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At least 523 records · Page 29Linked to original sources
USGS2011

Source-water susceptibility assessment in Texas—Approach and methodology

Public water systems provide potable water for the public's use. The Safe Drinking Water Act amendments of 1996 required States to prepare a source-water susceptibility assessment (SWSA) for each public water system (PWS). States were required to determine the source of water for each PWS, the origin of any contaminant of concern (COC) monitored or to be monitored, and the susceptibility of the public water system to COC exposure, to protect public water supplies from contamination. In Texas, the Texas Commission on Environmental Quality (TCEQ) was responsible for preparing SWSAs for the more than 6,000 public water systems, representing more than 18,000 surface-water intakes or groundwater wells. The U.S. Geological Survey (USGS) worked in cooperation with TCEQ to develop the Source Water Assessment Program (SWAP) approach and methodology. Texas' SWAP meets all requirements of the Safe Drinking Water Act and ultimately provides the TCEQ with a comprehensive tool for protection of public water systems from contamination by up to 247 individual COCs. TCEQ staff identified both the list of contaminants to be assessed and contaminant threshold values (THR) to be applied. COCs were chosen because they were regulated contaminants, were expected to become regulated contaminants in the near future, or were unregulated but thought to represent long-term health concerns. THRs were based on maximum contaminant levels from U.S. Environmental Protection Agency (EPA)'s National Primary Drinking Water Regulations. For reporting purposes, COCs were grouped into seven contaminant groups: inorganic compounds, volatile organic compounds, synthetic organic compounds, radiochemicals, disinfection byproducts, microbial organisms, and physical properties. Expanding on the TCEQ's definition of susceptibility, subject-matter expert working groups formulated the SWSA approach based on assumptions that natural processes and human activities contribute COCs in quantities that vary in space and time; that increased levels of COC-producing activities within a source area may increase susceptibility to COC exposure; and that natural and manmade conditions within the source area may increase, decrease, or have no observable effect on susceptibility to COC exposure. Incorporating these assumptions, eight SWSA components were defined: identification, delineation, intrinsic susceptibility, point- and nonpoint-source susceptibility, contaminant occurrence, area-of-primary influence, and summary components. Spatial datasets were prepared to represent approximately 170 attributes or indicators used in the assessment process. These primarily were static datasets (approximately 46 gigabytes (GB) in size). Selected datasets such as PWS surface-water-intake or groundwater-well locations and potential source of contamination (PSOC) locations were updated weekly. Completed assessments were archived, and that database is approximately 10 GB in size. SWSA components currently (2011) are implemented in the Source Water Assessment Program-Decision Support System (SWAP-DSS) computer software, specifically developed to produce SWSAs. On execution of the software, the components work to identify the source of water for the well or intake, assess intrinsic susceptibility of the water- supply source, assess susceptibility to contamination with COCs from point and nonpoint sources, identify any previous detections of COCs from existing water-quality databases, and summarize the results. Each water-supply source's susceptibility is assessed, source results are weighted by source capacity (when a PWS has multiple sources), and results are combined into a single SWSA for the PWS.'SWSA reports are generated using the software; during 2003, more than 6,000 reports were provided to PWS operators and the public. The ability to produce detailed or summary reports for individual sources, and detailed or summary reports for a PWS, by COC or COC group was a unique capability of SWAP-DSS. In 2004, the TCEQ began a rotating schedule for SWSA wherein one-third of PWSs statewide would be assessed annually, or sooner if protection-program activities deemed it necessary, and that schedule has continued to the present. Cooperative efforts by the TCEQ and the USGS for SWAP software maintenance and enhancements ended in 2011 with the TCEQ assuming responsibility for all tasks.

Texas↗
USGS2014

Unmanned aircraft systems (UAS) activities at the Department of the Interior

The U.S. Department of the Interior (DOI) is responsible for protecting and managing the natural resources and heritage on almost 20% of the land in the United States. The DOI’s mission requires access to remotely sensed data over vast lands, including areas that are remote and potentially dangerous to access. Unmanned Aircraft Systems (UAS) technology has the potential to enable the DOI to be a better steward of the land by: (1) Improving natural hazard forecasting and the analysis of the impacts. (2) Improving the understanding of climate change to better plan for likely impacts. (3) Developing precipitation and evaporation forecasting to better manage water resources. (4) Monitoring Arctic ice change and its impacts on ecosystems, coasts, and transportation. (5) Increasing safety and effectiveness of wildland fire management. (6) Enhancing search and rescue capabilities. (7) Broadening the abilities to monitor environmental or landscape conditions and changes. (8) Better understanding and protecting the Nation’s ecosystems. The initial operational testing and evaluations performed by the DOI have proven that UAS technology can be used to support many of the Department’s activities. UAS technology provides scientists a way to look longer, closer and more frequently at some of Earth’s most remote areas—places that were previously too dangerous or expensive to monitor in detail. The flexibility of operations and relative low cost to purchase and operate Small Unmanned Aerial System (sUAS) enhances the ability to track long-term landscape and environmental change. The initial testing indicates the operational costs are approximately 10% of traditional manned aircraft. In addition, users can quickly assess landscape-altering events such as wildland fires, floods and volcanoes. UAS technology will allow the DOI to do more with less and in the process enhance the Department’s ability to provide unbiased scientific information to help stakeholders make informed decisions. It will also provide a digital baseline record that can be archived and used when monitoring future events or conditions. One possible future scenario has scientists carrying sUAS into the field allowing quick deployment and operation to observe the environment or for emergency response. This scenario could also include a persistent monitoring capability provided by a UAS that can stay airborne over a small geographic area for days or weeks, or possibly longer. While the DOI focus is on sUAS, the Department recognizes that larger UAS systems will also play a role in meeting its mission. The Department anticipates meeting long-duration or specialized acquisition commitments, such as state or national aerial photography, by collaboration with other agencies or through commercial contracts. Even though the DOI continues to evaluate UAS and sensor technology to meet the Department’s mission, some of its bureaus are already moving towards an operational capability. The authors fully anticipate that by 2020 UAS will emerge as one of the primary platforms for DOI remote sensing applications.

Photogrammetric Engineering and Remote Sensing↗
USGS2013

Monitoring to assess progress toward meeting the total maximum daily load for phosphorus in the Assabet River, Massachusetts: phosphorus loads, 2008 through 2010

Wastewater discharges to the Assabet River contribute substantial amounts of phosphorus, which support accumulations of nuisance aquatic plants that are most evident in the river’s impounded reaches during the growing season. To restore the Assabet River’s water quality and aesthetics, the U.S. Environmental Protection Agency required the major wastewater-treatment plants in the drainage basin to reduce the amount of phosphorus discharged to the river by 2012. From October 2008 to December 2010, the U.S. Geological Survey, in cooperation with the Massachusetts Department of Environmental Protection and in support of the requirements of the Total Maximum Daily Load for Phosphorus, collected weekly flow-proportional, composite samples for analysis of concentrations of total phosphorus and orthophosphorus upstream and downstream from each of the Assabet River’s two largest impoundments: Hudson and Ben Smith. The purpose of this monitoring effort was to evaluate conditions in the river before enhanced treatment-plant technologies had effected reductions in phosphorus loads, thereby defining baseline conditions for comparison with conditions following the mandated load reductions. The locations of sampling sites with respect to the impoundments enabled examination of the impoundments’ effects on phosphorus sequestration and on the transformation of phosphorus between particulate and dissolved forms. The study evaluated the differences between loads upstream and downstream from the impoundments throughout the sampling period and compared differences during two seasonal periods of relevance to aquatic plants: April 1 through October 31, the growing season, and November 1 through March 31, the nongrowing season, when existing permit limits allowed average monthly wastewater-treatment-plant-effluent concentrations of 0.75 milligram per liter (growing season) or 1.0 milligram per liter (nongrowing season) for total phosphorus. At the four sampling sites during the growing season, median weekly total phosphorus loads ranged from 110 to 190 kilograms (kg) and median weekly orthophosphorus loads ranged from 17 to 41 kg. During the nongrowing season, median weekly total phosphorus loads ranged from 240 to 280 kg and median weekly orthophosphorus loads ranged from 56 to 66 kg. During periods of low and moderate streamflow, estimated loads of total phosphorus upstream from the Hudson impoundment generally exceeded those downstream during the same sampling periods throughout the study; orthophosphorus loads downstream from the impoundment were typically larger than those upstream. When storm runoff substantially increased the streamflow, loads of total phosphorus and orthophosphorus both tended to be larger downstream than upstream. At the Ben Smith impoundment, both total phosphorus and orthophosphorus loads were generally larger downstream than upstream during low and moderate streamflow, but the differences were not as pronounced as they were at the Hudson impoundment. High flows were also associated with substantially larger total phosphorus and orthophosphorus loads downstream than those entering the impoundment from upstream. In comparing periods of growing- and nongrowing-season loads, the same patterns of loads entering and leaving were observed at both impoundments. That is, at the Hudson impoundment, total phosphorus loads entering the impoundment were greater than those leaving it, and orthophosphorus loads leaving the impoundment were greater than those entering it. At the Ben Smith impoundment, both total phosphorus and orthophosphorus loads leaving the impoundment were greater than those entering it. However, the loads were greater during the nongrowing seasons than during the growing seasons, and the net differences between upstream and downstream loads were about the same. The results indicate that some of the particulate fraction of the total phosphorus loads is sequestered in the Hudson impoundment, where particulate phosphorus probably undergoes some physical and biogeochemical transformations to the dissolved form orthophosphorus. The orthophosphorus may be taken up by aquatic plants or transported out of the impoundments. The results for the Ben Smith impoundment are less clear and suggest net export of total phosphorus and orthophosphorus. Differences between results from the two impoundments may be attributable in part to differences in their sizes, morphology, unmonitored tributaries, riparian land use, and processes within the impoundments that have not been quantified for this study.

Massachusetts↗
USGS2009

Adaptive management: The U.S. Department of the Interior technical guide

The purpose of this technical guide is to present an operational definition of adaptive management, identify the conditions in which adaptive management should be considered, and describe the process of using adaptive management for managing natural resources. The guide is not an exhaustive discussion of adaptive management, nor does it include detailed specifications for individual projects. However, it should aid U.S. Department of the Interior (DOI) managers and practitioners in determining when and how to apply adaptive management. Adaptive management is framed within the context of structured decision making, with an emphasis on uncertainty about resource responses to management actions and the value of reducing that uncertainty to improve management. Though learning plays a key role in adaptive management, it is seen here as a means to an end, namely good management, and not an end in itself. The operational definition used in the guide is adopted from the National Research Council, which characterizes adaptive management as an iterative learning process producing improved understanding and improved management over time: Adaptive management [is a decision process that] promotes flexible decision making that can be adjusted in the face of uncertainties as outcomes from management actions and other events become better understood. Careful monitoring of these outcomes both advances scientific understanding and helps adjust policies or operations as part of an iterative learning process. Adaptive management also recognizes the importance of natural variability in contributing to ecological resilience and productivity. It is not a ‘trial and error’ process, but rather emphasizes learning while doing. Adaptive management does not represent an end in itself, but rather a means to more effective decisions and enhanced benefits. Its true measure is in how well it helps meet environmental, social, and economic goals, increases scientific knowledge, and reduces tensions among stakeholders. Adaptive management as defined here involves ongoing, real-time learning and knowledge creation, both in a substantive sense and in terms of the adaptive process itself. It is described in what follows in a series of 9 steps, as summarized in section 4.1, involving stakeholder involvement, management objectives, management alternatives, predictive models, monitoring plans, decision making, monitoring responses to management, assessment, and adjustment to management actions. An adaptive approach actively engages stakeholders in all phases of a project over its timeframe, facilitating mutual learning and reinforcing the commitment to learning-based management. Adaptive management in DOI is implemented within a legal context that includes statutory authorities such as the National Environmental Policy Act (NEPA), the Endangered Species Act, and the Federal Advisory Committee Act. For many important problems now facing the resource management community, adaptive management holds great promise in reducing the uncertainties that limit the effective management of natural resource systems. For many conservation and management problems, utilizing management itself in an experimental context may be the only feasible way to gain the system understanding needed to improve management. Though it is commonly thought that an adaptive approach can produce results quickly at low cost, the opposite is more likely to be true. An initial investment of time and effort will increase the likelihood of better decision making and resource stewardship in the future, but patience, flexibility, and support are needed over the life of an adaptive management project. For these reasons it is important to carefully consider the potential use of an adaptive approach, and to engage in careful planning and evaluation when adaptive management is used.

Report↗
USGS2014

The presence and distribution of polycyclic aromatic hydrocarbons and inorganic elements in water and lakebed materials and the potential for bioconcentration in biota at established sampling sites on Lake Powell, Utah and Arizona

The National Park Service is responsible for monitoring the effects of visitor use on the quality of water, lakebed material (bottom sediments), and biota, in Lake Powell, Utah and Arizona. A sampling program was begun in 2010 to assess the presence, distribution, and concentrations of organic and inorganic compounds in the water column and bottom sediment. In response to an Environmental Impact Statement regarding personal watercraft and as a continuation from previous studies by the U.S. Geological Survey and the National Park Service, Glen Canyon National Recreation Area, water samples were collected and analyzed for polycyclic aromatic hydrocarbons (PAHs) using semipermeable membrane devices and inorganic elements using a fixed-bottle sampler deployed at established monitoring sites during 2010 and 2011. Lakebed material samples were also analyzed for polycyclic aromatic hydrocarbons and inorganic elements, some of which could be harmful to aquatic biota if present at concentrations above established aquatic life criteria. Of the 44 PAH compounds analyzed, 26 individual compounds were detected above the censoring limit in the water column by semipermeable membrane devices. The highest number of compounds detected were at Lone Rock Beach, Wahweap Marina, Rainbow Bridge National Monument, and Antelope Marina which are all located in the southern part of Lake Powell where visitation and boat use is high. Because PAHs can remain near their source, the potential for bioconcentration is highest near these sites. The PAH compound found in the highest concentration was phenol (5,902 nanograms per liter), which is included in the U.S. Environmental Protection Agency’s priority pollutants list. The dissolved inorganic chemistry of water samples measured at the sampling sites in Lake Powell defined three different patterns of elements: (1) concentrations were similar between sites in the upper part of the lake near Farley Canyon downstream to Halls Crossing Marina, a distance of about 36 lake miles, (2) concentrations varied depending on the element between Halls Crossing Marina downstream to the mouth of the Escalante River, a distance of about 33 lake miles, and (3) concentrations were similar between sites from below the mouth of the Escalante River to Glen Canyon Dam, a distance of about 68 lake miles. Analysis of lakebed bottom sediment material samples detected PAH compounds at all sampling sites except at Halls Crossing Marina, Stanton Creek, and Forgotten Canyon. Twenty-four of 44 PAHs analyzed in lakebed material were detected above the reporting limit. Perylene was the most prevalent compound detected above the reporting limit in lakebed material and was detected at three sampling sites. Concentrations of perylene ranged from an estimate of 24.0 to 47.9 micrograms per kilogram (μg/kg). Fluoranthene had the highest concentration of any PAH and was detected at the Wahweap Marina with a concentration of 565 μg/kg. The highest sum of concentrations for all compounds found in lakebed material samples at one site was at the Wahweap Marina, which had concentrations five times higher than the next highest site. The three major tributaries to Lake Powell—the Colorado, Escalante, and San Juan Rivers—all showed elevated concentrations of inorganic elements in their delta sediments for most elements relative to the majority of the sediment samples taken from the lake itself. However, there were four lake sites that had concentrations for most inorganic elements that equaled or exceeded those of the tributaries. Two of these sites were at the northeast part of the lake, nearest to the Colorado River as it enters Lake Powell (Farley Canyon and Blue Notch Canyon), one was at the Escalante River below 50-Mile Canyon, and other was at Antelope Marina.

Arizona;Utah↗
USGS2018

Monitoring wadeable stream habitat conditions in Southeast Coast Network parks: Protocol narrative

The Southeast Coast Network (SECN) has initiated a monitoring effort to assess habitat conditions in wadeable streams at national parks, recreation areas, battlefields, and monuments in Alabama, Georgia, and South Carolina. This monitoring effort includes Chattahoochee River National Recreation Area, Kennesaw Mountain National Battlefield Park, Congaree National Park, Horseshoe Bend National Military Park, and Ocmulgee National Monument. Stream habitat monitoring was implemented in 2016, and focuses specifically on providing relevant data to assess the physical condition of Piedmont and upper Coastal Plain streams with respect to aquatic and riparian habitats and how these habitats may be changing over time. The habitat assessment methods proposed in this protocol rely on standard data collection methods and standard operating procedures currently in use by the U.S. Geological Survey, U.S. Environmental Protection Agency, and U.S. Forest Service that have been modified to better meet the needs of National Park Service (NPS) managers. The Southeast Coast Network’s wadeable stream protocol was developed to begin a monitoring program that will provide insight into the status of, and trends in, stream and riparian habitat conditions. The number of reaches surveyed at each park is dependent on the spatial extent of the park and the total number of wadeable streams that are present within park boundaries. Regardless of the size of the park and the number of reaches that are to be monitored, selected reaches (1) are representative of the processes influencing the streams in each park; (2) can address current and anticipated management concerns, and (3) offer the most utility for future complementary studies.

Natural Resource Report↗
USGS2024

Integrating monitoring and modeling information to develop an indicator of watershed progress toward nutrient reduction goals

Eutrophication has been a major environmental issue in many coastal and inland ecosystems, which is primarily attributed to excessive anthropogenic inputs of nutrients. Restoration efforts have therefore focused on the reduction of watershed nutrient loads, including in the Chesapeake Bay (USA). To facilitate watershed management, watershed models are often developed and used to assess the expected impact of scenarios of past and future management policies and practices and the impact of watershed conditions. However, the level of load reductions estimated using monitoring data often does not match with model predictions, which may cast doubt on the effectiveness of the restoration efforts, the reliability of the model, and the prospect of achieving pre-established reduction goals. To better reconcile such inconsistencies between expectation (i.e., modeling estimates) and reality (i.e., monitoring information), a watershed-wide indicator was developed for the Chesapeake Bay watershed to explicitly quantify the progress toward nutrient reduction goals in the context of the Chesapeake Bay Total Maximum Daily Load (TMDL). Results of the indicator show that since 1995 long-term progress has been made toward the TMDL planning targets for both nitrogen and phosphorus. Specifically, management practices that are implemented and realized (in monitoring data) have been increasing over time, whereas management practices that need to be implemented in the future to meet the goals have been decreasing. In addition, the progress of nutrient reduction toward meeting the goals has varied with source sectors and watershed locations: i.e., point source management has been fully or nearly fully implemented, whereas nonpoint source management has been implemented by 50%-70%. In summary, this indicator, which is largely based on monitoring data, can provide at least four benefits: (1) evaluating the validity of the modeled estimates of nutrient reductions by comparing them to monitoring information; (2) placing the monitored riverine trends into a management context; (3) comparing progress between different nutrient source sectors and watershed locations; and (4) facilitating communication of the progress to the Chesapeake Bay Program Partnership and the public. Although we focus on the indicator development and interpretation for the Chesapeake Bay watershed, the framework can be transferred to watersheds within and beyond this watershed, where similar modeling and monitoring information exists, to gauge expectations on the trajectory and pace of the progress toward meeting restoration goals.

Chesapeake Bay watershed↗
USGS2016

A modeling approach to compare ΣPCB concentrations between congener-specific analyses

Changes in analytical methods over time pose problems for assessing long-term trends in environmental contamination by polychlorinated biphenyls (PCBs). Congener-specific analyses vary widely in the number and identity of the 209 distinct PCB chemical configurations (congeners) that are quantified, leading to inconsistencies among summed PCB concentrations (ΣPCB) reported by different studies. Here we present a modeling approach using linear regression to compare ΣPCB concentrations derived from different congener-specific analyses measuring different co-eluting groups. The approach can be used to develop a specific conversion model between any two sets of congener-specific analytical data from similar samples (similar matrix and geographic origin). We demonstrate the method by developing a conversion model for an example data set that includes data from two different analytical methods, a low resolution method quantifying 119 congeners and a high resolution method quantifying all 209 congeners. We used the model to show that the 119-congener set captured most (93%) of the total PCB concentration (i.e., Σ 209 PCB) in sediment and biological samples. ΣPCB concentrations estimated using the model closely matched measured values (mean relative percent difference = 9.6). General applications of the modeling approach include (a) generating comparable ΣPCB concentrations for samples that were analyzed for different congener sets; and (b) estimating the proportional contribution of different congener sets to ΣPCB. This approach may be especially valuable for enabling comparison of long-term remediation monitoring results even as analytical methods change over time.

Integrated Environmental Assessment and Management↗
USGS2011

Predicting lake trophic state by relating Secchi-disk transparency measurements to Landsat-satellite imagery for Michigan inland lakes, 2003-05 and 2007-08

Inland lakes are an important economic and environmental resource for Michigan. The U.S. Geological Survey and the Michigan Department of Natural Resources and Environment have been cooperatively monitoring the quality of selected lakes in Michigan through the Lake Water Quality Assessment program. Sampling for this program began in 2001; by 2010, 730 of Michigan’s 11,000 inland lakes are expected to have been sampled once. Volunteers coordinated by the Michigan Department of Natural Resources and Environment began sampling lakes in 1974 and continue to sample (in 2010) approximately 250 inland lakes each year through the Michigan Cooperative Lakes Monitoring Program. Despite these sampling efforts, it still is impossible to physically collect measurements for all Michigan inland lakes; however, Landsat-satellite imagery has been used successfully in Minnesota, Wisconsin, Michigan, and elsewhere to predict the trophic state of unsampled inland lakes greater than 20 acres by producing regression equations relating in-place Secchi-disk measurements to Landsat bands. This study tested three alternatives to methods previously used in Michigan to improve results for predicted statewide Trophic State Index (TSI) computed from Secchi-disk transparency (TSI (SDT)). The alternative methods were used on 14 Landsat-satellite scenes with statewide TSI (SDT) for two time periods (2003– 05 and 2007–08). Specifically, the methods were (1) satellitedata processing techniques to remove areas affected by clouds, cloud shadows, haze, shoreline, and dense vegetation for inland lakes greater than 20 acres in Michigan; (2) comparison of the previous method for producing a single open-water predicted TSI (SDT) value (which was based on an area of interest (AOI) and lake-average approach) to an alternative Gethist method for identifying open-water areas in inland lakes (which follows the initial satellite-data processing and targets the darkest pixels, representing the deepest water, before regression equations are created); and (3) checking to see whether the predicted TSI (SDT) values compared well between two regression equations, one previously used in Michigan and an alternative equation from the hydrologic literature. The combination of improved satellite-data processing techniques and the Gethist method to identify open-water areas in inland lakes during 2003–05 and 2007–08 provided a stronger relation and statistical significance between predicted TSI (SDT) and measured TSI than did the AOI lake-average method; differences in results for the two methods were significant at the 99-percent confidence level. With regard to the comparison of the regression equations, there were no statistically significant differences at the 95-percent confidence level between results from the two equations. The previously used equation, in combination with the Gethist method, yielded coefficient of determination (R 2 ) values of 0.71 and 0.77 for the periods 2003–05 and 2007–08, respectively. The alternative equation, in combination with the Gethist method, yielded R 2 values of 0.74 and 0.75 for 2003–05 and 2007–08, respectively. Predicted TSI (SDT) and measured TSI (SDT) values for lakes used in the regression equations compared well, with R 2 values of 0.95 and 0.96 for predicted TSI (SDT) for 2003–05 and 2007–08, respectively. The R 2 values for statewide predicted TSI (SDT) for all inland lakes with available open-water areas for 2003–05 and 2007–08 were 0.91 and 0.93, respectively. Although the two equations predicted similar trophic-state classes, the alternative equation is planned to be used for future prediction of TSI (SDT) values for Michigan inland lakes, to promote consistency in comparing predicted values between States and for potential use in trend analysis.

Michigan↗
USGS2018

Combining multiple sources of data to inform conservation of Lesser Prairie-Chicken populations

Conservation of small populations is often based on limited data from spatially and temporally restricted studies, resulting in management actions based on an incomplete assessment of the population drivers. If fluctuations in abundance are related to changes in weather, proper management is especially important, because extreme weather events could disproportionately affect population abundance. Conservation assessments, especially for vulnerable populations, are aided by a knowledge of how extreme events influence population status and trends. Although important for conservation efforts, data may be limited for small or vulnerable populations. Integrated population models maximize information from various sources of data to yield population estimates that fully incorporate uncertainty from multiple data sources while allowing for the explicit incorporation of environmental covariates of interest. Our goal was to assess the relative influence of population drivers for the Lesser Prairie-Chicken ( Tympanuchus pallidicinctus ) in the core of its range, western and southern Kansas, USA. We used data from roadside lek count surveys, nest monitoring surveys, and survival data from telemetry monitoring combined with climate (Palmer drought severity index) data in an integrated population model. Our results indicate that variability in population growth rate was most influenced by variability in juvenile survival. The Palmer drought severity index had no measurable direct effects on adult survival or mean number of offspring per female; however, there were declines in population growth rate following severe drought. Because declines in population growth rate occurred at a broad spatial scale, declines in response to drought were likely due to decreases in chick and juvenile survival rather than emigration outside of the study area. Overall, our model highlights the importance of accounting for environmental and demographic sources of variability, and provides a thorough method for simultaneously evaluating population demography in response to long-term climate effects.

The Auk↗
USGS2019

Review of and recommendations for monitoring contaminants and their effects in the San Francisco Bay−Delta

Legacy and current-use contaminants enter into and accumulate throughout the San Francisco Bay−Delta (Bay−Delta), and are present at concentrations with known effects on species important to this diverse watershed. There remains major uncertainty and a lack of focused research able to address and provide understanding of effects across multiple biological scales, despite previous and ongoing emphasis on the need for it. These needs are challenging specifically because of the established regulatory programs that often monitor on a chemical- by-chemical basis, or in which decisions are grounded in lethality-based endpoints. To best address issues of contaminants in the Bay−Delta, monitoring efforts should consider effects of environmentally relevant mixtures and sub- lethal impacts that can affect ecosystem health. These efforts need to consider the complex environment in the Bay−Delta including variable abiotic (e.g., temperature, salinity) and biotic (e.g., pathogens) factors. This calls for controlled and focused research, and the development of a multi-disciplinary contaminant monitoring and assessment program that provides information across biological scales. Information gained in this manner will contribute toward evaluating parameters that could alleviate ecologically detrimental outcomes. This review is a result of a Special Symposium convened at the University of California−Davis (UCD) on January 31, 2017 to address critical information needed on how contaminants affect the Bay−Delta. The UCD Symposium focused on new tools and approaches for assessing multiple stressor effects to freshwater and estuarine systems. Our approach is similar to the recently proposed framework laid out by the U.S. Environmental Protection Agency (USEPA) that uses weight of evidence to scale toxicological responses to chemical contaminants in a laboratory, and to guide the conservation of priority species and habitats. As such, we also aimed to recommend multiple endpoints that could be used to promote a multi-disciplinary understanding of contaminant risks in Bay−Delta while supporting management needs.

California↗
USGS2011

Algal bioassessment metrics for wadeable streams and rivers of Maine, USA

Many state water-quality agencies use biological assessment methods based on lotic fish and macroinvertebrate communities, but relatively few states have incorporated algal multimetric indices into monitoring programs. Algae are good indicators for monitoring water quality because they are sensitive to many environmental stressors. We evaluated benthic algal community attributes along a landuse gradient affecting wadeable streams and rivers in Maine, USA, to identify potential bioassessment metrics. We collected epilithic algal samples from 193 locations across the state. We computed weighted-average optima for common taxa for total P, total N, specific conductance, % impervious cover, and % developed watershed, which included all land use that is no longer forest or wetland. We assigned Maine stream tolerance values and categories (sensitive, intermediate, tolerant) to taxa based on their optima and responses to watershed disturbance. We evaluated performance of algal community metrics used in multimetric indices from other regions and novel metrics based on Maine data. Metrics specific to Maine data, such as the relative richness of species characterized as being sensitive in Maine, were more correlated with % developed watershed than most metrics used in other regions. Few community-structure attributes (e.g., species richness) were useful metrics in Maine. Performance of algal bioassessment models would be improved if metrics were evaluated with attributes of local data before inclusion in multimetric indices or statistical models.

Maine↗
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↗
USGS2026

Composite samples for perfluorooctanesulfonate in fish may change contaminant threshold decisions

The widespread occurrence and persistence of the per- and polyfluoroalkyl substances (PFAS) in the environment may pose significant health risks to humans. Fish consumption is a direct pathway for exposure, prompting extensive monitoring. In the United States and Europe, fish consumption advisories for PFAS generally focus on perfluorooctanesulfonate (PFOS), the most frequent and abundant PFAS compound reported in fish. However, PFAS analysis is costly, leading monitoring programs to frequently use composite samples (i.e., combining different fish of the same species). This financial saving comes at an analytical cost of lost information on individual variation. It is unclear how this may influence threshold-based decisions. To test this, we used a modeling approach (i.e., Monte Carlo) based on aggregated data distributions from freshwater fish species. We simulated the measurement of PFOS for individual fish compared to composite means (three, five, and 10 fish) at different levels of error structure. These values were then compared to a typical do-not-eat threshold of 200 ng•g wet mass −1 and four metrics were estimated: (i) the probability of detecting a PFOS concentration above the threshold, (ii) the maximum simulated PFOS concentration, (iii) the number of false negative samples, and (iv) the rate of false negative samples. These results show that the probability of assigning PFOS levels above or below the threshold is shifted by masking individual value contributions in a composite sample. Because true individual contaminant loads are variable, composite sampling is a more conservative metric for contaminant thresholds. The model suggested that the greater the variability, the lower the detection probability for truly contaminated samples. Our study may help to inform sampling for monitoring programs aimed at managing human exposure to PFAS.

Integrated Environmental Assessment and Management↗
USGS2024

Environmental DNA

The widespread adoption of environmental DNA (eDNA) detection tools for biodiversity monitoring has led to the need for universal data standards to inform principled eDNA data applications. Improvements in understanding the meaning and possible uncertainty of eDNA data can minimize erroneous conclusions, increase confidence in eDNA data, and maximize conservation outcomes. -Environmental DNA (eDNA) is the genetic material left by organisms in the environment. -eDNA is increasingly being used to detect the presence of species and assess biodiversity, but broad-scale best practices are still being developed. -This affects the quality, accessibility, and usefulness of data. -Non-invasive eDNA sampling can complement or enhance conventional approaches, as it can be a highly sensitive, rapid, and cost-effective tool for biodiversity monitoring. -Creating unified eDNA data best practices and developing DNA reference libraries will ensure eDNA detection methods are applied consistently to accurately inform conservation and wildlife management.

Report↗
USGS2016

Evaluating the effectiveness of wildlife detection and observation technologies at a solar power tower facility

Solar power towers produce electrical energy from sunlight at an industrial scale. Little is known about the effects of this technology on flying animals and few methods exist for automatically detecting or observing wildlife at solar towers and other tall anthropogenic structures. Smoking objects are sometimes observed co-occurring with reflected, concentrated light (“solar flux”) in the airspace around solar towers, but the identity and origins of such objects can be difficult to determine. In this observational pilot study at the world’s largest solar tower facility, we assessed the efficacy of using radar, surveillance video, and insect trapping to detect and observe animals flying near the towers. During site visits in May and September 2014, we monitored the airspace surrounding towers and observed insects, birds, and bats under a variety of environmental and operational conditions. We detected and broadly differentiated animals or objects moving through the airspace generally using radar and near solar towers using several video imaging methods. Video revealed what appeared to be mostly small insects burning in the solar flux. Also, we occasionally detected birds flying in the solar flux but could not accurately identify birds to species or the types of insects and small objects composing the vast majority of smoking targets. Insect trapping on the ground was somewhat effective at sampling smaller insects around the tower, and presence and abundance of insects in the traps generally trended with radar and video observations. Traps did not tend to sample the larger insects we sometimes observed flying in the solar flux or found dead on the ground beneath the towers. Some of the methods we tested (e.g., video surveillance) could be further assessed and potentially used to automatically detect and observe flying animals in the vicinity of solar towers to advance understanding about their effects on wildlife.

California↗
USGS2024

Grassland Effectiveness Monitoring (GEM): A tiered approach for habitat treatment assessment across private lands incentive programs

Introduction The decline of North American grasslands is a topic of increasing interest as agencies and organizations work to address subsequent declines in wildlife species, including grassland birds (Rosenberg et al. 2019), pronghorn (Antilocapra americana) (Gedir et al. 2015), and other grassland-dependent taxa. In response to grassland habitat loss, conservation programs and policies have been developed to provide biologists and landowners mechanisms to restore grassland habitat on private lands. These range from federal programs such as the U.S. Fish and Wildlife Service’s (USFWS) Partners for Fish and Wildlife program (PFW) and the Natural Resources Conservation Service’s (NRCS) Environmental Quality Incentive Program, state programs such as Texas Parks and Wildlife Department’s Pastures for Upland Birds, and partnership-based programs such as the Oaks and Prairies Joint Venture’s Grassland Restoration Incentive Program (GRIP). When managing and restoring grassland habitat, these programs typically utilize the same set of practices: prescribed grazing, prescribed fire, herbicide, brush management, and range planting. To restore grasslands at scale, large sums of funding have been invested into these programs. For example, approximately $1 million is spent by PFW in Texas annually (D. Wilhelm, USFWS, personal communication). However, it is rare for these conservation programs to have associated monitoring efforts that are consistently used to assess the effectiveness of the aforementioned practices in achieving program and project objectives. As such, it is difficult to communicate to funders and the public whether these conservation programs are successfully addressing grassland decline. Similar objectives and practices across programs, however, provide a unique opportunity for developing an innovative monitoring methodology that focuses on providing a collaborative solution to this dilemma. Our objective is to develop a grassland monitoring program that can be used across agencies, organizations, and conservation programs to assess the effectiveness of practices and programs in restoring healthy grasslands. In addition, we seek to develop a program that maintains consistency to allow for regional to national-scale reporting while also allowing flexibility for achieving local and partner monitoring objectives. Our vision is for this program to be used across North American grasslands to improve our ability to address the questions: “Is it actually working?” and “How can we improve habitat delivery?”

Conference Paper↗
USGS2021

Eastward expansion of Round Goby in New York: Assessment of detection methods and current range

The Round Goby Neogobius melanostomus has spread rapidly around the Great Lakes region since its introduction to North America in 1990. In 2014, a specimen was captured in the New York State Canal System west of Utica, prompting concerns that Round Goby would soon reach the ecologically and economically valuable watersheds of Lake Champlain and the Hudson River estuary. The establishment of Round Goby populations elsewhere has been linked to a number of negative ecological consequences, yet methods for monitoring the invasion front of this species remain limited. The objectives of this study were to assess the current distribution of Round Goby in central New York and to determine the most effective methods for monitoring the invasion front. This was achieved by concurrently using benthic trawling, seining, minnow traps, and environmental DNA (eDNA) twice annually from 2016 to 2019 at 12 sites on the canal system between Oneida Lake and the Hudson River. Of the three traditional gear types, benthic trawling was the most effective method and captured Round Goby as far east as Utica by 2019. This finding suggests only minimal eastward expansion of Round Goby occurred between 2014 and 2019. Round Goby DNA was detected in water samples during all surveys in which individuals were captured with trawling, and the estimated concentration of DNA explained 69% of the variability in trawl catch. At multiple study sites, Round Goby DNA was identified during consecutive surveys before Round Goby were first captured with trawling. This suggests that in lotic waters, eDNA has the potential to forecast or serve as a sentinel for the expansion of Round Goby to new locations. Our results demonstrate the importance of using eDNA in a repeated sampling framework and supplementing eDNA sampling with some level of effort with traditional sampling methods.

Great Lakes↗