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At least 1,225 records · Page 68Linked to original sources
USGS1984

Flow-through bioassay for measuring bioaccumulation of toxic substances from sediment

Over 10 million cubic meters of sediment are dredged annually from Great Lakes waterways. Because much of this material is taken from harbors, connecting channels, and other nearshore areas that often are contaminated with toxic substances, the sediments proposed for dredging need to be evaluated for the presence of bioavailable contaminants and the potential for toxicity to the biota. Sound decisions on the appropriate disposal of the dredged material can be made only after such an evaluation. Presently, no standardized procedure exists for evaluating dredged material in freshwater systems although current criteria for discharge of dredged material into marine water have been developed (USEPA/CE 1977). In the ocean discharge guideline, it is recommended that bioassays be conducted on liquid, solid, and suspended particulate phases of dredged material. because it appears that the solid phase has the greatest potential for environmental damage and because measurement of bioaccumulation must be made to evaluate sediments for disposal (USEPA/CE 1977, Seeyle and Mac 1983), we developed a bioassay for testing the solid phase of dredged material that measures the survival of organisms and, perhaps more important, the bioaccumulation of toxic substances by aquatic organisms from naturally contaminated sediments (Peddicord et al. 1980; Rubinstein et al. 1980, 1983; Seeyle st al. 1982), several have used testing methods that result in unacceptable mortality to control organisms (Bahnick et al. 1981, Prater et al. 1983). Our bioassay is intended to estimate the potential for bioaccumlation of contaminants from sediments that are not acutely toxic to test organisms, but are suspected of containing persistent contaminants. By using test organisms that are not highly susceptible to toxic compounds, the bioaccumulation test allows estimation of the potential food-chain accumulation of contaminants that may occur in local biota from surficial sediments. In practice, bioaccumulation observed in this bioassay by organisms exposed to test sediments (sediments to be dredged) would be compared to bioaccumulation observed from sediments collected from a reference site (e.g. a disposal site or open lake), and also from control sediments (relatively clean sediment). Decisions could then be based on a comparison of results between tests and reference sediments to determine if disposal would cause dehydration to the habitat, and between reference and control sediment to determine if even the reference material is seriously contaminated. Although the test is not intended to be a toxicity test per se, use of test, reference, and control sediments enables interpretation of any mortality of organisms that may occur during the bioassays. High mortality in bioassays with test or reference sediment would indicate acute toxicity of sediments in the project area. However if high mortality occurs in all three sediments, it can be assumed that the organisms were not in a healthy state at the time of testing. We describe the results of 10-day sediment bioassays in which both mortality and bioaccumulation were measured in four aquatic organisms. We exposed two infaunal organisms and two species of fish to test and control sediments in the laboratory.

Report↗
USGS2026

Colocating artificial intelligence data centers with energy infrastructure on Federal public lands—A science synthesis and spatial analysis to inform decision making

Executive Summary Artificial intelligence (AI) is rapidly transforming industries and economies, creating an urgent need to strategically plan for the energy and infrastructure required to support increasing AI use. U.S. Federal agencies and bureaus have been directed to explore ways to accelerate permitting, development, and deployment of energy resources and AI technologies, including encouraging the colocation of energy infrastructure and data centers. To inform these initiatives, this report synthesizes relevant scientific information and presents a spatial analysis of existing energy infrastructure and data centers on or near U.S. Federal public lands managed by the Bureau of Land Management (BLM). The purpose of this science synthesis and spatial analysis is to provide the BLM with foundational information for considering potential colocation of data centers with energy infrastructure on Federal public lands to support evidence-based decisions. Additionally, this report provides insight into current (2025) and potential future energy demands by providing projections of a range of potential future environmental conditions relevant to maintaining industry-recommended cooling temperature standards necessary for efficient data center operations. As a part of this effort, a rapid response literature review was conducted of the best available science on the topic of data center development and energy infrastructure in July–August 2025, supplemented by additional resources recommended by U.S. Federal agency and bureau subject matter experts (hereafter experts; including the U.S. Department of Energy National Laboratory of the Rockies) and peer reviewers. To better understand current conditions relevant to AI data center development, a spatial analysis was conducted across Alaska and 11 States in the Western United States, Arizona, California, Colorado, Idaho, Montana, Nevada, New Mexico, Oregon, Utah, Washington, and Wyoming, all of which contain extensive BLM-managed surface lands (hereafter referred to as “BLM lands”) that could be considered for the colocation of energy infrastructure and AI data centers. This effort identified BLM lands within 10 miles of existing transmission lines, consistent with methods used in previous BLM programmatic environmental impact statements. This report describes the types of data centers operating within the United States, which vary in ownership, size, technology, and proximity to end users. This report then outlines the primary considerations of data center development, including reliable energy supply, natural resources (such as water availability to support cooling requirements), and relevant policy and regulatory considerations. Energy supply considerations are pivotal for data center operation. Between 2014 and 2018, data centers in the United States accounted for nearly 2 percent of the Nation’s total electricity consumption, and data center energy consumption is projected to increase from 2 to 6.7–12 percent of total U.S. electricity use by 2028. These energy requirements necessitate careful consideration of energy supply when considering potentially suitable locations for data center development. Experts anticipate that an increase in renewable energy generation will likely support most potential future power demand needs, including for data centers, followed by increases in natural gas, nuclear, and geothermal energy production. Additional capacity in the form of battery storage will likely not generate electricity, but may improve the reliability and flexibility of supply, helping to ensure that growing data center loads can be met. However, the U.S. Department of Energy estimates that the United States will need, on average, 57 percent more energy transmission infrastructure by 2035 to account for the growing power demand introduced by development such as data centers. Cooling server equipment in data centers requires large amounts of electricity and water, and this demand can be exacerbated by hot and humid conditions. Energy efficient water-based cooling technologies may reduce electricity consumption onsite but require more water consumption. This additional water demand has the potential to increase water stress and competition with other users. As such, developing data centers will likely need a thorough assessment of current and potential future water availability, as well as consideration of how water demand may change across other sectors. Data center development involves policy and regulatory considerations, as projects must undergo environmental review and authorization processes that can take 18–24 months. Coordinating these environmental reviews and authorizations with other energy development projects, such as building new transmission lines, may cause additional delays. Recent efforts by the U.S. Department of Energy and U.S. Department of the Interior aim to expedite environmental reviews and authorizations and improve coordination across agencies. The spatial analysis identified 771 existing AI data centers and more than 3,300 power plants. The spatial analysis found that 6 percent of AI data centers and 22 percent of power plants in the Western United States were on or within 1 mile of BLM lands, and California had the largest number of facilities. Most existing AI data centers were near high-voltage transmission lines and close to power plants, supporting efficient energy delivery. More than 90,000,000 acres of BLM lands were within 10 miles of existing high-voltage transmission lines, representing 38 percent of BLM lands in the study area. Available transmission infrastructure and the overlap with BLM lands varied by State, and Alaska had limited overlap compared to the rest of the Western United States. To operate most efficiently, data center temperatures must be at or below 80.6 degrees Fahrenheit. This analysis of future temperature and precipitation projections indicated increasing cooling demands for data centers, particularly in Arizona, California, and Nevada, where rising temperatures are expected to increase energy and operational costs while potentially stressing current regional electrical grid infrastructure. This report highlights relevant energy supply, natural resources, and regulatory considerations for data center development on BLM lands. This report does not provide a comprehensive ecological, regulatory, land suitability, or permitting analysis. The factors described here are contextual considerations only and are not intended to identify, rank, quantify, or recommend optimal areas for data center colocation. This spatial analysis focused solely on energy considerations relevant to data centers and did not consider water availability, critical habitats, BLM National Conservation Lands, areas of cultural or historical significance, and other sensitive resources. These topics are recognized as critical but were not within the scope of this science synthesis and spatial analysis.

Scientific Investigations Report↗
USGS2015

StreamStats in Georgia: A water-resources web application

Summary Part of the mission of the U.S. Geological Survey (USGS) is to provide information on streamflow in the Nation's streams to help understand the Nation's water resources. Streamflow statistics are used by water managers, engineers, scientists, and others to protect people and property during floods and droughts, and to manage, protect, and enhance water resources. StreamStats is a Web-based Geographic Information System (GIS) application that was created by the USGS, in cooperation with the Environmental Systems Research Institute, Inc., that allows users to easily obtain streamflow statistics, basin characteristics, and descriptive information for USGS streamgages and user-selected ungaged locations on streams (Ries and others, 2008). StreamStats is being implemented on a State-by-State basis to allow for customization of the data development and underlying datasets to address their specific needs, issues, and objectives. The USGS, in cooperation with the Georgia Environmental Protection Division and Georgia Department of Transportation, has implemented StreamStats for Georgia. The Georgia StreamStats Web site is available through the national StreamStats Web-page portal at http://streamstats.usgs.gov. Links are provided on this Web page for individual State applications, instructions for using StreamStats, definitions of basin characteristics and streamflow statistics, and other supporting information.

Georgia↗
USGS1996

Susceptibility of ground water to surface and shallow sources of contamination in Mississippi

Ground water, because of its extensive use in agriculture, industry, and public-water supply, is one of Mississippi's most important natural resources. Ground water is the source for about 80 percent of the total freshwater used by the State's population (Solley and others, 1993). About 2,600 Mgal/d of freshwater is withdrawn from aquifers in Mississippi (D.E. Burt, Jr., U.S. Geological Survey, oral commun., 1995). Wells capable of yielding 200 gal/min of water with quality suitable for most uses can be developed nearly anywhere in the State (Bednar, 1988). The U.S. Geological Survey (USGS), in cooperation with the Mississippi Department of Environmental Quality, Office of Pollution Control, and the Mississippi Department of Agriculture and Commerce, Bureau of Plant Industry, conducted an investigation to evaluate the susceptibility of ground water to contamination from surgace and shallow sources in Mississippi. A geographic information system (GIS) was used to develop and analyze statewide spatial data layers that contain geologic, hydrologic, physiographic, and cultural information.

Mississippi↗
USGS2013

Forecasting the effects of coastal protection and restoration projects on wetland morphology in coastal Louisiana under multiple environmental uncertainty scenarios

Few landscape scale models have assessed the effects of coastal protection and restoration projects on wetland morphology while taking into account important uncertainties in environmental factors such as sea-level rise (SLR) and subsidence. In support of Louisiana's 2012 Coastal Master Plan, we developed a spatially explicit wetland morphology model and coupled it with other predictive models. The model is capable of predicting effects of protection and restoration projects on wetland area, landscape configuration, surface elevation, and soil organic carbon (SOC) storage under multiple environmental uncertainty scenarios. These uncertainty scenarios included variability in parameters such as eustatic SLR (ESLR), subsidence rate, and Mississippi River discharge. Models were run for a 2010–2060 simulation period. Model results suggest that under a “future-without-action” condition (FWOA), coastal Louisiana is at risk of losing between 2118 and 4677 km 2 of land over the next 50 years, but with protection and restoration projects proposed in the Master Plan, between 40% and 75% of that loss could be mitigated. Moreover, model results indicate that under a FWOA condition, SOC storage (to a depth of 1 m) could decrease by between 108 and 250 million metric tons, a loss of 12% to 30% of the total coastwide SOC, but with the Master Plan implemented, between 35% and 74% of the SOC loss could be offset. Long-term maintenance of project effects was best attained in areas of low SLR and subsidence, with a sediment source to support marsh accretion. Our findings suggest that despite the efficacy of restoration projects in mitigating losses in certain areas, net loss of wetlands in coastal Louisiana is likely to continue. Model results suggest certain areas may eventually be lost regardless of proposed restoration investment, and, as such, other techniques and strategies of adaptation may have to be utilized in these areas.

Louisiana↗
USGS2015

Landscapes for energy and wildlife: conservation prioritization for golden eagles across large spatial scales

Proactive conservation planning for species requires the identification of important spatial attributes across ecologically relevant scales in a model-based framework. However, it is often difficult to develop predictive models, as the explanatory data required for model development across regional management scales is rarely available. Golden eagles are a large-ranging predator of conservation concern in the United States that may be negatively affected by wind energy development. Thus, identifying landscapes least likely to pose conflict between eagles and wind development via shared space prior to development will be critical for conserving populations in the face of imposing development. We used publicly available data on golden eagle nests to generate predictive models of golden eagle nesting sites in Wyoming, USA, using a suite of environmental and anthropogenic variables. By overlaying predictive models of golden eagle nesting habitat with wind energy resource maps, we highlight areas of potential conflict among eagle nesting habitat and wind development. However, our results suggest that wind potential and the relative probability of golden eagle nesting are not necessarily spatially correlated. Indeed, the majority of our sample frame includes areas with disparate predictions between suitable nesting habitat and potential for developing wind energy resources. Map predictions cannot replace on-the-ground monitoring for potential risk of wind turbines on wildlife populations, though they provide industry and managers a useful framework to first assess potential development.

Wyoming↗
USGS2010

A Review of Land-Cover Mapping Activities in Coastal Alabama and Mississippi

INTRODUCTION Land-use and land-cover (LULC) data provide important information for environmental management. Data pertaining to land-cover and land-management activities are a common requirement for spatial analyses, such as watershed modeling, climate change, and hazard assessment. In coastal areas, land development, storms, and shoreline modification amplify the need for frequent and detailed land-cover datasets. The northern Gulf of Mexico coastal area is no exception. The impact of severe storms, increases in urban area, dramatic changes in land cover, and loss of coastal-wetland habitat all indicate a vital need for reliable and comparable land-cover data. Four main attributes define a land-cover dataset: the date/time of data collection, the spatial resolution, the type of classification, and the source data. The source data are the foundation dataset used to generate LULC classification and are typically remotely sensed data, such as aerial photography or satellite imagery. These source data have a large influence on the final LULC data product, so much so that one can classify LULC datasets into two general groups: LULC data derived from aerial photography and LULC data derived from satellite imagery. The final LULC data can be converted from one format to another (for instance, vector LULC data can be converted into raster data for analysis purposes, and vice versa), but each subsequent dataset maintains the imprint of the source medium within its spatial accuracy and data features. The source data will also influence the spatial and temporal resolution, as well as the type of classification. The intended application of the LULC data typically defines the type of source data and methodology, with satellite imagery being selected for large landscapes (state-wide, national data products) and repeatability (environmental monitoring and change analysis). The coarse spatial scale and lack of refined land-use categories are typical drawbacks to satellite-based land-use classifications. Aerial photography is typically selected for smaller landscapes (watershed-basin scale), for greater definition of the land-use categories, and for increased spatial resolution. Disadvantages of using photography include time-consuming digitization, high costs for imagery collection, and lack of seasonal data. Recently, the availability of high-resolution satellite imagery has generated a new category of LULC data product. These new datasets have similar strengths to the aerial-photo-based LULC in that they possess the potential for refined definition of land-use categories and increased spatial resolution but also have the benefit of satellite-based classifications, such as repeatability for change analysis. LULC classification based on high-resolution satellite imagery is still in the early stages of development but merits greater attention because environmental-monitoring and landscape-modeling programs rely heavily on LULC data. This publication summarizes land-use and land-cover mapping activities for Alabama and Mississippi coastal areas within the U.S. Geological Survey (USGS) Northern Gulf of Mexico (NGOM) Ecosystem Change and Hazard Susceptibility Project boundaries. Existing LULC datasets will be described, as well as imagery data sources and ancillary data that may provide ground-truth or satellite training data for a forthcoming land-cover classification. Finally, potential areas for a high-resolution land-cover classification in the Alabama-Mississippi region will be identified.

Open-File Report↗
USGS2020

Smallmouth buffalo (Ictiobus bubalus) growth across a 1200km human use and ecological disturbance gradient in the Upper Mississippi River System

Smallmouth buffalo (Ictiobus bubalus) is a common and widely distributed large-bodied species of the family Catostomidae. It inhabits large rivers and reservoirs of the eastern continental United States (east of the continental Divide) and is most abundant and common in the large rivers of the Midwest and Central Plains, though it does occur as far north and east as the Hudson Bay drainage and as far south and west as Arizona (Edwards and Twoney 1982). Historically, smallmouth buffalo were an important component of commercial fisheries on both the Mississippi and Illinois Rivers. However, following the introduction of common carp (Cyprinus carpio) in the mid-1800s (Carlander 1954), the construction of a system of navigation dams on Upper Mississippi and Illinois River in the 1930s (USGS 1999), and water quality/pollution issues through the 1980s (Weiner 2010), the role of smallmouth buffalo in the overall UMRS fish community and commercial fishery has generally diminished relative to historical standards. Still, smallmouth buffalo remains an important and valued component of the UMRS commercial fishery. The study area is represented by three study reaches on the Illinois River and three study reaches on the Upper Mississippi River (Figure 1). Collectively, these study reaches represent nearly 1200 river km and exist across strong and pronounced ecological and disturbance gradients. For example, habitat composition, water quality, commercial navigation intensity, aquatic plant prominence, and the number and abundance of nonnative fish species vary strongly across the study domain, with northern Mississippi River reaches exhibiting less navigation traffic, better water quality, markedly greater aquatic plant prominence, more diverse habitat composition, and comparably much smaller numbers of nonnative species than the lower Mississippi River study reach and those on the Illinois River (USGS 1999; Johnson and Hagerty [eds] 2008; Irons et al. 2009). Long term monitoring efforts conducted under the auspices of the Upper Mississippi River Restoration program over the past 27 years have provided tremendous insights into shifts and changes of the overall UMRS fish community (Ickes et al. 2005; Garvey et al. 2010; Schramm and Ickes 2016). However, these monitoring efforts observe only the most basic aspects of the UMRS fish community (i.e., catch, length, weight, distribution, and occurrence). To gain a greater understanding of forces driving community level shifts and changes, more directed study is needed on the functional attributes of fish populations (i.e., growth, mortality, recruitment). Collectively, these functional attributes of populations are termed population dynamics and/or vital rates. It is important to note, the population dynamics of fishes in large rivers is generally poorly understood, especially for non-game species (Ickes 2018). The prevailing view is that abiotic factors largely govern inter-annual population dynamics, typically based upon rather short-term observations and correlations with assorted abiotic river attributes that vary on a seasonal or annual basis (for example, Risotto and Turner 1985). However, the role that longer-term abiotic factors play in regulating population abundance, or that biotic factors internal to the population (e.g., spawner-recruit dynamics, growth dynamics) or external to the population (e.g., predator-prey dynamics, sympatric competitors, disease) remain poorly understood. Achieving a greater understanding of these dynamics is important for stock, game, and invasive species management. In 2017, as part of a larger study designed to gain vital population rate information for smallmouth buffalo in the Upper Mississippi and Illinois Rivers (“Smallmouth Buffalo population demographics of the Upper Mississippi River System”; UMRR LTRM 2018SOW project items 2018MMBF1-2018MMBF6) annual growth patterns in smallmouth buffalo were determined and evaluated. This was accomplished by measuring growth histories recorded in annual growth increments on hard bony parts (here otoliths), a method known generically as biochronology, and somewhat analogous to dendrochronology practiced by foresters. These methods allow one to generate time-series of annual growth histories that depend upon age, year class (i.e., cohort), and annual environmental conditions experienced by the population over time (Weisberg, 1993). Biochronology methods were used to develop a 36-year time series of smallmouth buffalo growth in the Upper Mississippi and Illinois Rivers across a 1200 km ecological and human use disturbance gradient. Annual growth intervals were identified and measured from otoliths to determine fish age and growth history. A mixed model that parses the growth increment into age and year effects was fit to these data. Given the pronounced ecological and disturbance gradients inherent to the UMRS and the study domain, an a priori expectation of differing patterns in growth is accepted as a null hypothesis to test. The goal of this study was to model smallmouth buffalo growth as a function of the age of the fish and the growth year in which the growth was gained. The primary modeling objective was to parse growth observed on each annulus into a portion attributable to the age of the fish and the portion attributable to the year in which the growth was gained. In effect, this modeling approach removes the somewhat trivial age effects on growth so that a non-confounded growth year effect can be gained. Results attributable to growth year provide a time series of growth information that is of the same duration as the oldest fish observed and solely reflects environmental influences on growth. These model responses can then be investigated relative to environmental covariate time-series suspected of influencing growth of smallmouth buffalo in the Upper Mississippi and Illinois Rivers (e.g., temperature, discharge, population density, population mortality, forage availability, sympatric competition, habitat composition, navigation intensity, nonnative fish prominence, etc.). Thus, the primary scientific objective was to investigate if and how smallmouth buffalo growth varies in accordance with innate ecological and disturbance gradients across the study domain.

Illinois, Iowa, Minnesota, Missouri, Wisconsin↗
USGS2015

Habitat influences distribution of chronic wasting disease in white-tailed deer

Chronic wasting disease (CWD) is a transmissible spongiform encephalopathy that was first detected in 1967 in a captive research facility in Colorado. In the northeastern United States, CWD was first confirmed in white-tailed deer ( Odocoileus virginianus ) in 2005. Because CWD is a new and emerging disease with a spatial distribution that had yet to be assessed in the Northeast, we examined demographic, environmental, and spatial effects to determine how each related to this spatial distribution. The objectives of our study were to identify environmental and spatial effects that best described the spatial distribution of CWD in free-ranging white-tailed deer and identify areas that support deer that are at risk for CWD infection in the Northeast. We used Bayesian hierarchical modeling that incorporated demographic covariates, such as sex and age, along with environmental covariates, which included elevation, slope, riparian corridor, percent clay, and 3 landscapes (i.e., developed, forested, open). The model with the most support contained landscape covariates and spatial effects that represented clustering of CWD in adjacent grid cells. Forested landscapes had the strongest relationship with the distribution of CWD, with increased risk of CWD occurring in areas that had lesser amounts of forest. Our results will assist resource managers in understanding the spatial distribution of CWD within the study area, and in surrounding areas where CWD has yet to be found. Efficiency of disease surveillance and containment efforts can be improved by allocating resources used for surveillance in areas with deer populations that are at greatest risk for infection.

Journal of Wildlife Management↗
USGS2018

Evaluating the waterfowl breeding population and habitat survey for scaup

Potential bias in breeding population estimates of certain duck species from the Waterfowl Breeding Population and Habitat Survey (WBPHS) has been a concern for decades. The WBPHS does not differentiate between lesser ( Aythya affinis ) and greater ( A . marila ) scaup, but lesser scaup comprise 89% of the combined scaup population and their population estimates are suspected to be biased. We marked female lesser scaup (i.e., marked scaup) in the Mississippi and Atlantic Flyways, Canada and United States, with implantable satellite transmitters to track their spring migration through the traditional and eastern survey areas of the WBPHS, 2005–2010. Our goal was to use data independent of the WBPHS to evaluate whether breeding population estimates for scaup were biased and identify variables that might be used in the future to refine population estimates. We found that the WBPHS estimates of breeding scaup are biased because, across years, only 30% of our marked scaup had settled for the breeding period when the strata in which they settled were surveyed, 43% were available to be counted in multiple survey strata as their migration continued during the WBPHS, 32% settled outside the WBPHS area, the number of times a marked scaup was available to be counted by survey crews varied positively with the latitude that a marked scaup settled on breeding areas, the probability of a marked scaup being in a stratum while it was surveyed varied among years, and these probabilities were positively correlated with the traditional and eastern breeding population estimates for scaup. Annual population estimates derived from banding data provide a less biased and preferable method of monitoring scaup population status and trend. Development of models that include metrics such as survey stratum latitude and annual spring environmental conditions might potentially be used to improve scaup breeding population estimates derived from the WBPHS, but independent estimates from banding data would be important to evaluate such models.

Journal of Wildlife Management↗
USGS2016

Physical and chemical constraints limit the habitat window for an endangered mussel

Development of effective conservation and restoration strategies for freshwater pearly mussels requires identification of environmental constraints on the distributions of individual mussel species. We examined whether the spatial distribution of the endangered Alasmidonta heterodon in Flat Brook, a tributary of the upper Delaware River, was constrained by water chemistry (i.e., calcium availability), bed mobility, or both. Alasmidonta heterodon populations were bracketed between upstream reaches that were under-saturated with respect to aragonite and downstream reaches that were saturated for aragonite during summer baseflow but had steep channels with high bed mobility. Variability in bed mobility and water chemistry along the length of Flat Brook create a “habitat window” for A. heterodon defined by bed stability (mobility index ≤1) and aragonite saturation (saturation index ≥1). We suggest the species may exist in a narrow biogeochemical window that is seasonally near saturation. Alasmidonta heterodon populations may be susceptible to climate change or anthropogenic disturbances that increase discharge, decrease groundwater inflow or chemistry, and thus affect either bed mobility or aragonite saturation. Identifying the biogeochemical microhabitats and requirements of individual mussel species and incorporating this knowledge into management decisions should enhance the conservation and restoration of endangered mussel species.

New Jersey↗
USGS2016

Stock assessment in inland fisheries: a foundation for sustainable use and conservation

Fisheries stock assessments are essential for science-based fisheries management. Inland fisheries pose challenges, but also provide opportunities for biological assessments that differ from those encountered in large marine fisheries for which many of our assessment methods have been developed. These include the number and diversity of fisheries, high levels of ecological and environmental variation, and relative lack of institutional capacity for assessment. In addition, anthropogenic impacts on habitats, widespread presence of non-native species and the frequent use of enhancement and restoration measures such as stocking affect stock dynamics. This paper outlines various stock assessment and data collection approaches that can be adapted to a wide range of different inland fisheries and management challenges. Although this paper identifies challenges in assessment, it focuses on solutions that are practical, scalable and transferrable. A path forward is suggested in which biological assessment generates some of the critical information needed by fisheries managers to make effective decisions that benefit the resource and stakeholders.

Reviews in Fish Biology and Fisheries↗
USGS2015

Spatial and temporal variability in growth of southern flounder ( Paralichthys lethostigma )

Delineation of stock structure is important for understanding the ecology and management of many fish populations, particularly those with wide-ranging distributions and high levels of harvest. Southern flounder ( Paralichthys lethostigma ) is a popular commercial and recreational species along the southeast Atlantic coast and Gulf of Mexico, USA. Recent studies have provided genetic and otolith morphology evidence that the Gulf of Mexico and Atlantic Ocean stocks differ. Using age and growth data from four states (Texas, Alabama, South Carolina, and North Carolina) we expanded upon the traditional von Bertalanffy model in order to compare growth rates of putative geographic stocks of southern flounder. We improved the model fitting process by adding a hierarchical Bayesian framework to allow each parameter to vary spatially or temporally as a random effect, as well as log transforming the three model parameters ( L ∞ , K , and t 0 ). Multiple comparisons of parameters showed that growth rates varied (even within states) for females, but less for males. Growth rates were also consistent through time, when long-term data were available. Since within-basin populations are thought to be genetically well-mixed, our results suggest that consistent small-scale environmental conditions (i.e., within estuaries) likely drive growth rates and should be considered when developing broader scale management plans.

Fisheries Research↗
USGS2011

Comparing the role of fuel breaks across southern California national forests

Fuel treatment of wildland vegetation is the primary approach advocated for mitigating fire risk at the wildland–urban interface (WUI), but little systematic research has been conducted to understand what role fuel treatments play in controlling large fires, which factors influence this role, or how the role of fuel treatments may vary over space and time. We assembled a spatial database of fuel breaks and fires from the last 30 years in four southern California national forests to better understand which factors are consistently important for fuel breaks in the control of large fires. We also explored which landscape features influence where fires and fuel breaks are most likely to intersect. The relative importance of significant factors explaining fuel break outcome and number of fire and fuel break intersections varied among the forests, which reflects high levels of regional landscape diversity. Nevertheless, several factors were consistently important across all the forests. In general, fuel breaks played an important role in controlling large fires only when they facilitated fire management, primarily by providing access for firefighting activities. Fire weather and fuel break maintenance were also consistently important. Models and maps predicting where fuel breaks and fires are most likely to intersect performed well in the regions where the models were developed, but these models did not extend well to other regions, reflecting how the environmental controls of fire regimes vary even within a single ecoregion. Nevertheless, similar mapping methods could be adopted in different landscapes to help with strategic location of fuel breaks. Strategic location of fuel breaks should also account for access points near communities, where fire protection is most important.

California↗
USGS2016

The Grand Ethiopian Renaissance Dam: Source of cooperation or contention?

This paper discusses the challenges and benefits of the Grand Ethiopian Renaissance Dam (GERD), which is under construction and expected to be operational on the Blue Nile River in Ethiopia in a few years. Like many large-scale projects on transboundary rivers, the GERD has been criticized for potentially jeopardizing downstream water security and livelihoods through upstream unilateral decision making. In spite of the contentious nature of the project, the authors argue that this project can provide substantial benefits for regional development. The GERD, like any major river infrastructure project, will undeniably bring about social, environmental, and economic change, and in this unique case has, on balance, the potential to achieve success on all fronts. It must be stressed, however, that strong partnerships between riparian countries are essential. National success is contingent on regional cooperation.

Journal of Water Resources Planning and Management↗
USGS2022

Pharmaceutical pollution of the world’s rivers

Environmental exposure to active pharmaceutical ingredients (APIs) can have negative effects on the health of ecosystems and humans. While numerous studies have monitored APIs in rivers, these employ different analytical methods, measure different APIs, and have ignored many of the countries of the world. This makes it difficult to quantify the scale of the problem from a global perspective. Furthermore, comparison of the existing data, generated for different studies/regions/continents, is challenging due to the vast differences between the analytical methodologies employed. Here, we present a global-scale study of API pollution in 258 of the world’s rivers, representing the environmental influence of 471.4 million people across 137 geographic regions. Samples were obtained from 1,052 locations in 104 countries (representing all continents and 36 countries not previously studied for API contamination) and analyzed for 61 APIs. Highest cumulative API concentrations were observed in sub-Saharan Africa, south Asia, and South America. The most contaminated sites were in low- to middle-income countries and were associated with areas with poor wastewater and waste management infrastructure and pharmaceutical manufacturing. The most frequently detected APIs were carbamazepine, metformin, and caffeine (a compound also arising from lifestyle use), which were detected at over half of the sites monitored. Concentrations of at least one API at 25.7% of the sampling sites were greater than concentrations considered safe for aquatic organisms, or which are of concern in terms of selection for antimicrobial resistance. Therefore, pharmaceutical pollution poses a global threat to environmental and human health, as well as to delivery of the United Nations Sustainable Development Goals.

Proceedings of the National Academy of Sciences↗
USGS2012

A high-resolution bioclimate map of the world: a unifying framework for global biodiversity research and monitoring

Aim: To develop a novel global spatial framework for the integration and analysis of ecological and environmental data. Location: The global land surface excluding Antarctica. Methods: A broad set of climate-related variables were considered for inclusion in a quantitative model, which partitions geographic space into bioclimate regions. Statistical screening produced a subset of relevant bioclimate variables, which were further compacted into fewer independent dimensions using principal components analysis (PCA). An ISODATA clustering routine was then used to classify the principal components into relatively homogeneous environmental strata. The strata were aggregated into global environmental zones based on the attribute distances between strata to provide structure and support a consistent nomenclature. Results: The global environmental stratification (GEnS) consists of 125 strata, which have been aggregated into 18 global environmental zones. The stratification has a 30 arcsec resolution (equivalent to 0.86 km2 at the equator). Aggregations of the strata were compared with nine existing global, continental and national bioclimate and ecosystem classifications using the Kappa statistic. Values range between 0.54 and 0.72, indicating good agreement in bioclimate and ecosystem patterns between existing maps and the GEnS. Main conclusions: The GEnS provides a robust spatial analytical framework for the aggregation of local observations, identification of gaps in current monitoring efforts and systematic design of complementary and new monitoring and research. The dataset is available for non-commercial use through the GEO portal (http://www.geoportal.org).

Global Ecology and Biogeography↗
USGS2007

A comparison of delta change and downscaled GCM scenarios for three mountainous basins in the United States

Simulated daily precipitation, temperature, and runoff time series were compared in three mountainous basins in the United States: (1) the Animas River basin in Colorado, (2) the East Fork of the Carson River basin in Nevada and California, and (3) the Cle Elum River basin in Washington State. Two methods of climate scenario generation were compared: delta change and statistical downscaling. The delta change method uses differences between simulated current and future climate conditions from the Hadley Centre for Climate Prediction and Research (HadCM2) General Circulation Model (GCM) added to observed time series of climate variables. A statistical downscaling (SDS) model was developed for each basin using station data and output from the National Center for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) reanalysis regridded to the scale of HadCM2. The SDS model was then used to simulate local climate variables using HadCM2 output for current and future conditions. Surface climate variables from each scenario were used in a precipitation-runoff model. Results from this study show that, in the basins tested, a precipitation-runoff model can simulate realistic runoff series for current conditions using statistically downscaled NCEP output. But, use of downscaled HadCM2 output for current or future climate assessments are questionable because the GCM does not produce accurate estimates of the surface variables needed for runoff in these regions. Given the uncertainties in the GCMs ability to simulate current conditions based on either the delta change or downscaling approaches, future climate assessments based on either of these approaches must be treated with caution.

California, Colorado, Nevada, Washington↗