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Estimation of magnitude and frequency of floods for rural, unregulated streams in and near Virginia and West Virginia

Magnitude and frequency of annual peak streamflows were computed for 813 streamgages on rural, unregulated streams with annual peak streamflow data from 1791 through the 2021 water years in and near Virginia and West Virginia. The study was done in cooperation with the Federal Emergency Management Agency, the West Virginia Department of Transportation, and the Virginia Department of Transportation. Regression equations were developed for estimating flood frequency and magnitude. Twelve regions with homogeneous flood characteristics were identified. Generalized least squares regression equations relating logarithmic-transformed drainage area and peak streamflow were developed for the 0.5, 0.2, 0.1, 0.04, 0.02, 0.01, 0.005, and 0.002 annual exceedance probabilities (AEPs). Drainage area was the only significant variable for all equations. The range of drainage areas used to develop the equations differed for each region; the smallest drainage area in any region was 0.21 square miles (mi 2 ) and the largest drainage area in any region is 2,966 mi 2 . Pseudo coefficient of determination (pseudo- R 2 ) values for regression equations ranged from 0.481 to 0.995 for all regions and AEPs. Performance metrics and diagnostic plots indicated that equations for 11 of the 12 regions showed generally good performance, with pseudo- R 2 values ranging from 0.762 to 0.968 for the 0.01 AEP. The overall average change in at-site 0.01 AEP annual peak streamflows at individual streamgages was 0.5 percent compared to the most recent 2011 Virginia study and 2.3 percent compared to the most recent 2010 West Virginia study. Changes from the previous studies for estimates from regional equations for the 0.01 AEP, solved specifically for a 50 mi 2 basin, ranged from a 30 percent increase to a 45 percent decrease in areas where the previous regions overlapped with the current regions by 750 mi 2 or more. New regional skews were developed using Bayesian weighted least-squares/Bayesian generalized least-squares regression for two skew regions that included the study area. A constant regional skew of 0.50 was computed for streams in Virginia, West Virginia, and Maryland that drain to the Atlantic Ocean. A constant regional skew of 0.048 was computed for streams that drain to the Gulf of America, including streams in Kentucky and Tennessee, most of West Virginia, far southwestern Virginia, and part of western Maryland. About 12 percent of the 418 streamgages with 30 or more gaged peaks had statistically significant (p-value [significance level] less than or equal to 0.05) trends, with 40 of these exhibiting positive trends and 11 exhibiting negative trends. Streamgages with 30 percent or greater development were excluded from regression analyses. A regulation index was developed that accounted for storage and drainage area of dams and drainage area at the streamgage; a value of 0.0040 or more for the regulation index indicates regulated peak streamflow. Frequency analyses were done at 86 streamgages on regulated streams. Regression procedures developed in this study are applicable only to rural, unregulated streams within Virginia and West Virginia with drainage basins that (1) are within the range of drainage areas used to develop the equations for each region, (2) included less than 30 percent of developed area, and (3) had a regulation index less than 0.0040.

Kentucky, Maryland, North Carolina, Ohio, Pennsylv

Reproduction partially compensates for human-caused mortality in a cooperative breeder

Reproductive output can vary widely among mammalian species. There are many drivers that affect reproductive output including evolutionary, environmental, population, social, and individual traits. Although several factors, including human-caused mortality, can affect reproductive output, we generally have a poor understanding of how such factors interact to affect reproduction, particularly in cooperative breeders. Gray wolves ( Canis lupus ) in Idaho, USA, are exposed to annual hunting and trapping. Thus, they are an ideal species to answer questions about how turnover within groups affects reproduction in cooperative breeders. I hypothesized that the reproductive output of wolves would be affected by individual, social, and environmental factors. Contrary to my prediction, mid-summer litter size was positively associated with wolf harvest density, suggesting a compensatory response to harvest in cooperatively breeding gray wolves. Such compensation is only partial, however, and does not fully account for all the individuals lost from harvest. At the very highest harvest densities observed, mean litter size increased nearly 28%. In contrast, mid-summer litter size was negatively associated with multiple breeding in groups, suggesting resource limitation and competition within groups. I show that characteristics associated with harvest and breeding strategies predict variations in litter size in a cooperative breeder.

Idaho

Demonstration, validation, and application of hyperspectral microscopy for the collection of cyanobacterial spectral signatures

Cyanobacterial and other algal blooms are an environmental concern in waterbodies worldwide. While these blooms are a nuisance for recreational activities, they can also be harmful to human and wildlife health when the algae produce and release toxins. Algal community composition can be monitored and analyzed by acquiring hyperspectral images that provide information on various photosynthetic and accessory pigments. Validated, traceable measurements are needed to compare data collected by different hyperspectral instruments. In this proof-of-concept study, we detail the development and validation of a custom hyperspectral microscopy imaging system and assess whether this technology can differentiate between cyanobacteria genera based on differences in their reflectance characteristics. As not all cyanobacteria produce toxins, the ability to distinguish among taxa could be used to identify potential toxin-producers and guide field sampling and further research. Spectral characterization of these taxa contributes to remote sensing efforts to characterize and identify cyanobacterial genera at larger spatial scales.

Oregon

Small earthquake moment magnitude and implications for frequency–magnitude scaling of injection induced earthquakes of the Raton Basin

Accurate estimation of earthquake source parameters—such as moment magnitudes, corner frequencies, and stress drops—is essential for improving seismic hazard assessments and understanding earthquake physics. In this study, moment magnitudes ( M W ) are calculated for 31,581 earthquakes associated with wastewater injection in the Raton Basin (located along the border between northern New Mexico and southern Colorado) between 2016 and 2024 using radiative transfer theory to fit coda decay envelopes. Our results show that it is feasible to estimate moment magnitudes down to M W ~1 with coda envelopes from a small local monitoring network. Significant differences were found between M W and local magnitudes ( M L ) for small earthquakes ( M < 3.0). A linear relationship was optimized to convert M L to M W : M W = 0.7 M L + 0.96 and M W = 0.73 M L + 0.99 (for the events reported by the U.S. Geological Survey), which can be applied in future studies of Raton Basin seismicity. We find that b -values calculated employing different methods and using M L are approximately 1.0, while those using M W range from 1.2 to 1.4. A larger estimate of the b -value could influence interpretations of the statistical behavior of earthquakes associated with injection and consequently seismic hazard assessments based on a magnitude–frequency distribution. The potential differences between local versus moment magnitude-based earthquake statistics should be considered in other seismically active regions.

Colorado, New Mexico

Summary of fish communities in Underwood Creek, Milwaukee, Wisconsin, April 2021

Portions of Underwood Creek in Milwaukee County, Wisconsin were reconstructed beginning in 2010 to allow for improved fish habitat and better management of streamflow during storm events. Four reaches of Underwood Creek were sampled in April 2021 for fish abundance by species to evaluate the status of fish communities after reconstruction efforts were completed. A total of 25 fish species were collected during the April 2021 sampling events. Reach D, a recently restored reach, contained the most fish species (14) and individuals (391). White suckers ( Catostomus commersonii ) were present in three of four reaches, fulfilling one of the success metrics outlined in the Underwood Creek restoration plan. Another success metric, collection of young of year northern pike ( Esox lucius ), was not met in this sampling event. However, spawning steelhead ( Oncorhynchus mykiss ) were observed in several reaches, indicating that reconstruction allowed for suitable habitat and passage for some migratory fish.

Wisconsin

Site response models based on geometric parameters for southern California sedimentary basins

Site response in sedimentary basins is influenced by complex three-dimensional (3D) features, including trapping of seismic waves, focusing of seismic energy and basin resonance. Current ground motion models (GMMs) incorporate basin effects using one-dimensional parameters like V S30 and shear wave velocity isosurface depths, which are limited in capturing lateral and 3D effects. To address these limitations, we develop seismic site response models based on novel parameters that represent multi-dimensional properties of the Los Angeles Basin (LAB) geometry and shear wave velocity. We define a basin shape for the LAB using depth to subsurface geologic interfaces associated with the oldest sedimentary deposits (depth to a particular shear wave velocity horizon, i.e., 1.5 km/s - z 1.5 ) and the depth to the crystalline basement ( z cb ) which are determined using geologic cross sections and community seismic velocity model profiles. We explore a suite of geometric descriptors computed for the LAB and southern California, from which three parameters with the greatest predictive potential are selected and evaluated using empirical ground motion residual analyses in combination with the Boore et al. GMM. The results demonstrate that the zonal heterogeneity index ( ), standard deviation of the absolute difference between z 1.5 and z cb ( ) and standard deviation of z cb ( ) each provide a reduction in site-to-site variability ( ϕ S2S ) of empirical GMMs. The reduction in ϕ S2S is period-dependent, with average decreases of 3%, 26% and 6% for , , and , respectively. Although these reductions are modest from an engineering application perspective, they are statistically significant, underscoring the inherent difficulty in fully characterising complex basin effects. Collectively, these findings indicate that the inclusion of basin-specific geometric parameters yields measurable, albeit incremental, improvements in site response prediction and establishes a framework for the progressive refinement of seismic hazard characterisation within sedimentary basins.

California

Climate change and water quality influence on juvenile Atlantic sturgeon aggregation in the Altamaha River, Georgia

In the summer, juvenile Atlantic sturgeon ( Acipenser oxyrinchus oxyrinchus ) are vulnerable to extreme water quality conditions (i.e., temperature, dissolved oxygen [DO], and salinity) in the estuaries they inhabit. The effects of climate change on Atlantic sturgeon are largely unknown, but it may exacerbate these water quality issues. We used a 20-year dataset from the Altamaha River estuary, Georgia, USA to fit negative binomial mixed-effects models describing the relationship between water quality and catch per net hour of juvenile Atlantic sturgeon. Water temperature and DO were significant positive predictors of catch; salinity and sampling year were significant negative predictors. The interaction between temperature and DO was also significant. Water temperature, salinity, and year were significant in explaining variability in catch. Our modeling results suggest that response to water quality depends on fish age. Next, we used global climate projections to construct future climate scenarios incorporating warming water and increased salinity. By coupling these predictions with catch models, we forecast juvenile Atlantic sturgeon catch as a proxy for distribution. Water temperature increases of 1–5 °C led to predicted catch increases of 5–24%, although this result may be influenced by aggregation behavior or sampling limitations at high temperatures. Salinity increases of 1–2 ppt led to 9–17% decreases in catch, suggesting that saltwater intrusion may limit future Atlantic sturgeon estuarine habitat availability. Our study combines a long-term dataset with a robust statistical modeling approach to offer some of the first insights into future climate change effects on juvenile Atlantic sturgeon’s southern nursery habitats.

Georgia

Using sediment chemical fractions and multivariate statistics on water to identify sources, mobility, and bioavailability of aluminum in the Florida River near Durango, Colorado

The Florida River in southwestern Colorado, USA, flows through the Southern Ute Reservation and is a cultural and water resource to Tribal and non-Tribal communities. High concentrations of total Al, up to 16 400 µg l –1 , have been detected in the Florida River. Elevated Al concentrations in water may affect aquatic organisms’ ability to regulate ions and inhibit respiratory functions. Water chemistry collected during three sampling events in 2022 from the Florida River and two of its tributaries are used here to better understand the spatial distribution, seasonality, and sources of Al concentrations in the Florida River. Streambed sediment and rock chemistry is also used to infer geologic sources of Al in the watershed. A five-stage sequential extraction was performed on streambed sediment and rock samples to help determine Al transport processes. We assessed relations between major and trace elements in water using a principal component analysis, finding that high Al concentrations in the Florida River (>3500 µg l –1 total Al) are caused by the erosion of Al-laden sediments. We used a stepwise multiple linear regression to investigate the relationship between land use and Al concentrations. Land use did not reliably predict Al concentration, though increased streamflow connected to reservoir releases – particularly in the Salt Creek tributary – were found to contribute Al to the Florida River during the irrigation season. In this study, we demonstrate that successful metal source appropriation may be achieved through limited field sampling when performed with sufficient water chemistry analysis, sequential chemical extraction of stream sediments, and statistical and land-use analysis.

Colorado

Ground motions from finite faults with unknown geometry

Earthquake emergency response and loss modeling require accurate models of ground‐motion intensity metrics (IMs), such as those produced by ShakeMap. In the critical minutes and hours after an earthquake, however, knowledge of the earthquake source geometry limits the accuracy of these models, especially in areas where seismic instrumentation is insufficient to constrain the shaking intensity pattern. Previous attempts to overcome this limitation have centered on computing the mean distance metrics from a suite of assumed source geometries. That approach is inadequate with modern ground‐motion models (GMMs) because they typically include terms for the hanging wall effect, depth to top of rupture, and other nonlinear terms. Such approaches also propagate the distance uncertainty through the GMMs and may not properly allocate the additional uncertainty into the between‐ and within‐event components. Here we present Finite‐Fault SIMulation with Mixed Effects Regression (FFSIMMER), a method to address these limitations by computing IM distributions from a suite of rupture realizations that fully accounts for all geometry‐related GMM terms and allows for the separation of the between‐ and within‐event components of the total uncertainty. The accuracy of this method is limited by the available constraints on the source parameters. To address this, FFSIMMER can incorporate constraints based on knowledge of the source, such as the approximate strike and dip based on knowledge of the plate tectonics and focal mechanism of the earthquake. We demonstrate the improvement in accuracy that can be achieved with the 2025 M 7.7 Mandalay, Burma (Myanmar), earthquake by incorporating constraints on the range of plausible source parameters.

Bulletin of the Seismological Society of America

Wavelet Inversion for SliP (WISP): Open-source earthquake slip modeling software

Models of the spatiotemporal evolution of earthquake slip, termed finite-fault models, are a critical component of rapid earthquake and tsunami response, earthquake forecasting, seismic ground-motion estimates, and studies of earthquake kinematics. Here, we detail a newly released finite-fault modeling software, Wavelet Inversion for SliP (WISP), in use at the U.S. Geological Survey’s National Earthquake Information Center (NEIC) and available to the public. WISP version 1.1.0 allows inversion of teleseismic body and surface waves, as well as local strong-motion, static and dynamic Global Navigation Satellite System, and satellite imagery (e.g., Interferometric Synthetic Aperture Radar) observations on single or multiple planar fault segments. The software is used in NEIC rapid response of earthquakes M w ≥ 7, generally resulting in a published model within the first few hours after the event origin time. The rupture location and dimensions are then used as inputs to downstream products to estimate earthquake shaking, predict loss, and model the likelihood of secondary hazards, namely landslides and liquefaction. WISP is also used in research studies to evaluate the characteristics of complex ruptures including multifault ruptures and earthquake doublets, among others. The WISP version 1.1.0 software release is composed of Python-wrapped FORTRAN code to accomplish the inversion procedure. A simple command line interface facilitates ease of use even for those with only a cursory knowledge of Python scripting. WISP version 1.1.0 includes a Jupyter Notebook tutorial demonstrating use of the software for modeling the 2015 M w 8.3 Illapel, Chile, earthquake. In parallel with the tutorial, we demonstrate the typical usage of the WISP software using the M w 8.3 Illapel earthquake example here.

Seismological Research Letters

Design and function of the Autonomous Benthic Imaging and Surveying System (ABISS) for remote sensing of lake and seabed environments

Lake and seabed environments are home to fisheries and other biota that are important to ecosystems and economies, yet these environments and the species that use them are difficult to accurately assess and monitor. Traditional benthic survey techniques, like bottom trawling used by the U.S. Geological Survey, are limited by substrate constraints, poor spatial resolution and precision, and operational depth limits, hindering accurate assessment of benthic species and habitats. In response to these limitations, the U.S. Geological Survey developed the Autonomous Benthic Imaging and Surveying System, a camera system integrated into underwater vehicles, to capture high-resolution images of the lakebed. The system uses color and stereo cameras to collect imagery, which can be analyzed using computational methods to detect organisms and (or) characterize habitat features, such as geologic substrate types. The system has been integrated into autonomous underwater vehicles and into an underwater housing used by self-contained underwater breathing apparatus (SCUBA) divers. Although the engineering of the system was motivated by the need for data collection in the Great Lakes, it has potential to collect high quality data in any aqueous setting with sufficient water clarity and safe operating conditions. The Autonomous Benthic Imaging and Surveying System can operate across diverse depths and light conditions to map and quantify ecological patterns that were difficult or impossible to assess using traditional methods. The Autonomous Benthic Imaging and Surveying System offers the potential for accurate and precise monitoring and assessment of native benthic biota, invasive species, and habitat, potentially providing natural resource managers with improved information to support decision making about benthic resource management.

Great Lakes

Aquatic reflectance derived from Sentinel-2 Multispectral Imager data for inland waters in the conterminous United States

Satellite-based earth observation is a robust tool for tracking change in ecosystems. While terrestrially focused applications of remote sensing have empowered wide adoption for research and management, remote sensing of inland aquatic ecosystems remains comparably nascent. This divergence, in part, stems from the lack of standardized, accessible, and near real-time remotely sensed surface reflectance, atmospherically corrected for aquatic environments. To date, surface reflectance products at national scales and with minimal latency are typically designed exclusively for terrestrial environments. Rectifying this situation can be accomplished by applying aquatic-focused atmospheric correction algorithms independent of those used for terrestrial ecosystems. As a first step to filling this data gap, we present the first national scale, dynamically updated, analysis-ready, aquatic reflectance dataset for inland water derived from Sentinel-2 for the conterminous United States.

conterminous United States

Detecting volcanic deformation in Hawaii using trustworthy multimodal deep learning techniques

Monitoring volcanoes involves a variety of data sources and methods to maintain complete continuity of coverage. Global navigation satellite system (GNSS) and interferometric synthetic aperture radar (InSAR) are commonly used complementary methods to assess the deformation state of a volcano as magma migrates beneath the surface. The amount of data these methods produce, however, is growing rapidly beyond human analysis capabilities and is becoming difficult to manage. Here, we create a novel multimodal deep learning framework to ingest InSAR and GNSS data simultaneously and classify the deformation state of the system. We apply this methodology to Mauna Loa, Hawai‘i given its wealth of InSAR and GNSS data as well as its propensity to deform on multiple timescales. Our model performs with high accuracy and is able to identify both slow and fast deformation from 2015 to 2023. The multimodal nature of our model also allows us to identify the presence of atmospheric noise in InSAR data. Furthermore, we employ explainability algorithms to show that our model is making decisions for the right reasons and to connect complex black-box machine learning mappings to current real-world geodetic interpretations of the Mauna Loa magmatic system.

Hawaii

Trust-building as a keystone activity in beaver-related restoration practice

North American beavers ( Castor canadensis ) are increasingly being used to achieve restoration goals, prompting practitioners to engage with private landowners in efforts to promote beaver coexistence. Through 23 semi-structured interviews with restoration practitioners in Oregon, USA, we explored how practitioners from government agencies, non-governmental organizations (NGOs), service organizations, and private businesses communicate with private landowners about nonlethal beaver management and habitat creation. Using abductive analysis, we identified trust-building as an essential element of restoration practice. Practitioners described 60 tactics for building trust, which we organized using the Shared Foundations model of trust and distrust and the adaptive management cycle to bridge theory with field-based experience. Practitioners also reported navigating tensions between tactics and adapting their approaches to individual landowners and contexts. We argue that trust-building is a craft that can be mastered, propose a potential progression from novice to master trust-builder, and highlight the need for greater attention to trust, relationships, and trust repair in environmental management. Our findings offer a theoretically grounded yet practitioner-informed framework for understanding and improving trust-building efforts in restoration practice.

Oregon

Chronic exposure to waterborne nickel significantly reduced growth of juvenile crayfish (Faxonius virilis)

Crayfish are critical functional components of aquatic ecosystems. Previous research has documented adverse effects of mineral extraction on crayfish. Here, we characterize potential risks of mining-derived waterborne nickel (Ni) to crayfish by documenting the effects of dissolved Ni on growth and food consumption of juvenile virile crayfish ( Faxonius virilis) in a 28-day chronic laboratory exposure. Nominal Ni concentrations ranged from 31.25 to 500 micrograms per liter (µg/L; pH = 7.96 ± 0.20, hardness = 150 ± 1 milligrams per liter as calcium carbonate). Crayfish survival, carapace length, and wet weight were measured. After 28 days of exposure, a 24-h feeding trial was performed to determine differences in food consumption. During the growth trial, 99% of crayfish survived. Change in wet weight and final wet weight were the most sensitive endpoints, with 20% effect concentrations of 24.8 and 22.6 µg/L Ni, respectively. Crayfish exposed to an average of 438 µg/L Ni consumed 41% less, and weighed 65.1% less, than control crayfish. These results suggest chronic, sublethal exposure to waterborne Ni may have negative effects on crayfish growth. Reduced growth and consumption rates in crayfish could have wide-ranging consequences throughout aquatic ecosystems since crayfish are consumers, prey, keystone trophic regulators, and ecosystem engineers. Finally, these results could inform bioenergetics and may be coupled with population models to predict potential changes in population sizes of native and invasive crayfishes.

Ecotoxicology

Tidal forested wetlands can be incorporated into blue carbon conservation and restoration strategies

Purpose of Review Blue carbon is an important concept for environmental policy. Blue carbon strategies (conservation and restoration for carbon gain) have been primarily implemented with mangroves, though are likely to be suitable for other tidal forested wetlands. Here, we discuss the expanding definition of blue carbon encompassing all tidal forested wetlands, synthesize ecological and carbon sink knowledge of tidal forested wetlands, and reflect on key actions in mangrove blue carbon research and implementation that could be applied to other tidal forested wetlands. Recent Findings Conceptually, the blue carbon concept has now expanded beyond traditional coastal vegetated ecosystems to include all tidal wetlands, including tidal forested wetlands. Emerging data on carbon sequestration, emissions, and budgets from around the world now show that many tidal forested wetland ecosystems are carbon sinks at a magnitude similar to mangroves. At the global scale, mangroves have become incorporated into blue carbon strategies rapidly compared to other tidal forested wetlands, facilitated by agenda-setting papers, adequate data addressing concerns on emissions and permanence, the availability of global maps, a clear ecosystem definition, clear accounting and policy frameworks, and international stakeholders who acted as high profile ecosystem advocates, alongside long-term capacity building efforts. This provides a roadmap for implementation in other tidal forested wetlands. Summary Tidal forested wetlands other than mangroves have high potential for blue carbon management. Many tidal forested wetlands share biophysical similarities with mangroves, carbon stocks can be similar, and methane emissions are often no higher. An increasing evidence base, challenging assumptions around greenhouse gas fluxes, and robust engagement with policy actors and frameworks, could increase the use of blue carbon for tidal forested wetland conservation and restoration.

Current Forestry Reports

Communicating darkness: Visitor preferences for dark sky interpretation

Utah parks are attracting an increasing number of visitors due to the quality dark sky viewing opportunities. Despite increasing engagement in nighttime recreation, limited research exists on visitor interest in interpretation for dark skies in state and national parks. Nighttime visitors at nine Utah state and national park units certified as dark sky parks were surveyed to evaluate their preferences for dark sky-related interpretive topics and communication methods. Visitors expressed the strongest interest in astronomy and improving dark sky viewing, with ranger-led programs emerging as the most favored delivery method. National park visitors showed greater interest than state park visitors in self-guided learning formats such as interpretive displays and mobile apps for topics such as dark sky viewing/astronomy and viewing wildlife at night. These findings highlight the benefits of diverse, yet targeted communication strategies to improve visitor experiences of dark skies and foster stewardship of natural darkness in parks.

Utah