, does not improve results on this specific problem.

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Because data on rare species usually are sparse, it is important to have efficient ways to sample additional data. Traditional sampling approaches are of limited value for rare species because a very large proportion of randomly chosen sampling sites are unlikely to shelter the species. For these species, spatial predictions from niche-based distribution models can be used to stratify the sampling and increase sampling efficiency. New data sampled are then used to improve the initial model. Applying this approach repeatedly is an adaptive process that may allow increasing the number of new occurrences found. We illustrate the approach with a case study of a rare and endangered plant species in Switzerland and a simulation experiment. Our field survey confirmed that the method helps in the discovery of new populations of the target species in remote areas where the predicted habitat suitability is high. In our simulations the model-based approach provided a significant improvement (by a factor of 1.8 to 4 times, depending on the measure) over simple random sampling. In terms of cost this approach may save up to 70% of the time spent in the field.

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The objective of this work was to determine, through the use of the bearing capacity model, the traffic effects of the forest harvest operations on the preconsolidation pressure (sigmap), during one cycle of the eucalyptus plantation. The work was conducted using undisturbed soil samples, collected at the surface of the A horizon and in the top of the B horizon of an Udult (PA), Aquox (FX) and Udox (LA) soils. The undisturbed soil samples were used in the uniaxial compression tests. The soil sampling was done before and after the harvest operations. The operations performed with the Forwarder caused greater soil compaction than the ones done with the Feller Büncher and Harvester. The percentage of soil samples, in the region with additional soil compaction, indicated that the Udult was the soil class more susceptible to soil compaction, followed by the Aquox and Udox. Despite Udult is the more susceptible to soil compaction, the regeneration of the soil structure in this soil class was more efficient than in Aquox. The percentage of soil samples with sigmap values in the region with additional soil compaction in 1996, 1998 and 2004, after harvest operations, indicated a sustainable forest exploration in this period.

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The objective of this work was to assess the effects of a forest-field ecotone on earthworm assemblages. Five sites (blocks) differing in the type of crop rotation used in the field were studied in Central Bohemia, Czech Republic. In each block, sampling was carried out in seven parallel rows perpendicular to a transect from a forest (oak or oak-pine) to the centre of a field, both in spring and autumn 2001-2003. Individual rows were located in the forest (5 m from the edge), in the forest edge, and in the field (at 5, 10, 25, 50 and 100 m distances from the forest edge). The density and biomass of earthworms were lowest in the forest, increased markedly in the forest edge, decreased again at 5 or 10 m distance from the forest edge and then continuously increased along the distance to the field boundary. The highest number of species was found in the forest edge and in the field boundary. Individual species differed in their distribution along the transect. Both density and biomass of earthworms were correlated with distance from forest edge, soil organic matter content, soil porosity, and water infiltration rate.

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The objective of this work was to evaluate an inventory method efficiency for ants. We used subsamples collected in 24 transects of 100 m, distributed in 6 plots of 600 ha each in primary forest, as part of a long-term project. Ten litter subsamples were extracted per transect using Winkler extractors. Ants were identified to genus level, and Crematogaster, Gnamptogenys and Pachycondyla genera to species/morphospecies level. To evaluate the consequences of reduced sampling on the retention of ecological information, we estimated the lowest number of subsamples needed to detect the effects of environmental variables. Multidimensional scaling (MDS) was used to generate dissimilarity matrices, and Mantel correlations between each reduced-sampling effort and maximum effort were used as an index of how much information was maintained and could still be used in multivariate analyses. Lower p-values was observed on the effect of soil pH in the community of genera, and on the effect of the litter volume for the community of Crematogaster. The trend was still detectable in the analysis based on reduced-sampling. The number of subsamples can be reduced, and the cost-efficiency of the protocol can be improved with little loss of information.

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The objective of this work was to assess the soil oribatid mite communities in four sites of the Upper Paraná Bosque Atlántico, in the Iguazú National Park, Argentina and in surrounding areas: bamboo forest, palm forest and two mixed forests. A comparison between each pair of sites, based on the presence-absence of oribatid species, was performed using Jaccard's index. This is the first systematic sampling of oribatid mites in this area. A total of 56 genera and 96 oribatid species were found, 25 and 49 of them, respectively, are new citation for Argentina. The highest similarity was found between mixed forests. Almost 68% and 34% of the genera were cited for similar biotopes in Brazil and Paraguay, respectively.

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The objective of this work was to determine seasonal variation and vertical distribution of the soil rotifer assemblage in a climax beech forest in South Bohemia. During 2005, soil rotifer was investigated to the species level. Soil samples of 10 cm² and 10 cm in depth were divided into five layers, which were processed separately. Thirty one rotifer species were identified during the investigation. Dominant species significantly changed throughout the seasons. The most abundant species were Encentrum arvicola and Wierzejskiella vagneri among the monogononts, and Adineta steineri, Ceratotrocha cornigera, Habrotrocha filum, Habrotrocha ligula, Macrotrachela plicata, Mniobia tentans, Mniobia incrassata and Mniobia granulosa among the bdelloids. Mean Shannon diversity index varied from 1.99 to 2.63. Total rotifer abundance varied from 212±63 to 513±127 10³ individuals m-2 along the year, with the highest numbers found in May, and the lowest in July. The great part of the community was concentrated in the upper (fresh litter) and second (partially decomposed litter) layers and significantly decreased in the soil vertical profile on all sampling dates. The highest rotifer density of 43 individuals g-1 was found in the upper layer in May.

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The objective of this work was to evaluate the use of a low-cost trap to capture Cerambycidae in different seasons in planted forests in Brazil. Thirty polyethylene-terephthalate trap bottles per hectare were used, disposed at every 50 m. The traps were red painted and contained glass flasks with a mixture of ethanol, methanol and benzaldehyde. There were soap and water at the trap bottom. The traps were checked biweekly for beetle presence. Sampling time required one minute per sample, and traps were easy to use. Total sampling cost, including materials and labor, was US$ 13.46 per sample. Six Cerambycidae species were captured along the dry and rainy seasons.

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The objective of this work was to test methods for pre-harvest sprouting assessment in wheat cultivars. Fourteen wheat cultivars were grown in Londrina and Ponta Grossa municipalities, Paraná state, Brazil. They were sampled at 10 and 17 days after physiological maturity and evaluated using the methods of germination by rainfall simulation (in a greenhouse), in-ear grain sprouting, and grains removed from the ears. The in-ear grain sprouting method allowed the differentiation of cultivars, but showed different resistance levels from the available description of cultivars. The sprouting of grain removed from the ears did not allow a reliable distinction of data on germination in any harvest date or location. The method of rainfall simulation is the most suitable for the assessment of cultivars as to pre-harvest sprouting, regardless of the sampling date and evaluated location.