{"pageNumber":"44","pageRowStart":"1075","pageSize":"25","recordCount":41022,"records":[{"id":70265721,"text":"70265721 - 2025 - Influence of local river hydraulics on Kootenai River white sturgeon (Acipenser transmontanus) habitat selection during four spawning years, 2017–2020","interactions":[],"lastModifiedDate":"2025-04-15T14:30:02.48689","indexId":"70265721","displayToPublicDate":"2025-04-08T09:25:11","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1169,"text":"Canadian Journal of Fisheries and Aquatic Sciences","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Influence of local river hydraulics on Kootenai River white sturgeon (<i>Acipenser transmontanus</i>) habitat selection during four spawning years, 2017–2020","title":"Influence of local river hydraulics on Kootenai River white sturgeon (Acipenser transmontanus) habitat selection during four spawning years, 2017–2020","docAbstract":"<p><span>Understanding fine-scale habitat selection of endangered Kootenai River white sturgeon (</span><i>Acipenser transmontanus</i><span>) is an important component for monitoring and recovery efforts. Fine-scale habitat selection and quantifying temporal changes in suitable habitat contributes to the work of addressing recruitment failure within the Kootenai River population. Habitat suitability indices were developed using over 96 000 acoustic telemetry sturgeon detections and two-dimensional hydrodynamic model simulations near Bonners Ferry, Idaho, USA. The selected habitat was assessed to develop habitat suitability indices for sturgeon; females undergoing spawn migrations and non-spawners. The most frequented locations were 8–9 m deep and water velocities of 0.3–0.7&nbsp;m·s</span><sup>−1</sup><span>. These observations suggest sturgeon with different spawning capabilities selected similar habitat. Weighted usable area was calculated to understand temporal variability in habitat quality, which showed a positive relationship with increases in flow. Results help understand the habitat limiting factors in regulated hydrologic regimes; provide biologists insight for monitoring efforts in discrete habitat conditions; guidance for water managers and the regulation of upstream water resources; and guidance to restoration practitioners for in-stream structure designs.</span></p>","language":"English","publisher":"Canadian Science Publishing","doi":"10.1139/cjfas-2024-0244","usgsCitation":"Dudunake, T., Kenworthy, M.K., Smith, T., Stephenson, S., and Hardy, R.S., 2025, Influence of local river hydraulics on Kootenai River white sturgeon (Acipenser transmontanus) habitat selection during four spawning years, 2017–2020: Canadian Journal of Fisheries and Aquatic Sciences, v. 82, 16 p., https://doi.org/10.1139/cjfas-2024-0244.","productDescription":"16 p.","ipdsId":"IP-150378","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":488244,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1139/cjfas-2024-0244","text":"Publisher Index Page"},{"id":484574,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho","otherGeospatial":"Kootenai River","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -116.30893853974553,\n              48.70438566677956\n            ],\n            [\n              -116.33409421325345,\n              48.70438566677956\n            ],\n            [\n              -116.33409421325345,\n              48.691255343773804\n            ],\n            [\n              -116.30893853974553,\n              48.691255343773804\n            ],\n            [\n              -116.30893853974553,\n              48.70438566677956\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"82","noUsgsAuthors":false,"publicationDate":"2025-04-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Dudunake, Taylor 0000-0001-7650-2419 tdudunake@usgs.gov","orcid":"https://orcid.org/0000-0001-7650-2419","contributorId":191564,"corporation":false,"usgs":true,"family":"Dudunake","given":"Taylor","email":"tdudunake@usgs.gov","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":933385,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kenworthy, Megan K. 0000-0001-7108-3016","orcid":"https://orcid.org/0000-0001-7108-3016","contributorId":304286,"corporation":false,"usgs":true,"family":"Kenworthy","given":"Megan","middleInitial":"K.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":933386,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Smith, Troy","contributorId":353368,"corporation":false,"usgs":false,"family":"Smith","given":"Troy","affiliations":[{"id":36224,"text":"Idaho Department of Fish and Game","active":true,"usgs":false}],"preferred":false,"id":933387,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stephenson, Sarah","contributorId":353369,"corporation":false,"usgs":false,"family":"Stephenson","given":"Sarah","affiliations":[{"id":51972,"text":"British Columbia Ministry of Forests","active":true,"usgs":false}],"preferred":false,"id":933388,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hardy, Ryan S.","contributorId":167032,"corporation":false,"usgs":false,"family":"Hardy","given":"Ryan","email":"","middleInitial":"S.","affiliations":[{"id":6764,"text":"Idaho Department of Fish and Game, Nampa, Idaho","active":true,"usgs":false}],"preferred":false,"id":933389,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70265482,"text":"70265482 - 2025 - How quickly do brook trout lose long-term thermal acclimation?","interactions":[],"lastModifiedDate":"2025-04-08T15:42:42.223359","indexId":"70265482","displayToPublicDate":"2025-04-08T08:37:35","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2476,"text":"Journal of Thermal Biology","active":true,"publicationSubtype":{"id":10}},"title":"How quickly do brook trout lose long-term thermal acclimation?","docAbstract":"<p><span>Abundances of coldwater adapted stream fish populations are declining largely due to anthropogenic influences, including increased temperature. To persist in streams with unsuitable thermal habitat, fish must move to coldwater patches, acclimate, or adapt to water temperatures above thermal optima. Brook trout, a coldwater adapted salmonid, has previously displayed physiological plasticity and the ability for reversible thermal acclimation when reared at higher temperatures. However, because stream temperatures are not static, it is important to explore the rate at which thermal acclimation occurs to evaluate whether prior thermal experience will influence future thermal performance. To determine the temporal scale in loss of thermal acclimation as water temperatures cool, we acclimated brook trout to three thermal regimes: +0&nbsp;°C (ambient; mimicking the daily average water temperature of a nearby long-term study site), as well as +2&nbsp;°C and +4&nbsp;°C above ambient. After 2 years of being reared under those conditions, fish from the warmer treatments were moved to a common, colder temperature (ambient). We then used critical thermal maximum to measure the loss in acclimation response of fish from each treatment over time. We found that regardless of initial acclimation temperature, thermal tolerance of warm acclimated fish decreased rapidly for 1 week, then gradually decreased, and was completely lost within 42 days. This gradual loss of acclimation may be valuable to persistence in warmer streams and will be important to include in models of the impact climate change has on brook trout and other aquatic ectotherms with significant thermal plasticity.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.jtherbio.2025.104103","usgsCitation":"O'Donnell, M., Regish, A.M., McCormick, S., and Letcher, B., 2025, How quickly do brook trout lose long-term thermal acclimation?: Journal of Thermal Biology, v. 129, 104103, 7 p., https://doi.org/10.1016/j.jtherbio.2025.104103.","productDescription":"104103, 7 p.","ipdsId":"IP-173670","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":484335,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Massachusetts","city":"Whatley","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -72.6617758519881,\n              42.46221452312392\n            ],\n            [\n              -72.6617758519881,\n              42.418869656181016\n            ],\n            [\n              -72.59608138561572,\n              42.418869656181016\n            ],\n            [\n              -72.59608138561572,\n              42.46221452312392\n            ],\n            [\n              -72.6617758519881,\n              42.46221452312392\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"129","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"O'Donnell, Matthew J. 0000-0002-9089-2377","orcid":"https://orcid.org/0000-0002-9089-2377","contributorId":299019,"corporation":false,"usgs":true,"family":"O'Donnell","given":"Matthew J.","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":932809,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"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":932810,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McCormick, S.D.","contributorId":353071,"corporation":false,"usgs":false,"family":"McCormick","given":"S.D.","affiliations":[{"id":36396,"text":"University of Massachusetts","active":true,"usgs":false}],"preferred":false,"id":932811,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Letcher, Benjamin 0000-0003-0191-5678","orcid":"https://orcid.org/0000-0003-0191-5678","contributorId":242666,"corporation":false,"usgs":true,"family":"Letcher","given":"Benjamin","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":932812,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70265686,"text":"70265686 - 2025 - A nationwide evaluation of crowd-sourced ambient temperature data","interactions":[],"lastModifiedDate":"2025-04-14T16:38:37.174103","indexId":"70265686","displayToPublicDate":"2025-04-07T09:33:36","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1708,"text":"Frontiers of Environmental Science and Engineering in China","active":true,"publicationSubtype":{"id":10}},"title":"A nationwide evaluation of crowd-sourced ambient temperature data","docAbstract":"Growing concerns about heat in urban areas paired with the sparsity of weather stations have resulted in individuals drawing on data from citizen science sensor networks to fill in data gaps. The PurpleAir are the most widely-used low-cost air quality sensors in the contiguous United States with 14,777 deployed between 1 Jan 2017 and 20 July 2021. Although the air quality data from PurpleAir sensors have been widely studied, less attention has been paid to reported temperature. We compare temperature metrics reported by PurpleAir sensors with a gridded temperature product, the North American Land Data Assimilation System (NLDAS)-2, which although not a gold-standard measure of temperature, is widely used in epidemiologic research. We evaluate the lag between indoor and outdoor PurpleAir temperatures. We report associations of the difference between outdoor PurpleAir temperatures and NLDAS-2 temperatures, an indicator of degradation, and the duration of sensor operation. Finally, based on the temperature range recorded by the outdoor PurpleAir sensors vis.a.vis NLDAS-2 temperatures, we provide a list of 271 (2.5%) sensors potentially misclassified as outdoor and likely located indoors. We observed that outdoor PurpleAir sensors agreed well with NLDAS-2 (R2 > 0.82). This association broke down under warm conditions (daily average NLDAS ≥ 21.1oC). Landcover and climate zone were significant modifiers of the association between PurpleAir and NLDAS-2 temperature metrics with the poorest PurpleAir- NLDAS-2 agreement in urban areas. Indoor PurpleAir temperatures lagged hourly NLDAS temperatures by two hours across almost all climate zones. The mean difference in hourly PurpleAir and NLDAS-2 temperatures increased by 0.57oC for every operational year, suggesting that careful attention must be paid to degradation. Overall, we find for use in epidemiological studies, that the PurpleAir sensor data is a reliable metric of daytime mean air temperature, but researchers should be aware of its limitations when examining extreme heat, or when aggregating sensor data across multiple years.","language":"English","publisher":"Frontiers Media","doi":"10.3389/fenvs.2025.1527855","usgsCitation":"deSouza, P., Ibsen, P.C., Westervelt, D., Kahn, R., Zaitchik, B., and Kinney, P., 2025, A nationwide evaluation of crowd-sourced ambient temperature data: Frontiers of Environmental Science and Engineering in China, v. 13, 1527855, 13 p., https://doi.org/10.3389/fenvs.2025.1527855.","productDescription":"1527855, 13 p.","ipdsId":"IP-171526","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":490097,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fenvs.2025.1527855","text":"Publisher Index 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States\"}}]}","volume":"13","noUsgsAuthors":false,"publicationDate":"2025-04-08","publicationStatus":"PW","contributors":{"authors":[{"text":"deSouza, Priyanka","contributorId":353306,"corporation":false,"usgs":false,"family":"deSouza","given":"Priyanka","affiliations":[{"id":16824,"text":"University of Colorado Denver","active":true,"usgs":false}],"preferred":false,"id":933260,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ibsen, Peter Christian 0000-0002-3436-9100","orcid":"https://orcid.org/0000-0002-3436-9100","contributorId":260735,"corporation":false,"usgs":true,"family":"Ibsen","given":"Peter","email":"","middleInitial":"Christian","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":933261,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Westervelt, Daniel M.","contributorId":353308,"corporation":false,"usgs":false,"family":"Westervelt","given":"Daniel M.","affiliations":[{"id":7171,"text":"Columbia University","active":true,"usgs":false}],"preferred":false,"id":933262,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kahn, Ralph","contributorId":353311,"corporation":false,"usgs":false,"family":"Kahn","given":"Ralph","affiliations":[{"id":13693,"text":"University of Colorado Boulder","active":true,"usgs":false}],"preferred":false,"id":933263,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Zaitchik, Benjamin 0000-0002-0698-0658","orcid":"https://orcid.org/0000-0002-0698-0658","contributorId":333708,"corporation":false,"usgs":false,"family":"Zaitchik","given":"Benjamin","email":"","affiliations":[{"id":36717,"text":"Johns Hopkins University","active":true,"usgs":false}],"preferred":false,"id":933264,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kinney, Patrick","contributorId":353314,"corporation":false,"usgs":false,"family":"Kinney","given":"Patrick","affiliations":[{"id":13570,"text":"Boston University","active":true,"usgs":false}],"preferred":false,"id":933265,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70265786,"text":"70265786 - 2025 - A synthesis of freshwater forested wetland soil organic carbon storage","interactions":[],"lastModifiedDate":"2025-04-16T14:31:18.998298","indexId":"70265786","displayToPublicDate":"2025-04-07T09:27:41","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5860,"text":"Frontiers in Forests and Global Change","active":true,"publicationSubtype":{"id":10}},"title":"A synthesis of freshwater forested wetland soil organic carbon storage","docAbstract":"<p><span>Freshwater forested wetlands account for ~76% (918 M ha) of the total global wetland extent. However, freshwater forested wetlands are difficult to distinguish from upland forest due to canopy coverage, the abundance of wetland-nonwetland mosaics, seasonal hydropatterns, and fewer readily observable connections to large surface water bodies relative to marshes and other emergent habitats. Therefore, freshwater forested wetland ecosystems are often misclassified as upland forests in carbon accounting models, underestimating soil organic carbon (SOC) storage. This study highlights freshwater forested wetland SOC accounting challenges and presents SOC densities/stocks from a global literature synthesis across different freshwater forested wetland types. We reviewed 374 forested wetland articles, compiling and calculating carbon densities by depth from 90 freshwater forested wetland studies to construct a database of 334 study sites including nine countries. The median (± median absolute deviation) SOC stock was 91.2 ± 46.4 Mg C ha</span><sup>−1</sup><span>&nbsp;and 235.3 ± 125.6 Mg C ha</span><sup>−1</sup><span>&nbsp;in the top 30 cm and 100 cm of soil, respectively. The tidal freshwater forested wetland had highest SOC stock (341.6 ± 98.4 Mg C ha</span><sup>−1</sup><span>) in the upper 100 cm soil profile followed by rainforest (285.6 ± 75.8 Mg C ha</span><sup>−1</sup><span>), non-tidal swamps (229.3 ± 120.4 Mg C ha</span><sup>−1</sup><span>), and floodplain forested wetlands (176.6 ± 84 Mg C ha</span><sup>−1</sup><span>). Within the conterminous United States forest type groups, the&nbsp;</span><i>Tsuga</i><span>/</span><i>Picea</i><span>&nbsp;group had the highest median SOC stocks (353.6 ± 82.9 Mg ha</span><sup>−1</sup><span>) in the top 100 cm of soil followed by&nbsp;</span><i>Quercus/Pinus</i><span>&nbsp;(246.6 ± 82.3 Mg ha</span><sup>−1</sup><span>) and&nbsp;</span><i>Quercus/Liquidambar/Taxodium</i><span>&nbsp;(207.9 ± 87.7 Mg ha</span><sup>−1</sup><span>) groups, likely driven by variability in litter degradability, wetland hydroperiod, geomorphic positions, and regional climatic factors. This literature synthesis highlights SOC accounting in freshwater forested wetland carbon pools when estimating carbon stocks and fluxes. Results can be used to improve carbon modeling outcomes, as well as inform regional, national, and global management of wetland carbon resources.</span></p>","language":"English","publisher":"Frontiers Media","doi":"10.3389/ffgc.2025.1528440","usgsCitation":"Sapkota, Y., Berkowitz, J., Stagg, C., and Busby, R., 2025, A synthesis of freshwater forested wetland soil organic carbon storage: Frontiers in Forests and Global Change, v. 8, 1528440, 15 p., https://doi.org/10.3389/ffgc.2025.1528440.","productDescription":"1528440, 15 p.","ipdsId":"IP-176238","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":488264,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/ffgc.2025.1528440","text":"Publisher Index Page"},{"id":484639,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"8","noUsgsAuthors":false,"publicationDate":"2025-04-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Sapkota, Yadav","contributorId":353419,"corporation":false,"usgs":false,"family":"Sapkota","given":"Yadav","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":933528,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Berkowitz, Jacob F.","contributorId":353422,"corporation":false,"usgs":false,"family":"Berkowitz","given":"Jacob F.","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":933529,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stagg, Camille 0000-0002-1125-7253","orcid":"https://orcid.org/0000-0002-1125-7253","contributorId":214880,"corporation":false,"usgs":true,"family":"Stagg","given":"Camille","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":933530,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Busby, Ryan R.","contributorId":353425,"corporation":false,"usgs":false,"family":"Busby","given":"Ryan R.","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":933531,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70273025,"text":"70273025 - 2025 - Environmental conditions influencing the abundance of the salmonid ectoparasite Salmincola californiensis across upper Willamette River Reservoirs, Oregon","interactions":[],"lastModifiedDate":"2025-12-15T14:46:55.827369","indexId":"70273025","displayToPublicDate":"2025-04-07T08:38:09","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":860,"text":"Aquatic Biology","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Environmental conditions influencing the abundance of the salmonid ectoparasite <i>Salmincola californiensis</i> across upper Willamette River Reservoirs, Oregon","title":"Environmental conditions influencing the abundance of the salmonid ectoparasite Salmincola californiensis across upper Willamette River Reservoirs, Oregon","docAbstract":"<p><span id=\"_mce_caret\" data-mce-bogus=\"1\" data-mce-type=\"format-caret\"><span>The freshwater copepod&nbsp;</span><i>Salmincola californiensis</i><span>&nbsp;is an ectoparasite of Pacific salmon and trout (</span><i>Oncorhynchus</i><span>&nbsp;spp.). High levels of infection by this parasite can significantly damage gills and result in blood loss, affecting the fitness and survival of hosts, and it may hinder recovery efforts of threatened and endangered salmonids. Juvenile salmonids that rear in reservoirs have been reported to experience higher rates of infection than their stream-dwelling counterparts. To date, the relationship between reservoir environmental conditions and infection rates remains poorly understood. Here, we evaluated sampling methods designed to capture&nbsp;</span><i>S. californiensis</i><span>&nbsp;copepodids, the free-swimming infectious life stage of this parasitic copepod, and develop predictive models of parasite abundance in reservoirs</span><i>.</i><span>&nbsp;We used light traps to collect 675 zooplankton samples from various sites and depths in Cougar, Lookout Point, and Fall Creek reservoirs, Oregon, USA during five months in 2020. We tested several predictive models of parasite abundance using environmental covariates obtained concurrently during plankton surveys (</span><i>e.g.</i><span>, temperature, ambient light and water clarity, reservoir plankton profiles, and water flow). Our models showed a strong influence of water temperature on abundance of copepodids, with maximum initial abundance occurring at the mean water temperature 15.2&nbsp;°C. At that temperature, August abundance was estimated to be 58.6 copepodids per site in Cougar Reservoir, 43.8 copepodids per site in Fall Creek Reservoir, and 3.5 copepodids per site in Lookout Point Reservoir. Water temperature and reservoir outflow both affected population growth of copepodids: increased water temperature was associated with an increase in population growth rate while an increased reservoir outflow was associated with a decrease in population growth rate. The efficacy of our sampling method was influenced by percent of moon fullness, whether the sample site was above or below the thermocline, water temperature, and number of juvenile sculpin fishes (</span><i>Cottus</i><span>&nbsp;spp.) captured in the trap. The mean probability of detecting a single copepodid if one was present was 0.042, but detection probability increased to 0.29 under ideal trap set conditions of warmer water, location above the thermocline, and a full moon. Biologists and managers could use these methods to assess the presence and abundance of&nbsp;</span><i>S. californiensis</i><span>&nbsp;in other locations, or to inform reservoir operations to reduce potential salmonid infections.</span></span></p>","language":"English","publisher":"Peer J","doi":"10.7717/peerj.19228","usgsCitation":"Antonelli, K., Murphy, C.A., Pollock, A.M., and Arismendi, I., 2025, Environmental conditions influencing the abundance of the salmonid ectoparasite Salmincola californiensis across upper Willamette River Reservoirs, Oregon: Aquatic Biology, v. 13, e19228, 24 p., https://doi.org/10.7717/peerj.19228.","productDescription":"e19228, 24 p.","ipdsId":"IP-172281","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":497701,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.7717/peerj.19228","text":"Publisher Index Page"},{"id":497471,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon","otherGeospatial":"upper Willamette River reservoirs","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -123.32050813525171,\n              44.19989455893608\n            ],\n            [\n              -123.32050813525171,\n              44.045490802329965\n            ],\n            [\n              -122.8991546943831,\n              44.045490802329965\n            ],\n            [\n              -122.8991546943831,\n              44.19989455893608\n            ],\n            [\n              -123.32050813525171,\n              44.19989455893608\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"13","noUsgsAuthors":false,"publicationDate":"2025-04-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Antonelli, Kelsi","contributorId":341106,"corporation":false,"usgs":false,"family":"Antonelli","given":"Kelsi","email":"","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":952112,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Murphy, Christina Amy 0000-0002-3467-6610","orcid":"https://orcid.org/0000-0002-3467-6610","contributorId":335232,"corporation":false,"usgs":true,"family":"Murphy","given":"Christina","email":"","middleInitial":"Amy","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":952113,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pollock, Amanda M.M.","contributorId":363932,"corporation":false,"usgs":false,"family":"Pollock","given":"Amanda","middleInitial":"M.M.","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":952114,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Arismendi, Ivan","contributorId":341108,"corporation":false,"usgs":false,"family":"Arismendi","given":"Ivan","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":952115,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70265494,"text":"70265494 - 2025 - Equilibrium line altitudes, accumulation areas, and the vulnerability of glaciers in Alaska","interactions":[],"lastModifiedDate":"2025-04-08T15:11:34.579076","indexId":"70265494","displayToPublicDate":"2025-04-07T08:01:39","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2328,"text":"Journal of Glaciology","active":true,"publicationSubtype":{"id":10}},"title":"Equilibrium line altitudes, accumulation areas, and the vulnerability of glaciers in Alaska","docAbstract":"<p><span>The accumulation area ratio (AAR) of a glacier reflects its current state of equilibrium, or disequilibrium, with climate and its vulnerability to future climate change. Here, we present an inventory of glacier-specific annual accumulation areas and equilibrium line altitudes (ELAs) for over 3000 glaciers in Alaska and northwest Canada (88% of the regional glacier area) from 2018 to 2022 derived from Sentinel-2 imagery. We find that the 5 year average AAR of the entire study area is 0.41, with an inter-annual range of 0.25–0.49. More than 1000 glaciers, representing 8% of the investigated glacier area, were found to have effectively no accumulation area. Summer temperature and winter precipitation from ERA5-Land explained nearly 50% of the inter-annual ELA variability across the entire study region (<i>R</i><sup>2</sup> = 0.47</span><span>). An analysis of future climate scenarios (SSP2-4.5) projects that ELAs will rise by ∼170 m on average by the end of the 21st century. Such changes would result in a loss of 25% of the modern accumulation area, leaving a total of 1900 glaciers (22% of the investigated area) with no accumulation area. These results highlight the current state of glacier disequilibrium with modern climate, as well as glacier vulnerability to projected future warming.</span></p>","language":"English","publisher":"Cambridge University Press","doi":"10.1017/jog.2024.65","usgsCitation":"Zeller, L., McGrath, D.J., Sass, L., Florentine, C., and Downs, J., 2025, Equilibrium line altitudes, accumulation areas, and the vulnerability of glaciers in Alaska: Journal of Glaciology, v. 71, e28, 13 p., https://doi.org/10.1017/jog.2024.65.","productDescription":"e28, 13 p.","ipdsId":"IP-163494","costCenters":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"links":[{"id":488628,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1017/jog.2024.65","text":"Publisher Index Page"},{"id":484323,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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,{"id":70265447,"text":"70265447 - 2025 - Estimating indicators of cyanobacterial harmful algal blooms in New York State","interactions":[],"lastModifiedDate":"2025-04-07T14:54:27.747567","indexId":"70265447","displayToPublicDate":"2025-04-07T07:50:48","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1456,"text":"Ecological Indicators","active":true,"publicationSubtype":{"id":10}},"title":"Estimating indicators of cyanobacterial harmful algal blooms in New York State","docAbstract":"<p><span>Cyanobacteria harmful algal blooms (cyanoHABs) are a global concern for aquatic ecosystem and human health. Limited funding for monitoring programs and inconsistent determination of cyanoHAB occurrence present challenges for identifying commonly effective variables for characterizing cyanoHABs and the development of generalized models. We compiled a combination of water quality measurements, lake morphology, climatology, remote sensing data, and observations of cyanoHAB occurrence across New York State and used this dataset to develop two sets of predictive models. The first model predicted chlorophyll&nbsp;</span><i>a</i><span>, a common indicator of algal biomass, and assessed the importance of variables for modeled predictions. The most important variables were then used in a second set of models to classify cyanoHAB occurrence. The irradiance attenuation coefficient (</span><i>K<sub>d</sub></i><span>), which was estimated from Secchi depth measurements, and total phosphorus were the two most important variables for predicting chlorophyll&nbsp;</span><i>a</i><span>. The second model examined several variables for their ability to classify cyanoHAB occurrence. Predicted cyanoHAB occurrence based on thresholds of chlorophyll&nbsp;</span><i>a</i><span>,&nbsp;</span><i>K<sub>d</sub></i><span>, or total nitrogen all had moderate agreement and were able to correctly classify approximately 70% of observed cyanoHABs. Our analysis indicated that multiple data types were important for predicting chlorophyll&nbsp;</span><i>a</i><span>&nbsp;statewide and that simple widely available water quality parameters could classify cyanoHABs occurrence with reasonable accuracy. Identifying variables that can be monitored with increased frequency and decreased latency to detect cyanoHAB occurrence will better inform water managers and provide valuable additional data for further refining predictive models of the likelihood of cyanoHABs occurrence.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolind.2025.113403","usgsCitation":"Savoy, P., Gorney, R.M., and Graham, J.L., 2025, Estimating indicators of cyanobacterial harmful algal blooms in New York State: Ecological Indicators, v. 173, 113403, 11 p., https://doi.org/10.1016/j.ecolind.2025.113403.","productDescription":"113403, 11 p.","ipdsId":"IP-171481","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":488558,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecolind.2025.113403","text":"Publisher Index 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York\",\"nation\":\"USA  \"}}]}","volume":"173","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Savoy, Philip 0000-0002-6075-837X","orcid":"https://orcid.org/0000-0002-6075-837X","contributorId":300288,"corporation":false,"usgs":true,"family":"Savoy","given":"Philip","email":"","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":932740,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gorney, Rebecca M. 0000-0003-4406-261X","orcid":"https://orcid.org/0000-0003-4406-261X","contributorId":317259,"corporation":false,"usgs":true,"family":"Gorney","given":"Rebecca","middleInitial":"M.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":932741,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Graham, Jennifer L. 0000-0002-6420-9335 jlgraham@usgs.gov","orcid":"https://orcid.org/0000-0002-6420-9335","contributorId":1769,"corporation":false,"usgs":true,"family":"Graham","given":"Jennifer","email":"jlgraham@usgs.gov","middleInitial":"L.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":932742,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70272682,"text":"70272682 - 2025 - Uncertainty quantification of geophysical and hydrologic parameters estimated from borehole nuclear magnetic resonance data","interactions":[],"lastModifiedDate":"2025-12-04T16:46:03.167798","indexId":"70272682","displayToPublicDate":"2025-04-05T10:43:22","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":18010,"text":"JGR Machine Learning and Computation","active":true,"publicationSubtype":{"id":10}},"title":"Uncertainty quantification of geophysical and hydrologic parameters estimated from borehole nuclear magnetic resonance data","docAbstract":"<p><span>Borehole nuclear magnetic resonance (bNMR) data are typically used to infer in situ hydrologic properties. Partial water content as a function of pore size is estimated by fitting the measured NMR response to a multi-exponential&nbsp;</span><i>T</i><sub>2</sub><span>&nbsp;distribution, and the sum of estimated&nbsp;</span><i>T</i><sub>2</sub><span>&nbsp;amplitudes equals the total volumetric water content. From these estimated parameters, several empirical relationships are commonly used to infer hydraulic conductivity from the NMR-estimated water content and&nbsp;</span><i>T</i><sub>2</sub><span>&nbsp;distribution. Often, parameters are estimated through deterministic inversion methods that produce a single best-fit estimate, but do not reflect uncertainties in model parameters. Here, a Bayesian Markov chain Monte Carlo (McMC) approach for analyzing bNMR data is developed that allows for comprehensive uncertainty quantification of NMR parameters and derived hydrologic properties. The underlying model that describes the&nbsp;</span><i>T</i><sub>2</sub><span>&nbsp;distribution is defined by a set of spline interpolation points. The number of interpolation points is allowed to vary in a trans-dimensional algorithm that naturally favors simple models with fewer interpolation points, allowing the data to inform the necessary level of model complexity. Additionally, data error is estimated as an unknown parameter. Analysis of the ensemble of models output from the McMC algorithm provides useful details on the range of plausible&nbsp;</span><i>T</i><sub>2</sub><span>&nbsp;distributions that can fit a measured bNMR decay curve, as well as uncertainty estimates of total water content. The ensemble of NMR parameters can also be propagated through commonly used relationships to produce uncertainty estimates on derived parameters such as bound/capillary/mobile water content or hydraulic conductivity.</span></p>","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2024JH000461","usgsCitation":"Minsley, B.J., Phillips, S.N., and James, S.R., 2025, Uncertainty quantification of geophysical and hydrologic parameters estimated from borehole nuclear magnetic resonance data: JGR Machine Learning and Computation, v. 2, no. 2, e2024JH000461, 15 p., https://doi.org/10.1029/2024JH000461.","productDescription":"e2024JH000461, 15 p.","ipdsId":"IP-171454","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":497115,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2024jh000461","text":"Publisher Index Page"},{"id":497066,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"2","issue":"2","noUsgsAuthors":false,"publicationDate":"2025-04-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Minsley, Burke J. 0000-0003-1689-1306","orcid":"https://orcid.org/0000-0003-1689-1306","contributorId":248573,"corporation":false,"usgs":true,"family":"Minsley","given":"Burke","email":"","middleInitial":"J.","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":951326,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Phillips, Stephanie N. 0000-0002-2022-7726","orcid":"https://orcid.org/0000-0002-2022-7726","contributorId":214857,"corporation":false,"usgs":true,"family":"Phillips","given":"Stephanie","email":"","middleInitial":"N.","affiliations":[{"id":493,"text":"Office of Ground Water","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":951327,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"James, Stephanie R. 0000-0001-5715-253X","orcid":"https://orcid.org/0000-0001-5715-253X","contributorId":260620,"corporation":false,"usgs":true,"family":"James","given":"Stephanie","email":"","middleInitial":"R.","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":951328,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70265808,"text":"70265808 - 2025 - Salinas Valley integrated hydrologic and reservoir operations models, Monterey and San Luis Obispo Counties, California","interactions":[{"subject":{"id":70265808,"text":"70265808 - 2025 - Salinas Valley integrated hydrologic and reservoir operations models, Monterey and San Luis Obispo Counties, California","indexId":"70265808","publicationYear":"2025","noYear":false,"title":"Salinas Valley integrated hydrologic and reservoir operations models, Monterey and San Luis Obispo Counties, California"},"predicate":"SUPERSEDED_BY","object":{"id":70275668,"text":"sir20265005 - 2026 - Salinas Valley integrated hydrologic and reservoir operations models, Monterey and San Luis Obispo Counties, California","indexId":"sir20265005","publicationYear":"2026","noYear":false,"title":"Salinas Valley integrated hydrologic and reservoir operations models, Monterey and San Luis Obispo Counties, California"},"id":1}],"supersededBy":{"id":70275668,"text":"sir20265005 - 2026 - Salinas Valley integrated hydrologic and reservoir operations models, Monterey and San Luis Obispo Counties, California","indexId":"sir20265005","publicationYear":"2026","noYear":false,"title":"Salinas Valley integrated hydrologic and reservoir operations models, Monterey and San Luis Obispo Counties, California"},"lastModifiedDate":"2026-05-12T17:47:05.295379","indexId":"70265808","displayToPublicDate":"2025-04-05T09:01:07","publicationYear":"2025","noYear":false,"publicationType":{"id":27,"text":"Preprint"},"publicationSubtype":{"id":32,"text":"Preprint"},"seriesTitle":{"id":18346,"text":"EarthArXiv","active":true,"publicationSubtype":{"id":32}},"title":"Salinas Valley integrated hydrologic and reservoir operations models, Monterey and San Luis Obispo Counties, California","docAbstract":"<p><span>The area surrounding the Salinas Valley groundwater basin in Monterey and San Luis Obispo Counties of California is a highly productive agricultural area, contributes significantly to the local economy, and provides a substantial portion of vegetables and other agricultural commodities to the Nation. This region of California provides about half of the Nation’s lettuce, celery, broccoli, and spinach each year. Thus, this agricultural area provides significant volumes of agricultural products not just for California but the entire United States. Changes in population and increased agricultural development, which includes a shift toward more water-intensive crops, and climate variability, have put increasing demand on both surface water and groundwater resources in the valley. This has resulted in water management challenges in the Salinas Valley that are predominantly related to distribution of water supply throughout the basin. Where and when the water is present in the surface and subsurface does not coincide with where and when the water is needed. To deal with the distribution issue, historically water has been used conjunctively in the valley. Conjunctive use is a water management strategy that coordinates surface water and groundwater use to maximize water availability. Groundwater is used throughout the Salinas Valley to meet water demands when surface water supplies are insufficient. Availability of surface water is constrained by climate. Precipitation and streamflow vary seasonally and year to year. Although there are two reservoirs in the Salinas Valley to capture and store water during wet periods, the only conveyance of reservoir water to coastal agricultural areas is the Salinas River. Increasing demand on groundwater and surface water resources throughout the Salinas Valley has resulted in undesirable effects of unsustainable water use, such as surface water depletion, groundwater level declines, storage depletion in the principal aquifers, and seawater intrusion. To address these escalating issues, local communities, water management agencies, and groundwater sustainability agencies are evaluating how to sustainably manage both their surface water and groundwater resources. To meet water demands and reduce undesirable effects of unsustainable water use, continued conjunctive management of surface water and groundwater would ideally incorporate strategies to deal with increases in demand and a variable climate. To evaluate the challenging water management issues in the Salinas Valley, the U.S. Geological Survey, Monterey County Water Resource Agency, and the Salinas Valley Basin Groundwater Sustainability Agency developed a comprehensive suite of models that represent the Salinas Valley Hydrogeologic system called the Salinas Valley System Model. The Salinas Valley Geologic Framework was developed to characterize the subsurface using various topographic and geologic data sources, including information on hydrogeologic units, their surfaces and extents, geologic structures, lithology, and elevations from borehole data and cross sections, as well as details on faults and existing models. The Salinas Valley Watershed Model simulates the entire Salinas River watershed. Monthly surface water inflows into the integrated hydrologic model domain were simulated using the Salinas Valley Watershed Model. The historical model uses historical climate data, water and land use data, and reservoir releases to simulate agricultural operations, including landscape water demands, diversions, and reclaimed wastewater. The operational model adds an embedded reservoir operations framework to the simulation of the historical model that allows specified operational rules to simulate reservoir releases and changes in reservoir storage. The operational model assumes current reservoir operations and constant land use, which differs from historical conditions. Thus, the operational model is a hypothetical baseline model that can be used by local water managers to evaluate and quantify potential benefits of water supply projects. Together, the geologic framework, watershed, historical, and operational models form a tool that can be used to simulate irrigated agriculture and associated reservoir operations of the integrated hydrologic system of the Salinas Valley.</span></p>","language":"English","publisher":"Eartharxiv","doi":"10.31223/X5ZD9N","usgsCitation":"Henson, W.R., Hanson, R., Boyce, S., Hevesi, J., and Jachens, E.R., 2025, Salinas Valley integrated hydrologic and reservoir operations models, Monterey and San Luis Obispo Counties, California: EarthArXiv, https://doi.org/10.31223/X5ZD9N.","productDescription":"312 p.","ipdsId":"IP-172765","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":488263,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.31223/x5zd9n","text":"Publisher Index Page"},{"id":484636,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Henson, Wesley R. 0000-0003-4962-5565 whenson@usgs.gov","orcid":"https://orcid.org/0000-0003-4962-5565","contributorId":384,"corporation":false,"usgs":true,"family":"Henson","given":"Wesley","email":"whenson@usgs.gov","middleInitial":"R.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":933598,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hanson, Randy 0000-0002-9819-7141","orcid":"https://orcid.org/0000-0002-9819-7141","contributorId":216356,"corporation":false,"usgs":false,"family":"Hanson","given":"Randy","affiliations":[{"id":37374,"text":"Retired USGS","active":true,"usgs":false}],"preferred":false,"id":933667,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Boyce, Scott 0000-0003-0626-9492 seboyce@usgs.gov","orcid":"https://orcid.org/0000-0003-0626-9492","contributorId":4766,"corporation":false,"usgs":true,"family":"Boyce","given":"Scott","email":"seboyce@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":933668,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hevesi, Joseph 0000-0003-2898-1800 jhevesi@usgs.gov","orcid":"https://orcid.org/0000-0003-2898-1800","contributorId":1507,"corporation":false,"usgs":true,"family":"Hevesi","given":"Joseph","email":"jhevesi@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":933669,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jachens, Elizabeth R. 0000-0001-5885-8892","orcid":"https://orcid.org/0000-0001-5885-8892","contributorId":294690,"corporation":false,"usgs":true,"family":"Jachens","given":"Elizabeth","middleInitial":"R.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":933670,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70267524,"text":"70267524 - 2025 - Streamflow response to glacier mass loss varies with basin precipitation across Alaska","interactions":[],"lastModifiedDate":"2025-05-28T14:28:22.882379","indexId":"70267524","displayToPublicDate":"2025-04-04T09:24:54","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Streamflow response to glacier mass loss varies with basin precipitation across Alaska","docAbstract":"<p><span>Diminishing glaciers affect streamflow, and given the extent of glaciers in Alaska and adjacent Canada, continued glacier mass loss is likely to have profound effects on ecosystems sensitive to runoff. The effects of glacier mass loss on streamflow are likely to vary across the wide ranges of basin size, glacier cover, and precipitation in this region. In this study, we use U.S. Geological Survey (USGS) streamflow data with satellite-based glacier volume change estimates to quantify how glacier mass loss subsidized streamflow over the 2000–2019 period for 116 glacierized basins. We examine interannual variability in that subsidy at three USGS-monitored glaciers to explore the ability of the subsidy to buffer streamflow derived solely from precipitation. We found the relative importance of percent glacier cover on streamflow magnitude increases in drier basins. In the driest basins, glaciers produced 40 times greater percent glacier mass loss subsidies to streamflow for the percent glacier cover compared to the wettest basins. While the subsidy from glacier mass loss buffers interannual variability in streamflow to varying degrees, it can also increase streamflow variability. Smaller amounts of percent glacier cover are needed to produce summer-melt-dominated seasonal flow regimes in drier basins than in wetter basins. Decreasing glacier cover will eventually decrease summer streamflow, increasing spring streamflow in drier basins, and attenuating seasonality with increasing spring and autumnal streamflow in wetter basins. Quantifying the downstream effects of continued glacier mass loss without the computational expense of a hydrological model is broadly applicable in this changing climate.</span></p>","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2024WR037859","usgsCitation":"Curran, J.H., Rick, B., Littell, J., and Sass, L., 2025, Streamflow response to glacier mass loss varies with basin precipitation across Alaska: Water Resources Research, v. 61, no. 4, e2024WR037859, 18 p., https://doi.org/10.1029/2024WR037859.","productDescription":"e2024WR037859, 18 p.","ipdsId":"IP-165191","costCenters":[{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true}],"links":[{"id":490156,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2024wr037859","text":"Publisher Index Page"},{"id":486640,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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,{"id":70267440,"text":"70267440 - 2025 - Optimizing control of a freshwater invader in time and space","interactions":[],"lastModifiedDate":"2025-05-23T15:49:02.287668","indexId":"70267440","displayToPublicDate":"2025-04-04T08:37:29","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1450,"text":"Ecological Applications","active":true,"publicationSubtype":{"id":10}},"title":"Optimizing control of a freshwater invader in time and space","docAbstract":"The global spread of invasive species in aquatic ecosystems has prompted population control efforts to mitigate negative impacts on native species and ecosystem functions. Removal programs that optimally allocate removal effort across space and time offer promise for improving invader suppression or eradication, especially given the limited resources available to these programs. However, science-based guidance to inform such programs remains limited. This study leverages two intensive fish removal programs for nonnative green sunfish (Lepomis cyanellus) in intermittent streams of the Bill Williams River basin in Arizona, USA, to explore alternative management strategies involving variable allocation of removal effort in time and space and compare static versus dynamic decision rules. We used Bayesian hierarchical modeling to estimate demographic parameters using existing removal data, with evidence that both removal programs led to at least a 0.39 probability of eradication. Simulated alternative management strategies revealed that population suppression, but not eradication, could be achieved with reduced effort, and that dynamic management practices that respond to species abundance in real time can improve the efficiency of removal efforts. High removal frequency and program duration, including continued monitoring after zero fish were captured, contributed to successful population control. With management efforts struggling to keep pace with the rising spread and impacts of invasive species, this research demonstrates the utility of quantitative removal models to help improve invasive removal programs and robustly evaluate the success of population suppression and eradication.","language":"English","publisher":"Ecological Society of America","doi":"10.1002/eap.70026","usgsCitation":"Diallo, J., Converse, S.J., Chmiel, M., Stites, A., and Olden, J., 2025, Optimizing control of a freshwater invader in time and space: Ecological Applications, v. 35, no. 3, e70026, 17 p., https://doi.org/10.1002/eap.70026.","productDescription":"e70026, 17 p.","ipdsId":"IP-151980","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":487965,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/eap.70026","text":"Publisher Index Page"},{"id":486519,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"Bill Williams River basin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -113.87855871265536,\n              34.69978264689745\n            ],\n            [\n              -113.87855871265536,\n              34.0589425188774\n            ],\n            [\n              -113.23223159100554,\n              34.0589425188774\n            ],\n            [\n              -113.23223159100554,\n              34.69978264689745\n            ],\n            [\n              -113.87855871265536,\n              34.69978264689745\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"35","issue":"3","noUsgsAuthors":false,"publicationDate":"2025-05-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Diallo, Jessica O.","contributorId":355825,"corporation":false,"usgs":false,"family":"Diallo","given":"Jessica O.","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":938203,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Converse, Sarah J. 0000-0002-3719-5441 sconverse@usgs.gov","orcid":"https://orcid.org/0000-0002-3719-5441","contributorId":173772,"corporation":false,"usgs":true,"family":"Converse","given":"Sarah","email":"sconverse@usgs.gov","middleInitial":"J.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":938204,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Chmiel, Matthew","contributorId":355827,"corporation":false,"usgs":false,"family":"Chmiel","given":"Matthew","affiliations":[{"id":12922,"text":"Arizona Game and Fish Department","active":true,"usgs":false}],"preferred":false,"id":938205,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stites, Andy","contributorId":355829,"corporation":false,"usgs":false,"family":"Stites","given":"Andy","affiliations":[{"id":12922,"text":"Arizona Game and Fish Department","active":true,"usgs":false}],"preferred":false,"id":938206,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Olden, Julian D.","contributorId":338326,"corporation":false,"usgs":false,"family":"Olden","given":"Julian D.","affiliations":[],"preferred":false,"id":938207,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70268269,"text":"70268269 - 2025 - Sprague’s Pipits (Anthus spragueii) occupying high-elevation intermontane valley habitat throughout the breeding season in southwest Montana","interactions":[],"lastModifiedDate":"2025-06-18T15:23:10.932977","indexId":"70268269","displayToPublicDate":"2025-04-04T08:16:12","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3746,"text":"Western North American Naturalist","onlineIssn":"1944-8341","printIssn":"1527-0904","active":true,"publicationSubtype":{"id":10}},"title":"Sprague’s Pipits (Anthus spragueii) occupying high-elevation intermontane valley habitat throughout the breeding season in southwest Montana","docAbstract":"<p><span>Sprague's Pipit (</span><i>Anthus spragueii</i><span>) is an imperiled bird species that breeds in grasslands of the northern Great Plains of North America. While conducting avian surveys in the Centennial Valley, Beaverhead County, southwest Montana, during spring and summer 2023, we detected approximately 10 male Sprague's Pipits performing aerial displays. These represent the first detailed observations of Sprague's Pipits in Beaverhead County, Montana, and the first confirmed observations of territorial displays therein. Subsequent detections included multiple adults, one of which was seen flying with food in its bill. We hypothesize that these observations represent a small but previously undescribed breeding population occurring above 2000 m elevation, which is higher than elevations at which this species is generally thought to breed. Our discovery also expands the known breeding habitat of this species to include intermontane valley bottoms, raising questions of whether the historical range included this habitat prior to its large-scale modifications across western North America and contemporary global change. These additions to our understanding of Sprague's Pipit ecology may be important for both land managers in the region and conservation efforts for this species. The evidence described here, of a breeding population of Sprague's Pipits in the Centennial Valley, Montana, may warrant further investigations in intermontane valleys throughout the region to better understand the breeding extent and the management actions needed to conserve this species and its habitat.</span></p><p><br></p>","language":"English","publisher":"BioOne","doi":"10.3398/064.085.0107","usgsCitation":"Staufer, A., Maggs, E., Beever, E.A., and Mitchell, A., 2025, Sprague’s Pipits (Anthus spragueii) occupying high-elevation intermontane valley habitat throughout the breeding season in southwest Montana: Western North American Naturalist, v. 85, no. 1, p. 80-86, https://doi.org/10.3398/064.085.0107.","productDescription":"7 p.","startPage":"80","endPage":"86","ipdsId":"IP-165664","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":490918,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Montana","otherGeospatial":"southwest Montana","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -110.58135992462717,\n              47.43630025014619\n            ],\n            [\n              -110.58135992462717,\n              44.94886000398478\n            ],\n            [\n              -104.04233087797031,\n              44.94886000398478\n            ],\n            [\n              -104.04233087797031,\n              47.43630025014619\n            ],\n            [\n              -110.58135992462717,\n              47.43630025014619\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"85","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Staufer, Andrew C.","contributorId":357061,"corporation":false,"usgs":false,"family":"Staufer","given":"Andrew C.","affiliations":[{"id":85318,"text":"Department of Animal and Range Sciences, Montana State University","active":true,"usgs":false}],"preferred":false,"id":940652,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Maggs, Emilie K.","contributorId":357062,"corporation":false,"usgs":false,"family":"Maggs","given":"Emilie K.","affiliations":[{"id":85318,"text":"Department of Animal and Range Sciences, Montana State University","active":true,"usgs":false}],"preferred":false,"id":940653,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Beever, Erik A. 0000-0002-9369-486X ebeever@usgs.gov","orcid":"https://orcid.org/0000-0002-9369-486X","contributorId":2934,"corporation":false,"usgs":true,"family":"Beever","given":"Erik","email":"ebeever@usgs.gov","middleInitial":"A.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":940654,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mitchell, Adam E.","contributorId":338879,"corporation":false,"usgs":false,"family":"Mitchell","given":"Adam E.","affiliations":[{"id":48645,"text":"umt","active":true,"usgs":false}],"preferred":false,"id":940655,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70269958,"text":"70269958 - 2025 - Living with uncertainty: Using multi-model large ensembles to assess emperor penguin extinction risk for the IUCN Red List","interactions":[],"lastModifiedDate":"2025-08-07T15:36:23.659888","indexId":"70269958","displayToPublicDate":"2025-04-03T10:30:27","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":"Living with uncertainty: Using multi-model large ensembles to assess emperor penguin extinction risk for the IUCN Red List","docAbstract":"<p><span>Improved methods for identifying species at risk are needed to strengthen climate change vulnerability assessments, as current estimates indicate that up to one million species face extinction due to environmental changes. Integrating multiple sources of uncertainty enhances the robustness of Red List of Threatened Species assessments, providing a more comprehensive understanding of species’ risks. We present a comprehensive framework that incorporates uncertainties, including measurement error, structural uncertainty, natural variability, future climate emissions scenario, and extreme events of sea ice loss, to evaluate the extinction risk of the emperor penguin (</span><i>Aptenodytes forsteri</i><span>), currently classified as Near-Threatened. We apply three ecological models, one bioclimatic and two metapopulation models, combined with a multi-model large ensemble (MMLE) of climate projections from general circulation models, to conduct a Red List evaluation at both global, regional and colony levels. Our results show that emperor penguins could be classified under a range of Red List categories depending on the ecological model, Intergovernmental Panel on Climate Change (IPCC) climate emissions scenario, and extreme event frequency. Under Criterion A, global classifications vary from Vulnerable to Critically Endangered. Severe declines are projected in the Indian and East Pacific sectors, Dronning Maud Land and the Amundsen-Bellingshausen Sea, with Criterion E indicating that 24% to 100% of colonies meet&nbsp;</span><i>Endangered</i><span>&nbsp;status thresholds, depending on huddling thresholds and ecological models. This study represents the first application of an MMLE coupled with an ecological ensemble approach to project climate change impacts on a species, capturing a comprehensive range of uncertainties and offering a framework for improving forecasting and decision-making under climate change.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.biocon.2025.111037","usgsCitation":"Jenouvrier, S., Eparvier, A., Sen, B., Ventura, F., Che-Castaldo, C., Holland, M., Landrum, L., Krumhardt, K., Garnier, J., Delord, K., Barbraud, C., and Trathan, P., 2025, Living with uncertainty: Using multi-model large ensembles to assess emperor penguin extinction risk for the IUCN Red List: Biological Conservation, v. 305, 111037, 14 p., https://doi.org/10.1016/j.biocon.2025.111037.","productDescription":"111037, 14 p.","ipdsId":"IP-174001","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":493799,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.biocon.2025.111037","text":"Publisher Index Page"},{"id":493717,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"305","noUsgsAuthors":false,"publicationDate":"2025-04-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Jenouvrier, Stephanie","contributorId":359201,"corporation":false,"usgs":false,"family":"Jenouvrier","given":"Stephanie","affiliations":[{"id":36711,"text":"Woods Hole Oceanographic Institution","active":true,"usgs":false}],"preferred":false,"id":945042,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Eparvier, Alice","contributorId":359202,"corporation":false,"usgs":false,"family":"Eparvier","given":"Alice","affiliations":[{"id":85760,"text":"Universit´e Claude Bernard Lyon","active":true,"usgs":false}],"preferred":false,"id":945043,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sen, Bilgecan","contributorId":359203,"corporation":false,"usgs":false,"family":"Sen","given":"Bilgecan","affiliations":[{"id":36711,"text":"Woods Hole Oceanographic Institution","active":true,"usgs":false}],"preferred":false,"id":945044,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ventura, Francesco","contributorId":359204,"corporation":false,"usgs":false,"family":"Ventura","given":"Francesco","affiliations":[{"id":36711,"text":"Woods Hole Oceanographic Institution","active":true,"usgs":false}],"preferred":false,"id":945046,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Che-Castaldo, Christian Joseph 0000-0002-7670-2178","orcid":"https://orcid.org/0000-0002-7670-2178","contributorId":347906,"corporation":false,"usgs":true,"family":"Che-Castaldo","given":"Christian Joseph","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":945045,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Holland, Marika","contributorId":359205,"corporation":false,"usgs":false,"family":"Holland","given":"Marika","affiliations":[{"id":85742,"text":"NSF National Center for Atmospheric Research","active":true,"usgs":false}],"preferred":false,"id":945047,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Landrum, Laura","contributorId":359206,"corporation":false,"usgs":false,"family":"Landrum","given":"Laura","affiliations":[{"id":85742,"text":"NSF National Center for Atmospheric Research","active":true,"usgs":false}],"preferred":false,"id":945048,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Krumhardt, Kristen","contributorId":359207,"corporation":false,"usgs":false,"family":"Krumhardt","given":"Kristen","affiliations":[{"id":85742,"text":"NSF National Center for Atmospheric Research","active":true,"usgs":false}],"preferred":false,"id":945049,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Garnier, Jimmy","contributorId":359210,"corporation":false,"usgs":false,"family":"Garnier","given":"Jimmy","affiliations":[{"id":85761,"text":"CNRS-Universit´e Grenoble Alpes","active":true,"usgs":false}],"preferred":false,"id":945050,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Delord, Karine","contributorId":359211,"corporation":false,"usgs":false,"family":"Delord","given":"Karine","affiliations":[{"id":85764,"text":"Centre d’´Etudes Biologiques de Chiz´e","active":true,"usgs":false}],"preferred":false,"id":945051,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Barbraud, Christophe","contributorId":359212,"corporation":false,"usgs":false,"family":"Barbraud","given":"Christophe","affiliations":[{"id":85764,"text":"Centre d’´Etudes Biologiques de Chiz´e","active":true,"usgs":false}],"preferred":false,"id":945052,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Trathan, Philip","contributorId":359213,"corporation":false,"usgs":false,"family":"Trathan","given":"Philip","affiliations":[{"id":37955,"text":"University of Southampton","active":true,"usgs":false}],"preferred":false,"id":945053,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}}
,{"id":70265463,"text":"70265463 - 2025 - Assessing the effect of coral reef restoration location on coastal flood hazard along the San Juan Coastline, Puerto Rico","interactions":[],"lastModifiedDate":"2025-04-07T15:00:09.063332","indexId":"70265463","displayToPublicDate":"2025-04-03T09:53:57","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3912,"text":"Frontiers in Marine Science","onlineIssn":"2296-7745","active":true,"publicationSubtype":{"id":10}},"title":"Assessing the effect of coral reef restoration location on coastal flood hazard along the San Juan Coastline, Puerto Rico","docAbstract":"<p><span>Coastal resilience has become a pressing global issue due to the growing vulnerability of coastlines to the effects of climate change. Nature-based solutions have emerged as a promising approach to coastal protection to not only enhance coastal resilience, but also restore critical ecosystems. Coral reef restoration has the potential to provide ecosystem services benefits; however, there are still key uncertainties in linking restoration design to reductions in coastal flood hazard under current and future climate conditions. In this study, we applied one-dimensional and two-dimensional numerical coastal engineering models, calibrated and validated using field data, to evaluate the effectiveness of coral restoration scenarios on coastal waves, water levels, and flooding along the coast of San Juan, Puerto Rico, U.S.A. Model results indicate a small reduction in maximum water levels under the proposed restoration scenarios. This underscores the importance of these endeavors, not only for ecological preservation but also for preventing further reef deterioration. Such preservation is essential for mitigating the increased coastal risks anticipated in the future. Results from this study provide information to guide policymakers and coastal managers in making informed decisions on viable restoration project design options. By systematically evaluating how restoration location impacts coastal flood hazards, communities can develop and implement proactive strategies to mitigate flood-related risk. In addition, by restoring coral reefs, communities can contribute to environmental preservation while ensuring sustainable development and protection of coastal environments.</span></p>","language":"English","publisher":"Frontiers Media","doi":"10.3389/fmars.2025.1528460","usgsCitation":"Familkhalili, R., Storlazzi, C.D., Nemeth, M., and Viehman, S., 2025, Assessing the effect of coral reef restoration location on coastal flood hazard along the San Juan Coastline, Puerto Rico: Frontiers in Marine Science, v. 12, 1528460, 11 p., https://doi.org/10.3389/fmars.2025.1528460.","productDescription":"1528460, 11 p.","ipdsId":"IP-169548","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":488566,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fmars.2025.1528460","text":"Publisher Index Page"},{"id":484246,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Puerto Rico, San Juan coastline","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -66.08782395132914,\n              18.480815260981046\n            ],\n            [\n              -66.09096383189711,\n              18.45217867401871\n            ],\n            [\n              -65.96850848974445,\n              18.42720367145678\n            ],\n            [\n              -65.96005496513799,\n              18.468673931779904\n            ],\n            [\n              -66.08782395132914,\n              18.480815260981046\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"12","noUsgsAuthors":false,"publicationDate":"2025-04-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Familkhalili, Ramin","contributorId":353052,"corporation":false,"usgs":false,"family":"Familkhalili","given":"Ramin","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":932770,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Storlazzi, Curt D. 0000-0001-8057-4490","orcid":"https://orcid.org/0000-0001-8057-4490","contributorId":213610,"corporation":false,"usgs":true,"family":"Storlazzi","given":"Curt","middleInitial":"D.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":932772,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nemeth, Michael","contributorId":353056,"corporation":false,"usgs":false,"family":"Nemeth","given":"Michael","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":932773,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Viehman, Shay","contributorId":353053,"corporation":false,"usgs":false,"family":"Viehman","given":"Shay","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":932771,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70275050,"text":"70275050 - 2025 - Seismic intensities, ground motions and basin amplification from the 2022 Mw 6.4 Ferndale, California intraslab earthquake","interactions":[],"lastModifiedDate":"2026-04-13T14:42:19.508974","indexId":"70275050","displayToPublicDate":"2025-04-03T09:23:45","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3372,"text":"Seismological Research Letters","onlineIssn":"1938-2057","printIssn":"0895-0695","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Seismic intensities, ground motions and basin amplification from the 2022 M<sub>w</sub> 6.4 Ferndale, California intraslab earthquake","title":"Seismic intensities, ground motions and basin amplification from the 2022 Mw 6.4 Ferndale, California intraslab earthquake","docAbstract":"<p>On December 20, 2022, a Mw 6.4 earthquake occurred at a depth of 18 km within the subducting Gorda plate in the Mendocino Triple Junction (MTJ), one of the most seismically active regions of the contiguous United States, causing widespread damage to local communities. Here we document the seismic intensities, ground motions, and basin amplification effects recorded by this earthquake across Humboldt County as part of an ongoing scientific effort to understand subduction zone earthquake hazards. Modified Mercalli Intensity (MMI) values from our post-earthquake field survey report shaking intensities as high as VIII (Severe). Strong ground motion data from 54 seismic stations were processed to calculate amplitude and frequency content parameters across Northern California. The maximum calculated geometric mean PGA and PGV are 1053 cm/s<sup>2 </sup>and 52 cm/s (respectively), both recorded within the 3 km deep Eel River sedimentary basin. Comparisons with four published Ground Motion Prediction Equations indicate that PGA and PGV measurements align with expected attenuation-distance patterns for intraslab earthquakes of this nature. Within the Eel River Basin, ground motions for frequencies above 1 Hz are amplified, with respect to reference stations, by factors greater than 2. Our findings suggest that peak ground motions were mainly caused by sedimentary basin site-effects within the Eel River basin, although rupture directivity may have also increased ground motion amplitudes locally. While the Ferndale area is primarily impacted by shallow intraslab earthquakes, our results also raise questions about site-response and basin amplification hazards from a potential megathrust earthquake. The high seismicity rates of the southernmost Cascades call for stronger regional preparedness and improved strategies to mitigate the effects of such a large-scale disaster.</p>","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0220240338","usgsCitation":"Namazie, L., Medley, R., and Mooney, W.D., 2025, Seismic intensities, ground motions and basin amplification from the 2022 Mw 6.4 Ferndale, California intraslab earthquake: Seismological Research Letters, v. 96, no. 5, p. 2796-2811, https://doi.org/10.1785/0220240338.","productDescription":"16 p.","startPage":"2796","endPage":"2811","ipdsId":"IP-169390","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":502741,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","city":"Ferndale","otherGeospatial":"Eel River","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -123.25,\n              41\n            ],\n            [\n              -124.5,\n              41\n            ],\n            [\n              -124.5,\n              39.5\n            ],\n            [\n              -123.25,\n              39.5\n            ],\n            [\n              -123.25,\n              41\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"96","issue":"5","noUsgsAuthors":false,"publicationDate":"2025-04-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Namazie, Leyla Mariam 0009-0000-8378-8443","orcid":"https://orcid.org/0009-0000-8378-8443","contributorId":350275,"corporation":false,"usgs":true,"family":"Namazie","given":"Leyla Mariam","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":959304,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Medley, Rebecca","contributorId":369884,"corporation":false,"usgs":false,"family":"Medley","given":"Rebecca","affiliations":[],"preferred":false,"id":959305,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mooney, Walter D. 0000-0002-5310-3631 mooney@usgs.gov","orcid":"https://orcid.org/0000-0002-5310-3631","contributorId":3194,"corporation":false,"usgs":true,"family":"Mooney","given":"Walter","email":"mooney@usgs.gov","middleInitial":"D.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":959306,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70265884,"text":"70265884 - 2025 - Pathways for potential exposure to onshore oil and gas wastewater: What we need to know to protect human health","interactions":[],"lastModifiedDate":"2025-04-18T14:52:58.475289","indexId":"70265884","displayToPublicDate":"2025-04-03T07:49:20","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1542,"text":"Environmental Health Perspectives","active":true,"publicationSubtype":{"id":10}},"title":"Pathways for potential exposure to onshore oil and gas wastewater: What we need to know to protect human health","docAbstract":"<p><span>Produced water is a chemically complex waste stream generated during oil and gas development. Roughly four trillion liters were generated onshore in the United States in 2021 (ALL Consulting, 2022,&nbsp;</span><a class=\"linkBehavior\" href=\"https://www.gwpc.org/wp-content/uploads/2021/09/2021_Produced_Water_Volumes.pdf\" data-mce-href=\"https://www.gwpc.org/wp-content/uploads/2021/09/2021_Produced_Water_Volumes.pdf\">https://www.gwpc.org/wp-content/uploads/2021/09/2021_Produced_Water_Volumes.pdf</a><span>). Efforts are underway to expand historic uses of produced water to offset freshwater needs in water-stressed regions, avoid induced seismic activity associated with its disposal, and extract commodities. Understanding the potential exposures from current and proposed produced water uses and management practices can help to inform health-protective practices. This review summarizes what is known about potential human exposure to produced water from onshore oil and gas development in the United States. We synthesize 236 publications to create a conceptual model of potential human exposure that illustrates the current state of scientific inquiry and knowledge. Exposure to produced water can occur following its release to the environment through spills or leaks during its handling and management. Exposure can also arise from authorized releases, including permitted discharges to surface water, crop irrigation, and road treatment. Knowledge gaps include understanding the variable composition and toxicity of produced water released to the environment, the performance of treatment methods, migration pathways through the environment that can result in human exposure, and the significance of the exposures for human and ecosystem health. Reducing these uncertainties may help in realizing the benefits of produced water use while simultaneously protecting human health.</span></p>","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2024GH001263","usgsCitation":"Ariana, A., Cozzarelli, I.M., Danforth, C., McDevitt, B., Rosofsky, A., and Vorhees, D., 2025, Pathways for potential exposure to onshore oil and gas wastewater: What we need to know to protect human health: Environmental Health Perspectives, v. 9, no. 4, e2024GH001263, 21 p., https://doi.org/10.1029/2024GH001263.","productDescription":"e2024GH001263, 21 p.","ipdsId":"IP-166041","costCenters":[{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"links":[{"id":490099,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2024gh001263","text":"Publisher Index 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States\"}}]}","volume":"9","issue":"4","noUsgsAuthors":false,"publicationDate":"2025-04-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Ariana, Ayusha","contributorId":353543,"corporation":false,"usgs":false,"family":"Ariana","given":"Ayusha","affiliations":[{"id":84430,"text":"Health Effects Institute Energy, Boston, MA, USA","active":true,"usgs":false}],"preferred":false,"id":933805,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cozzarelli, Isabelle M. 0000-0002-5123-1007 icozzare@usgs.gov","orcid":"https://orcid.org/0000-0002-5123-1007","contributorId":1693,"corporation":false,"usgs":true,"family":"Cozzarelli","given":"Isabelle","email":"icozzare@usgs.gov","middleInitial":"M.","affiliations":[{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":933806,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Danforth, Cloelle","contributorId":353544,"corporation":false,"usgs":false,"family":"Danforth","given":"Cloelle","affiliations":[{"id":84430,"text":"Health Effects Institute Energy, Boston, MA, USA","active":true,"usgs":false}],"preferred":false,"id":933807,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McDevitt, Bonnie 0000-0001-8390-0028","orcid":"https://orcid.org/0000-0001-8390-0028","contributorId":291246,"corporation":false,"usgs":true,"family":"McDevitt","given":"Bonnie","email":"","affiliations":[{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"preferred":true,"id":933808,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rosofsky, Anna","contributorId":353545,"corporation":false,"usgs":false,"family":"Rosofsky","given":"Anna","affiliations":[{"id":84430,"text":"Health Effects Institute Energy, Boston, MA, USA","active":true,"usgs":false}],"preferred":false,"id":933809,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Vorhees, Donna","contributorId":353546,"corporation":false,"usgs":false,"family":"Vorhees","given":"Donna","affiliations":[{"id":84430,"text":"Health Effects Institute Energy, Boston, MA, USA","active":true,"usgs":false}],"preferred":false,"id":933810,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70275339,"text":"70275339 - 2025 - Evaluating the potential of co-located non-petroleum energy resources in the Gulf Coast using play fairwayaAnalysis","interactions":[],"lastModifiedDate":"2026-04-29T15:58:56.308065","indexId":"70275339","displayToPublicDate":"2025-04-01T10:55:33","publicationYear":"2025","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Evaluating the potential of co-located non-petroleum energy resources in the Gulf Coast using play fairwayaAnalysis","docAbstract":"<p id=\"id1\" class=\"first\">Geological resources critical to the energy transition, such as sedimentary geothermal, carbon storage potential, and lithium in brines, commonly struggle for economic feasibility as stand-alone developments but can have greater viability when the potential for more than one of these resources exist within the same reservoir or stacked in different stratigraphic intervals. There may also be instances where development of one resource inhibits development of others and decisions need to be made on how to best prioritize the use of those resources in the subsurface.</p><p id=\"id2\">Subsurface data sets were analyzed and integrated to evaluate the distribution of non-petroleum energy and related resources in the onshore and nearshore U.S. Gulf Coast. Temperature, pressure, brine composition (lithium content), and reservoir quality data for thirty-four depositional units have been compiled and visualized to high-grade areas where multiple resource opportunities likely coexist. For sedimentary geothermal, possible resource areas are defined as low potential (&lt;90°C), moderate potential (90–150°C), and high potential (&gt;150°C). For CO<sub>2</sub><span>&nbsp;</span>storage, high potential areas exhibit supercritical CO<sub>2</sub><span>&nbsp;</span>conditions less than 80% of the fracture gradient. Areas with pore pressure between 80% and 100% of the fracture gradient are considered to exhibit moderate potential and areas where the fracture gradient is equal to or greater than 100% are assigned low potential. Lithium resources in brines were defined by lithium concentrations as low potential (&lt;100ppm), moderate potential (100-200ppm), or high potential (&gt;200ppm). Reservoir quality affects the viability of all three of these resources and is evaluated using depositional environment maps of each unit. The resulting play fairway maps can be used for regional scale screening evaluations of these resources and to identify areas of interest where more detailed, prospect-scale studies can be undertaken.</p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"GeoGulf transactions","largerWorkSubtype":{"id":12,"text":"Conference publication"},"language":"English","publisher":"Gulf Coast Association of Geological Societies","usgsCitation":"Gardner, R., and Birdwell, J.E., 2025, Evaluating the potential of co-located non-petroleum energy resources in the Gulf Coast using play fairwayaAnalysis, <i>in</i> GeoGulf transactions, v. 74, no. 1, p. 99-110.","productDescription":"12 p.","startPage":"99","endPage":"110","ipdsId":"IP-171254","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":503630,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":503629,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://archives.datapages.com/data/gcags/data/074/074001/html/99.html?q=%2ByearSort%3A%5B2024+TO+2025%5D"}],"country":"United States","otherGeospatial":"Gulf Coast","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -80.9008042267321,\n              25.272547003111754\n            ],\n            [\n              -83.13477684884714,\n              29.76501336278585\n            ],\n            [\n              -87.60632518879635,\n              30.79937929794508\n            ],\n            [\n              -90.3728575608113,\n              29.672236526999\n            ],\n            [\n              -93.57099541239927,\n              30.28053303331002\n            ],\n            [\n              -97.99176750244868,\n              28.08066568281116\n            ],\n            [\n              -97.33354320920074,\n              25.795361924735644\n            ],\n            [\n              -83.10033137844977,\n              24.075924287426176\n            ],\n            [\n              -81.03033197293898,\n              24.793722639293094\n            ],\n            [\n              -80.9008042267321,\n              25.272547003111754\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"74","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Gardner, Rand 0000-0001-8711-5334","orcid":"https://orcid.org/0000-0001-8711-5334","contributorId":316831,"corporation":false,"usgs":true,"family":"Gardner","given":"Rand","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":960622,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Birdwell, Justin E. 0000-0001-8263-1452 jbirdwell@usgs.gov","orcid":"https://orcid.org/0000-0001-8263-1452","contributorId":3302,"corporation":false,"usgs":true,"family":"Birdwell","given":"Justin","email":"jbirdwell@usgs.gov","middleInitial":"E.","affiliations":[{"id":569,"text":"Southwest Climate Science Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true},{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":960623,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70266184,"text":"70266184 - 2025 - Behavioral plasticity in detection height of an invasive, arboreal snake based on size, condition, and prey","interactions":[],"lastModifiedDate":"2025-04-29T14:18:46.307912","indexId":"70266184","displayToPublicDate":"2025-04-01T09:14:20","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3777,"text":"Wildlife Research","active":true,"publicationSubtype":{"id":10}},"title":"Behavioral plasticity in detection height of an invasive, arboreal snake based on size, condition, and prey","docAbstract":"<div class=\"section\"><strong>Context</strong><p id=\"d6e276\">Animals may adjust their behavior in predictable ways to balance tradeoffs between resource acquisition and survival or fecundity. Microhabitat selection based on individual traits or environmental conditions is one measure of risk–reward tradeoffs by individuals.</p></div><div class=\"section\"><strong>Aims</strong><p id=\"d6e281\">We used data from observational and manipulative studies to investigate whether an arboreal snake (brown treesnake,<span>&nbsp;</span><i>Boiga irregularis</i>) had context-dependent behavior based on the relationship between estimated prey availability, body condition, size, and detection height (microhabitat use) in two Mariana Islands.</p></div><div class=\"section\"><strong>Methods</strong><p id=\"d6e289\">We used observational data collected in four study sites and data from a manipulative study that we collected over a 5-year period. The observational data focused on four sites with different counts of three prey types, including lizards, birds, and small mammals. During the manipulative study we removed snakes, which resulted in increased prey counts over time. Using these two approaches, we tested whether prey counts predicted body condition and then evaluated how prey counts, snake size, and snake condition interactively predicted the detection height of captured individuals.</p></div><div class=\"section\"><strong>Key results</strong><p id=\"d6e294\">We found that body condition was greater at sites or in years with greater prey counts across both the observational and manipulative studies. We also found that snakes displayed differential microhabitat use based on both their condition and size. Larger snakes tended to be detected lower than smaller snakes, but only at sites or during years with few bird or small mammal counts. Snakes at sites with greater mammal and bird counts had a positive relationship between size and detection height. Snakes with greater condition scores tended to be detected higher irrespective of size, but this was also dependent on prey counts. At sites with low bird counts, snakes that were in better condition tended to be closer to the ground.</p></div><div class=\"section\"><strong>Conclusions</strong><p id=\"d6e299\">Brown treesnakes modified microhabitat use based on their condition, size, and the number or type of prey available. Our findings were consistent with a hypothesis that they optimized habitat use to secure food resources and maximize survival.</p></div><div class=\"section\"><strong>Implications</strong><p id=\"d6e304\">Context-dependent behavioral plasticity may be an important consideration for management of reptiles for population control or growth.</p></div>","language":"English","publisher":"CSIRO Publishing","doi":"10.1071/WR24085","usgsCitation":"Nafus, M.G., Gray, L., Klug, P.E., Rodda, G.H., and Goetz, S.M., 2025, Behavioral plasticity in detection height of an invasive, arboreal snake based on size, condition, and prey: Wildlife Research, v. 52, WR24085, 13 p., https://doi.org/10.1071/WR24085.","productDescription":"WR24085, 13 p.","ipdsId":"IP-148796","costCenters":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"links":[{"id":496370,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1071/wr24085","text":"Publisher Index Page"},{"id":485129,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Cocos Island, Guam","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              144.9880503743945,\n              13.69255187982374\n            ],\n            [\n              144.51411886644297,\n              13.69255187982374\n            ],\n            [\n              144.51411886644297,\n              13.15444039485007\n            ],\n            [\n              144.9880503743945,\n              13.15444039485007\n            ],\n            [\n              144.9880503743945,\n              13.69255187982374\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"52","noUsgsAuthors":false,"publicationDate":"2025-04-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Nafus, Melia G. 0000-0002-7325-3055 mnafus@usgs.gov","orcid":"https://orcid.org/0000-0002-7325-3055","contributorId":197462,"corporation":false,"usgs":true,"family":"Nafus","given":"Melia","email":"mnafus@usgs.gov","middleInitial":"G.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":934826,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gray, Levi","contributorId":351880,"corporation":false,"usgs":false,"family":"Gray","given":"Levi","affiliations":[{"id":51975,"text":"USGS Fort Collins Science Center (formerly)","active":true,"usgs":false}],"preferred":false,"id":934827,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Klug, Page E. pklug@usgs.gov","contributorId":5545,"corporation":false,"usgs":true,"family":"Klug","given":"Page","email":"pklug@usgs.gov","middleInitial":"E.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":934828,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rodda, Gordon H. 0000-0002-6696-7308 roddag@usgs.gov","orcid":"https://orcid.org/0000-0002-6696-7308","contributorId":210066,"corporation":false,"usgs":true,"family":"Rodda","given":"Gordon","email":"roddag@usgs.gov","middleInitial":"H.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":934829,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"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":934830,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70261844,"text":"70261844 - 2025 - Evaluating the applicability of the generalized power-law rating curve model: With applications to paired discharge-stage data from Iceland, Sweden, and the United States","interactions":[],"lastModifiedDate":"2024-12-30T15:09:17.858395","indexId":"70261844","displayToPublicDate":"2025-04-01T08:00:28","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2342,"text":"Journal of Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"Evaluating the applicability of the generalized power-law rating curve model: With applications to paired discharge-stage data from Iceland, Sweden, and the United States","docAbstract":"Hydrologic research and operations make extensive use of streamflow time series. In most applications, these time series are estimated from rating curves, which relate flow to some easy-to-measure surrogate, typically stage. The conventional stage-discharge rating takes the form of a segmented power law, with one segment for each hydrologic control at the stream gauge. However, these ratings are notoriously difficult to estimate with numerical methods, so that most are still developed manually. A few automated algorithms have emerged, but their use is sporadic, and their relative merits have not been rigorously assessed. One recently developed approach, the generalized power-law, avoids the segmenting problem by representing the power-law exponent as a Gaussian process. On the one hand, this representation is more flexible and easier to fit, but its flexibility might allow unrealistic solutions, so it needs to be tested under a range of conditions to assess its operational viability. This study evaluates the generalized power-law rating curve model by applying it to observations from 180 streams in Iceland, Sweden, and the United States. Overall, the model proved flexible and computationally robust, generating convincing rating curves across a range of geographic settings and was comparable to curves generated by a segmented rating model. Lastly, we propose a model-selection algorithm based on information theory to help identify the best rating curve model for a particular stream gauge.","language":"English","publisher":"Elsevier","doi":"10.1016/j.jhydrol.2024.132537","usgsCitation":"Vias, R., Hrafnkelsson, B., Hodson, T.O., Rögnvaldsson, S., Jansson, A., and Gardarsson, S., 2025, Evaluating the applicability of the generalized power-law rating curve model: With applications to paired discharge-stage data from Iceland, Sweden, and the United States: Journal of Hydrology, v. 651, 132537, 19 p., https://doi.org/10.1016/j.jhydrol.2024.132537.","productDescription":"132537, 19 p.","ipdsId":"IP-167791","costCenters":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":488042,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jhydrol.2024.132537","text":"Publisher Index Page"},{"id":465527,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Iceland, Sweden, United 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,{"id":70266002,"text":"70266002 - 2025 - Complex staged emplacement of a basaltic lava: The example of the July 1974 flow of Kīlauea","interactions":[],"lastModifiedDate":"2025-04-23T14:27:13.610544","indexId":"70266002","displayToPublicDate":"2025-03-31T09:21:18","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":"Complex staged emplacement of a basaltic lava: The example of the July 1974 flow of Kīlauea","docAbstract":"<p><span>Basaltic lava flows can be highly destructive. Forecasting the future path and/or behavior of an active lava flow is challenging because topography is often poorly constrained and lava has a complex rheology and emplacement history. Preserved lavas are an important source of information which, combined with observations of active flows, underpins conceptual models of lava flow emplacement. However, the value of preserved lavas is limited because pre-eruptive topography and, thus, syn-eruptive lava flow geometry are usually not known. Here, we use tree-mold data to constrain pre-eruptive topography and syn-eruptive lava flow geometry of the July 1974 flow of Kīlauea (USA). Tree molds, which are formed after advancing lava encloses standing trees, preserve the lava inundation height and the final preserved thickness of lava. We used data from 282 tree molds to reconstruct the temporal and spatial evolution of the ~ 2.1&nbsp;km-long July 1974 flow. The tree mold dataset yields a detailed dynamic picture of staged emplacement, separated by intervals of ponding. In some ponded areas, flow depth during emplacement (~ 5&nbsp;m) was twice the preserved thickness of the final lava (2–3&nbsp;m). Drainage of the ponds led to episodic surges in flow advancement, decoupled from fluctuations in vent discharge rate. We infer that the final breakout occurred after the cessation of fountaining. Such complex emplacement histories may be common for pāhoehoe lavas at Kīlauea and elsewhere in situations where the terrain is of variable slope, and/or where lava is temporarily perched and stored.</span></p>","language":"English","publisher":"Springer","doi":"10.1007/s00445-025-01817-0","usgsCitation":"Biass, S., Houghton, B.F., Llewellin, E.W., Curran, K., Thordarson, T., Orr, T., Parcheta, C., and Mouginis-Mark, P.J., 2025, Complex staged emplacement of a basaltic lava: The example of the July 1974 flow of Kīlauea: Bulletin of Volcanology, v. 87, 30, 14 p., https://doi.org/10.1007/s00445-025-01817-0.","productDescription":"30, 14 p.","ipdsId":"IP-106014","costCenters":[{"id":336,"text":"Hawaiian Volcano Observatory","active":false,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":488501,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s00445-025-01817-0","text":"Publisher Index Page"},{"id":484914,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"Kilaueau volcano","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -155.28799286883776,\n              19.435261686847895\n            ],\n            [\n              -155.28799286883776,\n              19.272560860056274\n            ],\n            [\n              -155.1179644435753,\n              19.272560860056274\n            ],\n            [\n              -155.1179644435753,\n              19.435261686847895\n            ],\n            [\n              -155.28799286883776,\n              19.435261686847895\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"87","noUsgsAuthors":false,"publicationDate":"2025-03-31","publicationStatus":"PW","contributors":{"authors":[{"text":"Biass, Sebastian","contributorId":353667,"corporation":false,"usgs":false,"family":"Biass","given":"Sebastian","affiliations":[{"id":84453,"text":"University of Geneva, Geneva, Switzerland","active":true,"usgs":false}],"preferred":false,"id":934281,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Houghton, Bruce F. 0000-0002-7532-9770","orcid":"https://orcid.org/0000-0002-7532-9770","contributorId":140077,"corporation":false,"usgs":false,"family":"Houghton","given":"Bruce","email":"","middleInitial":"F.","affiliations":[{"id":6977,"text":"University of Hawai`i at Hilo","active":true,"usgs":false},{"id":13351,"text":"University of Hawaii Cooperative Studies Unit","active":true,"usgs":false}],"preferred":false,"id":934282,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Llewellin, Edward W.","contributorId":353668,"corporation":false,"usgs":false,"family":"Llewellin","given":"Edward","middleInitial":"W.","affiliations":[{"id":25252,"text":"Durham University","active":true,"usgs":false}],"preferred":false,"id":934283,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Curran, Kristine C","contributorId":353669,"corporation":false,"usgs":false,"family":"Curran","given":"Kristine C","affiliations":[{"id":39036,"text":"University of Hawaii at Manoa","active":true,"usgs":false}],"preferred":false,"id":934284,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Thordarson, Thorvaldur","contributorId":197925,"corporation":false,"usgs":false,"family":"Thordarson","given":"Thorvaldur","email":"","affiliations":[{"id":35089,"text":"Institute of Earth Sciences, Nordvulk, University of Iceland","active":true,"usgs":false}],"preferred":false,"id":934285,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Orr, Tim R. 0000-0003-1157-7588","orcid":"https://orcid.org/0000-0003-1157-7588","contributorId":26365,"corporation":false,"usgs":true,"family":"Orr","given":"Tim R.","affiliations":[{"id":336,"text":"Hawaiian Volcano Observatory","active":false,"usgs":true}],"preferred":true,"id":934286,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Parcheta, Carolyn 0000-0001-6556-4630 cparcheta@usgs.gov","orcid":"https://orcid.org/0000-0001-6556-4630","contributorId":215617,"corporation":false,"usgs":true,"family":"Parcheta","given":"Carolyn","email":"cparcheta@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":934287,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Mouginis-Mark, Peter J. 0000-0002-7173-6141","orcid":"https://orcid.org/0000-0002-7173-6141","contributorId":36793,"corporation":false,"usgs":false,"family":"Mouginis-Mark","given":"Peter","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":934288,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70270325,"text":"70270325 - 2025 - The effects of breeding status on common raven movement, home range, and habitat selection","interactions":[],"lastModifiedDate":"2025-08-14T14:21:36.529864","indexId":"70270325","displayToPublicDate":"2025-03-31T09:18:29","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"The effects of breeding status on common raven movement, home range, and habitat selection","docAbstract":"<p><span>Anthropogenic infrastructure has contributed to increasing common raven (</span><i>Corvus corax</i><span>) abundance across the Great Basin region of the United States, particularly in sagebrush ecosystems, where high raven densities are correlated with reduced sage-grouse (</span><i>Centrocercus urophasianus</i><span>) nest survival. Our understanding of how raven reproductive behavior affects sage-grouse nest predation is limited, especially considering their overlapping breeding seasons. Understanding differences in space use and resource selection between breeding and non-breeding ravens could help identify high-use areas and corresponding predation risk for sage-grouse nests. We analyzed space use and resource selection of breeding (</span><i>n</i><span> = 13) and non-breeding (</span><i>n</i><span> = 32) global positioning system (GPS)-marked ravens in Nevada, USA (2017–2022) during the breeding season (1 March–31 June). We compared home-range size, core area size, step lengths, and resource selection within a Bayesian framework with inference made by comparing Bayesian credible intervals (CRI). We generated home range and core area estimates using autocorrelated kernel density methods. We did not find a difference in home range size between breeding (469.33 km</span><sup>2</sup><span>, 95% CRI = 228.79–709.45 km</span><sup>2</sup><span>) and non-breeding (525.26 km</span><sup>2</sup><span>, 95% CRI = 410.71–654.10 km</span><sup>2</sup><span>) ravens. However, breeding ravens had smaller core areas (10.77 km</span><sup>2</sup><span>, 95% CRI = 3.16–35.78 km</span><sup>2</sup><span>) and shorter step lengths (1,160.33 m/hr, 95% CRI = 1,087.78–1,277.17 m/hr) than non-breeding ravens (core area = 279.50 km</span><sup>2</sup><span>, 95% CRI = 206.77–363.72 km</span><sup>2</sup><span>; step length = 1,953.74 m/hr, 95% CRI = 1,898.42–2,009.56 m/hr). Ravens in both breeding classes selected high normalized difference vegetation index (NDVI) and low annual grass and shrub cover, but non-breeding ravens showed stronger selection for low annual grass and shrub cover areas. We found strong differences in selection between breeding classes for 6 of our 9 covariates: distance to road, solar radiation, distance to natural water, distance to forest edge, percent annual grass cover, and percent shrub cover. Non-breeding ravens concentrated activity near forest edges, natural water sources, and anthropogenic features, whereas breeding ravens focused activity close to their nests. Our findings suggest that raven management could be more effective if it targeted areas with high NDVI and low annual grass and shrub cover, especially in anthropogenically modified landscapes and near forest edges, and prevented raven nest establishment near prey populations of concern.</span></p>","language":"English","publisher":"The Wildlife Society","doi":"10.1002/jwmg.70004","usgsCitation":"Brockman, J.C., Coates, P., Tull, J.C., Jackson, P.J., O’Neil, S.T., and Williams, P.J., 2025, The effects of breeding status on common raven movement, home range, and habitat selection: Journal of Wildlife Management, v. 89, e70004, 20 p., https://doi.org/10.1002/jwmg.70004.","productDescription":"e70004, 20 p.","ipdsId":"IP-166811","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":498236,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/jwmg.70004","text":"Publisher Index Page"},{"id":494091,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nevada","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -119.99706101795434,\n              41.99257312862932\n            ],\n            [\n              -119.99706101795434,\n              38.66664669711224\n            ],\n            [\n              -114.0973231285738,\n              38.66664669711224\n            ],\n            [\n              -114.0973231285738,\n              41.99257312862932\n            ],\n            [\n              -119.99706101795434,\n              41.99257312862932\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"89","noUsgsAuthors":false,"publicationDate":"2025-03-31","publicationStatus":"PW","contributors":{"authors":[{"text":"Brockman, Julia C.","contributorId":359680,"corporation":false,"usgs":false,"family":"Brockman","given":"Julia","middleInitial":"C.","affiliations":[{"id":16686,"text":"University of Nevada, Reno","active":true,"usgs":false}],"preferred":false,"id":946036,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Coates, Peter S. 0000-0003-2672-9994","orcid":"https://orcid.org/0000-0003-2672-9994","contributorId":352181,"corporation":false,"usgs":true,"family":"Coates","given":"Peter S.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":946037,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tull, John C.","contributorId":359682,"corporation":false,"usgs":false,"family":"Tull","given":"John","middleInitial":"C.","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":946038,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jackson, Pat J.","contributorId":359685,"corporation":false,"usgs":false,"family":"Jackson","given":"Pat","middleInitial":"J.","affiliations":[{"id":85566,"text":"NDOW","active":true,"usgs":false}],"preferred":false,"id":946039,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"O’Neil, Shawn T. 0000-0002-0899-5220","orcid":"https://orcid.org/0000-0002-0899-5220","contributorId":206589,"corporation":false,"usgs":true,"family":"O’Neil","given":"Shawn","email":"","middleInitial":"T.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":946040,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Williams, Perry J.","contributorId":359688,"corporation":false,"usgs":false,"family":"Williams","given":"Perry","middleInitial":"J.","affiliations":[{"id":16686,"text":"University of Nevada, Reno","active":true,"usgs":false}],"preferred":false,"id":946041,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70267980,"text":"70267980 - 2025 - Topographic controls on landslide mobility: Modeling hurricane-induced landslide runout and debris-flow inundation in Puerto Rico","interactions":[],"lastModifiedDate":"2025-06-10T14:20:41.696971","indexId":"70267980","displayToPublicDate":"2025-03-31T09:12:49","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2824,"text":"Natural Hazards and Earth System Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Topographic controls on landslide mobility: Modeling hurricane-induced landslide runout and debris-flow inundation in Puerto Rico","docAbstract":"<p id=\"d2e115\">In 2017, Hurricane Maria triggered more than 70 000 landslides in Puerto Rico. After initiation, these predominantly shallow landslides were mobilized to varying extents – some landslides only traveled partway downslope, whereas others reached drainage channels and were mobilized into long-traveled debris flows that could severely impact roads and infrastructure. Thus, forecasting potential landslide runout and inundation zones is critical for estimating landslide and debris-flow hazards. Here we conduct an in-depth topographic analysis of landslide-affected areas from nine study areas and apply a linked modeling technique to estimate locations susceptible to varying degrees of landslide runout in the Lares, Utuado, and Naranjito municipalities.</p><p id=\"d2e118\">We find that the longest runout lengths are observed on high-relief escarpments, although highly mobile long-runout debris flows also occurred in lower-relief dissected uplands. These topographic differences indicate that landslides that are initiated under similar conditions and possess equal potential to be mobilized as debris flows may not travel the same distances or affect the same areal extent. Our modeling approach allows the local topography to automatically control the implementation of two runout methods: (1) <i>H/L</i><span id=\"MathJax-Element-1-Frame\" class=\"MathJax\" data-mathml=\"&lt;math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot; id=&quot;M1&quot; display=&quot;inline&quot; overflow=&quot;scroll&quot; dspmath=&quot;mathml&quot;&gt;&lt;mrow&gt;&lt;mi&gt;H&lt;/mi&gt;&lt;mo&gt;/&lt;/mo&gt;&lt;mi&gt;L&lt;/mi&gt;&lt;/mrow&gt;&lt;/math&gt;\"></span><span>&nbsp;</span>runout zones are assigned directly downslope of landslide source zones, and (2)&nbsp;debris-flow inundation zones are estimated in the presence of a channel network. Debris-flow volumes are calculated as a function of area-integrated growth factors, estimated as a function of the upstream areas susceptible to shallow landslides. Applying our empirical modeling scheme over an area of 560 km<span class=\"inline-formula\"><sup>2</sup></span>, our results highlight the efficacy of our methods for the assessment of the potential for landslide runout and debris-flow inundation over diverse terrains with varied susceptibility.</p>","language":"English","publisher":"European Geosciences Union","doi":"10.5194/nhess-25-1229-2025","usgsCitation":"Brien, D.L., Reid, M.E., Cronkite-Ratcliff, C., and Perkins, J.P., 2025, Topographic controls on landslide mobility: Modeling hurricane-induced landslide runout and debris-flow inundation in Puerto Rico: Natural Hazards and Earth System Sciences, v. 25, no. 3, p. 1229-1253, https://doi.org/10.5194/nhess-25-1229-2025.","productDescription":"25 p.","startPage":"1229","endPage":"1253","ipdsId":"IP-147641","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":490625,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/nhess-25-1229-2025","text":"Publisher Index Page"},{"id":490306,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Puerto Rico","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -66.96551536620369,\n              18.33797102243001\n            ],\n            [\n              -66.96551536620369,\n              18.13229474686122\n            ],\n            [\n              -66.18238268856022,\n              18.13229474686122\n            ],\n            [\n              -66.18238268856022,\n              18.33797102243001\n            ],\n            [\n              -66.96551536620369,\n              18.33797102243001\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"25","issue":"3","noUsgsAuthors":false,"publicationDate":"2025-03-31","publicationStatus":"PW","contributors":{"authors":[{"text":"Brien, Dianne L. 0000-0003-3227-7963 dbrien@usgs.gov","orcid":"https://orcid.org/0000-0003-3227-7963","contributorId":229851,"corporation":false,"usgs":true,"family":"Brien","given":"Dianne","email":"dbrien@usgs.gov","middleInitial":"L.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":939854,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Reid, Mark E. 0000-0002-5595-1503 mreid@usgs.gov","orcid":"https://orcid.org/0000-0002-5595-1503","contributorId":1167,"corporation":false,"usgs":true,"family":"Reid","given":"Mark","email":"mreid@usgs.gov","middleInitial":"E.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":939855,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cronkite-Ratcliff, Collin 0000-0001-5485-3832 ccronkite-ratcliff@usgs.gov","orcid":"https://orcid.org/0000-0001-5485-3832","contributorId":203951,"corporation":false,"usgs":true,"family":"Cronkite-Ratcliff","given":"Collin","email":"ccronkite-ratcliff@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":939856,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Perkins, Jonathan P. 0000-0002-6113-338X","orcid":"https://orcid.org/0000-0002-6113-338X","contributorId":237053,"corporation":false,"usgs":true,"family":"Perkins","given":"Jonathan","email":"","middleInitial":"P.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":939857,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70266021,"text":"70266021 - 2025 - The GorDAS Distributed Acoustic Sensing experiment above the Cascadia locked zone and subducted Gorda Slab","interactions":[],"lastModifiedDate":"2025-07-09T15:59:50.150051","indexId":"70266021","displayToPublicDate":"2025-03-31T09:00:41","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3372,"text":"Seismological Research Letters","onlineIssn":"1938-2057","printIssn":"0895-0695","active":true,"publicationSubtype":{"id":10}},"title":"The GorDAS Distributed Acoustic Sensing experiment above the Cascadia locked zone and subducted Gorda Slab","docAbstract":"<p>The southernmost portion of the Cascadia Subduction zone in Northern California produces high rates of moderate and large earthquakes owing to subduction of the Gorda slab and deformation associated with the Mendocino Triple Junction. Distributed Acoustic Sensing (DAS) is rapidly advancing as a method for detecting earthquakes and imaging crustal structure. We have begun a long-term DAS monitoring experiment on buried telecom fiber in Arcata, California, with the goal of increasing the available recordings of moderate to large earthquakes as well as imaging seismogenic structures. We have recorded over a year's worth of data, including most aftershocks of the 2022 <i>M<sub>w</sub></i>6.4 Ferndale earthquake, though not the mainshock itself. The dataset includes numerous magnitude 3.5 and larger earthquakes including the 2023/01/01 <i>M<sub>w</sub></i>5.4 Rio Dell earthquake. Here we present initial results comparing an earthquake detection algorithm, run in real-time on the processing unit of the interrogator system, with both the ShakeAlert earthquake early warning system as well as a post-processed earthquake catalog developed with deep-learning phase-picker algorithms. The rapid onboard processing of the detector demonstrates the potential utility of DAS-based edge computing for earthquake early warning. We also verify the quality of the strain waveforms both in terms of peak amplitudes and waveform similarity using about five months of nodal seismometer data. These instruments were deployed roughly every 300 m along the ~15km long cable and validate large variations in peak strain over short distances that are seen in the DAS data. All data from time windows surrounding both the local and teleseismic earthquakes are publicly available, which will improve our understanding of both the performance of DAS systems in moderate earthquakes and earthquake hazards associated with the Gorda subduction zone.</p>","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0220240415","usgsCitation":"McGuire, J., Barbour, A.J., Stewart, C., Yartsev, V., Karrenbach, M., Hemphill-Haley, M., McPherson, R.C., Stockdale, K., Yoon, C., and Sawi, T., 2025, The GorDAS Distributed Acoustic Sensing experiment above the Cascadia locked zone and subducted Gorda Slab: Seismological Research Letters, v. 96, no. 4, p. 2489-2503, https://doi.org/10.1785/0220240415.","productDescription":"15 p.","startPage":"2489","endPage":"2503","ipdsId":"IP-171005","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":484911,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Cascadia locked zone, Gorda slab","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -126,\n              42\n            ],\n            [\n              -126,\n              39.5\n            ],\n            [\n              -122,\n              39.5\n            ],\n            [\n              -122,\n              42\n            ],\n            [\n              -126,\n              42\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"96","issue":"4","noUsgsAuthors":false,"publicationDate":"2025-03-31","publicationStatus":"PW","contributors":{"authors":[{"text":"McGuire, Jeffrey J. 0000-0001-9235-2166","orcid":"https://orcid.org/0000-0001-9235-2166","contributorId":219786,"corporation":false,"usgs":true,"family":"McGuire","given":"Jeffrey J.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":934338,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Barbour, Andrew J. 0000-0002-6890-2452","orcid":"https://orcid.org/0000-0002-6890-2452","contributorId":215339,"corporation":false,"usgs":true,"family":"Barbour","given":"Andrew","middleInitial":"J.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":934339,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stewart, Connie","contributorId":222103,"corporation":false,"usgs":false,"family":"Stewart","given":"Connie","email":"","affiliations":[{"id":18889,"text":"University of New Brunswick","active":true,"usgs":false}],"preferred":false,"id":934340,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Yartsev, Victor","contributorId":350345,"corporation":false,"usgs":false,"family":"Yartsev","given":"Victor","affiliations":[{"id":83720,"text":"Luna, Inc","active":true,"usgs":false}],"preferred":false,"id":934341,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Karrenbach, Martin","contributorId":353682,"corporation":false,"usgs":false,"family":"Karrenbach","given":"Martin","affiliations":[{"id":84462,"text":"Seismics Unuusal","active":true,"usgs":false}],"preferred":false,"id":934342,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hemphill-Haley, Mark","contributorId":295931,"corporation":false,"usgs":false,"family":"Hemphill-Haley","given":"Mark","affiliations":[{"id":63943,"text":"Cal Poly Humboldt","active":true,"usgs":false}],"preferred":false,"id":934343,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"McPherson, Robert C.","contributorId":350346,"corporation":false,"usgs":false,"family":"McPherson","given":"Robert","middleInitial":"C.","affiliations":[{"id":83721,"text":"Cal Poly Humboldt Univ.","active":true,"usgs":false}],"preferred":false,"id":934344,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Stockdale, Kari","contributorId":352201,"corporation":false,"usgs":false,"family":"Stockdale","given":"Kari","affiliations":[{"id":39079,"text":"NYSDEC","active":true,"usgs":false}],"preferred":false,"id":934345,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Yoon, Clara 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,{"id":70265069,"text":"70265069 - 2025 - Assessment of western Oregon debris-flow hazards in burned and unburned environments","interactions":[],"lastModifiedDate":"2025-04-01T15:02:09.946731","indexId":"70265069","displayToPublicDate":"2025-03-30T07:56:10","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1425,"text":"Earth Surface Processes and Landforms","active":true,"publicationSubtype":{"id":10}},"title":"Assessment of western Oregon debris-flow hazards in burned and unburned environments","docAbstract":"<p><span>In the steep and mountainous environment of western Oregon, debris flows pose a considerable threat to property, infrastructure and life. Wildfire is commonly known to increase the susceptibility of steep slopes to debris flows, but the extent of this process in the western Cascades is not well understood. The US Geological Survey (USGS) currently estimates postfire debris-flow likelihood and triggering rainfall thresholds using a model calibrated to a southern California inventory of debris flows generated by excess runoff within the first year after fire. Because of a lack of available data, this model has not been tested in western Oregon, or in locations where postfire debris flows initiate via other mechanisms (e.g., shallow landslides or in-channel failures). Using repeat field observations and aerial imagery, we developed two new debris-flow inventories within and adjacent to the perimeters of five 2020 wildfires in western Oregon: Archie Creek, Holiday Farm, Beachie Creek, Lionshead and Riverside. The first inventory focuses on postfire debris flows (2020–2022); the second focuses on debris flows prior to fires (1995–2020). Our inventories of prefire and postfire debris flows were used to document initiation mechanisms in Oregon's western Cascades and to evaluate the effects of wildfire. We found that wildfire changed the distribution of debris-flow initiation mechanisms in the western Cascades. After the wildfires, annual rates of runoff-generated debris flows increased by 22% and the number of shallow landslide-initiated debris flows decreased by 17% relative to before the wildfires. Despite this shift, shallow landsliding was the dominant debris-flow initiation mechanism in both unburned and burned environments. We found the performance of the current USGS debris-flow likelihood model was degraded relative to other previously tested locations across the intermountain western United States. Our results highlight the need for improved postfire hazard assessment in western Oregon based on regional model calibration that is tuned to the dominant debris-flow initiation mechanisms.</span></p>","language":"English","publisher":"Wiley","doi":"10.1002/ESP.70045","usgsCitation":"Selander, B., Calhoun, N.C., Burns, W., Kean, J.W., and Rengers, F.K., 2025, Assessment of western Oregon debris-flow hazards in burned and unburned environments: Earth Surface Processes and Landforms, v. 50, no. 4, e70045, 15 p., https://doi.org/10.1002/ESP.70045.","productDescription":"e70045, 15 p.","ipdsId":"IP-170327","costCenters":[{"id":78941,"text":"Geologic Hazards Science Center - Landslides / Earthquake Geology","active":true,"usgs":true}],"links":[{"id":488659,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/esp.70045","text":"Publisher Index Page"},{"id":484065,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon","otherGeospatial":"western Oregon","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -124.57278320768603,\n              46.34148488781506\n            ],\n            [\n              -124.57278320768603,\n              42.016342483468776\n            ],\n            [\n              -121.87720015148463,\n              42.016342483468776\n            ],\n            [\n              -121.87720015148463,\n              46.34148488781506\n            ],\n            [\n              -124.57278320768603,\n              46.34148488781506\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"50","issue":"4","noUsgsAuthors":false,"publicationDate":"2025-03-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Selander, Brittany Danielle 0000-0002-3332-1068","orcid":"https://orcid.org/0000-0002-3332-1068","contributorId":344520,"corporation":false,"usgs":true,"family":"Selander","given":"Brittany Danielle","affiliations":[{"id":78941,"text":"Geologic Hazards Science Center - Landslides / Earthquake Geology","active":true,"usgs":true}],"preferred":true,"id":932462,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Calhoun, Nancy C.","contributorId":216331,"corporation":false,"usgs":false,"family":"Calhoun","given":"Nancy","email":"","middleInitial":"C.","affiliations":[{"id":39395,"text":"DOGAMI","active":true,"usgs":false}],"preferred":false,"id":932463,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Burns, William 0000-0002-4379-6198","orcid":"https://orcid.org/0000-0002-4379-6198","contributorId":344522,"corporation":false,"usgs":false,"family":"Burns","given":"William","affiliations":[{"id":32397,"text":"Oregon Department of Geology and Mineral Industries","active":true,"usgs":false}],"preferred":false,"id":932464,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kean, Jason W. 0000-0003-3089-0369 jwkean@usgs.gov","orcid":"https://orcid.org/0000-0003-3089-0369","contributorId":1654,"corporation":false,"usgs":true,"family":"Kean","given":"Jason","email":"jwkean@usgs.gov","middleInitial":"W.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":932465,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rengers, Francis K. 0000-0002-1825-0943 frengers@usgs.gov","orcid":"https://orcid.org/0000-0002-1825-0943","contributorId":150422,"corporation":false,"usgs":true,"family":"Rengers","given":"Francis","email":"frengers@usgs.gov","middleInitial":"K.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":932466,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70265697,"text":"70265697 - 2025 - Understanding predator-prey-competitor dynamics between Lower Missouri River Macrhybopsis and Scaphirhynchus using a population—bioenergetics model ensemble","interactions":[],"lastModifiedDate":"2025-04-15T14:57:29.302648","indexId":"70265697","displayToPublicDate":"2025-03-29T07:49:57","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":16139,"text":"Ecological Modeling","active":true,"publicationSubtype":{"id":10}},"title":"Understanding predator-prey-competitor dynamics between Lower Missouri River Macrhybopsis and Scaphirhynchus using a population—bioenergetics model ensemble","docAbstract":"<p><span>The pallid sturgeon&nbsp;</span><i>Scaphirhynchus albus</i><span>&nbsp;is a long-lived, endangered fish in the Missouri River. Individuals become piscivorous as adults, so recruitment from stocking or reproduction could reduce populations of prey, including&nbsp;</span><i>Macrhybopsis</i><span>&nbsp;chubs. We constructed an individual- and age-based, multi-species, predator-prey-competitor model (IAMP) to represent the benthic community (sturgeons, chubs, and chironomids) of the Lower Missouri River (LMR) to explore scenarios of potential predator-prey-competitor dynamics. Our simulations suggest that chubs alone are unlikely able to support a level of LMR pallid sturgeon similar to historical or current populations. These simulations also suggest that adult pallid sturgeon may need to shift to non-chub prey fish to achieve the greater sizes observed in the Upper Missouri River. When annual hydrologic regimes were included, we found a negative relationship between chub relative abundance and previous year 30-day minimum flows. Inclusion of temporal environmental variability made it clear that large chub populations may be necessary to support LMR pallid sturgeon. When full stochasticity was included in the IAMP, chub population sizes needed to increase further to ensure continued reproduction and recruitment of both chubs and pallid sturgeon. These results support the hypothesis that the pallid sturgeon population in the Lower Missouri River may be food-limited. However, the full extent of this limitation and the management changes needed to address this will require more research on the biology and population dynamics of this fish community, on pallid sturgeon interactions with prey species, and on how sympatric species may be affected during the pallid sturgeon recovery process.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolmodel.2025.111097","usgsCitation":"Wildhaber, M.L., Albers, J.L., and Green, N., 2025, Understanding predator-prey-competitor dynamics between Lower Missouri River Macrhybopsis and Scaphirhynchus using a population—bioenergetics model ensemble: Ecological Modeling, v. 504, 111097, 28 p., https://doi.org/10.1016/j.ecolmodel.2025.111097.","productDescription":"111097, 28 p.","ipdsId":"IP-164525","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":488248,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecolmodel.2025.111097","text":"Publisher Index Page"},{"id":484578,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado, Kansas, Minnesota, Missouri, Montana, Nebraska, North Dakota, South Dakota, Wyoming","otherGeospatial":"Missouri River","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-111.048974,44.474072],[-111.323669,44.724474],[-111.50494,44.635746],[-111.469185,44.552044],[-112.258665,44.569516],[-112.387389,44.448058],[-112.749011,44.491233],[-112.844859,44.358221],[-113.134824,44.752763],[-113.455071,44.865424],[-113.802955,45.592631],[-114.015633,45.696127],[-114.345019,45.459916],[-114.559038,45.565706],[-114.422963,45.855381],[-114.527096,46.146218],[-114.322912,46.642938],[-114.76689,46.696901],[-115.294785,47.220914],[-115.731348,47.433381],[-115.72377,47.696671],[-116.049153,47.999923],[-116.049193,49.000912],[-95.153711,48.998903],[-95.153314,49.384358],[-94.878454,49.333193],[-94.640803,48.741171],[-93.818375,48.534442],[-92.984963,48.623731],[-92.634931,48.542873],[-92.698824,48.494892],[-92.341207,48.23248],[-92.066269,48.359602],[-91.542512,48.053268],[-90.88548,48.245784],[-90.703702,48.096009],[-89.489226,48.014528],[-90.735927,47.624343],[-92.058888,46.809938],[-92.025789,46.710839],[-92.189091,46.717541],[-92.291976,46.503997],[-92.33859,46.050111],[-92.869193,45.717568],[-92.646602,45.441635],[-92.807362,44.758909],[-91.410555,43.970892],[-91.244135,43.774667],[-91.243183,43.540309],[-96.591213,43.500514],[-96.439335,43.113916],[-96.630311,42.770885],[-96.396107,42.484095],[-96.272901,42.047281],[-96.129186,41.965136],[-96.081843,41.580407],[-95.850188,41.184798],[-95.885349,40.721093],[-95.758045,40.613759],[-91.625161,40.5435],[-91.452458,40.375501],[-91.510322,40.127994],[-91.369953,39.745042],[-90.721593,39.23273],[-90.653164,38.916141],[-90.113327,38.849306],[-90.367013,38.250054],[-89.952499,37.883218],[-89.516685,37.692762],[-89.438275,37.161287],[-89.102879,36.9697],[-89.120437,36.782071],[-89.429311,36.481875],[-89.55264,36.577178],[-89.527029,36.341679],[-89.703511,36.243412],[-89.615128,36.113816],[-89.733095,36.000608],[-90.368718,35.995812],[-90.075934,36.281485],[-90.157136,36.484317],[-94.617919,36.499414],[-94.699735,36.998805],[-109.045223,36.999084],[-109.050076,41.000659],[-111.046723,40.997959],[-111.048974,44.474072]]]},\"properties\":{\"name\":\"Colorado\",\"nation\":\"USA  \"}}]}","volume":"504","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Wildhaber, Mark L. 0000-0002-6538-9083 mwildhaber@usgs.gov","orcid":"https://orcid.org/0000-0002-6538-9083","contributorId":1386,"corporation":false,"usgs":true,"family":"Wildhaber","given":"Mark","email":"mwildhaber@usgs.gov","middleInitial":"L.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":933316,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Albers, Janice L. 0000-0002-6312-8269 jalbers@usgs.gov","orcid":"https://orcid.org/0000-0002-6312-8269","contributorId":3972,"corporation":false,"usgs":true,"family":"Albers","given":"Janice","email":"jalbers@usgs.gov","middleInitial":"L.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":933317,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Green, Nicholas S.","contributorId":301918,"corporation":false,"usgs":false,"family":"Green","given":"Nicholas S.","affiliations":[{"id":65362,"text":"Kennesaw State University","active":true,"usgs":false}],"preferred":false,"id":933318,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
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