{"pageNumber":"11","pageRowStart":"250","pageSize":"25","recordCount":184553,"records":[{"id":70273873,"text":"70273873 - 2026 - Teach me how to pycap: A high-capacity well decision support tool using analytical solutions in Python","interactions":[],"lastModifiedDate":"2026-03-23T14:50:21.582142","indexId":"70273873","displayToPublicDate":"2026-01-25T09:06:08","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3825,"text":"Groundwater","active":true,"publicationSubtype":{"id":10}},"title":"Teach me how to pycap: A high-capacity well decision support tool using analytical solutions in Python","docAbstract":"<p><span>Regulatory agencies in humid temperate environments rely on timely evaluations of streamflow depletion and drawdown to protect aquatic ecosystems and existing water users. Numerical models offer detailed insights, but their complexity and time demands often preclude their practical use in rapid decision-making. We present pycap-dss, an open-source Python package that implements a suite of analytical solutions for estimating streamflow depletion and drawdown. The tool supports superposition of multiple wells and time-varying pumping, enabling cumulative impact assessments in situations with multiple wells and streams. The software is modular and extensible, allowing users to interchange solutions or add new analytical methods. A YAML-based configuration supports batch processing of multiple wells, and an optional AnalysisProject class facilitates integration with regulatory workflows. Rigorous unit and regression testing ensures computational reliability, and continuous integration supports ongoing development. We demonstrate deterministic examples of drawdown where multiple solutions are readily compared and streamflow depletion with multiple wells in the Central Sands region of Wisconsin. We also show the value of Monte Carlo analyses of streamflow depletion in the same Central Sands example, leveraging computational efficiency to evaluate the uncertainty of individual and cumulative streamflow depletion calculations from over 200 high-capacity wells.</span></p>","language":"English","publisher":"National Groundwater Association","doi":"10.1111/gwat.70046","usgsCitation":"Fienen, M., Pruitt, A., and Reeves, H.W., 2026, Teach me how to pycap: A high-capacity well decision support tool using analytical solutions in Python: Groundwater, v. 64, no. 2, p. 223-234, https://doi.org/10.1111/gwat.70046.","productDescription":"12 p.","startPage":"223","endPage":"234","ipdsId":"IP-183720","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":499748,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":499946,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/gwat.70046","text":"Publisher Index Page"}],"country":"United States","state":"Wisconsin","otherGeospatial":"Tomorrow River","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -89.67725263192825,\n              44.6879674210181\n            ],\n            [\n              -89.67725263192825,\n              44.15565808301017\n            ],\n            [\n              -89.16563204911922,\n              44.15565808301017\n            ],\n            [\n              -89.16563204911922,\n              44.6879674210181\n            ],\n            [\n              -89.67725263192825,\n              44.6879674210181\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"64","issue":"2","noUsgsAuthors":false,"publicationDate":"2026-01-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Fienen, Michael N. 0000-0002-7756-4651","orcid":"https://orcid.org/0000-0002-7756-4651","contributorId":245632,"corporation":false,"usgs":true,"family":"Fienen","given":"Michael N.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":955343,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pruitt, Aaron","contributorId":214451,"corporation":false,"usgs":false,"family":"Pruitt","given":"Aaron","affiliations":[],"preferred":false,"id":955344,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Reeves, Howard W. 0000-0001-8057-2081 hwreeves@usgs.gov","orcid":"https://orcid.org/0000-0001-8057-2081","contributorId":2307,"corporation":false,"usgs":true,"family":"Reeves","given":"Howard","email":"hwreeves@usgs.gov","middleInitial":"W.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":955345,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70274634,"text":"70274634 - 2026 - Experimental lure design reveals the best attractants for increasing detection of multiple mesocarnivores","interactions":[],"lastModifiedDate":"2026-04-02T15:58:59.780155","indexId":"70274634","displayToPublicDate":"2026-01-25T08:49:59","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3766,"text":"Wildlife Biology","active":true,"publicationSubtype":{"id":10}},"title":"Experimental lure design reveals the best attractants for increasing detection of multiple mesocarnivores","docAbstract":"<p><span id=\"_mce_caret\" data-mce-bogus=\"1\" data-mce-type=\"format-caret\"><span>Many mesocarnivores have low detection rates that hinder practitioners' abilities to implement effective monitoring strategies. Using olfactory attractants (i.e. lures) may increase detection rates, but variation in effects among species is not well understood. Thus, investigating factors influencing detection of mesocarnivores, can inform and improve monitoring efforts. We evaluated the effects of lures and environmental covariates on the detection of plains spotted skunks&nbsp;</span><i>Spilogale interrupta</i><span>, striped skunks&nbsp;</span><i>Mephitis mephitis</i><span>, northern raccoons&nbsp;</span><i>Procyon lotor</i><span>, gray foxes&nbsp;</span><i>Urocyon cinereoargenteus</i><span>, coyotes&nbsp;</span><i>Canis latrans</i><span>, bobcats&nbsp;</span><i>Lynx rufus</i><span>&nbsp;and Virginia opossums&nbsp;</span><i>Didelphis virginiana</i><span>. We conducted surveys during January–May 2023 in southeast Oklahoma using motion-triggered cameras at randomly selected sites. We surveyed sites using a 4-camera cluster and leave-one-out lure design, where 3 cameras were randomly assigned 1 of 4 lures (i.e. skunk-based lure, fatty acid tablets, sweet lure or sardines) and 1 camera was a control (i.e. no lure). We analyzed species-specific detection data within an occupancy framework to determine the influence of lure combinations and environmental covariates (i.e. temperature, precipitation and moon illumination) on site-level detection patterns for each species. When lures influenced detection, we assessed species-specific preference among lures (and the control) within sites by comparing camera-level independent detections with Kruskal–Wallis and Dunn's tests at sites where the species was detected. The effect of lures varied among species; lure combinations influenced site-specific daily detection of plains spotted skunks, striped skunks, gray foxes, raccoons and bobcats, but did not affect detection of coyotes or opossums. One environmental covariate influenced detection of striped skunks (i.e. moon illumination), bobcats (i.e. temperature), and gray foxes (i.e. precipitation). Within sites, lure preference varied among species. Spotted skunks, gray foxes and raccoons preferred sardines whereas striped skunks preferred the skunk-based lure. Identifying lure preferences and effects of environmental factors can help optimize sampling and improve mesocarnivore monitoring efforts.</span></span></p>","language":"English","publisher":"Nordic Society Oikos","doi":"10.1002/wlb3.01579","usgsCitation":"Brosend, D.N., Moeller, A.K., and Lonsinger, R.C., 2026, Experimental lure design reveals the best attractants for increasing detection of multiple mesocarnivores: Wildlife Biology, e01579, 13 p., https://doi.org/10.1002/wlb3.01579.","productDescription":"e01579, 13 p.","ipdsId":"IP-180057","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":502085,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/wlb3.01579","text":"Publisher Index Page"},{"id":502007,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oklahoma","county":"LeFlore County","otherGeospatial":"Ouachita National Forest, Wister Wildlife Management Area","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -94.89305161506785,\n              34.979300535069825\n            ],\n            [\n              -94.89305161506785,\n              34.85490787523719\n            ],\n            [\n              -94.6470536880039,\n              34.85490787523719\n            ],\n            [\n              -94.6470536880039,\n              34.979300535069825\n            ],\n            [\n              -94.89305161506785,\n              34.979300535069825\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","edition":"Online First","noUsgsAuthors":false,"publicationDate":"2026-01-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Brosend, Danielle N.","contributorId":369128,"corporation":false,"usgs":false,"family":"Brosend","given":"Danielle","middleInitial":"N.","affiliations":[{"id":7249,"text":"Oklahoma State University","active":true,"usgs":false}],"preferred":false,"id":958501,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Moeller, Anna K.","contributorId":369129,"corporation":false,"usgs":false,"family":"Moeller","given":"Anna","middleInitial":"K.","affiliations":[{"id":7249,"text":"Oklahoma State University","active":true,"usgs":false}],"preferred":false,"id":958502,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lonsinger, Robert Charles 0000-0002-1040-7299","orcid":"https://orcid.org/0000-0002-1040-7299","contributorId":340524,"corporation":false,"usgs":true,"family":"Lonsinger","given":"Robert","email":"","middleInitial":"Charles","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":958503,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70273948,"text":"70273948 - 2026 - Modeling carbon fluxes in tidal forested wetlands in the Mississippi river deltaic plain under various hydrologic conditions: Implications for river diversions","interactions":[],"lastModifiedDate":"2026-03-02T17:49:22.623453","indexId":"70273948","displayToPublicDate":"2026-01-24T09:23:03","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3751,"text":"Wetlands Ecology and Management","active":true,"publicationSubtype":{"id":10}},"title":"Modeling carbon fluxes in tidal forested wetlands in the Mississippi river deltaic plain under various hydrologic conditions: Implications for river diversions","docAbstract":"<p><span>Our understanding of the impacts of climate change, sea-level rise (SLR), and freshwater management on the magnitude and variability of carbon fluxes in tidal forested wetlands remains limited. In this study, we applied a process-driven wetland biogeochemistry model, Wetland Carbon Assessment Tool—DeNitrification-DeComposition (WCAT-DNDC) model to explore responses of carbon fluxes in tidal swamp forests to climate change-induced alterations in hydrologic conditions and to predict impacts of planned reintroduction of river flows. We selected twelve sites in three habitats (throughput, relict, degraded) inside the Lake Maurepas swamp forests (Louisiana, USA) to represent various hydrological and salinity regimes. Environmental scenarios included dry, average, and wet conditions, SLR (low and high), and a Mississippi River (MR) diversion. Simulation results showed that the responses of net ecosystem exchange (NEE), net primary productivity (NPP), ecosystem respiration (ER), methane (CH</span><sub>4</sub><span>) and nitrous oxide (N</span><sub>2</sub><span>O) emissions in the Lake Maurepas swamp forests varied substantially among sites. However, the overall net carbon uptake capacity of the Lake Maurepas swamp forests was high (NEE: −&nbsp;1143 to −&nbsp;1650&nbsp;g C m</span><sup>−2</sup><span>&nbsp;yr</span><sup>−1</sup><span>), suggesting that Lake Maurepas swamp forests are large carbon sinks. The high net carbon uptake capacity could be significantly affected by climate change induced drought, flooding, and SLR with the bi-directional changes (increase or decrease) depending on the direction and magnitude of the hydrologic regime changes. The response of the net carbon uptake capacity to MR diversion is also bi-directional and site-specific, but enhancement of the capacity of NEE of up to −&nbsp;1957&nbsp;g C m</span><sup>2</sup><span>&nbsp;yr</span><sup>−1</sup><span>&nbsp;is possible, implying that MR diversion into the swamp forests could be beneficial in the context of carbon cycling and carbon sequestration.</span></p>","language":"English","publisher":"Springer Nature","doi":"10.1007/s11273-026-10111-5","usgsCitation":"Wang, H., Krauss, K.W., Shaffer, G.P., Patton, B., Kroes, D., Noe, G.E., Dai, Z., Dettwiller, L., and Trettin, C.C., 2026, Modeling carbon fluxes in tidal forested wetlands in the Mississippi river deltaic plain under various hydrologic conditions: Implications for river diversions: Wetlands Ecology and Management, v. 34, no. 1, 11, 27 p., https://doi.org/10.1007/s11273-026-10111-5.","productDescription":"11, 27 p.","ipdsId":"IP-180681","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":500188,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":500214,"rank":2,"type":{"id":42,"text":"Open Access USGS Document"},"url":"https://pubs.usgs.gov/publication/70273948/full"},{"id":500215,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/ja/70273948/70273948.XML"},{"id":500683,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/ja/70273948/images"}],"country":"United States","state":"Louisiana","otherGeospatial":"Lake Maurepas swamp forests","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -90.21451630425345,\n              30.450162758345343\n            ],\n            [\n              -90.90340771654913,\n              30.450162758345343\n            ],\n            [\n              -90.90340771654913,\n              29.978620193311116\n            ],\n            [\n              -90.21451630425345,\n              29.978620193311116\n            ],\n            [\n              -90.21451630425345,\n              30.450162758345343\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"34","issue":"1","noUsgsAuthors":false,"publicationDate":"2026-01-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Wang, Hongqing 0000-0002-2977-7732","orcid":"https://orcid.org/0000-0002-2977-7732","contributorId":222377,"corporation":false,"usgs":true,"family":"Wang","given":"Hongqing","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":955890,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Krauss, Ken W.","contributorId":366426,"corporation":false,"usgs":false,"family":"Krauss","given":"Ken","middleInitial":"W.","affiliations":[{"id":12699,"text":"Louisiana Universities Marine Consortium","active":true,"usgs":false}],"preferred":false,"id":955891,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shaffer, Gary P.","contributorId":366427,"corporation":false,"usgs":false,"family":"Shaffer","given":"Gary","middleInitial":"P.","affiliations":[{"id":28058,"text":"Southeastern Louisiana University","active":true,"usgs":false}],"preferred":false,"id":955892,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Patton, Brett 0000-0002-7396-3452 pattonb@usgs.gov","orcid":"https://orcid.org/0000-0002-7396-3452","contributorId":5458,"corporation":false,"usgs":true,"family":"Patton","given":"Brett","email":"pattonb@usgs.gov","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":true,"id":955893,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kroes, Daniel 0000-0001-9104-9077 dkroes@usgs.gov","orcid":"https://orcid.org/0000-0001-9104-9077","contributorId":3830,"corporation":false,"usgs":true,"family":"Kroes","given":"Daniel","email":"dkroes@usgs.gov","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":369,"text":"Louisiana Water Science Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":955894,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Noe, Gregory E. 0000-0002-6661-2646 gnoe@usgs.gov","orcid":"https://orcid.org/0000-0002-6661-2646","contributorId":139100,"corporation":false,"usgs":true,"family":"Noe","given":"Gregory","email":"gnoe@usgs.gov","middleInitial":"E.","affiliations":[{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":955895,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Dai, Zhaohua 0000-0002-0941-8345","orcid":"https://orcid.org/0000-0002-0941-8345","contributorId":290409,"corporation":false,"usgs":false,"family":"Dai","given":"Zhaohua","email":"","affiliations":[{"id":16203,"text":"Michigan Technological university","active":true,"usgs":false}],"preferred":false,"id":955896,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Dettwiller, Lindsey","contributorId":360880,"corporation":false,"usgs":false,"family":"Dettwiller","given":"Lindsey","affiliations":[{"id":28058,"text":"Southeastern Louisiana University","active":true,"usgs":false}],"preferred":false,"id":955897,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Trettin, Carl C.","contributorId":366432,"corporation":false,"usgs":false,"family":"Trettin","given":"Carl","middleInitial":"C.","affiliations":[{"id":36493,"text":"USDA Forest Service","active":true,"usgs":false}],"preferred":false,"id":955898,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70273779,"text":"70273779 - 2026 - Prioritizing resource protection and understanding potential susceptibility of springs to surficial changes in a low-temperature geothermal system","interactions":[],"lastModifiedDate":"2026-01-29T14:54:24.411943","indexId":"70273779","displayToPublicDate":"2026-01-24T08:46:07","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1828,"text":"Geothermics","active":true,"publicationSubtype":{"id":10}},"title":"Prioritizing resource protection and understanding potential susceptibility of springs to surficial changes in a low-temperature geothermal system","docAbstract":"<p><span>Geothermal systems are vulnerable to changes in water budget and composition, requiring science-based management. This study uses a dataset of spring water temperatures, time series of groundwater residence time tracers (tritium and carbon-14), and stable isotopes of water to understand geothermal flow in a low-temperature geothermal system in north west Colorado, United States (Steamboat Springs). The geothermal system is bisected by the Yampa River, necessitating a stream mass balance approach to quantify total discharge. Time series analysis of water temperature data provides a ranked list of features more susceptible to surficial changes, which is corroborated using time series of tritium which indicate spatially distinct patterns of mixing between modern and pre-modern groundwater. All springs contain a portion of pre-modern groundwater that is thousands to tens of thousands of years old, a period coinciding with melting of extensive Pleistocene glaciers that was likely one of the recharge sources to the geothermal system. Stream mass balance indicates that greater than 80% of the total geothermal discharge is derived from diffuse or small springs, highlighting the extensive nature of the geothermal outflow zone and the association with local geologic structures. This study provides baseline data to support management of the Steamboat Springs geothermal system and indicates the utility of these approaches in developing science-based geothermal management.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.geothermics.2026.103615","usgsCitation":"Newman, C.P., and Pepin, J.D., 2026, Prioritizing resource protection and understanding potential susceptibility of springs to surficial changes in a low-temperature geothermal system: Geothermics, v. 136, 103615, 14 p., https://doi.org/10.1016/j.geothermics.2026.103615.","productDescription":"103615, 14 p.","ipdsId":"IP-180997","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":499294,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.geothermics.2026.103615","text":"Publisher Index Page"},{"id":499224,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","city":"Steamboat Springs","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -106.87961681380281,\n              40.567\n            ],\n            [\n              -106.87961681380281,\n              40.45\n            ],\n            [\n              -106.68,\n              40.45\n            ],\n            [\n              -106.68,\n              40.567\n            ],\n            [\n              -106.87961681380281,\n              40.567\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"136","noUsgsAuthors":false,"publicationDate":"2026-01-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Newman, Connor P. 0000-0002-6978-3440","orcid":"https://orcid.org/0000-0002-6978-3440","contributorId":222596,"corporation":false,"usgs":true,"family":"Newman","given":"Connor","email":"","middleInitial":"P.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":954760,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pepin, Jeff D. 0000-0002-7410-9979","orcid":"https://orcid.org/0000-0002-7410-9979","contributorId":222161,"corporation":false,"usgs":true,"family":"Pepin","given":"Jeff","email":"","middleInitial":"D.","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":954761,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70274166,"text":"70274166 - 2026 - A catalogue of Do's and Don'ts in the modeling of environmental systems","interactions":[],"lastModifiedDate":"2026-03-03T15:08:37.444188","indexId":"70274166","displayToPublicDate":"2026-01-24T08:01:33","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1551,"text":"Environmental Modelling and Software","active":true,"publicationSubtype":{"id":10}},"title":"A catalogue of Do's and Don'ts in the modeling of environmental systems","docAbstract":"<p><span id=\"_mce_caret\" data-mce-bogus=\"1\" data-mce-type=\"format-caret\"><span>Modeling plays a vital role in understanding and managing complex environmental systems, but its credibility and quality depend heavily on a comprehensive set of defensible model activities and practices, especially when the system of interest is plagued with uncertainties and conflicting stakeholder perspectives. This paper proposes a catalogue of Do's and Don'ts to guide modelers in addressing the many pertinent considerations through the whole modeling cycle. This practical tool provides advice on approaching modeling effectively through adhering to good modeling practice. It emphasizes model choices that align with the model purpose and context, and the justification and documentation of modeling decisions and assumptions. Managing uncertainty is a core consideration. The identification, assessment and reporting of these uncertainties is important across the entire modeling process, which spans problem framing, technical design, implementation and application phases. Such good practices are critical for transparency and reliability of the modeling.</span></span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.envsoft.2026.106893","usgsCitation":"Sun, X., Jakeman, A.J., Hamilton, S.H., Grimm, V., Hunt, R.J., El Sawah, S., Wang, H., Croke, B., and Chen, M., 2026, A catalogue of Do's and Don'ts in the modeling of environmental systems: Environmental Modelling and Software, v. 198, 106893, 13 p., https://doi.org/10.1016/j.envsoft.2026.106893.","productDescription":"106893, 13 p.","ipdsId":"IP-176780","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":500725,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"198","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Sun, Xifu","contributorId":367094,"corporation":false,"usgs":false,"family":"Sun","given":"Xifu","affiliations":[{"id":27305,"text":"Australia National University","active":true,"usgs":false}],"preferred":false,"id":956745,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jakeman, Anthony J. 0000-0001-5282-2215","orcid":"https://orcid.org/0000-0001-5282-2215","contributorId":173848,"corporation":false,"usgs":false,"family":"Jakeman","given":"Anthony","email":"","middleInitial":"J.","affiliations":[{"id":17939,"text":"The Australian National University","active":true,"usgs":false}],"preferred":false,"id":956746,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hamilton, Serena H","contributorId":248834,"corporation":false,"usgs":false,"family":"Hamilton","given":"Serena","email":"","middleInitial":"H","affiliations":[{"id":50035,"text":"School of Science, Edith Cowan University, Joondalup, WA, Australia","active":true,"usgs":false}],"preferred":false,"id":956772,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Grimm, Volker","contributorId":224014,"corporation":false,"usgs":false,"family":"Grimm","given":"Volker","affiliations":[{"id":26949,"text":"Helmholtz Centre for Environmental Research, Germany","active":true,"usgs":false}],"preferred":false,"id":956773,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hunt, Randall J. 0000-0001-6465-9304 rjhunt@usgs.gov","orcid":"https://orcid.org/0000-0001-6465-9304","contributorId":214444,"corporation":false,"usgs":true,"family":"Hunt","given":"Randall","email":"rjhunt@usgs.gov","middleInitial":"J.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":956748,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"El Sawah, Sondoss","contributorId":367096,"corporation":false,"usgs":false,"family":"El Sawah","given":"Sondoss","affiliations":[{"id":87548,"text":"University of New South Wales Canberra","active":true,"usgs":false}],"preferred":false,"id":956749,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Wang, Hsiao-Hsuan","contributorId":349683,"corporation":false,"usgs":false,"family":"Wang","given":"Hsiao-Hsuan","affiliations":[{"id":6747,"text":"Texas A&M University","active":true,"usgs":false}],"preferred":false,"id":956750,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Croke, Barry 0000-0001-9216-1554","orcid":"https://orcid.org/0000-0001-9216-1554","contributorId":248856,"corporation":false,"usgs":false,"family":"Croke","given":"Barry","email":"","affiliations":[{"id":27305,"text":"Australia National University","active":true,"usgs":false}],"preferred":false,"id":956747,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Chen, Min","contributorId":330043,"corporation":false,"usgs":false,"family":"Chen","given":"Min","affiliations":[{"id":78773,"text":"University of Wisconsin-Madison, Wisconsin, USA","active":true,"usgs":false}],"preferred":false,"id":956751,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70273920,"text":"70273920 - 2026 - Earthquake-hazard exposure of residents with potential access and functional needs in the United States","interactions":[],"lastModifiedDate":"2026-02-17T17:31:14.852","indexId":"70273920","displayToPublicDate":"2026-01-23T11:24:56","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2036,"text":"International Journal of Disaster Risk Reduction","active":true,"publicationSubtype":{"id":10}},"title":"Earthquake-hazard exposure of residents with potential access and functional needs in the United States","docAbstract":"<p><span>Earthquake response plans and earthquake early warning (EEW) systems designed for general populations may not consider potential access and functional needs (AFN) of individuals with physical, sensory, cognitive, or social limitations. Previous efforts to map the distribution of these populations have focused on social-vulnerability indices that ignore or oversimply these limitations. The descriptive and exploratory analysis summarized in this United States (U.S.) case study addresses this gap by identifying and integrating spatially explicit data for AFN-related residential populations, earthquake hazards, and county and county equivalents for the conterminous U.S., Alaska, Puerto Rico, and Hawaii. We focus on 13 AFN-related attributes that relate to an individual's ability to access information contained in an EEW alert, to understand and process earthquake information or observed ground shaking, and to take self-protective actions based on this information and physical cues of an earthquake. Depending on the demographic attribute, there are millions to tens of millions of U.S. residents with AFN-related attributes in areas considered to have varying likelihoods (2%, 10%, and 50%) of exceedance of a damaging earthquake in the next 50 years. Although these amounts represent low percentages at the national level, the percentage of individuals with AFN-related attributes in many counties and county equivalents substantially exceeds national percentages. No one county, county equivalent, U.S. state, or U.S. territory has the highest percentage of individuals in all AFN-related attributes; therefore, future efforts to increase individual resilience to earthquakes may benefit from understanding the local context of individuals with potential access and functional needs.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.ijdrr.2026.106002","usgsCitation":"Wood, N.J., Pennaz, A., and Jones, J.M., 2026, Earthquake-hazard exposure of residents with potential access and functional needs in the United States: International Journal of Disaster Risk Reduction, v. 134, 106002, 20 p., https://doi.org/10.1016/j.ijdrr.2026.106002.","productDescription":"106002, 20 p.","ipdsId":"IP-183630","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":500248,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index 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nwood@usgs.gov","orcid":"https://orcid.org/0000-0002-6060-9729","contributorId":3347,"corporation":false,"usgs":true,"family":"Wood","given":"Nathan","email":"nwood@usgs.gov","middleInitial":"J.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":955761,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pennaz, Alice 0000-0002-7336-2761","orcid":"https://orcid.org/0000-0002-7336-2761","contributorId":205792,"corporation":false,"usgs":true,"family":"Pennaz","given":"Alice","email":"","affiliations":[{"id":508,"text":"Office of the AD Hazards","active":true,"usgs":true}],"preferred":true,"id":955762,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jones, Jeanne M. 0000-0001-7549-9270 jmjones@usgs.gov","orcid":"https://orcid.org/0000-0001-7549-9270","contributorId":4676,"corporation":false,"usgs":true,"family":"Jones","given":"Jeanne","email":"jmjones@usgs.gov","middleInitial":"M.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":955763,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70274011,"text":"70274011 - 2026 - A conceptual framework and methods for studying the connectivity of fishes","interactions":[],"lastModifiedDate":"2026-02-20T18:07:26.098266","indexId":"70274011","displayToPublicDate":"2026-01-23T10:58:09","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1652,"text":"Fish and Fisheries","active":true,"publicationSubtype":{"id":10}},"title":"A conceptual framework and methods for studying the connectivity of fishes","docAbstract":"<p><span id=\"_mce_caret\" data-mce-bogus=\"1\" data-mce-type=\"format-caret\"><span>Connectivity is a multifaceted concept that has important implications for the management and conservation of marine and freshwater fishes. We developed a conceptual framework that encompasses multiple, interrelated categories of connectedness, including landscape (e.g., structural, functional) connectivity and ecological (e.g., trophic, genetic, demographic) connectivity, that together shape the flow of organisms, energy and information across ecosystems. We also synthesised six key methods that can be used to study connectivity of fishes: (1) telemetry, including satellite, acoustic, radio and passive integrated transponders (PIT), (2) mark-recapture, (3) environmental tracers, including stable isotopes and otolith-microchemistry, (4) genetics, (5) community structure analysis and (6) emerging technologies and tools (e.g., remote sensing and artificial intelligence). For each method, we describe the categories of connectivity it can assess and provide real-world examples where they have been effectively used. We also identify limitations of each method. This article highlights the diverse and evolving toolbox of methods used to assess fish connectivity, underscoring the need for continued collaboration, innovation and integration of new approaches to refine our understanding and address remaining challenges in this critical area of aquatic ecology and fisheries management.</span></span></p>","language":"English","publisher":"Wiley","doi":"10.1111/faf.70058","usgsCitation":"Bergman, J.N., Robichaud, J.A., McCutcheon, J., Booth, M., Campbell, B., Casselberry, G.A., Cooper, C.R., Gillanders, B.M., Griffin, L.P., Hale, E., LaRochelle, L., Murchie, K.J., Peacock, M.M., Swanson, R.G., Stewart, S.D., Woodland, R.J., Zielinski, D.P., Cooke, S.J., Piczak, M.L., 2026, A conceptual framework and methods for studying the connectivity of fishes: Fish and Fisheries, v. 27, no. 2, p. 342-369, https://doi.org/10.1111/faf.70058.","productDescription":"28 p.","startPage":"342","endPage":"369","ipdsId":"IP-179238","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":500358,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"27","issue":"2","noUsgsAuthors":false,"publicationDate":"2026-01-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Bergman, Jordanna N.","contributorId":366642,"corporation":false,"usgs":false,"family":"Bergman","given":"Jordanna","middleInitial":"N.","affiliations":[{"id":17786,"text":"Carleton University","active":true,"usgs":false}],"preferred":false,"id":956120,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Robichaud, Jessica A.","contributorId":366643,"corporation":false,"usgs":false,"family":"Robichaud","given":"Jessica","middleInitial":"A.","affiliations":[{"id":17786,"text":"Carleton University","active":true,"usgs":false}],"preferred":false,"id":956121,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McCutcheon, Jasper","contributorId":366644,"corporation":false,"usgs":false,"family":"McCutcheon","given":"Jasper","affiliations":[{"id":87500,"text":"Ellensburg, Washington","active":true,"usgs":false}],"preferred":false,"id":956122,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Booth, Michael Thomas 0000-0002-9842-085X","orcid":"https://orcid.org/0000-0002-9842-085X","contributorId":357011,"corporation":false,"usgs":true,"family":"Booth","given":"Michael Thomas","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":956123,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Campbell, Brendan","contributorId":366645,"corporation":false,"usgs":false,"family":"Campbell","given":"Brendan","affiliations":[{"id":87501,"text":"University of  Delaware","active":true,"usgs":false}],"preferred":false,"id":956124,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Casselberry, Grace A.","contributorId":366646,"corporation":false,"usgs":false,"family":"Casselberry","given":"Grace","middleInitial":"A.","affiliations":[{"id":34616,"text":"University of Massachusetts Amherst","active":true,"usgs":false}],"preferred":false,"id":956125,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Cooper, Cienna R.","contributorId":366647,"corporation":false,"usgs":false,"family":"Cooper","given":"Cienna","middleInitial":"R.","affiliations":[{"id":36331,"text":"Texas Tech University","active":true,"usgs":false}],"preferred":false,"id":956126,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Gillanders, Bronwyn M.","contributorId":366648,"corporation":false,"usgs":false,"family":"Gillanders","given":"Bronwyn","middleInitial":"M.","affiliations":[{"id":36897,"text":"University of Adelaide","active":true,"usgs":false}],"preferred":false,"id":956127,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Griffin, Lucas P.","contributorId":366649,"corporation":false,"usgs":false,"family":"Griffin","given":"Lucas","middleInitial":"P.","affiliations":[{"id":7163,"text":"University of South Florida","active":true,"usgs":false}],"preferred":false,"id":956128,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Hale, Edward","contributorId":291609,"corporation":false,"usgs":false,"family":"Hale","given":"Edward","email":"","affiliations":[{"id":13359,"text":"University of Delaware","active":true,"usgs":false}],"preferred":false,"id":956129,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"LaRochelle, Luc","contributorId":366650,"corporation":false,"usgs":false,"family":"LaRochelle","given":"Luc","affiliations":[{"id":17786,"text":"Carleton University","active":true,"usgs":false}],"preferred":false,"id":956130,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Murchie, Karen J.","contributorId":366651,"corporation":false,"usgs":false,"family":"Murchie","given":"Karen","middleInitial":"J.","affiliations":[{"id":87193,"text":"John G. Shedd Aquarium","active":true,"usgs":false}],"preferred":false,"id":956131,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Peacock, Mary M.","contributorId":167605,"corporation":false,"usgs":false,"family":"Peacock","given":"Mary","email":"","middleInitial":"M.","affiliations":[{"id":24774,"text":"Department of Natural Resources, College of Agriculture and Life","active":true,"usgs":false}],"preferred":false,"id":956132,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Swanson, Reid G.","contributorId":366653,"corporation":false,"usgs":false,"family":"Swanson","given":"Reid","middleInitial":"G.","affiliations":[{"id":7019,"text":"Great Lakes Fishery Commission","active":true,"usgs":false}],"preferred":false,"id":956133,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Stewart, Simon D.","contributorId":366655,"corporation":false,"usgs":false,"family":"Stewart","given":"Simon","middleInitial":"D.","affiliations":[{"id":82905,"text":"Cawthron Institute","active":true,"usgs":false}],"preferred":false,"id":956134,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Woodland, Ryan. J.","contributorId":366656,"corporation":false,"usgs":false,"family":"Woodland","given":"Ryan.","middleInitial":"J.","affiliations":[{"id":7083,"text":"University of Maryland","active":true,"usgs":false}],"preferred":false,"id":956135,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Zielinski, Daniel P.","contributorId":366657,"corporation":false,"usgs":false,"family":"Zielinski","given":"Daniel","middleInitial":"P.","affiliations":[{"id":7019,"text":"Great Lakes Fishery Commission","active":true,"usgs":false}],"preferred":false,"id":956136,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Cooke, Steven J.","contributorId":366658,"corporation":false,"usgs":false,"family":"Cooke","given":"Steven","middleInitial":"J.","affiliations":[{"id":17786,"text":"Carleton University","active":true,"usgs":false}],"preferred":false,"id":956137,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Piczak, Morgan L.","contributorId":366659,"corporation":false,"usgs":false,"family":"Piczak","given":"Morgan","middleInitial":"L.","affiliations":[{"id":24650,"text":"Dalhousie University","active":true,"usgs":false}],"preferred":false,"id":956138,"contributorType":{"id":1,"text":"Authors"},"rank":19}]}}
,{"id":70274536,"text":"70274536 - 2026 - Extreme Potomac floods at Washington D.C. during the past 500 years","interactions":[],"lastModifiedDate":"2026-03-31T15:13:33.863387","indexId":"70274536","displayToPublicDate":"2026-01-23T10:08:43","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Extreme Potomac floods at Washington D.C. during the past 500 years","docAbstract":"<p><span>Washington D.C. faces one of the highest 100-year flood risks of any major city along the U.S. East Coast. In addition to storm-surge inundation during hurricanes and nor'easters, water-level observations for Washington are strongly skewed by major floods on the Potomac River. Using geologic and historic records we find new evidence for ice-jam flooding at Georgetown during the Little Ice Age, as recently as 1784, that was up to ∼2x the magnitude of the largest events of the past hundred years (1936, 1942). Over the 19th century (a) human modifications to the Potomac estuary as well as (b) increasingly heavy rainfall and (c) land-clearance in the watershed may have contributed to increasingly frequent large floods at Washington. Early surveys of the U.S. Capitol Building and other local landmarks also suggest sea level on the Potomac estuary at Washington has risen by upwards of 0.7&nbsp;m (2.2&nbsp;ft) since the 1790s.</span></p>","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2025GL118329","usgsCitation":"Toomey, M., Cronin, T.M., Rodysill, J.R., Seidenstein, J.L., and Willard, D., 2026, Extreme Potomac floods at Washington D.C. during the past 500 years: Geophysical Research Letters, v. 53, no. 2, e2025GL118329, 10 p., https://doi.org/10.1029/2025GL118329.","productDescription":"e2025GL118329, 10 p.","ipdsId":"IP-171642","costCenters":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":502073,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2025gl118329","text":"Publisher Index Page"},{"id":501861,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Maryland, Virginia","city":"WAshington D.C.","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -77.12661486872723,\n              38.949829500116806\n            ],\n            [\n              -77.12661486872723,\n              38.764446761388854\n            ],\n            [\n              -76.97381536652976,\n              38.764446761388854\n            ],\n            [\n              -76.97381536652976,\n              38.949829500116806\n            ],\n            [\n              -77.12661486872723,\n              38.949829500116806\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"53","issue":"2","noUsgsAuthors":false,"publicationDate":"2026-01-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Toomey, Michael 0000-0003-0167-9273 mtoomey@usgs.gov","orcid":"https://orcid.org/0000-0003-0167-9273","contributorId":184097,"corporation":false,"usgs":true,"family":"Toomey","given":"Michael","email":"mtoomey@usgs.gov","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":958149,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cronin, Thomas M. 0000-0002-2643-0979 tcronin@usgs.gov","orcid":"https://orcid.org/0000-0002-2643-0979","contributorId":2579,"corporation":false,"usgs":true,"family":"Cronin","given":"Thomas","email":"tcronin@usgs.gov","middleInitial":"M.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":958150,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rodysill, Jessica R. 0000-0002-3602-7227 jrodysill@usgs.gov","orcid":"https://orcid.org/0000-0002-3602-7227","contributorId":207577,"corporation":false,"usgs":true,"family":"Rodysill","given":"Jessica","email":"jrodysill@usgs.gov","middleInitial":"R.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":958151,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Seidenstein, Julia Lynn 0000-0002-0585-1977","orcid":"https://orcid.org/0000-0002-0585-1977","contributorId":290625,"corporation":false,"usgs":true,"family":"Seidenstein","given":"Julia","email":"","middleInitial":"Lynn","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":958152,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Willard, Debra A. 0000-0003-4878-0942","orcid":"https://orcid.org/0000-0003-4878-0942","contributorId":269840,"corporation":false,"usgs":true,"family":"Willard","given":"Debra A.","affiliations":[],"preferred":true,"id":958153,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70273793,"text":"70273793 - 2026 - Per- and polyfluoroalkyl substances (PFAS) and other contaminants of concern in tribal waters of Montana","interactions":[],"lastModifiedDate":"2026-03-10T13:50:38.007055","indexId":"70273793","displayToPublicDate":"2026-01-23T08:48:08","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":9161,"text":"Environmental Science: Processes & Impacts","active":true,"publicationSubtype":{"id":10}},"title":"Per- and polyfluoroalkyl substances (PFAS) and other contaminants of concern in tribal waters of Montana","docAbstract":"<p><span id=\"_mce_caret\" data-mce-bogus=\"1\" data-mce-type=\"format-caret\"><span>We assessed potential exposures to a broad suite of contaminants (inorganic, organic and microbial) in culturally important surface waters from three watersheds in a northern plains Native American community (Apsáalooke [Crow Tribe of Montana]) in south-central Montana, United States, with water insecurity concerns. Inorganic (37), organic (435) and microbial (3) constituents were assessed in 12 surface water sites from the Pryor Creek (</span><i>n</i><span>&nbsp;= 2), Bighorn River (</span><i>n</i><span>&nbsp;= 2) and Little Bighorn River (</span><i>n</i><span>&nbsp;= 8) valleys. Twenty-six organics, 33 inorganics and&nbsp;</span><i>Escherichia coli</i><span>&nbsp;were detected. Despite relatively low concentrations in surface waters within the Crow Reservation, mixture toxicity indicated prevalent chronic ecological effects and human-health secondary contact (recreation) effects at multiple sites. Further, to address Tribal concerns over the prevalence and corresponding risks of per- and polyfluoroalkyl substances (PFAS), we sampled water, sediment, biofilms and fish at a limited number of locations in the Little Bighorn River. Results indicated that PFAS were prevalent in fish tissues, including whole blood and filets, and to a lesser extent in biofilms, despite few detections in water and sediment samples. This is the first attempt to document environmental PFAS contamination within the reservation and the potential human-health concerns for the general population from consumption of recreational/subsistence fish. Overall, this effort provided preliminary information on the contaminant mixtures present and their potential health implications, which can support the protection of community health and culturally meaningful resources across the Crow Reservation.</span></span></p>","language":"English","publisher":"Royal Society of Chemistry","doi":"10.1039/d5em00565e","usgsCitation":"Smalling, K., Bradley, P., Romanok, K., Doyle, J.T., Eggers, M.J., Martin, C., Barnhart, E.P., Binette, P., Castro, E.M., Chavez, M., Ewing, S.A., Gordon, S.E., Fields, M.W., Gray, J.L., Groshong, A.M., Hwang, C., Kanagy, L.K., LaFrance, J.W., Loftin, K., Long, C.M., McCleskey, R., Meppelink, S.M., Richards, C.L., Schreiner, M., Shikany, J.I., and Tesfamariam, M., 2026, Per- and polyfluoroalkyl substances (PFAS) and other contaminants of concern in tribal waters of Montana: Environmental Science: Processes & Impacts, v. 28, p. 579-597, https://doi.org/10.1039/d5em00565e.","productDescription":"19 p.; Data 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,{"id":70273771,"text":"70273771 - 2026 - Surface variable‐based machine learning for scalable arsenic prediction in undersampled areas","interactions":[],"lastModifiedDate":"2026-01-28T15:44:10.069314","indexId":"70273771","displayToPublicDate":"2026-01-23T08:36:18","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":16135,"text":"GeoHealth","active":true,"publicationSubtype":{"id":10}},"title":"Surface variable‐based machine learning for scalable arsenic prediction in undersampled areas","docAbstract":"<p><span id=\"_mce_caret\" data-mce-bogus=\"1\" data-mce-type=\"format-caret\"><span>In the United States, private wells are not federally regulated, and many households do not test for Arsenic (As). Chronic exposure is linked with multiple health outcomes, and risk can change sharply over short distances and with well depth. Coarse maps or sparse sampling often miss exceedances. Most existing models operate at ∼1&nbsp;km resolution and use groundwater chemistry or detailed geologic logs, which limits their use in undersampled areas where improved guidance is most needed. We overcome these limitations by developing a machine learning model for Minnesota, USA, that predicts As exposure risk using only surficial variables from remote sensing and global data sets. Variables related to surface water hydrology and geomorphology are selected based on mechanistic links that control redox conditions and As mobilization. Local training was essential, and surficial geology variables that are more sensitive to local conditions were needed to maximize model accuracy. The resulting complete model was sufficiently sensitive to generate accurate and detailed risk maps and depth profiles of As concentrations above the 10&nbsp;μg/L maximum contaminant level. Accuracy depended on local training data density. We identified a training data density of 0.07 wells/km</span><sup>2</sup><span>&nbsp;as a practical target for stable county-level performance. Maps of exceedance probabilities highlight priority areas for testing that are particularly important in rural communities that have received less sampling. These results support public health action by guiding where to install wells and where to test them, how much new sampling is needed, and where treatment outreach is most urgent.</span></span></p>","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2025GH001666","usgsCitation":"Azad, S., Stahl, M.O., Erickson, M., DeYoung, B.A., Connolly, C.T., Chillrud, L., Schilling, K., Navas-Acien, A., Basu, A., Mailloux, B., Bostick, B.C., and Chillrud, S.N., 2026, Surface variable‐based machine learning for scalable arsenic prediction in undersampled areas: GeoHealth, v. 10, no. 1, e2025GH001666, 18 p., https://doi.org/10.1029/2025GH001666.","productDescription":"e2025GH001666, 18 p.","ipdsId":"IP-177700","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":499326,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2025gh001666","text":"Publisher Index 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,{"id":70273825,"text":"70273825 - 2026 - Waterfowl move less in heterogeneous and human-populated landscapes, with implications for spread of avian influenza viruses","interactions":[],"lastModifiedDate":"2026-02-05T14:59:54.617144","indexId":"70273825","displayToPublicDate":"2026-01-23T07:46:00","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1466,"text":"Ecology Letters","active":true,"publicationSubtype":{"id":10}},"title":"Waterfowl move less in heterogeneous and human-populated landscapes, with implications for spread of avian influenza viruses","docAbstract":"<p><span id=\"_mce_caret\" data-mce-bogus=\"1\" data-mce-type=\"format-caret\"><span>Animal movements contribute to the spread of infectious diseases and are driven in part by environmental conditions. We investigated the links among the environment, animal movement, and infectious disease dynamics in waterfowl, which are among the primary wildlife hosts of avian influenza viruses. By combining telemetry data on 4606 individuals from 26 waterfowl species with data on land cover, weather, and vegetation, we found that waterfowl moved less in areas of higher land cover heterogeneity and higher human population density. Moreover, predicted waterfowl movement distances were weakly but positively correlated with distances between detections of H5N1 highly pathogenic avian influenza in wild waterfowl, suggesting that environmental conditions might contribute to the spread of this disease via their effects on bird movements. By considering wildlife movements alongside other drivers of infectious disease dynamics, such as livestock production and human mobility, we move closer to predicting outbreaks and informing interventions.</span></span></p>","language":"English","publisher":"Wiley","doi":"10.1111/ele.70265","usgsCitation":"Teitelbaum, C.S., Prosser, D.J., Ackerman, J.T., Ahmed, S., Alam, A., Azmiri, K.Z., Batbayar, N., Bêty, J., Blake-Bradshaw, A., Boiko, D., Buitendijk, N.H., Buler, J.J., Cabot, D., Casazza, M.L., Cohen, B.S., Davaasuren, B., Farau, S., Feddersen, J., Fieberg, J.R., Fiedler, W., Glazov, P., Griffin, L.R., Guillemain, M., Hagy, H., Hardy, M.J., Highway, C., Hoffman, D., Kang, T., Keever, A., Kilburn, J., Kölzsch, A., Kruckenberg, H., Laaksonen, T., Ladman, B.S., Lee, H., Lee, S., Lefebvre, J., Legagneux, P., Linssen, H., Madsen, J., Masto, N.M., McWilliams, S.R., Mezebish Quinn, T., Mitchell, C., Moreau, A., Müskens, G., Newman, S., Nolet, B.A., Nuijten, R.J., Osenkowski, J., Overton, C.T., Piironen, A., Plaquin, B., Ramey, A.M., Rodrigue, J., Rodrigues, D., Schreven, K.H., Si, Y., Sullivan, J.D., Takekawa, J., Thomas, P.J., van Toor, M., Waldenström, J., Williams, C.K., Wolfson, D.W., Xu, F., Brosnan, I.G., and De La Cruz, S.E., 2026, Waterfowl move less in heterogeneous and human-populated landscapes, with implications for spread of avian influenza viruses: Ecology Letters, v. 29, no. 1, e70265, 13 p., https://doi.org/10.1111/ele.70265.","productDescription":"e70265, 13 p.","ipdsId":"IP-172843","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":499627,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/ele.70265","text":"Publisher Index Page"},{"id":499578,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"29","issue":"1","noUsgsAuthors":false,"publicationDate":"2026-01-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Teitelbaum, Claire Stewart 0000-0001-5646-3184","orcid":"https://orcid.org/0000-0001-5646-3184","contributorId":295336,"corporation":false,"usgs":true,"family":"Teitelbaum","given":"Claire","email":"","middleInitial":"Stewart","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":955035,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Prosser, Diann J. 0000-0002-5251-1799","orcid":"https://orcid.org/0000-0002-5251-1799","contributorId":221167,"corporation":false,"usgs":true,"family":"Prosser","given":"Diann","middleInitial":"J.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":955036,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ackerman, Joshua T. 0000-0002-3074-8322","orcid":"https://orcid.org/0000-0002-3074-8322","contributorId":202848,"corporation":false,"usgs":true,"family":"Ackerman","given":"Joshua","middleInitial":"T.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":955037,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ahmed, Sakib 0009-0004-1626-3427","orcid":"https://orcid.org/0009-0004-1626-3427","contributorId":365949,"corporation":false,"usgs":false,"family":"Ahmed","given":"Sakib","affiliations":[{"id":87279,"text":"International Union for Conservation of Nature, IUCN, Bangladesh Country Office","active":true,"usgs":false}],"preferred":false,"id":955038,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Alam, A.B.M. 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,{"id":70273715,"text":"70273715 - 2026 - Assessing the influence of conservation implementation on water quality during surface runoff events at edge-of-field monitoring sites located in the Laurentian Great Lakes basin","interactions":[],"lastModifiedDate":"2026-02-24T16:44:43.536327","indexId":"70273715","displayToPublicDate":"2026-01-23T07:45:06","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2456,"text":"Journal of Soil and Water Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Assessing the influence of conservation implementation on water quality during surface runoff events at edge-of-field monitoring sites located in the Laurentian Great Lakes basin","docAbstract":"<p><span id=\"_mce_caret\" data-mce-bogus=\"1\" data-mce-type=\"format-caret\"><span>The Laurentian Great Lakes are a vital freshwater resource in the United States, and nonpoint source (NPS) nutrient pollution, specifically phosphorus (P) and nitrogen (N), from agricultural land use continues to negatively impact water quality throughout the Great Lakes basin. One focus of the Great Lakes Restoration Initiative (GLRI), a mechanism to coordinate conservation efforts in the Great Lakes that began in 2010, is reducing NPS nutrient pollution through the implementation of conservation practices in priority watersheds (Genesee River, Fox River, Maumee River, and Saginaw River). As part of GLRI efforts, the objective of the study presented here was to evaluate the effects of conservation implementation, specifically increasing vegetative cover on fields and in primary flowpaths through perennial or cover crop planting and grassed waterways, on surface-runoff water quality at 12 agricultural fields (six paired and six unpaired) located in priority watersheds. We determined the percentage difference in mean event response variables between the periods before and after conservation implementation at individual sites, describing patterns across sites to synthesize lessons learned from these GLRI evaluations. Generally, we found that mean event flow-weighted concentration (FWC) and yield (kilograms per hectare) decreased for suspended sediment (SS) and nitrate (NO</span><sub>3</sub><sup>–</sup><span>-N) across many sites. Mean event FWC and yield for total P (TP) showed mixed results across sites, while mean event FWC and yield for orthophosphate generally increased across sites. These results indicate that perennial or cover crop planting and grassed waterways effectively reduce SS and NO</span><sub>3</sub><sup>–</sup><span>-N losses in surface runoff from agricultural fields, but mitigating TP and dissolved P losses remains a challenge.</span></span></p>","language":"English","publisher":"Journal of Soil and Water Conservation","doi":"10.1080/00224561.2025.2582435","usgsCitation":"Hanrahan, B., Diebel, M.W., Carvin, R.B., Dobrowolski, E.G., Hardebeck, M.J., Kowalczk, A., Toussant, C.A., and Komiskey, M.J., 2026, Assessing the influence of conservation implementation on water quality during surface runoff events at edge-of-field monitoring sites located in the Laurentian Great Lakes basin: Journal of Soil and Water Conservation, 25 p., https://doi.org/10.1080/00224561.2025.2582435.","productDescription":"25 p.","startPage":"654","endPage":"678","ipdsId":"IP-171260","costCenters":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"links":[{"id":499313,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1080/00224561.2025.2582435","text":"Publisher Index Page"},{"id":499010,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","otherGeospatial":"Laurentian Great Lakes basin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -90.29541668230794,\n              48.53215636260879\n            ],\n            [\n              -92.82981221322987,\n              46.303408761612985\n            ],\n            [\n              -90.12674309798746,\n              45.1199073824632\n            ],\n            [\n              -88.44380886375637,\n              41.60729883894802\n 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0000-0001-7778-4841 rbcarvin@usgs.gov","orcid":"https://orcid.org/0000-0001-7778-4841","contributorId":201609,"corporation":false,"usgs":true,"family":"Carvin","given":"Rebecca","email":"rbcarvin@usgs.gov","middleInitial":"B.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":954411,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dobrowolski, Edward G. 0000-0001-9840-4609 edobrowo@usgs.gov","orcid":"https://orcid.org/0000-0001-9840-4609","contributorId":5555,"corporation":false,"usgs":true,"family":"Dobrowolski","given":"Edward","email":"edobrowo@usgs.gov","middleInitial":"G.","affiliations":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true},{"id":346,"text":"Indiana Water Science Center","active":true,"usgs":true},{"id":27231,"text":"Indiana-Kentucky Water Science Center","active":true,"usgs":true}],"preferred":true,"id":954413,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hardebeck, Matthew John 0000-0002-9921-6113","orcid":"https://orcid.org/0000-0002-9921-6113","contributorId":236881,"corporation":false,"usgs":true,"family":"Hardebeck","given":"Matthew","email":"","middleInitial":"John","affiliations":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":954414,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kowalczk, Andrew Jason 0000-0003-0263-0156","orcid":"https://orcid.org/0000-0003-0263-0156","contributorId":329613,"corporation":false,"usgs":true,"family":"Kowalczk","given":"Andrew Jason","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":954416,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Toussant, Chad A. 0000-0002-1324-0914","orcid":"https://orcid.org/0000-0002-1324-0914","contributorId":210079,"corporation":false,"usgs":true,"family":"Toussant","given":"Chad","middleInitial":"A.","affiliations":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":954417,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Komiskey, Matthew J. 0000-0003-2962-6974 mjkomisk@usgs.gov","orcid":"https://orcid.org/0000-0003-2962-6974","contributorId":1776,"corporation":false,"usgs":true,"family":"Komiskey","given":"Matthew","email":"mjkomisk@usgs.gov","middleInitial":"J.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":954415,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70273774,"text":"70273774 - 2026 - Strength of depensation not influenced by fish population productivity","interactions":[],"lastModifiedDate":"2026-01-28T16:17:13.025728","indexId":"70273774","displayToPublicDate":"2026-01-22T10:11:49","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1661,"text":"Fisheries Research","active":true,"publicationSubtype":{"id":10}},"title":"Strength of depensation not influenced by fish population productivity","docAbstract":"<p><span>A long-held assumption in the management of exploited fisheries is that fish populations will compensate with increased recruit survival to replenish the population when adult stock size is reduced through harvest. Observations of depensatory recruitment (reduced recruit survival at low adult stock size) and critical depensatory thresholds have challenged the compensation assumption. Post et al. (2002) postulated that critical depensatory thresholds were related to fish population productivity. Walleye&nbsp;</span><i>Sander vitreus</i><span>&nbsp;are a culturally, economically, and recreationally important sportfish whose persistence is being challenged by natural recruitment declines throughout much of its native range. Depensation, among other abiotic and biotic stressors, has been implicated in walleye natural recruitment declines. If walleye population productivity is related to critical depensatory thresholds, then population productivity benchmarks could be established to reduce the probability of crossing them. We used empirically-derived and model predicted depensation values (</span><i>q</i><span>) and empirical estimates of walleye population productivity to test for relationships between these variables in northern Wisconsin lakes. We found little evidence for a relationship between&nbsp;</span><i>q</i><span>&nbsp;and walleye population productivity across all lakes examined. Our finding failed to support the theoretical postulation of a relationship between these variables by Post et al. (2002) for walleye. Little evidence for a relationship between&nbsp;</span><i>q</i><span>&nbsp;and population productivity suggests that depensatory thresholds may differ among individual walleye populations and that walleye populations may transition abruptly between compensatory and depensatory states. Given our findings, conservation efforts for walleye that solely focus on low productivity populations may miss other trends because population productivity may not be considered a broad predictor of crossing a critical depensatory threshold.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.fishres.2026.107665","usgsCitation":"Sass, G.S., Mrnak, J.T., Shaw, S.L., Feiner, Z., Dassow, C.J., Rypel, A.L., and Embke, H., 2026, Strength of depensation not influenced by fish population productivity: Fisheries Research, v. 294, 107665, 8 p., https://doi.org/10.1016/j.fishres.2026.107665.","productDescription":"107665, 8 p.","ipdsId":"IP-177311","costCenters":[{"id":65882,"text":"Midwest Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":499176,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"294","noUsgsAuthors":false,"publicationDate":"2026-01-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Sass, Greg S.","contributorId":365759,"corporation":false,"usgs":false,"family":"Sass","given":"Greg","middleInitial":"S.","affiliations":[{"id":6913,"text":"Wisconsin Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":954740,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mrnak, Joesph T.","contributorId":365760,"corporation":false,"usgs":false,"family":"Mrnak","given":"Joesph","middleInitial":"T.","affiliations":[{"id":24495,"text":"Iowa Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":954741,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shaw, Stephanie L","contributorId":365761,"corporation":false,"usgs":false,"family":"Shaw","given":"Stephanie","middleInitial":"L","affiliations":[{"id":6913,"text":"Wisconsin Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":954742,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Feiner, Zachary S.","contributorId":348857,"corporation":false,"usgs":false,"family":"Feiner","given":"Zachary S.","affiliations":[{"id":16925,"text":"University of Wisconsin-Madison","active":true,"usgs":false}],"preferred":false,"id":954743,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dassow, Colin J.","contributorId":293206,"corporation":false,"usgs":false,"family":"Dassow","given":"Colin","email":"","middleInitial":"J.","affiliations":[{"id":16117,"text":"Wisconsin DNR","active":true,"usgs":false}],"preferred":false,"id":954744,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Rypel, Andrew L.","contributorId":199498,"corporation":false,"usgs":false,"family":"Rypel","given":"Andrew","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":954745,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Embke, Holly Susan 0000-0002-9897-7068","orcid":"https://orcid.org/0000-0002-9897-7068","contributorId":358337,"corporation":false,"usgs":true,"family":"Embke","given":"Holly Susan","affiliations":[{"id":65882,"text":"Midwest Climate Adaptation Science Center","active":true,"usgs":true}],"preferred":true,"id":954746,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70273773,"text":"70273773 - 2026 - Mountain goat declines in a protected, interior, native population","interactions":[],"lastModifiedDate":"2026-01-28T15:42:30.936097","indexId":"70273773","displayToPublicDate":"2026-01-22T09:37:07","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Mountain goat declines in a protected, interior, native population","docAbstract":"<p><span>A shifting climate poses threats to alpine-adapted species including mountain goats. We used long-term (12 years) citizen science monitoring data and Bayesian N-mixture modeling to estimate population trends and drivers of population metrics among mountain goats in Glacier National Park (GNP). Median goats per site (</span><i>n</i><span> = 37 sites) declined by 45% (95% credible interval [CRI] = 32%, 57%) from 77.8 (95% CRI = 64.4, 95.1) in 2008 to 42.3 (95% CRI = 34.3, 52.2) in 2019, with consistent declines from 2008 until 2015, when the number of estimated goats stabilized. The decline exceeds IUCN criteria for classifying a population as vulnerable, &gt;30% declines over only two generations. Across years, relatively few goats occupied northwestern GNP. Goat numbers declined the most at northeastern sites, trended toward decline in most southern sites, and increased at only two west-central sites. The proportion of permanent snow and glaciers, the presence of natural mineral licks, and habituation strongly increased the initial abundance of goats in the area. Weather variables had the greatest influence on population growth rates, particularly precipitation between May 15 and June 15 of the previous summer, the neonatal period. Lower growth occurred with less snow water equivalent and lower mean winter temperature, early summer temperature, and early summer precipitation. Projected reductions of permanent snow, increasing spring and summer temperatures, and insufficient and variable spring precipitation raise concerns for the future of native goats in this region. Our analyses reveal ways to improve detection rates of goats during surveys, which is important for optimizing the precision of estimates and the power to detect future trends. Detection increased with goat habituation, retention of observers with experience, use of binoculars, and conducting surveys at lower temperatures and earlier dates. Improving detection will be particularly important given the lower number of goats currently observed in the park. Research to estimate park-wide population size, evaluate genetic structure and diversity, assess changing habitat, human recreation levels and forage, and forward-project climate effects on persistence will be crucial to understanding the context of these results and conserving this iconic, metapopulation at the southern edge of the distribution of native mountain goats.</span></p>","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.70465","usgsCitation":"Graves, T., Janousek, W.M., Yarnall, M., and Belt, J., 2026, Mountain goat declines in a protected, interior, native population: Ecosphere, v. 17, no. 1, e70465, 17 p., https://doi.org/10.1002/ecs2.70465.","productDescription":"e70465, 17 p.","ipdsId":"IP-128275","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":499325,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.70465","text":"Publisher Index Page"},{"id":499544,"rank":1,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P91GTUL3","text":"USGS data release","linkHelpText":"Mountain goats (Oreamnos americanus) in Glacier National Park, Montana, USA, and Waterton Lakes National Park, Alberta, Canada, 2008-2023"},{"id":499170,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Montana","otherGeospatial":"Glacier National Park","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -113.60080650878787,\n              48.99458864720981\n            ],\n            [\n              -114.48645916591128,\n              49.005131748927084\n            ],\n            [\n              -114.0989861284199,\n              48.45748119419969\n            ],\n            [\n              -113.89364327444952,\n              48.479975245922134\n            ],\n            [\n              -113.55795234795937,\n              48.2165274365571\n            ],\n            [\n              -113.33118241357474,\n              48.30924537874591\n            ],\n            [\n              -113.2169046513653,\n              48.412463176207496\n            ],\n            [\n              -113.40439160499024,\n              48.70318915560594\n            ],\n            [\n              -113.41331955516296,\n              48.74677172670576\n            ],\n            [\n              -113.46867284623328,\n              48.78796372490032\n            ],\n            [\n              -113.59723532871878,\n              48.93362924512738\n            ],\n            [\n              -113.60080650878787,\n              48.99458864720981\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"17","issue":"1","noUsgsAuthors":false,"publicationDate":"2026-01-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Graves, Tabitha A. 0000-0001-5145-2400","orcid":"https://orcid.org/0000-0001-5145-2400","contributorId":202084,"corporation":false,"usgs":true,"family":"Graves","given":"Tabitha A.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":954736,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Janousek, William Michael 0000-0003-3978-1775","orcid":"https://orcid.org/0000-0003-3978-1775","contributorId":237980,"corporation":false,"usgs":true,"family":"Janousek","given":"William","email":"","middleInitial":"Michael","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":954737,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Yarnall, Michael","contributorId":300614,"corporation":false,"usgs":false,"family":"Yarnall","given":"Michael","email":"","affiliations":[{"id":38050,"text":"Contractor","active":true,"usgs":false}],"preferred":false,"id":954738,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Belt, Jami","contributorId":177314,"corporation":false,"usgs":false,"family":"Belt","given":"Jami","affiliations":[],"preferred":false,"id":954739,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70273701,"text":"70273701 - 2026 - Miocene evolution of the Humboldt Current","interactions":[],"lastModifiedDate":"2026-01-23T15:12:43.427537","indexId":"70273701","displayToPublicDate":"2026-01-22T09:04:07","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2996,"text":"Palaeogeography, Palaeoclimatology, Palaeoecology","printIssn":"0031-0182","active":true,"publicationSubtype":{"id":10}},"title":"Miocene evolution of the Humboldt Current","docAbstract":"<p><span>Diatom records from the East Pisco Basin (EPB) of southern Peru and offshore Ocean Drilling Program (ODP) Hole 682&nbsp;A reveal stepwise increases in the primary productivity of the Humboldt Current during the middle and late Miocene. Although diatoms are present back through the late middle Eocene, successively enhanced diatom production occurs during the Miocene in four steps. The first step between 14.2 and 13.8&nbsp;Ma marks the onset of diatom deposition in the Pisco-0 sequence. A second step at ∼12.9&nbsp;Ma coincides with a major drop in global sea level during which diatom deposition ceased in the EPB but continued in ODP 682&nbsp;A as well as in Chile, Ecuador, and Colombia. Beginning at 10.4 to 10.0&nbsp;Ma, a major increase in diatom sedimentation rates in both the EPB and in ODP 682&nbsp;A signals an abrupt intensification of the Humboldt Current productivity, which may be related to the closure of the Central American Seaway to deeper water circulation. A fourth step coincides with the transgressive deposition of the diatom-rich Pisco-2 sequence at 8.4&nbsp;Ma and is enhanced by the onset of the global Late Miocene Biogenic Bloom (8.0–4.5&nbsp;Ma). Between 7 and 6&nbsp;Ma, common subtropical diatoms in ODP 682&nbsp;A contrast with high diatom deposition rates in the EPB, suggesting variable El Niño-La Niña conditions. During this time, fossil vegetation evidence from southern Peru supports the presence of seasonal periods of enhanced rainfall typical of El Niño conditions. The Miocene trend of increasing sea mammal diversity in the EPB parallels these steps, further supporting stepwise enhancement of primary productivity in the Humboldt Current during the Miocene.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.palaeo.2026.113558","usgsCitation":"Barron, J.A., DeVries, T.J., and Coenen, J.J., 2026, Miocene evolution of the Humboldt Current: Palaeogeography, Palaeoclimatology, Palaeoecology, v. 686, 113558, 12 p., https://doi.org/10.1016/j.palaeo.2026.113558.","productDescription":"113558, 12 p.","ipdsId":"IP-180806","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":498990,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Peru","otherGeospatial":"Humboldt Current","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -80.73639910834312,\n              -7.6494563030919664\n            ],\n            [\n              -80.73639910834312,\n              -16.02780933667553\n            ],\n            [\n              -73.96573832460824,\n              -16.02780933667553\n            ],\n            [\n              -73.96573832460824,\n              -7.6494563030919664\n            ],\n            [\n              -80.73639910834312,\n              -7.6494563030919664\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"686","noUsgsAuthors":false,"publicationDate":"2026-01-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Barron, John A. 0000-0002-9309-1145 jbarron@usgs.gov","orcid":"https://orcid.org/0000-0002-9309-1145","contributorId":2222,"corporation":false,"usgs":true,"family":"Barron","given":"John","email":"jbarron@usgs.gov","middleInitial":"A.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":954343,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"DeVries, Thomas J.","contributorId":365487,"corporation":false,"usgs":false,"family":"DeVries","given":"Thomas","middleInitial":"J.","affiliations":[{"id":87141,"text":"Burke Museum, University of Washington","active":true,"usgs":false}],"preferred":false,"id":954344,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Coenen, Jason J.","contributorId":365488,"corporation":false,"usgs":false,"family":"Coenen","given":"Jason","middleInitial":"J.","affiliations":[{"id":16602,"text":"University of Nebraska, Lincoln","active":true,"usgs":false}],"preferred":false,"id":954345,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70273821,"text":"70273821 - 2026 - Best practice guidelines for targeted environmental DNA-based proficiency testing in non-regulatory contexts","interactions":[],"lastModifiedDate":"2026-02-04T15:03:57.733999","indexId":"70273821","displayToPublicDate":"2026-01-22T08:57:02","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5840,"text":"Environmental DNA","active":true,"publicationSubtype":{"id":10}},"title":"Best practice guidelines for targeted environmental DNA-based proficiency testing in non-regulatory contexts","docAbstract":"<p><span>The effective use of environmental DNA (eDNA) tools is contingent on strict adherence to established and validated methods. Differences in eDNA methods and quality assurance protocols may contribute to variability in results. However, quality assurance measures such as proficiency testing can provide independent evaluation of laboratory performance against pre-established test criteria. With this commentary, we discuss how broad implementation of recurring proficiency testing in eDNA laboratories can build decision-maker confidence in eDNA results. It can also create a culture of continuous evaluation and improvement that minimizes error and meets performance requirements to inform the sustainable use&nbsp;or monitoring of natural resources. We provide an overview of proficiency testing across molecular disciplines, review the state of proficiency testing in eDNA applications, and draft a roadmap for the expanded application of proficiency testing informed by best practices for targeted eDNA detection. We suggest that best practice proficiency testing can be conducted by an independent, third-party sample provider. By demonstrating that laboratories are competent and capable of producing reliable results, implementation of proficiency testing best practices should foster confidence in eDNA measurements and its use in decision-making processes. Increased confidence in eDNA methods and a clear expectation of what is considered satisfactory performance are also likely to create more favorable conditions for investments in eDNA-based monitoring.</span></p>","language":"English","publisher":"Wiley","doi":"10.1002/edn3.70189","usgsCitation":"Hunter, M., Sepulveda, A., Gleeson, D.M., Trujillo-Gonzalez, A., Helbing, C., Rees, H.C., Jones-Slobodian, D.N., Miliano, R.C., Minamoto, T., Theroux, S., Villacorta Rath, C., Wilcox, T., Yamanaka, H., and Klymus, K.E., 2026, Best practice guidelines for targeted environmental DNA-based proficiency testing in non-regulatory contexts: Environmental DNA, v. 8, no. 1, e70189, 13 p., https://doi.org/10.1002/edn3.70189.","productDescription":"e70189, 13 p.","ipdsId":"IP-176967","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":499623,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index 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0000-0002-8861-1070","orcid":"https://orcid.org/0000-0002-8861-1070","contributorId":353489,"corporation":false,"usgs":false,"family":"Helbing","given":"Caren C.","affiliations":[{"id":84424,"text":"Department of Biochemistry and Microbiology, University of Victoria, Victoria, British Columbia, Canada","active":true,"usgs":false}],"preferred":false,"id":954947,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Rees, Helen C.","contributorId":365880,"corporation":false,"usgs":false,"family":"Rees","given":"Helen","middleInitial":"C.","affiliations":[{"id":87239,"text":"RSK ADAS Limited","active":true,"usgs":false}],"preferred":false,"id":954948,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Jones-Slobodian, Devin Nicole 0000-0001-9215-2930","orcid":"https://orcid.org/0000-0001-9215-2930","contributorId":305357,"corporation":false,"usgs":true,"family":"Jones-Slobodian","given":"Devin","middleInitial":"Nicole","affiliations":[{"id":481,"text":"Northern Rocky 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Hiroki","contributorId":268327,"corporation":false,"usgs":false,"family":"Yamanaka","given":"Hiroki","email":"","affiliations":[{"id":55627,"text":"Ryukoku University","active":true,"usgs":false}],"preferred":false,"id":954955,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Klymus, Katy E. 0000-0002-8843-6241 kklymus@usgs.gov","orcid":"https://orcid.org/0000-0002-8843-6241","contributorId":5043,"corporation":false,"usgs":true,"family":"Klymus","given":"Katy","email":"kklymus@usgs.gov","middleInitial":"E.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":954956,"contributorType":{"id":1,"text":"Authors"},"rank":14}]}}
,{"id":70274041,"text":"70274041 - 2026 - Remote compositional analyses of space-weathered lunar maria","interactions":[],"lastModifiedDate":"2026-02-20T14:58:36.389731","indexId":"70274041","displayToPublicDate":"2026-01-22T08:55:31","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":17061,"text":"Planetary Science Journal","active":true,"publicationSubtype":{"id":10}},"title":"Remote compositional analyses of space-weathered lunar maria","docAbstract":"<p><span>Visible-to-shortwave infrared (VSWIR) reflectance spectroscopy has revolutionized our understanding of planetary surface compositions. However, space-weathering processes on airless bodies complicate quantitative compositional analyses. Here, we present a framework to isolate the signatures of space weathering in VSWIR spectra of lunar maria by leveraging radiative transfer modeling under the assumptions that (i) a space-weathered target can be expressed as a mixture of fresh and fully space-weathered components and (ii) remaining signatures can be modeled by including agglutinates as an end-member component. We first validate this approach against laboratory spectra of space-weathered Apollo mare soils of known mineral compositions using a probabilistic Markov Chain Monte Carlo implementation of the Hapke radiative transfer model. Second, we illustrate how this approach can be applied to orbital Moon Mineralogy Mapper data. The proposed space-weathering correction workflow for lunar maria could be expanded to other lunar lithologies and applied to existing and future data sets.</span></p>","language":"English","publisher":"IOP Science","doi":"10.3847/PSJ/ae2b57","usgsCitation":"Jung, J., Lapotre, M.G., Milliken, R.E., Minson, S.E., 2026, Remote compositional analyses of space-weathered lunar maria: Planetary Science Journal, v. 7, no. 1, 18, 13 p., https://doi.org/10.3847/PSJ/ae2b57.","productDescription":"18, 13 p.","ipdsId":"IP-183800","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":500824,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3847/psj/ae2b57","text":"Publisher Index Page"},{"id":500336,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"7","issue":"1","noUsgsAuthors":false,"publicationDate":"2026-01-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Jung, Ji-In 0000-0001-8728-7320","orcid":"https://orcid.org/0000-0001-8728-7320","contributorId":366818,"corporation":false,"usgs":false,"family":"Jung","given":"Ji-In","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":956269,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lapotre, Matheiu G. 0000-0001-9941-1552","orcid":"https://orcid.org/0000-0001-9941-1552","contributorId":366819,"corporation":false,"usgs":false,"family":"Lapotre","given":"Matheiu","middleInitial":"G.","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":956270,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Milliken, Ralph E. 0000-0003-3240-4918","orcid":"https://orcid.org/0000-0003-3240-4918","contributorId":366820,"corporation":false,"usgs":false,"family":"Milliken","given":"Ralph","middleInitial":"E.","affiliations":[{"id":16929,"text":"Brown University","active":true,"usgs":false}],"preferred":false,"id":956271,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Minson, Sarah E. 0000-0001-5869-3477 sminson@usgs.gov","orcid":"https://orcid.org/0000-0001-5869-3477","contributorId":5357,"corporation":false,"usgs":true,"family":"Minson","given":"Sarah","email":"sminson@usgs.gov","middleInitial":"E.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":956272,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70273700,"text":"70273700 - 2026 - Compilation of a nationwide river image dataset for identifying river channels and river rapids via deep learning","interactions":[],"lastModifiedDate":"2026-01-26T14:20:22.073435","indexId":"70273700","displayToPublicDate":"2026-01-22T08:44:42","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3250,"text":"Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Compilation of a nationwide river image dataset for identifying river channels and river rapids via deep learning","docAbstract":"<p><span>Remote sensing enables large-scale, image-based assessments of river dynamics, offering new opportunities for hydrological monitoring. We present a publicly available dataset consisting of 281,024 satellite and aerial images of U.S. rivers, constructed using an Application Programming Interface (API) and the U.S. Geological Survey’s National Hydrography Dataset. The dataset includes images, primary keys, and ancillary geospatial information. We use a manually labeled subset of the images to train models for detecting rapids, defined as areas where high velocity and turbulence lead to a wavy, rough, or even broken water surface visible in the imagery. To demonstrate the utility of this dataset, we develop an image segmentation model to identify rivers within images. This model achieved a mean test intersection-over-union (</span><span id=\"MathJax-Element-1-Frame\" class=\"MathJax\" data-mathml=\"&lt;math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot; display=&quot;inline&quot;&gt;&lt;semantics&gt;&lt;mrow&gt;&lt;mi&gt;I&lt;/mi&gt;&lt;mi&gt;o&lt;/mi&gt;&lt;mi&gt;U&lt;/mi&gt;&lt;/mrow&gt;&lt;/semantics&gt;&lt;/math&gt;\"><span id=\"MathJax-Span-1\" class=\"math\"><span><span id=\"MathJax-Span-2\" class=\"mrow\"><span id=\"MathJax-Span-3\" class=\"semantics\"><span id=\"MathJax-Span-4\" class=\"mrow\"><span id=\"MathJax-Span-5\" class=\"mi\">\uD835\uDC3C</span><span id=\"MathJax-Span-6\" class=\"mi\">\uD835\uDC5C</span><span id=\"MathJax-Span-7\" class=\"mi\">\uD835\uDC48</span></span></span></span></span></span></span><span>) of 0.57, with performance rising to an actual&nbsp;</span><span id=\"MathJax-Element-2-Frame\" class=\"MathJax\" data-mathml=\"&lt;math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot; display=&quot;inline&quot;&gt;&lt;semantics&gt;&lt;mrow&gt;&lt;mi&gt;I&lt;/mi&gt;&lt;mi&gt;o&lt;/mi&gt;&lt;mi&gt;U&lt;/mi&gt;&lt;/mrow&gt;&lt;/semantics&gt;&lt;/math&gt;\"><span id=\"MathJax-Span-8\" class=\"math\"><span><span id=\"MathJax-Span-9\" class=\"mrow\"><span id=\"MathJax-Span-10\" class=\"semantics\"><span id=\"MathJax-Span-11\" class=\"mrow\"><span id=\"MathJax-Span-12\" class=\"mi\">\uD835\uDC3C</span><span id=\"MathJax-Span-13\" class=\"mi\">\uD835\uDC5C</span><span id=\"MathJax-Span-14\" class=\"mi\">\uD835\uDC48</span></span></span></span></span></span></span><span>&nbsp;of 0.89 on the subset of predictions with high confidence (predicted&nbsp;</span><span id=\"MathJax-Element-3-Frame\" class=\"MathJax\" data-mathml=\"&lt;math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot; display=&quot;inline&quot;&gt;&lt;semantics&gt;&lt;mrow&gt;&lt;mi&gt;I&lt;/mi&gt;&lt;mi&gt;o&lt;/mi&gt;&lt;mi&gt;U&lt;/mi&gt;&lt;/mrow&gt;&lt;/semantics&gt;&lt;/math&gt;\"><span id=\"MathJax-Span-15\" class=\"math\"><span><span id=\"MathJax-Span-16\" class=\"mrow\"><span id=\"MathJax-Span-17\" class=\"semantics\"><span id=\"MathJax-Span-18\" class=\"mrow\"><span id=\"MathJax-Span-19\" class=\"mi\">\uD835\uDC3C</span><span id=\"MathJax-Span-20\" class=\"mi\">\uD835\uDC5C</span><span id=\"MathJax-Span-21\" class=\"mi\">\uD835\uDC48</span></span></span></span></span></span></span><span>&nbsp;&gt; 0.9). Following this initial segmentation of river channels within the images, we trained several convolutional neural network (CNN) architectures to classify the presence or absence of rapids. Our selected model reached an accuracy and F1 score of 0.93, indicating strong performance for the classification of rapids that could support consistent, efficient inventory and monitoring of rapids. These data provide new resources for recreation planning, habitat assessment, and discharge estimation. Overall, the dataset and tools offer a foundation for scalable, automated identification of geomorphic features to support riverine science and resource management.</span></p>","language":"English","publisher":"MDPI","doi":"10.3390/rs18020375","usgsCitation":"Brimhall, N., Bladen, K.K., Kerby, T., Legleiter, C.J., Swapp, C., Fluckiger, H., Bahr, J.E., Roberts, M., Hart, K., Stegman, C.L., Bean, B., and Moon, K., 2026, Compilation of a nationwide river image dataset for identifying river channels and river rapids via deep learning: Remote Sensing, v. 18, no. 2, 375, 22 p., https://doi.org/10.3390/rs18020375.","productDescription":"375, 22 p.","ipdsId":"IP-182435","costCenters":[{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true}],"links":[{"id":499312,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs18020375","text":"Publisher Index 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0000-0002-4457-9988","orcid":"https://orcid.org/0000-0002-4457-9988","contributorId":365486,"corporation":false,"usgs":false,"family":"Moon","given":"Kevin","affiliations":[{"id":6682,"text":"Utah State University","active":true,"usgs":false}],"preferred":false,"id":954342,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}}
,{"id":70274644,"text":"70274644 - 2026 - Estimating the power of a standardized monitoring program for sportfish in Georgia, USA","interactions":[],"lastModifiedDate":"2026-04-03T13:48:00.723162","indexId":"70274644","displayToPublicDate":"2026-01-22T08:26:25","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2886,"text":"North American Journal of Fisheries Management","active":true,"publicationSubtype":{"id":10}},"title":"Estimating the power of a standardized monitoring program for sportfish in Georgia, USA","docAbstract":"<p>Objective</p><p><span>Biological monitoring is a major component of management decisions and operating budgets of many natural resource management agencies. Given the scientific and financial commitments to monitoring, it is critical to estimate the ability to detect trends through time (i.e., power).</span></p><p><span>Methods</span></p><p><span>The Georgia Department of Natural Resources has monitored reservoir sport fish populations since the 1980s. We estimated the power to detect simulated long-term (≥10 years) changes in relative abundance (CPUE) for Largemouth Bass (some of which are a potential genetic admixture of the recently described species&nbsp;<i>Micropterus nigricans</i>&nbsp;[now known as Largemouth Bass] and&nbsp;<i>M. salmoides</i>&nbsp;[now known as Florida Bass)] and Black Crappie&nbsp;<i>Pomoxis nigromaculatus</i>&nbsp;sampled with electrofishing and gill nets, respectively, across multiple reservoirs (<i>n</i>&nbsp;= 21). Reservoir-specific simulations were parameterized using 13 years (∼2010–2022) of monitoring data. Power was calculated as the proportion of simulations (<i>n</i>&nbsp;= 1,000) resulting in significant (<i>P</i>&nbsp;≤ 0.1) temporal trends across a 10-year period. We considered power ≥0.8 (i.e., 80% of simulations with significant trends) as the threshold for sufficient power across reservoirs. For both species, we estimated power under three scenarios: (1) declining CPUE, (2) increasing CPUE, and (3) reduction to biennial sampling effort with a 50% decline in CPUE.</span></p><p><span>Results</span></p><p><span>Most reservoirs had sufficient power to detect either a 50% decline or a 100% increase in CPUE of Largemouth Bass across a 10-year period. Switching from annual to biennial sampling for Largemouth Bass reduced the number of reservoirs with sufficient power by half. Power was generally lower for Black Crappie until larger declines (75%) or increases (400%) were imposed.</span></p><p><span>Conclusions</span></p><p><span>We found that Largemouth Bass monitoring was generally near or beyond our reference threshold, but post hoc correlation analyses suggested that the power of Black Crappie data could be increased with more within-reservoir station replication. Overall, using data simulation to estimate power proved a valuable tool in assessing the potential ability of common monitoring approaches to detect change.</span></p>","language":"English","publisher":"Oxford Academic","doi":"10.1093/najfmt/vqaf117","usgsCitation":"Simon, T.N., Robinson, K., and Irwin, B., 2026, Estimating the power of a standardized monitoring program for sportfish in Georgia, USA: North American Journal of Fisheries Management, vqaf117, 18 p., https://doi.org/10.1093/najfmt/vqaf117.","productDescription":"vqaf117, 18 p.","ipdsId":"IP-179756","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":502003,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":502068,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/najfmt/vqaf117","text":"Publisher Index Page"}],"country":"United 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,{"id":70274082,"text":"70274082 - 2026 - Microtextural characteristics of adularia in banded quartz veins from the Midas low-sulfidation epithermal deposit, Nevada","interactions":[],"lastModifiedDate":"2026-02-24T15:17:01.539054","indexId":"70274082","displayToPublicDate":"2026-01-22T08:11:03","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2746,"text":"Mineralium Deposita","active":true,"publicationSubtype":{"id":10}},"title":"Microtextural characteristics of adularia in banded quartz veins from the Midas low-sulfidation epithermal deposit, Nevada","docAbstract":"<p><span id=\"_mce_caret\" data-mce-bogus=\"1\" data-mce-type=\"format-caret\"><span>High-grade ores at the Miocene Midas low-sulfidation epithermal deposit in northern Nevada are confined to crustiform quartz veins containing abundant adularia. Micro-X-ray fluorescence elemental mapping reveals that adularia is a common gangue mineral occurring in colloform bands, bands showing bladed textures, and bands with dendritic terminations. The adularia aggregates have delicate shapes and are comprised of stacked, submillimeter crystals hosted by fine-grained quartz. The textural evidence suggests that the adularia aggregates originally formed within a gel-like, noncrystalline silica matrix, which subsequently transformed into quartz. This indicates that the adularia did not precipitate in open space along the vein walls. Correlative microscopy, involving scanning electron microscopy-based automated mineralogy and optical petrography, demonstrates that bands containing abundant adularia are not the primary host to ore minerals. The ore minerals occur in different bands within the crustiform veins, implying that adularia and ore mineral precipitation did not always occur simultaneously. It is hypothesized here that fluid flow at Midas involved intermittent short-lived events of fluid flashing, causing rapid solute supersaturation in the liquid. During each flashing event, different amounts of vapor were produced along a given vein. Compositional differences between adjacent bands in the crustiform quartz veins may, therefore, be linked to variations in the amount of vapor formed during each flash event.</span></span></p>","language":"English","publisher":"Springer Nature","doi":"10.1007/s00126-026-01430-x","usgsCitation":"Terry, L.R., Monecke, T., Reynolds, T., Kasprowicz, F., Pfaff, K.I., 2026, Microtextural characteristics of adularia in banded quartz veins from the Midas low-sulfidation epithermal deposit, Nevada: Mineralium Deposita, https://doi.org/10.1007/s00126-026-01430-x.","ipdsId":"IP-174519","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":500478,"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              -120.17483422284687,\n              42.06209612968607\n            ],\n            [\n              -119.92325247256808,\n              39.09238860917903\n            ],\n            [\n              -114.82956135832953,\n              35.02309662905567\n            ],\n            [\n              -114.86591889824984,\n              36.023284603589886\n            ],\n            [\n              -114.04429635880452,\n              36.24468483051718\n            ],\n            [\n              -113.99726749082308,\n              41.953759038434214\n            ],\n            [\n              -120.17483422284687,\n              42.06209612968607\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","edition":"Online First","noUsgsAuthors":false,"publicationDate":"2026-01-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Terry, Lauren R.","contributorId":361465,"corporation":false,"usgs":false,"family":"Terry","given":"Lauren","middleInitial":"R.","affiliations":[{"id":86290,"text":"Center to Advance the Science of Exploration to Reclamation in Mining, Department of Geology and Geological Engineering, Colorado School of Mines, Golden, Colorado, USA","active":true,"usgs":false}],"preferred":false,"id":956486,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Monecke, Thomas","contributorId":173585,"corporation":false,"usgs":false,"family":"Monecke","given":"Thomas","email":"","affiliations":[{"id":6606,"text":"Colorado School of Mines","active":true,"usgs":false}],"preferred":false,"id":956487,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Reynolds, T. James","contributorId":366972,"corporation":false,"usgs":false,"family":"Reynolds","given":"T. James","affiliations":[{"id":39908,"text":"FLUID INC.","active":true,"usgs":false}],"preferred":false,"id":956488,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kasprowicz, Filip","contributorId":363040,"corporation":false,"usgs":false,"family":"Kasprowicz","given":"Filip","affiliations":[{"id":86594,"text":"Center to Advance the Science of Exploration to Reclamation in Mining, Department of Geology and Geological Engineering, Colorado School of Mines","active":true,"usgs":false}],"preferred":false,"id":956489,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Pfaff, Katharina I. 0000-0002-6605-2722","orcid":"https://orcid.org/0000-0002-6605-2722","contributorId":362430,"corporation":false,"usgs":true,"family":"Pfaff","given":"Katharina","middleInitial":"I.","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":956490,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70273786,"text":"70273786 - 2026 - The biosphere in the Anthropocene","interactions":[],"lastModifiedDate":"2026-01-29T14:54:21.742094","indexId":"70273786","displayToPublicDate":"2026-01-22T07:49:34","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":23284,"text":"Transactions of the Royal Society of London","active":true,"publicationSubtype":{"id":10}},"title":"The biosphere in the Anthropocene","docAbstract":"<p><span id=\"_mce_caret\" data-mce-bogus=\"1\" data-mce-type=\"format-caret\"><span>Earth’s biosphere is in a period of rapid change, resulting from anthropogenic pressures such as climate change, habitat loss and species translocation and extinction. The extraordinary pace of change has led to the suggestion that we live in a new geological epoch of time called the Anthropocene. In this theme issue, we explore the major changes to the terrestrial and marine biospheres, from the deep oceans to the agricultural landscapes of the Anthropocene. We take a deliberately pluralistic approach that represents different viewpoints from the sciences and social sciences, examining our negative and sometimes calamitous impacts on species and ecosystems and our potential for positive interactions with the biosphere, and exploring change over millennia.</span></span></p>","language":"English","publisher":"The Royal Society","doi":"10.1098/rstb.2024.0416","usgsCitation":"Williams, M., McGann, M., Yasuhara, M., Chaudhary, C., Barber, L., and Allen, K., 2026, The biosphere in the Anthropocene: Transactions of the Royal Society of London, v. 381, no. 1942, 20240416, 5 p., https://doi.org/10.1098/rstb.2024.0416.","productDescription":"20240416, 5 p.","ipdsId":"IP-183696","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":499295,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1098/rstb.2024.0416","text":"Publisher Index Page"},{"id":499223,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"381","issue":"1942","noUsgsAuthors":false,"publicationDate":"2026-01-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Williams, Mark","contributorId":214696,"corporation":false,"usgs":false,"family":"Williams","given":"Mark","affiliations":[],"preferred":false,"id":954785,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McGann, Mary L. 0000-0002-3057-2945","orcid":"https://orcid.org/0000-0002-3057-2945","contributorId":354828,"corporation":false,"usgs":false,"family":"McGann","given":"Mary L.","affiliations":[{"id":84675,"text":"Formerly USGS PCMSC","active":true,"usgs":false}],"preferred":false,"id":954786,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Yasuhara, Moriaki","contributorId":178705,"corporation":false,"usgs":false,"family":"Yasuhara","given":"Moriaki","email":"","affiliations":[],"preferred":false,"id":954787,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Chaudhary, Chhaya","contributorId":365784,"corporation":false,"usgs":false,"family":"Chaudhary","given":"Chhaya","affiliations":[{"id":87219,"text":"Universität Hamburg, Hamburg, Germany","active":true,"usgs":false}],"preferred":false,"id":954788,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Barber, Lisa","contributorId":365785,"corporation":false,"usgs":false,"family":"Barber","given":"Lisa","affiliations":[{"id":81499,"text":"University of Leicester, Leicester, UK","active":true,"usgs":false}],"preferred":false,"id":954789,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Allen, Kerry","contributorId":365786,"corporation":false,"usgs":false,"family":"Allen","given":"Kerry","affiliations":[{"id":81499,"text":"University of Leicester, Leicester, UK","active":true,"usgs":false}],"preferred":false,"id":954790,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70273273,"text":"sim3542 - 2026 - Bedrock geologic map of the Eagle Lake quadrangle, Essex County, New York","interactions":[],"lastModifiedDate":"2026-02-03T17:09:44.672869","indexId":"sim3542","displayToPublicDate":"2026-01-21T19:43:00","publicationYear":"2026","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3542","displayTitle":"Bedrock Geologic Map of the Eagle Lake Quadrangle, Essex County, New York","title":"Bedrock geologic map of the Eagle Lake quadrangle, Essex County, New York","docAbstract":"<p>The bedrock geology of the 7.5-minute Eagle Lake quadrangle, Essex County, New York, consists of deformed and metamorphosed Mesoproterozoic gneisses of the Adirondack Highlands unconformably overlain by weakly deformed lower Paleozoic sedimentary rocks of the Champlain Valley. The Mesoproterozoic rocks occur on the eastern edge of the Adirondack Highlands and represent an extension of the Grenville Province of Laurentia. Granulite facies Mesoproterozoic paragneiss, marble, and amphibolite hosted the emplacement of an anorthosite-mangerite-charnockite-granite (AMCG) suite, now exposed mostly as orthogneiss, at approximately 1.18–1.15 giga-annum (Ga, billion years before present). The earliest of four phases of deformation (D1) predated AMCG magmatism and is characterized by gneissosity, rarely preserved F1 isoclinal folds, and migmatite in the paragneiss host rocks. A sample of hornblende quartz syenite from the AMCG suite, collected from an abandoned railroad cut on Old Furnace Road, yielded a U-Pb zircon age of 1,149±10 million years before present. D2 deformation produced a composite penetrative gneissosity, migmatite, and isoclinal F2 folds. Towards the end of D2, felsic magmatism (including the regionally extensive Lyon Mountain Granite Gneiss, abbreviated “LMG”) spread by penetrative migration as semiconcordant alkali feldspar granite sheets subparallel to S2 into the previously deformed lithologies. The LMG crystallized at approximately 1.15 to 1.14 Ga and displays synkinematic F2 folds thus constraining the time of D2 deformation. Exhumation of the Marcy anorthosite began during D3 along a mylonitic extensional detachment, as a type of core complex. Protracted D3 produced F3 folds exhibited in regional domes and basins, such as the Hammondville antiform, reactivation of the S2 foliation, partial melting, metamorphism, metasomatism, iron ore remobilization, and intrusion of magnetite-bearing pegmatite both as layer-parallel sills and crosscutting dikes. D4 created NE- and NW-trending boudinage, local high-grade ductile shear zones, and crosscutting granitic pegmatite dikes. Kilometer (km)-scale lineaments readily observed in lidar data are Ediacaran mafic dikes and Phanerozoic brittle faults. Lower Paleozoic rocks are part of the Early Cambrian to Late Ordovician great American carbonate bank on the ancient margin of Laurentia. The Potsdam Sandstone preserves the Cambrian stratigraphy in outliers above the Great Unconformity. The Paleozoic rocks are weakly folded and block faulted. Parts of the quadrangle are covered by undifferentiated glacial deposits, but much of the quadrangle contains only a variably thick, veneer of unmapped glacial till over significant areas of exposed bedrock. The map also shows waste rock piles and locations of historical mining operations. This study was undertaken to improve our understanding of the bedrock geology in the Adirondack Highlands, establish a modern framework for 1:24,000-scale bedrock geologic mapping in the Adirondack Mountains, and provide a modern context for historical mines. This Scientific Investigations Map of the Eagle Lake 7.5-minute quadrangle consists of a map sheet, an explanatory pamphlet, and a geographic information system database that includes bedrock geologic units, faults, outcrops, and structural geologic information. The map sheet includes a bedrock geologic map, a correlation of map units, a description of map units, an explanation of map symbols, and two cross sections. The explanatory pamphlet includes a discussion of the geology.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3542","collaboration":"Prepared in cooperation with the State of New York, Department of Education, New York Geological Survey","usgsCitation":"Walsh, G.J., Regan, S.P., Geer, P.S., Merschat, A.J., Suarez, K.A., McAleer, R.J., Walton, M.S., Jr., and Crider, E.A., Jr., 2026, Bedrock geologic map of the Eagle Lake quadrangle, Essex County, New York: U.S. Geological Survey Scientific Investigations Map 3542, 1 sheet, scale 1:24,000, 57-p. pamphlet, https://doi.org/10.3133/sim3542.","productDescription":"Pamphlet: ix, 57 p.; 1 Sheet: 63.43 x 35.22 inches; Data Release","numberOfPages":"57","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-151166","costCenters":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":498080,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3542/coverthb.jpg"},{"id":498081,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3542/sim3542_pamphlet.pdf","size":"10.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3542 Pamphlet"},{"id":498752,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sim/3542/sim3542_pamphlet.XML","description":"SIM 3542 XML"},{"id":498753,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9D6XYEL","text":"USGS data release","linkHelpText":"Database for the bedrock geologic map of the Eagle Lake quadrangle, Essex County, New York"},{"id":498867,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_119158.htm","linkFileType":{"id":5,"text":"html"}},{"id":498751,"rank":3,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3542/sim3542_sheet.pdf","size":"56.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3542 Sheet"}],"country":"United States","state":"New York","otherGeospatial":"Eagle Lake quadrangle","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -73.625,\n              44\n            ],\n            [\n              -73.625,\n              43.875\n            ],\n            [\n              -73.5,\n              43.875\n            ],\n            [\n              -73.5,\n              44\n            ],\n            [\n              -73.625,\n              44\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","contact":"<p>Director, <a href=\"https://www.usgs.gov/centers/florence-bascom-geoscience-center\" data-mce-href=\"https://www.usgs.gov/centers/florence-bascom-geoscience-center\">Florence Bascom Geoscience Center</a><br>U.S. Geological Survey<br>926A National Center<br>12201 Sunrise Valley Drive<br>Reston, VA 20192</p><p><a href=\"https://pubs.usgs.gov/contact\" data-mce-href=\"../contact\">Contact Pubs Warehouse</a></p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Plain Language Summary</li><li>Introduction</li><li>Lithostratigraphy</li><li>Gamma Radiation Measurements</li><li>Structural Geology</li><li>Tectonics and Metamorphism</li><li>U-Th-Pb Geochronology</li><li>Geochemistry</li><li>Economic Geology</li><li>References Cited</li><li>Appendix 1. Representative Photographs of Map Units From the Eagle Lake Quadrangle</li></ul>","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"publishedDate":"2026-01-21","noUsgsAuthors":false,"plainLanguageSummary":"<p>The U.S. Geological Survey mapped the bedrock geology of the 7.5-minute Eagle Lake quadrangle, Essex County, New York, to establish a framework for 1:24,000-scale detailed bedrock geologic mapping in the Adirondack Mountains, and provide a modern context for historical iron, graphite, and feldspar mines that operated in the 1800s. The report includes the most detailed 1:24,000-scale bedrock geologic map ever published in the Adirondack Mountains. The region is underlain by highly complex Precambrian igneous and metamorphic rocks that range in age from about 1.2 to 1.0 billion years old. The high quality of the naturally occurring mineral magnetite extracted from local iron mines led to the first use of an electric motor in Ironville, proclaimed to be the birthplace of the electric age. Abandoned iron and pegmatite mines locally contain elevated abundances of rare earth elements; some of the deposits have elevated natural radioactivity above background concentrations.</p>","publicationDate":"2026-01-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Walsh, Gregory J. 0000-0003-4264-8836","orcid":"https://orcid.org/0000-0003-4264-8836","contributorId":355444,"corporation":false,"usgs":true,"family":"Walsh","given":"Gregory J.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":952978,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Regan, Sean P. 0000-0002-8445-5138","orcid":"https://orcid.org/0000-0002-8445-5138","contributorId":360816,"corporation":false,"usgs":false,"family":"Regan","given":"Sean","middleInitial":"P.","affiliations":[{"id":7211,"text":"University of Alaska, Fairbanks","active":true,"usgs":false}],"preferred":false,"id":952979,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Geer, Phillip S.","contributorId":364641,"corporation":false,"usgs":false,"family":"Geer","given":"Phillip","middleInitial":"S.","affiliations":[{"id":83490,"text":"University of Massachusetts, Amherst, Mass.","active":true,"usgs":false}],"preferred":false,"id":952980,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Merschat, Arthur J. 0000-0002-9314-4067 amerschat@usgs.gov","orcid":"https://orcid.org/0000-0002-9314-4067","contributorId":4556,"corporation":false,"usgs":true,"family":"Merschat","given":"Arthur","email":"amerschat@usgs.gov","middleInitial":"J.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":952981,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Suarez, Kaitlyn A. 0000-0003-4133-3074","orcid":"https://orcid.org/0000-0003-4133-3074","contributorId":224240,"corporation":false,"usgs":false,"family":"Suarez","given":"Kaitlyn","middleInitial":"A.","affiliations":[{"id":33634,"text":"University of Massachusetts at Amherst","active":true,"usgs":false}],"preferred":false,"id":952982,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"McAleer, Ryan J. 0000-0003-3801-7441 rmcaleer@usgs.gov","orcid":"https://orcid.org/0000-0003-3801-7441","contributorId":215498,"corporation":false,"usgs":true,"family":"McAleer","given":"Ryan","email":"rmcaleer@usgs.gov","middleInitial":"J.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":952983,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Walton,, Matt S. Jr.","contributorId":364642,"corporation":false,"usgs":false,"family":"Walton,","given":"Matt","suffix":"Jr.","middleInitial":"S.","affiliations":[{"id":29853,"text":"Yale University, New Haven, Conn.","active":true,"usgs":false}],"preferred":false,"id":952984,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Crider,, E. Allen Jr. 0000-0003-2393-5290 ecrider@usgs.gov","orcid":"https://orcid.org/0000-0003-2393-5290","contributorId":203507,"corporation":false,"usgs":true,"family":"Crider,","given":"E. Allen","suffix":"Jr.","email":"ecrider@usgs.gov","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":952985,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70273704,"text":"70273704 - 2026 - An energetic tradeoff best explains parturition timing in grizzly bears","interactions":[],"lastModifiedDate":"2026-01-23T15:24:10.860219","indexId":"70273704","displayToPublicDate":"2026-01-21T09:14:16","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"An energetic tradeoff best explains parturition timing in grizzly bears","docAbstract":"<p><span>Timing of grizzly bear (</span><i>Ursus arctos</i><span>) parturition during hibernation has been explained by ancestral traits (delayed implantation, altricial young, obligate maternal denning), but the ultimate driver underlying precise timing has not been fully explored. Capitalizing on an observed latitudinal increase in denning duration among four populations in interior North America, we tested two alternative hypotheses. First, that birth timing results from a physiological cue that synchronizes implantation with the onset of hibernation, allowing females to forgo reproduction should they lack adequate fat stores. Alternatively, that parturition is optimally timed relative to den exit to balance an energetic tradeoff between minimizing lactation time to protect the mother and maximizing developmental time to increase cub survival. Using parturition dates previously predicted from accelerometer data (27 Dec–28 Feb), we classified 115 females according to apparent litter survival when first visually observed after den exit: 57% successful (with cubs), 22% unsuccessful (alone), and 21% unknown (not observed). The number of days between birth and den exit showed no association with latitude (</span><i>p</i><span> = 0.29). It averaged 103 days among successful females but only 77 days among unsuccessful females (</span><i>p</i><span> &lt; 0.001) owing to later births and earlier exit. With each increasing degree of latitude, birth date increased by 1.0 and number of days between den entry and birth increased by 2.5 (</span><i>p</i><span> &lt; 0.001). Implantation dates were not centered on den entry dates (</span><i>p</i><span> &lt; 0.001). These results supported the energetic tradeoff hypothesis and suggested natural selection has favored a consistent number of days between parturition and den exit under average body conditions and shifts toward later or earlier births for females with lower or higher levels of bodily stored energy, respectively. This flexible tradeoff may support resilience to climate change and present a possible mechanism explaining reduced natality and cub survival in high-density populations.</span></p>","language":"English","publisher":"Wiley","doi":"10.1002/ece3.72914","usgsCitation":"Costello, C.M., Roberts, L., Bjornlie, D.D., Cameron, M.D., Clapp, J.G., Haroldson, M., Hilderbrand, G.V., Joly, K., Kasworm, W., Nicholson, J.M., Radandt, T., Sorum, M.S., Teisberg, J.E., van Manen, F.T., and Vinks, M.A., 2026, An energetic tradeoff best explains parturition timing in grizzly bears: Ecology and Evolution, v. 16, no. 1, e72914, 12 p., https://doi.org/10.1002/ece3.72914.","productDescription":"e72914, 12 p.","ipdsId":"IP-180106","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":499310,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.72914","text":"Publisher Index Page"},{"id":498992,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","state":"Alaska, British Columbia, Idaho, Montana, Wyoming","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -162.45792781080903,\n              68.91031809670773\n            ],\n            [\n              -162.45792781080903,\n              65.1797348577656\n            ],\n            [\n              -141.25015661377543,\n              65.1797348577656\n            ],\n            [\n              -141.25015661377543,\n              68.91031809670773\n            ],\n            [\n              -162.45792781080903,\n              68.91031809670773\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    },\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -111.66121434291338,\n              45.570585569366614\n            ],\n            [\n              -111.66121434291338,\n              42.9324586570242\n            ],\n            [\n              -108.49816630387593,\n              42.9324586570242\n            ],\n            [\n              -108.49816630387593,\n              45.570585569366614\n            ],\n            [\n              -111.66121434291338,\n              45.570585569366614\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    },\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -118.00477942846378,\n              51.17475366345599\n            ],\n            [\n              -118.00477942846378,\n              47.24972185538144\n            ],\n            [\n              -113.69327860666921,\n              47.24972185538144\n            ],\n            [\n              -113.69327860666921,\n              51.17475366345599\n            ],\n            [\n              -118.00477942846378,\n              51.17475366345599\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"16","issue":"1","noUsgsAuthors":false,"publicationDate":"2026-01-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Costello, C. 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E.","contributorId":365515,"corporation":false,"usgs":false,"family":"Teisberg","given":"J.","middleInitial":"E.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":954358,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"van Manen, Frank T. 0000-0001-5340-8489 fvanmanen@usgs.gov","orcid":"https://orcid.org/0000-0001-5340-8489","contributorId":2267,"corporation":false,"usgs":true,"family":"van Manen","given":"Frank","email":"fvanmanen@usgs.gov","middleInitial":"T.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":954359,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Vinks, M. A.","contributorId":365519,"corporation":false,"usgs":false,"family":"Vinks","given":"M.","middleInitial":"A.","affiliations":[{"id":37431,"text":"Montana Fish, Wildlife and Parks","active":true,"usgs":false}],"preferred":false,"id":954360,"contributorType":{"id":1,"text":"Authors"},"rank":15}]}}
,{"id":70273409,"text":"ofr20251057 - 2026 - Distribution, abundance, breeding activities, and habitat use of the Least Bell's Vireo at Marine Corps Base Camp Pendleton, California—2020–24 summary report","interactions":[],"lastModifiedDate":"2026-02-03T17:09:16.100992","indexId":"ofr20251057","displayToPublicDate":"2026-01-21T07:00:00","publicationYear":"2026","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2025-1057","displayTitle":"Distribution, Abundance, Breeding Activities, and Habitat Use of the Least Bell's Vireo at Marine Corps Base Camp Pendleton, California—2020–24 Summary Report","title":"Distribution, abundance, breeding activities, and habitat use of the Least Bell's Vireo at Marine Corps Base Camp Pendleton, California—2020–24 summary report","docAbstract":"<h1>Executive Summary&nbsp;</h1><p>The purpose of this report is to provide the Marine Corps with a summary of abundance, breeding activity, demography, and habitat use of endangered Least Bell’s Vireos (<i>Vireo bellii pusillus</i>) at Marine Corps Base Camp Pendleton, California (MCBCP or Base). The report presents results of vireo surveys and monitoring in 2024 and summarizes a subset of data collected from 2020 through 2024. Surveys for the Least Bell's Vireo were completed at MCBCP between April 4 and July 9, 2024. Core survey areas and a subset of non-core areas in drainages containing riparian habitat suitable for vireos were surveyed two to four times. We detected 542 territorial male vireos and 17 transient vireos in core survey areas. An additional 102 territorial male vireos and 2 transients were detected in non-core survey areas. Transient vireos were detected on 5 of the 10 drainages/sites surveyed (core and non-core areas). In core survey areas, 87 percent of vireo territories were on the four most populated drainages, with the Santa Margarita River containing 67 percent of all territories in core areas surveyed on Base. In core areas, 77 percent of male vireos were confirmed as paired; 76 percent of male vireos in non-core areas were confirmed as paired.</p><p>The number of documented Least Bell’s Vireo territories in core survey areas on MCBCP decreased 3 percent from 2023. In five core survey area drainages, the number of territories increased by at least two, and in two core survey area drainages, the Santa Margarita River and Las Flores Creek, the number of vireo territories decreased by at least nine between 2023 and 2024. The number of vireo territories at Marine Corps Air Station, Camp Pendleton did not change from 2023 to 2024. The proportion of surveys during which Brown-headed Cowbirds (<i>Molothrus ater</i>) were detected decreased to 0.03 from a peak of 0.45 in 2022. Cowbirds were detected in April and June in 2024.</p><p>Most core-area vireos (58 percent, including transients) used mixed willow (<i>Salix</i> spp.) riparian habitat. An additional 9 percent of birds occupied willow habitat co-dominated by Western sycamores (<i>Platanus racemosa</i>). Riparian scrub dominated by mule fat (<i>Baccharis salicifolia</i>), sandbar willow (<i>S. exigua</i>), or blue elderberry (<i>Sambucus mexicana</i>) was used by 33 percent of vireos. Habitat dominated by non-native vegetation was used by 1 percent of vireos.</p><p>Since 2020, the number of vireos detected in each of the non-core survey groups was greater than expected, based on the change in vireo numbers in core survey areas. Although, the number of vireo territories on Base decreased from 2020–24, from approximately 1,224 to approximately 960, the trend in vireo territory numbers on Base since 2005 has been positive.</p><p>In 2019, MCBCP began operating an artificial seep along the Santa Margarita River; then, in 2021, two additional artificial seeps became operational. The artificial seeps pumped water to the surface during daylight hours starting in mid-April and ending in August each year and were designed to increase the amount of surface water to enhance Southwestern Willow Flycatcher (<i>Empidonax traillii extimus</i>) breeding habitat. Although this enhancement was designed to benefit flycatchers, few flycatchers have inhabited MCBCP, including the seep areas, within the past several years; therefore, vireos were selected as a surrogate species to determine effects of the habitat enhancement. This report presents the fifth year of annual monitoring and analyses summarizing all 5 years of vireo and vegetation response to the artificial seeps.</p><p>In 2020, we established four study sites along the Santa Margarita River, two surrounding and extending downstream from existing and proposed seep pumps at the Old Treatment Ponds and along Pump Road and two Reference sites in similar habitat downstream from the Seep sites. Seep pumps began operating at the Old Treatment Ponds in 2020 and along Pump Road in 2021. In 2023, seep pumps at the Pump Road Seep site did not function, and we recategorized that study site as Intermediate. We sampled vegetation at Seep, Intermediate, and Reference sites to determine the effects of surface-water enhancement by seep pumps. In 2024, vegetation cover was highest near the ground and decreased with increasing height. Woody vegetation made up most of the cover at all height categories. We determined that Seep and Intermediate sites differed from each other in addition to differing from Reference sites, which likely is, in part, because seep-pump operation at the Intermediate site was inconsistent compared to the Seep site. Soil saturation in 2024 was high at the Intermediate site and was associated with high native herbaceous cover and low non-native herbaceous cover. Sites differed, with the Intermediate site having more upper canopy cover in general, the Seep site having more low woody cover, and the Reference sites having more mid-canopy non-native vegetation cover.</p><p>Soil saturation significantly increased from 2020 through 2024 at the Seep site and was significantly higher at Seep and Intermediate sites than at their paired Reference sites in all years. Soil saturation likely was increased by the supplemental surface water at the Seep site. However, soil saturation at the Intermediate site was not clearly associated with seep pumps but likely affected by soil saturation at the site before seep-pump installation and flooding from high precipitation. Canopy height increased at the Intermediate site from 2020 through 2024 and increased with increasing soil saturation at the Intermediate and Reference sites. The canopy at the Seep site was shorter than at the Intermediate and Reference sites and decreased from 2020 through 2024 because tall trees were damaged and killed by shothole borer beetles (<i>Euwallacea</i> spp.).</p><p>We used Redundancy Analysis to discover associations among vegetation types, plant species, and other environmental variables (soil saturation, site, precipitation, and seep operation, defined as the site and year seep pumps were operating). These associations explained less than 15 percent of the variability in the vegetation, with the remaining 85 percent of variation unexplained. Generally, as soil saturation increased, understory vegetation increased and non-native cover decreased in the mid-and upper canopy. Non-native herbaceous plant species decreased in wetter soil.</p><p>The Seep site was characterized by more understory and less canopy, contrasting with the Intermediate site, which was characterized by less understory and more higher canopy cover. The addition of surface water via seep pumps or precipitation was associated with more vegetation near the ground. Higher early winter precipitation was associated with taller canopy and more woody vegetation in the upper canopy. We also created a Redundancy Analysis model isolating the components of Southwestern Willow Flycatcher habitat, as identified by Howell and others (2018). In this model, increased soil saturation resulted in increased cover of stinging nettle (<i>Urtica dioica</i>) and black willow (<i>Salix gooddingii</i>) below 3 meters (m), total cover 3–6 m, and black willow above 6 m. Cover of poison hemlock (<i>Conium maculatum</i>) and stinging nettle below 3 m was higher at the Seep site and lower at the Intermediate site.</p><p>Vireo territory density among the Seep, Intermediate, and Reference sites was similar before the seep pumps were installed. However, vireo territory density at Seep and Intermediate sites combined was significantly higher than at Reference sites after the seep pumps were installed.</p><p>We banded and resighted color banded vireos as part of a long-term evaluation of vireo survival, site fidelity, between-year movement, and the effect of surface-water enhancement on vireo return rate and between-year movement. We banded 164 Least Bell's Vireo nestlings during the 2024 season.</p><p>In 2024, we resighted 31 Least Bell's Vireos on Base that had been banded before the 2024 breeding season, and we were able to identify 25 of them. Of the 25 that we could identify, 24 were banded on Base and 1 was originally banded on the San Luis Rey River. Adult birds of known age ranged from 1 to 9 years old.</p><p>Base-wide survival of vireos was affected by sex, age, and year. Males had significantly higher annual survival than females (60 percent versus 47 percent, respectively). Adults had higher annual survival than first-year vireos (61 percent versus 11 percent, respectively). The return rate of adult vireos to Seep, Intermediate, or Reference sites was not affected by the original banding site (Seep versus Intermediate versus Reference).</p><p>Most returning adult vireos, predominantly males, showed strong between-year site fidelity. Of the adults present in 2023, 92 percent (all males) returned in 2024 to within 100 m of their previous territory. The average between-year movement for returning adult vireos was 0.4±0.03 kilometers (km). The average movement of first-year vireos detected in 2024 that fledged from a known nest on MCBCP in 2023 was 2.4±3.1 km.</p><p>We monitored 47 Least Bell's Vireo pairs to evaluate the effects of surface-water enhancement on nest success and breeding productivity. Breeding productivity in 2024 was similar among Seep, Intermediate, and Reference sites (2.8, 3.0, and 3.0 young fledged per pair, respectively), and the percentage of pairs that fledged at least one young was not significantly different among sites (83, 91, and 96 percent, respectively). According to the best model, daily nest survival from 2020–24 was not related to site. Other measures of breeding productivity were also similar among Seep, Intermediate, and Reference site pairs.</p><p>Between 2020 and 2024, the number of vireo fledglings produced per pair increased with increasing native herbaceous cover under 3 m and decreasing cover of all herbaceous vegetation under 5 m and was not affected by precipitation, site, or seep operation. The number of vireo fledglings produced per egg was lower at the Seep and Intermediate sites than at the Reference sites and increased with decreasing late winter precipitation, cover of poison hemlock, black mustard, non-native vegetation above 2 m, and all vegetation over 2 m. Vireo pairs at Seep and Intermediate sites were less likely to fledge young than vireo pairs at Reference sites. All vireo pairs were more likely to fledge young with less cover of poison hemlock and more cover of poison oak.</p><p>From 2020 through 2024, vireos placed their nests in 24 plant species. The most used plants in all years were willows, mostly red (<i>S. laevigata</i>), or arroyo (<i>S. lasiolepis</i>). The fate of a vireo nest (whether it successfully fledged young or not) was not affected by placement in native or non-native vegetation, by site, or by year, but nests were more likely to be successful if they were placed in woody plants than in herbaceous plants. Successful nests were placed higher in the host plant and farther from the outer edge of the nest clump than unsuccessful nests.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20251057","collaboration":"Prepared in cooperation with Assistant Chief of Staff, Environmental Security, U.S. Marine Corps Base Camp Pendleton","programNote":"Ecosystems Mission Area—Species Management Research Program","usgsCitation":"Lynn, S., Houston, A., Kus, B.E., and Mendia, S.M., 2026, Distribution, abundance, breeding activities, and habitat use of the Least Bell's Vireo at Marine Corps Base Camp Pendleton, California—2020–24 summary report: U.S. Geological Survey Open-File Report 2025–1057, 128 p., https://doi.org/10.3133/ofr20251057.","productDescription":"xii, 128 p.","numberOfPages":"128","onlineOnly":"Y","ipdsId":"IP-176723","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":498564,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2025/1057/images"},{"id":498563,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2025/1057/ofr20251057.XML","linkFileType":{"id":8,"text":"xml"},"description":"OFR 2025-1057 XML"},{"id":498562,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20251057/full","linkFileType":{"id":5,"text":"html"},"description":"OFR 2025-1057 HTML"},{"id":498561,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2025/1057/ofr20251057.pdf","size":"13.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2025-1057 PDF"},{"id":498560,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2025/1057/coverthb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Marine Corps Base Camp Pendleton","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -117.5833,\n              33.5\n            ],\n            [\n              -117.5833,\n              33.1667\n            ],\n            [\n              -117.25,\n              33.1667\n            ],\n            [\n              -117.25,\n              33.5\n            ],\n            [\n              -117.5833,\n              33.5\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","contact":"<p><a href=\"https://www.usgs.gov/centers/werc\" data-mce-href=\"https://www.usgs.gov/centers/werc\">Western Ecological Research Center</a><br><a href=\"https://www.usgs.gov/\" data-mce-href=\"https://www.usgs.gov/\">U.S. Geological Survey</a><br>3020 State University Drive East<br>Sacramento, California 95819</p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Executive Summary</li><li>Introduction</li><li>Study Area and Methods</li><li>Results</li><li>Discussion</li><li>Conclusions</li><li>References Cited</li><li>Appendix 1. Least Bell’s Vireo Survey Areas at Marine Corps Base Camp Pendleton, 2024</li><li>Appendix 2. Vegetation Sampling Locations and Vegetation Sampling Data Sheet, Marine Corps Base Camp Pendleton, California, 2024</li><li>Appendix 3. Principal Components Analysis Loadings for Vegetation Types and Plant Species at all Height Categories, 2020 through 2024</li><li>Appendix 4. Locations of Least Bell’s Vireos at Marine Corps Base Camp Pendleton, California, 2024</li><li>Appendix 5. Number of Territorial Male Least Bell Vireos in Core Survey Areas at Marine Corps Base Camp Pendleton, California, by Drainage, 2005–24</li><li>Appendix 6. Proportion of Lease Bell’s Vireo Territories, Including Areas Occupied by Transients, Dominated or Co-Dominated by Non-Native Vegetation, by Drainage, 2005–24</li><li>Appendix 7. Redundancy Analysis Loadings for Model 1, Vegetation Type Variation</li><li>Appendix 8. Redundancy Analysis Loadings for Model 2, Plant Species Variation</li><li>Appendix 9. Redundancy Analysis Loadings for Vegetation Variation for Southwestern Willow Flycatcher Habitat</li><li>Appendix 10. Banded Least Bell’s Vireos at Marine Corps Base Camp Pendleton, California, 2024</li><li>Appendix 11. Between-Year Movement of Adult and Juvenile Least Bell’s Vireos Detected at Marine Corps Base Camp Pendleton, California, 2024</li><li>Appendix 12. Status and Nesting Activities of Least Bell’s Vireos at Marine Corps Base Camp Pendleton, California, 2024</li></ul>","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"publishedDate":"2026-01-21","noUsgsAuthors":false,"publicationDate":"2026-01-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Lynn, Suellen 0000-0003-1543-0209 suellen_lynn@usgs.gov","orcid":"https://orcid.org/0000-0003-1543-0209","contributorId":3843,"corporation":false,"usgs":true,"family":"Lynn","given":"Suellen","email":"suellen_lynn@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":953615,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Houston, Alexandra 0000-0002-8599-8265 ahouston@usgs.gov","orcid":"https://orcid.org/0000-0002-8599-8265","contributorId":139460,"corporation":false,"usgs":true,"family":"Houston","given":"Alexandra","email":"ahouston@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":953616,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kus, Barbara E. 0000-0002-3679-3044 barbara_kus@usgs.gov","orcid":"https://orcid.org/0000-0002-3679-3044","contributorId":3026,"corporation":false,"usgs":true,"family":"Kus","given":"Barbara E.","email":"barbara_kus@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":953617,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mendia, Shannon M. 0000-0003-4520-7024 smendia@usgs.gov","orcid":"https://orcid.org/0000-0003-4520-7024","contributorId":223097,"corporation":false,"usgs":true,"family":"Mendia","given":"Shannon","email":"smendia@usgs.gov","middleInitial":"M.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":953618,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70273475,"text":"sir20255102 - 2026 - Comparison of two precipitation gage networks in Cook County, Illinois","interactions":[],"lastModifiedDate":"2026-02-03T17:08:35.729068","indexId":"sir20255102","displayToPublicDate":"2026-01-20T15:17:23","publicationYear":"2026","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2025-5102","displayTitle":"Comparison of Two Precipitation Gage Networks in Cook County, Illinois","title":"Comparison of two precipitation gage networks in Cook County, Illinois","docAbstract":"<p>The Cook County Precipitation Network is a set of 25 precipitation gages established within Cook County, Illinois, on approximately a 5- to 7-mile square grid and used by the U.S. Army Corps of Engineers to help account for diversions of water from Lake Michigan to the State of Illinois. The transition from the precipitation gage network operated by the Illinois State Water Survey to the precipitation gage network operated by the U.S. Geological Survey (USGS) was compared for periods of overlapping data. This transition took place from May through September during the 2019 water year. The USGS was able to establish replacement precipitation gages at 17 of the 25 sites by the conclusion of the overlapping operational period.</p><p>The double-mass curve method was used to compare the two networks by creating a graph of the cumulated data collected by the Illinois State Water Survey and the comparable data collected by the USGS. Breaks in the double-mass curve method are caused by a change in the relation between variables. The eight sites that were installed following the overlapping period have a gap in the recorded data; however, the slope of the line for each of the eight sites is nearly equivalent to the previous data. In general, the cumulated precipitation data from the two networks were similar. Three sites had greater than 8-percent difference in their cumulative data ratios, located at Cicero, Ping Tom Park at Chicago, and South Shore, Ill.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20255102","collaboration":"Prepared in cooperation with U.S. Army Corps of Engineers","usgsCitation":"Johnson, K.K., 2026, Comparison of two precipitation gage networks in Cook County, Illinois: U.S. Geological Survey Scientific Investigations Report 2025–5102, 73 p., https://doi.org/10.3133/sir20255102.","productDescription":"Report: iv, 73 p.; Linked Appendix Table; Dataset","numberOfPages":"82","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-142529","costCenters":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":498662,"rank":6,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2025/5102/downloads/sir20255102_table1.1.zip","text":"Appendix 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<a href=\"https://www.usgs.gov/centers/cm-water\" data-mce-href=\"https://www.usgs.gov/centers/cm-water\">Central Midwest Water Science Center</a><br>U.S. Geological Survey<br>405 North Goodwin<br>Urbana, IL 61801</p><p><a href=\"https://pubs.usgs.gov/contact\" data-mce-href=\"../contact\">Contact Pubs Warehouse</a></p>","tableOfContents":"<ul><li>Plain Language Summary</li><li>Abstract</li><li>Introduction</li><li>Comparison of Networks</li><li>Network Equipment</li><li>Summary</li><li>References Cited</li><li>Appendix 1. U.S. Army Corps of Engineers Supplied Monthly Data</li><li>Appendix 2. Station Descriptions of the U.S. Geological Survey Cook County Precipitation Network</li></ul>","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2026-01-20","noUsgsAuthors":false,"plainLanguageSummary":"<p>The Cook County Precipitation Network includes 25 precipitation gages spread out across Cook County, Illinois. These gages help the U.S. Army Corps of Engineers track how much water is diverted from Lake Michigan into Illinois. In 2019, the responsibility for operating and maintaining these gages shifted from the Illinois State Water Survey to the U.S. Geological Survey. To evaluate the data consistency during the transition, the two organizations operated their networks at the same time for a few months (May to September 2019). During this period, the U.S. Geological Survey installed new gages at 17 of the 25 sites. The remaining 8 sites were installed later, resulting in data gaps for those sites. An analytical method called a double-mass curve was used to compare the data from both networks. Overall, the precipitation totals from both networks were very similar. However, three sites had cumulative data ratio differences greater than 8 percent.</p>","publicationDate":"2026-01-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Johnson, Kevin K. 0000-0003-2703-5994 johnsonk@usgs.gov","orcid":"https://orcid.org/0000-0003-2703-5994","contributorId":4220,"corporation":false,"usgs":true,"family":"Johnson","given":"Kevin","email":"johnsonk@usgs.gov","middleInitial":"K.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":953872,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
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