{"pageNumber":"39","pageRowStart":"950","pageSize":"25","recordCount":46619,"records":[{"id":70264978,"text":"70264978 - 2025 - Local, regional, and distal recordings of seismic unrest at Tau Island volcano, American Samoa","interactions":[],"lastModifiedDate":"2025-03-27T15:18:39.378071","indexId":"70264978","displayToPublicDate":"2025-02-13T08:09:26","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1109,"text":"Bulletin of Volcanology","active":true,"publicationSubtype":{"id":10}},"title":"Local, regional, and distal recordings of seismic unrest at Tau Island volcano, American Samoa","docAbstract":"A seismic swarm near Taʻū Island, a volcanic island in eastern American Samoa, occurred from July to October 2022. The earliest unrest was noted as felt shaking reports in late July, and instrumentation varied in the beginning of the sequence as the U.S. Geological Survey (USGS) Hawaiian Volcano Observatory responded by installing temporary and then permanent seismometers to monitor the activity. This network variability made it difficult to characterize the earliest seismicity and contextualize the entire sequence to discriminate between an underlying tectonic or volcanic source. Here, we present results analyzing hydroacoustic detections from an International Monitoring System hydrophone array near Wake Island, 4500 km northwest of Taʻū Island volcano. Using least-squares beamforming analysis, we create a catalog of T-wave detections from the direction of Taʻū Island to track the earthquakes, some of which were located by the USGS National EarthquakeInformation Center. Both the rate and hydroacoustic pressures, which we interpret as a proxy for earthquake size, gradually increased from late July to August, peaking on August 19 (rate) and August 24 (size), before decreasing to background in late September. Minutes-long bursts of tremor were also contemporaneously recorded as local network data became avail-able on August 20. Tremor activity continued throughout the rest of August, peaking on August 25, before ending in earlySeptember. These tremor bursts were band-limited to ~ 1–5 Hz and recorded as S waves at a regional station on the island of Upolu in Samoa, 250 km to the west of Taʻū Island. Our results do not constrain the tremor locations, but comparisons of earthquake and tremor reduced displacements recorded locally and regionally suggest a deeper tremor source. We interpret the increase in earthquake size and rate, together with the occurrence, characteristics, and relative depth of the tremor to be the result of magmatic activity beneath Taʻū Island volcano.","language":"English","publisher":"Springer Nature","doi":"10.1007/s00445-025-01798-0","usgsCitation":"Wech, A., Haney, M.M., Chang, J., Jolly, A., Yoon, C., and Skoumal, R.J., 2025, Local, regional, and distal recordings of seismic unrest at Tau Island volcano, American Samoa: Bulletin of Volcanology, v. 87, 15, 15 p., https://doi.org/10.1007/s00445-025-01798-0.","productDescription":"15, 15 p.","ipdsId":"IP-172244","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":483947,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"American Samoa, Taʻū Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -169.53339284390117,\n -14.197912338111138\n ],\n [\n -169.53339284390117,\n -14.283297461659885\n ],\n [\n -169.4061487117877,\n -14.283297461659885\n ],\n [\n -169.4061487117877,\n -14.197912338111138\n ],\n [\n -169.53339284390117,\n -14.197912338111138\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"87","noUsgsAuthors":false,"publicationDate":"2025-02-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Wech, Aaron 0000-0003-4983-1991","orcid":"https://orcid.org/0000-0003-4983-1991","contributorId":202561,"corporation":false,"usgs":true,"family":"Wech","given":"Aaron","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":932148,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Haney, Matthew M. 0000-0003-3317-7884 mhaney@usgs.gov","orcid":"https://orcid.org/0000-0003-3317-7884","contributorId":172948,"corporation":false,"usgs":true,"family":"Haney","given":"Matthew","email":"mhaney@usgs.gov","middleInitial":"M.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true}],"preferred":true,"id":932149,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Chang, Jefferson 0000-0002-1258-589X","orcid":"https://orcid.org/0000-0002-1258-589X","contributorId":215608,"corporation":false,"usgs":true,"family":"Chang","given":"Jefferson","email":"","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":932150,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jolly, A.D. 0000-0003-1020-9062","orcid":"https://orcid.org/0000-0003-1020-9062","contributorId":296487,"corporation":false,"usgs":true,"family":"Jolly","given":"A.D.","email":"","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":932151,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Yoon, Clara 0000-0003-4521-3889","orcid":"https://orcid.org/0000-0003-4521-3889","contributorId":222019,"corporation":false,"usgs":true,"family":"Yoon","given":"Clara","email":"","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":932152,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Skoumal, Robert J. 0000-0002-5627-6239 rskoumal@usgs.gov","orcid":"https://orcid.org/0000-0002-5627-6239","contributorId":191213,"corporation":false,"usgs":true,"family":"Skoumal","given":"Robert","email":"rskoumal@usgs.gov","middleInitial":"J.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":932153,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70263552,"text":"70263552 - 2025 - A high-resolution 3-D P-wave velocity structure of the south-central Cascadia subduction zone from wide-angle shore-crossing seismic refraction data","interactions":[],"lastModifiedDate":"2025-02-13T17:14:40.999846","indexId":"70263552","displayToPublicDate":"2025-02-12T10:59:47","publicationYear":"2025","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":"A high-resolution 3-D P-wave velocity structure of the south-central Cascadia subduction zone from wide-angle shore-crossing seismic refraction data","docAbstract":"

This study addresses a significant gap in understanding the features of the south-central Cascadia subduction zone, a region characterized by complex geologic, tectonic, and seismic transitions both offshore and onshore. Unlike other segments along this margin, this area lacks a 3-D velocity model to delineate its structural and geological features on a fine scale. To address this void, we developed a high-resolution 3-D P-wave velocity model using active source seismic data from ship-borne seismic shots recorded on temporary and permanent onshore seismic stations and ocean-bottom seismometers. Our model shows velocity variations across the region with distinct velocity-depth profiles for the Siletz, Franciscan, and Klamath terranes in the overlying plate. We identified seaward dipping high-velocity static backstops associated with the Siletz and Klamath terranes, situated near the shoreline and further inland, respectively. Regions of reduced crustal velocity are associated with crustal faults. Moreover, there is significant along-strike depth variation in the subducting slab, which is about 4 km deeper near the thick, dense Siletz terrane and becomes shallower near the predominantly less-dense Franciscan terrane. This highlights a sudden tectonic and geologic transition at the southern boundary of the Siletz terrane. Our velocity model also indicates slightly increased hydration, though still minimal, in both the oceanic crust and the upper mantle of the subducting plate compared to other parts of the margin.

","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2024JB029525","usgsCitation":"Ashraf, A., Hooft, E., Toomey, D., Trehu, A., Nolan, S., Wirth, E.A., and Ward, K.M., 2025, A high-resolution 3-D P-wave velocity structure of the south-central Cascadia subduction zone from wide-angle shore-crossing seismic refraction data: JGR Solid Earth, v. 130, e2024JB029525, 23 p., https://doi.org/10.1029/2024JB029525.","productDescription":"e2024JB029525, 23 p.","ipdsId":"IP-165201","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":487643,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1029/2024JB029525","text":"External Repository"},{"id":482045,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","state":"British Columbia, California, Oregon, Washington","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -121.05502627728873,\n 50\n ],\n [\n -130,\n 50\n ],\n [\n -130,\n 40\n ],\n [\n -122,\n 40\n ],\n [\n -122,\n 50\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"130","noUsgsAuthors":false,"publicationDate":"2025-02-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Ashraf, Asif","contributorId":350925,"corporation":false,"usgs":false,"family":"Ashraf","given":"Asif","affiliations":[{"id":80428,"text":"Univ. of Oregon","active":true,"usgs":false}],"preferred":false,"id":927325,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hooft, Emilie","contributorId":350929,"corporation":false,"usgs":false,"family":"Hooft","given":"Emilie","affiliations":[{"id":80428,"text":"Univ. of Oregon","active":true,"usgs":false}],"preferred":false,"id":927326,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Toomey, Douglas 0000-0003-2873-4084","orcid":"https://orcid.org/0000-0003-2873-4084","contributorId":206934,"corporation":false,"usgs":false,"family":"Toomey","given":"Douglas","affiliations":[{"id":27574,"text":"UO","active":true,"usgs":false}],"preferred":false,"id":927327,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Trehu, Anne 0000-0002-5349-3289","orcid":"https://orcid.org/0000-0002-5349-3289","contributorId":242894,"corporation":false,"usgs":false,"family":"Trehu","given":"Anne","email":"","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":927328,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Nolan, Sarah","contributorId":350932,"corporation":false,"usgs":false,"family":"Nolan","given":"Sarah","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":927329,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wirth, Erin A. 0000-0002-8592-4442","orcid":"https://orcid.org/0000-0002-8592-4442","contributorId":207853,"corporation":false,"usgs":true,"family":"Wirth","given":"Erin","middleInitial":"A.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":927330,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ward, Kevin M.","contributorId":206723,"corporation":false,"usgs":false,"family":"Ward","given":"Kevin","email":"","middleInitial":"M.","affiliations":[{"id":7042,"text":"University of Arizona","active":true,"usgs":false}],"preferred":false,"id":927331,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70269042,"text":"70269042 - 2025 - Accounting for non-random samples with distance sampling to estimate population density","interactions":[],"lastModifiedDate":"2025-07-15T14:30:48.364427","indexId":"70269042","displayToPublicDate":"2025-02-12T09:28:01","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2163,"text":"Journal of Applied Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Accounting for non-random samples with distance sampling to estimate population density","docAbstract":"
  1. A critical assumption of standard distance sampling is that sampling lines are located such that animals are uniformly distributed as a function of distance from the line. Failure to meet this assumption can introduce bias in the estimator.
  2. Many studies have used landscape features, such as roads or rivers, as lines, which can violate assumptions of distance sampling in two ways. First, animals may be attracted or repelled by the landscape feature due to human activity (e.g. along roads) or habitat characteristics associated with the feature (e.g. rivers). Second, sampling along landscape features may not be representative of the larger area of interest.
  3. We used auxiliary data to generalize the distance sampling estimator and relax assumptions of a uniform distribution of animals relative to distance from the line (i.e. density gradient) and to allow the distribution of animals to differ by habitat type. The generalized estimator provides unbiased estimates of density within the area sampled but may not be representative of the study area.
  4. To address the problem of landscape features providing unrepresentative sampling, we used a resource selection model to estimate the proportion of the population that occurred within the surveyed area to obtain an estimate of abundance for the desired area of inference.
  5. We demonstrate our modified distance sampling estimator using white-tailed deer (Odocoileus virginianus) in a 972-km2 study area. We conducted infrared surveys of deer from roads to collect distance-to-transect data. We used locations of radio-collared deer to model the distribution of deer relative to the transects and to develop a resource selection model of deer based on distance to roads, habitat type, elevation and slope to account for roads being a non-representative sample of the study area.
  6. Synthesis and applications. When using landscape features as survey lines, the density gradient and deer distribution can introduce either positive or negative bias, which makes it impossible to assess the bias introduced without auxiliary data. The estimator we developed can improve precision because we obtained a better fit to distance observations and accounts for non-random placement of transects with minimal loss of precision.
","language":"English","publisher":"British Ecological Society","doi":"10.1111/1365-2664.70006","usgsCitation":"Diefenbach, D.R., Trowbridge, J., Van Buskirk, A.N., McConnell, T., Lamp, K., Marques, T.A., Walters, D., Wallingford, B., and Rosenberry, C., 2025, Accounting for non-random samples with distance sampling to estimate population density: Journal of Applied Ecology, v. 62, no. 4, p. 986-994, https://doi.org/10.1111/1365-2664.70006.","productDescription":"9 p.","startPage":"986","endPage":"994","ipdsId":"IP-168164","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":492797,"rank":1,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P1FUDEUS","text":"USGS data release","linkHelpText":"Code for Distance sampling accounting for density gradient and animal distribution"},{"id":492492,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/1365-2664.70006","text":"Publisher Index Page"},{"id":492242,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"62","issue":"4","noUsgsAuthors":false,"publicationDate":"2025-02-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Diefenbach, Duane R. 0000-0001-5111-1147 drd11@usgs.gov","orcid":"https://orcid.org/0000-0001-5111-1147","contributorId":5235,"corporation":false,"usgs":true,"family":"Diefenbach","given":"Duane","email":"drd11@usgs.gov","middleInitial":"R.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":943052,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Trowbridge, Jacob","contributorId":346086,"corporation":false,"usgs":false,"family":"Trowbridge","given":"Jacob","affiliations":[{"id":7260,"text":"Pennsylvania State University","active":true,"usgs":false}],"preferred":false,"id":943053,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Van Buskirk, Amanda N.","contributorId":276219,"corporation":false,"usgs":false,"family":"Van Buskirk","given":"Amanda","email":"","middleInitial":"N.","affiliations":[{"id":36985,"text":"Penn State University","active":true,"usgs":false}],"preferred":false,"id":943054,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McConnell, Tess","contributorId":358018,"corporation":false,"usgs":false,"family":"McConnell","given":"Tess","affiliations":[{"id":7260,"text":"Pennsylvania State University","active":true,"usgs":false}],"preferred":false,"id":943055,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lamp, Kevin","contributorId":346090,"corporation":false,"usgs":false,"family":"Lamp","given":"Kevin","affiliations":[{"id":7260,"text":"Pennsylvania State University","active":true,"usgs":false}],"preferred":false,"id":943056,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Marques, Tiago A.","contributorId":194662,"corporation":false,"usgs":false,"family":"Marques","given":"Tiago","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":943057,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Walters, David 0000-0002-4237-2158","orcid":"https://orcid.org/0000-0002-4237-2158","contributorId":203410,"corporation":false,"usgs":true,"family":"Walters","given":"David","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":943058,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Wallingford, Bret D.","contributorId":276207,"corporation":false,"usgs":false,"family":"Wallingford","given":"Bret D.","affiliations":[{"id":12891,"text":"Pennsylvania Game Commission","active":true,"usgs":false}],"preferred":false,"id":943059,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Rosenberry, Christopher S.","contributorId":276209,"corporation":false,"usgs":false,"family":"Rosenberry","given":"Christopher S.","affiliations":[{"id":12891,"text":"Pennsylvania Game Commission","active":true,"usgs":false}],"preferred":false,"id":943060,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70263588,"text":"70263588 - 2025 - How will we prepare for an uncertain future? The value of open data and code for unborn generations facing climate change","interactions":[],"lastModifiedDate":"2025-02-14T16:31:31.424956","indexId":"70263588","displayToPublicDate":"2025-02-12T09:27:26","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":20076,"text":"Proceedings of the Royal Society, B","active":true,"publicationSubtype":{"id":10}},"title":"How will we prepare for an uncertain future? The value of open data and code for unborn generations facing climate change","docAbstract":"As the impacts of climate change continue to intensify, humans face new challenges to long-term survival. Humans will likely be battling these problems long after 2100, when many climate projections currently end. A more forward-thinking view on our science and its direction may help better prepare for the future of our species. Researchers may consider datasets the basic units of knowledge, whose preservation is arguably more important than the articles that are written about them. Storing data and code in long-term repositories offers insurance against our uncertain future. To ensure open data are useful, data must be FAIR (Findable, Accessible, Interoperable, and Reusable) and be complete with all appropriate metadata. By embracing open science practices, contemporary scientists give the future of humanity the information to make better decisions, save time and other valuable resources, and increase global equity as access to information is made free. This, in turn, will enable and inspire a diversity of solutions, to the benefit of many. Imagine the collective science conducted, the models built, and the questions answered if all of the data researchers have collectively gathered were organized and immediately accessible and usable by everyone. Investing in open science today may ensure a brighter future for unborn generations.","language":"English","publisher":"The Royal Society","doi":"10.1098/rspb.2024.1515","usgsCitation":"Gomes, D.G., 2025, How will we prepare for an uncertain future? The value of open data and code for unborn generations facing climate change: Proceedings of the Royal Society, B, v. 292, no. 2040, 20241515, 9 p., https://doi.org/10.1098/rspb.2024.1515.","productDescription":"20241515, 9 p.","ipdsId":"IP-161414","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":489838,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1098/rspb.2024.1515","text":"Publisher Index Page"},{"id":482109,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"292","issue":"2040","noUsgsAuthors":false,"publicationDate":"2025-02-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Gomes, Dylan Gerald-Everett 0000-0002-2642-3728","orcid":"https://orcid.org/0000-0002-2642-3728","contributorId":346160,"corporation":false,"usgs":true,"family":"Gomes","given":"Dylan","email":"","middleInitial":"Gerald-Everett","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":927450,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70264730,"text":"70264730 - 2025 - An unexplained tsunami: Was there megathrust slip during the 2020 Mw7.6 Sand Point, Alaska, earthquake?","interactions":[],"lastModifiedDate":"2025-03-21T15:08:55.785308","indexId":"70264730","displayToPublicDate":"2025-02-12T07:59:39","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":17454,"text":"Seismica","active":true,"publicationSubtype":{"id":10}},"title":"An unexplained tsunami: Was there megathrust slip during the 2020 Mw7.6 Sand Point, Alaska, earthquake?","docAbstract":"

On October 19, 2020, the Mw7.6 Sand Point earthquake struck south of the Shumagin Islands in Alaska. Moment tensors indicate the earthquake was primarily strike-slip, yet the event produced an enigmatic tsunami that was larger and more widespread than expected for an earthquake of that magnitude and mechanism. Using a suite of hydrodynamic, seismic, and geodetic modeling techniques, we explore plausible causes of the tsunami. We find that strike-slip models consistent with the moment tensor orientation cannot produce the observed tsunami. Hydrodynamic inversion of sea surface deformation from deep ocean and tide gauge data suggest seafloor deformation more closely matches a megathrust, rather than a strike-slip, source. Static slip inversions, using sea level and Global Navigation Satellite System data, allow for a portion of co-seismic megathrust slip that can explain tsunamigenesis. Combining all available geophysical datasets to model the kinematic rupture, we show that considerable, relatively slow, megathrust slip is allowable in the Shumagin segment, concurrent with strike-slip faulting. We hypothesize that the slow megathrust rupture does not contribute much seismic radiation allowing it to previously go unnoticed with traditional seismic monitoring.

","language":"English","publisher":"McGill","doi":"10.26443/seismica.v4i1.1336","usgsCitation":"Santellanes, S., Goldberg, D.E., Koch, P., Melgar, D., Yeck, W.L., Crowell, B.W., and Lin, J., 2025, An unexplained tsunami: Was there megathrust slip during the 2020 Mw7.6 Sand Point, Alaska, earthquake?: Seismica, v. 4, no. 1, p. 1-13, https://doi.org/10.26443/seismica.v4i1.1336.","productDescription":"13 p.","startPage":"1","endPage":"13","ipdsId":"IP-156090","costCenters":[{"id":78686,"text":"Geologic Hazards Science Center - Seismology / Geomagnetism","active":true,"usgs":true}],"links":[{"id":488362,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.26443/seismica.v4i1.1336","text":"Publisher Index Page"},{"id":483661,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Sand Point","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -160.8287429707048,\n 55.46546760592042\n ],\n [\n -160.8287429707048,\n 55.238590952487215\n ],\n [\n -160.19346063892195,\n 55.238590952487215\n ],\n [\n -160.19346063892195,\n 55.46546760592042\n ],\n [\n -160.8287429707048,\n 55.46546760592042\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"4","issue":"1","noUsgsAuthors":false,"publicationDate":"2025-02-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Santellanes, Sean R. 0000-0003-4181-437X","orcid":"https://orcid.org/0000-0003-4181-437X","contributorId":347848,"corporation":false,"usgs":false,"family":"Santellanes","given":"Sean R.","affiliations":[{"id":6604,"text":"University of Oregon","active":true,"usgs":false}],"preferred":false,"id":931475,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Goldberg, Dara Elyse 0000-0002-0923-3180","orcid":"https://orcid.org/0000-0002-0923-3180","contributorId":289891,"corporation":false,"usgs":true,"family":"Goldberg","given":"Dara","email":"","middleInitial":"Elyse","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":931476,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Koch, Pablo","contributorId":294680,"corporation":false,"usgs":false,"family":"Koch","given":"Pablo","email":"","affiliations":[{"id":63624,"text":"National Seismological Center, University of Chile","active":true,"usgs":false}],"preferred":false,"id":931477,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Melgar, Diego","contributorId":341315,"corporation":false,"usgs":false,"family":"Melgar","given":"Diego","affiliations":[{"id":6604,"text":"University of Oregon","active":true,"usgs":false}],"preferred":false,"id":931478,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Yeck, William L. 0000-0002-2801-8873 wyeck@usgs.gov","orcid":"https://orcid.org/0000-0002-2801-8873","contributorId":147558,"corporation":false,"usgs":true,"family":"Yeck","given":"William","email":"wyeck@usgs.gov","middleInitial":"L.","affiliations":[{"id":309,"text":"Geology and Geophysics Science Center","active":true,"usgs":true},{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":931479,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Crowell, Brendan W.","contributorId":184207,"corporation":false,"usgs":false,"family":"Crowell","given":"Brendan","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":931480,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Lin, Jiun-Ting 0000-0002-8134-9612","orcid":"https://orcid.org/0000-0002-8134-9612","contributorId":347849,"corporation":false,"usgs":false,"family":"Lin","given":"Jiun-Ting","affiliations":[{"id":13621,"text":"Lawrence Livermore National Laboratory","active":true,"usgs":false}],"preferred":false,"id":931481,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70265052,"text":"70265052 - 2025 - Exploring the science and data foundation for Federal public lands decisions","interactions":[],"lastModifiedDate":"2025-04-01T14:33:16.699808","indexId":"70265052","displayToPublicDate":"2025-02-10T09:27:45","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Exploring the science and data foundation for Federal public lands decisions","docAbstract":"

Public lands provide diverse resources, values, and services worldwide. Laws and policies typically require consideration of science in public lands decisions, and resource managers are committed to science-informed decision-making. However, it can be challenging for managers to use, and document the use of, science and data in their decisions. To better understand science and data use in Federal public lands decisions in the United States, we assessed the number, type, and age of documents cited in 70 Environmental Assessments (EAs) completed by the Bureau of Land Management (BLM) in Colorado from 2015–2019. We focused on the BLM, as they manage the largest area of public lands in the United States. We selected Colorado as our study area, as actions proposed on BLM lands in Colorado are representative of those across the nation. Fifty percent of citations were categorized as science and 23% as data. EAs contained an average of 17 citations (range 0–111), with documents analyzing effects of oil and gas development and recreation actions including the highest and lowest mean number of citations (41 and 6, respectively). Of individual resource analysis sections within EAs, 24% contained ≥1 science citation and 21% contained ≥1 data citation. Journal articles were the most cited type of document (26% of citations) followed by non-BLM inventories (13%). Forty-seven percent of citations were relatively recent (2010 or later); the oldest citation was from 1927. Commonly analyzed resources with the highest mean number of citations were socioeconomics, mineral resources, and noise. Fourteen of 33 commonly analyzed resources included <1 citation on average. Actions and resources with no or few citations represent opportunities for strengthening the transparent use of science and data in public lands decision-making.

","language":"English","publisher":"PLoS","doi":"10.1371/journal.pone.0316013","usgsCitation":"Foster, A., Canchola, A., Haby, T.S., and Carter, S.K., 2025, Exploring the science and data foundation for Federal public lands decisions: PLoS ONE, v. 20, no. 2, e0316013, 17 p., https://doi.org/10.1371/journal.pone.0316013.","productDescription":"e0316013, 17 p.","ipdsId":"IP-147398","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":488656,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0316013","text":"Publisher Index Page"},{"id":484061,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -109.033613592161,\n 40.94360758769497\n ],\n [\n -109.033613592161,\n 37.00275906966762\n ],\n [\n -102.12660083351636,\n 37.00275906966762\n ],\n [\n -102.12660083351636,\n 40.94360758769497\n ],\n [\n -109.033613592161,\n 40.94360758769497\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"20","issue":"2","noUsgsAuthors":false,"publicationDate":"2025-02-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Foster, Alison C. 0000-0002-6659-2120","orcid":"https://orcid.org/0000-0002-6659-2120","contributorId":331240,"corporation":false,"usgs":false,"family":"Foster","given":"Alison C.","affiliations":[{"id":79166,"text":"USGS, currently US Forest Service","active":true,"usgs":false}],"preferred":false,"id":932427,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Canchola, Andrew T.","contributorId":350323,"corporation":false,"usgs":false,"family":"Canchola","given":"Andrew T.","affiliations":[{"id":83709,"text":"City of Greeley","active":true,"usgs":false}],"preferred":false,"id":932428,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Haby, Travis S. 0000-0003-2204-9967","orcid":"https://orcid.org/0000-0003-2204-9967","contributorId":138831,"corporation":false,"usgs":false,"family":"Haby","given":"Travis","email":"","middleInitial":"S.","affiliations":[{"id":7217,"text":"Bureau of Land Management","active":true,"usgs":false}],"preferred":false,"id":932429,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Carter, Sarah K. 0000-0003-3778-8615","orcid":"https://orcid.org/0000-0003-3778-8615","contributorId":192418,"corporation":false,"usgs":true,"family":"Carter","given":"Sarah","email":"","middleInitial":"K.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":932430,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70264077,"text":"70264077 - 2025 - The accuracy of capture per unit effort in predicting density of a cryptic snake was more sensitive to reductions in spatial than temporal coverage","interactions":[],"lastModifiedDate":"2025-03-05T16:22:30.657901","indexId":"70264077","displayToPublicDate":"2025-02-10T09:18:02","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"The accuracy of capture per unit effort in predicting density of a cryptic snake was more sensitive to reductions in spatial than temporal coverage","docAbstract":"

A critical component of monitoring wildlife populations is understanding changes in population size or abundance. However, for most populations a complete census is not possible; thus, trends or abundance need to be estimated through alternative means, such as indexes. An important aspect of using indexes, such as capture per unit effort (CPUE), is validating them as accurate or precise predictors of population trends or abundance. We completed such analyses using data collected from visual surveys and trapping for brown treesnakes (Boiga irregularis) within a 5-ha enclosure that was undergoing a continuous population decline. During a ~ 6-year period, we censused and marked the snake population to fully enumerated the population, with new individuals resulting from births and removals resulting only from mortality (natural or experimental). From trapping and visual surveys, we were also able to calculate CPUE as a function of trap nights or km surveyed and used regressions to forecast snake density (snakes/km) in the enclosure from CPUE. We also rarefied the true dataset to measure whether reductions in sampling intensity, either temporally or spatially, affected the accuracy or precision in predicting snake density from CPUE. We found that trap CPUE demonstrated no statistical relationship to density based on our study methods. CPUE during visual surveys did predict actual density, with sufficient spatial and temporal sampling intensity. CPUE from visual surveys was relatively robust against reductions in temporal sampling when spatial intensity remained high. However, reductions in the spatial area covered to less than 50% of the enclosure rapidly reduced the accuracy and precision in using CPUE to forecast density. Our results indicate that visual surveys are a relatively accurate measure of true density for brown treesnakes, given sufficient spatial sampling effort. The spatial area of coverage required for CPUE to accurately predict changes in abundance was, however, intense with > 50% of the spatial area required to be sampled on a given sampling night. Our results indicate that CPUE is only reliable as an index of abundance or population trends for cryptic snakes, if sampling effort covers most of the landscape over which populations are being estimated.

","language":"English","publisher":"PLOS","doi":"10.1371/journal.pone.0317764","usgsCitation":"Nafus, M., Hanslowe, E.B., and Goetz, S.M., 2025, The accuracy of capture per unit effort in predicting density of a cryptic snake was more sensitive to reductions in spatial than temporal coverage: PLoS ONE, v. 20, no. 2, e0317764, 15 p., https://doi.org/10.1371/journal.pone.0317764.","productDescription":"e0317764, 15 p.","ipdsId":"IP-151357","costCenters":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"links":[{"id":487742,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0317764","text":"Publisher Index Page"},{"id":482905,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Guam","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 144.57580570546742,\n 13.686292533777149\n ],\n [\n 144.57580570546742,\n 13.237404452388134\n ],\n [\n 144.9652940566009,\n 13.237404452388134\n ],\n [\n 144.9652940566009,\n 13.686292533777149\n ],\n [\n 144.57580570546742,\n 13.686292533777149\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"20","issue":"2","noUsgsAuthors":false,"publicationDate":"2025-02-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Nafus, Melia Gail 0000-0002-7325-3055","orcid":"https://orcid.org/0000-0002-7325-3055","contributorId":245717,"corporation":false,"usgs":true,"family":"Nafus","given":"Melia Gail","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":929687,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hanslowe, Emma B. 0000-0003-4331-6729","orcid":"https://orcid.org/0000-0003-4331-6729","contributorId":265394,"corporation":false,"usgs":false,"family":"Hanslowe","given":"Emma","email":"","middleInitial":"B.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":false,"id":929688,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Goetz, Scott Michael 0000-0002-8705-5316","orcid":"https://orcid.org/0000-0002-8705-5316","contributorId":228868,"corporation":false,"usgs":true,"family":"Goetz","given":"Scott","email":"","middleInitial":"Michael","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":929689,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70263819,"text":"70263819 - 2025 - Long-term trends in microseismicity during operational shut-ins at the Coso Geothermal Field, California","interactions":[],"lastModifiedDate":"2025-02-25T15:34:45.908287","indexId":"70263819","displayToPublicDate":"2025-02-10T08:29:43","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":10542,"text":"The Seismic Record","active":true,"publicationSubtype":{"id":10}},"title":"Long-term trends in microseismicity during operational shut-ins at the Coso Geothermal Field, California","docAbstract":"Pausing injection and production can lead to induced seismicity in a variety of settings, with some of the largest events occurring during these so-called shut-ins. In geothermal fields, shut-ins are periodically conducted for maintenance on wells and surface infrastructure, thereby offering recurring means of estimating stress changes in the subsurface that lead to increased seismicity rates. Here, we examine daily production and microseismicity data from the Coso Geothermal Field (CGF) in California between 1996 and 2010 to investigate the repetitive trends of operational shut-in microseismicity. Using 24 local seismic stations, we first analyze spatial and temporal trends of over 60,000 earthquakes with magnitudes between -0.4 to 3.8. We find that the northern region exhibits no significant seismicity changes during shut-ins, whereas the rest of the field experiences induced seismicity during almost every shut-in with an increasing intensity towards the southern and eastern portions of the field, highlighting local differences in stress within the CGF. Additionally, we cluster the seismicity using waveform cross-correlation, revealing several earthquake clusters primarily occurring during shut-in periods. These observations suggest that certain fracture and fault sections respond quicker to changes in pore pressure and poroelastic stresses within the geothermal system, possibly highlighting main fluid pathways.","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0320240041","usgsCitation":"Holmgren, J., Kaven, J., and Oye, V., 2025, Long-term trends in microseismicity during operational shut-ins at the Coso Geothermal Field, California: The Seismic Record, v. 5, no. 1, p. 73-82, https://doi.org/10.1785/0320240041.","productDescription":"10 p.","startPage":"73","endPage":"82","ipdsId":"IP-170795","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":487678,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1785/0320240041","text":"Publisher Index Page"},{"id":482446,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Coso Geothermal Field","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -117.93842593182427,\n 36.34881073898275\n ],\n [\n -117.93842593182427,\n 36.12479363858705\n ],\n [\n -117.62601162670973,\n 36.12479363858705\n ],\n [\n -117.62601162670973,\n 36.34881073898275\n ],\n [\n -117.93842593182427,\n 36.34881073898275\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"5","issue":"1","noUsgsAuthors":false,"publicationDate":"2025-02-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Holmgren, Joanna","contributorId":351460,"corporation":false,"usgs":false,"family":"Holmgren","given":"Joanna","affiliations":[{"id":18074,"text":"NORSAR","active":true,"usgs":false}],"preferred":false,"id":928536,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kaven, J. Ole 0000-0003-2625-2786 okaven@usgs.gov","orcid":"https://orcid.org/0000-0003-2625-2786","contributorId":3993,"corporation":false,"usgs":true,"family":"Kaven","given":"J. Ole","email":"okaven@usgs.gov","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":928537,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Oye, Volker","contributorId":194795,"corporation":false,"usgs":false,"family":"Oye","given":"Volker","email":"","affiliations":[],"preferred":false,"id":928538,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70267221,"text":"70267221 - 2025 - Filling the gaps: A Bayesian mixture model for imputing missing soil water content data","interactions":[],"lastModifiedDate":"2025-05-16T15:31:40.63399","indexId":"70267221","displayToPublicDate":"2025-02-10T08:27:47","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1447,"text":"Ecohydrology","active":true,"publicationSubtype":{"id":10}},"title":"Filling the gaps: A Bayesian mixture model for imputing missing soil water content data","docAbstract":"

Soil water content (SWC) data are central to evaluating how soil moisture varies over time and space and influences critical plant and ecosystem functions, especially in water-limited drylands. However, sensors that record SWC at high frequencies often malfunction, leading to incomplete timeseries and limiting our understanding of dryland ecosystem dynamics. We developed an analytical approach to impute missing SWC data, which we tested at six eddy flux tower sites along an elevation gradient in the southwestern United States. We impute missing data as a mixture of linearly interpolated SWC between the observed endpoints of a missing data gap and SWC simulated by an ecosystem water balance model (SOILWAT2). Within a Bayesian framework, we allowed the relative utility (mixture weight) of each component (linearly interpolated vs. SOILWAT2) to vary by depth, site and gap characteristics. We explored “fixed” weights versus “dynamic” weights that vary as a function of cumulative precipitation, average temperature, and time since the start of the gap. Both models estimated missing SWC data well (R2 = 0.70–0.88 vs. 0.75–0.91 for fixed vs. dynamic weights, respectively), but the utility of linearly interpolated versus SOILWAT2 values depended on site and depth. SOILWAT2 was more useful for more arid sites, shallower depths, longer and warmer gaps and gaps that received greater precipitation. Overall, the mixture model reliably gap-fills SWC, while lending insight into processes governing SWC dynamics. This approach to impute missing data could be adapted to accommodate more than two mixture components and other types of environmental timeseries. 

","language":"English","publisher":"Wiley","doi":"10.1002/eco.70004","usgsCitation":"Ogle, K., Reich, E., Samuels-Crow, K., Litvak, M., Bradford, J., Schlaepfer, D.R., and Devan, M., 2025, Filling the gaps: A Bayesian mixture model for imputing missing soil water content data: Ecohydrology, v. 18, no. 1, e70004, 17 p., https://doi.org/10.1002/eco.70004.","productDescription":"e70004, 17 p.","ipdsId":"IP-163652","costCenters":[{"id":49226,"text":"Northwest Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":490127,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1002/eco.70004","text":"External Repository"},{"id":486071,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Mexico","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -109.07993996238093,\n 37.04473109056555\n ],\n [\n -109.07993996238093,\n 31.382778545525298\n ],\n [\n -103.04352625964134,\n 31.382778545525298\n ],\n [\n -103.04352625964134,\n 37.04473109056555\n ],\n [\n -109.07993996238093,\n 37.04473109056555\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"18","issue":"1","noUsgsAuthors":false,"publicationDate":"2025-02-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Ogle, Kiona","contributorId":248351,"corporation":false,"usgs":false,"family":"Ogle","given":"Kiona","email":"","affiliations":[],"preferred":false,"id":937346,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Reich, Emma","contributorId":355440,"corporation":false,"usgs":false,"family":"Reich","given":"Emma","affiliations":[{"id":84751,"text":"School of Informatics, Computing, and Cyber Systems, Northern Arizona University, Flagstaff, Arizona, U.S.A.","active":true,"usgs":false}],"preferred":false,"id":937347,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Samuels-Crow, Kimberly","contributorId":289104,"corporation":false,"usgs":false,"family":"Samuels-Crow","given":"Kimberly","email":"","affiliations":[{"id":62051,"text":"School of Informatics, Computing, and Cyber Systems; Northern Arizona University, Flagstaff, AZ","active":true,"usgs":false}],"preferred":false,"id":937348,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Litvak, Marcy","contributorId":216915,"corporation":false,"usgs":false,"family":"Litvak","given":"Marcy","affiliations":[{"id":39549,"text":"University of New Mexico: Albuquerque, NM","active":true,"usgs":false}],"preferred":false,"id":937349,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bradford, John B. 0000-0001-9257-6303","orcid":"https://orcid.org/0000-0001-9257-6303","contributorId":219257,"corporation":false,"usgs":true,"family":"Bradford","given":"John B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":937350,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Schlaepfer, Daniel Rodolphe 0000-0001-9973-2065","orcid":"https://orcid.org/0000-0001-9973-2065","contributorId":225569,"corporation":false,"usgs":true,"family":"Schlaepfer","given":"Daniel","email":"","middleInitial":"Rodolphe","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":937351,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Devan, Megan","contributorId":355441,"corporation":false,"usgs":false,"family":"Devan","given":"Megan","affiliations":[{"id":84752,"text":"Department of Biology, University of New Mexico, Albuquerque, New Mexico, 87131, U.S.A.","active":true,"usgs":false}],"preferred":false,"id":937352,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70266568,"text":"70266568 - 2025 - A real-time fish detection system for partially dewatered fish to support selective fish passage","interactions":[],"lastModifiedDate":"2025-05-09T14:23:25.631013","indexId":"70266568","displayToPublicDate":"2025-02-09T09:15:02","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3380,"text":"Sensors","active":true,"publicationSubtype":{"id":10}},"title":"A real-time fish detection system for partially dewatered fish to support selective fish passage","docAbstract":"

Recent advances in fish transportation technologies and deep machine learning-based fish classification have created an opportunity for real-time, autonomous fish sorting through a selective passage mechanism. This research presents a case study of a novel application that utilizes deep machine learning to detect partially dewatered fish exiting an Archimedes Screw Fish Lift (ASFL). A MobileNet SSD model was trained on images of partially dewatered fish volitionally passing through an ASFL. Then, this model was integrated with a network video recorder to monitor video from the ASFL. Additional models were also trained using images from a similar fish scanning device to test the feasibility of this approach for fish classification. Open source software and edge computing design principles were employed to ensure that the system is capable of fast data processing. The findings from this research demonstrate that such a system integrated with an ASFL can support real-time fish detection. This research contributes to the goal of automated data collection in a selective fish passage system and presents a viable path towards realizing optical fish sorting.

","language":"English","publisher":"MDPI","doi":"10.3390/s25041022","usgsCitation":"Gregory, J., Miehls, S.M., Eickholt, J., and Zielinski, D., 2025, A real-time fish detection system for partially dewatered fish to support selective fish passage: Sensors, v. 25, no. 4, 1022, 23 p., https://doi.org/10.3390/s25041022.","productDescription":"1022, 23 p.","ipdsId":"IP-174633","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":490109,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/s25041022","text":"Publisher Index Page"},{"id":485641,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Michigan","otherGeospatial":"Swan River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -83.71462217594592,\n 45.40023637231536\n ],\n [\n -83.78015729775288,\n 45.40023637231536\n ],\n [\n -83.78015729775288,\n 45.337445622308564\n ],\n [\n -83.71462217594592,\n 45.337445622308564\n ],\n [\n -83.71462217594592,\n 45.40023637231536\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"25","issue":"4","noUsgsAuthors":false,"publicationDate":"2025-02-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Gregory, Jonathan","contributorId":354850,"corporation":false,"usgs":false,"family":"Gregory","given":"Jonathan","affiliations":[{"id":13588,"text":"Central Michigan University","active":true,"usgs":false}],"preferred":false,"id":936574,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Miehls, Scott M. 0000-0002-5546-1854 smiehls@usgs.gov","orcid":"https://orcid.org/0000-0002-5546-1854","contributorId":5007,"corporation":false,"usgs":true,"family":"Miehls","given":"Scott","email":"smiehls@usgs.gov","middleInitial":"M.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":936575,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Eickholt, Jesse","contributorId":205582,"corporation":false,"usgs":false,"family":"Eickholt","given":"Jesse","email":"","affiliations":[{"id":13588,"text":"Central Michigan University","active":true,"usgs":false}],"preferred":false,"id":936576,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Zielinski, Daniel","contributorId":245798,"corporation":false,"usgs":false,"family":"Zielinski","given":"Daniel","affiliations":[{"id":7019,"text":"Great Lakes Fishery Commission","active":true,"usgs":false}],"preferred":false,"id":936577,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70263464,"text":"70263464 - 2025 - Applications of unoccupied aerial systems (UAS) in landscape ecology: A review of recent research, challenges and emerging opportunities","interactions":[],"lastModifiedDate":"2025-02-12T14:53:37.848481","indexId":"70263464","displayToPublicDate":"2025-02-08T08:43:25","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2602,"text":"Landscape Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Applications of unoccupied aerial systems (UAS) in landscape ecology: A review of recent research, challenges and emerging opportunities","docAbstract":"

Context

Unoccupied aerial systems/vehicles (UAS/UAV, a.k.a. drones) have become an increasingly popular tool for ecological research. But much of the recent research is concerned with developing mapping and detection approaches, with few studies attempting to link UAS data to ecosystem processes and function. Landscape ecologists have long used high resolution imagery and spatial analyses to address ecological questions and are therefore uniquely positioned to advance UAS research for ecological applications.

Objectives

The review objectives are to: (1) provide background on how UAS are used in landscape ecological studies, (2) identify major advancements and research gaps, and (3) discuss ways to better facilitate the use of UAS in landscape ecology research.

Methods

We conducted a systematic review based on PRISMA guidelines using key search terms that are unique to landscape ecology research. We reviewed only papers that applied UAS data to investigate questions about ecological patterns, processes, or function.

Results

We summarize metadata from 161 papers that fit our review criteria. We highlight and discuss major research themes and applications, sensors and data collection techniques, image processing, feature extraction and spatial analysis, image fusion and satellite scaling, and open data and software.

Conclusion

We observed a diversity of UAS methods, applications, and creative spatial modeling and analysis approaches. Key aspects of UAS research in landscape ecology include modeling wildlife micro-habitats, scaling of ecosystem functions, landscape and geomorphic change detection, integrating UAS with historical aerial and satellite imagery, and novel applications of spatial statistics.

","language":"English","publisher":"Springer","doi":"10.1007/s10980-024-02040-6","usgsCitation":"Villarreal, M.L., Bishop, T., Sankey, T., Smith, W.K., Burgess, M.A., Caughlin, T., Gillan, J.K., Havrilla, C., Huang, T., LeBeau, R., Norton, C., Sankey, J., Scholl, V.M., Von Nonn, J.W., and Yao, E., 2025, Applications of unoccupied aerial systems (UAS) in landscape ecology: A review of recent research, challenges and emerging opportunities: Landscape Ecology, v. 40, 43, 32 p., https://doi.org/10.1007/s10980-024-02040-6.","productDescription":"43, 32 p.","ipdsId":"IP-165776","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":487638,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10980-024-02040-6","text":"Publisher Index Page"},{"id":481973,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"40","noUsgsAuthors":false,"publicationDate":"2025-02-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Villarreal, Miguel L. 0000-0003-0720-1422 mvillarreal@usgs.gov","orcid":"https://orcid.org/0000-0003-0720-1422","contributorId":1424,"corporation":false,"usgs":true,"family":"Villarreal","given":"Miguel","email":"mvillarreal@usgs.gov","middleInitial":"L.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":927062,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bishop, Tara B.B.","contributorId":215034,"corporation":false,"usgs":false,"family":"Bishop","given":"Tara B.B.","affiliations":[{"id":39160,"text":"Department of Plant and Wildlife Sciences, Brigham Young University, Provo, UT USA","active":true,"usgs":false}],"preferred":false,"id":927063,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sankey, Temuulen Ts.","contributorId":350813,"corporation":false,"usgs":false,"family":"Sankey","given":"Temuulen Ts.","affiliations":[{"id":83836,"text":"Northern Arizona University, School of Informatics, Computing, and Cyber Systems","active":true,"usgs":false}],"preferred":false,"id":927064,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Smith, William K. 0000-0002-5785-6489","orcid":"https://orcid.org/0000-0002-5785-6489","contributorId":239667,"corporation":false,"usgs":false,"family":"Smith","given":"William","email":"","middleInitial":"K.","affiliations":[{"id":47959,"text":"School of Natural Resources and the Environment, University of Arizona, Tucson, AZ","active":true,"usgs":false}],"preferred":false,"id":927065,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Burgess, Matthew Alexander 0000-0003-3487-4972 mburgess@usgs.gov","orcid":"https://orcid.org/0000-0003-3487-4972","contributorId":225090,"corporation":false,"usgs":true,"family":"Burgess","given":"Matthew","email":"mburgess@usgs.gov","middleInitial":"Alexander","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":927066,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Caughlin, Trevor 0000-0001-6752-2055","orcid":"https://orcid.org/0000-0001-6752-2055","contributorId":256964,"corporation":false,"usgs":false,"family":"Caughlin","given":"Trevor","email":"","affiliations":[{"id":16201,"text":"Boise State University","active":true,"usgs":false}],"preferred":false,"id":927067,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Gillan, Jeffrey K.","contributorId":51656,"corporation":false,"usgs":true,"family":"Gillan","given":"Jeffrey","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":927068,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Havrilla, Caroline 0000-0003-3913-0980","orcid":"https://orcid.org/0000-0003-3913-0980","contributorId":245368,"corporation":false,"usgs":false,"family":"Havrilla","given":"Caroline","affiliations":[{"id":12698,"text":"Northern Arizona University","active":true,"usgs":false}],"preferred":false,"id":927069,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Huang, Tao","contributorId":350818,"corporation":false,"usgs":false,"family":"Huang","given":"Tao","affiliations":[{"id":38130,"text":"Boise State University, Department of Biological Sciences","active":true,"usgs":false}],"preferred":false,"id":927070,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"LeBeau, Raymond 0009-0005-1520-5249","orcid":"https://orcid.org/0009-0005-1520-5249","contributorId":350819,"corporation":false,"usgs":true,"family":"LeBeau","given":"Raymond","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":927071,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Norton, Cindy L.","contributorId":350820,"corporation":false,"usgs":false,"family":"Norton","given":"Cindy L.","affiliations":[{"id":83841,"text":"School of Natural Resources and the Environment, Arizona Remote Sensing Center","active":true,"usgs":false}],"preferred":false,"id":927072,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Sankey, Joel B. 0000-0003-3150-4992","orcid":"https://orcid.org/0000-0003-3150-4992","contributorId":261248,"corporation":false,"usgs":true,"family":"Sankey","given":"Joel B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":927073,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Scholl, Victoria Mary 0000-0002-2085-1449","orcid":"https://orcid.org/0000-0002-2085-1449","contributorId":295713,"corporation":false,"usgs":true,"family":"Scholl","given":"Victoria","email":"","middleInitial":"Mary","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":927074,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Von Nonn, Joshua W. 0009-0003-7251-7308","orcid":"https://orcid.org/0009-0003-7251-7308","contributorId":332293,"corporation":false,"usgs":true,"family":"Von Nonn","given":"Joshua","email":"","middleInitial":"W.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":927075,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Yao, Erika","contributorId":280000,"corporation":false,"usgs":false,"family":"Yao","given":"Erika","email":"","affiliations":[{"id":57405,"text":"Contractor to Western Geographic Science Center","active":true,"usgs":false}],"preferred":false,"id":927076,"contributorType":{"id":1,"text":"Authors"},"rank":15}]}} ,{"id":70263885,"text":"70263885 - 2025 - Using GPS tracking data to validate the conservation value of bird migration counts","interactions":[],"lastModifiedDate":"2025-02-27T15:29:12.802856","indexId":"70263885","displayToPublicDate":"2025-02-07T08:21:14","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1015,"text":"Biological Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Using GPS tracking data to validate the conservation value of bird migration counts","docAbstract":"

Effective conservation of migratory birds requires gathering of information about their population trends, often acquired using migratory bird counts. These schemes ideally operate at migratory bottlenecks, through which a significant portion of the counted migratory populations is funneled. Yet it is rare to validate the conservation value of the data from these counts. Here we perform this validation using GPS tracking data collected from two migratory species during their movement over two count schemes: the globally endangered steppe eagle counted in Eilat, Israel, and the black kite, counted in Batumi, Georgia. We use tracking data to answer two questions: which populations are counted and what affects the probability that a given individual will be counted. Our results illustrate variability in the effectiveness of these two migratory bird counting schemes. Considering the goal of estimating population trends, we show that Eilat does not represent a good location for understanding population trends of steppe eagles, while Batumi appears to provide better information on demographic trends of black kites. We further present differences in annual and individual variability, evidence regarding the breeding area origins of the counted populations and effects of environmental factors on the raptors' routes and, consequently, on the probabilities of being counted. Beyond the direct implications of our results, this study provides an example of using telemetry data to parameterize inference from bird counts. Further coupling of migratory bird count data and GPS data can improve our understanding of migration ecology and the conservation of migratory species.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.biocon.2024.110959","usgsCitation":"Efrat, R., Lehnardt, Y., Berkowic, D., Leshem, Y., Dor, R., Bragin, A.E., Bragin, E., Katzner, T., and Sapir, N., 2025, Using GPS tracking data to validate the conservation value of bird migration counts: Biological Conservation, v. 302, 110959, 10 p., https://doi.org/10.1016/j.biocon.2024.110959.","productDescription":"110959, 10 p.","ipdsId":"IP-168274","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":482558,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Israel, 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However, because current field data cannot be gathered about these species, efforts to identify suitable habitat are often complicated and controversial. Here we present a case study examining a novel approach for identifying suitable habitat for the locally extirpated brown bear, known as the “grizzly,” in California, USA. Once home to a large population of grizzlies, the last credible sighting of a grizzly in California was in 1924, but recent discussions have explored a reintroduction. To study potential grizzly bear habitat suitability in California, we use a multi-model approach in which we consider three indirect methods, or “analogies,” each of which incorporates both environmental and social variables. In the “historical analogy,” we used a unique record of human encounters and museum specimens to build a habitat model of grizzlies in California 150 years ago. In the “geographic analogy,” we used data about contemporary brown bears in Europe and North America to identify potential suitable habitat in California. In the “taxonomic analogy,” we examined data from other large carnivores currently extant in California to draw conclusions about grizzlies. Because these methods yield varying results, we adopt a process known in the social sciences as “triangulation” to compare them. We show that a triangulation approach can improve our understanding of potential suitable habitat, clarifying the strengths and weaknesses of various methods and producing robust yet conservative estimates. Our findings suggest that large areas of suitable habitat for grizzlies exist in California. However, we note that place-based social science research and long-term investment in co-existence would be necessary to maintain suitability. The “analogy and triangulation” approach demonstrates the value of multi-model approaches for habitat suitability, especially for reintroductions.","language":"English","publisher":"Elsevier","doi":"10.1016/j.biocon.2025.110989","usgsCitation":"Mcinturff, M.C., Alagona, P., Cooper, S., Gaynor, K., Anderson, S., Forbes, E.S., Heilmayr, R., Hiroyasu, E., Kendall, B., Mychajliw, A.M., and Hardesty-Moore, M., 2025, Triangulating habitat suitability for the locally extirpated California grizzly bear: Biological Conservation, v. 303, 110989, 15 p., https://doi.org/10.1016/j.biocon.2025.110989.","productDescription":"110989, 15 p.","ipdsId":"IP-168408","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":486514,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": 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The ShakeAlert earthquake early warning (EEW) system partners along with U.S. Geological Survey (USGS) licensed operators deliver EEW alerts to the public and trigger automated systems when a significant earthquake is expected to impact California, Oregon, or Washington. ShakeAlert’s primary goal is to provide usable warning times before the arrival of damaging shaking. EEW is most likely to achieve this goal in large‐magnitude earthquakes. In recent years, ShakeAlert has gone through a series of upgrades to its underlying scientific algorithms aimed at improved performance during large earthquakes. Version 3 of this software recently went live in the production system and includes improvements to all algorithms. The main seismic algorithms that detect an earthquake and characterize its location, magnitude, and fault rupture orientation are faster than older versions. Other key changes include: using real‐time geodetic data to characterize the magnitude growth in large earthquakes; the introduction of an alert pause procedure to compromise between speed near the epicenter and improved accuracy at larger distances; and the inclusion of a nonergodic site‐response model in the ground‐motion predictions. ShakeAlert has achieved its primary goal of usable warning times before strong shaking at some locations in real‐time operations in recent M 6 earthquakes. Using offline tests, we demonstrate usable warning times are possible for many sites with peak shaking values of modified Mercalli intensity (MMI) 7–8 in M 7+ earthquakes and also for many MMI 8–9 sites in M 8+ earthquakes. ShakeAlert partners use a variety of MMI and magnitude thresholds in deciding when to alert their users within bounds set by the USGS. Our study shows that there is room to raise the magnitude thresholds up to about M 5.5 without adversely affecting performance in large earthquakes. The ground‐motion criteria are more complex owing to a significant drop‐off in warning times between the MMI 4 and 5 levels of predicted shaking. However, widely used ShakeAlert products, such as the MMI 3 and 4 contour products, can provide sufficiently long warning times before strong shaking in moderate‐to‐great earthquakes to enable a range of protective actions.

","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120240189","usgsCitation":"McGuire, J., Ulberg, C., Lux, A., Bose, M., Andrews, J., Smith, D., Crowell, B., Murray, J.R., Henson, I., Hartog, R., Felizardo, C., Huynh, M., Aranha, M., Parker, G.A., Baltay Sundstrom, A.S., Murray, M.H., Biasi, G., Guiwits, S., Saunders, J., Good, A., Santillan, V., Scrivener, C., Szeliga, W., Melbourne, T., Kress, V., de Groot, R., McBride, S., Given, D.D., Allen, R., Heaton, T.H., Husker, A.L., Thomas, V., Tobin, H., Jha, S., and Bunn, J., 2025, ShakeAlert® version 3: Expected performance in large earthquakes: Bulletin of the Seismological Society of America, v. 115, no. 2, p. 533-561, https://doi.org/10.1785/0120240189.","productDescription":"29 p.","startPage":"533","endPage":"561","ipdsId":"IP-167694","costCenters":[{"id":237,"text":"Earthquake Science 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2025 - The 3D Elevation Program—Supporting Utah’s economy","interactions":[],"lastModifiedDate":"2025-05-15T00:35:47.104765","indexId":"fs20253004","displayToPublicDate":"2025-02-05T12:40:00","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2025-3004","displayTitle":"The 3D Elevation Program—Supporting Utah’s Economy","title":"The 3D Elevation Program—Supporting Utah’s economy","docAbstract":"

Introduction 

High-quality elevation data for Utah inform decision making to improve the State’s economy. Light detection and ranging (lidar) data are used to support infrastructure planning and management, assess natural resources, and improve resiliency to hazards. The expanding availability of current and more accurate lidar data helps to better support natural resource conservation, wildfire risk management, geologic hazard investigation and mitigation, flood risk management, water supply planning, and urban planning and development. Critical applications that meet the State’s management needs depend on lidar data that provide a highly detailed three-dimensional (3D) model of the Earth’s surface and aboveground features.

The 3D Elevation Program is managed by the U.S. Geological Survey in partnership with Federal, State, Tribal, U.S. territorial, and local agencies to acquire consistent lidar coverage at quality level 2 or better to meet the many needs of the Nation and Utah. The status of available and in-progress 3DEP baseline lidar data in Utah is shown in figure 1. 3DEP baseline lidar data include quality level 2 or better, 1-meter or better digital elevation models, and lidar point clouds, and must meet the Lidar Base Specification version 1.2 (https://www.usgs.gov/3dep/lidarspec) or newer requirements. The National Enhanced Elevation Assessment identified user requirements and conservatively estimated that availability of lidar data would result in at least $8.70 million in new benefits annually to the State. The top 10 Utah business uses for 3D elevation data, which are based on the estimated annual conservative benefits of 3DEP, are shown in table 2.

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Director, National Geospatial Program
U.S. Geological Survey, MS 511
12201 Sunrise Valley Drive
Reston, VA 20192

Email: 3DEP@usgs.gov

","tableOfContents":"","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"publishedDate":"2025-02-05","noUsgsAuthors":false,"publicationDate":"2025-02-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Ritmiller, Cynthia L. 0000-0001-8186-3884","orcid":"https://orcid.org/0000-0001-8186-3884","contributorId":344312,"corporation":false,"usgs":true,"family":"Ritmiller","given":"Cynthia L.","affiliations":[{"id":5047,"text":"NGTOC Denver","active":true,"usgs":true}],"preferred":true,"id":926044,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70263262,"text":"ofr20241076 - 2025 - Continuous stream discharge, salinity, and associated data collected in the lower St. Johns River and its tributaries, Florida, 2022","interactions":[],"lastModifiedDate":"2025-07-21T18:11:15.378927","indexId":"ofr20241076","displayToPublicDate":"2025-02-04T14:11:40","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2024-1076","displayTitle":"Continuous Stream Discharge, Salinity, and Associated Data Collected in the Lower St. Johns River and Its Tributaries, Florida, 2022","title":"Continuous stream discharge, salinity, and associated data collected in the lower St. Johns River and its tributaries, Florida, 2022","docAbstract":"

The U.S. Army Corps of Engineers, Jacksonville District, deepened the St. Johns River channel in Jacksonville, Florida, to accommodate larger, fully loaded cargo vessels. The U.S. Geological Survey (USGS), in cooperation with the U.S. Army Corps of Engineers, monitored stage, discharge, and (or) water temperature and salinity at 26 continuous data collection sites in the St. Johns River and its tributaries.

This report contains information collected during the 2022 water year, from October 2021 to September 2022. Data at each site were compared for the length of the project and on a yearly basis to show the annual variability of discharge and salinity.

The countywide annual rainfall for the 2022 water year was above the average yearly rainfall in four of the five counties. Annual mean discharge at 8 of the 10 tributary monitoring sites was lower for the 2022 water year than for the 2021 water year, and the annual mean flow at Broward River below Biscayne Boulevard near Jacksonville, Florida (USGS site number 02246751), was the lowest recorded at that site over the 7 years of data collection. The annual mean discharge for each of the main-stem sites was lower for the 2022 water year than for the 2021 water year.

Among the tributary sites, annual mean salinity was highest at Clapboard Creek above Buckhorn Bluff near Jacksonville, Fla. (USGS site number 302657081312400), the site closest to the Atlantic Ocean, and was lowest at Durbin Creek near Fruit Cove, Fla. (USGS site number 022462002), the site farthest from the ocean, for all years. Annual mean salinity data from the main-stem sites indicate that salinity decreased with distance upstream from the ocean, which was expected. Annual mean salinity at all monitoring locations was higher for the 2022 water year than the 2021 water year, except at St. Johns River at Buffalo Bluff near Satsuma, Fla. (USGS site number 02244040) and St. Johns River at Dancy Point near Spuds, Fla. (USGS site number 294213081345300), which remained the same. St. Johns River Shands Bridge near Green Cove Springs, Fla. (USGS site number 295856081372301) and Durbin Creek near Fruit Cove, Fla. (USGS site number 022462002) had the highest annual mean salinities at their respective sites since data collection began.

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Director, Caribbean-Florida Water Science Center
U.S. Geological Survey
4446 Pet Lane, Suite 108
Lutz, FL 33559

Contact Us- USGS Publications Warehouse

","tableOfContents":"","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"publishedDate":"2025-02-04","noUsgsAuthors":false,"publicationDate":"2025-02-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Carson, Jennifer N. 0009-0003-2482-3386","orcid":"https://orcid.org/0009-0003-2482-3386","contributorId":350470,"corporation":false,"usgs":true,"family":"Carson","given":"Jennifer N.","affiliations":[{"id":27821,"text":"Caribbean-Florida Water Science Center","active":true,"usgs":true}],"preferred":true,"id":926102,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Benacquisto, Matthew T. 0009-0006-0681-0233","orcid":"https://orcid.org/0009-0006-0681-0233","contributorId":350471,"corporation":false,"usgs":true,"family":"Benacquisto","given":"Matthew T.","affiliations":[{"id":27821,"text":"Caribbean-Florida Water Science Center","active":true,"usgs":true}],"preferred":true,"id":926103,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70263109,"text":"dr1205 - 2025 - Streamflow, water quality, and constituent loads and yields, Scituate Reservoir drainage area, Rhode Island, water year 2022","interactions":[],"lastModifiedDate":"2025-07-21T18:04:59.673435","indexId":"dr1205","displayToPublicDate":"2025-02-04T06:10:00","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":9318,"text":"Data Report","code":"DR","onlineIssn":"2771-9448","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1205","displayTitle":"Streamflow, Water Quality, and Constituent Loads and Yields, Scituate Reservoir Drainage Area, Rhode Island, Water Year 2022","title":"Streamflow, water quality, and constituent loads and yields, Scituate Reservoir drainage area, Rhode Island, water year 2022","docAbstract":"

As part of a long-term cooperative program to monitor water quality within the Scituate Reservoir drainage area, the U.S. Geological Survey, in cooperation with Providence Water (formerly the Providence Water Supply Board), collected streamflow and water-quality data in tributaries to the Scituate Reservoir, Rhode Island. Streamflow and concentrations of chloride and sodium estimated from records of specific conductance for 16 tributaries were used to calculate loads of chloride and sodium during water year 2022 (October 1, 2021, through September 30, 2022). Water-quality samples were collected by Providence Water at 37 sampling stations on tributaries to the Scituate Reservoir during water year 2022. These water-quality data are summarized by using values of central tendency and are used, in combination with measured (or estimated) streamflows, to calculate loads and yields of selected water-quality constituents for water year 2022.

Annual mean streamflows for monitoring stations in this study ranged from about 0.31 to 28.0 cubic feet per second during water year 2022. At the 16 continuous-record streamgages, tributaries transported about 2,600 metric tons of chloride and 1,600 metric tons of sodium to the Scituate Reservoir; annual chloride yields for the tributaries ranged from 15 to 100 metric tons per square mile, and annual sodium yields ranged from 10 to 59 metric tons per square mile. At the stations where water-quality samples were collected by Providence Water, the medians of the median daily loads were 55,000 million colony forming units per day for coliform bacteria, 1,300 million colony forming units per day for Escherichia coli, 230 kilograms per day for chloride, 11 grams per day as nitrogen for nitrite, 620 grams per day as nitrogen for nitrate, and 440 grams per day as orthophosphate for phosphate, The medians of the median yields were 25,000 million colony forming units per day per square mile for coliform bacteria, 810 million colony forming units per day per square mile for Escherichia coli, 110 kilograms per day per square mile for chloride, 5.1 grams per day per square mile as nitrogen for nitrite, less than 300 grams per day per square mile as nitrogen for nitrate, and 230 grams per day per square mile as orthophosphate for phosphate.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/dr1205","collaboration":"Prepared in cooperation with Providence Water","usgsCitation":"Smith, K.P., and Spaetzel, A.B., 2025, Streamflow, water quality, and constituent loads and yields, Scituate Reservoir drainage area, Rhode Island, water year 2022: U.S. Geological Survey Data Report 1205, 33 p., https://doi.org/10.3133/dr1205.","productDescription":"Report: vi, 33 p.; Data Release","numberOfPages":"33","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-168044","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":492680,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_118425.htm","linkFileType":{"id":5,"text":"html"}},{"id":481543,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9WK8N0F","text":"USGS data release","linkHelpText":"Water-quality data from the Providence Water Supply Board for tributary streams to the Scituate Reservoir (ver. 3.0, November 2023)"},{"id":481542,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/dr/1205/images/"},{"id":481539,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/dr/1205/dr1205.pdf","text":"Report","size":"3.52 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DR 1205 PDF"},{"id":481461,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/dr/1205/coverthb.jpg"},{"id":481541,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/dr/1205/dr1205.XML","linkFileType":{"id":8,"text":"xml"},"description":"DR 1205 XML"},{"id":481540,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/dr1205/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"DR 1205 HTML"}],"country":"United States","state":"Rhode Island","otherGeospatial":"Scituate Reservoir Drainage Area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -71.74828321234178,\n 41.88241813157933\n ],\n [\n -71.74828321234178,\n 41.72949318006701\n ],\n [\n -71.53726504656385,\n 41.72949318006701\n ],\n [\n -71.53726504656385,\n 41.88241813157933\n ],\n [\n -71.74828321234178,\n 41.88241813157933\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"

Director, New England Water Science Center
U.S. Geological Survey
10 Bearfoot Road
Northborough, MA 01532

","tableOfContents":"","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"publishedDate":"2025-02-04","noUsgsAuthors":false,"plainLanguageSummary":"

The U.S. Geological Survey, in cooperation with Providence Water (formerly Providence Water Supply Board), conducted a long-term program to monitor water quality in the Scituate Reservoir drainage area in Rhode Island to collect streamflow and water-quality data from 16 tributaries to the reservoir during the water year 2022. These data were used to estimate loads of chloride and sodium. Additionally, water-quality samples were collected at 37 sampling stations on the tributaries, and the data were summarized using central tendency values.

","publicationDate":"2025-02-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Smith, Kirk 0000-0003-0269-474X","orcid":"https://orcid.org/0000-0003-0269-474X","contributorId":204404,"corporation":false,"usgs":true,"family":"Smith","given":"Kirk","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":925538,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Spaetzel, Alana B. 0000-0002-9871-812X","orcid":"https://orcid.org/0000-0002-9871-812X","contributorId":240935,"corporation":false,"usgs":true,"family":"Spaetzel","given":"Alana","email":"","middleInitial":"B.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":925539,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70269379,"text":"70269379 - 2025 - Water depth, position within the nesting colony, and nearest neighbor density affect nest survival in Aechmophorus occidentalis (Western Grebe)","interactions":[],"lastModifiedDate":"2025-11-26T16:17:18.8104","indexId":"70269379","displayToPublicDate":"2025-02-03T10:13:41","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":9101,"text":"Ornithological Applications","printIssn":"0010-5422","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Water depth, position within the nesting colony, and nearest neighbor density affect nest survival in Aechmophorus occidentalis (Western Grebe)","title":"Water depth, position within the nesting colony, and nearest neighbor density affect nest survival in Aechmophorus occidentalis (Western Grebe)","docAbstract":"

Aechmophorus occidentalis (Western Grebe) are colonial nesting waterbirds that have experienced population declines. We located and monitored 709 grebe nests using a drone within Lake Cascade, the largest grebe breeding colony in Idaho. We conducted 6 flights between June 20, 2018 and July 11, 2018 and used the photographs from each flight to create an orthomosaic image that we then digitized and georeferenced. The resolution of the images allowed for visualization of each nest, nest contents, and adult grebes on each flight. Using the georeferenced images, we created nest histories and estimated nest fate for the 709 grebe nests. We also collected data on the following covariates to assess whether any of them affected nest survival: distance of the nest to the center of the colony; distance of the nest to the edge of the colony; distance of the nest to deep water habitat; water depth at the nest; nearest neighbor distance, and an aggregation index (mean distance to the 5 nearest nests). The orthomosaics from repeated drone flights allowed us to estimate nesting success without disturbing the colony; 51.2% of nests survived until hatching. The daily survival probability of grebe nests was positively correlated with the aggregation index and water depth at the nest (albeit only slightly). Daily survival probabilities were negatively correlated with distance between the nest and the colony center and distance to deep water (i.e., foraging habitat). The results of this study can be used to inform conservation efforts by identifying areas of the Lake Cascade grebe colony that are most vulnerable to nest failures and formulating explicit management actions that could be implemented to increase nest survival such as changes in timing of water drawdowns and habitat management to ensure habitat suitable for grebe nesting is in close proximity to deep water foraging areas. Moreover, grebes are not the only waterbird that makes use of managed reservoirs; other waterbirds may benefit from the findings of this study to implement more informed management practices.

","language":"English","publisher":"Oxford Academic","doi":"10.1093/ornithapp/duaf011","usgsCitation":"Lachman, D.A., Conway, C.J., Vierling, K.T., and Matthews, T., 2025, Water depth, position within the nesting colony, and nearest neighbor density affect nest survival in Aechmophorus occidentalis (Western Grebe): Ornithological Applications, v. 127, no. 3, duaf011, https://doi.org/10.1093/ornithapp/duaf011.","productDescription":"duaf011","ipdsId":"IP-167752","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":496906,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho","otherGeospatial":"Lake Cascade","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -116.22230762170753,\n 44.76352823654196\n ],\n [\n -116.22230762170753,\n 44.46219778864179\n ],\n [\n -115.98703112617977,\n 44.46219778864179\n ],\n [\n -115.98703112617977,\n 44.76352823654196\n ],\n [\n -116.22230762170753,\n 44.76352823654196\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"127","issue":"3","noUsgsAuthors":false,"publicationDate":"2025-02-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Lachman, Deo A.","contributorId":338149,"corporation":false,"usgs":false,"family":"Lachman","given":"Deo","email":"","middleInitial":"A.","affiliations":[{"id":81087,"text":"University of Idaho, Department of Fish and Wildlife Sciences","active":true,"usgs":false}],"preferred":false,"id":943610,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Conway, Courtney J. 0000-0003-0492-2953 cconway@usgs.gov","orcid":"https://orcid.org/0000-0003-0492-2953","contributorId":2951,"corporation":false,"usgs":true,"family":"Conway","given":"Courtney","email":"cconway@usgs.gov","middleInitial":"J.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":943611,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Vierling, Kerri T.","contributorId":338150,"corporation":false,"usgs":false,"family":"Vierling","given":"Kerri","email":"","middleInitial":"T.","affiliations":[{"id":81087,"text":"University of Idaho, Department of Fish and Wildlife Sciences","active":true,"usgs":false}],"preferred":false,"id":943612,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Matthews, Ty","contributorId":280032,"corporation":false,"usgs":false,"family":"Matthews","given":"Ty","affiliations":[{"id":37461,"text":"fws","active":true,"usgs":false}],"preferred":false,"id":943613,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70265026,"text":"70265026 - 2025 - Snapshots of mid-to-late Holocene sea-surface temperature variability from a subtropical western Atlantic coral reef","interactions":[],"lastModifiedDate":"2025-03-31T14:16:41.461574","indexId":"70265026","displayToPublicDate":"2025-02-03T09:11:40","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2996,"text":"Palaeogeography, Palaeoclimatology, Palaeoecology","printIssn":"0031-0182","active":true,"publicationSubtype":{"id":10}},"title":"Snapshots of mid-to-late Holocene sea-surface temperature variability from a subtropical western Atlantic coral reef","docAbstract":"

Large-scale Holocene climate reconstructions rely heavily on extratropical proxy records. Coral-based temperature reconstructions from the tropical and subtropical oceans therefore fill a critical spatial and temporal data gap, allowing for reconstruction of seasonally resolved temperature variability. We present five new, monthly-resolved sea-surface temperature (SST) reconstructions (between 39 and 57 years in length) from 2 to 7 thousand years ago (ka) based on the strontium-to‑calcium ratio (Sr/Ca) of Orbicella faveolata corals from subtropical reefs in south Florida. Modern calibrations between O. faveolata Sr/Ca and in situ SST from the region allow us to directly compare the mean and variability of SSTs since the mid-Holocene. In contrast to the low climate variability observed in more tropical areas of the western Atlantic during the Holocene, our records from subtropical south Florida exhibit pronounced changes in mean SST and variability. Our records suggest that mid-Holocene SSTs in the Florida Keys were highly variable, with relatively cooler winters driving a cooler mean SST at ∼6.7 ka (23.7 ± 0.6°C at 6.7 ka and 25.0 ± 0.5°C at 6.6 ka), and relatively warmer summers and more variable temperatures by 5.8 ka (27.1 ± 0.4°C, seasonality of 8.7°C). We also analyzed stable oxygen isotopes in two of our corals and those data support our Sr/Ca-based estimate of climatic warming between 6.6 ka and 5.8 ka (−3.6‰ and − 3.9‰). Both winter and summer temperatures were significantly cooler than the other mid-to-late Holocene snapshots at 3.6 ka (21.2 ± 0.5°C) and SST warmed but remained highly variable at 2.6 ka (25.0 ± 0.6°C, seasonality of 7.9°C). These centennial-scale changes in climate variability potentially contributed to the regional shutdown of reef accretion by the late Holocene. Our reconstructions provide a proof-of-concept study that highlights the value of coral-based SST records from highly sensitive, subtropical locations for understanding Holocene climate on seasonal to centennial timescales.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.palaeo.2025.112777","usgsCitation":"Jacobs, J.A., Richey, J.N., Flannery, J., Thiumalai, K., and Toth, L., 2025, Snapshots of mid-to-late Holocene sea-surface temperature variability from a subtropical western Atlantic coral reef: Palaeogeography, Palaeoclimatology, Palaeoecology, v. 663, 112777, 13 p., https://doi.org/10.1016/j.palaeo.2025.112777.","productDescription":"112777, 13 p.","ipdsId":"IP-166418","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":488920,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.palaeo.2025.112777","text":"Publisher Index Page"},{"id":484015,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Dry Tortugas National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -82.74479831836513,\n 24.744714178430996\n ],\n [\n -83.00110001597643,\n 24.744714178430996\n ],\n [\n -83.00110001597643,\n 24.55302673998355\n ],\n [\n -82.74479831836513,\n 24.55302673998355\n ],\n [\n -82.74479831836513,\n 24.744714178430996\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"663","noUsgsAuthors":false,"publicationDate":"2025-02-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Jacobs, Jessica A. 0000-0001-5611-2093","orcid":"https://orcid.org/0000-0001-5611-2093","contributorId":333551,"corporation":false,"usgs":true,"family":"Jacobs","given":"Jessica","email":"","middleInitial":"A.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":932342,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Richey, Julie N. 0000-0002-2319-7980 jrichey@usgs.gov","orcid":"https://orcid.org/0000-0002-2319-7980","contributorId":174046,"corporation":false,"usgs":true,"family":"Richey","given":"Julie","email":"jrichey@usgs.gov","middleInitial":"N.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":932343,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Flannery, Jennifer A. 0000-0002-1692-2662","orcid":"https://orcid.org/0000-0002-1692-2662","contributorId":350413,"corporation":false,"usgs":false,"family":"Flannery","given":"Jennifer A.","affiliations":[{"id":37487,"text":"formerly USGS","active":true,"usgs":false}],"preferred":false,"id":932344,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Thiumalai, Kaustubh 0000-0002-7875-4182","orcid":"https://orcid.org/0000-0002-7875-4182","contributorId":264344,"corporation":false,"usgs":false,"family":"Thiumalai","given":"Kaustubh","email":"","affiliations":[{"id":7042,"text":"University of Arizona","active":true,"usgs":false}],"preferred":false,"id":932345,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Toth, Lauren T. 0000-0002-2568-802X ltoth@usgs.gov","orcid":"https://orcid.org/0000-0002-2568-802X","contributorId":181748,"corporation":false,"usgs":true,"family":"Toth","given":"Lauren","email":"ltoth@usgs.gov","middleInitial":"T.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":932346,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70263305,"text":"70263305 - 2025 - Concentration-discharge relations and transient metal loads reveal spatiotemporal variability in solute-generation mechanisms in a mine-affected watershed","interactions":[],"lastModifiedDate":"2025-02-11T15:50:56.369579","indexId":"70263305","displayToPublicDate":"2025-02-03T07:53:49","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2233,"text":"Journal of Contaminant Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"Concentration-discharge relations and transient metal loads reveal spatiotemporal variability in solute-generation mechanisms in a mine-affected watershed","docAbstract":"Concentration-discharge (CQ) relations are commonly used to understand geochemical and hydrologic controls on the generation of solutes in watersheds. Despite the widespread application of CQ relations, this technique has been infrequently applied to acid mine drainage (AMD) sites, but the CQ framework may allow mechanistic understanding of remedial outcomes such as impoundment of water within underground mines. Results of CQ analyses and changes in metal loads in an AMD affected watershed in Colorado, USA indicate that dissolved loads increased at many individual locations following water impoundment within mine workings. Although increased loads were observed at most individual locations, these increases were offset by a large decrease in loading from the largest mine. A loading analysis that included data from an instream monitoring location showed a statistically significant decrease in Fe and Zn after bulkhead emplacement, indicating a net positive effect of bulkheads. Streams generally displayed dilution CQ patterns whereas mines and springs showed either flushing or chemostatic patterns prior to bulkheading, which transitioned to chemostatic patterns following bulkheading, indicating a transition from dynamic to equilibrium geochemical processes. Saturation indices for sulfide and secondary minerals indicated that mines and springs were near equilibrium for phases including schwertmannite, fluorite, and gypsum. Saturation indices vary through time for mines suggesting progressive leaching of sulfide minerals as the mass of available minerals in the mine workings decreases. Together, these diverse analyses provide an integrated understanding of the variability in solute generating processes in this watershed and may inform remediation plans for similarly affected sites by indicating the nature of mineralogic controls on water quality.","language":"English","publisher":"Elsevier","doi":"10.1016/j.jconhyd.2025.104513","usgsCitation":"Newman, C.P., Navarre-Sitchler, A., Runkel, R.L., and Cowie, R.M., 2025, Concentration-discharge relations and transient metal loads reveal spatiotemporal variability in solute-generation mechanisms in a mine-affected watershed: Journal of Contaminant Hydrology, v. 269, 104513, 19 p., https://doi.org/10.1016/j.jconhyd.2025.104513.","productDescription":"104513, 19 p.","ipdsId":"IP-159009","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":489934,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index 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\"}}]}","volume":"269","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Newman, Connor P. 0000-0002-6978-3440","orcid":"https://orcid.org/0000-0002-6978-3440","contributorId":222596,"corporation":false,"usgs":true,"family":"Newman","given":"Connor","email":"","middleInitial":"P.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":926259,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Navarre-Sitchler, Alexis","contributorId":190441,"corporation":false,"usgs":false,"family":"Navarre-Sitchler","given":"Alexis","email":"","affiliations":[],"preferred":false,"id":926260,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Runkel, Robert L. 0000-0003-3220-481X 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rivers","interactions":[],"lastModifiedDate":"2025-02-24T16:59:51.078508","indexId":"70263607","displayToPublicDate":"2025-02-01T09:18:08","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1801,"text":"Geomorphology","active":true,"publicationSubtype":{"id":10}},"title":"Development of ‘SedCam’— A close-range remote sensing method of estimating suspended-sediment concentration in small rivers","docAbstract":"

The adaptation of suspended-sediment surrogate technologies continues to rapidly expand across geomorphology and fluvial sediment monitoring efforts. Over a decade of research and development shows increased reliability and accuracy of in-situ surrogates with reduced program cost as compared to traditional sample-based methods, but environmental fouling and probe damage can be problematic. The SedCam technique is a unique non-contact close-range remote sensing method to estimate suspended-sediment concentration from multispectral imagery of a river surface. In contrast to typical airborne- or satellite-based platforms, SedCam uses broadband sensors with lower spectral resolution (three bands covering wavelengths of 340 to 1100 nm) but greater spatial resolution (0.5 mm pixel size; equivalent to medium to coarse sand) and temporal resolution (15-min intervals during daylight hours). This paper summarizes lessons learned from two studies, utilizing three consumer-grade digital cameras (each with different spectral signatures) at two different rivers (each with different sediment characteristics). >90,000 images and 174 concurrent physical samples represent a collective period of 26 months. A subset of these data pairs supports the development of four regression models. Statistical diagnostics show model error can be <40 % when surface point samples are used, with coefficients of determination ≥0.90. This novel approach shows similar accuracy to other surrogate methods such as instream turbidity. Results of this study indicate that optimizing spectra based on expected suspended-sediment concentration increases model performance.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.geomorph.2025.109642","usgsCitation":"Mosbrucker, A.R., and Wood, M.S., 2025, Development of ‘SedCam’— A close-range remote sensing method of estimating suspended-sediment concentration in small rivers: Geomorphology, v. 476, 109642, 8 p., https://doi.org/10.1016/j.geomorph.2025.109642.","productDescription":"109642, 8 p.","ipdsId":"IP-146303","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":489813,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.geomorph.2025.109642","text":"Publisher Index Page"},{"id":482155,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"476","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Mosbrucker, Adam R. 0000-0003-0298-0324 amosbrucker@usgs.gov","orcid":"https://orcid.org/0000-0003-0298-0324","contributorId":4968,"corporation":false,"usgs":true,"family":"Mosbrucker","given":"Adam","email":"amosbrucker@usgs.gov","middleInitial":"R.","affiliations":[{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":927555,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wood, Molly S. 0000-0002-5184-8306 mswood@usgs.gov","orcid":"https://orcid.org/0000-0002-5184-8306","contributorId":788,"corporation":false,"usgs":true,"family":"Wood","given":"Molly","email":"mswood@usgs.gov","middleInitial":"S.","affiliations":[{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true},{"id":502,"text":"Office of Surface Water","active":true,"usgs":true},{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":927556,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70273857,"text":"70273857 - 2025 - Lower trophic level monitoring implementation plan for Barataria Basin: Protocols and programmatic management","interactions":[],"lastModifiedDate":"2026-02-10T14:32:53.901679","indexId":"70273857","displayToPublicDate":"2025-02-01T08:52:54","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":3,"text":"Organization Series"},"title":"Lower trophic level monitoring implementation plan for Barataria Basin: Protocols and programmatic management","docAbstract":"

Prior work completed by Kiskaddon et al. (2021, 2022b, 2022a) identified critical data gaps for Lower Trophic Level (LTL) organisms in Barataria Basin, Louisiana. A Monitoring and Adaptive Management (MAM) Activity Implementation Plan (MAIP) was subsequently developed to describe a MAM Activity that would address and fill these critical data gaps (hereafter termed the “LTL project”). As the lead implementing Trustee of the LTL project, the National Oceanic and Atmospheric Administration (NOAA), in collaboration with the Louisiana Trustee Implementation Group (LA TIG), is charged with implementing the LTL project (NOAA, 2022). The Water Institute (the Institute), in cooperation with federal, state, and private entities including NOAA, the U.S. Geological Survey (USGS), Louisiana State University (LSU), University of Louisiana at Lafayette (UL Lafayette), University of California (UC) Santa Cruz, and Dynamic Solutions, LLC developed this implementation plan to further detail LTL data collection in Barataria Basin that will fulfill the MAIP. This monitoring implementation plan describes procedures and protocols critical for data collection and project management. 

","language":"English","publisher":"The Water Institute","usgsCitation":"Kiskaddon, E.P., Bargu, S., Baustian, M.M., Carle, M., Cowan, J., Doerr, J., Glaspie, C.N., Jensen, B., Liu, B., Marshall, E., Polito, M.J., Reeves, D.B., Sable, S., Sutor, M., and Zink, I., 2025, Lower trophic level monitoring implementation plan for Barataria Basin: Protocols and programmatic management, 164 p.","productDescription":"164 p.","ipdsId":"IP-173453","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":499674,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":499669,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://www.gulfspillrestoration.noaa.gov/project?id=269"}],"country":"United States","state":"Louisiana","otherGeospatial":"Barataria Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": 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The behavior and abundance of sympatric predators can be affected by a complex dominance hierarchy. The strength of antagonistic interactions in predator communities is difficult to study and remains poorly understood for many predator assemblages. Predators directly and indirectly influence the broader ecosystem, so identifying the relative importance of competition, prey, and habitat in shaping predator interactions has broad conservation and management implications. We investigated space use among five predator species (black bear [Ursus americanus], bobcat [Lynx rufus], coyote [Canis latrans], mountain lion [Puma concolor], and gray wolf [Canis lupus]) across three temporal scales in northern Idaho, USA. We used camera trap data to test whether potentially subordinate predators spatially avoided dominant predators and how prey availability influenced those relationships. We found few instances of subordinate predators spatially avoiding dominant predators and only at the finest temporal scale of our analyses. Instead, habitat features generally influenced predator space use patterns at coarser scales whereas prey and competitor presence influenced space use patterns at finer scales. Co-occurrence was positively associated between coyotes and bobcats at coarser timescales and between mesopredators and apex predators at finer timescales. Bobcats and mountain lions temporarily delayed the use of sites recently visited by coyotes and black bears, respectively. And all predator species used sites sooner following the detection of a competitor in areas with higher relative abundances of prey (primarily white-tailed deer [Odocoileus virginianus]). Our results suggest attraction to shared habitats and prey resources influenced space use in the predator community more than avoidance of competitors. We propose that the effects of interspecific interactions on predator distributions were most evident for mesopredators because their trophic position requires balancing risks and rewards associated with prey, apex predators, and other mesopredators. In addition, relatively high densities of a common prey source likely facilitated the spatial coexistence in this predator community. Our study demonstrates the value of simultaneously assessing multiple interspecific interactions across different spatiotemporal scales to discern relationships within the predator guild.

","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecm.1648","collaboration":"Idaho Department of Fish and Game","usgsCitation":"Bassing, S., Ausband, D.E., Mumma, M., Thompson, S., Hurley, M., and Falcy, M.R., 2025, Mammalian predator co‐occurrence affected by prey and habitat more than competitor presence at multiple time scales: Ecological Monographs, v. 95, no. 1, e1648, 25 p., https://doi.org/10.1002/ecm.1648.","productDescription":"e1648, 25 p.","ipdsId":"IP-157343","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":498242,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecm.1648","text":"Publisher Index Page"},{"id":489257,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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0000-0002-3332-2239","orcid":"https://orcid.org/0000-0002-3332-2239","contributorId":288500,"corporation":false,"usgs":true,"family":"Falcy","given":"Matthew","email":"","middleInitial":"Richard","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":938774,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70270867,"text":"70270867 - 2025 - Artificial neural network multilayer perceptron models to classify California’s crops using Harmonized Landsat Sentinel (HLS) data","interactions":[],"lastModifiedDate":"2025-08-26T15:15:01.880335","indexId":"70270867","displayToPublicDate":"2025-02-01T08:07:35","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3052,"text":"Photogrammetric Engineering and Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Artificial neural network multilayer perceptron models to classify California’s crops using Harmonized Landsat Sentinel (HLS) data","docAbstract":"

Advances in remote sensing and machine learning are enhancing cropland classification, vital for global food and water security. We used multispectral Harmonized Landsat 8 Sentinel-2 (HLS) 30-m data in an artificial neural network (ANN) multi-layer perceptron (MLP) model to classify five crop classes (cotton, alfalfa, tree crops, grapes, and others) in California's Central Valley. The ANN MLP model, trained on 2021 data from the United States Department of Agriculture's Cropland Data Layer, was validated by classifying crops for an independent year, 2022. Across the five crop classes, the overall accuracy was 74%. Producer's and user's accuracies ranged from 65% to 87%, with cotton achieving the highest accuracies. The study highlights the potential of using deep learning with HLS time series data for accurate global crop classification.

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Over the past few decades, Ictalurus furcatus (Valenciennes in Cuvier and Valenciennes, 1840; blue catfish) have become a formidable invasive species in tidal tributaries of the Chesapeake Bay in Maryland and Delaware. Knowledge of their reproductive behaviors can support managers in the determination of ideal timing and implementation of mitigation strategies. In 2020–22, the U.S. Geological Survey sampled blue catfish from the Chesapeake Bay’s tidal reaches of the Nanticoke River, Broad Creek, Marshyhope Creek, and Patuxent River in Maryland and Delaware from March to October. All fish were analyzed with histology to assess reproductive stages (immature, pre-spawn [early and late], and post-spawn). Plasma was collected for multiple endpoints including 17β-estradiol (E2), calcium, and total protein. Results indicated that female spawning generally occurred from late April through June, as evidenced by the histological data showing that the number of vitellogenic oocytes in late pre-spawn females began to increase in April, peaked in May, and gradually declined through July. In males, the greatest number of late pre-spawn individuals was observed in April and gradually declined through June. Additionally, female E2 levels were highest in late, pre-spawn females, thus showing a similar trend as the histological results, indicating that this endpoint can be used for assessing reproductive changes over time. Collectively, this study documents typical spawning patterns in blue catfish within the Chesapeake Bay watershed. However, further research across different watersheds would enhance data availability and inform more comprehensive management strategies.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/ofr20241074","usgsCitation":"Walsh, H.L., Densmore, C.L., Regish, A.M., Norstog, J., Moore, J., Williams, B., Bressman, N., and Crum, Z., 2025, Reproductive parameters in invasive blue catfish (Ictalurus furcatus) from tributaries of the Chesapeake Bay in Maryland and Delaware, 2020–22: U.S. Geological Survey Open-File Report 2024–1074, 17 p., https://doi.org/10.3133/ofr20241074.","productDescription":"Report: vi, 17 p.; Data Release","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-171688","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":481526,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2024/1074/images"},{"id":481525,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P13W8K3Y","text":"USGS data release","linkHelpText":"Morphometric and reproductive data from blue catfish (Ictalurus furcatus) collected in tributaries of the Chesapeake Bay, Maryland and Delaware 2020–2022"},{"id":481522,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2024/1074/ofr20241074.pdf","text":"Report","size":"4.46 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2024-1074"},{"id":481521,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2024/1074/coverthb.jpg"},{"id":481555,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20241074/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2024-1074"},{"id":481527,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2024/1074/ofr20241074.xml"}],"country":"United States","state":"Delaware, Maryland","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -75.56331116045253,\n 38.61088599742371\n ],\n [\n -75.82395278530792,\n 38.61088599742371\n ],\n [\n -75.82395278530792,\n 38.38925412638224\n ],\n [\n -75.56331116045253,\n 38.38925412638224\n ],\n [\n -75.56331116045253,\n 38.61088599742371\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"

Director, Eastern Ecological Science Center
U.S. Geological Survey
11649 Leetown Rd.
Kearneysville, WV 25430

","tableOfContents":"","publishedDate":"2025-01-31","noUsgsAuthors":false,"publicationDate":"2025-01-31","publicationStatus":"PW","contributors":{"authors":[{"text":"Walsh, Heather L. 0000-0001-6392-4604 hwalsh@usgs.gov","orcid":"https://orcid.org/0000-0001-6392-4604","contributorId":4696,"corporation":false,"usgs":true,"family":"Walsh","given":"Heather","email":"hwalsh@usgs.gov","middleInitial":"L.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":925773,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Densmore, Christine L. 0000-0001-6440-0781","orcid":"https://orcid.org/0000-0001-6440-0781","contributorId":349917,"corporation":false,"usgs":false,"family":"Densmore","given":"Christine L.","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":925774,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Regish, Amy M. 0000-0003-4747-4265","orcid":"https://orcid.org/0000-0003-4747-4265","contributorId":265360,"corporation":false,"usgs":true,"family":"Regish","given":"Amy","email":"","middleInitial":"M.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":925775,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Norstog, Jessica L. 0000-0002-5495-5131","orcid":"https://orcid.org/0000-0002-5495-5131","contributorId":295345,"corporation":false,"usgs":false,"family":"Norstog","given":"Jessica","email":"","middleInitial":"L.","affiliations":[{"id":6932,"text":"University of Massachusetts, Amherst","active":true,"usgs":false}],"preferred":false,"id":925776,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Moore, Johnny","contributorId":349918,"corporation":false,"usgs":false,"family":"Moore","given":"Johnny","affiliations":[{"id":83536,"text":"Delaware DNR","active":true,"usgs":false}],"preferred":false,"id":925777,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Williams, Branson 0000-0003-0000-6720","orcid":"https://orcid.org/0000-0003-0000-6720","contributorId":349919,"corporation":false,"usgs":false,"family":"Williams","given":"Branson","affiliations":[{"id":83121,"text":"Maryland DNR","active":true,"usgs":false}],"preferred":false,"id":925778,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bressman, Noah 0000-0002-2916-3562","orcid":"https://orcid.org/0000-0002-2916-3562","contributorId":349920,"corporation":false,"usgs":false,"family":"Bressman","given":"Noah","affiliations":[{"id":36201,"text":"Salisbury University","active":true,"usgs":false}],"preferred":false,"id":925779,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Crum, Zachary","contributorId":349921,"corporation":false,"usgs":false,"family":"Crum","given":"Zachary","affiliations":[{"id":6952,"text":"California Department of Fish and Wildlife","active":true,"usgs":false}],"preferred":false,"id":925780,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ]}