957 resultados para Climate, Dengue, Models, Projection, Scenarios


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Dengue fever is a mosquito-borne viral disease estimated to cause about 230 million infections worldwide every year, of which 25,000 are fatal. Global incidence has risen rapidly in recent decades with some 3.6 billion people, over half of the world's population, now at risk, mainly in urban centres of the tropics and subtropics. Demographic and societal changes, in particular urbanization, globalization, and increased international travel, are major contributors to the rise in incidence and geographic expansion of dengue infections. Major research gaps continue to hamper the control of dengue. The European Commission launched a call under the 7th Framework Programme with the title of 'Comprehensive control of Dengue fever under changing climatic conditions'. Fourteen partners from several countries in Europe, Asia, and South America formed a consortium named 'DengueTools' to respond to the call to achieve better diagnosis, surveillance, prevention, and predictive models and improve our understanding of the spread of dengue to previously uninfected regions (including Europe) in the context of globalization and climate change. The consortium comprises 12 work packages to address a set of research questions in three areas: Research area 1: Develop a comprehensive early warning and surveillance system that has predictive capability for epidemic dengue and benefits from novel tools for laboratory diagnosis and vector monitoring. Research area 2: Develop novel strategies to prevent dengue in children. Research area 3: Understand and predict the risk of global spread of dengue, in particular the risk of introduction and establishment in Europe, within the context of parameters of vectorial capacity, global mobility, and climate change. In this paper, we report on the rationale and specific study objectives of 'DengueTools'. DengueTools is funded under the Health theme of the Seventh Framework Programme of the European Community, Grant Agreement Number: 282589 Dengue Tools.

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Native bees are important providers of pollination services, but there are cumulative evidences of their decline. Global changes such as habitat losses, invasions of exotic species and climate change have been suggested as the main causes of the decline of pollinators. In this study, the influence of climate change on the distribution of 10 species of Brazilian bees was estimated with species distribution modelling. We used Maxent algorithm (maximum entropy) and two different scenarios, an optimistic and a pessimistic, to the years 2050 and 2080. We also evaluated the percentage reduction of species habitat based on the future scenarios of climate change through Geographic Information System (GIS). Results showed that the total area of suitable habitats decreased for all species but one under the different future scenarios. The greatest reductions in habitat area were found for Melipona bicolor bicolor and Melipona scutellaris, which occur predominantly in areas related originally to Atlantic Moist Forest. The species analysed have been reported to be pollinators of some regional crops and the consequence of their decrease for these crops needs further clarification. (C) 2012 Elsevier B.V. All rights reserved.

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The aim of this study was to identify future distribution areas and propose actions to preserve passion fruit pollination service under a scenario of future climate change. We used four species of Xylocopa bees that are important for passion fruit pollination in Brazilian Tropical Savannas. We also used the known forage plant species (33 species) that are associated with this same area, since passion fruit flowers provide only nectar for bees and only during their blossoming period. We used species distribution modeling to predict the potential areas of occurrence for each bee and plant based on the current day distribution and a future climate scenario (moderate projections of climate change to 2050). We used a geographic information system to classify the models and to analyze the future areas for both groups of species. The current day distribution map showed that Xylocopa and plant species occurred primarily in the southern and central-eastern areas of the Brazilian Tropical Savannas. In the north, Xylocopa species only occurred in a small area between the states of Maranhão and Piauí while forage plant species were only observed in the northern part of the Tocantins State. However, both future scenarios (bees and plants) showed a shift in distribution, with occurrence predominantly detected in the northern areas of Brazilian Tropical Savannas. Possible conservation areas and the use of appropriate agricultural practices were suggested to ensure the maintenance of the bee/plant focal species.

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Climate change can be associated with variations in the frequency and intensity of extreme temperatures and precipitation events on the local and regional scales. Along coastal areas, flooding associated with increased occupation has seriously impacted products and services generated by marine life, in particular the biotechnological potential that macroalgae hold. Therefore, this paper analyzes the available information on the taxonomy, ecology and physiology of macroalgae and discusses the impacts of climate change and local stress on the biotechnological potential of Brazilian macroalgae. Based on data compiled from a series of floristic and ecological works, we note the disappearance in some Brazilian regions of major groups of biotechnological interest. In some cases, the introduction of exotic species has been documented, as well as expansion of the distribution range of economically important species. We also verify an increase in the similarities between the Brazilian phycogeographic provinces, although they still remain different. It is possible that these changes have resulted from the warming of South Atlantic water, as observed for its surface in southeastern Brazilian, mainly during the winter. However, unplanned urbanization of coastal areas can also produce similar biodiversity losses, which requires efforts to generate long-term temporal data on the composition, community structure and physiology of macroalgae.

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The study of the impact of climate change on the environment has been based, until very recently, on an global approach, whose interest from a local point of view is very limited. This thesis, on the contrary, has treated the study of the impact of climate change in the Adriatic Sea basin following a twofold strategy of regionalization and integration of numerical models in order to reproduce the present and future scenarios of the system through a more and more realistic and solid approach. In particular the focus of the study was on the impact on the physical environment and on the sediment transport in the basin. This latter is a very new and original issue, to our knowledge still uninvestigated. The study case of the coastal area of Montenegro was particularly studied, since it is characterized by an important supply of sediment through the Buna/Bojana river, second most important in the Adriatic basin in terms of flow. To do this, a methodology to introduce the tidal processes in a baroclinic primitive equations Ocean General Circulation Model was applied and tidal processes were successfully reproduced in the Adriatic Sea, analyzing also the impacts they have on the mean general circulation, on salt and heat transport and on mixing and stratification of the water column in the different seasons of the year. The new hydrodynamical model has been further coupled with a wave model and with a river and sea sediment transport model, showing good results in the reproduction of sediment transport processes. Finally this complex coupled platform was integrated in the period 2001-2030 under the A1B scenario of IPCC, and the impact of climate change on the physical system and on sediment transport was preliminarily evaluated.

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We use long instrumental temperature series together with available field reconstructions of sea-level pressure (SLP) and three-dimensional climate model simulations to analyze relations between temperature anomalies and atmospheric circulation patterns over much of Europe and the Mediterranean for the late winter/early spring (January–April, JFMA) season. A Canonical Correlation Analysis (CCA) investigates interannual to interdecadal covariability between a new gridded SLP field reconstruction and seven long instrumental temperature series covering the past 250 years. We then present and discuss prominent atmospheric circulation patterns related to anomalous warm and cold JFMA conditions within different European areas spanning the period 1760–2007. Next, using a data assimilation technique, we link gridded SLP data with a climate model (EC-Bilt-Clio) for a better dynamical understanding of the relationship between large scale circulation and European climate. We thus present an alternative approach to reconstruct climate for the pre-instrumental period based on the assimilated model simulations. Furthermore, we present an independent method to extend the dynamic circulation analysis for anomalously cold European JFMA conditions back to the sixteenth century. To this end, we use documentary records that are spatially representative for the long instrumental records and derive, through modern analogs, large-scale SLP, surface temperature and precipitation fields. The skill of the analog method is tested in the virtual world of two three-dimensional climate simulations (ECHO-G and HadCM3). This endeavor offers new possibilities to both constrain climate model into a reconstruction mode (through the assimilation approach) and to better asses documentary data in a quantitative way.

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Fully coupled climate carbon cycle models are sophisticated tools that are used to predict future climate change and its impact on the land and ocean carbon cycles. These models should be able to adequately represent natural variability, requiring model validation by observations. The present study focuses on the ocean carbon cycle component, in particular the spatial and temporal variability in net primary productivity (PP) and export production (EP) of particulate organic carbon (POC). Results from three coupled climate carbon cycle models (IPSL, MPIM, NCAR) are compared with observation-based estimates derived from satellite measurements of ocean colour and results from inverse modelling (data assimilation). Satellite observations of ocean colour have shown that temporal variability of PP on the global scale is largely dominated by the permanently stratified, low-latitude ocean (Behrenfeld et al., 2006) with stronger stratification (higher sea surface temperature; SST) being associated with negative PP anomalies. Results from all three coupled models confirm the role of the low-latitude, permanently stratified ocean for anomalies in globally integrated PP, but only one model (IPSL) also reproduces the inverse relationship between stratification (SST) and PP. An adequate representation of iron and macronutrient co-limitation of phytoplankton growth in the tropical ocean has shown to be the crucial mechanism determining the capability of the models to reproduce observed interactions between climate and PP.