Explore the vast range of titles available.

Human activity is a major driver of change and has contributed to many of the challenges we face today. Detailed information about human population distribution is fundamental and use of freely available, high-resolution, gridded datasets on global population as a source of such information is increasing. However, there is little research to guide users in dataset choice. This study evaluates five of the most commonly used global gridded population datasets against a high-resolution Swedish population dataset on a pixel level. We show that datasets which employ more complex modeling techniques exhibit lower errors overall but no one dataset performs best under all situations. Furthermore, differences exist in how unpopulated areas are identified and changes in algorithms over time affect accuracy. Our results provide guidance in navigating the differences between the most commonly used gridded population datasets and will help researchers and policy makers identify the most suitable datasets under varying conditions.

Human society has increased its capacity to exploit natural resources thanks to new technologies, which are one of the results of information exchange in the knowledge society. Many approaches to understanding the interactions between human society and natural systems have been developed in the last decades, and some have included considerations about information. However, none of them has considered information as an active variable or flowing entity in the human–natural/social-ecological system, or, moreover, even as a driving force of their interactions. This paper explores these interactions in socio-ecological systems by briefly introducing a conceptual frame focused on the exchange of information, matter, and energy. The human population is presented as a convergence variable of these three physical entities, and a population distribution model for Colombia is developed based on the maximum entropy principle to integrate the balances of related variables as macro-state restrictions. The selected variables were electrical consumption, water demand, and higher education rates (energy, matter, and information). The final model includes statistical moments for previous population distributions. It is shown how population distribution can be predicted yearly by combining these variables, allowing future dynamics exploration. The implications of this model can contribute to bridging information sciences and sustainability studies.

Background & objectives: Anaplasma phagocytophilum causes human granulocytic anaplasmosis; a febrile tick-borne bacterial zoonosis of increasing public health importance in many parts of the world which is life threatening in undiagnosed, misdiagnosed and untreated cases. In this study we determined and reported the global status of the pathogen in man. Methods: The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines was used to perform a systematic review and meta-analysis of data published in six electronic databases between 1970 and 2020. We pooled data using the random-effects model, performed sensitivity analysis by the single study deletion method and assess across study bias by the funnel plot and its statistical significance by the Egger's regression test. Results: A total of 7018 cases of A. phagocytophilum were reported from 48,619 individuals examined across 22 countries in three continents. Overall pooled estimate was 8.13% (95% CI: 5.70 - 11.47) with a range of 4.64 (95% CI: 1.78 - 11.54) to 12.18% (95% CI: 7.66 - 18.83) across sub-groups. Regional prevalence was highest in North America 11.07% (95% CI: 3.13 - 32.38), while that in relation to study population was highest among occupationally exposed population 11.41% (95% CI: 5.69 - 21.56). Interpretation & conclusion: The study revealed a significant variation in the prevalence of A. phagocytophilum across Asia, Europe and North America, with the highest prevalence in North America and among occupationally exposed population. To curtail the menace of this growing public health crisis, we recommend integrated control programmes involving tick control, the use of appropriate clothing by occupationally exposed population and health education.

The goals of this study were to quantify the relationship between population density and climatic variables over Russia. A paired GIS-analysis of the population density layer (a dependent variable) on climatic layers of warmth and water resources and climate severity (independent variables) resulted in a multiple linear bioclimatic model of the population density in Russia. The model explained 38% of the population density variation by climate. We applied our population model to the extreme climate change scenario RCP 8.5 of the twenty CMIP5 GCMs ensemble to identify tendencies of the population density redistribution in a warmer climate by the end of the 21st century. Under the extreme RCP 8.5 scenario, winter temperature anomalies would be 6-12°C and summer temperature anomalies 4-7°C warmer, and annual precipitation anomalies 50-200 mm greater than the 1961-90 climate. When coupled with ensemble RCP 8.5 climates, our population model predicted the population density distribution across Russia. Over most of the country, the potential population density would increase, on average, but would remain low in permafrost regions in Siberia and the Far East by the end of the century. However, the demographers predict that the population in Russia may decrease by the mid-century to 92-120 mln people of 146 mln at present. Only the replacement migration may compensate for this loss of labor resources.

Body fat distribution is a heritable trait and a well-established predictor of adverse metabolic outcomes, independent of overall adiposity. To increase our understanding of the genetic basis of body fat distribution and its molecular links to cardiometabolic traits, here we conduct genome-wide association meta-analyses of traits related to waist and hip circumferences in up to 224,459 individuals. We identify 49 loci (33 new) associated with waist-to-hip ratio adjusted for body mass index (BMI), and an additional 19 loci newly associated with related waist and hip circumference measures ( P  < 5 × 10 −8 ). In total, 20 of the 49 waist-to-hip ratio adjusted for BMI loci show significant sexual dimorphism, 19 of which display a stronger effect in women. The identified loci were enriched for genes expressed in adipose tissue and for putative regulatory elements in adipocytes. Pathway analyses implicated adipogenesis, angiogenesis, transcriptional regulation and insulin resistance as processes affecting fat distribution, providing insight into potential pathophysiological mechanisms. Genome-wide association meta-analyses of waist-to-hip ratio adjusted for body mass index in more than 224,000 individuals identify 49 loci, 33 of which are new and many showing significant sexual dimorphism with a stronger effect in women; pathway analyses implicate adipogenesis, angiogenesis, transcriptional regulation and insulin resistance as processes affecting fat distribution. Cardiometabolic traits linked to body fat distribution In the first of a pair of Articles in this issue from the GIANT Consortium, genome-wide association meta-analyses of waist and hip circumference-related traits in more than 200,000 individuals have been used to identify 49 loci — 33 of them new — associated with waist-to-hip ratio adjusted for body mass index and an additional 19 loci associated with related waist and hip circumference measures. A subset of these loci shows significant sexual dimorphism, with many showing a stronger effect in women. Analyses implicate adipogenesis, angiogenesis, transcriptional regulation and insulin resistance as processes affecting fat distribution, providing insight into potential pathophysiological mechanisms and offer potential targets for interventions in the risks associated with abdominal fat accumulation.

This chapter contains sections titled: Abstract Study Area and Background Pali Aike Volcanic Field (PAVF) The Cordillera Supra ‐ Regional Patterns General Discussion Conclusions Acknowledgments References

Using as his example post-World War I Italy and the government's interest in the size, growth rate, and \"vitality\" of its national population, David Horn suggests a genealogy for our present understanding of procreation as a site for technological intervention and political contestation.Social Bodieslooks at how population and reproductive bodies came to be the objects of new sciences, technologies, and government policies during this period. It examines the linked scientific constructions of Italian society as a body threatened by the \"disease\" of infertility, and of women and men associalbodies--located neither in nature nor in the private sphere, but in that modern domain of knowledge and intervention carved out by statistics, sociology, social hygiene, and social work. Situated at the intersection of anthropology, cultural studies, and feminist studies of science, the book explores the interrelated factors that produced the practices of reason we call social science and social planning. David Horn draws on many sources to analyze the discourses and practices of \"social experts,\" the resistance these encountered, and the often unintended effects of the new objectification of bodies and populations. He shows how science, while affirming that maternity was part of woman's \"nature,\" also worked to remove reproduction from the domain of the natural, making it an object of technological intervention. This reconstitution of bodies through the sciences and technologies of the social, Horn argues, continues to have material consequences for women and men throughout the West.

During the past few decades, technologies such as remote sensing, geographical information systems, and global positioning systems have transformed the way the distribution of human population is studied and modeled in space and time. However, the mapping of populations remains constrained by the logistics of censuses and surveys. Consequently, spatially detailed changes across scales of days, weeks, or months, or even year to year, are difficult to assess and limit the application of human population maps in situations in which timely information is required, such as disasters, conflicts, or epidemics. Mobile phones (MPs) now have an extremely high penetration rate across the globe, and analyzing the spatiotemporal distribution of MP calls geolocated to the tower level may overcome many limitations of census-based approaches, provided that the use of MP data is properly assessed and calibrated. Using datasets of more than 1 billion MP call records from Portugal and France, we show how spatially and temporarily explicit estimations of population densities can be produced at national scales, and how these estimates compare with outputs produced using alternative human population mapping methods. We also demonstrate how maps of human population changes can be produced over multiple timescales while preserving the anonymity of MP users. With similar data being collected every day by MP network providers across the world, the prospect of being able to map contemporary and changing human population distributions over relatively short intervals exists, paving the way for new applications and a near real-time understanding of patterns and processes in human geography.

Cimatti, M., Ranc, N., Benítez-López, A., Maiorano, L., Boitani, L., Cagnacci, F., Čengić, M., Ciucci, P., Huijbregts, M.A.J., Krofel, M., López-Bao, J.V., Selva, N., Andren, H., Bautista, C., Ćirović, D., Hemmingmoore, H., Reinhardt, I., Marenče, M., Mertzanis, Y., Pedrotti, L., Trbojević, I., Zetterberg, A., Zwijacz-Kozica, T., Santini, L.