Floristic composition and richness of urban domestic gardens in three urban socioeconomic stratifications in the city Heredia,Costa Rica

The urban domestic gardens that are part of urban green areas have become a very important element due to their ecosystematic benefits and the poor information about them. Information regarding the floristic richness of three socioeconomic stratifications from the city of Heredia, Costa Rica is presented in this study. Research was conducted from October 2011 to May 2012. Information was collected using a semi-structured questionnaire, which was provided to 61 garden owners, including the owner’s personal data, time living in the dwelling, area of the property and the garden, variation of its size in time and the garden’s location on the property. In addition, a floristic inventory was conducted in each garden as well as a taxonomic identification of all plants. Vegetative forms and substrates were also noted. Characteristics of the gardens and their owners were then analyzed to determine the relationship of species richness between the three sites studied. The number of plant species recorded was 618, corresponding to 102 families (19 % exotic). Regarding geographical origin, 64, 4 % were exotic, 35,6 % native. Orchidaceae (93 spp.) and Araceae (39 spp.) were the most dominant families. The variables of garden area and location and owner's age determined the garden’s floristic richness. In addition, the garden’s area and vegetative forms varied among the sites studied probably due to socioeconomic differences among them. Diversity of pioneer plants increased with the garden’s area. In sum, this research provides important floristic information of domestic gardens, since, being private property, data about them is scarce and municipal management guidelines are nonexistent.     

Plant-mycorrhizal fungi associations along an urbanization gradient: implications for tree seedling survival

Mycorrhizal fungi symbioses can be critical determining if established seedlings survive or not. Currently, in remnant forests, plants and their fungal symbionts are exposed to varied anthropomorphic effects related to urbanization, however, little is known about their impact on this association. We investigated the relationship between mycorrhizal fungi and tree seedling survival along an urbanization gradient. We planted three species of temperate tree seedlings (Acer rubrum, Carya ovata, and Quercus rubra) in three landscapes: urban, suburban, and rural. We measured the percent of root length colonized by mycorrhizal fungi and monitored survival during their first growing season. We analyzed mycorrhizal colonization as a function of landscape type (urban-rural) and additional variables known to contribute to mycorrhizal colonization (phosphorus, nitrogen, initial plant height). We then analyzed seedling survival as a function of the degree of mycorrhizal fungi colonization associated with the landscape gradient and of additional environmental factors (light and soil moisture). Within a species we found no changes in the levels of mycorrhizal fungi colonization across the urbanization gradient. Each species, however, had markedly different levels of colonization. Survival of A. rubrum was independent of mycorrhizal colonization, while C. ovata and Q. rubra had a significant positive response to increased mycorrhizal fungi. These findings highlight the resilience of mycorrhizal communities across the rural-urban gradient typical of this region, but they also underscore the potential sensitivity of some tree species to lower levels of mycorrhizal fungi colonization.     

Roma and the politics of double discourse in contemporary Europe

ABSTRACT

The article analyses the politics of ‘double discourse’ in relation to Roma that has evolved in contemporary neoliberal Europe. On the one hand, the double discourse promotes the integration, rights and equal opportunities of Roma, on the other, it denies recognition of, and ways to address, enduring structural violence and rising social insecurity. The article argues that the politics of ‘double discourse’, as a neoliberal approach towards Roma, is structured by two contradictory discourses that speak to different audiences, using duplicitous approaches to create anti-Roma consensus and maintain the critical difference and subordinated position of the racialised Romani populations in Europe. By studying the representation of Roma in the cases of so-called 'child theft' in Greece and Ireland, and in the recent ‘refugee crisis’, the paper identifies and discusses three dimensions of contemporary neoliberal double discourse: racialised de-Europeanisation, neoliberal undeservingness and (dis)articulation of citizenship.     

Usability and Feasibility Study of a Remote Cognitive Behavioral Therapy System with Long-Term Unemployed Women

We present the results of the use of a cognitive behavioral therapeutic intervention tool to improve the mental, physical, and social health of a group of long-term unemployed women in Spain. Method: We sent automated text messages (SMS) to the mobile phones of long-term unemployed women selected at random from public social services. During a 28-day intervention period, women received four daily automated text messages on her mobile phone on a predetermined hourly schedule. We measured depression symptoms at the start and end of the intervention and we analyzed qualitative data to determine the acceptability of a remote SMS program. Results: Depression symptoms using the Personal Health Questionnaire-9 (PHQ-9), went from an average of 13.8 at baseline to 4.9 at the end of 28 days (p?=?0.89). One hundred percent of the women reported that they liked receiving the text messages and most found them helpful.     

Approximate confidence intervals for the weighted kappa coefficient of a binary diagnostic test subject to a case–control design

Case–control design to assess the accuracy of a binary diagnostic test (BDT) is very frequent in clinical practice. This design consists of applying the diagnostic test to all of the individuals in a sample of those who have the disease and in another sample of those who do not have the disease. The sensitivity of the diagnostic test is estimated from the case sample and the specificity is estimated from the control sample. Another parameter which is used to assess the performance of a BDT is the weighted kappa coefficient. The weighted kappa coefficient depends on the sensitivity and specificity of the diagnostic test, on the disease prevalence and on the weighting index. In this article, confidence intervals are studied for the weighted kappa coefficient subject to a case–control design and a method is proposed to calculate the sample sizes to estimate this parameter. The results obtained were applied to a real example.     

Adaptive multiple importance sampling for Gaussian processes

In applications of Gaussian processes (GPs) where quantification of uncertainty is a strict requirement, it is necessary to accurately characterize the posterior distribution over Gaussian process covariance parameters. This is normally done by means of standard Markov chain Monte Carlo (MCMC) algorithms, which require repeated expensive calculations involving the marginal likelihood. Motivated by the desire to avoid the inefficiencies of MCMC algorithms rejecting a considerable amount of expensive proposals, this paper develops an alternative inference framework based on adaptive multiple importance sampling (AMIS). In particular, this paper studies the application of AMIS for GPs in the case of a Gaussian likelihood, and proposes a novel pseudo-marginal-based AMIS algorithm for non-Gaussian likelihoods, where the marginal likelihood is unbiasedly estimated. The results suggest that the proposed framework outperforms MCMC-based inference of covariance parameters in a wide range of scenarios.     

Tests for Structural Changes in Time Series of Counts

We propose methods for detecting structural changes in time series with discrete‐valued observations. The detector statistics come in familiar L2‐type formulations incorporating the empirical probability generating function. Special emphasis is given to the popular models of integer autoregression and Poisson autoregression. For both models, we study mainly structural changes due to a change in distribution, but we also comment for the classical problem of parameter change. The asymptotic properties of the proposed test statistics are studied under the null hypothesis as well as under alternatives. A Monte Carlo power study on bootstrap versions of the new methods is also included along with a real data example.     

Model selection criteria in beta regression with varying dispersion

We address the issue of model selection in beta regressions with varying dispersion. The model consists of two submodels, namely: for the mean and for the dispersion. Our focus is on the selection of the covariates for each submodel. Our Monte Carlo evidence reveals that the joint selection of covariates for the two submodels is not accurate in finite samples. We introduce two new model selection criteria that explicitly account for varying dispersion and propose a fast two step model selection scheme which is considerably more accurate and is computationally less costly than usual joint model selection. Monte Carlo evidence is presented and discussed. We also present the results of an empirical application.     

A comparison of L-, LQ-, TL-moment and maximum likelihood high quantile estimates of the GPD and GEV distribution

In this article, L-moments, LQ-moments and TL-moments of the generalized Pareto and generalized extreme-value distributions are derived up to the fourth order. The first three L-, LQ- and TL-moments are used to obtain estimators of their parameters. Performing a simulation study, high-quantile estimates based on L-, LQ-, and TL-moments are compared to the maximum likelihood estimate with respect to their sample mean squared error. This consists of identifying an optimal combination of parameters α and p both considered in the range [0, 0.5] for estimating quantiles by LQ-moments. The results show L-moment and maximum likelihood methods outperform other methods.