Intra-individual variability of self-esteem in adolescents with spina bifida.

The purpose of this study was to explore intra-individual variability of global self-esteem and physical self-worth in adolescents with spina bifida (n = 3). Three adolescents were assessed in their schools by auto-evaluation over a period of 12 weeks (three times a week) with the Physical Self Inventory-6, a six-item questionnaire with a visual analogue scale. Statistical analyses included auto-correlation function (ACF) for studying the time series. Descriptive statistics demonstrated that in all the dimensions of physical self and global self-esteem, participants showed great variability over time. Auto-correlation function indicated 20 non-stationary and unstable time series, and four stationary time series. The non-stationary evolution of physical self, and global self-esteem in the three adolescents with spina bifida studied may explain the absence of consensus in the literature on the level of the self-perception. Future longitudinal research needs to be engaged.SCOPUS: ar.jinfo:eu-repo/semantics/publishe

sPlot - A new tool for global vegetation analyses

Aims: Vegetation-plot records provide information on the presence and cover or abundance of plants co-occurring in the same community. Vegetation-plot data are spread across research groups, environmental agencies and biodiversity research centers and, thus, are rarely accessible at continental or global scales. Here we present the sPlot database, which collates vegetation plots worldwide to allow for the exploration of global patterns in taxonomic, functional and phylogenetic diversity at the plant community level. Results: sPlot version 2.1 contains records from 1,121,244 vegetation plots, which comprise 23,586,216 records of plant species and their relative cover or abundance in plots collected worldwide between 1885 and 2015. We complemented the information for each plot by retrieving climate and soil conditions and the biogeographic context (e.g., biomes) from external sources, and by calculating community-weighted means and variances of traits using gap-filled data from the global plant trait database TRY. Moreover, we created a phylogenetic tree for 50,167 out of the 54,519 species identified in the plots. We present the first maps of global patterns of community richness and community-weighted means of key traits. Conclusions: The availability of vegetation plot data in sPlot offers new avenues for vegetation analysis at the global scale