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USGS2009

A Chronosequence Feasibility Assessment of Emergency Fire Rehabilitation Records within the Intermountain Western United States - Final Report to the Joint Fire Science Program - Project 08-S-08

Department of the Interior (DOI) bureaus have invested heavily (for example, the U.S. Bureau of Land Management (BLM) spent more than $60 million in fiscal year 2007) in seeding vegetation for emergency stabilization and burned area rehabilitation of non-forested arid lands over the past 10 years. The primary objectives of these seedings commonly are to (1) reduce the post-fire dominance of non-native annual grasses, such as cheatgrass (Bromus tectorum) and red brome (Bromus rubens); (2) minimize the probability of recurrent fire; and (3) ultimately produce desirable vegetation characteristics (for example, ability to recover following disturbance [resilience], resistance to invasive species, and a capacity to support a diverse flora and fauna). Although these projects historically have been monitored to varying extents, land managers currently lack scientific evidence to verify whether seeding arid and semiarid lands achieves desired objectives. Given the amount of resources dedicated to post-fire seeding projects, a synthesis of information determining the factors that result in successful treatments is critically needed. Although results of recently established experiments and monitoring projects eventually will provide useful insights for the future direction of emergency stabilization and burned area rehabilitation programs, a chronosequence approach evaluating emergency stabilization and burned area rehabilitation treatments (both referenced hereafter as ESR treatments) over the past 30 years could provide a comprehensive assessment of treatment success across a range of regional environmental gradients. By randomly selecting a statistically robust sample from the population of historic ESR treatments in the Intermountain West, this chronosequence approach would have inference for most ecological sites in this region. The goal of this feasibility study was to compile and examine historic ESR records from BLM field offices across the Intermountain West to determine whether sufficient documentation existed for a future field-based chronosequence project. We collected ESR records and data at nine BLM field offices in four States (Oregon, Idaho, Nevada, and Utah) and examined the utility of these data for the development of a chronosequence study of post-fire seeding treatments from multiple sites and different ages (since seeding) throughout the Intermountain West. We collected records from 730 post-fire seeding projects with 1,238 individual seeding treatments. Records from each project ranged from minimal reporting of the project's occurrence to detailed documentation of planning, implementation, and monitoring. Of these 1,238 projects, we identified 468 (38 percent) that could potentially be used to implement a field-based chronosequence study. There were 206 ground-seeding treatments and 262 aerial-seeding treatments within this initial population, not including hand plantings. We also located a considerable number of additional records from other potential field offices that would be available for the chronosequence study but have yet to be compiled for this feasibility report. There are a number of potential challenges involved in going forward with a field-based chronosequence study derived from data collected at these nine BLM offices. One challenge is that not all seed mixtures in ESR project files have on-the-ground confirmation about what was sown or rates of application. Most projects, particularly records before 2000, just list the planned or purchased seed mixtures. Although this could potentially bias assessments of factors influencing establishment rates of individual species for treatments conducted before 2000, a chronosequence study would not be intended to assess success solely at the species-level. Treatment success would be evaluated based on the establishment of healthy vegetation communities, such as the abundance and density of perennial species, regardless of their lifeforms (grasses, fo

Open-File Report↗

USGS2020

Development and application of an empirical dune growth model for evaluating barrier island recovery from storms

Coastal zone managers require models that predict barrier island change on decadal time scales to estimate coastal vulnerability, and plan habitat restoration and coastal protection projects. To meet these needs, methods must be available for predicting dune recovery as well as dune erosion. In the present study, an empirical dune growth model (EDGR) was developed to predict the evolution of the primary foredune of a barrier island. Within EDGR, an island is represented as a sum of Gaussian shape functions representing dunes, berms, and the underlying island form. The model evolves the foredune based on estimated terminal dune height and location inputs. EDGR was assessed against observed dune evolution along the western end of Dauphin Island, Alabama over the 10 years following Hurricane Katrina (2005). The root mean square error with EDGR (ranging from 0.18 to 0.74 m over the model domain) was reduced compared to an alternate no-change model (0.69–0.96 m). Hindcasting with EDGR also supports the study of dune evolution processes. At Dauphin Island, results suggest that a low-lying portion of the site was dominated by overwash for ~5 years after Katrina, before approaching their terminal height and becoming growth-limited after 2010. EDGR’s computational efficiency allows dune evolution to be rapidly predicted and enables ensemble predictions to constrain the uncertainty that may result if terminal dune characteristics are unknown. In addition, EDGR can be coupled with an external model for estimating dune erosion and/or the long-term evolution of other subaerial features to allow decadal-scale prediction of barrier island evolution.

Alabama↗

USGS2020

Concentrations and size distribution of TiO2 and Ag engineered particles in five wastewater treatment plants in the United States

The growing use of engineered particles ( e.g. , nanosized and pigment sized particles, 1 to 100 nm and 100 to 300 nm, respectively) in a variety of consumer products increases the likelihood of their release into the environment. Wastewater treatment plants (WWTPs) are an important pathways of introduction of engineered particles to the aquatic systems. This study reports the concentrations, removal efficiencies, and particle size distributions of Ag and TiO 2 engineered particles in five WWTPs in three states in the United States. The concentration of Ag engineered particles was quantified as the total Ag concentration, whereas the concentration of TiO 2 engineered particles was quantified using mass-balance calculations and shifts in the elemental ratio of Ti/Nb above their natural background elemental ratio. Ratios of Ti/Nb in all WWTP influents, activated sludges, and effluents were 2–12 times higher ( e.g. , 519 to 3243) than the natural background Ti/Nb ratio ( e.g. , 267 ± 9), indicating that 49–92% of Ti originates from anthropogenic sources. The concentration of TiO 2 engineered particles (in μg TiO 2 L −1 ) in the influent, activated sludge, and effluent varied within the ranges of 70–670, 3570–6700, and 7–30, respectively. The concentration of Ag engineered particles (in μg Ag L −1 ) in the influent, activated sludge, and effluent varied within the ranges of 0.11–0.33, 1.45–1.65, and 0.01–0.04, respectively. The overall removal efficiency ( e.g. , effluent/influent concentrations) of TiO 2 engineered particles ( e.g. , 90 to 96%) was higher than that for Ag engineered particles ( e.g. , 82 to 95%). Particles entering WWTPs are in the nanosized range for Ag ( e.g. , >99%) and a mixture of nanosized ( e.g. , 15 to 90%) and pigment sized particles ( e.g. , 10 to 85%) for TiO 2 . Nearly all Ag (>99%) and 55 to 100% of TiO 2 particles discharged to surface water with WWTP effluent are within the nanosize range. This study provides evidence that TiO 2 and Ag engineered nanomaterials enter aquatic systems with WWTP effluents, and that their concentrations are expected to increase with the increased applications of TiO 2 and Ag engineered nanomaterials in consumer products.

California, Massachusetts, South Carolina↗

USGS2016

Accuracy assessment/validation methodology and results of 2010–11 land-cover/land-use data for Pools 13, 26, La Grange, and Open River South, Upper Mississippi River System

Introduction/Background The U.S. Geological Survey (USGS)-Upper Midwest Environmental Sciences Center (UMESC) was responsible for development of several land cover/land use (LCU) systemic datasets of the Upper Mississippi River System (UMRS). These efforts (1989 and 2000) were funded by the U.S. Army Corps of Engineers’ Upper Mississippi River Restoration Program (UMRR) Long Term Resource Monitoring (LTRM) element. Development of systemic datasets includes the acquisition, processing, and serving of high-resolution aerial photography and land cover/land use spatial datasets ( http://www.umesc.usgs.gov/data_library/land_cover_use/land_cover_use_data.html ). In 2008, the UMRR reached a collaborative agreement with the U.S. Fish and Wildlife Service-Region 3 to collect high-resolution digital imagery of the entire UMRS floodplain during 2010–11 for LTRM. The UMESC helped acquire, process, and serve this imagery, as well as produce and serve the 2010–11 LCU systemic dataset of the UMRS floodplain. Digital imagery for Pools 13, 26, La Grange, and Open River South was collected using an Applanix DSS 439 digital sensor system with a 40 millimeter lens and Color Infrared (CIR) filter. The imagery was collected at a resolution of 20 centimeters/pixel (8 inches/pixel) for Pool 13 and 40 centimeters/pixel (16 inches/pixel) for Pools 26, Open River South, and La Grange. All imagery was projected to Universal Transverse Mercator (UTM) Zone 15, North American Datum of 1983 (NAD 83). The General Wetland Vegetation Classification (GWVC) system used for mapping is hierarchical, and its 31 classes can be collapsed into broader categories using either a 15- or 7-class level. While the 1989 and 2000 LCU systemic datasets have not gone through a traditional thematic accuracy assessment (AA) in the past, nor have they undergone a validation analysis, the end products are of high quality. For each systemic dataset produced (1989, 2000, 2010–11), extensive field reconnaissance is performed before photointerpretation. The intent of this field reconnaissance is to learn, test, and verify image signatures as they relate to vegetation types. Questionable areas on the imagery are visited, and the plants or land features observed in the area are recorded for reference. This procedure verifies vegetation signatures on the imagery with those on the ground. In addition, once the photointerpretation is complete, the final LCU dataset undergoes extensive quality assurance/quality control to ensure the imagery is mapped correctly. Since the 2000 LCU systemic dataset was developed, there has been a growing interest in completing thematic AAs for the LTRM LCU spatial datasets. The objective of an AA is to measure the probability that a particular location has been assigned its correct vegetation class. An AA estimates thematic (map class) errors in the data, giving users information needed to determine data suitability for a particular application. At the same time, data producers are able to learn more about the nature of errors in the data. Thus, the two attributes of an AA are “producers’ accuracy,” which is the probability that an AA point has been mapped correctly (also referred to as an error of omission); and “users’ accuracy,” which is the probability that the map actually represents what was found on the ground (also referred to as error of commission). Producers’ and users’ accuracies can be obtained from the same set of data by using different analyses. Accuracy assessment is an extensive effort that requires seasonal field personnel and equipment, data entry, analyses, and post processing—tasks that are costly and time consuming. The geospatial team at the UMESC has suggested a validation process for understanding the accuracy of the spatial datasets, which will be tested on at least some areas of the UMRS. Validation is not a true verification of map-class type in the field; however, it can provide the user of the map with useful information that is similar to a field AA. Similar to an AA, validation involves generating random points based on the total area for each map class. However, instead of collecting field data, two or three individuals not involved with the photo-interpretative mapping separately review each of the points onscreen and record a best-fit vegetation type(s) for each site. Once the individual analyses are complete, results are joined together and a comparative analysis is performed. The objective of this initial analysis is to identify areas where the validation results were in agreement (matches) and areas where validation results were in disagreement (mismatches). The two or three individuals then perform an analysis, looking at each mismatched site, and agree upon a final validation class. (If two vegetation types at a specific site appear to be equally prevalent, the validation team is permitted to assign the site two best-fit vegetation types.) Following the validation team’s comparative analysis of vegetation assignments, the data are entered into a database and compared to the mappers’ vegetation assignments. Agreements and disagreements between the map and validation classes are identified, and a contingency table is produced. This document presents the AA processes/results for Pools 13 and La Grange, as well as the validation process/results for Pools 13 and 26 and Open River South.

Iowa, Illinois, Minnesota, Missouri, Wisconsin↗

USGS2021

Assessing the uncertainties in climatic estimates based on vegetation assemblages: Examples from modern vegetation assemblages in the American Southwest

Assemblages of fossil plant remains have been widely used to reconstruct past climatic conditions, usually through the application of methods that involve either finding vegetation analogues on the modern landscape (and using the modern associated climatic values as the basis for an estimate) or using the modern climatic ranges of individual taxa in an assemblage to determine the range of a given climate variable that would allow these plant taxa to live together. Although these approaches are relatively straightforward, it is difficult to assess the uncertainties associated with each approach, particularly in regard to their application to plant macrofossil assemblages. To explore the uncertainty that may arise from inaccuracy and imprecision in climate reconstructions and from ecological considerations we used variants of both approaches to estimate climate from two data sets of modern vegetation assemblages from the southwestern United States: (1) 1752 gridded “virtual plant assemblages” based on plant range maps that provide uniform spatial coverage of the presence or absence of major woody plant taxa across the study area; and (2) 43 modern packrat ( Neotoma spp.) midden presence-absence assemblages that are similar to fossil midden assemblages. By comparing observed and estimated climate values, we evaluated the quality of the climate estimates, identified sources of uncertainty, and characterized the nature and magnitude of the effects of these uncertainties on the climate estimates. Uncertainties in estimating climate from vegetation assemblages arise because any given plant taxon (or assemblage) must have the resiliency to survive a range of climatic variability, and because of the strong intercorrelations among climatic variables in the modern climate data. Additional sources of uncertainty in climate estimates from plant assemblages include: (1) the modern climate and plant distribution data that are selected as the basis for estimation; (2) the particular quantitative approach that is used to estimate climate; (3) the sufficiency of the number of taxa in the analysis for providing an unbiased representation of the vegetation community as it existed for each time period in the analysis; and, (4) the location of the assemblage on the climatic and environmental gradients in the calibration data set for each climate variable under consideration. We conclude that vegetation assemblages can provide valid and reproducible estimates of climatic variables and that the primary trends and mapped patterns in the observed climate data can be reconstructed from such estimates. However, many factors may affect the quality of an estimate from a given plant assemblage, including aspects of data selection, data adequacy, methodologies, and the location of the assemblage site relative to gradients in the base climate data. It is particularly difficult to accurately estimate extreme values in the observed climate data, because estimated values from either end of an observed climate gradient necessarily “move toward the middle” of the gradient. In addition, the interval chosen to represent modern climate (here we used 1961 to 1990) may have a large impact on the size of the estimated difference between modern and past climate at a given site.

Arizona, California, Colorado, Nevada, New Mexico,↗

USGS1998

Geospatial Technology Applications and Infrastructure in the Biological Resources Division

Executive Summary -- Automated spatial processing technology such as geographic information systems (GIS), telemetry, and satellite-based remote sensing are some of the more recent developments in the long history of geographic inquiry. For millennia, humankind has endeavored to map the Earth's surface and identify spatial relationships. But the precision with which we can locate geographic features has increased exponentially with satellite positioning systems. Remote sensing, GIS, thematic mapping, telemetry, and satellite positioning systems such as the Global Positioning System (GPS) are tools that greatly enhance the quality and rapidity of analysis of biological resources. These technologies allow researchers, planners, and managers to more quickly and accurately determine appropriate strategies and actions. Researchers and managers can view information from new and varying perspectives using GIS and remote sensing, and GPS receivers allow the researcher or manager to identify the exact location of interest. These geospatial technologies support the mission of the U.S. Geological Survey (USGS) Biological Resources Division (BRD) and the Strategic Science Plan (BRD 1996) by providing a cost-effective and efficient method for collection, analysis, and display of information. The BRD mission is 'to work with others to provide the scientific understanding and technologies needed to support the sound management and conservation of our Nation's biological resources.' A major responsibility of the BRD is to develop and employ advanced technologies needed to synthesize, analyze, and disseminate biological and ecological information. As the Strategic Science Plan (BRD 1996) states, 'fulfilling this mission depends on effectively balancing the immediate need for information to guide management of biological resources with the need for technical assistance and long-range, strategic information to understand and predict emerging patterns and trends in ecological systems.' Information sharing plays a key role in nearly everything BRD does. The Strategic Science Plan discusses the need to (1) develop tools and standards for information transfer, (2) disseminate information, and (3) facilitate effective use of information. This effort centers around the National Biological Information Infrastructure (NBII) and the National Spatial Data Infrastructure (NSDI), components of the National Information Infrastructure. The NBII and NSDI are distributed electronic networks of biological and geographical data and information, as well as tools to help users around the world easily find and retrieve the biological and geographical data and information they need. The BRD is responsible for developing scientifically and statistically reliable methods and protocols to assess the status and trends of the Nation's biological resources. Scientists also conduct important inventory and monitoring studies to maintain baseline information on these same resources. Research on those species for which the Department of the Interior (DOI) has trust responsibilities (including endangered species and migratory species) involves laboratory and field studies of individual animals and the environments in which they live. Researchboth tactical and strategicis conducted at the BRD's 17 science centers and 81 field stations, 54 Cooperative Fish and Wildlife Research Units in 40 states, and at 11 former Cooperative Park Study Units. Studies encompass fish, birds, mammals, and plants, as well as their ecosystems and the surrounding landscape. Biological Resources Division researchers use a variety of scientific tools in their endeavors to understand the causes of biological and ecological trends. Research results are used by managers to predict environmental changes and to help them take appropriate measures to manage resources effectively. The BRD Geospatial Technology Program facilitates the collection, analysis, and dissemination of data and informat

Information and Technology Report↗

USGS2025

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

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

Open-File Report↗

USGS2015

Modeling tidal freshwater marsh sustainability in the Sacramento-San Joaquin Delta under a broad suite of potential future scenarios

In this paper, we report on the adaptation and application of a one-dimensional marsh surface elevation model, the Wetland Accretion Rate Model of Ecosystem Resilience (WARMER), to explore the conditions that lead to sustainable tidal freshwater marshes in the Sacramento–San Joaquin Delta. We defined marsh accretion parameters to encapsulate the range of observed values over historic and modern time-scales based on measurements from four marshes in high and low energy fluvial environments as well as possible future trends in sediment supply and mean sea level. A sensitivity analysis of 450 simulations was conducted encompassing a range of eScholarship provides open access, scholarly publishing services to the University of California and delivers a dynamic research platform to scholars worldwide. porosity values, initial elevations, organic and inorganic matter accumulation rates, and sea-level rise rates. For the range of inputs considered, the magnitude of SLR over the next century was the primary driver of marsh surface elevation change. Sediment supply was the secondary control. More than 84% of the scenarios resulted in sustainable marshes with 88 cm of SLR by 2100, but only 32% and 11% of the scenarios resulted in surviving marshes when SLR was increased to 133 cm and 179 cm, respectively. Marshes situated in high-energy zones were marginally more resilient than those in low-energy zones because of their higher inorganic sediment supply. Overall, the results from this modeling exercise suggest that marshes at the upstream reaches of the Delta—where SLR may be attenuated—and high energy marshes along major channels with high inorganic sediment accumulation rates will be more resilient to global SLR in excess of 88 cm over the next century than their downstream and low-energy counterparts. However, considerable uncertainties exist in the projected rates of sea-level rise and sediment avail-ability. In addition, more research is needed to constrain future rates of aboveground and belowground plant productivity under increased CO<sub>2</sub> concentrations and flooding.

California↗

USGS2023

Land development and road salt usage drive long-term changes in major-ion chemistry of streamwater in six exurban and suburban watersheds, southeastern Pennsylvania, 1999-2019

In urbanized areas, the “freshwater salinization syndrome” (FSS), which pertains to long-term increases in concentrations of major ions and metals in fresh surface waters, has been attributed to road salt application. In addition to FSS, the water composition changes as an influx of sodium (Na + ) in recharge may displace calcium (Ca 2+ ), magnesium (Mg 2+ ), potassium (K + ), and trace metals by reverse cation exchange. These changing ion fluxes can result in adverse impacts on groundwater and surface waters used for municipal supplies. Few datasets exist to quantify the FSS on a watershed scale or link its manifestation to potential controlling factors such as changes in urban development, land use/land cover (LULC), or wastewater treatment plant (WWTP) discharges in upstream areas. Here, we use two decades (1999–2019) of monthly streamwater quality data combined with daily streamflow for six exurban and suburban watersheds in southeastern Pennsylvania to examine the relations among Ca 2+ , Mg 2+ , K + , Na + , chloride (Cl − ), sulfate (SO 4 2- ), and alkalinity (HCO 3 − ) concentrations and upstream controlling factors. Flow-normalized annual and baseflow (August ̶ November) concentrations for Ca 2+ , Mg 2+ , Na + , and Cl − increased in all six watersheds over the 20-year study, providing evidence of FSS’s impacts on groundwater that sustains streamflow. Additionally, a redundancy analysis using 2019 flow-normalized values identified the following positive associations between solute concentrations and controlling variables: 1) Cl − , Mg 2+ , and Ca 2+ with impervious surface cover (ISC), 2) Na + and SO 4 2- with ISC and total WWTP discharge volume, and 3) HCO 3 − with agriculture and total WWTP discharge volume. From a human health perspective, 2019 flow-normalized Na + concentrations exceeded the U.S. Environmental Protection Agency’s 20 mg L -1 threshold for individuals restricted to a low sodium diet. Furthermore, indices used to evaluate the corrosivity of source waters to drinking water infrastructure and inform municipal water treatment practices, such as the Chloride to Sulfate Mass Ratio and Larson Ratio, increased between two- and seven-fold over the 20-year time. Collectively, the results elucidate the causal factors of the FSS in suburban and exurban watersheds and its potential impacts on human health and drinking water infrastructure.

Pennsylvania↗

USGS2005

Yellowstone grizzly bear investigations: Annual report of the Interagency Grizzly Bear Study Team, 2004

The contents of this Annual Report summarize results of monitoring and research from the 2004 field season. The report also contains a summary of nuisance grizzly bear ( Ursus arctos horribilis ) management actions. The study team continues to work on issues associated with counts of unduplicated females with cubs-of-the-year (COY). These counts are used to establish a minimum population size, which is then used to establish mortality thresholds for the Recovery Plan (U.S. Fish and Wildlife Service [USFWS] 1993). A computer program that defines the rule set used by Knight et al. (1995) to differentiate unique family groups was completed in spring 2005. We will use an improved version of this model to verify the accuracy of the rules using known bears and their telemetry locations in test runs. We hope to have this work complete by the end of 2005. The grizzly bear recovery plan (USFWS 1993) established mortality quotas at 4% of the minimum population estimate derived from female with COY data and no more than 30% of the 4% (1.2%) could be female bears. Simulation modeling (Harris 1984) established sustainable mortality at around 6% of the population. We used the latest information on reproduction and survival to estimate population trajectory in the same simulation model originally used by Harris. A Wildlife Monograph has been accepted for publication and should be available by summer 2005. Our project addressing the potential application of stable isotopes and trace elements to quantify consumption rates of whitebark pine ( Pinus albicaulis ) and cutthroat trout ( Oncorhynchus clarki ) by grizzly bears was completed. Our manuscript on consumption rates of whitebark pine has been published (Canadian Journal of Zoology 81:763-770). The manuscript on fish consumption rates was also accepted and is published in the Canadian Journal of Zoology 82:493-501. Both can be found on the Interagency Grizzly Bear Study Team (IGBST) website http://www.nrmsc.usgs.gov/research/igbst-home.htm. We began a new study in Grand Teton National Park evaluating habitat use both temporally and spatially between grizzly and black ( Ursus americanus ) bears. We will employ a new form of Global Positioning System (GPS) technology that incorporates a spread spectrum communication system. Spread spectrum allows for transfer of stored GPS locations from the collar to a remote receiving station. Results of our first yea r’s field season are summarized in this report. Whitebark pine (WBP) has been identified as one of the import ant fall foods of the Yellowstone grizzly bear. Previous efforts to map the distribution of WBP were for the Cumulative Effects Model. Consequently the only coverage of WBP distribution was for the grizzly bear Recovery Zone. We were successful in getting financial support through the U.S. Geological Survey Land Remote Sensing Program and Interdisciplinary Science Support Activities Project to create an ecosystem-wide map of the distribution of WBP. The results of that project are reported in Appendix A. The study team annually estimates WBP cone production on a series of transects. That information is reported annually in our reports. Concern over the long-term health of WBP prompted us to investigate the usefulness of cone counts as an indirect index of WBP health. Results of this analysis (Appendix B) indicated that cone production is too variable to serve this purpose. Consequently, we partnered with several 2 other agencies and embarked on a program to develop a long-term monitoring program directed specifically at WBP health in the Greater Yellowstone Ecosystem (GYE). Our team (Greater Yellowstone Whitebark Pine Monitoring Working Group) was successful in obtaining funds to develop and implement a WBP health monitoring program. Results of our first years work are presented in Appendix C. We also successfully competed for funds in 2005 and will continue to collect information on WBP health. Army cutworm moths ( Euxoa auxiliaris ) are also a very important food for a segment of the GYE grizzly bear population. Hillary Robison, graduate student at University of Nevada, Reno, is nearing completion of her program. In this report, we post her annual work summary, and abstracts of her most recently submitted publications. These include one on the levels of pesticides in cutworm moths and their potential affect on grizzly bears (Appendix D), a spatial analysis to identify army cutworm moth habitat (Appendix E), and the results of a preliminary analysis of pollen grains on the mouth parts of moths (Appendix F) to help identify which plant species are commonly fed upon. Other study team members have also been working on various aspects of grizzly bear science. Study team member Kerry Gunther hosted a workshop on habituated grizzly bears in North America. A copy of the abstract of that report can be found in Appendix G. Additionally, Kerry Gunther and Doug Smith, wolf researcher in Yellowstone National Park (YNP), reported on the interactions between gray wolves ( Canis lupus ) and female grizzly bears with young. They report that of 15 interactions between these 2 carnivores, 8 involve d females with COY. They observed 2 incidents where cubs were killed by wolves at ungulate carcasses (Appendix H). The annual reports of the IGBST summarize annual data collection. Because additional information can be obtained after publication, data summaries are subject to change. For that reason, data analyses and summaries presented in this report supersede all previously published data. The study area and sampling techniques are reported by Blanchard (1985), Mattson et al. (1991 a ), and Haroldson et al. (1998).

Idaho, Montana, Wyoming↗

USGS2013

Application of a hydrodynamic and sediment transport model for guidance of response efforts related to the Deepwater Horizon oil spill in the Northern Gulf of Mexico along the coast of Alabama and Florida

U.S. Geological Survey (USGS) scientists have provided a model-based assessment of transport and deposition of residual Deepwater Horizon oil along the shoreline within the northern Gulf of Mexico in the form of mixtures of sand and weathered oil, known as surface residual balls (SRBs). The results of this USGS research, in combination with results from other components of the overall study, will inform operational decisionmaking. The results will provide guidance for response activities and data collection needs during future oil spills. In May 2012 the U.S. Coast Guard, acting as the Deepwater Horizon Federal on-scene coordinator, chartered an operational science advisory team to provide a science-based review of data collected and to conduct additional directed studies and sampling. The goal was to characterize typical shoreline profiles and morphology in the northern Gulf of Mexico to identify likely sources of residual oil and to evaluate mechanisms whereby reoiling phenomena may be occurring (for example, burial and exhumation and alongshore transport). A steering committee cochaired by British Petroleum Corporation (BP) and the National Oceanic and Atmospheric Administration (NOAA) is overseeing the project and includes State on-scene coordinators from four States (Alabama, Florida, Louisiana, and Mississippi), trustees of the U.S. Department of the Interior (DOI), and representatives from the U.S. Coast Guard. This report presents the results of hydrodynamic and sediment transport models and developed techniques for analyzing potential SRB movement and burial and exhumation along the coastline of Alabama and Florida. Results from these modeling efforts are being used to explain the complexity of reoiling in the nearshore environment and to broaden consideration of the different scenarios and difficulties that are being faced in identifying and removing residual oil. For instance, modeling results suggest that larger SRBs are not, under the most commonly observed low-energy wave conditions, likely to move very far alongshore. This finding suggests that SRBs from one source location may not (outside of storm conditions) be redistributed to other up or down coast locations. This information can guide operational response decisions. In addition, because SRBs are less mobile compared with sand, they are likely to become buried and unburied under normal sand transport processes thereby lengthening the time SRBs may take to move onshore. The rate of onshore movement was not specifically addressed by this study, yet the results resolve the cross-shore domain and cross-shore variations in alongshore transport that are relevant to achieving the primary objectives. Furthermore, during infrequent events (for example, winter storms and severe meteorological events such as Hurricane Isaac of August 2012), energy is shown to be sufficient to move a greater range of SRB sizes and potentially expose and break up submerged oil mats. When SRBs do move alongshore, the models indicate that there are regions that are more conducive to accumulation of SRB material than others. Accumulation can occur where there are reversals and decelerations in alongshore currents and where forces created by shear stress drops below critical thresholds to maintain or initiate SRB movement. In addition, flow and SRB mobility patterns around inlets indicate patterns in hydrodynamic forces that influence redistribution of SRBs and the surface oil that mixed with sediment to form oil mats in the first place.

Alabama;Florida↗

USGS2002

Meeting ecological and societal needs for freshwater

Human society has used freshwater from rivers, lakes, groundwater, and wetlands for many different urban, agricultural, and industrial activities, but in doing so has overlooked its value in supporting ecosystems. Freshwater is vital to human life and societal well-being, and thus its utilization for consumption, irrigation, and transport has long taken precedence over other commodities and services provided by freshwater ecosystems. However, there is growing recognition that functionally intact and biologically complex aquatic ecosystems provide many economically valuable services and long-term benefits to society. The short-term benefits include ecosystem goods and services, such as food supply, flood control, purification of human and industrial wastes, and habitat for plant and animal life—and these are costly, if not impossible, to replace. Long-term benefits include the sustained provision of those goods and services, as well as the adaptive capacity of aquatic ecosystems to respond to future environmental alterations, such as climate change. Thus, maintenance of the processes and properties that support freshwater ecosystem integrity should be included in debates over sustainable water resource allocation. The purpose of this report is to explain how the integrity of freshwater ecosystems depends upon adequate quantity, quality, timing, and temporal variability of water flow. Defining these requirements in a comprehensive but general manner provides a better foundation for their inclusion in current and future debates about allocation of water resources. In this way the needs of freshwater ecosystems can be legitimately recognized and addressed. We also recommend ways in which freshwater ecosystems can be protected, maintained, and restored. Freshwater ecosystem structure and function are tightly linked to the watershed or catchment of which they are a part. Because riverine networks, lakes, wetlands, and their connecting groundwaters, are literally the “sinks” into which landscapes drain, they are greatly influenced by terrestrial processes, including many human uses or modifications of land and water. Freshwater ecosystems, whether lakes, wetlands, or rivers, have specific requirements in terms of quantity, quality, and seasonality of their water supplies. Sustainability normally requires these systems to fluctuate within a natural range of variation. Flow regime, sediment and organic matter inputs, thermal and light characteristics, chemical and nutrient characteristics, and biotic assemblages are fundamental defining attributes of freshwater ecosystems. These attributes impart relatively unique characteristics of productivity and biodiversity to each ecosystem. The natural range of variation in each of these attributes is critical to maintaining the integrity and dynamic potential of aquatic ecosystems; therefore, management should allow for dynamic change. Piecemeal approaches cannot solve the problems confronting freshwater ecosystems. Scientific definitions of the requirements to protect and maintain aquatic ecosystems are necessary but insufficient for establishing the appropriate distribution between societal and ecosystem water needs. For scientific knowledge to be implemented science must be connected to a political agenda for sustainable development. We offer these recommendations as a beginning to redress how water is viewed and managed in the United States: (1) Frame national and regional water management policies to explicitly incorporate freshwater ecosystem needs, particularly those related to naturally variable flow regimes and to the linking of water quality with water quantity; (2) Define water resources to include watersheds, so that freshwaters are viewed within a landscape, or systems context; (3) Increase communication and education across disciplines, especially among engineers, hydrologists, economists, and ecologists to facilitate an integrated view of freshwater resources; (4) Increase restoration efforts, using well-grounded ecological principles as guidelines; (5) Maintain and protect the remaining freshwater ecosystems that have high integrity; and (6) Recognize the dependence of human society on naturally functioning ecosystems.

Ecological Applications↗

USGS2013

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

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

Minnesota;Montana;North Dakota;South Dakota↗