Neighbourhood perceptions among inner-city adolescents: Relationships with their individual characteristics and with independently assessed neighbourhood conditions

We investigated relationships between adolescents’ perceptions of their neighbourhood, their mental health and independently assessed indicators of conditions in their residential neighbourhood. The Research with East London Adolescents Community Health Survey (RELACHS) provided information for 2370 adolescents on area perceptions (specifically alienation from/attachment to the area and satisfaction/dissatisfaction with local amenities and services), and on individual and family attributes including mental distress (measured by the Strengths and Difficulties Questionnaire). These were combined for this study with independently assessed small area geographical indicators proposed by government to measure local deprivation in England. A Bayesian regression analysis using Gibbs sampling investigated associations between the predictor variables and neighbourhood perception. Alienation from neighbourhood and dissatisfaction with local amenities was greater for girls than for boys and for the older adolescents sampled. Those of ‘Asian’ or ‘Black’ ethnicity, from relatively harmonious families, or with higher levels of social support were less likely to express negative area perceptions. While previously published research found no significant direct association between mental health and small area indicators, this analysis suggests that those with relatively high levels of distress did have worse area perceptions. Also, certain independently assessed area indicators were associated with adolescents’ views of their neighbourhood.     

De-Europeanising or disengaging? EU environmental policy and Brexit

ABSTRACT

The European Union (EU) has had a profound effect upon its members’ environmental policy. Even in the United Kingdom (UK), the EU’s most recalcitrant member state (historically labeled the ‘Dirty man of Europe’), environmental policy has been Europeanised. As the UK moves to the EU’s exit door it is timely to assess the utility of Europeanisation for understanding policy dynamics in the UK. Drawing upon interviews and extensive engagement with stakeholders, this article analyses the potential impact of Brexit upon environmental policy and politics. The analytical toolkit offered by de-Europeanisation is developed to identify the factors that drive and inhibit de-Europeanisation processes, thereby providing insights that may be applicable in other settings. Disengagement and policy stagnation are presented as more likely environmental outcomes of Brexit, with capacity emerging as a central explanatory variable.     

Ensemble Bayesian model averaging using Markov Chain Monte Carlo sampling

Bayesian model averaging (BMA) has recently been proposed as a statistical method to calibrate forecast ensembles from numerical weather models. Successful implementation of BMA however, requires accurate estimates of the weights and variances of the individual competing models in the ensemble. In their seminal paper (Raftery et al. Mon Weather Rev 133:1155–1174, 2005) has recommended the Expectation–Maximization (EM) algorithm for BMA model training, even though global convergence of this algorithm cannot be guaranteed. In this paper, we compare the performance of the EM algorithm and the recently developed DiffeRential Evolution Adaptive Metropolis (DREAM) Markov Chain Monte Carlo (MCMC) algorithm for estimating the BMA weights and variances. Simulation experiments using 48-hour ensemble data of surface temperature and multi-model streamflow forecasts show that both methods produce similar results, and that their performance is unaffected by the length of the training data set. However, MCMC simulation with DREAM is capable of efficiently handling a wide variety of BMA predictive distributions, and provides useful information about the uncertainty associated with the estimated BMA weights and variances.     

Evaluating the sources of potential migrant species: implications under climate change

As changes in climate become more apparent, ecologists face the challenge of predicting species responses to the new conditions. Most forecasts are based on climate envelopes (CE), correlative approaches that project future distributions on the basis of the current climate often assuming some dispersal lag. One major caveat with this approach is that it ignores the complexity of factors other than climate that contribute to a species' distributional range. To overcome this limitation and to complement predictions based on CE modeling we carried out a transplant experiment of resident and potential-migrant species. Tree seedlings of 18 species were planted side by side from 2001 to 2004 at several locations in the Southern Appalachians and in the North Carolina Piedmont (U.S.A.). Growing seedlings under a large array of environmental conditions, including those forecasted for the next decades, allowed us to model seedling survival as a function of variables characteristic of each site, and from here we were able to make predictions on future seedling recruitment. In general, almost all species showed decreased survival in plots and years with lower soil moisture, including both residents and potential migrants, and in both locations, the Southern Appalachians and the Piedmont. The detrimental effects that anticipated arid conditions could have on seedling recruitment contradict some of the projections made by CE modeling, where many of the species tested are expected to increase in abundance or to expand their ranges. These results point out the importance of evaluating the potential sources of migrant species when modeling vegetation response to climate change, and considering that species adapted to the new climate and the local conditions may not be available in the surrounding regions.