989 resultados para Environmental heterogeneity


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Monocytes are central mediators in the development of atherosclerotic plaques. They circulate in blood and eventually migrate into tissue including the vessel wall where they give rise to macrophages and dendritic cells. The existence of monocyte subsets with distinct roles in homeostasis and inflammation suggests specialization of function. These subsets are identified based on expression of the CD14 and CD16 markers. Routinely applicable protocols remain elusive, however. Here, we present an optimized four-color flow cytometry protocol for analysis of human blood monocyte subsets using a specific PE-Cy5-conjugated monoclonal antibody (mAb) to HLA-DR, a PE-Cy7-conjugated mAb to CD14, a FITC-conjugated mAb to CD16, and PE-conjugated mAbs to additional markers relevant to monocyte function. Classical CD14(+)CD16(-) monocytes (here termed "Mo1" subset) expressed high CCR2, CD36, CD64, and CD62L, but low CX(3)CR1, whereas "nonclassical" CD14(lo)CD16(+) monocytes (Mo3) essentially showed the inverse expression pattern. CD14(+)CD16(+) monocytes (Mo2) expressed high HLA-DR, CD36, and CD64. In patients with stable coronary artery disease (n = 13), classical monocytes were decreased, whereas "nonclassical" monocytes were increased 90% compared with healthy subjects with angiographically normal coronary arteries (n = 14). Classical monocytes from CAD patients expressed higher CX(3)CR1 and CCR2 than controls. Thus, stable CAD is associated with expansion of the nonclassical monocyte subset and increased expression of inflammatory markers on monocytes. Flow cytometric analysis of monocyte subsets and marker expression may provide valuable information on vascular inflammation. This may translate into the identification of monocyte subsets as selective therapeutic targets, thus avoiding adverse events associated with indiscriminate monocyte inhibition.

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Cemeteries with many water-filled containers, flowers, sources of human blood, and shade are favorable urban habitats for the proliferation of Aedes aegypti, a vector of yellow fever and dengue. A total of 22,956 containers was examined in the five cemeteries of the city of Buenos Aires, Argentina. The vector was found in four cemeteries that showed an average infestation level of 5.5% (617 positive out of 11,196 water-filled containers). The four cemeteries positive for Ae. aegypti showed significantly different (p<0.01) infestation levels. Vegetation cover and percentage of infestation were significantly correlated (p<0.01), but neither cemetery area nor number of available containers were significantly related to the proportion of positive vases. Our results suggest that the cemeteries of Buenos Aires represent a gradient of habitat favorableness for this vector species, some of which may act as foci for its proliferation and dispersal.

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The main aim of this work is to define an environmental tax on products and services based on their carbon footprint. We examine the relevance of conventional life cycle analysis (LCA) and environmentally extended input-output analysis (EIO) as methodological tools to identify emission intensities of products and services on which the tax is based. The short-term price effects of the tax and the policy implications of considering non-GHG are also analyzed. The results from the specific case study on pulp production show that the environmental tax rate based on the LCA approach (1,8%) is higher than both EIO approaches (0,8% for product and 1,4% for industry approach), but they are comparable. Even though LCA is more product specific and provides detailed analysis, EIO would be the more relevant approach to apply economy wide environmental tax. When the environmental tax considers non-GHG emissions instead of only CO2, sectors such as agriculture, mining of coal and extraction of peat, and food exhibit higher environmental tax and price effects. Therefore, it is worthwhile for policy makers to pay attention on the implication of considering only CO2 tax or GHG emissions tax in order for such a policy measure to be effective and meaningful. Keywords: Environmental tax; Life cycle analysis; Environmental input-output analysis.

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Soil transmitted helminth (STH) infection are endemic in developing countries. A study was carried out of sewage farms, streams and vegetables to determine the sources and routes of STH infection in Sanliurfa, Turkey. Stool samples from farmhouse inhabitants as well as soil and vegetable samples from the gardens were collected and examined. In addition, water samples from streams and vegetable samples from the city market were collected and examined. One hundred and eighty-seven (59.5%) of a total of 314 samples, including 88.4% of the stool samples, 60.8% of the water samples, 84.4% of the soil samples and 14% of the vegetable samples, were found to be positive for STH eggs. These results indicate that the water, soil and vegetables are heavily contaminated, and suggest a vicious circle between humans and the environment. Improving environmental sanitation is imperative for the control of soil-transmitted helminthiasis in Sanliurfa.

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Why generalist and specialist species coexist in nature is a question that has interested evolutionary biologists for a long time. While the coexistence of specialists and generalists exploiting resources on a single ecological dimension has been theoretically and empirically explored, biological systems with multiple resource dimensions (e.g. trophic, ecological) are less well understood. Yet, such systems may provide an alternative to the classical theory of stable evolutionary coexistence of generalist and specialist species on a single resource dimension. We explore such systems and the potential trade-offs between different resource dimensions in clownfishes. All species of this iconic clade are obligate mutualists with sea anemones yet show interspecific variation in anemone host specificity. Moreover, clownfishes developed variable environmental specialization across their distribution. In this study, we test for the existence of a relationship between host-specificity (number of anemones associated with a clownfish species) and environmental-specificity (expressed as the size of the ecological niche breadth across climatic gradients). We find a negative correlation between host range and environmental specificities in temperature, salinity and pH, probably indicating a trade-off between both types of specialization forcing species to specialize only in a single direction. Trade-offs in a multi-dimensional resource space could be a novel way of explaining the coexistence of generalist and specialists.

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Directional selection for parasite resistance is often intense in highly social host species. Using a partial cross-fostering experiment we studied environmental and genetic variation in immune response and morphology in a highly colonial bird species, the house martin (Delichon urbica). We manipulated intensity of infestation of house martin nests by the haematophagous parasitic house martin bug Oeciacus hirundinis either by spraying nests with a weak pesticide or by inoculating them with 50 bugs. Parasitism significantly affected tarsus length, T cell response, immunoglobulin and leucocyte concentrations. We found evidence of strong environmental effects on nestling body mass, body condition, wing length and tarsus length, and evidence of significant additive genetic variance for wing length and haematocrit. We found significant environmental variance, but no significant additive genetic variance in immune response parameters such as T cell response to the antigenic phytohemagglutinin, immunoglobulins, and relative and absolute numbers of leucocytes. Environmental variances were generally greater than additive genetic variances, and the low heritabilities of phenotypic traits were mainly a consequence of large environmental variances and small additive genetic variances. Hence, highly social bird species such as the house martin, which are subject to intense selection by parasites, have a limited scope for immediate microevolutionary response to selection because of low heritabilities, but also a limited scope for long-term response to selection because evolvability as indicated by small additive genetic coefficients of variation is weak.

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The immature stages of Ochlerotatus albifasciatus develop in temporary pools. The present study aims at evaluating the seasonal dynamics of the aquatic stages of this mosquito, also analyzing the relationship among their presence and breeding success to some relevant climatic and environmental variables in the ephemeral rain pools of an urban park. Nineteen cohorts of O. albifasciatus that developed synchronously after rain events were recorded in all seasons. The proportions of mosquito-positive pools were significantly higher during the fall-winter period than in the spring-summer months (p < 0.001). The presence of this mosquito species was positively related to the amount of rain (p < 0.001), whereas negatively correlated to air temperature (p < 0.05) within a 5.2 to 29.7ºC range. The distribution of the number of cohorts per pool throughout the year was grouped (variance/mean: 3.96), indicating that these habitats were not equally suitable as breeding sites. The immature stages of O. albifasciatus were detected in pools belonging to all of the categories of surface area, depth, duration, vegetation cover, and insolation. However, the proportion of pools where immature mosquitoes were detected was positively and significantly related to surface, depth, duration, and vegetation cover. On the other hand, the proportion of mosquito-positive pools was higher at an intermediate insolation degree. Our results suggest that although preimaginal stages were present in all seasons, high temperatures may be unfavorable to larval development, and substrate vegetation may regulate water temperature. The positive relationship between the proportion of mosquito-positive pools and pool size and duration might reflect a strategy of O. albifasciatus to accomplish immature development.

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Syrian dry areas have been for several millennia a place of interaction between human populations and the environment. If environmental constraints and heterogeneity condition the human occupation and exploitation of resources, socio-political, economic and historical elements play a fundamental role. Since the late 1980s, Syrian dry areas are viewed as suffering a serious water crisis, due to groundwater overdraft. The Syrian administration and international development agencies believe that groundwater overexploitation is also leading to a decline of agricultural activities and to poverty increase. Action is thus required to address these problems.However, the overexploitation diagnosis needs to be reviewed. The overexploitation discourse appears in the context of Syria's opening to international organizations and to the market economy. It echoes the international discourse of "global water crisis". The diagnosis is based on national indicators recycling old Soviet data that has not been updated. In the post-Soviet era, the Syrian national water policy seems to abandon large surface water irrigation projects in favor of a strategy of water use rationalization and groundwater conservation in crisis regions, especially in the district of Salamieh.This groundwater conservation policy has a number of inconsistencies. It is justified for the administration and also probably for international donors, since it responds to an indisputable environmental emergency. However, efforts to conserve water are anecdotal or even counterproductive. The water conservation policy appears a posteriori as an extension of the national policy of food self-sufficiency. The dominant interpretation of overexploitation, and more generally of the water crisis, prevents any controversary approach of the status of resources and of the agricultural system in general and thus destroys any attempt to discuss alternatives with respect to groundwater management, allocation, and their inclusion in development programs.A revisited diagnosis of the situation needs to take into account spatial and temporal dimensions of the groundwater exploitation and to analyze the co-evolution of hydrogeological and agricultural systems. It should highlight the adjustments adopted to cope with environmental and economic variability, changes of water availability and regulatory measures enforcements. These elements play an important role for water availability and for the spatial, temporal, sectoral allocation of water resource. The groundwater exploitation in the last century has obviously had an impact on the environment, but the changes are not necessarily catastrophic.The current groundwater use in central Syria increases the uncertainty by reducing the ability of aquifers to buffer climatic changes. However, the climatic factor is not the only source of uncertainty. The high volatility of commodity prices, fuel, land and water, depending on the market but also on the will (and capacity) of the Syrian State to preserve social peace is a strong source of uncertainty. The research should consider the whole range of possibilities and propose alternatives that take into consideration the risks they imply for the water users, the political will to support or not the local access to water - thus involving a redefinition of the economic and social objectives - and finally the ability of international organizations to reconsider pre-established diagnoses.

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The Urn Sohryngkew section of Meghalaya, NE India, located 800-1000 km from the Deccan volcanic province, is one of the most complete Cretaceous-Tertiary boundary (KTB) transitions worldwide with all defining and supporting criteria present: mass extinction of planktic foraminifera, first appearance of Danian species, delta(13)C shift, Ir anomaly (12 ppb) and KTB red layer. The geochemical signature of the KTB layer indicates not only an extraterrestrial signal (Ni and all Platinum Group Elements (PGEs)) of a second impact that postdates Chicxulub, but also a significant component resulting from condensed sedimentation (P), redox fluctuations (As, Co, Fe, Pb, Zn, and to a lesser extent Ni and Cu) and volcanism. From the late Maastrichtian C29r into the early Danian, a humid climate prevailed (kaolinite: 40-60%, detrital minerals: 50-80%). During the latest Maastrichtian, periodic acid rains (carbonate dissolution; CIA index: 70-80) associated with pulsed Deccan eruptions and strong continental weathering resulted in mesotrophic waters. The resulting super-stressed environmental conditions led to the demise of nearly all planktic foraminiferal species and blooms (>95%) of the disaster opportunist Guembelitria cretacea. These data reveal that detrimental marine conditions prevailed surrounding the Deccan volcanic province during the main phase of eruptions in C29r below the KTB. Ultimately these environmental conditions led to regionally early extinctions followed by global extinctions at the KTB. (C) 2011 Elsevier B.V. All rights reserved.

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This paper presents general problems and approaches for the spatial data analysis using machine learning algorithms. Machine learning is a very powerful approach to adaptive data analysis, modelling and visualisation. The key feature of the machine learning algorithms is that they learn from empirical data and can be used in cases when the modelled environmental phenomena are hidden, nonlinear, noisy and highly variable in space and in time. Most of the machines learning algorithms are universal and adaptive modelling tools developed to solve basic problems of learning from data: classification/pattern recognition, regression/mapping and probability density modelling. In the present report some of the widely used machine learning algorithms, namely artificial neural networks (ANN) of different architectures and Support Vector Machines (SVM), are adapted to the problems of the analysis and modelling of geo-spatial data. Machine learning algorithms have an important advantage over traditional models of spatial statistics when problems are considered in a high dimensional geo-feature spaces, when the dimension of space exceeds 5. Such features are usually generated, for example, from digital elevation models, remote sensing images, etc. An important extension of models concerns considering of real space constrains like geomorphology, networks, and other natural structures. Recent developments in semi-supervised learning can improve modelling of environmental phenomena taking into account on geo-manifolds. An important part of the study deals with the analysis of relevant variables and models' inputs. This problem is approached by using different feature selection/feature extraction nonlinear tools. To demonstrate the application of machine learning algorithms several interesting case studies are considered: digital soil mapping using SVM, automatic mapping of soil and water system pollution using ANN; natural hazards risk analysis (avalanches, landslides), assessments of renewable resources (wind fields) with SVM and ANN models, etc. The dimensionality of spaces considered varies from 2 to more than 30. Figures 1, 2, 3 demonstrate some results of the studies and their outputs. Finally, the results of environmental mapping are discussed and compared with traditional models of geostatistics.