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At least 37 records · Page 2Linked to original sources
USGS2013

Fort Collins Science Center Ecosystem Dynamics branch--interdisciplinary research for addressing complex natural resource issues across landscapes and time

The Ecosystem Dynamics Branch of the Fort Collins Science Center offers an interdisciplinary team of talented and creative scientists with expertise in biology, botany, ecology, geology, biogeochemistry, physical sciences, geographic information systems, and remote-sensing, for tackling complex questions about natural resources. As demand for natural resources increases, the issues facing natural resource managers, planners, policy makers, industry, and private landowners are increasing in spatial and temporal scope, often involving entire regions, multiple jurisdictions, and long timeframes. Needs for addressing these issues include (1) a better understanding of biotic and abiotic ecosystem components and their complex interactions; (2) the ability to easily monitor, assess, and visualize the spatially complex movements of animals, plants, water, and elements across highly variable landscapes; and (3) the techniques for accurately predicting both immediate and long-term responses of system components to natural and human-caused change. The overall objectives of our research are to provide the knowledge, tools, and techniques needed by the U.S. Department of the Interior, state agencies, and other stakeholders in their endeavors to meet the demand for natural resources while conserving biodiversity and ecosystem services. Ecosystem Dynamics scientists use field and laboratory research, data assimilation, and ecological modeling to understand ecosystem patterns, trends, and mechanistic processes. This information is used to predict the outcomes of changes imposed on species, habitats, landscapes, and climate across spatiotemporal scales. The products we develop include conceptual models to illustrate system structure and processes; regional baseline and integrated assessments; predictive spatial and mathematical models; literature syntheses; and frameworks or protocols for improved ecosystem monitoring, adaptive management, and program evaluation. The descriptions in this fact sheet provide snapshots of our three research emphases, followed by descriptions of select current projects.

Fact Sheet↗
USGS2011

Natural resource mitigation, adaptation and research needs related to climate change in the Great Basin and Mojave Desert

This report synthesizes the knowledge, opinions, and concerns of many Federal and State land managers, scientists, stakeholders, and partners from a workshop, held at the University of Nevada, Las Vegas, on April 20-22, 2010. Land managers, research scientists, and resource specialists identified common concerns regarding the potential effects of climate change on public lands and natural resources in the Great Basin and Mojave Desert and developed recommendations for mitigation, adaptation, and research needs. Water and, conversely, the effects of drought emerged as a common theme in all breakout sessions on terrestrial and aquatic species at risk, managing across boundaries, monitoring, and ecosystem services. Climate change models for the southwestern deserts predict general warming and drying with increasing precipitation variability year to year. Scientists noted that under these changing conditions the past may no longer be a guide to the future in which managers envision increasing conflicts between human water uses and sustaining ecosystems. Increasing environmental stress also is expected as a consequence of shifting ecosystem boundaries and species distributions, expansion of non-native species, and decoupling of biotic mutualisms, leading to increasingly unstable biologic communities. Managers uniformly expressed a desire to work across management and agency boundaries at a landscape scale but conceded that conflicting agency missions and budgetary constraints often impede collaboration. More and better science is needed to cope with the effects of climate change but, perhaps even more important is the application of science to management issues using the methods of adaptive management based on long-term monitoring to assess the merits of management actions. Access to data is essential for science-based land management. Basic inventories, spatial databases, baseline condition assessments, data quality assurance, and data sharing were identified as top information priorities by all participants at this workshop. Optimizing the utility of ecosystem monitoring data will require standardizing monitoring protocols across agencies. Better communication among researchers and managers and cooperation through partnerships to manage resources across boundaries were emphasized as necessary for adapting to changing climatic conditions. However, even these strategies may be insufficient unless policy mandates, agency missions, and funding are coordinated at a high level.

Scientific Investigations Report↗
USGS2024

Boundary spanning increases knowledge and action on invasive species in a changing climate

Challenges associated with global change stressors on ecosystems have prompted calls to improve actionable science, including through boundary-spanning activities, which aim to build connections and communication between researchers and natural resource practitioners. By synthesizing and translating research and practitioner knowledge, boundary-spanning activities could support proactive, research-informed conservation practice, but the success of these efforts is rarely evaluated. Using repeat survey data from the Northeast Regional Invasive Species and Climate Change (NE RISCC) Management Network, a boundary-spanning organization, we evaluate whether participating in NE RISCC affected practitioners' knowledge, actions and priorities related to invasive species management under a changing climate. Our survey results suggest that practitioners who participate in NE RISCC have greater knowledge about invasive species and climate change and are incorporating climate change in more ways into their invasive species management. We also found NE RISCC membership affected the perceived usefulness of informational resources, with NE RISCC members more frequently identifying research syntheses and targeted workshops (both are common products used by NE RISCC to translate science into practice and share manager knowledge) as useful compared to non-members. Practitioners who participate in NE RISCC also identified somewhat different research priorities, with non-members and short-term members more frequently identifying range-shifting neonative species and their impacts on native communities as higher priorities compared to long-term NE RISCC members. NE RISCC research activities and outreach materials have consistently framed range-shifting neonative species as comparatively low risk, suggesting that this information has influenced practitioner's perception of risk. Practical implication : Although real-world impacts of applied ecology are notoriously difficult to quantify, this analysis illustrates that if research results are actively translated, they can affect the knowledge and actions of natural resource practitioners. These impacts illustrate the potential for boundary-spanning efforts to address other global change challenges to conservation.

Ecological Solutions and Evidence↗
USGS2025

Relationship-centered engagement bridges the divide between science and management, and enhances climate adaptation

The rapid pace of climate change demands changes in management practices. Despite abundant climate adaptation research, the implementation of climate adaptation can lag in the management space. In the present article, we argue that relationship-centered engagement—establishing and maintaining relationships among researchers and natural resource managers—is critical for bridging the research–management gap. We evaluated researcher–manager partnerships within the US Northeast Climate Adaptation Science Center and identified three cultural shifts that institutions, funders, researchers, and managers could adopt to boost the odds of translating findings into action: acknowledging and supporting the central role of relationships in creating and implementing actionable science, lengthening funding timelines to better support establishing and maintaining relationships, and aligning institutional rewards to support relationship building. A renewed focus on relationships can lead to more diverse and effective partnerships that bridge knowledge to practice and hasten adaptation to climate change.

BioScience↗
USGS2015

Social and Economic Analysis Branch: integrating policy, social, economic, and natural science

The Fort Collins Science Center's Social and Economic Analysis Branch provides unique capabilities in the U.S. Geological Survey by leading projects that integrate social, behavioral, economic, and natural science in the context of human–natural resource interactions. Our research provides scientific understanding and support for the management and conservation of our natural resources in support of multiple agency missions. We focus on meeting the scientific needs of the Department of the Interior natural resource management bureaus in addition to fostering partnerships with other Federal and State managers to protect, restore, and enhance our environment. The Social and Economic Analysis Branch has an interdisciplinary group of scientists whose primary functions are to conduct both theoretical and applied social science research, provide technical assistance, and offer training to support the development of skills in natural resource management activities. Management and research issues associated with human-resource interactions typically occur in a unique context and require knowledge of both natural and social sciences, along with the skill to integrate multiple science disciplines. In response to these challenging contexts, Social and Economic Analysis Branch researchers apply a wide variety of social science concepts and methods which complement our rangeland/agricultural, wildlife, ecology, and biology capabilities. The goal of the Social and Economic Analysis Branch's research is to enhance natural-resource management, agency functions, policies, and decisionmaking.

Fact Sheet↗
USGS2015

Proceedings of the 9th U.S.-Japan natural resources panel for earthquake research

Introduction The UJNR Panel on Earthquake Research promotes advanced study toward a more fundamental understanding of the earthquake process and hazard estimation. The Ninth Joint meeting was extremely beneficial in furthering cooperation and deepening understanding of problems common to both the U.S. and Japan. The meeting included productive exchanges of information on approaches to systematic observation and modeling of earthquake processes. Regarding the earthquake and tsunami of March 2011 off the Pacific coast of Tohoku, the Panel recognizes that further efforts are necessary to achieve our common goal of reducing earthquake risk through close collaboration and focused discussions at the 10th UJNR meeting. We look forward to continued cooperation on issues involving the densification of observation networks and the open exchange of data among scientific communities. We recognize the importance of making information publicly available in a timely manner. We also recognize the importance of information exchange on research policy and strategies, including the frameworks of research organizations. Areas of Cooperation –Specific areas of earthquake research where cooperative research between the U.S. and Japan may lead to significant advancement include, but are not limited to: –Probabilistic earthquake and tsunami hazard estimation, including extraordinarily large earthquakes, both in our respective countries and worldwide, incorporating knowledge of current and past behavior, and physics based computational models; –Real-time information from seismic, geodetic and strain measurements, including borehole strainmeters and seafloor observations using offshore cabled networks; –Technologies for measuring crustal deformation; –Early warning technologies for earthquakes and tsunamis; Studies of recurrence of large and extraordinary large earthquakes using paleoseismic, paleotsunami, geodetic and seismic methods; –Laboratory, theoretical and in situ studies of fault-zone processes; –Studies of episodic tremor and slow slip events using seismic, geodetic, and borehole strain measurements, and simulation techniques; –Systematic studies of earthquake predictability through rigorously evaluated scientific prediction experiments and robust databases; –Studies of near-source ground motions, geological effects and the response of engineered structures. The Panel strongly urges that the appropriate agencies in the U.S. and Japan that are represented on this panel work together with the academic sector to support and coordinate scientific work in these areas of cooperation. The Panel recognizes the importance of promoting the exchange of scientific personnel, exchange of data, and fundamental studies to advance progress in earthquake research. The U.S. and Japan should promote these exchanges throughout the world. The Panel endorses continuation of these activities.

Open-File Report↗
USGS2017

Proceedings of the 11th United States-Japan natural resources panel for earthquake research, Napa Valley, California, November 16–18, 2016

The UJNR Panel on Earthquake Research promotes advanced research toward a more fundamental understanding of the earthquake process and hazard estimation. The Eleventh Joint meeting was extremely beneficial in furthering cooperation and deepening understanding of problems common to both Japan and the United States. The meeting included productive exchanges of information on approaches to systematic observation and modeling of earthquake processes. Regarding the earthquake and tsunami of March 2011 off the Pacific coast of Tohoku and the 2016 Kumamoto earthquake sequence, the Panel recognizes that further efforts are necessary to achieve our common goal of reducing earthquake risk through close collaboration and focused discussions at the 12th UJNR meeting.

Open-File Report↗
USGS2009

Unconventional energy resources: 2007-2008 review

This paper summarizes five 2007–2008 resource commodity committee reports prepared by the Energy Minerals Division (EMD) of the American Association of Petroleum Geologists. Current United States and global research and development activities related to gas hydrates, gas shales, geothermal resources, oil sands, and uranium resources are included in this review. These commodity reports were written to advise EMD leadership and membership of the current status of research and development of unconventional energy resources. Unconventional energy resources are defined as those resources other than conventional oil and natural gas that typically occur in sandstone and carbonate rocks. Gas hydrate resources are potentially enormous; however, production technologies are still under development. Gas shale, geothermal, oil sand, and uranium resources are now increasing targets of exploration and development, and are rapidly becoming important energy resources that will continue to be developed in the future.

Natural Resources Research↗
USGS2026

Quantitative mineral resource assessment of lithium pegmatite deposits in the northern Appalachian orogen, USA

Lithium demand is projected to increase more than 48 times by 2040 due to electric vehicle production and other energy storage needs. Most lithium production is outside of the USA, thereby increasing supply chain vulnerability. The combined end use importance and heightened supply risk of lithium make this lightest metallic element a critical commodity to the USA. To mitigate this supply risk, the US Geological Survey is actively assessing lithium deposits in the USA. Herein, we detail an assessment for lithium-mineralized pegmatites in the US northern Appalachian Mountains. Permissive tracts were generated by cross-referencing tectonic and geologic maps and mineral occurrence data with mappable criteria derived from generalized and region-specific lithium pegmatite ore deposit models; tracts were then ranked as having high, medium, or low permissibility. Available geophysical and geochemical data were found to be of minimal utility for this deposit type at the scale of the assessment. The number of undiscovered deposits were estimated and integrated into probabilistic simulations, which included an expanded and updated global grade and tonnage model of pegmatite-hosted lithium ore. The estimated total amount of undiscovered resources for the northern Appalachian Orogen has a median value of 1,410,000 metric tons of Li 2 O when considering moderate correlation across sub-regions. At a confidence level of 90%, a resource of at least 90,000 metric tons of Li 2 O remains undiscovered, and at a 10% confidence level, a resource of as much as 7,380,000 metric tons Li 2 O remains undiscovered. After applying an up-to-date economic filter to convert median contained lithium to recoverable material, a correlated total of 900,000 metric tons of Li 2 O may be economically extractable, equating to enough Li 2 O to provide the current annual US lithium supply deficit (presently obtained through net imports) for 127 years at 2025 rates of apparent consumption. This period of provision will inevitably shorten with projected increasing consumption rates, emphasizing that further research could be completed to better delineate regions of high lithium resource potential and support exploration and domestic production.

Connecticut, Delaware, Maine, Massachusetts, New H↗
USGS2023

The Government eDNA Working Group 6th Annual eDNA Technical Exchange Workshop

The 6th annual Environmental DNA (eDNA) Technical Exchange Workshop was a virtual workshop hosted and coordinated by the Government eDNA Working Group (GEDWG) on January 24–26, 2023. GEDWG is a no-cost consortium that focuses on bringing together stakeholders associated with federal, state, provincial, municipal, and other government and non-government agencies interested in eDNA and related fields, for the purposes of sharing technical expertise and experience during monthly discussion meetings and annual workshops. Over 400 participants registered for the virtual Workshop, which featured four keynote speakers, 23 platform talks, eight short-form poster presentations, and an extended discussion session. Workshop attendees represented a broad cross-section of disciplines and backgrounds, including research scientists, natural resource managers, and conservation policy experts, and many different government agencies, private environmental consulting firms, trade organizations, non-governmental organizations, and others in the environmental management sector. Key takeaways from the workshop included moving the application of eDNA into resource management and discovering ways to improve policy uptake in the development of nationwide biodiversity monitoring, some of which is happening in the development of eDNA networks and national strategies. Future research directions discussed include studies of fate and transport, autonomous sampling/sample processing, and reference library curation. Additionally, co-design of studies and improved engagement and communication among scientists and managers are needed to ensure clear expectations and outcomes.

Environmental DNA↗
USGS2014

Evaluation of development options for Alaska North Slope viscous and heavy oil

Current estimates of discovered viscous and heavy oil in Alaska’s North Slope are 12 billion barrels of oil-in-place and 12–18 billion barrels of oil-in-place, respectively (see Appendix 1 for conversion to SI units). Since the early 1990s to the end of 2010, cumulative viscous oil production has amounted to 150 million barrels, and there has been no commercial production of heavy oil. During the last three decades, the industry has been challenged to develop technologies to commercially produce these untapped oil resources in this Arctic environment. In this paper, the general locations and geologic properties of the viscous oil-bearing West Sak/Schrader Bluff and heavy oil-bearing Ugnu stratigraphic intervals are described first. The geologic variability within these deposits and the evolution of technology have forced an incremental development approach, requiring costly field testing at the pilot scale of innovative extraction techniques. Although viscous oil is currently produced, its development is not mature, and firms appear to be still spending large sums on new approaches to improve recovery. The analysis specifies a representative viscous oil project and then applies a “real options” framework using simulation to determine whether the risked expected project value is sufficient to fund required expenditures on extraction process research and field testing. Computations show available field test funds to be highly sensitive to the operator’s hurdle rate of return as well as the range in magnitude of potential State revenues. The contribution of the paper is solving this problem using an approach where the extreme low return and high scenarios need only be specified, and where the uncertainties are modeled with beta distributions based on historical data or expert opinion.

Alaska↗
USGS2021

National Park Service Vegetation Mapping Inventory Program: Great Smoky Mountains National Park vegetation mapping project

The National Park Service (NPS) Vegetation Mapping Inventory (VMI) Program is an effort to classify, describe, and map existing vegetation communities in national park units throughout the United States. The NPS VMI Program is managed by the NPS Natural Resource Stewardship and Science Inventory and Monitoring Program and provides baseline vegetation information to natural resource managers, researchers, and ecologists. The U.S. Geological Survey Upper Midwest Environmental Sciences Center, NatureServe, and NPS Great Smoky Mountains National Park (GRSM, also referred to as the “Park”) have completed vegetation classification and mapping of GRSM, including the Foothills Parkway, for the NPS VMI Program. Mappers, ecologists, and botanists collaborated to affirm vegetation types of GRSM and to determine how best to map the vegetation types by using aerial imagery. A vegetation classification developed in 2003 by NatureServe and the NPS served as a foundation to further classify and map the vegetation types of the Park. Data from an additional 10 vegetation plots supported vegetation types either rare or not documented in the 2003 classification. Data from 203 verification sites were collected to test the field key to vegetation types and the application of vegetation types to a sample set of map polygons. Furthermore, data from 972 accuracy assessment (AA) sites were collected (of which 966 were used to test accuracy of the vegetation map layer). This GRSM vegetation mapping project identified 112 vegetation types consisting of 105 association types in the U.S. National Vegetation Classification (USNVC), 2 “park-special” types, 1 “map-special” type, and 4 cultural types in the USNVC. To map the vegetation and land cover of GRSM, 52 map classes were developed. Of these 52 map classes, 46 represent natural (including ruderal) vegetation types, most of which types are recognized in the USNVC. For the remaining 6 of the 52 map classes, 4 represent USNVC cultural types for agricultural and developed areas, and 2 represent non-USNVC types for nonvegetated open water and nonvegetated rock. Features were interpreted from viewing four-band digital aerial imagery using digital onscreen three-dimensional stereoscopic workflow systems in geographic information systems; digital aerial imagery was collected during September 23–October 30, 2015. The interpreted data were digitally and spatially referenced, thus making the spatial-database layers usable in a geographic information system. Polygon units were mapped to either a 0.5- or 0.25- hectare (ha) minimum mapping unit, depending on vegetation type. A geodatabase containing several feature-class layers and tables provides the locations and data of USNVC vegetation types (vegetation map layer), vegetation plots, verification sites, AA sites, project boundary extent, and aerial image centers and flight lines. Covering 210,875 ha, the feature-class layer and related tables for the vegetation map layer provide 34,084 polygons of detailed attribute data when special modifiers are not considered (average polygon size of 6.2 ha) and 36,589 polygons of detailed attribute data when special modifiers are considered (average polygon size of 5.8 ha). Each map polygon is assigned a map-class code and name and, when applicable, are linked to USNVC classification tables within the geodatabase. The vegetation map extent includes the administrative boundary for GRSM and the Foothills Parkway. A summary report, generated from the vegetation map layer, concludes that the 46 map classes representing natural (including ruderal) vegetation types apply to 99.2% of polygons (33,797 polygons; average size of 6.2 ha) and cover 98.6% of the Park (207,971.4 ha). Further broken down, map classes representing natural vegetation types indicate that the Park is 97.7% forest and woodland (205,882.5 ha), 0.6% shrubland (1,174.6 ha), and 0.4% herbaceous (914.3 ha). Map classes representing cultural vegetation types apply to 0.8% of polygons (259 polygons; average size of 4.9 ha) and cover 0.6% of the Park (1,277.4 ha). Map classes representing nonvegetation open and flowing water and unvegetated rock apply to 0.08% of polygons (28 polygons; average size of 58.1 ha) and cover 0.8% of the Park (1,625.9 ha). A thematic AA study was completed of map classes representing the natural (including ruderal) vegetation types of the Park. Initial AA results were discussed with NPS staff from the Park. Following input from NPS staff on how to handle map classes that fell below accuracy standards, adjustments were made to the vegetation map layer. Final results indicate an overall accuracy of 80.64% (kappa index of 79.96% for chance agreements) based on data from 966 of the 972 AA sites. Most individual map-class themes exceed the NPS VMI Program standard of 80% with a 90% confidence interval. The GRSM vegetation mapping project delivers many geospatial and vegetation data products, including an in-depth project report discussing methods and results, which includes map classification and map-class descriptions. This suite of products also includes descriptions and a field key to vegetation types; a database of vegetation plots, verification sites, and AA sites; digital images of field sites; field data sheets; digital aerial imagery; hardcopy and digital maps; a geodatabase of vegetation and land cover (map layer), field sites (vegetation plots, verification sites, and AA sites), aerial imagery index, project boundary, and metadata; and a contingency table listing AA results. Geospatial products are projected in the Universal Transverse Mercator, Zone 17 North, by using the North American Datum of 1983. Information on the NPS VMI Program and completed mapping projects are on the internet at https://www.nps.gov/im/vegetation-inventory.htm.

North Carolina, Tennessee↗
USGS2011

Empirical methods for detecting regional trends and other spatial expressions in antrim shale gas productivity, with implications for improving resource projections using local nonparametric estimation techniques

The primary objectives of this research were to (1) investigate empirical methods for establishing regional trends in unconventional gas resources as exhibited by historical production data and (2) determine whether or not incorporating additional knowledge of a regional trend in a suite of previously established local nonparametric resource prediction algorithms influences assessment results. Three different trend detection methods were applied to publicly available production data (well EUR aggregated to 80-acre cells) from the Devonian Antrim Shale gas play in the Michigan Basin. This effort led to the identification of a southeast–northwest trend in cell EUR values across the play that, in a very general sense, conforms to the primary fracture and structural orientations of the province. However, including this trend in the resource prediction algorithms did not lead to improved results. Further analysis indicated the existence of clustering among cell EUR values that likely dampens the contribution of the regional trend. The reason for the clustering, a somewhat unexpected result, is not completely understood, although the geological literature provides some possible explanations. With appropriate data, a better understanding of this clustering phenomenon may lead to important information about the factors and their interactions that control Antrim Shale gas production, which may, in turn, help establish a more general protocol for better estimating resources in this and other shale gas plays.

Michigan↗
USGS2007

Porphyry copper deposit tract definition - A global analysis comparing geologic map scales

Geologic maps are a fundamental data source used to define mineral-resource potential tracts for the first step of a mineral resource assessment. Further, it is generally believed that the scale of the geologic map is a critical consideration. Previously published research has demonstrated that the U.S. Geological Survey porphyry tracts identified for the United States, which are based on 1:500,000-scale geology and larger scale data and published at 1:1,000,000 scale, can be approximated using a more generalized 1:2,500,000-scale geologic map. Comparison of the USGS porphyry tracts for the United States with weights-of-evidence models made using a 1:10,000,000-scale geologic map, which was made for petroleum applications, and a 1:35,000,000-scale geologic map, which was created as context for the distribution of porphyry deposits, demonstrates that, again, the USGS US porphyry tracts identified are similar to tracts defined on features from these small scale maps. In fact, the results using the 1:35,000,000-scale map show a slightly higher correlation with the USGS US tract definition, probably because the conceptual context for this small-scale map is more appropriate for porphyry tract definition than either of the other maps. This finding demonstrates that geologic maps are conceptual maps. The map information shown in each map is selected and generalized for the map to display the concepts deemed important for the map maker's purpose. Some geologic maps of small scale prove to be useful for regional mineral-resource tract definition, despite the decrease in spatial accuracy with decreasing scale. The utility of a particular geologic map for a particular application is critically dependent on the alignment of the intention of the map maker with the application. ?? International Association for Mathematical Geology 2007.

Natural Resources Research↗
USGS2015

Hydrologic record extension of water-level data in the Everglades Depth Estimation Network (EDEN), 1991-99

The real-time Everglades Depth Estimation Network (EDEN) has been established to support a variety of scientific and water management purposes. The expansiveness of the Everglades, limited number of gaging stations, and extreme sensitivity of the ecosystem to small changes in water depth have created a need for accurate water-level and water-depth maps. The EDEN water-surface elevation model uses data from approximately 240 gages in the Everglades to create daily continuous interpolations of the water-surface elevation and water depth for the freshwater portion of the Everglades from 2000 to the present (2014). These maps provide hydrologic data previously unavailable for assessing biological and ecological studies. Ecologists working in the Everglades expressed a need to the EDEN project team for daily EDEN water-level surfaces from 1990 to 1999. The additional 10 years of surfaces will provide ecologists and resource managers with two decades (1991–2011) of surfaces to analyze hydrologic dynamics. Before 2000, many of the EDEN gages used to generate water surfaces were not in operation. These datasets were extended to provide estimations of hydrologic time-series histories. The general approach to the record extension (hindcasts) was to (1) create a database of available data from 1990 to the present; (2) use dynamic cluster analysis to group stations with similar hydrologic behaviors for subareas of the Everglades with a large number of stations; (3) use results from the cluster analysis to select candidate explanatory variables; (4) develop linear regression or artificial neural network models to extend water-level records; and (5) evaluate record extensions by using model performance statistics and comparison of water-surface maps for similar hydrologic conditions for the hindcasted period (1991–99) and measured period (2000–11). To hindcast and fill data records, 214 empirical models were developed—189 are linear regression models and 25 are artificial neural network models. The coefficient of determination (R 2 ) for 163 of the models is greater than 0.80 and the median percent model error (root mean square error divided by the range of the measured data) is 5 percent. To evaluate the performance of the hindcast models as a group, contour maps of modeled water-level surfaces at 2-centimeter (cm) intervals were generated using the hindcasted data. The 2-cm contour maps were examined for selected days to verify that water surfaces from the EDEN model are consistent with the input data. The biweekly 2-cm contour maps did show a higher number of issues during days in 1990 as compared to days after 1990. May 1990 had the lowest water levels in the Everglades of the 21-year dataset used for the hindcasting study. To hindcast these record low conditions in 1990, many of the hindcast models would require large extrapolations beyond the range of the predictive quality of the models. For these reasons, it was decided to limit the hindcasted data to the period January 1, 1991, to December 31, 1999. Overall, the hindcasted and gap-filled data are assumed to provide reasonable estimates of station-specific water-level data for an extended historical period to inform research and natural resource management in the Everglades.

Florida↗
USGS2021

Correspondence analysis for mineral commodity research: An example workflow for mineralized calderas, southwest United States

Historical mine and mineral deposit datasets are routinely used to inform quantitative mineral assessment models, but they also can contain a wealth of supplementary qualitative information that is generally underutilized. We present a workflow that uses correspondence analysis, an exploratory tool commonly applied to multivariate abundance data, to better utilize qualitative data in these historical datasets. The workflow involves extraction of qualitative information on ore mineralogy from a mineral deposit database, attaches those data to a target geological feature, and analyzes the underlying data structure with correspondence analysis and hierarchical clustering. The output of correspondence analysis is inversely weighted to the relative frequency of ore minerals, and therefore rare mineral species (i.e., those with unusually low frequencies) can disproportionately contribute to the total variance of the dataset. We present a novel technique for aggregating frequencies of rare mineral species that minimizes this effect. We apply this workflow to evaluate how ore mineral assemblages in former and active mines vary in spatial relation to silicic calderas in the southwestern United States. The most common ore mineral associations observed spatially and genetically associated to calderas include those related to polymetallic, base metal-rich systems and epithermal Au–Ag systems. Three other groups of mineralized calderas were identified, including: (1) Hg–Sb mineralized calderas in the northern Great Basin and western Nevada volcanic field; (2) calderas associated with elevated abundances of Mn oxides/hydroxides, fluorite, and Be-minerals, mostly in eastern Utah and New Mexico; and (3) calderas with numerous U ± F deposits, which are located in central Colorado, the eastern Great Basin and in northern Nevada. The latter three groups are associated with economically significant critical mineral resources, including the Li resources of the McDermitt complex and Be associated with the Spor Mountain on the margin of the Thomas caldera complex. We conclude that correspondence analysis is a promising technique that can enhance data exploration of the qualitative information held within mineral deposit datasets. Consequently, it could have numerous applications for mineral potential mapping, resource assessment projects, and characterization of mineral systems.

Natural Resources Research↗
USGS2026

Quantitative mineral resource assessment of lithium pegmatite deposits in the southern Appalachian orogen

The first quantitative mineral resource assessment for undiscovered lithium pegmatite deposits in the southern Appalachian region of the United States was conducted. Permissive tracts for lithium pegmatite deposits were delineated by integrating lithological, tectonic, geochemical, geophysical and mineral occurrence data. Lithium pegmatite prospectivity of the tracts was ranked with simplified mappable criteria, including proximity to Paleozoic felsic intrusions and major lithotectonic structures, stream sediment geochemical anomalies, and pegmatite occurrence data. The geospatial data and permissive tracts were used to estimate the number of undiscovered lithium pegmatite deposits. These estimates were integrated into probabilistic simulations along with a new global lithium pegmatite grade and tonnage dataset to quantify potential contained undiscovered lithium resources. An economic filter was applied to convert the probabilistic estimates of contained lithium into recoverable material. The identified lithium pegmatite resources for the Carolina Lithium and Kings Mountain deposits, North Carolina, contain 1589 thousand tons (kt) of Li 2 O. The median contained undiscovered resource for the southern Appalachian orogen was estimated to be 2240 kt Li 2 O. At 90% confidence, the region contains at least 130 kt Li 2 O, and 10,700 kt at 10% confidence. After applying economic filters, the median recoverable contained resource was 1430 kt Li 2 O, corresponding to approximately 201 years of current lithium imports for consumption in the United States. North and South Carolina are likely to contain most of these resources. Coarse data resolution and intra-state variations in the geological data contribute to uncertainty of undiscovered lithium pegmatite resources. Continued efforts to harmonize disparate geospatial datasets with updated or new information can improve the accuracy and precision of estimated undiscovered lithium pegmatite resources in the study area and at broader scales.

Alabama, Georgia, Maryland, North Carolina, South ↗