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Ecology and the ratchet of events: climate variability, niche dimensions, and species distributions

Climate change in the coming centuries will be characterized by interannual, decadal, and multidecadal fluctuations superimposed on anthropogenic trends. Predicting ecological and biogeographic responses to these changes constitutes an immense challenge for ecologists. Perspectives from climatic and ecological history indicate that responses will be laden with contingencies, resulting from episodic climatic events interacting with demographic and colonization events. This effect is compounded by the dependency of environmental sensitivity upon life-stage for many species. Climate variables often used in empirical niche models may become decoupled from the proximal variables that directly influence individuals and populations. Greater predictive capacity, and more-fundamental ecological and biogeographic understanding, will come from integration of correlational niche modeling with mechanistic niche modeling, dynamic ecological modeling, targeted experiments, and systematic observations of past and present patterns and dynamics.

Proceedings of the National Academy of Sciences

Towards improved environmental modeling outcomes: Enabling low-cost access to high-dimensional, geostatistical-based decision-support analyses

Computer models of environmental systems routinely inform decision making for water resource management. In this context, quantifying uncertainty in the important simulated outputs, and reducing uncertainty through assimilating historic system-state observations, is as important as the numerical model. However, implementing high-dimensional and stochastic workflows are challenging, often requiring that practitioners have theoretical and practical understanding of several advanced topics. Worse, implementing these important analyses can take substantial time and effort. This additional effort is often cited as justification for postponing, or even forgoing, these analyses. Herein, we present scripting tools to facilitate the efficient and repeatable construction of high-dimensional, geostatistical-based PEST interfaces, including uncertainty analyses. As demonstrated, these tools can be applied with minimal effort to a model with varied temporal and spatial discretization. Ultimately, these tools can enable low-cost access to valuable decision-support analyses earlier and more frequently during the modeling workflow.

Environmental Modelling & Software

National-scale assessment of total gaseous mercury isotopes across the United States

With the 2011 promulgation of the Mercury and Air Toxics Standards by the U.S. Environmental Protection Agency, and the successful negotiation by the United Nations Environment Program of the Minamata Convention, emissions of mercury (Hg) have declined in the United States. While the declines in atmospheric Hg concentrations in North America are encouraging, linking the declines to changing domestic and global source portfolios remains challenging. To address these research gaps, the U.S. Geological Survey initiated the first national-scale effort to establish a baseline of total gaseous mercury stable isotope values at 31 sites distributed across the United States. Results indicated that unique Hg sources, such as Hg evasion from an elemental Hg contaminated site or free tropospheric intrusions in high altitude sites, were distinguishable from background atmospheric values. Minor gradients were observed across the nation, with regions of heavy industrial activity demonstrating lower δ 202 Hg, but no consistent changes in other isotopes such as Δ 199 Hg and Δ 200 Hg were observed. Furthermore, δ 202 Hg was impacted by foliar uptake and senescence but trends varied between forested regions in the northeastern and midwestern United States. These data demonstrate regional emission sources and other environmental variables can impact total gaseous Hg (TGM) isotope values, highlighting the need to characterize atmospheric Hg isotopes over larger geographical areas to evaluate changes related to national and international Hg regulations.

JGR Atmospheres

Too much and not enough data: Challenges and solutions for generating information in freshwater research and monitoring

Evaluating progress toward achieving freshwater conservation and sustainability goals requires transforming diverse types of data into useful information for scientists, managers, and other interest groups. Despite substantial increases in the volume of freshwater data collected worldwide, many regions and ecosystems still lack sufficient data collection and/or data access. We illustrate how these data challenges result from a diverse set of underlying mechanisms and propose solutions that can be applied by individuals or organizations. We discuss creative approaches to address data scarcity, including the use of community science, remote-sensing, environmental sensors, and legacy datasets. We highlight the importance of coordinated data collection efforts among groups and training programs to improve data access. At the institutional level, we emphasize the power of prioritizing data curation, incentivizing data publication, and promoting research that enhances data coverage and representativeness. Some of these strategies involve technological and analytical approaches, but many necessitate shifting the priorities and incentives of organizations such as academic and government research institutions, monitoring groups, journals, and funding agencies. Our overarching goal is to stimulate discussion to narrow the data disparities hindering the understanding of freshwater processes and their change across spatial scales.

Nahuel Huapi Lake, Lake Tahoe

An interferometric synthetic aperture radar (InSAR) habitat suitability model to identify overwinter conditions for coregonine whitefishes in Arctic lagoons

Lagoons provide critical habitats for many fishes, including coregonine whitefishes, which are a mainstay in many subsistence fisheries of rural communities in Arctic Alaska. Despite their importance, little is known about the overwintering habits of whitefishes in Arctic Alaska due to the challenges associated with sampling during winter. We developed a habitat suitability (HS) model to understand the potential range of physical conditions that whitefishes experience during the Arctic winter, using three indicator lagoons that represent a range of environmental characteristics. The HS model was built using a three-step approach. First, remote sensing that uses interferometric synthetic aperture radar (InSAR) identified areas of floating and bottomfast ice. Second, through in-field ground-truthing, we confirmed the presence and quality of liquid water (water depth, temperature, and dissolved oxygen) beneath the ice cover. Third, we assessed the suitability of that liquid water as habitat for whitefishes based on published literature and expert interpretation of water quality parameters. InSAR determined that 0, 65.4, and 88.2% of the three lagoons were composed of floating ice corresponding with areas of liquid water beneath a layer of ice. The HS model indicated that all three lagoons had reduced suitability as whitefish habitat in winter than in summer due to the loss of habitat because of the presence of bottomfast ice and a reduction in the quality of liquid water due to cold temperatures, high salinities, and low dissolved oxygen levels. However, only the shallowest lagoon had lethal conditions and zero suitability as whitefish habitat. The methods outlined here provide a simple, cost-effective method to identify habitats that consistently provide critical winter habitat and integrate remote sensing in a HS model framework.

Alaska

Advances and applications of Unoccupied Aerial Systems (UAS) research in landscape ecology

Landscape ecologists have long depended on satellite and aerial remote sensing to address questions about landscape pattern and process, structure, and change (Foody 2023 ). Unoccupied aerial systems/vehicles (UAS/UAV, a.k.a. drones) technology is becoming an increasingly popular research tool in environmental sciences allowing scientists to generate low-cost, high-quality, and high-resolution imagery on demand that can be tailored to specific research questions. While satellite data are of a fixed resolution and temporal interval, UAS offer researchers control and flexibility to design studies and collect data at resolutions and scales that provide ecologically relevant information at finer spatial resolutions (e.g., < 30 cm) than what is currently available from satellite platforms (typically > 3m), thus helping capture objects such as individual plant canopies, micro-topography, and individual animals. Unlike satellites with fixed orbits, UAS can be deployed at more optimal temporal frequencies for ecological monitoring. We organized the special collection “Advances and Applications of Unoccupied Aerial Systems (UAS) Research in Landscape Ecology” to showcase the many ways that UAS tools and technologies are currently applied to advance landscape ecological research. When we announced the collection in 2023, only 11 papers published in the journal Landscape Ecology used UAS data, which was a notably small number compared to many other general ecology, environmental science and remote sensing journals. In an attempt to understand why UAS were not more widely used in landscape ecology and provide possible solutions, we published a review article (Villarreal et al. 2025) that identified the challenges, knowledge gaps, and obstacles for the adoption of UAS technologies in landscape ecology research. The main issues we identified include: (1) an abundance of UAS methods papers in the existing literature, with comparatively few studies demonstrating how UAS can be applied to address ecological questions; (2) a perceived scale mismatch between the geographic extent of UAS data collection (local) compared to larger study areas (landscapes) and a need to design robust scaling approaches to connect fine-scale UAS data with broader ecological patterns; and (3) a need for improved integration of UAS data with other commonly used remote sensing datasets including historical high resolution aerial imagery. Additionally, researchers new to UAS remote sensing may be discouraged or overwhelmed by the general lack of scientific consensus and standardized protocols for typical tasks such as data collection, vegetation classification, and change detection, as well as restrictive and/or confusing policy, regulatory, and legal issues surrounding UAS operations (Villarreal et al. 2025).

Landscape Ecology

Estimating domestic self-supplied water use in Rhode Island, 2014–21

Water withdrawal from private groundwater wells is often unaccounted for in water planning studies, and water from private wells can be a source of exposure to environmental contaminants. The sizes of populations that depend on private wells for domestic water use and the amounts of water that are withdrawn from these wells are generally poorly represented in data collection efforts because of the challenges of locating, metering, or gathering withdrawal information from individual property owners. To address this problem, the U.S. Geological Survey, in cooperation with the Rhode Island Water Resources Board, estimated the volume of water withdrawn from domestic self-supply wells and the populations who use them for the State of Rhode Island at a 30-meter pixel spatial resolution and one-month temporal resolution between July 2014 and June 2021. The number of people reliant on domestic self-supply wells has increased in Rhode Island over the study period; however, the statewide estimate of total water withdrawal has not statistically increased. Withdrawals from private wells are largest in the inland areas of the western part of the State, and the towns of Scituate and Charlestown have the highest estimated withdrawals. Statewide monthly withdrawals ranged from 3.987 million gallons per day in March 2018 to 7.767 million gallons per day in September 2016. The median per capita domestic water use rate was 46.0 gallons per capita per day.

Rhode Island

The challenge and opportunity of recovering wolf populations

The gray wolf once inhabited a wide variety of habitats throughout most of the northern hemisphere north of 20°N latitude. Because the animal preyed on livestock and competed with humans for wild prey, it was extirpated from much of its range outside of wilderness areas. Environmental awareness in the late 1960s brought for the wolf legal protection, increased research, and favorable media coverage. The species has increased in both Europe and North America, is beginning to reoccupy semiwilderness and agricultural land, and is causing increased damage to livestock. Because of the wolf's high reproductive rate and long dispersal tendencies, the animal can recolonize many more areas. In most such areas control will be necessary, but the same public sentiments that promoted wolf recovery reject control. If wolf advocates could accept control by the public rather than by the government, wolves could live in far more places. Insistence on government control discourages some officials and government agencies from promoting recovery. The use of large- or small-scale zoning for wolf management may help resolve the issue. Public education is probably the most effective way to minimize the problem and maximize wolf recovery, but the effort must begin immediately.

Conservation Biology

Preface—Evaluating the response of critical zone processes to human impacts with sediment source fingerprinting

1) Background: Critical Zone Processes in the Anthropocene The Earth’s Critical Zone encompasses a suite of interconnected processes in the near-surface lithosphere, pedosphere, biosphere, atmosphere, and hydrosphere (Brantley et al., 2007; Lin, 2010) (Fig. 1). Processes and interactions both within and between these various Critical Zone components supports life-sustaining ecosystem services and resources that establish the foundation for humanity (NRC, 2001). This includes the formation production of fertile soils, flourishing vegetation, productive rivers, lakes and oceans, and our life-sustaining atmosphere (Gaillardet, 2014; Guo and Lin, 2016). Rapid population growth, land use intensification, and global environmental change are disturbing many of these fundamental Critical Zone processes. More than half of the Earth’s terrestrial surface is now impacted by anthropogenic activities (e.g., clearing, grazing, plowing, mining, and logging) (Hooke et al., 2012; Richter and Mobley, 2009). These changes are so widespread and pervasive that the great acceleration of socioeconomic development that occurred around 1950 (Fig. 2) has been recommended to delineate the dawn of the Anthropocene (Waters et al., 2016). Although the utility of adopting and delineating the Anthropocene as the current epoch is subject to debate (Crutzen, 2002; Ruddiman et al., 2015; Smith and Zeder, 2013), the concept effectively highlights both the nature and the extent of our global impact on Earth’s Critical Zone. Soil forming processes and ecosystem services provided by the pedosphere are central to the Critical Zone (Banwart et al., 2011; Lin, 2010). Many of these processes have been disturbed by the agricultural intensification that coincided with the great acceleration resulting in unsustainable land use practices now outpacing soil formation processes (Brantley et al., 2007). As agricultural landscapes now cover an area equivalent to what was scoured during the last glacial maximum (Amundson et al., 2007), the broad-scale intensification of anthropogenic activities has resulted in significant on- and off-site impacts. On-site, soil loss has resulted in decreases in soil fertility and agricultural yields (Ladha et al., 2009) threatening the ability to feed the world’s growing population (Brantley et al., 2007). Off-site, the excess delivery of particulate matter downstream is degrading riverine, lacustrine, and estuarine ecosystems (Bilotta and Brazier, 2008; Clark, 1985; Owens et al., 2005). The challenge, as noted by Brantley et al., (2007), is that despite our society having over 10,000 years of experience working with soils, our conceptual and quantitative models remain inadequate at predicting Critical Zone dynamics under current conditions. Notwithstanding growing pressure for improved environmental management, we still have a limited capacity to predict changes in the Critical Zone in response to anthropogenic activities owing to the multiple spatial and temporal scales at which these complex processes and feedbacks are manifest. As river basin systems are impacted by many of these processes, a deep understanding of soil-sediment continuum dynamics may provide a valuable framework for evaluating the disturbance response of Critical Zone processes. Understanding these processes may also provide land and resource managers with the information necessary to manage both the on-site and off-site effects of accelerated soil erosion.

Journal of Soils and Sediments

Effectiveness of a confinement strategy for reducing campsite impacts in Shenandoah National Park

The expansion and proliferation of backcountry campsites is a persistent problem in many parks and protected areas. Shenandoah National Park (SNP) has one of the highest backcountry overnight use densities in the USA national parks system. SNP managers implemented a multi-option backcountry camping policy in 2000 that included camping containment with established campsites. These actions were intended to reduce the number of campsites and the area of camping disturbance at each site. This paper describes a longitudinal adaptive management assessment of the new campsite policies, applying quantitative measures of campsite conditions to evaluate the efficacy of management interventions. Physical campsite measurements combined with qualitative visitor interviews indicated SNP had successfully reduced the number of campsites and aggregate measures of camping-related disturbance in the Park, while minimizing the use of regulations, site facilities and staff resources. Implications for managers of other protected areas are that an established site camping policy can minimize camping disturbance, including the number and size of campsites, provided managers can sustain rehabilitation efforts to close and restore unneeded campsites. Experiential attributes, such as the potential for solitude, can also be manipulated through control over the selection of established campsites. Integrating resource and social science methods also provided a more holistic perspective on management policy assessments. Adaptive management research provided a timely evaluation of management success while facilitating effective modifications in response to unforeseen challenges. Conclusions regarding the effectiveness of a visitor impact containment strategy involving an established site camping option are offered.

Virginia

A systematic literature review of forecasting and predictive models of harmful algal blooms in flowing waters

Occurrences of harmful algal blooms (HABs) in rivers challenge the belief that rivers are not susceptible to HABs because of their short residence times and fluctuating hydrology. Here we present a systematic literature review of predictive and forecasting models for HABs in flowing waters, including rivers, flowing in-stream reservoirs (e.g., run-of-river reservoirs and lock-and-dam systems) and tidal or estuarine systems with riverine processes. The review aimed to understand current and historical modeling approaches for predicting and forecasting river HABs, without restricting to specific taxa, such as cyanobacteria, or modeling endpoints. The review included 162 articles published over nearly 50 years, covering more than 80 rivers worldwide. Eutrophic, non-wadable rivers with in-stream obstruction were commonly modeled, though diverse environmental characteristics were reported. Most articles used algal biomass or chlorophyll as modeling endpoints, with a quarter using novel or unique endpoints. Algal toxins motivated model development in 23% of the articles, however just 5% used algal toxins as an endpoint. Only 6% of the articles modeled benthic HABs; the rest focused on pelagic HABs. There was no standard model used for modeling river HABs. Process-based models were more common (59%) than data-driven approaches (37%), with model formulations ranging from simple to complex, which contrasts with a lake-focused literature review of HAB models that found data-driven models were more common. Models in river settings shared similar input variables as those previously identified for lakes, such as water temperature, nutrients, and light availability. However, streamflow and other transport metrics took prominence in river models compared to lake models. Algal cell physiology (such as growth, predation, and motility) was routinely included as input data or as mathematical formulations in process-based models and these processes were frequently identified as an important predictor by the articles’ authors. Conversely, data-driven models rarely included these processes, instead using predictors related to environmental conditions, such as nutrients, water quality, water temperature, and streamflow. These important proxy predictors have apparent success with modeling overall algal biomass (irrespective of taxa) whereas other factors, such as those related to algal physiology and other biological processes, are likely responsible for more subtle shifts in community composition. These differences highlight the influence of data availability, especially for processes that are difficult, time-consuming, or expensive to measure, on model development and model outcomes, raising questions about the selection of modeling inputs and endpoints. Challenges to advancing river HAB modeling include the lack of site-specific model inputs representing key processes (e.g., photosynthetic parameters and predation rates), overlooked riverine environments like the benthos and side/back-channel areas, lack of information on environmental settings, and poorly reported model performance metrics. This review emphasizes opportunities for advancing river HAB modeling by learning from well-honed estuarine models, supporting current forecasting and operationalization efforts, and developing common datasets for river HAB model development and evaluation.

BioRxiv

Opportunities and challenges of macrogenetic studies

The rapidly emerging field of macrogenetics focuses on analysing publicly accessible genetic datasets from thousands of species to explore large-scale patterns and predictors of intraspecific genetic variation. Facilitated by advances in evolutionary biology, technology, data infrastructure, statistics and open science, macrogenetics addresses core evolutionary hypotheses (such as disentangling environmental and life-history effects on genetic variation) with a global focus. Yet, there are important, often overlooked, limitations to this approach and best practices need to be considered and adopted if macrogenetics is to continue its exciting trajectory and reach its full potential in fields such as biodiversity monitoring and conservation. Here, we review the history of this rapidly growing field, highlight knowledge gaps and future directions, and provide guidelines for further research.

Nature Reviews Genetics

EthoCRED: A framework to guide reporting and evaluation of the relevance and reliability of behavioural ecotoxicity studies

Behavioural analysis has been attracting significant attention as a broad indicator of sub-lethal toxicity and has secured a place as an important subdiscipline in ecotoxicology. Among the most notable characteristics of behavioural research, compared to other established approaches in sub-lethal ecotoxicology (e.g. reproductive and developmental bioassays), are the wide range of study designs being used and the diversity of endpoints considered. At the same time, environmental hazard and risk assessment, which underpins regulatory decisions to protect the environment from potentially harmful chemicals, often recommends that ecotoxicological data be produced following accepted and validated test guidelines. These guidelines typically do not address behavioural changes, meaning that these, often sensitive, effects are not represented in hazard and risk assessments. Here, we propose a new tool, the EthoCRED evaluation method, for assessing the relevance and reliability of behavioural ecotoxicity data, which considers the unique requirements and challenges encountered in this field. This method and accompanying reporting recommendations are designed to serve as an extension of the “Criteria for Reporting and Evaluating Ecotoxicity Data (CRED)” project. As such, EthoCRED can both accommodate the wide array of experimental design approaches seen in behavioural ecotoxicology, and could be readily implemented into regulatory frameworks as deemed appropriate by policy makers of different jurisdictions to allow better integration of knowledge gained from behavioural testing into environmental protection. Furthermore, through our reporting recommendations, we aim to improve the reporting of behavioural studies in the peer-reviewed literature, and thereby increase their usefulness to inform chemical regulation.

Biological Reviews

Mapping croplands of Europe, Middle East, Russia, and Central Asia using Landsat 30-m data, machine learning algorithms and Google Earth Engine

Accurate and timely information on croplands is important for environmental, food security, and policy studies. Spatially explicit cropland datasets are also required to derive information on crop type, crop yield, cropping intensity, as well as irrigated areas. Large area defined as continental to global cropland mapping is challenging due to differential manifestation of croplands, wide range of cultivation practices and limited reference data availability. This study presents the results of a cropland extent mapping of 64 Countriescovering large parts of Europe, Middle East, Russia and Central Asia. To cover such a vast area, roughly 160,000 Landsat scenes from 3,351 footprints between 2014 and 2016 were processed within the Google Earth Engine (GEE) cloud-platform. We used the pixel-based supervised Random Forest (RF) machine learning algorithm with a set of satellite data inputs capturing diverse spectral, temporal and topographical characteristics across twelve agroecological zones (AEZs). The reference data to train the classification model were collected from very high spatial resolution imagery (VHRI) and ancillary datasets. The result is a binary map showing cultivated/non-cultivated areas ca. 2015. The map produced an overall accuracy of 94 percent with roughly 14 percent omission and commission errors for the cropland class based on a large set of independent validation samples. The map suggests the entire study area has a total 546 million hectares (Mha) of croplands occupying 18 percent of the land area. Comparison between national cropland area estimates from United Nations Food and Agricultural Organizations (FAO) and those derived from this work also showed an R-square value of 0.95. For the entire Landsat-derived 30-m product the overall accuracy was 93.8% with cropland class providing producers accuracy of 86.5% (errors of omissions = 13.5%) and users accuracy of 85.7% (errors of commissions = 14.3%). This Landsat-derived 30-m cropland product (GFSAD30) provided 10-30% greater cropland areas compared to UN FAO in the 64 Countries. Finally, the map-to-map comparison between GFSAD30 with several other cropland products revealed that the best similarity matrix was with the 30m global land cover (GLC30) product providing an overall accuracy of 88.8 percent (Kappa 0.7) with producers cropland similarity of 89.2 percent (errors of omissions = 10.8%) and users cropland similarity of 81.8 percent (errors of commissions = 8.1%). GFSAD30 captured the missing croplands in GLC30 product around significantly irrigated agricultural areas in Germany and Belgium and rainfed agriculture in Italy. This study also established that the real strength of GFSAD30 product, compared to other products, were in: 1. Identifying precise location of croplands, and 2. Capturing fragmented croplands. The cropland extent map dataset is available through NASAs Land Processes Distributed Active Archive Center (LP DAAC) at https://doi.org/10.5067/MEaSUREs/GFSAD/GFSAD30EUCEARUMECE.001, while the training and reference data as well as visualization are available at the Global Croplands website.

ISPRS Journal of Photogrammetry and Remote Sensing

The future of fungi: Threats and opportunities

The fungal kingdom represents an extraordinary diversity of organisms with profound impacts across animal, plant, and ecosystem health. Fungi simultaneously support life, by forming beneficial symbioses with plants and producing life-saving medicines, and bring death, by causing devastating diseases in humans, plants, and animals. With climate change, increased antimicrobial resistance, global trade, environmental degradation, and novel viruses altering the impact of fungi on health and disease, developing new approaches is now more crucial than ever to combat the threats posed by fungi and to harness their extraordinary potential for applications in human health, food supply, and environmental remediation. To address this aim, the Canadian Institute for Advanced Research (CIFAR) and the Burroughs Wellcome Fund convened a workshop to unite leading experts on fungal biology from academia and industry to strategize innovative solutions to global challenges and fungal threats. This report provides recommendations to accelerate fungal research and highlights the major research advances and ideas discussed at the meeting pertaining to 5 major topics: (1) Connections between fungi and climate change and ways to avert climate catastrophe; (2) Fungal threats to humans and ways to mitigate them; (3) Fungal threats to agriculture and food security and approaches to ensure a robust global food supply; (4) Fungal threats to animals and approaches to avoid species collapse and extinction; and (5) Opportunities presented by the fungal kingdom, including novel medicines and enzymes.

G3 Genes, Genomes, Genetics

A network extension of species occupancy models in a patchy environment applied to the Yosemite toad ( Anaxyrus canorus )

A central challenge of conservation biology is using limited data to predict rare species occurrence and identify conservation areas that play a disproportionate role in regional persistence. Where species occupy discrete patches in a landscape, such predictions require data about environmental quality of individual patches and the connectivity among high quality patches. We present a novel extension to species occupancy modeling that blends traditionalpredictions of individual patch environmental quality with network analysis to estimate connectivity characteristics using limited survey data. We demonstrate this approach using environmental and geospatial attributes to predict observed occupancy patterns of the Yosemite toad ( Anaxyrus (= Bufo) canorus ) across >2,500 meadows in Yosemite National Park (USA). A. canorus , a Federal Proposed Species, breeds in shallow water associated with meadows. Our generalized linear model (GLM) accurately predicted ~84% of true presence-absence data on a subset of data withheld for testing. The predicted environmental quality of each meadow was iteratively ‘boosted’ by the quality of neighbors within dispersal distance. We used this park-wide meadow connectivity network to estimate the relative influence of an individual Meadow’s ‘environmental quality’ versus its ‘network quality’ to predict: a) clusters of high quality breeding meadows potentially linked by dispersal, b) breeding meadows with high environmental quality that are isolated from other such meadows, c) breeding meadows with lower environmental quality where long-term persistence may critically depend on the network neighborhood, and d) breeding meadows with the biggest impact on park-wide breeding patterns. Combined with targeted data on dispersal, genetics, disease, and other potential stressors, these results can guide designation of core conservation areas for A. canorus in Yosemite National Park.

California

USGS Environmental Health Program—Per- and polyfluoroalkyl substances (PFAS) science activities [postcard]

Introduction The U.S. Geological Survey (USGS) Environmental Health Program conducts various activities related to PFAS (per- and polyfluoroalkyl substances) to understand their impacts on human health and the environment. Through these activities, the program aims to provide critical information and resources to address the challenges posed by PFAS contamination.

General Information Product

U.S. Geological Survey science vision for native freshwater mussel research in the United States

Executive Summary North America is a global center for native freshwater mussel (order Unionida, hereinafter “mussels”) diversity, with more than 350 species. Mussels are among the most imperiled fauna on the planet. Reasons for both local and widespread declines in mussels are mostly unknown, although the threats may include habitat loss and fragmentation, diseases, environmental contaminants, altered flow regimes, migration barriers to larval hosts, non-native species, and climate change. Over the past three decades, research on mussels has been substantial. Nevertheless, current conservation and management efforts are limited by significant information gaps. For example, the effects of emerging stressors on mussels are largely unknown and identifying when habitats are rehabilitated and suitable for reestablishment of mussels remains challenging. Additionally, historical and current information on the distribution, taxonomy, and life histories are often unreliable or lacking altogether, and more reliable information is needed for many species. We identified focal research themes, goals, and objectives where research on mussels is needed based on information gaps identified through conversations with resource partners across local, regional, and national organizations. Research on biodiversity seeks to enhance the diversity of mussel species and populations to support healthy aquatic ecosystems. Research on emerging stressors seeks to improve the understanding of how mussel species, populations, and communities respond to emerging stressors, including environmental contaminants and climate change. Research on conservation seeks to enhance the recovery of species and populations and to identify data gaps limiting the conservation of mussels and their habitats. Mussels are in urgent need of proactive conservation because they are an integral part of our natural heritage, enhance biodiversity, and provide vital ecological services that support freshwater ecosystems. The U.S. Geological Survey (USGS) has been, and continues to be, a leader in mussel research. Although the USGS is well suited to address the broad-scale multidisciplinary research needed to conserve mussels, the USGS has had substantial loss of scientists with mussel expertise over the past 20 years. However, the breadth of the USGS expertise on mussels can be leveraged internally across other USGS mission and program areas and externally across research partners. Given the breadth and scope of the issues facing mussels across the United States, the research themes outlined in this science vision can only be accomplished through extensive collaborations between the USGS and the full spectrum of natural resource partners, including other Federal and State agencies, Tribal organizations, universities, industries, and nongovernmental organizations.

Circular