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USGS2013

Internet-based Modeling, Mapping, and Analysis for the Greater Everglades (IMMAGE; Version 1.0): web-based tools to assess the impact of sea level rise in south Florida

South Florida's Greater Everglades area is particularly vulnerable to sea level rise, due to its rich endowment of animal and plant species and its heavily populated urban areas along the coast. Rising sea levels are expected to have substantial impacts on inland flooding, the depth and extent of surge from coastal storms, the degradation of water supplies by saltwater intrusion, and the integrity of plant and animal habitats. Planners and managers responsible for mitigating these impacts require advanced tools to help them more effectively identify areas at risk. The U.S. Geological Survey's (USGS) Internet-based Modeling, Mapping, and Analysis for the Greater Everglades (IMMAGE) Web site has been developed to address these needs by providing more convenient access to projections from models that forecast the effects of sea level rise on surface water and groundwater, the extent of surge and resulting economic losses from coastal storms, and the distribution of habitats. IMMAGE not only provides an advanced geographic information system (GIS) interface to support decision making, but also includes topic-based modules that explain and illustrate key concepts for nontechnical users. The purpose of this report is to familiarize both technical and nontechnical users with the IMMAGE Web site and its various applications.

Florida↗

USGS2007

Tracking acid mine-drainage in Southeast Arizona using GIS and sediment delivery models

This study investigates the application of models traditionally used to estimate erosion and sediment deposition to assess the potential risk of water quality impairment resulting from metal-bearing materials related to mining and mineralization. An integrated watershed analysis using Geographic Information Systems (GIS) based tools was undertaken to examine erosion and sediment transport characteristics within the watersheds. Estimates of stream deposits of sediment from mine tailings were related to the chemistry of surface water to assess the effectiveness of the methodology to assess the risk of acid mine-drainage being dispersed downstream of abandoned tailings and waste rock piles. A watershed analysis was preformed in the Patagonia Mountains in southeastern Arizona which has seen substantial mining and where recent water quality samples have reported acidic surface waters. This research demonstrates an improvement of the ability to predict streams that are likely to have severely degraded water quality as a result of past mining activities. ?? Springer Science+Business Media B.V. 2007.

Environmental Monitoring and Assessment↗

USGS2018

A case study and a meta-analysis of seasonal variation in fish mercury concentrations

Mercury contamination in aquatic ecosystems is a concern due to health risks of consuming fish. Fish mercury concentrations are highly variable and influenced by a range of environmental factors. However, seasonal variation in mercury levels are typically overlooked when monitoring fish mercury concentrations, establishing consumption advisories, or creating accumulation models. Temporal variation in sampling could bias mercury concentration estimates of accumulation potential. Thus, the objectives of this study were to first evaluate seasonal variation of largemouth bass ( Micropterus salmoides ) axial muscle mercury concentration from two Iowa, USA impoundments. Second, we conducted a meta-analysis to evaluate if seasonal variation in mercury concentration is dependent upon mean mercury concentration, waterbody type, or fish trophic level or mean length. Largemouth bass were collected four times between May and October (24–36 fish per month) from Twelve Mile (2013) and Red Haw (2014) lakes. Largemouth bass axial muscle mercury concentrations were variable within and between lakes, ranging from undetectable ( < 0.05 mg/kg) to 0.54 mg/kg. Largemouth bass mercury concentrations were similar across months in Twelve Mile but varied temporally in Red Haw and were highest in July, intermediate in May and September, and lowest during October. Results of the meta-analysis suggest that seasonal variation in mercury concentrations is more likely to occur as mean mercury concentration of the population increases but is unrelated to waterbody type, trophic status, and fish size. Understanding seasonal variation in fish mercury concentrations will aid in the development of standardized sampling programs for long-term monitoring programs and fish consumption advisories.

Iowa↗

USGS2019

Synthesis of maternal transfer of mercury in birds: Implications for altered toxicity risk

Maternal transfer is the predominant route of methylmercury (MeHg) exposure to offspring. We reviewed and synthesized published and unpublished data on maternal transfer of MeHg in birds. Using paired samples of females’ blood (n=564) and their eggs (n=1814) from 26 bird species in 6 taxonomic orders, we conducted a meta-analysis to evaluate whether maternal transfer of MeHg to eggs differed among species and caused differential toxicity risk to embryos. Total mercury (THg) concentrations in eggs increased with maternal blood THg concentrations; however, the proportion of THg transferred from females to their eggs differed among bird taxa and with maternal THg exposure. Specifically, a smaller proportion of maternal THg was transferred to eggs with increasing female THg concentrations. Additionally, the proportion of THg that was transferred to eggs at the same maternal blood THg concentration differed among taxonomic orders, with waterfowl (Anseriformes) transferring up to 382% more THg into their eggs than songbirds (Passeriformes). We provide equations to predict THg concentrations in eggs using female blood THg concentrations, and vice versa, which may help translate toxicity benchmarks across tissues and life stages. Our results indicate that toxicity risk of MeHg can vary among bird taxa due to differences in the maternal transfer of MeHg to offspring.

Environmental Science & Technology↗

USGS1991

An analysis of a seismic reflection from the base of a gas hydrate zone, offshore Peru

Seismic reflection data recorded near ODP Site 688, offshore Peru, exhibit a persistent bottom-simulating reflector (BSR) from a depth corresponding to the theoretical base of the gas hydrate stability field. Although gas hydrate has been recovered in cores from scientific drilling in both the Pacific and the Atlantic, drilling in areas exhibiting a BSR has usually been avoided because of the perceived risk of releasing free gas trapped beneath the hydrated sediments. To carry out a quantitative analysis of the BSR, the seismic data were reprocessed using signature deconvolution and true amplitude recovery techniques. Synthetic seismograms that were created using acoustic parameters extracted from the seismic data and physical properties from Site 688 borehole measurement were compared to the observed seismic data to estimate the thickness of the free-gas zone. Results indicate the BSR is discontinuous laterally. Where the BSR is of high amplitude, free gas in a zone 5.5-17 m thick beneath the hydrated sediments provides the observed waveform; where the BSR amplitude is low, the free-gas zone is much thinner than 5.5 m or is entirely absent.

American Association of Petroleum Geologists Bulle↗

USGS2016

Introduction to “Global tsunami science: Past and future, Volume I”

Twenty-five papers on the study of tsunamis are included in Volume I of the PAGEOPH topical issue “Global Tsunami Science: Past and Future”. Six papers examine various aspects of tsunami probability and uncertainty analysis related to hazard assessment. Three papers relate to deterministic hazard and risk assessment. Five more papers present new methods for tsunami warning and detection. Six papers describe new methods for modeling tsunami hydrodynamics. Two papers investigate tsunamis generated by non-seismic sources: landslides and meteorological disturbances. The final three papers describe important case studies of recent and historical events. Collectively, this volume highlights contemporary trends in global tsunami research, both fundamental and applied toward hazard assessment and mitigation.

Pure and Applied Geophysics PAGEOPH↗

USGS2024

Predicted potential for aquatic exposure effects of per- and polyfluorinated alkyl substances (PFAS) in Pennsylvania’s statewide network of streams

Per- and polyfluoroalkyl substances (PFAS) are contaminants that can lead to adverse health effects in aquatic organisms, including reproductive toxicity and developmental abnormalities. To assess the ecological health risk of PFAS in Pennsylvania stream surface water, we conducted a comprehensive analysis that included both measured and predicted estimates. The potential combined exposure effects of 14 individual PFAS to aquatic biota were estimated using the sum of exposure-activity ratios ( Σ EARs) in 280 streams. Additionally, machine learning techniques were utilized to predict potential PFAS exposure effects in unmonitored stream reaches, considering factors such as land use, climate, and geology. Leveraging a tailored convolutional neural network (CNN), a validation accuracy of 78% was achieved, directly outperforming traditional methods that were also used, such as logistic regression and gradient boosting (accuracies of ~65%). Feature importance analysis highlighted key variables that contributed to the CNN’s predictive power. The most influential features highlighted the complex interplay of anthropogenic and environmental factors contributing to PFAS contamination in surface waters. Industrial and urban land cover, rainfall intensity, underlying geology, agricultural factors, and their interactions emerged as key determinants. These findings may help to inform biotic sampling strategies, water quality monitoring efforts, and policy decisions aimed to mitigate the ecological impacts of PFAS in surface waters.

Pennsylvania↗

USGS2015

Spatial and seasonal responses of precipitation in the Ganges and Brahmaputra river basins to ENSO and Indian Ocean dipole modes: Implications for flooding and drought

We evaluated the spatial and seasonal responses of precipitation in the Ganges and Brahmaputra basins as modulated by the El Niño Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD) modes using Global Precipitation Climatology Centre (GPCC) full data reanalysis of monthly global land-surface precipitation data from 1901 to 2010 with a spatial resolution of 0.5° × 0.5°. The GPCC monthly total precipitation climatology targeting the period 1951–2000 was used to compute gridded monthly anomalies for the entire time period. The gridded monthly anomalies were averaged for the years influenced by combinations of climate modes. Occurrences of El Niño alone significantly reduce (88% of the long-term average (LTA)) precipitation during the monsoon months in the western and southeastern Ganges Basin. In contrast, occurrences of La Niña and co-occurrences of La Niña and negative IOD events significantly enhance (110 and 109% of LTA in the Ganges and Brahmaputra Basin, respectively) precipitation across both basins. When El Niño co-occurs with positive IOD events, the impacts of El Niño on the basins' precipitation diminishes. When there is no active ENSO or IOD events (occurring in 41 out of 110 years), precipitation remains below average (95% of LTA) in the agriculturally intensive areas of Haryana, Uttar Pradesh, Rajasthan, Madhya Pradesh, and Western Nepal in the Ganges Basin, whereas precipitation remains average to above average (104% of LTA) across the Brahmaputra Basin. This pattern implies that a regular water deficit is likely, especially in the Ganges Basin, with implications for the agriculture sector due to its reliance on consistent rainfall for successful production. Historically, major droughts occurred during El Niño and co-occurrences of El Niño and positive IOD events, while major flooding occurred during La Niña and co-occurrences of La Niña and negative IOD events in the basins. This observational analysis will facilitate well-informed decision making in minimizing natural hazard risks and climate impacts on agriculture, and supports development of strategies ensuring optimized use of water resources in best management practice under a changing climate.

Brahmaputra Basin, Ganges Basin↗

USGS2026

Seasonal trophic dynamics drive growth potential and predation risk for reintroduced Chinook salmon in Shasta Reservoir

Reservoir ecosystems can significantly affect anadromous salmon populations reintroduced upstream of impassable high-head dams. In this study, we examine how a novel reservoir food web created by an impoundment can limit juvenile growth or survival through the seasonal production or access to food, promote competition for available resources, and affect risk of the food supply or predation mortality, all of which can be strongly influenced by the thermal regime. Shasta Reservoir, the largest impoundment in California’s Central Valley Project, presents opportunities and risks for winter-run Chinook salmon ( Oncorhynchus tshawytscha ), a federally endangered population targeted for reintroduction into the McCloud River, which flows into the reservoir. We integrated field sampling, stable isotope analysis, hydroacoustic surveys, and bioenergetics modeling to characterize Shasta Reservoir’s food web and evaluate seasonal growth potential and predation risk for juvenile salmon. Zooplankton, dominated by Daphnia , provided favorable foraging conditions in spring but declined sharply by late summer, coinciding with high consumption demand from abundant threadfin shad ( Dorosoma petenense ). Bioenergetics simulations indicated that fry that would ordinarily enter the reservoir in autumn would face poor growth opportunities. They would also be exposed to elevated predation risk driven by warm temperatures and high metabolic demand, particularly from piscivorous salmonids and Sacramento pikeminnow ( Ptychocheilus grandis ). Limited information on predator abundances precludes the ability to quantify total predation demand. Alternatively, juveniles entering the reservoir the following spring would encounter greater prey availability and reduced predation pressure. These findings highlight the strong influence of seasonal thermal structure and food web dynamics on reservoir constraints and underscore the need to incorporate the dynamics of key habitats into reintroduction management and decisions. Our framework provides a quantitative, mechanistically-based approach for evaluating the role of reservoirs in salmon reintroductions above high-head dams.

California↗

USGS2024

A meta-analysis of mercury biomagnification in freshwater predatory invertebrates: Community diversity and dietary exposure drive variability

Accurate estimates of methylmercury (MeHg) exposure are valuable to actionably assess risk and protect wildlife and human health. MeHg trophic transfer is a critical driver of risk: MeHg is generally biomagnified by a factor of 8.3 ± 7.5 from one trophic level to the next, averaged across freshwater communities (mean ± standard deviation). This variability can produce disparate risks even where basal MeHg concentrations are similar. Taxonomy may be one driver of this variability: physiologically diverse groups, like vertebrates and invertebrates, may assimilate MeHg differently. To determine whether taxonomy affects trophic transfer efficiency, we conducted a meta-analysis characterizing predatory invertebrate MeHg biomagnification. Our analyses estimated that freshwater predatory invertebrates biomagnify MeHg by factors of 2.1 ± 0.2 to 4.3 ± 0.3, with a 98.9 ± 0.4% posterior probability that factors are below 5 (mean ± standard error). When vertebrates or primary producers were included, a site’s trophic magnification factor was 18.6 ± 6.2 to 54.1 ± 7.7% higher than estimates for invertebrates alone. Biomagnification was inversely correlated to prey MeHg concentration and varied among systematic and functional groups. These data suggest that predatory invertebrates biomagnify MeHg less efficiently than vertebrates and that a community’s diversity and structure determine its biomagnification efficiency. Incorporating organismal variation in trophic transfer estimates may improve the assessment, communication, and management of MeHg risk.

Environmental Science & Technology↗

USGS2021

Capacity assessment for Earth Monitoring, Analysis, and Prediction (EarthMAP) and future integrated monitoring and predictive science at the U.S. Geological Survey

Executive Summary Managers of our Nation’s resources face unprecedented challenges driven by the convergence of increasing, competing societal demands and a changing climate that affects the stability, vulnerability, and predictability of those resources. To help meet these challenges, the scientific community must take advantage of all available technologies, data, and integrative Earth systems modeling capacity to better inform resource and risk management decisions. This is the overarching goal of the U.S. Geological Survey (USGS) Earth Monitoring, Analysis, and Prediction (EarthMAP) vision: “By 2030, the USGS will deliver well integrated observations and predictions of the future state of natural systems—water, ecosystems, energy, minerals, hazards—at regional and national scales, working primarily with federal, state, and academic partners to develop and operate the capability” (U.S. Geological Survey, 2021). Providing more integrated Earth systems science and actionable information to decision makers, stakeholders, and the public requires a better understanding of the depth and distribution of existing capacity (capabilities, tools, and techniques) across the Bureau. Identifying existing capacity is also a critical first step toward gap analysis and targeted investments to increase capacity over time. The USGS formed a Capacity Assessment Team (CAT) and charged it with (1) conducting a Request for Information (RFI) to identify existing USGS expertise and activities supportive of integrated and predictive science to inform decision making, (2) developing a strategy and proof-of-concept for a continuously updated capacity assessment capability, and (3) identifying lessons learned to inform development of best practices for future capacity assessment efforts. The RFI took the form of a survey, with content guided by the science and technology needs identified in a USGS report titled “Grand Challenges for Integrated U.S. Geological Survey Science—A Workshop Report” (Jenni and others, 2017). The 44-question survey provided respondents the ability to rate their level of experience with a suite of priority disciplines, analysis and modeling approaches, technologies, and stakeholder engagement strategies and to enter optional narrative text for supporting context. An introductory portion focused on general science capacity assessment, followed by three sections targeting capabilities related to the foundational components of EarthMAP: (1) data and information integration, (2) integrated predictive science, and (3) actionable information. The survey results provided a high-level snapshot of USGS capacity in the targeted areas. Respondents (1,035 individuals) represented approximately 13 percent of the USGS across all mission areas and regions. Seventy-four percent of the respondents held a science-focused position title and the remainder had position titles in information technology, computer science, management, administrative, or other (contractors, volunteers, emeritus, and unknown). To provide greater insight into respondent capabilities and activities, information from the U.S. Department of the Interior and USGS enterprise information systems were used to further characterize topical expertise and organizational associations of survey respondents. To address the ongoing need to assess the Bureau’s capacity to address integrated predictive science priorities, the CAT developed a software-based proof-of-concept called the Integrated Science Assessment Information Database (iSAID) for assembling various information sources together toward making the full extent of USGS capabilities and scientific assets available for routine capacity assessment. This proof-of-concept is intended to serve as a catalyst for further development. The process of implementing the EarthMAP capacity assessment survey, analyzing survey responses, and developing the proof-of-concept resulted in lessons learned, findings, and recommendations. Example scenarios throughout the report demonstrate how capacity assessment data can inform science planning. Three overarching findings and recommendations are: (1) Finding: Capacity is limited in some critical disciplines, skills, and technology applications, but “sufficient” depends on the question and the need relative to availability at a given point in time. Recommendation: Develop an on-demand capacity assessment framework that enables rapid identification and evaluation of existing and available expertise to support decision needs as they arise. (2) Finding: Institutional barriers and lack of awareness constrain the ability of USGS staff to adopt new technologies, collaborate across administrative boundaries, and deliver actionable information to stakeholders in a timely manner. However, these barriers are not universally experienced. Recommendation: Pursue more targeted inquiries to clarify which institutional barriers are obstructing the adoption of new technologies and approaches or the sharing of expertise and equipment across organizational and regional boundaries. These inquiries should inform USGS leadership, mission areas, and regions whether policies can be revised or whether a lack of understanding is creating perceived obstacles. Highlight cases when staff have successfully adopted new technologies and approaches to advance EarthMAP priorities and provide actionable information in a timely manner to spread awareness of how perceived obstacles can be navigated and overcome when appropriate. (3) Finding: Examples of people and projects integrating across disciplines and scales and applying advanced approaches to meet complex stakeholder needs exist. Such examples provide transfer value across the spectrum from approach to decision making. Many projects, already underway, appear to meet elements of the EarthMAP vision, and the USGS has people who can provide leadership in multiple types of specific integrated science efforts. Recommendation: Use these findings as a starting point for near-term strategic planning for integrated science. Highlight, incentivize, and build on existing interdisciplinary predictive science and information delivery activities across the USGS to advance toward further realization of an EarthMAP capacity. The CAT efforts to develop and assess existing USGS capacity to advance the EarthMAP vision revealed a fundamental challenge for not only this effort but any effort to assess existing capacity: A considerable amount of thought, time, and effort is required to survey and assess capabilities and tools available to support a given need, yet best results are still likely to provide an incomplete assessment. To better meet the frequent need to assess capabilities, tools, products, and projects that address an expressed strategic priority, the CAT proposes the concept of an on-demand capacity assessment framework supported by a software package that dynamically pulls and integrates information from existing USGS information systems and public domain registries. Although existing USGS enterprise information systems currently lack the structure, cross-system consistency, interoperability, and stability to support a continuously updated capacity assessment capability, we identify reasonable near-term steps to improve the utility of information gathered on expertise and project capacity and to improve the consistency and completeness of information and the ability of USGS systems to share that information. The ability to search and characterize this information will make future assessments of capacity faster, more complete, more efficient, and more targeted. This approach would grow the Bureau’s capacity knowledge over time, iteratively improving the ability to access, leverage, and synthesize existing capabilities and assets as well as identify and fill critical gaps. The greatest promise for developing integrated science could lie in linking across existing projects and expertise to create a multi-project capacity for addressing large, complex environmental issues.

Open-File Report↗

USGS2010

Seismic hazard assessment: Issues and alternatives

Seismic hazard and risk are two very important concepts in engineering design and other policy considerations. Although seismic hazard and risk have often been used inter-changeably, they are fundamentally different. Furthermore, seismic risk is more important in engineering design and other policy considerations. Seismic hazard assessment is an effort by earth scientists to quantify seismic hazard and its associated uncertainty in time and space and to provide seismic hazard estimates for seismic risk assessment and other applications. Although seismic hazard assessment is more a scientific issue, it deserves special attention because of its significant implication to society. Two approaches, probabilistic seismic hazard analysis (PSHA) and deterministic seismic hazard analysis (DSHA), are commonly used for seismic hazard assessment. Although PSHA has been pro-claimed as the best approach for seismic hazard assessment, it is scientifically flawed (i.e., the physics and mathematics that PSHA is based on are not valid). Use of PSHA could lead to either unsafe or overly conservative engineering design or public policy, each of which has dire consequences to society. On the other hand, DSHA is a viable approach for seismic hazard assessment even though it has been labeled as unreliable. The biggest drawback of DSHA is that the temporal characteristics (i.e., earthquake frequency of occurrence and the associated uncertainty) are often neglected. An alternative, seismic hazard analysis (SHA), utilizes earthquake science and statistics directly and provides a seismic hazard estimate that can be readily used for seismic risk assessment and other applications. ?? 2010 Springer Basel AG.

Pure and Applied Geophysics↗

USGS2020

A decision framework to analyze tide-gate options for restoration of the Herring River Estuary, Massachusetts

The collective set of decisions involved with the restoration of degraded wetlands is often more complex than considering only ecological responses and outcomes. Restoration is commonly driven by a complex interaction of social, economic, and ecological factors representing the mandate of resource stewards and the values of stakeholders. The authors worked with the Herring River Restoration Committee (HRRC) to develop a decision framework to understand the implications of complex tradeoffs and to guide decision making for the restoration of the 1,100-acre Herring River estuary within Cape Cod National Seashore, which has been restricted from tidal influence for more than 100 years. The HRRC represents decision maker and stakeholder interests in the restoration process. For a 25-year planning horizon, decisions involve the rate at which newly constructed water-control structures allow tidal exchange, and the timing and location of implementing numerous secondary management options. Decisions affect multiple stakeholders, including residents of two adjacent towns who value the watershed for numerous benefits and whose economy relies on seasonal activities and aquaculture. System response to management decisions is characterized by a high degree of uncertainty and risk with positive and negative outcomes possible. Decision policies will affect biophysical (for example, sediment transport, discharge of fecal coliform bacteria) and ecological (for example, vegetation response, fish passage, effects on shellfish) processes, as well as socioeconomic interests (for example, effects on property, viewscapes, recreation). The framework provides a structured approach for evaluating tradeoffs among multiple objectives (ecological and social) while appropriately characterizing relevant uncertainties and accounting for levels of risk tolerances and the values of decision makers and stakeholders. Consequences of tide-gate management options are predicted using a range of methods from quantitative physical process models to elicited expert judgement. The decision framework is presented, and the software developed to implement the tradeoff analysis is introduced. The results from an initial prototype analysis using a software application developed for analyses of tradeoffs and of sensitivity of the decision to risk and uncertainty are presented. The next step is to use the decision-support application to analyze options using improved predictions.

Massachusetts↗

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↗

USGS2007

A Quantitative Threats Analysis for the Florida Manatee ( Trichechus manatus latirostris )

The Florida manatee (Trichechus manatus latirostris) is an endangered marine mammal endemic to the southeastern United States. The primary threats to manatee populations are collisions with watercraft and the potential loss of warm-water refuges. For the purposes of listing, recovery, and regulation under the Endangered Species Act (ESA), an understanding of the relative effects of the principal threats is needed. This work is a quantitative approach to threats analysis, grounded in the assumption that an appropriate measure of status under the ESA is based on the risk of extinction, as quantified by the probability of quasi-extinction. This is related to the qualitative threats analyses that are more common under the ESA, but provides an additional level of rigor, objectivity, and integration. In this approach, our philosophy is that analysis of the five threat factors described in Section 4(a)(1) of the ESA can be undertaken within an integrated quantitative framework. The basis of this threats analysis is a comparative population viability analysis. This involves forecasting the Florida manatee population under different scenarios regarding the presence of threats, while accounting for process variation (environmental, demographic, and catastrophic stochasticity) as well as parametric and structural uncertainty. We used the manatee core biological model (CBM) for this viability analysis, and considered the role of five threats: watercraft-related mortality, loss of warm-water habitat in winter, mortality in water-control structures, entanglement, and red tide. All scenarios were run with an underlying parallel structure that allowed a more powerful estimation of the effects of the various threats. The results reflect our understanding of manatee ecology (as captured in the structure of the CBM), our estimates of manatee demography (as described by the parameters in the model), and our characterization of the mechanisms by which the threats act on manatees. As an example of the type of results generated, we estimated that the probability of the manatee population falling to less than 250 adults on either the Atlantic or Gulf coasts (from a current statewide population size of near 3300) within 100 years is 8.6%. Complete removal of the watercraft threat alone would reduce this risk to 0.4%; complete removal of the warm-water threat to 4.2%; removal of both threats would reduce the risk to 0.1%. The modeling approach we have taken also allows us to consider partial removal of threats, as well as removal of multiple threats simultaneously. We believe the measure we have proposed (probability of quasi-extinction over y years, with quasi-extinction defined as dropping below a threshold of z on either coast) is a suitable measure of status that integrates a number of the elements that are relevant to interpretation under the ESA (it directly integrates risk of extinction and reduction of range, and indirectly integrates loss of genetic diversity). But the identification of the time frame of interest and the tolerable risk of quasi-extinction are policy decisions, and an ecology-based quasi-extinction threshold has not yet been determined. We have endeavored to provide results over a wide range of these parameters to give decision-makers useful information to assess status. This assessment of threats suggests that watercraft-related mortality is having the greatest impact on manatee population growth and resilience. Elimination of this single threat would greatly reduce the probability of quasi-extinction. Loss of warm-water is also a significant threat, particularly over the long-term. Red tide and entanglement, while noticeable threats, have had less of an impact on the manatee population. The effect of water control structures may have already been largely mitigated. We did not, however, consider an exhaustive list of threats. Other threats (e.g., reduction of food resources due to storms and development) may play a

Open-File Report↗

USGS2010

Local sensitivity analysis for inverse problems solved by singular value decomposition

Local sensitivity analysis provides computationally frugal ways to evaluate models commonly used for resource management, risk assessment, and so on. This includes diagnosing inverse model convergence problems caused by parameter insensitivity and(or) parameter interdependence (correlation), understanding what aspects of the model and data contribute to measures of uncertainty, and identifying new data likely to reduce model uncertainty. Here, we consider sensitivity statistics relevant to models in which the process model parameters are transformed using singular value decomposition (SVD) to create SVD parameters for model calibration. The statistics considered include the PEST identifiability statistic, and combined use of the process-model parameter statistics composite scaled sensitivities and parameter correlation coefficients (CSS and PCC). The statistics are complimentary in that the identifiability statistic integrates the effects of parameter sensitivity and interdependence, while CSS and PCC provide individual measures of sensitivity and interdependence. PCC quantifies correlations between pairs or larger sets of parameters; when a set of parameters is intercorrelated, the absolute value of PCC is close to 1.00 for all pairs in the set. The number of singular vectors to include in the calculation of the identifiability statistic is somewhat subjective and influences the statistic. To demonstrate the statistics, we use the USDA’s Root Zone Water Quality Model to simulate nitrogen fate and transport in the unsaturated zone of the Merced River Basin, CA. There are 16 log-transformed process-model parameters, including water content at field capacity (WFC) and bulk density (BD) for each of five soil layers. Calibration data consisted of 1,670 observations comprising soil moisture, soil water tension, aqueous nitrate and bromide concentrations, soil nitrate concentration, and organic matter content. All 16 of the SVD parameters could be estimated by regression based on the range of singular values. Identifiability statistic results varied based on the number of SVD parameters included. Identifiability statistics calculated for four SVD parameters indicate the same three most important process-model parameters as CSS/PCC (WFC1, WFC2, and BD2), but the order differed. Additionally, the identifiability statistic showed that BD1 was almost as dominant as WFC1. The CSS/PCC analysis showed that this results from its high correlation with WCF1 (-0.94), and not its individual sensitivity. Such distinctions, combined with analysis of how high correlations and(or) sensitivities result from the constructed model, can produce important insights into, for example, the use of sensitivity analysis to design monitoring networks. In conclusion, the statistics considered identified similar important parameters. They differ because (1) with CSS/PCC can be more awkward because sensitivity and interdependence are considered separately and (2) identifiability requires consideration of how many SVD parameters to include. A continuing challenge is to understand how these computationally efficient methods compare with computationally demanding global methods like Markov-Chain Monte Carlo given common nonlinear processes and the often even more nonlinear models.

Book↗

USGS2012

The U.S. Geological Survey Ecosystem Science Strategy, 2012-2022 - Advancing discovery and application through collaboration

Ecosystem science is critical to making informed decisions about natural resources that can sustain our Nation’s economic and environmental well-being. Resource managers and policy-makers are faced with countless decisions each year at local, state, tribal, territorial, and national levels on issues as diverse as renewable and non-renewable energy development, agriculture, forestry, water supply, and resource allocations at the urban-rural interface. The urgency for sound decision-making is increasing dramatically as the world is being transformed at an unprecedented pace and in uncertain directions. Environmental changes are associated with natural hazards, greenhouse gas emissions, and increasing demands for water, land, food, energy, mineral, and living resources. At risk is the Nation’s environmental capital, the goods and services provided by resilient ecosystems that are vital to the health and well-being of human societies. Ecosystem science—the study of systems of organisms interacting with their environment and the consequences of natural and human-induced change on these systems—is necessary to inform decision-makers as they develop policies to adapt to these changes. This Ecosystems Science Strategy is built on a framework that includes basic and applied science. It highlights the critical roles that USGS scientists and partners can play in building scientific understanding and providing timely information to decision-makers. The strategy underscores the connection between scientific discoveries and the application of new knowledge. The strategy integrates ecosystem science and decision-making, producing new scientific outcomes to assist resource managers and providing public benefits. The USGS is uniquely positioned to play an important role in ecosystem science. With its wide range of expertise, the agency can bring holistic, cross-scale, interdisciplinary capabilities to the design and conduct of monitoring, research, and modeling and to new technologies for data collection, management, and visualization. Collectively, these capabilities can be used to reveal ecological patterns and processes, explain how and why ecosystems change, and forecast change over different spatial and temporal scales. USGS science can provide managers with options and decision-support tools to use resources sustainably. The USGS has long-standing, collaborative relationships with the DOI and other partners in the natural sciences, in both conducting science and its application. The USGS engages these partners in cooperative investigations that otherwise would lack the necessary support or be too expensive for a single bureau to conduct. The heart of this strategy is a framework and vision for USGS ecosystems science that focuses on five long-term goals, which are seen as interconnected and reinforcing components: • Improve understanding of ecosystem structure, function, and processes. The focus for this goal is an understanding of how ecosystems work, including the dynamics of species, their populations, interactions, and genetics, and how they change across spatial and temporal scales. • Advance understanding of how drivers influence ecosystem change. The challenges here are explaining the drivers of ecosystem change, their spatio-temporal patterns, their uncertainties and interactions, and their influence on ecosystem processes and dynamics. • Improve understanding of the services that ecosystems provide to society. Here the emphasis is on the measurement of environmental capital and ecosystem services, and the identification of sources and patterns of change in space and time. • Develop tools, technologies, and capacities to inform decision-making about ecosystems. This includes developing new technologies and approaches for conducting applications-oriented ecosystem science. A principal challenge will be how to quantify uncertainty and incorporate it in decision analysis. • Apply science to enhance strategies for management, conservation, and restoration of ecosystems. These challenges include development of novel approaches to monitoring, assessment, and restoration of ecosystems; new methods to address species of concern and communities at risk; and innovations in decision analysis and support to address imminent ecosystem changes or those that are underway. Closely integrated with the five goals are four strategic approaches that provide the path forward for the USGS Ecosystems Mission Area. These approaches cross-cut all of the goals and are seen as essential to the implementation of this strategy: • Assess information needs for ecosystem science through enhanced partnerships. Work with the DOI and other agencies and institutions to identify, design, and implement priority decision-driven ecological research. • Promote the use of interdisciplinary ecosystem science. Design and conduct interdisciplinary process-oriented research in ecosystem science. • Enhance modeling and forecasting. Build models to forecast ecosystem change, assess future management scenarios, and reduce uncertainties through an adaptive learning process. • Support decision-making. Use quantitative approaches to assess the vulnerabilities of ecosystems, habitats, and species, and evaluate strategies for adaptation, restoration, and sustainable management. Following the strategic approaches are a set of proposed actions that represent a sampling of specific activities that align with this strategy and that address the Nation’s most pressing environmental needs. The strategy emphasizes coordination of activities across the USGS mission areas pursuant to these goals. Ecosystem science is inherently interdisciplinary and requires a broad perspective that incorporates the biological and physical sciences, climate science, information technology, and scientific capacity in mission areas across the Bureau. With its emphasis on coordination, this strategy can provide a critical underpinning for integrated science efforts with scientists from multiple mission areas of the USGS working together. Of course, the USGS will continue to conduct both discipline-specific and interdisciplinary investigations, and both will continue to be vital parts of the ecosystem science portfolio. Finally, the strategy stresses the importance of coordination with other Federal agencies and organizations in the natural resources community. The USGS collaborates with resource agencies in the DOI and other organizations throughout the world to meet societal needs for species and ecosystem management. Working with these agencies and organizations, the USGS will play a key role over the next decade in advancing the scientific foundation for sustaining the natural resources that diverse, productive, resilient ecosystems provide.

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USGS2013

U.S. Geological Survey ecosystems science strategy—Advancing discovery and application through collaboration

Executive Summary Ecosystem science is critical to making informed decisions about natural resources that can sustain our Nation’s economic and environmental well-being. Resource managers and policymakers are faced with countless decisions each year at local, regional, and national levels on issues as diverse as renewable and nonrenewable energy development, agriculture, forestry, water supply, and resource allocations at the urban-rural interface. The urgency for sound decisionmaking is increasing dramatically as the world is being transformed at an unprecedented pace and in uncertain directions. Environmental changes are associated with natural hazards, greenhouse gas emissions, and increasing demands for water, land, food, energy, mineral, and living resources. At risk is the Nation’s environmental capital, the goods and services provided by resilient ecosystems that are vital to the health and wellbeing of human societies. Ecosystem science—the study of systems of organisms interacting with their environment and the consequences of natural and human-induced change on these systems—is necessary to inform decisionmakers as they develop policies to adapt to these changes. This Ecosystems Science Strategy is built on a framework that includes basic and applied science. It highlights the critical roles that U.S. Geological Survey (USGS) scientists and partners can play in building scientific understanding and providing timely information to decisionmakers. The strategy underscores the connection between scientific discoveries and the application of new knowledge, and it integrates ecosystem science and decisionmaking, producing new scientific outcomes to assist resource managers and providing public benefits. We envision the USGS as a leader in integrating scientific information into decisionmaking processes that affect the Nation’s natural resources and human well-being. The USGS is uniquely positioned to play a pivotal role in ecosystem science. With its wide range of expertise, the Bureau can bring holistic, cross-scale, interdisciplinary capabilities to the design and conduct of monitoring, research, and modeling and to new technologies for data collection, management, and visualization. Collectively, these capabilities can be used to reveal ecological patterns and processes, explain how and why ecosystems change, and forecast change over different spatial and temporal scales. USGS science can provide managers with options and decision-support tools to use resources sustainably. The USGS has long-standing, collaborative relationships with the Department of the Interior (DOI) and other partners in the natural sciences, in both conducting science and applying the results. The USGS engages these partners in cooperative investigations that otherwise would lack the necessary support or be too expensive for a single bureau to conduct. The heart of this strategy is a framework for USGS ecosystems science that focuses on five long-term goals, which are seen as interconnected components that reinforce our vision of the USGS providing science that is at the forefront of decisionmaking: Improve understanding of ecosystem structure, function, and processes. The focus for this goal is an understanding of how ecosystems work, including the dynamics of species, their populations, interactions, and genetics, and how they change across spatial and temporal scales. Advance understanding of how drivers influence ecosystem change. The challenges here are explaining the drivers of ecosystem change, their spatio-temporal patterns, their uncertainties and interactions, and their influence on ecosystem processes and dynamics. Improve understanding of the services that ecosystems provide to society. Here the emphasis is on the measurement of environmental capital and ecosystem services, and the identification of sources and patterns of change in space and time. Develop tools, technologies, and capacities to inform decisionmaking about ecosystems. This includes developing new technologies and approaches for conducting applications-oriented ecosystem science. A principal challenge will be how to quantify uncertainty and incorporate it in decision analysis. Apply science to enhance strategies for management, conservation, and restoration of ecosystems. These challenges include development of novel approaches to monitoring, assessment, and restoration of ecosystems; new methods to address species of concern and communities at risk; and innovations in decision analysis and support to address imminent ecosystem changes or those that are underway. Closely integrated with the five goals are four strategic approaches that provide the path forward for the USGS Ecosystems Mission Area. These approaches cross-cut all of the goals and are seen as essential to the implementation of this strategy: Assess information needs for ecosystem science through enhanced partnerships. Work with the DOI and other agencies and institutions to identify, design, and implement priority decision-driven ecological research. Promote the use of interdisciplinary ecosystem science. Design and conduct interdisciplinary process-oriented research in ecosystem science. Enhance modeling and forecasting. Build models to forecast ecosystem change, assess future management scenarios, and reduce uncertainties through an adaptive learning process. Support decisionmaking. Use quantitative approaches to assess the vulnerabilities of ecosystems, habitats, and species, and evaluate strategies for adaptation, restoration, and sustainable management. Following the four strategic approaches are a set of proposed actions that represent a sampling of specific USGS activities that align with this strategy and that address the Nation’s most pressing environmental needs. The strategy emphasizes coordination of activities across the USGS mission areas pursuant to these goals. Ecosystem science is inherently interdisciplinary and requires a broad perspective that incorporates the biological and physical sciences, climate science, information technology, and scientific capacity in mission areas across the Bureau. With its emphasis on coordination, this strategy can provide a critical underpinning for integrated science efforts with scientists from multiple mission areas of the USGS working together. Of course, the USGS will continue to conduct discipline-specific and interdisciplinary investigations, and both will continue to be vital parts of the ecosystem science portfolio. Finally, the strategy stresses the importance of coordination with other Federal agencies and organizations in the natural resources community. The USGS collaborates with resource agencies in the DOI and other organizations throughout the world to meet societal needs for species and ecosystem management. Working with these agencies and organizations, the USGS will play a key role in guiding sound decisionmaking during the next decade by advancing the scientific foundation for sustaining the natural resources that diverse, productive, resilient ecosystems provide.

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