Occupancy models have become increasingly popular for species monitoring and assessment, in part, because detection/non-detection data are readily obtained using a variety of methods. Multispecies occupancy models (MSOMs) can yield more accurate parameter estimates than single-species models (SSOMs) with less data through their hierarchical structure, making MSOMs an attractive option when species are hard to detect or when data collection is constrained, leading to sparse datasets. Such constraints may arise from limited sampling resources, but also occur in rare species monitoring or where preliminary results are desired to inform adaptive management. Further, experimental habitat treatments often impose spatial constraints on sampling based on the scale of their implementation. Whether a MSOM outperforms SSOMs depends on the volume of data, characteristics of the ecological community, research goals of a study and how these factors align with modeling assumptions. We performed a simulation study of hypothetical pollinator communities under varying sampling intensities for scenarios in which experimental habitat treatments produced different community-level effects. We fit occupancy models to simulated datasets and assessed model performance. At lower sampling intensities (< 20 spatial replicates and < 4 temporal replicates), MSOM community-level treatment effect estimates were biased. Even at twice this sampling intensity, SSOMs yielded more accurate species-specific effect estimates in treatment effect scenarios with high variance. In some cases, MSOMs can pull species in the tails of distributions too far toward the community mean effect, which risks incorrect conclusions concerning whether treatments help or harm individual species. When quantifying species-specific effects is the main objective, particularly for rarely observed species, SSOMs are more robust to outliers across a range of community response scenarios. Researchers can use this information to inform study design, guide simulation studies and decide whether the higher precision of MSOMs outweighs risks of improperly estimated effects for some species.
","language":"English","publisher":"Wiley","doi":"10.1002/ece3.72315","usgsCitation":"Cotterill, G.G., Keinath, D.A., and Graves, T., 2025, When do single-species occupancy models outperform multispecies models?: Ecology and Evolution, v. 15, no. 11, e72315, 14 p., https://doi.org/10.1002/ece3.72315.","productDescription":"e72315, 14 p.","ipdsId":"IP-178046","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":496936,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.72315","text":"Publisher Index Page"},{"id":496899,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"15","issue":"11","noUsgsAuthors":false,"publicationDate":"2025-11-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Cotterill, Gavin G. 0000-0002-1408-778X","orcid":"https://orcid.org/0000-0002-1408-778X","contributorId":346534,"corporation":false,"usgs":true,"family":"Cotterill","given":"Gavin","middleInitial":"G.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":951037,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Keinath, Douglas A.","contributorId":363056,"corporation":false,"usgs":false,"family":"Keinath","given":"Douglas","middleInitial":"A.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":951038,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Graves, Tabitha A. 0000-0001-5145-2400","orcid":"https://orcid.org/0000-0001-5145-2400","contributorId":202084,"corporation":false,"usgs":true,"family":"Graves","given":"Tabitha A.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":951039,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70273831,"text":"70273831 - 2025 - Topographic, climatic, and age controls on the reworking of volcanic debris avalanche deposits","interactions":[],"lastModifiedDate":"2026-02-05T15:07:01.492317","indexId":"70273831","displayToPublicDate":"2025-11-23T08:01:52","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1109,"text":"Bulletin of Volcanology","active":true,"publicationSubtype":{"id":10}},"title":"Topographic, climatic, and age controls on the reworking of volcanic debris avalanche deposits","docAbstract":"Volcanic debris avalanches have deposited as much as 1000 km3 of largely unconsolidated material on landscapes and remodeled existing drainage networks. The landscape disturbances created by these events pose severe, cascading downstream sedimentation hazards that can require long-term societal management, as demonstrated by decades of observations and ongoing interventions after the deposition of the 1980 debris avalanche of Mount St. Helens (United States). There, post-emplacement sediment yields caused by deposit erosion remain several times above estimated background yield and lakes impounded by the deposit still pose threats of downstream flooding. Despite the length and quality of measurements of the geomorphic evolution and consequent sediment release at Mount St. Helens, the long-term trajectory of drainage network evolution across, and the associated sediment release from, large volcanic debris avalanches remains uncertain. Observations and modeling at Mount St. Helens, however, indicate channel instability can persist many decades and may persist for centuries to millennia. We examined potential influences on the erosion and preservation of volcanic debris avalanche deposits (VDADs) by mapping valley networks developed on 89 VDADs selected from volcanic arcs across the world and spanning a variety of topographic settings and climate regimes. Using the best available topographic data (1 m lidar to 30 m radar-derived data depending on location) and aerial imagery, we estimated the areas of deposits that have been reworked relative to initial deposit footprints as a proxy for post-emplacement erosion. We found that a primary influence on reworking is the topographic confinement of the VDAD: confined, valley-filling deposits are systematically more reworked than unconfined deposits. There is no apparent relationship between deposit age and reworking for valley-filling deposits, indicating that drainage networks on deposits in confined topographic settings like at Mount St. Helens reform rapidly after emplacement. In contrast, our data indicate that the reworking of unconfined deposits has a monotonic positive relationship with age. This observation agrees with a conceptual model of channel formation at Mount Taranaki (New Zealand), which posits that an unconfined VDAD created a topographic high that initially (e.g., 2–8 ky for the Pungarehu formation at Taranaki) diverted erosion to the deposit margins. We found only a weak to moderate relationship between reworking and modern precipitation regimes, which may reflect differences between modern and paleo-precipitation conditions at many of our study sites. We also found no correlation between the size (surface area or volume) of deposits and the degree of reworking. The work presented here implies that downstream cascading sediment hazards from landscape-resetting processes like VDADs (such as thick, extensive pyroclastic flow deposits) depend on the relief and organization of the surrounding landscape.
","language":"English","publisher":"Springer Nature","doi":"10.1007/s00445-025-01914-0","usgsCitation":"Sweeney, K., and Major, J.J., 2025, Topographic, climatic, and age controls on the reworking of volcanic debris avalanche deposits: Bulletin of Volcanology, v. 87, 115, https://doi.org/10.1007/s00445-025-01914-0.","productDescription":"115","ipdsId":"IP-167440","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":499579,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Mount St. Helens","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.35475363838827,\n 46.30537067138167\n ],\n [\n -122.35475363838827,\n 46.11419720033388\n ],\n [\n -121.99492703337631,\n 46.11419720033388\n ],\n [\n -121.99492703337631,\n 46.30537067138167\n ],\n [\n -122.35475363838827,\n 46.30537067138167\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"87","noUsgsAuthors":false,"publicationDate":"2025-11-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Sweeney, Kristin","contributorId":365989,"corporation":false,"usgs":false,"family":"Sweeney","given":"Kristin","affiliations":[{"id":61798,"text":"University of Portland","active":true,"usgs":false}],"preferred":false,"id":955119,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Major, Jon J. 0000-0003-2449-4466 jjmajor@usgs.gov","orcid":"https://orcid.org/0000-0003-2449-4466","contributorId":439,"corporation":false,"usgs":true,"family":"Major","given":"Jon","email":"jjmajor@usgs.gov","middleInitial":"J.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":955120,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70272209,"text":"70272209 - 2025 - Simulation of the impacts of spring fiversions on streamflow in the Strawberry Creek watershed, San Bernardino County, California, using an integrated hydrological model","interactions":[],"lastModifiedDate":"2025-12-19T17:06:16.579717","indexId":"70272209","displayToPublicDate":"2025-11-21T11:02:59","publicationYear":"2025","noYear":false,"publicationType":{"id":27,"text":"Preprint"},"publicationSubtype":{"id":32,"text":"Preprint"},"seriesTitle":{"id":18346,"text":"EarthArXiv","active":true,"publicationSubtype":{"id":32}},"title":"Simulation of the impacts of spring fiversions on streamflow in the Strawberry Creek watershed, San Bernardino County, California, using an integrated hydrological model","docAbstract":"The Strawberry Creek watershed, situated in the San Bernardino Mountains of southern California, features a group of natural springs known as Arrowhead Springs that have been augmented with diversions in the form of sub-horizontal borings and tunnels. Understanding the impact of these structures on streamflow through groundwater capture is crucial for managing surface-water resources in this watershed. In this study we constructed the Strawberry Creek integrated hydrological model (SCIHM) to increase this understanding. The SCIHM is an integrated surface runoff and groundwater model that uses the coupled groundwater and surface-water flow model (GSFLOW), which is based on the integration of the precipitation-runoff modeling system (PRMS) and the modular groundwater flow model commonly called MODFLOW, version MODFLOW-2005 software to simulate surface runoff and infiltration and groundwater flow. The model has three layers, 263 rows, and 176 columns. The model area includes the Strawberry Creek and four adjacent watersheds. The PRMS model was calibrated using two streamflow gaging stations and the GSFLOW model was calibrated to reported spring diversion discharge and a sparse number of groundwater-level measurements. The SCIHM was run with and without diversions active and simulated streamflow was compared, finding that in the headwaters of Strawberry Creek about 35 percent of the diversion flow was captured from base flow.
","language":"English","publisher":"EartharXiv","doi":"10.31223/X5JB2K","usgsCitation":"Ryter, D.W., Hevesi, J.A., and Woolfenden, L.R., 2025, Simulation of the impacts of spring fiversions on streamflow in the Strawberry Creek watershed, San Bernardino County, California, using an integrated hydrological model: EarthArXiv, https://doi.org/10.31223/X5JB2K.","productDescription":"52 p.","ipdsId":"IP-181734","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":497778,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Ryter, Derek W. 0000-0002-2488-626X dryter@usgs.gov","orcid":"https://orcid.org/0000-0002-2488-626X","contributorId":3395,"corporation":false,"usgs":true,"family":"Ryter","given":"Derek","email":"dryter@usgs.gov","middleInitial":"W.","affiliations":[{"id":516,"text":"Oklahoma Water Science Center","active":true,"usgs":true},{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":950446,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hevesi, Joseph A.","contributorId":362410,"corporation":false,"usgs":false,"family":"Hevesi","given":"Joseph","middleInitial":"A.","affiliations":[{"id":36206,"text":"Retired","active":true,"usgs":false}],"preferred":false,"id":950447,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Woolfenden, Linda R.","contributorId":362411,"corporation":false,"usgs":false,"family":"Woolfenden","given":"Linda","middleInitial":"R.","affiliations":[{"id":36206,"text":"Retired","active":true,"usgs":false}],"preferred":false,"id":950448,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70272698,"text":"70272698 - 2025 - Long‐period ground motions from dynamic rupture simulations of large earthquakes on the creeping Hayward–Calaveras–Rodgers Creek fault system","interactions":[],"lastModifiedDate":"2025-12-04T15:30:13.079195","indexId":"70272698","displayToPublicDate":"2025-11-21T09:23:42","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3372,"text":"Seismological Research Letters","onlineIssn":"1938-2057","printIssn":"0895-0695","active":true,"publicationSubtype":{"id":10}},"title":"Long‐period ground motions from dynamic rupture simulations of large earthquakes on the creeping Hayward–Calaveras–Rodgers Creek fault system","docAbstract":"he Hayward, Calaveras, and Rodgers Creek faults in the San Francisco Bay region of California have a high probability of producing a large earthquake in the next decades. Although these faults creep, the creep is insufficient to keep up with their relatively rapid slip rates on their deepest sections, so they have been storing tectonic strain since their last large earthquakes, with the Hayward’s and Rodgers Creek’s more than 150 yr ago. We do not know what the next large Hayward–Calaveras–Rodgers Creek earthquakes will look like or how strongly they will shake the San Francisco Bay region. Harris et al. (2021) used the 3D dynamic (spontaneous) rupture method to simulate large earthquakes on these creeping faults. In this article, we examine the resulting simulated long‐period (T > 1 s) ground shaking from 0 to 50 km distance, for earthquakes nucleating on the Hayward fault and earthquakes nucleating on the Rodgers Creek fault. We compare these simulated long‐period ground motions with the Boore et al. (2014) well‐established empirically based ground‐motion model suitable for the slowest material velocity in our 3D velocity structure. We find that the simulated long‐period ground motions from the creeping‐fault earthquake scenarios produce a reasonable agreement with the empirical expectations if frictional cohesion is included only where it is appropriate.
","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0220250194","usgsCitation":"Harris, R.A., Barall, M., Parker, G.A., and Hirakawa, E.T., 2025, Long‐period ground motions from dynamic rupture simulations of large earthquakes on the creeping Hayward–Calaveras–Rodgers Creek fault system: Seismological Research Letters, https://doi.org/10.1785/0220250194.","ipdsId":"IP-170265","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":497108,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1785/0220250194","text":"Publisher Index Page"},{"id":497053,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Hayward, Calaveras, and Rodgers Creek faults, San Francisco Bay region","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -124,\n 39\n ],\n [\n -124,\n 36\n ],\n [\n -120,\n 36\n ],\n [\n -120,\n 39\n ],\n [\n -124,\n 39\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","edition":"Online First","noUsgsAuthors":false,"publicationDate":"2025-11-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Harris, Ruth A. 0000-0002-9247-0768 harris@usgs.gov","orcid":"https://orcid.org/0000-0002-9247-0768","contributorId":786,"corporation":false,"usgs":true,"family":"Harris","given":"Ruth","email":"harris@usgs.gov","middleInitial":"A.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":951358,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Barall, Michael 0000-0001-7724-8563 mbarall@usgs.gov","orcid":"https://orcid.org/0000-0001-7724-8563","contributorId":271197,"corporation":false,"usgs":true,"family":"Barall","given":"Michael","email":"mbarall@usgs.gov","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":951359,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Parker, Grace Alexandra 0000-0002-9445-2571","orcid":"https://orcid.org/0000-0002-9445-2571","contributorId":237091,"corporation":false,"usgs":true,"family":"Parker","given":"Grace","email":"","middleInitial":"Alexandra","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":951360,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hirakawa, Evan Tyler 0000-0002-5720-0850","orcid":"https://orcid.org/0000-0002-5720-0850","contributorId":295776,"corporation":false,"usgs":true,"family":"Hirakawa","given":"Evan","email":"","middleInitial":"Tyler","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":951361,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70274557,"text":"70274557 - 2025 - Wetter winters, drier summers: Quantifying the change in hydrological response around the Puget Sound area using the wflow_sbm hydrological model and CMIP6 projections","interactions":[],"lastModifiedDate":"2026-03-31T13:53:52.426422","indexId":"70274557","displayToPublicDate":"2025-11-21T08:40:53","publicationYear":"2025","noYear":false,"publicationType":{"id":27,"text":"Preprint"},"publicationSubtype":{"id":32,"text":"Preprint"},"seriesTitle":{"id":18346,"text":"EarthArXiv","active":true,"publicationSubtype":{"id":32}},"title":"Wetter winters, drier summers: Quantifying the change in hydrological response around the Puget Sound area using the wflow_sbm hydrological model and CMIP6 projections","docAbstract":"Climate change is expected to impact hydrological regimes worldwide, including the Pacific Northwest of the United States. This study investigates how climate change will affect river discharge in the Puget Sound region of the State of Washington, with a focus on King and Pierce Counties. We simulated river discharge under historical and future conditions using
the physically based, spatially distributed wflow_sbm hydrological model, which was calibrated and validated against U.S. Geological Survey discharge records. Future forcing was based on an ensemble of six high-resolution CMIP6 climate models, which were bias corrected using empirical quantile mapping. The results indicate a decrease in summer discharges (5–10%) and an increase in winter discharges (5–10%) across the study region. The high discharges (90th percentile) are projected to increase in winter, and the low discharges are projected to decrease in summer, due to shifts in precipitation regimes, snowpack hydrology, and evapotranspiration. However, variability between individual CMIP6 models often exceeds the magnitude of ensemble mean changes, underscoring substantial uncertainty in climate projections and the importance of including multiple climate models in climate change analysis. Furthermore, model consensus increased with elevation, which could be the result of the higher elevation areas being driven by less diverse hydrological processes. These findings highlight potential challenges for regional water management, ecosystem health, and flood risk mitigation in the Puget Sound region under future climate conditions.
Barrier island resilience to climate impacts depends on sediment redistribution between the subaqueous shoreface and subaerial barrier during sea-level rise and storms. However, autogenic interactions between the upper and lower shoreface and their influence on the subaerial barrier are poorly characterized. Here, we explore the influences of various shoreface components on barrier morphology using a model of barrier and shoreface evolution under sea-level rise, the Articulated Barrier Shoreface (ABSF) Model. This reduced-complexity model divides the shoreface into upper and lower shoreface panels that respond independently to sea-level rise and deviations from the equilibrium slope. We couple the ABSF with the Lorenzo-Trueba & Ashton, 2014, https://doi.org/10.1002/2013jf002941 model (LTA), a barrier island evolution model driven by overwash and sea-level rise. Through this coupled framework, we examine the influences of upper and lower shoreface slopes, their respective depths, and sensitivity to wave climate on long-term barrier evolution. Results show that the relative depths of the upper and lower shoreface toes influence barrier response to rising seas, alongside overwash flux and closure depth. Notably, the lower shoreface response to sea-level change lags that of the upper shoreface over decades, diminishing the resilience of the barrier over centennial timescales by slowing the overall barrier response. In fact, the ABSF model predicts barriers will drown faster and more than predicted with a linear shoreface. Results highlight the shoreface as an important sediment reservoir for barrier islands and that differences in upper and lower shoreface responses can reduce barrier resilience to sea-level rise due to limited lower shoreface sediment accessibility.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2025JF008391","usgsCitation":"Palermo, R.E., Miselis, J.L., Ciarletta, D.J., and Wei, E., 2025, Modeling the influence of upper and lower shoreface dynamics on barrier island evolution: JGR Earth Surface, v. 130, no. 11, e2025JF008391, 22 p., https://doi.org/10.1029/2025JF008391.","productDescription":"e2025JF008391, 22 p.","ipdsId":"IP-176281","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":496926,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2025jf008391","text":"Publisher Index Page"},{"id":496791,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"130","issue":"11","noUsgsAuthors":false,"publicationDate":"2025-11-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Palermo, Rose Elizabeth 0000-0002-7438-361X","orcid":"https://orcid.org/0000-0002-7438-361X","contributorId":300046,"corporation":false,"usgs":true,"family":"Palermo","given":"Rose","email":"","middleInitial":"Elizabeth","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":950826,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Miselis, Jennifer L. 0000-0002-4925-3979 jmiselis@usgs.gov","orcid":"https://orcid.org/0000-0002-4925-3979","contributorId":3914,"corporation":false,"usgs":true,"family":"Miselis","given":"Jennifer","email":"jmiselis@usgs.gov","middleInitial":"L.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":950827,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ciarletta, Daniel J. 0000-0002-8555-2239","orcid":"https://orcid.org/0000-0002-8555-2239","contributorId":256700,"corporation":false,"usgs":true,"family":"Ciarletta","given":"Daniel","email":"","middleInitial":"J.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":950828,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wei, Emily A","contributorId":290630,"corporation":false,"usgs":false,"family":"Wei","given":"Emily A","affiliations":[{"id":62462,"text":"University of California San Diego, La Jolla, CA","active":true,"usgs":false}],"preferred":false,"id":950829,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70272190,"text":"pp1890I - 2025 - Spatio-temporal evolution of distributed volcanic fields, case studies—Sierra Chichinautzin and Michoacán-Guanajuato, México","interactions":[{"subject":{"id":70272190,"text":"pp1890I - 2025 - Spatio-temporal evolution of distributed volcanic fields, case studies—Sierra Chichinautzin and Michoacán-Guanajuato, México","indexId":"pp1890I","publicationYear":"2025","noYear":false,"chapter":"I","displayTitle":"Spatio-Temporal Evolution of Distributed Volcanic Fields, Case Studies—Sierra Chichinautzin and Michoacán-Guanajuato, México","title":"Spatio-temporal evolution of distributed volcanic fields, case studies—Sierra Chichinautzin and Michoacán-Guanajuato, México"},"predicate":"IS_PART_OF","object":{"id":70259456,"text":"pp1890 - 2024 - Distributed volcanism—Characteristics, processes, and hazards","indexId":"pp1890","publicationYear":"2024","noYear":false,"title":"Distributed volcanism—Characteristics, processes, and hazards"},"id":1}],"isPartOf":{"id":70259456,"text":"pp1890 - 2024 - Distributed volcanism—Characteristics, processes, and hazards","indexId":"pp1890","publicationYear":"2024","noYear":false,"title":"Distributed volcanism—Characteristics, processes, and hazards"},"lastModifiedDate":"2026-02-03T16:35:11.775005","indexId":"pp1890I","displayToPublicDate":"2025-11-20T11:30:00","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":331,"text":"Professional Paper","code":"PP","onlineIssn":"2330-7102","printIssn":"1044-9612","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1890","chapter":"I","displayTitle":"Spatio-Temporal Evolution of Distributed Volcanic Fields, Case Studies—Sierra Chichinautzin and Michoacán-Guanajuato, México","title":"Spatio-temporal evolution of distributed volcanic fields, case studies—Sierra Chichinautzin and Michoacán-Guanajuato, México","docAbstract":"An analysis of 1,375 volcanoes in the Michoacán-Guanajuato (1,148 volcanoes in a 26,200 square-kilometer area) and Sierra Chichinautzin (227 volcanoes in a 3,500 square-kilometer area) volcanic fields in central Mexico identified patterns in the spatial and temporal distribution of past eruptions. A cluster agglomerative hierarchical method and kernel analysis confirmed that the Michoacán-Guanajuato volcanic field comprises four volcanic fields (Valle de Santiago, Uruapan, Apatzingán, and Pátzcuaro volcanic fields) controlled by different fault systems, indicating that it is not a single volcanic field but rather a group of volcanic fields (a “superfield”), each of which has distinct characteristics.
In the Sierra Chichinautzin volcanic field, well-constrained isotopic ages were used to build a model of how the spatial distribution of the eruptions has changed over time. Two new 40Ar/39Ar ages from a locally recognized volcanic feature near the town of El Cantil, herein called El Cantil volcano (1,537±17 kilo-annum [ka]) and the volcanic feature at Cerro el Elefante (herein called El Elefante dome) (1,485±92 ka) belong to the oldest volcanic group identified in the Sierra Chichinautzin volcanic field, confirming the timing of the beginning of monogenetic volcanism in the region. Based on the volcanic groups identified in the Sierra Chichinautzin volcanic field, the youngest volcanism (less than 35 ka) is found only in the central-western sector of the field. Principal component analysis determined the directional trends of feeder dikes only for vents <10 ka in the Sierra Chichinautzin volcanic field. Possible magma migration paths through the crust were identified using seismic data from both volcanic fields using an earthquake catalog from 1973 to 2023, which includes 9,016 earthquakes in the Michoacán-Guanajuato volcanic field and 841 in the Sierra Chichinautzin volcanic field. The spatial distribution of the hypocenters does not highlight any trend that could be associated with superficial movement of magma in the Sierra Chichinautzin volcanic field. In the Michoacán-Guanajuato volcanic field, however, eight seismic swarms since 1997 have been detected. These swarms are interpreted to result from ascending magma. Strengthening monitoring systems and reinforcing mitigation measures to address volcanic hazards and risk are important means of preparing for future eruptions in both regions. Analysis such as those herein provide insights as to where an eruption might occur and may help mitigate volcanic hazards.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/pp1890I","usgsCitation":"Jaimes-Viera, C., Nieto-Torres, A., Martin Del Pozzo, A.L., Germa, A., Connor, C., Ort, M., Layer, P., and Benowitz, J., 2025, Spatio-Temporal Evolution of Distributed Volcanic Fields, Case Studies—Sierra Chichinautzin and Michoacán-Guanajuato, México, chap. I of Poland, M.P., Ort, M.H., Stovall, W.K., Vaughan, G.R., Conner, C.B., and Rumpf, M.E., eds., Distributed volcanism—Characteristics, processes, and hazards: U.S. Geological Survey Professional Paper 1890, 28 p., https://doi.org/10.3133/pp1890I.","productDescription":"Report: v, 28 p.; 3 Tables","onlineOnly":"Y","ipdsId":"IP-157952","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":496700,"rank":7,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/pp/1890/i/pp1890I.XML"},{"id":496699,"rank":6,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/pp/1890/i/images"},{"id":496625,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/pp/1890/i/coverthb.jpg"},{"id":496626,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/pp/1890/i/pp1890I.pdf","text":"Report","size":"7.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Professional Paper 1890-I"},{"id":496629,"rank":3,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/pp/1890/i/PP1890I_supptable1A.csv","text":"Table 1A","size":"12.0 KB","linkFileType":{"id":7,"text":"csv"},"description":"Professional Paper 1890-I, Table 1A","linkHelpText":"Radiometric (14C and 40Ar/39Ar) ages from volcanoes from Sierra Chichinautzin volcanic field"},{"id":496632,"rank":4,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/pp/1890/i/PP1890I_supptable1B.csv","text":"Table 1B","size":"12.0 KB","linkFileType":{"id":7,"text":"csv"},"description":"Professional Paper 1890-I, Table 1B","linkHelpText":"Estimated and calibrated ages from the volcanoes from Sierra Chichinautzin volcanic field"},{"id":496633,"rank":5,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/pp/1890/i/PP1890I_supptable2.csv","text":"Table 2","size":"80.0 KB","linkFileType":{"id":7,"text":"csv"},"description":"Professional Paper 1890-I, Table 2","linkHelpText":"Location, h/wb ratio and age of main cones in Michoacán-Guanajuato and Sierra Chichinautzin volcanic fields"},{"id":497260,"rank":8,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/pp1890I/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"Professional Paper 1890-I"}],"country":"Mexico","otherGeospatial":"Michoacán-Guanajuato, Sierra Chichinautzin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -99.667,\n 19.333\n ],\n [\n -99.667,\n 18.833\n ],\n [\n -98.5,\n 18.833\n ],\n [\n -98.5,\n 19.333\n ],\n [\n -99.667,\n 19.333\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -104,\n 20.6\n ],\n [\n -104,\n 19\n ],\n [\n -100,\n 19\n ],\n [\n -100,\n 20.6\n ],\n [\n -104,\n 20.6\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Volcano Science Center
U.S. Geological Survey
1300 SE Cardinal Court Bldg. 10
Vancouver, WA 98683
Rare earth elements (REEs) are a scarce but vital resource for our modern economies and lifestyles. Since the late 1990s, China has supplied the vast majority of the world’s refined REEs. Increasing global demand has broadened the search for REE deposits to unconventional places, including the Moon. Although most lunar rocks have very low REE concentrations, Apollo samples showed that one type of lunar rock containing potassium (K), REEs, and phosphorus (P)—known by the acronym KREEP—has high concentrations of REEs. Data from orbiting satellites have identified locations where substantial deposits of KREEP are likely. The viability of mining these deposits depends on the evolution of REE economics, the development of the Earth-Moon infrastructure, and the findings from future lunar mineral exploration missions.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20253049","usgsCitation":"Keszthelyi, L.P., Coyan, J.A., Pigue, L.M., Bennett, K.A., and Gabriel, T.S.J., 2025, Rare earth elements on the Moon: U.S. Geological Survey Fact Sheet 2025-3049, 4 p., https://doi.org/10.3133/fs20253049.","productDescription":"4 p.","numberOfPages":"4","onlineOnly":"N","ipdsId":"IP-177188","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":496650,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2025/3049/fs20253049.pdf","text":"Report","size":"9.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2025-3049 PDF"},{"id":496649,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2025/3049/coverthb.jpg"}],"otherGeospatial":"the Moon","contact":"Astrogeology Science Center
U.S. Geological Survey
2255 N. Gemini Dr.
Flagstaff, AZ 86001
Plasticity of diel activity rhythms may be a key element for adaptations of wildlife populations to changing environmental conditions. In the last decades, grizzly bears Ursus arctos in the Greater Yellowstone Ecosystem (GYE) have experienced notable environmental fluctuations, including changes in availability of food sources and severe droughts. Although substantial research has been conducted on grizzly bear diets, space use, and demographic parameters, studies on factors that may influence their diel activity patterns are lacking. We investigated diel activity of grizzly bears in the GYE as a function of anthropogenic landscape modification, maximum daily ambient temperature, drought severity, and bear density. Specifically, we used accelerometry readings of 169 bears (39 females, 130 males) from 2009 to 2022 to compute three complementary activity measures, hourly intensity of activity, daily active minutes, and active bout length, each used as a response variable within a Bayesian modeling framework. Grizzly bears generally exhibited bimodal diel activity, with crepuscular peaks and slight variations across seasons. Females with young (i.e. cubs or yearlings) were an exception, with more pronounced diurnal activity patterns, possibly as a strategy to avoid infanticide by dominant males. Landscape modification and maximum ambient temperature were the factors most strongly associated with activity patterns of grizzly bears, with greater nocturnality observed in lone females and males as these factors increased. Females with young were comparatively less affected. The GYE is changing because of increasing land development, human recreation pressures, and effects of climate change. Given their greater diurnal activity compared with other cohorts, female grizzly bears with dependent offspring may be more constrained in their ability to modify activity patterns. Our findings add to a growing body of research emphasizing the importance of the temporal dimension of wildlife behavior as a critical factor in assessing species adaptability and vulnerability in a changing world.
","language":"English","publisher":"Nordic Society Oikos","doi":"10.1002/oik.11851","usgsCitation":"Donatelli, A., Haroldson, M., Clapp, J.G., Ciucci, P., and van Manen, F.T., 2025, Bioclimatic, demographic, and anthropogenic correlates of grizzly bear activity patterns in the Greater Yellowstone Ecosystem: Oikos, https://doi.org/10.1002/oik.11851.","ipdsId":"IP-179581","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":497083,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/oik.11851","text":"Publisher Index Page"},{"id":496987,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho, Montana, Wyoming","otherGeospatial":"Greater Yellowstone Ecosystem","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -112.3187629306571,\n 45.33972157168918\n ],\n [\n -112.3187629306571,\n 42.05504689696562\n ],\n [\n -108.71329990703327,\n 42.05504689696562\n ],\n [\n -108.71329990703327,\n 45.33972157168918\n ],\n [\n -112.3187629306571,\n 45.33972157168918\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","edition":"Online First","noUsgsAuthors":false,"publicationDate":"2025-11-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Donatelli, A.","contributorId":358394,"corporation":false,"usgs":false,"family":"Donatelli","given":"A.","affiliations":[{"id":81866,"text":"University of Rome La Sapienza","active":true,"usgs":false}],"preferred":false,"id":951221,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Haroldson, Mark 0000-0002-7457-7676","orcid":"https://orcid.org/0000-0002-7457-7676","contributorId":316737,"corporation":false,"usgs":true,"family":"Haroldson","given":"Mark","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":951222,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Clapp, Justin G.","contributorId":363181,"corporation":false,"usgs":false,"family":"Clapp","given":"Justin","middleInitial":"G.","affiliations":[{"id":36596,"text":"Wyoming Game and Fish Department","active":true,"usgs":false}],"preferred":false,"id":951223,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ciucci, P.","contributorId":358405,"corporation":false,"usgs":false,"family":"Ciucci","given":"P.","affiliations":[{"id":81866,"text":"University of Rome La Sapienza","active":true,"usgs":false}],"preferred":false,"id":951224,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"van Manen, Frank T. 0000-0001-5340-8489 fvanmanen@usgs.gov","orcid":"https://orcid.org/0000-0001-5340-8489","contributorId":2267,"corporation":false,"usgs":true,"family":"van Manen","given":"Frank","email":"fvanmanen@usgs.gov","middleInitial":"T.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":951225,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70274532,"text":"70274532 - 2025 - Quantifying floodplain forest community change following large-scale flood events in the Upper Mississippi River System","interactions":[],"lastModifiedDate":"2026-04-01T16:26:53.395861","indexId":"70274532","displayToPublicDate":"2025-11-20T09:20:20","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Quantifying floodplain forest community change following large-scale flood events in the Upper Mississippi River System","docAbstract":"Effects of large-scale flooding on forest composition and structure are a function of flood duration, depth, timing, and frequency. Throughout the Upper Mississippi River System (UMRS), floods in 1993 and 2019 were record-setting events followed by high rates of tree mortality. These events generated interest in species adaptations to flood event characteristics and how forest communities have changed in response to large-scale floods. We investigated associated tree mortality, how the floods differed spatially, and how floodplain forest communities have changed since 1993. Eight UMRS reaches were surveyed in a 1995 study, documenting vegetation species composition, size, and abundance. In 2021, a selection of plots (63%) were revisited and surveyed to quantify 2019 flood effects. For each site, we extracted daily inundation data for flood years and preceding decades from a surface water inundation model. We found post-flood mortality varied spatially and generally reflected inundation duration patterns. Lower latitude reaches experienced longer inundation durations and greater tree mortality in 1993 than in 2019, while higher latitude reaches experienced similar inundation duration and depth and similar mortality between events. Decadal inundation attributes also differed. During 2009–2018, inundation duration was greater and events occurred later than during 1983–1992 in all reaches. Most forest trajectories were Acer saccharinum-dominated and changed relatively little in species composition and structure. The greatest change in composition occurred at plots with high mortality from the 1993 flood, particularly in more flood-prone locations or where there were many small-diameter individuals. In plots dominated by either Quercus spp. or Populus deltoides, species importance shifted toward more shade and flood-tolerant species after 1995 surveys. Self-replacement of these species may be limited by a change in regeneration conditions resulting from an ongoing inundation regime shift in the case of Quercus spp., or succession to more shade-tolerant species in the case of Populus communities. Overall, effects on floodplain forests from the two flood events were heterogeneous. In some cases, forest change was likely just as influenced by shifts in flood regime as it was from singular flood events.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.70440","usgsCitation":"Weiss, S.A., Guyon, L.J., De Jager, N.R., Cosgriff, R.J., and Van Appledorn, M., 2025, Quantifying floodplain forest community change following large-scale flood events in the Upper Mississippi River System: Ecosphere, v. 16, no. 11, e70440, 25 p., https://doi.org/10.1002/ecs2.70440.","productDescription":"e70440, 25 p.","ipdsId":"IP-168280","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":502048,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.70440","text":"Publisher Index Page"},{"id":501951,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Illinois, Iowa, Minnesota, Missouri, Wisconsin","otherGeospatial":"Upper Mississippi River System","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -92.95959025406495,\n 44.864528650415735\n ],\n [\n -91.03900071075344,\n 42.05364635279252\n ],\n [\n -91.77356103532435,\n 40.00507367513167\n ],\n [\n -90.02194205702455,\n 36.004010100510584\n ],\n [\n -88.88384187139445,\n 36.26259089451513\n ],\n [\n -90.52583463005158,\n 39.94132189789401\n ],\n [\n -89.73636511669805,\n 42.189192561781\n ],\n [\n -91.24649150402311,\n 45.075229707941105\n ],\n [\n -92.95959025406495,\n 44.864528650415735\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"16","issue":"11","noUsgsAuthors":false,"publicationDate":"2025-11-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Weiss, Shelby A.","contributorId":368922,"corporation":false,"usgs":false,"family":"Weiss","given":"Shelby","middleInitial":"A.","affiliations":[{"id":55549,"text":"National Great Rivers Research and Education Center","active":true,"usgs":false}],"preferred":false,"id":958115,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Guyon, Lyle J.","contributorId":215690,"corporation":false,"usgs":false,"family":"Guyon","given":"Lyle","email":"","middleInitial":"J.","affiliations":[{"id":36894,"text":"Illinois Natural History Survey","active":true,"usgs":false}],"preferred":false,"id":958116,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"De Jager, Nathan R. 0000-0002-6649-4125 ndejager@usgs.gov","orcid":"https://orcid.org/0000-0002-6649-4125","contributorId":3717,"corporation":false,"usgs":true,"family":"De Jager","given":"Nathan","email":"ndejager@usgs.gov","middleInitial":"R.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":958117,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cosgriff, Robert J.","contributorId":215692,"corporation":false,"usgs":false,"family":"Cosgriff","given":"Robert","email":"","middleInitial":"J.","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":958118,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Van Appledorn, Molly 0000-0002-8029-0014","orcid":"https://orcid.org/0000-0002-8029-0014","contributorId":205785,"corporation":false,"usgs":true,"family":"Van Appledorn","given":"Molly","email":"","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":958119,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70272760,"text":"70272760 - 2025 - Structural controls on splay fault rupture dynamics during Cascadia megathrust earthquakes","interactions":[],"lastModifiedDate":"2025-12-08T16:27:04.053909","indexId":"70272760","displayToPublicDate":"2025-11-20T09:20:07","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7751,"text":"AGU Advances","active":true,"publicationSubtype":{"id":10}},"title":"Structural controls on splay fault rupture dynamics during Cascadia megathrust earthquakes","docAbstract":"Great subduction earthquakes (Mw ≥ 8.0) can generate devastating tsunamis by rapidly displacing the seafloor and overlying water column. These potentially tsunamigenic seafloor offsets result from coseismic fault slip and deformation beneath or within the accretionary wedge. The mechanics of these shallow rupture phenomena and their dependence on subduction zone properties remain unresolved, partly due to the sparsity of offshore observations of shallow megathrust earthquake deformation. Here, we analyze how offshore structure influences shallow rupture mechanics and slip partitioning using 3D dynamic earthquake simulations of the Cascadia subduction zone (CSZ) megathrust with and without variably dipping seaward- or landward-vergent splay faults in the wedge that sole into the megathrust. Resulting tradeoffs between splay and megathrust slip reveal structural controls on rupture partitioning, with greater splay slip leading to less shallow megathrust slip updip. Gently dipping and seaward-vergent splays host more slip than those with steeper, landward-vergent splays. To isolate the underlying mechanisms, we compare models with Andersonian and plunging principal stresses. Results suggest distinct static and dynamic processes control the dip- and vergence-dependence of splay rupture: static (mis)alignment relative to far-field tectonic loading favors slip on more optimally oriented, shallowly dipping splay faults. In contrast, dynamic stress interactions of an updip-propagating megathrust rupture front with the free surface and potential branch faults favor forward branching onto seaward-vergent splays and inhibit backward branching onto landward-vergent splays. Resulting seafloor displacements suggest splay fault structure may influence coseismic tsunami source processes, highlighting the importance of dynamically viable rupture scenarios in subduction hazard assessments.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2025AV001812","usgsCitation":"Biemiller, J.B., Gabriel, A., Staisch, L.M., Ulrich, T., Dunham, A., Wirth, E.A., Watt, J., Lucas, M.C., and Ledeczi, A., 2025, Structural controls on splay fault rupture dynamics during Cascadia megathrust earthquakes: AGU Advances, v. 6, no. 6, e2025AV001812, 22 p., https://doi.org/10.1029/2025AV001812.","productDescription":"e2025AV001812, 22 p.","ipdsId":"IP-178619","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":497403,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2025av001812","text":"Publisher Index Page"},{"id":497199,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","otherGeospatial":"Cascadia subduction zone","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -129.06174594550313,\n 50.792270218333016\n ],\n [\n -123.78891671425012,\n 35.05484640084913\n ],\n [\n -120.83491668887615,\n 36.08348722338981\n ],\n [\n -121.77409533925982,\n 45.94148964580287\n ],\n [\n -124.46022466182565,\n 51.84936657852123\n ],\n [\n -129.06174594550313,\n 50.792270218333016\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"6","issue":"6","noUsgsAuthors":false,"publicationDate":"2025-11-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Biemiller, James Burkhardt 0000-0001-6663-7811","orcid":"https://orcid.org/0000-0001-6663-7811","contributorId":343684,"corporation":false,"usgs":true,"family":"Biemiller","given":"James","email":"","middleInitial":"Burkhardt","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":951617,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gabriel, Alice-Agnes","contributorId":204611,"corporation":false,"usgs":false,"family":"Gabriel","given":"Alice-Agnes","email":"","affiliations":[{"id":36958,"text":"LMU Munich, Germany","active":true,"usgs":false}],"preferred":false,"id":951618,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Staisch, Lydia M. 0000-0002-1414-5994 lstaisch@usgs.gov","orcid":"https://orcid.org/0000-0002-1414-5994","contributorId":167068,"corporation":false,"usgs":true,"family":"Staisch","given":"Lydia","email":"lstaisch@usgs.gov","middleInitial":"M.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":951619,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ulrich, Thomas","contributorId":204613,"corporation":false,"usgs":false,"family":"Ulrich","given":"Thomas","email":"","affiliations":[{"id":36958,"text":"LMU Munich, Germany","active":true,"usgs":false}],"preferred":false,"id":951620,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dunham, Audrey 0000-0001-9719-9287","orcid":"https://orcid.org/0000-0001-9719-9287","contributorId":361490,"corporation":false,"usgs":true,"family":"Dunham","given":"Audrey","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":951621,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wirth, Erin A. 0000-0002-8592-4442","orcid":"https://orcid.org/0000-0002-8592-4442","contributorId":207853,"corporation":false,"usgs":true,"family":"Wirth","given":"Erin","middleInitial":"A.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":951622,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Watt, Janet 0000-0002-4759-3814","orcid":"https://orcid.org/0000-0002-4759-3814","contributorId":221271,"corporation":false,"usgs":true,"family":"Watt","given":"Janet","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":951623,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Lucas, Madeleine C.","contributorId":336741,"corporation":false,"usgs":false,"family":"Lucas","given":"Madeleine","middleInitial":"C.","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":951624,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Ledeczi, Anna","contributorId":336740,"corporation":false,"usgs":false,"family":"Ledeczi","given":"Anna","email":"","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":951625,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70272630,"text":"70272630 - 2025 - Systematic approach to prioritize wells for effective groundwater monitoring and management in the Arkansas Headwaters Basin, Colorado, USA","interactions":[],"lastModifiedDate":"2025-11-26T15:19:53.684111","indexId":"70272630","displayToPublicDate":"2025-11-20T09:11:16","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3823,"text":"Journal of Hydrology: Regional Studies","active":true,"publicationSubtype":{"id":10}},"title":"Systematic approach to prioritize wells for effective groundwater monitoring and management in the Arkansas Headwaters Basin, Colorado, USA","docAbstract":"In recent years, Single-Image Super-Resolution (SISR) has gained significant attention in the geoscience and remote sensing community for its potential to improve the resolution of low-quality underwater imagery. This paper introduces MIMAR-Net (Multiscale Inception-based Manhattan Attention Residual Network), a new deep learning architecture designed to increase the spatial resolution of input color images. MIMAR-Net integrates a multiscale inception module, cascaded residue learning, and advanced attention mechanisms, such as the MaSA layer, to capture both local and global contextual information effectively. By utilizing multiscale processing and advanced attention strategies, MIMAR-Net allows us to handle the complexities of underwater environments with precision and robustness. We evaluate the model on three popular underwater image datasets, namely UFO-120, USR-248, and EUVP, and perform extensive comparisons against state-of-the-art methods. Experimental results demonstrate that MIMAR-Net consistently outperforms existing approaches, achieving superior qualitative and quantitative improvements in image quality, making it a reliable solution for underwater image enhancement in various challenging scenarios.
","language":"English","publisher":"MDPI","doi":"10.3390/electronics14224544","usgsCitation":"Zahan, N., Paheding, S., Saleem, A., Havens, T.C., and Esselman, P., 2025, MIMAR-Net: Multiscale Inception-based Manhattan Attention Residual Network and its application to underwater image super-resolution: Electronics, v. 14, no. 22, 4544, 24 p., https://doi.org/10.3390/electronics14224544.","productDescription":"4544, 24 p.","ipdsId":"IP-175539","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":496934,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/electronics14224544","text":"Publisher Index Page"},{"id":496897,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"14","issue":"22","noUsgsAuthors":false,"publicationDate":"2025-11-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Zahan, Nusrat","contributorId":363057,"corporation":false,"usgs":false,"family":"Zahan","given":"Nusrat","affiliations":[{"id":86604,"text":"Fairfield University","active":true,"usgs":false}],"preferred":false,"id":951040,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Paheding, Sidike","contributorId":347829,"corporation":false,"usgs":false,"family":"Paheding","given":"Sidike","affiliations":[{"id":16203,"text":"Michigan Technological university","active":true,"usgs":false}],"preferred":false,"id":951041,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Saleem, Ashraf","contributorId":347827,"corporation":false,"usgs":false,"family":"Saleem","given":"Ashraf","affiliations":[{"id":16203,"text":"Michigan Technological university","active":true,"usgs":false}],"preferred":false,"id":951042,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Havens, Timothy C.","contributorId":363058,"corporation":false,"usgs":false,"family":"Havens","given":"Timothy","middleInitial":"C.","affiliations":[{"id":16203,"text":"Michigan Technological university","active":true,"usgs":false}],"preferred":false,"id":951043,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Esselman, Peter C. 0000-0002-0085-903X","orcid":"https://orcid.org/0000-0002-0085-903X","contributorId":204291,"corporation":false,"usgs":true,"family":"Esselman","given":"Peter C.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":951044,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70271405,"text":"sir20255017 - 2025 - Groundwater response to managed aquifer recharge at the Southeast Houghton Artificial Recharge Project in Tucson, Arizona","interactions":[],"lastModifiedDate":"2026-02-03T16:32:26.605397","indexId":"sir20255017","displayToPublicDate":"2025-11-19T11:56:06","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2025-5017","displayTitle":"Groundwater Response to Managed Aquifer Recharge at the Southeast Houghton Artificial Recharge Project in Tucson, Arizona","title":"Groundwater response to managed aquifer recharge at the Southeast Houghton Artificial Recharge Project in Tucson, Arizona","docAbstract":"Managed aquifer recharge is a widespread practice for storing water in the subsurface as groundwater. At a managed aquifer recharge facility in southern Arizona, groundwater-level and repeat microgravity data were collected to monitor aquifer response. These data were used to inform parameter identification for an unsaturated-zone flow model used to simulate the recharge process. The facility, the Southeast Houghton Artificial Recharge Project (SHARP), consists of 3 surface basins (about 27,600 square meters [6.8 acres] total surface area) where recycled water is distributed in recharge cycles lasting several months, with dry periods in between. During the study period, December 2020–December 2022, Tucson Water (the City of Tucson’s water utility) reported 6.56×106 cubic meters of water (5,320 acre-feet) recharged.
Monitoring included groundwater-level observations at 3 monitoring wells and repeat microgravity measurements at as many as 22 locations (some stations were destroyed between surveys). Six gravity surveys were carried out using absolute- and relative-gravity meters. Large gravity increases, more than 250 microgals, were observed during the first repeat survey, 3.5 months after the start of recharge, but only in the immediate vicinity of the recharge basins. Data show that water moved downward to the water table, and storage changes in the unsaturated zone away from the facility were likely minimal. Gravity decreased at stations more than 1 kilometer from the facility, consistent with regional groundwater-level changes. Groundwater-level increases in wells adjacent to the recharge basins began 2 months after the second repeat gravity survey, and 5.5 months after recharge began.
Unsaturated-zone flow modeling was carried out using software that simulates water movement and parameter estimation. Model calibration was carried out by minimizing an objective function calculated from the differences between simulated and observed groundwater levels, and between simulated and observed repeat microgravity data. Including repeat microgravity data in the objective function reduced the uncertainty in estimated parameter values for saturated hydraulic conductivity and saturated water content. Modeling indicated that the unsaturated zone between the recharge basins and the water table does not become saturated even after 685 days of simulated infiltration. This gradual wetting may account for increasing infiltration rates over time, as hydraulic conductivity increases with increasing water content. Unsaturated-zone water content decreased rapidly between recharge cycles. Model-simulated groundwater mounding extended about 1 kilometer from the center of SHARP after the 685-day period following the onset of recharge.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20255017","collaboration":"Prepared in cooperation with Tucson Water","programNote":"Water Availability and Use Program","usgsCitation":"Wildermuth, L.M., Kennedy, J.R., and Conrad, J.L., 2025, Groundwater response to managed aquifer recharge at the Southeast Houghton Artificial Recharge Project in Tucson, Arizona: U.S. Geological Survey Scientific Investigations\nReport 2025–5017, 38 p., https://doi.org/10.3133/sir20255017.","productDescription":"Report: v, 38 p.; Data Release","numberOfPages":"38","onlineOnly":"Y","ipdsId":"IP-152298","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"links":[{"id":497795,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_118986.htm"},{"id":495375,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9E19SSK","text":"USGS data release","description":"Landrum, M.T., 2021, Repeat microgravity data from South Houghton Area Recharge Project, Tucson, Arizona, 2020-2022 (ver. 2.0, August 2024): U.S. Geological Survey data release, https://doi.org/10.5066/P9E19SSK.","linkHelpText":"Repeat microgravity data from South Houghton Area Recharge Project, Tucson, Arizona, 2020-2022 (ver. 2.0, August 2024)"},{"id":495371,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2025/5017/sir20255017.pdf","text":"Report","size":"35 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2025-5017 PDF"},{"id":495370,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2025/5017/coverthb.jpg"},{"id":495372,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20255017/full","linkFileType":{"id":5,"text":"html"},"description":"SIR 2025-5017 HTML"},{"id":495374,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2025/5017/images"},{"id":495373,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2025/5017/sir20255017.XML","description":"SIR 2025-5017 XML"}],"country":"United States","state":"Arizona","city":"Tucson","otherGeospatial":"Southeast Houghton Artificial Recharge Project","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -110.758333,\n 32.159722\n ],\n [\n -110.758333,\n 32.141667\n ],\n [\n -110.791667,\n 32.141667\n ],\n [\n -110.791667,\n 32.159722\n ],\n [\n -110.758333,\n 32.159722\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director,
Arizona Water Science Center
U.S. Geological Survey
520 N. Park Avenue
Tucson, AZ 85719
Despite their ubiquity and importance as freshwater habitat, small headwater streams are under-monitored by existing stream gage networks. To address this gap, we describe a low-cost, non-contact, and low-effort method that enables organizations to monitor relative streamflow dynamics in small headwater streams. The method uses a camera to capture repeat images of the stream from a fixed position. A person then annotates pairs of images, in each case indicating which image has more apparent streamflow or indicating equal flow if no difference is discernible. A deep learning modeling framework called streamflow rank estimation (SRE) is then trained on the annotated image pairs and applied to rank all images from highest to lowest apparent streamflow. From this result a relative hydrograph can be derived. We found that our modeled relative hydrograph dynamics matched the observed hydrograph dynamics well for 11 cameras at 8 streamflow sites in western Massachusetts. Higher performance was observed during the annotation period (median Kendall's Tau rank correlation of 0.75, with a range of 0.6–0.83) than after it (median Kendall's Tau of 0.59, with range 0.34–0.74). We found that annotation performance was generally consistent across the 11 camera sites and 2 individual annotators and was positively correlated with streamflow variability at a site. A scaling simulation determined that model performance improvements were limited after 1000 annotation pairs. Our model's estimates of relative flow, while not equivalent to absolute flow, may still be useful for many applications, such as ecological modeling and calculating event-based hydrological statistics (e.g., the number of out-of-bank floods). We anticipate that this method will be a valuable tool to extend existing stream monitoring networks and provide new insights on dynamic headwater systems.
","language":"English","publisher":"European Geosciences Union","doi":"10.5194/hess-29-6445-2025","usgsCitation":"Goodling, P.J., Fair, J.H., Gupta, A., Walker, J.D., Dubreuil, T., Hayden, M.J., and Letcher, B., 2025, Technical note: A low-cost approach to monitoring relative streamflow dynamics in small headwater streams using time lapse imagery and a deep learning model: Hydrology and Earth System Sciences, v. 29, no. 22, p. 6445-6460, https://doi.org/10.5194/hess-29-6445-2025.","productDescription":"16 p.","startPage":"6445","endPage":"6460","ipdsId":"IP-179122","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":496753,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/hess-29-6445-2025","text":"Publisher Index Page"},{"id":496681,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Massachusetts","otherGeospatial":"western Massachusetts","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -72.82742857720734,\n 42.73921316092924\n ],\n [\n -72.82742857720734,\n 42.42241182456118\n ],\n [\n -72.32535093532236,\n 42.42241182456118\n ],\n [\n -72.32535093532236,\n 42.73921316092924\n ],\n [\n -72.82742857720734,\n 42.73921316092924\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"29","issue":"22","noUsgsAuthors":false,"publicationDate":"2025-11-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Goodling, Phillip J. 0000-0001-5715-8579","orcid":"https://orcid.org/0000-0001-5715-8579","contributorId":239738,"corporation":false,"usgs":true,"family":"Goodling","given":"Phillip","email":"","middleInitial":"J.","affiliations":[{"id":41514,"text":"Maryland-Delaware-District of Columbia Water Science Center","active":true,"usgs":true}],"preferred":true,"id":950550,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fair, Jennifer H. 0000-0002-9902-1893","orcid":"https://orcid.org/0000-0002-9902-1893","contributorId":245941,"corporation":false,"usgs":true,"family":"Fair","given":"Jennifer","middleInitial":"H.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":950551,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gupta, Amrita 0000-0003-2643-5865","orcid":"https://orcid.org/0000-0003-2643-5865","contributorId":264600,"corporation":false,"usgs":false,"family":"Gupta","given":"Amrita","email":"","affiliations":[{"id":54512,"text":"Georgia Institute of Techniology","active":true,"usgs":false}],"preferred":false,"id":950552,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Walker, Jeffrey D. 0000-0003-1923-6550","orcid":"https://orcid.org/0000-0003-1923-6550","contributorId":244114,"corporation":false,"usgs":false,"family":"Walker","given":"Jeffrey","middleInitial":"D.","affiliations":[{"id":48839,"text":"Walker Environmental Research LLC","active":true,"usgs":false}],"preferred":false,"id":950553,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dubreuil, Todd 0000-0003-0189-4336","orcid":"https://orcid.org/0000-0003-0189-4336","contributorId":217872,"corporation":false,"usgs":true,"family":"Dubreuil","given":"Todd","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":950554,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hayden, Michael J. 0000-0002-9010-6831","orcid":"https://orcid.org/0000-0002-9010-6831","contributorId":291388,"corporation":false,"usgs":true,"family":"Hayden","given":"Michael","middleInitial":"J.","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":950555,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Letcher, Benjamin H. 0000-0003-0191-5678","orcid":"https://orcid.org/0000-0003-0191-5678","contributorId":315442,"corporation":false,"usgs":true,"family":"Letcher","given":"Benjamin H.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":950556,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70271480,"text":"sir20255055 - 2025 - An inset groundwater-flow model to evaluate the effects of layering configuration on model calibration and assess managed aquifer recharge near Shellmound, Mississippi","interactions":[],"lastModifiedDate":"2026-02-03T16:31:45.919091","indexId":"sir20255055","displayToPublicDate":"2025-11-18T12:06:15","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2025-5055","displayTitle":"An Inset Groundwater-Flow Model to Evaluate the Effects of Layering Configuration on Model Calibration and Assess Managed Aquifer Recharge near Shellmound, Mississippi","title":"An inset groundwater-flow model to evaluate the effects of layering configuration on model calibration and assess managed aquifer recharge near Shellmound, Mississippi","docAbstract":"The U.S. Geological Survey has developed a high-resolution inset groundwater-flow model in the Mississippi Delta as part of an interdisciplinary collaboration coordinated by the Mississippi Alluvial Plain project to provide a tool that stakeholders can use to support water-resource management decisions. Groundwater withdrawals from the Mississippi River Valley alluvial (MRVA) aquifer have been vital to support agricultural production in the region, but substantial groundwater-level declines near Shellmound, Mississippi, have caused concerns for long-term sustainability of the aquifer. To better understand the subsurface and try to mitigate the long-term groundwater-level declines, stakeholders have undertaken actions including a Groundwater Transfer and Injection Pilot (GTIP) project using a riverbank filtration-based managed aquifer recharge approach. The pilot project consisted of extracting groundwater near the Tallahatchie River and reinjecting it into the aquifer 3 kilometers west where water levels have substantially declined. A high-resolution airborne electromagnetic (AEM) survey was also completed to collect electrical resistivity data to support the GTIP project and the development of the groundwater model.
The inset groundwater-flow model was developed to (1) integrate the AEM data into the optimal layering configuration of the MRVA aquifer that the available observation data can support through calibration, and (2) assess the potential effect of the GTIP project on the groundwater levels. The AEM data were processed into three different layering configurations leading to the development of model A (18 layers), model B (16 layers), and model C (8 layers), all at a 100- x 100-meter cell spatial resolution using the U.S. Geological Survey modular finite-difference flow model 6 code with Newton-Raphson formulation. The model development process integrated recent advances in modeling, such as the incorporation of AEM data, the use of outputs from the soil-water-balance (SWB) model, and the Aquaculture and Irrigation Water-Use Model, and was facilitated by robust automation using the open-source python packages Modflow-setup and SFRmaker. Using Parameter Estimation ++ Iterative Ensemble Smoother, the three numerical groundwater-flow models (models A, B, and C) were calibrated against a set of observations, which included aquifer groundwater levels, streamflows, stream stage, and aquifer transmissivity. Results indicate that the detailed representation of MRVA aquifer layers in model A produced the best calibrated model by history matching, and the integration of data representing surficial connectivity played a key role in improving groundwater recharge and enhancing the ability of the model to match groundwater levels in the cone of depression. A forecast model simulated the managed aquifer recharge approach, and the results indicated that, given average irrigation and recharge conditions (2010–15), the GTIP project has the potential to induce groundwater-level increases of as much as 3 meters around the injection site, but a sustained increase would require repetition in subsequent years of water transfer at 2022 rates or above.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20255055","collaboration":"Prepared in cooperation with U.S. Department of Agriculture Agricultural Research Service and the Mississippi Department of Environmental Quality","programNote":"Water Availability and Use Science Program","usgsCitation":"Guira, M., Traylor, J.P., Leaf, A.T., and Weisser, A.R., 2025, An inset groundwater-flow model to evaluate the effects of layering configuration on model calibration and assess managed aquifer recharge near Shellmound, Mississippi: U.S. Geological Survey Scientific Investigations Report 2025–5055, 134 p., https://doi.org/10.3133/sir20255055.","productDescription":"Report: ix, 134 p.; 3 Figures: 11.00 x 8.50 inches; Data Release; Dataset","numberOfPages":"148","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-154357","costCenters":[{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":84311,"text":"Central Plains Water Science Center","active":true,"usgs":true}],"links":[{"id":497793,"rank":9,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_118974.htm"},{"id":495719,"rank":8,"type":{"id":29,"text":"Figure"},"url":"https://pubs.usgs.gov/sir/2025/5055/downloads/","text":"Layered figures","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"Downloadable layered PDF files for figures 11, 12, and 13"},{"id":495626,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P13DWA86","text":"USGS data release","linkHelpText":"Inset models used to evaluate the effects of layering configuration on model calibration from 1900 to 2018, and assess managed aquifer recharge near Shellmound, Mississippi, from 2019 to 2050"},{"id":495670,"rank":7,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20255055/full"},{"id":495623,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2025/5055/sir20255055.XML"},{"id":495622,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2025/5055/sir20255055.pdf","text":"Report","size":"40 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2025-5055"},{"id":495625,"rank":5,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"- USGS water data for the Nation"},{"id":495624,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2025/5055/images/"},{"id":495621,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2025/5055/coverthb.jpg"}],"country":"United States","state":"Mississippi","city":"Shellmound","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -90.55,\n 33.8\n ],\n [\n -90.55,\n 33.5\n ],\n [\n -90.1667,\n 33.5\n ],\n [\n -90.1667,\n 33.8\n ],\n [\n -90.55,\n 33.8\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Nebraska Water Science Center
U.S. Geological Survey
5231 South 19th Street
Lincoln, NE 68512
In 2021–22, clade 2.3.4.4b highly pathogenic avian influenza (HPAI) viruses were introduced by wild birds into North America, leading to geographically widespread disease. In response to HPAI outbreaks throughout late 2021 and early 2022, we recorded observations of sick and dead birds, estimated abundance of carcasses, collected swab and sera samples to detect viruses, and monitored bird nesting on the Yukon-Kuskokwim Delta region of Alaska to document potential effects of disease. Thirty-six reports of sick and dead birds were registered across the region. Nineteen carcasses were opportunistically collected for diagnostic testing, of which 12 were confirmed to be infected with clade 2.3.4.4b HPAI viruses. Carcass abundance estimates from line-distance sampling provided evidence that the most common species of dead birds from the western Yukon-Kuskokwim Delta region were Cackling Goose (Branta hutchinsii minima), Glaucous Gull (Larus hyperboreus), and Black Brant (Branta bernicla nigricans). Only one paired cloacal and oropharyngeal swab sample from a Northern Pintail (Anas acuta) tested positive for clade 2.3.4.4b HPAI virus, out of 464 live-captured duck and goose samples. Of 195 sera samples from waterfowl screened for antibodies reactive to influenza A viruses, antibodies were found in 41–98% of samples collected from Emperor Goose (Anser canagicus), Cackling Goose, Black Brant, and Spectacled Eider (Somateria fischeri). In addition, 15–98% of the same sera samples were reactive to a clade 2.3.4.4b H5 antigen. Fewer Black Brant and Emperor Goose nests were found on long-term study plots during 2022 than in previous years. Collectively, we found that HPAI viruses affected at least seven species of wild birds inhabiting the region during 2022. The full scope of impacts of HPAI at this location during 2022 is unknown, but our data indicate that acute effects to avian population health on the Yukon-Kuskokwim Delta region were likely modest.
","language":"English","publisher":"Wildlife Disease Association","doi":"10.7589/JWD-D-24-00199","usgsCitation":"Daniels, B., Osnas, E.E., Boldenow, M., Gerlach, R., Ahlstrom, C., Coburn, S., Brook, M.J., Brubaker, M., Fischer, J., Koons, D.N., Matz, A., Murphy, M., Rizzolo, D., Scott, L.C., Sinnett, D.R., Thompson, J.M., Lenoch, J., Kim Torchetti, M., Stallknecht, D., Poulson, R., and Ramey, A.M., 2025, Observational, virological, and serological data provide insights into an outbreak of highly pathogenic avian influenza among wild birds on the Yukon-Kuskokwim Delta, Alaska in 2022: Journal of Wildlife Diseases, v. 61, no. 4, p. 1010-1027, https://doi.org/10.7589/JWD-D-24-00199.","productDescription":"18 p.","startPage":"1010","endPage":"1027","ipdsId":"IP-171898","costCenters":[{"id":65299,"text":"Alaska Science Center Ecosystems","active":true,"usgs":true}],"links":[{"id":496752,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index 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Wisconsin-Stevens Point","active":true,"usgs":false}],"preferred":false,"id":950513,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Lenoch, Juliana","contributorId":347254,"corporation":false,"usgs":false,"family":"Lenoch","given":"Juliana","email":"","affiliations":[{"id":83108,"text":"WS National Wildlife Disease Program, U.S. Department of Agriculture, Fort Collins, CO 80521, USA","active":true,"usgs":false}],"preferred":false,"id":950514,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Kim Torchetti, Mia","contributorId":139355,"corporation":false,"usgs":false,"family":"Kim Torchetti","given":"Mia","email":"","affiliations":[{"id":12747,"text":"USDA APHIS VS National Veterinary Services Laboratories, Ames, IA","active":true,"usgs":false}],"preferred":false,"id":950515,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Stallknecht, David E.","contributorId":225107,"corporation":false,"usgs":false,"family":"Stallknecht","given":"David E.","affiliations":[{"id":36701,"text":"Southeastern Cooperative Wildlife Disease Study, Department of Population Health, College of Veterinary Medicine, University of Georgia","active":true,"usgs":false}],"preferred":false,"id":950516,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Poulson, Rebecca L.","contributorId":198807,"corporation":false,"usgs":false,"family":"Poulson","given":"Rebecca L.","affiliations":[{"id":7125,"text":"Southeastern Cooperative Wildlife Disease Study, College of Veterinary Medicine, University of Georgia, Athens, GA 30602, USA.","active":true,"usgs":false}],"preferred":false,"id":950517,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"Ramey, Andrew M. 0000-0002-3601-8400 aramey@usgs.gov","orcid":"https://orcid.org/0000-0002-3601-8400","contributorId":1872,"corporation":false,"usgs":true,"family":"Ramey","given":"Andrew","email":"aramey@usgs.gov","middleInitial":"M.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":950518,"contributorType":{"id":1,"text":"Authors"},"rank":21}]}} ,{"id":70272192,"text":"70272192 - 2025 - East Greenland Ice Sheet retreat history from Scoresby Sund and Storstrømmen Glacier during the last deglaciation","interactions":[],"lastModifiedDate":"2025-11-19T15:39:42.522563","indexId":"70272192","displayToPublicDate":"2025-11-18T08:33:39","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1250,"text":"Climate of the Past","active":true,"publicationSubtype":{"id":10}},"title":"East Greenland Ice Sheet retreat history from Scoresby Sund and Storstrømmen Glacier during the last deglaciation","docAbstract":"The lack of geological constraints on past ice-sheet change in marine-based sectors of the Greenland Ice Sheet (GrIS) following the Last Glacial Maximum limits our ability to assess (1) the drivers of ice-sheet change, and (2) the performance of ice-sheet models that are benchmarked against the paleo-record of GrIS change. Here, we provide new in situ 10Be surface exposure chronologies of ice-sheet margin retreat from the outer Scoresby Sund and Storstrømmen Glacier regions in eastern and northeastern Greenland, respectively. Ice retreated from Rathbone Island, east of Scoresby Sund, by ∼ 14.1 ka, recording some of the earliest documentations of terrestrial deglaciation in Greenland. The mouth of Scoresby Sund deglaciated by ∼ 13.2 ka, and retreated at an average rate of ∼ 43 m yr−1 between 13.2 and 9.7 ka. Storstrømmen Glacier retreated from the outer coast to within ∼ 3 km of the modern ice margin between ∼ 12.7 and 8.6 ka at an average rate of ∼ 28 m yr−1. Retreat then slowed or reached a stillstand as ice retreated ∼ 3 km between ∼ 8.6 ka to the modern ice margin at ∼ 8.0 ka. These retreat rates are consistent with late glacial and Holocene estimates for marine-terminating outlet glaciers across East Greenland, and comparable to modern retreat rates observed at the largest ice streams in northeastern, and northwestern Greenland.
","language":"English","publisher":"European Geosciences Union","doi":"10.5194/cp-21-2263-2025","usgsCitation":"Anderson, J.T., Young, N.E., Balter-Kennedy, A., Prince, K., Walcott-George, C.K., Graham, B.L., Charton, J., Briner, J.P., and Shaefer, J.M., 2025, East Greenland Ice Sheet retreat history from Scoresby Sund and Storstrømmen Glacier during the last deglaciation: Climate of the Past, v. 21, no. 11, p. 2263-2281, https://doi.org/10.5194/cp-21-2263-2025.","productDescription":"19 p.","startPage":"2263","endPage":"2281","ipdsId":"IP-178844","costCenters":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":496745,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/cp-21-2263-2025","text":"Publisher Index Page"},{"id":496637,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Greenland","otherGeospatial":"Scoresby Sund, Storstrømmen Glacier","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -47.161725727082626,\n 84.57071318603391\n ],\n [\n -47.161725727082626,\n 66.73876185091967\n ],\n [\n -27.30980297025164,\n 64.59666796479314\n ],\n [\n 2.0505995222399918,\n 81.78653428489469\n ],\n [\n -47.161725727082626,\n 84.57071318603391\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"21","issue":"11","noUsgsAuthors":false,"publicationDate":"2025-11-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Anderson, Jacob T. 0000-0002-4329-4200","orcid":"https://orcid.org/0000-0002-4329-4200","contributorId":362365,"corporation":false,"usgs":false,"family":"Anderson","given":"Jacob","middleInitial":"T.","affiliations":[{"id":17701,"text":"Lamont-Doherty Earth Observatory","active":true,"usgs":false}],"preferred":false,"id":950381,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Young, Nicolas E.","contributorId":362367,"corporation":false,"usgs":false,"family":"Young","given":"Nicolas","middleInitial":"E.","affiliations":[{"id":17701,"text":"Lamont-Doherty Earth Observatory","active":true,"usgs":false}],"preferred":false,"id":950382,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Balter-Kennedy, Allie 0000-0002-7828-7174","orcid":"https://orcid.org/0000-0002-7828-7174","contributorId":362369,"corporation":false,"usgs":false,"family":"Balter-Kennedy","given":"Allie","affiliations":[{"id":17701,"text":"Lamont-Doherty Earth Observatory","active":true,"usgs":false}],"preferred":false,"id":950383,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Prince, Karlee 0000-0003-4843-9322","orcid":"https://orcid.org/0000-0003-4843-9322","contributorId":362371,"corporation":false,"usgs":false,"family":"Prince","given":"Karlee","affiliations":[{"id":37334,"text":"University at Buffalo","active":true,"usgs":false}],"preferred":false,"id":950384,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Walcott-George, Caleb K. 0000-0003-4754-9466","orcid":"https://orcid.org/0000-0003-4754-9466","contributorId":362373,"corporation":false,"usgs":false,"family":"Walcott-George","given":"Caleb","middleInitial":"K.","affiliations":[{"id":37334,"text":"University at Buffalo","active":true,"usgs":false}],"preferred":false,"id":950385,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Graham, Brandon L. 0000-0002-7197-0413","orcid":"https://orcid.org/0000-0002-7197-0413","contributorId":340458,"corporation":false,"usgs":true,"family":"Graham","given":"Brandon","middleInitial":"L.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":950386,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Charton, Joanna","contributorId":362375,"corporation":false,"usgs":false,"family":"Charton","given":"Joanna","affiliations":[{"id":17701,"text":"Lamont-Doherty Earth Observatory","active":true,"usgs":false}],"preferred":false,"id":950387,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Briner, Jason P.","contributorId":362377,"corporation":false,"usgs":false,"family":"Briner","given":"Jason","middleInitial":"P.","affiliations":[{"id":37334,"text":"University at Buffalo","active":true,"usgs":false}],"preferred":false,"id":950388,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Shaefer, Joerg M.","contributorId":362379,"corporation":false,"usgs":false,"family":"Shaefer","given":"Joerg","middleInitial":"M.","affiliations":[{"id":17701,"text":"Lamont-Doherty Earth Observatory","active":true,"usgs":false}],"preferred":false,"id":950389,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70272215,"text":"70272215 - 2025 - Cryptic life history diversity supports endangered species recovery in an ultra-urbanized landscape","interactions":[],"lastModifiedDate":"2025-11-19T15:31:57.22913","indexId":"70272215","displayToPublicDate":"2025-11-18T08:28:18","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3358,"text":"Scientific Reports","active":true,"publicationSubtype":{"id":10}},"title":"Cryptic life history diversity supports endangered species recovery in an ultra-urbanized landscape","docAbstract":"Urban landscapes are often overlooked in conservation planning, allowing human activities to take precedence in ecosystem management. However, even heavily modified environments can support diverse species profiles, but continued expansion of the human footprint could transform these biodiversity hotspots into ecological traps that serve as hidden catalysts for demographic declines. In the backdrop of one of the world’s most urbanized landscapes-New York City, USA—is a federally endangered population of shortnose sturgeon (Acipenser brevirostrum) that has been quietly recovering for several decades despite many demographic threats. Here, we identify a unique behavioral phenotype of shortnose sturgeon that occupies habitats in New York Harbor in late spring and fall, likely using the area to optimize bioenergetic processes. As this study highlights, urbanized environments can be a nexus for cryptic phenotypic diversity which, if overlooked, can disrupt eco-evolutionary processes and contribute to population and species loss.
","language":"English","publisher":"Springer Nature","doi":"10.1038/s41598-025-24360-6","usgsCitation":"White, S.L., Higgs, A., and Fox, D., 2025, Cryptic life history diversity supports endangered species recovery in an ultra-urbanized landscape: Scientific Reports, v. 15, 40634, 8 p., https://doi.org/10.1038/s41598-025-24360-6.","productDescription":"40634, 8 p.","ipdsId":"IP-178198","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":496744,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41598-025-24360-6","text":"Publisher Index Page"},{"id":496636,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New York","city":"New York City","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -74.09993061657431,\n 40.736082719013496\n ],\n [\n -74.09993061657431,\n 40.588831128093005\n ],\n [\n -73.96403648299037,\n 40.588831128093005\n ],\n [\n -73.96403648299037,\n 40.736082719013496\n ],\n [\n -74.09993061657431,\n 40.736082719013496\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"15","noUsgsAuthors":false,"publicationDate":"2025-11-18","publicationStatus":"PW","contributors":{"authors":[{"text":"White, Shannon L. 0000-0003-4687-6596","orcid":"https://orcid.org/0000-0003-4687-6596","contributorId":263424,"corporation":false,"usgs":true,"family":"White","given":"Shannon","email":"","middleInitial":"L.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":950464,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Higgs, Amanda","contributorId":225402,"corporation":false,"usgs":false,"family":"Higgs","given":"Amanda","affiliations":[{"id":13678,"text":"New York State Department of Environmental Conservation","active":true,"usgs":false}],"preferred":false,"id":950465,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fox, Dewayne","contributorId":340954,"corporation":false,"usgs":false,"family":"Fox","given":"Dewayne","affiliations":[{"id":37219,"text":"Delaware State University","active":true,"usgs":false}],"preferred":false,"id":950466,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70274548,"text":"70274548 - 2025 - Population genetics of the endangered narrowly endemic Island Marble butterfly (Euchloe ausonides insulanus)","interactions":[],"lastModifiedDate":"2026-04-02T13:57:15.166442","indexId":"70274548","displayToPublicDate":"2025-11-18T00:00:00","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1324,"text":"Conservation Genetics","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Population genetics of the endangered narrowly endemic Island Marble butterfly (Euchloe ausonides insulanus)","title":"Population genetics of the endangered narrowly endemic Island Marble butterfly (Euchloe ausonides insulanus)","docAbstract":"The Island Marble butterfly (Euchloe ausonides insulanus) is an endangered species endemic to the San Juan Islands off the coast of Washington State, United States, and British Columbia, Canada. The species was thought to be extinct for ~ 90 years before it was rediscovered at American Camp, San Juan Island National Historical Park in 1998. Here, we report the results of the first population genetic analyses for insulanus, using DNA collected non-invasively from individuals in the last known stronghold for the species. We used DNA extracted from meconium, larval exuviae, and natural mortalities to generate and test thirteen new microsatellite markers to estimate genetic diversity, population structure, and kinship. We assembled and annotated mitochondrial genomes, which were used alongside museum specimens of insulanus collected ~ 100 years ago from Vancouver Island, and other members of the E. ausonides species complex, to infer the evolutionary history of the species. The results indicated that insulanus experiences low heterozygosity, a small effective population size (Ne), and low allelic diversity. High levels of inbreeding were found in some individuals, but inbreeding was uneven across the population. No population structure or partitioning of genetic variation by host plant was detected. The mitogenomes of extant insulanus were all identical and modern samples showed a loss of allelic diversity compared to insulanus from museums. Extant insulanus formed a clade with museum specimens and we identified multiple putatively diagnostic alleles to differentiate insulanus from other subspecies. Based on these results, we outline considerations for species management and genetic monitoring.
","language":"English","publisher":"Springer Nature","doi":"10.1007/s10592-025-01737-8","usgsCitation":"Jones, K., Aunins, A.W., Young, C., Johnson, R.L., and Morrison, C.L., 2025, Population genetics of the endangered narrowly endemic Island Marble butterfly (Euchloe ausonides insulanus): Conservation Genetics, v. 27, 5, https://doi.org/10.1007/s10592-025-01737-8.","productDescription":"5","ipdsId":"IP-177244","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":501970,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","state":"British Columbia, Washington","otherGeospatial":"San Juan Islands","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -123.1794965908473,\n 48.762742021779246\n ],\n [\n -123.1794965908473,\n 48.384126042901784\n ],\n [\n -122.67085884048696,\n 48.384126042901784\n ],\n [\n -122.67085884048696,\n 48.762742021779246\n ],\n [\n -123.1794965908473,\n 48.762742021779246\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"27","noUsgsAuthors":false,"publicationDate":"2025-11-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Jones, Kara Suzanne 0000-0002-8168-0815","orcid":"https://orcid.org/0000-0002-8168-0815","contributorId":331477,"corporation":false,"usgs":true,"family":"Jones","given":"Kara Suzanne","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":958246,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Aunins, Aaron W. 0000-0001-5240-1453 aaunins@usgs.gov","orcid":"https://orcid.org/0000-0001-5240-1453","contributorId":5863,"corporation":false,"usgs":true,"family":"Aunins","given":"Aaron","email":"aaunins@usgs.gov","middleInitial":"W.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":958247,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Young, Colleen Callahan 0000-0002-9858-4897","orcid":"https://orcid.org/0000-0002-9858-4897","contributorId":344669,"corporation":false,"usgs":true,"family":"Young","given":"Colleen Callahan","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":958248,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Johnson, Robin L. 0000-0003-4314-3792 rjohnson1@usgs.gov","orcid":"https://orcid.org/0000-0003-4314-3792","contributorId":224717,"corporation":false,"usgs":true,"family":"Johnson","given":"Robin","email":"rjohnson1@usgs.gov","middleInitial":"L.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":958249,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Morrison, Cheryl L. 0000-0001-9425-691X","orcid":"https://orcid.org/0000-0001-9425-691X","contributorId":239844,"corporation":false,"usgs":true,"family":"Morrison","given":"Cheryl","middleInitial":"L.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":958250,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70272104,"text":"ofr20251046 - 2025 - Modeling floods, sediment entrainment, and downstream debris flows from hypothetical breaches of the blockage at Spirit Lake, Washington","interactions":[],"lastModifiedDate":"2026-02-03T16:29:30.731045","indexId":"ofr20251046","displayToPublicDate":"2025-11-17T07:48:44","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2025-1046","displayTitle":"Modeling Floods, Sediment Entrainment, and Downstream Debris Flows from Hypothetical Breaches of the Blockage at Spirit Lake, Washington","title":"Modeling floods, sediment entrainment, and downstream debris flows from hypothetical breaches of the blockage at Spirit Lake, Washington","docAbstract":"This report describes a modeling investigation by the U.S. Geological Survey (USGS) of hazards in the Toutle and Cowlitz River valleys posed by hypothetical outburst floods from Spirit Lake, Washington. A massive debris avalanche resulting from the collapse of Mount St. Helens’ north flank during the May 18, 1980, eruption blocked Spirit Lake’s natural outlet into the North Fork Toutle River. Lacking a natural outlet, subsequent runoff in the Spirit Lake watershed contributed to a rising lake level, elevating the potential for debris-dam breaching or catastrophic failure. The influence of highly erodible bed sediment in the upper North Fork Toutle River on downstream flood and debris-flow dynamics and extent is assessed in this study. Simulations of clear-water (non-erosive) outburst floods were used as a baseline and compared to erosive flows that entrain large volumes of material and transition into debris flows along their flow path, revealing the influence of entrainment on hazard extent. Clear-water floods were modeled with the shallow water equations. Erosive flows were modeled with a two-phase granular fluid model that accommodates mobilization and incorporation of sediment from the bed into the overlying flow and resultant changes in flow rheology across a wide range of solid concentrations, from dilute suspensions to dense-granular debris flows. Entrainment of bed material was found to substantially increase the total flow volume (total volume of transported water and sediment is approximately 150 percent of the water volume for non-erosive flows). Erosive flows are shown to exhibit higher flow-front speeds and faster downstream arrival times than non-erosive flows, consistent with volume amplification effects near the actively mobilizing flow front. However, the larger total volume of transported material does not necessarily lead to an enhancement of total volume throughput (cumulative discharge) or inundation extent (total affected area) for all locations along the entire flow path; while entrainment leads to the displacement of a larger volume of material overall, much of this dislocated material (water and sediment) deposits upstream from the distal extent of the flows. These results are consistent with energetic considerations of initial potential energy and granular shear resistance.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20251046","usgsCitation":"George, D.L., and Cannon, C.M., 2025, Modeling floods, sediment entrainment, and downstream debris flows from hypothetical breaches of the blockage at Spirit Lake, Washington: U.S. Geological Survey Open-File Report 2025–1046, 37 p., https://doi.org/10.3133/ofr20251046.","productDescription":"Report: ix, 37 p.; Data Release","numberOfPages":"37","onlineOnly":"Y","ipdsId":"IP-154709","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":496509,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P139AC3R","text":"USGS data release","description":"George, D.L., and Cannon, C.M., 2025, Simulated floods, sediment entrainment, and debris-flow inundation in the Toutle and Cowlitz River valleys resulting from hypothetical dam breaches of Spirit Lake, Washington: U.S. Geological Survey data release, https://doi.org/10.5066/P139AC3R.","linkHelpText":"Simulated floods, sediment entrainment, and debris-flow inundation in the Toutle and Cowlitz River valleys resulting from hypothetical dam breaches of Spirit Lake, Washington"},{"id":496505,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2025/1046/ofr20251046.pdf","text":"Report","size":"26.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2025-1046 PDF"},{"id":496504,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2025/1046/coverthb.jpg"},{"id":497791,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_118953.htm"},{"id":496508,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2025/1046/images"},{"id":496507,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2025/1046/ofr20251046.XML","linkFileType":{"id":8,"text":"xml"},"description":"OFR 2025-1046 XML"},{"id":496506,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20251046/full","linkFileType":{"id":5,"text":"html"},"description":"OFR 2025-1046 HTML"}],"country":"United States","state":"Washington","otherGeospatial":"Spirit Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.133333,\n 46.2833\n ],\n [\n -122.2,\n 46.2833\n ],\n [\n -122.2,\n 46.25\n ],\n [\n -122.133333,\n 46.25\n ],\n [\n -122.133333,\n 46.2833\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"David A. Johnston Cascades Volcano Observatory
U.S. Geological Survey
1300 SE Cardinal Court
Building 10, Suite 100
Vancouver, WA 98683
Email: askCVO@usgs.gov
","tableOfContents":"Barrier islands provide resources and ecological services that are integral to economic and environmental interests, such as protection of coastal infrastructure and provision of wildlife habitat. Over time, barrier islands may become eroded and experience land loss, which can require management actions to restore island integrity. Barrier island restoration can create or modify habitats, which can impact the organisms depending on them. Our objective was to understand how the abundance and behaviors of a suite of shorebird species responded to restoration and habitat factors at two restored sites in coastal Louisiana (USA). For five focal species, we used abundance from the breeding and non-breeding seasons as well as breeding, foraging, and maintenance behaviors as response variables in boosted regression tree models to determine the importance of various geospatial and remotely sensed predictor variables related to restoration. Across sites and species, remotely sensed variables, particularly a brightness index, tended to be more important than restoration phases as predictors of bird abundance and behavior. Our results suggest that sediment composition, moisture, and vegetative cover are related to shorebird coastal habitat selection, although the direction and strength of relationships differ among these variables and our focal species. Tying these remote sensing metrics to restoration design and management actions can help land managers better understand factors that attract and benefit birds. Additional research can advance understanding in how remote sensing can be used to monitor the availability of functional habitats for shorebirds.
","language":"English","publisher":"BioRxiv","doi":"10.1101/2025.11.15.688530","usgsCitation":"Zenzal, T.J., Anderson, A.N., Enwright, N., Thurman, H.R., Cheney, W.C., LeBlanc, D., Dobbs, R.C., Geary, B., and Waddle, H., 2025, Understanding abundances and behaviors of shorebirds in coastal Louisiana: BioRxiv, https://doi.org/10.1101/2025.11.15.688530.","productDescription":"57 p.","ipdsId":"IP-160584","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":497396,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1101/2025.11.15.688530","text":"External Repository"},{"id":497186,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Zenzal, Theodore J. Jr. 0000-0001-7342-1373","orcid":"https://orcid.org/0000-0001-7342-1373","contributorId":224399,"corporation":false,"usgs":true,"family":"Zenzal","given":"Theodore","suffix":"Jr.","email":"","middleInitial":"J.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":951478,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Anderson, Amanda Nicole 0000-0003-3930-3896","orcid":"https://orcid.org/0000-0003-3930-3896","contributorId":224400,"corporation":false,"usgs":true,"family":"Anderson","given":"Amanda","email":"","middleInitial":"Nicole","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":951479,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Enwright, Nicholas 0000-0002-7887-3261","orcid":"https://orcid.org/0000-0002-7887-3261","contributorId":217771,"corporation":false,"usgs":true,"family":"Enwright","given":"Nicholas","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":951480,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Thurman, Hana R.","contributorId":363355,"corporation":false,"usgs":false,"family":"Thurman","given":"Hana","middleInitial":"R.","affiliations":[{"id":64427,"text":"Cherokee Nation System Solutions","active":true,"usgs":false}],"preferred":false,"id":951481,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cheney, Wyatt C.","contributorId":363356,"corporation":false,"usgs":false,"family":"Cheney","given":"Wyatt","middleInitial":"C.","affiliations":[{"id":86667,"text":"Cheney Consulting","active":true,"usgs":false}],"preferred":false,"id":951482,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"LeBlanc, Delaina","contributorId":330122,"corporation":false,"usgs":false,"family":"LeBlanc","given":"Delaina","email":"","affiliations":[{"id":78819,"text":"Barataria-Terrebonne National Estuary","active":true,"usgs":false}],"preferred":false,"id":951483,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Dobbs, Robert C.","contributorId":363357,"corporation":false,"usgs":false,"family":"Dobbs","given":"Robert","middleInitial":"C.","affiliations":[{"id":12717,"text":"Louisiana Department of Wildlife and Fisheries","active":true,"usgs":false}],"preferred":false,"id":951484,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Geary, Brock","contributorId":352310,"corporation":false,"usgs":false,"family":"Geary","given":"Brock","affiliations":[{"id":16979,"text":"University of Pennsylvania","active":true,"usgs":false}],"preferred":false,"id":951485,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Waddle, Hardin 0000-0003-1940-2133","orcid":"https://orcid.org/0000-0003-1940-2133","contributorId":222187,"corporation":false,"usgs":true,"family":"Waddle","given":"Hardin","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":951486,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70273069,"text":"70273069 - 2025 - DeepFaune New England: A species classification model for trail camera images in northeastern North America","interactions":[],"lastModifiedDate":"2025-12-12T18:32:36.615236","indexId":"70273069","displayToPublicDate":"2025-11-14T11:21:21","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"DeepFaune New England: A species classification model for trail camera images in northeastern North America","docAbstract":"The DeepFaune New England model classifies wildlife species in trail camera images, identifying 24 taxa from northeastern North America with high (97%) accuracy. The model was adapted from the DeepFaune model for identifying European wildlife, demonstrating the practicality of transfer learning across continents. The majority of training data is openly licensed, and the model itself is open source, enabling easy integration into camera trapping workflows. The open source software is available at (https://code.usgs.gov/vtcfwru/deepfaune-new-england), and has been further integrated into the PyTorch-Wildlife framework.
","language":"English","publisher":"Wiley","doi":"10.1002/ece3.72174","usgsCitation":"Clarfeld, L.A., Gieder, K.D., Fuller, A.K., Miao, Z., Sirén, A.P., Webb, S.M., Morelli, T.L., Kilborn, J.R., Callahan, C.B., Prout, L.S., Cliché, R., Patry, R.K., Bernier, C., Staats, S., and Donovan, T.M., 2025, DeepFaune New England: A species classification model for trail camera images in northeastern North America: Ecology and Evolution, v. 15, no. 11, e72174, 10 p., https://doi.org/10.1002/ece3.72174.","productDescription":"e72174, 10 p.","ipdsId":"IP-178678","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":497712,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.72174","text":"Publisher Index Page"},{"id":497496,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"New England","geographicExtents":"{\n 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Economy of Massachusetts","title":"The 3D Elevation Program—Supporting the economy of Massachusetts","docAbstract":"Massachusetts extends from the mountains of the Appalachian system in the west of the State to the sandy beaches and rocky shorelines of the Atlantic coast in the east. Inland topographic data support a wide range of important activities, including geologic mapping, transportation planning, forest and wildlife management, quantifying ecological services, water supply protection, commonwealth-wide infrastructure planning, local site planning, and flood-plain management. Nearshore bathymetry can be used to support coastal portions of the Commonwealth by addressing the combined threats of ocean warming, strong storm surge, and rising sea levels. The maintenance and (or) expansion of Massachusetts ports (for instance, Boston, New Bedford) and Cape Cod sediment management depends upon the accurate mapping of bathymetry and the frequent influx of sediment and redeposition. Critical applications that address the broad range of requirements depend on light detection and ranging (lidar) data that provide a highly detailed three-dimensional (3D) model of the Earth’s surface and aboveground features.
The 3D Elevation Program (3DEP) is managed by the U.S. Geological Survey (USGS) in partnership with Federal, State, Tribal, U.S. territorial, and local agencies to acquire consistent lidar coverage at quality level 2 or better to meet the many needs of the Nation and Massachusetts. The status of available and in-progress 3DEP baseline lidar data in Massachusetts is shown in figure 1. 3DEP baseline lidar data include quality level 2 or better, 1-meter or better digital elevation models, and lidar point clouds, and must meet the Lidar Base Specification version 1.2 (https://www.usgs.gov/3dep/lidarspec) or newer requirements. The National Enhanced Elevation Assessment identified user requirements and conservatively estimated that availability of lidar data would result in at least $1.23 million in new benefits annually to Massachusetts. The top 10 Massachusetts business uses for 3D elevation data, which are based on the estimated annual conservative benefits of 3DEP, are shown in table 2.
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\"}}]}","contact":"Director, National Geospatial Program
U.S. Geological Survey
12201 Sunrise Valley Drive, MS 511
Reston, VA 20192