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At least 739 records · Page 41Linked to original sources
USGS2024

U.S. Geological Survey Grand Canyon Monitoring and Research Center: Proceedings of the fiscal year 2023 annual reporting meeting to the Glen Canyon Dam Adaptive Management Program

This proceedings is prepared for the USBR and Glen Canyon Dam Adaptive Management Program (GCDAMP) to account for work conducted and products delivered in FY 2023 by SBSC's Grand Canyon Monitoring and Research Center (GCMRC) and to inform the Technical Work Group of science conducted by GCMRC and its cooperators in support of the GCDAMP. It includes a summary of accomplishments, modifications to work plans, and results related to projects included in GCMRC’s FY 2021-23 Triennial Work Plan. This work was done to support the 11 resource goals identified in the Glen Canyon Dam Long-Term Experimental and Management Plan (LTEMP) Environmental Impact Statement and Record of Decision.

Arizona, Nevada, Utah↗
USGS2023

Mapping habitats and shorelines pre-, during, and post-restoration on Caminada Headland and Whiskey Island, Louisiana, 2012–2020

Barrier islands and headlands provide ecological services that are integral to economic and environmental interests. Adaptive management may help in ensuring their resilience and the continued provision of ecosystems goods and services over time. The dynamic nature of these environments makes evaluating the impacts from restoration and extreme events an important part of adaptively managing these resources.

Louisiana↗
USGS2025

Identifying strategies to manage boreal forests: Simulating moose and timber management scenarios at a landscape scale in the face of changing environmental conditions

There are ongoing debates among different stakeholders about which forest and ungulate management strategies will sustain high levels of timber and animal harvest and maintain important ecosystem functions under climate change. Ungulate-forest interactions are complex, including periods where forest regeneration is sensitive to browsing pressure, making it difficult to predict the consequences of a given strategy over time. To aid decision-making, we simulated the impacts of moose browsing on forest succession under 18 different combinations of moose ( Alces alces ) harvest rate levels and forest management scenarios in a boreal forest landscape in southern Sweden given projected changes in forest growth due to climate change. We found that the current management practices are important for sustaining a moose-forest system. Increasing moose harvest rates led to slightly smaller moose populations, larger estimates of landscape carrying capacity, and less biomass removal of Scots pine ( Pinus sylvestris ), a commercially valuable species. However, minor changes in the moose harvest were hardly affecting timber production. Increasing the timber harvest rotation time led to the highest estimates of Scots pine biomass, while thinning younger cohorts lead to the highest estimates of Norway spruce ( Picea abies ) biomass. These changes came without much effect to moose population dynamics. However, the increased broadleaf production scenario had a very large positive effect on total aboveground live biomass of deciduous species and on landscape carrying capacity and moose density. This scenario subsequently resulted in the greatest estimates of biomass removal of Scots pine, highlighting the tradeoffs associated with increased moose production.

European Journal of Forest Research↗
USGS2025

Climate consideration in environmental effects analyses on federal public lands in the United States

Effects of a changing climate, including drought, wildfire, and invasive species encroachment, are evident on public lands across the United States. Decision making on Federal public lands requires analyses under the National Environmental Policy Act (NEPA), and there are guidelines for considering climate in NEPA analyses. To better understand how climate most recently has been considered, we analyzed a stratified random sample of 130 environmental assessments (EAs) completed by the Bureau of Land Management (BLM) from 2021 to 2023 across the contiguous United States. We assessed whether EAs considered (1) potential effects of the proposed action on climate (2) potential climate effects on the proposed action, and (3) potential climate effects on resources of concern. We also identified whether EAs included data and science about climate or greenhouse gas emissions, and which datasets and documents were cited. We used two approaches: automated keyword searches and document analysis. Thirty-seven percent of EAs considered the potential effects of the proposed action on climate, 8% considered the potential effects of climate on the proposed action, and 4% of individual resource analyses considered the potential effects of climate on the resource. EAs in the ‘oil and gas development,’ ‘renewable energy,’ and ‘forestry and timber management’ proposed action categories most frequently considered the potential effects of climate and used climate data and science. Our findings suggest an opportunity for scientists to work more closely with public land managers to identify available data and science for considering climate in environmental effects analyses and to provide science delivery mechanisms that can facilitate the consideration and use of climate science in decision making.

Environmental Management↗
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↗