991 resultados para Landscape Interactions


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Invasive plants can have different effects of ecosystem functioning and on the provision of ecosystem services, from strongly deleterious impacts to positive effects. The nature and intensity of such effects will depend on the service and ecosystem being considered, but also on features of life strategies of invaders that influence their invasiveness as well as their influence of key processes of receiving ecosystems. To address the combined effect of these various factors we developed a robust and efficient methodological framework that allows to identify areas of possible conflict between ecosystem services and alien invasive plants, considering interactions between landscape invasibility and species invasiveness. Our framework combines the statistical robustness of multi-model inference, efficient techniques to map ecosystem services, and life strategies as a functional link between invasion, functional changes and potential provision of services by invaded ecosystems. The framework was applied to a test region in Portugal, for which we could successfully predict the current patterns of plant invasion, of ecosystem service provision, and finally of probable conflict (expressing concern for negative impacts, and value for positive impacts on services) between alien species richness (total and per plant life strategy) and the potential provision of selected services. Potential conflicts were identified for all combinations of plant strategy and ecosystem service, with an emphasis for those concerning conflicts with carbon sequestration, water regulation and wood production. Lower levels of conflict were obtained between invasive plant strategies and the habitat for biodiversity supporting service. The added value of the proposed framework in the context of landscape management and planning is discussed in perspective of anticipation of conflicts, mitigation of negative impacts, and potentiation of positive effects of plant invasions on ecosystems and their services.

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Peroxisome proliferator-activated receptors (PPARs) compose a family of nuclear receptors that mediate the effects of lipidic ligands at the transcriptional level. In this review, we highlight advances in the understanding of the PPAR ligand binding domain (LBD) structure at the atomic level. The overall structure of PPARs LBD is described, and important protein ligand interactions are presented. Structure-activity relationships between isotypes structures and ligand specificity are addressed. It is shown that the numerous experimental three-dimensional structures available, together with in silico simulations, help understanding the role played by the activating function-2 (AF-2) in PPARs activation and its underlying molecular mechanism. The relation between the PPARs constitutive activity and the intrinsic stability of the active conformation is discussed. Finally, the interactions of PPARs LBD with co-activators or co-repressors, as well as with the retinoid X receptor (RXR) are described and considered in relation to PPARs activation.

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In recent years, one of the most significant progress in the understanding of liver diseases was the demonstration that liver fibrosis is a dynamic process resulting from a balance between synthesis and degradation of several matrix components, collagen in particular. Thus, fibrosis has been found to be a very early event during liver diseases, be it of toxic, viral or parasitic origin, and to be spontaneously reversible, either partially or totally. In liver fibrosis cell matrix interactions are dependent on the existence of the many factors (sometimes acting in combination) which produce the same events at the cellular and molecular levels. These events are: (i) the recruitment of fiber-producing cells, (ii) their proliferation, (iii) the secretion of matrix constituents of the extracellular matrix, and (iv) the remodeling and degradation of the newly formed matrix. All these events represent, at least in principle, a target for a therapeutic intervention aimed at influencing the experimentally induced hepatic fibrosis. In this context, hepatosplenic schistosomiasis is of particular interest, being an immune cell-mediated granulomatous disease and a model of liver fibrosis allowing extensive studies in human and animals as well as providing original in vitro models.

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Anti-idiotypic (anti-Id) T cells from schistosomiasis patients or former patients proliferate upon exposure to polyclonal or monoclonal anti-soluble egg antigen (SEA) antibodies. Chloroquine does not inhibit, the response, which is induced by F(ab')2 (but not soluble Fab) fragments of these antibodies. Purified T cells from former patients require macrophages or exogenous IL-1 to respond to anti-SEA Ids and can respond to matrix-bound Fab fragments in the presence of IL-1. These anti-Id T cells recognize the Ids directly. Chronic schistosomiasis patients immunoregulate the production of a non-IL-2 lymphokine that stimulates IL-2 receptor expression on resting T cells. This regulation is reversed upon chemotherapeutic cure.

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In this study, we explored the predictive role of family interactions and family representations in mothers and fathers during pregnancy for postnatal motherfatherinfant interactions during the first 2 years after birth. Families (N = 42) were seen at the fifth month of pregnancy and at 3 and 18 months after birth. During pregnancy, parents were asked to play with their baby at the first meeting by using a doll in accordance with the procedure of the prenatal Lausanne Trilogue Play (LTP; A. Corboz-Warnery & E. Fivaz-Depeursinge, 2001; E. Fivaz-Depeursinge, F. Frascarolo-Moutinot, & A. Corboz-Warnery, 2010). Family representations were assessed by administering the Family System Test (T. Gehring, 1998). Marital satisfaction and the history of the couple were assessed through self-reported questionnaires. At 3 and 18 months, family interactions were assessed in the postnatal LTP. Infant temperament was assessed through parent reports. Results show that (a) prenatal interactions and child temperament are the most important predictors of family interactions and (b) paternal representations are predictive of family interactions at 3 months. These results show that observational assessment of nascent family interactions is possible during pregnancy, which would allow early screening of family maladjustment. The findings also highlight the necessity of taking into account paternal representations as a significant variable in the development of family interactions.

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Report for the scientific sojourn at the Simon Fraser University, Canada, from July to September 2007. General context: landscape change during the last years is having significant impacts on biodiversity in many Mediterranean areas. Land abandonment, urbanisation and specially fire are profoundly transforming large areas in the Western Mediterranean basin and we know little on how these changes influence species distribution and in particular how these species will respond to further change in a context of global change including climate. General objectives: integrate landscape and population dynamics models in a platform allowing capturing species distribution responses to landscape changes and assessing impact on species distribution of different scenarios of further change. Specific objective 1: develop a landscape dynamic model capturing fire and forest succession dynamics in Catalonia and linked to a stochastic landscape occupancy (SLOM) (or spatially explicit population, SEPM) model for the Ortolan bunting, a species strongly linked to fire related habitat in the region. Predictions from the occupancy or spatially explicit population Ortolan bunting model (SEPM) should be evaluated using data from the DINDIS database. This database tracks bird colonisation of recently burnt big areas (&50 ha). Through a number of different SEPM scenarios with different values for a number of parameter, we should be able to assess different hypothesis in factors driving bird colonisation in new burnt patches. These factors to be mainly, landscape context (i.e. difficulty to reach the patch, and potential presence of coloniser sources), dispersal constraints, type of regenerating vegetation after fire, and species characteristics (niche breadth, etc).

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Report for the scientific sojourn at the University of Lund, Sweden, between May and September 2007. A landscape-scale research approach has been highlighted by a growing body of literature as essential for understanding important ecosystem services as biological control. Aphids are victims of a diversity of enemies making the aphid-enemy interaction a nice example for the role of enemy diversity for the functioning of biological control. Here it is examined the effects of landscape complexity on cereal aphids and associated natural enemies that varied in the degree of specialization. Parasitoids wasps abundance did not differ between landscape types but was strongly negatively related to the percentage of arable land. In contrast, abundances of generalist predators like Coccinellidae were significantly higher in simple landscapes since can benefit from the high availability of a variety of alternative resources within cropping systems. Consequently coccinellidae-to-aphid ratio was significantly higher in fields in homogenous landscapes as compared to fields included in an heterogeneous landscape, suggesting that enemy pressure on cereal aphids increases with landscape simplification. The landscape effect will depend mainly on the degree of specialization of functionally dominant natural enemies, so that the results imply that conservation actions aiming to optimise abundance for one taxonomic group in the agricultural landscape will not automatically increase abundance of other groups. Given that the strength of natural enemy impact on biocontrol depends on landscape features and the role of functionally dominant natural enemies. So, therefore it is essential to focus the future empirical work in examining the schedule of agricultural landscapes that maintain a diversity of generalist and specialist natural enemies.

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Until recently, much effort has been devoted to the estimation of panel data regression models without adequate attention being paid to the drivers of diffusion and interaction across cross section and spatial units. We discuss some new methodologies in this emerging area and demonstrate their use in measurement and inferences on cross section and spatial interactions. Specifically, we highlight the important distinction between spatial dependence driven by unobserved common factors and those based on a spatial weights matrix. We argue that, purely factor driven models of spatial dependence may be somewhat inadequate because of their connection with the exchangeability assumption. Limitations and potential enhancements of the existing methods are discussed, and several directions for new research are highlighted.

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While much of the literature on cross section dependence has focused mainly on estimation of the regression coefficients in the underlying model, estimation and inferences on the magnitude and strength of spill-overs and interactions has been largely ignored. At the same time, such inferences are important in many applications, not least because they have structural interpretations and provide useful interpretation and structural explanation for the strength of any interactions. In this paper we propose GMM methods designed to uncover underlying (hidden) interactions in social networks and committees. Special attention is paid to the interval censored regression model. Our methods are applied to a study of committee decision making within the Bank of England’s monetary policy committee.

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Spatial heterogeneity, spatial dependence and spatial scale constitute key features of spatial analysis of housing markets. However, the common practice of modelling spatial dependence as being generated by spatial interactions through a known spatial weights matrix is often not satisfactory. While existing estimators of spatial weights matrices are based on repeat sales or panel data, this paper takes this approach to a cross-section setting. Specifically, based on an a priori definition of housing submarkets and the assumption of a multifactor model, we develop maximum likelihood methodology to estimate hedonic models that facilitate understanding of both spatial heterogeneity and spatial interactions. The methodology, based on statistical orthogonal factor analysis, is applied to the urban housing market of Aveiro, Portugal at two different spatial scales.

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Until recently, the airways were thought to be sterile unless infected; however, a shift towards molecular methods for the quantification and sequencing of bacterial DNA has revealed that the airways harbour a unique steady-state microbiota. This paradigm shift is changing the way that respiratory research is approached, with a clear need now to consider the effects of host-microorganism interactions in both healthy and diseased lungs. We propose that akin to recent discoveries in intestinal research, dysbiosis of the airway microbiota could underlie susceptibility to, and progression and chronicity of lung disease. In this Opinion article, we summarize current knowledge of the airway microbiota and outline how host-microorganism interactions in the lungs and other tissues might influence respiratory health and disease.