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At least 235 records · Page 13Linked to original sources
USGS2014

Strong influence of El Niño Southern Oscillation on flood risk around the world

El Niño Southern Oscillation (ENSO) is the most dominant interannual signal of climate variability and has a strong influence on climate over large parts of the world. In turn, it strongly influences many natural hazards (such as hurricanes and droughts) and their resulting socioeconomic impacts, including economic damage and loss of life. However, although ENSO is known to influence hydrology in many regions of the world, little is known about its influence on the socioeconomic impacts of floods (i.e., flood risk). To address this, we developed a modeling framework to assess ENSO’s influence on flood risk at the global scale, expressed in terms of affected population and gross domestic product and economic damages. We show that ENSO exerts strong and widespread influences on both flood hazard and risk. Reliable anomalies of flood risk exist during El Niño or La Niña years, or both, in basins spanning almost half (44%) of Earth’s land surface. Our results show that climate variability, especially from ENSO, should be incorporated into disaster-risk analyses and policies. Because ENSO has some predictive skill with lead times of several seasons, the findings suggest the possibility to develop probabilistic flood-risk projections, which could be used for improved disaster planning. The findings are also relevant in the context of climate change. If the frequency and/or magnitude of ENSO events were to change in the future, this finding could imply changes in flood-risk variations across almost half of the world’s terrestrial regions.

Proceedings of the National Academy of Sciences↗
USGS1982

Contour map showing minimum depth to ground water, upper Santa Ana River valley, California, 1973-1979

A contour map showing minimum depth to ground water from 1973 through 1979 was constructed for the upper Santa Ana River valley region. The map was prepared as an initial step in an ongoing liquefaction-potential study, but is not a liquefaction-hazard map. The contour map indicates where ground water shallower than 50 ft below land surface occurred at least once during the 1973-1979 period, and also indicates the probable future distribution of ground water shallower than 50 ft below land surface for periods when climatic conditions and water-management policies similar to those in the 1970's recur. This contour map does not show how the water table actually looked at any particular instant during the reporting period, nor does it show average or typical ground-water conditions during the reporting period. Instead, this map shows what the regional ground-water table would look like if the shallowest water level measured in each well during the 1973-1979 period is used as the basis for constructing a map of minimum depth to ground water. This map identifies twenty areas within the upper Santa Ana River valley where water levels in wells were shallower than 50 ft below land surface at least once during the period 1973-1979. In the greater Santa Ana River area, between the San Jacinto ground-water barrier and Prado flood-control dam, ground water was shallower than 50 ft below land surface intermittently throughout the 1973-1979 period. In this area, shallow water generally reflects shallow depths to impermeable bedrock and the ease and frequency with which ground water is replenished by natural and artificial recharge. Most of the other areas of shallow ground water identified on this map experienced pervasive shallow water levels only after mid-1977. Prior to mid-1977, ground water in these areas generally was deeper than 50 ft below land surface. During later parts of the 1973-1979 period, water tables rose mainly because of two factors: (1) wetter-than-normal winters in 1977-1978 and 19781979 contributed increased volumes of surface runoff and natural recharge in the upper Santa Ana River valley region; and (2) commencing in 1972, ground water in the Valley region has been replenished by artificial recharge of imported water derived from the California State Water Project. The accelerated natural and artificial recharge of ground water basins in 1977, 1978, and 1979 raised ground water tables throughout the Valley region. Water-level records more recent than September 1979 indicate that for most of the twenty areas of shallow ground water, water levels have remained shallower than 50 ft below land surface through December 1981. In some areas, water levels have risen even more. For example, in the San Bernardino area, rising water locally has invaded basements, undermined roadways, and affected foundation construction. Where post-1979 water levels have continued to rise, the areas underlain by shallow ground water have expanded and now are larger than the areas shown on the contour map of this report.

California↗
USGS2014

Effects of environmental amenities and locational disamenities on home values in the Santa Cruz watershed: a hedonic analysis using census data

For this study, we used the hedonic pricing method to measure the effects of natural amenities on home prices in the U.S-side of the Santa Cruz Watershed. We employed multivariate spatial regression techniques to estimate how difference factors affect median home values in 613 census block groups of the 2000 Census, accounting for spatial autocorrelation, spatial lags, and/or spatial heterogeneity in the data. Diagnostic tests suggest that failure to account for the hedonic model can be classified as (1) physical features of the housing stock, (2) neighborhood characteristics, and (3) environmental attributes. Census data was combined with GIS data for vegetation and land cover, land administration, measures of species richness and open space, and proximity to amenities and disamenities. Census block groups close to the US-Mexico border of airports/air bases were negative. Results suggest that policies to maintain biodiversity and open space provide economic benefits to homeowners, reflected in higher home values. Future research will quantify the marginal effects of regression explanatory variables on home values to assess their economic and policy significant. These marginal effects will be used as input indicators to discern potential economic impacts of various scenarios in the Santa Cruz Watershed Ecosystem Portfolio Model (SCWEPM). Future research will also expand this effort into the Mexican-portion of the watershed.

Arizona↗
USGS2010

Hazards affecting grizzly bear survival in the Greater Yellowstone Ecosystem

During the past 2 decades, the grizzly bear ( Ursus arctos ) population in the Greater Yellowstone Ecosystem (GYE) has increased in numbers and expanded its range. Early efforts to model grizzly bear mortality were principally focused within the United States Fish and Wildlife Service Grizzly Bear Recovery Zone, which currently represents only about 61% of known bear distribution in the GYE. A more recent analysis that explored one spatial covariate that encompassed the entire GYE suggested that grizzly bear survival was highest in Yellowstone National Park, followed by areas in the grizzly bear Recovery Zone outside the park, and lowest outside the Recovery Zone. Although management differences within these areas partially explained differences in grizzly bear survival, these simple spatial covariates did not capture site-specific reasons why bears die at higher rates outside the Recovery Zone. Here, we model annual survival of grizzly bears in the GYE to 1) identify landscape features (i.e., foods, land management policies, or human disturbances factors) that best describe spatial heterogeneity among bear mortalities, 2) spatially depict the differences in grizzly bear survival across the GYE, and 3) demonstrate how our spatially explicit model of survival can be linked with demographic parameters to identify source and sink habitats. We used recent data from radiomarked bears to estimate survival (1983–2003) using the known-fate data type in Program MARK. Our top models suggested that survival of independent (age ≥2 yr) grizzly bears was best explained by the level of human development of the landscape within the home ranges of bears. Survival improved as secure habitat and elevation increased but declined as road density, number of homes, and site developments increased. Bears living in areas open to fall ungulate hunting suffered higher rates of mortality than bears living in areas closed to hunting. Our top model strongly supported previous research that identified roads and developed sites as hazards to grizzly bear survival. We also demonstrated that rural homes and ungulate hunting negatively affected survival, both new findings. We illustrate how our survival model, when linked with estimates of reproduction and survival of dependent young, can be used to identify demographically the source and sink habitats in the GYE. Finally, we discuss how this demographic model constitutes one component of a habitat-based framework for grizzly bear conservation. Such a framework can spatially depict the areas of risk in otherwise good habitat, providing a focus for resource management in the GYE.

Idaho, Montana, Wyoming↗
USGS2013

Symposium 9: Rocky Mountain futures: preserving, utilizing, and sustaining Rocky Mountain ecosystems

In 2002 we published Rocky Mountain Futures, an Ecological Perspective (Island Press) to examine the cumulative ecological effects of human activity in the Rocky Mountains. We concluded that multiple local activities concerning land use, hydrologic manipulation, and resource extraction have altered ecosystems, although there were examples where the “tyranny of small decisions” worked in a positive way toward more sustainable coupled human/environment interactions. Superimposed on local change was climate change, atmospheric deposition of nitrogen and other pollutants, regional population growth, and some national management policies such as fire suppression.

Bulletin of the Ecological Society of America↗
USGS2004

A decision support system for map projections of small scale data

The use of commercial geographic information system software to process large raster datasets of terrain elevation, population, land cover, vegetation, soils, temperature, and rainfall requires both projection from spherical coordinates to plane coordinate systems and transformation from one plane system to another. Decision support systems deliver information resulting in knowledge that assists in policies, priorities, or processes. This paper presents an approach to handling the problems of raster dataset projection and transformation through the development of a Web-enabled decision support system to aid users of transformation processes with the selection of appropriate map projections based on data type, areal extent, location, and preservation properties.

Scientific Investigations Report↗
USGS2019

Integrating landscape simulation models with economic and decision tools for invasive species control

In managing invasive species, land managers and policy makers need information to help allocate scarce resources as efficiently and effectively as possible. Decisions regarding treatment methods, locations, effort, and timing can be informed by the integration of landscape simulation models with economic tools. State and transition simulation models align with conceptual models of ecosystem change often used by practitioners and have been used to characterize the potential consequences of invasions. Outputs of these simulations are typically summarized to describe landscape changes (e.g., infested area), which may provide sufficient information for mangers to make informed decisions. However, it is sometimes helpful or necessary to go a step further to consider the social and economic values associated with treating (or not treating) invasions. Here, we describe when and how to integrate state and transition simulation models with economic and decision tools to aid in the control of emerging and established populations of invasive species. The paper provides an overview of three types of questions that can be addressed: 1) how big is the problem? 2) which management strategy is most appropriate? and 3) what are key sources of uncertainty? For each question, we describe aspects that can be addressed by landscape simulation models alone, and outstanding questions that can be evaluated by integrating economic and decision tools. Through a series of example applications from the literature, we reinforce how the integration of these tools, and the interdisciplinary perspective such an integration requires, can increase relevance and utility of modeling efforts for resource managers and decision makers.

Management of Biological Invasions↗
USGS1998

Effect of interannual climate variability on carbon storage in Amazonian ecosystems

The Amazon Basin contains almost one-half of the world's undisturbed tropical evergreen forest as well as large areas of tropical savanna. The forests account for about 10 per cent of the world's terrestrial primary productivity and for a similar fraction of the carbon stored in land ecosystems, and short-term field measurements suggest that these ecosystems are globally important carbon sinks. But tropical land ecosystems have experienced substantial interannual climate variability owing to frequent El Nino episodes in recent decades. Of particular importance to climate change policy is how such climate variations, coupled with increases in atmospheric CO2 concentration, affect terrestrial carbon storage. Previous model analyses have demonstrated the importance of temperature in controlling carbon storage. Here we use a transient process-based biogeochemical model of terrestrial ecosystems to investigate interannual variations of carbon storage in undisturbed Amazonian ecosystems in response to climate variability and increasing atmospheric CO2 concentration during the period 1980 to 1994. In El Nino years, which bring hot, dry weather to much of the Amazon region, the ecosystems act as a source of carbon to the atmosphere (up to 0.2 petagrams of carbon in 1987 and 1992). In other years, these ecosystems act as a carbon sink (up to 0.7 Pg C in 1981 and 1993). These fluxes are large; they compare to a 0.3 Pg C per year source to the atmosphere associated with deforestation in the Amazon Basin in the early 1990s. Soil moisture, which is affected by both precipitation and temperature, and which affects both plant and soil processes, appears to be an important control on carbon storage.

Nature↗
USGS2024

Structured science syntheses to inform decision making on Federal public lands

The U.S. Geological Survey, Bureau of Land Management, and U.S. Fish and Wildlife Service partnered to develop a new type of science product: the structured science synthesis. Structured science syntheses are peer-reviewed reports that synthesize science information about a priority resource management issue on public lands. Structured science syntheses are developed explicitly to facilitate the application of science to decision making. Key characteristics of structured science syntheses include that they are coproduced with resource managers, developed using clear, repeatable methods and designed for ease of use. The syntheses include different types of science information needed for analyses completed under the National Environmental Policy Act.

Fact Sheet↗
USGS2012

An economic value of remote-sensing information—Application to agricultural production and maintaining groundwater quality

Does remote-sensing information provide economic benefits to society, and can a value be assigned to those benefits? Can resource management and policy decisions be better informed by coupling past and present Earth observations with groundwater nitrate measurements? Using an integrated assessment approach, the U.S. Geological Survey (USGS) applied an established conceptual framework to answer these questions, as well as to estimate the value of information (VOI) for remote-sensing imagery. The approach uses moderate-resolution land-imagery (MRLI) data from the Landsat and Advanced Wide Field Sensor satellites that has been classified by the National Agricultural Statistics Service into the Cropland Data Layer (CDL). Within the constraint of the U.S. Environmental Protection Agency's public health threshold for potable groundwater resources, the USGS modeled the relation between a population of the CDL's land uses and dynamic nitrate (NO3-) contamination of aquifers in a case study region in northeastern Iowa. Employing various multiscaled, multitemporal geospatial datasets with MRLI to maximize the value of agricultural production, the approach develops and uses multiple environmental science models to address dynamic nitrogen loading and transport at specified distances from specific sites (wells) and at landscape scales (for example, across 35 counties and two aquifers). In addition to the ecosystem service of potable groundwater, this effort focuses on the use of MRLI for the management of the major land uses in the study region-the production of corn and soybeans, which can impact groundwater quality. Derived methods and results include (1) economic and dynamic nitrate-pollution models, (2) probabilities of the survival of groundwater, and (3) a VOI for remote sensing. For the northeastern Iowa study region, the marginal benefit of the MRLI VOI (in 2010 dollars) is $858 million ±$197 million annualized, which corresponds to a net present value of $38.1 billion ±$8.8 billion for that flow of benefits in perpetuity. Given that these economic estimates are derived from one case study in a part of only one State, the estimates provide a lower estimate related to the potential value of the Landsat Data Continuity Mission.

Professional Paper↗
USGS2025

Impact of land subsidence on housing sale values: Evidence from the San Joaquin Valley, California

This study assesses the impact of land subsidence on housing sale values in the San Joaquin Valley, California. The study utilizes home sale transactions and vertical land-surface displacement data from Interferometric Synthetic Aperture Radar techniques. Using fine-scale fixed effects, matching, as well as a repeat-sales approach, our results indicate that land subsidence resulted in a 2.4% to 5.8% reduction in housing sale values, with the largest reductions occurring in areas where substantial subsidence occurred. Such findings may have implications for groundwater management and can potentially help inform policy design to help mitigate the causes and impacts of land subsidence.

California↗
USGS2022

Riparian plant evapotranspiration and consumptive use for selected areas of the Little Colorado River watershed on the Navajo Nation

Estimates of riparian vegetation water use are important for hydromorphological assessment, partitioning within human and natural environments, and informing environmental policy decisions. The objectives of this study were to calculate the actual evapotranspiration (ETa) (mm/day and mm/year) and derive riparian vegetation annual consumptive use (CU) in acre-feet (AF) for select riparian areas of the Little Colorado River watershed within the Navajo Nation, in northeastern Arizona, USA. This was accomplished by first estimating the riparian land cover area for trees and shrubs using a 2019 summer scene from National Agricultural Imagery Program (NAIP) (1 m resolution), and then fusing the riparian delineation with Landsat-8 OLI (30-m) to estimate ETa for 2014–2020. We used indirect remote sensing methods based on gridded weather data, Daymet (1 km) and PRISM (4 km), and Landsat measurements of vegetation activity using the two-band Enhanced Vegetation Index (EVI2). Estimates of potential ET were calculated using Blaney-Criddle. Riparian ETa was quantified using the Nagler ET(EVI2) approach. Using both vector and raster estimates of tree, shrub, and total riparian area, we produced the first CU measurements for this region. Our best estimate of annual CU is 36,983 AF with a range between 31,648–41,585 AF and refines earlier projections of 25,387–46,397 AF.

Arizona, Colorado, New Mexico, Utah↗
USGS2020

A socio-environmental geodatabase for integrative research in the transboundary Rio Grande/Río Bravo basin

Management of water resources in the transboundary Rio Grande/Río Bravo Basin (the Basin) presents challenges for state and Federal entities in the United States and Mexico making management decisions on shared water resources. Damming, channelization, water availability, and allocation are governed by water rights and water-sharing agreements. Data and information sharing are important aspects of transboundary cooperation, but differences in format, content, spatial and temporal resolution, and language hinder collaboration. In addition, data on the kinds and geographic distribution of water governance and management institutions across the Basin have not been consistently documented. Existing data disparities parallel the hydrological and social fragmentation of the Basin. Seeking to underscore the interdependence between social and environmental processes in the Basin, anthropologists and modelers collaborated to develop a socio-environmental geodatabase. This geodatabase is a first step in modeling the social components of decision making and their connectivity to environmental processes across the Basin. The geodatabase is available in an open-access domain and contains geospatial data related to water and land governance, hydrology, water use and hydraulic infrastructure, socioeconomics, and the biophysical environment necessary to advance the understanding of basin dynamics. Having these data documented and compiled in a central location serves as a resource to help decision makers better understand upstream and downstream social-environmental characteristics. This knowledge is useful for developing sustainable water management policies in a region where water resources are increasingly under pressure from climatic, environmental, and human-related changes.

Chihuahua, New Mexico, Texas↗
USGS2026

Cumulative effects analysis to inform public land management in the United States: Key characteristics and legal challenges

Considering potential cumulative effects of proposed actions is fundamental to environmental impact analysis. However, cumulative effects analyses historically are not robust, especially for site-specific decisions. We sought to identify opportunities to strengthen cumulative effects analysis in a large United States public land management agency, the Bureau of Land Management (BLM). We asked 1) how cumulative effects analyses were legally challenged, 2) how site-specific cumulative effects analyses aligned with policy and compared to the broader-scale analyses to which they tiered, and 3) whether characteristics of cumulative effects analyses varied with category of proposed action, type of resource, or agency office. We used thematic analysis to assess litigation and appeals case documents finalized from 2010 to 2020 and a set of document analysis questions to assess National Environmental Policy Act (NEPA) analyses for BLM decisions completed prior to 2020 in Alaska and Colorado. We found that legal challenges related to cumulative effects focused on absence of cumulative effects analysis. In NEPA analyses, cumulative effects were frequently considered, but elements recommended in policy, such as citations, methods, and scope, were rarely included. These elements were present more often in the broader analyses to which site-specific analyses tiered. Many elements of cumulative effects analyses varied by proposed action and BLM office, and analyses of potential cumulative effects on air quality were consistently more detailed than for other resources. Our results suggest that many problems that historically plagued cumulative effects analysis persist. Advances in methods, training, and guidance could strengthen the defensibility of NEPA analyses.

Alaska, Colorado↗
USGS2005

Fire history of the San Francisco East Bay region and implications for landscape patterns

The San Francisco East Bay landscape is a rich mosaic of grasslands, shrublands and woodlands that is experiencing losses of grassland due to colonization by shrubs and succession towards woodland associations. The instability of these grasslands is apparently due to their disturbance-dependent nature coupled with 20th century changes in fire and grazing activity. This study uses fire history records to determine the potential for fire in this region and for evidence of changes in the second half of the 20th century that would account for shrubland expansion. This region has a largely anthropogenic fire regime with no lightning-ignited fires in most years. Fire suppression policy has not excluded fire from this region; however, it has been effective at maintaining roughly similar burning levels in the face of increasing anthropogenic fires, and effective at decreasing the size of fires. Fire frequency parallels increasing population growth until the latter part of the 20th century, when it reached a plateau. Fire does not appear to have been a major factor in the shrub colonization of grasslands, and cessation of grazing is a more likely immediate cause. Because grasslands are not under strong edaphic control, rather their distribution appears to be disturbance-dependent, and natural lightning ignitions are rare in the region, I hypothesize that, before the entrance of people into the region, grasslands were of limited extent. Native Americans played a major role in creation of grasslands through repeated burning and these disturbance-dependent grasslands were maintained by early European settlers through overstocking of these range lands with cattle and sheep. Twentieth century reduction in grazing, coupled with a lack of natural fires and effective suppression of anthropogenic fires, have acted in concert to favor shrubland expansion.

International Journal of Wildland Fire↗
USGS2026

Colocating artificial intelligence data centers with energy infrastructure on Federal public lands—A science synthesis and spatial analysis to inform decision making

Executive Summary Artificial intelligence (AI) is rapidly transforming industries and economies, creating an urgent need to strategically plan for the energy and infrastructure required to support increasing AI use. U.S. Federal agencies and bureaus have been directed to explore ways to accelerate permitting, development, and deployment of energy resources and AI technologies, including encouraging the colocation of energy infrastructure and data centers. To inform these initiatives, this report synthesizes relevant scientific information and presents a spatial analysis of existing energy infrastructure and data centers on or near U.S. Federal public lands managed by the Bureau of Land Management (BLM). The purpose of this science synthesis and spatial analysis is to provide the BLM with foundational information for considering potential colocation of data centers with energy infrastructure on Federal public lands to support evidence-based decisions. Additionally, this report provides insight into current (2025) and potential future energy demands by providing projections of a range of potential future environmental conditions relevant to maintaining industry-recommended cooling temperature standards necessary for efficient data center operations. As a part of this effort, a rapid response literature review was conducted of the best available science on the topic of data center development and energy infrastructure in July–August 2025, supplemented by additional resources recommended by U.S. Federal agency and bureau subject matter experts (hereafter experts; including the U.S. Department of Energy National Laboratory of the Rockies) and peer reviewers. To better understand current conditions relevant to AI data center development, a spatial analysis was conducted across Alaska and 11 States in the Western United States, Arizona, California, Colorado, Idaho, Montana, Nevada, New Mexico, Oregon, Utah, Washington, and Wyoming, all of which contain extensive BLM-managed surface lands (hereafter referred to as “BLM lands”) that could be considered for the colocation of energy infrastructure and AI data centers. This effort identified BLM lands within 10 miles of existing transmission lines, consistent with methods used in previous BLM programmatic environmental impact statements. This report describes the types of data centers operating within the United States, which vary in ownership, size, technology, and proximity to end users. This report then outlines the primary considerations of data center development, including reliable energy supply, natural resources (such as water availability to support cooling requirements), and relevant policy and regulatory considerations. Energy supply considerations are pivotal for data center operation. Between 2014 and 2018, data centers in the United States accounted for nearly 2 percent of the Nation’s total electricity consumption, and data center energy consumption is projected to increase from 2 to 6.7–12 percent of total U.S. electricity use by 2028. These energy requirements necessitate careful consideration of energy supply when considering potentially suitable locations for data center development. Experts anticipate that an increase in renewable energy generation will likely support most potential future power demand needs, including for data centers, followed by increases in natural gas, nuclear, and geothermal energy production. Additional capacity in the form of battery storage will likely not generate electricity, but may improve the reliability and flexibility of supply, helping to ensure that growing data center loads can be met. However, the U.S. Department of Energy estimates that the United States will need, on average, 57 percent more energy transmission infrastructure by 2035 to account for the growing power demand introduced by development such as data centers. Cooling server equipment in data centers requires large amounts of electricity and water, and this demand can be exacerbated by hot and humid conditions. Energy efficient water-based cooling technologies may reduce electricity consumption onsite but require more water consumption. This additional water demand has the potential to increase water stress and competition with other users. As such, developing data centers will likely need a thorough assessment of current and potential future water availability, as well as consideration of how water demand may change across other sectors. Data center development involves policy and regulatory considerations, as projects must undergo environmental review and authorization processes that can take 18–24 months. Coordinating these environmental reviews and authorizations with other energy development projects, such as building new transmission lines, may cause additional delays. Recent efforts by the U.S. Department of Energy and U.S. Department of the Interior aim to expedite environmental reviews and authorizations and improve coordination across agencies. The spatial analysis identified 771 existing AI data centers and more than 3,300 power plants. The spatial analysis found that 6 percent of AI data centers and 22 percent of power plants in the Western United States were on or within 1 mile of BLM lands, and California had the largest number of facilities. Most existing AI data centers were near high-voltage transmission lines and close to power plants, supporting efficient energy delivery. More than 90,000,000 acres of BLM lands were within 10 miles of existing high-voltage transmission lines, representing 38 percent of BLM lands in the study area. Available transmission infrastructure and the overlap with BLM lands varied by State, and Alaska had limited overlap compared to the rest of the Western United States. To operate most efficiently, data center temperatures must be at or below 80.6 degrees Fahrenheit. This analysis of future temperature and precipitation projections indicated increasing cooling demands for data centers, particularly in Arizona, California, and Nevada, where rising temperatures are expected to increase energy and operational costs while potentially stressing current regional electrical grid infrastructure. This report highlights relevant energy supply, natural resources, and regulatory considerations for data center development on BLM lands. This report does not provide a comprehensive ecological, regulatory, land suitability, or permitting analysis. The factors described here are contextual considerations only and are not intended to identify, rank, quantify, or recommend optimal areas for data center colocation. This spatial analysis focused solely on energy considerations relevant to data centers and did not consider water availability, critical habitats, BLM National Conservation Lands, areas of cultural or historical significance, and other sensitive resources. These topics are recognized as critical but were not within the scope of this science synthesis and spatial analysis.

Scientific Investigations Report↗
USGS2010

Evolution of Ore Deposits and Technology Transfer Project: Isotope and Chemical Methods in Support of the U.S. Geological Survey Science Strategy, 2003-2008

Principal functions of the U.S. Geological Survey (USGS) Mineral Resources Program are providing assessments of the location, quantity, and quality of undiscovered mineral deposits, and predicting the environmental impacts of exploration and mine development. The mineral and environmental assessments of domestic deposits are used by planners and decisionmakers to improve the stewardship of public lands and public resources. Assessments of undiscovered mineral deposits on a global scale reveal the potential availability of minerals to the United States and other countries that manufacture goods imported to the United States. These resources are of fundamental relevance to national and international economic and security policy in our globalized world economy. Performing mineral and environmental assessments requires that predictions be made of the likelihood of undiscovered deposits. The predictions are based on geologic and geoenvironmental models that are constructed for the diverse types of mineral deposits from detailed descriptions of actual deposits and detailed understanding of the processes that formed them. Over the past three decades the understanding of ore-forming processes has benefited greatly from the integration of laboratory-based geochemical tools with field observations and other data sources. Under the aegis of the Evolution of Ore Deposits and Technology Transfer Project (referred to hereinafter as the Project), a 5-year effort that terminated in 2008, the Mineral Resources Program provided state-of-the-art analytical capabilities to support applications of several related geochemical tools to ore-deposit-related studies. The analytical capabilities and scientific approaches developed within the Project have wide applicability within Earth-system science. For this reason the Project Laboratories represent a valuable catalyst for interdisciplinary collaborations of the type that should be formed in the coming years for the United States to meet its natural-resources and natural-science needs. This circular presents an overview of the Project. Descriptions of the Project laboratories are given first including descriptions of the types of chemical or isotopic analyses that are made and the utility of the measurements. This is followed by summaries of select measurements that were carried out by the Project scientists. The studies are grouped by science direction. Virtually all of them were collaborations with USGS colleagues or with scientists from other governmental agencies, academia, or the private sector.

Circular↗
USGS2002

Application of landscape models to alternative futures analyses

Scientists and environmental managers alike are concerned about broadscale changes in land use and landscape pattern and their cumulative impact on environmental and economic end points, such as water quality and quantity, species habitat, productivity, erosion potential, recreational value, and overall ecological health (Rapport et al., 1998). They also are interested in predicting short-and long-term future impacts on ecological goods and services based on current land management policies and decisions (Steinitz, 1996). Because we have the means to adjust land management policies, it is worthwhile to develop approaches that can predict the consequences (alternative futures) of different land management policies for different environmental end points. This type of analysis can, for example, allow decision makers in resource conservation and restoration programs to estimate how they can get the most ecological benefit for the least cost

Delaware, Maryland, New York, Pennsylvania, Virgin↗