877 resultados para Q Science


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This study determined annual and monthly fluctuations in concentration of 20 fungal genera. The selection of taxa was made based upon their high frequency in the air as well as their well-known allergenic properties. Air samples were collected using a spore trap of Hirst design at an urban site where the trap continuously worked throughout a 5-year survey. Weather data were acquired from a meteorological station co-located with the air sampler. Influence of several meteorological parameters was then examined to reveal species–environment interactions and the potential location of fungal spore sources within the urban area. The maximum monthly sum of mean daily spore concentration varied between genera, and the earliest peaks were recorded for Pleospora sp. in April and Ustilago sp. in June. However, the majority of investigated spore types occurred in the greatest concentrations between August and September. Out of the 20 studied taxa, the most dominant genus was Cladosporium sp., which exceeded an allergenic threshold of 3000 s m-3 40 times during very rainy years and twice as much during dry years. A Spearman’s rank test showed that statistically significant (p B 0.05) relationships between spore concentration and weather parameters were mainly rs B 0.50. Potential sources of spores at Worcester were likely to be localised outside the city area.

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Background: The invasive alien species Ambrosia artemisiifolia (common or short ragweed) is increasing its range in Europe. In the UK and the Netherlands airborne concentrations of Ambrosia pollen are usually low. However, more than 30 Ambrosia pollen grains per cubic metre of air (above the level capable to trigger allergic symptoms) were recorded in Leicester (UK) and Leiden (NL) on 4 and 5 September 2014. Objective: The aims of this study were to determine whether the highly allergenic Ambrosia pollen recorded during the episode could be the result of long distance transport, to identify the potential sources of these pollen grains and describe the conditions that facilitated this possible long distance transport. Methods: Airborne Ambrosia pollen data were collected at 10 sites in Europe. Back trajectory and atmospheric dispersion calculations were performed using HYSPLIT_4. Results: Back trajectories calculated at Leicester and Leiden show that higher altitude air masses (1500m) originated from source areas on the Pannonian Plain and Ukraine. During the episode, air masses veered to the west and passed over the Rhône Valley. Dispersion calculations showed that the atmospheric conditions were suitable for Ambrosia pollen released from the Pannonian Plain and the Rhône Valley to reach the higher levels and enter the air stream moving to Northwest Europe where they were deposited at ground level and recorded by monitoring sites. Conclusions: The study indicates that the Ambrosia pollen grains recorded during the episode in Leicester and Leiden were probably not produced by local sources, but transported long distances from potential source regions in East Europe, i.e. the Pannonian Plain and Ukraine, as well as the Rhône Valley in France.

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Acknowledgements This work was supported by the UK Energy Research Centre Phase 2, under its Energy and Environment theme Grant Number NE/J005924/1 and NE/G007748/1. Open Access funded by Natural Environment Research Council

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The authors thank M. C. Romano, I. Stansfield, L. Ciandrini, A. Kort, and M. Rehberg for helpful discussions. This work was funded by BBSRC grants BB/F00513/X1 and BB/G010722, and the Scottish Universities Life Science Alliance (SULSA).

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The authors thank M. C. Romano, I. Stansfield, L. Ciandrini, A. Kort, and M. Rehberg for helpful discussions. This work was funded by BBSRC grants BB/F00513/X1 and BB/G010722, and the Scottish Universities Life Science Alliance (SULSA).

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Acknowledgments Y.Y. acknowledges the financial support from “973” Program (2012CB721006) and National Natural Science Foundation of China (31570033). R.E., K.K., H.D., and M.J. acknowledge the financial support of the Leverhulme Trust-Royal Society Africa Award (AA090088).

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Purpose Drafting in cycling influences collective behaviour of pelotons. Whilst evidence for collective behaviour in competitive running events exists, it is not clear if this results from energetic savings conferred by drafting. This study modelled the effects of drafting on behavior in elite 10,000 m runners. Methods Using performance data from a men’s elite 10,000 m track running event, computer simulations were constructed using Netlogo 5.1 to test the effects of three different drafting quantities on collective behaviour: no drafting, drafting to 3m behind with up to ~8% energy savings (a realistic running draft); and drafting up to 3m behind with up to 38% energy savings (a realistic cycling draft). Three measures of collective behaviour were analysed in each condition; mean speed, mean group stretch (distance between first and last placed runner), and Runner Convergence Ratio (RCR) which represents the degree of drafting benefit obtained by the follower in a pair of coupled runners. Results Mean speeds were 6.32±0.28m.s-1, 5.57±0.18 m.s-1, and 5.51±0.13 m.s-1 in the cycling draft, runner draft, and no draft conditions respectively (all P<0.001). RCR was lower in the cycling draft condition, but did not differ between the other two. Mean stretch did not differ between conditions. Conclusions Collective behaviours observed in running events cannot be fully explained through energetic savings conferred by realistic drafting benefits. They may therefore result from other, possibly psychological, processes. The benefits or otherwise of engaging in such behavior are, as yet, unclear.

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The numbers of water-borne oomycete propagules in outdoor reservoirs used in horticultural nurseries within the UK are investigated in this study. Water samples were recovered from 11 different horticultural nurseries in the southern UK during Jan-May in two ‘cool’ years (2010.and 2013; winter temperatures 2.0 and 0.4oC below UK Met Office 30 year winter average respectively) and two ‘warm’ years (2008 and 2012; winter temperatures 1.2 and 0.9oC above UK Met Office 30 year winter average respectively). Samples were analysed for total number of oomycete colony forming units (CFU), predominantly members of the families Saprolegniaceae and Pythiaceae, and these were combined to give monthly mean counts. The numbers of CFU were investigated with respect to prevailing climate in the region: mean monthly air temperatures calculated by using daily observations from the nearest climatological station. The investigations show that the number of CFU during spring can be explained by a linear first-order equation and a statistically significant r2 value of 0.66 with the simple relationship: [CFU] = a(T-Tb )-b, where a is the rate of inoculum development with temperature T, and b is the baseload population at temperatures below Tb. Despite the majority of oomycete CFU detected being non-phytopathogenic members of the Saprolegniaceae, total oomycete CFU counts are still of considerable value as indicators of irrigation water treatment efficacy and cleanliness of storage tanks. The presence/absence of Pythium spp. was also determined for all samples tested, and Pythium CFU were found to be present in the majority, the exceptions all being particularly cold months (January and February 2010 and January 2008). A simple scenario study (+2 deg C) suggests that abundance of water-borne oomycetes during spring could be affected by increased temperatures due to climate change.

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Surface flow types (SFT) are advocated as ecologically relevant hydraulic units, often mapped visually from the bankside to characterise rapidly the physical habitat of rivers. SFT mapping is simple, non-invasive and cost-efficient. However, it is also qualitative, subjective and plagued by difficulties in recording accurately the spatial extent of SFT units. Quantitative validation of the underlying physical habitat parameters is often lacking, and does not consistently differentiate between SFTs. Here, we investigate explicitly the accuracy, reliability and statistical separability of traditionally mapped SFTs as indicators of physical habitat, using independent, hydraulic and topographic data collected during three surveys of a c. 50m reach of the River Arrow, Warwickshire, England. We also explore the potential of a novel remote sensing approach, comprising a small unmanned aerial system (sUAS) and Structure-from-Motion photogrammetry (SfM), as an alternative method of physical habitat characterisation. Our key findings indicate that SFT mapping accuracy is highly variable, with overall mapping accuracy not exceeding 74%. Results from analysis of similarity (ANOSIM) tests found that strong differences did not exist between all SFT pairs. This leads us to question the suitability of SFTs for characterising physical habitat for river science and management applications. In contrast, the sUAS-SfM approach provided high resolution, spatially continuous, spatially explicit, quantitative measurements of water depth and point cloud roughness at the microscale (spatial scales ≤1m). Such data are acquired rapidly, inexpensively, and provide new opportunities for examining the heterogeneity of physical habitat over a range of spatial and temporal scales. Whilst continued refinement of the sUAS-SfM approach is required, we propose that this method offers an opportunity to move away from broad, mesoscale classifications of physical habitat (spatial scales 10-100m), and towards continuous, quantitative measurements of the continuum of hydraulic and geomorphic conditions which actually exists at the microscale.

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Mathematical models are increasingly used in environmental science thus increasing the importance of uncertainty and sensitivity analyses. In the present study, an iterative parameter estimation and identifiability analysis methodology is applied to an atmospheric model – the Operational Street Pollution Model (OSPMr). To assess the predictive validity of the model, the data is split into an estimation and a prediction data set using two data splitting approaches and data preparation techniques (clustering and outlier detection) are analysed. The sensitivity analysis, being part of the identifiability analysis, showed that some model parameters were significantly more sensitive than others. The application of the determined optimal parameter values was shown to succesfully equilibrate the model biases among the individual streets and species. It was as well shown that the frequentist approach applied for the uncertainty calculations underestimated the parameter uncertainties. The model parameter uncertainty was qualitatively assessed to be significant, and reduction strategies were identified.

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Planted meadows are increasingly used to improve the biodiversity and aesthetic amenity value of urban areas. Although many ‘pollinator-friendly’ seed mixes are available, the floral resources these provide to flower-visiting insects, and how these change through time, are largely unknown. Such data are necessary to compare the resources provided by alternative meadow seed mixes to each other and to other flowering habitats. We used quantitative surveys of over 2 million flowers to estimate the nectar and pollen resources offered by two exemplar commercial seed mixes (one annual, one perennial) and associated weeds grown as 300m2 meadows across four UK cities, sampled at six time points between May and September 2013. Nectar sugar and pollen rewards per flower varied widely across 65 species surveyed, with native British weed species (including dandelion, Taraxacum agg.) contributing the top five nectar producers and two of the top ten pollen producers. Seed mix species yielding the highest rewards per flower included Leontodon hispidus, Centaurea cyanus and C. nigra for nectar, and Papaver rhoeas, Eschscholzia californica and Malva moschata for pollen. Perennial meadows produced up to 20x more nectar and up to 6x more pollen than annual meadows, which in turn produced far more than amenity grassland controls. Perennial meadows produced resources earlier in the year than annual meadows, but both seed mixes delivered very low resource levels early in the year and these were provided almost entirely by native weeds. Pollen volume per flower is well predicted statistically by floral morphology, and nectar sugar mass and pollen volume per unit area are correlated with flower counts, raising the possibility that resource levels can be estimated for species or habitats where they cannot be measured directly. Our approach does not incorporate resource quality information (for example, pollen protein or essential amino acid content), but can easily do so when suitable data exist. Our approach should inform the design of new seed mixes to ensure continuity in floral resource availability throughout the year, and to identify suitable species to fill resource gaps in established mixes.

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The meteorological and chemical transport model WRF-Chem was implemented to forecast PM10 concentrations over Poland. WRF-Chem version 3.5 was configured with three one-way nested domains using the GFS meteorological data and the TNO MACC II emissions. The 48 hour forecasts were run for each day of the winter and summer period of 2014 and there is only a small decrease in model performance for winter with respect to forecast lead time. The model in general captures the variability in observed PM10 concentrations for most of the stations. However, for some locations and specific episodes, the model performance is poor and the results cannot yet be used by official authorities. We argue that a higher resolution sector-based emission data will be helpful for this analysis in connection with a focus on planetary boundary layer processes in WRF-Chem and their impact on the initial distribution of emissions on both time and space.

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We explored the temporal and spatial variations in airborne Alternaria spore quantitative and phenological features in Europe using 23 sites with annual time series between 3 and 15 years. The study covers seven countries and four of the main biogeographical regions in Europe. The observations were obtained with Hirst-type spore traps providing time series with daily records. Site locations extend from Spain in the south to Denmark in the north and from England in the West to Poland in the East. The study is therefore the largest assessment ever carried out for Europe concerning Alternaria. Aerobiological data were investigated for temporal and spatial patterns in their start and peak season dates and their spore indices. Moreover, the effects of climate were checked using meteorological data for the same period, using a crop growth model. We found that local climate, vegetation patterns and management of landscape are governing parameters for the overall spore concentration, while the annual variations caused by weather are of secondary importance but should not be neglected. The start of the Alternaria spore season varies by several months in Europe, but the peak of the season is more synchronised in central northern Europe in the middle of the summer, while many southern sites have peak dates either earlier or later than northern Europe. The use of a crop growth model to explain the start and peak of season suggests that such methods could be useful to describe Alternaria seasonality in areas with no available observations.

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This study provides the first spatially detailed and complete inventory of Ambrosia pollen sources in Italy – the third largest centre of ragweed in Europe. The inventory relies on a well tested top-down approach that combines local knowledge, detailed land cover, pollen observations and a digital elevation model that assumes permanent ragweed populations mainly grow below 745m. The pollen data were obtained from 92 volumetric pollen traps located throughout Italy during 2004-2013. Land cover is derived from Corine Land cover information with 100m resolution. The digital elevation model is based on the NASA shuttle radar mission with 90m resolution. The inventory is produced using a combination of ArcGIS and Python for automation and validated using cross-correlation and has a final resolution of 5km x 5km. The method includes a harmonization of the inventory with other European inventories for the Pannonian Plain, France and Austria in order to provide a coherent picture of all major ragweed sources. The results show that the mean annual pollen index varies from 0 in South Italy to 6779 in the Po Valley. The results also show that very large pollen indexes are observed in the Milan region, but this region has smaller amounts of ragweed habitats compared to other parts of the Po Valley and known ragweed areas in France and the Pannonian Plain. A significant decrease in Ambrosia pollen concentrations was recorded in 2013 by pollen monitoring stations located in the Po Valley, particularly in the Northwest of Milan. This was the same year as the appearance of the Ophraella communa leaf beetle in Northern Italy. These results suggest that ragweed habitats near to the Milan region have very high densities of Ambrosia plants compared to other known ragweed habitats in Europe. The Milan region therefore appears to contain habitats with the largest ragweed infestation in Europe, but a smaller amount of habitats is a likely cause the pollen index to be lower compared to central parts of the Pannonian Plain. A low number of densely packed habitats may have increased the impact of the Ophraella beetle and might account for the documented decrease in airborne Ambrosia pollen levels, an event that cannot be explained by meteorology alone. Further investigations that model atmospheric pollen before and after the appearance of the beetle in this part of Northern Italy are needed to assess the influence of the beetle on airborne Ambrosia pollen concentrations. Future work will focus on short distance transport episodes for stations located in the Po Valley, and long distance transport events for stations in Central Italy that exhibit peaks in daily airborne Ambrosia pollen levels.