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At least 847 records · Page 47Linked to original sources

Upper Klamath Basin Landsat Image for July 25, 2006: Path 45 Rows 30 and 31

This image is a mosaic of Landsat-5 images of the upper Klamath Basin. The original images were obtained from the U.S. Geological Survey Earth Resources Observation and Science Center (EROS). EROS is responsible for archive management and distribution of Landsat data products. The Landsat-5 satellite is part of an ongoing mission to provide quality remote sensing data in support of research and applications activities. The launch of Landsat-5 on March 1, 1984 marks the addition of the fifth satellite to the Landsat series. The Landsat-5 satellite carries the Thematic Mapper (TM) sensor. More information on the Landsat program can be found online at http://landsat.usgs.gov/.

Oregon↗

Upper Klamath Basin Landsat Image for September 27, 2006: Path 45 Rows 30 and 31

This image is a mosaic of Landsat-5 images of the upper Klamath Basin. The original images were obtained from the U.S. Geological Survey Earth Resources Observation and Science Center (EROS). EROS is responsible for archive management and distribution of Landsat data products. The Landsat-5 satellite is part of an ongoing mission to provide quality remote sensing data in support of research and applications activities. The launch of Landsat-5 on March 1, 1984 marks the addition of the fifth satellite to the Landsat series. The Landsat-5 satellite carries the Thematic Mapper (TM) sensor. More information on the Landsat program can be found online at http://landsat.usgs.gov/.

Oregon↗

Upper Klamath Basin Landsat Image for October 29, 2006: Path 45 Rows 30 and 31

This image is a mosaic of Landsat-5 images of the upper Klamath Basin. The original images were obtained from the U.S. Geological Survey Earth Resources Observation and Science Center (EROS). EROS is responsible for archive management and distribution of Landsat data products. The Landsat-5 satellite is part of an ongoing mission to provide quality remote sensing data in support of research and applications activities. The launch of Landsat-5 on March 1, 1984 marks the addition of the fifth satellite to the Landsat series. The Landsat-5 satellite carries the Thematic Mapper (TM) sensor. More information on the Landsat program can be found online at http://landsat.usgs.gov/.

Oregon↗

Upper Klamath Basin Landsat Image for April 28, 2006: Path 45 Rows 30 and 31

This image is a mosaic of Landsat-7 images of the upper Klamath Basin. The original images were obtained from the U.S. Geological Survey Earth Resources Observation and Science Center (EROS). EROS is responsible for archive management and distribution of Landsat data products. The Landsat-7 satellite is part of an ongoing mission to provide quality remote sensing data in support of research and applications activities. The launch of Landsat-7 on April 15, 1999 marks the addition of the latest satellite to the Landsat series. The Landsat-7 satellite carries the Enhanced Thematic Mapper Plus (ETM+) sensor. A mechanical failure of the ETM+ Scan Line Corrector (SLC) occurred on May 31, 2003, with the result that all Landsat 7 scenes acquired from July 14, 2003 to present have been collected in 'SLC-off' mode. More information on the Landsat program can be found online at http://landsat.usgs.gov/.

Oregon↗

Upper Klamath Basin Landsat Image for May 30, 2006: Path 45 Rows 30 and 31

This image is a mosaic of Landsat-7 images of the upper Klamath Basin. The original images were obtained from the U.S. Geological Survey Earth Resources Observation and Science Center (EROS). EROS is responsible for archive management and distribution of Landsat data products. The Landsat-7 satellite is part of an ongoing mission to provide quality remote sensing data in support of research and applications activities. The launch of Landsat-7 on April 15, 1999 marks the addition of the latest satellite to the Landsat series. The Landsat-7 satellite carries the Enhanced Thematic Mapper Plus (ETM+) sensor. A mechanical failure of the ETM+ Scan Line Corrector (SLC) occurred on May 31, 2003, with the result that all Landsat 7 scenes acquired from July 14, 2003 to present have been collected in 'SLC-off' mode. More information on the Landsat program can be found online at http://landsat.usgs.gov/.

Oregon↗

Floods of May 2006 and April 2007 in Southern Maine

The U.S. Geological Survey Maine Water Science Center has worked with the Federal Emergency Management Agency for decades to document the magnitude and extent of major floods in Maine. Reports describing the May 2006 and April 2007 floods in southern Maine are examples of this cooperative relationship. The documentation of peak stream elevations and peak streamflow magnitudes and recurrence intervals provides essential information for the delineation of flood plains and for flood-mitigation decisions by local, State, and Federal emergency management officials.

Fact Sheet↗

Simulation of water availability in the Southeastern United States for historical and potential future climate and land-cover conditions

A study was conducted by the U.S. Geological Survey (USGS), in cooperation with the Gulf Coastal Plains and Ozarks Landscape Conservation Cooperative (GCPO LCC) and the Department of the Interior Southeast Climate Adaptation Science Center, to evaluate the hydrologic response of a daily time step hydrologic model to historical observations and projections of potential climate and land-cover change for the period 1952–2099. The model simulations were used to compute the potential changes in hydrologic response and streamflow statistics across the Southeastern United States, using historical observations of climate and streamflow. Thirteen downscaled general circulation models with four representative concentration pathways were used to represent a range of potential future changes in climate (a total of 45 future simulations) from the Coupled Model Intercomparison Project Phase 5. The streamflow statistics were selected to describe streamflow conditions that may be most useful in defining the suitability for each river or stream to support sustaining populations of priority aquatic species across the GCPO LCC. An application of the Precipitation-Runoff Modeling System (included as part of the USGS National Hydrologic Model) was used to develop the hydrologic simulations. The results showed increases in air temperature across the study area, with the highest increases occurring in the northern part of the study area during July to September. The results showed a mix of increases and decreases in precipitation accumulation across the study area and across seasons, with decreases in precipitation accumulation across all seasons for the southwestern part of the study area. Actual evapotranspiration decreased for the southeastern part of the study area and increased for the northwestern part of the study area. The results showed general decreases in runoff across the study area, with increases in runoff in areas surrounding large metropolitan regions where potential future increases in impervious area occur. Results from a statistical analysis (Kolmogorov-Smirnov test) showed that the downscaled general circulation models generally have more skill in producing historical streamflow statistics in the duration and magnitude categories and less skill in producing historical streamflow statistics in the frequency, rate of change, and timing categories for this study area. The potential changes in the streamflow statistics and the results of the Kolmogorov-Smirnov test are available through the GCPO LCC Conservation Planning Atlas, an online science-based mapping platform built specifically for land managers and planners.

Alabama, Arkansas, Florida, Georgia, Illinois, Kan↗

Long Term Resource Monitoring procedures—Aquatic vegetation monitoring

This standard operating procedure (SOP) manual describes the collection of standardized, long-term data for aquatic vegetation communities in selected study pools of the Upper Mississippi River System in the United States. The primary intent of the data collection is to assess the status and trends that aid in understanding the unique river ecosystem and to guide large-scale ecological restoration of the river and its biological communities, like aquatic plants and their dependent wildlife. This SOP is an update to the version published in 2000 and reflects modifications to sample sizes and additions of new data collection procedures. All long-term monitoring programs and their SOPs must be adapted to changing conditions and be improved through learning, and this SOP clarifies procedures and adds new elements since the initial SOP was written more than 25 years ago. The SOP is intended for multiple audiences, including vegetation specialists through the Upper Mississippi River Restoration Program, data analysts using the publicly available data generated through this SOP, and natural resource managers and restoration practitioners who need data and science to guide some decisions. This SOP may be transferable and adaptable to other ecosystems when the aquatic plant community is the focus.

Illinois, Iowa, Minnesota, Missouri, Wisconsin↗

Seven recommendations to make your invasive alien species data more useful

Science-based strategies to tackle biological invasions depend on recent, accurate, well-documented, standardized and openly accessible information on alien species. Currently and historically, biodiversity data are scattered in numerous disconnected data silos that lack interoperability. The situation is no different for alien species data, and this obstructs efficient retrieval, combination, and use of these kinds of information for research and policy-making. Standardization and interoperability are particularly important as many alien species related research and policy activities require pooling data. We describe seven ways that data on alien species can be made more accessible and useful, based on the results of a European Cooperation in Science and Technology (COST) workshop: (1) Create data management plans; (2) Increase interoperability of information sources; (3) Document data through metadata; (4) Format data using existing standards; (5) Adopt controlled vocabularies; (6) Increase data availability; and (7) Ensure long-term data preservation. We identify four properties specific and integral to alien species data (species status, introduction pathway, degree of establishment, and impact mechanism) that are either missing from existing data standards or lack a recommended controlled vocabulary. Improved access to accurate, real-time and historical data will repay the long-term investment in data management infrastructure, by providing more accurate, timely and realistic assessments and analyses. If we improve core biodiversity data standards by developing their relevance to alien species, it will allow the automation of common activities regarding data processing in support of environmental policy. Furthermore, we call for considerable effort to maintain, update, standardize, archive, and aggregate datasets, to ensure proper valorization of alien species data and information before they become obsolete or lost.

Frontiers in Applied Mathematics and Statistics↗

Quantifying uncertainty and tradeoffs in resilience assessments

Several frameworks have been developed to assess the resilience of social-ecological systems, but most require substantial data inputs, time, and technical expertise. Stakeholders and practitioners often lack the resources for such intensive efforts. Furthermore, most end with problem framing and fail to explicitly address trade-offs and uncertainty. To remedy this gap, we developed a rapid survey assessment that compares the relative resilience of social-ecological systems with respect to a number of resilience properties. This approach generates large amounts of information relative to stakeholder inputs. We targeted four stakeholder categories: government (policy, regulation, management), end users (farmers, ranchers, landowners, industry), agency/public science (research, university, extension), and NGOs (environmental, citizen, social justice) in four North American watersheds, to assess social-ecological resilience through surveys. Conceptually, social-ecological systems are comprised of components ranging from strictly human to strictly ecological, but that relate directly or indirectly to one another. They have soft boundaries and several important dimensions or axes that together describe the nature of social-ecological interactions, e.g., variability, diversity, modularity, slow variables, feedbacks, capital, innovation, redundancy, and ecosystem services. There is no absolute measure of resilience, so our design takes advantage of cross-watershed comparisons and therefore focuses on relative resilience. Our approach quantifies and compares the relative resilience across watershed systems and potential trade-offs among different aspects of the social-ecological system, e.g., between social, economic, and ecological contributions. This approach permits explicit assessment of several types of uncertainty (e.g., self-assigned uncertainty for stakeholders; uncertainty across respondents, watersheds, and subsystems), and subjectivity in perceptions of resilience among key actors and decision makers and provides an efficient way to develop the mental models that inform our stakeholders and stakeholder categories.

Ecology and Society↗

U.S. Geological Survey ecosystems science strategy—Advancing discovery and application through collaboration

Executive Summary Ecosystem science is critical to making informed decisions about natural resources that can sustain our Nation’s economic and environmental well-being. Resource managers and policymakers are faced with countless decisions each year at local, regional, and national levels on issues as diverse as renewable and nonrenewable energy development, agriculture, forestry, water supply, and resource allocations at the urban-rural interface. The urgency for sound decisionmaking is increasing dramatically as the world is being transformed at an unprecedented pace and in uncertain directions. Environmental changes are associated with natural hazards, greenhouse gas emissions, and increasing demands for water, land, food, energy, mineral, and living resources. At risk is the Nation’s environmental capital, the goods and services provided by resilient ecosystems that are vital to the health and wellbeing of human societies. Ecosystem science—the study of systems of organisms interacting with their environment and the consequences of natural and human-induced change on these systems—is necessary to inform decisionmakers as they develop policies to adapt to these changes. This Ecosystems Science Strategy is built on a framework that includes basic and applied science. It highlights the critical roles that U.S. Geological Survey (USGS) scientists and partners can play in building scientific understanding and providing timely information to decisionmakers. The strategy underscores the connection between scientific discoveries and the application of new knowledge, and it integrates ecosystem science and decisionmaking, producing new scientific outcomes to assist resource managers and providing public benefits. We envision the USGS as a leader in integrating scientific information into decisionmaking processes that affect the Nation’s natural resources and human well-being. The USGS is uniquely positioned to play a pivotal role in ecosystem science. With its wide range of expertise, the Bureau can bring holistic, cross-scale, interdisciplinary capabilities to the design and conduct of monitoring, research, and modeling and to new technologies for data collection, management, and visualization. Collectively, these capabilities can be used to reveal ecological patterns and processes, explain how and why ecosystems change, and forecast change over different spatial and temporal scales. USGS science can provide managers with options and decision-support tools to use resources sustainably. The USGS has long-standing, collaborative relationships with the Department of the Interior (DOI) and other partners in the natural sciences, in both conducting science and applying the results. The USGS engages these partners in cooperative investigations that otherwise would lack the necessary support or be too expensive for a single bureau to conduct. The heart of this strategy is a framework for USGS ecosystems science that focuses on five long-term goals, which are seen as interconnected components that reinforce our vision of the USGS providing science that is at the forefront of decisionmaking: Improve understanding of ecosystem structure, function, and processes. The focus for this goal is an understanding of how ecosystems work, including the dynamics of species, their populations, interactions, and genetics, and how they change across spatial and temporal scales. Advance understanding of how drivers influence ecosystem change. The challenges here are explaining the drivers of ecosystem change, their spatio-temporal patterns, their uncertainties and interactions, and their influence on ecosystem processes and dynamics. Improve understanding of the services that ecosystems provide to society. Here the emphasis is on the measurement of environmental capital and ecosystem services, and the identification of sources and patterns of change in space and time. Develop tools, technologies, and capacities to inform decisionmaking about ecosystems. This includes developing new technologies and approaches for conducting applications-oriented ecosystem science. A principal challenge will be how to quantify uncertainty and incorporate it in decision analysis. Apply science to enhance strategies for management, conservation, and restoration of ecosystems. These challenges include development of novel approaches to monitoring, assessment, and restoration of ecosystems; new methods to address species of concern and communities at risk; and innovations in decision analysis and support to address imminent ecosystem changes or those that are underway. Closely integrated with the five goals are four strategic approaches that provide the path forward for the USGS Ecosystems Mission Area. These approaches cross-cut all of the goals and are seen as essential to the implementation of this strategy: Assess information needs for ecosystem science through enhanced partnerships. Work with the DOI and other agencies and institutions to identify, design, and implement priority decision-driven ecological research. Promote the use of interdisciplinary ecosystem science. Design and conduct interdisciplinary process-oriented research in ecosystem science. Enhance modeling and forecasting. Build models to forecast ecosystem change, assess future management scenarios, and reduce uncertainties through an adaptive learning process. Support decisionmaking. Use quantitative approaches to assess the vulnerabilities of ecosystems, habitats, and species, and evaluate strategies for adaptation, restoration, and sustainable management. Following the four strategic approaches are a set of proposed actions that represent a sampling of specific USGS activities that align with this strategy and that address the Nation’s most pressing environmental needs. The strategy emphasizes coordination of activities across the USGS mission areas pursuant to these goals. Ecosystem science is inherently interdisciplinary and requires a broad perspective that incorporates the biological and physical sciences, climate science, information technology, and scientific capacity in mission areas across the Bureau. With its emphasis on coordination, this strategy can provide a critical underpinning for integrated science efforts with scientists from multiple mission areas of the USGS working together. Of course, the USGS will continue to conduct discipline-specific and interdisciplinary investigations, and both will continue to be vital parts of the ecosystem science portfolio. Finally, the strategy stresses the importance of coordination with other Federal agencies and organizations in the natural resources community. The USGS collaborates with resource agencies in the DOI and other organizations throughout the world to meet societal needs for species and ecosystem management. Working with these agencies and organizations, the USGS will play a key role in guiding sound decisionmaking during the next decade by advancing the scientific foundation for sustaining the natural resources that diverse, productive, resilient ecosystems provide.

Circular↗

Surface-Water Quality-Assurance Plan for the USGS Wisconsin Water Science Center

This surface-water quality-assurance plan documents the standards, policies, and procedures used by the Wisconsin Water Science Center of the U.S. Geological Survey, Water Resources Discipline, for activities related to the collection, processing, storage, analysis, management, and publication of surface-water data. The roles and responsibilities of Water Science Center personnel in following these policies and procedures including those related to safety and training are presented.

Open-File Report↗

U.S. Geological Survey Cooperative Research Units Program—A hawk’s view of 2024

Introduction The U.S. Geological Survey Cooperative Fish and Wildlife Research Units (USGS CRU) program was established in 1935 and codified by Congress in 1960 to enhance graduate education in wildlife and fisheries sciences and to facilitate research and technical assistance among natural resource agencies and universities on fisheries and wildlife management topics of mutual concern. The success of the CRU program lies in its cooperative approach. State and Federal fish and wildlife agencies determine where focused, science-based studies for wildlife and natural resource management for societal benefit are needed. The CRU scientists conduct applied research to contribute results to inform and aid partners in determining best practices for managing resources. Each Unit is a unique partnership among the U.S. Geological Survey, a host university, one or more State agencies, the Wildlife Management Institute, and the U.S. Fish and Wildlife Service.

Fact Sheet↗

U.S. Geological Survey wildland fire science strategic plan, 2021–26

The U.S. Geological Survey (USGS) Wildland Fire Science Strategic Plan defines critical, core fire science capabilities for understanding fire-related and fire-responsive earth system processes and patterns, and informing management decision making. Developed by USGS fire scientists and executive leadership, and informed by conversations with external stakeholders, the Strategic Plan is aligned with the needs of the fire science stakeholder community–fire, land, natural resource, and emergency managers from Federal, State, Tribal, and community organizations, as well as members of the scientific community. The Strategic Plan is composed of four integrated priorities, each with associated goals and specific strategies for accomplishing the goals: Priority 1: Produce state-of-the-art, actionable fire science; Priority 2: Engage stakeholders in science production and science delivery; Priority 3: Effectively communicate USGS fire science capacity, products, and information to a broad audience; and Priority 4: Enhance USGS organizational structure and advance support for fire science. The priorities of this Strategic Plan define the USGS’s commitment to producing and delivering cutting edge fire science, information, and decision-support tools in support of national, regional, and local priorities and stakeholder needs.

Circular↗

U.S. Geological Survey Mississippi River Science Forum—Summary of data and science needs and next steps

The U.S. Geological Survey hosted a Mississippi River Science Forum with Federal agencies; Tribal, State, and local governments located in States that border the Mississippi River; academia; and other interested stakeholders. The purpose of the forum was to share current (2023) science; identify data gaps and areas of concern; and to prioritize next steps needed to advance the goals of improving water quality, restoring habitat and natural systems, improving navigation, eliminating aquatic invasive species, and building local resilience to natural disasters along the Mississippi River. The forum was a directive for the U.S. Geological Survey in the Consolidated Appropriations Act of 2022 (Public Law 117—103, 136 Stat. 49). Participants and stakeholders that attended the Mississippi River Science Forum indicated the following. A Mississippi River Science Committee could bring together the voices of all stakeholders, including Federal agencies; State, local, and Tribal governments; academia; nongovernmental organizations; business and industry; and other interested parties. This committee would also work with (but not replace) Mississippi River Basin entities already in place and establish effective communication to identify and address Basin-wide management needs and to develop holistic solutions for those needs. A Mississippi River science plan could expand on the science and data gaps identified by the Forum. This plan could guide data collection and help resource managers develop and implement restoration initiatives within the Basin, recognizing that addressing these needs will require substantial resources. The science committee, working with other entities in the basin, should develop data standards for the Mississippi River Basin that allow stakeholders to utilize comparable data to address their needs. These standards would include data findability, accessibility, interoperability, and reusability. This report highlights data gaps and areas of concern discussed during the forum, and it identifies needs to advance the goals of improving water quality, restoring habitat and natural systems, improving navigation, eliminating aquatic invasive species, and building local resilience to natural disasters with specific emphasis on data collection and measurement, and scientific investigation. The report also summarizes stakeholder input and feedback and outlines next steps identified by forum participants.

Open-File Report↗

Fort Collins Science Center- Policy Analysis and Science Assistance Branch : Integrating social, behavioral, economic and biological sciences

The Fort Collins Science Center's Policy Analysis and Science Assistance (PASA) Branch is a team of approximately 22 scientists, technicians, and graduate student researchers. PASA provides unique capabilities in the U.S. Geological Survey by leading projects that integrate social, behavioral, economic, and biological analyses in the context of human-natural resource interactions. Resource planners, managers, and policymakers in the U.S. Departments of the Interior (DOI) and Agriculture (USDA), State and local agencies, as well as international agencies use information from PASA studies to make informed natural resource management and policy decisions. PASA scientists' primary functions are to conduct both theoretical and applied social science research, provide technical assistance, and offer training to advance performance in policy relevant research areas. Management and research issues associated with human-resource interactions typically occur in a unique context, involve difficult to access populations, require knowledge of both natural/biological science in addition to social science, and require the skill to integrate multiple science disciplines. In response to these difficult contexts, PASA researchers apply traditional and state-of-the-art social science methods drawing from the fields of sociology, demography, economics, political science, communications, social-psychology, and applied industrial organization psychology. Social science methods work in concert with our rangeland/agricultural management, wildlife, ecology, and biology capabilities. The goal of PASA's research is to enhance natural resource management, agency functions, policies, and decision-making. Our research is organized into four broad areas of study.

Fact Sheet↗

Leveraging the strengths of citizen science and structured surveys to achieve scalable inference on population size

Population size is a key metric for management and policy decisions, yet wildlife monitoring programmes are often limited by the spatial and temporal scope of surveys. In these cases, citizen science data may provide complementary information at higher resolution and greater extent. We present a case study demonstrating how data from the eBird citizen science programme can be combined with regional monitoring efforts by the US Fish and Wildlife Service to produce high-resolution estimates of golden eagle abundance. We developed a model that uses aerial survey data from the western United States to calibrate high-resolution annual estimates of relative abundance from eBird. Using this model, we compared regional population size estimates based on the calibrated eBird information with those based on aerial survey data alone. Population size estimates based on the calibrated eBird information had strong correspondence to estimates from aerial survey data in two out of four regions, and population trajectories based on the two approaches showed high correlations. We demonstrate how the combination of citizen science data and targeted surveys can be used to (a) increase the spatial resolution of population size estimates, (b) extend the spatial extent of inference and (c) predict population size beyond the temporal period of surveys. Findings based on this case study can be used to refine policy metrics used by the US Fish and Wildlife Service and inform permitting regulations (e.g. mortality/harm associated with wind energy development). Policy implications : Our results demonstrate the ability of citizen science data to complement targeted monitoring programmes and improve the efficacy of decision frameworks that require information on population size or trajectory. After validating citizen science data against survey-based benchmarks, agencies can harness strengths of citizen science data to supplement information needs and increase the resolution and extent of population size predictions.

Journal of Applied Ecology↗

Identifying policy-relevant indicators for assessing landscape vegetation patterns to inform planning and management on multiple use public lands

Understanding the structure and composition of landscapes can empower agencies to effectively manage public lands for multiple uses while sustaining land health. Many landscape metrics exist, but they are not often used in public land decision-making. Our objectives were to (1) develop and (2) apply a process for identifying a core set of indicators that public land managers can use to understand landscape-level resource patterns on and around public lands. We first developed a process for identifying indicators that are grounded in policy, feasible to quantify using existing data and resources, and useful for managers. We surveyed landscape monitoring efforts by other agencies, gathered science and agency input on monitoring goals, and quantified the prevalence of potential indicators in agency land health standards to identify five landscape indicators: amount, distribution, patch size, structural connectivity, and diversity of vegetation types. We then conducted pilot applications in four bureau of land management (BLM) field offices in Arizona, California, and Colorado to refine procedures for quantifying the indicators and assess the utility of the indicators for managers. Results highlighted the dominance of upland and the limited extent of riparian/wetland vegetation communities, moderate connectivity of priority vegetation patches, and lower diversity of native vegetation types on BLM compared to non-BLM lands. Agency staff can use the indicators to inform the development of quantitative resource management objectives in land use plans, evaluate progress in meeting those objectives, quantify potential impacts of proposed actions, and as a foundation for an all-lands approach to landscape-level management across public lands.

Environmental Management↗