920 resultados para Ecosystem-level models


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Com o advento da agricultura ampliou-se a produção alimentar e os bens de consumo, no entanto, os riscos ambientais também foram maximizados em função da adoção de técnicas produtivas baseadas no uso intensivo de insumos agrícolas. Esta problemática é mundial, embora mais evidenciada nos países em desenvolvimento e que tem, na produção agrícola, a base de sua economia. O Brasil enquadra-se nesta situação e desde 2009 é considerado o maior consumidor de agrotóxicos do mundo, criando um cenário de risco ambiental e de saúde humana. Os efeitos ambientais, base deste estudo, estão relacionados não somente à perda de espécies não-alvo, uma vez que os agrotóxicos não são seletivos, mas também as alterações em nível ecossistêmico, a qual se relaciona com as perdas das funções e dos serviços gerados pelos sistemas naturais. Adiciona-se a esta complexidade, a forma de ação de cada agrotóxico, a distribuição dos mesmos nos diferentes compartimentos (ar, solo e água), o período de permanência de cada um, as relações sinérgicas decorrentes das interações entre diferentes produtos, a formação de subprodutos no processo de degradação, entre outros fatores, como as diferenças existentes entre o ingrediente ativo e a formulação comercial, na qual existem os chamados ingredientes inertes em sua composição, os quais podem ser muito mais tóxicos para espécies e ecossistemas. Considerando esta abordagem, a presente pesquisa foi desenvolvida com base na realidade de um local de referência, o município de Bom Repouso (MG/BR), no qual a intensificação da produção de morango e batata tem trazido uma série de riscos sociais e ambientais. Semelhante a outras regiões produtivas do país, o uso de agrotóxicos é recorrente, amplo e irrestrito, com destaque para as formulações comerciais Kraft®36EC e Score®250EC, as quais, juntamente com seus respectivos ingredientes ativos (abamectina e difenoconazol), foram avaliadas por meio de testes de toxicidade com espécies de diferentes níveis tróficos representativas de um ecossistema aquático, gerando informações que foram avaliadas em nível de espécie e de ecossistema, simulando o cenário de aplicação dos produtos no local de referência. Os resultados obtidos permitiram concluir sobre as diferenças de sensibilidade das espécies e quais seriam as mais indicadas para se avaliar os efeitos tóxicos de ambos os agrotóxicos; os efeitos diferenciados entre a formulação comercial e os ingredientes ativos; bem como as respostas em termos de espécies e de ecossistemas, demonstrando a necessidade de que ambas as análises sejam consideradas na avaliação de risco ecológico.

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To determine the influence of fire and thermokarst in a boreal landscape, we investigated peat cores within and adjacent to a permafrost collapse feature on the Tanana River Floodplain of Interior Alaska. Radioisotope dating, diatom assemblages, plant macrofossils, charcoal fragments, and carbon and nitrogen content of the peat profile indicate ~600 years of vegetation succession with a transition from a terrestrial forest to a sedge-dominated wetland over 100 years ago, and to a Sphagnum-dominated peatland in approximately 1970. The shift from sedge to Sphagnum, and a decrease in the detrended tree-ring width index of black spruce trees adjacent to the collapse coincided with an increase in the growing season temperature record from Fairbanks. This concurrent wetland succession and reduced growth of black spruce trees indicates a step-wise ecosystem-level response to a change in regional climate. In 2001, fire was observed coincident with permafrost collapse and resulted in lateral expansion of the peatland. These observations and the peat profile suggest that future warming and/or increased fire disturbance could promote permafrost degradation, peatland expansion, and increase carbon storage across this landscape; however, the development of drought conditions could reduce the success of both black spruce and Sphagnum, and potentially decrease the long-term ecosystem carbon storage.

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In boreal bogs plant species are low in number, but they differ greatly in their growth forms and photosynthetic properties. We assessed how ecosystem carbon (C) sink dynamics were affected by seasonal variations in photosynthetic rate and leaf area of different species. Photosynthetic properties (light-response parameters), leaf area development and areal cover (abundance) of the species were used to quantify species-specific net and gross photosynthesis rates (PN and PG, respectively), which were summed to express ecosystem-level PN and PG. The ecosystem-level PG was compared with a gross primary production (GPP) estimate derived from eddy covariance measurements (EC). Species areal cover rather than differences in photosynthetic properties determined the species with the highest PG of both vascular plants and Sphagna. Species-specific contributions to the ecosystem PG varied over the growing season, which in turn determined the seasonal variation in ecosystem PG. The upscaled growing-season PG estimate, 230 g C/m**2, agreed well with the GPP estimated by the EC, 243 g C/m**2. Sphagna were superior to vascular plants in ecosystem-level PG throughout the growing season but had a lower PN. PN results indicated that areal cover of the species together with their differences in photosynthetic parameters shape the ecosystem-level C balance. Species with low areal cover but high photosynthetic efficiency appear to be potentially important for the ecosystem C sink. Results imply that functional diversity may increase the stability of C sink of boreal bogs.

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It is widely supposed that things tend to look blurred when they are moving fast. Previous work has shown that this is true for sharp edges but, paradoxically, blurred edges look sharper when they are moving than when stationary. This is 'motion sharpening'. We show that blurred edges also look up to 50% sharper when they are presented briefly (8-24 ms) than at longer durations (100-500 ms) without motion. This argues strongly against high-level models of sharpening based specifically on compensation for motion blur. It also argues against a recent, low-level, linear filter model that requires motion to produce sharpening. No linear filter model can explain our finding that sharpening was similar for sinusoidal and non-sinusoidal gratings, since linear filters can never distort sine waves. We also conclude that the idea of a 'default' assumption of sharpness is not supported by experimental evidence. A possible source of sharpening is a nonlinearity in the contrast response of early visual mechanisms to fast or transient temporal changes, perhaps based on the magnocellular (M-cell) pathway. Our finding that sharpening is not diminished at low contrast sets strong constraints on the nature of the nonlinearity.

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Often observations are nested within other units. This is particularly the case in the educational sector where school performance in terms of value added is the result of school contribution as well as pupil academic ability and other features relating to the pupil. Traditionally, the literature uses parametric (i.e. it assumes a priori a particular function on the production process) Multi-Level Models to estimate the performance of nested entities. This paper discusses the use of the non-parametric (i.e. without a priori assumptions on the production process) Free Disposal Hull model as an alternative approach. While taking into account contextual characteristics as well as atypical observations, we show how to decompose non-parametrically the overall inefficiency of a pupil into a unit specific and a higher level (i.e. a school) component. By a sample of entry and exit attainments of 3017 girls in British ordinary single sex schools, we test the robustness of the non-parametric and parametric estimates. We find that the two methods agree in the relative measures of the scope for potential attainment improvement. Further, the two methods agree on the variation in pupil attainment and the proportion attributable to pupil and school level.

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Software development methodologies are becoming increasingly abstract, progressing from low level assembly and implementation languages such as C and Ada, to component based approaches that can be used to assemble applications using technologies such as JavaBeans and the .NET framework. Meanwhile, model driven approaches emphasise the role of higher level models and notations, and embody a process of automatically deriving lower level representations and concrete software implementations. The relationship between data and software is also evolving. Modern data formats are becoming increasingly standardised, open and empowered in order to support a growing need to share data in both academia and industry. Many contemporary data formats, most notably those based on XML, are self-describing, able to specify valid data structure and content, and can also describe data manipulations and transformations. Furthermore, while applications of the past have made extensive use of data, the runtime behaviour of future applications may be driven by data, as demonstrated by the field of dynamic data driven application systems. The combination of empowered data formats and high level software development methodologies forms the basis of modern game development technologies, which drive software capabilities and runtime behaviour using empowered data formats describing game content. While low level libraries provide optimised runtime execution, content data is used to drive a wide variety of interactive and immersive experiences. This thesis describes the Fluid project, which combines component based software development and game development technologies in order to define novel component technologies for the description of data driven component based applications. The thesis makes explicit contributions to the fields of component based software development and visualisation of spatiotemporal scenes, and also describes potential implications for game development technologies. The thesis also proposes a number of developments in dynamic data driven application systems in order to further empower the role of data in this field.

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Performance analysis has become a vital part of the management practices in the banking industry. There are numerous applications using DEA models to estimate efficiency in banking, and most of them assume that inputs and outputs are known with absolute precision. Here, we propose new Fuzzy-DEA α-level models to assess underlying uncertainty. Further, bootstrap truncated regressions with fixed factors are used to measure the impact of each model on the efficiency scores and to identify the most relevant contextual variables on efficiency. The proposed models have been demonstrated using an application in Mozambican banks to handle the underlying uncertainty. Findings reveal that fuzziness is predominant over randomness in interpreting the results. In addition, fuzziness can be used by decision-makers to identify missing variables to help in interpreting the results. Price of labor, price of capital, and market-share were found to be the significant factors in measuring bank efficiency. Managerial implications are addressed.

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Over the past few decades, we have been enjoying tremendous benefits thanks to the revolutionary advancement of computing systems, driven mainly by the remarkable semiconductor technology scaling and the increasingly complicated processor architecture. However, the exponentially increased transistor density has directly led to exponentially increased power consumption and dramatically elevated system temperature, which not only adversely impacts the system's cost, performance and reliability, but also increases the leakage and thus the overall power consumption. Today, the power and thermal issues have posed enormous challenges and threaten to slow down the continuous evolvement of computer technology. Effective power/thermal-aware design techniques are urgently demanded, at all design abstraction levels, from the circuit-level, the logic-level, to the architectural-level and the system-level. ^ In this dissertation, we present our research efforts to employ real-time scheduling techniques to solve the resource-constrained power/thermal-aware, design-optimization problems. In our research, we developed a set of simple yet accurate system-level models to capture the processor's thermal dynamic as well as the interdependency of leakage power consumption, temperature, and supply voltage. Based on these models, we investigated the fundamental principles in power/thermal-aware scheduling, and developed real-time scheduling techniques targeting at a variety of design objectives, including peak temperature minimization, overall energy reduction, and performance maximization. ^ The novelty of this work is that we integrate the cutting-edge research on power and thermal at the circuit and architectural-level into a set of accurate yet simplified system-level models, and are able to conduct system-level analysis and design based on these models. The theoretical study in this work serves as a solid foundation for the guidance of the power/thermal-aware scheduling algorithms development in practical computing systems.^

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Precise relative sea level (RSL) data are important for inferring regional ice sheet histories, as well as helping to validate numerical models of ice sheet evolution and glacial isostatic adjustment. Here we develop a new RSL curve for Fildes Peninsula, South Shetland Islands (SSIs), a sub-Antarctic archipelago peripheral to the northern Antarctic Peninsula ice sheet, by integrating sedimentary evidence from isolation basins with geomorphological evidence from raised beaches. This combined approach yields not only a Holocene RSL curve, but also the spatial pattern of how RSL change varied across the archipelago. The curve shows a mid-Holocene RSL highstand on Fildes Peninsula at 15.5 m above mean sea level between 8000 and 7000 cal a BP. Subsequently RSL gradually fell as a consequence of isostatic uplift in response to regional deglaciation. We propose that isostatic uplift occurred at a non-steady rate, with a temporary pause in ice retreat ca. 7200 cal a BP, leading to a short-lived RSL rise of ~1 m and forming a second peak to the mid-Holocene highstand. Two independent approaches were taken to constrain the long-term tectonic uplift rate of the SSIs at 0.22-0.48 m/ka, placing the tectonic contribution to the reconstructed RSL highstand between 1.4 and 2.9 m. Finally, we make comparisons to predictions from three global sea level models.

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Ocean acidification (OA) is believed to be a major threat for near-future marine ecosystems, and that the most sensitive organisms will be calcifying organisms and the free-living larval stages produced by most benthic marine species. In this respect, echinoderms are one of the taxa most at risk. Earlier research on the impact of near-future OA on echinoderm larval stages showed negative effects, such as a decreased growth rate, increased mortality, and developmental abnormalities. However, all the long-term studies were performed on planktotrophic larvae while alternative life-history strategies, such as nonfeeding lecithotrophy, were largely ignored. Here, we show that lecithotrophic echinoderm larvae and juveniles are positively impacted by ocean acidification. When cultured at low pH, larvae and juveniles of the sea star Crossaster papposus grow faster with no visible affects on survival or skeletogenesis. This suggests that in future oceans, lecithotrophic species may be better adapted to deal with the threat of OA compared with planktotrophic ones with potentially important consequences at the ecosystem level. For example, an increase in populations of the top predator C. papposus will likely have huge consequences for community structure. Our results also highlight the importance of taking varying life-history strategies into account when assessing the impacts of climate change, an approach that also provides insight into understanding the evolution of life-history strategies.

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Network intrusion detection sensors are usually built around low level models of network traffic. This means that their output is of a similarly low level and as a consequence, is difficult to analyze. Intrusion alert correlation is the task of automating some of this analysis by grouping related alerts together. Attack graphs provide an intuitive model for such analysis. Unfortunately alert flooding attacks can still cause a loss of service on sensors, and when performing attack graph correlation, there can be a large number of extraneous alerts included in the output graph. This obscures the fine structure of genuine attacks and makes them more difficult for human operators to discern. This paper explores modified correlation algorithms which attempt to minimize the impact of this attack.

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Dissertação (mestrado)—Universidade de Brasília, Instituto de Ciências Exatas, Departamento de Ciência da Computação, 2015.

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At the ecosystem level, sustainable exploitation of fisheries resources depends not only on the status of target species but also on that of bycatch species, some of which are even more sensitive to exploitation. This is the case for a number of elasmobranchs (skates, rays and sharks) species whose abundance declined during the 20th century. Further, the biology of elamobranchs is still poorly known and traditional fisheries stock assessment methods using fisheries catches and scientific survey data for estimating abundance are expensive or even inapplicable due to the small numbers observed. The GenoPopTaille project attempts to apply to the case of the thornback ray (Raja clavata) recent genetic-based methods for absolute population abundance estimation as well as characterizing its genetic diversity and population structure in the Northeast Atlantic. The poster will present the objectives, challenges and progress made so far by the project.

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Tese (doutorado)—Universidade de Brasília, Instituto de Ciências Biológicas, Programa de Pós-Graduação em Ecologia, 2016.

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Many tissue level models of neural networks are written in the language of nonlinear integro-differential equations. Analytical solutions have only been obtained for the special case that the nonlinearity is a Heaviside function. Thus the pursuit of even approximate solutions to such models is of interest to the broad mathematical neuroscience community. Here we develop one such scheme, for stationary and travelling wave solutions, that can deal with a certain class of smoothed Heaviside functions. The distribution that smoothes the Heaviside is viewed as a fundamental object, and all expressions describing the scheme are constructed in terms of integrals over this distribution. The comparison of our scheme and results from direct numerical simulations is used to highlight the very good levels of approximation that can be achieved by iterating the process only a small number of times.