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At least 217 records · Page 12Linked to original sources
USGS2025

The value of reducing uncertainties to support the management of a high‐elevation endemic salamander

Many salamander populations are declining, and methods to determine how best to allocate limited resources to slow or reverse these declines could support land managers in their decision‐making processes. Multiple types of uncertainty may delay management decisions, including when (1) knowledge of a species' ecology is incomplete, (2) climate change effects on environmental covariates are uncertain, and (3) the efficacy of management alternatives is unknown. For management decisions, a value‐of‐information analysis can identify which uncertainties are critical to reduce in order to identify an optimal strategy from a set of possible management actions. If the same management action is optimal across the full range of uncertainties, then resources for research can be redirected toward active management. Using value‐of‐information analyses, we examine the effect of uncertainty on identifying optimal management to maximize the future expected occupancy of Plethodon shenandoah , a Federally Endangered high‐elevation endemic salamander that is threatened by climate change. Out of 11 management actions proposed by National Park Service managers, those that increase environmental moisture are expected to maximize occupancy, and we find that the selection of this action is robust to all the identified uncertainties. We show that, even in systems with multiple sources of large uncertainty, value of information analyses discriminate among investments in species management.

Ecosphere↗
USGS2021

Elemental and radionuclide exposures and uptakes by small rodents, invertebrates, and vegetation at active and post-production uranium mines in the Grand Canyon watershed

The effects of breccia pipe uranium mining in the Grand Canyon watershed (Arizona) on ecological and cultural resources are largely unknown. We characterized the exposure of biota to uranium and co-occurring ore body elements during active ore production and at a site where ore production had recently concluded. Our results indicate that biota have taken up uranium and other elements (e.g., arsenic, cadmium, copper, molybdenum, uranium) from exposure to ore and surficial contamination, like blowing dust. Results indicate the potential for prolonged exposure to elements and radionuclides upon conclusion of active ore production. Mean radium-226 in deer mice was up to 4 times greater than uranium-234 and uranium-238 in those same samples; this may indicate a potential for, but does not necessarily imply, radium-226 toxicity. Soil screening benchmarks for uranium and molybdenum and other toxicity thresholds for arsenic, copper, selenium, uranium (e.g., growth effects) were exceeded in vegetation, invertebrates, and rodents ( Peromyscus spp. , Thomomys bottae, Tamias dorsalis, Dipodomys deserti ). However, the prevalence and severity of microscopic lesions in rodent tissues (as direct evidence of biological effects of uptake and exposure) could not be definitively linked to mining. Our data indicate that land managers might consider factors like species, seasonal changes in environmental concentrations, and bioavailability, when determining mine permitting and remediation in the Grand Canyon watershed. Ultimately, our results will be useful for site-specific ecological risk analysis and can support future decisions regarding the mineral extraction withdrawal in the Grand Canyon watershed and elsewhere.

Arizona↗
USGS2019

Roost- and perch-site selection by Golden Eagles (Aquila chrysaetos) in eastern North America

Birds select critical resources to meet needs that vary in response to spatial, temporal, and individual variation. As an example, perch or roost sites may be at locations that provide protection from predators, mobbing, or inclement weather. Applied to large, soaring predators, this theory suggests that they may select perch and roost sites near food resources or at sites where environmental updrafts develop. To test these theories, we characterized selection of nonflight locations throughout the annual cycle for Golden Eagles ( Aquila chrysaetos ) in eastern North America. We determined factors associated with selection of perching (daytime) and roosting (nighttime) sites by eagles by comparing land cover and topographic characteristics of GPS telemetry locations for eagles (used) with random (available) locations. We separately assessed selection for perch and roost sites during each of 4 seasons (winter, summer, and spring and fall migration). Golden Eagles showed different selection patterns for perching by season and age. Throughout the year, eagles selected perch sites on steep slopes. The direction these slopes faced differed among seasons, with eagles selecting south-facing slopes in summer and east-facing slopes during migration. Adults showed greater preferences for broadleaf forests in summer and for ridges in fall. Patterns of perch-site use were consistent with selection for sites that provide thermal protection and access to thermal updrafts. We found few patterns of selection for roosting sites. Our analysis provides insight into decision-making by a longdistance migrant across its annual cycle and throughout its geographic range, and thus into how resource selection changes seasonally.

Wilson Journal of Ornithology↗
USGS2026

Using structured decision-making to develop a communications strategy for the U.S. Geological Survey Cooperative Research Units Program

Communication regarding the mission of the U.S. Geological Survey (USGS) Cooperative Research Units Program (CRU) can take many forms, yet clear and concise messaging for various audiences is critical to highlight program accomplishments and increase visibility. Before the work described in this report, CRU did not have a communication strategy; therefore, CRU leadership supported a structured decision-making (SDM) workshop to develop a comprehensive strategy for multiple audiences. The workshop was conducted in November 2024, in Nebraska City, Nebraska. The working group for this SDM process included CRU Program leadership, the CRU Communications Team lead, Unit scientists, a Unit administrative assistant, a representative of the Wildlife Management Institute (WMI), a member of the USGS Ecosystems Mission Area (EMA), Office of Communications and Publishing (OCAP) team, and the team lead for the CRU Program strategic planning process, as well as three facilitators who were also unit scientists as well as experts in SDM. Over the course of a week, the SDM team followed the PrOACT framework which identified the problem, objectives, alternatives, consequences, and tradeoffs to guide us toward a strategy for implementation of a set of actions for CRU communications. Results of the SDM workshop included the development of a problem statement, an objectives hierarchy, a suite of alternatives that were evaluated using a consequences table and a clear process for assessing tradeoffs among alternative communication actions and strategies. Through the evaluation of consequences of each action or campaign, the team developed both the assessment tool (for the future) and an immediate plan for communication product development and distribution. The consequences table for this problem was meant to be flexible to accommodate changes in CRU thematic priorities and can be easily updated with new objectives, measures, and alternatives. In addition, the weight placed on objectives may change as the Team moves forward; the ranking and scoring system used in the workshop can be easily updated. Overall, the working group identified three different actions or campaigns—Fact Sheets, Who Are We Campaign, and Alumni Campaign—that scored high in the prototype decision framework. However, the tradeoffs analysis indicated that each action(s) performed better on some objectives than others. The working group identified a need to therefore develop an implementation plan that is composed of individual actions that each target different objectives to potentially create a holistic and feasible communications strategy that performs well for all objectives. In addition, the SDM prototype developed a scalable, objective-based framework for effectively communication of the value and accomplishments of the CRU program.

Preprints.org↗
USGS2024

Quantifying the coastal hazard risk reduction benefits of coral reef restoration in the U.S. Virgin Islands

Coastal habitat restoration, especially of coral reef ecosystems, can significantly reduce the exposure of coastal communities to natural hazards and, consequently, the risk of wave-driven flooding. Likewise, reef degradation can increase coastal flood risks to people and property. In this study, the valuation of coral reefs in the United States Virgin Islands (USVI), along the coasts of St. Croix, St. John, and St. Thomas, demonstrated the social and economic benefits provided by these natural defenses. Across the territory, more than 481 people and $31.2 million of infrastructure were estimated to receive protection from coral reefs per year (2010 U.S. dollars). In 2017, Hurricanes Irma and Maria significantly damaged coral reefs throughout the archipelago. By combining engineering, ecological, geospatial, social, and economic data and tools, this study provided a rigorous valuation of where potential coral reef restoration projects could help rebuild these damaged habitats and decrease the risks from coastal hazards faced by USVI’s reef-fronted communities. Multiple restoration scenarios were considered in the analysis, two of which are detailed in this report. These include (1) ‘Ecological’ restoration, where restoration creates a structure that is 0.25 m high and 25-m-wide reef, and (2) ‘Hybrid’ restoration, where restoration creates a structure that is 1.25 m high and 5 m wide. There are many ways that such structures could be developed. In the hydrodynamic analyses, there are no assumptions about how the restoration is developed. Many practitioners of both coral (and oyster reef) restoration consider that a reef height of 0.25 m might be delivered from planting corals alone and that 1.25 m might require a combination of artificial structures and coral planting. In a third scenario, the analysis investigated the reduction of protection benefits that would occur through the reduction of 1 meter of naturally occurring reef height due to reef degradation. The reduction of protection due to the loss of reefs can also be interpreted as the protection value of the existing reefs. In all studied restoration scenarios, it was assumed that the planting of corals would enhance hydrodynamic roughness, effectively dissipating incident wave energy and reducing the potential for coastal flooding. A standardized approach was employed to strategically locate potential restoration projects along the entire linear extent of existing reefs bordering the USVI, and to identify where coral reef restoration could offer valuable benefits in flood reduction. Potential restoration projects were only located within the existing distribution of reefs across the region, even though numerous sites were positioned far offshore (2-3 km), and some were at relatively deep depths (up to 7 m). Risk-based valuation approaches were followed to delineate flood zones at a 10 m 2 resolution along the entire region's reef-lined shorelines for all the potential coral reef restoration scenarios. These were subsequently compared to flood zones without coral reef restoration. The potential reduction in coastal flood risk provided by coral reef restoration, and the protection value of existing reefs, were quantified utilizing the latest information available at the time of analysis from the U.S. Census Bureau, Federal Emergency Management Agency (FEMA), and Bureau of Economic Analysis for return-interval storm events. The change in Expected Annual Damages (EAD), a metric indicating the annual protection gained due to coral reef restoration, was calculated based on the damages associated with each storm probability. The findings suggest that the benefits of reef restoration are spatially variable within the USVI. In some areas, the analysis showed limited benefits from reef restoration, which may be attributed to the depth or offshore distances of proposed restoration sites. However, there were a number of key areas where reef restoration could have substantial benefits for flood risk reduction. The annual flood risk reduction attributed to potential ‘ecological’ coral reef restoration in the USVI was 99 people and $6.1 million (2010 U.S. dollars). The Benefit-to-Cost Ratio (BCR) for this restoration approach was found to be larger than 1 (i.e., cost-effective) along 11% of the St. Croix coastline, 4.9% of the St. John coastline, and 8.7% of the St. Thomas coastline. This analysis offers stakeholders and decision-makers a spatially explicit and rigorous evaluation that illustrates how, where, and when potential coral reef restoration efforts in St. Croix, St. John, and St. Thomas could be instrumental to reducing coastal storm-induced flooding. Understanding areas where reef management, recovery, and restoration could effectively reduce climate hazard-related risks is crucial to protect and enhance the resilience of coastal communities in USVI.

Report↗
USGS2003

Regional forest land cover characterisation using medium spatial resolution satellite data

Increasing demands on forest resources require comprehensive, consistent and up-to-date information on those resources at spatial scales appropriate for management decision-making and for scientific analysis. While such information can be derived using coarse spatial resolution satellite data (e.g. Tucker et al. 1984; Zhu and Evans 1994; Cihlar et al. 1996; Cihlar et al., Chapter 12), many regional applications require more spatial and thematic details than can be derived by using coarse resolution imagery. High spatial resolution satellite data such as IKONOS and Quick Bird images (Aplin et al. 1997), though usable for deriving detailed forest information (Culvenor, Chapter 9), are currently not feasible for wall-to-wall regional applications because of extremely high data cost, huge data volume, and lack of contiguous coverage over large areas. Forest studies over large areas have often been accomplished using data acquired by intermediate spatial resolution sensor systems, including the Multi-Spectral Scanner (MSS), Thematic Mapper (TM) and the Enhanced Thematic Mapper Plus (ETM+) of Landsat, the High Resolution Visible (HRV) of the Systeme Pour l'Observation de la Terre (SPOT), and the Linear Image Self-Scanner (LISS) of the Indian Remote Sensing satellite. These sensor systems are more appropriate for regional applications because they can routinely produce spatially contiguous data over large areas at relatively low cost, and can be used to derive a host of forest attributes (e.g. Cohen et al. 1995; Kimes et al. 1999; Cohen et al. 2001; Huang et al. 2001; Sugumaran 2001). Of the above intermediate spatial resolution satellites, Landsat is perhaps the most widely used in various types of land remote sensing applications, in part because it has provided more extensive spatial and temporal coverage of the globe than any other intermediate resolution satellite. Spatially contiguous Landsat data have been developed for many regions of the globe (e.g. Lunetta and Sturdevant 1993; Fuller et al. 1994b; Skole et al. 1997), and a circa 1990 Landsat image data set covering the entire land area of the globe has also been developed recently (Jones and Smith 2001). An acquisition strategy aimed at acquiring at least one cloud free image per year for the entire land area of the globe has been initiated for Landsat-7 (Arvidson et al. 2001). This will probably ensure the continued dominance of Landsat in the near future.

Book chapter↗
USGS2009

Prioritizing removal of dams for passage of diadromous fishes on a major river system

Native diadromous fishes have been extirpated from much of the Susquehanna River system for nearly a century. Recent restoration efforts have focused on removal of dams, but there are hundreds of dams and presently there is no biologically based system to assist in prioritizing their removal. We present a new method that uses existing habitat suitability index models (HSI) for American shad Alosa sapidissima, alewife A. pseudoharengus, blueback herring A. aestivalis, and American eel Anguilla rostrata to prioritize the removal of non-hydropower dams within the Susquehanna River system. We ranked HSI scores for each of the four species, association between a landscape-scale factor and HSIs, length of river opened by removing a dam, and distance from the mouth at Chesapeake Bay for each dam and then calculated a mean rank prioritization for dam removal by averaging the ranks for the seven criteria. This prioritization method is resistant to outliers, is not strongly affected by somewhat arbitrary decisions on metrics included in the analysis, and provides a biologically based prioritization for dam removal that can be easily amended to include other metrics or adapted to other river systems and that complements other social and economic considerations that must be included in decisions to remove dams.

River Research and Applications↗
USGS2008

Analysis of trade-offs between threats of invasion by nonnative brook trout (Salvelinus fontinalis) and intentional isolation for native westslope cutthroat trout (Oncorhynchus clarkii lewisi)

Native salmonid fishes often face simultaneous threats from habitat fragmentation and invasion by nonnative trout species. Unfortunately, management actions to address one may create or exacerbate the other. A consistent decision process would include a systematic analysis of when and where intentional use or removal of barriers is the most appropriate action. We developed a Bayesian belief network as a tool for such analyses. We focused on native westslope cutthroat trout (Oncorhynchus clarkii lewisi) and nonnative brook trout (Salvelinus fontinalis) and considered the environmental factors influencing both species, their potential interactions, and the effects of isolation on the persistence of local cutthroat trout populations. The trade-offs between isolation and invasion were strongly influenced by size and habitat quality of the stream network to be isolated and existing demographic linkages within and among populations. An application of the model in several sites in western Montana (USA) showed the process could help clarify management objectives and options and prioritize conservation actions among streams. The approach can also facilitate communication among parties concerned with native salmonids, nonnative fish invasions, barriers and intentional isolation, and management of the associated habitats and populations. ?? 2008 NRC.

Canadian Journal of Fisheries and Aquatic Sciences↗
USGS2023

The Landscape Data Commons: A system for standardizing, accessing, and applying large environmental datasets for agroecosystem research and management

Understanding where, when, and why agroecosystems are changing requires quality information about ecosystems that span land tenure, ecological processes, and spatial scales. Over the past two decades, land management agencies and research groups have adopted a suite of standardized methods for monitoring rangelands, which have been implemented at over 85,000 monitoring locations globally. However, the ability to use these data to understand agroecosystem dynamics and change across scales and across land ownership has been limited because, until now, these data have not been available in a harmonized, accessible format for analyses, modeling, and decision-support tools. We present the Landscape Data Commons, a cyberinfrastructure platform that harmonizes and aggregates standardized agroecosystem data, enables linkages to models, and facilitates analysis and interpretation of data within decision-support tools. The Landscape Data Commons provides a community platform for users to contribute data and develop next-generation tools to support agroecosystem management through the 21st century.

Agricultural & Environmental Letters↗
USGS2015

Training conservation practitioners to be better decision makers

Traditional conservation curricula and training typically emphasizes only one part of systematic decision making ( i.e. , the science), at the expense of preparing conservation practitioners with critical skills in values-setting, working with decision makers and stakeholders, and effective problem framing. In this article we describe how the application of decision science is relevant to conservation problems and suggest how current and future conservation practitioners can be trained to be better decision makers. Though decision-analytic approaches vary considerably, they all involve: (1) properly formulating the decision problem; (2) specifying feasible alternative actions; and (3) selecting criteria for evaluating potential outcomes. Two approaches are available for providing training in decision science, with each serving different needs. Formal education is useful for providing simple, well-defined problems that allow demonstrations of the structure, axioms and general characteristics of a decision-analytic approach. In contrast, practical training can offer complex, realistic decision problems requiring more careful structuring and analysis than those used for formal training purposes. Ultimately, the kinds and degree of training necessary depend on the role conservation practitioners play in a decision-making process. Those attempting to facilitate decision-making processes will need advanced training in both technical aspects of decision science and in facilitation techniques, as well as opportunities to apprentice under decision analysts/consultants. Our primary goal should be an attempt to ingrain a discipline for applying clarity of thought to all decisions.

Sustainability↗
USGS2016

Combining statistical inference and decisions in ecology

Statistical decision theory (SDT) is a sub-field of decision theory that formally incorporates statistical investigation into a decision-theoretic framework to account for uncertainties in a decision problem. SDT provides a unifying analysis of three types of information: statistical results from a data set, knowledge of the consequences of potential choices (i.e., loss), and prior beliefs about a system. SDT links the theoretical development of a large body of statistical methods including point estimation, hypothesis testing, and confidence interval estimation. The theory and application of SDT have mainly been developed and published in the fields of mathematics, statistics, operations research, and other decision sciences, but have had limited exposure in ecology. Thus, we provide an introduction to SDT for ecologists and describe its utility for linking the conventionally separate tasks of statistical investigation and decision making in a single framework. We describe the basic framework of both Bayesian and frequentist SDT, its traditional use in statistics, and discuss its application to decision problems that occur in ecology. We demonstrate SDT with two types of decisions: Bayesian point estimation, and an applied management problem of selecting a prescribed fire rotation for managing a grassland bird species. Central to SDT, and decision theory in general, are loss functions. Thus, we also provide basic guidance and references for constructing loss functions for an SDT problem.

Ecological Applications↗
USGS2020

Using value of information to prioritize research needs for migratory bird management under climate change: A case study using federal land acquisition in the United States

In response to global habitat loss, many governmental and non‐governmental organizations have implemented land acquisition programs to protect critical habitats permanently for priority species. The ability of these protected areas to meet future management objectives may be compromised if the effects of climate change are not considered in acquisition decisions. Unfortunately, the effects of climate change on ecological systems are complex and plagued by uncertainty, making it difficult for organizations to prioritize research needs to improve decision‐making. Herein, we demonstrate the use of qualitative value of information analysis to identify and prioritize which sources of uncertainty should be reduced to improve land acquisition decisions to protect migratory birds in the face of climate change. The qualitative value of information analysis process involves four steps: ( i ) articulating alternative hypotheses; ( ii ) determining the magnitude of uncertainty regarding each hypothesis; ( iii ) evaluating the relevance of each hypothesis to acquisition decision‐making; and ( iv ) assessing the feasibility of reducing the uncertainty surrounding each hypothesis through research and monitoring. We demonstrate this approach using the objectives of 3 U.S. federal land acquisition programs that focus on migratory bird management. We used a comprehensive literature review, expert elicitation, and professional judgement to evaluate 11 hypotheses about the effect of climate change on migratory birds. Based on our results, we provide a list of priorities for future research and monitoring to reduce uncertainty and improve land acquisition decisions for the programs considered in our case study. Reducing uncertainty about how climate change will influence the spatial distribution of priority species and biotic homogenization were identified as the highest priorities for future research due to both the value of this information for improving land acquisition decisions and the feasibility of reducing uncertainty through research and monitoring. Research on how changes in precipitation patterns and winter severity will influence migratory bird abundance is also expected to benefit land acquisition decisions. By contrast, hypotheses about phenology and migration distance were identified as low priorities for research. By providing a rigorous and transparent approach to prioritizing research, we demonstrate that qualitative value of information is a valuable tool for prioritizing research and improving management decisions in other complex, high‐uncertainty cases where traditional quantitative value of information analysis is not possible. Given the inherent complexity of ecological systems under climate change, and the difficulty of identifying management‐relevant research priorities, we expect this approach to have wide applications within the field of natural resource management.

Biological Reviews↗
USGS1998

Considerations in As analysis and speciation

This article summarizes recent experiences in arsenic (As) quantification, preservation, and speciation developed during AWWA Research Foundation (AWWARF) and Water Industry Technical Action Fund (WITAF) projects. The goal of this article is to alert analysts and decision-makers to potential problems in As analysis and speciation, because there appear to be several unresolved problems with routine analytical approaches. In true split drinking water samples As was quantified by three accepted analytical methods in three laboratories. The techniques used were graphite furnace atomic absorption spectrometry (GFAAS), inductively coupled plasma mass spectrometry (ICP-MS), and hydride generation inductively coupled plasma-emission spectrometry (HG-ICP-AES). Experimental findings are organized into sections on As analysis, particulate As in water supplies, and examination of As speciation methods.

Journal of the American Water Works Association↗
USGS2019

Employing an ecosystem services framework to deliver decision ready science

Public land managers have limited information to allow for the integration and balancing of multiple objectives in land management decisions including the social (cultural and health), economic (monetary and nonmonetary), and environmental aspects. In this article, we document an approach to consider the many facets of decision making by incorporating them into a decision context using an ecosystem services framework. This analysis is based on a multi-partner project led by the US Geological Survey and the US Fish and Wildlife Service to provide land management decision support for the Great Dismal Swamp National Wildlife Refuge. It is an integrated ecologic-economic analysis of baseline (current) and potential future quantities, qualities, and values of selected ecosystem services from the Refuge. Alternative management scenarios are modeled to consider the impact of specific management actions or natural disturbances on priority ecosystem services. We examine the benefits and challenges of using this framework. Key lessons learned from this effort include the mismatch in timing between physical and social science; the challenge of integrating methods from multiple disciplines; the importance of frequent communication to overcome siloed research; and the utility of an integrating framework for ecosystem services and supporting tools such as the dynamic ecosystem model.

Advances in Ecological Research↗
USGS2009

Applications of a broad-spectrum tool for conservation and fisheries analysis: Aquatic gap analysis

Natural resources support all of our social and economic activities, as well as our biological existence. Humans have little control over most of the physical, biological, and sociological conditions dictating the status and capacity of natural resources in any particular area. However, the most rapid and threatening influences on natural resources typically are anthropogenic overuse and degradation. In addition, living natural resources (i.e., organisms) do not respect political boundaries, but are aware of their optimal habitat and environmental conditions. Most organisms have wider spatial ranges than the jurisdictional boundaries of environmental agencies that deal with them; even within those jurisdictions, information is patchy and disconnected. Planning and projecting effects of ecological management are difficult, because many organisms, habitat conditions, and interactions are involved. Conservation and responsible resource use involves wise management and manipulation of the aspects of the environment and biological communities that can be effectively changed. Tools and data sets that provide new insights and analysis capabilities can enhance the ability of resource managers to make wise decisions and plan effective, long-term management strategies. Aquatic gap analysis has been developed to provide those benefits. Gap analysis is more than just the assessment of the match or mis-match (i.e., gaps) between habitats of ecological value and areas with an appropriate level of environmental protection (e.g., refuges, parks, preserves), as the name suggests. Rather, a Gap Analysis project is a process which leads to an organized database of georeferenced information and previously available tools to examine conservation and other ecological issues; it provides a geographic analysis platform that serves as a foundation for aquatic ecological studies. This analytical tool box allows one to conduct assessments of all habitat elements within an area of interest. Aquatic gap analysis naturally focuses on aquatic habitats. The analytical tools are largely based on specification of the species-habitat relations for the system and organism group of interest (Morrison et al. 2003; McKenna et al. 2006; Steen et al. 2006; Sowa et al. 2007). The Great Lakes Regional Aquatic Gap Analysis (GLGap) project focuses primarily on lotic habitat of the U.S. Great Lakes drainage basin and associated states and has been developed to address fish and fisheries issues. These tools are unique because they allow us to address problems at a range of scales from the region to the stream segment and include the ability to predict species specific occurrence or abundance for most of the fish species in the study area. The results and types of questions that can be addressed provide better global understanding of the ecological context within which specific natural resources fit (e.g., neighboring environments and resources, and large and small scale processes). The geographic analysis platform consists of broad and flexible geospatial tools (and associated data) with many potential applications. The objectives of this article are to provide a brief overview of GLGap methods and analysis tools, and demonstrate conservation and planning applications of those data and tools. Although there are many potential applications, we will highlight just three: (1) support for the Eastern Brook Trout Joint Venture (EBTJV), (2) Aquatic Life classification in Wisconsin, and (3) an educational tool that makes use of Google Earth (use of trade or product names does not imply endorsement by the U.S. Government) and Internet accessibility.

Gap Analysis Bulletin↗
USGS1999

Linking stressors and ecological responses

To characterize risk, it is necessary to quantify the linkages and interactions between chemical, physical and biological stressors and endpoints in the conceptual framework for ecological risk assessment (ERA). This can present challenges in a multiple stressor analysis, and it will not always be possible to develop a quantitative stressor-response profile. This review commences with a conceptual representation of the problem of developing a linkage analysis for multiple stressors and responses. The remainder of the review surveys a variety of mathematical and statistical methods (e.g., ranking methods, matrix models, multivariate dose-response for mixtures, indices, visualization, simulation modeling and decision-oriented methods) for accomplishing the linkage analysis for multiple stressors. Describing the relationships between multiple stressors and ecological effects are critical components of 'effects assessment' in the ecological risk assessment framework.

Book chapter↗
USGS2011

An adaptive approach to invasive plant management on U.S. Fish and Wildlife Service-owned native prairies in the Prairie Pothole Region: decision support under uncertainity

Much of the native prairie managed by the U.S. Fish and Wildlife Service (Service) in the Prairie Pothole Region (PPR) is extensively invaded by the introduced cool-season grasses smooth brome (Bromus inermis) and Kentucky bluegrass (Poa pratensis). The central challenge to managers is selecting appropriate management actions in the face of biological and environmental uncertainties. We describe the technical components of a USGS management project, and explain 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. In partnership with the Service, the U.S. Geological Survey is developing an adaptive decision support framework to assist managers in selecting management actions under uncertainty and maximizing learning from management outcomes. The framework is built around practical constraints faced by 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 Service field stations, spanning four states of the PPR, are participating in the project. They share a common management objective, available management strategies, and biological uncertainties. While the scope is broad, the project interfaces with individual land managers who provide refuge-specific information and receive updated decision guidance that incorporates understanding gained from the collective experience of all cooperators.

Prairie Pothole Region↗
USGS2014

Hydrologic Drought Decision Support System (HyDroDSS)

The hydrologic drought decision support system (HyDroDSS) was developed by the U.S. Geological Survey (USGS) in cooperation with the Rhode Island Water Resources Board (RIWRB) for use in the analysis of hydrologic variables that may indicate the risk for streamflows to be below user-defined flow targets at a designated site of interest, which is defined herein as data-collection site on a stream that may be adversely affected by pumping. Hydrologic drought is defined for this study as a period of lower than normal streamflows caused by precipitation deficits and (or) water withdrawals. The HyDroDSS is designed to provide water managers with risk-based information for balancing water-supply needs and aquatic-habitat protection goals to mitigate potential effects of hydrologic drought. This report describes the theory and methods for retrospective streamflow-depletion analysis, rank correlation analysis, and drought-projection analysis. All three methods are designed to inform decisions made by drought steering committees and decisionmakers on the basis of quantitative risk assessment. All three methods use estimates of unaltered streamflow, which is the measured or modeled flow without major withdrawals or discharges, to approximate a natural low-flow regime. Retrospective streamflow-depletion analysis can be used by water-resource managers to evaluate relations between withdrawal plans and the potential effects of withdrawal plans on streams at one or more sites of interest in an area. Retrospective streamflow-depletion analysis indicates the historical risk of being below user-defined flow targets if different pumping plans were implemented for the period of record. Retrospective streamflow-depletion analysis also indicates the risk for creating hydrologic drought conditions caused by use of a pumping plan. Retrospective streamflow-depletion analysis is done by calculating the net streamflow depletions from withdrawals and discharges and applying these depletions to a simulated record of unaltered streamflow. Rank correlation analysis in the HyDroDSS indicates the persistence of hydrologic measurements from month to month for the prediction of developing hydrologic drought conditions and quantitatively indicates which hydrologic variables may be used to indicate the onset of hydrologic drought conditions. Rank correlation analysis also indicates the potential use of each variable for estimating the monthly minimum unaltered flow at a site of interest for use in the drought-projection analysis. Rank correlation analysis in the HyDroDSS is done by calculating Spearman’s rho for paired samples and the 95-percent confidence limits of this rho value. Rank correlation analysis can be done by using precipitation, groundwater levels, measured streamflows, and estimated unaltered streamflows. Serial correlation analysis, which indicates relations between current and future values, can be done for a single site. Cross correlation analysis, which indicates relations among current values at one site and current and future values at a second site, also can be done. Drought-projection analysis in the HyDroDSS indicates the risk for being in a hydrologic drought condition during the current month and the five following months with and without pumping. Drought-projection analysis also indicates the potential effectiveness of water-conservation methods for mitigating the effect of withdrawals in the coming months on the basis of the amount of depletion caused by different pumping plans and on the risk of unaltered flows being below streamflow targets. Drought-projection analysis in the HyDroDSS is done with Monte Carlo methods by using the position analysis method. In this method the initial value of estimated unaltered streamflows is calculated by correlation to a measured hydrologic variable (monthly precipitation, groundwater levels, or streamflows from an index station identified with the rank correlation analysis). Then a pseudorandom number generator is used to create 251 six-month-long flow traces by using a bootstrap method. Serial correlation of the estimated unaltered monthly minimum streamflows determined from the rank correlation analysis is preserved within each flow trace. The sample of unaltered streamflows indicates the risk of being below flow targets in the coming months under simulated natural conditions (without historic withdrawals). The streamflow-depletion algorithms are then used to estimate risks of flow being below targets if selected pumping plans are used. This report also describes the implementation of the HyDroDSS. The HyDroDSS was developed as a Microsoft Access® database application to facilitate storage, handling, and use of hydrologic datasets with a simple graphical user interface. The program is implemented in the database by using the Visual Basic for Applications® (VBA) programming language. Program source code for the analytical techniques is provided in the HyDroDSS and in electronic text files accompanying this report. Program source code for the graphical user interface and for data-handling code, which is specific to Microsoft Access® and the HyDroDSS, is provided in the database. An installation package with a run-time version of the software is available with this report for potential users who do not have a compatible copy of Microsoft Access®. Administrative rights are needed to install this version of the HyDroDSS. A case study, to demonstrate the use of HyDroDSS and interpretation of results for a site of interest, is detailed for the USGS streamgage on the Hunt River (station 01117000) near East Greenwich in central Rhode Island. The Hunt River streamgage was used because it has a long record of streamflow and is in a well-studied basin with a substantial amount of hydrologic and water-use data including groundwater pumping for municipal water supply.

Rhode Island↗