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At least 1,405 records · Page 78
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Effects of Genetic and Physiological Divergence on the Evolution of a Sulfate-Reducing Bacterium under Conditions of Elevated Temperature

ABSTRACT Adaptation via natural selection is an important driver of evolution, and repeatable adaptations of replicate populations, under conditions of a constant environment, have been extensively reported. However, isolated groups of populations in nature tend to harbor both genetic and physiological divergence due to multiple selective pressures that they have encountered. How this divergence affects adaptation of these populations to a new common environment remains unclear. To determine the impact of prior genetic and physiological divergence in shaping adaptive evolution to accommodate a new common environment, an experimental evolution study with the sulfate-reducing bacterium Desulfovibrio vulgaris Hildenborough (DvH) was conducted. Two groups of replicate populations with genetic and physiological divergence, derived from a previous evolution study, were propagated in an elevated-temperature environment for 1,000 generations. Ancestor populations without prior experimental evolution were also propagated in the same environment as a control. After 1,000 generations, all the populations had increased growth rates and all but one had greater fitness in the new environment than the ancestor population. Moreover, improvements in growth rate were moderately affected by the divergence in the starting populations, while changes in fitness were not significantly affected. The mutations acquired at the gene level in each group of populations were quite different, indicating that the observed phenotypic changes were achieved by evolutionary responses that differed between the groups. Overall, our work demonstrated that the initial differences in fitness between the starting populations were eliminated by adaptation and that phenotypic convergence was achieved by acquisition of mutations in different genes. IMPORTANCE Improving our understanding of how previous adaptation influences evolution has been a long-standing goal in evolutionary biology. Natural selection tends to drive populations to find similar adaptive solutions for the same selective conditions. However, variations in historical environments can lead to both physiological and genetic divergence that can make evolution unpredictable. Here, we assessed the influence of divergence on the evolution of a model sulfate-reducing bacterium, Desulfovibrio vulgaris Hildenborough, in response to elevated temperature and found a significant effect at the genetic but not the phenotypic level. Understanding how these influences drive evolution will allow us to better predict how bacteria will adapt to various ecological constraints.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

IM3 SELECT Urbanization Data

IM3 SELECT Urbanization Data Urban fraction is provided in TIF files projected on the WGS84 datum at coarse (1/8 degree) and downscaled (1km) resolutions across the globe for each of three Shared Socioeconomic Pathway (SSP) scenarios corresponding to SSP2, SSP3, and SSP5; and each of two population scenarios corresponding to the default population scenario and an updated population scenario with more detailed projections for the United States. The population projections are provided as CSV files. Folder structure: default_population population urban_fraction coarse SSP2 SSP3 SSP5 downscaled SSP2 SSP3 SSP5united_states_updated_population population urban_fraction coarse SSP2 SSP3 SSP5 downscaled SSP2 SSP3 SSP5 Urban fraction data was produced using the SELECT model v1.0.0 (Gao, J. & O'Neill, B.C. 2019). Default population data derived from Gao, J. & O'Neill, B.C. 2020. Original model outputs produced using the default population data are available from Gao, J. 2020. Updated United States population data derived from Zoraghein, H. & O'Neill, B.C. 2020. Other SELECT input files available at Gao, J. & O'Neill, B.C. 2022.

McManamay, Ryan↗
NASA NTRS1997

Biodiversity within hot spring microbial mat communities: molecular monitoring of enrichment cultures

We have begun to examine the basis for incongruence between hot spring microbial mat populations detected by cultivation or by 16S rRNA methods. We used denaturing gradient gel electrophoresis (DGGE) to monitor enrichments and isolates plated therefrom. At near extincting inoculum dilutions we observed Chloroflexus-like and cyanobacterial populations whose 16S rRNA sequences have been detected in the 'New Pit' Spring Chloroflexus mat and the Octopus Spring cyanobacterial mat. Cyanobacterial populations enriched from 44 to 54 degrees C and 56 to 63 degrees C samples at near habitat temperatures were similar to those previously detected in mat samples of comparable temperatures. However, a lower temperature enrichment from the higher temperature sample selected for the populations found in the lower temperature sample. Three Thermus populations detected by both DGGE and isolation exemplify even more how enrichment may bias our view of community structure. The most abundant population was adapted to the habitat temperature (50 degrees C), while populations adapted to 65 degrees C and 70 degrees C were 10(2)- and 10(4)-fold less abundant, respectively. However, enrichment at 70 degrees C favored the least abundant strain. Inoculum dilution and incubation at the habitat temperature favored the more numerically relevant populations. We enriched many other aerobic chemoorganotrophic populations at various inoculum dilutions and substrate concentrations, most of whose 16S rRNA sequences have not been detected in mats. A common feature of numerically relevant cyanobacterial, Chloroflexus-like and aerobic chemorganotrophic populations, is that they grow poorly and resist cultivation on solidified medium, suggesting plating bias, and that the medium composition and incubation conditions may not reflect the natural microenvironments these populations inhabit.

Non-NASA Center↗
DOE OSTI2022

Verification and Validation of the Stakeholder Tool for Assessing Radioactive Transportation (START) – 22323

The U.S. Department of Energy (DOE) Office of Integrated Waste Management is planning for the eventual transportation, storage, and disposal of spent nuclear fuel (SNF) and high-level radioactive waste (HLW) from nuclear power plant and DOE sites. The Stakeholder Tool for Assessing Radioactive Transportation (START) is a web-based, geospatial decision-support tool developed for evaluating routing options and other aspects of transporting SNF and HLW, covering rail, truck, barge, and intermodal infrastructure and operations in the continental United States. The verification and validation (V&V) process is intended to independently assess START to provide confidence in the ability of START to accurately provide intended results. The V&V process checks the START tool using a variety of methods, ranging from independent hand calculations to comparison of START performance and results to those of other codes. The V&V activity was conducted independently from the START development team with opportunities to provide feedback and collaborate throughout the process. The V&V analyzed attributes of transportation routes produced by START, including route distance and both population and population density captured within buffer zones around routes. Population in the buffer zone, population density in the buffer zone, and route distance were all identified as crucial outputs of the START code and were subject to V&V tasks. Some of the improvements identified through the V&V process were standardizing the underlying population data in START, changing the projection of the population raster data, and changes to the methodology used for population density to improve its applicability for expected users. This collaboration also led to suggested improvements to some of the underlying shape file segments within START. A formal series of test routes went through the V&V process from START version 3.2.1 following the implementation of the recommended improvements to START. The V&V of the buffer zone population and distance reported in START were achieved by utilizing a custom workflow developed in QGIS. This platform was chosen because it is fully independent of START. The buffer zone population and route distances in START showed excellent agreement to independent V&V test results. Over 200 route test cases were run; in all cases, the percent difference in the population within the buffer zone was less than +/- 5%, and the majority of cases were below +/- 1%. These cases were also duplicated in ArcMap, which is Environmental Systems Research Institute’s (ESRI) GIS desktop application. The ArcMap results also show good agreement; however, they cannot be considered independent of START because START also uses ESRI software. The V&V tasks are currently addressing population density and estimated radiation dose in START as well as implementing further automation of the V&V process to allow larger suites of test routes to be run more easily and quickly by less experienced GIS users. These improvements to the V&V process will make it a valuable tool for the development team and the stakeholders so that each new iteration of START can easily be checked for quality and consistency. This paper and presentation will describe the V&V process, findings and implications, and ongoing V&V activities.

START, DOE, Transporation, dose, GIS↗
DOE OSTI2020

Implications from Monitoring Gopher Tortoises at Two Spatial Scales

A problem that conservation biologists face is how to monitor species, given both resource limitations and the inherent challenges of assessing long-term demographic processes. We assessed gopher tortoise (Gopherus polyphemus) abundance at a landscape scale and at the scale of 3 local populations within the Conecuh National Forest (CNF).USA between 1991 and 2017. Landscape-level data were collected 26 from line transect distance sampling arranged uniformly across the CNF and collected during a single season (2011); data for local populations were generated from long-term mark-recapture of individuals at three sites selected based on prior knowledge of high density at each. At a landscape scale, we estimated 5,242 (95% CI = 3,538-7,768) tortoises occurred across the approximately 34,000-ha forest, yielding a density of 0.14-0.32 tortoises/ ha. These low densities across the landscape suggest that, on average, management activities across the property have not allowed tortoise populations to retain social structure needed for long-term persistence. The three local populations, however, contained 25-60 individuals and densities of 1.9–6.9 tortoises/ha. Over the study period, populations at two sites were stable and the third experienced significant population growth. Mean annual survival of individuals was 0.89 and invariant across size classes. Altogether, line transect distance sampling is important for assessing landscape-scale abundance of tortoises but may fail to detect local clusters of high-density sites important for population persistence. Our mark-recapture efforts at the local scale revealed that small populations on these high-density sites can exhibit long-term stability or growth even though they do not meet current established criteria for viability. Improved models that incorporate immigration and emigration and better reflect dynamics of peripheral populations would assist in determining how such populations best contribute to species recovery and regional conservation targets.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Validating Greater Sage-Grouse Individual-based Model (IBM) Tool (Final Report)

The project focused on validating the previously developed Greater Sage-Grouse Individual-based Model (GrSG IBM; LaGory et al. 2012, 2021). The objective was to transform this predictive, spatially and temporally explicit model into a portable resource to assist siting/resource managers in proactively assessing the cumulative impacts of wind energy development on the greater sage-grouse. Utilizing a bottom-up, individual-based approach, the GrSG IBM accounts for landscape context and species behavior, aiming to reduce uncertainty in estimating development impacts and support ecologically mindful land-based wind energy development. The validation effort covered approximately 6,540 km 2 near the Seven Mile Hill Wind Project in Wyoming. The GrSG IBM tool, built on the NetLogo platform (Tisue and Wilensky 2004), was executed over a 50-year period, with the analysis focusing on years following a 10-year initialization phase. Key results demonstrated the tool’s biological soundness across five key biological metrics: non-chick age class distribution (older than 10 weeks), adult sex ratio, life expectancy, population size, and overall population growth. For instance, the tool estimated that 58.6% of the non-chick population was reproductively immature, while the reference ranges from 51.4% to 57.8% (Patterson 1952, Rogers 1964). Experts confirmed the tool’s estimate was within a reasonable range for the species. The tool estimated average life expectancy of 1.43 years, while the reference ranges from 0.9 years to 1.1 years (Ammann 1957, Hamerstrom 1949). Experts also supported the model’s life-expectancy estimate as ecologically sound for the species in the study area. In terms of population change, the model estimated an annual shift between a 0.6% decline and a 1.0% increase over 50 years. While the reference suggests 2.9% annual decline in range-wide populations (Cortes et al. 2023), that includes many at-risk populations in South Dakota and Washington, for example. Our study area—in the northeastern part of Carbon County and western-edge of Albany County, Wyoming—is one of the remaining greater sage-grouse habitats supporting some of the most stable populations. Experts confirmed that the range of the annual population change spanning from a 0.6% decline to a 1.0% increase estimated by the tool was reasonable for our study area for this reason and confirmed that aligned with population estimates from existing studies on the greater sage-grouse and wind energy development in the study area (LeBeau et al. 2017a, Smith et al. 2024). Furthermore, the project showed that temporally explicit biological metrics generated by the GrSG IBM tool can complement the USGS’ Prioritizing Restoration of Sagebrush Ecosystems Tool (PReSET; Duchardt et al. 2021) by incorporating habitat restoration strategies into seasonal habitat suitability models to visualize population responses over time.

17 WIND ENERGY↗
DOE OSTI2021

Uniformly Ordered Binary Decision Algorithm for Benchmark Experiment Correlations in Whisper Validation

When performing a validation exercise for determining the upper subcritical limit of a nuclear criticality safety application, an analyst should select and perform a statistical analysis on a population of benchmark experiments that are neutronically similar to the application. The size of this population should be sufficiently large such that the statistical analysis has a high degree of confidence that the bias plus bias uncertainty (calculational margin) has been accurately quantified. A complication arises because many benchmark experiments share common components, leading to correlations in their measured effective multiplication factors. Correlations between benchmark experiments within the population reduces its predictive power. This motivates the need for methods that consider benchmark experiment correlations and ensure adequate statistical significance of results. The Whisper code is a statistical analysis pack- age that incorporates nuclear data sensitivity coefficients from MCNP to assess benchmark experiment similarity and then performs an extreme-value analysis to estimate the bias plus bias uncertainty. The original methodology in Whisper does not consider the effect of benchmark experiment correlations when making this estimation, and this summary proposes the uniformly ordered binary decision algorithm to address this shortcoming. The original methodology in Whisper computes similarity coefficients ck for an application compared to all benchmark experiments in its library and develops weighting factors for a selected population proportional to the ck values. The methodology can be interpreted as statistically emulating a validation exercise for a particular application where the weighting factors may be viewed as the likelihood that an analyst would include a particular benchmark experiment within the population. The effective sample size of the population is the expected or mean number of benchmark experiments in the population. The uniformly ordered binary decision algorithm identifies clusters of correlated benchmark experiments within the population and then computes adjusted weighting factors based on the magnitude of the correlation coefficients within the cluster to compute a reduced effective sample size accounting for the lower information content because of correlations. Benchmark experiments within the cluster are ordered randomly with equal probability and probabilistic decisions are made as to whether a benchmark. experiment within the cluster should treated as redundant with a previous one; if two redundant benchmark experiments are included, then the conservative worst case bias plus bias uncertainty is used and the pair is counted as a single benchmark experiment in the population. Results are provided for HEU solutions in a research version of the Whisper software using benchmark experiment correlations provided by DICE, the Database for the International Criticality Safety Benchmark Evaluation Project (ICSBEP). These show that there can be a significant increase in the bias plus bias uncertainty because the effective sample size is reduced, and therefore the algorithm, needing to meet sample size requirements, expands the benchmark experiment population by accepting less similar benchmark experiments that would have otherwise not been included.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Waif Gopher Tortoise Survival and Site Fidelity Following Translocation

Gopher tortoises (Gopherus polyphemus) are among the most commonly translocated reptiles. While there are risks associated with any translocation, waif tortoises— animals frequently of unknown origin that have been displaced from the wild and often held in human possession for various reasons and durations—are generally excluded from translocation projects due to heightened concerns of introducing pathogens and uncertainty about the post-release survival of these individuals. If these risks could be managed, waif tortoises could have conservation value, as they can provide the needed numbers to stabilize populations. In the early 1990s, the discovery of an isolated population of gopher tortoises (≤15 individuals) near Aiken, South Carolina, USA, prioritized establishment of the Aiken Gopher Tortoise Heritage Preserve (AGTHP). Due to the population’s need for augmentation and the site’s isolation from other tortoise populations, the AGTHP provided the opportunity to evaluate the post-release survival of translocated waif tortoises without compromising a viable population. Since 2006, >260 waif tortoises have been introduced to the preserve. Using a Cormack-Jolly-Seber modeling framework to analyze release records and capture histories from trapping efforts in 2017 and 2018, we estimated the long-term apparent survival and site fidelity of this population composed largely of waif tortoises. We estimated annual apparent survival probabilities to be high (≥0.90) for subadult, adult male, and adult female tortoises, and these rates were similar to those reported for wild-to-wild translocated gopher tortoises and those from unmanipulated populations. Of the tortoises recaptured within the boundaries of the preserve, 75% were located within 400 m of their release location. Furthermore, these results suggest that waif tortoises could be an important resource in reducing the extirpation risk of isolated populations.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Divergence in heritable life history traits suggests potential for local adaptation and trade‐offs associated with a coal ash disposal site

Abstract Globally, human activities have resulted in rapid environmental changes that present unique challenges for wildlife. However, investigations of local adaptation in response to simultaneous exposure to multiple anthropogenic selection pressures are rare and often generate conflicting results. We used an in situ reciprocal transplant design within a quantitative genetic framework to examine how adaptive evolution and phenotypic plasticity contribute to the persistence of an amphibian population inhabiting an environment characterized by high levels of multiple toxic trace elements. We found evidence of phenotypic divergence that is largely consistent with local adaptation to an environment contaminated with multiple chemical stressors, tied to potential trade‐offs in the absence of contaminants. Specifically, the population derived from the contaminated environment had a reduced risk of mortality and greater larval growth and in the contaminated environment, relative to offspring from the naïve population. Further, while survival in the uncontaminated environment was not compromised in offspring from the contaminant‐exposed population, they did show delayed development and reduced growth rates over larval development, relative to the naïve population. We found no evidence of reduced additive genetic variation in the contaminant‐exposed population, suggesting long‐term selection in a novel environment has not reduced the evolutionary potential of that population. We also saw little evidence that past selection in the ASH environment had reduced trait plasticity in the resident population. Maternal effects were prominent in early development, but we did not detect any trends suggesting these effects were associated with the maternal transfer of toxic trace elements. Our results demonstrate the potential for adaptation to multiple contaminants in a wild amphibian population, which may have facilitated long‐term persistence in a heavily impacted environment.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

LandScan Mosaic

The LandScan program at Oak Ridge National Laboratory (ORNL), in collaboration with the National Geospatial-Intelligence Agency (NGA), continues to deliver the most accurate and up to date global, high resolution gridded population data. Additionally, the latest advancements in the LandScan HD methodology led to reduced latency in development of rapid updates for geopolitical events. With momentum towards reporting more up to date population estimates, feedback from the user community expressed interest in reporting population estimates in ranges - whether to express a level of uncertainty or confirm to leadership and stakeholders the modeled data are estimates. Building upon the need to understand uncertainty or confidence in the modeled data and report ranges at the global scale, LandScan Mosaic was developed. LandScan Mosaic represents the next generation of high-resolution population modeling, building upon the established success of previous LandScan HD iterations. While LandScan HD employed a deterministic big data fusion approach, LandScan Mosaic enhances this methodology by integrating advanced machine learning techniques to impute missing, yet crucial, population model parameters. This advancement allows for probabilistic modeling of building occupancy and population distribution, incorporating uncertainty quantification through Monte Carlo sampling methods. By combining big data fusion with machine learning-driven imputation and stochastic modeling, LandScan Mosaic provides a more comprehensive and robust representation of population dynamics. LandScan Mosaic will be following the in the footsteps of its longstanding counterpart LandScan Global and releasing a global gridded population raster, at the 3-arcsecond resolution. This technical report documents the current stage of development of LandScan Mosaic, detailing the methodologies and data sources behind the modeling. Stakeholders are encouraged to use this document as an authoritative reference for insight into Mosaic’s data development processes. However, readers should note that LandScan Mosaic remains in a late-stage research and development phase, and methodologies and data presented here are subject to refinements ahead of the anticipated global release in Summer 2025. Feedback and inquiries from users and stakeholders are welcomed as we continue to refine and enhance this important population resource.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1993

Triton's cratering record and its time of capture

Recent impact crater counts on the Voyager 2 high resolution images of Triton have resulted in a more accurate crater size/frequency distribution down to about 3 km diameter. These counts reveal a size/frequency distribution characterized by a differential -4 slope. This is consistent with the observation that there are no craters larger than 27 km diameter on the 20 percent of Triton viewed at resolutions capable of detecting them. A -4 slope is deficient in large craters and at the very low crater density on Triton no craters larger than about 30 km are expected on just 20 percent of the satellite. The Triton size distribution is significantly different from the differential -3 slope of the fresh crater population on Miranda, but both show leading/trailing asymmetries. Since Miranda is in prograde orbit this crater population is probably due to objects in heliocentric orbit, i.e., comets. If this crater population is due to comets, then the significantly different crater population on Triton is probably due to some other population of impacting objects. The most likely origin of these objects is planetesimals in planetocentric orbits. Because Triton is in retrograde orbit, objects in prograde planetocentric orbits will also produce a leading/trailing asymmetry. If the Triton craters are largely the result of objects in planetocentric orbit, then where are the comet craters that should be there if they have a differential -3 distribution function as inferred from the Miranda fresh crater population? The most likely answer is that they are there, but at such a low density that they can not be distinguished from the planetocentric population. An upper bound on this density can be estimated by determining the density of a crater population with a differential -3 slope where no craters larger than 27 km would be expected on the 20 percent of Triton viewed by Voyager at resolutions sufficient to detect them. This density is at the density of the largest crater. At this density the number of craters in size bins greater than 27 km is less than 1 for a -3 distribution function. The observed size distribution, the upper limit of the hypothetical comet crater size distribution, and the difference between the observed and the hypothetical comet crater populations is shown.

Strom, R. G.↗
NASA NTRS1991

Demographics of Investigators Involved in OSSA-Funded Research

The birth of the U.S. civil space program and the subsequent, dramatic growth in the ranks of the space science research population occurred in the 1950s and 1960s'. The large, post- Sputnik/ Apollo buildup in space program manpower is now approximately one career-lifetime in the past. It is therefore natural to anticipate that a large fraction of the space program engineers, scientists, and managers who pioneered the early exploration of space are approaching retirement. Such a "retirement wave" bodes both a loss of manpower and, more fundamentally, a loss of experience from the civil-space manpower base. Such losses could play a critical role constraining in NASA's ability to expand or maintain its technical capabilities. If this indeed applies to the NASA space science research population, then the potential for problems is exacerbated by the anticipated growth in flight rates, data volume, and data-set diversity which will accompany the planned expansion in the OSSA science effort during the 1990s and 2000s. The purpose of this study was to describe the OSSA PI/Co-I population and to determine the degree to which the OSSA space science investigator population faces a retirement wave, and to estimate the future population of PIs in the 1990-2010 era. To conduct such a study, we investigated the present demographics of the PI and Co-1 population contained in the NASA/OSSA Announcement of Opportunity (AO) mailing list. PIs represent the "leadership" class of the OSSA scientific researcher population, and Co-Is represent one important, oncoming component of the "replacement" generation. Using the PI population data, we then make projection estimates of the future PI population from 1991 through 2010, under various NASA growth/PI demand scenarios.

Stern, S. Alan↗
NASA NTRSDate not supplied

The Pheno-Evo Model: Evolution of Microbial Phenotypic Diversity in 2D Space

Biologists appreciate microbes for their simplicity and predictability: we assume that a population of genetically identical cells in a uniform environment will all behave the same way. While this assumption is often useful, it is also often wrong. Not only might microbes in a clonal population act differently from one another, the differences may be categorical (growing v. non-growing; toxin-sensitive v. tolerant), and this diversity might be an evolved trait conferring increased fitness on the population. How does such phenotypic heterogeneity evolve? And how does a population find the optimal distribution of phenotypes for a given environment? Efforts at modeling microbial phenotypic heterogeneity often focus on populations with two discrete phenotypic types; phenotypes in continuous distributions remain poorly explored. To address this gap and to explore the role of spatial relationships, we use agent-based modeling to simulate a phenotypically diverse population of microbial cells evolving in the presence of periodic toxic stress. Cells on patches in a 2D grid may degrade toxin, suffer damage from toxin, switch phenotype, and reproduce. An individual's phenotype its toxin degradation rate-- for which there is a tradeoff with reproduction-- and the genotype encodes the distribution of phenotypic values in the population. The rate of toxin diffusion determines how individuals influence their neighbors' environments. We examine the effects of toxin concentration, diffusion rate, and environmental predictability on the survival success of populations with different phenotype distributions, and populations' evolutionary trajectories when phenotype distribution is allowed to evolve. We conduct all simulations on the platform NetLogo, which provides a friendly interface allowing users of any experience level to tweak parameters and run their own simulations. We have also created custom tools in R for analyzing and visualizing the results of multiple runs.

microbial evolution↗
DOE OSTI2026

Synthesizing land use and demographic change in Southeast Asia’s smaller urbanized areas from 2000–2015

The majority of the human population now reside in urban areas today. The United Nations estimates that nearly half of all urban dwellers currently live in cities smaller than 500 000 persons and the majority of future urban growth will take place in Asia and Africa, likely in these smaller urban areas, not mega cities. Thus, understanding the factors that influence urban demographic trajectories in small urban areas is critical to address sustainable and equitable policy initiatives related to food security, changing climate hazard exposure, and economic opportunities. Here we focus on Southeast Asia—a region historically characterized by lower urban population proportions, yet with a rapidly shifting dynamic demographic—to examine correlates of demographic change among smaller cities. We combine two open-source satellite-informed datasets: GHS urban center database (2015) and age-sex gridded data from WorldPop to calculate socio-demographic characteristics to model drivers of change in annualized urban population growth from 2000–2015 for 505 urbanized places. We find a general pattern of decreasing dependency ratios as city-size increases for most urban areas in Southeast Asia. Higher rates of growth and more variation is observed for smaller cities—those with fewer than 300 000 persons, the lowest population limit for UN data on urbanization. When examining covariates of urban population growth, we find significant statistical associations of population change in smaller urbanized areas with climatic, economic, and land cover/land use variables, but with country-specific variations. Characterizing a continuum of urban population development in the context of changing environmental, economic and climate conditions has been an important sustainable development and equity issue for decades, but newer analysis of city-level drivers allows for systematic inquiry thus moving beyond total population counts for policy-relevant insight.

Southeast Asia synthesis↗
DOE OSTI2022

UrbanPop: A spatial microsimulation framework for exploring demographic influences on human dynamics

Ensuring the social equity of planning measures in social systems requires an understanding of human dynamics, particularly how individual relationships, activities, and interactions intersect with individual needs. Spatial microsimulation models (SMSMs) support planning for human security goals by representing human dynamics through realistic, georeferenced synthetic populations, that a) provide a complete representation of social systems while b) also protecting individual privacy. In this paper, we present UrbanPop, an open and reproducible SMSM framework for analysis of human dynamics with high spatial, temporal, and demographic resolution. UrbanPop creates synthetic populations of demographically detailed worker and student agents, positioning them first at probable nighttime locations (home), then moving them to probable daytime locations (work/school). Summary aggregations of these populations match the granular detail available at the census block group level in the American Community Survey Summary File (SF), providing realistic approximations of the actual population. UrbanPop users can select particular demographic traits important in their application, resulting in a highly tailored agent population. We first lay out UrbanPop's baseline methodology, including population synthesis, activity modeling, and diagnostics, then demonstrate these capabilities by developing case studies of shifting population distributions and high-risk populations in Knox County, TN during the global COVID-19 pandemic.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Differential contagiousness of respiratory disease across the United States

The initial contagiousness of a communicable disease within a given population is quantified by the basic reproduction number, $R_0$. This number depends on both pathogen and population properties. On the basis of compartmental models that reproduce Coronavirus Disease 2019 (COVID-19) surveillance data, we used Bayesian inference and the next-generation matrix approach to estimate region-specific $R_0$ values for 280 of 384 metropolitan statistical areas (MSAs) in the United States (US), which account for 95% of the US population living in urban areas and 82% of the total population. We focused on MSA populations after finding that these populations were more uniformly impacted by COVID-19 than state populations. Our maximum a posteriori (MAP) estimates for $R_0$ range from 1.9 to 7.7 and quantify the relative susceptibilities of regional populations to spread of respiratory diseases.

60 APPLIED LIFE SCIENCES↗
NASA NTRS2002

Dynamics of cell proliferation in the adult dentate gyrus of two inbred strains of mice

The output potential of proliferating populations in either the developing or the adult nervous system is critically dependent on the length of the cell cycle (T(c)) and the size of the proliferating population. We developed a new approach for analyzing the cell cycle, the 'Saturate and Survive Method' (SSM), that also reveals the dynamic behaviors in the proliferative population and estimates of the size of the proliferating population. We used this method to analyze the proliferating population of the adult dentate gyrus in 60 day old mice of two inbred strains, C57BL/6J and BALB/cByJ. The results show that the number of cells labeled by exposure to BUdR changes dramatically with time as a function of the number of proliferating cells in the population, the length of the S-phase, cell division, the length of the cell cycle, dilution of the S-phase label, and cell death. The major difference between C57BL/6J and BALB/cByJ mice is the size of the proliferating population, which differs by a factor of two; the lengths of the cell cycle and the S-phase and the probability that a newly produced cell will die within the first 10 days do not differ in these two strains. This indicates that genetic regulation of the size of the proliferating population is independent of the genetic regulation of cell death among those newly produced cells. The dynamic changes in the number of labeled cells as revealed by the SSM protocol also indicate that neither single nor repeated daily injections of BUdR accurately measure 'proliferation.'.

Non-NASA Center↗