USGS Science⌕ Search

SEARCH · USGS Science

Results for “Environmental Management”

Search indexed USGS publications on groundwater, aquifers, geologic maps, mineral resources and earthquakes. Explore source records by subject and place.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 703 records · Page 39Linked to original sources
USGS2018

Prioritization framework for ranking riverine ecosystem stressors using example sites from the Tualatin River Basin, Oregon

As human populations increase, so does their influence over the environment. Altered terrain, degraded water quality, and threatened or endangered species are all-too-common consequences of a growing anthropogenic influence on the landscape. To help manage these effects, researchers have developed new ways to characterize current environmental conditions and help resource managers seek solutions to bring affected areas back to their best attainable health. Before an ecosystem can be improved, however, its current level of ecological stress must be determined. Characterizing environmental conditions at many sites across a landscape helps managers understand the range of current conditions and prioritize where they might focus restoration and protection efforts. This report details the development of a prioritization framework to score riverine ecosystem stressors in a watershed based on example sites from the Tualatin River Basin in northwestern Oregon. The framework incorporated the most influential site-specific stressors throughout the basin built on a long history of data collection. These stressors were characterized with 13 metrics that were organized into 4 groups: hydrologic, water quality, physical habitat, and biological. Each stressor metric used readily accessible data and was translated to a score between 0 and 10. The higher the score, the healthier the site. This initial application of the framework used field observations and measurements to rank site conditions at two Tualatin River sites and four Tualatin River tributary sites. Given the versatility of this framework, it easily could be expanded to include more sites or new metrics, if necessary. Because stressors varied by season, all metrics for the tributary sites were scored separately during the wet season (November through April) and dry season (May through October). Water-quality data were available over a prolonged period; therefore, water-quality metrics were assessed by season and by decade (1990–99 compared to 2000–12) to evaluate long-term stressor trends. Results for the Tualatin River Basin prioritization framework indicated that the urban tributaries demonstrated the greatest stress throughout the year, especially during the dry summer months. Spatially, the upper Tualatin River was healthier than the lower reaches of the river. Water-quality has improved in the last 10 years, mostly due to improvements in the dry period contaminant scores, but challenges remain with high water temperatures and low dissolved-oxygen conditions. The biggest challenge with this type of research derived from inconsistencies within the available data. Both spatial and temporal data gaps must be addressed to improve the prioritization. Incorporating both discrete and continuous datasets into the prioritization framework remains a challenge because the datasets have slightly different information and criteria and are not always comparable. Regardless, this report provides guidelines for developing a prioritization framework that ranks the ecological health of sites in a watershed and provides guidance on management actions for improving conditions by targeting factors that greatly affect the health of river ecosystems.

Oregon↗
USGS1988

Land cover mapping of the upper Kuskokwim Resource Managment Area using LANDSAT and a digital data base approach

Digital land cover and terrain data for the Upper Kuskokwim Resource Hanagement Area (UKRMA) were produced by the U.S. Geological Survey, Earth Resources Observation Systems Field Office, Anchorage, Alaska for the Bureau of Land Management. These and other environmental data, were incorporated into a digital data base to assist in the management and planning of the UKRMA. The digital data base includes land cover classifications, elevation, slope, and aspect data centering on the UKRMA boundaries. The data are stored on computer compatible tapes at a 50-m pixel size. Additional digital data in the data base include: (a) summer and winter Landsat multispectral scanner (MSS) data registered to a 50-m Universal Transverse Mercator grid; (b) elevation, slope, aspect, and solar illumination data; (c) soils and surficial geology; and (e) study area boundary. The classification of Landsat MSS data resulted in seven major classes and 24 subclasses. Major classes include: forest, shrubland, dwarf scrub, herbaceous, barren, water, and other. The final data base will be used by resource personnel for management and planning within the UKRMA.

Alaska↗
USGS2020

Development and testing of species-specific quantitative PCR assays for environmental DNA applications

New, non-invasive methods for detecting and monitoring species presence are being developed to aid in fisheries and wildlife conservation management. The use of environmental DNA (eDNA) samples for detecting macrobiota is one such group of methods that is rapidly becoming popular and being implemented in national management programs. Here we focus on the development of species-specific targeted assays for probe-based quantitative PCR (qPCR) applications. Using probe-based qPCR offers greater specificity than is possible with primers alone. Furthermore, the ability to quantify the amount of DNA in a sample can be useful in our understanding of the ecology of eDNA and the interpretation of eDNA detection patterns in the field. Careful consideration is needed in the development and testing of these assays to ensure the sensitivity and specificity of detecting the target species from an environmental sample. In this protocol we will delineate the steps needed to design and test probe-based assays for the detection of a target species; including creation of sequence databases, assay design, assay selection and optimization, testing assay performance, and field validation. Following these steps will help achieve an efficient, sensitive, and specific assay that can be used with confidence. We demonstrate this process with our assay designed for populations of the mucket ( Actinonaias ligamentina ), a freshwater mussel species found in the Clinch River, USA.

JOVE Journal Of Visualized Experiments↗
USGS2009

Planning for an uncertain future - Monitoring, integration, and adaptation

The 6.7 billion human inhabitants of the earth have the ability to drastically alter ecosystems and the populations of species that have taken eons to evolve. By better understanding how our actions affect the environment, we stand a better chance of designing successful strategies to manage ecosystems sustainably. Toward this end, the Third Interagency Conference on Research in the Watersheds (ICRW) was convened in Estes Park, CO, on September 8-11, 2008. The Conference provided a forum to present adaptive management as a practical tool for learning how to manage complex ecosystems more sustainably. Further complexity introduced by spatially variable and continuously changing environmental drivers favors this management approach because of its emphasis on adaptation in response to changing conditions or ineffective actions. For climate change in particular, an adaptive approach can more effectively accommodate the uncertainty in future climate scenarios. Scenarios compiled by the Intergovernmental Panel on Climate Change are built on distinct economic, energy, and societal models. The scenarios predict potential changes in greenhouse gases, temperature, precipitation, and atmospheric aerosols, which would have direct or indirect impacts on the timing, volume, and quality of runoff, vegetation, snowpack, stream temperature, groundwater, thawing permafrost, and icecaps. Through presentations and field trips, researchers and stakeholders described how their findings and issues fit into the adaptive management 'learning by doing' paradigm of Assess > Design > Implement > Monitor > Evaluate > Adjust > Assess.

Scientific Investigations Report↗
USGS2020

A round-robin evaluation of the repeatability and reproducibility of environmental DNA assays for dreissenid mussels

Resource managers may be hesitant to make decisions based on environmental (e)DNA results alone since eDNA is an indirect method of species detection. One way to reduce the uncertainty of eDNA is to identify laboratory‐based protocols that ensure repeatable and reproducible results. We conducted a double‐blind round‐robin analysis of probe‐based assays for DNA of dreissenid ( Dreissena spp.) mussels, which are prolific aquatic invaders that can cause significant economic and ecological impacts. DNA extract from water samples spiked with known amounts of dreissenid DNA and from water samples collected from waters with and without dreissenids were analyzed by four independent research laboratories. We used results to calculate detection repeatability within laboratories and assays, detection reproducibility among laboratories and assays, and estimated dreissenid DNA copy number precision and accuracy. Laboratory and assay repeatability and reproducibility of detection results were high, 91% and 92%, respectively. The estimated copy numbers were neither precise nor accurate for samples spiked with <773 gene copies. These results suggest that eDNA surveillance of dreissenid mussels, using the protocols evaluated herein, can generate reliable detection data for decision‐making. However, managers should be cautious about using the quantitative information often associated with eDNA detections, especially when DNA is at lower abundance. Our results provide strong support that eDNA has the potential to provide repeatable and reproducible evidence under varying laboratory conditions and for different sample water chemistries. This is reassuring since the demand for eDNA surveillance is widespread and number of laboratories that process eDNA samples is growing steadily.

California, Montana, Nevada, New York, Oregon, Was↗
USGS2019

Toward sustainable environmental quality: Priority research questions for North America

Anticipating, identifying, and prioritizing strategic needs represent essential activities by research organizations. Decided benefits emerge when these pursuits engage globally important environment and health goals, including the United Nations Sustainable Development Goals. To this end, horizon scanning efforts can facilitate identification of specific research needs to address grand challenges. We report and discuss 40 priority research questions following engagement of scientists and engineers in North America. These timely questions identify the importance of stimulating innovation and developing new methods, tools, and concepts in environmental chemistry and toxicology to improve assessment and management of chemical contaminants and other diverse environmental stressors. Grand challenges to achieving sustainable management of the environment are becoming increasingly complex and structured by global megatrends, which collectively challenge existing sustainable environmental quality efforts. Transdisciplinary, systems‐based approaches will be required to define and avoid adverse biological effects across temporal and spatial gradients. Similarly, coordinated research activities among organizations within and among countries are necessary to address the priority research needs reported here. Acquiring answers to these 40 research questions will not be trivial, but doing so promises to advance sustainable environmental quality in the 21st century.

Environmental Toxicology and Chemistry↗
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&mdash;either naturally occurring or injected as a method to enhance production&mdash;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↗