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At least 1,189 records · Page 66Linked to original sources
USGS2015

Mapping migratory flyways in Asia using dynamic Brownian bridge movement models

Background Identifying movement routes and stopover sites is necessary for developing effective management and conservation strategies for migratory animals. In the case of migratory birds, a collection of migration routes, known as a flyway, is often hundreds to thousands of kilometers long and can extend across political boundaries. Flyways encompass the entire geographic range between the breeding and non-breeding areas of a population, species, or a group of species, and they provide spatial frameworks for management and conservation across international borders. Existing flyway maps are largely qualitative accounts based on band returns and survey data rather than observed movement routes. In this study, we use satellite and GPS telemetry data and dynamic Brownian bridge movement models to build upon existing maps and describe waterfowl space use probabilistically in the Central Asian and East Asian-Australasian Flyways. Results Our approach provided new information on migratory routes that was not easily attainable with existing methods to describe flyways. Utilization distributions from dynamic Brownian bridge movement models identified key staging and stopover sites, migration corridors and general flyway outlines in the Central Asian and East Asian-Australasian Flyways. A map of space use from ruddy shelducks depicted two separate movement corridors within the Central Asian Flyway, likely representing two distinct populations that show relatively strong connectivity between breeding and wintering areas. Bar-headed geese marked at seven locations in the Central Asian Flyway showed heaviest use at several stopover sites in the same general region of high-elevation lakes along the eastern Qinghai-Tibetan Plateau. Our analysis of data from multiple Anatidae species marked at sites throughout Asia highlighted major movement corridors across species and confirmed that the Central Asian and East Asian-Australasian Flyways were spatially distinct. Conclusions The dynamic Brownian bridge movement model improves our understanding of flyways by estimating relative use of regions in the flyway while providing detailed, quantitative information on migration timing and population connectivity including uncertainty between locations. This model effectively quantifies the relative importance of different migration corridors and stopover sites and may help prioritize specific areas in flyways for conservation of waterbird populations.

Movement Ecology↗
USGS2014

An application of Social Values for Ecosystem Services (SolVES) to three national forests in Colorado and Wyoming

Despite widespread recognition that social-value information is needed to inform stakeholders and decision makers regarding trade-offs in environmental management, it too often remains absent from ecosystem service assessments. Although quantitative indicators of social values need to be explicitly accounted for in the decision-making process, they need not be monetary. Ongoing efforts to map such values demonstrate how they can also be made spatially explicit and relatable to underlying ecological information. We originally developed Social Values for Ecosystem Services (SolVES) as a tool to assess, map, and quantify nonmarket values perceived by various groups of ecosystem stakeholders. With SolVES 2.0 we have extended the functionality by integrating SolVES with Maxent maximum entropy modeling software to generate more complete social-value maps from available value and preference survey data and to produce more robust models describing the relationship between social values and ecosystems. The current study has two objectives: (1) evaluate how effectively the value index, a quantitative, nonmonetary social-value indicator calculated by SolVES, reproduces results from more common statistical methods of social-survey data analysis and (2) examine how the spatial results produced by SolVES provide additional information that could be used by managers and stakeholders to better understand more complex relationships among stakeholder values, attitudes, and preferences. To achieve these objectives, we applied SolVES to value and preference survey data collected for three national forests, the Pike and San Isabel in Colorado and the Bridger–Teton and the Shoshone in Wyoming. Value index results were generally consistent with results found through more common statistical analyses of the survey data such as frequency, discriminant function, and correlation analyses. In addition, spatial analysis of the social-value maps produced by SolVES provided information that was useful for explaining relationships between stakeholder values and forest uses. Our results suggest that SolVES can effectively reproduce information derived from traditional statistical analyses while adding spatially explicit, social-value information that can contribute to integrated resource assessment, planning, and management of forests and other ecosystems.

Colorado;Wyoming↗
USGS2008

Comments on potential geologic and seismic hazards affecting proposed liquefied natural gas site in Santa Monica Bay, California

In a letter to the U.S. Geological Survey (USGS) dated March 25, 2008, Representative Jane Harman (California 36th district) requested advice on geologic hazards that should be considered in the review of a proposed liquefied natural gas (LNG) facility off the California coast in Santa Monica Bay. In 2004, the USGS responded to a similar request from Representative Lois Capps, regarding two proposed LNG facilities offshore Ventura County, Calif., with a report summarizing potential geologic and seismic hazards (Ross and others, 2004). The proposed LNG Deepwater Port (DWP) facility includes single point moorings (SPMs) and 35 miles of underwater pipelines. The DWP submersible buoys, manifolds, and risers would be situated on the floor of the southern Santa Monica Basin, in 3,000 feet of water, about 23 miles offshore of the Palos Verdes Peninsula. Twin 24-inch diameter pipelines would extend northeastward from the buoys across the basin floor, up the basin slope and across the continental shelf, skirting north around the Santa Monica submarine canyon. Figure 1 provides locations of the project and geologic features. Acronyms are defined in table 1. This facility is being proposed in a region of known geologic hazards that arise from both the potential for strong earthquakes and geologic processes related to sediment transport and accumulation in the offshore environment. The probability of a damaging earthquake (considered here as magnitude 6.5 or greater) in the next 30 years within about 30 miles (50 km) of the proposed pipeline ranges from 16% at the pipeline's offshore end to 48% where it nears land (Petersen, 2008). Earthquakes of this magnitude are capable of producing strong shaking, surface fault offsets, liquefaction phenomena, landslides, underwater turbidity currents and debris flow avalanches, and tsunamis. As part of the DWP license application for the Woodside Natural Gas proposal in Santa Monica Bay (known as the OceanWay Secure Energy Project), Fugro West, Inc., had already prepared a document discussing geologic hazards in the area, titled 'Exhibit B Topic Report 6 - Geological Resources' (Fugro West, Inc., 2007); hereafter, this will be called the 'Geological Resources document'. The USGS agreed to evaluate the information in the Geological Resources document regarding (1) proximity of active faults to the proposed project, (2) potential magnitude of seismic events from nearby faults, (3) thoroughness of the assessment of earthquake hazards in general, (4) potential hazards from ground rupture and strong shaking, (5) potential hazards from tsunamis, and (6) other geologic hazards including landslides and debris flows. Because two new earthquake probability reports were scheduled to be released in mid-April, 2008, by the USGS and the California Geological Survey (CGS), the USGS suggested a 6-month review period to enable a thorough incorporation of this new information. Twenty-seven scientists from the USGS and the CGS reviewed various sections of the Geological Resources document. This report outlines our major conclusions. The appendix is a longer list of comments by these reviewers, grouped by section of the Geological Resources document. Before discussing our reviews, we first provide a brief overview of geologic hazards in the proposed site area. This report is a snapshot in time and any future work in the area will need to take into account ongoing research efforts. For example, USGS scientists collected seismic reflection data in the spring of 2008 to study the structure and seismic potential of several faults in the area. Their interpretations (Conrad and others, 2008a and 2008b) are too preliminary to be included in this report, but their final results, along with other researchers' studies in the project area, should be considered in any future work on the Deepwater Port project.

California↗
USGS1978

Statistical inference from capture data on closed animal populations

The estimation of animal abundance is an important problem in both the theoretical and applied biological sciences. Serious work to develop estimation methods began during the 1950s, with a few attempts before that time. The literature on estimation methods has increased tremendously during the past 25 years (Cormack 1968, Seber 1973). However, in large part, the problem remains unsolved. Past efforts toward comprehensive and systematic estimation of density (D) or population size (N) have been inadequate, in general. While more than 200 papers have been published on the subject, one is generally left without a unified approach to the estimation of abundance of an animal population This situation is unfortunate because a number of pressing research problems require such information. In addition, a wide array of environmental assessment studies and biological inventory programs require the estimation of animal abundance. These needs have been further emphasized by the requirement for the preparation of Environmental Impact Statements imposed by the National Environmental Protection Act in 1970. This publication treats inference procedures for certain types of capture data on closed animal populations. This includes multiple capture-recapture studies (variously called capture-mark-recapture, mark-recapture, or tag-recapture studies) involving livetrapping techniques and removal studies involving kill traps or at least temporary removal of captured individuals during the study. Animals do not necessarily need to be physically trapped; visual sightings of marked animals and electrofishing studies also produce data suitable for the methods described in this monograph. To provide a frame of reference for what follows, we give an exampled of a capture-recapture experiment to estimate population size of small animals using live traps. The general field experiment is similar for all capture-recapture studies (a removal study is, of course, slightly different). A typical field experiment is the following: a number of traps are positioned in the area to be studied, say 144 traps in a 12 X 12 grid, 7 m apart. At the beginning of the study (j=1) a sample size of n 1 is taken from the population, the animals are tagged and marked for future identification, and then returned to the population, usually at the same point where they were trapped. After allowing time of the marked and unmarked animals to mix, a second sample (j=2, often the following day) or n 2 animals is then taken.the second sample normally contains both marked and unmarked animals. The unmarked animals are marked and all captured animals are released back into the population. This procedure continues for t periods where t ≥ 2. The animals should be marked in such a way that the capture-recapture history of each animal caught during the study is known. In practice, toes are often clipped to uniquely identify individual animals (Taber and Cowan 1969) or serially numbered tags are sometimes used on larger animals. Such capture studies are classified by 2 schemes that are directly related to what class of models are appropriate and what parameters can be estimated. The first classification addresses the subject of closure. Closure usually means the size of the population is constant over the priod of investigation, i.e., no recruitment (birth or immigration) or losses (death or emigration). This is a strong assumption and, of course, never completely true in a natural biological population. For greater generality, we define closure to mean there are no unknown changes to the initial population. In practice, this means known losses (trap death), or deliberate removals) do not violate our definition of closure. If the study is properly designed, closure can be met at least approximately. Open or nonclosed populations explicitly allow for one or more types of recruitment or losses to operate during the course of the experiment (Jolly 1965, Seber 1965, Robson 1969, Pollock 1975). Only closed populations will be considered in this monograph. The second classification depends on the type of data collected with 2 possibilities occurring (Pollock 1974, unpublished doctoral dissertation, Cornell University, Ithaca, New York): (1) only information on the recovery of marked animals is available for each sampling occasion, j, j=1, 2, ... t. (2) information on both marked and unmarked animals is available for each sampling occasion, j, j=1, 2, ... t. In case (1), population size (N) is not identifiable, however, other parameters can be estimated (Brownie et al. 1978). In case (2), N can be estimated using a wide variety of approaches depending upon what we wish to assume. Only case (2) will be dealt with here.

Wildlife Monographs↗
USGS2000

Combining information from monitoring programs: Complications associated with indices and geographic scale

To adequately monitor Neotropical migratory birds, information must be collected to assess population change at local, regional, and continent-wide scales. I suggest that large-scale survey results (such as those derived from the North American Breeding Bird Survey) should not be used to predict population attributes on parks, refuges, and other protected areas. These areas are often managed, and generally contain habitats that can be poorly sampled in large scale surveys, hence local bird populations might be quite different from those sampled in the large-scale surveys. Furthermore, we are limited in our capabilities to combine information from local surveys with large-scale survey data. Most surveys of bird populations collect indices of abundance which are often not comparable among surveys due to habitat and region specific differences in probabilities of detecting birds. In assessing the effects of management, it is important to understand the limitations of monitoring at different geographic scales and to design programs to monitor at the scale at which management is conducted.

Book chapter↗
USGS2013

Aquatic assessment of the Pike Hill Copper Mine Superfund site, Corinth, Vermont

The Pike Hill Copper Mine Superfund site in Corinth, Orange County, Vermont, includes the Eureka, Union, and Smith mines along with areas of downstream aquatic ecosystem impairment. The site was placed on the U.S. Environmental Protection Agency (USEPA) National Priorities List in 2004. The mines, which operated from about 1847 to 1919, contain underground workings, foundations from historical structures, several waste-rock piles, and some flotation tailings. The mine site is drained to the northeast by Pike Hill Brook, which includes several wetland areas, and to the southeast by an unnamed tributary that flows to the south and enters Cookville Brook. Both brooks eventually drain into the Waits River, which flows into the Connecticut River. The aquatic ecosystem at the site was assessed using a variety of approaches that investigated surface-water quality, sediment quality, and various ecological indicators of stream-ecosystem health. The degradation of surface-water quality is caused by elevated concentrations of copper, and to a lesser extent cadmium, with localized effects caused by aluminum, iron, and zinc. Copper concentrations in surface waters reached or exceeded the USEPA national recommended chronic water-quality criteria for the protection of aquatic life in all of the Pike Hill Brook sampling locations except for the location farthest downstream, in half of the locations sampled in the tributary to Cookville Brook, and in about half of the locations in one wetland area located in Pike Hill Brook. Most of these same locations also contained concentrations of cadmium that exceeded the chronic water-quality criteria. In contrast, surface waters at background sampling locations were below these criteria for copper and cadmium. Comparison of hardness-based and Biotic Ligand Model (BLM)-based criteria for copper yields similar results with respect to the extent or number of stations impaired for surface waters in the affected area. However, the BLM-based criteria are commonly lower values than the hardness-based criteria and thus suggest a greater degree or magnitude of impairment at the sampling locations. The riffle-habitat benthic invertebrate richness and abundance data correlate strongly with the extent of impact based on water quality for both brooks. Similarly, the fish community assessments document degraded conditions throughout most of Pike Hill Brook, whereas the data for the tributary to Cookville Brook suggest less degradation to this brook. The sediment environment shows similar extents of impairment to the surface-water environment, with most sampling locations in Pike Hill Brook, including the wetland areas, and the tributary to Cookville Brook affected. Sediment impairment is caused by elevated copper concentrations, although localized degradation due to elevated cadmium and zinc concentrations was documented on the basis of exceedances of probable effects concentrations (PECs). In contrast to impairment determined by exceedances of PECs, equilibrium-partitioning sediment benchmarks (based on simultaneously extracted metals, acid volatile sulfides, and total organic carbon) predict no toxic effects in sediments at the background locations and uncertain toxic effects throughout Pike Hill Brook and the tributary to Cookville Brook, with the exception of the most downstream Cookville Brook location, which indicated no toxic effects. Acute laboratory toxicity testing using the amphipod Hyalella azteca and the midge Chironomus dilutus on pore waters extracted from sediment in situ indicate impairment (based on tests with H. azteca ) at only one location in Pike Hill Brook and no impairment in the tributary to Cookville Brook. Chronic laboratory sediment toxicity testing using H. azteca and C. dilutus indicated toxicity in Pike Hill Brook at several locations in the lower reach and two locations in the tributary to Cookville Brook. Toxicity was not indicated for either species in sediment from the most acidic metal-rich location, likely due to the low lability of copper in that sediment, as indicated by a low proportion of extractable copper (simultaneously extracted metal (SEM) copper only 5 percent of total copper) and due to the flushing of acidic metal-rich pore water from experimental chambers as overlying test water was introduced before and replaced periodically during the toxicity tests. Depositional habitat invertebrate richness and abundance data generally agreed with the results of toxicity tests and with the extent of impact in the watersheds on the basis of sediment and pore waters. The information was used to develop an overall assessment of the impact of mine drainage on the aquatic system downstream from the Pike Hill copper mines. Most of Pike Hill Brook, including several wetland areas that are all downstream from the Eureka and Union mines, was found to be impaired on the basis of water-quality data and biological assessments of fish or benthic invertebrate communities. In contrast, only one location in the tributary to Cookville Brook, downstream from the Smith mine, is definitively impaired. The biological community begins to recover at the most downstream locations in both brooks due to natural attenuation from mixing with unimpaired streams. On the basis of water quality and biological assessment, the reference locations were of good quality. The sediment toxicity, chemistry, and aquatic community survey data suggest that the sediments could be a source of toxicity in Pike Hill Brook and the tributary to Cookville Brook. On the basis of water quality, sediment quality, and biologic communities, the impacts of mine drainage on the aquatic ecosystem health of the watersheds in the study area are generally consistent with the toxicity suggested from laboratory toxicity testing on pore water and sediments.

Vermont↗
USGS2012

USGS Environmental health science strategy: providing environmental health science for a changing world: Public review release

America has an abundance of natural resources. We have bountiful clean water, fertile soil, and unrivaled national parks, wildlife refuges, and public lands. These resources enrich our lives and preserve our health and wellbeing. These resources have been maintained because of our history of respect for their value and an enduring commitment to their vigilant protection. Awareness of the social, economic, and personal value of the health of our environment is increasing. The emergence of environmentally driven diseases caused by environmental exposure to contaminants and pathogens is a growing concern worldwide. New health threats and patterns of established threats are affected by both natural and anthropogenic changes to the environment. Human activities are key drivers of emerging (new and re-emerging) health threats. Societal demands for land and natural resources, a better quality of life, improved economic prosperity, and the environmental impacts associated with these demands will continue to increase. Natural earth processes, climate trends, and related climatic events will add to the environmental impact of human activities. These environmental drivers will influence exposure to disease agents, including viral, bacterial, prion, and fungal pathogens, parasites, natural earth materials, toxins and other biogenic compounds, and synthetic chemicals and substances. The U.S. Geological Survey (USGS) defines environmental health science broadly as the interdisciplinary study of relations among the quality of the physical environment, the health of the living environment, and human health. The interactions among these three spheres are driven by human activities, ecological processes, and natural earth processes; the interactions affect exposure to contaminants and pathogens and the severity of environmentally driven diseases in animals and people. This definition provides USGS with a framework for synthesizing natural science information from across the Bureau and providing it to environmental, natural resource, agricultural, and public-health managers. The USGS is a Federal science agency with a broad range of natural science expertise relevant to environmental health. USGS provides scientific information and tools as a scientific basis for management and policy decision making. USGS specializes in science at the environment-health interface, by characterizing the processes that affect the interaction among the physical environment, the living environment, and people, and the resulting factors that affect ecological and human exposure to disease agents. This report describes a 10-year strategy that encompasses the portfolio of USGS environmental health science. It summarizes national environmental health priorities that USGS is best suited to address, and will serve as a strategic framework for USGS environmental health science goals, actions, and outcomes for the next decade. Implementation of this strategy is intended to aid coordination of USGS environmental health activities and to provide a focal point for disseminating information to stakeholders. The "One Health" paradigm advocated by the World Health Organization (WHO, 2011), and the American Veterinary Medicine Association (AVMA, 2008), among others, is based on a general recognition that the health of humans, animals, and the environment are inextricably linked. Thus, successful efforts to protect that health will require increased interdisciplinary research and increased communication and collaboration among the broader scientific and health community. This strategy is built upon that paradigm. The vision, mission, and five cornerstone goals of the USGS Environmental Health Science Strategy were developed with significant input from a wide range of stakeholders. Vision - The USGS is a premier source of the environmental health science needed to safeguard the health of the environment, fish, wildlife, and people. Mission - The mission of USGS in environmental health science is to contribute scientific information to environmental, natural resource, agricultural, and public-health managers, who use that science to support sound decision making. USGS provides the science to: - Goal 1: Identify, prioritize, and detect contaminants and pathogens of emerging environmental concern. - Goal 2: Reduce the impact of contaminants on the environment, fish, wildlife, and people. - Goal 3: Reduce the impact of pathogens on the environment, fish, wildlife, and people. - Goal 4: Discover the complex interactions and combined effects of exposure to contaminants and pathogens. - Goal 5: Prepare for and respond to environmental impacts and related health threats of natural and anthropogenic disasters. Goals 1 through 4 are intended to provide science to address environmental health threats in a logical order, from informing prevention and preparedness, to supporting systematic management response to environmental health issues. Goal 4 addresses the interaction among contaminants and pathogens, an issue of emerging concern in environmental health science. Goal 5 acknowledges the fact that natural and anthropogenic disasters can cause immediate and prolonged adverse environmental health threats. This strategy proposes that USGS take the following strategic science actions to achieve each of the five goals of this strategy: Goal 1: Identify, prioritize, and detect contaminants and pathogens of emerging environmental concern. - Strategic Science Action 1. - Prioritize contaminants and pathogens of emerging concern to guide research, detection, and management activities. - Strategic Science Action 2. - Conduct surveillance and monitoring to provide early warning of emerging health threats. - Strategic Science Action 3. - Develop approaches and tools that identify vulnerable environmental settings, ecosystems, and species. Goal 2: Reduce the impact of contaminants on the environment, fish, wildlife, and people. - Strategic Science Action 1. - Systematically characterize the sources, occurrence, transport and fate of environmental contaminants to guide efforts to manage and mitigate contamination. - Strategic Science Action 2. - Evaluate the threats of contamination on the health of the environment, fish, wildlife, and people, and inform the associated management and protection efforts. - Strategic Science Action 3. - Characterize potential human exposure to support establishment of health-based standards or guidelines and contamination-reduction efforts. Goal 3: Reduce the impact of pathogens on the environment, fish, wildlife, and people. - Strategic Science Action 1. - Determine the biotic and abiotic factors that control the ecology of infectious diseases affecting natural populations of aquatic and terrestrial species and potential transmission to other animals and humans. - Strategic Science Action 2. - Establish how natural and anthropogenic environmental changes affect the distribution and severity of infectious diseases in natural populations of aquatic and terrestrial species and potential transmission to other animals and humans. - Strategic Science Action 3. - Develop surveillance systems to identify changing patterns of disease activity in priority geographic areas. Goal 4: Discover the complex interactions and combined effects of exposure to contaminants and pathogens. - Strategic Science Action 1. - Identify how exposure to one class of disease agents (contaminants or pathogens) can make an organism more susceptible to effects from exposure to the other class of disease agents. - Strategic Science Action 2. - Implement interdisciplinary studies that characterize the effects of combined exposure to pathogens and contaminants. Goal 5: Prepare for and respond to the environmental impacts and related health threats of natural and anthropogenic disasters. - Strategic Science Action 1. - Establish a formal interdisciplinary science capability to rapidly assess the environmental health risks associated with disasters. - Strategic Science Action 2. - Enhance methods to anticipate, prepare for, and identify environmental, ecological, and related health impacts of future disasters. This strategy is one of seven USGS science strategies developed concurrently: - Climate and Land Use Change - Core Science Systems - Ecosystems - Energy and Mineral Resources - Environmental Health - Natural Hazards - Water. This strategy describes how USGS will address the highest priority environmental health issues facing the Nation. The ultimate intended outcome of this science strategy is prevention and reduction of adverse impacts to the quality of the environment, the health of our living resources, and human health. Communication with, and receiving input from, partners and stakeholders regarding their science needs is essential for successful implementation of this strategy. It is incumbent on USGS to reach out to all stakeholders to ensure that USGS efforts are focused on the highest priority environmental health issues and that products are provided in the most timely and usable form to all those who can use them. USGS must reach out to the scientific community, internally and externally, to ensure that our efforts are integrated with and take full advantage of the activities of others.

Open-File Report↗
USGS2019

Filling knowledge gaps in a threatened shorebird flyway through satellite tracking

Satellite‐based technologies that track individual animal movements enable the mapping of their spatial and temporal patterns of occurrence. This is particularly useful in poorly studied or remote regions where there is a need for the rapid gathering of relevant ecological knowledge to inform management actions. One such region is East Asia, where many intertidal habitats are being degraded at unprecedented rates and shorebird populations relying on these habitats show rapid declines. We examine the utility of satellite tracking to accelerate the identification of coastal sites of conservation importance in the East Asian–Australasian Flyway. In 2015–2017, we used solar‐powered satellite transmitters to track the migration of 32 great knots ( Calidris tenuirostris ), an “Endangered” shorebird species widely distributed in the Flyway and fully dependent on intertidal habitats for foraging during the non‐breeding season. From the great knot tracks, a total of 92 stopping sites along the Flyway were identified. Surprisingly, 63% of these sites were not known as important shorebird sites before our study; in fact, every one of the tracked individuals used sites that were previously unrecognized. Site knowledge from on‐ground studies in the Flyway is most complete for the Yellow Sea and generally lacking for Southeast Asia, Southern China and Eastern Russia. Synthesis and applications . Satellite tracking highlighted coastal habitats that are potentially important for shorebirds but lack ecological information and conservation recognition, such as those in Southern China and Southeast Asia. At the same time, the distributional data of tracked individuals can direct on‐ground surveys at the lesser known sites to collect information on bird numbers and habitat characteristics. To recognize and subsequently protect valuable coastal habitats, filling knowledge gaps by integrating bird tracking with ground‐based methods should be prioritized.

East Asian-Australasian Flyway↗
USGS2014

Development of a globally applicable model for near real-time prediction of seismically induced landslides

Substantial effort has been invested to understand where seismically induced landslides may occur in the future, as they are a costly and frequently fatal threat in mountainous regions. The goal of this work is to develop a statistical model for estimating the spatial distribution of landslides in near real-time around the globe for use in conjunction with the U.S. Geological Survey (USGS) Prompt Assessment of Global Earthquakes for Response ( PAGER ) system. This model uses standardized outputs of ground shaking from the USGS ShakeMap Atlas 2.0 to develop an empirical landslide probability model, combining shaking estimates with broadly available landslide susceptibility proxies, i.e., topographic slope, surface geology, and climate parameters. We focus on four earthquakes for which digitally mapped landslide inventories and well-constrained ShakeMaps are available. The resulting database is used to build a predictive model of the probability of landslide occurrence. The landslide database includes the Guatemala (1976), Northridge (1994), Chi-Chi (1999), and Wenchuan (2008) earthquakes. Performance of the regression model is assessed using statistical goodness-of-fit metrics and a qualitative review to determine which combination of the proxies provides both the optimum prediction of landslide-affected areas and minimizes the false alarms in non-landslide zones. Combined with near real-time ShakeMaps , these models can be used to make generalized predictions of whether or not landslides are likely to occur (and if so, where) for earthquakes around the globe, and eventually to inform loss estimates within the framework of the PAGER system.

Engineering Geology↗
USGS2023

Climate-induced shifts in grassland bird nesting phenology have implications for grassland management

Grasslands are among the most impacted ecosystems globally. In the midcontinent of North America, a > 80% loss of grasslands has made their conservation a major priority for resource managers. Grassland ecosystems evolved under periodic disturbances; consequently, grassland management often involves regular actions such as grazing, haying, or burning to maintain ecosystem integrity. The timing of such practices has direct implications on grassland ecology, agricultural economics, and survival and fecundity of grassland nesting birds (hereafter grassland birds). We conducted a meta-analysis on the nesting phenology of grassland birds throughout North America, focusing on nest-survival literature. We constructed a well-fitting model to predict median date of expected nest departure (hereafter fledge date) for grassland birds across the midcontinent. Predictions from our model demonstrate considerable spatial variation in median nesting phenology that is predictable using a spatially explicit spring phenology index. Median fledge dates were 8 or 13 days earlier in years of extreme weather conditions (dry or wet, respectively) than in years of average conditions. Species that generally nest in taller vegetation tended to have later median nest phenologies than those using shorter vegetation. Our results incorporate the most rigorous information available in the literature on nesting phenology of 36 grassland bird species and improve information available to managers about nesting phenology of grassland birds in the midcontinent of North America. Our predictions approximate the day when one-half of the nesting efforts would be complete for a given area within the midcontinent grasslands and can inform management and conservation decisions about the timing of management actions in grassland ecosystems.

Global Ecology and Conservation↗
USGS2024

Evaluating seawater intrusion forecast uncertainty under climate change in the Pajaro Valley, California

Climate change and climate variability impacts such as rising sea levels have the potential to exacerbate seawater intrusion and the strain on coastal freshwater resources in already stressed groundwater basins such as those in the Pajaro Valley groundwater basin, California. Regional hydrologic models are often coupled with climate projections to forecast future hydrologic conditions and inform adaptive resources management strategies. However, there is high uncertainty in the future projections of water resources due to uncertainties from downscaling global general circulation models (GCMs) to local scale climate change projections, future land use changes, and the inherent uncertainty of developed hydrologic models. Future climate projections and the magnitude of their influence on modeled hydrologic drivers are highly variable. Therefore, to develop a forecast model, an ensemble of different projections can be used to capture a wider range of basin responses and the associated uncertainties in the modeled forecasts. Understanding the reliability and uncertainty of forecasts is important for developing climate adaptation strategies such as developing protective thresholds, particularly at the basin scale where the impacts are felt, and adaptation is implemented. To demonstrate this, an uncertainty analysis of groundwater level and seawater intrusion forecasts for the Pajaro Valley groundwater basin was performed using an ensemble of three future climate projections with the Pajaro Valley Integrated Hydrologic Model (PVIHM) and the first-order second moment (FOSM) method. FOSM uncertainty analysis of hydrologic forecasts across a multi-GCM climate ensemble provides an upper and lower bound of potential impacts of climate change on sustainability targets related to mitigating seawater intrusion. The groundwater level forecasts’ narrow range of variability can help policymakers in adaptation planning by constraining possible outcomes to a focused range for risk-management decisions. However, less than one-third of groundwater level forecasts met the current protection thresholds to prevent chronic lowering of groundwater. Therefore, sustainability targets may need to be reassessed. Relative to groundwater level changes, the seawater intrusion forecasts had larger uncertainty due to the GCM climate projections and the simulated hydrologic response that were compounded by the propagation of scaling and bias from the GCMs and model simplifications in simulating the coastal boundary.

California↗
USGS2015

From patterns to causal understanding: Structural equation modeling (SEM) in soil ecology

In this perspectives paper we highlight a heretofore underused statistical method in soil ecological research, structural equation modeling (SEM). SEM is commonly used in the general ecological literature to develop causal understanding from observational data, but has been more slowly adopted by soil ecologists. We provide some basic information on the many advantages and possibilities associated with using SEM and provide some examples of how SEM can be used by soil ecologists to shift focus from describing patterns to developing causal understanding and inspiring new types of experimental tests. SEM is a promising tool to aid the growth of soil ecology as a discipline, particularly by supporting research that is increasingly hypothesis-driven and interdisciplinary, thus shining light into the black box of interactions belowground.

Pedobiologia↗
USGS2021

Validation of the U.S. Geological Survey’s Land Change Monitoring, Assessment and Projection (LCMAP) collection 1.0 annual land cover products 1985–2017

The U.S. Geological Survey Land Change Monitoring, Assessment and Projection (USGS LCMAP) has released a suite of annual land cover and land cover change products for the conterminous United States (CONUS). The accuracy of these products was assessed using an independently collected land cover reference sample dataset produced by analysts interpreting Landsat data, high-resolution aerial photographs, and other ancillary data. The reference sample of nearly 25,000 pixels and the accompanying 33-year time series of annual land cover reference labels allowed for a comprehensive assessment of accuracy of the LCMAP land cover and land cover change products. Overall accuracy (± standard error) for the per-pixel assessment across all years for the eight land cover classes was 82.5% (±0.2%). Overall accuracy was consistent year-to-year within a range of 1.5% but varied regionally with lower accuracy in the eastern United States. User’s accuracy (UA) and producer’s accuracy (PA) for CONUS ranged from the higher accuracies of Water (UA=96%, PA=93%) and Tree Cover (UA=90%, PA=83%) to the lower accuracies of Wetland (UA=69%, PA=74%) and Barren (UA=43%, PA=57%). For a binary change / no change classification, UA of change was 13% (±0.5%) and PA was 16% (±0.6%) for CONUS when agreement was defined as a match by the exact year of change. UA and PA improved to 28% and 34% when agreement was defined as the change being detected by the map and reference data within a ±2-year window. Change accuracy was higher in the eastern United States compared to the western US. UA was 49% (±0.3) and PA was 54% (±0.3) for the footprint of change (defined as the area experiencing at least one land cover change from 1985–2017). For class-specific loss and gain when agreement was defined as an exact year match, UA and PA were generally below 30%, with Tree Cover loss being the most accurately mapped change (UA=25%, PA=31%). These accuracy results provide users with information to assess the suitability of LCMAP data and information to guide future research for improving LCMAP products, particularly focusing on the challenges of accurately mapping annual land cover change.

Remote Sensing of Environment↗
USGS2013

Conceptualizing and communicating ecological river restoration

We present a general conceptual model for communicating aspects of river restoration and management. The model is generic and adaptable to most riverine settings, independent of size. The model has separate categories of natural and social-economic drivers, and management actions are envisioned as modifiers of naturally dynamic systems. The model includes a decision-making structure in which managers, stakeholders, and scientists interact to define management objectives and performance evaluation. The model depicts a stress to the riverine ecosystem as either (1) deviation in the regimes (flow, sediment, temperature, light, biogeochemical, and genetic) by altering the frequency, magnitude, duration, timing, or rate of change of the fluxes or (2) imposition of a hard structural constraint on channel form. Restoration is depicted as naturalization of those regimes or removal of the constraint. The model recognizes the importance of river history in conditioning future responses. Three hierarchical tiers of essential ecosystem characteristics (EECs) illustrate how management actions typically propagate through physical/chemical processes to habitat to biotic responses. Uncertainty and expense in modeling or measuring responses increase in moving from tiers 1 to 3. Social-economic characteristics are shown in a parallel structure that emphasizes the need to quantify trade-offs between ecological and social-economic systems. Performance measures for EECs are also hierarchical, showing that selection of measures depend on participants’ willingness to accept uncertainty. The general form is of an adaptive management loop in which the performance measures are compared to reference conditions or success criteria and the information is fed back into the decision-making process.

Book chapter↗
USGS2026

Drift and dispersion of silver carp (Hypophthalmichthys molitrix) eggs and larvae for hypothetical spawning scenarios in the Upper Mississippi River

Invasive carp pose ecological and economic risks to North American freshwater systems. This study uses the Fluvial Egg Drift Simulator to model the drift of invasive silver carp ( Hypophthalmichthys molitrix) eggs and larvae after hypothetical spawning in Pools 1–10 of the Upper Mississippi River. Although adult invasive carps have been detected in this region, no reproduction has been confirmed as of this publication. A total of 450 spawning scenarios were simulated, representing 5 water temperatures, 9 flows, and 10 spawning locations in the tailwaters of lock and dam structures. The study examined egg and larval positions at two key developmental stages: hatching and gas bladder inflation, when larvae seek nursery habitat. Under a wide variety of flow conditions and water temperatures, eggs spawned upstream from Lake Pepin (Pool 4) are likely to settle in the lake before hatching, possibly increasing mortality rates. Eggs that survive passage through Lake Pepin reach gas bladder inflation within the study area, except in scenarios with lower temperatures and higher flows. Conversely, larvae spawned downstream from Lake Pepin generally drift out of the study area before reaching gas bladder inflation, except in cases of higher temperatures and lower flows. These findings inform ichthyoplankton sampling strategies and management actions aimed at reducing invasive carp populations in areas likely to support recruitment.

Iowa, Minnesota, Wisconsin↗
USGS2016

The Maryland Coastal Plain Aquifer Information System: A GIS-based tool for assessing groundwater resources

Groundwater is the source of drinking water for ∼1.4 million people in the Coastal Plain Province of Maryland (USA). In addition, groundwater is essential for commercial, industrial, and agricultural uses. Approximately 0.757 × 109 L d –1 (200 million gallons/d) were withdrawn in 2010. As a result of decades of withdrawals from the coastal plain confined aquifers, groundwater levels have declined by as much as 70 m (230 ft) from estimated prepumping levels. Other issues posing challenges to long-term groundwater sustainability include degraded water quality from both man-made and natural sources, reduced stream base flow, land subsidence, and changing recharge patterns (drought) caused by climate change. In Maryland, groundwater supply is managed primarily by the Maryland Department of the Environment, which seeks to balance reasonable use of the resource with long-term sustainability. The chief goal of groundwater management in Maryland is to ensure safe and adequate supplies for all current and future users through the implementation of appropriate usage, planning, and conservation policies. To assist in that effort, the geographic information system (GIS)–based Maryland Coastal Plain Aquifer Information System was developed as a tool to help water managers access and visualize groundwater data for use in the evaluation of groundwater allocation and use permits. The system, contained within an ESRI ArcMap desktop environment, includes both interpreted and basic data for 16 aquifers and 14 confining units. Data map layers include aquifer and ­confining unit layer surfaces, aquifer extents, borehole information, hydraulic properties, time-series groundwater-level data, well records, and geophysical and lithologic logs. The aquifer and confining unit layer surfaces were generated specifically for the GIS system. The system also contains select groundwater-quality data and map layers that quantify groundwater and surface-water withdrawals. The aquifer information system can serve as a pre- and postprocessing environment for groundwater-flow models for use in water-supply planning, development, and management. The system also can be expanded to include features that evaluate constraints to groundwater development, such as insufficient available drawdown, degraded groundwater quality, insufficient aquifer yields, and well-field interference. Ultimately, the aquifer information system is intended to function as an interactive Web-based utility that provides a broad array of information related to groundwater resources in Maryland’s coastal plain to a wide-ranging audience, including well drillers, consultants, academia, and the general public.

Special Paper of the Geological Society of America↗
USGS2020

Spatial variability in seasonal snowpack trends across the Rio Grande headwaters (1984 - 2017)

This study evaluated the spatial variability of trends in simulated snowpack properties across the Rio Grande headwaters of Colorado using the SnowModel snow evolution modeling system. SnowModel simulations were performed using a grid resolution of 100 m and 3-hourly time step over a 34-yr period (1984–2017). Atmospheric forcing was provided by phase 2 of the North American Land Data Assimilation System, and the simulations accounted for temporal changes in forest canopy from bark beetle and wildfire disturbances. Annual summary values of simulated snowpack properties [snow metrics; e.g., peak snow water equivalent (SWE), snowmelt rate and timing, and snow sublimation] were used to compute trends across the domain. Trends in simulated snow metrics varied depending on elevation, aspect, and land cover. Statistically significant trends did not occur evenly within the basin, and some areas were more sensitive than others. In addition, there were distinct trend differences between the different snow metrics. Upward trends in mean winter air temperature were 0.3°C decade −1 , and downward trends in winter precipitation were −52 mm decade −1 . Middle elevation zones, coincident with the greatest volumetric snow water storage, exhibited the greatest sensitivity to changes in peak SWE and snowmelt rate. Across the Rio Grande headwaters, snowmelt rates decreased by 20% decade −1 , peak SWE decreased by 14% decade −1 , and total snowmelt quantity decreased by 13% decade −1 . These snow trends are in general agreement with widespread snow declines that have been reported for this region. This study further quantifies these snow declines and provides trend information for additional snow variables across a greater spatial coverage at finer spatial resolution.

Colorado↗
USGS2021

Sources and risk factors for nitrate and microbial contamination of private household wells in the fractured dolomite aquifer of northeastern Wisconsin

Background: Groundwater quality in the Silurian dolomite aquifer in northeastern Wisconsin, USA, has become contentious as dairy farms and exurban development expand. Objectives: We investigated private household wells in the region, determining the extent, sources, and risk factors of nitrate and microbial contamination. Methods: Total coliforms, Escherichia coli , and nitrate were evaluated by synoptic sampling during groundwater recharge and no-recharge periods. Additional seasonal sampling measured genetic markers of human and bovine fecal-associated microbes and enteric zoonotic pathogens. We constructed multivariable regression models of detection probability (log-binomial) and concentration (gamma) for each contaminant to identify risk factors related to land use, precipitation, hydrogeology, and well construction. Results: Total coliforms and nitrate were strongly associated with depth-to-bedrock at well sites and nearby agricultural land use, but not septic systems. Both human wastewater and cattle manure contributed to well contamination. Rotavirus group A, Cryptosporidium , and Salmonella were the most frequently detected pathogens. Wells positive for human fecal markers were associated with depth-to-groundwater and number of septic system drainfield within 229 m "> 229 m 229m . Manure-contaminated wells were associated with groundwater recharge and the area size of nearby agricultural land. Wells positive for any fecal-associated microbe, regardless of source, were associated with septic system density and manure storage proximity modified by bedrock depth. Well construction was generally not related to contamination, indicating land use, groundwater recharge, and bedrock depth were the most important risk factors. Discussion: These findings may inform policies to minimize contamination of the Silurian dolomite aquifer, a major water supply for the U.S. and Canadian Great Lakes region.

Wisconsin↗