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At least 487 records · Page 27Linked to original sources
USGS2004

Summary of available state ambient stream-water-quality data, 1990-98, and limitations for national assessment

The investigation described in this report summarized data from State ambient stream-water-quality monitoring sites for 10 water-quality constituents or measurements (suspended solids, fecal coliform bacteria, ammonia as nitrogen, nitrite plus nitrate as nitrogen, total phosphorus, total arsenic, dissolved solids, chloride, sulfate, and pH). These 10 water-quality constituents or measurements commonly are listed nationally as major contributors to degradation of surface water. Water-quality data were limited to that electronically accessible from the U.S. Environmental Protection Agency Storage and Retrieval System (STORET), the U.S. Geological Survey National Water Information System (NWIS), or individual State databases. Forty-two States had ambient stream-water-quality data electronically accessible for some or all of the constituents or measurements summarized during this investigation. Ambient in this report refers to data collected for the purpose of evaluating stream ecosystems in relation to human health, environmental and ecological conditions, and designated uses. Generally, data were from monitoring sites assessed for State 305(b) reports. Comparisons of monitoring data among States are problematic for several reasons, including differences in the basic spatial design of monitoring networks; water-quality constituents for which samples are analyzed; water-quality criteria to which constituent concentrations are compared; quantity and comprehensiveness of water-quality data; sample collection, processing, and handling; analytical methods; temporal variability in sample collection; and quality-assurance practices. Large differences among the States in number of monitoring sites precluded a general assumption that statewide water-quality conditions were represented by data from these sites. Furthermore, data from individual monitoring sites may not represent water-quality conditions at the sites because sampling conditions and protocols are unknown. Because of these factors, a high level of uncertainty exists in a national assessment of water quality. The purpose of this report is to present a summary of electronically available State ambient stream-water-quality data for 10 selected constituents and measurements from monitoring sites with nine or more analyses for 199098 and to discuss limitations for use of the data for national assessment. These analyses were statistiscally summarized by monitoring site and State, and the results presented in tabular format. Most of the selected constituents or measurements have U.S. Environmental Protection Agency criteria or guidelines for aquatic-life or drinking-water purposes. A significant finding of this investigation is that for a large percentage of monitoring sites in the Nation, there are insufficient data to meet U.S. Environmental Protection Agency recommendations for determining if water-quality conditions are degraded and for making informed decisions regarding total maximum daily loads.

Water-Resources Investigations Report↗
USGS2011

Dissolved organic matter in the Florida everglades: Implications for ecosystem restoration

Dissolved organic matter (DOM) in the Florida Everglades controls a number of environmental processes important for ecosystem function including the absorption of light, mineral dissolution/precipitation, transport of hydrophobic compounds (e.g., pesticides), and the transport and reactivity of metals, such as mercury. Proposed attempts to return the Everglades to more natural flow conditions will result in changes to the present transport of DOM from the Everglades Agricultural Area and the northern conservation areas to Florida Bay. In part, the restoration plan calls for increasing water flow throughout the Everglades by removing some of the manmade barriers to flow in place today. The land- and water-use practices associated with the plan will likely result in changes in the quality, quantity, and reactivity of DOM throughout the greater Everglades ecosystem. The authors discuss the factors controlling DOM concentrations and chemistry, present distribution of DOM throughout the Everglades, the potential effects of DOM on key water-quality issues, and the potential utility of dissolved organic matter as an indicator of success of restoration efforts.

Florida↗
USGS2026

Ecovoltaic solar energy development creates novel microclimate, temperature, and soil moisture patterns under solar panels in a warm desert

Background: As solar energy development expands in desert regions, new installation practices and solar technologies seek to balance ecosystem conservation and energy generation (ecovoltaics). The Gemini Solar Project, a large ecovoltaic facility located in the northeastern Mojave Desert, employed low impact installation methods to reduce disturbance of the desert ecosystem within arrays of bifacial panels mounted on solar tracking systems. We evaluated microclimate and environmental conditions across five locations: four within-facility microsites (underneath solar panels, east and west panel driplines, and interspaces between panel rows) and one in the undisturbed desert outside the facility. Results: Under panel microsites experienced lower solar radiation and evaporative demand than panel driplines, and driplines experienced lower solar radiation and evaporative demand than interspaces and undisturbed desert outside the facility. Air temperature was similar among microsites, whereas soil surface temperature was highest in interspaces and lower in under-panel and dripline microsites due to diurnal panel shading. Soil temperature was higher under panels compared to interspaces from March to September and lower in other months, and higher during daytime and lower at nighttime periods. Panel tracking and the more frequent occurrence of afternoon precipitation promoted higher soil moisture in west driplines. Water redistribution was also influenced by soil hydraulic conductivity—deep soils experienced greater west dripline soil moisture, whereas shallow soils experienced surface water pooling and greater soil moisture in the west dripline and under solar panels. Conclusions: Gemini’s ecovoltaic design promotes microclimate heterogeneity, moderating some environmental conditions while intensifying others, and often differing from fixed panel facilities with higher disturbance. This research provides critical information to balance renewable energy expansion and ecological function in warm deserts.

Nevada↗
USGS2013

Native Prairie Adaptive Management: a multi region adaptive approach to invasive plant management on Fish and Wildlife Service owned native prairies

Much of the native prairie managed by the U.S. Fish and Wildlife Service (FWS) in the Prairie Pothole Region (PPR) of the northern Great Plains is extensively invaded by the introduced cool-season grasses, smooth brome ( Bromus inermis ) and Kentucky bluegrass ( Poa pratensis ). Management to suppress these invasive plants has had poor to inconsistent success. The central challenge to managers is selecting appropriate management actions in the face of biological and environmental uncertainties. In partnership with the FWS, the U.S. Geological Survey (USGS) developed an adaptive decision support framework to assist managers in selecting management actions under uncertainty and maximizing learning from management outcomes. This joint partnership is known as the Native Prairie Adaptive Management (NPAM) initiative. The NPAM decision framework is built around practical constraints faced by FWS refuge managers and includes identification of the management objective and strategies, analysis of uncertainty and construction of competing decision models, monitoring, and mechanisms for model feedback and decision selection. Nineteen FWS field stations, spanning four states of the PPR, have participated in the initiative. These FWS cooperators share a common management objective, available management strategies, and biological uncertainties. Though the scope is broad, the initiative interfaces with individual land managers who provide site-specific information and receive updated decision guidance that incorporates understanding gained from the collective experience of all cooperators. We describe the technical components of this approach, how the components integrate and inform each other, how data feedback from individual cooperators serves to reduce uncertainty across the whole region, and how a successful adaptive management project is coordinated and maintained on a large scale. During an initial scoping workshop, FWS cooperators developed a consensus management objective: increase the composition of native grasses and forbs on native sod while minimizing cost. Cooperators agreed that decision guidance should be provided annually and should account for local, real-time vegetation conditions observed on the ground. Over the course of development, two prototypes of the decision framework were considered. The final framework recognized four alternative actions that managers could take in any given year: (1) Graze—targeted use of grazing ungulates to achieve defoliation, (2) Burn—application of prescribed fire as the single form of defoliation, (3) Burn/Graze—a combination treatment, and (4) Rest—no action. The study area included northern mixed-grass and tallgrass prairie. Native vegetation in mixed–grass prairie has a strong cool-season component and thus the dominant native species have a phenology similar to that of smooth brome and Kentucky bluegrass, making management of those species challenging. In contrast, tallgrass prairie has a strong warm-season native component, leading to an existence of cool-season windows, periods of time in the fall and spring when cool‐season invasive grass species are actively growing and vulnerable to damage via select management actions, but warm‐season grass species are not active and are thus less susceptible to damage via the same actions. This dichotomy between prairie types necessitated the development of separate but parallel decision support systems for mixed-grass and tallgrass biomes. Management units are parcels of native prairie that receive a single management treatment at any one time over their entire extent. At any particular time, the vegetation state of each management unit is characterized by the amount of cover of native grasses and forbs and the type of invasive grass that is dominant. In addition, each unit has a defoliation state which reflects the number of years since the last defoliation event and an index to how intensively the unit was managed during the previous 7 years. State-transition models are used to predict the state of a management unit in year t+1 from its state in year t and a prescribed management action that was applied between the two monitoring events. Alternative models are built around key uncertainties that make choice of a management action difficult. Three uncertainties revolve around whether the effect of management actions depends on (1) type of dominant invader, (2) past defoliation history, and (3) level of invasion. Two additional uncertainties are considered when choosing a management action for tallgrass units: (4) the effectiveness of grazing within the cool-season window as a surrogate for burning when smooth brome is the dominant invader, and (5) the differential effect of active management outside the window as compared to rest. Because data on the probability of transitioning from one state to another under the various models were lacking, expert opinion and elicitation were used to parameterize the models. In addition, cooperators participated in elicitation exercises to extract their beliefs regarding the value of having native prairie compared to the cost of achieving it. Quantifying the subjective expression of utility in this way allowed for mathematical representation of the management objective into an objective function. By maximizing the objective function, cumulative utility is maximized, leading to the identification of a sequence of decisions that will achieve the management objective. The NPAM system adopted a vegetation monitoring protocol that was rapid, inexpensive, and familiar to many of the cooperators. The monitoring protocol served three purposes: (1) determining current vegetation and defoliation states of each unit, (2) evaluating progress toward the management objective, and (3) assessing predictive performance of the alternative models. The management year runs from September 1 to August 31. Management can be applied anytime during that period and monitoring takes places from late June to mid-August. Cooperators enter vegetation data and management information into a centralized database by August 25 of each year. Given the current state of the system (vegetation and defoliation states) and the current understanding of the system (or the belief state), identifying the current best management decision is a matter of looking up the combination (that is, system state and belief state) in the appropriate (mixed-grass or tallgrass) optimal decision table. Given complete uncertainty at the outset of decision-making, initial assignment of equal belief weights to each model was believed reasonable. The decisions in the optimal decision table that correspond to the current belief state constitute the current optimal decision policy. By August 31 of each year, individual cooperators are provided with a recommended management action for each of their management units for the upcoming management year. Upon receiving the management recommendations for their units, managers consider the recommendation, along with other relevant information, and at some point during the year one of the management alternatives is carried out. This iterative cycle of making and implementing a management decision, predicting the response, monitoring the outcome, comparing predicted and observed outcomes, updating model weights, and recommending a management action for the next cycle is expected to result in an accumulation of weight on a representative model of system dynamics, thereby increasing understanding needed to effectively manage native prairies. The NPAM system is now entering its second full year of complete operation, and represents one of only a few fully implemented applications of adaptive management within the U.S. Fish and Wildlife Service. NPAM is truly unique in that it originated from the ground up as a result of the leadership and steadfastness of several refuge biologists and managers confronted with a common problem. These biologists recognized that working together across a large landscape presented perhaps the best opportunity for halting and reversing the invasion of native grasslands by non-native cool-season grasses. Importantly, the NPAM system encapsulates the collective thinking and experience of tens if not hundreds of individuals who have battled this vexing problem for much of their careers. The NPAM initiative is rooted in principles of adaptive management, thereby affording the opportunity for grassland managers to pursue management objectives while acquiring information to reduce uncertainty and improve future management. The project introduced a number of technical innovations that will serve as templates for conservation efforts throughout and beyond the U.S. Fish and Wildlife Service. First, NPAM is an on-the-ground implementation of active adaptive management—possibly the first of its kind in conservation management—in which recommended management actions result from a prospective analysis of future learning (Williams, 1996). Second, by the use of dynamic optimization, NPAM demonstrates how decisions can be made that take into account possible future transitions of the system. Third, NPAM demonstrates how models of partial controllability are an effective means of accommodating unpredictable circumstances that cause a manager to follow a different course than was intended. Finally, the database developed for NPAM is an unparalleled system that enables the rapid integration of data from the field for the generation of ‘just-in-time’ management recommendations. In all, NPAM provides an example of how a science-management partnership can be forged to achieve large-scale conservation objectives.

Minnesota;Montana;North Dakota;South Dakota↗
USGS2011

Estimation of land surface evapotranspiration with A satellite remote sensing procedure

There are various methods available for estimating magnitude and trends of evapotranspiration. Bowen ratio energy balance system and eddy correlation techniques offer powerful alternatives for measuring land surface evapotranspiration. In spite of the elegance, high accuracy, and theoretical attractions of these techniques for measuring evapotranspiration, their practical use over large areas can be limited due to the number of sites needed and the related expense. Application of evapotranspiration mapping from satellite measurements can overcome the limitations. The objective of this study was to utilize the METRIC TM (Mapping Evapotranspiration at High Resolution using Internalized Calibration) model in Great Plains environmental settings to understand water use in managed ecosystems on a regional scale. We investigated spatiotemporal distribution of a fraction of reference evapotranspiration (ETrF) using eight Landsat 5 images during the 2005 and 2006 growing season for path 29, row 32. The ETrF maps generated by METRIC TM allowed us to follow the magnitude and trend in ETrF for major land-use classes during the growing season. The ETrF was lower early in the growing season for agricultural crops and gradually increased as the normalized difference vegetation index of crops increased, thus presenting more surface area over which water could transpire toward the midseason. Comparison of predictions with Bowen ratio energy balance system measurements at Clay Center, NE, showed that METRIC TM performed well at the field scale for predicting evapotranspiration from a cornfield. If calibrated properly, the model could be a viable tool to estimate water use in managed ecosystems in subhumid climates at a large scale.

Great Plains Research↗
USGS2014

Reflections on a vision for integrated research and monitoring after 15 years

In May of 1998, Owen Bricker and his co-author Michael Ruggiero introduced a conceptual design for integrating the Nation’s environmental research and monitoring programs. The Framework for Integrated Monitoring and Related Research was an organizing strategy for relating data collected by various programs, at multiple spatial and temporal scales, and by multiple science disciplines to solve complex ecological issues that individual research or monitoring programs were not designed to address. The concept nested existing intensive monitoring and research stations within national and regional surveys, remotely sensed data, and inventories to produce a collaborative program for multi-scale, multi-network integrated environmental monitoring and research. Analyses of gaps in data needed for specific issues would drive decisions on network improvements or enhancements. Data contributions to the Framework from existing networks would help indicate critical research and monitoring programs to protect during budget reductions. Significant progress has been made since 1998 on refining the Framework strategy. Methods and models for projecting scientific information across spatial and temporal scales have been improved, and a few regional pilots of multi-scale data-integration concepts have been attempted. The links between science and decision-making are also slowly improving and being incorporated into science practice. Experiments with the Framework strategy since 1998 have revealed the foundational elements essential to its successful implementation, such as defining core measurements, establishing standards of data collection and management, integrating research and long-term monitoring, and describing baseline ecological conditions. They have also shown us the remaining challenges to establishing the Framework concept: protecting and enhancing critical long-term monitoring, filling gaps in measurement methods, improving science for decision support, and integrating the disparate integrated science efforts now underway. In the 15 years since the Bricker and Ruggiero (Ecol Appl 8(2):326–329, 1998) paper challenged us with a new paradigm for bringing sound and comprehensive science to environmental decisions, the scientific community can take pride in the progress that has been made, while also taking stock of the challenges ahead for completing the Framework vision.

Aquatic Geochemistry↗
USGS2016

Resampling of spatially correlated data with preferential sampling for the estimation of frequency distributions and semivariograms

Spatial data are commonly minimal and may have been collected in the process of confirming the profitability of a mining venture or investigating a contaminated site. In such situations, it is common to have measurements preferentially taken in the most critical areas (sweet spots, allegedly contaminated areas), thus conditionally biasing the sample. While preferential sampling makes good practical sense, its direct use leads to distorted sample moments and percentiles. Spatial clusters are a problem that has been identified in the past and solved with approaches ranging from ad hoc solutions to highly elaborate mathematical formulations, covering mostly the effect of clustering on the cumulative frequency distribution. The method proposed here is a form of resample, free of special assumptions, does not use weights to ponder the measurements, does not find solutions by successive approximation and provides variability in the results. The new method is illustrated with a synthetic dataset with an exponential semivariogram and purposely generated to follow a lognormal distribution. The lognormal distribution is both difficult to work with and typical of many attributes of practical interest. Testing of the new solution shows that sample subsets derived from resampled datasets can closely approximate the true probability distribution and the semivariogram, clearly outperforming the original preferentially sampled data.

Stochastic Environmental Research and Risk Assessm↗
USGS2022

A statistical framework for modelling migration corridors

1. Management of animal populations requires spatially explicit knowledge of movement corridors, such as those used during seasonal migrations. GPS tracking data allows for mapping of corridors from directly observed movements, providing important insights, but tracking data is absent for many populations. 2. We developed a novel statistical corridor modeling approach that predicts movement corridors from cost-distance movement models fit directly to migration tracking data. Unlike existing predictive approaches, this does not require the ad-hoc transformation of habitat suitability surfaces into resistance surfaces. We tested the ability of the approach to recover parameters used to generate simulated movements. We then used GPS data from three migrating mule deer (Odocoileus hemionus) herds in Idaho and Wyoming to model corridors as a function of elevation, slope, aspect, percent shrub, date of peak green-up, snow-off date, and human footprint. We assessed the predictive ability of the fitted models using validation tracks from the same herd as well as from the other herds. 3. The approach reproduced parameters used to generate the simulated movements, predicted the corridors used by migratory populations, and described the direction, magnitude, and confidence levels of the effects of environmental variables on corridors. The effects environmental variables had on corridors differed depending on the herd. Within-herd validation indicated that fitted corridor models are more accurate at predicting migration corridors than null models, and cross-herd validation indicated that fitted models for some herds accurately predicted the observed migrations of other herds. 4. In addition to the practical benefit of mapping corridors for management, our statistical corridor modeling framework sets the stage for evaluating fundamental questions about the fitness tradeoffs, navigation, learning, fidelity, and movement constraints that influence migratory and other corridor-generating behavior. Models of predictive corridors can inform management and planning for the conservation of migrations across taxa, including the potential restoration of corridors. Our corridor modeling approach is also readily applied to non-migratory animal movements.

Idaho, Wyoming↗
USGS2019

Seasonal variation in sediment and phosphorus yields in four Wisconsin agricultural watersheds

Agricultural water quality projects in two distinct topographic regions in Wisconsin collected 5 to 10 yr of continuous stream discharge, suspended sediment (SS), total P (TP), and total dissolved P (TDP) in four watersheds (2100–5000 ha) from 2006 to 2016. Previous agricultural nonpoint SS and TP reduction efforts in two of these watersheds documented cold versus warm season differences in water quality response. The goal of this study was to identify seasonal partitioning of SS, TP, and TDP in storm event loads to inform stream water quality protection efforts. We used National Weather Service Coop Observer frost depth reports to identify dates when watershed soils were frozen. By comparing daily mean event discharge for dates relative to frost, we identified a 32‐d post‐frost high‐discharge “thaw” period. Combined, the frozen and thaw periods contributed about half of the annual SS and TP runoff event loads, ranging from 47 to 63% for SS and from 45 to 51% for TP. The proportion of runoff event TDP during this time was even higher, 62 to 79%, with the majority during thaw. Watershed average volumetric runoff coefficients (event flow/precipitation and snowmelt) were two to four times higher during the freeze and the thaw compared with the rest of the year. To reduce total stream loads in regions with similar climates to Wisconsin, this study indicates that using management practices that curb sediment and P delivery to streams in the winter and early spring may be as important as those designed for nonfrozen conditions.

Wisconsin↗
USGS2022

Supplemental habitat is reservoir dependent: Identifying optimal planting decision using Bayesian Decision Networks

Environmental management often requires making decisions despite system uncertainty. One such example is mudflat mediation in flood control reservoirs. Reservoir mudflats limit development of diverse fish assemblages due to the lack of structural habitat provided by plants. Seeding mudflats with agricultural plants may mimic floodplain wetlands once inundated and provide fish habitat and achieve habitat management objectives. However, planting success is uncertain because of unpredictable water level fluctuations that affect plant survival and growth. Decision support tools can account for uncertainty that influences decision outcomes and reduce the risk in reservoir mudflat planting decisions. We used Bayesian decision networks and sensitivity analyses to quantify uncertainty surrounding mudflat plantings as supplemental fish habitat in four northwest Mississippi reservoirs. When averaged across all uncertainty, planting was the optimal decision only in Enid Lake. Response profiles indicated planting decisions depended on elevation contours within Enid, Sardis, and Grenada reservoirs. No planting was optimal at all elevations for Arkabutla Lake. These results provide a quantified basis for establishing best management practices and identify key system states that influence decision outcomes. The process used in this study to evaluate planting decisions can be applied to any reservoir by modifying reservoir dependent inputs to evaluate planting decisions to provide supplemental fish habitat.

Mississippi↗
USGS2021

The role of behavioral ecotoxicology in environmental protection

For decades, we have known that chemicals affect human and wildlife behavior. Moreover, due to recent technological and computational advances, scientists are now increasingly aware that a wide variety of contaminants and other environmental stressors adversely affect organismal behavior and subsequent ecological outcomes in terrestrial and aquatic ecosystems. There is also a groundswell of concern that regulatory ecotoxicology does not adequately consider behavior, primarily due to a lack of standardized toxicity methods. This has, in turn, led to the exclusion of many behavioral ecotoxicology studies from chemical risk assessments. To improve understanding of the challenges and opportunities for behavioral ecotoxicology within regulatory toxicology/risk assessment, a unique workshop with international representatives from the fields of behavioral ecology, ecotoxicology, regulatory (eco)toxicology, neurotoxicology, test standardization, and risk assessment resulted in the formation of consensus perspectives and recommendations, which promise to serve as a roadmap to advance interfaces among the basic and translational sciences, and regulatory practices.

Environmental Science & Technology↗
USGS2025

A metadata checklist and data formatting guidelines to make eDNA FAIR (Findable, Accessible, Interoperable and Reusable)

The success of environmental DNA (eDNA) approaches for species detection has revolutionized biodiversity monitoring and distribution mapping. Targeted eDNA amplification approaches, such as quantitative PCR, have improved our understanding of species distribution, and metabarcoding-based approaches have enabled biodiversity assessment at unprecedented scales and taxonomic resolution. eDNA datasets, however, are often scattered across repositories with inconsistent formats, varying access restrictions, and inadequate metadata; this limits their interoperation, reuse, and overall impact. Adopting FAIR (Findable, Accessible, Interoperable, and Reusable) data practices with eDNA data can transform the monitoring of biodiversity and individual species and support data-driven biodiversity management across broad scales. FAIR practices remain underdeveloped in the eDNA community, partly due to gaps in adapting existing vocabularies, such as Darwin Core (DwC) and Minimum Information about any (x) Sequence (MIxS), to eDNA-specific needs and workflows. To address these challenges, we propose a comprehensive FAIR eDNA (FAIRe) Metadata Checklist, which integrates existing data standards and introduces new terms tailored to eDNA workflows. Metadata are systematically linked to both raw data (e.g., metabarcoding sequences, Ct/Cq values of targeted qPCR assays) and derived biological observations (e.g., Amplicon Sequence Variant (ASV)/Operational Taxonomic Unit (OTU) tables, species presence/absence). Along with formatting guidelines, tools, templates, and example datasets, we introduce a standardized, ready-to-use approach for FAIR eDNA practices. Through broad collaboration, we seek to integrate these guidelines into established biodiversity and molecular data standards, promote journal data policies, and foster user-driven improvements and uptake of FAIR practices among eDNA data producers. In proposing this standardized approach and developing a long-term plan with key databases and data standard organizations, the goal is to enhance accessibility, maximize reuse, and elevate the scientific impact of these valuable biodiversity data resources.

Environmental DNA↗
USGS2006

A global perspective on the use, sales, exposure pathways, occurrence, fate and effects of veterinary antibiotics (VAs) in the environment

Veterinary antibiotics (VAs) are widely used in many countries worldwide to treat disease and protect the health of animals. They are also incorporated into animal feed to improve growth rate and feed efficiency. As antibiotics are poorly adsorbed in the gut of the animals, the majority is excreted unchanged in faeces and urine. Given that land application of animal waste as a supplement to fertilizer is often a common practice in many countries, there is a growing international concern about the potential impact of antibiotic residues on the environment. Frequent use of antibiotics has also raised concerns about increased antibiotic resistance of microorganisms. We have attempted in this paper to summarize the latest information available in the literature on the use, sales, exposure pathways, environmental occurrence, fate and effects of veterinary antibiotics in animal agriculture. The review has focused on four important groups of antibiotics (tylosin, tetracycline, sulfonamides and, to a lesser extent, bacitracin) giving a background on their chemical nature, fate processes, occurrence, and effects on plants, soil organisms and bacterial community. Recognising the importance and the growing debate, the issue of antibiotic resistance due to the frequent use of antibiotics in food-producing animals is also briefly covered. The final section highlights some unresolved questions and presents a way forward on issues requiring urgent attention.

Chemosphere↗
USGS1996

Sampling design for assessing water quality of the Red River of the North basin, Minnesota, North Dakota, and South Dakota, 1993-1995

This map report describes the sampling design for a comprehensive regional assessment of water quality in the Red River of the North Basin, a study unit under the U.S. Geological Survey’s National Water-Quality Assessment Program. The sampling design was developed to address questions about the presence, distribution, and loads of nutrients and pesticides associated with large agricultural regions in the basin and across the Nation. The design also begins to address major local and regional concerns about suspended sediment in surface water and naturally occurring salinity in ground water. Recognizing that the Red River of the North Basin study unit realistically could not be analyzed as a single homogeneous area, a hierarchical sampling stratification for assessing water quality was developed. Landscape features consisting of physiography, soils, land cover and land use, and cropping patterns provided the environmental framework for stratification of streams and surficial aquifers. The environmental framework characterizes the climate and hydrology and relates closely to an ecoregions framework. The environmental and ecoregions frameworks were considered in locating ecological sampling sites. For the subsurface framework, buried sand and gravel aquifers in study unit were subdivided into two general subregions of differing potential saline recharge from underlying bedrock aquifers. Actual sampling sites for streams, aquatic biology, and ground water were described within the proposed sampling stratification. Practical considerations of previously established sampling sites, background information from previous hydrologic investigations, and site suitability for sampling protocols also were considered for final site selection.

Minnesota, North Dakota, South Dakota↗
USGS2022

Global genetic diversity status and trends: Towards a suite of Essential Biodiversity Variables (EBVs) for genetic composition

Biodiversity underlies ecosystem resilience, ecosystem function, sustainable economies, and human well-being. Understanding how biodiversity sustains ecosystems under anthropogenic stressors and global environmental change will require new ways of deriving and applying biodiversity data. A major challenge is that biodiversity data and knowledge are scattered, biased, collected with numerous methods, and stored in inconsistent ways. The Group on Earth Observations Biodiversity Observation Network (GEO BON) has developed the Essential Biodiversity Variables (EBVs) as fundamental metrics to help aggregate, harmonize, and interpret biodiversity observation data from diverse sources. Mapping and analyzing EBVs can help to evaluate how aspects of biodiversity are distributed geographically and how they change over time. EBVs are also intended to serve as inputs and validation to forecast the status and trends of biodiversity, and to support policy and decision making. Here, we assess the feasibility of implementing Genetic Composition EBVs (Genetic EBVs), which are metrics of within-species genetic variation. We review and bring together numerous areas of the field of genetics and evaluate how each contributes to global and regional genetic biodiversity monitoring with respect to theory, sampling logistics, metadata, archiving, data aggregation, modeling, and technological advances. We propose four Genetic EBVs: ( i ) Genetic Diversity; ( ii ) Genetic Differentiation; ( iii ) Inbreeding; and ( iv ) Effective Population Size ( N e ). We rank Genetic EBVs according to their relevance, sensitivity to change, generalizability, scalability, feasibility and data availability. We outline the workflow for generating genetic data underlying the Genetic EBVs, and review advances and needs in archiving genetic composition data and metadata. We discuss how Genetic EBVs can be operationalized by visualizing EBVs in space and time across species and by forecasting Genetic EBVs beyond current observations using various modeling approaches. Our review then explores challenges of aggregation, standardization, and costs of operationalizing the Genetic EBVs, as well as future directions and opportunities to maximize their uptake globally in research and policy. The collection, annotation, and availability of genetic data has made major advances in the past decade, each of which contributes to the practical and standardized framework for large-scale genetic observation reporting. Rapid advances in DNA sequencing technology present new opportunities, but also challenges for operationalizing Genetic EBVs for biodiversity monitoring regionally and globally. With these advances, genetic composition monitoring is starting to be integrated into global conservation policy, which can help support the foundation of all biodiversity and species' long-term persistence in the face of environmental change. We conclude with a summary of concrete steps for researchers and policy makers for advancing operationalization of Genetic EBVs. The technical and analytical foundations of Genetic EBVs are well developed, and conservation practitioners should anticipate their increasing application as efforts emerge to scale up genetic biodiversity monitoring regionally and globally.

Biological Reviews↗
USGS1998

Water quality in the central Columbia Plateau, Washington and Idaho, 1992-95

Water quality in the Central Columbia Plateau of eastern Washington and western Idaho has been adversely affected by agriculture, especially in irrigated areas, according to the results of a five-year investigation by the U. S. Geological Survey (USGS). Some improvements, however, are noticeable, such as less sediment being washed into streams. These improvements may be the result of increased use of best management practices (BMPs) by area farmers. Areas with intensive fertilizer use and irrigation, such as in the Columbia Basin Irrigation Project (CBIP), showed the greatest impacts on ground-water quality. (The CBIP includes parts of Franklin, Grant, and Adams counties in eastern Washington.) <Shallow wells, generally those less than 150 feet deep, are the most susceptible to contamination, the USGS report says. A reassuring aspect of this finding, however, is that many public water supplies draw from wells at greater depths and are less susceptible to contamination from agricultural practices. From the standpoint of human health, we were most concerned about checking for nitrate and pesticides in drinking water,' said Sandy Williamson, USGS hydrologist and chief of the study. 'We found nitrate levels exceeding the maximum contaminant level in about 20 percent of all wells.' (A maximum contaminant level-or MCL-is a drinking water regulatory standard that is set by the U.S. Environmental Protection Agency.) 'The story on pesticides is a mixed bag,' Williamson said. 'We found at least one pesticide in nearly half of the drinking water wells sampled, but pesticide levels were only a very small fraction of their MCLs.' As a cautionary note, however, Williamson said that about half of the pesticides detected in Central Columbia Plateau wells do not have MCLs established. A lack of information makes it difficult to assess the significance of finding pesticides in drinking water. 'As scientists, we don't know enough yet about what happens when these pesticides are combined,' he said. 'In some of the very shallow wells that the USGS installed for monitoring purposes, we found up to seven different pesticides.' Encouraging news is that none of the newer pesticides, which break down more rapidly in the environment, were found at concentrations exceeding MCLs. Compounds that exceed drinking water standards were found in only 1 percent of the wells sampled-and those compounds have not been sold as pesticides since the mid-1980s. However, agricultural impacts on water quality go beyond the concerns for drinking water-the aquatic ecosystem of the plateau also has been significantly affected. 'Very little surface water is used for drinking water in this area, but fish are harmed by decreased stream-water quality,' said Mark Munn, the biologist for the USGS study. 'Pesticides and habitat degradation are the main concerns.' He noted that stream sampling by the USGS showed seven currently used pesticides at concentrations above the limits recommended for protecting aquatic life. Soil erosion, a long-term problem for farmers in the Palouse River Basin, transports some soil to streams, degrading habitat and carrying with it older pesticides and their breakdown products. A breakdown product of the banned insecticide DDT was found in both streambed sediment and bottom fish at concentrations exceeding guidelines for the protection of aquatic life. 'Another problem for fish habitat is excessive plant growth caused by high levels of nutrients in streams,' said Munn, who explained that these nutrients enter streams in runoff from agricultural fields and discharge from urban wastewater treatment plants. Some agricultural practices, such as allowing cattle to graze near streams, are associated with higher rates of erosion. However, increased use of BMPs may improve water quality of the plateau. The USGS study showed that use of sprinkler or drip rather than furrow irrigation has decreased soil erosion in the CBIP area. In the Palouse, erosion

Circular↗
USGS2011

U.S. Department of Energy's regional carbon sequestration partnership initiative: Update on validation and development phases

The U.S. Department of Energy (DOE) is the lead federal agency for the development and deployment of carbon sequestration technologies. The Regional Carbon Sequestration Partnerships (RCSPs) are the mechanism DOE utilizes to prove the technology and to develop human capital, stakeholder networks, information for regulatory policy, best practices documents and training to work toward the commercialization of carbon capture and storage (CCS). The RCSPs are tasked with determining the most suitable technologies, regulations, and infrastructure for carbon capture, transport, and storage in their respective geographic areas of responsibility. The seven partnerships include more than 400 state agencies, universities, national laboratories, private companies, and environmental organizations, spanning 43 states and four Canadian provinces. The Regional Partnerships Initiative is being implemented in three phases: Characterization, Validation, and Development. The initial Characterization Phase began in 2003 and was completed in 2005 and focused on characterization of CO2 storage potential within each region. It was followed by the Validation Phase, which began in 2005 and is nearing completion in 2011. The focus of the Validation Phase has been on small-scale field tests throughout the seven partnerships in various formation types such as saline, oil-bearing, and coal seams. The Validation Phase has characterized suitable CO2 storage reservoirs and identified the need for comprehensive legal and regulatory frameworks to enable commercial-scale CCS deployment. Finally, the Development Phase will consist of a series of large-scale, one-million-ton, injection tests throughout the United States and Canada. The objective of these large-scale tests is to identify the regulatory path or challenges in permitting CCS projects, to demonstrate the technology can inject CO2 safely, and to verify its permanence in geologic formations in preparation for the commercialization of geologic sequestration. ?? 2010 Elsevier Ltd. All rights reserved. ?? 2011 Published by Elsevier Ltd.

Conference Paper↗
USGS2018

Prediction uncertainty and data worth assessment for groundwater transport times in an agricultural catchment

Uncertainties about the age of base-flow discharge can have serious implications for the management of degraded environmental systems where subsurface pathways, and the ongoing release of pollutants that accumulated in the subsurface during past decades, dominate the water quality signal. Numerical groundwater models may be used to estimate groundwater return times and base-flow ages and thus predict the time required for stakeholders to see the results of improved agricultural management practices. However, the uncertainty inherent in the relationship between (i) the observations of atmospherically-derived tracers that are required to calibrate such models and (ii) the predictions of system age that the observations inform have not been investigated. For example, few if any studies have assessed the uncertainty of numerically-simulated system ages or evaluated the uncertainty reductions that may result from the expense of collecting additional subsurface tracer data. In this study we combine numerical flow and transport modeling of atmospherically-derived tracers with prediction uncertainty methods to accomplish four objectives. First, we show the relative importance of head, discharge, and tracer information for characterizing response times in a uniquely data rich catchment that includes 266 age-tracer measurements (SF 6 , CFCs, and 3 H) in addition to long term monitoring of water levels and stream discharge. Second, we calculate uncertainty intervals for model-simulated base-flow ages using both linear and non-linear methods, and find that the prediction sensitivity vector used by linear first-order second-moment methods results in much larger uncertainties than non-linear Monte Carlo methods operating on the same parameter uncertainty. Third, by combining prediction uncertainty analysis with multiple models of the system, we show that data-worth calculations and monitoring network design are sensitive to variations in the amount of water leaving the system via stream discharge and irrigation withdrawals. Finally, we demonstrate a novel model-averaged computation of potential data worth that can account for these uncertainties in model structure.

Maryland↗