891 resultados para large spatial scale
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Mitigation of diffuse nutrient and sediment delivery to streams requires successful identification andmanagement of critical source areas within catchments. Approaches to predicting high risk areas forsediment loss have typically relied on structural drivers of connectivity and risk, with little considera-tion given to process driven water quality responses. To assess the applicability of structural metrics topredict critical source areas, geochemical tracing of land use sources was conducted in three headwateragricultural catchments in Co. Down and Co. Louth, Ireland, within a Monte Carlo framework. Outputswere applied to the inverse optimisation of a connectivity model, based on LiDAR DEM data, to assess theefficacy of land use risk weightings to predict sediment source contributions over the 18 month studyperiod in the Louth Upper, Louth Lower and Down catchments. Results of the study indicated sedimentproportions over the study period varied from 6 to 10%, 84 to 87%, 4%, and 2 to 3% for the Down Catch-ment, 79 to 85%, 9 to 17%, 1 to 3% and 2 to 3% in the Louth Upper and 2 to 3%, 79 to 85%, 10 to 17%and 2 to 3% in the Louth Lower for arable, channel bank, grassland, and woodland sources, respectively.Optimised land use risk weightings for each sampling period showed that at the larger catchment scale,no variation in median land use weightings were required to predict land use contributions. However,for the two smaller study catchments, variation in median risk weightings was considerable, which mayindicate the importance of functional connectivity processes at this spatial scale. In all instances, arableland consistently generated the highest risk of sediment loss across all catchments and sampling times.This study documents some of the first data on sediment provenance in Ireland and indicates the needfor cautious consideration of land use as a tool to predict critical source areas at the headwater scale
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Kelp forests along temperate and polar coastlines represent some of most diverse and productive habitats on the Earth. Here, we synthesize information from >60 years of research on the structure and functioning of kelp forest habitats in European waters, with particular emphasis on the coasts of UK and Ireland, which represents an important biogeographic transition zone that is subjected to multiple threats and stressors. We collated existing data on kelp distribution and abundance and reanalyzed these data to describe the structure of kelp forests along a spatial gradient spanning more than 10° of latitude. We then examined ecological goods and services provided by kelp forests, including elevated secondary production, nutrient cycling, energy capture and flow, coastal defense, direct applications, and biodiversity repositories, before discussing current and future threats posed to kelp forests and identifying key knowledge gaps. Recent evidence unequivocally demonstrates that the structure of kelp forests in the NE Atlantic is changing in response to climate- and non-climate-related stressors, which will have major implications for the structure and functioning of coastal ecosystems. However, kelp-dominated habitats along much of the NE Atlantic coastline have been chronically understudied over recent decades in comparison with other regions such as Australasia and North America. The paucity of field-based research currently impedes our ability to conserve and manage these important ecosystems. Targeted observational and experimental research conducted over large spatial and temporal scales is urgently needed to address these knowledge gaps.
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Summary
1.While plant–fungal interactions are important determinants of plant community assembly and ecosystem functioning, the processes underlying fungal community composition are poorly understood.
2.Here, we studied for the first time the root-associated eumycotan communities in a set of co-occurring plant species of varying relatedness in a species-rich, semi-arid grassland in Germany. The study system provides an opportunity to evaluate the importance of host plants and gradients in soil type and landscape structure as drivers of fungal community structure on a relevant spatial scale. We used 454 pyrosequencing of the fungal internal transcribed spacer region to analyse root-associated eumycotan communities of 25 species within the Asteraceae, which were sampled at different locations within a soil type gradient. We partitioned the variance accounted for by three predictors (host plant phylogeny, spatial distribution and soil type) to quantify their relative roles in determining fungal community composition and used null model analyses to determine whether community composition was influenced by biotic interactions among the fungi.
3.We found a high fungal diversity (156 816 sequences clustered in 1100 operational taxonomic units (OTUs)). Most OTUs belonged to the phylum Ascomycota (35.8%); the most abundant phylotype best-matched Phialophora mustea. Basidiomycota were represented by 18.3%, with Sebacina as most abundant genus. The three predictors explained 30% of variation in the community structure of root-associated fungi, with host plant phylogeny being the most important variance component. Null model analysis suggested that many fungal taxa co-occurred less often than expected by chance, which demonstrates spatial segregation and indicates that negative interactions may prevail in the assembly of fungal communities.
4.Synthesis. The results show that the phylogenetic relationship of host plants is the most important predictor of root-associated fungal community assembly, indicating that fungal colonization of host plants might be facilitated by certain plant traits that may be shared among closely related plant species.
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Spatial variability of conductivity in ceria is explored using scanning probe microscopy (SPM) with galvanostatic control. Ionically blocking electrodes are used to probe the conductivity under opposite polarities to reveal possible differences in the defect structure across a thin film of CeO2. Data suggests the existence of a large spatial inhomogeneity that could give rise to constant phase elements during standard electrochemical characterization, potentially affecting the overall conductivity of films on the macroscale. The approach discussed here can also be utilized for other mixed ionic electronic conductor (MIEC) systems including memristors and electroresistors, as well as physical systems such as ferroelectric tunneling barriers.
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Statistical downscaling (SD) methods have become a popular, low-cost and accessible means of bridging the gap between the coarse spatial resolution at which climate models output climate scenarios and the finer spatial scale at which impact modellers require these scenarios, with various different SD techniques used for a wide range of applications across the world. This paper compares the Generator for Point Climate Change (GPCC) model and the Statistical DownScaling Model (SDSM)—two contrasting SD methods—in terms of their ability to generate precipitation series under non-stationary conditions across ten contrasting global climates. The mean, maximum and a selection of distribution statistics as well as the cumulative frequencies of dry and wet spells for four different temporal resolutions were compared between the models and the observed series for a validation period. Results indicate that both methods can generate daily precipitation series that generally closely mirror observed series for a wide range of non-stationary climates. However, GPCC tends to overestimate higher precipitation amounts, whilst SDSM tends to underestimate these. This infers that GPCC is more likely to overestimate the effects of precipitation on a given impact sector, whilst SDSM is likely to underestimate the effects. GPCC performs better than SDSM in reproducing wet and dry day frequency, which is a key advantage for many impact sectors. Overall, the mixed performance of the two methods illustrates the importance of users performing a thorough validation in order to determine the influence of simulated precipitation on their chosen impact sector.
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Species-area relationships (SAR) are fundamental in the understanding of biodiversity patterns and of critical importance for predicting species extinction risk worldwide. Despite the enormous attention given to SAR in the form of many individual analyses, little attempt has been made to synthesize these studies. We conducted a quantitative meta-analysis of 794 SAR, comprising a wide span of organisms, habitats and locations. We identified factors reflecting both pattern-based and dynamic approaches to SAR and tested whether these factors leave significant imprints on the slope and strength of SAR. Our analysis revealed that SAR are significantly affected by variables characterizing the sampling scheme, the spatial scale, and the types of organisms or habitats involved. We found that steeper SAR are generated at lower latitudes and by larger organisms. SAR varied significantly between nested and independent sampling schemes and between major ecosystem types, but not generally between the terrestrial and the aquatic realm. Both the fit and the slope of the SAR were scale-dependent. We conclude that factors dynamically regulating species richness at different spatial scales strongly affect the shape of SAR. We highlight important consequences of this systematic variation in SAR for ecological theory, conservation management and extinction risk predictions.
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The spatial distribution of a species can be characterized at many different spatial scales, from fine-scale measures of local population density to coarse-scale geographical-range structure. Previous studies have shown a degree of correlation in species' distribution patterns across narrow ranges of scales, making it possible to predict fine-scale properties from coarser-scale distributions. To test the limits of such extrapolation, we have compiled distributional information on 16 species of British plants, at scales ranging across six orders of magnitude in linear resolution (1 in to 100 km). As expected, the correlation between patterns at different spatial scales tends to degrade as the scales become more widely separated. There is, however, an abrupt breakdown in cross-scale correlations across intermediate (ca. 0.5 km) scales, suggesting that local and regional patterns are influenced by essentially non-overlapping sets of processes. The scaling discontinuity may also reflect characteristic scales of human land use in Britain, suggesting a novel method for analysing the 'footprint' of humanity on a landscape.
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Background: Although Plasmodium falciparum transmission frequently exhibits seasonal patterns, the drivers of malaria seasonality are often unclear. Given the massive variation in the landscape upon which transmission acts, intra-annual fluctuations are likely influenced by different factors in different settings. Further, the presence of potentially substantial inter-annual variation can mask seasonal patterns; it may be that a location has "strongly seasonal" transmission and yet no single season ever matches the mean, or synoptic, curve. Accurate accounting of seasonality can inform efficient malaria control and treatment strategies. In spite of the demonstrable importance of accurately capturing the seasonality of malaria, data required to describe these patterns is not universally accessible and as such localized and regional efforts at quantifying malaria seasonality are disjointed and not easily generalized.
Methods: The purpose of this review was to audit the literature on seasonality of P. falciparum and quantitatively summarize the collective findings. Six search terms were selected to systematically compile a list of papers relevant to the seasonality of P. falciparum transmission, and a questionnaire was developed to catalogue the manuscripts.
Results and discussion: 152 manuscripts were identified as relating to the seasonality of malaria transmission, deaths due to malaria or the population dynamics of mosquito vectors of malaria. Among these, there were 126 statistical analyses and 31 mechanistic analyses (some manuscripts did both).
Discussion: Identified relationships between temporal patterns in malaria and climatological drivers of malaria varied greatly across the globe, with different drivers appearing important in different locations. Although commonly studied drivers of malaria such as temperature and rainfall were often found to significantly influence transmission, the lags between a weather event and a resulting change in malaria transmission also varied greatly by location.
Conclusions: The contradicting results of studies using similar data and modelling approaches from similar locations as well as the confounding nature of climatological covariates underlines the importance of a multi-faceted modelling approach that attempts to capture seasonal patterns at both small and large spatial scales.
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International policy frameworks such as the Common Fisheries Policy and the European Marine Strategy Framework Directive define high-level strategic goals for marine ecosystems. Strategic goals are addressed via general and operational management objectives. To add credibility and legitimacy to the development of objectives, for this study stakeholders explored intermediate level ecological, economic and social management objectives for Northeast Atlantic pelagic ecosystems. Stakeholder workshops were undertaken with participants being free to identify objectives based on their own insights and needs. Overall 26 objectives were proposed, with 58% agreement in proposed objectives between two workshops. Based on published evidence for pressure-state links, examples of operational objectives and suitable indicators for each of the 26 objectives were then selected. It is argued that given the strong species-specific links of pelagic species with the environment and the large geographic scale of their life cycles, which contrast to demersal systems, pelagic indicators are needed at the level of species (or stocks) independent of legislative region. Pelagic community indicators may be set at regional scale in some cases. In the evidence-based approach used in this study, the selection of species or region specific operational objectives and indicators was based on demonstrated pressure-state links. Hence observed changes in indicators can reliably inform on appropriate management measures
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An organism’s home range dictates the spatial scale on which important processes occur (e.g. competition and predation) and directly affects the relationship between individual fitness and local habitat quality. Many reef fish species have very restricted home ranges after settlement and, here, we quantify home-range size in juveniles of a widespread and abundant reef fish in New Zealand, the common triplefin (Forsterygion lapillum). We conducted visual observations on 49 juveniles (mean size = 35-mm total length) within the Wellington harbour, New Zealand. Home ranges were extremely small, 0.053 m2 ± 0.029 (mean ± s.d.) and were unaffected by adult density, body size or substrate composition. A regression tree indicated that home-range size sharply decreased ~4.5 juveniles m–2 and a linear mixed model confirmed that home-range sizes in high-density areas (>4.5 juveniles m–2) were significantly smaller (34%) than those in low-density areas (after accounting for a significant effect of fish movement on our home-range estimates). Our results suggest that conspecific density may have negative and non-linear effects on home-range size, which could shape the spatial distribution of juveniles within a population, as well as influence individual fitness across local density gradients.
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Dissertação de mest., Recursos Hídricos, Faculdade de Ciências e Tecnologia, Univ. do Algarve, 2011
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Tese de doutoramento, Ciências do Mar, Faculdade de Ciências e Tecnologia, Universidade do Algarve, 2015
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Affiliation: Pascal Michel : Département de pathologie et microbiologie, Faculté de médecine vétérinaire, Université de Montréal
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Réalisées aux échelles internationales et nationales, les études de vulnérabilité aux changements et à la variabilité climatiques sont peu pertinentes dans un processus de prise de décisions à des échelles géographiques plus petites qui représentent les lieux d’implantation des stratégies de réponses envisagées. Les études de vulnérabilité aux changements et à la variabilité climatiques à des échelles géographiques relativement petites dans le secteur agricole sont généralement rares, voire inexistantes au Canada, notamment au Québec. Dans le souci de combler ce vide et de favoriser un processus décisionnel plus éclairé à l’échelle de la ferme, cette étude cherchait principalement à dresser un portrait de l’évolution de la vulnérabilité des fermes productrices de maïs-grain des régions de Montérégie-Ouest et du Lac-St-Jean-Est aux changements et à la variabilité climatiques dans un contexte de multiples sources de pression. Une méthodologie générale constituée d'une évaluation de la vulnérabilité globale à partir d’une combinaison de profils de vulnérabilité aux conditions climatiques et socio-économiques a été adoptée. Pour la période de référence (1985-2005), les profils de vulnérabilité ont été dressés à l’aide d’analyses des coefficients de variation des séries temporelles de rendements et de superficies en maïs-grain. Au moyen de méthodes ethnographiques associées à une technique d’analyse multicritère, le Processus d’analyse hiérarchique (PAH), des scénarios d’indicateurs de capacité adaptative du secteur agricole susmentionné ont été développés pour la période de référence. Ceux-ci ont ensuite servi de point de départ dans l’élaboration des indicateurs de capacité de réponses des producteurs agricoles pour la période future 2010-2039. Pour celle-ci, les deux profils de vulnérabilité sont issus d’une simplification du cadre théorique de « Intergovernmental Panel on Climate Change » (IPCC) relatif aux principales composantes du concept de vulnérabilité. Pour la dimension « sensibilité » du secteur des fermes productrices de maïs-grain des deux régions agricoles aux conditions climatiques, une série de données de rendements a été simulée pour la période future. Ces simulations ont été réalisées à l’aide d’un couplage de cinq scénarios climatiques et du modèle de culture CERES-Maize de « Decision Support System for Agrotechnology Transfer » (DSSAT), version 4.0.2.0. En ce qui concerne l’évaluation de la « capacité adaptative » au cours de la période future, la construction des scénarios d’indicateurs de cette composante a été effectuée selon l’influence potentielle des grandes orientations économiques et environnementales considérées dans l’élaboration des lignes directrices des deux familles d’émissions de gaz à effet de serre (GES) A2 et A1B. L’application de la démarche méthodologique préalablement mentionnée a conduit aux principaux résultats suivants. Au cours de la période de référence, la région agricole du Lac-St-Jean-Est semblait être plus vulnérable aux conditions climatiques que celle de Montérégie-Ouest. En effet, le coefficient de variation des rendements du maïs-grain pour la région du Lac-St-Jean-Est était évalué à 0,35; tandis que celui pour la région de Montérégie-Ouest n’était que de 0,23. Toutefois, par rapport aux conditions socio-économiques, la région de Montérégie-Ouest affichait une vulnérabilité plus élevée que celle du Lac-St-Jean-Est. Les valeurs des coefficients de variation pour les superficies en maïs-grain au cours de la période de référence pour la Montérégie-Ouest et le Lac-St-Jean-Est étaient de 0,66 et 0,48, respectivement. Au cours de la période future 2010-2039, la région du Lac-St-Jean-Est serait, dans l’ensemble, toujours plus vulnérable aux conditions climatiques que celle de Montérégie-Ouest. Les valeurs moyennes des coefficients de variation pour les rendements agricoles anticipés fluctuent entre 0,21 et 0,25 pour la région de Montérégie-Ouest et entre 0,31 et 0,50 pour la région du Lac-St-Jean-Est. Néanmoins, en matière de vulnérabilité future aux conditions socio-économiques, la position relative des deux régions serait fonction du scénario de capacité adaptative considéré. Avec les orientations économiques et environnementales considérées dans l’élaboration des lignes directrices de la famille d’émission de GES A2, les indicateurs de capacité adaptative du secteur à l’étude seraient respectivement de 0,13 et 0,08 pour la Montérégie-Ouest et le Lac-St-Jean-Est. D’autre part, en considérant les lignes directrices de la famille d’émission de GES A1B, la région agricole du Lac-St-Jean-Est aurait une capacité adaptative légèrement supérieure (0,07) à celle de la Montérégie-Ouest (0,06). De façon générale, au cours de la période future, la région du Lac-St-Jean-Est devrait posséder une vulnérabilité globale plus élevée que la région de Montérégie-Ouest. Cette situation s’expliquerait principalement par une plus grande vulnérabilité de la région du Lac-St-Jean-Est aux conditions climatiques. Les résultats de cette étude doivent être appréciés dans le contexte des postulats considérés, de la méthodologie suivie et des spécificités des deux régions agricoles examinées. Essentiellement, avec l’adoption d’une démarche méthodologique simple, cette étude a révélé les caractéristiques « dynamique et relative » du concept de vulnérabilité, l’importance de l’échelle géographique et de la prise en compte d’autres sources de pression et surtout de la considération d’une approche contraire à celle du « agriculteur réfractaire aux changements » dans les travaux d’évaluation de ce concept dans le secteur agricole. Finalement, elle a aussi présenté plusieurs pistes de recherche susceptibles de contribuer à une meilleure évaluation de la vulnérabilité des agriculteurs aux changements climatiques dans un contexte de multiples sources de pression.
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Objectif : L’objectif principal de cette thèse est d’examiner les déterminants de l’utilisation des services de soins pour des raisons de santé mentale dans le sud-ouest de Montréal. Données et méthodes : L’étude utilise les données de la première phase du projet portant sur « le développement d’une zone circonscrite d’études épidémiologiques en psychiatrie dans le sud-ouest de Montréal ». Les données ont été collectées entre mai 2007 et août 2008 auprès d’un échantillon de 2434 personnes sélectionnées au hasard dans tout le territoire de l’étude. De cet échantillon, nous avons sélectionné un sous-échantillon de personnes ayant eu au moins un diagnostic de santé mentale au cours de la dernière année. 423 personnes ont rencontrées ce critère et constituent l’échantillon pour les analyses de la présente thèse. Le modèle comportemental d’Andersen a servi de cadre pour le choix des variables à analyser. Parce que l’approche socio-spatiale a été privilégiée pour modéliser les déterminants de l’utilisation des services, les analyses ont été effectuées à l’aide de quatre logiciels distincts à savoir : SPSS, AMOS, ArcGIS et MlWin. Résultats : Les résultats montrent que 53,66% de notre échantillon ont utilisés au moins un service de santé pour des raisons de santé mentale. On constate néanmoins que les déterminants de l’utilisation des services en santé mentale sont à la fois complexes et spatialement inégalement réparties. En ce qui concerne les caractéristiques sociodémographiques et cliniques, les femmes et ceux qui perçoivent la stigmatisation envers les personnes ayant un problème de santé mentale utilisent plus les services. Le nombre de diagnostics de santé mentale est aussi associé à l’utilisation des services. L’augmentation du nombre de diagnostics entraîne une augmentation de l’utilisation des services (=0,38; p<0,001). D’autres variables comme l’âge, le statut matrimonial, la taille du ménage, le soutien social et la qualité de vie influencent indirectement l’utilisation des services. À titre illustratif toute augmentation de l’âge entraîne une augmentation du soutien social de (=0,69; p<0,001) qui à son tour fait diminuer la détresse psychiatrique (= -0,09 (p<0,05). Or, toute augmentation d’une unité de détresse psychiatrique entraîne une augmentation de l’utilisation des services (=0,58 (p<0,001). Sur le plan spatiale, il existe une corrélation positive entre l’utilisation des services et la défavorisation matérielle, la défavorisation sociale et le nombre d’immigrants récents sur un territoire. Par contre, la corrélation entre la prévalence de la santé mentale et l’utilisation des services est négative. Les analyses plus poussées indiquent que le contexte de résidence explique 12,26 % (p<0,05) de la variation totale de l’utilisation des services. De plus, lorsqu’on contrôle pour les caractéristiques individuelles, vivre dans un environnement stable augmente l’utilisation des services (O.R=1,24; p<0,05) tandis que les contextes défavorisés du point de vue socioéconomique ont un effet néfaste sur l’utilisation (O.R=0,71; p<0,05). Conclusion : Les résultats de l’étude suggèrent que si on veut optimiser l’utilisation des services en santé mentale, il est important d’agir prioritairement au niveau de la collectivité. Plus spécifiquement, il faudrait mener des campagnes de sensibilisation auprès de la population pour combattre la stigmatisation des personnes ayant un problème de santé mentale. Sur le plan de la planification des soins de santé, on devrait augmenter l’offre des services dans les territoires défavorisés pour en faciliter l’accès aux habitants.