Understanding preferences for tree attributes: the relative effects of socio-economic and local environmental factors

Urban plant biodiversity is influenced by both the physical environment and attitudes and preferences of urban residents for specific plant types. Urban residents are assumed to be disconnected from their immediate environment, and cultural and societal factors have been emphasized over environmental factors in studies of landscaping choices. However, we postulate that local climatic and environmental factors can also affect preferences for plant attributes. Therefore, spatial and temporal patterns in urban tree biodiversity may be driven not only by the direct effect of environmental variables on plant function, but also by the effect of environmental variables on attitudes toward trees and associated choices about which types of trees to plant. Here, we tested the relative effects of socio-economic and local environmental factors on preferences toward tree attributes in five counties in southern California in and surrounding Los Angeles, based on 1,029 household surveys. We found that local environmental factors have as strong an effect on preferences for tree attributes as socio-economic factors. Specifically, people located in hotter climates (average maximum temperature 25.1 °C) were more likely to value shade trees than those located in cooler regions (23.1 °C). Additionally, people located in desert areas were less likely to consider trees to be important in their city compared with people located in naturally forested areas. Overall, our research demonstrates the inherent connections between local environmental factors and perceptions of nature, even in large modern cities. Accounting for these factors can contribute to the growing interest in understanding patterns of urban biodiversity

The accretion of galaxies into groups and clusters

We use the galaxy stellar mass and halo merger tree information from the semi-analyticmodel galaxy catalogue of Font et al. (2008) to examine the accretion of galaxies into a large sample of groups and clusters, covering a wide range in halo mass (1012.9 to 1015.3 h−1 M⊙), and selected from each of four redshift epochs (z=0, 0.5, 1.0 and 1.5). We find that clusters at all examined redshifts have accreted a significant fraction of their final galaxy populations through galaxy groups. A 1014.5 h−1 M⊙ mass cluster at z=0 has, on average, accreted_ 40% of its galaxies (Mstellar > 109 h−1 M⊙) from halos with masses greater than 1013 h−1 M⊙. Further, the galaxies which are accreted through groups are more massive, on average, than galaxies accreted through smaller halos or from the field population. We find that at a given epoch, the fraction of galaxies accreted from isolated environments is independent of the final cluster or group mass. In contrast, we find that observing a cluster of the same halo mass at each redshift epoch implies different accretion rates of isolated galaxies, from 5-6 % per Gyr at z=0 to 15% per Gyr at z=1.5. We find that combining the existence of a Butcher Oemler effect at z=0.5 and the observations that galaxies within groups display significant environmental effects with galaxy accretion histories justifies striking conclusions. Namely, that the dominant environmental process must begin to occur in halos of 1012 – 1013 h−1 M⊙, and act over timescales of > 2 Gyrs. This argues in favor of a mechanism like “strangulation”, in which the hot halo of a galaxy is stripped upon infalling into a more massive halo . This simple model predicts that by z=1.5 galaxy groups and clusters will display little to no environmental effects. This conclusion may limit the effectiveness of red sequence cluster finding methods at high redshift

Area-level deprivation and adiposity in children: is the relationship linear?

OBJECTIVE: It has been suggested that childhood obesity is inversely associated with deprivation, such that the prevalence is higher in more deprived groups. However, comparatively few studies actually use an area-level measure of deprivation, limiting the scope to assess trends in the association with obesity for this indicator. Furthermore, most assume a linear relationship. Therefore, the aim of this study was to investigate associations between area-level deprivation and three measures of adiposity in children: body mass index (BMI), waist circumference (WC) and waist-to-height ratio (WHtR). DESIGN: This is a cross-sectional study in which data were collected on three occasions a year apart (2005-2007). SUBJECTS: Data were available for 13,333 children, typically aged 11-12 years, from 37 schools and 542 lower super-output areas (LSOAs). MEASURES: Stature, mass and WC. Obesity was defined as a BMI and WC exceeding the 95th centile according to British reference data. WHtR exceeding 0.5 defined obesity. The Index of Multiple Deprivation affecting children (IDACI) was used to determine area-level deprivation. RESULTS: Considerable differences in the prevalence of obesity exist between the three different measures. However, for all measures of adiposity the highest probability of being classified as obese is in the middle of the IDACI range. This relationship is more marked in girls, such that the probability of being obese for girls living in areas at the two extremes of deprivation is around half that at the peak, occurring in the middle. CONCLUSION: These data confirm the high prevalence of obesity in children and suggest that the relationship between obesity and residential area-level deprivation is not linear. This is contrary to the 'deprivation theory' and questions the current understanding and interpretation of the relationship between obesity and deprivation in children. These results could help make informed decisions at the local level

Patterns of primary care and mortality among patients with schizophrenia or diabetes: a cluster analysis approach to the retrospective study of healthcare utilization

Abstract Background Patients with schizophrenia have difficulty managing their medical healthcare needs, possibly resulting in delayed treatment and poor outcomes. We analyzed whether patients reduced primary care use over time, differentially by diagnosis with schizophrenia, diabetes, or both schizophrenia and diabetes. We also assessed whether such patterns of primary care use were a significant predictor of mortality over a 4-year period. Methods The Veterans Healthcare Administration (VA) is the largest integrated healthcare system in the United States. Administrative extracts of the VA's all-electronic medical records were studied. Patients over age 50 and diagnosed with schizophrenia in 2002 were age-matched 1:4 to diabetes patients. All patients were followed through 2005. Cluster analysis explored trajectories of primary care use. Proportional hazards regression modelled the impact of these primary care utilization trajectories on survival, controlling for demographic and clinical covariates. Results Patients comprised three diagnostic groups: diabetes only (n = 188,332), schizophrenia only (n = 40,109), and schizophrenia with diabetes (Scz-DM, n = 13,025). Cluster analysis revealed four distinct trajectories of primary care use: consistent over time, increasing over time, high and decreasing, low and decreasing. Patients with schizophrenia only were likely to have low-decreasing use (73% schizophrenia-only vs 54% Scz-DM vs 52% diabetes). Increasing use was least common among schizophrenia patients (4% vs 8% Scz-DM vs 7% diabetes) and was associated with improved survival. Low-decreasing primary care, compared to consistent use, was associated with shorter survival controlling for demographics and case-mix. The observational study was limited by reliance on administrative data. Conclusion Regular primary care and high levels of primary care were associated with better survival for patients with chronic illness, whether psychiatric or medical. For schizophrenia patients, with or without comorbid diabetes, primary care offers a survival benefit, suggesting that innovations in treatment retention targeting at-risk groups can offer significant promise of improving outcomes.http://deepblue.lib.umich.edu/bitstream/2027.42/78274/1/1472-6963-9-127.xmlhttp://deepblue.lib.umich.edu/bitstream/2027.42/78274/2/1472-6963-9-127.pdfPeer Reviewe

Discovery of Sexual Dimorphisms in Metabolic and Genetic Biomarkers

Metabolomic profiling and the integration of whole-genome genetic association data has proven to be a powerful tool to comprehensively explore gene regulatory networks and to investigate the effects of genetic variation at the molecular level. Serum metabolite concentrations allow a direct readout of biological processes, and association of specific metabolomic signatures with complex diseases such as Alzheimer's disease and cardiovascular and metabolic disorders has been shown. There are well-known correlations between sex and the incidence, prevalence, age of onset, symptoms, and severity of a disease, as well as the reaction to drugs. However, most of the studies published so far did not consider the role of sexual dimorphism and did not analyse their data stratified by gender. This study investigated sex-specific differences of serum metabolite concentrations and their underlying genetic determination. For discovery and replication we used more than 3,300 independent individuals from KORA F3 and F4 with metabolite measurements of 131 metabolites, including amino acids, phosphatidylcholines, sphingomyelins, acylcarnitines, and C6-sugars. A linear regression approach revealed significant concentration differences between males and females for 102 out of 131 metabolites (p-values<3.8 x 10(-4); Bonferroni-corrected threshold). Sex-specific genome-wide association studies (GWAS) showed genome-wide significant differences in beta-estimates for SNPs in the CPS1 locus (carbamoyl-phosphate synthase 1, significance level: p<3.8 x 10(-10); Bonferroni-corrected threshold) for glycine. We showed that the metabolite profiles of males and females are significantly different and, furthermore, that specific genetic variants in metabolism-related genes depict sexual dimorphism. Our study provides new important insights into sex-specific differences of cell regulatory processes and underscores that studies should consider sex-specific effects in design and interpretation

Transkingdom Networks: A Systems Biology Approach to Identify Causal Members of Host-Microbiota Interactions

Improvements in sequencing technologies and reduced experimental costs have resulted in a vast number of studies generating high-throughput data. Although the number of methods to analyze these "omics" data has also increased, computational complexity and lack of documentation hinder researchers from analyzing their high-throughput data to its true potential. In this chapter we detail our data-driven, transkingdom network (TransNet) analysis protocol to integrate and interrogate multi-omics data. This systems biology approach has allowed us to successfully identify important causal relationships between different taxonomic kingdoms (e.g. mammals and microbes) using diverse types of data

Garden and landscape-scale correlates of moths of differing conservation status: significant effects of urbanization and habitat diversity

Moths are abundant and ubiquitous in vegetated terrestrial environments and are pollinators, important herbivores of wild plants, and food for birds, bats and rodents. In recent years, many once abundant and widespread species have shown sharp declines that have been cited by some as indicative of a widespread insect biodiversity crisis. Likely causes of these declines include agricultural intensification, light pollution, climate change, and urbanization; however, the real underlying cause(s) is still open to conjecture. We used data collected from the citizen science Garden Moth Scheme (GMS) to explore the spatial association between the abundance of 195 widespread British species of moth, and garden habitat and landscape features, to see if spatial habitat and landscape associations varied for species of differing conservation status. We found that associations with habitat and landscape composition were species-specific, but that there were consistent trends in species richness and total moth abundance. Gardens with more diverse and extensive microhabitats were associated with higher species richness and moth abundance; gardens near to the coast were associated with higher richness and moth abundance; and gardens in more urbanized locations were associated with lower species richness and moth abundance. The same trends were also found for species classified as increasing, declining and vulnerable under IUCN (World Conservation Union) criteria

Social media-predicted personality traits and values can help match people to their ideal jobs

© 2019 National Academy of Sciences. All rights reserved. Work is thought to be more enjoyable and beneficial to individuals and society when there is congruence between one's personality and one's occupation. We provide large-scale evidence that occupations have distinctive psychological profiles, which can successfully be predicted from linguistic information unobtrusively collected through social media. Based on 128,279 Twitter users representing 3,513 occupations, we automatically assess user personalities and visually map the personality profiles of different professions. Similar occupations cluster together, pointing to specific sets of jobs that one might be well suited for. Observations that contradict existing classifications may point to emerging occupations relevant to the 21st century workplace. Findings illustrate how social media can be used to match people to their ideal occupation