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At least 757 records · Page 42Linked to original sources
USGS2006

2005 annual progress report: Elk and bison grazing ecology in the Great Sand Dunes complex of lands

In 2000 the U.S. Congress authorized the expansion of the former Great Sand Dunes National Monument by establishing a new Great Sand Dunes National Park and Preserve in its place, and establishing the Baca National Wildlife Refuge. The establishment of Great Sand Dunes National Park and Preserve and the new Baca National Wildlife Refuge in the San Luis Valley (SLV), Colorado was one of the most significant land conservation actions in the western U.S. in recent years. The action was a result of cooperation between the National Park Service (NPS), U.S. Fish and Wildlife Service (USFWS), Bureau of Land Management (BLM), U.S. Forest Service (USDA-FS), and The Nature Conservancy (TNC). The new national park, when fully implemented, will consist of 107,265 acres, the new national preserve 41,872 acres, and the new national wildlife refuge (USFWS lands) 92,180 acres (fig. 1). The area encompassed by this designation protects a number of natural wonders and features including a unique ecosystem of natural sand dunes, the entire watershed of surface and groundwaters that are necessary to preserve and recharge the dunes and adjacent wetlands, a unique stunted forest, and other valuable riparian vegetation communities that support a host of associated wildlife and bird species. When the National Park was initially established, there were concerns about overconcentrations and impacts on native plant communities of the unhunted segments of a large and possibly growing elk (Cervus elaphus) population. This led to the designation of the Preserve as a compromise solution, where the elk could be harvested. The Preserve Unit, however, will not address all the ungulate management challenges. In order to reduce the current elk population, harvests of elk may need to be aggressive. But aggressive special hunts of elk to achieve population reductions can result in elk avoidance of certain areas or elk seeking refuge in areas where they cannot be hunted, while removals of whole herd segments and abandonment or alterations of migration routes can occur (Smith and Robbins, 1994; Boyce and others, 1991). Elk may seek refuge from hunting in the newly expanded Park Unit and TNC lands where they might overconcentrate and impact unique vegetation communities. In these sites of refugia, or preferred loafing sites, elk and bison could accelerate a decline in woody riparian shrubs and trees. This decline may also be due to changes in hydrology, climatic, or dunal processes, but ungulate herbivory might exacerbate the effects of those processes. To address the questions and needs of local resource managers, a multi-agency research project was initiated in 2005 to study the ecology, forage relations, and habitat relations of elk and bison in the Great Sand Dunes–Sangre de Cristo–Baca complex of lands. Meetings and discussions of what this research should include were started in 2001 with representatives from NPS, USFWS, TNC, the Colorado Division of Wildlife (CDOW), and USDA-FS/BLM. The final study plan was successfully funded in 2004 with research scheduled to start in 2005. The research was designed to encompass three major study elements: (1) animal movements and population dynamics, (2) vegetation and nutrient effects from ungulate herbivory, and (3) development of ecological models, using empirical data collected from the first two components, that will include estimates of elk carrying capacity and management scenarios for resource managers.

Colorado↗
USGS2002

Evaluation of factors affecting ice forces at selected bridges in South Dakota

During 1998-2002, the U.S. Geological Survey, in cooperation with the South Dakota Department of Transportation (SDDOT), conducted a study to evaluate factors affecting ice forces at selected bridges in South Dakota. The focus of this ice-force evaluation was on maximum ice thickness and ice-crushing strength, which are the most important variables in the SDDOT bridge-design equations for ice forces in South Dakota. Six sites, the James River at Huron, the James River near Scotland, the White River near Oacoma/Presho, the Grand River at Little Eagle, the Oahe Reservoir near Mobridge, and the Lake Francis Case at the Platte-Winner Bridge, were selected for collection of ice-thickness and ice-crushing-strength data. Ice thickness was measured at the six sites from February 1999 until April 2001. This period is representative of the climate extremes of record in South Dakota because it included both one of the warmest and one of the coldest winters on record. The 2000 and 2001 winters were the 8th warmest and 11th coldest winters, respectively, on record at Sioux Falls, South Dakota, which was used to represent the climate at all bridges in South Dakota. Ice thickness measured at the James River sites at Huron and Scotland during 1999-2001 ranged from 0.7 to 2.3 feet and 0 to 1.7 feet, respectively, and ice thickness measured at the White River near Oacoma/Presho site during 2000-01 ranged from 0.1 to 1.5 feet. At the Grand River at Little Eagle site, ice thickness was measured at 1.2 feet in 1999, ranged from 0.5 to 1.2 feet in 2000, and ranged from 0.2 to 1.4 feet in 2001. Ice thickness measured at the Oahe Reservoir near Mobridge site ranged from 1.7 to 1.8 feet in 1999, 0.9 to 1.2 feet in 2000, and 0 to 2.2 feet in 2001. At the Lake Francis Case at the Platte-Winner Bridge site, ice thickness ranged from 1.2 to 1.8 feet in 2001. Historical ice-thickness data measured by the U.S. Geological Survey (USGS) at eight selected streamflow-gaging stations in South Dakota were compiled for 1970-97. The gaging stations included the Grand River at Little Eagle, the White River near Oacoma, the James River near Scotland, the James River near Yankton, the Vermillion River near Wakonda, the Vermillion River near Vermillion, the Big Sioux River near Brookings, and the Big Sioux River near Dell Rapids. Three ice-thickness-estimation equations that potentially could be used for bridge design in South Dakota were selected and included the Accumulative Freezing Degree Day (AFDD), Incremental Accumulative Freezing Degree Day (IAFDD), and Simplified Energy Budget (SEB) equations. These three equations were evaluated by comparing study-collected and historical ice-thickness measurements to equation-estimated ice thicknesses. Input data required by the equations either were collected or compiled for the study or were obtained from the National Weather Service (NWS). An analysis of the data indicated that the AFDD equation best estimated ice thickness in South Dakota using available data sources with an average variation about the measured value of about 0.4 foot. Maximum potential ice thickness was estimated using the AFDD equation at 19 NWS stations located throughout South Dakota. The 1979 winter (the coldest winter on record at Sioux Falls) was the winter used to estimate the maximum potential ice thickness. The estimated maximum potential ice thicknesses generally are largest in northeastern South Dakota at about 3 feet and are smallest in southwestern and south-central South Dakota at about 2 feet. From 1999 to 2001, ice-crushing strength was measured at the same six sites where ice thickness was measured. Ice-crushing-strength measurements were done both in the middle of the winter and near spring breakup. The maximum ice-crushing strengths were measured in the mid- to late winter before the spring thaw. Measured ice-crushing strengths were much smaller near spring breakup. Ice-crushing strength measured at the six sites

Water-Resources Investigations Report↗
USGS2024

Characterization of change in tree cover state and condition over the conterminous United States

Variability in the effects of disturbances and extreme climate events can lead to changes in tree cover over time, including partial or complete loss, with diverse ecological consequences. It is therefore critical to identify in space and time the change processes that lead to tree cover change. Studies of change are often hampered by the lack of data capable of consistently detecting different types of change. Using the Landsat satellite record to create a long time-series of land cover and land cover change, the U.S. Geological Survey Land Change Monitoring Assessment and Projection (LCMAP) project has made an annual time series of land cover across the conterminous United States for the period 1985 to 2018. Multiple LCMAP products analyzed together with map validation reference plots provide a robust basis for understanding tree cover change. In LCMAP (Collection 1.2), annual change detection is based on harmonic model breaks calculated at each Landsat pixel from the Continuous Change Detection and Classification (CCDC) algorithm. The results showed that the majority of CCDC harmonic model breaks (signifying change) indicated partial tree cover loss (associated with management practices such as tree cover thinning) as compared to complete tree cover loss (associated with practices like clearcut harvest or fire disturbance). Substantially fewer occurrences of complete tree cover loss were associated with change in land cover state. The area of annual tree cover change increased after the late 1990s and stayed high for the rest of the study period. The reference data showed that tree harvest dominated across the conterminous United States. The majority of tree cover change occurred in evergreen forests. Large estimates of disturbance-related tree cover change indicated that tree cover loss may have previously been underreported due to omission of partial tree cover loss in prior studies. This has considerable implications for forest carbon accounting along with tracking ecosystem goods and services.

Forests↗
USGS2022

Contaminants of emerging concern in the Great Lakes: Science to inform management practices for protecting the health and integrity of wildlife populations from adverse effects: GLRI action plan I, focus area 1, goal 5

Executive Summary: Under Action Plan I (2010-2014) of the Great Lakes Restoration Initiative (GLRI), Federal and Academic partners began an investigation of the presence and distribution of contaminants of emerging concern (CECs) in the Great Lakes and potential impacts on fish and wildlife. The term CECs is applied to a broad range of chemicals that are currently in use but for which we currently lack good understanding of whether fish, wildlife, or humans are being exposed and/or whether negative health or environmental effects are expected if exposure occurs. Pharmaceuticals, personal care products, flame retardants, many current use pesticides, and poly- and perfluorinated chemicals are some well-known groups of CECs, but there is no definitive or comprehensive list that can be used to support the management of CECs to reduce impacts on the Great Lakes ecosystem. Four overarching goals were identified for this collaborative investigation: 1. Evaluate the sources, occurrence, and distribution of CECs across the Great Lakes Basin. 2. Examine associations between the distribution of CECs and land-use patterns. 3. Review both scientific literature and field-generated data to determine the potential for CECs to cause adverse effects on Great Lakes fish and wildlife populations. 4. Develop efficient strategies to survey and/or monitor for threats that CECs may pose in order to take effective management actions before those threats evolve into large scale impacts on Great Lakes ecosystems or the services they provide. Achievement of these goals ensures progress towards Focus Area 1: Toxic Substances and Areas of Concern from GLRI Action Plan I, Goal 5: “ The health and integrity of wildlife populations and habitat are protected from adverse chemical and biological effects associated with the presence of toxic substances in the Great Lakes Basin ”. This large-scale research effort was comprised of individual and collaborative projects from multiple federal agencies and academic institutions, involving over 85 investigators, and overseen by the U.S. Environmental Protection Agency (EPA) Region 5, Great Lakes National Program Office. Partners include the United States Geological Survey, the National Oceanic and Atmospheric Administration, U.S. Fish and Wildlife Service, Saint Cloud State University, the U.S. EPA Office of Research and Development, and the U.S. Army Corps of Engineers. Key findings: 1. Contaminants of emerging concern were found throughout the monitored Great Lakes tributaries, but types and concentrations vary in association with regional land use. CECs were detected in nearly all samples collected. The type and concentration of the specific contaminants detected varied considerably among field sites and in association with land use type, such as urban, agricultural, wetland, 2 or forest. Contaminants were detected in the water column, sediment, and tissues of all species surveyed in the current work (mussels, aquatic insects, fish, and insect-eating birds). 2. There were over 20 contaminants for which CEC concentrations approached or exceeded those reported to cause toxicity in laboratory experiments. This was based on detection in water, sediments and or biota at one or more field sites. These contaminants represent compounds that warrant further investigation and monitoring with respect to potential impacts in certain areas of the Great Lakes basin. Based on the present investigation, compounds of greatest concern include: polycyclic aromatic hydrocarbons, associated with oil-based products and combustion of organic matter; atrazine, an herbicide; dichlorvos, an insecticide; and ibuprofen and venlafaxine, both pharmaceuticals. 3. Results suggest that mixtures of CECs presently found in most Great Lakes tributary locations surveyed may elicit subtle biological effects, but likely are not, alone, causing obvious detriment to current communities of fish and wildlife. CECs detected in the Great Lakes were associated with subtle biological effects like changes in gene expression, altered circulating glucose, etc. in both wild-caught and laboratory-reared organisms. These effects were generally not indicative of reproductive failure or mortality. However, the effects may have more serious implications when combined with other sources of stress like habitat degradation, changing climate conditions, and competition with invasive species. Due to limited historical data, it is unknown whether severe CEC-related impacts have already affected aquatic communities in waterbodies that have received long-term inputs of these contaminants. Likewise, under Action Plan I, biological effects were not necessarily evaluated at the sites where CEC concentrations exceeding laboratory toxicity thresholds were detected. As a result, strategic, ongoing surveillance and monitoring of CECs is warranted. This collaborative investigation resulted in new tools, approaches, and data that can be used to inform and support the management of CECs to reduce their impacts on Great Lakes natural resources. The following products of this research effort are available through https://communities.geoplatform.gov/glri/ or by contacting the investigators (see technical chapters found in Appendices A-F): 1. Database of CEC occurrence and concentrations in US tributary streams. The database includes CEC detections in water, sediment, and fish and wildlife tissues, and represents the most comprehensive survey of CECs in the Great Lakes Region. 2. Synopses of results and key findings. Integrated summaries of results, conclusions, and management implications of the CEC research are available through reports, topical fact sheets, and presentations. 3. Technical publications: This collaborative research effort has resulted in over 50 peer-reviewed publications, agency reports, and data releases that can be of use to resource managers, the scientific community, and members of the public. 4. Innovative tools. Innovative monitoring devices, sampling equipment, conceptual frameworks, and software applications were developed over the course of this 3 research. These tools are transferable to stakeholders via internet accessibility or via specifications, instructions, and demonstration detailed in technical publications. Hypotheses to guide CECs research under Action Plan II. Findings from 2010-2014 were used to guide further research in 2015-2018 for basin-wide surveillance of CECs and for sites warranting further study of potential biological impacts of CECs. Additional surveillance included both evaluation of additional classes of contaminants and expanded lists for chemical classes shown to be of greatest concern. Mixtures of some of the most frequently detected contaminants were also tested in laboratory studies to understand whether long term exposures to multiple contaminants may result in effects not evident from uncontrolled, short-term field experiments.

Great Lakes↗
USGS2015

Global trends in emerging viral diseases of wildlife origin

Fifty years ago, infectious diseases were rarely considered threats to wildlife populations, and the study of wildlife diseases was largely a neglected endeavor. Furthermore, public health leaders at that time had declared that “it is time to close the book on infectious diseases and the war against pestilence won,” a quote attributed to Dr. William H. Stewart in 1967. There is some debate whether he actually said these words; however, they reflect the widespread belief at that time (Spellberg, 2008). Leap forward to today, and the book on infectious diseases has been dusted off. There is general consensus that the global environment favors the emergence of infectious diseases, and in particular, diseases of wildlife origin (Taylor et al., 2001). Examples of drivers of these infectious diseases include climate and landscape changes, human demographic and behavior changes, global travel and trade, microbial adaptation, and lack of appropriate infrastructure for wildlife disease control and prevention (Daszak et al., 2001). The consequences of these emerging diseases are global and profound with increased burden on the public health system, negative impacts on the global economy and food security, declines and extinctions of wildlife species, and subsequent loss of ecosystem integrity. For example, 35 million people are currently living with HIV infection globally (http://www.who.int/gho/hiv/en); 400 million poultry have been culled since 2003 as a result of efforts to control highly pathogenic H5N1 avian influenza (http://www.fao.org/avianflu/en/index.html), and there are increasing biological and ecological consequences. Examples of health threats to biodiversity include the “spillover” of human diseases to great ape populations (Köndgen et al., 2008), the near-extirpation of the black-footed ferret from canine distemper and sylvatic plague (for a review see Abbott et al., 2012), and threats to Hawaiian forest birds from introduced pathogens such as avian malaria and avian pox (van Riper et al., 1986, 2002). There are also newly discovered pathogens or diseases that have resulted in population declines, and global extinctions of several species. Examples include Batrachochytrium dendrobatidis, which causes a cutaneous fungal infection of amphibians and is linked to declines of amphibians globally (Kriger and Hero, 2009); and recently discovered Pseudogymnoascus (Geomyces) destructans, the etiologic agent of white-nose syndrome (WNS), which has caused precipitous declines of North American bat species (Blehert et al., 2009). Furthermore, there is increasing evidence of the subsequent impacts on human and ecosystem health; for example, increasing risk of exposure to Lyme disease as a consequence of decreased biodiversity (LoGiudice et al., 2003) as well as the economic cost of the loss of bats due to decreased insect control services (Boyles et al., 2011). Figure A12-1 is a timeline of important diseases investigated by the U.S. Geological Survey since the 1970s, which illustrates three factors: 1. The unprecedented emergence of new pathogens and geographic spread of known pathogens since the 1990s; 2. Diseases are increasingly causing large-scale, negative impacts on wildlife populations and spreading over larger geographic areas rather than remaining localized; and 3. Diseases are increasingly of concern for multiple sectors, including public health, agriculture and wildlife management agencies. Of increasing concern are these novel diseases such as WNS as they are hard to anticipate, particularly devastating to human health or wildlife populations, challenging to manage, spread over large geographic areas in short time periods, and may result in ecological ripple effects that are difficult to predict. The following article provides examples of recently emerged viral diseases of wildlife origin. The examples have been selected to illustrate the drivers of emerging viral diseases, both novel pathogens and previously known diseases, the impacts of these diseases, as well as the role of wildlife both as “villains” or reservoirs as well as “victims” of these viral diseases. The article also discusses potential management strategies for emerging viral diseases in wildlife populations and future science directions in wildlife health to prevent, prepare, respond to, and recover from these disease events. Finally, the concept of One Health and its potential role in developing solutions to these issues of mutual concern is discussed.

Conference Paper↗
USGS2019

The unprecedented loss of Florida's reef-building corals and the emergence of a novel coral-reef assemblage

Over the last half century, climate change, coral disease, and other anthropogenic disturbances have restructured coral-reef ecosystems on a global scale. The disproportionate loss of once-dominant, reef-building taxa has facilitated relative increases in the abundance of “weedy” or stress-tolerant coral species. Although the recent transformation of coral-reef assemblages is unprecedented on ecological timescales, determining whether modern coral reefs have truly reached a novel ecosystem state requires evaluating the dynamics of reef composition over much longer periods of time. Here, we provide a geologic perspective on the shifting composition of Florida's reefs by reconstructing the millennial-scale spatial and temporal variability in reef assemblages using 59 Holocene reef cores collected throughout the Florida Keys Reef Tract (FKRT). We then compare the relative abundances of reef-building species in the Holocene reef framework to data from contemporary reef surveys to determine how much Florida's modern reef assemblages have diverged from long-term baselines. We show that the composition of Florida's reefs was, until recently, remarkably stable over the last 8000 yr. The same corals that have dominated shallow-water reefs throughout the western Atlantic for hundreds of thousands of years, Acropora palmata , Orbicella spp., and other massive coral taxa, accounted for nearly 90% of Florida's Holocene reef framework. In contrast, the species that now have the highest relative abundances on the FKRT, primarily Porites astreoides and Siderastrea siderea , were rare in the reef framework, suggesting that recent shifts in species assemblages are unprecedented over millennial timescales. Although it may not be possible to return coral reefs to pre-Anthropocene states, our results suggest that coral-reef management focused on the conservation and restoration of the reef-building species of the past, will optimize efforts to preserve coral reefs, and the valuable ecosystem services they provide into the future.

Florida↗
USGS2013

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↗
USGS2009

Estimation of Streamflow Characteristics for Charles M. Russell National Wildlife Refuge, Northeastern Montana

Charles M. Russell National Wildlife Refuge (CMR) encompasses about 1.1 million acres (including Fort Peck Reservoir on the Missouri River) in northeastern Montana. To ensure that sufficient streamflow remains in the tributary streams to maintain the riparian corridors, the U.S. Fish and Wildlife Service is negotiating water-rights issues with the Reserved Water Rights Compact Commission of Montana. The U.S. Geological Survey, in cooperation with the U.S. Fish and Wildlife Service, conducted a study to gage, for a short period, selected streams that cross CMR, and analyze data to estimate long-term streamflow characteristics for CMR. The long-term streamflow characteristics of primary interest include the monthly and annual 90-, 80-, 50-, and 20-percent exceedance streamflows and mean streamflows (Q.90, Q.80, Q.50, Q.20, and QM, respectively), and the 1.5-, 2-, and 2.33- year peak flows (PK1.5, PK2, and PK2.33, respectively). The Regional Adjustment Relationship (RAR) was investigated for estimating the monthly and annual Q.90, Q.80, Q.50, Q.20, and QM, and the PK1.5, PK2, and PK2.33 for the short-term CMR gaging stations (hereinafter referred to as CMR stations). The RAR was determined to provide acceptable results for estimating the long-term Q.90, Q.80, Q.50, Q.20, and QM on a monthly basis for the months of March through June, and also on an annual basis. For the months of September through January, the RAR regression equations did not provide acceptable results for any long-term streamflow characteristic. For the month of February, the RAR regression equations provided acceptable results for the long-term Q.50 and QM, but poor results for the long-term Q.90, Q.80, and Q.20. For the months of July and August, the RAR provided acceptable results for the long-term Q.50, Q.20, and QM, but poor results for the long-term Q.90 and Q.80. Estimation coefficients were developed for estimating the long-term streamflow characteristics for which the RAR did not provide acceptable results. The RAR also was determined to provide acceptable results for estimating the PK1.5., PK2, and PK2.33 for the three CMR stations that lacked suitable peak-flow records. Methods for estimating streamflow characteristics at ungaged sites also were derived. Regression analyses that relate individual streamflow characteristics to various basin and climatic characteristics for gaging stations were performed to develop regression equations to estimate streamflow characteristics at ungaged sites. Final equations for the annual Q.50, Q.20, and QM are reported. Acceptable equations also were developed for estimating QM for the months of February, March, April, June, and July, and Q.50, Q.20, and QM on an annual basis. However, equations for QM for the months of February, March, April, June, and July were determined to be less consistent and reliable than the use of estimation coefficients applied to the regression equation results for the annual QM. Acceptable regression equations also were developed for the PK1.5, PK2, and PK2.33.

Scientific Investigations Report↗
USGS2012

The U.S. Geological Survey Ecosystem Science Strategy, 2012-2022 - Advancing discovery and application through collaboration

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 policy-makers are faced with countless decisions each year at local, state, tribal, territorial, and national levels on issues as diverse as renewable and non-renewable energy development, agriculture, forestry, water supply, and resource allocations at the urban-rural interface. The urgency for sound decision-making 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 well-being 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 decision-makers 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 USGS scientists and partners can play in building scientific understanding and providing timely information to decision-makers. The strategy underscores the connection between scientific discoveries and the application of new knowledge. The strategy integrates ecosystem science and decision-making, producing new scientific outcomes to assist resource managers and providing public benefits. The USGS is uniquely positioned to play an important role in ecosystem science. With its wide range of expertise, the agency 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 DOI and other partners in the natural sciences, in both conducting science and its application. 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 and vision for USGS ecosystems science that focuses on five long-term goals, which are seen as interconnected and reinforcing components: • 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 decision-making 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 decision-making. Use quantitative approaches to assess the vulnerabilities of ecosystems, habitats, and species, and evaluate strategies for adaptation, restoration, and sustainable management. Following the strategic approaches are a set of proposed actions that represent a sampling of specific 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 both 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 over the next decade in advancing the scientific foundation for sustaining the natural resources that diverse, productive, resilient ecosystems provide.

Open-File Report↗
USGS2021

Sagebrush conservation strategy—Challenges to sagebrush conservation

The sagebrush ( Artemisia spp.) biome, its wildlife, and the services and benefits it provides people and local communities are at risk. Development in the sagebrush biome, for many purposes, has resulted in multiple and often cumulative negative impacts. These impacts, ranging from simple habitat loss to complex, interactive changes in ecosystem function, continue to accelerate even as the need grows for the resources provided by this biome. This “Sagebrush Conservation Strategy—Challenges to Sagebrush Conservation,” is an overview and assessment of the challenges facing land managers and landowners in conserving sagebrush ecosystems. This strategy is intended to provide guidance so that the unparalleled collaborative efforts to conserve the iconic greater sage-grouse ( Centrocercus urophasianus ) by State and Federal agencies, Tribes, academia, nongovernmental organizations, and stakeholders can be expanded to the entire sagebrush biome to benefit the people and wildlife that depend on this ecosystem. This report is organized into 3 parts. “Part I. Importance of the Sagebrush Biome to People and Wildlife” introduces the biome and a subset of the more than 350 species of plants and animals associated with sagebrush for which there is some level of conservation concern. These include several sagebrush obligates that have been petitioned for listing under the Endangered Species Act of 1973 (16 U.S.C. 1531 et seq.), including greater sage-grouse, Gunnison sage-grouse ( C. minimus ; listed as threatened), and pygmy rabbit ( Brachylagus idahoensis ). Other sagebrush-dependent species, such as pronghorn ( Antilocapra americana ) and mule deer ( Odocoileus hemionus ), have experienced significant population declines. “Part II. Change Agents in the Sagebrush Biome—Extent, Impacts, and Effort to Address Them” is an overview of the variety of change agents that are causing the continued loss and degradation of sagebrush. Topics covered include altered fire regimes, invasive plant species, conifer expansion, overabundant free-roaming equids, and human land uses, including energy development, cropland conversion, infrastructure, and improper livestock grazing. Climate changes, including warmer temperatures and altered amounts and timing of precipitation, have and will likely increasingly compound negative effects to sagebrush ecosystems from all these threats. “Part III. Current Conservation Paradigm and Other Conservation Needs for Sagebrush” begins with an overview of how sage-grouse conservation, and the associated efforts and collaborations, may be able to address threats to and restoring degraded sagebrush and habitat for other sagebrush-dependent and -associated species. Meeting conservation goals for sage-grouse, mule deer, pygmy rabbits, and other sagebrush-associated wildlife will require extensive restoration of sagebrush communities already converted or degraded by the change agents outlined in Part II of this report. Concepts, considerations, techniques for restoration, and adaptive management and monitoring are discussed to help set the stage for potential strategies to improve conditions throughout the sagebrush biome. Communication, outreach, and engagement can enhance grassroots conservation efforts and build the next generation of managers, practitioners, scientists, and communicators who will care for the sagebrush ecosystem and stimulate or sustain public participation in sagebrush conservation issues.

Arizona, California, Colorado, Idaho, Montana, Neb↗
USGS2022

Integration of satellite-based optical and synthetic aperture radar imagery to estimate winter cover crop performance in cereal grasses

The magnitude of ecosystem services provided by winter cover crops is linked to their performance (i.e., biomass and associated nitrogen content, forage quality, and fractional ground cover), although few studies quantify these characteristics across the landscape. Remote sensing can produce landscape-level assessments of cover crop performance. However, commonly employed optical vegetation indices (VI) saturate, limiting their ability to measure high-biomass cover crops. Contemporary VIs that employ red-edge bands have been shown to be more robust to saturation issues. Additionally, synthetic aperture radar (SAR) data have been effective at estimating crop biophysical characteristics, although this has not been demonstrated on winter cover crops. We assessed the integration of optical (Sentinel-2) and SAR (Sentinel-1) imagery to estimate winter cover crops biomass across 27 fields over three winter–spring seasons (2018–2021) in Maryland. We used log-linear models to predict cover crop biomass as a function of 27 VIs and eight SAR metrics. Our results suggest that the integration of the normalized difference red-edge vegetation index (NDVI_RE1; employing Sentinel-2 bands 5 and 8A), combined with SAR interferometric (InSAR) coherence, best estimated the biomass of cereal grass cover crops. However, these results were season- and species-specific (R 2 = 0.74, 0.81, and 0.34; RMSE = 1227, 793, and 776 kg ha −1 , for wheat ( Triticum aestivum L.), triticale ( Triticale hexaploide L.), and cereal rye ( Secale cereale ), respectively, in spring (March–May)). Compared to the optical-only model, InSAR coherence improved biomass estimations by 4% in wheat, 5% in triticale, and by 11% in cereal rye. Both optical-only and optical-SAR biomass prediction models exhibited saturation occurring at ~1900 kg ha −1 ; thus, more work is needed to enable accurate biomass estimations past the point of saturation. To address this continued concern, future work could consider the use of weather and climate variables, machine learning models, the integration of proximal sensing and satellite observations, and/or the integration of process-based crop-soil simulation models and remote sensing observations.

Maryland↗
USGS2016

Forecasting tidal marsh elevation and habitat change through fusion of Earth observations and a process model

Reducing uncertainty in data inputs at relevant spatial scales can improve tidal marsh forecasting models, and their usefulness in coastal climate change adaptation decisions. The Marsh Equilibrium Model (MEM), a one-dimensional mechanistic elevation model, incorporates feedbacks of organic and inorganic inputs to project elevations under sea-level rise scenarios. We tested the feasibility of deriving two key MEM inputs—average annual suspended sediment concentration (SSC) and aboveground peak biomass—from remote sensing data in order to apply MEM across a broader geographic region. We analyzed the precision and representativeness (spatial distribution) of these remote sensing inputs to improve understanding of our study region, a brackish tidal marsh in San Francisco Bay, and to test the applicable spatial extent for coastal modeling. We compared biomass and SSC models derived from Landsat 8, DigitalGlobe WorldView-2, and hyperspectral airborne imagery. Landsat 8-derived inputs were evaluated in a MEM sensitivity analysis. Biomass models were comparable although peak biomass from Landsat 8 best matched field-measured values. The Portable Remote Imaging Spectrometer SSC model was most accurate, although a Landsat 8 time series provided annual average SSC estimates. Landsat 8-measured peak biomass values were randomly distributed, and annual average SSC (30 mg/L) was well represented in the main channels (IQR: 29–32 mg/L), illustrating the suitability of these inputs across the model domain. Trend response surface analysis identified significant diversion between field and remote sensing-based model runs at 60 yr due to model sensitivity at the marsh edge (80–140 cm NAVD88), although at 100 yr, elevation forecasts differed less than 10 cm across 97% of the marsh surface (150–200 cm NAVD88). Results demonstrate the utility of Landsat 8 for landscape-scale tidal marsh elevation projections due to its comparable performance with the other sensors, temporal frequency, and cost. Integration of remote sensing data with MEM should advance regional projections of marsh vegetation change by better parameterizing MEM inputs spatially. Improving information for coastal modeling will support planning for ecosystem services, including habitat, carbon storage, and flood protection.

California↗
USGS2017

Developing an effective Agassiz's Desert Tortoise monitoring program: Final report to the Coachella Valley Conservation Commission

Agassiz’s desert tortoise (Gopherus agassizii) is a conservation-reliant species with populations north and west of the Colorado River protected as threatened under the Endangered Species Act (Averill-Murray et al. 2012). Since it was listed under this category in 1990, a great deal has been learned about the natural history of the species, and it is now one of the best-studied turtles in the United States (Lovich and Ennen 2013). However, the accumulated body of scientific data available for the species has not yet been translated into recovery or delisting of the species. Successful conservation of any species requires knowledge of their natural history and how vital rates affect their ability to maintain stable populations in the face of natural and anthropogenic stresses. Agassiz’s desert tortoises occur from southwestern Utah to near the Mexican border in California – a distance of over 450 km – but population densities vary greatly across this immense landscape (U.S. Fish and Wildlife Service 2015). Tortoises occur in the Sonoran Desert of California, including the eastern and western ends of the Coachella Valley, where it is one of 27 species covered under the Coachella Valley Multiple Species Habitat Conservation Plan and Natural Community Conservation Plan (CVMSHCP/NCCP). The southern portion of Joshua Tree National Park (JTNP) lies within this 1.1 million acre planning area, and was predicted to be an area of low-density tortoise populations using habitat suitability modeling (Barrows 2011). JTNP is near the southern distributional limit of G. agassizii, yet very little has been published regarding the ecology of tortoises in the Sonoran Desert of California. Reproductive output is an important gross measure of the ability of a population to persist. When integrated with data on fertility and survivorship, this information forms a foundation for assessing population status and formulating effective management strategies (e.g., Congdon et al. 1993, 1994), especially for imperiled species. One aspect of the biology of G. agassizii that has been particularly well-studied is reproductive output. However, most of what we know about this topic comes from research in the Mojave Desert portion of the species’ range (Ernst and Lovich 2009). Comparatively little has been published on the reproductive ecology of populations living in the Sonoran Desert ecosystem of California. Publications by Lovich et al. (1999, 2011, 2012, 2014, 2015) constitute the main body of literature on desert tortoise reproductive ecology in the Sonoran Desert of California, with one study population located at the western end of the CVMSHCP/NCCP area. Collecting data on Agassiz’s desert tortoise ecology in the Sonoran Desert ecosystem is important due to significant differences between the two adjacent desert ecosystems, especially the timing and amounts of annual precipitation, and their potential effects on reproductive output (e.g., Lovich et al. 5 2015). There are also differences in the vulnerability of tortoises to the effects of a warming, drying climate between the two deserts (Barrows 2011; Zylstra et al. 2012). The overall goal of this study was to collect data on demography, reproductive output, and genetic affinities at a study site in the Sonoran Desert portion of JTNP in the eastern end of the CVMSHCP/NCCP area. Specific objectives included: 1) Collect data to establish baselines on tortoise populations and/or their habitat suitability in core habitat within the CVNCCP area, including biotic and abiotic variables affecting persistence of tortoise populations; 2) Compare and contrast with data collected on desert tortoises at USGS/BLM study site near Palm Springs over 16 years; 3) Support long-term modeling efforts needed to determine tortoise population viability; 4) Refine modeled relationships with identified threats such as fire, invasive species and climate change; and 5) Prioritize adaptive management needs for the desert tortoise in and beyond the CVNCCP area. The data from this study will aid in determining baseline estimates of the desert tortoise population size within the planning area as well as establish a marked population of Agassiz’s desert tortoises for future monitoring. Data will be integrated with habitat modeling in order to refine model output. Genetic data will be collected on both the north and south sides of Interstate 10 to determine the potential effects of habitat fragmentation and genetic mixing. Analyses are ongoing and results beyond those presented in this report will be published in peer-reviewed scientific journals following inclusion of additional data collected on the south side of Shavers Valley in 2017-2018.

Report↗
USGS2019

The risk reduction benefits of the Mesoamerican Reef in Mexico

Coastal development and climate change are dramatically increasing the risks of flooding, erosion, and extreme weather events. Coral reefs and other coastal ecosystems act as natural defenses against coastal hazards, but their degradation increases risk to people and property. Environmental degradation, however, has rarely been quantified as a driver of coastal risk. In Quintana Roo, Mexico, a region on the Mexican Caribbean coast with an annual tourism economy of 10 billion USD, coral reefs constitute a natural barrier against flooding from hurricanes. This study spatially quantifies the risk reduction benefits of the Mesoamerican Reef in Quintana Roo for people, buildings, and hotel infrastructure. The risk reduction benefits are substantial. For example, the reefs prevented 43% additional damage during Hurricane Dean in (2007) and provide nowadays hazard risk reduction for 4.3% of the people, 1.9% of the built capital, and 2.4% of the hotel infrastructure, per year. The annual benefits are estimated in 4,600 people, 42 million USD damage prevention for buildings, and 20.8 million USD for hotel infrastructure. The study also compares the risk reduction of coral reefs with (i) the protection offered by dunes and (ii) the increase in coastal risk from sea-level rise (SLR). The risk reduction of dunes is more critical where there are no coral reefs offshore and for small return-periods storms. Sea-level rise, however, will make the more frequent storms more impactful and will drive significant increases in annual expected damages across the region. However, we demonstrate that, in coral reef environments, the contribution of reef degradation to coastal risk is larger than the expected increase in risk from SLR. However, the spatial distribution of the risk reduction benefits from reefs differs for people and infrastructure, and in particular for hotels, which receive the most protection from reefs. Furthermore, many sections present larger benefits than the typical costs of restoration. This valuation makes a compelling case for protecting and maintaining this natural infrastructure for its risk reduction service, but also allows the development of piloting innovative strategies, such as risk finance and insurance strategies, that can align environmental and risk management goals.

Mesoamerican Reef↗
USGS2009

Geography of Alaska lake districts: Identification, description, and analysis of lake-rich regions of a diverse and dynamic state

Lakes are abundant landforms and important ecosystems in Alaska, but are unevenly distributed on the landscape with expansive lake-poor regions and several lake-rich regions. Such lake-rich areas are termed lake districts and have landscape characteristics that can be considered distinctive in similar respects to mountain ranges. In this report, we explore the nature of lake-rich areas by quantitatively identifying Alaska’s lake districts, describing and comparing their physical characteristics, and analyzing how Alaska lake districts are naturally organized and correspond to climatic and geophysical characteristics, as well as studied and managed by people. We use a digital dataset (National Hydrography Dataset) of lakes greater than 1 hectare, which includes 409,040 individual lakes and represents 3.3 percent of the land-surface area of Alaska. The selection criteria we used to identify lake districts were (1) a lake area (termed limnetic ratio, in percent) greater than the mean for the State, and (2) a lake density (number of lakes per unit area) greater than the mean for the State using a pixel size scaled to the area of interest and number of lakes in the census. Pixels meeting these criteria were grouped and delineated and all groups greater than 1,000 square kilometers were identified as Alaska’s lake districts. These lake districts were described according to lake size-frequency metrics, elevation distributions, geology, climate, and ecoregions to better understand their similarities and differences. We also looked at where lake research and relevant ecological monitoring has occurred in Alaska relative to lake districts and how lake district lands and waters are currently managed. We identified and delineated 20 lake districts in Alaska representing 16 percent of the State, but including 65 percent of lakes and 75 percent of lake area. The largest lake districts identified are the Yukon-Kuskokwim Delta, Arctic Coastal Plain, and Iliamna lake districts with high limnetic ratios of 19, 17, and 21 percent, respectively. The three smallest districts we considered were Tetlin in the eastern interior, Menhiskof on the Alaska Peninsula, and Matanuska–Susitna at the head of Cook Inlet with limnetic ratios of 14, 9, and 9 percent, respectively. Lake density and limnetic ratio were poorly related among lake districts, such that some districts had a few large lakes like Iliamna with Lakes Iliamna and Becharof—the two largest in the State, compared to other districts with many very small lakes like Yukon-Kuskokwim Delta with 111,130 lakes and 63 percent of these less than 10 hectares. Most lake districts are in regions with relatively low precipitation, but temperature regimes varied widely among lake districts. Approximately one-half of lake districts were glaciated during the Pleistocene and similar numbers occur in regions classified as having continuous, discontinuous, and sporadic permafrost, or perennially unfrozen soils. Most districts are at low elevations (less than 250 meters) with two important exceptions being Tetlin with a mean elevation of 530 meters and Ahtna with a mean elevation of 760 meters. These higher elevation districts, particularly Ahtna, had distinct characteristics from other lake districts such as continuous permafrost and Pleistocene glaciation. Several lake districts share similar boundaries to defined ecoregions with lake districts occurring in less than one-half of these 32 ecoregions of Alaska. Most lake districts are lands fully or partly managed by the U.S. Fish and Wildlife Service and the National Park Service, with other land management by the Bureau of Land Management and State and borough government. Much of the U.S. Geological Survey’s lake water-quality sampling efforts has been done in the Arctic Coastal Plain, Matanuska-Susitna, and Iliamna districts but no recorded collections in nine lake districts. Similarly, most lake limnological studies in Alaska were site-specific and represent only a small portion of Alaska’s lake districts. This identification, characterization, and analysis of lake-rich regions may help provide a template to guide future limnological and other scientific research for Alaska.

Alaska↗
USGS2010

Development of monitoring protocols to detect change in rocky intertidal communities of Glacier Bay National Park and Preserve

Glacier Bay National Park and Preserve in southeastern Alaska includes extensive coastlines representing a major proportion of all coastlines held by the National Park Service. The marine plants and invertebrates that occupy intertidal shores form highly productive communities that are ecologically important to a number of vertebrate and invertebrate consumers and that are vulnerable to human disturbances. To better understand these communities and their sensitivity, it is important to obtain information on species abundances over space and time. During field studies from 1997 to 2001, I investigated probability-based rocky intertidal monitoring designs that allow inference of results to similar habitat within the bay and that reduce bias. Aerial surveys of a subset of intertidal habitat indicated that the original target habitat of bedrock-dominated sites with slope less than or equal to 30 degrees was rare. This finding illustrated the value of probability-based surveys and led to a shift in the target habitat type to more mixed rocky habitat with steeper slopes. Subsequently, I investigated different sampling methods and strategies for their relative power to detect changes in the abundances of the predominant sessile intertidal taxa: barnacles -Balanomorpha, the mussel Mytilus trossulus and the rockweed Fucus distichus subsp. evanescens. I found that lower-intensity sampling of 25 randomly selected sites (= coarse-grained sampling) provided a greater ability to detect changes in the abundances of these taxa than did more intensive sampling of 6 sites (= fine-grained sampling). Because of its greater power, the coarse-grained sampling scheme was adopted in subsequent years. This report provides detailed analyses of the 4 years of data and evaluates the relative effect of different sampling attributes and management-set parameters on the ability of the sampling to detect changes in the abundances of these taxa. The intent was to provide managers with information to guide design choices for intertidal monitoring. I found that the coarse-grained surveys, as conducted from 1998 to 2001, had power ranging from 0.68 to 1.0 to detect 10 percent annual changes in the abundances of these predominant sessile species. The information gained through intertidal monitoring would be useful in assessing changes due to climate (including ocean acidification), invasive species, trampling effects, and oil spills.

Open-File Report↗
USGS1996

Ground-water resources and water-supply alternatives in the Wawona area of Yosemite National Park, California

Planning efforts to implement the 1980 General Management Plan, which recommends relocating park administrative facilities and employee housing from Yosemite Valley in Yosemite National Park, California, have focused on the availability of water at potential relocation sites within the park. Ground-water resources and water-supply alternatives in the Wawona area, one of several potential relocation sites, were evaluated between June 1991 and October 1993. Ground water flowing from Biledo Spring near the headwaters of Rainier Creek, about 5 miles southeast of Wawona, is probably the most reliable source of good quality ground water for Wawona. A dilute calcium bicarbonate ground water flows from the spring at about 250 gallons per minute. No Giardia was detected in a water sample collected from Biledo Spring in July 1992. The concentration of dissolved 222 radon at Biledo Spring was 420 picoCuries per liter, exceeding the primary drinking-water standard of 300 picoCuries per liter proposed by the U.S. Environmental Protection Agency. This concentration, however, was considerably lower than the concentrations of dissolved 222 radon measured in ground water at Wawona. The median value for 15 wells sampled at Wawona was 4,500 picoCuries per liter. Water-quality samples from 45 wells indicate that ground water in the South Fork Merced River valley at Wawona is segregated vertically. Shallow wells produce a dilute calcium sodium bicarbonate water that results from chemical dissolution of minerals as water flows through fractured granitic rock from hillside recharge areas toward the valley floor. Tritium concentrations indicate that ground water in the shallow wells originated as precipitation after the 1960's when testing of atmospheric nuclear devices stopped. Ground water from the deep flowing wells in the valley floor is older sodium calcium chloride water. This older water probably originated either as precipitation during a climatically cooler period or as precipitation from altitudes between 1,400 and 3,700 feet higher than precipitation that recharged the local shallow ground-water-flow system. Chloride and associated cations in the deepground-water-flow system may result from upward leakage of saline ground water or from leaching of saline fluid inclusions in the granitic rocks. Water-level and pressure-gage measurements for 38 wells in the South Fork Merced River valley also indicate that the ground water in the valley is segregated vertically. Hydraulic head in deep fractures is as much as 160 feet above the valley floor. Vertical hydraulic gradients between the shallow and deep systems are as high as 4.5 feet per foot in one of two test holes drilled for this study. Measurements of in situ stress in the two test holes indicate that the vertical segregation of ground water may be related to pressures in the earth that squeeze horizontal fractures closed at depth. Fractures within a few hundred feet of land surface are poorly connected to fractures deeper beneath the valley. About 100 privately owned wells currently are in use at Wawona; but, the ground-water-flow system may not be an adequate source of good quality ground water for relocated park facilities. Yields from existing wells are low (median 4-5 gallons per minute) and traditional methods for locating high-yielding wells in fractured rocks have not been successful in this area. Concentrations of dissolved 222 radon (median 4,500 picoCuries per liter) are high, and the development of deep ground water could cause deeper saline water to migrate upward into producing wells. The South Fork Merced River, the primary source of water supply for Wawona, does not meet current demands during late summer and autumn. Data collected between 1958 and 1968 indicate that 25 percent of the time discharge of the South Fork River at Wawona during the dry season (August through October) was less than 2 cubic feet per second-the discharge rate at which the National Park Service is restricted from withdrawing water from the river. the river, however, could be relied on for additional water supply if facilities were constructed to divert and store water during periods of high flow for use later in the year.

California↗
USGS2008

StreamStats: A water resources web application

Streamflow statistics, such as the 1-percent flood, the mean flow, and the 7-day 10-year low flow, are used by engineers, land managers, biologists, and many others to help guide decisions in their everyday work. For example, estimates of the 1-percent flood (the flow that is exceeded, on average, once in 100 years and has a 1-percent chance of being exceeded in any year, sometimes referred to as the 100-year flood) are used to create flood-plain maps that form the basis for setting insurance rates and land-use zoning. This and other streamflow statistics also are used for dam, bridge, and culvert design; water-supply planning and management; water-use appropriations and permitting; wastewater and industrial discharge permitting; hydropower facility design and regulation; and the setting of minimum required streamflows to protect freshwater ecosystems. In addition, researchers, planners, regulators, and others often need to know the physical and climatic characteristics of the drainage basins (basin characteristics) and the influence of human activities, such as dams and water withdrawals, on streamflow upstream from locations of interest to understand the mechanisms that control water availability and quality at those locations. Knowledge of the streamflow network and downstream human activities also is necessary to adequately determine whether an upstream activity, such as a water withdrawal, can be allowed without adversely affecting downstream activities. Streamflow statistics could be needed at any location along a stream. Most often, streamflow statistics are needed at ungaged sites, where no streamflow data are available to compute the statistics. At U.S. Geological Survey (USGS) streamflow data-collection stations, which include streamgaging stations, partial-record stations, and miscellaneous-measurement stations, streamflow statistics can be computed from available data for the stations. Streamflow data are collected continuously at streamgaging stations. Streamflow measurements are collected systematically over a period of years at partial-record stations to estimate peak-flow or low-flow statistics. Streamflow measurements usually are collected at miscellaneous-measurement stations for specific hydrologic studies with various objectives. StreamStats is a Web-based Geographic Information System (GIS) application (fig. 1) that was created by the USGS, in cooperation with Environmental Systems Research Institute, Inc. (ESRI) 1 , to provide users with access to an assortment of analytical tools that are useful for water-resources planning and management. StreamStats functionality is based on ESRI's ArcHydro Data Model and Tools, described on the Web at http://support.esri.com/index.cfm?fa=downloads.dataModels.filteredGateway&dmid=15 . StreamStats allows users to easily obtain streamflow statistics, basin characteristics, and descriptive information for USGS data-collection stations and user-selected ungaged sites. It also allows users to identify stream reaches that are upstream and downstream from user-selected sites, and to identify and obtain information for locations along the streams where activities that may affect streamflow conditions are occurring. This functionality can be accessed through a map-based user interface that appears in the user’s Web browser (fig. 1), or individual functions can be requested remotely as Web services by other Web or desktop computer applications. StreamStats can perform these analyses much faster than historically used manual techniques. StreamStats was designed so that each state would be implemented as a separate application, with a reliance on local partnerships to fund the individual applications, and a goal of eventual full national implementation. Idaho became the first state to implement StreamStats in 2003. By mid-2008, 14 states had applications available to the public, and 18 other states were in various stages of implementation.

Fact Sheet↗