Biological invasions, driven by the spread of non-native species, have become a critical global issue because of their far-reaching ecological and socioeconomic impacts. Effective communication of the risks of biological invasions is essential for implementing robust policy and legislation and gaining public support for conservation efforts. However, current policies often suffer from fragmentation and ineffectiveness, largely due to inadequate risk communication and complex multilevel governance. To address this challenge, we develop a global framework designed to enhance clearer communication about biological invasion risks. The framework contextualizes key terms across three domains in invasion science: species invasiveness, risk analysis, and decision support tools. Using both diffusion-of-English and ecology-of-language paradigms, and following a three-step process involving preliminary consensus, AI querying, and ground-truthing with final consensus, we validate the framework in 70 non-English languages which, together with English, have official status in at least one country and collectively cover all 195 countries worldwide. Our findings reveal that while terminology for risk analysis is well established, terminology for species invasiveness and, especially, for decision support tools remains underdeveloped in many languages, hindering effective communication and policy implementation. Our framework underscores the importance of cultural and political neutrality. By promoting clearer risk communication among scientists, policymakers, and the public globally, we aim to reduce policy fragmentation and foster enhanced collaboration in risk mitigation. We recommend expanding multilingual decision support tools to include the full risk analysis process: risk identification, risk assessment, and risk management. This will support intergovernmental mitigation efforts and promote a unified global response to biological invasions.
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Using olfactory attractants (i.e. lures) may increase detection rates, but variation in effects among species is not well understood. Thus, investigating factors influencing detection of mesocarnivores, can inform and improve monitoring efforts. We evaluated the effects of lures and environmental covariates on the detection of plains spotted skunks Spilogale interrupta, striped skunks Mephitis mephitis, northern raccoons Procyon lotor, gray foxes Urocyon cinereoargenteus, coyotes Canis latrans, bobcats Lynx rufus and Virginia opossums Didelphis virginiana. We conducted surveys during January–May 2023 in southeast Oklahoma using motion-triggered cameras at randomly selected sites. We surveyed sites using a 4-camera cluster and leave-one-out lure design, where 3 cameras were randomly assigned 1 of 4 lures (i.e. skunk-based lure, fatty acid tablets, sweet lure or sardines) and 1 camera was a control (i.e. no lure). 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0000-0002-7336-2761","orcid":"https://orcid.org/0000-0002-7336-2761","contributorId":205792,"corporation":false,"usgs":true,"family":"Pennaz","given":"Alice","email":"","affiliations":[{"id":508,"text":"Office of the AD Hazards","active":true,"usgs":true}],"preferred":true,"id":955762,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jones, Jeanne M. 0000-0001-7549-9270 jmjones@usgs.gov","orcid":"https://orcid.org/0000-0001-7549-9270","contributorId":4676,"corporation":false,"usgs":true,"family":"Jones","given":"Jeanne","email":"jmjones@usgs.gov","middleInitial":"M.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":955763,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70273409,"text":"ofr20251057 - 2026 - Distribution, abundance, breeding activities, and habitat use of the Least Bell's Vireo at Marine Corps Base Camp Pendleton, California—2020–24 summary report","interactions":[],"lastModifiedDate":"2026-02-03T17:09:16.100992","indexId":"ofr20251057","displayToPublicDate":"2026-01-21T07:00:00","publicationYear":"2026","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":"2025-1057","displayTitle":"Distribution, Abundance, Breeding Activities, and Habitat Use of the Least Bell's Vireo at Marine Corps Base Camp Pendleton, California—2020–24 Summary Report","title":"Distribution, abundance, breeding activities, and habitat use of the Least Bell's Vireo at Marine Corps Base Camp Pendleton, California—2020–24 summary report","docAbstract":"The purpose of this report is to provide the Marine Corps with a summary of abundance, breeding activity, demography, and habitat use of endangered Least Bell’s Vireos (Vireo bellii pusillus) at Marine Corps Base Camp Pendleton, California (MCBCP or Base). The report presents results of vireo surveys and monitoring in 2024 and summarizes a subset of data collected from 2020 through 2024. Surveys for the Least Bell's Vireo were completed at MCBCP between April 4 and July 9, 2024. Core survey areas and a subset of non-core areas in drainages containing riparian habitat suitable for vireos were surveyed two to four times. We detected 542 territorial male vireos and 17 transient vireos in core survey areas. An additional 102 territorial male vireos and 2 transients were detected in non-core survey areas. Transient vireos were detected on 5 of the 10 drainages/sites surveyed (core and non-core areas). In core survey areas, 87 percent of vireo territories were on the four most populated drainages, with the Santa Margarita River containing 67 percent of all territories in core areas surveyed on Base. In core areas, 77 percent of male vireos were confirmed as paired; 76 percent of male vireos in non-core areas were confirmed as paired.
The number of documented Least Bell’s Vireo territories in core survey areas on MCBCP decreased 3 percent from 2023. In five core survey area drainages, the number of territories increased by at least two, and in two core survey area drainages, the Santa Margarita River and Las Flores Creek, the number of vireo territories decreased by at least nine between 2023 and 2024. The number of vireo territories at Marine Corps Air Station, Camp Pendleton did not change from 2023 to 2024. The proportion of surveys during which Brown-headed Cowbirds (Molothrus ater) were detected decreased to 0.03 from a peak of 0.45 in 2022. Cowbirds were detected in April and June in 2024.
Most core-area vireos (58 percent, including transients) used mixed willow (Salix spp.) riparian habitat. An additional 9 percent of birds occupied willow habitat co-dominated by Western sycamores (Platanus racemosa). Riparian scrub dominated by mule fat (Baccharis salicifolia), sandbar willow (S. exigua), or blue elderberry (Sambucus mexicana) was used by 33 percent of vireos. Habitat dominated by non-native vegetation was used by 1 percent of vireos.
Since 2020, the number of vireos detected in each of the non-core survey groups was greater than expected, based on the change in vireo numbers in core survey areas. Although, the number of vireo territories on Base decreased from 2020–24, from approximately 1,224 to approximately 960, the trend in vireo territory numbers on Base since 2005 has been positive.
In 2019, MCBCP began operating an artificial seep along the Santa Margarita River; then, in 2021, two additional artificial seeps became operational. The artificial seeps pumped water to the surface during daylight hours starting in mid-April and ending in August each year and were designed to increase the amount of surface water to enhance Southwestern Willow Flycatcher (Empidonax traillii extimus) breeding habitat. Although this enhancement was designed to benefit flycatchers, few flycatchers have inhabited MCBCP, including the seep areas, within the past several years; therefore, vireos were selected as a surrogate species to determine effects of the habitat enhancement. This report presents the fifth year of annual monitoring and analyses summarizing all 5 years of vireo and vegetation response to the artificial seeps.
In 2020, we established four study sites along the Santa Margarita River, two surrounding and extending downstream from existing and proposed seep pumps at the Old Treatment Ponds and along Pump Road and two Reference sites in similar habitat downstream from the Seep sites. Seep pumps began operating at the Old Treatment Ponds in 2020 and along Pump Road in 2021. In 2023, seep pumps at the Pump Road Seep site did not function, and we recategorized that study site as Intermediate. We sampled vegetation at Seep, Intermediate, and Reference sites to determine the effects of surface-water enhancement by seep pumps. In 2024, vegetation cover was highest near the ground and decreased with increasing height. Woody vegetation made up most of the cover at all height categories. We determined that Seep and Intermediate sites differed from each other in addition to differing from Reference sites, which likely is, in part, because seep-pump operation at the Intermediate site was inconsistent compared to the Seep site. Soil saturation in 2024 was high at the Intermediate site and was associated with high native herbaceous cover and low non-native herbaceous cover. Sites differed, with the Intermediate site having more upper canopy cover in general, the Seep site having more low woody cover, and the Reference sites having more mid-canopy non-native vegetation cover.
Soil saturation significantly increased from 2020 through 2024 at the Seep site and was significantly higher at Seep and Intermediate sites than at their paired Reference sites in all years. Soil saturation likely was increased by the supplemental surface water at the Seep site. However, soil saturation at the Intermediate site was not clearly associated with seep pumps but likely affected by soil saturation at the site before seep-pump installation and flooding from high precipitation. Canopy height increased at the Intermediate site from 2020 through 2024 and increased with increasing soil saturation at the Intermediate and Reference sites. The canopy at the Seep site was shorter than at the Intermediate and Reference sites and decreased from 2020 through 2024 because tall trees were damaged and killed by shothole borer beetles (Euwallacea spp.).
We used Redundancy Analysis to discover associations among vegetation types, plant species, and other environmental variables (soil saturation, site, precipitation, and seep operation, defined as the site and year seep pumps were operating). These associations explained less than 15 percent of the variability in the vegetation, with the remaining 85 percent of variation unexplained. Generally, as soil saturation increased, understory vegetation increased and non-native cover decreased in the mid-and upper canopy. Non-native herbaceous plant species decreased in wetter soil.
The Seep site was characterized by more understory and less canopy, contrasting with the Intermediate site, which was characterized by less understory and more higher canopy cover. The addition of surface water via seep pumps or precipitation was associated with more vegetation near the ground. Higher early winter precipitation was associated with taller canopy and more woody vegetation in the upper canopy. We also created a Redundancy Analysis model isolating the components of Southwestern Willow Flycatcher habitat, as identified by Howell and others (2018). In this model, increased soil saturation resulted in increased cover of stinging nettle (Urtica dioica) and black willow (Salix gooddingii) below 3 meters (m), total cover 3–6 m, and black willow above 6 m. Cover of poison hemlock (Conium maculatum) and stinging nettle below 3 m was higher at the Seep site and lower at the Intermediate site.
Vireo territory density among the Seep, Intermediate, and Reference sites was similar before the seep pumps were installed. However, vireo territory density at Seep and Intermediate sites combined was significantly higher than at Reference sites after the seep pumps were installed.
We banded and resighted color banded vireos as part of a long-term evaluation of vireo survival, site fidelity, between-year movement, and the effect of surface-water enhancement on vireo return rate and between-year movement. We banded 164 Least Bell's Vireo nestlings during the 2024 season.
In 2024, we resighted 31 Least Bell's Vireos on Base that had been banded before the 2024 breeding season, and we were able to identify 25 of them. Of the 25 that we could identify, 24 were banded on Base and 1 was originally banded on the San Luis Rey River. Adult birds of known age ranged from 1 to 9 years old.
Base-wide survival of vireos was affected by sex, age, and year. Males had significantly higher annual survival than females (60 percent versus 47 percent, respectively). Adults had higher annual survival than first-year vireos (61 percent versus 11 percent, respectively). The return rate of adult vireos to Seep, Intermediate, or Reference sites was not affected by the original banding site (Seep versus Intermediate versus Reference).
Most returning adult vireos, predominantly males, showed strong between-year site fidelity. Of the adults present in 2023, 92 percent (all males) returned in 2024 to within 100 m of their previous territory. The average between-year movement for returning adult vireos was 0.4±0.03 kilometers (km). The average movement of first-year vireos detected in 2024 that fledged from a known nest on MCBCP in 2023 was 2.4±3.1 km.
We monitored 47 Least Bell's Vireo pairs to evaluate the effects of surface-water enhancement on nest success and breeding productivity. Breeding productivity in 2024 was similar among Seep, Intermediate, and Reference sites (2.8, 3.0, and 3.0 young fledged per pair, respectively), and the percentage of pairs that fledged at least one young was not significantly different among sites (83, 91, and 96 percent, respectively). According to the best model, daily nest survival from 2020–24 was not related to site. Other measures of breeding productivity were also similar among Seep, Intermediate, and Reference site pairs.
Between 2020 and 2024, the number of vireo fledglings produced per pair increased with increasing native herbaceous cover under 3 m and decreasing cover of all herbaceous vegetation under 5 m and was not affected by precipitation, site, or seep operation. The number of vireo fledglings produced per egg was lower at the Seep and Intermediate sites than at the Reference sites and increased with decreasing late winter precipitation, cover of poison hemlock, black mustard, non-native vegetation above 2 m, and all vegetation over 2 m. Vireo pairs at Seep and Intermediate sites were less likely to fledge young than vireo pairs at Reference sites. All vireo pairs were more likely to fledge young with less cover of poison hemlock and more cover of poison oak.
From 2020 through 2024, vireos placed their nests in 24 plant species. The most used plants in all years were willows, mostly red (S. laevigata), or arroyo (S. lasiolepis). The fate of a vireo nest (whether it successfully fledged young or not) was not affected by placement in native or non-native vegetation, by site, or by year, but nests were more likely to be successful if they were placed in woody plants than in herbaceous plants. Successful nests were placed higher in the host plant and farther from the outer edge of the nest clump than unsuccessful nests.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20251057","collaboration":"Prepared in cooperation with Assistant Chief of Staff, Environmental Security, U.S. Marine Corps Base Camp Pendleton","programNote":"Ecosystems Mission Area—Species Management Research Program","usgsCitation":"Lynn, S., Houston, A., Kus, B.E., and Mendia, S.M., 2026, Distribution, abundance, breeding activities, and habitat use of the Least Bell's Vireo at Marine Corps Base Camp Pendleton, California—2020–24 summary report: U.S. Geological Survey Open-File Report 2025–1057, 128 p., https://doi.org/10.3133/ofr20251057.","productDescription":"xii, 128 p.","numberOfPages":"128","onlineOnly":"Y","ipdsId":"IP-176723","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":498564,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2025/1057/images"},{"id":498563,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2025/1057/ofr20251057.XML","linkFileType":{"id":8,"text":"xml"},"description":"OFR 2025-1057 XML"},{"id":498562,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20251057/full","linkFileType":{"id":5,"text":"html"},"description":"OFR 2025-1057 HTML"},{"id":498561,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2025/1057/ofr20251057.pdf","size":"13.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2025-1057 PDF"},{"id":498560,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2025/1057/coverthb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Marine Corps Base Camp Pendleton","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -117.5833,\n 33.5\n ],\n [\n -117.5833,\n 33.1667\n ],\n [\n -117.25,\n 33.1667\n ],\n [\n -117.25,\n 33.5\n ],\n [\n -117.5833,\n 33.5\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Western Ecological Research Center
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Accurate mapping of post-fire surviving trees is important for tracking forest recovery and prioritizing land management decisions. Satellite-based remote sensing is an effective method to assess post-fire forest conditions. Traditionally, differenced satellite-derived burn severity indices are computed by differencing one year pre- and post-fire spectral reflectance values. Differenced burn severity indices are useful for quantifying and mapping the magnitude of ecological change, but their application to detecting and mapping post-fire live trees may not be as appropriate, particularly for delayed tree mortality. Delayed tree mortality (“delayed mortality”) is a phenomenon where trees that initially survive fire then die over an extended period (between one and five years), and it can be challenging to measure and predict. In this study, we demonstrate the potential of mapping delayed mortality using readily available remotely sensed imagery alone. We used random forest models to detect post-fire live trees using 10-m resolution Sentinel-2 data at one-, three-, and five-years post-fire for four fires in the southern Sierra Nevada, California, USA. Using imagery from the National Agriculture Imagery Program (NAIP; 60-cm resolution), we manually classified live tree presence in 6000 Sentinel-2 pixels (500 pixels for each fire-year combination) to calibrate and validate models. Sentinel-2 based model accuracies ranged from 65 % to 86 % with F-scores ranging from 0.52 to 0.86, and their predictions of live pixel area were on average 44 % lower than inferred from more traditional indices such as relative differenced normalized burn ratio (RdNBR). This work represents a promising first step in using freely available post-fire spectral reflectance imagery to detect live trees over an extended period to support post-fire management.
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In this study, we use a three-dimensional (3D) seismic velocity model to better constrain the depth and focal mechanism of the April 5th, 2024, moment magnitude 4.8 Tewksbury earthquake and investigate the spatial variability of earthquake ground motions and the effects of nearby sedimentary basins. We perform earthquake ground-motion simulations up to 0.5 Hz using the 3D spectral-element wave-propagation solver SPECFEM3D over a region 280-km wide by 260-km long by 77-km deep. Topography and subsurface geophysical structure are assigned using the U.S. Geological Survey National Crustal Model with a minimum shear-wave velocity of 200 m/s. We use earthquake time series from 13 broadband seismic stations in the region that have a uniform azimuthal distribution and epicentral distances ranging from 76 to 131 km to compare with synthetics and explore the effects of 1D versus 3D seismic structure on focal mechanism and depth solutions. Ground-motion intensity metrics are also presented relative to the NGA-East ground-motion models (GMMs) currently used in seismic hazard assessments for the region. We find that the 3D model, which reveals a wide spatial variability of period-dependent ground motions, yields better predictions of earthquake ground motions relative to the 1D model and the NGA-East ergodic ground-motion model, with 76 percent reduction of residual variance in observed ground motions averaged over 3-, 5-, 7-, and 10-second periods. Use of the 3D model to solve for a focal mechanism yields a shallower focal depth at 4 km and a shallower east-dipping focal plane relative to the U.S. Geological Survey regional moment tensor and Global Centroid Moment Tensor. Our study demonstrates that use of 3D seismic velocity models can improve estimates of earthquake focal mechanisms, ground motions, and seismic hazard.","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0220250333","usgsCitation":"Boyd, O.S., Bozdağ, E., Kehoe, H.L., Moschetti, M.P., 2026, Ground-motion simulations for the 2024 Mw 4.8 Tewksbury, New Jersey, earthquake: Seismological Research Letters, v. 97, no. 2A, p. 755-766, https://doi.org/10.1785/0220250333.","productDescription":"12 p.","startPage":"755","endPage":"766","ipdsId":"IP-184176","costCenters":[{"id":78686,"text":"Geologic Hazards Science Center - Seismology / Geomagnetism","active":true,"usgs":true}],"links":[{"id":500604,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1785/0220250333","text":"Publisher Index Page"},{"id":500477,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Jersey","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -75.13460496006654,\n 41.13685910148769\n ],\n [\n -75.13460496006654,\n 40.31012949967425\n ],\n [\n -74.00929946762524,\n 40.31012949967425\n ],\n [\n -74.00929946762524,\n 41.13685910148769\n ],\n [\n -75.13460496006654,\n 41.13685910148769\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"97","issue":"2A","noUsgsAuthors":false,"publicationDate":"2026-01-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Boyd, Oliver S. 0000-0001-9457-0407 olboyd@usgs.gov","orcid":"https://orcid.org/0000-0001-9457-0407","contributorId":140739,"corporation":false,"usgs":true,"family":"Boyd","given":"Oliver","email":"olboyd@usgs.gov","middleInitial":"S.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true}],"preferred":true,"id":956499,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bozdağ, Ebru","contributorId":365873,"corporation":false,"usgs":false,"family":"Bozdağ","given":"Ebru","affiliations":[{"id":6606,"text":"Colorado School of Mines","active":true,"usgs":false}],"preferred":false,"id":956500,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kehoe, Haiyang Liam 0000-0002-5818-6077","orcid":"https://orcid.org/0000-0002-5818-6077","contributorId":362101,"corporation":false,"usgs":true,"family":"Kehoe","given":"Haiyang","middleInitial":"Liam","affiliations":[{"id":78686,"text":"Geologic Hazards Science Center - Seismology / Geomagnetism","active":true,"usgs":true}],"preferred":true,"id":956501,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Moschetti, Morgan P. 0000-0001-7261-0295 mmoschetti@usgs.gov","orcid":"https://orcid.org/0000-0001-7261-0295","contributorId":1662,"corporation":false,"usgs":true,"family":"Moschetti","given":"Morgan","email":"mmoschetti@usgs.gov","middleInitial":"P.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":956502,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70273800,"text":"70273800 - 2026 - An entropic explanation for Gutenberg-Richter scaling","interactions":[],"lastModifiedDate":"2026-02-02T20:26:15.963383","indexId":"70273800","displayToPublicDate":"2026-01-10T08:43:51","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7501,"text":"JGR Solid Earth","active":true,"publicationSubtype":{"id":10}},"title":"An entropic explanation for Gutenberg-Richter scaling","docAbstract":"We develop a simple explanation for Gutenberg-Richter (G-R) size scaling of earthquakes on a single fault. We discretize the fault and consider all possible contiguous ruptures at that level of discretization. In this static model, we assume that slip scales with rupture length, and that the rupture rates at each point along the fault are consistent with an a priori long-term slip rate. These simple assumptions define an (under-determined) non-negative least-squares inverse problem. Each solution to this inverse problem is a set of earthquake rates that matches the slip-rate constraint. We use a Markov Chain Monte Carlo (MCMC) algorithm to uniformly sample the solution space assuming constant slip rates along the fault. At finer discretizations, deviations from G-R behavior decrease, which is consistent with an entropic pressure towards G-R solutions. When the fault is discretized into 10 or more segments, random solutions found by the MCMC algorithm have G-R size scaling, even though there are trivial solutions that, for example, have earthquakes of only one size. This is because there are simply far more solutions that have G-R scaling; as the problem size increases, the strong degeneracy of GR solutions results in other solutions becoming improbably rare. Also, the entropically favored G-R distribution has a b-value of approximately 1, which agrees with measured b-values in real earthquake catalogs.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2025JB032719","usgsCitation":"Page, M.T., and Field, E.H., 2026, An entropic explanation for Gutenberg-Richter scaling: JGR Solid Earth, v. 131, no. 1, e2025JB032719, 10 p., https://doi.org/10.1029/2025JB032719.","productDescription":"e2025JB032719, 10 p.","ipdsId":"IP-176974","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":499351,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"131","issue":"1","noUsgsAuthors":false,"publicationDate":"2026-01-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Page, Morgan T. 0000-0001-9321-2990 mpage@usgs.gov","orcid":"https://orcid.org/0000-0001-9321-2990","contributorId":3762,"corporation":false,"usgs":true,"family":"Page","given":"Morgan","email":"mpage@usgs.gov","middleInitial":"T.","affiliations":[{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":954864,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Field, Edward H. 0000-0001-8172-7882 field@usgs.gov","orcid":"https://orcid.org/0000-0001-8172-7882","contributorId":52242,"corporation":false,"usgs":true,"family":"Field","given":"Edward","email":"field@usgs.gov","middleInitial":"H.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":954865,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70273442,"text":"70273442 - 2026 - Is satellite-derived bathymetry vertical accuracy dependent on satellite mission and processing method?","interactions":[],"lastModifiedDate":"2026-01-14T15:23:53.929478","indexId":"70273442","displayToPublicDate":"2026-01-05T08:18:13","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3250,"text":"Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Is satellite-derived bathymetry vertical accuracy dependent on satellite mission and processing method?","docAbstract":"This research focusses on three satellite-derived bathymetry methods and optical satellite instruments: (1) a stereo photogrammetry bathymetry module (SaTSeaD) developed for the NASA Ames stereo pipeline open-source software (version 3.6.0) using stereo WorldView data; (2) physics-based radiative transfer equations (PBSDB) using Landsat data; and (3) a modified composite band-ratio method for Sentinel-2 (SatBathy) with an initial simplified calibration, followed by a more rigorous linear regression against in situ bathymetry data. All methods were tested in three different areas with different geological and environmental conditions, Cabo Rojo, Puerto Rico; Key West, Florida; and Cocos Lagoon and Achang Flat Reef Preserve, Guam. It is demonstrated that all satellite derived bathymetry (SDB) methods have increased accuracy when the results are aligned with higher-accuracy ICESat-2 ATL24 track bathymetry data using the iterative closest point (ICP). SDB vertical accuracy depends more on location characteristics than the method or optical satellite instrument used. All error metrics considered (mean absolute error, median absolute deviation, and root mean square error) can be less than 5% of the maximum bathymetry depth penetration for at least one method, although not necessarily for the same method for all sites. The SDB error distribution tends to be bimodal irrespective of method, satellite instrument, alignment, site, or maximum bathymetry depth, leading to the potential ineffectiveness of traditional error metrics, such as the root mean square error. However, our analysis demonstrates that performing detrending where possible can achieve an error distribution as close to normality as possible for which error metrics are more diagnostic.
","language":"English","publisher":"MDPI","doi":"10.3390/rs18020195","usgsCitation":"Palaseanu-Lovejoy, M., Danielson, J.J., Kim, M., Eder, B., Imahori, G., and Storlazzi, C.D., 2026, Is satellite-derived bathymetry vertical accuracy dependent on satellite mission and processing method?: Remote Sensing, v. 18, no. 2, 195, 30 p., https://doi.org/10.3390/rs18020195.","productDescription":"195, 30 p.","ipdsId":"IP-183102","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":498700,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs18020195","text":"Publisher Index Page"},{"id":498609,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Guam, Puerto Rico","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -88.29886149831057,\n 31.035877030602435\n ],\n [\n -88.29886149831057,\n 24.818271329127427\n ],\n [\n -79.18887863828726,\n 24.818271329127427\n ],\n [\n -79.18887863828726,\n 31.035877030602435\n ],\n [\n -88.29886149831057,\n 31.035877030602435\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -67.91979115320188,\n 18.80997482085145\n ],\n [\n -67.91979115320188,\n 17.365111187758373\n ],\n [\n -64.61443502140921,\n 17.365111187758373\n ],\n [\n -64.61443502140921,\n 18.80997482085145\n ],\n [\n -67.91979115320188,\n 18.80997482085145\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 144.5400287592969,\n 13.788590651628851\n ],\n [\n 144.5400287592969,\n 13.156374228238235\n ],\n [\n 145.08326832494907,\n 13.156374228238235\n ],\n [\n 145.08326832494907,\n 13.788590651628851\n ],\n [\n 144.5400287592969,\n 13.788590651628851\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"18","issue":"2","noUsgsAuthors":false,"publicationDate":"2026-01-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Palaseanu-Lovejoy, Monica 0000-0002-3786-5118","orcid":"https://orcid.org/0000-0002-3786-5118","contributorId":305576,"corporation":false,"usgs":true,"family":"Palaseanu-Lovejoy","given":"Monica","affiliations":[],"preferred":true,"id":953719,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Danielson, Jeffrey J. 0000-0003-0907-034X daniels@usgs.gov","orcid":"https://orcid.org/0000-0003-0907-034X","contributorId":3996,"corporation":false,"usgs":true,"family":"Danielson","given":"Jeffrey","email":"daniels@usgs.gov","middleInitial":"J.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":953720,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kim, Minsu 0000-0003-4472-0926","orcid":"https://orcid.org/0000-0003-4472-0926","contributorId":297371,"corporation":false,"usgs":false,"family":"Kim","given":"Minsu","affiliations":[{"id":54490,"text":"KBR, Inc., under contract to USGS","active":true,"usgs":false}],"preferred":false,"id":953721,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Eder, Bryan","contributorId":365118,"corporation":false,"usgs":false,"family":"Eder","given":"Bryan","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":953722,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Imahori, Gretchen","contributorId":365119,"corporation":false,"usgs":false,"family":"Imahori","given":"Gretchen","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":953723,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Storlazzi, Curt D. 0000-0001-8057-4490","orcid":"https://orcid.org/0000-0001-8057-4490","contributorId":213610,"corporation":false,"usgs":true,"family":"Storlazzi","given":"Curt","middleInitial":"D.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":953724,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70273293,"text":"70273293 - 2026 - Insights into widespread landsliding in southern Appalachia from Hurricane Helene","interactions":[],"lastModifiedDate":"2026-01-05T15:55:55.615417","indexId":"70273293","displayToPublicDate":"2026-01-01T09:49:34","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1728,"text":"GSA Today","active":true,"publicationSubtype":{"id":10}},"title":"Insights into widespread landsliding in southern Appalachia from Hurricane Helene","docAbstract":"Between 23 and 27 September 2024, antecedent rain followed by Hurricane Helene produced one of the most damaging weather events in southern Appalachia history. The back-to-back storm events resulted in a maximum cumulative rainfall of 848 mm and hurricane-force wind gusts over 170 km/h in western North Carolina, eastern Tennessee, and southwestern Virginia. The resulting regional flooding, landslides, and tree blowdown caused over 100 fatalities, damaged or destroyed critical infrastructure and thousands of structures, and severed connectivity across the region. Over the next several weeks, a multi-agency landslide response produced a rapid hazard assessment and mapped 2217 landslides, 55% of which damaged infrastructure or property. Orographic uplift enhanced rainfall, resulting in concentrated landsliding along the ~250 km swath of the Blue Ridge escarpment in western North Carolina. Landslides initiated predominantly on windward-facing (southeast-facing) slopes, and localized clustering of initiation points indicated a strong influence of hillslope-scale meteorological and geomorphic factors. Many shallow landslides mobilized into larger, highly mobile, and damaging debris flows that graded into floods. Here, we put our preliminary observations in the context of historical storm-driven landslide events and open new avenues for investigating the nature and extent of landslides and their effects in southern Appalachia and similar environments.
","language":"English","publisher":"Geological Society of America","doi":"10.1130/GSATG625A.1","usgsCitation":"Schaefer, L.N., Rengers, F.K., Mirus, B., Toney, L., Allstadt, K.E., Wooten, R., Moore, P., Burgi, P.M., Witt, A., Bilderback, E., Bauer, J., Korte, D., and Crawford, M., 2026, Insights into widespread landsliding in southern Appalachia from Hurricane Helene: GSA Today, v. 36, no. 1, p. 4-11, https://doi.org/10.1130/GSATG625A.1.","productDescription":"8 p.","startPage":"4","endPage":"11","ipdsId":"IP-176367","costCenters":[{"id":78941,"text":"Geologic Hazards Science Center - Landslides / Earthquake Geology","active":true,"usgs":true}],"links":[{"id":498456,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/gsatg625a.1","text":"Publisher Index Page"},{"id":498323,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Georgia, North Carolina, South Carolina, Tennessee, Virginia","otherGeospatial":"southern Appalachia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -84.0956246997159,\n 33.16712093076947\n ],\n [\n -80.70056220609001,\n 35.44500558858594\n ],\n [\n -78.92252283909625,\n 36.85612515045237\n ],\n [\n -78.86465883497438,\n 37.53726534359846\n ],\n [\n -81.27319094443648,\n 37.03692920257846\n ],\n [\n -83.98040433088295,\n 36.20191656996158\n ],\n [\n -85.11083948910141,\n 34.93803598167824\n ],\n [\n -84.63563450266271,\n 33.976759781860224\n ],\n [\n -84.49843468082626,\n 33.14701998591154\n ],\n [\n -84.0956246997159,\n 33.16712093076947\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"36","issue":"1","noUsgsAuthors":false,"publicationDate":"2026-01-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Schaefer, Lauren N. 0000-0003-3216-7983","orcid":"https://orcid.org/0000-0003-3216-7983","contributorId":241997,"corporation":false,"usgs":true,"family":"Schaefer","given":"Lauren","email":"","middleInitial":"N.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":953236,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rengers, Francis K. 0000-0002-1825-0943 frengers@usgs.gov","orcid":"https://orcid.org/0000-0002-1825-0943","contributorId":150422,"corporation":false,"usgs":true,"family":"Rengers","given":"Francis","email":"frengers@usgs.gov","middleInitial":"K.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":953237,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mirus, Benjamin 0000-0001-5550-014X bbmirus@usgs.gov","orcid":"https://orcid.org/0000-0001-5550-014X","contributorId":169597,"corporation":false,"usgs":true,"family":"Mirus","given":"Benjamin","email":"bbmirus@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":953238,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Toney, Liam 0000-0003-0167-9433","orcid":"https://orcid.org/0000-0003-0167-9433","contributorId":257264,"corporation":false,"usgs":true,"family":"Toney","given":"Liam","email":"","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":953239,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Allstadt, Kate E. 0000-0003-4977-5248","orcid":"https://orcid.org/0000-0003-4977-5248","contributorId":138704,"corporation":false,"usgs":true,"family":"Allstadt","given":"Kate","email":"","middleInitial":"E.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":953240,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wooten, Richard","contributorId":364820,"corporation":false,"usgs":false,"family":"Wooten","given":"Richard","affiliations":[{"id":24614,"text":"North Carolina Geological Survey","active":true,"usgs":false}],"preferred":false,"id":953241,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Moore, Patrick","contributorId":364821,"corporation":false,"usgs":false,"family":"Moore","given":"Patrick","affiliations":[{"id":86982,"text":"National Weather Service Greenville-Spartanburg Forecast Office","active":true,"usgs":false}],"preferred":false,"id":953242,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Burgi, Paula Madeline 0000-0003-3001-5759","orcid":"https://orcid.org/0000-0003-3001-5759","contributorId":317875,"corporation":false,"usgs":true,"family":"Burgi","given":"Paula","email":"","middleInitial":"Madeline","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":953243,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Witt, Anne","contributorId":349948,"corporation":false,"usgs":false,"family":"Witt","given":"Anne","affiliations":[{"id":83542,"text":"Virginia Department of Energy, Geology and Mineral Resources Program","active":true,"usgs":false}],"preferred":false,"id":953244,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Bilderback, Eric Leland 0000-0002-2027-5699","orcid":"https://orcid.org/0000-0002-2027-5699","contributorId":349936,"corporation":false,"usgs":true,"family":"Bilderback","given":"Eric Leland","affiliations":[{"id":78941,"text":"Geologic Hazards Science Center - Landslides / Earthquake Geology","active":true,"usgs":true}],"preferred":true,"id":953245,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Bauer, Jennifer","contributorId":364824,"corporation":false,"usgs":false,"family":"Bauer","given":"Jennifer","affiliations":[{"id":86985,"text":"Appalachian Landslide Consultants, PLLC","active":true,"usgs":false}],"preferred":false,"id":953246,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Korte, David 0000-0001-9830-4333","orcid":"https://orcid.org/0000-0001-9830-4333","contributorId":349945,"corporation":false,"usgs":false,"family":"Korte","given":"David","affiliations":[{"id":24614,"text":"North Carolina Geological Survey","active":true,"usgs":false}],"preferred":false,"id":953247,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Crawford, Matthew","contributorId":224687,"corporation":false,"usgs":false,"family":"Crawford","given":"Matthew","email":"","affiliations":[{"id":40489,"text":"Kentucky Geological Survey","active":true,"usgs":false}],"preferred":false,"id":953248,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}} ,{"id":70273323,"text":"70273323 - 2026 - Effect of passive integrated transponder tag size on survival, tag loss, and growth of Santa Ana Sucker","interactions":[],"lastModifiedDate":"2026-02-09T16:20:17.765608","indexId":"70273323","displayToPublicDate":"2025-12-30T09:41:33","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2886,"text":"North American Journal of Fisheries Management","active":true,"publicationSubtype":{"id":10}},"title":"Effect of passive integrated transponder tag size on survival, tag loss, and growth of Santa Ana Sucker","docAbstract":"The Santa Ana Sucker Pantosteus santaanae is endemic to southern California and is listed as threatened under the U.S. Endangered Species Act. Seasonal limitations on conventional sampling and inconsistencies in survey methodologies have led to an incomplete understanding of population dynamics. Alternative sampling methods have the potential to fill important knowledge gaps in biology and life history. One option is to use passive integrated transponder (PIT) tags to identify individuals and track their movements. The objective of this study was to test the effect of PIT tag size on survival, tag loss, and growth of Santa Ana Suckers.
Sixty-one Santa Ana Suckers were randomly assigned to one of three treatments (control: N = 20; 8-mm PIT tag: N = 21; or 12-mm PIT tag: N = 20). A full-duplex PIT tag was injected into each fish, and lengths (standard, fork, and total length) and weight were recorded. Fish remained in raceways for 36 d, after which they were retrieved, scanned, and remeasured.
There were five fish mortalities within 48 h of tagging, resulting in an 87.8% overall survival rate. There were two fish mortalities from the 8-mm tag treatment and three mortalities from the 12-mm tag treatment. One fish from each tagging treatment lost their tag, resulting in a 5.6% overall tag loss rate. The Fisher’s exact test indicated no statistically significant difference in survival or tag loss between treatments. The ordinary least squares regression detected no effect of tag size on growth for Santa Ana Suckers.
Results suggest that 8- and 12-mm PIT tags are suitable options for tagging Santa Ana Suckers measuring at least 62 and 70 mm fork length, respectively. Supplementing the current sampling strategy with PIT tags could help monitoring efforts to expand spatially and temporally while providing expanded population data to inform adaptive management actions for the Santa Ana Sucker.
Solar energy development is increasing in warm deserts of the southwestern United States, and ecovoltaics has emerged as an approach to maintain ecosystem function within solar facilities while meeting increasing regional energy demands. The Solar Gemini Project, located in the northeastern Mojave Desert, USA, is one of largest photovoltaic facilities incorporating an ecovoltaics approach, including novel installation practices to reduce disturbance to soil and vegetation and solar tracking bifacial photovoltaic panels to maximize energy generation. To further understand the influence of the facility on environmental conditions, we compared microclimate, temperature, and soil moisture in bare soil interspaces between panel arrays inside the facility to undisturbed desert in nearby areas outside the facility from June 2023–February 2025. Our comparisons included different seasons (summer versus winter), soil depth (shallow versus deep), and facility operation (inactive versus active panels with solar-tracking). We found lower solar radiation, wind speed, and evaporative demand inside the facility compared to outside the facility, with greater differences when panels were actively tracking. When panels were active, air temperature inside and outside the facility was similar on average, but was higher inside the facility during the day and lower at night. Soil surface temperature was lower inside the facility due to panel shading in the morning and evening, whereas soil temperature (0–15 cm) was consistently higher inside the facility. Soil moisture was higher inside the facility and did not drop to the low levels observed outside the facility. In total, we found lower evaporative demand, less heat loading, and higher soil moisture inside the Gemini facility, potentially benefitting flora and fauna in the harsh desert landscape. Yet, we also found daytime increases in air and soil surface temperature inside the facility, and persistent increases to soil temperature. These findings highlight the potentially positive and negative environmental changes associated with ecovoltaics solar energy development in warm deserts and provide evidence that can inform the optimization of solar photovoltaics design and management.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jenvman.2025.128436","usgsCitation":"Pinos, J., Munson, S.M., Karban, C.C., and Petrie, M.D., 2026, Ecovoltaic solar energy development effects to microclimate, temperature, and soil moisture in panel array interspaces in a warm desert: Journal of Environmental Management, v. 398, 128436, 13 p., https://doi.org/10.1016/j.jenvman.2025.128436.","productDescription":"128436, 13 p.","ipdsId":"IP-180614","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":498510,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nevada","otherGeospatial":"Gemini Solar Project facilty","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -114.80278104138198,\n 36.49946370519997\n ],\n [\n -114.80278104138198,\n 36.399575927541804\n ],\n [\n -114.71715812361246,\n 36.399575927541804\n ],\n [\n -114.71715812361246,\n 36.49946370519997\n ],\n [\n -114.80278104138198,\n 36.49946370519997\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"398","noUsgsAuthors":false,"publicationDate":"2025-12-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Pinos, Juan","contributorId":357729,"corporation":false,"usgs":false,"family":"Pinos","given":"Juan","affiliations":[{"id":85544,"text":"School of Life Sciences, University of Nevada Las Vegas, Las Vegas, Nevada 89154, USA","active":true,"usgs":false}],"preferred":false,"id":953429,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Munson, Seth M. 0000-0002-2736-6374 smunson@usgs.gov","orcid":"https://orcid.org/0000-0002-2736-6374","contributorId":220026,"corporation":false,"usgs":true,"family":"Munson","given":"Seth","email":"smunson@usgs.gov","middleInitial":"M.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":953430,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Karban, Claire C 0000-0002-6157-031X","orcid":"https://orcid.org/0000-0002-6157-031X","contributorId":344987,"corporation":false,"usgs":true,"family":"Karban","given":"Claire","email":"","middleInitial":"C","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":953431,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Petrie, Matthew D.","contributorId":364911,"corporation":false,"usgs":false,"family":"Petrie","given":"Matthew","middleInitial":"D.","affiliations":[{"id":87009,"text":"School of Life Sciences, University of Nevada Las Vegas, Las Vegas, NV, USA","active":true,"usgs":false}],"preferred":false,"id":953432,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70273446,"text":"70273446 - 2026 - An analysis of the linked decisions in the confiscation of illegally traded turtles","interactions":[],"lastModifiedDate":"2026-02-24T16:39:30.348704","indexId":"70273446","displayToPublicDate":"2025-12-22T08:46:47","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5803,"text":"Conservation Science and Practice","active":true,"publicationSubtype":{"id":10}},"title":"An analysis of the linked decisions in the confiscation of illegally traded turtles","docAbstract":"Over the last few decades, freshwater turtles have become more common in the illegal wildlife trade because of growing global demand. Illegally traded turtles may be intercepted by several different agencies with separate jurisdictions. When turtles are confiscated, uncertainties may make releasing them back to the wild difficult. We used tools from decision analysis to achieve the following three objectives: (1) map elements of the decision process and their relationships in the illegal turtle trade using conceptual models, (2) outline the linked decisions for turtle confiscation and repatriation using decision trees, and (3) evaluate the decision trees for two example scenarios, one with moderate uncertainty and one with high uncertainty. We used the wood turtle (Glyptemys insculpta) as a case study, which is a species of conservation concern in part due to illegal wildlife trafficking. We conducted 23 semi-structured interviews of decision makers in law enforcement, biologists, land managers, and zoo staff. Interviews revealed that decisions regarding the disposition of confiscated turtles are complicated by uncertainty in disease status and origin. Decision makers that handle confiscated turtles also recognize that their decisions are often made in sequence and dependent on the outcome of antecedent decisions. In evaluating our decision trees, we found that the optimal decisions for example scenarios were similar and insensitive to uncertainty. Future applications of the decision trees by decision makers would involve a decision analyst to parameterize and interpret the choices and consequences involved in working through these decision trees. Collectively, our work shows how the use of decision trees can help structure and evaluate risky decisions for repatriating confiscated wildlife.
","language":"English","publisher":"Society for Conservation Biology","doi":"10.1111/csp2.70165","usgsCitation":"Smith, D., DiRenzo, G.V., Fleming, J.E., McEachran, M.C., and Campbell Grant, E.H., 2025, An analysis of the linked decisions in the confiscation of illegally traded turtles: Conservation Science and Practice, e70165, 12 p., https://doi.org/10.1111/csp2.70165.","productDescription":"e70165, 12 p.","ipdsId":"IP-166499","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":498702,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/csp2.70165","text":"Publisher Index Page"},{"id":498616,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -97.61952248598104,\n 51.579179045299185\n ],\n [\n -97.61952248598104,\n 37.42140161216963\n ],\n [\n -66.83408644894973,\n 37.42140161216963\n ],\n [\n -66.83408644894973,\n 51.579179045299185\n ],\n [\n -97.61952248598104,\n 51.579179045299185\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"8","issue":"2","noUsgsAuthors":false,"publicationDate":"2025-12-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Smith, Desireé","contributorId":365126,"corporation":false,"usgs":false,"family":"Smith","given":"Desireé","affiliations":[{"id":36396,"text":"University of Massachusetts","active":true,"usgs":false}],"preferred":false,"id":953733,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"DiRenzo, Graziella V.","contributorId":365127,"corporation":false,"usgs":false,"family":"DiRenzo","given":"Graziella","middleInitial":"V.","affiliations":[{"id":36396,"text":"University of Massachusetts","active":true,"usgs":false}],"preferred":false,"id":953734,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fleming, Jillian Elizabeth 0000-0003-2570-914X","orcid":"https://orcid.org/0000-0003-2570-914X","contributorId":238931,"corporation":false,"usgs":true,"family":"Fleming","given":"Jillian","email":"","middleInitial":"Elizabeth","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":953735,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McEachran, Margaret C.","contributorId":365130,"corporation":false,"usgs":false,"family":"McEachran","given":"Margaret","middleInitial":"C.","affiliations":[{"id":36396,"text":"University of Massachusetts","active":true,"usgs":false}],"preferred":false,"id":953736,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Campbell Grant, Evan H. 0000-0003-4401-6496 ehgrant@usgs.gov","orcid":"https://orcid.org/0000-0003-4401-6496","contributorId":150443,"corporation":false,"usgs":true,"family":"Campbell Grant","given":"Evan","email":"ehgrant@usgs.gov","middleInitial":"H.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":953737,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70273308,"text":"70273308 - 2026 - Where to restore and conserve? A regional benefit cost analysis of coral reef protection and restoration for coastal flood resilience","interactions":[],"lastModifiedDate":"2026-01-06T14:49:27.601532","indexId":"70273308","displayToPublicDate":"2025-12-22T08:42:30","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2258,"text":"Journal of Environmental Management","active":true,"publicationSubtype":{"id":10}},"title":"Where to restore and conserve? A regional benefit cost analysis of coral reef protection and restoration for coastal flood resilience","docAbstract":"Momentum is growing for the management of coral reefs as a strategy to reduce climate risks in tropical coastlines. Yet, quantification of the life-time costs, impacts, and benefits remains limited. This study provides one of the first rigorous, spatially explicit, regional-scale Benefit:Cost Analyses (BCA) for coral reef restoration and was designed to meet the BCA requirements of major hazard mitigation funding and programs. This study simulates coastal flooding using a hydrodynamic model under different scenarios representing current coral reef conditions, reef degradation, and reef restoration. These coastal flood maps are used to estimate socioeconomic damages, which are included in a BCA to assess cost-effectiveness and priority areas for coral reef conservation and restoration. The United States Virgin Islands is used as a case study given recent impacts from storms and their new policy that declares reefs as natural infrastructure. The results show that flood risk across the islands of Saint Croix, Saint John, and Saint Thomas is $51.4 million USD per year. Annually, coral reefs prevent flood damages to 481 people and $43.6 million USD of infrastructure, which represents 87 % of the flood risk. These results identify the communities that could receive the greatest benefits from coral conservation and restoration, which overlap significantly. Coral reef restoration is found to be a cost-effective strategy for flood mitigation although how reefs are restored matters. Hybrid coral reef restoration provides greater flood mitigation benefits than ecological restoration, but its cost-effectiveness is overall lower given its greater costs. Many coastal areas have benefit:cost ratios exceeding 1.5, which complies with typical government agencies’ requirements for accessing hazard mitigation funds. This valuation framework helps provide rigorous regional-scale quantification of nature-based coastal protection solutions for coastal risk management decisions.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jenvman.2025.128166","usgsCitation":"Reguero, B., Gaido-Lassare, C., Storlazzi, C.D., McNulty, V., Perez, D., and Beck, M.W., 2026, Where to restore and conserve? A regional benefit cost analysis of coral reef protection and restoration for coastal flood resilience: Journal of Environmental Management, v. 397, 128166, 15 p., https://doi.org/10.1016/j.jenvman.2025.128166.","productDescription":"128166, 15 p.","ipdsId":"IP-170993","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":498342,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"U.S. Virgin Islands","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -64.65441321858593,\n 18.38265061411741\n ],\n [\n -65.08683971208158,\n 18.38265061411741\n ],\n [\n -65.08683971208158,\n 18.287140701134334\n ],\n [\n -64.65441321858593,\n 18.287140701134334\n ],\n [\n -64.65441321858593,\n 18.38265061411741\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -64.91799534519654,\n 17.811855495330647\n ],\n [\n -64.91799534519654,\n 17.657306327448765\n ],\n [\n -64.54674404449649,\n 17.657306327448765\n ],\n [\n -64.54674404449649,\n 17.811855495330647\n ],\n [\n -64.91799534519654,\n 17.811855495330647\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"397","noUsgsAuthors":false,"publicationDate":"2025-12-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Reguero, Borja","contributorId":264485,"corporation":false,"usgs":false,"family":"Reguero","given":"Borja","affiliations":[{"id":6949,"text":"University of California, Santa Cruz","active":true,"usgs":false}],"preferred":false,"id":953291,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gaido-Lassare, Camila","contributorId":364839,"corporation":false,"usgs":false,"family":"Gaido-Lassare","given":"Camila","affiliations":[{"id":17620,"text":"UCSC","active":true,"usgs":false}],"preferred":false,"id":953292,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Storlazzi, Curt D. 0000-0001-8057-4490","orcid":"https://orcid.org/0000-0001-8057-4490","contributorId":213610,"corporation":false,"usgs":true,"family":"Storlazzi","given":"Curt","middleInitial":"D.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":953293,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McNulty, Valerie","contributorId":341998,"corporation":false,"usgs":false,"family":"McNulty","given":"Valerie","affiliations":[{"id":33811,"text":"TNC","active":true,"usgs":false}],"preferred":false,"id":953294,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Perez, Denise","contributorId":341897,"corporation":false,"usgs":false,"family":"Perez","given":"Denise","email":"","affiliations":[{"id":33811,"text":"TNC","active":true,"usgs":false}],"preferred":false,"id":953295,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Beck, Michael W.","contributorId":259298,"corporation":false,"usgs":false,"family":"Beck","given":"Michael","email":"","middleInitial":"W.","affiliations":[{"id":6949,"text":"University of California, Santa Cruz","active":true,"usgs":false}],"preferred":true,"id":953296,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70273205,"text":"70273205 - 2026 - From sample to sonde to Sentinel-2: Insights from a multi-scale chlorophyll-a monitoring effort in the Hudson River, New York","interactions":[],"lastModifiedDate":"2025-12-19T14:48:05.059591","indexId":"70273205","displayToPublicDate":"2025-12-09T08:42:26","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1552,"text":"Environmental Monitoring and Assessment","onlineIssn":"1573-2959","printIssn":"0167-6369","active":true,"publicationSubtype":{"id":10}},"title":"From sample to sonde to Sentinel-2: Insights from a multi-scale chlorophyll-a monitoring effort in the Hudson River, New York","docAbstract":"Monitoring cyanobacteria and other nuisance phytoplankton in the Hudson River is of great interest given its societal and ecological importance. Satellite remote sensing provides a cost-effective method to monitor chlorophyll-a (chl-a), a common proxy for algal biomass; however, the dynamic nature of rivers complicates approaches traditionally applied to lakes and oceans. During 2021–2023, we collected discrete samples for laboratory measurement of chl-a and measured in situ chl-a fluorescence during a series of longitudinal boat surveys along a 220-km reach of the lower Hudson River. Surveys were timed to coincide with Sentinel-2 satellite overpasses. We first investigated relations between laboratory-measured chl-a concentration and field-measured chl-a fluorescence, observing a weak correlation (r2 = 0.25) that improved substantially after splitting data by day (mean r2 = 0.53). Separately, to estimate chl-a fluorescence using satellite data, we developed a series of random forest models leveraging the rich fluorescence dataset collected. We tested three model types: individual day models, leave-one-out models trained on all days except a holdout test day, and a single pooled model trained on all days. Generally, individual day models exhibited lowest error (mean of mean absolute error [MAE] = 0.16 relative fluorescence units [RFU]), followed by the single pooled model (MAE = 0.22 RFU). Daily holdout models showed highest error (mean MAE = 0.40 RFU); this approach was intended to represent model performance on a day unseen in the training set, providing a more conservative estimate of performance than the more traditional pooled approach. Findings from both analyses emphasize the importance of considering temporal variability when modeling riverine systems.
","language":"English","publisher":"Springer Nature","doi":"10.1007/s10661-025-14844-3","usgsCitation":"Salls, W.B., Welk, R., King, T.V., Scavotto, N., Gorney, R.M., Gifford, S.R., Stouder, M.D., Nystrom, E.A., and Graham, J.L., 2026, From sample to sonde to Sentinel-2: Insights from a multi-scale chlorophyll-a monitoring effort in the Hudson River, New York: Environmental Monitoring and Assessment, v. 198, 25, 30 p., https://doi.org/10.1007/s10661-025-14844-3.","productDescription":"25, 30 p.","ipdsId":"IP-176108","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":498038,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10661-025-14844-3","text":"Publisher Index Page"},{"id":497763,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Jersey, New York","otherGeospatial":"Hudson River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -73.53385971301769,\n 42.80598359016898\n ],\n [\n -74.21892882912005,\n 42.80598359016898\n ],\n [\n -74.21892882912005,\n 40.6507605560374\n ],\n [\n -73.53385971301769,\n 40.6507605560374\n ],\n [\n -73.53385971301769,\n 42.80598359016898\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"198","noUsgsAuthors":false,"publicationDate":"2025-12-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Salls, Wilson Barg 0000-0001-7505-0828","orcid":"https://orcid.org/0000-0001-7505-0828","contributorId":364473,"corporation":false,"usgs":true,"family":"Salls","given":"Wilson","middleInitial":"Barg","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":952701,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Welk, 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0000-0002-0724-4986","orcid":"https://orcid.org/0000-0002-0724-4986","contributorId":310415,"corporation":false,"usgs":true,"family":"Gifford","given":"Sabina","email":"","middleInitial":"R.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":952706,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Stouder, Michael D.W. 0000-0002-0446-2574","orcid":"https://orcid.org/0000-0002-0446-2574","contributorId":301805,"corporation":false,"usgs":true,"family":"Stouder","given":"Michael","middleInitial":"D.W.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":952707,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Nystrom, Elizabeth A. 0000-0002-0886-3439 nystrom@usgs.gov","orcid":"https://orcid.org/0000-0002-0886-3439","contributorId":1072,"corporation":false,"usgs":true,"family":"Nystrom","given":"Elizabeth","email":"nystrom@usgs.gov","middleInitial":"A.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":952708,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Graham, Jennifer L. 0000-0002-6420-9335 jlgraham@usgs.gov","orcid":"https://orcid.org/0000-0002-6420-9335","contributorId":202923,"corporation":false,"usgs":true,"family":"Graham","given":"Jennifer","email":"jlgraham@usgs.gov","middleInitial":"L.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":true,"id":952709,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70273453,"text":"70273453 - 2026 - The 1912 Ms 7.2 earthquake in the Denali region of central Alaska","interactions":[],"lastModifiedDate":"2026-02-09T16:24:50.573071","indexId":"70273453","displayToPublicDate":"2025-11-20T09:50:26","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"displayTitle":"The 1912 Ms 7.2 earthquake in the Denali region of central Alaska","title":"The 1912 Ms 7.2 earthquake in the Denali region of central Alaska","docAbstract":"The 2002 Mw 7.9 earthquake in central Alaska ruptured 340 km on three faults—Susitna Glacier thrust fault, Denali fault, Totschunda fault—crossing both the Richardson Highway and the Alaska Pipeline. Its occurrence prompted renewed interest in historical large earthquakes that possibly originated on the Denali fault. One of these earthquakes was a Ms 7.2 event on July 7, 1912, which we revisit with two approaches: (1) probabilistic relocation of the epicenter using globally recorded arrival times, and (2) compilation and reassessment of shaking intensity reports to estimate a macroseismic epicenter. Our preferred instrumental epicenter is west of the Parks Highway and in agreement with the maximum‐reported shaking, which was from the Parker–Browne expedition of Denali. We also relocated a Ms 6.4 aftershock, whose epicenter is 11 km from the mainshock. Candidate faults for the 1912 earthquake include the Denali fault, the McLeod Creek thrust fault, and the Kantishna Hills thrust fault. Future analysis of active faults, paleoseismic results, 1912 instrumental data, and 1912 felt reports may help in interpreting the fault and mechanism of the 1912 earthquake.
","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120250150","usgsCitation":"Tape, C., Aquino-Lopez, M., Bemis, S., Haeussler, P., and Ginnaty, J., 2026, The 1912 Ms 7.2 earthquake in the Denali region of central Alaska: Bulletin of the Seismological Society of America, v. 116, no. 1, p. 322-354, https://doi.org/10.1785/0120250150.","productDescription":"33 p.","startPage":"322","endPage":"354","ipdsId":"IP-182077","costCenters":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"links":[{"id":498617,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":498703,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1785/0120250150","text":"Publisher Index Page"}],"country":"United States","state":"Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -169.43690719365998,\n 66.58359872082357\n ],\n [\n -169.43690719365998,\n 53.57022459464301\n ],\n [\n -130.19988331357695,\n 53.57022459464301\n ],\n [\n -130.19988331357695,\n 66.58359872082357\n ],\n [\n -169.43690719365998,\n 66.58359872082357\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"116","issue":"1","noUsgsAuthors":false,"publicationDate":"2025-11-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Tape, Carl","contributorId":219960,"corporation":false,"usgs":false,"family":"Tape","given":"Carl","email":"","affiliations":[{"id":40098,"text":"Geophysical Institute, 2156 Koyukuk Drive, University of Alaska Fairbanks, Fairbanks, AK 99775","active":true,"usgs":false}],"preferred":false,"id":953755,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Aquino-Lopez, Marco","contributorId":331553,"corporation":false,"usgs":false,"family":"Aquino-Lopez","given":"Marco","affiliations":[],"preferred":false,"id":953756,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bemis, Sean","contributorId":175460,"corporation":false,"usgs":false,"family":"Bemis","given":"Sean","affiliations":[{"id":27572,"text":"UK","active":true,"usgs":false}],"preferred":false,"id":953757,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Haeussler, Peter J. 0000-0002-1503-6247","orcid":"https://orcid.org/0000-0002-1503-6247","contributorId":219956,"corporation":false,"usgs":true,"family":"Haeussler","given":"Peter J.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"preferred":true,"id":953758,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ginnaty, Jessalyn","contributorId":365145,"corporation":false,"usgs":false,"family":"Ginnaty","given":"Jessalyn","affiliations":[{"id":7211,"text":"University of Alaska, Fairbanks","active":true,"usgs":false}],"preferred":false,"id":953759,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70273661,"text":"70273661 - 2026 - Demographic mechanisms of snowshoe hare population cycles in Yukon, Canada","interactions":[],"lastModifiedDate":"2026-01-22T15:15:07.211159","indexId":"70273661","displayToPublicDate":"2025-11-20T09:09:45","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2158,"text":"Journal of Animal Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Demographic mechanisms of snowshoe hare population cycles in Yukon, Canada","docAbstract":"The karst habitats of central Texas, USA, are home to an array of endemic subterranean-obligate (troglobiotic) invertebrates. This includes several species of rove beetles (Coleoptera: Staphylinidae: Pselaphinae). Here we developed a molecular dataset using sequence capture of Ultra-Conserved Elements (UCEs) from the Coleoptera-UCE-1.1 K v1 baits kit. These data were used to assess species relationships and patterns of diversification in this group, specifically among species within the genera Batrisodes Reitter 1882 and Texamaurops Barr and Steeves 1963; with a specific focus on the relationships of the federally listed as endangered B. texanus Chandler 1992 and B.cryptotexanus Chandler and Reddell 2001. Our final datasets consisted of 69 individuals (two genera, Batrisodes [five species] and Texamaurops [one species], from 34 localities), and a molecular dataset of 658,560 aligned base pairs across 672 UCE loci. Concatenated and species-tree phylogenetic analyses resolved all troglobiotic taxa as a monophyletic group. Within the Travis and Williamson County troglobionts, we recovered four well-supported clades that generally follow hypothesized geologic barriers to dispersal formalized as karst fauna regions (KFRs). A northward pattern of diversification was observed among these groups: (A) Texamaurops reddelli Barr and Steeves 1963 (Jollyville Plateau KFR); (B) Batrisodes reyesi Chandler 1997 (West Cedar Park and Post Oak Ridge KFRs); (C) B. reyesi (McNeil-Round Rock KFR); (D) B. cryptotexanus + B. texanus (Georgetown and North Williamson KFRs). The morphologically defined Batrisodes texanus and B. cryptotexanus were not reciprocally monophyletic, nor clustered into two unique groups in clustering analyses of single nucleotide polymorphisms (SNPs). Rather, we found support for five major subclades and five to seven genetic clusters. These results suggest that diversification and subsequent isolation of clades may have occurred with the progressive availability of karst habitats over time in the North Williamson and Georgetown KFRs resulting from the interactions of faulting, geologic structure, and drainage basin evolution. Comparison with recent U.S. Fish and Wildlife Service cave habitat resiliency assessments indicated that four genetic clusters occur within at least partially resilient habitat, whereas three are confined to caves with low or impaired resiliency. Integrating genetic results presented here along with results of other molecular studies of co-occurring troglobiotic invertebrates supports considering additional geological substructure within the North Williamson KFR in conservation efforts for these rare and unique lineages and systems.
","language":"English","publisher":"Springer Nature","doi":"10.1007/s10592-025-01733-y","usgsCitation":"Wood, P.L., Chandler, D.S., Gladstone, N.S., Mitelberg, A., Smith, J.G., White, K., Wilson, J., and Vandergast, A.G., 2026, Phylogenomics of endangered troglobiotic rove beetles (Coleoptera: Staphylinidae: Pselaphinae) from central Texas karst regions: Conservation Genetics, v. 27, 6, 17 p., https://doi.org/10.1007/s10592-025-01733-y.","productDescription":"6, 17 p.","ipdsId":"IP-180017","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":497406,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10592-025-01733-y","text":"Publisher Index Page"},{"id":497192,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Texas","otherGeospatial":"central Texas","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -98.73468272013145,\n 32.73358466173568\n ],\n [\n -98.73468272013145,\n 30.565934073926556\n ],\n [\n -96.59794469143151,\n 30.565934073926556\n ],\n [\n -96.59794469143151,\n 32.73358466173568\n ],\n [\n -98.73468272013145,\n 32.73358466173568\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"27","noUsgsAuthors":false,"publicationDate":"2025-11-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Wood, Perry L. Jr. 0000-0003-3767-5274","orcid":"https://orcid.org/0000-0003-3767-5274","contributorId":363405,"corporation":false,"usgs":true,"family":"Wood","given":"Perry","suffix":"Jr.","middleInitial":"L.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":951627,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chandler, Donald S.","contributorId":363406,"corporation":false,"usgs":false,"family":"Chandler","given":"Donald","middleInitial":"S.","affiliations":[{"id":12667,"text":"University of New Hampshire","active":true,"usgs":false}],"preferred":false,"id":951628,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gladstone, Nicholas S.","contributorId":363407,"corporation":false,"usgs":false,"family":"Gladstone","given":"Nicholas","middleInitial":"S.","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":951629,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mitelberg, Anna 0000-0002-3309-9946 amitelberg@usgs.gov","orcid":"https://orcid.org/0000-0002-3309-9946","contributorId":218945,"corporation":false,"usgs":true,"family":"Mitelberg","given":"Anna","email":"amitelberg@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":951630,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Smith, Julia G. 0000-0001-9841-1809","orcid":"https://orcid.org/0000-0001-9841-1809","contributorId":221086,"corporation":false,"usgs":true,"family":"Smith","given":"Julia","email":"","middleInitial":"G.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":951631,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"White, Kemble","contributorId":363408,"corporation":false,"usgs":false,"family":"White","given":"Kemble","affiliations":[{"id":86694,"text":"Cambrian Environmental","active":true,"usgs":false}],"preferred":false,"id":951632,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Wilson, Jenny","contributorId":363409,"corporation":false,"usgs":false,"family":"Wilson","given":"Jenny","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":951633,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Vandergast, Amy G. 0000-0002-7835-6571","orcid":"https://orcid.org/0000-0002-7835-6571","contributorId":57201,"corporation":false,"usgs":true,"family":"Vandergast","given":"Amy","middleInitial":"G.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":951634,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70272719,"text":"70272719 - 2026 - Variation in soil organic carbon across a latitudinal chronosequence of mangrove poleward expansion","interactions":[],"lastModifiedDate":"2025-12-05T16:10:48.459229","indexId":"70272719","displayToPublicDate":"2025-11-10T10:03:52","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1478,"text":"Ecosystems","active":true,"publicationSubtype":{"id":10}},"title":"Variation in soil organic carbon across a latitudinal chronosequence of mangrove poleward expansion","docAbstract":"The critical carbon sink provided by coastal wetlands, known as blue carbon, can be affected by multiple aspects of climate change. One important example is warming-induced mangrove poleward expansion, which is shifting dominant plant cover across tropical–temperate transitional zones and altering ecosystem structure and function. We examined how mangrove expansion affects soil organic carbon (SOC) quantity and source, using measurements of SOC density and isotopic signatures (δ13C and δ15N) at 15 sites across Florida’s west coast (USA). The sampled sites represent examples of three expansion stages: a latitudinal chronosequence of mangrove expansion, spanning mature mangroves in the south, former ecotones at mid latitudes, and current ecotones in the north. Our analyses of soil core data indicate that mangrove expansion stage is a significant predictor of SOC density, δ13C, and δ15N, but not C:N ratio. Current ecotones exhibited significantly lower SOC density but higher δ13C, suggesting a greater contribution of preexisting C4 salt marshes, while no difference was found between former ecotones and mature mangroves. SOC density, δ13C, and δ15N were found to vary with mangrove aboveground biomass, stage, and sedimentary setting along the latitudinal gradient. For all three mangrove expansion stages, SOC density decreased with depth, but δ13C showed no vertical trend, suggesting that mangroves contributed organic carbon to the entire 20-cm soil profile. The observed regional trend of SOC across mangrove expansion stages highlights the ecological impacts of warming-driven vegetation shifts in coastal wetlands, though further evidence is needed to determine the primary drivers and mechanisms, while also considering local and regional environmental factors.
","language":"English","publisher":"Springer","doi":"10.1007/s10021-025-01021-3","usgsCitation":"Kang, Y., Assavapanuvat, P., Osland, M., and Kaplan, D.A., 2026, Variation in soil organic carbon across a latitudinal chronosequence of mangrove poleward expansion: Ecosystems, v. 29, no. 1, 2, 16 p., https://doi.org/10.1007/s10021-025-01021-3.","productDescription":"2, 16 p.","ipdsId":"IP-177314","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":497146,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -81.32160751894271,\n 25.054902179361207\n ],\n [\n -80.63726301014596,\n 25.258298250546616\n ],\n [\n -81.8527400049156,\n 27.227832172418474\n ],\n [\n -82.33280191711681,\n 28.84154022988217\n ],\n [\n -83.06821596269705,\n 29.7501155011185\n ],\n [\n -84.31432949640975,\n 30.536225351129545\n ],\n [\n -84.93739349566832,\n 30.13070589776649\n ],\n [\n -85.98944614179287,\n 30.421797338238022\n ],\n [\n -86.25501595921092,\n 30.342496828735193\n ],\n [\n -85.20296443450356,\n 29.55483610748952\n ],\n [\n -84.09984046033792,\n 29.989262856477296\n ],\n [\n -82.94564883333466,\n 28.859434680310557\n ],\n [\n -83.07843222809143,\n 27.699106909720854\n ],\n [\n -81.32160751894271,\n 25.054902179361207\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"29","issue":"1","noUsgsAuthors":false,"publicationDate":"2025-11-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Kang, Yiyang","contributorId":305365,"corporation":false,"usgs":false,"family":"Kang","given":"Yiyang","email":"","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":951430,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Assavapanuvat, Prakhin","contributorId":363279,"corporation":false,"usgs":false,"family":"Assavapanuvat","given":"Prakhin","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":951431,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Osland, Michael J. 0000-0001-9902-8692","orcid":"https://orcid.org/0000-0001-9902-8692","contributorId":206443,"corporation":false,"usgs":true,"family":"Osland","given":"Michael","middleInitial":"J.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":951432,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kaplan, David A.","contributorId":363282,"corporation":false,"usgs":false,"family":"Kaplan","given":"David","middleInitial":"A.","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":951433,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70272143,"text":"70272143 - 2026 - Refined chronology of late Quaternary eruptions at Harrat Khaybar, Saudi Arabia, with implications for magma dynamics and regional volcanic history","interactions":[],"lastModifiedDate":"2026-03-09T14:33:25.048727","indexId":"70272143","displayToPublicDate":"2025-11-05T08:00:19","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1723,"text":"GSA Bulletin","active":true,"publicationSubtype":{"id":10}},"title":"Refined chronology of late Quaternary eruptions at Harrat Khaybar, Saudi Arabia, with implications for magma dynamics and regional volcanic history","docAbstract":"Determining accurate and precise ages for Quaternary volcanic centers is essential for reconstructing volcanic field histories, understanding magmatic processes, and assessing potential hazards or risk. Harrat Khaybar, western Saudi Arabia, is one of the youngest and potentially most active volcanic fields on the Arabian plate, has been active since ca. 1.7 Ma, and is characterized by a spectrum of rock compositions ranging from predominantly alkalic basalt to trachyte and comendite. Previous work in Harrat Khaybar utilizing 40Ar/39Ar incremental heating geochronology to constrain morphological preservation and superpositional relationships bracketed the volcanic activity into broad age groups in intervals of ∼150 k.y., and the youngest and most compositionally evolved volcanoes, including Jabal Abyad, Jabal Bayda, and Jabal Qidr, were assigned to the age groups between ca. 300 ka and present. Herein, we establish a detailed chronology of prehistoric silicic and historical basaltic eruptions at central Harrat Khaybar using four independent eruption age determination techniques: zircon double-dating (ZDD), which combines 238U-230Th disequilibrium or U-Pb with (U-Th)/He dating; zircon U-Pb dating; cosmogenic 3He dating; and cosmogenic 36Cl geochronology. These were employed to accurately date six volcanic centers, including the comenditic Jabal Abyad, Jabal Bayda, Jabal Ibayl, and Jabal Alhayyirah, the trachytic Jabal Aluthmor, and the basaltic Jabal Qidr. Additionally, our previously published 40Ar/39Ar ages have been recalculated using isochron intercept (nonatmospheric) 40Ar/36Ar for the trapped Ar component. Our new results reveal that zircon rims from Jabal Abyad and Jabal Bayda define isochron 238U-230Th crystallization ages of 125 ± 4 ka and 144 ± 6 ka, concordant with ZDD eruption ages of 132 ± 4 ka and 149 ± 5 ka, respectively. Zircon U-Pb crystallization and (U-Th)/He eruption ages from Jabal Alhayyirah are concordant at 471 ± 14 ka and 458 ± 18 ka, respectively. Finally, zircons from the nearby Jabal Ibayl yield a U-Pb weighted mean crystallization age of 566 ± 16 ka concordant with the corresponding (U-Th)/He eruption age of 554 ± 12 ka, both of which are notably older than the previously proposed eruption ages of 300−150 ka. Recalculations of published 40Ar/39Ar ages for the youngest volcanoes at central Harrat Khaybar are now in excellent agreement with new geochronological data.
Our new age data reveal several new insights into the development of Harrat Khaybar. It is now clear that the comenditic eruptions do not belong to the same eruptive phase and indicate an extended history during which comendites have episodically punctuated the basaltic volcanism since at least 600 ka. The data indicate that Jabal Ibayl and Jabal Alhayyirah represent separate older volcanic events, whereas the younger Jabal Abyad and Jabal Bayda volcanoes appear to be coeval, and their spatial proximity implies that they share a magmatic lineage and maybe a common plumbing system. Zircon age spectra of the comendites reveal obvious xenocrysts and antecrysts indicating assimilation of basement and plutonic progenitors, but otherwise they define broad unimodal populations of crystallization ages that overlap within error with the respective eruption ages. We interpret this to indicate that zircon crystallization continued up to the time of eruption. The cosmogenic ages of Jabal Aluthmor and Jabal Qidr reveal that these centers erupted as recently as ca. 2000 and 760 years ago, respectively. Broadly coeval young silicic and basaltic eruptions at northern Harrat Rahat, the harrat immediately south of Harrat Khaybar, may imply a shared geodynamic forcing between the two adjacent volcanic fields.
","language":"English","publisher":"GeoScienceWorld","doi":"10.1130/B38611.1","usgsCitation":"Aohali, A., de Silva, S.L., de Leon, A., Lewis, C., Schmitt, A.K., Danišík, M., Stelten, M.E., Mukhopadhyay, S., Duncan, R., and Ramos, F.C., 2026, Refined chronology of late Quaternary eruptions at Harrat Khaybar, Saudi Arabia, with implications for magma dynamics and regional volcanic history: GSA Bulletin, 20 p., https://doi.org/10.1130/B38611.1.","productDescription":"20 p.","ipdsId":"IP-179667","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":496536,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Saudi Arabia","otherGeospatial":"Harrat Khaybar","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 32.85295692715516,\n 31.09037520506034\n ],\n [\n 32.4913950501539,\n 29.629285602110514\n ],\n [\n 42.48408268197696,\n 16.295959844508005\n ],\n [\n 44.73156011376457,\n 17.35801132821274\n ],\n [\n 44.40883286040667,\n 19.46824225247422\n ],\n [\n 45.04342709873005,\n 21.136426902843187\n ],\n [\n 43.12386232882824,\n 25.38842500405898\n ],\n [\n 39.48524523909565,\n 28.58924888259447\n ],\n [\n 37.25829032269033,\n 29.051927055631452\n ],\n [\n 32.85295692715516,\n 31.09037520506034\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","edition":"Online First","noUsgsAuthors":false,"publicationDate":"2025-11-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Aohali, Abdullah","contributorId":362243,"corporation":false,"usgs":false,"family":"Aohali","given":"Abdullah","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":950211,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"de Silva, Shanaka L. 0000-0002-0310-5516","orcid":"https://orcid.org/0000-0002-0310-5516","contributorId":242616,"corporation":false,"usgs":false,"family":"de Silva","given":"Shanaka","email":"","middleInitial":"L.","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":950212,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"de Leon, Alejandro Cisneros 0000-0002-0133-2838","orcid":"https://orcid.org/0000-0002-0133-2838","contributorId":362244,"corporation":false,"usgs":false,"family":"de Leon","given":"Alejandro Cisneros","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":950213,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lewis, Charles","contributorId":362245,"corporation":false,"usgs":false,"family":"Lewis","given":"Charles","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":950214,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Schmitt, Axel K.","contributorId":362246,"corporation":false,"usgs":false,"family":"Schmitt","given":"Axel","middleInitial":"K.","affiliations":[{"id":13639,"text":"Curtin University","active":true,"usgs":false}],"preferred":false,"id":950215,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Danišík, Martin","contributorId":362247,"corporation":false,"usgs":false,"family":"Danišík","given":"Martin","affiliations":[{"id":13639,"text":"Curtin University","active":true,"usgs":false}],"preferred":false,"id":950216,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Stelten, Mark E. 0000-0002-5294-3161 mstelten@usgs.gov","orcid":"https://orcid.org/0000-0002-5294-3161","contributorId":145923,"corporation":false,"usgs":true,"family":"Stelten","given":"Mark","email":"mstelten@usgs.gov","middleInitial":"E.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":950217,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Mukhopadhyay, Sujoy","contributorId":362248,"corporation":false,"usgs":false,"family":"Mukhopadhyay","given":"Sujoy","affiliations":[{"id":6607,"text":"Arizona State University","active":true,"usgs":false}],"preferred":false,"id":950218,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Duncan, Robert","contributorId":362249,"corporation":false,"usgs":false,"family":"Duncan","given":"Robert","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":950219,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Ramos, Frank C.","contributorId":362250,"corporation":false,"usgs":false,"family":"Ramos","given":"Frank","middleInitial":"C.","affiliations":[{"id":12628,"text":"New Mexico State University","active":true,"usgs":false}],"preferred":false,"id":950220,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70271326,"text":"70271326 - 2026 - Origin and evolution of mafic volcanism associated with 3 m.y. of andesite production at the Goat Rocks volcanic cluster, southern Washington Cascade Range","interactions":[],"lastModifiedDate":"2026-01-05T16:42:08.542449","indexId":"70271326","displayToPublicDate":"2025-09-04T08:06:46","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1786,"text":"Geological Society of America Bulletin","active":true,"publicationSubtype":{"id":10}},"title":"Origin and evolution of mafic volcanism associated with 3 m.y. of andesite production at the Goat Rocks volcanic cluster, southern Washington Cascade Range","docAbstract":"More than 3 m.y. of mafic volcanism near the Goat Rocks volcanic cluster in the southern Washington Cascade Range, USA, lends insight into the evolution of basalts and the subarc mantle at a long-lived, major arc volcanic locus. We contribute field observations, 40Ar/39Ar dates, paleomagnetic directions, and bulk rock and mineral compositions to characterize nine mafic units that erupted in association with the Goat Rocks volcanic cluster. The time frame of mafic volcanism, ca. 3.6 Ma to 60 ka, encompasses the lifespan of the central volcanic cluster (3.1 Ma to 115 ka), with a lull from ca. 2.7 Ma to 1.4 Ma. A climactic period of voluminous mafic activity and far-traveled lava flows, including construction of the Hogback Mountain shield volcano, coincided with voluminous andesite eruptions from the central volcanic cluster.
The basaltic rocks in the Goat Rocks area are calc-alkaline to barely tholeiitic and have high field strength element depletion relative to large-ion lithophile elements characteristic of calc-alkaline basalts (CAB) of the Cascade volcanic arc. Unlike at neighboring andesitic volcanic centers (Mounts Adams, St. Helens, and Rainier), no other mafic end members such as high-aluminum olivine tholeiite (HAOT) or intraplate-type basalt (IPB) are present at or near the Goat Rocks volcanic cluster, although some of the calc-alkaline basalts in this study have IPB-like affinities. The Goat Rocks mafic units exhibit two main temporal trends in composition: (1) the most primitive basalts erupted earlier, compared to less primitive and more evolved compositions later, and (2) high field strength element concentrations are higher in the younger basalt units relative to the oldest two. In contrast to these temporal trends, the mafic units define two compositional groups that recur through time, a low-Sr and a high-Sr group, each with distinct trace element and Sr and Nd isotope ratios. Although radiogenic isotope ratios are generally aligned with High Cascades CAB and HAOT, some extend toward IPB of Mount Adams and Simcoe Mountains volcanic field.
Olivine-dominated crystal fractionation at shallow pressure from a small range of parent magma compositions accounts for much of the variation among the basalts and basaltic andesites. A high-pressure fractionation model is plausible for only one of the youngest basalt units (basalt of Walupt Lake volcano). Mafic recharge and crustal assimilation accounts for the incompatible-element enriched composition of basaltic andesites erupted during construction of the largest andesitic centers, further supporting sustained basalt mass flux and thermal energy driving andesite genesis.
We model the most primitive members of the Goat Rocks mafic units as partial melts of successively less depleted mantle in time. Variable degrees of fluxing with fluids and melts from subduction explain the distinction between high-Sr and low-Sr groups. We propose that mantle metasomatism by ancestral subduction and fluid-flux melting is heterogeneously distributed through the local subarc mantle and played a greater role in the genesis of the high-Sr basalt group.
The limited range of primitive basalt types around the Goat Rocks volcanic cluster contrasts with the much greater diversity of basalts throughout the southern Washington to northern Oregon Cascade arc. On the other hand, the central volcanic cluster encompasses nearly the entire diversity observed at neighboring composite volcanoes. In the case of the Goat Rocks area at least, and perhaps attributable to the entire region, this means that the genesis of diverse intermediate magmas is independent from and does not require vastly different parental basalt compositions.
","language":"English","publisher":"Geological Society of America","doi":"10.1130/B38046.1","usgsCitation":"Wall, K., Grunder, A.L., Biasi, J., Weis, D., Swanson, D., and Stelten, M.E., 2026, Origin and evolution of mafic volcanism associated with 3 m.y. of andesite production at the Goat Rocks volcanic cluster, southern Washington Cascade Range: Geological Society of America Bulletin, v. 138, no. 1-2, p. 709-743, https://doi.org/10.1130/B38046.1.","productDescription":"35 p.","startPage":"709","endPage":"743","ipdsId":"IP-171208","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":495199,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","state":"California, Oregon, Washington","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -128.395483482341,\n 50.865572536238915\n ],\n [\n -125.60869035746057,\n 46.041667735587566\n ],\n [\n -124.98377466492585,\n 38.57668752987752\n ],\n [\n -120.96754220889056,\n 38.41486403323435\n ],\n [\n -121.34435422163615,\n 48.16096017318148\n ],\n [\n -123.77679244748882,\n 51.47194946290554\n ],\n [\n -128.395483482341,\n 50.865572536238915\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"138","issue":"1-2","noUsgsAuthors":false,"publicationDate":"2025-09-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Wall, Kellie Taylor 0000-0002-2391-6658","orcid":"https://orcid.org/0000-0002-2391-6658","contributorId":353879,"corporation":false,"usgs":true,"family":"Wall","given":"Kellie Taylor","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":948055,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Grunder, Anita L.","contributorId":194549,"corporation":false,"usgs":false,"family":"Grunder","given":"Anita","middleInitial":"L.","affiliations":[],"preferred":false,"id":948056,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Biasi, Joseph","contributorId":189110,"corporation":false,"usgs":false,"family":"Biasi","given":"Joseph","email":"","affiliations":[],"preferred":false,"id":948057,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Weis, Dominique","contributorId":236887,"corporation":false,"usgs":false,"family":"Weis","given":"Dominique","affiliations":[],"preferred":false,"id":948058,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Swanson, Don 0000-0002-1680-3591 donswan@usgs.gov","orcid":"https://orcid.org/0000-0002-1680-3591","contributorId":168817,"corporation":false,"usgs":true,"family":"Swanson","given":"Don","email":"donswan@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":948059,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Stelten, Mark E. 0000-0002-5294-3161 mstelten@usgs.gov","orcid":"https://orcid.org/0000-0002-5294-3161","contributorId":145923,"corporation":false,"usgs":true,"family":"Stelten","given":"Mark","email":"mstelten@usgs.gov","middleInitial":"E.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":948060,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70274076,"text":"70274076 - 2026 - Temporal associations between ambrosia beetles and ʻōhiʻa (Metrosideros polymorpha) artificially inoculated with Ceratocystis lukuohia","interactions":[],"lastModifiedDate":"2026-02-23T16:21:05.664149","indexId":"70274076","displayToPublicDate":"2025-08-11T10:15:47","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":17777,"text":"Agricultural and Forest Entomology","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Temporal associations between ambrosia beetles and ʻōhiʻa (Metrosideros polymorpha) artificially inoculated with Ceratocystis lukuohia","title":"Temporal associations between ambrosia beetles and ʻōhiʻa (Metrosideros polymorpha) artificially inoculated with Ceratocystis lukuohia","docAbstract":"1. The biodiversity crisis necessitates spatially extensive methods to monitor multiple taxonomic groups for evidence of change in response to evolving environmental conditions. Programs that combine passive acoustic monitoring and machine learning are increasingly used to meet this need. These methods require large, annotated datasets, which are time-consuming and expensive to produce, creating potential barriers to adoption in data- and funding-poor regions. Recently released pre-trained avian acoustic classification models provide opportunities to reduce the need for manual labelling and accelerate the development of new acoustic classification algorithms through transfer learning. Transfer learning is a strategy for developing algorithms under data scarcity that uses pre-trained models from related tasks to adapt to new tasks.
2. Our primary objective was to develop a transfer learning strategy using the feature embeddings of a pre-trained avian classification model to train custom acoustic classification models in data-scarce contexts. We used three annotated avian acoustic datasets to test whether transfer learning and soundscape simulation-based data augmentation could substantially reduce the annotated training data necessary to develop performant custom acoustic classifiers. We also conducted a sensitivity analysis for hyperparameter choice and model architecture. We then assessed the generalizability of our strategy to increasingly novel non-avian classification tasks.
3. With as few as two training examples per class, our soundscape simulation data augmentation approach consistently yielded new classifiers with improved performance relative to the pre-trained classification model and transfer learning classifiers trained with other augmentation approaches. Performance increases were evident for three avian test datasets, including single-class and multi-label contexts. We observed that the relative performance among our data augmentation approaches varied for the avian datasets and nearly converged for one dataset when we included more training examples.
4. We demonstrate an efficient approach to developing new acoustic classifiers leveraging open-source sound repositories and pre-trained networks to reduce manual labelling. With very few examples, our soundscape simulation approach to data augmentation yielded classifiers with performance equivalent to those trained with many more examples, showing it is possible to reduce manual label-ling while still achieving high-performance classifiers and, in turn, expanding the potential for passive acoustic monitoring to address rising biodiversity monitoring needs.
","language":"English","publisher":"British Ecological Society","doi":"10.1111/2041-210X.70089","usgsCitation":"Weldy, M.J., Lesmeister, D.B., Denton, T., Duarte, A., Vernasco, B.J., Gasc, A., Rowe, J., Adams, M.J., and Betts, M., 2026, Simulated soundscapes and transfer learning boost the performance of acoustic classifiers under data scarcity: Methods in Ecology and Evolution, v. 17, no. 2, p. 322-338, https://doi.org/10.1111/2041-210X.70089.","productDescription":"17 p.","startPage":"322","endPage":"338","ipdsId":"IP-169596","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":491718,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/2041-210x.70089","text":"Publisher Index Page"},{"id":491528,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"17","issue":"2","noUsgsAuthors":false,"publicationDate":"2025-06-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Weldy, Matthew J","contributorId":300545,"corporation":false,"usgs":false,"family":"Weldy","given":"Matthew","email":"","middleInitial":"J","affiliations":[{"id":65191,"text":"Pacific Northwest Research Station, USDA Forest Service, Corvallis, OR 97331, USA; Department of Forest Ecosystems and Society, Oregon State University, Corvallis, OR 97331, USA","active":true,"usgs":false}],"preferred":false,"id":941424,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lesmeister, Damon B. 0000-0003-1102-0122","orcid":"https://orcid.org/0000-0003-1102-0122","contributorId":205006,"corporation":false,"usgs":false,"family":"Lesmeister","given":"Damon","email":"","middleInitial":"B.","affiliations":[{"id":37019,"text":"USDA Forest Service, Pacific Northwest Research Station","active":true,"usgs":false}],"preferred":false,"id":941425,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Denton, Tom 0000-0003-3866-0031","orcid":"https://orcid.org/0000-0003-3866-0031","contributorId":351479,"corporation":false,"usgs":false,"family":"Denton","given":"Tom","affiliations":[{"id":83995,"text":"Google Deepmind, Google","active":true,"usgs":false}],"preferred":false,"id":941426,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Duarte, Adam","contributorId":337608,"corporation":false,"usgs":false,"family":"Duarte","given":"Adam","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":941427,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Vernasco, Ben J.","contributorId":166945,"corporation":false,"usgs":false,"family":"Vernasco","given":"Ben","email":"","middleInitial":"J.","affiliations":[{"id":24577,"text":"University of Minnesota, St. Paul, MN","active":true,"usgs":false}],"preferred":false,"id":941428,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Gasc, Amandine 0000-0001-8369-4930","orcid":"https://orcid.org/0000-0001-8369-4930","contributorId":357451,"corporation":false,"usgs":false,"family":"Gasc","given":"Amandine","affiliations":[{"id":85421,"text":"Institut Méditerranéen de Biodiversité et d'Ecologie marine et continentale","active":true,"usgs":false}],"preferred":false,"id":941429,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Rowe, Jennifer 0000-0002-5253-2223 jrowe@usgs.gov","orcid":"https://orcid.org/0000-0002-5253-2223","contributorId":172670,"corporation":false,"usgs":true,"family":"Rowe","given":"Jennifer","email":"jrowe@usgs.gov","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":true,"id":941430,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Adams, Michael J. 0000-0001-8844-042X","orcid":"https://orcid.org/0000-0001-8844-042X","contributorId":211916,"corporation":false,"usgs":true,"family":"Adams","given":"Michael","email":"","middleInitial":"J.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":941431,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Betts, Matthew G.","contributorId":340630,"corporation":false,"usgs":false,"family":"Betts","given":"Matthew G.","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":941432,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70273393,"text":"70273393 - 2026 - Iguanas rafted more than 8,000 km from North America to Fiji","interactions":[],"lastModifiedDate":"2026-01-12T15:35:09.447753","indexId":"70273393","displayToPublicDate":"2025-03-17T09:31:35","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3164,"text":"Proceedings of the National Academy of Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Iguanas rafted more than 8,000 km from North America to Fiji","docAbstract":"Founder-event speciation can occur when one or more organisms colonize a distant, unoccupied area via long-distance dispersal, leading to the evolution of a new species lineage. Species radiations established by long-distance, and especially transoceanic, dispersal can cause substantial shifts in regional biodiversity. Here, we investigate the occurrence and timing of the greatest known long-distance oceanic dispersal event in the history of terrestrial vertebrates—the rafting of iguanas from North America to Fiji. Iguanas are large-bodied herbivores that are well-known overwater dispersers, including species that colonized the Caribbean and the Galápagos islands. However, the origin of Fijian iguanas had not been comprehensively tested. We estimated the phylogenetic relationships and evolutionary timescale of the iguanid lizard radiation using genome-wide exons and ultraconserved elements (UCEs). Those data indicate that the closest living relative of extant Fijian iguanas is the North American desert iguana and that the two taxa likely diverged during the late Paleogene near or after the onset of volcanism that produced the Fijian archipelago. Biogeographic models estimate North America as the most probable ancestral range of Fijian iguanas. Our analyses support the hypothesis that iguanas reached Fiji via an extraordinary oceanic dispersal event from western North America, and which spanned a fifth of the earth’s circumference (>8,000 km). Overwater rafting of iguanas from North America to Fiji strengthens the importance of founder-event speciation in the diversification of iguanids and elucidates the scope of long-distance dispersal across terrestrial vertebrates.
","language":"English","publisher":"National Academy of Sciences","doi":"10.1073/pnas.2318622122","usgsCitation":"Scarpetta, S.G., Fisher, R.D., Karin, B.R., Niukula, J.B., Corl, A., Jackman, T.R., and McGuire, J.A., 2026, Iguanas rafted more than 8,000 km from North America to Fiji: Proceedings of the National Academy of Sciences, v. 122, no. 12, e2318622122, 10 p., https://doi.org/10.1073/pnas.2318622122.","productDescription":"e2318622122, 10 p.","ipdsId":"IP-166203","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":498685,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1073/pnas.2318622122","text":"Publisher Index Page"},{"id":498552,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"122","issue":"12","noUsgsAuthors":false,"publicationDate":"2025-03-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Scarpetta, Simon G.","contributorId":364984,"corporation":false,"usgs":false,"family":"Scarpetta","given":"Simon","middleInitial":"G.","affiliations":[{"id":87022,"text":"University of San Francisco; UC Berkeley","active":true,"usgs":false}],"preferred":false,"id":953556,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fisher, Robert D. 0000-0002-2956-3240 rdfisher@usgs.gov","orcid":"https://orcid.org/0000-0002-2956-3240","contributorId":3913,"corporation":false,"usgs":true,"family":"Fisher","given":"Robert","email":"rdfisher@usgs.gov","middleInitial":"D.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":953557,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Karin, Benjamin R.","contributorId":364985,"corporation":false,"usgs":false,"family":"Karin","given":"Benjamin","middleInitial":"R.","affiliations":[{"id":6609,"text":"UC Berkeley","active":true,"usgs":false}],"preferred":false,"id":953558,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Niukula, Jone B.","contributorId":364986,"corporation":false,"usgs":false,"family":"Niukula","given":"Jone","middleInitial":"B.","affiliations":[{"id":87025,"text":"NatureFiji-MareqetiViti","active":true,"usgs":false}],"preferred":false,"id":953559,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Corl, Ammon","contributorId":364987,"corporation":false,"usgs":false,"family":"Corl","given":"Ammon","affiliations":[{"id":6609,"text":"UC Berkeley","active":true,"usgs":false}],"preferred":false,"id":953560,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Jackman, Todd R.","contributorId":364988,"corporation":false,"usgs":false,"family":"Jackman","given":"Todd","middleInitial":"R.","affiliations":[{"id":12766,"text":"Villanova University","active":true,"usgs":false}],"preferred":false,"id":953561,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"McGuire, Jimmy A.","contributorId":364989,"corporation":false,"usgs":false,"family":"McGuire","given":"Jimmy","middleInitial":"A.","affiliations":[{"id":6609,"text":"UC Berkeley","active":true,"usgs":false}],"preferred":false,"id":953562,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70273662,"text":"70273662 - 2025 - Moose survival and habitat‐associated risk of endoparasites","interactions":[],"lastModifiedDate":"2026-01-22T16:05:29.482923","indexId":"70273662","displayToPublicDate":"2025-12-29T09:56:14","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":"Moose survival and habitat‐associated risk of endoparasites","docAbstract":"Parasite-induced morbidity and mortality can alter the trajectories of incidental host populations. Yet, parasites rarely act in isolation and may be one of a multitude of biotic and abiotic stressors that collectively shape mortality risk in vertebrate populations. We quantified sources of mortality in a low-density population of moose (Alces alces) in New York State and investigated factors including parasite infection, nutritional limitation, and thermal stress influencing mortality risk in calf moose. We observed high rates of annual survival (0.81–0.92) in adult (n = 25) and calf (n = 27) moose monitored 2015–2018 and 2022–2024, respectively. The majority of cause-specific mortality was attributed to disease induced by giant liver fluke (Fascioloides magna; 75% in adults, 67% in calves). Calf mortality risk increased by 72% for every unit increase in giant liver fluke infection risk, measured as cumulative monthly proportion of wetlands used by moose, and decreased by 16% with each additional unit of nutritional energy available. The combination of flukes, coinfecting parasites, and available nutritional energy is important to calf survival in this population, highlighting the importance of managing multiple stressors for species conservation, although the effects are hard to disentangle given the high rates of survival observed. Identifying causes of mortality and mechanisms underlying increased mortality risk contributes to the continued conservation of moose in fluctuating populations and highlights the importance of managing parasite-induced disease.
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