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USGS2007

Use of dissolved chloride concentrations in tributary streams to support geospatial estimates of Cl contamination potential near Skiatook Lake, northeastern Oklahoma

Releases of NaCl-rich (>100 000 mg/L) water that is co-produced from petroleum wells can adversely affect the quality of ground and surface waters. To evaluate produced water impacts on lakes, rivers and streams, an assessment of the contamination potential must be attainable using reliable and cost-effective methods. This study examines the feasibility of using geographic information system (GIS) analysis to assess the contamination potential of Cl to Skiatook Lake in the Hominy Creek drainage basin in northeastern Oklahoma. GIS-based predictions of affects of Cl within individual subdrainages are supported by measurements of Cl concentration and discharge in 19 tributaries to Skiatook Lake. Dissolved Cl concentrations measured in October, 2004 provide a snapshot of conditions assumed to be reasonably representative of typical inputs to the lake. Chloride concentrations ranged from 5.8 to 2300 mg/L and compare to a value of 34 mg/L in the lake. At the time of sampling, Hominy Creek provided 63% of the surface water entering the lake and 80% of the Cl load. The Cl load from the other tributaries is relatively small (<600 kg/day) compared to Hominy Creek (11 900 kg/day) because their discharges are relatively small (<0.44 m3/s) relative to Hominy Creek (3.1 m3/s). Examination of chemical components other than Cl in stream and lake waters indicates that many species, such as SO4, cannot be used to assess contamination potential because they participate in a number of common biogeochemical processes that alter their concentrations. GIS estimates of well density, well proximity to tributaries (wells within 200 m), and subdrainage area identified tributaries with the most potential for Cl contamination. Tributaries with large measured Cl concentrations (>150 mg/L) were generally in subdrainages with greater well density (>15 wells/km2), relatively large numbers of petroleum wells in close proximity (>2 proximity wells/stream km), and relatively small discharge (<0.005 m3/s). GIS calculations of subdrainage areas can be used to estimate the expected discharge of the tributary for each subdrainage. GIS-based assessment of Cl contamination potential at Skiatook Lake and at other lakes surrounded by oil fields can proceed even when direct measurements of Cl or discharge in tributary streams may be limited or absent.

Oklahoma↗

USGS2009

Regional variations in water quality and relationships to soil and bedrock weathering in the southern Sacramento Valley, California, USA

Regional patterns in ground- and surface-water chemistry of the southern Sacramento Valley in California were evaluated using publicly available geochemical data from the US Geological Survey's National Water Information System (NWIS). Within the boundaries of the study area, more than 2300 ground-water analyses and more than 20,000 surface-water analyses were available. Ground-waters from the west side of the Sacramento Valley contain greater concentrations of Na, Ca, Mg, B, Cl and SO 4 , while the east-side ground-waters contain greater concentrations of silica and K. These differences result from variations in surface-water chemistry as well as from chemical reactions between water and aquifer materials. Sediments that fill the Sacramento Valley were derived from highlands to the west (the Coast Ranges) and east (the Sierra Nevada Mountains), the former having an oceanic provenance and the latter continental. These geologic differences are at least in part responsible for the observed patterns in ground-water chemistry. Thermal springs that are common along the west side of the Sacramento Valley appear to have an effect on surface-water chemistry, which in turn may affect the ground-water chemistry.

Applied Geochemistry↗

USGS2009

Exploratory and spatial data analysis (EDA-SDA) for determining regional background levels and anomalies of potentially toxic elements in soils from Catorce-Matehuala, Mexico

The threshold between geochemical background and anomalies can be influenced by the methodology selected for its estimation. Environmental evaluations, particularly those conducted in mineralized areas, must consider this when trying to determinate the natural geochemical status of a study area, quantifying human impacts, or establishing soil restoration values for contaminated sites. Some methods in environmental geochemistry incorporate the premise that anomalies (natural or anthropogenic) and background data are characterized by their own probabilistic distributions. One of these methods uses exploratory data analysis (EDA) on regional geochemical data sets coupled with a geographic information system (GIS) to spatially understand the processes that influence the geochemical landscape in a technique that can be called a spatial data analysis (SDA). This EDA-SDA methodology was used to establish the regional background range from the area of Catorce-Matehuala in north-central Mexico. Probability plots of the data, particularly for those areas affected by human activities, show that the regional geochemical background population is composed of smaller subpopulations associated with factors such as soil type and parent material. This paper demonstrates that the EDA-SDA method offers more certainty in defining thresholds between geochemical background and anomaly than a numeric technique, making it a useful tool for regional geochemical landscape analysis and environmental geochemistry studies.

Applied Geochemistry↗

USGS2016

Use of mineral/solution equilibrium calculations to assess the potential for carnotite precipitation from groundwater in the Texas Panhandle, USA

This study investigated the potential for the uranium mineral carnotite (K 2 (UO 2 ) 2 (VO 4 ) 2 ·3H 2 O) to precipitate from evaporating groundwater in the Texas Panhandle region of the United States. The evolution of groundwater chemistry during evaporation was modeled with the USGS geochemical code PHREEQC using water-quality data from 100 groundwater wells downloaded from the USGS National Water Information System (NWIS) database. While most modeled groundwater compositions precipitated calcite upon evaporation, not all groundwater became saturated with respect to carnotite with the system open to CO 2 . Thus, the formation of calcite is not a necessary condition for carnotite to form. Rather, the determining factor in achieving carnotite saturation was the evolution of groundwater chemistry during evaporation following calcite precipitation. Modeling in this study showed that if the initial major-ion groundwater composition was dominated by calcium-magnesium-sulfate (>70 precent Ca + Mg and >50 percent SO 4 + Cl) or calcium-magnesium-bicarbonate (>70 percent Ca + Mg and <70 percent HCO 3 + CO 3 ) and following the precipitation of calcite, the concentration of calcium was greater than the carbonate alkalinity (2 m Ca +2 > m HCO 3 − + 2 m CO 3 −2 ) carnotite saturation was achieved. If, however, the initial major-ion groundwater composition is sodium-bicarbonate (varying amounts of Na, 40–100 percent Na), calcium-sodium-sulfate, or calcium-magnesium-bicarbonate composition (>70 percent HCO 3 + CO 3 ) and following the precipitation of calcite, the concentration of calcium was less than the carbonate alkalinity (2 m Ca +2 < m HCO 3 - + 2 m CO 3 −2 ) carnotite saturation was not achieved. In systems open to CO 2, carnotite saturation occurred in most samples in evaporation amounts ranging from 95 percent to 99 percent with the partial pressure of CO 2 ranging from 10 −3.5 to 10 −2.5 atm. Carnotite saturation occurred in a few samples in evaporation amounts ranging from 98 percent to 99 percent with the partial pressure of CO 2 equal to 10 −2.0 atm. Carnotite saturation did not occur in any groundwater with the system closed to CO 2 .

Texas↗

USGS2003

Atmospheric deposition maps for the Rocky Mountains

Variability in atmospheric deposition across the Rocky Mountains is influenced by elevation, slope, aspect, and precipitation amount and by regional and local sources of air pollution. To improve estimates of deposition in mountainous regions, maps of average annual atmospheric deposition loadings of nitrate, sulfate, and acidity were developed for the Rocky Mountains by using spatial statistics. A parameter-elevation regressions on independent slopes model (PRISM) was incorporated to account for variations in precipitation amount over mountainous regions. Chemical data were obtained from the National Atmospheric Deposition Program/National Trends Network and from annual snowpack surveys conducted by the US Geological Survey and National Park Service, in cooperation with other Federal, State and local agencies. Surface concentration maps were created by ordinary kriging in a geographic information system, using a local trend and mathematical model to estimate the spatial variance. Atmospheric-deposition maps were constructed at 1-km resolution by multiplying surface concentrations from the kriged grid and estimates of precipitation amount from the PRISM model. Maps indicate an increasing spatial trend in concentration and deposition of the modeled constituents, particularly nitrate and sulfate, from north to south throughout the Rocky Mountains and identify hot-spots of atmospheric deposition that result from combined local and regional sources of air pollution. Highest nitrate (2.5-3.0kg/ha N) and sulfate (10.0-12.0kg/ha SO4) deposition is found in northern Colorado.

Atmospheric Environment↗

USGS2026

Long lives, short futures: Freshwater turtle and tortoise imports to the United States highlight global trade and conservation challenges

Global trade of freshwater turtles and tortoises presents substantial conservation, biosecurity, and regulatory challenges, particularly for long-lived species that are already highly imperiled. While the United States has historically played a key role in supplying the international chelonian trade, investigations into its role as an importer remain limited. We used import data from the U.S. Fish and Wildlife Service Law Enforcement Management Information System (LEMIS) between 2000 and 2022 to evaluate the trade of freshwater turtles and tortoises. Over 2.5 million individuals were imported into the United States during this period, comprising 172 species that are likely imported for the pet trade, food, and traditional medicine markets. Reported annual imports for freshwater turtles increased until approximately 2013 and decreased thereafter, whereas reported annual imports for tortoises have remained relatively constant. Two species, Chinese softshell turtles ( Pelodiscus sinensis ) and Horsfield's tortoises ( Testudo horsfieldii ) represent 62.9% of all imports. Imported species were largely classified as Vulnerable, Endangered, or Critically Endangered by the IUCN Red List, yet the conservation status of a concerning number of species ( n = 45; 26.2%) has not been evaluated. Many imports appear to be sourced from wild populations (28.3% of freshwater turtles, 71.3% of tortoises); however, captive-sourced imports increased significantly over time across both groups. Import volumes raise concerns regarding the sustainability of freshwater turtle and tortoise trade, the potential for invasive species establishment, and disease spread. Our results highlight the need for updated IUCN assessments, verification of trade records, and strengthening of biosecurity screening at U.S. ports of entry.

Biological Conservation↗

USGS2009

A mosaic of diverse ideas: The ecological legacy of J. Frederick Grassle

During the 40 years (and counting) of his scientific career, J. Frederick Grassle has made fundamental contributions to our understanding of marine ecosystems from coral reefs to deep-sea sediments. His advocacy and passion for marine biodiversity in the form of myriad groundbreaking studies and influential reviews, his generosity of ideas and capacity to catalyze and inspire those working with him as well as the science community in general, his breakthroughs in improved ocean observation, his marine science infrastructure initiatives, together with his tireless persistence, have helped lead to major shifts in approaches to marine science and the shape of modern ocean studies to one that favours multidisciplinary research, teamwork, continuous, long-term observation, in situ experimentation, recognition of the importance of marine biodiversity, and global cooperation on research and data sharing. In shallow-water ecology, he co-discovered sibling species of Capitella spp., important not only because it is a key pollution indicator but also because the work helped to pave the way for the discovery of numerous sibling species in other taxa with major ramifications for ecological understanding. He was also a key player in the West Falmouth oil spill study which, along with complementary mesocosm experiments, remains one of the most important and detailed studies of its kind. He was also a lead player in the first biological expedition to hydrothermal vents and wrote the seminal articles that helped to inspire the flurry of vent research that followed. He is perhaps best known for his deep-sea work, where he brought submersibles to the forefront as a sampling tool, brought experimental manipulative studies to the primarily descriptive discipline of deep-sea benthic ecology, and generated tremendous excitement, debate, and rekindled interest in marine biodiversity with the first quantitative estimate of global deep-sea diversity. His efforts to document marine biodiversity resulted in the international Census of Marine Life, and his emphasis on the need for continuous, long-term ocean observation has led to breakthroughs in international cooperation in cabled observatories such as LEO-15. These efforts have also enhanced efforts to integrate ocean data on a global scale in platforms such as the Ocean Biogeographic Information System (OBIS). The diversity of his contributions to marine science mirror the immense marine diversity he has recognized, documented, and championed so effectively over the last four decades.

Deep-Sea Research Part II: Topical Studies in Ocea↗

USGS2014

Mapping and monitoring Mount Graham red squirrel habitat with Lidar and Landsat imagery

The Mount Graham red squirrel ( Tamiasciurus hudsonicus grahamensis ) is an endemic subspecies located in the Pinaleño Mountains of southeast Arizona. Living in a conifer forest on a sky-island surrounded by desert, the Mount Graham red squirrel is one of the rarest mammals in North America. Over the last two decades, drought, insect infestations, and fire destroyed much of its habitat. A federal recovery team is working on a plan to recover the squirrel and detailed information is necessary on its habitat requirements and population dynamics. Toward that goal I developed and compared three probabilistic models of Mount Graham red squirrel habitat with a geographic information system and logistic regression. Each model contained the same topographic variables (slope, aspect, elevation), but the Landsat model contained a greenness variable (Normalized Difference Vegetation Index) extracted from Landsat, the Lidar model contained three forest-inventory variables extracted from lidar, while the Hybrid model contained Landsat and lidar variables. The Hybrid model produced the best habitat classification accuracy, followed by the Landsat and Lidar models, respectively. Landsat-derived forest greenness was the best predictor of habitat, followed by topographic (elevation, slope, aspect) and lidar (tree height, canopy bulk density, and live basal area) variables, respectively. The Landsat model's probabilities were significantly correlated with all 12 lidar variables, indicating its utility for habitat mapping. While the Hybrid model produced the best classification results, only the Landsat model was suitable for creating a habitat time series or habitat–population function between 1986 and 2013. The techniques I highlight should prove valuable in the development of Landsat- or lidar-based habitat models range wide.

Arizona↗

USGS2006

Seafloor habitat mapping of the New York Bight incorporating sidescan sonar data

The efficacy of using sidescan sonar imagery, image classification algorithms and geographic information system (GIS) techniques to characterize the seafloor bottom of the New York Bight were assessed. The resulting seafloor bottom type map was compared with fish trawl survey data to determine whether there were any discernable habitat associations. An unsupervised classification with 20 spectral classes was produced using the sidescan sonar imagery, bathymetry and secondarily derived spatial heterogeneity to characterize homogenous regions within the study area. The spectral classes, geologic interpretations of the study region, bathymetry and a bottom landform index were used to produce a seafloor bottom type map of 9 different bottom types. Examination of sediment sample data by bottom type indicated that each bottom type class had a distinct composition of sediments. Analysis of adult summer flounder, Paralichthys dentatus, and adult silver hake, Merluccius bilinearis, presence/absence data from trawl surveys did not show evidence of strong associations between the species distributions and seafloor bottom type. However, the absence of strong habitat associations may be more attributable to the coarse scale and geographic uncertainty of the trawl sampling data than conclusive evidence that no habitat associations exist for these two species. ?? 2006 Elsevier Ltd. All rights reserved.

Estuarine, Coastal and Shelf Science↗

USGS2005

Tree species and size structure of old-growth Douglas-fir forests in central western Oregon, USA

We characterized the structure of 91 old-growth forests dominated by Douglas-fir ( Pseudotsuga menziesii (Mirb.) Franco), using inventory data from recent (1985–1991) old-growth timber sales in western Oregon. The data were complete counts (i.e., censuses) of all live trees >20 cm diameter at breast height (dbh, measured at 1.4 m above the ground) over a mean area of 17.1 ha at each site. Across all sites, Douglas-fir accounted for 79% of the total basal area (m 2 /ha) of all species. The average density of trees >100 cm dbh was 19 trees/ha and 90% of these trees were Douglas-fir. Species other than Douglas-fir constituted only about 20% of the total basal area at each old-growth site, on average, but largely accounted for the structural variation between sites. We used multivariate techniques such as cluster analysis, indicator species analysis, and ordination with non-metric multidimensional scaling (NMS) to identify and characterize six structural groups in terms of basal area in different species–diameter classes. Almost 97% of the structural information was captured by the first ( r 2 = 0.841) and second ( r 2 = 0.128) NMS ordination axis. Geographic information systems (GIS) analysis and NMS indicated that the structural differences among groups of sites were associated with moisture, temperature, and elevation gradients within the study area. This type of analysis can be used to help define differences among old-growth forests and to set local structural goals for growing forests with old-growth characteristics.

Oregon↗

USGS2016

POLARIS: A 30-meter probabilistic soil series map of the contiguous United States

A new complete map of soil series probabilities has been produced for the contiguous United States at a 30 m spatial resolution. This innovative database, named POLARIS, is constructed using available high-resolution geospatial environmental data and a state-of-the-art machine learning algorithm (DSMART-HPC) to remap the Soil Survey Geographic (SSURGO) database. This 9 billion grid cell database is possible using available high performance computing resources. POLARIS provides a spatially continuous, internally consistent, quantitative prediction of soil series. It offers potential solutions to the primary weaknesses in SSURGO: 1) unmapped areas are gap-filled using survey data from the surrounding regions, 2) the artificial discontinuities at political boundaries are removed, and 3) the use of high resolution environmental covariate data leads to a spatial disaggregation of the coarse polygons. The geospatial environmental covariates that have the largest role in assembling POLARIS over the contiguous United States (CONUS) are fine-scale (30 m) elevation data and coarse-scale (~ 2 km) estimates of the geographic distribution of uranium, thorium, and potassium. A preliminary validation of POLARIS using the NRCS National Soil Information System (NASIS) database shows variable performance over CONUS. In general, the best performance is obtained at grid cells where DSMART-HPC is most able to reduce the chance of misclassification. The important role of environmental covariates in limiting prediction uncertainty suggests including additional covariates is pivotal to improving POLARIS' accuracy. This database has the potential to improve the modeling of biogeochemical, water, and energy cycles in environmental models; enhance availability of data for precision agriculture; and assist hydrologic monitoring and forecasting to ensure food and water security.

Geoderma↗

USGS2005

Conceptual model of sediment processes in the upper Yuba River watershed, Sierra Nevada, CA

This study examines the development of a conceptual model of sediment processes in the upper Yuba River watershed; and we hypothesize how components of the conceptual model may be spatially distributed using a geographical information system (GIS). The conceptual model illustrates key processes controlling sediment dynamics in the upper Yuba River watershed and was tested and revised using field measurements, aerial photography, and low elevation videography. Field reconnaissance included mass wasting and channel storage inventories, assessment of annual channel change in upland tributaries, and evaluation of the relative importance of sediment sources and transport processes. Hillslope erosion rates throughout the study area are relatively low when compared to more rapidly eroding landscapes such as the Pacific Northwest and notable hillslope sediment sources include highly erodible andesitic mudflows, serpentinized ultramafics, and unvegetated hydraulic mine pits. Mass wasting dominates surface erosion on the hillslopes; however, erosion of stored channel sediment is the primary contributor to annual sediment yield. We used GIS to spatially distribute the components of the conceptual model and created hillslope erosion potential and channel storage models. The GIS models exemplify the conceptual model in that landscapes with low potential evapotranspiration, sparse vegetation, steep slopes, erodible geology and soils, and high road densities display the greatest hillslope erosion potential and channel storage increases with increasing stream order. In-channel storage in upland tributaries impacted by hydraulic mining is an exception. Reworking of stored hydraulic mining sediment in low-order tributaries continues to elevate upper Yuba River sediment yields. Finally, we propose that spatially distributing the components of a conceptual model in a GIS framework provides a guide for developing more detailed sediment budgets or numerical models making it an inexpensive way to develop a roadmap for understanding sediment dynamics at a watershed scale.

Geomorphology↗

USGS2008

GIS technology and models for assessing landslide hazard and risk

Advances in Geographical Information Systems (GIS) technology and the mathematical/statistical tools for modelling and simulation have led to the growing application of quantitative techniques in many areas of the earth sciences. Few disciplines have embraced these developments more enthusiastically than the study of landslide hazards. Because the shape of the land surface plays a fundamental role in landslide processes, much of this new work has been driven by the increasing availability of digital elevation models (DEMs) and the software to manipulate them. As a result, investigators worldwide are devising spatial models to forecast slope instability in efforts to keep landslide hazards from becoming landslide disasters. The methods range from empirical and heuristic to statistical and physically-based. Despite nearly a quarter-century of progress, e.g. since Carrara (1983) , and a veritable “cottage industry” of current DEM-based hazard mapping, many of these spatial predictions either are based on unsuitable data or are not properly modelled.

Geomorphology↗

USGS2011

Hillslope chemical weathering across Paraná, Brazil: a data mining-GIS hybrid approach

Self-organizing map (SOM) and geographic information system (GIS) models were used to investigate the nonlinear relationships associated with geochemical weathering processes at local (~100 km 2 ) and regional (~50,000 km 2 ) scales. The data set consisted of 1) 22 B-horizon soil variables: P, C, pH, Al, total acidity, Ca, Mg, K, total cation exchange capacity, sum of exchangeable bases, base saturation, Cu, Zn, Fe, B, S, Mn, gammaspectrometry (total count, potassium, thorium, and uranium) and magnetic susceptibility measures; and 2) six topographic variables: elevation, slope, aspect, hydrological accumulated flux, horizontal curvature and vertical curvature. It is characterized at 304 locations from a quasi-regular grid spaced about 24 km across the state of Paraná. This data base was split into two subsets: one for analysis and modeling (274 samples) and the other for validation (30 samples) purposes. The self-organizing map and clustering methods were used to identify and classify the relations among solid-phase chemical element concentrations and GIS derived topographic models. The correlation between elevation and k-means clusters related the relative position inside hydrologic macro basins, which was interpreted as an expression of the weathering process reaching a steady-state condition at the regional scale. Locally, the chemical element concentrations were related to the vertical curvature representing concave–convex hillslope features, where concave hillslopes with convergent flux tends to be a reducing environment and convex hillslopes with divergent flux, oxidizing environments. Stochastic cross validation demonstrated that the SOM produced unbiased classifications and quantified the relative amount of uncertainty in predictions. This work strengthens the hypothesis that, at B-horizon steady-state conditions, the terrain morphometry were linked with the soil geochemical weathering in a two-way dependent process: the topographic relief was a factor on environmental geochemistry while chemical weathering was for terrain feature delineation.

Parana↗

USGS2020

Global physical controls on estuarine habitat distribution during sea levelchange: Consequences for genetic diversification through time

Determining the extrinsic (physical) factors controlling speciation and diversification of species through time is of key interest in paleontology and evolutionary biology. The role of sea-level change in shaping species richness patterns of marginal marine species has received much attention, but with variable conclusions. Recent work combining genetic data and Geographical Information Systems (GIS)-based habitat modeling yielded a framework for how geomorphology of continental margins mediates genetic connectivity of populations during sealevel change. This approach may ultimately yield insights on how distinct lineages, species, and biodiversity accumulate in coastal settings. Here, we expand this GIS work globally to different geomorphic settings to model estuarine habitat in a larger geographic framework and test how tectonic setting, oceanographic setting, climate, and margin age affect habitat distribution during sea-level change. In addition, independent of estuaries we explore paleobiologic (e.g. Olsson, 1961) and neontolologic effects of sea-level change on evolution, and test the relation between overall shelf area and species richness using data of 1721 fish species. We find 82% global reduction of estuarine habitat abundance at lowstand relative to highstand, and find large habitats change in size much more than small habitats. Consistent with prior work, narrow continental margins have significantly less habitat at highstand and lowstand than wide margins, and narrow margins significantly associate with fore-arc settings, effectively linking tectonic setting to habitat abundance. Surprisingly, narrow margins host greater species richness, a finding which violates the canonical species-area relation. This finding can be explained if: 1) the physical isolation imposed by narrow margins facilitates the formation of new species over time; 2) the sizestability of small habitats, which disproportionately occur on narrow margins, accumulate and retain species extirpated in the more variable habitats on wide margins; or 3) the smaller habitats on narrow margins facilitate greater species richness through greater habitat heterogeneity. These results are generally at odds with prior interpretations, but the combination of richness data and population genetic principles offer a different perspective on these long-studied questions. Finally, we emphasize that the nuance of Pleistocene-Holocene sea level oscillations should be more explicitly considered in genetic studies.

Global and Planetary Change↗

USGS2022

Multi-hazard risk analysis for the U.S. Department of the Interior: An integration of expert elicitation, planning priorities, and geospatial analysis

An integral part of disaster risk management is identifying and prioritizing hazards and their potential impacts in a meaningful way to support risk-reduction planning. There has been considerable use and subsequent criticism of threat prioritization efforts that simply compare likelihoods and consequences of plausible threats. This article summarizes a new mixed-methods and scalable approach for prioritizing risks in a multi-hazard, multi-objective, and multi-criteria organizational context. This approach integrates (1) hazard characterizations using subject-matter-expert (SME) elicitation, (2) expressed preferences in planning priorities provided by emergency managers, and (3) quantitative estimates of asset exposure to hazards using geospatial data and geographic-information-systems (GIS) software. We demonstrate this approach with a case study designed to support multi-hazard mitigation and response planning done by the U.S. Department of the Interior (DOI) Office of Emergency Management, which required a national understanding of the risks posed by 75 natural, technological, and adversarial hazards to DOI managed and administered lands, facilities, people, revenues, and resources. Results demonstrate that hazard priorities vary depending on the asset, scale, and risk-management context, thereby making the case that “one-size-fits-all” hazard rankings have limited utility or relevance to real-world, risk mitigation and response planning. Our results suggest that recognizing the risk-management context provides greater transparency, flexibility, and relevance in comparing threats than traditional likelihood-threat matrices or the use of hazard SMEs to decide for planners which hazard scenarios are emphasized in risk planning.

International Journal of Disaster Risk Reduction↗

USGS2009

GIS applications for military operations in coastal zones

In order to successfully support current and future US military operations in coastal zones, geospatial information must be rapidly integrated and analyzed to meet ongoing force structure evolution and new mission directives. Coastal zones in a military-operational environment are complex regions that include sea, land and air features that demand high-volume databases of extreme detail within relatively narrow geographic corridors. Static products in the form of analog maps at varying scales traditionally have been used by military commanders and their operational planners. The rapidly changing battlefield of 21st Century warfare, however, demands dynamic mapping solutions. Commercial geographic information system (GIS) software for military-specific applications is now being developed and employed with digital databases to provide customized digital maps of variable scale, content and symbolization tailored to unique demands of military units. Research conducted by the Center for Remote Sensing and Mapping Science at the University of Georgia demonstrated the utility of GIS-based analysis and digital map creation when developing large-scale (1:10,000) products from littoral warfare databases. The methodology employed-selection of data sources (including high resolution commercial images and Lidar), establishment of analysis/modeling parameters, conduct of vehicle mobility analysis, development of models and generation of products (such as a continuous sea-land DEM and geo-visualization of changing shorelines with tidal levels)-is discussed. Based on observations and identified needs from the National Geospatial-Intelligence Agency, formerly the National Imagery and Mapping Agency, and the Department of Defense, prototype GIS models for military operations in sea, land and air environments were created from multiple data sets of a study area at US Marine Corps Base Camp Lejeune, North Carolina. Results of these models, along with methodologies for developing large-scale littoral warfare databases, aid the National Geospatial-Intelligence Agency in meeting littoral warfare analysis, modeling and map generation requirements for US military organizations. ?? 2008 International Society for Photogrammetry and Remote Sensing, Inc. (ISPRS).

ISPRS Journal of Photogrammetry and Remote Sensing↗

USGS2018

Landscape-scale processes influence riparian plant composition along a regulated river

Hierarchical frameworks are useful constructs when exploring landscape- and local-scale factors affecting patterns of vegetation in riparian areas. In drylands, which have steep environmental gradients and high habitat heterogeneity, landscape-scale variables, such as climate, can change rapidly along a river's course, affecting the relative influence of environmental variables at different scales. To assess how landscape-scale factors change the structure of riparian vegetation, we measured riparian vegetation composition along the Colorado River through Grand Canyon, determined which factors best explain observed changes, identified how richness and functional diversity vary, and described the implications of our results for river management. Cluster analysis identified three divergent floristic groups that are distributed longitudinally along the river. These groups were distributed along gradients of elevation, temperature and seasonal precipitation, but were not associated with annual precipitation or local-scale factors. Species richness and functional diversity decreased as a function of distance downstream showing that changing landscape-scale factors result in changes to ecosystem characteristics. Species composition and distribution remain closely linked to seasonal precipitation and temperature. These patterns in floristic composition in a semiarid system inform management and provide insights into potential future changes as a result of shifts in climate and changes in flow management.

Arizona↗