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At least 703 records · Page 39Linked to original sources
USGS2014

USGS investigations of water produced during hydrocarbon reservoir development

Significant quantities of water are present in hydrocarbon reservoirs. When brought to the land surface during oil, gas, and coalbed methane production, the water—either naturally occurring or injected as a method to enhance production—is termed produced water. Produced water is currently managed through processes such as recycling, treatment and discharge, spreading on roads, evaporation or infiltration, and deep well injection. U.S. Geological Survey (USGS) scientists conduct research and publish data related to produced water, thus providing information and insight to scientists, decisionmakers, the energy industry, and the public. The information advances scientific knowledge, informs resource management decisions, and facilitates environmental protection. This fact sheet discusses integrated research being conducted by USGS scientists supported by programs in the Energy and Minerals and Environmental Health Mission Areas. The research products help inform decisions pertaining to understanding the nature and management of produced water in the United States.

Fact Sheet↗
USGS2024

The potential of remote sensing for improved infectious disease ecology research and practice

Outbreaks of Covid-19 in humans, Dutch elm disease in forests, and highly pathogenic avian influenza in wild birds and poultry highlight the disruptive impacts of emerging infectious diseases on public health, ecosystems, and economies. Infectious disease dynamics often depend on environmental conditions that drive occurrence, transmission, and outbreaks. Remote sensing can contribute to infectious disease research and management by providing standardized environmental data across broad spatial and temporal extents, often at no cost to the user. Here, we 1) conduct a systematic review of primary literature to quantify current uses of remote sensing in disease ecology and 2) synthesize qualitative information to identify opportunities for further integration of remote sensing into disease ecology. We identify that modern advances in airborne remote sensing are promoting early detection of forest pathogens and that satellite data is contributing to the study of geographically widespread human diseases. We discuss opportunities for increased use of data products that characterize vegetation, surface water, and soil; provide data at high spatio-temporal and spectral resolutions; and quantify uncertainty in measurements. Additionally, combining remote sensing with animal movement telemetry can provide novel insights into wildlife disease. Integrating these opportunities will advance research and management of infectious diseases.

Proceedings of the Royal Society B: Biological Sci↗
USGS2020

Using NASA Earth observations and Google Earth Engine to map winter cover crop conservation performance in the Chesapeake Bay watershed

Winter cover crops such as barley, rye, and wheat help to improve soil structure by increasing porosity, aggregate stability, and organic matter, while reducing the loss of agricultural nutrients and sediments into waterways. The environmental performance of cover crops is affected by choice of species, planting date, planting method, nutrient inputs, temperature, and precipitation. The Maryland Department of Agriculture (MDA) oversees an agricultural cost-share program that provides farmers with funding to cover costs associated with planting winter cover crops, and the U.S. Geological Survey (USGS) and the U.S. Department of Agriculture-Agricultural Research Service (USDA-ARS) have partnered with the MDA to develop satellite remote sensing techniques for measuring cover crop performance. The MDA has developed the capacity to digitize field boundaries for all fields enrolled in their cover crop programs (>26,000 fields per year) to support a remote sensing performance analysis at a statewide scal,e and has requested assistance with the associated imagery processing from the National Aeronautics and Space Administration (NASA). Using the Google Earth Engine (GEE) cloud computing platform, scripts were developed to process Landsat 5/7/8 and Harmonized Sentinel-2 imagery to measure winter cover crop performance. We calibrated cover crop performance models using linear regression between satellite vegetation indices and USGS / USDA-ARS field sampling data collected on Maryland farms between 2006 and 2012 (1298 samples). Satellite-derived Normalized Difference Vegetation Index (NDVI) values showed significant correlation with the natural logarithm of cover crop biomass ( p ≤0.01, R 2 = 0.56) and with observed percent vegetative ground cover (p ≤0.01, R 2 = 0.68). The GEE scripts were used to composite seasonal maximum NDVI values for each enrolled cover crop field and calculate performance metrics for the winter and spring seasons of three enrollment years (2014–15, 2015–16, and 2017–18) for four Maryland counties. Results from winter 2017–18 demonstrate that rye and barley fields had higher biomass than wheat fields, and that early planting, along with planting methods that increase seed-soil contact, increased performance. The processing capabilities of GEE will support the MDA in scaling up remote sensing performance analysis statewide, providing information to evaluate the environmental outcomes associated with various agronomic management strategies. The tool can be modified for different seasonal cutoffs, utilize new sensors to capture phenology in winter and spring, and scale to larger regions for use in adaptive management of winter cover crops planted for environmental benefit.

Maryland↗
USGS2022

Resisting ecosystem transformation through an intensive whole-lake fish removal experiment

Lake ecosystems are shifting due to many drivers including climate change and landscape-scale habitat disturbance, diminishing their potential to support some fisheries. Walleye Sander vitreus (Mitchill) populations, which support recreational and tribal fisheries across North America, have declined in some lakes. Climate change, harvest, invasive species and concurrent increases in warm-water fishes (e.g. Centrarchidae) may have contributed to declines. To test the utility of an intensive management action to resist walleye loss, an experimental removal of ~285,000 centrarchids from a 33-ha lake over 4 years was conducted while monitoring the fish community response. Centrarchid abundance declined and yellow perch Perca flavescens (Mitchill) increased, yet no evidence of walleye recruitment was observed. These findings explore the feasibility of intensive resistance as a management strategy in supporting walleye facing environmental change and provide a platform for management discussions to move beyond resist strategies in the Resist-Accept-Direct (RAD) framework to navigate ecosystem change.

Fisheries Management and Ecology↗
USGS2009

Climate alters response of an endemic island plant to removal of invasive herbivores

Islands experience higher rates of species extinction than mainland ecosystems, with biological invasions among the leading causes; they also serve as important model systems for testing ideas in basic and applied ecology. Invasive removal programs on islands are conservation efforts that can also be viewed as powerful manipulative experiments, but few data are available to evaluate their effects. We collected demographic and herbivore damage data for Castilleja mollis Pennell, an endangered plant endemic to Santa Rosa Island, California, over a 12-year period before, during, and after the implementation of control for introduced cattle, deer, and elk. We used these long-term data to explore mechanisms underlying herbivore effects, assess the results of herbivore reduction at the scales of both individual plants and populations, and determine how temporal variability in herbivory and plant demography influenced responses to herbivore removals. For individual plants, herbivore effects mediated by disturbance were greater than those of grazing. Deer and elk scraping of the ground substantially increased plant mortality and dormancy and reduced flowering and growth. Stem damage from browsing did not affect survivorship but significantly reduced plant growth and flower production. Herbivore control successfully lowered damage rates, which declined steeply between 1997 and 2000 and have remained relatively low. Castilleja mollis abundances rose sharply after 1997, suggesting a positive effect of herbivore control, but then began to decline steadily again after 2003. The recent decline appears to be driven by higher mean growing season temperatures; interestingly, not only reductions in scraping damage but a period of cooler conditions were significant in explaining increases in C. mollis populations between 1997 and 2002. Our results demonstrate strong effects of introduced herbivores on both plant demography and population dynamics and show that climate-driven variation may counteract and mask positive responses to herbivore removal. Regional mean temperatures already have risen significantly over the last 50 years, suggesting that climate change could increasingly swamp the effects of management targeted at other environmental problems. Similar interactions between climate and invasive species will play an even greater role in future management, with long-term data sets like this critical to quantifying such effects. ?? 2009 by the Ecological Society of America.

Ecological Applications↗
USGS2009

The Water Availability Tool for Environmental Resources (WATER): A water-budget modeling approach for managing water-supply resources in non-karst areas of Kentucky (phase I) — Data processing and model structure documentstion

The Water Availability Tool for Environmental Resources (WATER) was developed in cooperation with the Kentucky Division of Water to provide a consistent and defensible method of estimating streamflow and water availability in ungaged basins. WATER is process oriented; it is based on the TOPMODEL code and incorporates historical water-use data together with physiographic data that quantitatively describe topography and soil-water storage. The result is a user-friendly decision tool that can estimate water availability in non-karst areas of Kentucky without additional data or processing. The model runs on a daily time step, and critical source data include a historical record of daily temperature and precipitation, digital elevation models (DEMs), the Soil Survey Geographic Database (SSURGO), and historical records of water discharges and withdrawals. The model was calibrated and statistically evaluated for 12 basins by comparing the estimated discharge to that observed at U.S. Geological Survey streamflow-gaging stations. When statistically evaluated over a 2,119-day time period, the discharge estimates showed a bias of -0.29 to 0.42, a root mean square error of 1.66 to 5.06, a correlation of 0.54 to 0.85, and a Nash-Sutcliffe Efficiency of 0.26 to 0.72. The parameter and input modifications that most significantly improved the accuracy and precision of streamflow-discharge estimates were the addition of Next Generation radar (NEXRAD) precipitation data, a rooting depth of 30 centimeters, and a TOPMODEL scaling parameter (m) derived directly from SSURGO data that was multiplied by an adjustment factor of 0.10. No site-specific optimization was used.

Kentucky↗
USGS2022

Using structured decision making to evaluate potential management responses to detection of dreissenid mussel (Dreissena spp.) environmental DNA

Environmental (e)DNA tools are sensitive and cost-effective for early detection of invasive species. However, the uncertainty associated with the interpretation of positive eDNA detections makes it challenging to determine appropriate natural resource management responses. Multiple sources of error can give rise to positive detections of eDNA in a sample when individuals of that species are not present at the site or a widespread infestation is not imminent. Acting on an erroneous eDNA inference could result in needless costs or reductions in desirable resources. Alternatively, failure to rapidly act on eDNA results that truly indicate invader presence could compound negative impacts and lead to high, long-term costs to manage infestations. We used a structured decision making (SDM) process, which incorporates tradeoffs and uncertainties, to evaluate appropriate response actions following hypothetical eDNA detections of invasive dreissenid mussel ( Dreissena spp.) eDNA in Jordanelle Reservoir, Utah (USA). We worked with decision-makers and stakeholders to identify objectives and discrete management action alternatives to assess consequences and tradeoffs. Alternatives ranged from no action to intensive and expensive control efforts. The best performing alternative was delayed containment described by immediate attempts to confirm the eDNA detections using non-molecular sampling techniques followed by mandatory watercraft exit inspections to prevent dreissenid mussel spread to regional water bodies. Non-molecular sampling increased public support for management by demonstrating a commitment to monitor the invasion state before action, whereas containment decreased likelihood of regional spread to other waters. Delayed containment had the lowest downside risk, and the highest upside gains relative to other alternative actions. Sensitivity analyses showed our results to be robust to parameter and outcome uncertainty.

Management of Biological Invasions↗
USGS2022

Both real-time and long-term environmental data perform well in predicting shorebird distributions in managed habitat

Highly mobile species, such as migratory birds, respond to seasonal and inter-annual variability in resource availability by moving to better habitats. Despite the recognized importance of resource thresholds, species distribution models typically rely on long-term average habitat conditions, mostly because large-extent, temporally-resolved, environmental data are difficult to obtain. Recent advances in remote sensing make it possible to incorporate more frequent measurements of changing landscapes; however, there is often a cost in terms of model building and processing and the added value of such efforts is unknown. Our study tests whether incorporating real-time environmental data increases the predictive ability of distribution models, relative to using long-term average data. We developed and compared distribution models for shorebirds in California's Central Valley based on high temporal resolution (every 16-days), and 17-year long-term average, surface water data. Using abundance-weighted boosted regression trees, we modeled monthly shorebird occurrence as a function of surface water availability, crop type, wetland type, road density, temperature, and bird data source. While modeling with both real-time and long-term average data provided good fit to withheld validation data (0.79 < AUC < 0.89 across taxa), there were small differences in model performance. The best models incorporated long-term average conditions and spatial pattern information for real-time flooding (e.g. perimeter-area ratio of real-time water bodies). There was not a substantial difference in the performance of real-time and long-term average data models within time periods when real-time surface water differed substantially from the long-term average (specifically during drought years 2013-2016) and in intermittently flooded months or locations. Spatial predictions resulting from the models differed most in the southern region of the study area where there is lower water availability, fewer birds, and lower sampling density. Prediction uncertainty in the southern region of the study area highlights the need for increased sampling in this area. Because both sets of data performed similarly, the choice of which data to use may depend on the management context. Real-time data may ultimately be best for guiding dynamic, adaptive conservation actions whereas models based on long-term averages may be more helpful for guiding permanent wetland protection and restoration.

Ecological Applications↗
USGS2001

Identifying determinants of nations' wetland management programs using structural equation modeling: An exploratory analysis

Integrated management and policy models suggest that solutions to environmental issues may be linked to the socioeconomic and political Characteristics of a nation. In this study, we empirically explore these suggestions by applying them to the wetland management activities of nations. Structural equation modeling was used to evaluate a model of national wetland management effort and one of national wetland protection. Using five predictor variables of social capital, economic capital, environmental and political characteristics, and land-use pressure, the multivariate models were able to explain 60% of the variation in nations' wetland protection efforts based on data from 90 nations, as defined by level of participation, in the international wetland convention. Social capital had the largest direct effect on wetland protection efforts, suggesting that increased social development may eventually lead to better wetland protection. In contrast, increasing economic development had a negative linear relationship with wetland protection efforts, suggesting the need for explicit wetland protection programs as nations continue to focus on economic development. Government, environmental characteristics, and land-use pressure also had a positive direct effect on wetland protection, and mediated the effect of social capital on wetland protection. Explicit wetland protection policies, combined with a focus on social development, would lead to better wetland protection at the national level.

Environmental Management↗
USGS2006

USGS environmental characterization of flood sediments left in the New Orleans area after Hurricanes Katrina and Rita, 2005 — Progress Report

Introduction: The flooding in the greater New Orleans area that resulted from Hurricanes Katrina and Rita in September, 2005, left behind accumulations of sediments up to many centimeters thick on streets, lawns, parking lots, and other flat surfaces. These flood sediment deposits have been the focus of extensive study by the US Environmental Protection Agency (EPA) and Louisiana Department of Environmental Quality (LDEQ) due to concerns that the sediments may contain elevated levels of heavy metals, organic contaminants, and microbes. The U.S. Geological Survey (USGS) is characterizing a limited number of flood sediment samples that were collected on September 15-16 and October 6-7, 2005, from the greater New Orleans area by personnel from the USGS Louisiana Water Science Center in Baton Rouge. Small samples (< 3 pints each) of wet to dry flood sediment were collected from 11 localities around downtown New Orleans on September 15, 2005, and two large samples (40 pints each) of wet flood sediment were collected from the Chalmette area on September 16. Twelve additional samples (8-10 pints each) were collected from New Orleans, Slidell, Rigolets, and Violet on October 6 and 7. The USGS characterization studies of these flood sediments are designed to produce data and interpretations regarding how the sediments and any contained contaminants may respond to environmental processes. This information will be of use to cleanup managers and DoI/USGS scientists assessing environmental impacts of the hurricanes and subsequent cleanup activities.

Louisiana↗
USGS2019

Seed bank community and soil texture relationships in a cold desert

Sustainable dryland management depends on understanding environmental factors driving composition of current and future ecological communities. While there has been extensive research on aboveground plant communities, less is known about belowground soil seed bank communities, which can reflect both past and potential future communities. In the Colorado Plateau of the western United States, we explored aboveground and belowground plant communities and how they varied across sites with similar climate but contrasting soil textures. We found that aboveground vegetation and belowground seed bank community composition each varied significantly among sites. However, we also observed marked aboveground-belowground compositional dissimilarity across sites, suggesting that the two spatially-associated communities may respond differently to the same environmental gradient. Lastly, we found that cheatgrass seed prevalence (Bromus tectorum) – one of the region’s major exotic invasive plants – varied strongly by soil texture, a finding with potential implications for invasive species management. From our research findings, we highlight two general patterns for dryland managers. Firstly, we show aboveground and belowground plant communities will not always respond to the same environmental changes in a coordinated manner. Secondly, the data underscore a large potential role for soil texture in mediating the plant community responses to other environmental factors.

Utah↗
USGS2026

Quantifying avian resilience to habitat change to support conservation decision-making

Habitat loss and degradation are two of the main drivers of contemporary avian population declines. Wildlife managers are increasingly advocating for tools that provide decision support to set priorities for restoration or conservation efficiently. We demonstrate how to derive two species-specific management and resilience metrics: the greatest management impact point (GMIP) and the ecological resilience threshold (RT). The GMIP indicates the amount of environmental change in a landscape where habitat improvements are expected to have the greatest impact on species’ occurrence. The RT represents the amount of environmental change in a landscape that a species can tolerate before the steepest change in occupancy is expected to begin. We estimate species-specific metrics using the amount of uncharacteristic exotic vegetation as an index of environmental change, and demonstrate how multispecies patterns may suggest potential management strategies. We estimated occupancy models using 5 years of multispecies avian detection data from the Integrated Monitoring in Bird Conservation Regions program in the State of Utah, USA (hereafter, Utah). Based on the estimated relationship between species’ occupancy and amounts of uncharacteristic exotic vegetation, we derive RT and GMIP scores for 61 species breeding in Utah. We found wide interspecific variation in resilience to amounts of exotic vegetation, with species generally clustering at extreme values. Our results demonstrate that birds in Utah appear more resilient to amounts of uncharacteristic exotic vegetation at coarser spatial resolution, showing greater variance and lower average RTs at finer spatial resolution. Species that are not fully resilient to the range of uncharacteristic exotic vegetation observed in this study are expected to respond most strongly, on average, to management actions in landscapes with high levels of exotic vegetation; however, early detection and rapid response is likely the most effective strategy. Quantified across many species, these metrics can be used to identify and prioritize landscapes where current environmental conditions could be maintained to avoid the greatest species’ declines, or which maximize expected biodiversity returns on investment in environmental restoration. Managers can consider either focal species’ resilience for tailored conservation planning or summarize species resilience to create efficient management plans that maximize outcomes for multiple species.

Utah↗
USGS2012

Approaches in highly parameterized inversion-PESTCommander, a graphical user interface for file and run management across networks

Models of environmental systems have become increasingly complex, incorporating increasingly large numbers of parameters in an effort to represent physical processes on a scale approaching that at which they occur in nature. Consequently, the inverse problem of parameter estimation (specifically, model calibration) and subsequent uncertainty analysis have become increasingly computation-intensive endeavors. Fortunately, advances in computing have made computational power equivalent to that of dozens to hundreds of desktop computers accessible through a variety of alternate means: modelers have various possibilities, ranging from traditional Local Area Networks (LANs) to cloud computing. Commonly used parameter estimation software is well suited to take advantage of the availability of such increased computing power. Unfortunately, logistical issues become increasingly important as an increasing number and variety of computers are brought to bear on the inverse problem. To facilitate efficient access to disparate computer resources, the PESTCommander program documented herein has been developed to provide a Graphical User Interface (GUI) that facilitates the management of model files ("file management") and remote launching and termination of "slave" computers across a distributed network of computers ("run management"). In version 1.0 described here, PESTCommander can access and ascertain resources across traditional Windows LANs: however, the architecture of PESTCommander has been developed with the intent that future releases will be able to access computing resources (1) via trusted domains established in Wide Area Networks (WANs) in multiple remote locations and (2) via heterogeneous networks of Windows- and Unix-based operating systems. The design of PESTCommander also makes it suitable for extension to other computational resources, such as those that are available via cloud computing. Version 1.0 of PESTCommander was developed primarily to work with the parameter estimation software PEST; the discussion presented in this report focuses on the use of the PESTCommander together with Parallel PEST. However, PESTCommander can be used with a wide variety of programs and models that require management, distribution, and cleanup of files before or after model execution. In addition to its use with the Parallel PEST program suite, discussion is also included in this report regarding the use of PESTCommander with the Global Run Manager GENIE, which was developed simultaneously with PESTCommander.

Techniques and Methods↗
USGS2011

Application of neural networks to prediction of fish diversity and salmonid production in the Lake Ontario basin

Diversity and fish productivity are important measures of the health and status of aquatic systems. Being able to predict the values of these indices as a function of environmental variables would be valuable to management. Diversity and productivity have been related to environmental conditions by multiple linear regression and discriminant analysis, but such methods have several shortcomings. In an effort to predict fish species diversity and estimate salmonid production for streams in the eastern basin of Lake Ontario, I constructed neural networks and trained them on a data set containing abiotic information and either fish diversity or juvenile salmonid abundance. Twenty percent of the original data were retained as a test data set and used in the training. The ability to extend these neural networks to conditions throughout the streams was tested with data not involved in the network training. The resulting neural networks were able to predict the number of salmonids with more than 84% accuracy and diversity with more than 73% accuracy, which was far superior to the performance of multiple regression. The networks also identified the environmental variables with the greatest predictive power, namely, those describing water movement, stream size, and water chemistry. Thirteen input variables were used to predict diversity and 17 to predict salmonid abundance.

Transactions of the American Fisheries Society↗
USGS2011

Proceedings of the Klamath Basin Science Conference, Medford, Oregon, February 1-5, 2010

This report presents the proceedings of the Klamath Basin Science Conference (February 2010). A primary purpose of the meeting was to inform and update Klamath Basin stakeholders about areas of scientific progress and accomplishment during the last 5 years. Secondary conference objectives focused on the identification of outstanding information needs and science priorities as they relate to whole watershed management, restoration ecology, and possible reintroduction of Pacific salmon associated with the Klamath Basin Restoration Agreement (KBRA). Information presented in plenary, technical, breakout, and poster sessions has been assembled into chapters that reflect the organization, major themes, and content of the conference. Chapter 1 reviews the major environmental issues and resource management and other stakeholder needs of the basin. Importantly, this assessment of information needs included the possibility of large-scale restoration projects in the future and lessons learned from a case study in South Florida. Other chapters (2-6) summarize information about key components of the Klamath Basin, support conceptual modeling of the aquatic ecosystem (Chapter 7), and synthesize our impressions of the most pressing science priorities for management and restoration. A wealth of information was presented at the conference and this has been captured in chapters addressing environmental setting and human development of the basin, hydrology, watershed processes, fishery resources, and potential effects from climate change. The final chapter (8) culminates in a discussion of many specific research priorities that relate to and bookend the broader management needs and restoration goals identified in Chapter 1. In many instances, the conferees emphasized long-term and process-oriented approaches to watershed science in the basin as planning moves forward.

California, Oregon↗
USGS2013

Preliminary stratigraphic and hydrogeologic cross sections and seismic profile of the Floridan aquifer system of Broward County, Florida

To help water-resource managers evaluate the Floridan aquifer system (FAS) as an alternative water supply, the U.S. Geological Survey initiated a study, in cooperation with the Broward County Environmental Protection and Growth Management Department, to refine the hydrogeologic framework of the FAS in the eastern part of Broward County. This report presents three preliminary cross sections illustrating stratigraphy and hydrogeology in eastern Broward County as well as an interpreted seismic profile along one of the cross sections. Marker horizons were identified using borehole geophysical data and were initially used to perform well-to-well correlation. Core sample data were integrated with the borehole geophysical data to support stratigraphic and hydrogeologic interpretations of marker horizons. Stratigraphic and hydrogeologic units were correlated across the county using borehole geophysical data from multiple wells. Seismic-reflection data were collected along the Hillsboro Canal. Borehole geophysical data were used to identify and correlate hydrogeologic units in the seismic-reflection profile. Faults and collapse structures that intersect hydrogeologic units were also identified in the seismic profile. The information provided in the cross sections and the seismic profile is preliminary and subject to revision.

Florida↗
USGS1987

Arctic National Wildlife Refuge, Alaska, Coastal Plain Resource Assessment: Report and recommendation to the Congress of the United States and final legislative environmental impact statement

The Arctic National Wildlife Refuge, in the northeastern corner of Alaska, was first established as the Arctic National Wildlife Range by Public Land Order 2214 in 1960, for the purpose of preserving unique wildlife, wilderness, and recreational values. The original 8.9-millionacre Range was withdrawn from all forms of appropriation under the public land laws, including mining laws but not including mineral leasing laws. This order culminated extensive efforts begun more than a decade earlier to preserve this unique part of Alaska. The following report analyzes the potential environmental consequences of five management alternatives for the coastal plain, ranging from opening for lease of the entire area for oil and gas development, to wilderness designation. A legislative environmental impact statement has been integrated into the report.

Alaska↗