{"pageNumber":"225","pageRowStart":"5600","pageSize":"25","recordCount":184717,"records":[{"id":70267462,"text":"70267462 - 2023 - Mapping closed depressions in the karst region of northwest Puerto Rico using lidar-derived elevation data obtained in 2018 after Hurricane Maria","interactions":[],"lastModifiedDate":"2025-05-23T14:09:15.876291","indexId":"70267462","displayToPublicDate":"2023-12-01T09:08:54","publicationYear":"2023","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Mapping closed depressions in the karst region of northwest Puerto Rico using lidar-derived elevation data obtained in 2018 after Hurricane Maria","docAbstract":"Identifying and analyzing closed depressions in karst areas is important for sinkhole hazard evaluation and land management. We created a sinkhole inventory in the karst region of northwest Puerto Rico using a lidar-derived elevation model acquired in 2018 approximately eleven months after Hurricane Maria. The goal of this project is to develop a geodatabase of sinkhole feature classes (polygons and points), relevant geometric attributes of each feature, and a density raster to portray areas of greater clustering of sinkholes as an input for future sinkhole susceptibility assessment. We used ArcGIS Pro® v3.0 to create closed depression polygons using two semi-automated extraction methods. A fill-difference method was used to capture depressions nine square meters and larger, and a contour tree method was used to capture nested depressions larger than one hundred square meters. Quality checks were conducted to eliminate non-karst depressions, such as human-made depressions and those resulting as artifacts from the automated methods. Geospatial data of land cover, soils, and geology helped to refine the results and improve quality control. The most challenging aspect of this effort was determining a true karst sinkhole from other depressions extracted from the lidar-derived elevation model. Limitations of this semi-automated method include false-positive depressions in the automated results and the exclusion of sinkholes in conducting large-scale eliminations based on landscape attributes. We approached this challenge by combining layers of other geospatial information to evaluate the type of process that could result in a closed depression. This project will help develop an efficient method to visualize karst hazards utilizing lidar-derived elevation models and sinkhole geomorphic expressions. The resulting geodatabase can be used to efficiently identify sinkhole susceptibility and support land management decision-making in karst areas.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of the 17th multidisciplinary conference on sinkholes and the engineering and environmental impacts of karst","largerWorkSubtype":{"id":12,"text":"Conference publication"},"language":"English","publisher":"National Cave and Karst Research Institute","usgsCitation":"Smith, L., Doctor, D.H., and Cox, C., 2023, Mapping closed depressions in the karst region of northwest Puerto Rico using lidar-derived elevation data obtained in 2018 after Hurricane Maria, <i>in</i> Proceedings of the 17th multidisciplinary conference on sinkholes and the engineering and environmental impacts of karst, v. 17, p. 239-248.","productDescription":"10 p.","startPage":"239","endPage":"248","ipdsId":"IP-148086","costCenters":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":486487,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://digitalcommons.usf.edu/sinkhole_2022/ProceedingswithProgram/"},{"id":486498,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Puerto Rico","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -67.30291697689199,\n              18.559923243339426\n            ],\n            [\n              -67.30291697689199,\n              18.330982046375794\n            ],\n            [\n              -66.86489408952299,\n              18.228131112250153\n            ],\n            [\n              -66.11901997545601,\n              18.330982046375794\n            ],\n            [\n              -66.11901997545601,\n              18.559923243339426\n            ],\n            [\n              -67.30291697689199,\n              18.559923243339426\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"17","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Smith, Lillian G.","contributorId":355868,"corporation":false,"usgs":false,"family":"Smith","given":"Lillian G.","affiliations":[{"id":36213,"text":"University of Redlands","active":true,"usgs":false}],"preferred":false,"id":938308,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Doctor, Daniel H. 0000-0002-8338-9722 dhdoctor@usgs.gov","orcid":"https://orcid.org/0000-0002-8338-9722","contributorId":2037,"corporation":false,"usgs":true,"family":"Doctor","given":"Daniel","email":"dhdoctor@usgs.gov","middleInitial":"H.","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":938309,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cox, Cheyenne L.","contributorId":355869,"corporation":false,"usgs":false,"family":"Cox","given":"Cheyenne L.","affiliations":[{"id":24583,"text":"former USGS employee","active":true,"usgs":false}],"preferred":false,"id":938310,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70250237,"text":"70250237 - 2023 - Yellowstone River Compact Commission seventy-first annual report 2022","interactions":[],"lastModifiedDate":"2026-02-03T15:10:40.474823","indexId":"70250237","displayToPublicDate":"2023-12-01T09:05:09","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":5883,"text":"Cooperator Report","active":true,"publicationSubtype":{"id":1}},"title":"Yellowstone River Compact Commission seventy-first annual report 2022","docAbstract":"<p>No abstract available.</p>","language":"English","publisher":"Yellowstone River Compact Commission","usgsCitation":"Davidson, S.L., 2023, Yellowstone River Compact Commission seventy-first annual report 2022: Cooperator Report, 45 p.","productDescription":"45 p.","ipdsId":"IP-152465","costCenters":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"links":[{"id":499440,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":499439,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.usgs.gov/media/files/yellowstone-river-compact-commission-seventy-first-annual-report-2022"}],"country":"United States","state":"Montana, North Dakota, Wyoming","otherGeospatial":"Yellowstone River basin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -103.30202023998697,\n              46.91729828037356\n            ],\n            [\n              -102.86275606887625,\n              47.305932172917124\n            ],\n            [\n              -102.86275606887625,\n              47.721288979115684\n            ],\n            [\n              -103.34594665709811,\n              47.8393587156163\n            ],\n            [\n              -104.66373917043084,\n              47.246327039430156\n            ],\n            [\n              -106.24509018642983,\n              46.82721042008123\n            ],\n            [\n              -107.60680911687372,\n              46.73697132311386\n            ],\n            [\n              -109.27601296709494,\n              46.73697132311386\n            ],\n            [\n              -110.28632056064981,\n              46.94729396432527\n            ],\n            [\n              -111.95552441087104,\n              46.94729396432527\n            ],\n            [\n              -112.79012633598192,\n              46.31385501970888\n            ],\n            [\n              -113.05368483864815,\n              45.611577424913406\n            ],\n            [\n              -112.57049425042628,\n              44.58840676429884\n            ],\n            [\n              -111.73589232531539,\n              44.71340404194632\n            ],\n            [\n              -111.03306965153841,\n              44.21179870462521\n            ],\n            [\n              -110.85736398309392,\n              43.163632537948956\n            ],\n            [\n              -110.59380548042715,\n              42.38983470662791\n            ],\n            [\n              -109.53957146976119,\n              41.77039401552537\n            ],\n            [\n              -106.94791286020732,\n              42.194875226416286\n            ],\n            [\n              -106.11331093509645,\n              42.84239196344987\n            ],\n            [\n              -105.93760526665194,\n              43.73763032826872\n            ],\n            [\n              -105.05907692443046,\n              45.08677944735058\n            ],\n            [\n              -103.91699007954222,\n              46.34418691818388\n            ],\n            [\n              -103.30202023998697,\n              46.91729828037356\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Davidson, Seth L. 0000-0002-9548-468X sdavids@usgs.gov","orcid":"https://orcid.org/0000-0002-9548-468X","contributorId":3626,"corporation":false,"usgs":true,"family":"Davidson","given":"Seth","email":"sdavids@usgs.gov","middleInitial":"L.","affiliations":[],"preferred":true,"id":889012,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70265060,"text":"70265060 - 2023 - Red Knot stopover population size and migration ecology at Delaware Bay, USA, 2023","interactions":[],"lastModifiedDate":"2025-04-01T14:07:00.224393","indexId":"70265060","displayToPublicDate":"2023-12-01T09:02:18","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":2,"text":"State or Local Government Series"},"title":"Red Knot stopover population size and migration ecology at Delaware Bay, USA, 2023","docAbstract":"<p>Red Knots (<i>Calidris canutus rufa</i>) stop at Delaware Bay on the mid-Atlantic coast of North America during northward migration to feed on eggs of horseshoe crabs (<i>Limulus polyphemus</i>). We conducted a mark-recapture-resight investigation to estimate the passage population of Red Knots at Delaware Bay in 2023. We used a Bayesian analysis of a Jolly-Seber model, which accounts for turnover in the population and the probability of detection during surveys. The 2023 passage population size was estimated at 39,361 (95% credible interval: 33,724–47,556). Although there is broad overlap in the credible intervals for population estimates from 2020–2023, the population estimate for 2023 was below 40,000 birds for only the second time since 2011. Horseshoe crabs have been harvested for use as bait in eel (<i>Anguilla rostrata</i>) and whelk (<i>Busycon</i>) fisheries since at least 1990. In the late 1990s and early 2000s, the number of Red Knots counted during aerial surveys at Delaware Bay declined from ~50,000 to ~13,000 and some avian conservation biologists hypothesized that horseshoe crab harvest levels in the 1990s prevented sufficient refueling for successful migration to the Arctic breeding grounds, reproduction, and survival for the remainder of the annual cycle. Since 2013, the harvest of horseshoe crabs in the Delaware Bay region has been managed using an Adaptive Resource Management (ARM) framework. The objective of the ARM framework is to manage sustainable harvest of Delaware Bay horseshoe crabs while maintaining ecosystem integrity and supporting Red Knot recovery with adequate stopover habitat for Red Knots and other migrating shorebirds. For annual harvest recommendations, the ARM framework requires annual estimates of horseshoe crab population size and the Red Knot stopover population size. The 2023 population size estimate will inform harvest recommendations in the next management cycle for decision making by the Atlantic States Marine Fisheries Commission.</p>","language":"English","publisher":"Delaware Division of Fish and Wildlife","usgsCitation":"Lyons, J.E., 2023, Red Knot stopover population size and migration ecology at Delaware Bay, USA, 2023, 15 p.","productDescription":"15 p.","ipdsId":"IP-159297","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":484058,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":484043,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://dnrec.alpha.delaware.gov/fish-wildlife/conservation/shorebirds/research/"}],"country":"United States","state":"Delaware, New Jersey","otherGeospatial":"Delaware Bay","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -75.08367028503963,\n              38.719590525784895\n            ],\n            [\n              -74.91863610562206,\n              38.97012711441013\n            ],\n            [\n              -74.8543007475435,\n              39.15256976333487\n            ],\n            [\n              -75.3829695595777,\n              39.44695257658836\n            ],\n            [\n              -75.51443746521609,\n              39.64539134375613\n            ],\n            [\n              -75.65429693929858,\n              39.619540213656876\n            ],\n            [\n              -75.56198968640427,\n              39.36698574058866\n            ],\n            [\n              -75.42772459128453,\n              39.14606207448017\n            ],\n            [\n              -75.3745779911329,\n              38.9679523390096\n            ],\n            [\n              -75.08367028503963,\n              38.719590525784895\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Lyons, James E. 0000-0002-9810-8751","orcid":"https://orcid.org/0000-0002-9810-8751","contributorId":222844,"corporation":false,"usgs":true,"family":"Lyons","given":"James","email":"","middleInitial":"E.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":932440,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70271371,"text":"70271371 - 2023 - Foreword","interactions":[],"lastModifiedDate":"2025-09-10T14:02:05.438173","indexId":"70271371","displayToPublicDate":"2023-12-01T08:59:10","publicationYear":"2023","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Foreword","docAbstract":"<p>No abstract available.</p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"The bog turtle: Natural history and conservation","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"ECO Wear & Publishing","usgsCitation":"Lovich, J.E., 2023, Foreword, chap. <i>of</i> The bog turtle: Natural history and conservation.","ipdsId":"IP-141777","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":495272,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"editors":[{"text":"Zappalorti, Robert T.","contributorId":169450,"corporation":false,"usgs":false,"family":"Zappalorti","given":"Robert","email":"","middleInitial":"T.","affiliations":[{"id":25511,"text":"Herpetological Associates, Inc., Plant and Wildlife Consultants, 575 Toms River Road, Jackson, NJ 08527 USA. Corresponding author e-mail: RZappalort@aol.com","active":true,"usgs":false}],"preferred":false,"id":948326,"contributorType":{"id":2,"text":"Editors"},"rank":1}],"authors":[{"text":"Lovich, Jeffrey E. 0000-0002-7789-2831 jeffrey_lovich@usgs.gov","orcid":"https://orcid.org/0000-0002-7789-2831","contributorId":458,"corporation":false,"usgs":true,"family":"Lovich","given":"Jeffrey","email":"jeffrey_lovich@usgs.gov","middleInitial":"E.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true},{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":948234,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70250953,"text":"70250953 - 2023 - Examining current bias and future projection consistency of globally downscaled climate projections commonly used in climate impact studies","interactions":[],"lastModifiedDate":"2024-01-13T14:57:56.409648","indexId":"70250953","displayToPublicDate":"2023-12-01T08:55:53","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1252,"text":"Climatic Change","active":true,"publicationSubtype":{"id":10}},"title":"Examining current bias and future projection consistency of globally downscaled climate projections commonly used in climate impact studies","docAbstract":"<div id=\"Abs1-section\" class=\"c-article-section\"><div id=\"Abs1-content\" class=\"c-article-section__content\"><p>The associated uncertainties of future climate projections are one of the biggest obstacles to overcome in studies exploring the potential regional impacts of future climate shifts. In remote and climatically complex regions, the limited number of available downscaled projections may not provide an accurate representation of the underlying uncertainty in future climate or the possible range of potential scenarios. Consequently, global downscaled projections are now some of the most widely used climate datasets in the world. However, they are rarely examined for representativeness of local climate or the plausibility of their projected changes. Here we explore the utility of two such global datasets (CHELSA and WorldClim2) in providing plausible future climate scenarios for regional climate change impact studies. Our analysis was based on three steps: (1) standardizing a baseline period to compare available global downscaled projections with regional observation-based datasets and regional downscaled datasets; (2) bias correcting projections using a single observation-based baseline; and (3) having controlled differences in baselines between datasets, exploring the patterns and magnitude of projected climate shifts from these datasets to determine their plausibility as future climate scenarios, using Hawaiʻi as an example region. Focusing on mean annual temperature and precipitation, we show projected climate shifts from these commonly used global datasets not only may vary significantly from one another but may also fall well outside the range of future scenarios derived from regional downscaling efforts. As species distribution models are commonly created from these datasets, we further illustrate how a substantial portion of variability in future species distribution shifts can arise from the choice of global dataset used. Hence, projected shifts between baseline and future scenarios from these global downscaled projections warrant careful evaluation before use in climate impact studies, something rarely done in the existing literature.</p></div></div>","language":"English","publisher":"Springer","doi":"10.1007/s10584-023-03623-z","usgsCitation":"Fortini, L., Kaiser, L.R., Frazier, A.G., and Giambelluca, T.W., 2023, Examining current bias and future projection consistency of globally downscaled climate projections commonly used in climate impact studies: Climatic Change, v. 176, https://doi.org/10.1007/s10584-023-03623-z.","productDescription":"169, 21 p.","startPage":"169","ipdsId":"IP-136355","costCenters":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"links":[{"id":441499,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10584-023-03623-z","text":"Publisher Index 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 \"}}]}","volume":"176","noUsgsAuthors":false,"publicationDate":"2023-12-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Fortini, Lucas Berio 0000-0002-5781-7295","orcid":"https://orcid.org/0000-0002-5781-7295","contributorId":236984,"corporation":false,"usgs":true,"family":"Fortini","given":"Lucas Berio","affiliations":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"preferred":true,"id":892396,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kaiser, Lauren R.","contributorId":200422,"corporation":false,"usgs":false,"family":"Kaiser","given":"Lauren","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":892397,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Frazier, Abby G.","contributorId":221112,"corporation":false,"usgs":false,"family":"Frazier","given":"Abby","email":"","middleInitial":"G.","affiliations":[{"id":40321,"text":"USDA Forest Service, Pacific Southwest Research Station","active":true,"usgs":false}],"preferred":false,"id":892398,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Giambelluca, Thomas W","contributorId":296956,"corporation":false,"usgs":false,"family":"Giambelluca","given":"Thomas","email":"","middleInitial":"W","affiliations":[{"id":64253,"text":"University of Hawaiʻi at Mānoa","active":true,"usgs":false}],"preferred":false,"id":892399,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70261199,"text":"70261199 - 2023 - New high resolution airborne geophysical surveys in Nevada And California for geothermal and mineral resource studies","interactions":[],"lastModifiedDate":"2024-11-29T14:54:09.70735","indexId":"70261199","displayToPublicDate":"2023-12-01T08:53:31","publicationYear":"2023","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"New high resolution airborne geophysical surveys in Nevada And California for geothermal and mineral resource studies","docAbstract":"The U.S. Geological Survey (USGS) and the Department of Energy (DOE) are collaborating to acquire high-resolution airborne magnetic and radiometric data to support geologic and geophysical mapping and modeling that will assist geothermal and critical mineral studies. Coordinated with these efforts are programs supporting geologic mapping and airborne LiDAR (light detection and ranging) surveys that yield detailed surface topographic models of the terrain over the same regions spanned by the geophysical surveys. The collaboration leverages resources from the USGS and DOE to acquire large regional datasets that will provide fundamental data necessary to map surface and subsurface geology and structure to benefit mineral and resource program objectives of both agencies. Such regionally uniform datasets are important for geothermal research to assist in identifying geologically favorable settings and as invaluable inputs in predictive models targeting undiscovered resources that use knowledge-driven (e.g., play fairway analysis) or data-driven approaches (e.g., machine-learning methods) to reduce risk associated with resource exploration. These data will also serve a wide range of other related activities from hazard (earthquake, volcano, landslide, environmental) and resource (water, mineral, energy) studies, to mapping and land management.\n\nSurveys were conducted in two areas that were selected because they host substantial geothermal and mineral potential in California and Nevada. The data will aid several ongoing USGS and DOE projects aimed at characterizing geothermal and mineral systems, understanding the factors controlling their occurrence, and improving future national resource assessments. The first of these surveys (referred to as GeoDAWN) was collected over northern and western Nevada and eastern California and spans areas of major resource potential associated with the Walker Lane and western Great Basin. This includes Clayton Valley, which hosts substantial lithium brine and clay resources, and the Humboldt Mafic Complex, which constitutes a potentially important resource of critical minerals (including cobalt, rare earth elements, platinum group elements, iron, chromium, nickel, and copper). The second survey area (referred to as GeoFlight) is focused over\n\nthe Salton Trough in southern California that contains some of the largest and hottest known hydrothermal systems in the world, as well as a substantial lithium brine resource that could potentially meet the nation’s lithium demand for electric vehicles. Data from both surveys will be made publicly available through USGS publications and online data repositories. Future efforts under this collaboration are presently being evaluated and may involve acquisition of other data sets such as airborne gravity, electromagnetic or hyperspectral data to address research targets.","language":"English","publisher":"Geothermal Resources Council","usgsCitation":"Glen, J.M., and Earney, T.E., 2023, New high resolution airborne geophysical surveys in Nevada And California for geothermal and mineral resource studies, v. 47, p. 1738-1762.","productDescription":"25 p.","startPage":"1738","endPage":"1762","ipdsId":"IP-156123","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":464588,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":464580,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.geothermal-library.org/index.php?mode=pubs&action=view&record=1034804","linkFileType":{"id":5,"text":"html"}}],"volume":"47","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Glen, Jonathan M.G. 0000-0002-3502-3355 jglen@usgs.gov","orcid":"https://orcid.org/0000-0002-3502-3355","contributorId":176530,"corporation":false,"usgs":true,"family":"Glen","given":"Jonathan","email":"jglen@usgs.gov","middleInitial":"M.G.","affiliations":[{"id":309,"text":"Geology and Geophysics Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":919603,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Earney, Tait E. 0000-0002-1504-0457","orcid":"https://orcid.org/0000-0002-1504-0457","contributorId":210080,"corporation":false,"usgs":true,"family":"Earney","given":"Tait","email":"","middleInitial":"E.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":919604,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70250443,"text":"70250443 - 2023 - Fractures, scarps, faults, and landslides mapped using LiDAR, Glacier Bay National Park and Preserve, Alaska","interactions":[],"lastModifiedDate":"2023-12-09T14:53:33.90405","indexId":"70250443","displayToPublicDate":"2023-12-01T08:48:59","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"title":"Fractures, scarps, faults, and landslides mapped using LiDAR, Glacier Bay National Park and Preserve, Alaska","docAbstract":"<p><span>This map of fractures, scarps, faults, and landslides was completed to identify areas in Glacier Bay National Park and Preserve that may present a landslide-generated tsunami hazard. To address the potential of landslide and tsunami hazards in the park, the National Park Service (NPS) and the US Geological Survey (USGS) partnered to conduct a multi-year hazard assessment of Glacier Bay National Park and Preserve. To produce the map described in this report, we used the newly acquired (2019-2020) light detection and ranging (LiDAR) 0.5 to 1.0 m digital elevation models (DEMs) that cover all the coastal areas of the park and extend up to the ridgetops in places with steep slopes. A bare earth DEM was used to identify and map areas of incipient landslides (i.e., fractures and scarps), fault scarps, and areas where landslides have clearly occurred in the past (i.e., areas where scars and deposits are clearly visible). This map provides a baseline data set that can be used to aid forecasts of where landslides are most likely to occur in the future.</span></p>","language":"English","publisher":"National Park Service","doi":"10.36967/2300706","collaboration":"National Park Service","usgsCitation":"Hults, C., Coe, J.A., and Avdievitch, N.N., 2023, Fractures, scarps, faults, and landslides mapped using LiDAR, Glacier Bay National Park and Preserve, Alaska, iv, 14 p., https://doi.org/10.36967/2300706.","productDescription":"iv, 14 p.","ipdsId":"IP-147660","costCenters":[{"id":78686,"text":"Geologic Hazards Science Center - Seismology / Geomagnetism","active":true,"usgs":true}],"links":[{"id":423385,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Glacier Bay National Park and Preserve","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -139.23040794383448,\n              59.9305550708161\n            ],\n            [\n              -139.23040794383448,\n              57.252640525398476\n            ],\n            [\n              -134.22064231883454,\n              57.252640525398476\n            ],\n            [\n              -134.22064231883454,\n              59.9305550708161\n            ],\n            [\n              -139.23040794383448,\n              59.9305550708161\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Hults, Chad","contributorId":332290,"corporation":false,"usgs":false,"family":"Hults","given":"Chad","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":889926,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Coe, Jeffrey A. 0000-0002-0842-9608 jcoe@usgs.gov","orcid":"https://orcid.org/0000-0002-0842-9608","contributorId":1333,"corporation":false,"usgs":true,"family":"Coe","given":"Jeffrey","email":"jcoe@usgs.gov","middleInitial":"A.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":309,"text":"Geology and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":889927,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Avdievitch, Nikita N. 0000-0002-2507-2962","orcid":"https://orcid.org/0000-0002-2507-2962","contributorId":225492,"corporation":false,"usgs":true,"family":"Avdievitch","given":"Nikita","email":"","middleInitial":"N.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":889928,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70257372,"text":"70257372 - 2023 - Simulation modeling to assess line transect distance sampling under a range of translocation scenarios","interactions":[],"lastModifiedDate":"2024-09-04T15:33:06.278948","indexId":"70257372","displayToPublicDate":"2023-12-01T08:35:40","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2287,"text":"Journal of Fish and Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Simulation modeling to assess line transect distance sampling under a range of translocation scenarios","docAbstract":"<p><span>The accuracy of posttranslocation population monitoring methods is critical to assessing long-term success in translocation programs. Translocation can produce unique challenges to monitoring efforts; therefore, it is important to understand the flexibility and robustness of commonly used monitoring methods. In Florida, USA, thousands of gopher tortoises&nbsp;</span><i>Gopherus polyphemus</i><span>&nbsp;have been, and continue to be, translocated from development sites to permitted recipient sites. These recipient sites create a broad range of potential monitoring scenarios due to variability in soft-release strategies, habitat conditions, and population demographics. Line transect distance sampling is an effective method for monitoring natural tortoise populations, but it is currently untested for translocated populations. We therefore produced 3,024 individual-based, spatially explicit scenarios of translocated tortoise populations that differed in recipient site and tortoise population properties, based on real-world examples, literature review, and expert opinion. We virtually sampled simulated tortoise populations by using line transect distance sampling methods and built a Bayesian hierarchical model to estimate the population density for each simulation, which incorporated individual-level covariates (i.e., burrow width and burrow occupancy). Line transect distance sampling was largely appropriate for the conditions that typify gopher tortoise recipient sites, particularly when detection probability on the transect lines was greater than or equal to 0.85. Designing the layout of transects relative to the orientation of soft-release pens, to avoid possible sampling biases that lead to extreme outliers in estimates of tortoise densities, resulted in more accurate population estimates. We also suggest that use of individual-level covariates, applied using a Bayesian framework as demonstrated in our study, may improve the applicability of line transect distance sampling surveys in a variety of contexts and that simulation can be a powerful tool for assessing survey design in complex sampling situations.</span></p>","language":"English","publisher":"U.S. Fish and Wildlife Service","doi":"10.3996/JFWM-23-029","usgsCitation":"Jones, M.D., Smith, L., Gentry Richardson, K., DeSha, J., Castellón, T., Hipes, D., Kalfin, A., Halstead, N.T., and Hunter, E.A., 2023, Simulation modeling to assess line transect distance sampling under a range of translocation scenarios: Journal of Fish and Wildlife Management, v. 14, no. 2, p. 385-399, https://doi.org/10.3996/JFWM-23-029.","productDescription":"15 p.","startPage":"385","endPage":"399","ipdsId":"IP-151978","costCenters":[{"id":199,"text":"Coop Res Unit 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Nicole","contributorId":342510,"corporation":false,"usgs":false,"family":"DeSha","given":"J. Nicole","affiliations":[{"id":12556,"text":"Florida Fish and Wildlife Conservation Commission","active":true,"usgs":false}],"preferred":false,"id":910149,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Castellón, Traci","contributorId":342511,"corporation":false,"usgs":false,"family":"Castellón","given":"Traci","affiliations":[{"id":12556,"text":"Florida Fish and Wildlife Conservation Commission","active":true,"usgs":false}],"preferred":false,"id":910150,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hipes, Dan","contributorId":342512,"corporation":false,"usgs":false,"family":"Hipes","given":"Dan","email":"","affiliations":[{"id":81882,"text":"Florida Natural Areas Inventory","active":true,"usgs":false}],"preferred":false,"id":910151,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kalfin, Alex","contributorId":342513,"corporation":false,"usgs":false,"family":"Kalfin","given":"Alex","email":"","affiliations":[{"id":12556,"text":"Florida Fish and Wildlife Conservation Commission","active":true,"usgs":false}],"preferred":false,"id":910152,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Halstead, Neal T.","contributorId":342514,"corporation":false,"usgs":false,"family":"Halstead","given":"Neal","email":"","middleInitial":"T.","affiliations":[{"id":81883,"text":"Wildlands Conservation","active":true,"usgs":false}],"preferred":false,"id":910153,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Hunter, Elizabeth Ann 0000-0003-4710-167X","orcid":"https://orcid.org/0000-0003-4710-167X","contributorId":288535,"corporation":false,"usgs":true,"family":"Hunter","given":"Elizabeth","email":"","middleInitial":"Ann","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":911525,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70250393,"text":"70250393 - 2023 - Blue snowflakes in a warming world: Karner blue butterfly climate change vulnerability synthesis and best practices for adaptation","interactions":[],"lastModifiedDate":"2023-12-06T14:23:57.214451","indexId":"70250393","displayToPublicDate":"2023-12-01T08:23:21","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":53,"text":"Natural Resource Report","active":false,"publicationSubtype":{"id":1}},"seriesNumber":"NPS/NRSS/CCRP/NRR—2023/2602","title":"Blue snowflakes in a warming world: Karner blue butterfly climate change vulnerability synthesis and best practices for adaptation","docAbstract":"<p><span>This report—developed at the request of the United States Fish and Wildlife Service-led Karner Blue Butterfly Recovery Team by Recovery Team members and partners—provides a Karner blue butterfly climate change vulnerability synthesis, explores a range of potential responses, and presents best practices for climate change-informed conservation of the species.</span><br><br><span>The three decades since the Karner blue butterfly’s (Lycaeides [Plebejus] melissa samuelis Nabokov) listing as federally endangered in the United States have seen a diverse and dedicated research and management community coalesce around the species’ recovery. This geographically expansive conservation collaboration has broken new ground for threatened and endangered species recovery. Many Karner blue recovery areas are making steady progress towards recovery goals, but some are not. An extremely hot and dry 2012, perhaps aided by adverse longer-term climate trends such as declining snow cover, extirpated the Karner blue from Indiana Dunes National Park and the surrounding Indiana Dunes Karner Blue Butterfly Recovery Unit—the southernmost recovery unit and once host to one of the species’ largest populations—as well as from northwest Ohio.</span><br><br><span>Because of the fundamental challenge that climate change represents to Karner blue butterfly recovery and of the general need for endangered species conservation plans to better address climate change, the United States Fish and Wildlife Service-led Karner Blue Butterfly Recovery Team tasked a subset of the team to:</span><br><br><span>Explore the species’ climate change sensitivity and adaptive capacity, review ongoing and projected climate change across the Karner blue range and associated uncertainties, and develop and suggest best practices concerning long-term adaptation strategies.</span><br><br><span>Consistent with that mandate, this report synthesizes what is known about Karner blue climate change vulnerability and applies current thinking in climate change adaptation to help foster strategic, long-term, climate change-informed Karner blue recovery and conservation. It develops and explores a range of potential climate change-informed butterfly- and habitat-stewardship responses, using the resist-accept-direct (RAD) framework to foster a broad range of approaches, and provides guidance regarding how they may be pursued. The report also provides suggestions for improving the climate change-exposure component of Karner blue vulnerability assessment.</span></p>","language":"English","publisher":"National Park Service","doi":"10.36967/2301333","usgsCitation":"Schuurman, G.W., Hoving, C.L., Hess, A.N., Bristow, L.V., Delphey, P.J., Hellmann, J., Keough, H.L., Knutson, R.L., and Kellner, A., 2023, Blue snowflakes in a warming world: Karner blue butterfly climate change vulnerability synthesis and best practices for adaptation: Natural Resource Report NPS/NRSS/CCRP/NRR—2023/2602, xvii, 154 p., https://doi.org/10.36967/2301333.","productDescription":"xvii, 154 p.","ipdsId":"IP-152801","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":423268,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n 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Gregor W.","contributorId":173975,"corporation":false,"usgs":false,"family":"Schuurman","given":"Gregor","email":"","middleInitial":"W.","affiliations":[{"id":5106,"text":"National Park Service, Yellowstone National Park, Mammoth, Wyoming 82190","active":true,"usgs":false}],"preferred":false,"id":889720,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hoving, Christopher L.","contributorId":329860,"corporation":false,"usgs":false,"family":"Hoving","given":"Christopher","email":"","middleInitial":"L.","affiliations":[{"id":36986,"text":"Michigan Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":889721,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hess, Anna N. 0000-0001-7523-3050","orcid":"https://orcid.org/0000-0001-7523-3050","contributorId":332226,"corporation":false,"usgs":false,"family":"Hess","given":"Anna","email":"","middleInitial":"N.","affiliations":[{"id":79419,"text":"Upper Midwest Environmental Sciences Center (former USGS employee)","active":true,"usgs":false}],"preferred":false,"id":889722,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bristow, Lainey V.","contributorId":332227,"corporation":false,"usgs":false,"family":"Bristow","given":"Lainey","email":"","middleInitial":"V.","affiliations":[{"id":79421,"text":"Hiawatha Academies","active":true,"usgs":false}],"preferred":false,"id":889723,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Delphey, Philip J.","contributorId":332228,"corporation":false,"usgs":false,"family":"Delphey","given":"Philip","email":"","middleInitial":"J.","affiliations":[{"id":79422,"text":"U.S. Fish and Wildlife Society","active":true,"usgs":false}],"preferred":false,"id":889724,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hellmann, Jessica J.","contributorId":331509,"corporation":false,"usgs":false,"family":"Hellmann","given":"Jessica J.","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":889725,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Keough, Heather L.","contributorId":332229,"corporation":false,"usgs":false,"family":"Keough","given":"Heather","email":"","middleInitial":"L.","affiliations":[{"id":79423,"text":"U.S. Forest Service- Huron-Manistee National Forests","active":true,"usgs":false}],"preferred":false,"id":889726,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Knutson, Randy L.","contributorId":332230,"corporation":false,"usgs":false,"family":"Knutson","given":"Randy","email":"","middleInitial":"L.","affiliations":[{"id":79424,"text":"National Park Service- Indiana Dunes National Park","active":true,"usgs":false}],"preferred":false,"id":889727,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Kellner, Annie","contributorId":302415,"corporation":false,"usgs":false,"family":"Kellner","given":"Annie","email":"","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":889728,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70258638,"text":"70258638 - 2023 - Sonoran desert tortoise: Gopherus morafkai","interactions":[],"lastModifiedDate":"2024-09-19T13:31:49.500487","indexId":"70258638","displayToPublicDate":"2023-12-01T08:16:19","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":18631,"text":"IUCN Red List of Threatened Species","active":true,"publicationSubtype":{"id":10}},"title":"Sonoran desert tortoise: Gopherus morafkai","docAbstract":"<p><span>Sonoran Desert Tortoise&nbsp;</span><i>Gopherus morafkai</i><span>&nbsp;has most recently been assessed for&nbsp;</span><i>The IUCN Red List of Threatened Species</i><span>&nbsp;in 2019.&nbsp;</span><i>Gopherus morafkai</i><span>&nbsp;is listed as Vulnerable under criteria A2abce+4abce.</span></p>","language":"English","publisher":"IUCN","doi":"10.2305/IUCN.UK.2023-1.RLTS.T97246109A97246177.en","usgsCitation":"Averill-Murray, R., Rosen, P., Jones, C., Jones, T., Lara-Resendiz, R.A., Edwards, T., Karl, A., and Berry, K.H., 2023, Sonoran desert tortoise: Gopherus morafkai: IUCN Red List of Threatened Species, HTML Document, https://doi.org/10.2305/IUCN.UK.2023-1.RLTS.T97246109A97246177.en.","productDescription":"HTML Document","ipdsId":"IP-141177","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":441509,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"http://dx.doi.org/10.2305/iucn.uk.2023-1.rlts.t97246109a97246177.en","text":"Publisher Index Page"},{"id":439134,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Mexico, United States","state":"Arizona, Sonora","otherGeospatial":"Sonoran Desert","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -110.49110469886017,\n              27.729764903155512\n            ],\n            [\n              -109.68036417007879,\n              29.323278884808353\n            ],\n            [\n              -109.50954231107093,\n              31.88120530174399\n            ],\n            [\n              -109.83798108105655,\n              33.351483999963165\n            ],\n            [\n              -110.53104774254575,\n              33.782727941901754\n            ],\n            [\n              -112.39560264303194,\n              34.75304507185233\n            ],\n            [\n              -113.32141073849851,\n              36.376959089787405\n            ],\n            [\n              -113.93130211754695,\n              36.39393440910057\n            ],\n            [\n              -114.17530901823386,\n              35.238424276141174\n            ],\n            [\n              -114.2054690932774,\n              33.10177972804529\n            ],\n            [\n              -113.89750443383366,\n              32.123749576741005\n            ],\n            [\n              -112.59845871401433,\n              30.041055151051935\n            ],\n            [\n              -112.36405466098628,\n              28.6740514227059\n            ],\n            [\n              -110.49110469886017,\n              27.729764903155512\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Averill-Murray, R.C. 0000-0002-4424-2269","orcid":"https://orcid.org/0000-0002-4424-2269","contributorId":238891,"corporation":false,"usgs":false,"family":"Averill-Murray","given":"R.C.","email":"","affiliations":[{"id":27594,"text":"Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":913490,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rosen, P.C.","contributorId":107640,"corporation":false,"usgs":true,"family":"Rosen","given":"P.C.","email":"","affiliations":[],"preferred":false,"id":913491,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jones, C.A.","contributorId":344334,"corporation":false,"usgs":false,"family":"Jones","given":"C.A.","email":"","affiliations":[],"preferred":false,"id":913492,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jones, T.R.","contributorId":344326,"corporation":false,"usgs":false,"family":"Jones","given":"T.R.","email":"","affiliations":[{"id":12922,"text":"Arizona Game and Fish Department","active":true,"usgs":false}],"preferred":false,"id":913493,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lara-Resendiz, R. A.","contributorId":344327,"corporation":false,"usgs":false,"family":"Lara-Resendiz","given":"R.","middleInitial":"A.","affiliations":[{"id":25354,"text":"Universidad Nacional Autónoma de México","active":true,"usgs":false}],"preferred":false,"id":913494,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Edwards, Taylor","contributorId":239460,"corporation":false,"usgs":false,"family":"Edwards","given":"Taylor","affiliations":[{"id":47864,"text":"Genetics Core, University of Arizona, Tucson, AR, USA","active":true,"usgs":false}],"preferred":false,"id":913495,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Karl, A.","contributorId":344333,"corporation":false,"usgs":false,"family":"Karl","given":"A.","email":"","affiliations":[],"preferred":false,"id":913496,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Berry, Kristin H. 0000-0003-1591-8394 kristin_berry@usgs.gov","orcid":"https://orcid.org/0000-0003-1591-8394","contributorId":437,"corporation":false,"usgs":true,"family":"Berry","given":"Kristin","email":"kristin_berry@usgs.gov","middleInitial":"H.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":913524,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70250639,"text":"70250639 - 2023 - Detrending Great Basin elevation to identify structural patterns for identifying geothermal favorability","interactions":[],"lastModifiedDate":"2024-10-15T17:20:38.127462","indexId":"70250639","displayToPublicDate":"2023-12-01T07:22:20","publicationYear":"2023","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"seriesTitle":{"id":18745,"text":"Geothermal Resources Council Transactions","active":true,"publicationSubtype":{"id":19}},"title":"Detrending Great Basin elevation to identify structural patterns for identifying geothermal favorability","docAbstract":"Topography provides information about the structural controls of the Great Basin and therefore information that may be used to identify favorable structural settings for geothermal systems. The Nevada Machine Learning Project (NVML) tested the use of a digital elevation map (DEM) of topography as an input feature to predict geothermal system favorability. A recent study re-examines the NVML data, identifying the DEM as the most important feature, showing a broad uniform pattern of high-favorability in the lower-elevation west and low-favorability in the higher elevation east of their study area in north-central Nevada. This regional elevation trend conflicts with the geologic notion that local relative topography should be used to identify geologic structures associated with favorable structural settings for hydrothermal upflow. Specifically, local relative topography gives information about position in the mountains, in the valleys, or at the transitions between, aiding in identification of faults and fault intersections. As part of U.S. Geological Survey efforts to engineer features that are useful for predicting geothermal resources, we construct a detrended elevation map that emphasizes local relative topography and highlights features that geologists use for identifying geothermal systems (i.e., providing machine learning algorithms with features that may improve predictive skill by emphasizing the information used by geologists). Herein, we describe the removal of the regional trend in elevation to emphasize the basin-and-range scale structural features, creating detrended elevation maps.\nRegional elevation trends were estimated using a local linear regression and subtracted from the actual elevation using a 30-m DEM. In an effort to optimize the detrended surface, alternate versions were produced with different rates of smoothness resulting in three detrended elevation maps. The resulting elevation trend surfaces (a proxy for crustal thickness) are compared with conductive heat flow maps, and a general pattern was observed of a negative correlation between heat flow and regional elevation in many areas, indicating that thinner crust may be causing elevated heat flow in some areas and thicker crust may cause the observed heat flow lows. Because these detrended elevation maps emphasize geologic structure and relative displacement, these products may also be useful for other geologic research including mineral exploration, hydrologic research, and defining geologic provinces.","language":"English","publisher":"Geothermal Rising","usgsCitation":"DeAngelo, J., Burns, E.R., Mordensky, S.P., and Lindsey, C.R., 2023, Detrending Great Basin elevation to identify structural patterns for identifying geothermal favorability, v. 47, p. 1694-1702.","productDescription":"9 p.","startPage":"1694","endPage":"1702","ipdsId":"IP-155138","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":423865,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":423843,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://www.geothermal-library.org/index.php?mode=pubs&action=view&record=1034786","linkFileType":{"id":5,"text":"html"}}],"volume":"47","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"DeAngelo, Jacob 0000-0002-7348-7839 jdeangelo@usgs.gov","orcid":"https://orcid.org/0000-0002-7348-7839","contributorId":237879,"corporation":false,"usgs":true,"family":"DeAngelo","given":"Jacob","email":"jdeangelo@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":890682,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Burns, Erick R. 0000-0002-1747-0506 eburns@usgs.gov","orcid":"https://orcid.org/0000-0002-1747-0506","contributorId":192154,"corporation":false,"usgs":true,"family":"Burns","given":"Erick","email":"eburns@usgs.gov","middleInitial":"R.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":890683,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mordensky, Stanley Paul 0000-0001-8607-303X","orcid":"https://orcid.org/0000-0001-8607-303X","contributorId":292014,"corporation":false,"usgs":true,"family":"Mordensky","given":"Stanley","email":"","middleInitial":"Paul","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":890684,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lindsey, Cary Ruth 0000-0001-5693-9664","orcid":"https://orcid.org/0000-0001-5693-9664","contributorId":292016,"corporation":false,"usgs":true,"family":"Lindsey","given":"Cary","email":"","middleInitial":"Ruth","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":890685,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70251485,"text":"70251485 - 2023 - Modeling extreme water levels in the Salish Sea: The importance of including remote sea level anomalies for application in hydrodynamic simulations","interactions":[],"lastModifiedDate":"2024-02-13T13:12:40.92934","indexId":"70251485","displayToPublicDate":"2023-12-01T07:05:06","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3709,"text":"Water","active":true,"publicationSubtype":{"id":10}},"title":"Modeling extreme water levels in the Salish Sea: The importance of including remote sea level anomalies for application in hydrodynamic simulations","docAbstract":"<div class=\"html-p\">Extreme water-level recurrence estimates for a complex estuary using a high-resolution 2D model and a new method for estimating remotely generated sea level anomalies (SLAs) at the model boundary have been developed. The hydrodynamic model accurately resolves the dominant physical processes contributing to extreme water levels across the Washington State waters of the Salish Sea, including the relative contribution of remote SLA and other non-tidal residual processes that drive extreme water levels above the predicted tide. The model’s predictions have errors of less than 15 cm (&lt;5% of 3–4 m tidal range) at eight tide gauge locations across the model domain. The influence of remote SLAs at the seaward boundary of the model was implemented using a multivariate regression of readily available and locally relevant wind, sea surface temperature, and pressure anomaly data, combined with El Niño Index data (R<sup>2</sup><span>&nbsp;</span>= 0.76). The hydrodynamic model simulations using the remote SLA predictor compared well with simulations using the widely used data-assimilative global ocean model HYCOM SLA data (root mean square difference of 5.5 cm). Extreme water-level recurrence estimates with and without remote SLA show that remote forcing accounts for 50–60% of the total water level anomaly observed along Salish Sea shorelines. The resulting model simulations across decadal timescales provide estimates of extreme water level recurrence across the Salish Sea, capturing climate variability important to long-term coastal hazard planning. This approach has widespread applications for other complex estuarine systems.</div>","language":"English","publisher":"MDPI","doi":"10.3390/w15234167","usgsCitation":"Grossman, E.E., Tehranirad, B., Nederhoff, K., Crosby, S., Stevens, A.W., VanArendonk, N.R., Nowacki, D.J., Erikson, L.H., and Barnard, P.L., 2023, Modeling extreme water levels in the Salish Sea: The importance of including remote sea level anomalies for application in hydrodynamic simulations: Water, v. 15, no. 23, 4167, 24 p., https://doi.org/10.3390/w15234167.","productDescription":"4167, 24 p.","ipdsId":"IP-146065","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":441512,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/w15234167","text":"Publisher Index Page"},{"id":425601,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -130.71708563654397,\n              52.25092388193306\n            ],\n            [\n              -130.71708563654397,\n              44.0989255001023\n            ],\n            [\n              -118.67607001154398,\n              44.0989255001023\n            ],\n            [\n              -118.67607001154398,\n              52.25092388193306\n            ],\n            [\n              -130.71708563654397,\n              52.25092388193306\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"15","issue":"23","noUsgsAuthors":false,"publicationDate":"2023-12-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Grossman, Eric E. 0000-0003-0269-6307 egrossman@usgs.gov","orcid":"https://orcid.org/0000-0003-0269-6307","contributorId":196610,"corporation":false,"usgs":true,"family":"Grossman","given":"Eric","email":"egrossman@usgs.gov","middleInitial":"E.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true}],"preferred":true,"id":894698,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tehranirad, Babak 0000-0002-1634-9165","orcid":"https://orcid.org/0000-0002-1634-9165","contributorId":299107,"corporation":false,"usgs":false,"family":"Tehranirad","given":"Babak","affiliations":[{"id":64774,"text":"contracted to USGS PCMSC","active":true,"usgs":false}],"preferred":false,"id":894699,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nederhoff, Kees 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Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":894702,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"VanArendonk, Nathan R.","contributorId":334097,"corporation":false,"usgs":false,"family":"VanArendonk","given":"Nathan","email":"","middleInitial":"R.","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":894703,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Nowacki, Daniel J. 0000-0002-7015-3710 dnowacki@usgs.gov","orcid":"https://orcid.org/0000-0002-7015-3710","contributorId":174586,"corporation":false,"usgs":true,"family":"Nowacki","given":"Daniel","email":"dnowacki@usgs.gov","middleInitial":"J.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science 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,{"id":70250655,"text":"70250655 - 2023 - A simple approach to modeling light attenuation in the Sacramento-San Joaquin Delta using commonly available data","interactions":[],"lastModifiedDate":"2023-12-22T12:57:30.745882","indexId":"70250655","displayToPublicDate":"2023-12-01T06:52:05","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":10389,"text":"San Francisco Estuary and Watershed Sciences","active":true,"publicationSubtype":{"id":10}},"title":"A simple approach to modeling light attenuation in the Sacramento-San Joaquin Delta using commonly available data","docAbstract":"<div id=\"main\"><div data-reactroot=\"\"><div class=\"body\"><div><div class=\"c-columns--sticky-sidebar\"><div class=\"c-tabs\"><div class=\"c-tabs__content\"><div class=\"c-tabcontent\"><div class=\"c-clientmarkup\"><p>The diffuse attenuation coefficient of photosynthetically active radiation (KdPAR) is commonly used to predict light attenuation in aquatic productivity models, but obtaining measurements of PAR to compute KdPAR is difficult. In situ calculations of KdPAR require multiple measurements of PAR through the water column, and these measurements are infeasible for real-time recording. Instead, predictive models using surface-water measurements may be used. Traditional KdPAR models are based on open-ocean habitats and rely on chlorophyll—as a proxy measurement for phytoplankton abundance—as the main predictive parameter. However, elevated suspended sediments and dissolved organic materials may also affect KdPAR values of inland water bodies and estuaries. In this study, we leverage KdPAR calculations derived from in situ light measurements collected along with surface-water-quality parameters across the Sacramento-San Joaquin River Delta in California, USA (the Delta). Sampling occurred between January of 2013 and May of 2014. We also explored regional and seasonal effects, but these did not clearly affect the model. Ultimately, the best-performing model included surface-level turbidity only (R2 = 0.91). The simplicity of the model facilitates use of KdPAR estimates for a variety of purposes throughout the Delta, including euphotic depth calculations, and as inputs to primary-productivity and habitat-suitability models. We demonstrate the model’s usability with two open-sources data sets (one spatially dense, and one temporally dense), and estimate KdPAR, euphotic depth, and primary productivity within the Delta. We provide calculations for each estimation, allowing users to easily adopt these models and apply them to their own data or with open-sourced data, which are abundant.</p></div></div></div></div></div></div></div></div></div>","language":"English","publisher":"University of California","doi":"10.15447/sfews.2023v21iss4art5","usgsCitation":"Richardson, E.T., Bouma-Gregson, K., O’Donnell, K., and Bergamaschi, B.A., 2023, A simple approach to modeling light attenuation in the Sacramento-San Joaquin Delta using commonly available data: San Francisco Estuary and Watershed Sciences, v. 21, no. 4, 5, 15 p., https://doi.org/10.15447/sfews.2023v21iss4art5.","productDescription":"5, 15 p.","ipdsId":"IP-149629","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":441515,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.15447/sfews.2023v21iss4art5","text":"Publisher Index Page"},{"id":423859,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Sacramento-San Joaquin Delta","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -122.26086948103463,\n              38.478699734733226\n            ],\n            [\n              -122.26086948103463,\n              37.77218409560264\n            ],\n            [\n              -121.28033969587833,\n              37.77218409560264\n            ],\n            [\n              -121.28033969587833,\n              38.478699734733226\n            ],\n            [\n              -122.26086948103463,\n              38.478699734733226\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"21","issue":"4","noUsgsAuthors":false,"publicationDate":"2023-12-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Richardson, Emily T. 0000-0003-2696-8266","orcid":"https://orcid.org/0000-0003-2696-8266","contributorId":304430,"corporation":false,"usgs":true,"family":"Richardson","given":"Emily","email":"","middleInitial":"T.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":890899,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bouma-Gregson, Keith 0000-0002-0304-6034","orcid":"https://orcid.org/0000-0002-0304-6034","contributorId":311235,"corporation":false,"usgs":true,"family":"Bouma-Gregson","given":"Keith","email":"","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":890900,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"O’Donnell, Katy 0000-0003-2323-8970 kodonnell@usgs.gov","orcid":"https://orcid.org/0000-0003-2323-8970","contributorId":5640,"corporation":false,"usgs":true,"family":"O’Donnell","given":"Katy","email":"kodonnell@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":890901,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bergamaschi, Brian A. 0000-0002-9610-5581 bbergama@usgs.gov","orcid":"https://orcid.org/0000-0002-9610-5581","contributorId":140776,"corporation":false,"usgs":true,"family":"Bergamaschi","given":"Brian","email":"bbergama@usgs.gov","middleInitial":"A.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":890902,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70250601,"text":"70250601 - 2023 - Divergent responses of western Alaska salmon to a changing climate","interactions":[],"lastModifiedDate":"2024-02-07T17:14:56.026768","indexId":"70250601","displayToPublicDate":"2023-12-01T06:49:07","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"title":"Divergent responses of western Alaska salmon to a changing climate","docAbstract":"<h3 class=\"wp-block-heading\">Headlines</h3><ul><li>Western Alaska salmon abundance reached historic extremes during 2021-22, with record lows for Chinook and chum salmon (81% and 92% below the 30-year mean, respectively) and record highs for sockeye salmon (98% above the 30-year mean).</li><li>Salmon are maturing at smaller sizes. Since the 1970s, for example, Yukon River Chinook salmon have decreased an estimated 6% in mean adult body length and 15% in fecundity, likely exacerbating population declines.</li><li>Salmon population declines have led to fishery closures, worsened user conflicts, and had profound cultural and food security impacts in Indigenous communities that have been tied to salmon for millennia.</li><li>Changes in abundance and size are associated with climatic changes in freshwater and marine ecosystems and competition in the ocean. Changes in predators, food supply, and disease are also likely important drivers.</li></ul>","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"2023 Arctic Report Card","largerWorkSubtype":{"id":4,"text":"Other Government Series"},"language":"English","publisher":"NOAA","doi":"10.25923/f2hv-5581","usgsCitation":"Schoen, E., Howard, K.G., Murphy, J., Schindler, D., Westley, P., and von Biela, V.R., 2023, Divergent responses of western Alaska salmon to a changing climate, HTML Document, https://doi.org/10.25923/f2hv-5581.","productDescription":"HTML Document","ipdsId":"IP-158550","costCenters":[{"id":65299,"text":"Alaska Science Center Ecosystems","active":true,"usgs":true}],"links":[{"id":423744,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -139.6101604988394,\n              61.2015830860681\n            ],\n            [\n              -139.43437924883952,\n              66.17389289158615\n            ],\n            [\n              -140.1375042488394,\n              67.95408453891542\n            ],\n            [\n              -144.7078167488394,\n              68.92291840612816\n            ],\n            [\n              -153.8484417488394,\n              67.42020730537521\n            ],\n            [\n              -160.87969174883918,\n              65.52668632036398\n            ],\n            [\n              -162.9890667488394,\n              64.10587463586813\n            ],\n            [\n              -167.20781674883932,\n              62.364181084501865\n            ],\n            [\n              -166.50469174883943,\n              59.81851305865456\n            ],\n            [\n              -161.40703549883915,\n              58.556875579514866\n            ],\n            [\n              -159.1218792488393,\n              57.53360560212221\n            ],\n            [\n              -165.09844174883935,\n              54.59125546767737\n            ],\n            [\n              -162.28594174883924,\n              54.794443813412215\n            ],\n            [\n              -157.18828549883924,\n              57.344396153787955\n            ],\n            [\n              -154.7273479988392,\n              58.185754905844135\n            ],\n            [\n              -152.96953549883932,\n              60.85620691034802\n            ],\n            [\n              -150.5085979988393,\n              62.850205674657445\n            ],\n            [\n              -145.76250424883938,\n              63.32755335378286\n            ],\n            [\n              -139.6101604988394,\n              61.2015830860681\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Schoen, Erik","contributorId":280216,"corporation":false,"usgs":false,"family":"Schoen","given":"Erik","affiliations":[{"id":6695,"text":"UAF","active":true,"usgs":false}],"preferred":false,"id":890521,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Howard, Kathrine G.","contributorId":302903,"corporation":false,"usgs":false,"family":"Howard","given":"Kathrine","email":"","middleInitial":"G.","affiliations":[{"id":7058,"text":"Alaska Department of Fish and Game","active":true,"usgs":false}],"preferred":false,"id":890522,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Murphy, James","contributorId":210957,"corporation":false,"usgs":false,"family":"Murphy","given":"James","affiliations":[],"preferred":false,"id":890523,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schindler, Daniel","contributorId":331940,"corporation":false,"usgs":false,"family":"Schindler","given":"Daniel","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":890524,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Westley, Peter A. H.","contributorId":287084,"corporation":false,"usgs":false,"family":"Westley","given":"Peter A. H.","affiliations":[{"id":61459,"text":"afg","active":true,"usgs":false}],"preferred":false,"id":890525,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"von Biela, Vanessa R. 0000-0002-7139-5981 vvonbiela@usgs.gov","orcid":"https://orcid.org/0000-0002-7139-5981","contributorId":3104,"corporation":false,"usgs":true,"family":"von Biela","given":"Vanessa","email":"vvonbiela@usgs.gov","middleInitial":"R.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true}],"preferred":true,"id":890526,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70250597,"text":"70250597 - 2023 - Bridging the gap between mathematical biology and undergraduate education using applicable natural resource modeling","interactions":[],"lastModifiedDate":"2023-12-19T12:40:36.280538","indexId":"70250597","displayToPublicDate":"2023-12-01T06:38:55","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3824,"text":"Letters in Biomathematics","active":true,"publicationSubtype":{"id":10}},"title":"Bridging the gap between mathematical biology and undergraduate education using applicable natural resource modeling","docAbstract":"Mathematical biology is a wide field of study with many venues that undergraduate students can access through research. However, the topics of study for these students can be overwhelming, and many topics of study yield either only trivial results or abstract outcomes that are nonintuitive and diffcult to understand. We have used natural resource modeling, and more specifically, a partnership between academic researchers and federal scientists, as a bridge between undergraduate research and mathematical biology. Our collaboration is an interdisciplinary team that combines biology, mathematics, and statistics professors with government research scientists. As a team, we have mentored students through opportunities such as a Research Experiences for Undergraduates and other projects. In this article, we provide an overview of how we develop questions for undergraduates and outline two case studies, both of which resulted in peer reviewed journal articles. Last, we describe how we also transfer the results from these undergraduate projects to resource managers so the results may be applied to real world problems.","language":"English","publisher":"Intercollegiate Biomathematics Alliance","usgsCitation":"Erickson, R.A., Baumann, D., Bennie, B., Bungula, W., Cupp, A.R., Diffendorfer, J., Eager, E., Haro, R.J., Jankowski, K.J., Larson, D.M., Sandland, G., Van Appledorn, M., and Peirce, J.P., 2023, Bridging the gap between mathematical biology and undergraduate education using applicable natural resource modeling: Letters in Biomathematics, v. 10, no. 1, p. 185-191.","productDescription":"7 p.","startPage":"185","endPage":"191","ipdsId":"IP-147034","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true},{"id":651,"text":"Western Ecological Research 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Douglas","contributorId":328549,"corporation":false,"usgs":false,"family":"Baumann","given":"Douglas","affiliations":[{"id":68293,"text":"University of Wisconsin La Crosse","active":true,"usgs":false}],"preferred":false,"id":890503,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bennie, Barbara","contributorId":328550,"corporation":false,"usgs":false,"family":"Bennie","given":"Barbara","affiliations":[{"id":68293,"text":"University of Wisconsin La Crosse","active":true,"usgs":false}],"preferred":false,"id":890504,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bungula, Wako","contributorId":315367,"corporation":false,"usgs":false,"family":"Bungula","given":"Wako","email":"","affiliations":[{"id":68293,"text":"University of Wisconsin La Crosse","active":true,"usgs":false}],"preferred":false,"id":890505,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cupp, Aaron R. 0000-0001-5995-2100 acupp@usgs.gov","orcid":"https://orcid.org/0000-0001-5995-2100","contributorId":5162,"corporation":false,"usgs":true,"family":"Cupp","given":"Aaron","email":"acupp@usgs.gov","middleInitial":"R.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":890506,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Diffendorfer, James E. 0000-0003-1093-6948 jediffendorfer@usgs.gov","orcid":"https://orcid.org/0000-0003-1093-6948","contributorId":3208,"corporation":false,"usgs":true,"family":"Diffendorfer","given":"James E.","email":"jediffendorfer@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":890507,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Eager, Eric A.","contributorId":140447,"corporation":false,"usgs":false,"family":"Eager","given":"Eric A.","affiliations":[{"id":13504,"text":"Department of Mathematics, University of Wisconsin-La Crosse","active":true,"usgs":false}],"preferred":false,"id":890508,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Haro, Roger J.","contributorId":139538,"corporation":false,"usgs":false,"family":"Haro","given":"Roger","email":"","middleInitial":"J.","affiliations":[{"id":12793,"text":"University of Wisconsin-La Crosse","active":true,"usgs":false}],"preferred":false,"id":890509,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Jankowski, Kathi Jo 0000-0002-3292-4182","orcid":"https://orcid.org/0000-0002-3292-4182","contributorId":207429,"corporation":false,"usgs":true,"family":"Jankowski","given":"Kathi","email":"","middleInitial":"Jo","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences 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Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":890513,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Peirce, James P 0000-0002-7147-3695","orcid":"https://orcid.org/0000-0002-7147-3695","contributorId":316559,"corporation":false,"usgs":false,"family":"Peirce","given":"James","email":"","middleInitial":"P","affiliations":[{"id":47908,"text":"University of Wisconsin - La Crosse","active":true,"usgs":false}],"preferred":false,"id":890514,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}}
,{"id":70256529,"text":"70256529 - 2023 - Aging, climate, and invasions threaten reservoirs in the Mississippi basin","interactions":[],"lastModifiedDate":"2024-08-16T16:37:24.141886","indexId":"70256529","displayToPublicDate":"2023-12-01T00:00:00","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5686,"text":"Fisheries Magazine","active":true,"publicationSubtype":{"id":10}},"title":"Aging, climate, and invasions threaten reservoirs in the Mississippi basin","docAbstract":"<p><span>Reservoirs in the Mississippi River basin are facing three momentous threats. The first two, aging and climate change, are relatively slow moving and their signal can be hard to discern given their stretched temporal scales. The third, species invasions, is faster paced and discernable within shorter temporal scales and restricted spatial scales. Aging and climate directly affect reservoir environments and indirectly affect their biotic communities. Climate change is expected to interact with aging to speed up and, in some instances, slow down aging. Conversely, invasions primarily imperil biotic communities but can also impact environmental elements. This triple jeopardy is expected to transform reservoir environs and their biotic assemblages in various, often uncertain, ways. I take a broad view of these threats within the Mississippi River basin. A basin-scale perspective, in contrast to a single reservoir or regional scale, may enhance awareness of reservoirs at a larger level and produce understanding less evident at local levels, hence possibly offering a wider range of choices for confronting threats. My aim is to (1) provide a synopsis of the assemblage of reservoirs and their attributes over the Mississippi River basin, (2) describe the issues related to aging, climate change, and invasions, and (3) consider a conservation framework for confronting these pressures. Given the overlapping temporal, spatial, and ecological effects of these threats, it is essential to address their effects simultaneously.</span></p>","language":"English","publisher":"American Fisheries Society","doi":"10.1002/fsh.10990","usgsCitation":"Miranda, L.E., 2023, Aging, climate, and invasions threaten reservoirs in the Mississippi basin: Fisheries Magazine, v. 48, no. 12, p. 499-514, https://doi.org/10.1002/fsh.10990.","productDescription":"16 p.","startPage":"499","endPage":"514","ipdsId":"IP-151790","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":441518,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/fsh.10990","text":"Publisher Index Page"},{"id":432866,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Mississippi River basin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -88.70500995271088,\n              29.01665894418747\n            ],\n            [\n              -87.84690317711288,\n              33.54915630164602\n            ],\n            [\n              -81.00873115774787,\n              37.45591553762907\n            ],\n            [\n              -78.93790401814765,\n              41.96679217920834\n            ],\n            [\n              -83.62542898487561,\n              41.81918715620617\n            ],\n            [\n              -87.73555865475336,\n              41.70064246159154\n            ],\n            [\n              -88.67261557203858,\n              44.96630422012075\n            ],\n            [\n              -93.08599492063011,\n              47.38065175487887\n            ],\n            [\n              -98.48423664388794,\n              48.43354009429689\n            ],\n            [\n              -112.80019584593275,\n              48.34084011217669\n            ],\n            [\n              -109.13885539240077,\n              44.853455766288505\n            ],\n            [\n              -105.17484654049274,\n              41.33941938263584\n            ],\n            [\n              -103.17753122235543,\n              38.76054766960715\n            ],\n            [\n              -101.04477212147036,\n              36.16726262455268\n            ],\n            [\n              -98.00084294825474,\n              32.268870505741845\n            ],\n            [\n              -92.62187823928058,\n              29.79492566370429\n            ],\n            [\n              -88.70500995271088,\n              29.01665894418747\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"48","issue":"12","noUsgsAuthors":false,"publicationDate":"2023-12-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Miranda, Leandro E. 0000-0002-2138-7924 smiranda@usgs.gov","orcid":"https://orcid.org/0000-0002-2138-7924","contributorId":531,"corporation":false,"usgs":true,"family":"Miranda","given":"Leandro","email":"smiranda@usgs.gov","middleInitial":"E.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":907834,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70257366,"text":"70257366 - 2023 - A continuous classification of the 476,697 lakes of the conterminous US based on geographic archetypes","interactions":[],"lastModifiedDate":"2024-08-23T16:23:27.893177","indexId":"70257366","displayToPublicDate":"2023-12-01T00:00:00","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2620,"text":"Limnology and Oceanography","active":true,"publicationSubtype":{"id":10}},"title":"A continuous classification of the 476,697 lakes of the conterminous US based on geographic archetypes","docAbstract":"<p><span>A variety of classification approaches are used to facilitate understanding, prediction, monitoring, and the management of lakes. However, broad-scale applicability of current approaches is limited by either the need for in situ lake data, incompatibilities among approaches, or a lack of empirical testing of approaches based on ex situ data. We developed a new geographic classification approach for 476,697 lakes ≥ 1 ha in the conterminous U.S. based on lake archetypes representing end members along gradients of multiple geographic features. We identified seven lake archetypes with distinct combinations of climate, hydrologic, geologic, topographic, and morphometric properties. Individual lakes were assigned weights for each of the seven archetypes such that groups of lakes with similar combinations of archetype weights tended to cluster spatially (although not strictly contiguous) and to have similar limnological properties (e.g., concentrations of nutrients, chlorophyll&nbsp;</span><i>a</i><span>&nbsp;(Chl&nbsp;</span><i>a</i><span>), and dissolved organic carbon). Further, archetype lake classification improved commonly measured limnological relationships (e.g., between nutrients and Chl&nbsp;</span><i>a</i><span>) compared to a global model; a discrete archetype classification slightly outperformed an ecoregion classification; and considering lakes as continuous mixtures of archetypes in a more complex model further improved fit. Overall, archetype classification of US lakes as continuous mixtures of geographic features improved understanding and prediction of lake responses to limnological drivers and should help researchers and managers better characterize and forecast lake states and responses to environmental change.</span></p>","language":"English","publisher":"Wiley","doi":"10.1002/lno.12457","usgsCitation":"Lapierre, J., Webster, K.E., Hanks, E., Wagner, T., Soranno, P.A., McCullough, I., Reinl, K.L., Domka, M., and Lotting, N.R., 2023, A continuous classification of the 476,697 lakes of the conterminous US based on geographic archetypes: Limnology and Oceanography, v. 69, no. 12, p. 2759-2773, https://doi.org/10.1002/lno.12457.","productDescription":"15 p.","startPage":"2759","endPage":"2773","ipdsId":"IP-145952","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":441521,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index 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 \"}}]}","contact":"<p>Director, <a href=\"https://www.usgs.gov/programs/national-geospatial-program\" data-mce-href=\"https://www.usgs.gov/programs/national-geospatial-program\">National Geospatial Program</a><br>U.S. Geological Survey<br>12201 Sunrise Valley Drive, Mail Stop 511<br>Reston, VA 20192</p><p>Email: <a href=\"mailto:3DEP@usgs.gov\" data-mce-href=\"mailto:3DEP@usgs.gov\">3DEP@usgs.gov</a></p>","tableOfContents":"<ul><li>Introduction</li><li>Status of 3DEP in Minnesota</li><li>Water Supply and Quality</li><li>Forest Resources Management</li><li>Infrastructure and Construction Management</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"publishedDate":"2023-11-30","noUsgsAuthors":false,"publicationDate":"2023-11-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Bergeson, Mitch 0000-0002-4675-8082 mbergeson@usgs.gov","orcid":"https://orcid.org/0000-0002-4675-8082","contributorId":331686,"corporation":false,"usgs":true,"family":"Bergeson","given":"Mitch","email":"mbergeson@usgs.gov","affiliations":[],"preferred":true,"id":888470,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nail, David 0000-0003-0793-2305 dnail@usgs.gov","orcid":"https://orcid.org/0000-0003-0793-2305","contributorId":331534,"corporation":false,"usgs":true,"family":"Nail","given":"David","email":"dnail@usgs.gov","affiliations":[{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"preferred":true,"id":888471,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
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Because of its location along the Continental Divide, the rivers in Montana drain into either the Pacific Ocean or the Gulf of Mexico. Montana is often called the Treasure State due to its mineral wealth, which includes oil, gas, and coal, but the State’s primary economic activity is agriculture. Other economic activities include natural resources conservation, water supply and quality, infrastructure and construction management, flood risk management, and geologic resource assessment and hazard mitigation. 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 \"}}]}","contact":"<p>Director, <a href=\"https://www.usgs.gov/programs/national-geospatial-program\" data-mce-href=\"https://www.usgs.gov/programs/national-geospatial-program\">National Geospatial Program</a><br>U.S. Geological Survey<br>12201 Sunrise Valley Drive, Mail Stop 511<br>Reston, VA 20192</p><p>Email: <a href=\"mailto:3DEP@usgs.gov\" data-mce-href=\"mailto:3DEP@usgs.gov\">3DEP@usgs.gov</a></p>","tableOfContents":"<ul><li>Introduction</li><li>Status of 3DEP in Montana</li><li>Agriculture and Precision Farming</li><li>Flood Risk Management</li><li>Geologic Resource Assessment and Hazard Mitigation</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"publishedDate":"2023-11-30","noUsgsAuthors":false,"publicationDate":"2023-11-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Carlson, Tom 0000-0002-5682-8988","orcid":"https://orcid.org/0000-0002-5682-8988","contributorId":304658,"corporation":false,"usgs":true,"family":"Carlson","given":"Tom","email":"","affiliations":[{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"preferred":true,"id":888663,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70250421,"text":"70250421 - 2023 - Hawksbill and green turtle niche overlap in a marine protected area, US Virgin Islands","interactions":[],"lastModifiedDate":"2023-12-08T13:09:02.418401","indexId":"70250421","displayToPublicDate":"2023-11-30T07:06:45","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1497,"text":"Endangered Species Research","active":true,"publicationSubtype":{"id":10}},"title":"Hawksbill and green turtle niche overlap in a marine protected area, US Virgin Islands","docAbstract":"<p><span>Studying how species interact with their environment and other co-occurring species are 2 main aspects of ecology. For marine turtles, ocean currents drive migratory routes and may determine the location of surrounding foraging grounds. As a result, circumglobal species like the hawksbill turtle&nbsp;</span><i>Eretmochelys imbricata</i><span>&nbsp;and green turtle&nbsp;</span><i>Chelonia mydas</i><span>&nbsp;adapt to diverse foraging habitats and employ varied feeding strategies. Dietary specializations may reduce competition for available food and space resources between co-occurring hawksbill and green turtles in US Virgin Island shallow reef habitats. This study analyzed isotopic data from immature hawksbill (n = 49; range: 18.7-49.8 cm straight carapace length [SCL]) and green turtles (n = 225; range: 24.1-69.4 cm SCL) to examine foraging niche. We used nitrogen stable isotope (δ</span><sup>15</sup><span>N) values as an indicator of trophic positioning and carbon stable isotope (δ</span><sup>13</sup><span>C) values as a habitat variable. Turtles were hand-captured across an 8 yr period (2012-2019), which facilitated the distinction of isotopic patterns in both the environment and among individual turtles. Understanding variations in habitat, community dynamics, and dietary consumption allowed us to utilize a 5 point framework to translate isotopic space to foraging niche. We found that the site’s relatively stable environmental conditions allow for isotopic overlap between hawksbill and green turtles despite the specialized feeding strategies each species employs. We also underscore the need to evaluate species-specific tissue turnover estimates as evidenced by the influence of tropical storms on recaptured turtle isotopic signatures. These findings inform our understanding of resource use for these imperiled species at our study site and are useful for future global isotopic comparisons.</span></p>","language":"English","publisher":"Inter-Research","doi":"10.3354/esr01276","usgsCitation":"Moorehouse, M.A., Baldwin, J.D., and Hart, K., 2023, Hawksbill and green turtle niche overlap in a marine protected area, US Virgin Islands: Endangered Species Research, v. 52, p. 265-283, https://doi.org/10.3354/esr01276.","productDescription":"19 p.","startPage":"265","endPage":"283","ipdsId":"IP-142711","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":441523,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3354/esr01276","text":"Publisher Index Page"},{"id":435114,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9ED29DJ","text":"USGS data release","linkHelpText":"Stable isotope signatures from green turtles and hawksbills at Buck Island Reef National Monument, U.S. Virgin Islands from 2012-2019"},{"id":423325,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"U.S. Virgin Islands","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -65.06621906831514,\n              18.4297449274477\n            ],\n            [\n              -65.06621906831514,\n              17.60831911760907\n            ],\n            [\n              -64.46197361578831,\n              17.60831911760907\n            ],\n            [\n              -64.46197361578831,\n              18.4297449274477\n            ],\n            [\n              -65.06621906831514,\n              18.4297449274477\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"52","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Moorehouse, Melissa A. 0000-0001-5891-4110","orcid":"https://orcid.org/0000-0001-5891-4110","contributorId":332281,"corporation":false,"usgs":false,"family":"Moorehouse","given":"Melissa","email":"","middleInitial":"A.","affiliations":[{"id":79441,"text":"United States Military Academy","active":true,"usgs":false}],"preferred":false,"id":889869,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Baldwin, John D.","contributorId":210505,"corporation":false,"usgs":false,"family":"Baldwin","given":"John","email":"","middleInitial":"D.","affiliations":[{"id":15312,"text":"Florida Atlantic University","active":true,"usgs":false}],"preferred":false,"id":889870,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hart, Kristen 0000-0002-5257-7974","orcid":"https://orcid.org/0000-0002-5257-7974","contributorId":220333,"corporation":false,"usgs":true,"family":"Hart","given":"Kristen","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":889871,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70250366,"text":"70250366 - 2023 - Predicted distribution of ‘ua‘u (Hawaiian petrel Pterodroma sandwichensis) nest sites on Haleakalā, Maui","interactions":[],"lastModifiedDate":"2023-12-05T13:13:51.187375","indexId":"70250366","displayToPublicDate":"2023-11-30T07:05:31","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1497,"text":"Endangered Species Research","active":true,"publicationSubtype":{"id":10}},"title":"Predicted distribution of ‘ua‘u (Hawaiian petrel Pterodroma sandwichensis) nest sites on Haleakalā, Maui","docAbstract":"<p class=\"abstract_block\">Haleakalā National Park and montane areas on east Maui, Hawaiian Archipelago, support critical nesting habitat for endangered ‘ua‘u Hawaiian petrel<span>&nbsp;</span><i>Pterodroma sandwichensis</i>. Habitat loss, non-native predators, and damage by feral ungulates are limiting factors for ground-nesting petrels at Haleakalā and throughout Hawai‘i. Because nesting habitats differ among the Hawaiian Islands, habitat distribution modeling for Hawaiian petrel has been island specific. Based on 2453 known nest site locations, we provide the first landscape-scale predictive model describing relative abundance and habitat available for nesting petrels throughout upper Haleakalā (1830 to 3055 m). We evaluated (principal components analyses and Pearson’s correlation) 13 spatial landscape and climate predictor variables associated with nest sites and the background landscape followed by random forest modeling to predict nest site density. Six variables (elevation, slope, topographic position index at 2 scales, heat load index, presence-absence ash/cinder, and presence-absence vegetation) indicated nest sites occurred non-randomly throughout the central part of the summit and crater; greatest concentrations were predicted along the crater rim and a ridgeline extending southwest from the summit. Moderately high predicted density occurred in the northeastern and northern crater. Lower elevations to the north, west, and south flanks of Haleakalā had relatively fewer predicted nest sites. Although we focused on higher elevations on Haleakalā, there is no reason to suspect that conservation efforts would not be successful at lower elevations, provided nesting petrels were protected from invasive predators, grazing ungulates, and significant land alteration.</p>","language":"English","publisher":"Inter-Research Science Publisher","doi":"10.3354/esr01280","usgsCitation":"Adams, J., Felis, J., Klinger, R.C., Kelsey, E.C., Tamayose, J., Kaholoa’a, R., Bailey, C.N., Penniman, J.F., Learned, J., Ganter, C., Medeiros, J., and Chen, H., 2023, Predicted distribution of ‘ua‘u (Hawaiian petrel Pterodroma sandwichensis) nest sites on Haleakalā, Maui: Endangered Species Research, v. 52, p. 231-246, https://doi.org/10.3354/esr01280.","productDescription":"16 p.","startPage":"231","endPage":"246","ipdsId":"IP-148421","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":441525,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3354/esr01280","text":"Publisher Index Page"},{"id":423239,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"Haleakalā, Maui","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -156.31986912490262,\n              20.79241841577982\n            ],\n            [\n              -156.31986912490262,\n              20.617670800708467\n            ],\n            [\n              -156.03010472060575,\n              20.617670800708467\n            ],\n            [\n              -156.03010472060575,\n              20.79241841577982\n            ],\n            [\n              -156.31986912490262,\n              20.79241841577982\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"52","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Adams, Josh 0000-0003-3056-925X","orcid":"https://orcid.org/0000-0003-3056-925X","contributorId":213442,"corporation":false,"usgs":true,"family":"Adams","given":"Josh","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":889570,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Felis, Jonathan J. 0000-0002-0608-8950","orcid":"https://orcid.org/0000-0002-0608-8950","contributorId":332148,"corporation":false,"usgs":false,"family":"Felis","given":"Jonathan J.","affiliations":[{"id":17847,"text":"USGS-WERC","active":true,"usgs":false}],"preferred":false,"id":889571,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Klinger, Robert C. 0000-0003-3193-3199 rcklinger@usgs.gov","orcid":"https://orcid.org/0000-0003-3193-3199","contributorId":5395,"corporation":false,"usgs":true,"family":"Klinger","given":"Robert","email":"rcklinger@usgs.gov","middleInitial":"C.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true},{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":889572,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kelsey, Emily C. 0000-0002-0107-3530 ekelsey@usgs.gov","orcid":"https://orcid.org/0000-0002-0107-3530","contributorId":206505,"corporation":false,"usgs":true,"family":"Kelsey","given":"Emily","email":"ekelsey@usgs.gov","middleInitial":"C.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":889573,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Tamayose, Joy","contributorId":332150,"corporation":false,"usgs":false,"family":"Tamayose","given":"Joy","email":"","affiliations":[{"id":36245,"text":"NPS","active":true,"usgs":false}],"preferred":false,"id":889574,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kaholoa’a, Raina","contributorId":332151,"corporation":false,"usgs":false,"family":"Kaholoa’a","given":"Raina","email":"","affiliations":[{"id":36245,"text":"NPS","active":true,"usgs":false}],"preferred":false,"id":889575,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bailey, Cathleen Natividad","contributorId":220473,"corporation":false,"usgs":false,"family":"Bailey","given":"Cathleen","email":"","middleInitial":"Natividad","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":889576,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Penniman, Jay F.","contributorId":332154,"corporation":false,"usgs":false,"family":"Penniman","given":"Jay","email":"","middleInitial":"F.","affiliations":[{"id":79395,"text":"Maui Nui Seabird Recovery Project","active":true,"usgs":false}],"preferred":false,"id":889577,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Learned, Jennifer","contributorId":332155,"corporation":false,"usgs":false,"family":"Learned","given":"Jennifer","email":"","affiliations":[{"id":79395,"text":"Maui Nui Seabird Recovery Project","active":true,"usgs":false}],"preferred":false,"id":889578,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Ganter, Ciara","contributorId":332156,"corporation":false,"usgs":false,"family":"Ganter","given":"Ciara","email":"","affiliations":[{"id":79397,"text":"Hawai'i State of Dep. of Land and Natural Resources","active":true,"usgs":false}],"preferred":false,"id":889579,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Medeiros, John","contributorId":167591,"corporation":false,"usgs":false,"family":"Medeiros","given":"John","email":"","affiliations":[{"id":24766,"text":"4. State of Hawaii, Division of Forestry and Wildlife-Maui, 54 South High Street # 101, Wailuku, HI 96793.","active":true,"usgs":false}],"preferred":false,"id":889580,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Chen, Huisheng","contributorId":332157,"corporation":false,"usgs":false,"family":"Chen","given":"Huisheng","email":"","affiliations":[{"id":79398,"text":"NPS; University of Hawai'i","active":true,"usgs":false}],"preferred":false,"id":889581,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}}
,{"id":70251909,"text":"70251909 - 2023 - Micropaleontological evidence of a submarine fan in the lower Coaledo Formation, Southwestern Oregon, USA","interactions":[],"lastModifiedDate":"2025-01-27T16:22:06.901739","indexId":"70251909","displayToPublicDate":"2023-11-30T06:57:17","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2294,"text":"Journal of Foraminiferal Research","active":true,"publicationSubtype":{"id":10}},"title":"Micropaleontological evidence of a submarine fan in the lower Coaledo Formation, Southwestern Oregon, USA","docAbstract":"<div id=\"141891235\" class=\"article-section-wrapper js-article-section js-content-section  \" data-section-parent-id=\"0\"><p>The middle Eocene lower Coaledo Formation was interpreted as ten shoaling upward delta-margin cycles based on sediments and macrofauna. The strata, however, contains deep-water foraminifers. Explanations to resolve this anomaly included reworking, bathymetric range extension, or upward migration of water masses. Paleoecology analysis of foraminifers indicates that the few shelf species are poorly preserved whereas the well-preserved lower bathyal species dominate, and planktic organisms are present. Evidence for reworking, bathymetric range extension, or upward migration of water masses was not found in any of the cycles. The paleoecologic utility of hummocky cross-bedded sandstones is questioned as these features are controversial. In addition, there is no evidence of sea-level changes or tectonic activity to accommodate the bathymetric changes needed. Deposition of the lower Coaledo Formation on a submarine fan at lower bathyal depths eliminates the need to explain bathymetric anomalies or lack of tectonic movement.</p></div>","language":"English","publisher":"Cushman Foundation for Foraminiferal Research","doi":"10.2113/gsjfr.53.4.311","usgsCitation":"McDougall-Reid, K., 2023, Micropaleontological evidence of a submarine fan in the lower Coaledo Formation, Southwestern Oregon, USA: Journal of Foraminiferal Research, v. 53, no. 4, p. 311-337, https://doi.org/10.2113/gsjfr.53.4.311.","productDescription":"27 p.","startPage":"311","endPage":"337","ipdsId":"IP-142682","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":501082,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.2113/gsjfr.53.4.311","text":"Publisher Index Page"},{"id":426363,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -126.02697115657307,\n              45.34305686940033\n            ],\n            [\n              -126.02697115657307,\n              41.77805423530663\n            ],\n            [\n              -121.58849459407304,\n              41.77805423530663\n            ],\n            [\n              -121.58849459407304,\n              45.34305686940033\n            ],\n            [\n              -126.02697115657307,\n              45.34305686940033\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"53","issue":"4","noUsgsAuthors":false,"publicationDate":"2023-11-30","publicationStatus":"PW","contributors":{"authors":[{"text":"McDougall-Reid, Kristin 0000-0002-8788-3664","orcid":"https://orcid.org/0000-0002-8788-3664","contributorId":216211,"corporation":false,"usgs":true,"family":"McDougall-Reid","given":"Kristin","email":"","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":896042,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70250696,"text":"70250696 - 2023 - FishPass baseline assessment of fish community assemblage and migratory patterns in in the Boardman River, Traverse City, Michigan, USA","interactions":[],"lastModifiedDate":"2023-12-27T12:54:08.529","indexId":"70250696","displayToPublicDate":"2023-11-30T06:50:51","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"title":"FishPass baseline assessment of fish community assemblage and migratory patterns in in the Boardman River, Traverse City, Michigan, USA","docAbstract":"This report on baseline assessment of fish community assemblage and migratory patterns of fishes in the lower Boardman River (LBR; Traverse City, MI (USA)) is one of four assessment projects conceived circa 2017 after the Boardman (Ottaway) River was selected by the Great Lakes Fishery Commission (GLFC) and collaborating agencies as the future site of the Selective Bi-directional Fish Passage (FishPass) project. This report describes the results from\nfisheries community sampling from 2017-2021 and the concurrent bio-telemetry project aimed at understanding phenological changes in the fish community and movement and space-use of a variety of large-bodied fishes in the LBR against which selective fish passage treatments will be developed and evaluated.\nFish migration in riverine environments is a growing area of concern as mounting anthropogenic influences, particularly fragmentation from dams and barriers, constitute a major threat to global river species diversity. Specifically, In the Laurentian Great Lakes basin, more than 250,000 dams, weirs, culverts, and other significant obstructions prevent the movement of species both between the Great Lakes and rivers, and within rivers. Barriers\nimpede the movement of fishes between areas critical to the completion of their lifecycle, affecting both population and ecosystem viability. However, a conundrum arises in that the same barriers can also prevent the upstream invasion of non-native or undesirable species (most notably the sea lamprey Petromyzon marinus in the Great Lakes),prevent the transfer of contaminants and diseases, halt deleterious genes, provide recreational opportunities, or\ngenerate power. As a result, fish passage solutions with the capability of selectively passing desirable taxa while restricting the dispersal of undesirable taxa (selective connectivity) are sought to solve this connectivity conundrum. FishPass is a multi-agency initiative planned to replace the Union Street Dam on the Boardman River in Traverse City,MI (USA), aimed at developing and implementing automatic or semiautomatic selective bi-directional fish guidance,\nsorting, and passage techniques and technologies. Pivotal to both the successful development of selective connectivity and assessment of its effects is a more complete understanding of the Boardman River’s fishery. Specifically, understanding the species and size composition of the fish community, fish movement phenology and the associated abiotic conditions.\n\nFish community sampling confirmed the presence of 28 unique species in the LBR (Boardman River reach below Union Street Dam). Passive Integrated Transponder (PIT) tag telemetry increased the resolution of phenological shifts in the fish community that could not have been captured from periodic fish sampling. This data demonstrates large variation within species and overlap between species presence. However, discrete periods of presence were identified across most species when considering the central tendencies in the distribution of their presence. Rainbow trout Oncorhynchus mykiss were found to be omni-present in the river while brown trout Salmo trutta and smallmouth bass Micropterus dolomieu also persisted throughout a majority of the year; all of which will require continually sorting at FishPass. PIT tag telemetry also provided the important understanding that individuals (3-64%) of all species return to\nthe LBR across multiple years.\n\nRadio telemetry (RT) proved useful in refining the entry and exit timing and in evaluating the proportion of individuals that encountered the current Union Street Dam and Kid’s Creek (the only tributary confluence below the Union Street Dam) across six species (common white sucker Catostomus commersonii, rainbow trout, smallmouth bass, walleye Sander vitreus, brown trout, and common carp Cyprinus carpio). The RT results show that these species are present in FishPass Research Publication: baseline assessment\nof fish community assemblage and migratory pattern in the Boardman River, Traverse City, Michigan, USA November 2023 7 between April and August. Our analysis also demonstrated that not all fish that entered the river proceeded to the Union Street Dam, but those that did, did so prior to being detected encountering Kid’s Creek. Common white sucker and rainbow trout were the only species to be detected encountering Kid’s Creek.\n\nCollectively, the results of this study provide a baseline understanding of the seasonal fish diversity and relative abundance of fishes in the LBR, and a basic description of observed movement patterns of a subset of species in the context of seasonal phenology, entry and exit behavior within the LBR, and the propensity at which telemetered individuals encounter the Union Street dam and/or Kid’s Creek.","language":"English","publisher":"Great Lakes Fishery Commission","collaboration":"Great Lakes Fisheries Commission","usgsCitation":"Swanson, R.G., Zielinski, D.P., Castro-Santos, T., and Muir, A., 2023, FishPass baseline assessment of fish community assemblage and migratory patterns in in the Boardman River, Traverse City, Michigan, USA, 49 p.","productDescription":"49 p.","ipdsId":"IP-155321","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":423903,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":423897,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"http://www.glfc.org/pubs/pdfs/research/FishPassResearchPublication2023-CommunityAssemblage.pdf"}],"country":"United States","state":"Michigan","city":"Traverse City","otherGeospatial":"Boardman River","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -85.7182012975478,\n              44.78761727288912\n            ],\n            [\n              -85.7182012975478,\n              44.70666411909653\n            ],\n            [\n              -85.53349365594626,\n              44.70666411909653\n            ],\n            [\n              -85.53349365594626,\n              44.78761727288912\n            ],\n            [\n              -85.7182012975478,\n              44.78761727288912\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Swanson, Reid G.","contributorId":332833,"corporation":false,"usgs":false,"family":"Swanson","given":"Reid","email":"","middleInitial":"G.","affiliations":[{"id":65273,"text":"GLFC","active":true,"usgs":false}],"preferred":false,"id":891020,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zielinski, Daniel P.","contributorId":211034,"corporation":false,"usgs":false,"family":"Zielinski","given":"Daniel","email":"","middleInitial":"P.","affiliations":[{"id":34820,"text":"Great Lakes Fisheries Commission, Ann Arbor, MI","active":true,"usgs":false}],"preferred":false,"id":891021,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Castro-Santos, Theodore 0000-0003-2575-9120","orcid":"https://orcid.org/0000-0003-2575-9120","contributorId":315433,"corporation":false,"usgs":true,"family":"Castro-Santos","given":"Theodore","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":891022,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Muir, Andrew M.","contributorId":103933,"corporation":false,"usgs":false,"family":"Muir","given":"Andrew M.","affiliations":[],"preferred":false,"id":891023,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70250826,"text":"70250826 - 2023 - Dynamics of magma mixing and magma mobilization beneath Mauna Loa – Insights from the 1950 AD Southwest Rift Zone eruption.","interactions":[],"lastModifiedDate":"2024-01-08T16:55:00.87656","indexId":"70250826","displayToPublicDate":"2023-11-29T10:49:02","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1109,"text":"Bulletin of Volcanology","active":true,"publicationSubtype":{"id":10}},"title":"Dynamics of magma mixing and magma mobilization beneath Mauna Loa – Insights from the 1950 AD Southwest Rift Zone eruption.","docAbstract":"<p><span>Eruptions from Mauna Loa’s Southwest Rift Zone (SWRZ) pose a significant threat to nearby communities due to high eruption rates and steep slopes resulting in little time for evacuation. Despite the large body of research done on Mauna Loa, knowledge of the timing and duration of magma residence and transfer through its internal plumbing system is still poorly constrained. This study presents a first quantitative look at thermochemical conditions and timescales of potentially deep storage and disaggregation of magmatic mush during the run-up to the voluminous 1950 AD SWRZ eruption. Details of heterogeneous compositions and textures of the macrocryst and glomerocryst cargo in 1950 AD lavas suggest magma mixing and crystal recycling along the entire plumbing system. Furthermore, the crystal cargo contains evidence for the direct interaction between primitive, deeply stored magma and pockets of more evolved magma stored at shallow to intermediate depths. An enigmatic attribute of 1950 near-vent lava is the near-ubiquitous presence of subhedral, unreacted Mg-rich orthopyroxene phenocrysts (Mg#&gt;80). Phase relations of Mauna Loa olivine-tholeiite indicate that orthopyroxene joins olivine as a primary phase at pressures higher than 0.6 GPa. Coexisting Mg-rich olivine and orthopyroxene and the occurrence of harzburgitic (olivine-orthopyroxene) glomerocrysts provide evidence for cognate crystallisation at near-Moho (~ 18 km) depths (Thornber and Trusdell&nbsp;</span>2008<span>). Petrogenetically diverse populations of glomerocrysts and macrocrysts alongside evidence of multilevel magma storage indicate a network of ephemeral and possibly interconnected magma pockets from near-Moho depths to the upper/mid-crust. Fe-Mg diffusion chronometry applied to 1950 AD olivine populations implies rapid mobilisation and transport of large volumes of magma (376×10</span><sup>6</sup><span>&nbsp;m</span><sup>3</sup><span>) from near-Moho storage to the surface within less than 8 months, with little residence time (~ 2 weeks) in the shallow (3–5 km) plumbing system.</span></p>","language":"English","publisher":"Springer","doi":"10.1007/s00445-023-01680-x","usgsCitation":"Kahl, M., Morgan, D.J., Thornber, C., Walshaw, R., Lynn, K.J., and Trusdell, F., 2023, Dynamics of magma mixing and magma mobilization beneath Mauna Loa – Insights from the 1950 AD Southwest Rift Zone eruption.: Bulletin of Volcanology, v. 85, 75, 21 p., https://doi.org/10.1007/s00445-023-01680-x.","productDescription":"75, 21 p.","ipdsId":"IP-152183","costCenters":[{"id":157,"text":"Cascades Volcano Observatory","active":false,"usgs":true},{"id":617,"text":"Volcano Science 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