Summer habitat associations of bats between riparian landscapes and within riparian areas

The present study examines those features which promote bat feeding in agricultural riparian areas and the riparian habitat associations of individual species. Activity of Nathusius' pipistrelle (Pipistrellus nathusii), common pipistrelle (Pipistrellus pipistrellus), soprano pipistrelle (Pipistrellus pygmaeus), Leisler's bat (Nyctalus leisleri), and Myotis species (Myotis sp.) were recorded, and their habitat associations both "between" and "within" riparian areas were analyzed. General feeding activity was associated with reduced agricultural intensity, riparian hedgerow provision, and habitat diversity. Significant habitat associations for P. pipistrellus were observed only within riparian areas. Myotis species and P. pygmaeus were significantly related to indices of landscape structure and riparian hedgerow across spatial scales. Myotis species were also related to lower levels of riffle flow at both scales of analysis. The importance of these variables changed significantly, however, between analysis scales. The multi-scale investigation of species-habitat associations demonstrated the necessity to consider habitat and landscape characteristics across spatial scales to derive appropriate conservation plans.

Residential segregation in Northern Ireland in 2001: assessing the value of exploring spatial variations

Segregation measures have been applied in the study of many societies, and traditionally such measures have been used to assess the degree of division between social and cultural groups across urban areas, wider regions, or perhaps national areas. The degree of segregation can vary substantially from place to place even within very small areas. In this paper the substantive concern is with religious/political segregation in Northern Ireland—particularly the proportion of Protestants (often taken as an indicator of those who wish to retain the union with Britain) to Catholics (often taken as an indicator of those who favour union with the Republic of Ireland). Traditionally, segregation is measured globally—that is, across all units in a given area. A recent trend in spatial data analysis generally, and in segregation analysis specifically, is to assess local features of spatial datasets. The rationale behind such approaches is that global methods may obscure important spatial variations in the property of interest, and thus prevent full use of the data. In this paper the utility of local measures of residential segregation is assessed with reference to the religious/political composition of Northern Ireland. The paper demonstrates marked spatial variations in the degree and nature of residential segregation across Northern Ireland. It is argued that local measures provide highly useful information in addition to that provided in maps of the raw variables and in standard global segregation measures.

Residential segregation and health in Northern Ireland

Patterns of residential segregation in Northern Ireland reflect historic sectarian conflict as well as current animosities. A number of indices of segregation are examined in this paper and their relative merits in capturing localised societal divisions are discussed.The implications of such divisions on health as mediated through conflict-related stress are then considered. Costed datasets of hospital, community and anxiety/depression prescribing data havebeen assembled and attributed to local geographies.The association between geographical variations in these costs and levels of segregation was modelled using regression analysis.It was found that the level of segregation does not help to explain variations in costed utilisation of acute and elderly services but does explain variations in the costs of prescribing for anxiety and depression with controls for socio-economic deprivation included. Results in this paper would indicate that strategies to promote good relations in Northern Ireland have positive implications for mental health.

Agricultural intensification and biodiversity partitioning in European landscapes comparing plants, carabids, and birds

Effects of agricultural intensification (AI) on biodiversity are often assessed on the plot scale, although processes determining diversity also operate on larger spatial scales. Here, we analyzed the diversity of vascular plants, carabid beetles, and birds in agricultural landscapes in cereal crop fields at the field (n = 1350), farm (n = 270), and European-region (n = 9) scale. We partitioned diversity into its additive components alpha, beta, and gamma, and assessed the relative contribution of beta diversity to total species richness at each spatial scale. AI was determined using pesticide and fertilizer inputs, as well as tillage operations and categorized into low, medium, and high levels. As AI was not significantly related to landscape complexity, we could disentangle potential AI effects on local vs. landscape community homogenization. AI negatively affected the species richness of plants and birds, but not carabid beetles, at all spatial scales. Hence, local AI was closely correlated to beta diversity on larger scales up to the farm and region level, and thereby was an indicator of farm-and region-wide biodiversity losses. At the scale of farms (12.83-20.52%) and regions (68.34-80.18%), beta diversity accounted for the major part of the total species richness for all three taxa, indicating great dissimilarity in environmental conditions on larger spatial scales. For plants, relative importance of alpha diversity decreased with AI, while relative importance of beta diversity on the farm scale increased with AI for carabids and birds. Hence, and in contrast to our expectations, AI does not necessarily homogenize local communities, presumably due to the heterogeneity of farming practices. In conclusion, a more detailed understanding of AI effects on diversity patterns of various taxa and at multiple spatial scales would contribute to more efficient agri-environmental schemes in agroecosystems.

Why is housing tenure associated with a lower risk of admission to a nursing or residential home? Wealth, health and the incentive to keep 'my home'

Background Previous research has shown that home ownership is associated with a reduced risk of admission to institutional care. The extent to which this reflects associations between wealth and health, between wealth and ability to buy in care or increased motivation to avoid admission related to policies on charging is unclear. Taking account of the value of the home, as well as housing tenure, may provide some clarification as to the relative importance of these factors.
Aims To analyse the probability of admission to residential and nursing home care according to housing tenure and house value.
Methods Cox regression was used to examine the association between home ownership, house value and risk of care home admissions over 6 years of follow-up among a cohort of 51 619 people aged 65 years or older drawn from the Northern Ireland Longitudinal Study, a representative sample of approximate to 28% of the population of Northern Ireland.
Results 4% of the cohort (2138) was admitted during follow-up. Homeowners were less likely than those who rented to be admitted to care homes (HR 0.77, 95% CI 0.70 to 0.85, after adjusting for age, sex, health, living arrangement and urban/rural differences). There was a strong association between house value/tenure and health with those in the highest valued houses having the lowest odds of less than good health or limiting long-term illness. However, there was no difference in probability of admission according to house value; HRs of 0.78 (95% CI 0.67 to 0.90) and 0.81 (95% CI 0.70 to 0.95), respectively, for the lowest and highest value houses compared with renters.
Conclusions The requirement for people in the UK with capital resources to contribute to their care is a significant disincentive to institutional admission. This may place an additional burden on carers.

Approximating the Set of Local Minima in Partial RNA Folding Landscapes

Motivation: We study a stochastic method for approximating the set of local minima in partial RNA folding landscapes associated with a bounded-distance neighbourhood of folding conformations. The conformations are limited to RNA secondary structures without pseudoknots. The method aims at exploring partial energy landscapes pL induced by folding simulations and their underlying neighbourhood relations. It combines an approximation of the number of local optima devised by Garnier and Kallel (2002) with a run-time estimation for identifying sets of local optima established by Reeves and Eremeev (2004).

Results: The method is tested on nine sequences of length between 50 nt and 400 nt, which allows us to compare the results with data generated by RNAsubopt and subsequent barrier tree calculations. On the nine sequences, the method captures on average 92% of local minima with settings designed for a target of 95%. The run-time of the heuristic can be estimated by O(n2D?ln?), where n is the sequence length, ? is the number of local minima in the partial landscape pL under consideration and D is the maximum number of steepest descent steps in attraction basins associated with pL.

Residential consumption of gas and electricity in the U.S.: The role of prices and income

We study the residential demand for electricity and gas, working with nationwide household-level data that cover recent years, namely 1997-2007. Our dataset is a mixed panel/multi-year cross-sections of dwellings/households in the 50 largest metropolitan areas in the United States as of 2008. We estimate static and dynamic models of electricity and gas demand. We find strong household response to energy prices, both in the short and long term. From the static models, we get estimates of the own price elasticity of electricity demand in the -0.860 to -0.667 range, while the own price elasticity of gas demand is -0.693 to -0.566. These results are robust to a variety of checks. Contrary to earlier literature (Metcalf and Hassett, 1999; Reiss and White, 2005), we find no evidence of significantly different elasticities across households with electric and gas heat. The price elasticity of electricity demand declines with income, but the magnitude of this effect is small. These results are in sharp contrast to much of the literature on residential energy consumption in the United States, and with the figures used in current government agency practice. Our results suggest that there might be greater potential for policies which affect energy price than may have been previously appreciated. (C) 2011 Elsevier B.V. All rights reserved.