TRY plant trait database - enhanced coverage and open access

Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

Secular Trends in the Prevalence of Overweight and Obesity in Sicilian Schoolchildren Aged 11–13 Years During the Last Decade

The present study evaluates trends in the prevalence of overweight and obesity in relation to gender and area of residence between two cohorts of students aged 11–13 years in Sicily. The analysis was performed on 1,839 schoolchildren, with 924 and 915 children being studied in 1999–2001 and 2009–2010, respectively. The children who were enrolled during 2009–2010 had significantly higher body mass indexes (BMI), BMI z-scores, and waist circumferences than the children who were studied during 1999–2001 (p<0.0001 for all); these differences was also observed when the cohort was subdivided according to gender or residence area The prevalence of obesity increased significantly from 7.9% in 1999–2001 to 13.7% in 2009–2010 (p<0.0001), whereas thinness decreased significantly from 10.1% to 2.3% (p<0.0001) in the same periods. The increase of trends in the prevalence of obesity was significantly higher in males (9.7% vs. 17.6%, p = 0.0006) than in females (6.3% vs. 9.8%, p = 0.04) and was slightly higher in urban areas (8.8% vs. 14.3%, p = 0.002) than in rural areas (7.8% vs. 13.0%, p = 0.012). The male gender was associated with a higher risk of being overweight or obese (odds ratio: 1.63; 95% confidence intervals: 1.24–2.15; p = 0.0005) in 2009–2010 than in 1999–2001, after adjusting for age and the residence area. In conclusion, this study showed an increasing trend in the prevalence of overweight and obesity in Sicilian schoolchildren during the last decade and that this trend was related to gender, age and the area of residence. More specifically, our data indicated that the prevalence of obesity increased by 5.8%, the prevalence of thinness decreased by 7.8% and the prevalence of normal-weight children did not change over the course of a decade. These results suggest a shift in the body weights of Sicilian children toward the upper percentiles

Measurement of the Positive Muon Anomalous Magnetic Moment to 0.20 ppm

We present a new measurement of the positive muon magnetic anomaly, a_{μ}≡(g_{μ}-2)/2, from the Fermilab Muon g-2 Experiment using data collected in 2019 and 2020. We have analyzed more than 4 times the number of positrons from muon decay than in our previous result from 2018 data. The systematic error is reduced by more than a factor of 2 due to better running conditions, a more stable beam, and improved knowledge of the magnetic field weighted by the muon distribution, ω[over ˜]_{p}^{'}, and of the anomalous precession frequency corrected for beam dynamics effects, ω_{a}. From the ratio ω_{a}/ω[over ˜]_{p}^{'}, together with precisely determined external parameters, we determine a_{μ}=116 592 057(25)×10^{-11} (0.21 ppm). Combining this result with our previous result from the 2018 data, we obtain a_{μ}(FNAL)=116 592 055(24)×10^{-11} (0.20 ppm). The new experimental world average is a_{μ}(exp)=116 592 059(22)×10^{-11} (0.19 ppm), which represents a factor of 2 improvement in precision

TRY plant trait database - enhanced coverage and open access

Plant traits—the morphological, anatomical, physiological, biochemical and phenological characteristics of plants—determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits—almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

A comparison of a social support physical activity intervention in weight management among post-partum Latinas

BACKGROUND: Weight gain during the childbearing years and failure to lose pregnancy weight after birth contribute to the development of obesity in postpartum Latinas. METHODS: Madres para la Salud [Mothers for Health] was a 12-month, randomized controlled trial exploring a social support intervention with moderate-intensity physical activity (PA) seeking to effect changes in body fat, fat tissue inflammation, and depression symptoms in sedentary postpartum Latinas. This report describes the efficacy of the Madres intervention. RESULTS: The results show that while social support increased during the active intervention delivery, it declined to pre-intervention levels by the end of the intervention. There were significant achievements in aerobic and total steps across the 12 months of the intervention, and declines in body adiposity assessed with bioelectric impedance. CONCLUSIONS: Social support from family and friends mediated increases in aerobic PA resulting in decrease in percent body fat. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT01908959

A review of zoonotic infection risks associated with the wild meat trade in Malaysia.

The overhunting of wildlife for food and commercial gain presents a major threat to biodiversity in tropical forests and poses health risks to humans from contact with wild animals. Using a recent survey of wildlife offered at wild meat markets in Malaysia as a basis, we review the literature to determine the potential zoonotic infection risks from hunting, butchering and consuming the species offered. We also determine which taxa potentially host the highest number of pathogens and discuss the significant disease risks from traded wildlife, considering how cultural practices influence zoonotic transmission. We identify 51 zoonotic pathogens (16 viruses, 19 bacteria and 16 parasites) potentially hosted by wildlife and describe the human health risks. The Suidae and the Cervidae families potentially host the highest number of pathogens. We conclude that there are substantial gaps in our knowledge of zoonotic pathogens and recommend performing microbial food safety risk assessments to assess the hazards of wild meat consumption. Overall, there may be considerable zoonotic risks to people involved in the hunting, butchering or consumption of wild meat in Southeast Asia, and these should be considered in public health strategies