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USGS2016

Bivalve effects on the food web supporting delta smelt - A long-term study of bivalve recruitment, biomass, and grazing rate patterns with varying freshwater outflow

Executive Summary Phytoplankton is an important and limiting food source in the Sacramento-San Joaquin Delta (the Delta) and San Francisco Bay; the decline of phytoplankton biomass is one possible factor in the pelagic organism decline and specifically in the decline of the protected delta smelt. The bivalves Corbicula fluminea and Potamocorbula amurensis have been shown to control phytoplankton biomass in several locations throughout the system, and their distribution and population dynamics are therefore of great interest. We were able to describe the distribution and dynamics of bivalve biomass through use of samples collected by the California Department of Water Resources (DWR) as part of a monitoring program from 1977 to 2013. As one element of DWR’s and the Bureau of Reclamation’s Environmental Monitoring Program (EMP), the DWR benthic monitoring program examines the impact of water project operations on the estuary as prescribed by a series of Water Rights Decisions mandated by the State Water Resources Control Board (SWRCB). The availability of multidecade samples allowed us to examine long-term trends in biomass, recruitment, and size of bivalves at the 15 stations sampled. Biomass and grazing rate had the same basic trends, and the conclusions that we apply to biomass can be applied to grazing rate data. During winter of most years, Potamocorbula biomass was low at all locations and was near zero in the shallow San Pablo Bay station. The Potamocorbula biomass at shallow stations consistently peaked during summer and fall, but there was no consistent peak season in the deep stations. Corbicula had a much less consistent seasonal biomass pattern than Potamocorbula . However, some interannual patterns were consistent between stations. Corbicula biomass at three stations declined after 2003 (C9, D16, and D28). The Franks Tract (D19) Corbicula biomass had a baseline shift up (that is, all values were > 0) in 1985 until DWR ceased sampling at the station in 1995. Two other stations showed a similar increase in baseline but at different times; D24 shifted up after 2007 and D11 shifted up in 1991. Potamocorbula recruitment (any bivalve ≤ 2.5 millimeters [mm] in length) occurred anytime between spring and fall, with bivalves at the most downstream stations in San Pablo Bay recruiting in spring and animals at the most upstream stations recruiting in fall. The bivalves at the stations between these endpoints recruited in (1) spring or (2) summer and fall (Carquinez Strait), or in some combination of two of those three seasons in Grizzly Bay. The few locations where Potamocorbula and Corbicula overlapped showed recruitment abundance opposing each other, with Potamocorbula recruits peaking during the more saline time of year and Corbicula recruits peaking during periods of lower salinities. Corbicula recruits were present throughout most of the year with some peaks in abundance, but the patterns were not seasonally consistent at any station. Mean size peaked in both bivalves in late summer and early fall and never got above a certain size; maximum size depended on location. The mean size of both bivalves has decreased over the years, with the size distributions throughout the Delta now skewed toward smaller, younger Corbicula (< 10 mm). The mean size of Potamocorbula has also become skewed toward the small, younger bivalves, with sizes in the range of 2 – 8 mm. The mean size of Potamocorbula increased from spring to fall and decreased in winter. A similar generalization is not possible with Corbicula because seasonal patterns in size varied depending on station location. Station D24 on the Sacramento River was the only location with an increase in Corbicula mean size over the sampling period. The largest mean sized Potamocorbula were seen in the channel areas, where sizes of 15 mm were common at stations D41C, 8.1, and D6; sizes in excess of 15 mm were observed at all three D4 stations during the mid 1990s. The mean size of Potamocorbula in the shoals was ≈5 – 7 mm in most years in Grizzly Bay (D7) and San Pablo Bay (D41A), with an increase to > 10 mm at D7 in the wet years. The largest mean sized Corbicula were in the southern Delta (C9 ≈25 mm during 1996 – 97 and 2012 – 2013), and the smallest average sizes were in the San Joaquin River (P8 and D16). Corbicula at the upstream Sacramento River station (D24) and in the southern Delta (C9) showed similar interannual patterns in average size although the animals at C9 were consistently larger than those at D24 were. Corbicula in Franks Tract (D19) and the Old River (D28A) south of Franks Tract were also similar in size and in interannual patterns. At the few stations where Potamocorbula and Corbicula co-occur, it appears that they did not hinder each other’s growth. Both bivalves had large animals at D4, where Corbicula size increased coincident with the presence of Potamocorbula in 1987. Corbicula were observed in wet years prior to Potamocorbula’s invasion at D7 (Grizzly Bay) and were capable of growing to significant size in wet years (> 20 mm in 1986).

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USGS2006

Evaluation of some software measuring displacements using GPS in real-time

For the past decade, the USGS has been monitoring deformation at various locations in the western United States using continuous GPS. The main focus of these measurements are estimates of displacement averaged over one day. Essentially, these consist of recording at 30 seconds intervals the carrier-frequency phase-data (equivalent to travel-time) between a GPS receiver and the GPS satellite network. In turn, these observations, which are converted to pseudo—ranges, are processed using one of the “research grade” programs (GIPSY, Zumberge et al., or GAMIT, wwwgpsg.mit.edu/~simon/gtgk) to estimate the position of the GPS receiver averaged over 24 hours. However, it is possible and desirable to estimate the position of the receiver (actually the antenna) more frequently and to do this within a few seconds of the time actual measurement (known as real-time). A recent example, the 2004 Magnitude 6, Parkfield, California earthquake, demonstrated that having GPS estimates of position more frequently than simply a daily average is required if one requires discrimination between co-seismic and post-seismic deformation (Langbein et al., 2006). The high-rate estimates of position obtained at Parkfield show that post-seismic deformation started less than one-hour after the mainshock and that this deformation was roughly the same magnitude as the co-seismic deformation. The high-rate solutions for Parkfield were done by others including Yehuda Bock at UCSD and Kristine Larson at U. of Colorado, but not the USGS. The Parkfield experience points out the need for an in-house capability by the USGS to be able to accurately measure co-seismic displacements and other rapid, deformation signals using GPS. This applies to both the Earthquake and Volcano Hazard programs. Although at many locations where we monitor deformation, we have strainmeters and tiltmeters in addition to GPS which, in principle, are far more sensitive to rapid deformation over periods of less than a day (Langbein and Bock, 2004). But, not all locales include strain and tiltmeters. Thus, having the capability to extract signals with periods of less than a day is desirable since the distribution of GPS is more extensive than strain and tilt. At both Parkfield and Long Valley, the USGS has been using other software packages to process the GPS data at sub-daily intervals and in real-time. The underlying goal of these types of measurements is to detect any deformation event as it evolves; the 24 hour processing might not provide timely results if such a deformation event is precursory to a geologic hazard (an earthquake for Parkfield and either a volcanic event or an earthquake for Long Valley). In Long Valley, We use the software package called 3DTracker (http://www.3dtracker.com, http://www.condorearth.com) to estimate the changes of in position of a remote site relative to a “fixed” site. The 3DTracker software uses double difference GPS code measurements and receiversatellite-time triple differences from one epoch to the next of the GPS phase data (a proxy for travel-time measurements) and employs a Kalman filter to obtain stability in the estimate of position. That is, the estimate of the current position depends upon the estimate of the prior position. Hence, a time series of position looks fairly smooth depending upon the coefficient selected for the Kalman filter. With triple differences, the sometimes troublesome initial integer cycle ambiguity terms cancel (number of wavelengths between the receiver and each satellite), but only the incremental change in position is calculated. This triple difference Kalman filter solution is slow to converge and less accurate than a double difference (e.g., RTD, Track) solution, but it is robust and computationally efficient (Remondi and Brown, 2000). 3D-Tracker allows use of various single-frequency and dual-frequency GPS phase and code observables including the ionospheric-free combinations (known as LC or L3 and P(L3)) formed from an linear combination of the L1 and L2 carrier phase and code data. The lowest noise observable is the L1 carrier, but it is biased by ionospheric refraction that has amplitudes of about 1 to 10 ppm. This results in a systematic scale error in the relative positions. The L3 phase noise is about 3 times greater than the L1 phase noise, but it is generally used to solve for all but the shortest baselines (< 5 km). In addition, the software does output the position changes is a standard format that can be used for other analysis. At Parkfield, we use the software package called RTD (http://www.geodetics.com). The RTD software has been described in the literature (Bock et al., 2000) but basically, it estimates the position without the constraint of a Kalman filter. It uses double differences (in our studies the LC or ionospheric free observable is used) and the integer ambiguities are resolved independently for each 1-second measurement; Most GPS software that use double-differences require several epochs of measurements to resolve the integer ambiguities. The data files use a proprietary format and can not be read by me or others; rather, Yehuda Bock at UCSD (and author of RTD) translates these files into a standard format that can be read by me. Recently, Tom Herring of MIT has modified the GAMIT software to process kinematically GPS data (www-gpsg.mit.edu/~simon/gtgk/tutorial/Lecture_13.pdf). At this time, the software, known as TRACK, does not process the observations in real-time. Consequently, the latency between the time of the observation and the time when a position estimate is available depends upon the frequency that the data are downloaded and the speed of actually processing the observations; there could be a delay of an hour or two before the a position estimates are available. Unlike RTD and 3DTracker, TRACK comes with GAMIT (which is distributed freely) and is currently operating in a test mode at the USGS office in Pasadena. The LC or ionosphere free observable is used in our TRACK solutions. JPL has a version of their GIPSY software called “Real-time GIPSY (RTG)” (gipsy.jpl.nasa.gov/orms/rtg), which, like TRACK, can process the pseudo-range data “off—line”. However, this software is not freely distributed. Instead, at least one company, NAVCOM, has teamed with JPL to integrate RTG with GPS receivers and telemetry that yields positions in realtime. Kristine Larson of University of Colorado has modified the original GIPSY to estimate positions kinematically. Again, like TRACK, the positions are estimated off—line. Much of her research is described in Larson et al. (2003), and Choi et al. (2004). For Long Valley, out of the 17 GPS sites, we monitor 5 baselines within the caldera at 5 second intervals relative to the Bald Mountain site at the edge of the caldera using 3DTracker. The baseline measurement using 3DTracker consists of determination of the 3 dimensional positions of the 5 remote points (GPS receivers) relative to a GPS site at Bald. A second, independent system collects and downloads once a day the 30-second data used for the 24-hour solutions for the 12 sites not monitored with 3DTracker. For the sites monitored with 3DTracker, the pseudo—range data are decimated to 30 seconds and converted to a form used for the 24-hour solutions. Both sets of telemetry employ 900 MHz spread spectrum radios which require line of site between all of the links. The telemetry for the 3DTracker sites require a dedicated radios at each end and intermediate repeaters as needed, while the telemetry required for the other sites use a single master radio, repeaters as needed, and a radio at each remote site. (The 5 sites being monitored with 3DTracker require 13 radios.) At Parkfield, RTD is used to measure the position changes all 12 baselines at 1 second intervals relative to a site, Pomm, adjacent to the San Andreas Fault. The complete RTD package (hardware and software) collects all of the data and determines the position of each site relative to Pomm. In addition, the system stores both the 1-second and 30-second pseudo-range data for later downloading which are ultimately used in the 24-hour solutions. To do this, each site has a 2.4 GHz radio and a telemetry buffer. The telemetry buffer holds 24-hours of data (in the event that the telemetry link is broken) and converts the RS232 data stream from the GPS receiver into a form compatible with an IP (Internet protocol) network connection. In contrast with the Long Valley system, the telemetry link for GPS at Parkfield consists of a single radio at each remote sites and a single radio at the central site. Although position estimates are produced within 1-second of the observations, these results are not immediately available because there is no high speed Internet connection to Parkfield. Instead, the data are stored on a removable disk and sent to UCSD once per month. Below, I describe the results of a simple experiment to examine the response of some of these systems to simulated deformation that could be an analogue of a tectonic or volcanic event. In many engineering applications, the system response is tested by inputting a step to the system and measuring the output of the system. Essentially, this is what I've done. The experiment described below moves the GPS antenna from its original position to a new position within 1 second; the software tracks the translation. These measurements were conducted in August 2004 with the RTD software at Parkfield, and twice in Long Valley. The first Long Valley test was conducted in September 2004 using 3DTracker on a single baseline. The test was repeated in September 2005 using 3DTracker on two baselines and, importantly, saving the RINEX files of the data so that the data could be replayed through 3DTracker using other options in the program and, using other software packages including TRACK. In addition, we observed a short-term event at the Three Sisters volcano in Oregon. This event was snow melt at a remote GPS site which gave an apparent 15 cm displacement in vertical in less than one-day. 3DTracker is used to monitor this site, and the event was captured with this software. In addition, with the assistance of others, I got additional estimates of position using other software packages; those results are presented. Finally, the precision of both 3DTracker and RTD are compared using a power spectrum. Those results would suggest that 3DTracker using appropriate Kalman filter coefficients would have better precision than RTD; instead, the lower noise level from 3DTracker is a result of smoothing from the Kalman filter. Given the results described in this report, high-rate GPS is certainly capable of accurately measuring displacements of 1 centimeter with a high degree of statistical confidence. Plotting these results show that the time of the displacement can be visually determined to that of the sampling interval of the data. However, especially with small amplitude signals, any of the software packages can yield erroneous deformation “signals” that are either due excess travel-time of the GPS carrier frequency from multipath or a limitation in the software. Thus, the time series of displacements must be viewed with caution and knowledge of external circumstances that might cause a change in position. The casual reader should continue with the next section describing the methods then jump to the last two sections for the discussion and conclusions. I have made some recommendations there.

Open-File Report↗

USGS2010

Southeast Regional Assessment Project for the National Climate Change and Wildlife Science Center, U.S. Geological Survey

The Southeastern United States spans a broad range of physiographic settings and maintains exceptionally high levels of faunal diversity. Unfortunately, many of these ecosystems are increasingly under threat due to rapid human development, and management agencies are increasingly aware of the potential effects that climate change will have on these ecosystems. Natural resource managers and conservation planners can be effective at preserving ecosystems in the face of these stressors only if they can adapt current conservation efforts to increase the overall resilience of the system. Climate change, in particular, challenges many of the basic assumptions used by conservation planners and managers. Previous conservation planning efforts identified and prioritized areas for conservation based on the current environmental conditions, such as habitat quality, and assumed that conditions in conservation lands would be largely controlled by management actions (including no action). Climate change, however, will likely alter important system drivers (temperature, precipitation, and sea-level rise) and make it difficult, if not impossible, to maintain recent historic conditions in conservation lands into the future. Climate change will also influence the future conservation potential of non-conservation lands, further complicating conservation planning. Therefore, there is a need to develop and adapt effective conservation strategies to cope with the effects of climate and landscape change on future environmental conditions. Congress recognized this important issue and authorized the U.S. Geological Survey (USGS) National Climate Change and Wildlife Science Center (NCCWSC; http://nccw.usgs.gov/) in the Fiscal Year 2008. The NCCWSC will produce science that will help resource management agencies anticipate and adapt to climate change impacts to fish, wildlife, and their habitats. With the release of Secretarial Order 3289 on September 14, 2009, the mandate of the NCCWSC was expanded to address climate change-related impacts on all Department of the Interior (DOI) resources. The NCCWSC will establish a network of eight DOI Regional Climate Science Centers (RCSCs) that will work with a variety of partners to provide natural resource managers with tools and information that will help them anticipate and adapt conservation planning and design for projected climate change. The forecasting products produced by the RCSCs will aid fish, wildlife, and land managers in designing suitable adaptive management approaches for their programs. The DOI also is developing Landscape Conservation Cooperatives (LCCs) as science and conservation action partnerships at subregional scales. The USGS is working with the Southeast Region of the U.S. Fish and Wildlife Service (FWS) to develop science collaboration between the future Southeast RCSC and future LCCs. The NCCWSC Southeast Regional Assessment Project (SERAP) will begin to develop regional downscaled climate models, land cover change models, regional ecological models, regional watershed models, and other science tools. Models and data produced by SERAP will be used in a collaborative process between the USGS, the FWS (LCCs), State and federal partners, nongovernmental organizations, and academia to produce science at appropriate scales to answer resource management questions. The SERAP will produce an assessment of climate change, and impacts on land cover, ecosystems, and priority species in the region. The predictive tools developed by the SERAP project team will allow end users to better understand potential impacts of climate change and sea level rise on terrestrial and aquatic populations in the Southeastern United States. The SERAP capitalizes on the integration of five existing projects: (1) the Multi-State Conservation Grants Program project "Designing Sustainable Landscapes," (2) the USGS multidisciplinary Science Thrust project "Water Availability for Ecological Needs," (3) the USGS Southeast Pilot Project "Climate Change in the Southeastern U.S. and its Impacts on Bird Distributions and Habitats," (4) a sea-level rise impacts study envisioned jointly with the National Oceanic and Atmospheric Administration (NOAA), and (5) two USGS sea-level rise impact assessment projects that address inundation hazards and provide probabilistic forecasts of coastal geomorphic change. The SERAP will expand on these existing projects and include the following tasks, which were initiated in summer 2009: * Regionally downscaled probabilistic climate-change projections * Integrated coastal assessment * Integrated terrestrial assessment * Multi-resolution assessment of potential climate change effects on biological resources: aquatic and hydrologic dynamics * Optimal conservation strategies to cope with climate change The SERAP seeks to formally integrate these tasks to aid conservation planning and design so that ecosystem management decisions can be optimized for providing desirable outcomes across a range of species and environments. The following chapters detail SERAP's efforts in providing a suite of regional climate, watershed, and landscape-change analyses and develop the interdisciplinary framework required for the biological planning phases of adaptive management and strategic conservation. The planning phase will include the identification of conservation alternatives, development of predictive models and decision support tools, and development of a template to address similar challenges and goals in other regions. The project teams will explore and develop ways to link the various ecological models arising from each component. The SERAP project team also will work closely with members of the LCCs and other partnerships throughout the life of the project to ensure that the objectives of the project meet resources mangers needs in the Southeast.

Open-File Report↗

USGS2007

Applying radar technology to migratory bird conservation and management: Strengthening and expanding a collaborative

Executive Summary Understanding the factors affecting migratory bird and bat populations during all three phases of their life cycle—breeding, nonbreeding, and migration—is critical to species conservation planning. This includes the need for information about these species’ responses to natural challenges, as well as information about the effects of human activities and structures. Habitats and other resources critical to migrants during passage and stopover are being destroyed, degraded, and threatened by human activities. Birds and bats are also uniquely susceptible to human use of the airspace. Wind turbines, communication and power transmission towers, and other tall structures, known to cause bird and bat mortality, are being erected or proposed in increasing numbers across the country. In addition, the potential for bird/aircraft collisions poses human safety threats. Management and regulatory agencies, conservation organizations, and industry currently lack the information they need to meet their missions and statutory responsibilities. The biological data available from various radar technologies offer a unique opportunity to learn more about the spatiotemporal distribution patterns, flight characteristics, and habitat use of “aero-fauna.” Recognizing the opportunities presented by radar technologies, the U.S. Geological Survey (USGS), the U.S. Fish and Wildlife Service (USFWS), and university partners collaborated first on individual projects and then in a broader, informal “collaborative” to coordinate their radar-related research and work together to develop the suite of products needed for conservation of birds and bats. Having produced two summary documents (Sojda and others, 2005; Ruth and others, 2005), the next objective was to convene a workshop for researchers, management and regulatory agencies, and other interested parties. The focus of this initial workshop was on strengthening the existing USGS-USFWS-university partnership and expanding the “collaborative” to include new Federal agency partners. The subject matter was centered on discussing available technologies, appropriate applications, management-related needs, and ways to strengthen collaborative research and conservation efforts. The workshop opened with presentations about the history of the “radar collaborative,” a description of the workshop objectives and focuses, and a summary of resource management and regulatory needs. Scientific presentations describing current research projects or subjects followed, given by USGS scientists, as well as scientists from other Federal agencies, academia, conservation and ornithological organizations, and a private contracting firm. Presenters addressed a wide variety of management issues including siting of wind-power facilities, bird/aircraft collisions, effects of hurricanes Katrina and Rita on bird migration, bird use of Conservation Reserve Program land, defining bird migration patterns at a broad regional scale, and associating migrant birds with their stopover habitats. Presentations described a variety of radar technologies including NEXRAD weather surveillance radar, modified mobile marine radar, military tracking radar, pencil beam radar, and dual polarization radar, as well as complementary techniques and analysis methods such as acoustic monitoring, thermal imaging, artificial intelligence, and individual-based modeling. Key issues, themes, and questions identified during the open discussions that followed fell into five main categories: (1) agency needs and challenges; (2) radar technology and applications—technical questions and issues; (3) tools and resources for managers and researchers; (4) standardization of protocols; and (5) collaborative opportunities. Participants identified the following management, regulatory, or business issues facing them which may be addressed with radar technologies: tall structures; wind turbines; identification and protection of key habitats; assessment of management activities; and bird/aircraft strikes. Participants frequently expressed the need for specific information about which radar technologies are best used for answering particular questions. User groups emphasized the importance of clear, defensible scientific information on which they can base their activities. In turn, researchers emphasized their need for clearly defined, specific questions from managers so that they can design and conduct the required research. Discussions about technical issues requiring further research and collaboration included target identity, ground-truthing, linking migrants to habitat, and standardized protocols for applied research. Workshop participants identified and endorsed a series of seven action items that would promote collaboration and begin to address key issues identified at the workshop: Action Item #1 : Establish a working subgroup to address large-scale surveillance radar standardization issues. Action Item #2 : Establish a working subgroup to address small-scale radar standardization issues. Action Item #3 : Bring management and regulatory agencies together to identify the three most important information needs for each key management issue relating to radar technologies. Action Item #4 : Develop Fact Sheet(s) to provide information about radar technology applications to migratory bird and bat conservation issues. Action Item #5 : Create a “radar collaborative” Website to provide information about radar biology applications, contacts, publications, and so forth. Action Item #6 : Formalize and expand the USGS-USFWS “radar collaborative.” Action Item #7 : Advance basic research, such as target identity and validation, which will support and improve our abilities to apply radar technologies to conservation objectives. There was considerable interest in expanding the “radar collaborative” to include those agencies, organizations, and industries represented at the workshop. It was felt that the publication of the workshop proceedings, implementation of action items, and additional future meetings or workshops will be crucial in strengthening the “radar collaborative” effort and promoting the use of these valuable technologies for conserving migratory species.

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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.

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USGS2014

Anthropogenic organic compounds in source water of select community water systems in the United States, 2002-10

Drinking water delivered by community water systems (CWSs) comes from one or both of two sources: surface water and groundwater. Source water is raw, untreated water used by CWSs and is usually treated before distribution to consumers. Beginning in 2002, the U.S. Geological Survey’s (USGS) National Water-Quality Assessment Program initiated Source Water-Quality Assessments (SWQAs) at select CWSs across the United States, primarily to characterize the occurrence of a large number of anthropogenic organic compounds that are predominantly unregulated by the U.S. Environmental Protection Agency. Source-water samples from CWSs were collected during 2002–10 from 20 surface-water sites (river intakes) and during 2002–09 from 448 groundwater sites (supply wells). River intakes were sampled approximately 16 times during a 1-year sampling period, and supply wells were sampled once. Samples were monitored for 265 anthropogenic organic compounds. An additional 3 herbicides and 16 herbicide degradates were monitored in samples collected from 8 river intakes and 118 supply wells in areas where these compounds likely have been used. Thirty-seven compounds have an established U.S. Environmental Protection Agency (EPA) Maximum Contaminant Level (MCL) for drinking water, 123 have USGS Health-Based Screening Levels (HBSLs), and 29 are included on the EPA Contaminant Candidate List 3. All compounds detected in source water were evaluated both with and without an assessment level and were grouped into 13 categories (hereafter termed as “use groups”) based on their primary use or source. The CWS sites were characterized in a national context using an extract of the EPA Safe Drinking Water Information System to develop spatially derived and system-specific ancillary data. Community water system information is contained in the EPA Public Supply Database, which includes 2,016 active river intakes and 112,099 active supply wells. Ancillary variables including population served, watershed size, land use, population density, and recharge were characterized for each of the watersheds for river intakes and contributing areas for supply wells. A total of 313 samples were collected from 20 river intakes. Between the years of 2002 through 2010, samples were collected approximately 16 times over the course of a year. Seventy-one compounds from 12 of the 13 use groups commonly occurred (detected in greater than or equal to 1 percent of samples using an assessment level of 0.05 microgram per liter or when a compound was detected in greater than or equal to 10 percent of samples without an assessment level) indicating a wide variety of sources and pathways to these rivers and highlighting the importance of source-water protection strategies. A total of 448 supply wells were sampled once during 2002–10 as part of 30 independent groundwater studies. About 15 CWS supply wells were sampled for each independent groundwater study. Twenty-eight compounds from 7 of the 13 use groups commonly occurred indicating a wide variety of sources and pathways exist for these compounds to reach these wells and highlighting the importance of wellhead protection strategies. About one-half the 265 compounds monitored (122) were detected in both surface water and groundwater samples. A more diverse suite of compounds were detected in surface water in comparison to groundwater. However, herbicides and herbicide degradates were the most frequent group of compounds detected in both surface water and groundwater. Sixty-five of the most commonly occurring compounds were detected in one or more samples from both surface water and groundwater. Human-health benchmarks (MCLs for regulated compounds and HBSLs for unregulated compounds) were available for more than one-half the compounds (160 of the 265) monitored in this study. Fifty-eight percent (41 of 71) of the commonly occurring compounds in surface water have a human-health benchmark to which concentrations can be compared; 19 have MCLs and 22 have HBSLs. Eighty-three percent (24 of 28) of the most commonly occurring compounds in groundwater have a human-health benchmark for which concentrations can be compared; 14 have MCLs and 10 have HBSLs. To put results from this study into context with the national distribution of river intakes and supply wells used by CWSs, sites were grouped into the respective national population of land-use quartiles. The increase in compound occurrence with increasing urban and agricultural land use in the watershed or contributing area was more evident for rivers than for supply wells. The increase in detection frequency of herbicides and herbicide degradates with increasing agricultural land use was more evident for rivers than for supply wells. The occurrence of solvents did not change substantially with increasing urban land use for rivers or supply wells. Basic co-occurrence analyses were completed with and without an assessment level. Considering all detections in surface water without an assessment level, approximately 86 percent of source-water samples contained 2 or more compounds, and 50 percent of samples contained at least 14 compounds. Considering all detections in groundwater without an assessment level, 50 percent of samples contained at least three compounds. For the most part, the compounds detected most frequently as individual compounds in the environment often composed the most frequent unique mixtures. Five of the 10 most frequently co-occurring unique mixtures in both surface water and groundwater were the same: atrazine and deethylatrazine; atrazine and chloroform; deethylatrazine and simazine; atrazine and simazine; and deethylatrazine, atrazine, and simazine. Because similar mixtures were identified in both surface water and groundwater without an assessment level, future studies could be directed toward better understanding the toxicological importance of these unique mixtures. Summed concentrations of herbicide degradates were compared to concentrations of the parent herbicides in surface-water and groundwater samples collected from 8 river intakes and 118 CWS wells, from which samples were analyzed for an additional 3 herbicides and 16 degradates. The toxicity to humans for many of these degradate products is largely unknown and thus points to the importance of monitoring these compounds (both the parent and degradate) in the environment. This study highlights the importance of anthropogenic organic compounds in source water of select CWSs in the United States by characterizing their occurrence in surface-water and groundwater samples. Compound concentrations and occurrence are summarized and evaluated in a human-health context, when possible. Additionally, compounds found to co-occur as mixtures for both surface water and groundwater highlight the significance of low-level compound co-occurrence.

Scientific Investigations Report↗

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↗

USGS1984

The evolution of the southern California uplift, 1955 through 1976

The southern California uplift culminated in 1974 as a 150- km-wide crustal swell that extended about 600 km eastward and east-southeastward from Point Arguello to the Colorado River and Salton Sea, respectively; it was characterized by remarkably uniform height changes between 1959 and 1974 of 0.30-0.35 m over at least half of its 60,000-70,000 km 2 area. At its zenith, the uplift included virtually the entire Transverse Ranges geologic province and parts of the Coast Ranges, San Joaquin Valley, Sierra Nevada, Basin and Range, Mojave Desert, Peninsular Ranges, and Salton Trough provinces. The alinement of the western part of the uplift closely paralleled the east-trending Transverse Ranges, whereas the southern flank of the eastern lobe roughly coincided with the west-northwest-trending San Andreas fault. The position and configuration of the uplift associate it with a singularly complex section of the boundary between the North American and Pacific plates that has certainly sustained major modification during the past 5 million years and probably during the past 1 million years. Surface deformation can be categorized as tectonic or nontectonic. Nontectonic vertical displacements associated with the activities of man have overwhelmed natural compaction and areally significant soil expansion in the southern California area. Because tectonic displacements are implicitly defined as those that cannot be otherwise explained, those vertical movements that can be reasonably attributed to artificial processes have been subtracted from our reconstructed configurations of the uplift. Hence this reconstruction has necessarily included the assembly and evaluation of an enormous volume of data on oil-field operations, changes in ground-water levels, and measured subsidence (or rebound) associated with changes in the underground fluid regimen. Measured changes in height at various stages in the evolution of the uplift have been based chiefly on first-order levelings carried out between 1953 and 1976. Exceptions to this generalization consist largely of the results of pre-1953 surveys through the western Transverse Ranges and the eastern Mojave Desert. Errors in measured height differences derive from blunders, systematic survey errors, random survey errors, improperly formulated orthometric corrections, and intrasurvey movement; the last of these has created the most serious problems encountered in our reconstruction of the basic data. A variety of independent tests indicate that survey error associated with the utilized levelings was generally small and fell largely within the predicted random-error range. Moreover, the redundancy and coherence displayed by the entire data set provide convincing evidence of survey accuracy and the virtual absence of height- and slope-dependent error in particular. Our reconstructions of the changing configuration of the uplift derive chiefly from comparisons among sequentially developed observed elevations along the same route. Most of the observed elevations from which the vertical displacements were computed have been reconstructed with respect to bench mark Tidal 8, San Pedro, as invariant in height. Because the San Pedro tide station has been characterized by a history of modest relative uplift, vertical displacements referred to this station are biased slightly toward the appearance of subsidence. Where the observed elevations cannot be conveniently tied to Tidal 8, they have been referred to secondary control points whose history with respect to Tidal 8 can be independently established. Each of the lines of observed elevation changes provides, accordingly, a section athwart or along the axis of the uplift from which the changes in the configuration of the uplift can be roughly generalized. Because relatively few surveys were run in 1955, which we choose as a representative temporal datum, we have commonly incorporated the results of earlier or of somewhat later levelings as the equivalents of 1955 surveys. Although this procedure introduces a certain subjectivity, the probable equivalence between the results of these earlier or later surveys with those that would have been obtained had this leveling been carried out in 1955, usually can be independently tested. Wherever the calculated vertical displacements are based on comparisons between the results of levelings over different routes, the observed elevations have been orthometrically corrected to agree with those that would have been produced had each of these surveys been along the same route. The growth of the southern California uplift consisted of two well-defined spasms of positive movement, the second of which was closely followed by partial collapse. Our reconstruction, although it clearly errs in detail, indicates that the uplift, together with marginal and apparently ephemeral tectonic subsidence, nucleated in the west-central Transverse Ranges near Ozena, sometime between the spring of 1959 and the spring of 1960. The uplift expanded rapidly eastward (and probably westward as well), and by the fall of 1961 much of the Transverse Ranges and the Mojave Desert at least as far east as Twentynine Palms had risen by as much as 0.25 m. Between 1962 and 1972 the area included by the initially developed (1959-61) uplift sustained additional but clearly decelerating uplift accompanied locally by oscillatory displacements. Between 1972/ 73 and 1974 a second crustal spasm extended the uplift eastward to the Colorado River and elevated much of the eastern Mojave Desert by values that equaled or exceeded those developed within the western lobe. Between 1974 and 1976, at least the central part of the uplift sustained partial collapse that nowhere amounted to less than 50 percent of the cumulative uplift since 1959. Whether this collapse affected the entire uplift is conjectural, but we now recognize well-defined evidence of major down-to-the-north tilting that must have occurred within the eastern part of the uplift at some time between 1974 and 1976. Accumulating evidence indicates that nearly all the area included with the southern California uplift underwent similar uplift and partial collapse during the early part of the 20th century. Thus we infer that the recent uplift represents but a single event in an ongoing, more or less cyclic deformational process characterized by a period of about 50 years. Even though less than two full cycles are expressed in the geodetic record, the cumulative rate of uplift near the center of the recent uplift probably has averaged about 5 mm/yr, a value that is roughly consistent with the uplift rates that have been deduced for the late Quaternary emergent marine terraces along the south flank of the Transverse Ranges. Although the evolution of the recent uplift is relatively well defined, its correlation with the regional seismicity is poorly defined. A comparison between the occurrence of southern California earthquakes of magnitude ≥4 during the period 1932 to 1976 with the 1974 configuration of the uplift demonstrates the existence of (1) relatively aseismic areas within the western lobe of the uplift (in the western Transverse Ranges), in the central part of the uplift (in the western Mojave Desert), and along an east-trending zone that extends into the eastern Mojave athwart the south flank of the uplift (north of the Salton Sea) and (2) localized concentrations of seismic activity along the flanks of the uplift. Moreover, 9 of the 10 largest earthquakes recorded within or around the area of the southern California uplift during the period 1932 to 1976 (the 1933 Long Beach, the 1941 Santa Barbara, the 1946 Walker Pass, the 1947 Manix, the 1948 Desert Hot Springs, and the four major 1952 Kern County shocks) occurred before the inception of the uplift in 1959 or 1960. The area embraced by the southern California uplift has been identified with geodetically defined horizontal strain, part of which may have accumulated as a major north-south contractional event that roughly coincided with the first spasm of uplift. Nonetheless, continuing contractional strain associated with regionally developed partial collapse argues that the uplift cannot be fully explained simply as the vertical expression of continuing north-south compression. Consideration of the two well-defined historical episodes of uplift and partial collapse indicate that the southern California uplift may be the product of decoupling and viscous flow beneath the seismogenic zone, presumably driven by continuing motion between the irregularly margined plates south of the great bend of the San Andreas fault. Because the magnitude of the maximum uplift associated with each episode was approximately the same, there may be some threshold value above which collapse (viscous flow) may ensue; the absence of total collapse may be a function of precollapse strain hardening within the postulated subseismogenic viscoelastic layer.

California↗