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USGS2018

Columbia River Basin dreissenid mussel monitoring forum workshop

To address actions identified in the Department of Interior’s “Safeguarding the West” strategy, the Pacific States Marine Fisheries Commission (PSMFC) and US Geological Survey (USGS) convened 43 invasive species coordinators and scientific experts June 5-6, 2018 in Portland, Oregon to assess the status of dreissenid monitoring efforts in the Columbia River Basin (CRB); identify key strengths and weaknesses of existing collaborative efforts to monitor for dreissenids; identify priority monitoring gaps foundational to dreissenid prevention efforts; and achieve consensus on a set of strategies to address those gaps and maintain a strong monitoring collaborative and framework moving forward. Prior to the workshop, two webinars were conducted to summarize how states and provinces are estimating and using metrics that describe dreissenid mussel introduction (i.e., the risk of mussels being introduced into a waterbody) and establishment (i.e., the risk of a mussel population becoming established after an introduction event). The goal of the webinars was to provide context to discussions at the Columbia River Basin Dreissenid Mussel Monitoring Forum. As part of the webinars expert practitioners, gave presentations that summarized the origins and basis for metrics typically used to characterize invasive species invasion risk. During the first webinar which was held on May 7, 2018, Dr. Bob McMahon, University of Texas at Arlington gave a presentation discussing factors affecting the establishment of dreissenid mussels. During the second webinar which was held on May 30, 2018, Samuel Fischer and Mark Lewis from the University of Alberta presented information on factors affecting the introduction of mussels. Presentations at the workshop were given to update participants on the status of dreissenid mussel monitoring in the Columbia River Basin. Staff from the US Army Corps of Engineers (ACOE), Bureau of Reclamation (BOR), USGS, Bureau of Indian Affairs (BIA), and National Park Service (NPS) gave presentations that described the status of dreissenid mussel monitoring efforts conducted by federal agencies. Participants also heard presentations on the status of other monitoring related efforts. Representatives from the Western Regional Panel and Montana Fish Wildlife and Parks (MFWP) presented information about method and protocol standardization coordination activities. Staff from the British Columbia Ministry of Environment and Climate Change Strategy also presented an update on their sampling and resource allocation protocols. The USGS then presented an overview of the evolution and status of dreissenid mussel monitoring in the CRB as well as summary of the results of webinars that addressed facets of dreissenid mussel introduction and establishment risk estimation. To facilitate learning from ongoing efforts that address similar invasive species coordination, monitoring, and research activities, Kelly Baerwaldt, US Fish and Wildlife Service (USFWS) presented remotely on the activities of the Asian Carp Coordinating Committee, informing workshop participants of the how the effort formed and is funded, priority goals and activities, as well as key successes and challenges. The meeting culminated with workshop attendees participating in four breakout groups (risk assessment and research, data/lab analysis, monitoring/coordination, and funding) to identify priority key gaps or weaknesses to existing monitoring/coordination efforts as well as identify priority actions or strategies could help address those gaps or weaknesses. The recommended priority actions from each breakout group were compiled into one overall recommendation to build on existing strengths and address weaknesses associated with monitoring for dreissenids in the Columbia River Basin: Using existing infrastructure and datasets, develop a transboundary, interagency, adaptive, coordinated, regional monitoring framework/partnership to ensure optimal resource allocation.

Conference Paper↗

USGS2003

Predicting coastal retreat in the Florida Big Bend region of the Gulf Coast under climate change induced sea-level rise

Many wildlife preserves and refuges in coastal areas of our nation are slowly being inundated by rising sea-level. Land elevation and tidal flooding are key factors controlling the extent and zonation of coastal habitats. Warming of our global environment threatens to speed the rate of sea-level rise and perhaps further amplify the detrimental effects of tropical storms, droughts, and lightning fires. A field and modeling study was conducted to determine the current status of emergent vegetation and surficial hydrology and to predict marsh transgression under rising sea-level. Field surveys were conducted to relate vegetation cover and ecotones to surface elevation and tidal inundation. A regional site application of a GIS-based simulation model, WETLANDS, was developed to predict ecosystem response to changing sea-level conditions on a coastal reach of the Big Bend region in northwest Florida. The WETLANDS model contains functional probabilities of community tolerance to flooding conditions that dictate the rate and process of ecological succession and coastal retreat. Map information of hypsography and bathymetry of the study area were digitized and interpolated to construct a digital elevation model. Classified thematic mapper imagery of aquatic and terrestrial habitat at a community level was used to initialize model simulation by vegetative type. Model simulations were generated to predict a likelihood index of habitat change and conversion under different scenarios of sea-level rise. The WETLANDS model was applied to track the process and pattern of coastal inundation over space and time for low, mid, and high sea-level rise projections of 15, 50, and 95 cm over the next century. Model results indicated that major portions of this coastal zone will be permanently inundated by 2100, bringing about a combined migration of marsh habitat and displacement of forest habitat. Results show that lowland pine forests will undergo retreat on the order of thousands of hectares over the 21st century. Coastal marsh extent may actually increase slightly as a function of the low lying topography. Socioeconomic implications may be nominal for this area given its remote and fairly undeveloped and protected coast-202 line. The model offers a technological tool for research and policy purposes that allows for effective land and water management, risk assessment, and cumulative impact analysis of wetland systems and landscapes.

Florida↗

USGS1991

Water withdrawals in the Black Warrior-Tombigbee Basin and Alcorn County, Mississippi, 1985-87

Public-supply and industrial water withdrawals were inventoried for the Mississippi part of the Black Warrior-Tombigbee Basin and for Alcorn County, Mississippi. The study area, located in the northeastern part of the State, is largely forested or agricultural land, with some industries near the larger towns. A water-resource capacity analysis was done to determine a risk rating for each inventoried facility, evaluating the likelihood of the facility exceeding the capacity of its current source of water at the existing level of use. Published reports and potentiometric maps were used in this analysis to determine the source capacity and the effects withdrawals have had on each water source. The public-supply and industrial water withdrawals in the basin are from ground water, with the exception of the city of Columbus. About 97 percent of the total withdrawal of 80 million gallons per day is from ground water. Water-supply systems in three areas were determined to have a high risk of exceeding the water-resource capacity: the Tupelo-Lee County area, the West Point (Clay County) area, and the Starkville (Oktibbeha County) area.

Mississippi↗

USGS2020

Evaluating the mineral commodity supply risk of the U.S. manufacturing sector

Trade tensions, resource nationalism, and various other factors are increasing concerns regarding the supply reliability of nonfuel mineral commodities. This is especially the case for commodities required for new and emerging technologies ranging from electric vehicles to wind turbines. In this analysis, we utilize a conventional risk-modeling framework to develop and apply a new methodology for assessing the supply risk to the U.S. manufacturing sector. Specifically, supply risk is defined as the confluence of three factors: the likelihood of a foreign supply disruption, the dependency of U.S. manufacturers on foreign supplies, and the ability of U.S. manufacturers to withstand a supply disruption. The methodology is applied to 52 commodities for the decade spanning 2007-2016. The results indicate that a subset of 23 commodities, including cobalt, niobium, rare earth elements, and tungsten, pose the greatest supply risk. Importantly, this supply risk is dynamic, shifting with changes in global market conditions.

Science Advances↗

USGS2026

Combining branching processes and Allee effects into an integral projection model to assess invasion risk

Invasive species threaten both ecological systems and economies. Successful establishment is governed partly by demographic stochasticity, where random individual-level variation can significantly influence invasion dynamics. A critical factor is the Allee effect, which describes reduced population growth at low densities, potentially serving as a barrier to persistence. Size-dependent growth and survival further shape outcomes based on the size distribution of individuals within the population. To address these complexities, we developed a population-level model integrating an Integral Projection Model (IPM) for the expected size distribution with an Allee effect for recruitment dynamics and a branching process to account for demographic stochasticity. We applied this framework to Silver Carp ( Hypophthalmichthys molitrix ), a species established in the Upper Mississippi River system that poses significant risk of expanding into the Great Lakes. Our analysis compared temporal dynamics and population-size distributions under hypothetical introduction scenarios for large adult and smaller subadult fish. In both cases, initial population size relative to the Allee threshold was a critical determinant of establishment probability, with introductions below the threshold requiring stochastic growth across a critical biomass boundary before self-sustaining dynamics could take hold. Sensitivity analysis further indicated that per-spawner recruitment played a compounding role in invasion risk: higher recruitment rates reduced the critical introduction size for establishment and compressed the time to self-sustaining population size, jointly broadening the window of invasion risk. These findings highlight the framework’s potential for invasion assessments and offer insights into how Allee effects, size structure, and recruitment rates interact to govern establishment outcomes, while underscoring the need for species-specific parameter estimates before quantitative outputs can guide management decisions.

PLOS Ecosystems↗

USGS2006

A review of methods to estimate cause-specific mortality in presence of competing risks

Estimating cause-specific mortality is often of central importance for understanding the dynamics of wildlife populations. Despite such importance, methodology for estimating and analyzing cause-specific mortality has received little attention in wildlife ecology during the past 20 years. The issue of analyzing cause-specific, mutually exclusive events in time is not unique to wildlife. In fact, this general problem has received substantial attention in human biomedical applications within the context of biostatistical survival analysis. Here, we consider cause-specific mortality from a modern biostatistical perspective. This requires carefully defining what we mean by cause-specific mortality and then providing an appropriate hazard-based representation as a competing risks problem. This leads to the general solution of cause-specific mortality as the cumulative incidence function (CIF). We describe the appropriate generalization of the fully nonparametric staggered-entry Kaplan–Meier survival estimator to cause-specific mortality via the nonparametric CIF estimator (NPCIFE), which in many situations offers an attractive alternative to the Heisey–Fuller estimator. An advantage of the NPCIFE is that it lends itself readily to risk factors analysis with standard software for Cox proportional hazards model. The competing risks–based approach also clarifies issues regarding another intuitive but erroneous “cause-specific mortality” estimator based on the Kaplan–Meier survival estimator and commonly seen in the life sciences literature.

Journal of Wildlife Management↗

USGS2024

Non-negligible near-term risk of extinction to the eastern migratory population of monarch butterflies—An updated assessment (2006–22)

The eastern migratory population of monarch butterflies ( Danaus plexippus ) started declining as early as the mid-1970s and seemed to stop declining by the early 2000s; the population now (about 2022) persists at a much-reduced abundance. Stochastic variation in abundance, at levels typical of monarch butterflies and other insects, was assessed to determine whether this population is at heightened risk of quasi-extinction, a level of abundance below which recovery of the migratory behavior is uncertain. Using previously published Bayesian state-space modeling methods it was determined roughly equivalent risk of quasi-extinction as was reported in 2016 for the species (28.7 percent [1.9–81.0 credible interval] and 52.0 percent [3.2–97.7 credible interval] at the 10- and 20-year marks, respectively). Though highly uncertain, the risk is non-negligibly positive. Warning signal analysis indicates the current dynamic is dominated by stochastic variation, which seems to be heightening risk with the passage of time. Increasing breeding opportunities through restoration of milkweed in its northern breeding locations seems to be the most promising means of mitigating extinction risk for this species.

Open-File Report↗

USGS2023

Taming wildfires in the context of climate change: The case of the United States

This report provides a global assessment and outlook on wildfire risk in the context of climate change. It discusses the drivers behind the growing incidence of extreme wildfires and the attribution effect of climate change. It outlines the environmental, social and economic impacts of wildfires by illustrating the losses and costs observed during recent extreme wildfire events. Building on this, the report presents the findings of a cross-country comparative analysis of how countries’ policies and practices have evolved in recent years in light of observed and projected changes in wildfire risk. The analysis draws on in-depth case studies conducted in Australia, Costa Rica, Greece, Portugal and the United States. The report underlines the urgent need for governments to scale up climate change adaptation efforts to limit future wildfire costs.

Report↗

USGS2026

Feathers and flu: Identifying data gaps in avian influenza host dynamics to prioritize wildlife conservation

Highly pathogenic avian influenza viruses (HPAIV) have had disastrous, worldwide effects on wild birds and domestic poultry since the emergence of the A/goose/Guangdong/1/1996 (Gs/GD/96) lineage. The currently circulating H5N1 clade 2.3.4.4b has an expanded set of susceptible hosts, including many migratory wild birds, and is associated with higher transmission rates, increased susceptibility among wild bird hosts, and a greater number of wildlife reservoirs. Certain wild bird life-history strategies and behaviors have been suggested to explain avian hosts’ susceptibility and exposure to HPAIV. These biological traits include gregariousness, such as colonial nesting and mixed flock foraging, predation or scavenging on wild birds, and association with aquatic habitats. Variation in host infection responses (e.g., infectability, shedding rates and duration, mortality rate, antibody development) informs the overall infection risk across avian species, yet the specific role of biological traits is often inconsistent and unclear across taxa. Moreover, the interactions and potential compounding effects among these biological traits remain largely unknown. To develop a more holistic understanding of cumulative risk across bird species, we integrate existing information on infection risk factors (i.e., susceptibility, immunological response, and behavioral traits) into a qualitative multivariate analysis. This approach enabled us to examine how infection risk factors relate to biological traits (e.g., phylogeny, physiology, behavior, species range) and to begin disentangling their complex interactions. We quantified and summarized these risk factors across host species and qualitatively ranked species by their viral responses along a proposed HPAIV response continuum, guided by expectations of traits and metrics associated with competence or vulnerability to HPAIV. In doing so, we aimed to better understand how viral responses and biological traits synergistically interact to influence cumulative risk across wild bird species. This work broadly expands on the previous avian influenza literature, which has focused on Anseriformes and Charadriiformes as primary viral reservoirs. We tie our findings to effective disease management responses with links to risk components, including descriptions of potential surveillance strategies applied to research and One Health goals, as well as a fuller understanding of how resources may be better deployed for rapid response when spillovers do inevitably occur. Additionally, we identified numerous areas where vital epidemiological information is lacking to best characterize the spread of these viruses. Ultimately, this improved understanding will help identify and inform disease management needs and decision making.

Wildlife Monographs↗

USGS2018

Defining the risk landscape in the context of pathogen pollution: Toxoplasma gondii in sea otters along the Pacific Rim

Pathogens entering the marine environment as pollutants exhibit a spatial signature driven by their transport mechanisms. The sea otter ( Enhydra lutris ), a marine animal which lives much of its life within sight of land, presents a unique opportunity to understand land–sea pathogen transmission. Using a dataset on Toxoplasma gondii prevalence across sea otter range from Alaska to California, we found that the dominant drivers of infection risk vary depending upon the spatial scale of analysis. At the population level, regions with high T. gondii prevalence had higher human population density and a greater proportion of human-dominated land uses, suggesting a strong role for population density of the felid definitive host of this parasite. This relationship persisted when a subset of data were analysed at the individual level: large-scale patterns in sea otter T. gondii infection prevalence were largely explained by individual exposure to areas of high human housing unit density, and other landscape features associated with anthropogenic land use, such as impervious surfaces and cropping land. These results contrast with the small-scale, within-region analysis, in which age, sex and prey choice accounted for most of the variation in infection risk, and terrestrial environmental features provided little variation to help in explaining observed patterns. These results underscore the importance of spatial scale in study design when quantifying both individual-level risk factors and landscape-scale variation in infection risk.

California↗

USGS2016

Assessing the seismic risk potential of South America

We present here a simplified approach to quantifying regional seismic risk. The seismic risk for a given region can be inferred in terms of average annual loss (AAL) that represents long-term value of earthquake losses in any one year caused from a long-term seismic hazard. The AAL are commonly measured in the form of earthquake shaking-induced deaths, direct economic impacts or indirect losses caused due to loss of functionality. In the context of South American subcontinent, the analysis makes use of readily available public data on seismicity, population exposure, and the hazard and vulnerability models for the region. The seismic hazard model was derived using available seismic catalogs, fault databases, and the hazard methodologies that are analogous to the U.S. Geological Survey’s national seismic hazard mapping process. The Prompt Assessment of Global Earthquakes for Response (PAGER) system’s direct empirical vulnerability functions in terms of fatality and economic impact were used for performing exposure and risk analyses. The broad findings presented and the risk maps produced herein are preliminary, yet they do offer important insights into the underlying zones of high and low seismic risks in the South American subcontinent. A more detailed analysis of risk may be warranted by engaging local experts, especially in some of the high risk zones identified through the present investigation.

Conference Paper↗

USGS2022

Evaluating the risk of SARS-CoV-2 transmission to bats in the context of wildlife research, rehabilitation, and control

Preventing wildlife disease outbreaks is a priority for natural resource agencies, and management decisions can be urgent, especially in epidemic circumstances. With the emergence of SARS-CoV-2, wildlife agencies were concerned whether the activities they authorize might increase the risk of viral transmission from humans to North American bats, but had a limited amount of time in which to make decisions. We describe how decision analysis provides a powerful framework to analyze and reanalyze complex natural resource management problems as knowledge evolves. Coupled with expert judgment and avenues for the rapid release of information, risk assessment can provide timely scientific information for evolving decisions. In April 2020, the first rapid risk assessment was conducted to evaluate the risk of transmission of SARS-CoV-2 from humans to North American bats. Based on the best available information and relying heavily on expert judgment, the risk assessment found a small possibility of transmission during summer work activities. Following that assessment, additional knowledge and data emerged, such as bat viral challenge studies, that further elucidated the risks of human-to-bat transmission and culminated in a second risk assessment in the fall of 2020. We updated the first SARS-CoV-2 risk assessment with new management alternatives and new estimates of little brown bat ( Myotis lucifugus ) susceptibility, using findings from the fall 2020 assessment and other empirical studies. We found that new knowledge led to an 88% decrease in the median number of bats estimated to be infected per 1,000 encountered when compared to earlier results. The use of facemasks during, or a negative COVID-19 test or vaccination prior to, bat encounters further reduced those risks. Using a combination of decision analysis, expert judgment, rapid risk assessment, and efficient modes of information distribution, we provided timely science-based support to decision makers for summer bat work in North America.

Wildlife Society Bulletin↗

USGS2016

Population viability analysis for endangered Roanoke logperch

A common strategy for recovering endangered species is ensuring that populations exceed the minimum viable population size (MVP), a demographic benchmark that theoretically ensures low long-term extinction risk. One method of establishing MVP is population viability analysis, a modeling technique that simulates population trajectories and forecasts extinction risk based on a series of biological, environmental, and management assumptions. Such models also help identify key uncertainties that have a large influence on extinction risk. We used stochastic count-based simulation models to explore extinction risk, MVP, and the possible benefits of alternative management strategies in populations of Roanoke logperch Percina rex , an endangered stream fish. Estimates of extinction risk were sensitive to the assumed population growth rate and model type, carrying capacity, and catastrophe regime (frequency and severity of anthropogenic fish kills), whereas demographic augmentation did little to reduce extinction risk. Under density-dependent growth, the estimated MVP for Roanoke logperch ranged from 200 to 4200 individuals, depending on the assumed severity of catastrophes. Thus, depending on the MVP threshold, anywhere from two to all five of the logperch populations we assessed were projected to be viable. Despite this uncertainty, these results help identify populations with the greatest relative extinction risk, as well as management strategies that might reduce this risk the most, such as increasing carrying capacity and reducing fish kills. Better estimates of population growth parameters and catastrophe regimes would facilitate the refinement of MVP and extinction-risk estimates, and they should be a high priority for future research on Roanoke logperch and other imperiled stream-fish species.

Journal of Fish and Wildlife Management↗

USGS2019

Projected urban growth in the Southeastern USA puts small streams at risk

Future land-use development has the potential to profoundly affect the health of aquatic ecosystems in the coming decades. We developed regression models predicting the loss of sensitive fish (R2=0.39) and macroinvertebrate (R2=0.64) taxa as a function of urban and agricultural land uses and applied them to projected urbanization of the rapidly urbanizing Piedmont ecoregion of the southeastern USA for 2030 and 2060. The regression models are based on a 2014 investigation of water quality and ecology of 75 wadeable streams across the region. Based on these projections, stream kilometers experiencing >50% loss of sensitive fish and invertebrate taxa will nearly quadruple to 19,500 and 38,950 km by 2060 (16 and 32% of small stream kilometers in the region), respectively. Uncertainty was assessed using the 20 and 80% probability of urbanization for the land-use projection model and using the 95% confidence intervals for the regression models. Adverse effects on stream health were linked to elevated concentrations of contaminants and nutrients, low dissolved oxygen, and streamflow alteration, all associated with urbanization. The results of this analysis provide a warning of potential risks from future urbanization and perhaps some guidance on how those risks might be mitigated.

PLoS ONE↗

USGS2026

Bayesian belief network model to predict human-wildlife conflict in protected areas

Human-wildlife conflict (HWC) poses a pervasive global challenge, affecting livelihoods and threatening biodiversity. To better anticipate and mitigate HWC risk, we developed a large-scale predictive model using a Bayesian Belief Network (BBN). We surveyed 1,011 park rangers across 135 terrestrial protected areas in three Andean countries, documenting recent HWC incidents involving wildlife persecution or killing, livestock depredation, crop damage, or threats to human safety and property. We identified key drivers of HWC risk, including governance, wildlife acceptance, participation, and habitat quality. A sensitivity analysis revealed that enhancing governance and improving wildlife acceptance could reduce HWC risk by > 85%. The BBN model demonstrated scalability, effectively identifying strategies to reduce HWC risk at multiple scales, from individual protected areas to national networks. Our findings highlight the importance of strengthening governance, increasing wildlife acceptance, and enhancing community participation in conservation efforts. BBNs provide a flexible, cost-effective, and data-driven tool to guide protected areas and wildlife managers in monitoring, anticipating, and making informed decisions to mitigate conflict and promote coexistence.

Scientific Reports↗

USGS2021

Conservation of northwestern and southwestern pond turtles: Threats, population size estimates, and population viability analysis

Accurate status assessments of long-lived, widely distributed taxa depend on the availability of long-term monitoring data from multiple populations. However, monitoring populations across large temporal and spatial scales is often beyond the scope of any one researcher or research group. Consequently, wildlife managers may be tasked with utilizing limited information from different sources to detect range-wide evidence of population declines and their causes. When assessments need to be made under such constraints, the research and management communities must determine how to extrapolate from variable population data to species-level inferences. Here, using three different approaches, we integrate and analyze data from the peer-reviewed literature and government agency reports to inform conservation for northwestern pond turtles (NPT) Actinemys marmorata and southwestern pond turtles (SPT) Actinemys pallida . Both NPT and SPT are long-lived freshwater turtles distributed along the west coast of the United States and Mexico. Conservation concerns exist for both species; however, SPT may face more severe threats and are thought to exist at lower densities throughout their range than NPT. For each species, we ranked the impacts of 13 potential threats, estimated population sizes, and modeled population viability with and without long-term droughts. Our results suggest that predation of hatchlings by invasive predators, such as American bullfrogs Lithobates catesbeianus and Largemouth Bass Micropterus salmoides, is a high-ranking threat for NPT and SPT. Southwestern pond turtles may also face more severe impacts associated with natural disasters (droughts, wildfires, and floods) than do NPT. Population size estimates from trapping surveys indicate that SPT have smaller population sizes on average than do NPT ( P = 0.0003), suggesting they may be at greater risk of local extirpation. Population viability analysis models revealed that long-term droughts are a key environmental parameter; as the frequency of severe droughts increases with climate change, the likelihood of population recovery decreases, especially when census sizes are low. Given current population trends and vulnerability to natural disasters throughout their range, we suggest that conservation and recovery actions first focus on SPT to prevent further population declines.

Journal of Fish and Wildlife Management↗

USGS2017

Viability analysis for multiple populations

Many species of conservation interest exist solely or largely in isolated populations. Ideally, prioritization of management actions among such populations would be guided by quantitative estimates of extinction risk, but conventional methods of demographic population viability analysis (PVA) model each population separately and require temporally extensive datasets that are rarely available in practice. We introduce a general class of statistical PVA that can be applied to many populations at once, which we term multiple population viability analysis or MPVA. The approach combines models of abundance at multiple spatial locations with temporal models of population dynamics, effectively borrowing information from more data-rich populations to inform inferences for data-poor populations. Covariates are used to explain population variability in space and time. Using Bayesian analysis, we illustrate the method with a dataset of Lahontan cutthroat trout ( Oncorhynchus clarkii henshawi ) observations that previously had been analyzed with conventional PVA. We find that MPVA predictions are similar in bias and higher in precision than predictions from simple PVA models that treat each population individually; moreover, the use of covariates in MPVA allows for predictions in minimally-sampled and unsampled populations. The basic MPVA model can be extended in multiple ways, such as by linking to a sampling and observation model to provide a full accounting of uncertainty. We conclude that the approach has great potential to expand the use of PVA for species that exist in multiple, isolated populations.

Biological Conservation↗

USGS2013

Choices in recreational water quality monitoring: new opportunities and health risk trade-offs

With the recent release of new recreational water quality monitoring criteria, there are more options for regulatory agencies seeking to protect beachgoers from waterborne pathogens. Included are methods that can reduce analytical time, providing timelier estimates of water quality, but the application of these methods has not been examined at most beaches for expectation of health risk and management decisions. In this analysis, we explore health and monitoring outcomes expected at Lake Michigan beaches using protocols for indicator bacteria including culturable Escherichia coli (E. coli; EC), culturable enterococci (ENT), and enterococci as analyzed by qPCR (QENT). Correlations between method results were generally high, except at beaches with historically high concentrations of EC. The “beach action value” was exceeded most often when using EC or ENT as the target indicator; QENT exceeded the limit far less frequently. Measured water quality between years was varied. Although methods with equivalent health expectation have been established, the lack of relationship among method outcomes and annual changes in mean indicator bacteria concentrations complicates the decision-making process. The monitoring approach selected by beach managers may be a combination of available tools that maximizes timely health protection, cost efficiency, and collaboration among beach jurisdictions.

Environmental Science & Technology↗