949 resultados para Local Scale Model


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Dissertação (mestrado)—Universidade de Brasília, Instituto de Geociências, 2016.

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Understanding factors that affect the distribution and abundance of species is critical to developing effective management plans for conservation. Our goal was to quantify the distribution and abundance of Canada Warbler (Cardellina canadensis), a threatened old-forest associate in Alberta, Canada. The Canada Warbler has declined across its range, including in Alberta where habitat loss and alteration from urban expansion, forestry, and energy development are changing the forest landscape. We used 110,427 point count survey visits from 32,287 unique survey stations to model local-level (150-m radius circular buffers) and stand-level (564-m radius circular buffers) habitat associations of the Canada Warbler. We found that habitat supporting higher densities of Canada Warblers was locally concentrated yet broadly distributed across Alberta’s boreal forest region. Canada Warblers were most commonly associated with older deciduous forest at the local scale, particularly near small, incised streams, and greater amounts of deciduous forest at the stand scale. Predicted density was lower in other forest types and younger age classes measured at the local scale. There was little evidence that local-scale fragmentation (i.e., edges created by linear features) influenced Canada Warbler abundance. However, current forestry practices in the province likely will reduce the availability of Canada Warbler habitat over time by cutting old deciduous forest stands. Our results suggest that conservation efforts aimed at Canada Warbler focus on retaining large stands of old deciduous forest, specifically stands adjacent to streams, by increasing the width of deciduous retention buffers along streams during harvest and increasing the size and number of old forest residual patches in harvested stands.

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We propose an alternative crack propagation algo- rithm which effectively circumvents the variable transfer procedure adopted with classical mesh adaptation algo- rithms. The present alternative consists of two stages: a mesh-creation stage where a local damage model is employed with the objective of defining a crack-conforming mesh and a subsequent analysis stage with a localization limiter in the form of a modified screened Poisson equation which is exempt of crack path calculations. In the second stage, the crack naturally occurs within the refined region. A staggered scheme for standard equilibrium and screened Poisson equa- tions is used in this second stage. Element subdivision is based on edge split operations using a constitutive quantity (damage). To assess the robustness and accuracy of this algo- rithm, we use five quasi-brittle benchmarks, all successfully solved.

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Brazil's Low Carbon Agriculture is one the initiatives that puts the climate in the agricultural agenda towards a more sustainable and adapted agriculture under global changes. Among the several practices listed and supported by the ABC Plan, zero tillage and integrated crop-livestock-forestry systems including the recovery of degraded pasture are the most relevant ones. The objective of this paper is to present the Geo-ABC Project, a procedure to monitor the implementation of the Brazil?s Low Carbon Agriculture (ABC Plan) and aiming at the development of remote sensing methods to monitor agricultural systems listed in the ABC Plan and adopted at local scale.

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Cancer is a challenging disease that involves multiple types of biological interactions in different time and space scales. Often computational modelling has been facing problems that, in the current technology level, is impracticable to represent in a single space-time continuum. To handle this sort of problems, complex orchestrations of multiscale models is frequently done. PRIMAGE is a large EU project that aims to support personalized childhood cancer diagnosis and prognosis. The goal is to do so predicting the growth of the solid tumour using multiscale in-silico technologies. The project proposes an open cloud-based platform to support decision making in the clinical management of paediatric cancers. The orchestration of predictive models is in general complex and would require a software framework that support and facilitate such task. The present work, proposes the development of an updated framework, referred herein as the VPH-HFv3, as a part of the PRIMAGE project. This framework, a complete re-writing with respect to the previous versions, aims to orchestrate several models, which are in concurrent development, using an architecture as simple as possible, easy to maintain and with high reusability. This sort of problem generally requires unfeasible execution times. To overcome this problem was developed a strategy of particularisation, which maps the upper-scale model results into a smaller number and homogenisation which does the inverse way and analysed the accuracy of this approach.

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This thesis analyzes the impact of heat extremes in urban and rural environments, considering processes related to severely high temperatures and unusual dryness. The first part deals with the influence of large-scale heatwave events on the local-scale urban heat island (UHI) effect. The temperatures recorded over a 20-year summer period by meteorological stations in 37 European cities are examined to evaluate the variations of UHI during heatwaves with respect to non-heatwave days. A statistical analysis reveals a negligible impact of large-scale extreme temperatures on the local daytime urban climate, while a notable exacerbation of UHI effect at night. A comparison with the UrbClim model outputs confirms the UHI strengthening during heatwave episodes, with an intensity independent of the climate zone. The investigation of the relationship between large-scale temperature anomalies and UHI highlights a smooth and continuous dependence, but with a strong variability. The lack of a threshold behavior in this relationship suggests that large-scale temperature variability can affect the local-scale UHI even in different conditions than during extreme events. The second part examines the transition from meteorological to agricultural drought, being the first stage of the drought propagation process. A multi-year reanalysis dataset involving numerous drought events over the Iberian Peninsula is considered. The behavior of different non-parametric standardized drought indices in drought detection is evaluated. A statistical approach based on run theory is employed, analyzing the main characteristics of drought propagation. The propagation from meteorological to agricultural drought events is found to develop in about 1-2 months. The duration of agricultural drought appears shorter than that of meteorological drought, but the onset is delayed. The propagation probability increases with the severity of the originating meteorological drought. A new combined agricultural drought index is developed to be a useful tool for balancing the characteristics of other adopted indices.

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The ecosystem services provided by bees are very important. Factors as habitat fragmentation, intensive agriculture and climate change are contributing to the decline of bee populations. The use of remote sensing could be a useful tool for the recognition of sites with a high diversity, before performing a more expensive survey in the field. In this study the ability of Unmanned Aerial Vehicles (UAV) images to estimate biodiversity at local scale has been analysed testing the concept of the Height Variation Hypothesis (HVH). This approach states that, the higher the vegetation height heterogeneity (HH) measured by remote sensing information, the higher the vertical complexity and the higher vegetation species diversity. In this thesis the concept has been brought to a higher level, in order to understand if the vegetation HH can be considered a proxy also of bee species diversity and abundance. We tested this approach collecting field data on bees/flowers and RGB images through an UAV campaign in 30 grasslands in the South of the Netherlands. The Canopy Height Model (CHM) were derived through the photogrammetry technique "Structure from Motion" (SfM) with resolutions of 10cm, 25cm, 50cm. Successively, the HH assessed on the CHM using the Rao's Q heterogeneity index was correlated to the field data (bee abundance, diversity and bee/flower species richness). The correlations were all positive and significant. The highest R2 values were found when the HH was calculated at 10cm and correlated to bee species richness (R2 = 0.41) and Shannon’s H index (R2 = 0.38). Using a lower spatial resolution the goodness of fit slightly decreases. For flower species richness the R2 ranged between 0.36 to 0.39. Our results suggest that methods based on the concept behind the HVH, in this case deriving information of HH from UAV data, can be developed into valuable tools for large-scale, standardized and cost-effective monitoring of flower diversity and of the habitat quality for bees.

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Background: Freshwaters are the most threatened ecosystems on earth. Although recent assessments provide data on global priority regions for freshwater conservation, local scale priorities remain unknown. Refining the scale of global biodiversity assessments (both at terrestrial and freshwater realms) and translating these into conservation priorities on the ground remains a major challenge to biodiversity science, and depends directly on species occurrence data of high taxonomic and geographic resolution. Brazil harbors the richest freshwater ichthyofauna in the world, but knowledge on endemic areas and conservation in Brazilian rivers is still scarce. Methodology/Principal Findings: Using data on environmental threats and revised species distribution data we detect and delineate 540 small watershed areas harboring 819 restricted-range fishes in Brazil. Many of these areas are already highly threatened, as 159 (29%) watersheds have lost more than 70% of their original vegetation cover, and only 141 (26%) show significant overlap with formally protected areas or indigenous lands. We detected 220 (40%) critical watersheds overlapping hydroelectric dams or showing both poor formal protection and widespread habitat loss; these sites harbor 344 endemic fish species that may face extinction if no conservation action is in place in the near future. Conclusions/Significance: We provide the first analysis of site-scale conservation priorities in the richest freshwater ecosystems of the globe. Our results corroborate the hypothesis that freshwater biodiversity has been neglected in former conservation assessments. The study provides a simple and straightforward method for detecting freshwater priority areas based on endemism and threat, and represents a starting point for integrating freshwater and terrestrial conservation in representative and biogeographically consistent site-scale conservation strategies, that may be scaled-up following naturally linked drainage systems. Proper management (e. g. forestry code enforcement, landscape planning) and conservation (e. g. formal protection) of the 540 watersheds detected herein will be decisive in avoiding species extinction in the richest aquatic ecosystems on the planet.

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Live aboveground biomass (AGB) is an important source of uncertainty in the carbon balance from the tropical regions in part due scarcity of reliable estimates of live AGB and its variation across landscapes and forest types. Studies of forest structure and biomass stocks of Neotropical forests are biased toward Amazonian and Central American sites. In particular, standardized estimates of aboveground biomass stocks for the Brazilian Atlantic forest are rarely available. Notwithstanding the role of environmental variables that control the distribution and abundance of biomass in tropical lowland forests has been the subject of considerable research, the effect of short, steep elevational gradients on tropical forest structure and carbon dynamics is not well known. In order to evaluate forest structure and live AGB variation along an elevational gradient (0-1100 m a.s.l.) of coastal Atlantic Forest in SE Brazil, we carried out a standard census of woody stems >= 4.8 cm dbh in 13 1-ha permanent plots established on four different sites in 2006-2007. Live AGB ranged from 166.3 Mg ha(-1) (bootstrapped 95% CI: 1444,187.0) to 283.2 Mg ha(-1) (bootstrapped 95% CI: 253.0,325.2) and increased with elevation. We found that local-scale topographic variation associated with elevation influences the distribution of trees >50 cm dbh and total live AGB. Across all elevations, we found more stems (64-75%) with limited crown illumination but the largest proportion of the live AGB (68-85%) was stored in stems with highly illuminated or fully exposed crowns. Topography, disturbance and associated changes in light and nutrient supply probably control biomass distribution along this short but representative elevational gradient. Our findings also showed that intact Atlantic forest sites stored substantial amounts of carbon aboveground. The live tree AGB of the stands was found to be lower than Central Amazonian forests, but within the range of Neotropical forests, in particular when compared to Central American forests. Our comparative data suggests that differences in live tree AGB among Neotropical forests are probably related to the heterogeneous distribution of large and medium-sized diameter trees within forests and how the live biomass is partitioned among those size classes, in accordance with general trends found by previous studies. In addition, the elevational variation in live AGB stocks suggests a large spatial variability over coastal Atlantic forests in Brazil, clearly indicating that it is important to consider regional differences in biomass stocks for evaluating the role of this threatened tropical biome in the global carbon cycle. (C) 2010 Elsevier B.V. All rights reserved.

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The practicability of estimating directional wave spectra based on a vessel`s 1st order response has been recently addressed by several researchers. Different alternatives regarding statistical inference methods and possible drawbacks that could arise from their application have been extensively discussed, with an apparent preference for estimations based on Bayesian inference algorithms. Most of the results on this matter, however, rely exclusively on numerical simulations or at best on few and sparse full-scale measurements, comprising a questionable basis for validation purposes. This paper discusses several issues that have recently been debated regarding the advantages of Bayesian inference and different alternatives for its implementation. Among those are the definition of the best set of input motions, the number of parameters required for guaranteeing smoothness of the spectrum in frequency and direction and how to determine their optimum values. These subjects are addressed in the light of an extensive experimental campaign performed with a small-scale model of an FPSO platform (VLCC hull), which was conducted in an ocean basin in Brazil. Tests involved long and short crested seas with variable levels of directional spreading and also bimodal conditions. The calibration spectra measured in the tank by means of an array of wave probes configured the paradigm for estimations. Results showed that a wide range of sea conditions could be estimated with good precision, even those with somewhat low peak periods. Some possible drawbacks that have been pointed out in previous works concerning the viability of employing large vessels for such a task are then refuted. Also, it is shown that a second parameter for smoothing the spectrum in frequency may indeed increase the accuracy in some situations, although the criterion usually proposed for estimating the optimum values (ABIC) demands large computational effort and does not seem adequate for practical on-board systems, which require expeditious estimations. (C) 2009 Elsevier Ltd. All rights reserved.

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Force measurement in hypervelocity expansion tubes is not possible using conventional techniques. The stress wave force balance technique can be applied in expansion tubes to measure forces despite the short test times involved. This paper presents a new calibration technique for multiple-component stress wave force balances where an impulse response created using a load distribution is required and no orthogonal surfaces on the model exist.. This new technique relies on the tensorial superposition of single-component impulse responses analogous to the vectorial superposition of the calibration loads. The example presented here is that of a scale model of the Mars Pathfinder, but the technique is applicable to any geometry and may be useful for cases where orthogonal loads cannot be applied.

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Polytomous Item Response Theory Models provides a unified, comprehensive introduction to the range of polytomous models available within item response theory (IRT). It begins by outlining the primary structural distinction between the two major types of polytomous IRT models. This focuses on the two types of response probability that are unique to polytomous models and their associated response functions, which are modeled differently by the different types of IRT model. It describes, both conceptually and mathematically, the major specific polytomous models, including the Nominal Response Model, the Partial Credit Model, the Rating Scale model, and the Graded Response Model. Important variations, such as the Generalized Partial Credit Model are also described as are less common variations, such as the Rating Scale version of the Graded Response Model. Relationships among the models are also investigated and the operation of measurement information is described for each major model. Practical examples of major models using real data are provided, as is a chapter on choosing an appropriate model. Figures are used throughout to illustrate important elements as they are described.

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Many studies have used genetic markers to understand global migration patterns of our species. However, there are only few studies of human migration on a local scale. We, therefore, researched migration dynamics in three Afro-Brazilian rural communities, using demographic data and ten Ancestry Informative Markers. In addition to the description of migration and marriage structures, we carried out genetic comparisons between the three populations, as well as between locals and migrants from each community. Genetic admixture analyses were conducted according to the gene-identity method, with Sub-Saharan Africans, Amerindians, and Europeans as parental populations. The three analyzed Afro-Brazilian rural communities consisted of 16% to 30% of migrants, most of them women. The age pyramid revealed a gap in the segment of men aged between 20 to 30 yrs. While endogamous marriages predominated, exogamous marriages were mainly patrilocal. Migration dynamics are apparently associated with matrimonial customs and other social practices of such communities. The impact of migration upon the populations` genetic composition was low but showed an increase in European alleles with a concomitant decrease in the Amerindian contribution. Admixture analysis evidenced a higher African contribution to the gene pool of the studied populations, followed by the contribution of Europeans and Amerindians, respectively.

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Fault detection and isolation (FDI) are important steps in the monitoring and supervision of industrial processes. Biological wastewater treatment (WWT) plants are difficult to model, and hence to monitor, because of the complexity of the biological reactions and because plant influent and disturbances are highly variable and/or unmeasured. Multivariate statistical models have been developed for a wide variety of situations over the past few decades, proving successful in many applications. In this paper we develop a new monitoring algorithm based on Principal Components Analysis (PCA). It can be seen equivalently as making Multiscale PCA (MSPCA) adaptive, or as a multiscale decomposition of adaptive PCA. Adaptive Multiscale PCA (AdMSPCA) exploits the changing multivariate relationships between variables at different time-scales. Adaptation of scale PCA models over time permits them to follow the evolution of the process, inputs or disturbances. Performance of AdMSPCA and adaptive PCA on a real WWT data set is compared and contrasted. The most significant difference observed was the ability of AdMSPCA to adapt to a much wider range of changes. This was mainly due to the flexibility afforded by allowing each scale model to adapt whenever it did not signal an abnormal event at that scale. Relative detection speeds were examined only summarily, but seemed to depend on the characteristics of the faults/disturbances. The results of the algorithms were similar for sudden changes, but AdMSPCA appeared more sensitive to slower changes.

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Local scale windfield and air mass characteristics during the onset of two foehn wind events in an alpine hydro-catchment are presented. Grounding of the topographically modified foehn was found to be dependent on daytime surface heating and topographic channelling of flow. The foehn front was observed to advance down-valley until the valley widened significantly. The foehn wind appeared to decouple from the surface downstream of the accelerated flow associated with the valley constriction. and to be lifted above local thermally generated circulations including a lake breeze. Towards evening. the foehn front retreated up valley in response to reduced surface heating and the intrusion into the study area of a deep and cool air mass associated with a regional scale mountain-plain circulation. Differences in the local windfield observed during both case study events reflect the importance of different thermal and dynamic forcings on airflow in complex terrain. These are the result of variation in surface energy exchanges, channelling and blocking of airflow. Observations presented here have both theoretical and applied implications with regard to forecasting foehn onset, wind hazard management, recreational activities and air quality management in alpine settings.