Monthly average temperature modelling

This research is associated with the goal of the horticultural sector of the Colombian southwest, which is to obtain climatic information, specifically, to predict the monthly average temperature in sites where it has not been measured. The data correspond to monthly average temperature, and were recorded in meteorological stations at Valle del Cauca, Colombia, South America. Two components are identified in the data of this research: (1) a component due to the temporal aspects, determined by characteristics of the time series, distribution of the monthly average temperature through the months and the temporal phenomena, which increased (El Nino) and decreased (La Nina) the temperature values, and (2) a component due to the sites, which is determined for the clear differentiation of two populations, the valley and the mountains, which are associated with the pattern of monthly average temperature and with the altitude. Finally, due to the closeness between meteorological stations it is possible to find spatial correlation between data from nearby sites. In the first instance a random coefficient model without spatial covariance structure in the errors is obtained by month and geographical location (mountains and valley, respectively). Models for wet periods in mountains show a normal distribution in the errors; models for the valley and dry periods in mountains do not exhibit a normal pattern in the errors. In models of mountains and wet periods, omni-directional weighted variograms for residuals show spatial continuity. The random coefficient model without spatial covariance structure in the errors and the random coefficient model with spatial covariance structure in the errors are capturing the influence of the El Nino and La Nina phenomena, which indicates that the inclusion of the random part in the model is appropriate. The altitude variable contributes significantly in the models for mountains. In general, the cross-validation process indicates that the random coefficient model with spatial spherical and the random coefficient model with spatial Gaussian are the best models for the wet periods in mountains, and the worst model is the model used by the Colombian Institute for Meteorology, Hydrology and Environmental Studies (IDEAM) to predict temperature.

API-CALC 1.0: a computer program for calculating the average probability of identity allowing for substructure, inbreeding and the presence of close relatives

Individual identification via DNA profiling is important in molecular ecology, particularly in the case of noninvasive sampling. A key quantity in determining the number of loci required is the probability of identity (PIave), the probability of observing two copies of any profile in the population. Previously this has been calculated assuming no inbreeding or population structure. Here we introduce formulae that account for these factors, whilst also accounting for relatedness structure in the population. These formulae are implemented in API-CALC 1.0, which calculates PIave for either a specified value, or a range of values, for F-IS and F-ST.

Planning the sustainable eco-city in Taipei: The implementation of green design and green building schemes

Taipei City has put a significant effort toward the implementation of green design and green building schemes towards a sustainable eco-city. Although some of the environmental indicators have not indicated significant progress in environmental improvement, implementing the two schemes has obtained considerable results; therefore, the two schemes are on the right path towards promoting a sustainable eco-city. However, it has to be admitted that the two schemes are a rather “technocratic” set of solutions and eco-centric approach. It is suggested that not only the public sector but also the private sector need to put more effort toward implement the schemes, and the government needs to encourage the private sector to adopt the schemes in practice.

Potential roles and clinical utility of prebiotics in newborns, infants, and children: proceedings from a global prebiotic summit meeting, New York City, June 27-28, 2008

Initial bacterial colonization, including colonization with health-positive bacteria, such as bifidobacteria and lactobacilli, is necessary for the normal development of intestinal innate and adaptive immune defenses. The predominance of beneficial bacteria in the gut microflora of breast-fed infants is thought to be, at least in part, supported by the metabolism of the complex mixture of oligosaccharides present in human breast milk, and a more adult-type intestinal microbiota is found in formula-fed infants. Inadequate gut colonization, dysbiosis, may lead to an increased risk of infectious, allergic, and autoimmune disorders later in life. The addition of appropriate amounts of selected prebiotics to infant formulas can enhance the growth of bifidobacteria or lactobacilli in the colonic microbiota and, thereby, might produce beneficial effects. Among the substrates considered as prebiotics are the oligosaccharides inulin, fructo-oligosaccharides, galacto-oligosaccharides, and lactulose. There are some reports that such prebiotics have beneficial effects on various markers of health. For example, primary prevention trials in infants have provided promising data on prevention of infections and atopic dermatitis. Additional well-designed prospective clinical trials and mechanistic studies are needed to advance knowledge further in this promising field. (J Pediatr 2009;155:S61-70).

Habitat associations and breeding bird community composition within the city of Bristol, UK

Capsule: Different urban breeding bird communities are associated with different habitat types, but, although community species diversity varies significantly, total bird density does not. Aims: To investigate the association between breeding bird communities and habitats within Bristol, UK and how these communities vary in terms of species diversity and total bird abundance. Methods: Breeding density data for 70 species in the metropolitan area of Bristol, UK were subjected to de-trended correspondence analysis to identify the number of different communities present and their indicator species. These data were then used to identify patterns of habitat association with each community and differences in species richness and total bird density. Results: Three communities were identified: a rural community associated with woodland, managed grassland and inland water; a suburban community associated with buildings and residential gardens; and an intermediate community that shared some of these habitat characteristics. Species richness, but not total bird abundance, was lowest in the suburban community. Conclusion: The diversity of species in urban areas appears to be most dependent upon the availability of patches of natural and semi-natural habitats. Residential gardens support fewer species, but those species that are present may be found at high densities.