SEARCH · USGS Science

Results for “Applied Geography”

Search indexed USGS publications on groundwater, aquifers, geologic maps, mineral resources and earthquakes. Explore source records by subject and place.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 37 records · Page 2Linked to original sources

USGS2014

Strategic conservation planning for the Eastern North Carolina/Southeastern Virginia Strategic Habitat Conservation Team

The Eastern North Carolina/Southeastern Virginia Strategic Habitat Conservation Team (ENCSEVA) is a partnership among local federal agencies and programs with a mission to apply Strategic Habitat Conservation to accomplish priority landscape-level conservation within its geographic region. ENCSEVA seeks to further landscape-scale conservation through collaboration with local partners. To accomplish this mission, ENCSEVA is developing a comprehensive Strategic Habitat Conservation Plan (Plan) to provide guidance for its members, partners, and collaborators by establishing mutual conservation goals, objectives, strategies, and metrics to gauge the success of conservation efforts. Identifying common goals allows the ENCSEVA team to develop strategies that leverage joint resources and are more likely to achieve desired impacts across the landscape. The Plan will also provide an approach for ENCSEVA to meet applied research needs (identify knowledge gaps), foster adaptive management principles, identify conservation priorities, prioritize threats (including potential impacts of climate change), and identify the required capacity to implement strategies to create more resilient landscapes. ENCSEVA seeks to support the overarching goals of the South Atlantic Landscape Conservation Cooperative (SALCC) and to provide scientific and technical support for conservation at landscape scales as well as inform the management of natural resources in response to shifts in climate, habitat fragmentation and loss, and other landscape-level challenges (South Atlantic LCC 2012). The ENCSEVA ecoregion encompasses the northern third of the SALCC geography and offers a unique opportunity to apply landscape conservation at multiple scales through the guidance of local conservation and natural resource management efforts and by reporting metrics that reflect the effectiveness of those efforts (Figure 1). The Environmental Decision Analysis Team, housed within the North Carolina Cooperative Fish and Wildlife Research Unit at North Carolina State University, is assisting the ENCSEVA team in developing a scientifically sound basis for the Plan though the elicitation of expert knowledge and the organization of that knowledge using the Open Standards for the Practice of Conservation. The Open Standards for the Practice of Conservation is a framework that is well suited to incorporating decision-making tools such as Structured Decision Making and provides a multi-step process to conceptually organize conservation projects in a manner that enhances the rigor and transparency of expert and knowledge-based plans. It helps define explicit pathways from 2 planned conservation activities and ultimate impact, as well as indicators to measure success (Stem et al. 2005). Specifically, the framework identifies conservation targets, key ecological attributes, threats, and associated indicators to monitor responses given the implementation of a conservation action (Conservation Measures Partnership 2007). This report serves to provide a scientific foundation for the Plan by summarizing the expert opinion of wildlife biologists, ecologists, hydrologists, researchers, natural resource managers, and conservation practitioners regarding five environments (wetlands, riverine systems, estuaries, uplands, and barrier islands) within the ENCSEVA geography. Specifically, this report describes (1) the approach to elicit expert knowledge meant to support the strategic plan, (2) how this knowledge can inform collaborative conservation planning, and (3) a summary of opportunities available for the ENCSEVA team to address threats and impacts associated with climate change within the ecoregion.

Technical Bulletin↗

USGS2014

Geomorphological Fieldwork

Geomorphological Fieldwork addresses a topic that always remains popular within the geosciences and environmental science. More specifically, the volume conveys a growing legacy of field-based learning for young geomorphologists that can be used as a student book for field-based university courses and postgraduate research requiring fieldwork or field schools. The editors have much experience of field-based learning within geomorphology and extend this to physical geography. The topics covered are relevant to basic geomorphology as well as applied approaches in environmental and cultural geomorphology. The book integrates a physical-human approach to geography, but focuses on physical geography and geomorphology from an integrated field-based geoscience perspective.

Book↗

USGS2025

Scientific opportunities in the National Landscape Conservation System

The National Landscape Conservation System consists of unique and beautiful places across America’s landscapes where identified resources and values are protected and science is highlighted. The mission of the National Landscape Conservation System (NLCS), which is managed by the Bureau of Land Management and is often referred to as the agency’s National Conservation Lands, is to conserve, protect, and restore nationally significant landscapes for their cultural, ecological, and scientific values. This clear inclusion of science in the NLCS mission sets the stage for individual units to serve as places of learning, teaching, discovery, and innovation. Science is an integral part of managing the National Conservation Lands, and science conducted within and across the more than 900 units that make up the NLCS can inform and influence conservation and public land management well beyond its boundaries. Here, we highlight seven core aspects of National Conservation Lands that present valuable science opportunities: (1) the scientific values for which individual units are designated; (2) the many other resources, objects, and values within units; (3) the value of units as “control” sites for understanding the effects of activities such as mineral extraction that commonly occur elsewhere on multiple-use public lands but are often prohibited within National Conservation Lands; (4) the value of units for studying the effects of activities such as recreation that regularly occur and may be intensified on National Conservation Lands; (5) the high visibility of units, which draws strong interest and engagement from scientists, partners, and the public; (6) the functioning of the units as a network managed for a common purpose, which provides an opportunity to explore cross-cutting science questions across widely varying contexts and geographies; and (7) the opportunities units provide to promote and apply Indigenous Knowledge to scientific research to manage natural and cultural resources. Because of all of these characteristics, National Conservation Lands can serve as hubs for basic and applied science that can inform management of all public lands and resources into the future. We highlight these science opportunities through examples from existing units and suggest two actions that could help further science activities and impact on National Conservation Lands.

Parks Stewardship Forum↗

USGS2023

Learning from arid and urban aquatic ecosystems to inform more sustainable and resilient futures

The hydrology and aquatic ecology of arid environments has long been understudied relative to temperate regions. Yet spatially and temporally intermittent and ephemeral waters characterized by flashy hydrographs typify arid regions that comprise a substantial proportion of the Earth. Additionally, drought, intense storms, and human modification of landscapes increasingly affect many temperate regions, resulting in hydrologic regimes more similar to aridlands. Here we review the contributions of Dr. Nancy Grimm to aridland hydrology and ecology, and applications of these insights to urban ecosystems and resilience of social-ecological-technological systems. Grimm catalyzed study of nitrogen cycling in streams and characterized feedbacks between surface water-groundwater exchange, nitrogen transformations, and aquatic biota. In aridlands, outcomes of these interactions depend on short- and long-term variation in the hydrologic regime. Grimm and colleagues applied hydrological and biogeochemical insights gained from study of aridland streams to urban ecosystems, integrating engineering, social and behavioral sciences, and geography. These studies evolved from characterizing the spatial heterogeneity of urban systems (i.e., watersheds, novel aquatic systems) and its influence on nutrient dynamics to an approach that evaluated human decision-making as a driver of disturbance regimes and changes in ecosystem function. Finally, Grimm and colleagues have applied principles of urban ecology to look toward the future of cities, considering scenarios of sustainable and resilient futures. We identify cross-cutting themes and approaches that have motivated discoveries across Grimm’s multi-decadal career, including spatial and temporal heterogeneity, hydrologic connectivity and regime, disturbance, systems thinking, and resilience. Finally, we emphasize Grimm’s broad contributions to science via support of long-term research, dedication to mentoring, and extensive collaborations that facilitated transdisciplinary research.

Journal of Hydrology↗

USGS2021

Applying biodiversity metrics as surrogates to a habitat conservation plan

Unabated urbanization has led to environmental degradation and subsequent biodiversity loss across the globe. As an outcome of unmitigated land use, multi-jurisdictional agencies have developed land use plans that attempt to protect threatened or endangered species across selected areas by which some trade-offs between harm to species and additional conservation approaches are allowed among the partnering organizations. Typical conservation plans can be created to focus on single or multiple species, and although they may protect a species or groups of species, they may not account for biodiversity or its protection across the given area. We applied an approach that clustered deductive habitat models for terrestrial vertebrates into metrics that serve as surrogates for biodiversity and relate to ecosystem services. In order to evaluate this process, we collaborated with the partnering agencies who are creating a Multi-Species Habitat Conservation Plan in southern California and compared it to the entire Mojave Desert Ecoregion. We focused on total terrestrial vertebrate species richness and taxon groupings representing amphibians, birds, mammals, and reptiles, and two special status species using the Normalized Index of Biodiversity (NIB). The conservation planning area had a lower NIB and was less species rich than the Mojave Desert Ecoregion, but the Mojave River riparian corridor had a higher NIB and was more species-rich, and while taxon analysis varied across the geographies, this pattern generally held. Additionally, we analyzed desert tortoise ( Gopherus agassizii ) and desert kit fox ( Vulpes macrotis arsipus ) as umbrella species and determined that both species are associated with increased NIB and large numbers of species for the conservation area. Our process provided the ability to incorporate value-added surrogate information into a formal land use planning process and used a metric, NIB, which allowed comparison of the various planning areas and geographic units. Although this process has been applied to Apple Valley, CA, and other geographies within the U.S., the approach has practical application for other global biodiversity initiatives.

California↗

USGS2015

Challenges of establishing big sgebrush ( Artemisia tridentata ) in rangeland restoration: effects of herbicide, mowing, whole-community seeding, and sagebrush seed sources

The loss of big sagebrush (Artemisia tridentata Nutt.) on sites disturbed by fire has motivated restoration seeding and planting efforts. However, the resulting sagebrush establishment is often lower than desired, especially in dry areas. Sagebrush establishment may be increased by addressing factors such as seed source and condition or management of the plant community. We assessed initial establishment of seeded sagebrush and four populations of small outplants (from different geographies, climates, and cytotypes) and small sagebrush outplants in an early seral community where mowing, herbicide, and seeding of other native plants had been experimentally applied. No emergence of seeded sagebrush was detected. Mowing the site before planting seedlings led to greater initial survival probabilities for sagebrush outplants, except where seeding also occurred, and these effects were related to corresponding changes in bare soil exposure. Initial survival probabilities were > 30% greater for the local population of big sagebrush relative to populations imported to the site from typical seed transfer distances of ~320–800 km. Overcoming the high first-year mortality of outplanted or seeded sagebrush is one of the most challenging aspects of postfire restoration and rehabilitation, and further evaluation of the impacts of herb treatments and sagebrush seed sources across different site types and years is needed.

Rangeland Ecology and Management↗

USGS2002

A landscape ecology approach to assessing development impacts in the tropics: A geothermal energy example in Hawaii

Geographic information systems (GIS) are increasingly being used in environmental impact assessments (EIA) because GIS is useful for analysing spatial impacts of various development scenarios. Spatially representing these impacts provides another tool for landscape ecology in environmental and geographical investigations by facilitating analysis of the effects of landscape patterns on ecological processes and examining change over time. Landscape ecological principles are applied in this study to a hypothetical geothermal development project on the Island of Hawaii. Some common landscape pattern metrics were used to analyse dispersed versus condensed development scenarios and their effect on landscape pattern. Indices of fragmentation and patch shape did not appreciably change with additional development. The amount of forest to open edge, however, greatly increased with the dispersed development scenario. In addition, landscape metrics showed that a human disturbance had a greater simplifying effect on patch shape and also increased fragmentation than a natural disturbance. The use of these landscape pattern metrics can advance the methodology of applying GIS to EIA.

Singapore Journal of Tropical Geography↗

USGS2009

Geographic relatedness and predictability of Escherichia coli along a peninsular beach complex of Lake Michigan

To determine more accurately the real-time concentration of fecal indicator bacteria (FIB) in beach water, predictive modeling has been applied in several locations around the Great Lakes to individual or small groups of similar beaches. Using 24 beaches in Door County, Wisconsin, we attempted to expand predictive models to multiple beaches of complex geography. We examined the importance of geographic location and independent variables and the consequential limitations for potential beach or beach group models. An analysis of Escherichia coli populations over 4 yr revealed a geographic gradient to the beaches, with mean E. coli concentrations decreasing with increasing distance from the city of Sturgeon Bay. Beaches grouped strongly by water type (lake, bay, Sturgeon Bay) and proximity to one another, followed by presence of a storm or creek outfall or amount of shoreline enclosure. Predictive models developed for beach groups commonly included wave height and cumulative 48-h rainfall but generally explained little E. coli variation (adj. R 2 = 0.19-0.36). Generally low concentrations of E. coli at the beaches influenced the effectiveness of model results presumably because of low signal-to-noise ratios and the rarity of elevated concentrations. Our results highlight the importance of the sensitivity of regressors and the need for careful methods evaluation. Despite the attractiveness of predictive models as an alternative beach monitoring approach, it is likely that FIB fluctuations at some beaches defy simple prediction approaches. Regional, multi-beach, and individual beach predictive models should be explored alongside other techniques for improving monitoring reliability at Great Lakes beaches. Copyright ?? 2009 by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America. All rights reserved.

Journal of Environmental Quality↗

USGS2013

Predicting what helminth parasites a fish species should have using Parasite Co-occurrence Modeler (PaCo)

Fish pathologists are often interested in which parasites would likely be present in a particular host. Parasite Co-occurrence Modeler (PaCo) is a tool for identifying a list of parasites known from fish species that are similar ecologically, phylogenetically, and geographically to the host of interest. PaCo uses data from FishBase (maximum length, growth rate, life span, age at maturity, trophic level, phylogeny, and biogeography) to estimate compatibility between a target host and parasite species–genera from the major helminth groups (Acanthocephala, Cestoda, Monogenea, Nematoda, and Trematoda). Users can include any combination of host attributes in a model. These unique features make PaCo an innovative tool for addressing both theoretical and applied questions in parasitology. In addition to predicting the occurrence of parasites, PaCo can be used to investigate how host characteristics shape parasite communities. To test the performance of the PaCo algorithm, we created 12,400 parasite lists by applying any possible combination of model parameters (248) to 50 fish hosts. We then measured the relative importance of each parameter by assessing their frequency in the best models for each host. Host phylogeny and host geography were identified as the most important factors, with both present in 88% of the best models. Habitat (64%) was identified in more than half of the best models. Among ecological parameters, trophic level (41%) was the most relevant while life span (34%), growth rate (32%), maximum length (28%), and age at maturity (20%) were less commonly linked to best models. PaCo is free to use at www.purl.oclc.org/fishpest .

Journal of Parasitology↗

USGS2019

Advancing barrier island habitat mapping using landscape position information

Barrier islands are dynamic ecosystems that change gradually from coastal processes, including currents and tides, and rapidly from episodic events, such as storms. These islands provide many important ecosystem services, including storm protection and erosion control to the mainland, habitat for fish and wildlife, and tourism. Habitat maps, developed by scientists, provide a critical tool for monitoring changes to these dynamic ecosystems. Barrier island monitoring often requires custom habitat maps due to several factors, including island size and the classification of unique geomorphology-based habitats, such as beach, dune, and barrier flats. In this study, we reviewed barrier-island-specific habitat mapping efforts and highlighted common habitat class types, source data, and mapping approaches. We also developed a framework for mapping geomorphology-based barrier island habitats using a rule-based, geographic object-based image analysis approach, which included the use of field data, tide data, high-resolution orthophotography, and lidar data. This framework integrates several barrier island mapping advancements with regard to the use of landscape position information for automated dune extraction and the use of Monte Carlo analyses for the treatment of elevation uncertainty for elevation-dependent habitats. Specifically, we used the uncertainty analyses to refine automated dune delineation based on elevation relative to extreme storm water levels and to increase the accuracy of intertidal and supratidal/upland habitat delineation. We found that dune extraction results were enhanced when elevation relative to storm water levels and visual interpretation were also applied. This framework could also be applied to beach–dune systems found along a mainland.

Alabama↗

USGS2026

High-resolution transboundary vegetation community maps of the Sonoran and Mojave Desert ecoregion to support critical landscape conservation planning and habitat management needs

We produced a 30-m resolution binational land cover map of Bird Conservation Region 33 (BCR 33) for the U.S. North American Bird Conservation Initiative. The region covers large portions of the Sonoran and Mojave Deserts. The map can support the U.S. Fish and Wildlife Service (FWS) Migratory Bird Program’s recovery planning efforts and constitutes the first known binational land cover dataset spanning sections of the United States–Mexico border and using a consistent classification system for both countries. The mapped region includes 152 distinct land cover classes, covering a total area of 38,421,453 ha (148,345 mi 2 ), of which 13,148,345 ha (52,706 mi 2 ) are located in Mexico and 24,770,640 ha (95,639 mi 2 ) in the United States. We primarily used Landsat 8 (OLI) imagery, supplemented by limited ground surveys from two field campaigns, drone-based aerial data, and existing vegetation classification frameworks from both countries. The classification applied a data-fusion approach integrating 30-m Landsat 8 imagery, decadal phenology metrics from vegetation indices, and a random forest model trained mainly with datasets from a comprehensive national mapping project from the U.S. Geological Survey (USGS) GAP Analysis Project (GAP) and federal wildland fire agencies’ Landscape Fire and Resource Management Planning Tools (LANDFIRE) (GAP/LANDFIRE) [United States side] and the National Institute of Statistics and Geography (INEGI) [Mexico side] as well as land cover maps and opportunistic open-access and field observations. Mapping of the full BCR 33 region was carried out in two phases: 1) Phase I, the prototype map, covered a smaller portion of the transboundary area and identified 31 land cover classes, and 2) Phase II, the full BCR 33 map (refer to Figure 1), which resulted in 152 land cover classes. Using a Random Forest classifier, we achieved an overall prediction accuracy of 92% for the Phase I map and 87% for the Phase II full region map. This slight decrease can be attributed to working on a larger, more complex area with a greater number of land cover classes. No formal validation was conducted, aside from using a subset of the collected field observations and training data to assess model performance during and after training. The training sites were further verified using Google Earth (Google, 2026) imagery. Two undergraduate students who worked for over a year visually inspected imagery and open access public images to confirm each training site during model training using in-house developed, online, visual tools. A portion of this field training data was reserved for model validation, and the corresponding results are to be presented in later sections. The project developed an end-to-end, medium- and fine-resolution remote sensing–based data fusion mapping approach. This effort produced a map (Nagler et al., 2025) and the online tools to support a dynamic, live, online map for visualizing the transboundary vegetation communities in BCR 33. The toolset is currently hosted by the University of Arizona (UofA) Vegetation Index and Phenology (VIP) Lab to support FWS partners (https://vip.arizona.edu/viplab_data_explorer?LCM_BCR33). The online map is designed to allow rapid updates using new training, validation, or correction data, making it dynamic and maintainable. The approach we took established a framework for rapid updating and correction of land cover maps, as the model can be quickly retrained with new field observations, updated training data, or other sources. This enables dynamic mapping and change detection of the region’s vegetation. This framework is an advance in data fusion and crowdsourced mapping of complex, vulnerable regions, providing support to regional stakeholders and the wider user community. This transboundary map can inform the protection, conservation, and restoration of vegetation, habitat, and ecosystems, particularly for threatened and endangered species across the two nations using consistent and harmonized binational mapping systems. Beyond supporting land management decisions and stakeholders in the transboundary desert ecoregions, this BCR 33 mapping effort establishes a foundation for future rapid, low-cost, cross-border land cover mapping that can benefit and advance ecosystem management.

Arizona, Baja California, California, Nevada, Sina↗

USGS2008

Seabed mapping and characterization of sediment variability using the usSEABED data base

We present a methodology for statistical analysis of randomly located marine sediment point data, and apply it to the US continental shelf portions of usSEABED mean grain size records. The usSEABED database, like many modern, large environmental datasets, is heterogeneous and interdisciplinary. We statistically test the database as a source of mean grain size data, and from it provide a first examination of regional seafloor sediment variability across the entire US continental shelf. Data derived from laboratory analyses ("extracted") and from word-based descriptions ("parsed") are treated separately, and they are compared statistically and deterministically. Data records are selected for spatial analysis by their location within sample regions: polygonal areas defined in ArcGIS chosen by geography, water depth, and data sufficiency. We derive isotropic, binned semivariograms from the data, and invert these for estimates of noise variance, field variance, and decorrelation distance. The highly erratic nature of the semivariograms is a result both of the random locations of the data and of the high level of data uncertainty (noise). This decorrelates the data covariance matrix for the inversion, and largely prevents robust estimation of the fractal dimension. Our comparison of the extracted and parsed mean grain size data demonstrates important differences between the two. In particular, extracted measurements generally produce finer mean grain sizes, lower noise variance, and lower field variance than parsed values. Such relationships can be used to derive a regionally dependent conversion factor between the two. Our analysis of sample regions on the US continental shelf revealed considerable geographic variability in the estimated statistical parameters of field variance and decorrelation distance. Some regional relationships are evident, and overall there is a tendency for field variance to be higher where the average mean grain size is finer grained. Surprisingly, parsed and extracted noise magnitudes correlate with each other, which may indicate that some portion of the data variability that we identify as "noise" is caused by real grain size variability at very short scales. Our analyses demonstrate that by applying a bias-correction proxy, usSEABED data can be used to generate reliable interpolated maps of regional mean grain size and sediment character.

Continental Shelf Research↗

USGS2012

Structures data collection for the national map using volunteered geographic information

The U.S. Geological Survey (USGS) has historically sponsored volunteered data collection projects to enhance its topographic paper and digital map products. This report describes one phase of an ongoing project to encourage volunteers to contribute data to The National Map using online editing tools. The USGS recruited students studying geographic information systems (GIS) at the University of Colorado Denver and the University of Denver in the spring of 2011 to add data on structures - manmade features such as schools, hospitals, and libraries - to four quadrangles covering metropolitan Denver. The USGS customized a version of the online Potlatch editor created by the OpenStreetMap project and populated it with 30 structure types drawn from the Geographic Names Information System (GNIS), a USGS database of geographic features. The students corrected the location and attributes of these points and added information on structures that were missing. There were two rounds of quality control. Student volunteers reviewed each point, and an in-house review of each point by the USGS followed. Nine-hundred and thirty-eight structure points were initially downloaded from the USGS database. Editing and quality control resulted in 1,214 structure points that were subsequently added to The National Map . A post-project analysis of the data shows that after student edit and peer review, 92 percent of the points contributed by volunteers met National Map Accuracy Standards for horizontal accuracy. Lessons from this project will be applied to later phases. These include: simplifying editing tasks and the user interfaces, stressing to volunteers the importance of adding structures that are missing, and emphasizing the importance of conforming to editorial guidelines for formatting names and addresses of structures. The next phase of the project will encompass the entire State of Colorado and will allow any citizen to contribute structures data. Volunteers will benefit from this project by engaging with their local geography and contributing to a national resource of topographic information that remains in the public domain for anyone to download.

Denver↗

USGS2023

Spatially interactive modeling of land change identifies location-specific adaptations most likely to lower future flood risk

Impacts of sea level rise will last for centuries; therefore, flood risk modeling must transition from identifying risky locations to assessing how populations can best cope. We present the first spatially interactive (i.e., what happens at one location affects another) land change model (FUTURES 3.0) that can probabilistically predict urban growth while simulating human migration and other responses to flooding, essentially depicting the geography of impact and response. Accounting for human migration reduced total amounts of projected developed land exposed to flooding by 2050 by 5%–24%, depending on flood hazard zone (50%–0.2% annual probability). We simulated various “what-if” scenarios and found managed retreat to be the only intervention with predicted exposure below baseline conditions. In the business-as-usual scenario, existing and future development must be either protected or abandoned to cope with future flooding. Our open framework can be applied to different regions and advances local to regional-scale efforts to evaluate potential risks and tradeoffs.

South Carolina↗

USGS2013

U.S. Geological Survey natural hazards science strategy— Promoting the safety, security, and economic well-being of the Nation

Executive Summary The mission of the U.S. Geological Survey (USGS) in natural hazards is to develop and apply hazard science to help protect the safety, security, and economic well-being of the Nation. The costs and consequences of natural hazards can be enormous, and each year more people and infrastructure are at risk. USGS scientific research—founded on detailed observations and improved understanding of the responsible physical processes—can help to understand and reduce natural hazard risks and to make and effectively communicate reliable statements about hazard characteristics, such as frequency, magnitude, extent, onset, consequences, and where possible, the time of future events. To accomplish its broad hazard mission, the USGS maintains an expert workforce of scientists and technicians in the earth sciences, hydrology, biology, geography, social and behavioral sciences, and other fields, and engages cooperatively with numerous agencies, research institutions, and organizations in the public and private sectors, across the Nation and around the world. The scientific expertise required to accomplish the USGS mission in natural hazards includes a wide range of disciplines that this report refers to, in aggregate, as hazard science. In October 2010, the Natural Hazards Science Strategy Planning Team (H–SSPT) was charged with developing a long-term (10-year) Science Strategy for the USGS mission in natural hazards. This report fulfills that charge, with a document hereinafter referred to as the Strategy, to provide scientific observations, analyses, and research that are critical for the Nation to become more resilient to natural hazards. Science provides the information that decisionmakers need to determine whether risk management activities are worthwhile. Moreover, as the agency with the perspective of geologic time, the USGS is uniquely positioned to extend the collective experience of society to prepare for events outside current memory. The USGS has critical statutory and nonstatutory roles regarding floods, earthquakes, tsunamis, landslides, coastal erosion, volcanic eruptions, wildfires, and magnetic storms—the hazards considered in this plan. There are numerous other hazards of societal importance that are considered either only peripherally or not at all in this Strategy because they are either in another of the USGS strategic science plans (such as drought) or not in the overall mission of the USGS (such as tornados).

Circular↗

USGS2012

Natural hazards science strategy

The mission of the U.S. Geological Survey (USGS) in natural hazards is to develop and apply hazard science to help protect the safety, security, and economic well-being of the Nation. The costs and consequences of natural hazards can be enormous, and each year more people and infrastructure are at risk. USGS scientific research—founded on detailed observations and improved understanding of the responsible physical processes—can help to understand and reduce natural hazard risks and to make and effectively communicate reliable statements about hazard characteristics, such as frequency, magnitude, extent, onset, consequences, and where possible, the time of future events. To accomplish its broad hazard mission, the USGS maintains an expert workforce of scientists and technicians in the earth sciences, hydrology, biology, geography, social and behavioral sciences, and other fields, and engages cooperatively with numerous agencies, research institutions, and organizations in the public and private sectors, across the Nation and around the world. The scientific expertise required to accomplish the USGS mission in natural hazards includes a wide range of disciplines that this report refers to, in aggregate, as hazard science. In October 2010, the Natural Hazards Science Strategy Planning Team (H–SSPT) was charged with developing a long-term (10-year) Science Strategy for the USGS mission in natural hazards. This report fulfills that charge, with a document hereinafter referred to as the Strategy, to provide scientific observations, analyses, and research that are critical for the Nation to become more resilient to natural hazards. Science provides the information that decisionmakers need to determine whether risk management activities are worthwhile. Moreover, as the agency with the perspective of geologic time, the USGS is uniquely positioned to extend the collective experience of society to prepare for events outside current memory. The USGS has critical statutory and nonstatutory roles regarding floods, earthquakes, tsunamis, landslides, coastal erosion, volcanic eruptions, wildfires, and magnetic storms—the hazards considered in this plan. There are numerous other hazards of societal importance that are considered either only peripherally or not at all in this Strategy because they are either in another of the USGS strategic science plans (such as drought) or not in the overall mission of the USGS (such as tornados).

Open-File Report↗

USGS2025

Evaluating hydrologic data products for scientific and management applications related to potential future streamflow conditions in the Upper Mississippi and Illinois Rivers

The hydrology of the Upper Mississippi and Illinois Rivers is a fundamental driver of ecosystem patterns and processes across a large portion of the United States. Quantitative hydrologic data for the main stems of these rivers underlie numerous scientific investigations, statistical models, and decision-making processes for local, State, and Federal agencies involved in the Upper Mississippi River Restoration program. Although historical hydrologic data exist, data representing potential future conditions of the Upper Mississippi and Illinois Rivers lack the resolution necessary to anticipate biotic and abiotic responses to altered hydrology and to determine resilient management actions. A source of future hydrologic scenarios is the readily available LOCA–VIC–mizuRoute hydrologic data products (named for the chain of models the data are produced from—localized constructed analogs, Variable Infiltration Capacity macroscale hydrological model, and the mizuRoute hydrologic routing model—that we shorten further to LVM in this report) that include simulated discharges for historic and future timeframes. The objective of this study is to assess the reliability of the hydrologic data products for their use in Upper Mississippi River Restoration program applications. Key study questions are (1) do the hydrologic data products reproduce characteristics of hydrology necessary to support ecological modeling and restoration decision-making applications within the Upper Mississippi River Restoration program? and (2) are there geographic differences in the reliability of the hydrologic data products? Seven characteristics of river hydrology were selected related to flow magnitude, seasonality, and regime for evaluation. The seven characteristics were calculated using observed and historical simulated hydrologic data at 19 U.S. Geological Survey streamgages throughout the basins of the Upper Mississippi and Illinois Rivers; two streamgages are located on the main stem of the Mississippi River and two streamgages are located on the main stem of the Illinois River. Statistical comparisons between observed and historical simulated characteristics indicated that the hydrologic data products did not reliably represent historical hydrologic conditions in the basin or main stem. The hydrologic data products we evaluated could not reliably capture the overall hydrologic regime or flow magnitudes; the latter is evidenced by substantial underestimates of discharge at most streamgages. Seasonal hydrologic characteristics were captured more reliably than flow magnitude, but overall correspondence was low for most streamgages. A weak latitudinal pattern in seasonal characteristics indicated the hydrologic data products poorly represent streamflow timing in snow-affected regions of the basin. Discrepancies in magnitude, seasonality, and regime indicate the potential for multiple sources of error. Because poor correspondence was present across all 19 streamgages, it was not possible to identify specific drivers of poor performance (that is, drainage area or geography). The modeling chain should be evaluated for biases associated with meteorologic forcing data, as well as hydrologic model formulation and calibration. We conclude that the hydrologic data products we evaluated appear unsuitable for applications tied to habitat and ecosystem restoration and management in the Upper Mississippi and Illinois Rivers. Plans to develop a future hydrology dataset for the Upper Mississippi River Restoration program would benefit from ongoing work to improve global climate model output downscaling methods, to improve hydrologic models, to make use of innovations in machine-learning approaches for projecting hydrology, and other efforts. The framework developed herein to evaluate hydrometeorological outputs generated using global climate models for a specific water resources application is a transferrable approach that could be applied to other data products and river systems.

Illinois, Indiana, Iowa, Minnesota, Missouri, Sout↗

USGS2024

Geographic distribution of feather δ34S in Europe

Geographic distribution models of environmentally stable isotopes (the so-called “isoscapes”) are widely employed in animal ecology, and wildlife forensics and conservation. However, the application of isoscapes is limited to elements and regions for which the spatial patterns have been estimated. Here, we focused on the ubiquitous yet less commonly used stable sulfur isotopes (δ 34 S). To predict the European δ 34 S isoscape, we used 242 feather samples from Eurasian Reed Warbler ( Acrocephalus scirpaceus ) formed at 69 European wetland sites. We quantified the relationships between sample δ 34 S and environmental covariates using a random forest regression model and applied the model to predict the geographic distribution of δ 34 S. We also quantified within-site variation in δ 34 S and complementarity with other isotopes on both individual and isoscape levels. The predicted feather δ 34 S isoscape shows only slight differences between the central and southern parts of Europe while the coastal regions were most enriched in 34 S. The most important covariates of δ 34 S were distance to coastline, surface elevation, and atmospheric concentrations of SO 2 gases. The absence of a systematic spatial pattern impedes the application of the δ 34 S isoscape, but high complementarity with other isoscapes advocates the combination of multiple isoscapes to increase the precision of animal tracing. Feather δ 34 S compositions showed considerable within-site variation with highest values in inland parts of Europe, likely attributed to wetland anaerobic conditions and redox sensitivity of sulfur. The complex European geography and topography as well as using δ 34 S samples from wetlands may contribute to the absence of a systematic spatial gradient of δ 34 S values in Europe. We thus encourage future studies to focus on the geographic distribution of δ 34 S using tissues from diverse taxa collected in various habitats over large land masses in the world (i.e., Africa, South America, or East Asia).

Ecosphere↗