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USGS2022

HydroBench: Jupyter supported reproducible hydrological model benchmarking and diagnostic tool

Evaluating whether hydrological models are right for the right reasons demands reproducible model benchmarking and diagnostics that evaluate not just statistical predictive model performance but also internal processes. Such model benchmarking and diagnostic efforts will benefit from standardized methods and ready-to-use toolkits. Using the Jupyter platform, this work presents HydroBench, a model-agnostic benchmarking tool consisting of three sets of metrics: 1) common statistical predictive measures, 2) hydrological signature-based process metrics, including a new time-linked flow duration curve and 3) information-theoretic diagnostics that measure the flow of information among model variables. As a test case, HydroBench was applied to compare two model products (calibrated and uncalibrated) of the National Hydrologic Model - Precipitation Runoff Modeling System (NHM-PRMS) at the Cedar River watershed, WA, United States. Although the uncalibrated model has the highest predictive performance, particularly for high flows, the signature-based diagnostics showed that the model overestimates low flows and poorly represents the recession processes. Elucidating why low flows may have been overestimated, the information-theoretic diagnostics indicated a higher flow of information from precipitation to snowmelt to streamflow in the uncalibrated model compared to the calibrated model, where information flowed more directly from precipitation to streamflow. This test case demonstrated the capability of HydroBench in process diagnostics and model predictive and functional performance evaluations, along with their tradeoffs. Having such a model benchmarking tool not only provides modelers with a comprehensive model evaluation system but also provides an open-source tool that can further be developed by the hydrological community.

Frontiers in Earth Sciences↗

USGS2012

The population structure of Escherichia coli isolated from subtropical and temperate soils

While genotypically-distinct naturalized Escherichia coli strains have been shown to occur in riparian soils of Lake Michigan and Lake Superior watersheds, comparative analyses of E. coli populations in diverse soils across a range of geographic and climatic conditions have not been investigated. The main objectives of this study were to: (a) examine the population structure and genetic relatedness of E. coli isolates collected from different soil types on a tropical island (Hawaii), and (b) determine if E. coli populations from Hawaii and temperate soils (Indiana, Minnesota) shared similar genotypes that may be reflective of biome-related soil conditions. DNA fingerprint and multivariate statistical analyses were used to examine the population structure and genotypic characteristics of the E. coli isolates. About 33% (98 of 293) of the E. coli from different soil types and locations on the island of Oahu, Hawaii, had unique DNA fingerprints, indicating that these bacteria were relatively diverse; the Shannon diversity index for the population was 4.03. Nearly 60% (171 of 293) of the E. coli isolates from Hawaii clustered into two major groups and the rest, with two or more isolates, fell into one of 22 smaller groups, or individual lineages. Multivariate analysis of variance of 89, 21, and 106 unique E. coli DNA fingerprints for Hawaii, Indiana, and Minnesota soils, respectively, showed that isolates formed tight cohesive groups, clustering mainly by location. However, there were several instances of clonal isolates being shared between geographically different locations. Thus, while nearly identical E. coli strains were shared between disparate climatologically- and geographically-distinct locations, a vast majority of the soil E. coli strains were genotypically diverse and were likely derived from separate lineages. This supports the hypothesis that these bacteria are not unique and multiple genotypes can readily adapt to become part of the soil autochthonous microflora.

Hawai'i, Indiana, Minnesota↗

USGS2019

Differentiating anthropogenic and natural sources of uranium by geochemical fingerprinting of groundwater at the Homestake Uranium Mill, Milan, New Mexico, USA

A multiparameter geochemical-isotopic fingerprinting approach was used to differentiate natural and anthropogenic signatures of uranium contamination near the Homestake uranium mill site (Site), near Milan, New Mexico, USA. The Site consists of two tailings piles from milling operations and groundwater contamination from these tailings have been noted. The Site lies within the lower San Mateo Creek Basin with multiple regional sources of U contamination from mining and mill operations and is underlain by a heterogeneous alluvial aquifer, which is underlain by basement rock of the Chinle Group and the lowermost San Andres-Glorieta aquifer. To help decipher signatures, several statistical approaches were used including PCA, NMDS, and cluster analysis. Trilinear piper diagrams indicate two end member water types at the Site, sulfate-Na-K and sulfate-Ca. Natural alluvial aquifer groundwater in this area, relatively unaffected by mining or milling, appears to be more dominated by bicarbonate than sulfate and the deeper San Andres-Glorieta aquifer that has a mixture of sulfate and bicarbonate. Uranium concentrations from the Site fall into three broad categories, less than the drinking water standard of 30 µg/L (n=3), from 30 to 100 µg/L (n=9) and greater than 100 µg/L (n=8). Component loadings in a principal component analysis are highest for uranium isotopes, 228Ra, gross alpha-beta, molybdenum, chloride, uranium, and sodium, which affect the similarities or differences among wells sampled. Results suggest that several alluvial wells upgradient from the Site have anthropogenic fingerprints from regional sources related to upgradient mining. Wells with higher uranium concentrations have uranium activity ratios close to 1, which is indicative of mining or milling signatures. These same wells have elevated radon activities. This information can be used to inform Site managers on the source of water related to uranium at the Site and provide an approach for geochemical fingerprinting.

New Mexico↗

USGS2020

Understanding the relationship between stream metabolism and biological assemblages

Biological assemblages are commonly used for assessing stream health, but there is increased interest among the freshwater research community in incorporating measures of stream function, such as metabolism, to strengthen stream-health assessments. Presently, there is limited information about the relationships between stream metabolism and biological assemblages, along with the measurement period required to relate metabolism with stream biota. Our study assessed which environmental factors explained stream metabolism and to what degree stream metabolism and minimum dissolved oxygen (DOmin) were related to invertebrate and fish metrics in streams distributed across several regions of the United States. Furthermore, we evaluated the number of metabolism monitoring days required for maximizing the ability to detect relationships between stream metabolism and biological assemblage metrics. We sampled 17 sites distributed among reference, agricultural, and urban areas for stream metabolism, nutrients, habitat, and biological assemblages (invertebrates and fishes). Overall, sites were heterotrophic with gross primary production (GPP) and ecosystem respiration (ER) related primarily to days since last high flow, canopy cover, maximum water temperature, and total phosphorus. DOmin was related to days since last high flow, canopy cover, and maximum water temperature. We were unable to determine a clear statistical relationship between invertebrate metrics (invertebrate richness; Ephemeroptera, Plecoptera, and Trichoptera richness; and scraper-taxa richness) and GPP, ER, or DOmin. In contrast, we found that 2 fish-assemblage metrics were associated with stream metabolism and DOmin. A fish multimetric index (FMMI) was negatively correlated with GPP ( r = −0.5, p = 0.048) and positively correlated with DOmin ( r = 0.47, p = 0.06). Percentage of omnivorous fish taxa was positively correlated with GPP ( r = 0.72, p = 0.001) and ER ( r = 0.55, p = 0.02) and negatively correlated with DOmin ( r = −0.67, p = 0.003). The lack of detected relationships for most of the biological-assemblage metrics with stream metabolism may be partially due to 1 or more factors, including high variability, low sample size, limited range in metabolism values, assemblage metrics used, and geographic distribution of sites. Comparing stream-metabolism measurement periods (in days) to biological-assemblage metrics indicated that optimum correlations occurred at 2 d for DOmin, 3 d for GPP, and 14 d for ER. Although our study found limited relationships of stream metabolism and DOmin with biological assemblages, future studies should consider a larger sample size (≥30), 14-d or longer metabolism measurement period, and assessment of other taxa-specific or assemblage metrics.

Freshwater Science↗

USGS2016

Combined effects of projected sea level rise, storm surge, and peak river flows on water levels in the Skagit Floodplain

Current understanding of the combined effects of sea level rise (SLR), storm surge, and changes in river flooding on near-coastal environments is very limited. This project uses a suite of numerical models to examine the combined effects of projected future climate change on flooding in the Skagit floodplain and estuary. Statistically and dynamically downscaled global climate model scenarios from the ECHAM-5 GCM were used as the climate forcings. Unregulated daily river flows were simulated using the VIC hydrology model, and regulated river flows were simulated using the SkagitSim reservoir operations model. Daily tidal anomalies (TA) were calculated using a regression approach based on ENSO and atmospheric pressure forcing simulated by the WRF regional climate model. A 2-D hydrodynamic model was used to estimate water surface elevations in the Skagit floodplain using resampled hourly hydrographs keyed to regulated daily flood flows produced by the reservoir simulation model, and tide predictions adjusted for SLR and TA. Combining peak annual TA with projected sea level rise, the historical (1970–1999) 100-yr peak high water level is exceeded essentially every year by the 2050s. The combination of projected sea level rise and larger floods by the 2080s yields both increased flood inundation area (+ 74%), and increased average water depth (+ 25 cm) in the Skagit floodplain during a 100-year flood. Adding sea level rise to the historical FEMA 100-year flood resulted in a 35% increase in inundation area by the 2040's, compared to a 57% increase when both SLR and projected changes in river flow were combined.

Washington↗

USGS2017

Streamflow characteristics from modelled runoff time series: Importance of calibration criteria selection

Ecologically relevant streamflow characteristics (SFCs) of ungauged catchments are often estimated from simulated runoff of hydrologic models that were originally calibrated on gauged catchments. However, SFC estimates of the gauged donor catchments and subsequently the ungauged catchments can be substantially uncertain when models are calibrated using traditional approaches based on optimization of statistical performance metrics (e.g., Nash–Sutcliffe model efficiency). An improved calibration strategy for gauged catchments is therefore crucial to help reduce the uncertainties of estimated SFCs for ungauged catchments. The aim of this study was to improve SFC estimates from modeled runoff time series in gauged catchments by explicitly including one or several SFCs in the calibration process. Different types of objective functions were defined consisting of the Nash–Sutcliffe model efficiency, single SFCs, or combinations thereof. We calibrated a bucket-type runoff model (HBV – Hydrologiska Byråns Vattenavdelning – model) for 25 catchments in the Tennessee River basin and evaluated the proposed calibration approach on 13 ecologically relevant SFCs representing major flow regime components and different flow conditions. While the model generally tended to underestimate the tested SFCs related to mean and high-flow conditions, SFCs related to low flow were generally overestimated. The highest estimation accuracies were achieved by a SFC-specific model calibration. Estimates of SFCs not included in the calibration process were of similar quality when comparing a multi-SFC calibration approach to a traditional model efficiency calibration. For practical applications, this implies that SFCs should preferably be estimated from targeted runoff model calibration, and modeled estimates need to be carefully interpreted.

Tennessee↗

USGS2020

Post-fire vegetation response in a repeatedly burned low-elevation sagebrush steppe protected area provides insights about resilience and invasion resistance

Sagebrush steppe ecosystems are threatened by human land-use legacies, biological invasions, and altered fire and climate dynamics. Steppe protected areas are therefore of heightened conservation importance but are few and vulnerable to the same impacts broadly affecting sagebrush steppe. To address this problem, sagebrush steppe conservation science is increasingly emphasizing a focus on resilience to fire and resistance to non-native annual grass invasion as a decision framework. It is well-established that the positive feedback loop between fire and annual grass invasion is the driving process of most contemporary steppe degradation. We use a newly developed ordinal zero-augmented beta regression model fit to large-sample vegetation monitoring data from John Day Fossil Beds National Monument, USA, spanning 7 years to evaluate fire responses of two native perennial foundation bunchgrasses and two non-native invasive annual grasses in a repeatedly burned, historically grazed, and inherently low-resilient protected area. We structured our model hierarchically to support inferences about variation among ecological site types and over time after also accounting for growing-season water deficit, fine-scale topographic variation, and burn severity. We use a state-and-transition conceptual diagram and abundances of plants listed in ecological site reference conditions to formalize our hypothesis of fire-accelerated transition to ecologically novel annual grassland. Notably, big sagebrush ( Artemisia tridentata ) and other woody species were entirely removed by fire. The two perennial grasses, bluebunch wheatgrass ( Pseudoroegneria spicata ) and Thurber's needlegrass ( Achnatherum thurberianum ) exhibited fire resiliency, with no apparent trend after fire. The two annual grasses, cheatgrass ( Bromus tectorum ) and medusahead ( Taeniatherum caput-medusae ), increased in response to burn severity, most notably medusahead. Surprisingly, we found no variation in grass cover among ecological sites, suggesting fire-driven homogenization as shrubs were removed and annual grasses became dominant. We found contrasting responses among all four grass species along gradients of topography and water deficit, informative to protected-area conservation strategies. The fine-grained influence of topography was particularly important to variation in cover among species and provides a foothold for conservation in low-resilient, aridic steppe. Broadly, our study demonstrates how to operationalize resilience and resistance concepts for protected areas by integrating empirical data with conceptual and statistical models.

Oregon↗

USGS2025

Vegetation community monitoring: Forest structure in Klamath Network parks

The Klamath Network, comprising six national park units in northern California and southern Oregon, initiated a vegetation monitoring protocol in 2011 to discern ecologically significant vegetation trends in these parks. The premise of the protocol is that multivariate analyses of species composition data is the most robust means for early detection of vegetation change over time. Here, we present these community metrics based on our sampling efforts from 2011 to 2019. Observations from the first sampling event (2011–2013) were used to establish baseline conditions for the vegetation communities. Observations from subsequent sampling in 2014–2019 were used to identify potential temporal variation in forest structure across habitat types and parks. Park landscapes were categorized into three strata: matrix (low- to mid-elevation upland habitats), riparian (within 10 m of a perennial stream), and high-elevation (above a predefined elevation, park-specific). At the onset of the network’s vegetation monitoring protocol, 241 permanent plots were established at random locations across the three strata. We present summary statistics from three repeated samplings (2011–2019) of each plot, describing variation in forest structure across broad habitat types and parks. Observable differences in forest structure aligned with expected productivity gradients across the parks. Measures of forest structure (vegetation cover, stem density, basal area, tree heights, height to live crown, shrub cover, and surface fuels) were generally higher in mesic sites, compared to sites located in more arid, continental climates. Differences across sampling frames also followed this general pattern of productivity. Matrix and riparian sampling frames had similar ranges of values in most cases, while high elevation sites had relatively lower stem density, basal area, shrub cover, fuels, and recruitment. Notably, we observed a relative lack of change in forest structure over time. This is not surprising given the relatively short (six-year) timespan of observations in each park. The fourth set of Klamath Network surveys (2021–2023) is likely to show substantial changes in vegetation cover and forest structure, particularly for parks that have recently experienced major fires. Continued long-term vegetation monitoring is crucial for understanding ecosystem responses to a rapidly changing world. This report on vegetation composition is the second in a series; upcoming reports will analyze structure and function, aiming to detect spatiotemporal trends.

California, Oregon↗

USGS2012

Zinc isotope investigation of surface and pore waters in a mountain watershed impacted by acid rock drainage

The pollution of natural waters with metals derived from the oxidation of sulfide minerals like pyrite is a global environmental problem. However, the metal loading pathways and transport mechanisms associated with acid rock drainage reactions are often difficult to characterize using bulk chemical data alone. In this study, we evaluated the use of zinc (Zn) isotopes to complement traditional geochemical tools in the investigation of contaminated waters at the former Waldorf mining site in the Rocky Mountains, Colorado, U.S.A. Geochemical signatures and statistical analysis helped in identifying two primary metal loading pathways at the Waldorf site. The first was characterized by a circumneutral pH, high alkalinity, and high Zn/Cd ratios. The second was characterized by acidic pHs and low Zn/Cd ratios. Zinc isotope signatures in surface water samples collected across the site were remarkably similar (the δ 66 Zn, relative to JMC 3-0749-L, for most samples ranged from 0.20 to 0.30‰ ± 0.09‰ 2σ). This probably suggests that the ultimate source of Zn is consistent across the Waldorf site, regardless of the metal loading pathway. The δ 66 Zn of pore water samples collected within a nearby metal-impacted wetland area, however, were more variable, ranging from 0.20 to 0.80‰ ± 0.09‰ 2σ. Here the Zn isotopes seemed to reflect differences in groundwater flow pathways. However, a host of secondary processes might also have impacted Zn isotopes, including adsorption of Zn onto soil components, complexation of Zn with dissolved organic matter, uptake of Zn into plants, and the precipitation of Zn during the formation of reduced sulfur species. Zinc isotope analysis proved useful in this study; however, the utility of this isotopic tool would improve considerably with the addition of a comprehensive experimental foundation for interpreting the complex isotopic relationships found in soil pore waters.

Colorado↗

USGS2015

Evaluation of statistical treatments of left-censored environmental data using coincident uncensored data sets. II. Group comparisons

The main classes of statistical treatments that have been used to determine if two groups of censored environmental data arise from the same distribution are substitution methods, maximum likelihood (MLE) techniques, and nonparametric methods. These treatments along with using all instrument-generated data (IN), even those less than the detection limit, were evaluated by examining 550 data sets in which the true values of the censored data were known, and therefore “true” probabilities could be calculated and used as a yardstick for comparison. It was found that technique “quality” was strongly dependent on the degree of censoring present in the groups. For low degrees of censoring (<25% in each group), the Generalized Wilcoxon (GW) technique and substitution of √2/2 times the detection limit gave overall the best results. For moderate degrees of censoring, MLE worked best, but only if the distribution could be estimated to be normal or log-normal prior to its application; otherwise, GW was a suitable alternative. For higher degrees of censoring (each group >40% censoring), no technique provided reliable estimates of the true probability. Group size did not appear to influence the quality of the result, and no technique appeared to become better or worse than other techniques relative to group size. Finally, IN appeared to do very well relative to the other techniques regardless of censoring or group size.

Environmental Science & Technology↗

USGS2005

Attitudinal survey component of the study Quantity, quality, and support for research in the U.S. Fish and Wildlife Service: An organizational assessment : Report of methods and frequencies

The U.S. Fish and Wildlife Service (FWS) is responsible for managing the Nation’s fish and wildlife resources so that these trust resources are preserved for the present and future use and enjoyment of the citizens of the United States. The FWS achieves this mission by managing many programs. These include the national system of refuges and fish hatcheries, Fish and Wildlife Management Assistance Offices, migratory birds program, law enforcement, and working with tribal, state, and other Federal agencies to ensure protection of threatened and endangered species. Another role of the FWS is consulting with tribal, state, and other Federal agencies and private sector interests on the best conservation management practices consistent with Federal law. Each of these activities requires a workforce that is recognized for its professionalism, dedication to public service, and command of expert knowledge. Recognition for expert knowledge in fish and wildlife conservation is demonstrated, in part, when FWS personnel direct, conduct, or report research that is well-designed to answer questions of importance for natural resource management. The data reported in this document are one part of a three-part study of the status of organizational support for research in FWS, which was commissioned by the Directorate of the FWS. Funding for this study was provided by the FWS, and the Science Support Program of the U.S. Geological Survey (USGS). In 1994, the biological research functions of the FWS were transferred to the National Biological Survey, and subsequently into the USGS. This transfer was principally accomplished by moving whole research units from one agency to another. The result was that some employees whose positions were involved with research were not transferred. In addition, some research, information, and management needs of the FWS have continued to be met by studies conducted within the FWS itself. Although the FWS relies on the USGS and others for most basic research investigations, the FWS also conducts its own studies to meet management needs. Because it is vital for FWS employees to be able to conduct such tactical and applied research tasks in a timely manner, the agency must promote the culture necessary to support and encourage these activities. Such research activities are spread widely across the various programs of the FWS, and there is presently no collective, formal, or systematic record of planned or existing research activities. In commissioning this organizational assessment research, the Directorate of the FWS recognized that it would be to the advantage of the agency to more fully understand its research capacity. To develop a clearer picture of the nature, extent, quality, and degree of administrative support available for conducting research within the FWS, investigations have been undertaken to: 1. identify positions in the FWS that may include, in whole or in part, a component of scientific research; 2. identify organizational units within the FWS that may conduct research as a significant portion of their mission; and 3. assess the attitudes of employees and managers about the obstacles and opportunities for scientific research existing within the FWS by using a scaled-response survey instrument. The findings presented in this report represent the basic results derived from the attitude assessment survey conducted in the last quarter of 2004. The findings set forth in this report are the frequency distributions for each question in the survey instrument for all respondents. The only statistics provided are descriptive in character - namely, means and associated standard deviations.

Open-File Report↗

USGS2015

Patterns and predictability in the intra-annual organic carbon variability across the boreal and hemiboreal landscape

Factors affecting total organic carbon (TOC) concentrations in 215 watercourses across Sweden were investigated using parameter parsimonious regression approaches to explain spatial and temporal variabilities of the TOC water quality responses. We systematically quantified the effects of discharge, seasonality, and long-term trend as factors controlling intra-annual (among year) and inter-annual (within year) variabilities of TOC by evaluating the spatial variability in model coefficients and catchment characteristics (e.g. land cover, retention time, soil type). Catchment area (0.18–47,000 km 2 ) and land cover types (forests, agriculture and alpine terrain) are typical for the boreal and hemiboreal zones across Fennoscandia. Watercourses had at least 6 years of monthly water quality observations between 1990 and 2010. Statistically significant models (p < 0.05) describing variation of TOC in streamflow were identified in 209 of 215 watercourses with a mean Nash-Sutcliffe efficiency index of 0.44. Increasing long-term trends were observed in 149 (70%) of the watercourses, and intra-annual variation in TOC far exceeded inter-annual variation. The average influences of the discharge and seasonality terms on intra-annual variations in daily TOC concentration were 1.4 and 1.3 mg l − 1 (13 and 12% of the mean annual TOC), respectively. The average increase in TOC was 0.17 mg l − 1 year − 1 (1.6% year − 1 ). Multivariate regression with over 90 different catchment characteristics explained 21% of the spatial variation in the linear trend coefficient, less than 20% of the variation in the discharge coefficient and 73% of the spatial variation in mean TOC. Specific discharge, water residence time, the variance of daily precipitation, and lake area, explained 45% of the spatial variation in the amplitude of the TOC seasonality. Because the main drivers of temporal variability in TOC are seasonality and discharge, first-order estimates of the influences of climatic variability and change on TOC concentration should be predictable if the studied catchments continue to respond similarly.

Science of the Total Environment↗

USGS2025

Insights and strategic opportunities from the USGS 2024 Per- and Polyfluoroalkyl Substances (PFAS) Interagency Workshop

Introduction In 2021, the U.S. Geological Survey (USGS) published Circular 1490 titled, “Integrated Science for the Study of Perfluoroalkyl and Polyfluoroalkyl Substances (PFAS) in the Environment: A Strategic Science Vision for the U.S. Geological Survey” (Tokranov and others, 2021). Circular 1490 was created to be a resource for USGS scientists prioritizing and planning research related to per- and polyfluoroalkyl substances (PFAS) and to be a guide for developing partnerships with other scientists, State and Federal agencies, and stakeholders engaged in PFAS research and management and mitigation of the environmental and human-health effects of PFAS. This USGS PFAS Strategic Science Vision document was intended to be the foundation for a “living strategic vision,” periodically providing updates on the state of USGS PFAS research, emerging PFAS data gaps and needs, and progress on interagency and stakeholder PFAS partnerships and priorities. To meet this objective, the USGS planned to host an Interagency and Stakeholder PFAS Workshop every 2–3 years. During September 10–12, 2024, the USGS hosted the first Interagency and Stakeholder PFAS Workshop in Reston, Virginia. The Workshop brought together experts from other Federal agencies (U.S. Environmental Protection Agency, National Institute of Environmental Health Sciences, Food and Drug Administration, Department of Defense [Air Force, Army]), State agencies (Washington Fish and Wildlife, Virginia Department of Transportation), and academia (Harvard University, University of Maryland) to address key challenges relating to the measurement and modeling of PFAS and the implications for environmental health. Participants engaged in in-depth discussions centered around six pivotal topics related to PFAS: (1) sampling protocols, methods and interpretation; (2) environmental sources, source apportionment, and occurrence; (3) environmental fate and transport; (4) human and wildlife exposure routes and risk; (5) bioconcentration, bioaccumulation, and biomagnification; and (6) ecotoxicology and effects. Each topic had three breakout sessions. A recurrent theme of workshop discussions was how data on a nationwide scale for PFAS occurrence in various environmental matrices, including air, water, food crops, biota, soil, and streambed sediment could help to advance scientific understanding. Participants noted significant geospatial data gaps, particularly in the midwestern and southern United States and the Pacific Northwest. PFAS data collection tends to be more robust along the eastern seaboard and in California. Participants stressed how enhancing the integration of large and small datasets across various agencies could help to support national scale understanding of PFAS. To address these gaps, attendees suggested leveraging datasets from Federal entities like the USGS and the U.S. Department of Defense, State agencies, and municipal utility services to develop predictive contaminant detection and transport models. Improved coordination between water quality programs and USGS research could help to facilitate access to valuable data, leading to comprehensive databases that inform PFAS point (wastewater treatment plants and landfills) and nonpoint (runoff from land, atmospheric deposition, food packaging) sources, environmental transport mechanisms, environmental detection and concentrations, potential exposure routes, and health effects on different biota, including humans. A specific request was made to develop a map demarking the depth of modern (1953 or later) groundwater, which is susceptible to surface-derived anthropogenic (that is, human-made) contamination, based on tritium-age dating. Emphasis was placed on incorporation of hydrology, groundwater flow paths, groundwater–surface water interactions, and landscape factors in predictive statistical models as a step to improve contaminant source identification and tracking. Molecular fingerprinting approaches garnered attention as techniques to link specific PFAS mixtures detected in a sample to environmental sources and levels in biota (Dávila-Santiago and others, 2022). Integrating data from abiotic (that is, water, soil, and air) and biotic (that is, living organisms) systems identified as a research opportunity. For example, understanding the composition of soils and sediments, which include a mixture of mineral, plant, and animal components, could advance understanding of exposure pathways. The discussions highlighted opportunities to explore and understand the potential redistribution and biotic exposures of PFAS from biosolid and wastewater treatment plant effluent land application practices, in addition to atmospheric releases and discharges from landfill and wastewater treatment plants. Participants identified research gaps surrounding how these sources may contribute to contamination and may affect surrounding ecosystems, including a better definition of anthropogenic background concentrations. Moving forward, the collection of co-occurrence data was noted as a means to improve understanding of complex mixtures and to leverage companion modeling efforts focused on areas with high and low contamination levels to identify areas of concern and unaffected resources. Participants emphasized how centralized USGS databases and the establishment of sample-metadata archives can help to ensure that samples are preserved and accessible for future research. In conclusion, the workshop participants identified opportunities to bridge data gaps and improve measurement techniques, modeling frameworks, databases, and communication, to enhance the understanding of PFAS and their effects on environmental and human health. Upon completion of the workshop, participants indicated an interest in developing strategic data collection, modeling, and analytical approaches to address these challenges.

Open-File Report↗

USGS2021

Movement of synthetic organic compounds in the food web after the introduction of invasive quagga mussels (Dreissena bugensis) in Lake Mead, Nevada and Arizona, USA

Introductions of dreissenid mussels in North America have been a significant concern over the last few decades. This study assessed the distribution of synthetic organic compounds (SOCs) in the food web of Lake Mead, Nevada/Arizona, USA and how this distribution was influenced by the introduction of invasive quagga mussels. A clear spatial gradient of SOC concentrations in water was observed between lake basins downstream of populated areas and more rural areas. Within the food web, trophic magnification factors (TMF) indicated statistically significant biomagnification for nine, and biodilution for two, of 22 SOCs examined. The highest value recorded was for PCB 118 (TMF, 5.14), and biomagnification of methyl triclosan (TMF, 3.85) was also apparent. Biodilution was observed for Tonalide® (0.06) and Galaxolide® (0.38). Total SOC concentration in quagga mussels was higher than in three pelagic fishes. Also, 19 of 20 SOC examined in Largemouth Bass ( Micropterus salmoides ) had substantially lower concentrations in 2013, when quagga mussels had become well established, than in 2007/08, soon after quagga mussels were introduced. Estimates of SOC concentrations in the water column and quagga mussels suggest that a considerable portion (~10.5%) of the SOC mass in the lake has shifted from the pelagic to the benthic environments due to quagga mussel growth. These observations suggest that benthic species, such as the endangered Razorback Sucker, may be experiencing increased risk of SOC exposure. In addition, stable isotope analysis (carbon and nitrogen) indicated a decrease in the nutritional value of zooplankton to consumers (e.g., Razorback Sucker larvae) since quagga mussels became established. These changes could affect Razorback Sucker larval survival and recruitment. Results from this study strongly suggest that the introduction of quagga mussels has greatly altered the dynamics of SOCs and other processes in the food web of Lake Mead.

Arizona, Nevada↗

USGS2025

A monitoring framework to assess forest bird population response to landscape scale mosquito suppression using the Incompatible Insect Technique

The Birds, Not Mosquitoes Monitoring and Support Science Working Group detailed methods for monitoring the population response of Hawaiian forest birds during implementation of the Incompatible Insect Technique (IIT) on the islands of Maui and Kauaʻi. The group prioritized methods for measuring the influence of mosquito suppression on populations within IIT treatment and control areas and identified focal species for IIT efficacy monitoring in birds. Three primary metrics were established to assess the impact of IIT on vulnerable species: population demography, density, and geographic range. Each metric can be evaluated using multiple methods. This report reviews those methods, with emphasis on approaches supported by pre-IIT baseline data and compatible with a before-after control-impact (BACI) study design for evaluating population responses over time. Focal avian species were selected based on population size estimates, fecundity, and disease susceptibility. We identified ʻākohekohe (Palmeria dolei), ʻiʻiwi (Drepanis coccinea), Maui ʻalauahio (Paroreomyza montana), Hawaiʻi ʻamakihi (Chlorodrepanis virens), Kauaʻi ʻamakihi (Chlorodrepanis stejnegeri), Kauaʻi ʻelepaio (Chasiempis sclateri), and ʻanianiau (Magumma parva) as focal species for monitoring population level response to disease suppression. Populations of kiwikiu (Pseudonestor xanthophrys), ʻakikiki (Oreomystis bairdi), akekeʻe (Loxops caeruleirostris), and the ʻiʻiwi population on Kauaʻi may be too small (e.g., <100 individuals) to effectively monitor, and it is unlikely that sufficient data can be collected from these birds to show IIT efficacy in a relatively short time frame (i.e., 5–10 years). Despite the logistical challenges to IIT implementation, there is potential to maintain disease-free status in individual populations of birds. Indeed, the continued existence of these critically endangered species in the wild within or near IIT treatment areas could be considered an accomplishment of IIT, given the current predictions for their extinction in the wild within 5–10 years. Demographic monitoring methods, including territory mapping, nest monitoring, mist-netting, and mark-recapture studies, provide direct evidence of survivorship and reproductive output. When combined with disease surveillance, these approaches could provide the most robust evidence of increased survivorship and productivity resulting from avian malaria suppression via IIT. However, demographic studies require several years of monitoring to achieve statistically robust BACI comparisons of survivorship and are more difficult to implement relative to other approaches. Given that these field efforts are labor-intensive and heavily reliant on personnel availability and funding, demographic monitoring could be conducted when adequate resources permit. On both Maui and Kauaʻi, passive acoustic monitoring (PAM) was identified as a priority method for monitoring the range, occupancy, and relative abundance of focal species. Autonomous recording units (ARUs) can record bird vocalizations in remote areas for several months. Innovative machine learning techniques permit rapid and semi-autonomous identification of most endemic honeycreepers on each island, maximizing sampling efficiencies and minimizing data processing costs. We predict mosquito suppression could support expansion of focal species into areas where disease transmission is currently excluding these species and expect acoustic monitoring data of focal species to reflect these spatial patterns. Additionally, the relative occupancy and call densities can be monitored temporally and spatially to assess the efficacy of IIT for supporting positive growth in vulnerable bird species. It is not yet clear if PAM is more effective than other methods, such as distance sampling, for detecting trends in the densities of rare species. However, the increased detections resulting from the larger sample size per observation point using ARUs will likely improve accuracy in detecting changes in species’ ranges. Collection of during and after treatment data within the BACI design could help to provide critical information to track avian population response, recovery, and potential range expansion related to IIT efforts. Point-transect distance sampling (point-counts) was prioritized as a method for monitoring population densities of focal species. Extensive historical sampling across focal species’ ranges provides a robust baseline for detecting change. These counts provide updated population densities and can be used to assess the distribution of focal species within IIT treatment areas. However, detecting subtle population changes with traditional distance sampling requires intensive spatial and temporal effort and may be less effective for rare species. To improve resolution, density surface modeling can integrate multiple data sources (e.g., point-counts, PAM, spot-mapping, and resightings) to estimate species-specific densities at finer spatial scales, including within and outside IIT treatment areas. This integrated modeling approach allows for detailed comparisons and may reveal early signs of recovery, including recolonization of formerly occupied sites. A coordinated monitoring strategy can allow managers to evaluate the success of mosquito suppression as a conservation intervention and support adaptive management in the face of emerging challenges.

Hawaii↗

USGS2022

A comparison of orbital-resolution, Late Pleistocene Alkenone and foraminiferal assemblage-based sea surface temperature reconstructions from the Southwest Pacific

Global and regional reconstructions of past climate conditions often incorporate sea surface temperature (SST) estimates from multiple proxies because not every paleotemperature proxy is applicable in all geographic locations. This practice of assimilating estimates from different proxies in global or regional temperature syntheses makes the implicit assumption that estimates derived from different proxies can be meaningfully intercompared. However, evidence to support the validity of this assumption is limited. Using paleotemperature data from sediments collected from ODP Site 1125 in the Southwest Pacific, we conduct a ∼1 Myr, orbital-scale SST proxy comparison of a recently published alkenone-derived SST record with a previously published foraminiferal assemblage-based SST record. These alkenone and foraminiferal assemblage SST datasets show strong structural similarity and yield remarkably similar estimates for basic climate metrics, including mean, median, standard deviation, and range. Statistical analysis indicates that the correlation between the two SST records is highly significant. In the spectral domain, the records share the same dominant 100 kyr beat, are coherent and in phase with each other at this frequency, and have the same coherence and phase relationship with benthic foraminiferal δ 18 O. Results from this work demonstrate that these two proxies would yield very similar estimates for the paleoclimate metrics most commonly used in empirical paleoclimate reconstructions that seek to document the evolution of climate over this interval. However, significant disparities between SST estimates derived from the two proxies exist for some time periods, particularly during glacial and interglacial extrema. This comparison suggests that treating estimates from these proxies as equivalent in studies that focus on short time windows (e.g. a few thousand to tens-of-thousands of years), particularly in investigations that seek to characterize glacial or interglacial extrema, could be potentially problematic. However, the sensitive location of Site 1125, just north of the Subtropical Front, likely accentuates the difference between temperature estimates from these proxies, which may be attenuated in other oceanographic settings. We attribute the discrepancies between the two SST records to two main causes: seasonal leakages of cold water across the Subtropical Front during glacial extrema and differential seasonality of maximum alkenone and foraminiferal production.

Quaternary Science Reviews↗

USGS2020

Estimation of nonlinear water-quality trends in high-frequency monitoring data

Recent advances in high-frequency water-quality sensors have enabled direct measurements of physical and chemical attributes in rivers and streams nearly continuously. Water-quality trends can be used to identify important watershed-scale changes driven by natural and anthropogenic influences. Statistical methods to estimate trends using high-frequency data are lacking. To address this gap, an evaluation of the generalized additive model (GAM) approach to test for trends in high-frequency data was conducted. Our proposed framework includes methods for handling serial correlation, trend estimation and slope-change detection, and trend interpretation at arithmetic scale for log-transformed variables. Water-temperature and turbidity data, representing two analytes with different temporal patterns, collected from the James River at Cartersville, Virginia, USA, were chosen for this analysis. Results indicated that the model, including flow, season, time covariates, and interaction between flow and season performed well for both analytes. The same model structure was applied to specific conductance data, collected from a small highly urbanized watershed, with satisfactory model performance. The water temperature GAM results indicated that the significant decreasing-then-increasing patterns after 2012 were mainly driven by air temperature changes. The turbidity trend was not significant over time. The specific conductance results showed a consistently upward trend over the last decade due to ever-increasing urbanization in the small watershed. This study suggests that the GAM method has great potential as a useful tool for trend analysis on high-frequency data, and for informing watershed managers of hydro-climatic and human influences on water quality by detecting crucial signal variation over time.

Chesapeake Bay watershed↗

USGS2006

Sensitivity of Last Glacial Maximum climate to uncertainties in tropical and subtropical ocean temperatures

The faunal and floral gradients that underlie the CLIMAP (1981) sea-surface temperature (SST) reconstructions for the Last Glacial Maximum (LGM) reflect ocean temperature gradients and frontal positions. The transfer functions used to reconstruct SSTs from biologic gradients are biased, however, because at the warmest sites they display inherently low sensitivity in translating fauna to SST and they underestimate SST within the euphotic zones where the pycnocline is strong. Here we assemble available data and apply a statistical approach to adjust for hypothetical biases in the faunal-based SST estimates of LGM temperature. The largest bias adjustments are distributed in the tropics (to address low sensitivity) and subtropics (to address underestimation in the euphotic zones). The resulting SSTs are generally in better agreement than CLIMAP with recent geochemical estimates of glacial-interglacial temperature changes. We conducted a series of model experiments using the GENESIS general atmospheric circulation model to assess the sensitivity of the climate system to our bias-adjusted SSTs. Globally, the new SST field results in a modeled LGM surface-air cooling relative to present of 6.4 ??C (1.9 ??C cooler than that of CLIMAP). Relative to the simulation with CLIMAP SSTs, modeled precipitation over the oceans is reduced by 0.4 mm d-1 (an anomaly -0.4 versus 0.0 mm d-1 for CLIMAP) and increased over land (an anomaly -0.2 versus -0.5 mm d-1 for CLIMAP). Regionally strong responses are induced by changes in SST gradients. Data-model comparisons indicate improvement in agreement relative to CLIMAP, but differences among terrestrial data inferences and simulated moisture and temperature remain. Our SSTs result in positive mass balance over the northern hemisphere ice sheets (primarily through reduced summer ablation), supporting the hypothesis that tropical and subtropical ocean temperatures may have played a role in triggering glacial changes at higher latitudes.

Quaternary Science Reviews↗