Geology topics

Daniel K. Jones

Publications and source records attributed to Daniel K. Jones.

33 records · Page 2Linked to original sources

USGS2021

A review of algal toxin exposures on reserved federal lands and among trust species in the United States

Associated health effects from algal toxin exposure are a growing concern for human and animal health. Algal toxin poisonings may occur from contact with or consumption of water supplies or from ingestion of contaminated animals. The U.S. Federal Government owns or holds in trust about 259 million hectares of land, in addition to the Trust species obligations. We completed the first comprehensive review of potential toxin-producing algal blooms in surface waters on Federal lands and Trust species exposed to algal toxins. Events were sorted into three tiers based on potentially toxic algae abundance or toxin concentration and related effects on animal morbidity and mortality. At least 11.1% of Federal lands are known to have been affected by algal events, but exposure is likely underreported. The occurrence of potential toxin producers and their toxins (Tier 1) have been documented 337 times, health advisory threshold exceedances (Tier 2) were reported 943 times, and 86 events involved animal sickness or death linked to cyanobacteria or marine toxins (Tier 3). Trust species exposed to cyano- or algal toxins included marine mammals, migratory birds, threatened and endangered species, and species of concern. We report numerous data gaps ranging from potential effects on human health from consuming intoxicated animals to the infrequency of measuring and reporting certain toxins. Improvements to field and laboratory methods, more consistent evaluation of toxin exposure, decreased latency on data analysis, delivery and interpretation will be necessary to improve response and management strategies for protecting human and animal health where issues persist.

Critical Reviews in Environmental Science and Tech↗

USGS2021

How will baseflow respond to climate change in the Upper Colorado River Basin?

Baseflow is critical to sustaining streamflow in the Upper Colorado River Basin. Therefore, effective water resources management requires estimates of baseflow response to climatic changes. This study provides the first estimates of projected baseflow changes from historical (1984 – 2012) to thirty-year periods centered around 2030, 2050, and 2080 under warm/wet, median, and hot/dry climatic conditions using a hybrid statistical-deterministic baseflow model. Total baseflow supplied to the Lower Colorado River Basin may decline by up to 33%, although this value may increase in the near future by 6% under warm/wet conditions. The percentage of baseflow lost during in-stream transport is projected to increase by 1 - 5% relative to historical conditions. Results highlight that climate driven changes in high elevation hydrology have impacts on basin-wide water availability. Study results have implications for human and ecological water availability in one of the most heavily managed watersheds in the world.

Arizona, Colorado, New Mexico, Utah, Wyoming↗

USGS2021

Machine learning models of arsenic in private wells throughout the conterminous United States as a tool for exposure assessment in human health studies

Arsenic from geologic sources is widespread in groundwater within the United States (U.S.). In several areas, groundwater arsenic concentrations exceed the U.S. Environmental Protection Agency maximum contaminant level of 10 μg per liter (μg/L). However, this standard applies only to public-supply drinking water and not to private-supply, which is not federally regulated and is rarely monitored. As a result, arsenic exposure from private wells is a potentially substantial, but largely hidden, public health concern. Machine learning models using boosted regression trees (BRT) and random forest classification (RFC) techniques were developed to estimate probabilities and concentration ranges of arsenic in private wells throughout the conterminous U.S. Three BRT models were fit separately to estimate the probability of private well arsenic concentrations exceeding 1, 5, or 10 μg/L whereas the RFC model estimates the most probable category (≤5, >5 to ≤10, or >10 μg/L). Overall, the models perform best at identifying areas with low concentrations of arsenic in private wells. The BRT 10 μg/L model estimates for testing data have an overall accuracy of 91.2%, sensitivity of 33.9%, and specificity of 98.2%. Influential variables identified across all models included average annual precipitation and soil geochemistry. Models were developed in collaboration with public health experts to support U.S.-based studies focused on health effects from arsenic exposure.

Environmental Science and Technology↗

USGS2021

Modeling estrogenic activity in streams throughout the Potomac and Chesapeake Bay watersheds

Endocrine-disrupting compounds (EDCs), specifically estrogenic endocrine-disrupting compounds, vary in concentration and composition in surface waters under the influence of different landscape sources and landcover gradients. Estrogenic activity in surface waters may lead to adverse effects in aquatic species at both individual and population levels, often observed through the presence of intersex and vitellogenin induction in male fish. In the Chesapeake Bay Watershed, located on the mid-Atlantic coast of the USA, intersex has been observed in several sub-watersheds where previous studies have identified specific landscape sources of EDCs in tandem with observed fish health effects. Previous work in the Potomac River Watershed (PRW), the largest basin within the Chesapeake Bay Watershed, was leveraged to build random forest regression models to predict estrogenic activity at unsampled reaches in both the Potomac River and larger Chesapeake Bay Watersheds (CBW). Model outputs including important variables, partial dependence plots, and predicted values of estrogenic activity at unsampled reaches provide insight into drivers of estrogenic activity at different seasons and scales. Using the US Environmental Protection Agency effects-based threshold of 1.0 ng/L 17 β-estradiol equivalents, catchments predicted to exceed this value were categorized as at risk for adverse effects from exposure to estrogenic compounds and evaluated relative to healthy watersheds and recreation access locations throughout the PRW. Results show immediate catchment scale models are more reliable than upstream models, and the best predictive variables differ by season and scale. A small percentage of healthy watersheds (< 13%) and public access sites were classified as at risk using the “Total” (annual) model in the CBW. This study is the first Potomac River Watershed assessment of estrogenic activity, providing a new foundation for future risk assessment and management design efforts, with additional context provided for the entire Chesapeake Bay Watershed.

Delaware, Maryland, New York, Pennsylvania, Virgin↗

USGS2021

Retrospective analysis of estrogenic endocrine disruption and land-use influences in the Chesapeake Bay watershed

The Chesapeake Bay is the largest estuary in the United States and its watershed includes river drainages in six states and the District of Columbia. Sportfishing is of major economic interest, however, the rivers within the watershed provide numerous other ecological, recreational, cultural and economic benefits, as well as serving as a drinking water source for millions of people. Consequently, major fish kills and the subsequent finding of estrogenic endocrine disruption (intersex or testicular oocytes and plasma vitellogenin in male fishes) raised public and management concerns. Studies have occurred at various sites within the Bay watershed to document the extent and severity of endocrine disruption, identify risk factors and document temporal and spatial variability. Data from these focal studies, which began in 2004, were used in CART (classification and regression trees) analyses to better identify land use associations and potential management practices that influence estrogenic endocrine disruption. These analyses emphasized the importance of scale (immediate versus upstream catchment) and the complex mixtures of stressors which can contribute to surface water estrogenicity and the associated adverse effects of exposure. Both agricultural (percent cultivated, pesticide application, phytoestrogen cover crops) and developed (population density, road density, impervious surface) land cover showed positive relationships to estrogenic indicators, while percent forest and shrubs generally had a negative association. The findings can serve as a baseline for assessing ongoing restoration and management practices.

Chesapeake Bay river watersheds↗

USGS2021

Changing climate drives future streamflow declines and challenges in meeting water demand across the southwestern United States

Society and the environment in the arid southwestern United States depend on reliable water availability, yet current water use outpaces supply. Water demand is projected to grow in the future and climate change is expected to reduce supply. To adapt, water managers need robust estimates of future regional water supply to support management decisions. To address this need, we estimate future streamflow in seven water resource regions in the southwestern U.S. using a new SPAtially Referenced Regressions On Watershed attributes (SPARROW) streamflow model. We present streamflow projections corresponding to input data from seven climate models and two greenhouse gas Representative Concentration Pathways (RCP4.5 and 8.5) for three, thirty-year intervals centered on the 2030s, 2050s, and 2080s, and for a historical thirty year interval centered on the 1990s. Across water resource regions, about half of the RCP4.5 models (51%) and two thirds of the RCP8.5 models (67%) indicate decreases in streamflow in the 2080s relative to the historical period. Models project maximum decreases in streamflow of 36–80% in all water resource regions for all periods and RCPs relative to historical streamflow, and maximum streamflow decreases of up to 20–45% in the 2080s at sites along the Colorado River used for measuring compliance with interstate and international water agreements. Headwaters are projected to experience the greatest declines, with substantial downstream implications. Among these estimates, the streamflows from models forced with RCP8.5 tend to be lower than those forced with RCP4.5. Not all climate models, times, and RCPs project widespread streamflow declines. The most ubiquitous streamflow increases are projected to occur in the 2030s under RCP4.5. Later time periods and enhanced greenhouse gas forcings indicate smaller regions of streamflow increase and lower accumulated streamflows, suggesting that limiting or reducing greenhouse gas concentrations could support future water availability. Although some possible streamflow increases are promising, the modest and spatially limited increases in streamflow projected for later time periods are still unlikely to be sufficient to meet the projected water demand. These results inform the likelihood of future water agreement compliance, and support developing strategies to balance water supply and demand.

Arizona, California, Colorado Idaho, Nevada, New M↗

USGS2020

A geospatially resolved wetland vulnerability index: Synthesis of physical drivers

Assessing wetland vulnerability to chronic and episodic physical drivers is fundamental for establishing restoration priorities. We synthesized multiple data sets from E.B Forsythe National Wildlife Refuge, New Jersey, to establish a wetland vulnerability metric that integrates a range of physical processes, regulatory information and physical/biophysical features. The geospatial data are based on aerial imagery, remote sensing, regulatory information, and hydrodynamic modeling, and include elevation, tidal range, unvegetated to vegetated marsh ratio (UVVR), shoreline erosion, potential exposure to contaminants, residence time, marsh condition change, change in salinity and salinity exposure, and sediment concentration. First, we delineated the wetland complex into individual marsh units based on surface contours and then defined a wetland vulnerability index that combined contributions from all parameters. We applied principal component and cluster analyses to explore the interrelations between the data layers and separate regions that exhibited common characteristics. Our analysis shows that the spatial variation of vulnerability in this domain cannot be explained satisfactorily by a smaller subset of the variables. The most influential factor on the vulnerability index was the combined effect of elevation, tide range, residence time, and UVVR. Tide range and residence time had the highest correlation, and similar bay-wide spatial variation. Some variables (e.g., shoreline erosion) had no significant correlation with the rest of the variables. The aggregated index based on the complete dataset allows us to assess the overall state of a given marsh unit and quickly locate the most vulnerable units in a larger marsh complex. The application of geospatially complete datasets and consideration of chronic and episodic physical drivers represents an advance over traditional point-based methods for wetland assessment.

New Jersey↗

USGS2019

The presence of antibiotic resistance genes in coastal soil and sediment samples from the eastern seaboard of the USA

Infections from antibiotic resistant microorganisms are considered to be one of the greatest global public health challenges that result in huge annual economic losses. While genes that impart resistance to antibiotics (AbR) existed long before the discovery and use of antibiotics, anthropogenic uses of antibiotics in agriculture, domesticated animals, and humans are known to influence the prevalence of these genes in pathogenic microorganisms. It is critical to understand the role that natural and anthropogenic processes have on the occurrence and distribution of antibiotic resistance in microbial populations to minimize health risks associated with exposures. As part of this research, 15 antibiotic resistance genes were analyzed in coastal sediments and soils along the eastern seaboard of the USA using presence/absence quantitative and digital polymerase chain reaction assays. Samples (53 soil and 192 sediment samples including 54 replicates) were collected from a variety of coastal settings where human and wildlife exposure is likely. At least one of the antibiotic resistance genes was detected in 76.4% of the samples. Samples that contained at least five or more antibiotic resistance genes (5.7%) where typically hydrologically down gradient of watersheds influenced by combined sewer outfalls (CSO). The most frequently detected antibiotic resistance target genes were found in 33.2%, 34.4%, and 42.2% of samples (target genes bla SHV , tetO , and aadA2 , respectively). These data provide unique insight into potential exposure of AbR genes over a large geographical region of the eastern seaboard of the USA.

Connecticut, Delaware, District of Columbia, Maine↗

USGS2017

Expanded target-chemical analysis reveals extensive mixed-organic-contaminant exposure in USA streams

Surface water from 38 streams nationwide was assessed using 14 target-organic methods (719 compounds). Designed-bioactive anthropogenic contaminants (biocides, pharmaceuticals) comprised 57% of 406 organics detected at least once. The 10 most-frequently detected anthropogenic-organics included eight pesticides (desulfinylfipronil, AMPA, chlorpyrifos, dieldrin, metolachlor, atrazine, CIAT, glyphosate) and two pharmaceuticals (caffeine, metformin) with detection frequencies ranging 66–84% of all sites. Detected contaminant concentrations varied from less than 1 ng L –1 to greater than 10 μg L –1 , with 77 and 278 having median detected concentrations greater than 100 ng L –1 and 10 ng L –1 , respectively. Cumulative detections and concentrations ranged 4–161 compounds (median 70) and 8.5–102 847 ng L –1 , respectively, and correlated significantly with wastewater discharge, watershed development, and toxic release inventory metrics. Log 10 concentrations of widely monitored HHCB, triclosan, and carbamazepine explained 71–82% of the variability in the total number of compounds detected (linear regression; p -values: < 0.001–0.012), providing a statistical inference tool for unmonitored contaminants. Due to multiple modes of action, high bioactivity, biorecalcitrance, and direct environment application (pesticides), designed-bioactive organics (median 41 per site at μg L –1 cumulative concentrations) in developed watersheds present aquatic health concerns, given their acknowledged potential for sublethal effects to sensitive species and lifecycle stages at low ng L –1 .

Environmental Science & Technology↗

USGS2016

The new Landsat 8 potential for remote sensing of colored dissolved organic matter (CDOM)

Due to a combination of factors, such as a new coastal/aerosol band and improved radiometric sensitivity of the Operational Land Imager aboard Landsat 8, the atmospherically-corrected Surface Reflectance product for Landsat data, and the growing availability of corrected fDOM data from U.S. Geological Survey gaging stations, moderate-resolution remote sensing of fDOM may now be achievable. This paper explores the background of previous efforts and shows preliminary examples of the remote sensing and data relationships between corrected fDOM and Landsat 8 reflectance values. Although preliminary results before and after Hurricane Sandy are encouraging, more research is needed to explore the full potential of Landsat 8 to continuously map fDOM in a number of water profiles.

Marine Pollution Bulletin↗

USGS2016

Regional variability in bed-sediment concentrations of wastewater compounds, hormones and PAHs for portions of coastal New York and New Jersey impacted by hurricane Sandy

Bed sediment samples from 79 coastal New York and New Jersey, USA sites were analyzed for 75 compounds including wastewater associated contaminants, PAHs, and other organic compounds to assess the post-Hurricane Sandy distribution of organic contaminants among six regions. These results provide the first assessment of wastewater compounds, hormones, and PAHs in bed sediment for this region. Concentrations of most wastewater contaminants and PAHs were highest in the most developed region (Upper Harbor/Newark Bay, UHNB) and reflected the wastewater inputs to this area. Although the lack of pre-Hurricane Sandy data for most of these compounds make it impossible to assess the effect of the storm on wastewater contaminant concentrations, PAH concentrations in the UHNB region reflect pre-Hurricane Sandy conditions in this region. Lower hormone concentrations than predicted by the total organic carbon relation occurred in UHNB samples, suggesting that hormones are being degraded in the UHNB region.

New Jersey, New York↗

USGS2015

Standard operating procedures for collection of soil and sediment samples for the Sediment-bound Contaminant Resiliency and Response (SCoRR) strategy pilot study

An understanding of the effects on human and ecological health brought by major coastal storms or flooding events is typically limited because of a lack of regionally consistent baseline and trends data in locations proximal to potential contaminant sources and mitigation activities, sensitive ecosystems, and recreational facilities where exposures are probable. In an attempt to close this gap, the U.S. Geological Survey (USGS) has implemented the Sediment-bound Contaminant Resiliency and Response (SCoRR) strategy pilot study to collect regional sediment-quality data prior to and in response to future coastal storms. The standard operating procedure (SOP) detailed in this document serves as the sample-collection protocol for the SCoRR strategy by providing step-by-step instructions for site preparation, sample collection and processing, and shipping of soil and surficial sediment (for example, bed sediment, marsh sediment, or beach material). The objectives of the SCoRR strategy pilot study are (1) to create a baseline of soil-, sand-, marsh sediment-, and bed-sediment-quality data from sites located in the coastal counties from Maine to Virginia based on their potential risk of being contaminated in the event of a major coastal storm or flooding (defined as Resiliency mode); and (2) respond to major coastal storms and flooding by reoccupying select baseline sites and sampling within days of the event (defined as Response mode). For both modes, samples are collected in a consistent manner to minimize bias and maximize quality control by ensuring that all sampling personnel across the region collect, document, and process soil and sediment samples following the procedures outlined in this SOP. Samples are analyzed using four USGS-developed screening methods—inorganic geochemistry, organic geochemistry, pathogens, and biological assays—which are also outlined in this SOP. Because the SCoRR strategy employs a multi-metric approach for sample analyses, this protocol expands upon and reconciles differences in the sample collection protocols outlined in the USGS “National Field Manual for the Collection of Water-Quality Data,” which should be used in conjunction with this SOP. A new data entry and sample tracking system also is presented to ensure all relevant data and metadata are gathered at the sample locations and in the laboratories.

Open-File Report↗

USGS2015

Strategy to evaluate persistent contaminant hazards resulting from sea-level rise and storm-derived disturbances—Study design and methodology for station prioritization

Coastal communities are uniquely vulnerable to sea-level rise (SLR) and severe storms such as hurricanes. These events enhance the dispersion and concentration of natural and anthropogenic chemicals and pathogenic microorganisms that could adversely affect the health and resilience of coastal communities and ecosystems in coming years. The U.S. Geological Survey has developed a strategy to define baseline and post-event sediment-bound environmental health (EH) stressors (hereafter referred to as the Sediment-Bound Contaminant Resiliency and Response [SCoRR] strategy). A tiered, multimetric approach will be used to (1) identify and map contaminant sources and potential exposure pathways for human and ecological receptors, (2) define the baseline mixtures of EH stressors present in sediments and correlations of relevance, (3) document post-event changes in EH stressors present in sediments, and (4) establish and apply metrics to quantify changes in coastal resilience associated with sediment-bound contaminants. Integration of this information provides a means to improve assessment of the baseline status of a complex system and the significance of changes in contaminant hazards due to storm-induced (episodic) and SLR (incremental) disturbances. This report describes the purpose and design of the SCoRR strategy and the methods used to construct a decision support tool to identify candidate sampling stations vulnerable to contaminants that may be mobilized by coastal storms.

Connecticut, Delaware, District of Columbia, Maine↗

USGS2015

Estuarine bed-sediment-quality data collected in New Jersey and New York after Hurricane Sandy, 2013

This report describes a reconnaissance study of estuarine bed-sediment quality conducted June–October 2013 in New Jersey and New York after Hurricane Sandy in October 2012 to assess the extent of contamination and the potential long-term human and ecological impacts of the storm. The study, funded through the Disaster Relief Appropriations Act of 2013 (PL 113-2), was conducted by the U.S. Geological Survey in cooperation with the U.S. Environmental Protection Agency and the National Oceanographic and Atmospheric Administration. In addition to presenting the bed-sediment-quality data, the report describes the study design, documents the methods of sample collection and analysis, and discusses the steps taken to assure the quality of the data. Bed-sediment samples were collected from June to October 2013 from 167 estuarine sites extending from Cape May, New Jersey, to the New York Harbor and the eastern end of Long Island. Each sampling location and study region was characterized by using geographic information to identify potential contaminant sources. Characterizations included land cover, locations and types of businesses (industrial, financial, and others), spills (sewage, chemical, and others), bulk storage facilities, effluent discharges within 2 kilometers of the sampling point, and discharges within inundated and non-inundated regions near the sampling location. Samples were analyzed for particle size, total organic carbon, metals and trace elements, semivolatile organic compounds, wastewater compounds, hormones, and sediment toxicity. Samples were also screened using x-ray fluorescence, Fourier transform infrared spectroscopy, and x-ray diffraction. In addition, bioassays for endocrine disruptors and protein phosphatase 2A inhibition were conducted. The study was designed to provide the data needed to understand the extent and sources of contamination resulting from Hurricane Sandy, to compare the chemistry and toxicity of estuarine bed sediments before and after the storm, and to evaluate the usefulness of rapid screening and bioassay approaches in disaster settings.

New Jersey, New York↗

USGS2014

Tracking geomorphic signatures of watershed suburbanization with multi-temporal LiDAR

Urban development practices redistribute surface materials through filling, grading, and terracing, causing drastic changes to the geomorphic organization of the landscape. Many studies document the hydrologic, biologic, or geomorphic consequences of urbanization using space-for-time comparisons of disparate urban and rural landscapes. However, no previous studies have documented geomorphic changes from development using multiple dates of high-resolution topographic data at the watershed scale. This study utilized a time series of five sequential light detection and ranging (LiDAR) derived digital elevation models (DEMs) to track watershed geomorphic changes within two watersheds throughout development (2002–2008) and across multiple spatial scales (0.01–1 km 2 ). Development-induced changes were compared against an undeveloped forested watershed during the same time period. Changes in elevations, slopes, hypsometry, and surface flow pathways were tracked throughout the development process to assess watershed geomorphic alterations. Results suggest that development produced an increase in sharp topographic breaks between relatively flat surfaces and steep slopes, replacing smoothly varying hillslopes and leading to greater variation in slopes. Examinations of flowpath distributions highlight systematic modifications that favor rapid convergence in unchanneled upland areas. Evidence of channel additions in the form of engineered surface conduits is apparent in comparisons of pre- and post-development stream maps. These results suggest that topographic modification, in addition to impervious surfaces, contributes to altered hydrologic dynamics observed in urban systems. This work highlights important considerations for the use of repeat LiDAR flights in analyzing watershed change through time. Novel methods introduced here may allow improved understanding and targeted mitigation of the processes driving geomorphic changes during development and help guide future research directions for development-based watershed studies.

Geomorphology↗