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Localized adverse events, including natural hazards, epidemiological events, and human conflict, underscore the criticality of quantifying and mapping current population. Building on the spatial interpolation technique previously developed for high-resolution population distribution data (LandScan Global and LandScan USA), we have constructed an empirically informed spatial distribution of projected population of the contiguous United States for 2030 and 2050, depicting one of many possible population futures. Whereas most current large-scale, spatially explicit population projections typically rely on a population gravity model to determine areas of future growth, our projection model departs from these by accounting for multiple components that affect population distribution. Modeled variables, which included land cover, slope, distances to larger cities, and a moving average of current population, were locally adaptive and geographically varying. The resulting weighted surface was used to determine which areas had the greatest likelihood for future population change. Population projections of county level numbers were developed using a modified version of the US Census's projectionmethodology, with the US Census's official projection as the benchmark. Applications of our model include incorporating multiple various scenario-driven events to produce a range of spatially explicit population futures for suitability modeling, service area planning for governmental agencies, consequence assessment, mitigation planning and implementation, and assessment of spatially vulnerable populations. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

We develop a potential landscape approach to quantitatively describe experimental data from a fibroblast cell line that exhibits a wide range of GFP expression levels under the control of the promoter for tenascin-C. Time-lapse live-cell microscopy provides data about short-term fluctuations in promoter activity, and flow cytometry measurements provide data about the long-term kinetics, because isolated subpopulations of cells relax from a relatively narrow distribution of GFP expression back to the original broad distribution of responses. The landscape is obtained from the steady state distribution of GFP expression and connected to a potential-like function using a stochastic differential equation description (Langevin/Fokker-Planck). The range of cell states is constrained by a force that is proportional to the gradient of the potential, and biochemical noise causes movement of cells within the landscape. Analyzing the mean square displacement of GFP intensity changes in live cells indicates that these fluctuations are described by a single diffusion constant in log GFP space. This finding allows application of the Kramers' model to calculate rates of switching between two attractor states and enables an accurate simulation of the dynamics of relaxation back to the steady state with no adjustable parameters. With this approach, it is possible to use the steady state distribution of phenotypes and a quantitative description of the short-term fluctuations in individual cells to accurately predict the rates at which different phenotypes will arise from an isolated subpopulation of cells. [ABSTRACT FROM AUTHOR]

The regional community concept embraces the idea that species interactions across large areas shape both the geographic/ecological distributions and the local abundances of populations. Within this framework, I analyzed the distribution and abundance of 79 species of land birds across 142 ca. 10-ha census plots from standardized breeding bird censuses in deciduous and mixed forests of eastern North America. To characterize the regional ecological space, plots were ordinated on the basis of species abundances. Within the regional community defined by these synthetic axes, the distribution and abundance of individual species did not appear to be shaped by competition or to reflect the adaptations of individuals: (i) local abundance and population extent across the ordination axes were unrelated, (ii) pairwise correlation coefficients of species abundances were centered on 0, (iii) average species distribution and abundance were independent of the number of close relatives, and (iv) distribution and abundance exhibited no evolutionary (phylogenetic) conservatism. To explain these seemingly random patterns, I speculate that species are approximately evenly matched competitors over much of the region and that their distributions and relative abundances are determined by the labile coevolutionary outcomes of interactions with specialized pathogens. Thus, despite the appearance that random processes determine patterns in the distribution and abundance of populations in the regional community, it is plausible that species-specific deterministic interactions are responsible. Although competition is a dominant force in ecological communities, variation in the distribution and abundance of individual species might instead reflect the outcome of interactions with specialized antagonists, including pathogens. [ABSTRACT FROM AUTHOR]