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At least 433 records · Page 24Linked to original sources
USGS2017

Advancing mangrove macroecology

Mangrove forests provide a wide range of ecosystem services to society, yet they are among the most anthropogenically impacted coastal ecosystems in the world. In this chapter, we discuss and provide examples for how macroecology can advance our understanding of mangrove ecosystems. Macroecology is broadly defined as a discipline that uses statistical analyses to investigate large-scale, universal patterns in the distribution, abundance, diversity, and organization of species and ecosystems, including the scaling of ecological processes and structural and functional relationships. Macroecological methods can be used to advance our understanding of how non-linear responses in natural systems can be triggered by human impacts at local, regional, and global scales. Although macroecology has the potential to gain knowledge on universal patterns and processes that govern mangrove ecosystems, the application of macroecological methods to mangroves has historically been limited by constraints in data quality and availability. Here we provide examples that include evaluations of the variation in mangrove forest ecosystem structure and function in relation to macroclimatic drivers (e.g., temperature and rainfall regimes) and climate change. Additional examples include work focused upon the continental distribution of aboveground net primary productivity and carbon storage, which are rapidly advancing research areas. These examples demonstrate the value of a macroecological perspective for the understanding of global- and regional-scale effects of both changing environmental conditions and management actions on ecosystem structure, function, and the supply of goods and services. We also present current trends in mangrove modeling approaches and their potential utility to test hypotheses about mangrove structural and functional properties. Given the gap in relevant experimental work at the regional scale, we also discuss the potential use of mangrove restoration and rehabilitation projects as macroecological studies that advance the critical selection and conservation of ecosystem services when managing mangrove resources. Future work to further incorporate macroecology into mangrove research will require a concerted effort by research groups and institutions to launch research initiatives and synthesize data collected across broad biogeographic regions.

Book chapter↗
USGS2016

Science to support aquatic animal health

Healthy aquatic ecosystems are home to a diversity of plants, invertebrates, fish and wildlife. Aquatic animal populations face unprecedented threats to their health and survival from climate change, water shortages, habitat alteration, invasive species and environmental contaminants. These environmental stressors can directly impact the prevalence and severity of disease in aquatic populations. For example, periodic fish kills in the upper Chesapeake Bay Watershed are associated with many different opportunistic pathogens that proliferate in stressed fish populations. An estimated 80 percent of endangered juvenile Puget Sound steelhead trout die within two weeks of entering the marine environment, and a role for disease in these losses is being investigated. The introduction of viral hemorrhagic septicemia virus (VHSV) into the Great Lakes—a fishery worth an estimated 7 billion dollars annually—resulted in widespread fish die-offs and virus detections in 28 different fish species. Millions of dying sea stars along the west coast of North America have led to investigations into sea star wasting disease. U.S. Geological Survey (USGS) scientists are assisting managers with these issues through ecological investigations of aquatic animal diseases, field surveillance, and research to promote the development of mitigation strategies.

Fact Sheet↗
USGS2019

A General Lake Model (GLM 3.0) for linking with high-frequency sensor data from the Global Lake Ecological Observatory Network (GLEON)

The General Lake Model (GLM) is a one-dimensional open-source code designed to simulate the hydrodynamics of lakes, reservoirs, and wetlands. GLM was developed to support the science needs of the Global Lake Ecological Observatory Network (GLEON), a network of researchers using sensors to understand lake functioning and address questions about how lakes around the world respond to climate and land use change. The scale and diversity of lake types, locations, and sizes, and the expanding observational datasets created the need for a robust community model of lake dynamics with sufficient flexibility to accommodate a range of scientific and management questions relevant to the GLEON community. This paper summarizes the scientific basis and numerical implementation of the model algorithms, including details of sub-models that simulate surface heat exchange and ice cover dynamics, vertical mixing, and inflow–outflow dynamics. We demonstrate the suitability of the model for different lake types that vary substantially in their morphology, hydrology, and climatic conditions. GLM supports a dynamic coupling with biogeochemical and ecological modelling libraries for integrated simulations of water quality and ecosystem health, and options for integration with other environmental models are outlined. Finally, we discuss utilities for the analysis of model outputs and uncertainty assessments, model operation within a distributed cloud-computing environment, and as a tool to support the learning of network participants.

Geoscientific Model Development↗
USGS2006

Modeling habitat distribution from organism occurrences and environmental data: Case study using anemonefishes and their sea anemone hosts

We demonstrate the KGSMapper (Kansas Geological Survey Mapper), a straightforward, web-based biogeographic tool that uses environmental conditions of places where members of a taxon are known to occur to find other places containing suitable habitat for them. Using occurrence data for anemonefishes or their host sea anemones, and data for environmental parameters, we generated maps of suitable habitat for the organisms. The fact that the fishes are obligate symbionts of the anemones allowed us to validate the KGSMapper output: we were able to compare the inferred occurrence of the organism to that of the actual occurrence of its symbiont. Characterizing suitable habitat for these organisms in the Indo-West Pacific, the region where they naturally occur, can be used to guide conservation efforts, field work, etc.; defining suitable habitat for them in the Atlantic and eastern Pacific is relevant to identifying areas vulnerable to biological invasions. We advocate distinguishing between these 2 sorts of model output, terming the former maps of realized habitat and the latter maps of potential habitat. Creation of a niche model requires adding biotic data to the environmental data used for habitat maps: we included data on fish occurrences to infer anemone distribution and vice versa. Altering the selection of environmental variables allowed us to investigate which variables may exert the most influence on organism distribution. Adding variables does not necessarily improve precision of the model output. KGSMapper output distinguishes areas that fall within 1 standard deviation (SD) of the mean environmental variable values for places where members of the taxon occur, within 2 SD, and within the entire range of values; eliminating outliers or data known to be imprecise or inaccurate improved output precision mainly in the 2 SD range and beyond. Thus, KGSMapper is robust in the face of questionable data, offering the user a way to recognize and clean such data. It also functions well with sparse datasets. These features make it useful for biogeographic meta-analyses with the diverse, distributed datasets that are typical for marine organisms lacking direct commercial value. ?? Inter-Research 2006.

Marine Ecology Progress Series↗
USGS2021

Demographic risk assessment for a harvested species threatened by climate change: Polar bears in the Chukchi Sea

Climate change threatens global biodiversity. Many species vulnerable to climate change are important to humans for nutritional, cultural, and economic reasons. Polar bears Ursus maritimus are threatened by sea-ice loss and represent a subsistence resource for Indigenous people. We applied a novel population modeling-management framework that is based on species life history and accounts for habitat loss to evaluate subsistence harvest for the Chukchi Sea (CS) polar bear subpopulation. Harvest strategies followed a state-dependent approach under which new data were used to update the harvest on a predetermined management interval. We found that a harvest strategy with a starting total harvest rate of 2.7% (˜85 bears/yr at current abundance), a 2:1 male-to-female ratio, and a 10-yr management interval would likely maintain subpopulation abundance above maximum net productivity level for the next 35 yr (approximately three polar bear generations), our primary criterion for sustainability. Plausible bounds on starting total harvest rate were 1.7–3.9%, where the range reflects uncertainty due to sampling variation, environmental variation, model selection, and differing levels of risk tolerance. The risk of undesired demographic outcomes (e.g., overharvest) was positively related to harvest rate, management interval, and projected declines in environmental carrying capacity; and negatively related to precision in population data. Results reflect several lines of evidence that the CS subpopulation has been productive in recent years, although it is uncertain how long this will last as sea-ice loss continues. Our methods provide a template for balancing trade-offs among protection, use, research investment, and other factors. Demographic risk assessment and state-dependent management will become increasingly important for harvested species, like polar bears, that exhibit spatiotemporal variation in their response to climate change.

Chukchi Sea↗
USGS2021

Grand challenges of hydrologic modeling for food-energy-water nexus security in high mountain Asia

Climate-influenced changes in hydrology affect water-food-energy security that may impact up to two billion people downstream of the High Mountain Asia (HMA) region. Changes in water supply affect energy, industry, transportation, and ecosystems (agriculture, fisheries) and as a result, also affect the region's social, environmental, and economic fabrics. Sustaining the highly interconnected food-energy-water nexus (FEWN) will be a fundamental and increasing challenge under a changing climate regime. High variability in topography and distribution of glaciated and snow-covered areas in the HMA region, and scarcity of high resolution ( in-situ ) data make it difficult to model and project climate change impacts on individual watersheds. We lack basic understanding of the spatial and temporal variations in climate, surface impurities in snow and ice such as black carbon and dust that alter surface albedo, and glacier mass balance and dynamics. These knowledge gaps create challenges in predicting where and when the impact of changes in river flow will be the most significant economically and ecologically. In response to these challenges, the United States National Aeronautics and Space Administration (NASA) established the High Mountain Asia Team (HiMAT) in 2016 to conduct research to address knowledge gaps. This paper summarizes some of the advances HiMAT made over the past 5 years, highlights the scientific challenges in improving our understanding of the hydrology of the HMA region, and introduces an integrated assessment framework to assess the impacts of climate changes on the FEWN for the HMA region. The framework, developed under a NASA HMA project, links climate models, hydrology, hydropower, fish biology, and economic analysis. The framework could be applied to develop scientific understanding of spatio-temporal variability in water availability and the resultant downstream impacts on the FEWN to support water resource management under a changing climate regime.

Frontiers in Water↗
USGS2026

A review of extraction techniques for per- and polyfluoroalkyl substances in graminaceous plants

Per- and polyfluoroalkyl substances (PFAS) are a wide-ranging class of manufactured chemicals that are environmentally persistent. Due to their ubiquity and resistance to degradation, PFAS readily bioaccumulate in a variety of environmental matrices and elicit a range of toxicological impacts. Despite an increase in research into these compounds, there is a clear gap in consensus on extraction techniques to quantify many PFAS in certain environmental media, particularly at critical points in agricultural food systems such as pasture grasses and feedstocks. Developing methods for more comprehensive and accurate extraction of PFAS in plant tissues is crucial for the biomonitoring of PFAS contamination in these ecosystems. This review seeks to identify relevant information pertaining to the partitioning of PFAS in plant matrices and evaluate the performance of previously established methods for the extraction of PFAS in graminaceous plants. Evaluated methods varied widely in extraction techniques, limits of detection and accuracy. This review provides a framework for enhancing PFAS analysis by tailoring extraction and cleanup strategies to both complex plant matrices and diverse analyte properties. Standardizing these methodologies will provide the high-quality data essential for ecotoxicologists and policymakers to accurately map the metabolic fate and ecological risks of these pollutants across food webs.

Critical Reviews in Analytical Chemistry↗
USGS2015

Influences of supplemental feeding on winter elk calf:cow ratios in the southern Greater Yellowstone Ecosystem

Several elk herds in the Greater Yellowstone Ecosystem are fed during winter to alleviate interactions with livestock, reduce damage to stored crops, and to manage for high elk numbers. The effects of supplemental feeding on ungulate population dynamics has rarely been examined, despite the fact that supplemental feeding is partially justified as necessary for maintaining or enhancing population growth rates. We used linear regression to assess how the presence of feedgrounds, snowpack, summer rainfall, indices of grizzly bear density and wolves per elk, elk population trend counts, brucellosis seroprevalence, and survey date were correlated with midwinter calf:cow ratios, a metric correlated with population growth, from 1983–2010 from 12 ecologically similar elk herd units (7 fed and 5 unfed) in Wyoming, USA. Our statistical approach allowed for rigorous tests of the hypotheses that supplemental feeding had positive effects on calf:cow ratios and reduced sensitivity of calf:cow ratios to bottom-up limitation relative to top-down limitation from native predators. Calf:cow ratios generally declined across all herd units over the study period and varied widely among units with feedgrounds. We found no evidence that the presence of feedgrounds had positive effects on midwinter calf:cow ratios in Wyoming. Further, fed elk showed stronger correlations with environmental factors, whereas calf:cow ratios for unfed elk showed stronger correlations with predator indices. Although we found no consistent association between winter feeding and higher calf:cow ratios, we did not assess late winter mortality and differences in human offtake between fed and unfed regions, which remain a priority for future research.

Wyoming↗
USGS2021

The application of metacommunity theory to the management of riverine ecosystems

River managers strive to use the best available science to sustain biodiversity and ecosystem function. To achieve this goal requires consideration of processes at different scales. Metacommunity theory describes how multiple species from different communities potentially interact with local-scale environmental drivers to influence population dynamics and community structure. However, this body of knowledge has only rarely been used to inform management practices for river ecosystems. In this article, we present a conceptual model outlining how the metacommunity processes of local niche sorting and dispersal can influence the outcomes of management interventions and provide a series of specific recommendations for applying these ideas as well as research needs. In all cases, we identify situations where traditional approaches to riverine management could be enhanced by incorporating an understanding of metacommunity dynamics. A common theme is developing guidelines for assessing the metacommunity context of a site or region, evaluating how that context may affect the desired outcome, and incorporating that understanding into the planning process and methods used. To maximize the effectiveness of management activities, scientists, and resource managers should update the toolbox of approaches to riverine management to reflect theoretical advances in metacommunity ecology.

WIREs Water↗
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↗
USGS2025

Estimates of global surface water dynamics harnessing near real-time land cover observations and open science geospatial capabilities

Spatio-temporal changes to our world’s surface water resources are escalating. Translating how these changes impact communities and ecosystems requires time-varying data of Global Surface Water Extents (GSWE). Traditionally, GSWE mapping has been limited to static estimates, with recent efforts focusing on annual averages, frequency and occurrence of long-term variations. Building upon these foundational capabilities, we harnessed remotely sensed Sentinel-2 based near real-time Dynamic World (DW) land cover products to produce the first-of-its-kind 10 m resolution GSWE dataset representing 2015–2023. Our dataset estimated 2.5 million km 2 of permanent waters and 8 million km 2 of seasonal waters worldwide. Comparing our Sentinel-2 based data to contemporary Landsat-based GSWE, we observed that our data mapped less water within the >50% probability of occurrence range, suggesting a lower presence of open permanent water especially in high latitudes, deviating from what we previously learnt from Landsat data. Statistical analysis compared to well-established observational products and widely used GSWE datasets across some of the world’s most ecologically significant regions, including Pantanal in South America and Haor in South Asia, supports the overall physical realism of our data in predicting global open surface water dynamics. Our key contribution is a prototype Open Science operational framework that extracts routinely available DW products, runs geospatial analytics, and creates actionable water information for educators, researchers, and stakeholders at any scale of practical interest. We present examples of this operational capability through instant mapping of flood in Spain and drought in Lake Urmia, Central Asia, frequent monitoring of river extent changes at the Ganges–Brahmaputra confluence, and above all, interoperability with other existing GSWE applications.

Environmental Research Letters↗
USGS2007

Paleoecology and ecosystem restoration: Case studies from Chesapeake Bay and the Florida Everglades

Climate extremes that cause droughts, floods, or large temperature fluctuations can complicate ecosystem restoration efforts focused on local and regional human disturbance. Restoration targets are often based primarily on monitoring data and modeling simulations, which provide information on species' short-term response to disturbance and environmental variables. Consequently, the targets may be unsustainable under the spectrum of natural variability inherent in the system or under future climate change. Increasingly, ecologists and restoration planners recognize the value of the long temporal perspective provided by paleoecological data. Advances in paleoclimatology, including better climate proxy methods and temporal resolution, contribute to our understanding of ecosystem response to anthropogenic and climatic forcing at all time scales. We highlight paleoecological research in the Chesapeake Bay and the Florida Everglades and summarize the resulting contributions to restoration planning. Integration of paleoecological, historic, monitoring, and modeling efforts will lead to the development of sustainable, adaptive management strategies for ecosystem restoration.

Delaware, Florida, Maryland, New York, Pennsylvani↗
USGS2014

USGS ecosystem research for the next decade: advancing discovery and application in parks and protected areas through collaboration

Ecosystems within parks and protected areas in the United States and throughout the world are being transformed at an unprecedented rate. Changes associated with natural hazards, greenhouse gas emissions, and increasing demands for water, food, land, energy and mineral resources are placing urgency on sound decision making that will help sustain our Nation’s economic and environmental well-being (Millennium Ecosystem Assessment, 2005). In recognition of the importance of science in making these decisions, the U.S. Geological Survey (USGS) in 2007 identified ecosystem science as one of six science directions included in a comprehensive decadal strategy (USGS 2007). The Ecosystems Mission Area was identified as essential for integrating activity within the USGS and as a key to enhanced integration with other Federal and private sector research and management organizations (Myers at al., 2007). This paper focuses on benefits to parks and protected areas from the USGS Ecosystems Mission Area plan that expanded the scope of the original 2007 science strategy, to identify the Bureau’s work in ecosystem science over the next decade (Williams et al., 2013). The plan describes a framework that encompasses both basic and applied science and allows the USGS to continue to contribute meaningfully to conservation and management issues related to the Nation’s parks and ecological resources. This framework relies on maintaining long-standing, collaborative relationships with partners in both conducting science and applying scientific results. Here we summarize the major components of the USGS Ecosystems Science Strategy, articulating the vision, goals and strategic approaches, then outlining some of the proposed actions that will ultimately prove useful to those managing parks and protected areas. We end with a discussion on the future of ecosystem science for the USGS and how it can be used to evaluate ecosystem change and the associated consequences to management of our Nation’s natural resources.

The George Wright Forum↗
USGS2022

Ocean acidification in the Gulf of Mexico: Drivers, impacts, and unknowns

Ocean acidification (OA) has resulted in global-scale changes in ocean chemistry, which can disturb marine organisms and ecosystems. Despite its extensively populated coastline, many marine-dependent communities, and valuable economies, the Gulf of Mexico (GOM) remains a relatively understudied region with respect to acidification. In general, the warm waters of the GOM are better buffered from acidification compared to higher latitude seas, yet long-term acidification has been documented in several GOM regions. OA within the GOM is recognized as spatially variable, particularly within the coastal zone where numerous physical and biogeochemical processes contribute to carbonate chemistry dynamics. The historical progression of OA within the entire GOM is difficult to assess because only a few dedicated long-term monitoring sites have recently been established, and full-water column observations are limited. However, environmental drivers on smaller scales that affect GOM acidification were found to include freshwater, nutrient, and carbonate discharge from large rivers; ocean warming, circulation and residence times; and episodic extreme weather events. GOM marine ecosystems provide essential services, including coastline protection and carbon dioxide removal, and habitats for many marine species that are economically and ecologically important. However, organismal and ecosystem responses to OA are not well constrained for the GOM due to a lack of studies examining the specific effects of OA on regionally relevant species under contemporary and projected conditions. Tackling the vast number of remaining scientific unknowns in this region can be best coordinated through regional capacity networks, such as the Gulf of Mexico Coastal Acidification Network (GCAN), working to achieve a system-wide understanding of Gulf OA and its impacts. Here we synthesize the current peer-reviewed literature on GOM acidification across the ocean-estuarine continuum and identify critical knowledge, research, and monitoring gaps that require future attention.

Progress in Oceanography↗
USGS2025

Science needs for determining the effects of climate change on harmful algal blooms in the southeastern United States

The Southeastern United States has many lakes, streams, and reservoirs that serve as important drinking water sources with recreational, agricultural, and ecological uses. However, harmful algal blooms (HABs) are becoming more common in these waters, causing health issues for humans and animals. HABs have been listed as a contaminant of emerging concern, and the magnitude, frequency, and duration of HABs appear to be increasing at the global scale. While it is well known that nutrients stimulate algae growth, it is not clear how climate change and other parameters stimulate the development of toxin production by HABs. The scientific literature describes parameters, such as storm occurrence, temperature, dissolved metals, erosion of soils, increasing length of growing season, discharge, and hydroperiod, that may affect algae growth and toxin production. Climate and hydrologic models address many of the physical and environmental parameters that influence HABs, but no climate models directly address HABs. This report compiles information from the existing literature pertaining to HABs and the modeling and forecasting of HABS. This compilation is done through the incorporation of climate change models. HAB research that involves climate change will require multiple disciplines that bring together ecologists, hydrologists, climatologists, engineers, economists, and new technology. Resource managers could use geographic data about the occurrence and distribution of HABs to develop models that identify waterbodies more vulnerable to HAB events. Development of such models will require teams capable of integrating biological, chemical, and physical factors. Model development will require additional research that can resolve anthropogenic and climate-related environmental factors to identify trends in freshwater HABs. The complexity and interconnectedness of the parameters that influence HAB occurrences will make model development challenging and require rigorous regional calibration.

Open-File Report↗
USGS2017

Occurrence of dichloroacetamide herbicide safeners and co-applied herbicides in midwestern U.S. streams

Dichloroacetamide safeners (e.g., AD-67, benoxacor, dichlormid, and furilazole) are co-applied with chloroacetanilide herbicides to protect crops from herbicide toxicity. While such safeners have been used since the early 1970s, there are minimal data about safener usage, occurrence in streams, or potential ecological effects. This study focused on one of these research gaps, occurrence in streams. Seven Midwestern U.S. streams (five in Iowa and two in Illinois), with extensive row-crop agriculture, were sampled at varying frequencies from spring 2016 through summer 2017. All four safeners were detected at least once; furilazole was the most frequently detected (31%), followed by benoxacor (29%), dichlormid (15%), and AD-67 (2%). The maximum concentrations ranged from 42 to 190 ng/L. Stream detections and concentrations of safeners appear to be driven by a combination of timing of application (spring following herbicide application) and precipitation events. Detected concentrations were below known toxicity levels for aquatic organisms.

Illinois, Iowa↗
USGS2014

A quantitative life history of endangered humpback chub that spawn in the Little Colorado River: variation in movement, growth, and survival

While the ecology and evolution of partial migratory systems (defined broadly to include skip spawning) have been well studied, we are only beginning to understand how partial migratory populations are responding to ongoing environmental change. Environmental change can lead to differences in the fitness of residents and migrants, which could eventually lead to changes in the frequency of the strategies in the overall population. Here, we address questions concerning the life history of the endangered Gila cypha (humpback chub) in the regulated Colorado River and the unregulated tributary and primary spawning area, the Little Colorado River. We develop eight multistate models for the population based on three movement hypotheses, in which states are defined in terms of fish size classes and river locations. We fit these models to mark–recapture data collected in 2009–2012. We compare survival and growth estimates between the Colorado River and Little Colorado River and calculate abundances for all size classes. The best model supports the hypotheses that larger adults spawn more frequently than smaller adults, that there are residents in the spawning grounds, and that juveniles move out of the Little Colorado River in large numbers during the monsoon season (July–September). Monthly survival rates for G. cypha in the Colorado River are higher than in the Little Colorado River in all size classes; however, growth is slower. While the hypothetical life histories of life-long residents in the Little Colorado River and partial migrants spending most of its time in the Colorado River are very different, they lead to roughly similar fitness expectations when we used expected number of spawns as a proxy. However, more research is needed because our study period covers a period of years when conditions in the Colorado River for G. cypha are likely to have been better than has been typical over the last few decades.

Colorado River;Little Colorado River↗
USGS2013

Multi-laboratory evaluations of the performance of Catellicoccus marimammalium PCR assays developed to target gull fecal sources

Here we report results from a multi-laboratory ( n = 11) evaluation of four different PCR methods targeting the 16S rRNA gene of Catellicoccus marimammalium originally developed to detect gull fecal contamination in coastal environments. The methods included a conventional end-point PCR method, a SYBR ® Green qPCR method, and two TaqMan ® qPCR methods. Different techniques for data normalization and analysis were tested. Data analysis methods had a pronounced impact on assay sensitivity and specificity calculations. Across-laboratory standardization of metrics including the lower limit of quantification (LLOQ), target detected but not quantifiable (DNQ), and target not detected (ND) significantly improved results compared to results submitted by individual laboratories prior to definition standardization. The unit of measure used for data normalization also had a pronounced effect on measured assay performance. Data normalization to DNA mass improved quantitative method performance as compared to enterococcus normalization. The MST methods tested here were originally designed for gulls but were found in this study to also detect feces from other birds, particularly feces composited from pigeons. Sequencing efforts showed that some pigeon feces from California contained sequences similar to C. marimammalium found in gull feces. These data suggest that the prevalence, geographic scope, and ecology of C. marimammalium in host birds other than gulls require further investigation. This study represents an important first step in the multi-laboratory assessment of these methods and highlights the need to broaden and standardize additional evaluations, including environmentally relevant target concentrations in ambient waters from diverse geographic regions.

Water Research↗