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USGS2026

Global framework for communication of biological invasion risks

Biological invasions, driven by the spread of non-native species, have become a critical global issue because of their far-reaching ecological and socioeconomic impacts. Effective communication of the risks of biological invasions is essential for implementing robust policy and legislation and gaining public support for conservation efforts. However, current policies often suffer from fragmentation and ineffectiveness, largely due to inadequate risk communication and complex multilevel governance. To address this challenge, we develop a global framework designed to enhance clearer communication about biological invasion risks. The framework contextualizes key terms across three domains in invasion science: species invasiveness, risk analysis, and decision support tools. Using both diffusion-of-English and ecology-of-language paradigms, and following a three-step process involving preliminary consensus, AI querying, and ground-truthing with final consensus, we validate the framework in 70 non-English languages which, together with English, have official status in at least one country and collectively cover all 195 countries worldwide. Our findings reveal that while terminology for risk analysis is well established, terminology for species invasiveness and, especially, for decision support tools remains underdeveloped in many languages, hindering effective communication and policy implementation. Our framework underscores the importance of cultural and political neutrality. By promoting clearer risk communication among scientists, policymakers, and the public globally, we aim to reduce policy fragmentation and foster enhanced collaboration in risk mitigation. We recommend expanding multilingual decision support tools to include the full risk analysis process: risk identification, risk assessment, and risk management. This will support intergovernmental mitigation efforts and promote a unified global response to biological invasions.

Management of Biological Invasions↗
USGS2026

Sea-level rise in a coastal marsh: Linking increasing tidal inundation, decreasing soil strength and increasing pond expansion

Coastal marsh conversion into ponds, which may be triggered by sea-level rise, is considered an important driver of marsh loss and their valuable ecosystem services. Previous studies have focused on the role of wind waves in driving the expansion of interior marsh ponds, through lateral erosion of marsh edges surrounding the ponds. Here, we propose another mechanism between sea-level rise, increasing marsh inundation, and decreasing marsh soil strength (approximated here as resistance to shear and penetration stress), that further contributes to marsh erosion and pond expansion. Our field measurements in the Blackwater marshes (Maryland, USA), a microtidal marsh system with organic-rich soils, indicate that (1) an increase in tidal inundation time of the marsh surface above a certain threshold (around 50 % of the time) is associated with a substantial loss of strength of the surficial soils; and (2) this decrease in soil strength is strongly related to the amount of belowground vegetation biomass, which is also found to decrease with increasing tidal inundation at pond bottoms, where the soil has a very low strength. Our finding of decreasing marsh soil strength along a spatial gradient of increasing marsh inundation coincides with a gradient of increasing historical marsh loss by pond expansion, suggesting that feedbacks between sea-level rise, increasing marsh inundation and decreasing marsh soil strength combine to amplify marsh erosion and pond expansion.

Maryland↗
USGS2026

Experimental lure design reveals the best attractants for increasing detection of multiple mesocarnivores

Many mesocarnivores have low detection rates that hinder practitioners' abilities to implement effective monitoring strategies. Using olfactory attractants (i.e. lures) may increase detection rates, but variation in effects among species is not well understood. Thus, investigating factors influencing detection of mesocarnivores, can inform and improve monitoring efforts. We evaluated the effects of lures and environmental covariates on the detection of plains spotted skunks Spilogale interrupta , striped skunks Mephitis mephitis , northern raccoons Procyon lotor , gray foxes Urocyon cinereoargenteus , coyotes Canis latrans , bobcats Lynx rufus and Virginia opossums Didelphis virginiana . We conducted surveys during January–May 2023 in southeast Oklahoma using motion-triggered cameras at randomly selected sites. We surveyed sites using a 4-camera cluster and leave-one-out lure design, where 3 cameras were randomly assigned 1 of 4 lures (i.e. skunk-based lure, fatty acid tablets, sweet lure or sardines) and 1 camera was a control (i.e. no lure). We analyzed species-specific detection data within an occupancy framework to determine the influence of lure combinations and environmental covariates (i.e. temperature, precipitation and moon illumination) on site-level detection patterns for each species. When lures influenced detection, we assessed species-specific preference among lures (and the control) within sites by comparing camera-level independent detections with Kruskal–Wallis and Dunn's tests at sites where the species was detected. The effect of lures varied among species; lure combinations influenced site-specific daily detection of plains spotted skunks, striped skunks, gray foxes, raccoons and bobcats, but did not affect detection of coyotes or opossums. One environmental covariate influenced detection of striped skunks (i.e. moon illumination), bobcats (i.e. temperature), and gray foxes (i.e. precipitation). Within sites, lure preference varied among species. Spotted skunks, gray foxes and raccoons preferred sardines whereas striped skunks preferred the skunk-based lure. Identifying lure preferences and effects of environmental factors can help optimize sampling and improve mesocarnivore monitoring efforts.

Oklahoma↗
USGS2026

Teach me how to pycap: A high-capacity well decision support tool using analytical solutions in Python

Regulatory agencies in humid temperate environments rely on timely evaluations of streamflow depletion and drawdown to protect aquatic ecosystems and existing water users. Numerical models offer detailed insights, but their complexity and time demands often preclude their practical use in rapid decision-making. We present pycap-dss, an open-source Python package that implements a suite of analytical solutions for estimating streamflow depletion and drawdown. The tool supports superposition of multiple wells and time-varying pumping, enabling cumulative impact assessments in situations with multiple wells and streams. The software is modular and extensible, allowing users to interchange solutions or add new analytical methods. A YAML-based configuration supports batch processing of multiple wells, and an optional AnalysisProject class facilitates integration with regulatory workflows. Rigorous unit and regression testing ensures computational reliability, and continuous integration supports ongoing development. We demonstrate deterministic examples of drawdown where multiple solutions are readily compared and streamflow depletion with multiple wells in the Central Sands region of Wisconsin. We also show the value of Monte Carlo analyses of streamflow depletion in the same Central Sands example, leveraging computational efficiency to evaluate the uncertainty of individual and cumulative streamflow depletion calculations from over 200 high-capacity wells.

Wisconsin↗
USGS2026

Modeling carbon fluxes in tidal forested wetlands in the Mississippi river deltaic plain under various hydrologic conditions: Implications for river diversions

Our understanding of the impacts of climate change, sea-level rise (SLR), and freshwater management on the magnitude and variability of carbon fluxes in tidal forested wetlands remains limited. In this study, we applied a process-driven wetland biogeochemistry model, Wetland Carbon Assessment Tool—DeNitrification-DeComposition (WCAT-DNDC) model to explore responses of carbon fluxes in tidal swamp forests to climate change-induced alterations in hydrologic conditions and to predict impacts of planned reintroduction of river flows. We selected twelve sites in three habitats (throughput, relict, degraded) inside the Lake Maurepas swamp forests (Louisiana, USA) to represent various hydrological and salinity regimes. Environmental scenarios included dry, average, and wet conditions, SLR (low and high), and a Mississippi River (MR) diversion. Simulation results showed that the responses of net ecosystem exchange (NEE), net primary productivity (NPP), ecosystem respiration (ER), methane (CH 4 ) and nitrous oxide (N 2 O) emissions in the Lake Maurepas swamp forests varied substantially among sites. However, the overall net carbon uptake capacity of the Lake Maurepas swamp forests was high (NEE: − 1143 to − 1650 g C m −2 yr −1 ), suggesting that Lake Maurepas swamp forests are large carbon sinks. The high net carbon uptake capacity could be significantly affected by climate change induced drought, flooding, and SLR with the bi-directional changes (increase or decrease) depending on the direction and magnitude of the hydrologic regime changes. The response of the net carbon uptake capacity to MR diversion is also bi-directional and site-specific, but enhancement of the capacity of NEE of up to − 1957 g C m 2 yr −1 is possible, implying that MR diversion into the swamp forests could be beneficial in the context of carbon cycling and carbon sequestration.

Louisiana↗
USGS2026

Prioritizing resource protection and understanding potential susceptibility of springs to surficial changes in a low-temperature geothermal system

Geothermal systems are vulnerable to changes in water budget and composition, requiring science-based management. This study uses a dataset of spring water temperatures, time series of groundwater residence time tracers (tritium and carbon-14), and stable isotopes of water to understand geothermal flow in a low-temperature geothermal system in north west Colorado, United States (Steamboat Springs). The geothermal system is bisected by the Yampa River, necessitating a stream mass balance approach to quantify total discharge. Time series analysis of water temperature data provides a ranked list of features more susceptible to surficial changes, which is corroborated using time series of tritium which indicate spatially distinct patterns of mixing between modern and pre-modern groundwater. All springs contain a portion of pre-modern groundwater that is thousands to tens of thousands of years old, a period coinciding with melting of extensive Pleistocene glaciers that was likely one of the recharge sources to the geothermal system. Stream mass balance indicates that greater than 80% of the total geothermal discharge is derived from diffuse or small springs, highlighting the extensive nature of the geothermal outflow zone and the association with local geologic structures. This study provides baseline data to support management of the Steamboat Springs geothermal system and indicates the utility of these approaches in developing science-based geothermal management.

Colorado↗
USGS2026

Earthquake-hazard exposure of residents with potential access and functional needs in the United States

Earthquake response plans and earthquake early warning (EEW) systems designed for general populations may not consider potential access and functional needs (AFN) of individuals with physical, sensory, cognitive, or social limitations. Previous efforts to map the distribution of these populations have focused on social-vulnerability indices that ignore or oversimply these limitations. The descriptive and exploratory analysis summarized in this United States (U.S.) case study addresses this gap by identifying and integrating spatially explicit data for AFN-related residential populations, earthquake hazards, and county and county equivalents for the conterminous U.S., Alaska, Puerto Rico, and Hawaii. We focus on 13 AFN-related attributes that relate to an individual's ability to access information contained in an EEW alert, to understand and process earthquake information or observed ground shaking, and to take self-protective actions based on this information and physical cues of an earthquake. Depending on the demographic attribute, there are millions to tens of millions of U.S. residents with AFN-related attributes in areas considered to have varying likelihoods (2%, 10%, and 50%) of exceedance of a damaging earthquake in the next 50 years. Although these amounts represent low percentages at the national level, the percentage of individuals with AFN-related attributes in many counties and county equivalents substantially exceeds national percentages. No one county, county equivalent, U.S. state, or U.S. territory has the highest percentage of individuals in all AFN-related attributes; therefore, future efforts to increase individual resilience to earthquakes may benefit from understanding the local context of individuals with potential access and functional needs.

International Journal of Disaster Risk Reduction↗
USGS2026

Surface variable‐based machine learning for scalable arsenic prediction in undersampled areas

In the United States, private wells are not federally regulated, and many households do not test for Arsenic (As). Chronic exposure is linked with multiple health outcomes, and risk can change sharply over short distances and with well depth. Coarse maps or sparse sampling often miss exceedances. Most existing models operate at ∼1 km resolution and use groundwater chemistry or detailed geologic logs, which limits their use in undersampled areas where improved guidance is most needed. We overcome these limitations by developing a machine learning model for Minnesota, USA, that predicts As exposure risk using only surficial variables from remote sensing and global data sets. Variables related to surface water hydrology and geomorphology are selected based on mechanistic links that control redox conditions and As mobilization. Local training was essential, and surficial geology variables that are more sensitive to local conditions were needed to maximize model accuracy. The resulting complete model was sufficiently sensitive to generate accurate and detailed risk maps and depth profiles of As concentrations above the 10 μg/L maximum contaminant level. Accuracy depended on local training data density. We identified a training data density of 0.07 wells/km 2 as a practical target for stable county-level performance. Maps of exceedance probabilities highlight priority areas for testing that are particularly important in rural communities that have received less sampling. These results support public health action by guiding where to install wells and where to test them, how much new sampling is needed, and where treatment outreach is most urgent.

Minnesota↗
USGS2026

Extreme Potomac floods at Washington D.C. during the past 500 years

Washington D.C. faces one of the highest 100-year flood risks of any major city along the U.S. East Coast. In addition to storm-surge inundation during hurricanes and nor'easters, water-level observations for Washington are strongly skewed by major floods on the Potomac River. Using geologic and historic records we find new evidence for ice-jam flooding at Georgetown during the Little Ice Age, as recently as 1784, that was up to ∼2x the magnitude of the largest events of the past hundred years (1936, 1942). Over the 19th century (a) human modifications to the Potomac estuary as well as (b) increasingly heavy rainfall and (c) land-clearance in the watershed may have contributed to increasingly frequent large floods at Washington. Early surveys of the U.S. Capitol Building and other local landmarks also suggest sea level on the Potomac estuary at Washington has risen by upwards of 0.7 m (2.2 ft) since the 1790s.

Maryland, Virginia↗
USGS2026

Assessing the influence of conservation implementation on water quality during surface runoff events at edge-of-field monitoring sites located in the Laurentian Great Lakes basin

The Laurentian Great Lakes are a vital freshwater resource in the United States, and nonpoint source (NPS) nutrient pollution, specifically phosphorus (P) and nitrogen (N), from agricultural land use continues to negatively impact water quality throughout the Great Lakes basin. One focus of the Great Lakes Restoration Initiative (GLRI), a mechanism to coordinate conservation efforts in the Great Lakes that began in 2010, is reducing NPS nutrient pollution through the implementation of conservation practices in priority watersheds (Genesee River, Fox River, Maumee River, and Saginaw River). As part of GLRI efforts, the objective of the study presented here was to evaluate the effects of conservation implementation, specifically increasing vegetative cover on fields and in primary flowpaths through perennial or cover crop planting and grassed waterways, on surface-runoff water quality at 12 agricultural fields (six paired and six unpaired) located in priority watersheds. We determined the percentage difference in mean event response variables between the periods before and after conservation implementation at individual sites, describing patterns across sites to synthesize lessons learned from these GLRI evaluations. Generally, we found that mean event flow-weighted concentration (FWC) and yield (kilograms per hectare) decreased for suspended sediment (SS) and nitrate (NO 3 – -N) across many sites. Mean event FWC and yield for total P (TP) showed mixed results across sites, while mean event FWC and yield for orthophosphate generally increased across sites. These results indicate that perennial or cover crop planting and grassed waterways effectively reduce SS and NO 3 – -N losses in surface runoff from agricultural fields, but mitigating TP and dissolved P losses remains a challenge.

Laurentian Great Lakes basin↗
USGS2026

Year-round daytime pCO2 undersaturation in an instream series of urban reservoirs with a history of harmful algal blooms

Daytime water quality was determined monthly over two years in an instream series of four urban reservoirs with recurring blooms of Prymnesium parvum —a cool-season toxigenic species. Temperature, pH, and laboratory-measured total alkalinity were used to estimate p CO 2 . System-wide, p CO 2 was negatively associated with dissolved oxygen. Chlorophyll- a , phycocyanin (cyanobacterial pigment), and P. parvum were negatively associated with p CO 2 and positively with dissolved oxygen. Three reservoirs were productive and, during daytime, p CO 2 -undersaturated year-round or near-year-round, while a fourth (third in the series) was unproductive and mostly p CO 2 -oversaturated. Seasonal phycocyanin and chlorophyll- a patterns indicated that cyanobacterial and eukaryotic ( P. parvum included) phytoplankton growth drives daytime CO 2 depletion in the productive reservoirs during the warm and cool seasons, respectively. The system’s moderate alkalinity (HCO 3 − ) may serve as an alternative carbon source for photosynthesis; however, the persistent depletion of CO 2 and the energetic cost of using HCO 3 − are consistent with a scenario where phytoplankton growth is CO 2 -limited. Daytime p CO 2 undersaturation across seasons has been rarely reported, but this study indicated it occurs more often than recognized. The non-monotonic spatial patterns in productivity and carbonate system conditions across the study reservoirs indicate that localized influences from a heterogeneous urban landscape may help shape individual lake metabolism.

Texas↗
USGS2026

Waterfowl move less in heterogeneous and human-populated landscapes, with implications for spread of avian influenza viruses

Animal movements contribute to the spread of infectious diseases and are driven in part by environmental conditions. We investigated the links among the environment, animal movement, and infectious disease dynamics in waterfowl, which are among the primary wildlife hosts of avian influenza viruses. By combining telemetry data on 4606 individuals from 26 waterfowl species with data on land cover, weather, and vegetation, we found that waterfowl moved less in areas of higher land cover heterogeneity and higher human population density. Moreover, predicted waterfowl movement distances were weakly but positively correlated with distances between detections of H5N1 highly pathogenic avian influenza in wild waterfowl, suggesting that environmental conditions might contribute to the spread of this disease via their effects on bird movements. By considering wildlife movements alongside other drivers of infectious disease dynamics, such as livestock production and human mobility, we move closer to predicting outbreaks and informing interventions.

Ecology Letters↗
USGS2026

Linking community-climate disequilibrium to ecosystem function

Turnover in species composition often lags behind the pace of climate change, resulting in mismatches between climate and communities. However, the impact of these community-climate disequilibria on ecosystem functions is rarely considered, and current methods for measuring disequilibria assume that species ranges were, until recently, in equilibrium with climate. Here, we develop a simple theoretical model to address both of these problems by linking community-climate disequilibrium with ecosystem functioning. We show how disequilibrium can impair functioning in the near-term even when climate change is expected to enhance functioning in the long-term. Responses are most likely to change over time in communities where turnover is slow, the impact of disequilibrium counteracts the direct effects of climate on ecosystem function, and pre-existing disequilibrium is large. These findings emphasise the importance of precise and unbiased estimates of community-climate disequilibria for improving ecological forecasts. By fitting our model to time series of both climate and ecosystem function from a metacommunity simulation, we show the potential for community-climate disequilibrium to be inferred without direct knowledge about species' distributions or climatic tolerances. We end by outlining a research agenda to apply dynamic disequilibrium concepts and test novel hypotheses across diverse ecosystems.

Ecology Letters↗
USGS2026

A conceptual framework and methods for studying the connectivity of fishes

Connectivity is a multifaceted concept that has important implications for the management and conservation of marine and freshwater fishes. We developed a conceptual framework that encompasses multiple, interrelated categories of connectedness, including landscape (e.g., structural, functional) connectivity and ecological (e.g., trophic, genetic, demographic) connectivity, that together shape the flow of organisms, energy and information across ecosystems. We also synthesised six key methods that can be used to study connectivity of fishes: (1) telemetry, including satellite, acoustic, radio and passive integrated transponders (PIT), (2) mark-recapture, (3) environmental tracers, including stable isotopes and otolith-microchemistry, (4) genetics, (5) community structure analysis and (6) emerging technologies and tools (e.g., remote sensing and artificial intelligence). For each method, we describe the categories of connectivity it can assess and provide real-world examples where they have been effectively used. We also identify limitations of each method. This article highlights the diverse and evolving toolbox of methods used to assess fish connectivity, underscoring the need for continued collaboration, innovation and integration of new approaches to refine our understanding and address remaining challenges in this critical area of aquatic ecology and fisheries management.

Fish and Fisheries↗
USGS2026

The development of long-term mean annual total nitrogen and total phosphorus load models for Mississippi, U.S., using RSPARROW

Water-quality degradation from nutrient pollution remains a major challenge for resource managers. Developing effective strategies requires tools to characterize nutrient sources and transport. This study used the RSPARROW framework to develop and assess new, smaller-scale models for Total Nitrogen (TN) and Total Phosphorus (TP) transport across Mississippi (MS). These state-level models were built using 15 years (2005–2020) of observation data and considered variables including multiple nutrient sources, land characteristics, and attenuation processes. The MS models demonstrated comparable accuracy to larger regional SPARROW models, validating the use of smaller-scale models for local management. Results showed agricultural sources are the major contributors to TN, dominated by fertilizer in northern MS and livestock manure in the south. Urban land cover also significantly influenced TN and was the second most significant source of TP, following geologic material (background P). Fertilizer and manure were also important TP sources. This study provides valuable, spatially explicit data on nutrient distribution in MS streams, supporting the state’s nutrient reduction planning. It concludes by highlighting the need for future model improvements via updated source data and mean annual flow estimates.

Alabama, Georgia, Louisiana, Mississippi, North Ca↗
USGS2026

Mountain goat declines in a protected, interior, native population

A shifting climate poses threats to alpine-adapted species including mountain goats. We used long-term (12 years) citizen science monitoring data and Bayesian N-mixture modeling to estimate population trends and drivers of population metrics among mountain goats in Glacier National Park (GNP). Median goats per site ( n = 37 sites) declined by 45% (95% credible interval [CRI] = 32%, 57%) from 77.8 (95% CRI = 64.4, 95.1) in 2008 to 42.3 (95% CRI = 34.3, 52.2) in 2019, with consistent declines from 2008 until 2015, when the number of estimated goats stabilized. The decline exceeds IUCN criteria for classifying a population as vulnerable, >30% declines over only two generations. Across years, relatively few goats occupied northwestern GNP. Goat numbers declined the most at northeastern sites, trended toward decline in most southern sites, and increased at only two west-central sites. The proportion of permanent snow and glaciers, the presence of natural mineral licks, and habituation strongly increased the initial abundance of goats in the area. Weather variables had the greatest influence on population growth rates, particularly precipitation between May 15 and June 15 of the previous summer, the neonatal period. Lower growth occurred with less snow water equivalent and lower mean winter temperature, early summer temperature, and early summer precipitation. Projected reductions of permanent snow, increasing spring and summer temperatures, and insufficient and variable spring precipitation raise concerns for the future of native goats in this region. Our analyses reveal ways to improve detection rates of goats during surveys, which is important for optimizing the precision of estimates and the power to detect future trends. Detection increased with goat habituation, retention of observers with experience, use of binoculars, and conducting surveys at lower temperatures and earlier dates. Improving detection will be particularly important given the lower number of goats currently observed in the park. Research to estimate park-wide population size, evaluate genetic structure and diversity, assess changing habitat, human recreation levels and forage, and forward-project climate effects on persistence will be crucial to understanding the context of these results and conserving this iconic, metapopulation at the southern edge of the distribution of native mountain goats.

Montana↗
USGS2026

Best practice guidelines for targeted environmental DNA-based proficiency testing in non-regulatory contexts

The effective use of environmental DNA (eDNA) tools is contingent on strict adherence to established and validated methods. Differences in eDNA methods and quality assurance protocols may contribute to variability in results. However, quality assurance measures such as proficiency testing can provide independent evaluation of laboratory performance against pre-established test criteria. With this commentary, we discuss how broad implementation of recurring proficiency testing in eDNA laboratories can build decision-maker confidence in eDNA results. It can also create a culture of continuous evaluation and improvement that minimizes error and meets performance requirements to inform the sustainable use or monitoring of natural resources. We provide an overview of proficiency testing across molecular disciplines, review the state of proficiency testing in eDNA applications, and draft a roadmap for the expanded application of proficiency testing informed by best practices for targeted eDNA detection. We suggest that best practice proficiency testing can be conducted by an independent, third-party sample provider. By demonstrating that laboratories are competent and capable of producing reliable results, implementation of proficiency testing best practices should foster confidence in eDNA measurements and its use in decision-making processes. Increased confidence in eDNA methods and a clear expectation of what is considered satisfactory performance are also likely to create more favorable conditions for investments in eDNA-based monitoring.

Environmental DNA↗
USGS2026

Microtextural characteristics of adularia in banded quartz veins from the Midas low-sulfidation epithermal deposit, Nevada

High-grade ores at the Miocene Midas low-sulfidation epithermal deposit in northern Nevada are confined to crustiform quartz veins containing abundant adularia. Micro-X-ray fluorescence elemental mapping reveals that adularia is a common gangue mineral occurring in colloform bands, bands showing bladed textures, and bands with dendritic terminations. The adularia aggregates have delicate shapes and are comprised of stacked, submillimeter crystals hosted by fine-grained quartz. The textural evidence suggests that the adularia aggregates originally formed within a gel-like, noncrystalline silica matrix, which subsequently transformed into quartz. This indicates that the adularia did not precipitate in open space along the vein walls. Correlative microscopy, involving scanning electron microscopy-based automated mineralogy and optical petrography, demonstrates that bands containing abundant adularia are not the primary host to ore minerals. The ore minerals occur in different bands within the crustiform veins, implying that adularia and ore mineral precipitation did not always occur simultaneously. It is hypothesized here that fluid flow at Midas involved intermittent short-lived events of fluid flashing, causing rapid solute supersaturation in the liquid. During each flashing event, different amounts of vapor were produced along a given vein. Compositional differences between adjacent bands in the crustiform quartz veins may, therefore, be linked to variations in the amount of vapor formed during each flash event.

Nevada↗