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At least 55 records · Page 3

Geographic patterns of genomic diversity and structure in the C4 grass Panicum hallii across its natural distribution

Abstract Geographic patterns of within-species genomic diversity are shaped by evolutionary processes, life history and historical and contemporary factors. New genomic approaches can be used to infer the influence of such factors on the current distribution of infraspecific lineages. In this study, we evaluated the genomic and morphological diversity as well as the genetic structure of the C4 grass Panicum hallii across its complex natural distribution in North America. We sampled extensively across the natural range of P. hallii in Mexico and the USA to generate double-digestion restriction-associated DNA (ddRAD) sequence data for 423 individuals from 118 localities. We used these individuals to study the divergence between the two varieties of P. hallii, P. hallii var. filipes and P. hallii var. hallii as well as the genetic diversity and structure within these groups. We also examined the possibility of admixture in the geographically sympatric zone shared by both varieties, and assessed distribution shifts related with past climatic fluctuations. There is strong genetic and morphological divergence between the varieties and consistent genetic structure defining seven genetic clusters that follow major ecoregions across the range. South Texas constitutes a hotspot of genetic diversity with the co-occurrence of all genetic clusters and admixture between the two varieties. It is likely a recolonization and convergence point of populations that previously diverged in isolation during fragmentation events following glaciation periods.

54 ENVIRONMENTAL SCIENCES↗

Human papillomavirus–associated anal squamous cell carcinoma: sociodemographic, geographic, and county-level economic trends in incidence rates—United States, 2001-2019

Abstract Background Incidence of anal squamous cell carcinoma is increasing, but vaccination against human papillomavirus (HPV) and removal of precancerous anal lesions could prevent new cases. The overall HPV-associated cancer incidence is reported to be higher in rural populations and in counties with lower economic status. We assessed these differences specifically for HPV-associated anal squamous cell carcinoma and described the geographic, county-level economic, and sociodemographic variations in incidence rates and trends. Methods We analyzed data from the US Cancer Statistics to assess age-standardized incidence rates of HPV-associated squamous cell carcinomas among adults aged 18 years and older from 2001 to 2019. We calculated rate ratios and 95% confidence intervals to examine differences in incidence rates. We also quantified changes in incidence rates over time using joinpoint regression. Results From 2001 to 2019, 72 421 new cases of HPV-associated anal squamous cell carcinoma were diagnosed among women (2.8 per 100 000) and 37 147 among men (1.7 per 100 000). Age-standardized incidence rates were higher in the South compared with other census regions and in counties ranked in the bottom 25% and 25%-75% economically than in the top 25%. The overall incidence rate increased in women but remained stable in men during 2009-2019. Incidence rates increased in adults aged 50 years and older but decreased among those aged 40-44 years from 2001 to 2019 in women and from 2007 to 2019 in men. Conclusions There were inequities in HPV-associated anal squamous cell carcinoma incidence by geographic and county-level economic characteristics. Failure to improve vaccine and treatment equity may widen existing disparities.

Oncology↗

Regional Differences in the Structure of Juglans nigra Phytobiome Reflect Geographical Differences in Thousand Cankers Disease Severity

Thousand cankers disease threatens Juglans nigra (Eastern Black Walnut) in urban and natural landscapes. Incidence and severity of thousand cankers disease is higher in the host’s introduced range in the western United States. We hypothesized that these differences are driven partly by geographical variation in the host phytobiome due to its roles in host stress tolerance, nutrient acquisition, and defense. To evaluate the role of the phytobiome in mediating thousand cankers disease, we characterized the J. nigra phytobiome of diseased and healthy trees in portions of its native (Indiana and Tennessee) and introduced (Washington) ranges. Grafted clones present in each state and open-pollinated populations were sampled. DNA was extracted from soil and branch (caulosphere) tissues and internal transcribed spacer and 16s regions were sequenced for characterization of fungal and bacterial communities. We found that microbial communities in the caulosphere and soil differ between native and introduced ranges of J. nigra and harbor different mutualistic and pathogenic microorganisms. Additionally, caulosphere microbial communities were more species rich and diverse in the native range of J. nigra, suggesting greater levels of functional redundancy and multifunctionality in the native-range phytobiome compared with the introduced range. We also found higher network complexity in the caulosphere of trees in the introduced range and evidence for two alternative stable community states associated with diseased and healthy trees. Our results provide support for the hypothesis that geographical variation in thousand cankers disease incidence and severity is partially driven by differences in the phytobiome of J. nigra in its introduced and native ranges.

59 BASIC BIOLOGICAL SCIENCES↗

Geographical Insights into Suicide Mortality Through Spatial Machine Learning

Suicide mortality is a leading cause of death in the United States, with an upward trend that emphasizes its significance as a public health issue. Previous research has employed global models like ordinary least squares (OLS) regression and local models such as geographically weighted regression (GWR). While local models are useful for analyzing spatial variations in suicide mortality, they share limitations with traditional global models, particularly about their inability to handle multi-collinearity and non-linear relationships. Machine learning approaches, like random forests (RF), can address some of these limitations but often fail to account for spatial variability. This gap highlights the need for spatial ML models specifically designed to tackle suicide mortality. This research seeks to fill this void by using a geographically weighted random forest model (GWRF) to examine the associations between county-level suicide mortality in the U.S. from 2010 to 2020 and various social and environmental determinants of health. A key aspect of our methodology is disciplined feature selection, which reduces the pool of explanatory variables by about 90%. This refinement enhances the explanatory power of both global (R2 improved from 0.59 to 0.67) and local (R2 improved from 0.64 to 0.67) RF models while reducing their run times. An analysis of the importance scores for these selected features reveals that the drivers of suicide mortality vary by context. Thus, to effectively address regional disparities and inform targeted public health interventions, a holistic approach that incorporates multiple county-level characteristics is essential.

Lebakula, Viswadeep [ORNL] (ORCID:0000000152935914↗

Geographic variation in the genetic basis of resistance to leaf rust between locally adapted ecotypes of the biofuel crop switchgrass ( Panicum virgatum )

Local adaptation is an important process in plant evolution, which can be impacted by differential pathogen pressures along environmental gradients. However, the degree to which pathogen resistance loci vary in effect across space and time is incompletely described. As such, to understand how the genetic architecture of resistance varies across time and geographic space, we quantified rust ( Puccinia spp.) severity in switchgrass ( Panicum virgatum ) plantings at eight locations across the central USA for 3 yr and conducted quantitative trait locus (QTL) mapping for rust progression. We mapped several variable QTLs, but two large-effect QTLs which we have named Prr1 and Prr2 were consistently associated with rust severity in multiple sites and years, particularly in northern sites. By contrast, there were numerous small-effect QTLs at southern sites, indicating a genotype-by-environment interaction in rust resistance loci. Interestingly, Prr1 and Prr2 had a strong epistatic interaction, which also varied in the strength and direction of effect across space. Our results suggest that abiotic factors covarying with latitude interact with the genetic loci underlying plant resistance to control rust infection severity. Furthermore, our results indicate that segregating genetic variation in epistatically interacting loci may play a key role in determining response to infection across geographic space.

09 BIOMASS FUELS↗

Geographic location and year determine virulence, and year determines genetic change, in populations of Neopseudocercosporella capsellae

White leaf spot ( Neopseudocercosporella capsellae ) can be severe and problematic worldwide across both horticultural and oilseed Brassicaceae, including susceptible rapeseed. In this study, 82 isolates from 2015 and 106 isolates from across Australia in 2016 were first assessed for their virulence against three different rapeseed ( Brassica napus ) cultivars. For both years there were significant ( P < 0.001) differences. Also, there were significant (all P < 0.001) differences between isolates in each year, and between cultivars. For 2016 isolates, there were also significant differences ( P < 0.001) between isolates across three different Australian states, and a significant interaction ( P < 0.001) between isolates with cultivars. Of the three Australian states, isolates from Victoria were most virulent. Among tested cultivars, cv. Scoop was most susceptible. Subsequently, phylogenetic analysis of 114 of these same 2015 and 2016 isolates showed current isolates clustered separately from the majority of 2005 N. capsellae isolates collected from Western Australia a decade earlier, confirming significant genetic change within N. capsellae populations over the past decade. However, isolate clusters showed no association with geographical location. The results suggest that phylogenetic association among 2005 and 2015–2016 N. capsellae isolates is complementary with pathogenicity variations explained by geographically different N. capsellae pathogen populations. Neopseudocercosporella capsellae populations are evolving rapidly, challenging management through host resistance at a time of increasing incidence and severity of white leaf spot disease over the past decade. The outcome is well illustrated by cv. Scoop, previously resistant to 2005 isolates but moderately susceptible to 2015 and highly susceptible to 2016 isolates.

Murtza, T.↗

Diverging drivers of fungal diversity: seasonal effects shape aboveground communities, while geographical patterns govern belowground communities in rubber tree ecosystems

Understanding the spatiotemporal dynamics of microbial communities is essential for predicting their ecological roles and interactions with host plants. In a recent study, Wei and colleagues (Microbiol Spectr 13:e02097-24, 2024) investigated fungal diversity across multiple plant and soil compartments in rubber trees over two seasons and two geographically distinct regions in China. Their findings revealed that alpha diversity was primarily influenced by seasonal changes and physicochemical factors, while beta diversity exhibited a strong geographical pattern, shaped by leaf phosphorus and soil available potassium. These results highlight the role of environmental drivers in shaping within-community diversity, while other factors contribute to the differences between fungal communities across the soil–plant continuum. By distinguishing the effects of temporal and spatial factors, this study provides detailed insights into plant-associated microbiomes and emphasizes the need for further research on the functional implications of microbial diversity in the context of changing environmental and agricultural conditions.

fungal diversity↗

Denudation, solute export, landscape evolution modeling, and geographic information system data for the East River watershed, Colorado, USA (2020-2024)

This data package contains geographic information system (GIS) layers and tabular datasets associated with the study of lithologic controls on denudation, solute export, carbon-scaling relationships, and transient landscape evolution in the East River watershed near Crested Butte, Colorado, USA. The package includes GIS layers used to produce the Figure 2 map, including drainage, hillshade, lithology, sample locations, and basin polygons, together with comma-separated value (CSV) tables and matching CSV data dictionaries. One group of tables reports sample-level and catchment-level information for river-sediment samples analyzed for in situ-produced cosmogenic beryllium-10 (10Be), including sample names, outlet elevations, geographic coordinates, upstream drainage area, rock-type classes, production-rate scaling scheme, analyzed nuclide, catchment-averaged denudation rates, and associated lower and upper analytical uncertainties. Sample and catchment attributes provide the basis for comparing denudation rates across intrusive, shale, sedimentary, and mixed-lithology settings. A second group of tables reports supporting information for landscape-evolution modeling and the mapped geologic framework of the study area. Included files list parameter values and definitions for the two-phase landscape-evolution simulations, summarize full-domain model erosion fluxes and topographic metrics for different simulation configurations, provide a fixed-area carbon-model scaling table, and summarize mapped geologic units within the East River study domain, including geologic code, formation name, lithologic description, mapped area, and lithologic class grouping. Model outputs and geologic summaries support interpretation of transient landscape behavior and its relation to the mapped distribution of shale, intrusive, sedimentary, and surficial units. A third group of tables reports hydrologic and hydrochemical information used to quantify dissolved export from the watershed. Included files provide site-level values for drainage area, mean annual solute export, standard error of annual export, area-normalized solute yield, and equivalent weathering rate for five East River monitoring sites, along with metadata describing the number, sampling cadence, and date range of discharge records and partial and full total dissolved solids observations used in the solute-yield analyses. The package also contains a supplementary daily ion-load time series with daily mean discharge, discharge observation counts, dissolved concentrations, and daily loads for calcium, magnesium, sodium, potassium, chloride, sulfate, nitrate, fluoride, dissolved silica, charge-balance bicarbonate, and total dissolved solids. The package contains GIS files, comma-separated value files (.csv), CSV data dictionaries, a file-level metadata table, a package-tree text file, and a readme text file.

10Be↗

The geology, geochemistry, and geographic distribution of southern Idaho obsidian

The Snake River Plain Volcanic Province of Southern Idaho is host to an abundance of pyroclastic obsidian deposits that constitute the principal lithic raw material utilized by Native Americans of the region throughout the Precontact Period. Archaeologists have long looked to obsidian as a source of information on past patterns of raw material selection, landscape use, and mobility through geochemical analysis of obsidian artifacts and lithic raw materials. Formation of the Snake River Plain through cataclysmic “super-eruptions” of the Yellowstone hotspot, however, presents one of the most complex and poorly understood obsidian source-scapes of North America. To clarify the geographic distribution of Southern Idaho obsidian source groups, the INL CRMO has compiled a comprehensive reference library of geologic obsidian from 138 source locales distributed across the southern half of the state. In this report, we define 28 geochemically distinct obsidian source groups that occur at these deposits through X-ray Fluorescence spectrometry and contextualize the geographic distribution of each source group relative to the history of silicic magmatism on the Snake River Plain. This research facilitates ongoing investigations at the INL CRMO into patterns of obsidian procurement, conveyance, and exchange in Southern Idaho throughout the Precontact Period.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Geographic patterns and determinants of antibiotic resistomes in coastal sediments across complex ecological gradients

Coastal areas are highly influenced by terrestrial runoffs and anthropogenic disturbances, commonly leading to ecological gradients from bay, nearshore, to offshore areas. Although the occurrence and distribution of sediment antibiotic resistome are explored in various coastal environments, little information is available regarding geographic patterns and determinants of coastal sediment antibiotic resistomes across ecological gradients at the regional scale. Here, using high-throughput quantitative PCR, we investigated the geographic patterns of 285 antibiotic resistance genes (ARGs) in coastal sediments across a ~ 200 km scale in the East China Sea. Sediment bacterial communities and physicochemical properties were characterized to identify the determinants of sediments antibiotic resistome. Higher richness and abundance of ARGs were detected in the bay samples compared with those in nearshore and offshore samples, and significant negative correlations between the richness and/or abundance of ARGs and the distance to coastline (DTC) were identified, whereas different types of ARGs showed inconsistency in their relationships with DTC. The composition of antibiotic resistome showed significant correlations with nutrition-related variables (including NH 4 + -N, NO 3 − -N, and total phosphorus) and metals/metalloid (including As, Cu, Ni, and Zn), suggesting that terrestrial disturbances largely shape the antibiotic resistome. The Bipartite network showed strong associations between ARGs and mobile genetic elements (MGEs), and Partial Least Squares Path Modeling further revealed that terrestrial disturbance strength (as indicated by DTC) directly affected abiotic environmental conditions and bacterial community composition, and indirectly affected antibiotic resistome via MGEs. These findings provide insights into regional variability of sediment antibiotic resistome and its shaping path across complex ecological gradients, highlighting terrestrial disturbances as determinative forces in shaping coastal sediment antibiotic resistomes.

Xiong, Shangling↗

Restoration of Geographically Isolated Wetlands: An Amphibian-Centric Review of Methods and Effectiveness

Geographically isolated wetlands provide a critical habitat for pond-breeding amphibians, a taxa of broad conservation concern. Global wetland loss and degradation has made restoration essential for amphibian conservation. Restoration goals typically include recovering the wetlands’ physiochemical, hydrological, and ecological functions. However, for pond-breeding amphibians, successful restoration should also result in sustained populations, which is difficult to assess and infrequently reported. In this paper, we review the available evidence that restoration of geographically isolated wetlands promotes pond-breeding amphibian occupancy and population persistence. We provide an overview of restoration practices addressing hydrology, vegetation, and ecological processes within these unique environments and across spatial scales. We then summarize the evidence, and discuss the limitations, for evaluating successful restoration within the context of amphibian conservation across these categories. Finally, we provide recommendations for researchers and practitioners to leverage prior successes and establish systematic data collection and dissemination. Moving restoration of wetlands for amphibian conservation forward will require more robust data collection and reporting.

59 BASIC BIOLOGICAL SCIENCES↗

Spatially-Explicit Prediction of Capacity Density Advances Geographic Characterization of Wind Power Technical Potential

Mounting interest in ambitious clean energy goals is exposing critical gaps in our understanding of onshore wind power potential. Conventional approaches to evaluating wind power technical potential at the national scale rely on coarse geographic representations of land area requirements for wind power. These methods overlook sizable spatial variation in real-world capacity densities (i.e., nameplate power capacity per unit area) and assume that potential installation densities are uniform across space. Here, we propose a data-driven approach to overcome persistent challenges in characterizing localized deployment potentials over broad extents. We use machine learning to develop predictive relationships between observed capacity densities and geospatial variables. The model is validated against a comprehensive data set of United States (U.S.) wind facilities and subjected to interrogation techniques to reveal that key explanatory features behind geographic variation of capacity density are related to wind resource as well as urban accessibility and forest cover. We demonstrate application of the model by producing a high-resolution (2 km × 2 km) national map of capacity density for use in technical potential assessments for the United States. Our findings illustrate that this methodology offers meaningful improvements in the characterization of spatial aspects of technical potential, which are increasingly critical to draw reliable and actionable planning and research insights from renewable energy scenarios.

17 WIND ENERGY↗

Empirical analytic transformations between geographic and corrected geomagnetic coordinates

Based upon a mathematical model of contours of constant corrected geomagnetic latitude in a polar projection of geographic coordinates, analytic equations are developed for converting geographic coordinates to corrected geomagnetic coordinates and vice versa. The equations were programmed for use on a small computer. This treatment is restricted to the Northern Hemisphere.

Comfort, R. H.↗

Interpretation of geographic patterns in simulated orbital television imagery of earth resources

In order to better determine the effects of the television imagery characteristics upon the interpretation of geographic patterns obtainable from orbital television sensors, and in order to better evaluate the influences of alternative sensor system parameters such as changes in orbital altitudes or scan line rates, a team of three professional interpreters independently mapped thematically the selected geographic phenomena that they could detect in orbital television imagery produced on a fourteen inch monitor and recorded photographically for analysis. Three thematic maps were compiled by each interpreter. The maps were: (1) transportation patterns; (2) other land use; and (3) physical regions. The results from the three interpreters are compared, agreements noted, and differences analyzed for cause such as disagreement on identification of phenomenon, visual acuity, differences in interpretation techniques, and differing professional backgrounds.

Latham, J. P.↗

Geographical correlation of TV and IR images obtained from weather satellites

The requirements on the accuracy of geographical correlation of TV and IR cloud cover images are determined by the objective of the analysis of the weather information contained in these images. In the operational analysis case, the correlation accuracy need not be high. Errors of several tens of kilometers in determining the location of the cloud formation contours are considered acceptable in this case. Such correlation must be provided in real image reception time. Scientific studies require accurate correlation of the cloud formation contours. The errors in determining their position should be commensurate with the imaging system resolution. The geometric aspects of developing methods and equipment for geographical correlation of television and infrared images of cloud cover taken from Meteor satellites are discussed.

Ziman, Y. L.↗

Remote sensing and geographically based information systems

A structure is proposed for a geographically-oriented computer-based information system applicable to the analysis of remote sensing digital data. The structure, intended to answer a wide variety of user needs, would permit multiple views of the data, provide independent management of data security, quality and integrity, and rely on automatic data filing. Problems in geographically-oriented data systems, including those related to line encoding and cell encoding, are considered.

Cicone, R. C.↗

A study of the geographic coverage properties of a satellite borne Doppler lidar wind velocity measuring system

Geographic coverage frequency and geographic shot density for a satellite borne Doppler lidar wind velocity measuring system are measured. The equations of motion of the light path on the ground were derived and a computer program devised to compute shot density and coverage frequency by latitude-longitude sections. The equations for the coverage boundaries were derived and a computer program developed to plot these boundaries, thus making it possible, after an application of a map coloring algorithm, to actually see the areas of multiple coverage. A theoretical cross-swath shot density function that gives close approximations in certain cases was also derived. This information should aid in the design of an efficient data-processing system for the Doppler lidar.

Pate, T. H.↗

Toward multidisciplinary use of LANDSAT: Interfacing computerized LANDSAT analysis systems with geographic information systems

The LANDSAT-geographic information system (GIS) interface must summarize the results of the LANDSAT classification over the same cells that serve as geographic referencing units for the GIS, and output these summaries on a cell-by-cell basis in a form that is readable by the input routines of the GIS. The ZONAL interface for cell-oriented systems consists of two primary programs. The PIXCEL program scans the grid of cells and outputs a channel of pixels. Each pixel contains not the reflectance values but the identifier of the cell in which the center of the pixel is located. This file of pixelized cells along with the results of a pixel-by-pixel classification of the scene produced by the LANDSAT analysis system are input to the CELSUM program which then outputs a cell-by-cell summary formatted according to the requirements of the host GIS. Cross-correlation of the LANDSAT layer with the other layers in the data base is accomplished with the analysis and display facilities of the GIS.

Myers, W. L.↗