5 resultados para Iberians -- Catalonia

em CentAUR: Central Archive University of Reading - UK


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The aim of this work was to couple a nitrogen (N) sub-model to already existent hydrological lumped (LU4-N) and semi-distributed (LU4-R-N and SD4-R-N) conceptual models, to improve our understanding of the factors and processes controlling nitrogen cycling and losses in Mediterranean catchments. The N model adopted provides a simplified conceptualization of the soil nitrogen cycle considering mineralization, nitrification, immobilization, denitrification, plant uptake, and ammonium adsorption/desorption. It also includes nitrification and denitrification in the shallow perched aquifer. We included a soil moisture threshold for all the considered soil biological processes. The results suggested that all the nitrogen processes were highly influenced by the rain episodes and that soil microbial processes occurred in pulses stimulated by soil moisture increasing after rain. Our simulation highlighted the riparian zone as a possible source of nitrate, especially after the summer drought period, but it can also act as an important sink of nitrate due to denitrification, in particular during the wettest period of the year. The riparian zone was a key element to simulate the catchment nitrate behaviour. The lumped LU4-N model (which does not include the riparian zone) could not be validated, while both the semi-distributed LU4-R-N and SD4-R-N model (which include the riparian zone) gave satisfactory results for the calibration process and acceptable results for the temporal validation process.

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Modelling spatial covariance is an essential part of all geostatistical methods. Traditionally, parametric semivariogram models are fit from available data. More recently, it has been suggested to use nonparametric correlograms obtained from spatially complete data fields. Here, both estimation techniques are compared. Nonparametric correlograms are shown to have a substantial negative bias. Nonetheless, when combined with the sample variance of the spatial field under consideration, they yield an estimate of the semivariogram that is unbiased for small lag distances. This justifies the use of this estimation technique in geostatistical applications. Various formulations of geostatistical combination (Kriging) methods are used here for the construction of hourly precipitation grids for Switzerland based on data from a sparse realtime network of raingauges and from a spatially complete radar composite. Two variants of Ordinary Kriging (OK) are used to interpolate the sparse gauge observations. In both OK variants, the radar data are only used to determine the semivariogram model. One variant relies on a traditional parametric semivariogram estimate, whereas the other variant uses the nonparametric correlogram. The variants are tested for three cases and the impact of the semivariogram model on the Kriging prediction is illustrated. For the three test cases, the method using nonparametric correlograms performs equally well or better than the traditional method, and at the same time offers great practical advantages. Furthermore, two variants of Kriging with external drift (KED) are tested, both of which use the radar data to estimate nonparametric correlograms, and as the external drift variable. The first KED variant has been used previously for geostatistical radar-raingauge merging in Catalonia (Spain). The second variant is newly proposed here and is an extension of the first. Both variants are evaluated for the three test cases as well as an extended evaluation period. It is found that both methods yield merged fields of better quality than the original radar field or fields obtained by OK of gauge data. The newly suggested KED formulation is shown to be beneficial, in particular in mountainous regions where the quality of the Swiss radar composite is comparatively low. An analysis of the Kriging variances shows that none of the methods tested here provides a satisfactory uncertainty estimate. A suitable variable transformation is expected to improve this.

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In this EUDO CITIZENSHIP Forum Debate, several authors consider the interrelations between eligibility criteria for participation in independence referendum (that may result in the creation of a new independent state) and the determination of putative citizenship ab initio (on day one) of such a state. The kick-off contribution argues for resemblance of an independence referendum franchise and of the initial determination of the citizenry, critically appraising the incongruence between the franchise for the 18 September 2014 Scottish independence referendum, and the blueprint for Scottish citizenship ab initio put forward by the Scottish Government in its 'Scotland's Future' White Paper. Contributors to this debate come from divergent disciplines (law, political science, sociology, philosophy). They reflect on and contest the above claims, both generally and in relation to regional settings including (in addition to Scotland) Catalonia/Spain, Flanders/Belgium, Quebec/Canada, Post-Yugoslavia and Puerto-Rico/USA.

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The variability of populations over time is positively associated with their risk of local extinction. Previous work has shown that populations at the high-latitude boundary of species’ ranges show higher inter-annual variability, consistent with increased sensitivity and exposure to adverse climatic conditions. However, patterns of population variability at both high- and low-latitude species range boundaries have not yet been concurrently examined. Here, we assess the inter-annual population variability of 28 butterfly species between 1994 and 2009 at 351 and 18 sites in the United Kingdom and Catalonia, Spain, respectively. Local population variability is examined with respect to the position of the species’ bioclimatic envelopes (i.e. whether the population falls within areas of the ‘core’ climatic suitability or is a climatically ‘marginal’ population), and in relation to local landscape heterogeneity, which may influence these range location – population dynamic relationships. We found that butterfly species consistently show latitudinal gradients in population variability, with increased variability in the more northerly UK. This pattern is even more marked for southerly distributed species with ‘marginal’ climatic suitability in the UK but ‘core’ climatic suitability in Catalonia. In addition, local landscape heterogeneity did influence these range location – population dynamic relationships. Habitat heterogeneity was associated with dampened population dynamics, especially for populations in the UK. Our results suggest that promoting habitat heterogeneity may promote the persistence of populations at high-latitude range boundaries, which may potentially aid northwards expansion under climate warming. We did not find evidence that population variability increases towards southern range boundaries. Sample sizes for this region were low, but there was tentative evidence, in line with previous ecological theory, that local landscape heterogeneity may promote persistence in these retracting low-latitude range boundary populations.