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Introduction

The Rocky Mountains and the Colorado River Basin in the Western United States represent complex, interconnected systems that sustain a number of species, including tens of millions of humans. These systems face several challenges, including worsening drought, altered wildfire regimes, climate change, and the spread of invasive species. These factors can exacerbate one another, further contributing to habitat loss and affecting species of conservation concern. Characterizing and managing these challenges require interdisciplinary communities of scientists to develop information and decision-support tools that can inform holistic land and water management solutions. The U.S. Geological Survey (USGS) Rocky Mountain Region 2022 Science Exchange focused on the use of interdisciplinary and state-of-the-art science being conducted by USGS scientists in the region to address these complex problems.

The USGS Rocky Mountain Regional Office organized its first Science Exchange in 2017 to share scientific information between leaders and early career scientists throughout the region. Science Exchanges held in 2018 and 2020 focused on drought science relevant to the region and the Earth Monitoring, Analyses, and Prediction (EarthMAP) concept, which is designed to facilitate interdisciplinary, timely, and actionable science related to drought in the Colorado River Basin and other areas. Based on the emerging need for more holistic approaches to address increasingly complex natural resource issues that affect society, the Region hosted a virtual fourth Science Exchange for three days in April 2022. This event focused on barriers and bridges to interdisciplinary science and highlighted studies from the Region to inspire collaboration across disciplines. Presentations described recent and ongoing research that applied collaborative and state-of-the-art methods to address problems in the fields of geology, hydrology, ecology, and natural hazards. Science collaboration and outreach to all levels of stakeholders are vital elements needed for providing timely and actionable data, interpretations, analytical tools, and products. These presentations led to active online chats and panel discussions and showcased interdisciplinary science and advanced methods that may inform and lead to more effective, holistic management decisions as the Western United States adapts to ongoing and future changes.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20233017","usgsCitation":"Peterson, D.E., French, K.L., Oden, J.H., Anderson, P.J., Titus, T.N., Dahm, K.G., Driscoll, J., Andrews, W.J., 2022, U.S. Geological Survey Rocky Mountain Region 2022 Science Exchange, Showcasing Interdisciplinary and State-of-the-Art USGS Science, U.S. Geological Survey Fact Sheet 2023-3017, 6 p., https://doi.org/10.3133/fs20233017.","productDescription":"6 p.","onlineOnly":"Y","ipdsId":"IP-144708","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true},{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true},{"id":547,"text":"Rocky Mountain Geographic Science Center","active":true,"usgs":true},{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":418590,"rank":3,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/fs/2023/3017/images"},{"id":418591,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/fs/2023/3017/fs20233017.xml"},{"id":418596,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/fs20233017/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"FS 2023-3017"},{"id":418480,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2023/3017/coverthb.jpg"},{"id":418481,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2023/3017/fs20233017.pdf","text":"Report","size":"4.83 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2023-3017"}],"contact":"

Director, Region 7 - Upper Colorado Basin
U.S. Geological Survey
Box 25046, MS-911
Denver, CO 80225-0046

","tableOfContents":"","publishedDate":"2023-06-28","noUsgsAuthors":false,"publicationDate":"2023-06-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Peterson, Dana E. 0000-0002-1941-265X","orcid":"https://orcid.org/0000-0002-1941-265X","contributorId":225536,"corporation":false,"usgs":true,"family":"Peterson","given":"Dana","email":"","middleInitial":"E.","affiliations":[{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true}],"preferred":true,"id":876266,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"French, Katherine L. 0000-0002-0153-8035","orcid":"https://orcid.org/0000-0002-0153-8035","contributorId":205462,"corporation":false,"usgs":true,"family":"French","given":"Katherine","email":"","middleInitial":"L.","affiliations":[{"id":255,"text":"Energy Resources Program","active":true,"usgs":true},{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":false,"id":876267,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Oden, Jeannette H. 0000-0002-6473-1553","orcid":"https://orcid.org/0000-0002-6473-1553","contributorId":216965,"corporation":false,"usgs":true,"family":"Oden","given":"Jeannette","email":"","middleInitial":"H.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":876268,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Anderson, Patrick J. 0000-0003-2281-389X andersonpj@usgs.gov","orcid":"https://orcid.org/0000-0003-2281-389X","contributorId":3590,"corporation":false,"usgs":true,"family":"Anderson","given":"Patrick","email":"andersonpj@usgs.gov","middleInitial":"J.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":876269,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Titus, Timothy N. 0000-0003-0700-4875 ttitus@usgs.gov","orcid":"https://orcid.org/0000-0003-0700-4875","contributorId":146,"corporation":false,"usgs":true,"family":"Titus","given":"Timothy","email":"ttitus@usgs.gov","middleInitial":"N.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":876270,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Dahm, Katharine G. 0000-0002-4024-8110","orcid":"https://orcid.org/0000-0002-4024-8110","contributorId":299422,"corporation":false,"usgs":true,"family":"Dahm","given":"Katharine","email":"","middleInitial":"G.","affiliations":[{"id":64844,"text":"Rocky Mountain Region Director’s Office","active":true,"usgs":true}],"preferred":true,"id":876271,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Driscoll, Jessica M. 0000-0003-3097-9603 jdriscoll@usgs.gov","orcid":"https://orcid.org/0000-0003-3097-9603","contributorId":167585,"corporation":false,"usgs":true,"family":"Driscoll","given":"Jessica","email":"jdriscoll@usgs.gov","middleInitial":"M.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":876272,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Andrews, William J. 0000-0003-4780-8835","orcid":"https://orcid.org/0000-0003-4780-8835","contributorId":216006,"corporation":false,"usgs":true,"family":"Andrews","given":"William","email":"","middleInitial":"J.","affiliations":[{"id":516,"text":"Oklahoma Water Science Center","active":true,"usgs":true},{"id":547,"text":"Rocky Mountain Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":876273,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70247321,"text":"70247321 - 2023 - Cryptic tolerant fish species and their potential effect on index of biotic integrity (IBI) scores","interactions":[],"lastModifiedDate":"2023-07-27T16:32:22.397158","indexId":"70247321","displayToPublicDate":"2023-06-28T11:29:42","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1456,"text":"Ecological Indicators","active":true,"publicationSubtype":{"id":10}},"title":"Cryptic tolerant fish species and their potential effect on index of biotic integrity (IBI) scores","docAbstract":"

Indices such as the Index of Biotic Integrity (IBI) are often used by management agencies to estimate the abstract property of stream health. These indices are usually predicated on the belief that certain fish species are tolerant to environmental perturbation while others are sensitive. Species are usually designated as either tolerant or sensitive in these analyses based on inherent ecological or taxonomic characteristics. However, previous literature has shown that certain species from ecological or taxonomic “sensitive” groups experience increased abundance in degraded streams. We term such species “cryptic tolerants”. Using a stream fish assemblage dataset of 433 unique sample locations across the state of Alabama and the National Landcover Dataset, our objectives were to 1) identify the most common cryptic tolerant species, 2) investigate how cryptic tolerant species might inflate indices of stream health, and 3) compare an alternative measure of stream health in which species are statistically defined rather than defined using the traditional trait-based approach. We identified cryptic tolerants using Nonmetric Multidimensional Scaling in six ecoregions. A series of regressions revealed that the proportion of cryptic tolerant species decreased in response to an increasing proportion of forested land in catchments while the proportion of true sensitives increased in all ecoregions except for the Cumberland Plateau. An index that simply used the percentage of statistically defined, non-tolerant species generally had lower p-values and higher r2 values than IBI scores when both were regressed against percentage of forest in catchment. However, both indices had low degrees of correlation with expected disturbance, indicating a univariate index may be inadequate to characterize stream health. Our results highlight a potential issue with applying the IBI to diverse southeastern systems in the United States, which may be alleviated by designating species sensitivity based on empirical response to disturbance rather than taxonomic or ecological characteristics.

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\"}}]}","volume":"154","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Hilburn, Bryson G.","contributorId":317735,"corporation":false,"usgs":false,"family":"Hilburn","given":"Bryson","email":"","middleInitial":"G.","affiliations":[{"id":13360,"text":"Auburn University","active":true,"usgs":false}],"preferred":false,"id":879202,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Freeman, Mary 0000-0001-7615-6923 mcfreeman@usgs.gov","orcid":"https://orcid.org/0000-0001-7615-6923","contributorId":3528,"corporation":false,"usgs":true,"family":"Freeman","given":"Mary","email":"mcfreeman@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":879203,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lawson, Katelyn M.","contributorId":201981,"corporation":false,"usgs":false,"family":"Lawson","given":"Katelyn M.","affiliations":[{"id":36314,"text":"University of Florida/IFAS","active":true,"usgs":false}],"preferred":false,"id":879204,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rider, Steven J.","contributorId":317736,"corporation":false,"usgs":false,"family":"Rider","given":"Steven","email":"","middleInitial":"J.","affiliations":[{"id":35940,"text":"Alabama Division of Wildlife and Freshwater Fisheries","active":true,"usgs":false}],"preferred":false,"id":879205,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Johnston, Carol E.","contributorId":317737,"corporation":false,"usgs":false,"family":"Johnston","given":"Carol","email":"","middleInitial":"E.","affiliations":[{"id":13360,"text":"Auburn University","active":true,"usgs":false}],"preferred":false,"id":879206,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70247867,"text":"70247867 - 2023 - Assessment of public and private land cover change in the United States from 1985–2018","interactions":[],"lastModifiedDate":"2023-08-22T12:04:51.65435","indexId":"70247867","displayToPublicDate":"2023-06-27T06:56:50","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":10763,"text":"Environmental Research Communications","active":true,"publicationSubtype":{"id":10}},"title":"Assessment of public and private land cover change in the United States from 1985–2018","docAbstract":"

An assessment of annual land cover on publicly and privately managed lands across the conterminous United States (CONUS) from 1985–2018 was performed, including land cover conversions within their management category, to inform future policy and land-use decision-making in natural resource management. Synthesizing land cover data with land management delineations aids our ability to address effects of land management decisions by public or private entities. The U.S. Geological Survey (USGS) Protected Areas Database of the United States (PAD-US) version 2.1 data delineate land management categories and enable examination of land cover composition and change using the USGS Land Change Monitoring, Assessment, and Projection (LCMAP) reference data. Average composition of our delineated CONUS results using LCMAP land cover classes is 40% Grass/Shrub (GS), 29% Tree Cover (TC), 18% Cropland (CP), 5% Developed (DV), 5% Wetland (WL), 1.8% Water (WR), and 0.9% Barren (BN). Private (public) land is composed of 35% (52%) GS, 27% (36%) TC, 25% (1%) CP, 7% (1%) DV, 5% (5%) WL, 2% (2%) WR, and less than 1% (3%) BN. Land cover change averaged less than 1% per year. The largest net percentage gains across CONUS were in DV land and GS, and the greatest net losses were in CP and TC. Approximately 73% of CONUS is private land and, thus, land cover change across CONUS is largely a reflection of private land change dynamics. Private compositional changes show net gains from 1985–2018 in DV (2.3%), WR (0.2%), and GS (0.1%) classes, while net losses occurred in CP (−1.9%), TC (−0.6%), WL (−0.1%), and BN (−0.01%). Public land cover changes show net gains in GS (1%), DV (0.2%), WR (0.01%), WL (0.05%), and BN (0.1%) classes, and net losses in CP (−0.3%) and TC (−1%). Our study reveals connections between land cover conversion and various policy and socioeconomic decisions through time.

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0000-0002-9418-5215","orcid":"https://orcid.org/0000-0002-9418-5215","contributorId":290239,"corporation":false,"usgs":false,"family":"Taylor","given":"Janis","email":"","middleInitial":"L.","affiliations":[{"id":53079,"text":"KBR, contractor to U.S. Geological Survey","active":true,"usgs":false}],"preferred":false,"id":880798,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Auch, Roger F. 0000-0002-5382-5044 auch@usgs.gov","orcid":"https://orcid.org/0000-0002-5382-5044","contributorId":667,"corporation":false,"usgs":true,"family":"Auch","given":"Roger","email":"auch@usgs.gov","middleInitial":"F.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":880799,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70246263,"text":"70246263 - 2023 - Modeling the maturation history of the stacked petroleum systems of the Williston Basin, USA","interactions":[],"lastModifiedDate":"2023-06-29T11:44:43.799768","indexId":"70246263","displayToPublicDate":"2023-06-27T06:41:26","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2682,"text":"Marine and Petroleum Geology","active":true,"publicationSubtype":{"id":10}},"title":"Modeling the maturation history of the stacked petroleum systems of the Williston Basin, USA","docAbstract":"

A three-dimensional petroleum systems model was built to support U.S. Geological Survey assessments of undiscovered oil and gas resources in the Williston Basin of North Dakota, Montana, and South Dakota. Numerous Paleozoic source rocks have been proven or postulated in the basin, of which five were the focus of maturation and migration modeling: the Ordovician Icebox Formation, the kukersite beds of the Ordovician Red River Formation, the shales of the Devonian–Mississippian Bakken Formation, the Mississippian Madison Group, and the Pennsylvanian Tyler Formation. Calibration of the three-dimensional model to present-day temperature data indicates the existence of a north-south trend of high heat flow in western North Dakota, along with a region of high heat flow in eastern Montana. These high heat flow trends strongly control the maturity of all studied source intervals. A Bakken-specific hydrocarbon generation kinetic model was developed to match the calibrated time-temperature history of the basin to spatial trends in hydrogen index from programmed pyrolysis data. Generation of hydrocarbons occurred in the Cretaceous through Paleogene due to increased burial. Subsequent uplift and erosion in the Neogene cooled the basin, ending hydrocarbon generation for all source rocks. The cumulative volume of hydrocarbons generated by each of the source rocks was calculated and used to compare their relative robustness. The shales of the Bakken Formation are estimated to have generated approximately 460 billion barrels of oil equivalent (BBOE), while the Red River Formation generated approximately 130 BBOE, the Tyler Formation 94 BBOE, the Madison Group 44 BBOE, and the Icebox Formation 28 BBOE. Gross migration trends were analyzed with respect to historical oil and gas production in the basin and generally indicate segregation of petroleum systems throughout the stratigraphic column. However, most modeled scenarios indicated significant loss of Bakken oil to the Madison Group, suggesting that mixing of Madison and Bakken oils may be more prevalent than has recently been recognized in the U.S. portion of the Williston Basin and is particularly likely in fractured regions of the basin.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.marpetgeo.2023.106390","usgsCitation":"Gelman, S.E., 2023, Modeling the maturation history of the stacked petroleum systems of the Williston Basin, USA: Marine and Petroleum Geology, v. 155, 106390, 25 p., https://doi.org/10.1016/j.marpetgeo.2023.106390.","productDescription":"106390, 25 p.","ipdsId":"IP-145695","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":442945,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.marpetgeo.2023.106390","text":"Publisher Index Page"},{"id":435274,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9N7O1OT","text":"USGS data release","linkHelpText":"Data release for the 3D petroleum systems model of the Williston Basin, USA"},{"id":418615,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Montana, North Dakota","otherGeospatial":"Williston Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -107.05487036081263,\n 49.09401622161886\n ],\n [\n -107.05487036081263,\n 45.9204646960259\n ],\n [\n -100.81731222757732,\n 45.9204646960259\n ],\n [\n -100.81731222757732,\n 49.09401622161886\n ],\n [\n -107.05487036081263,\n 49.09401622161886\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"155","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Gelman, Sarah E. 0000-0003-2549-9509","orcid":"https://orcid.org/0000-0003-2549-9509","contributorId":270004,"corporation":false,"usgs":true,"family":"Gelman","given":"Sarah","email":"","middleInitial":"E.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":876492,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70246249,"text":"70246249 - 2023 - Connecting dryland fine-fuel assessments to wildfire exposure and natural resource values at risk","interactions":[],"lastModifiedDate":"2023-06-28T13:32:26.611","indexId":"70246249","displayToPublicDate":"2023-06-26T08:27:27","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1636,"text":"Fire Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Connecting dryland fine-fuel assessments to wildfire exposure and natural resource values at risk","docAbstract":"

Background

Wildland fire in arid and semi-arid (dryland) regions can intensify when climatic, biophysical, and land-use factors increase fuel load and continuity. To inform wildland fire management under these conditions, we developed high-resolution (10-m) estimates of fine fuel across the Altar Valley in southern Arizona, USA, which spans dryland, grass-dominated ecosystems that are administered by multiple land managers and owners. We coupled field measurements at the end of the 2021 growing season with Sentinel-2 satellite imagery and vegetation indices acquired during and after the growing season to develop predictions of fine fuel across the entire valley. We then assessed how climate, soil, vegetation, and land-use factors influenced the amount and distribution of fine fuels. We connected fine fuels to fire management points, past ignition history, and socio-economic vulnerability to evaluate wildfire exposure and assessed how fuel related to habitat of the endangered masked bobwhite quail (Colinus virginianus ridgwayi).

Results

The high amount of fine fuel (400–3600 kg/ha; mean = 1392 kg/ha) predicted by our remote sensing model (R2 = 0.63) for 2021 compared to previous years in the valley was stimulated by near-record high growing season precipitation that was 177% of the 1990–2020 mean. Fine fuel increased across the valley if it was contained within the wildlife refuge boundary and had lower temperature and vapor pressure deficit, higher soil organic content, and abundant annual plants and an invasive perennial grass (R2 = 0.24). The index of potential exposure to wildfire showed a clustering of high exposure centered around roads and low-density housing development distant from fire management points and extending into the upper elevations flanking the valley. Within the Buenos Aires National Wildlife Refuge, fine fuel increased with habitat suitability for the masked bobwhite quail within and adjacent to core habitat areas, representing a natural resource value at risk, accompanied with higher overall mean fine fuel (1672 kg/ha) in relation to 2015 (1347 kg/ha) and 2020 (1363 kg/ha) means.

Conclusions

By connecting high-resolution estimates of fine fuel to climatic, biophysical and land-use factors, wildfire exposure, and a natural resource value at risk, we provide a pro-active and adaptive framework for fire risk management within highly variable and rapidly changing dryland landscapes.

","language":"English","publisher":"Springer","doi":"10.1186/s42408-023-00196-1","usgsCitation":"Wells, A.G., Munson, S.M., Villarreal, M.L., Sesnie, S., and Laushman, K., 2023, Connecting dryland fine-fuel assessments to wildfire exposure and natural resource values at risk: Fire Ecology, v. 19, 37, 20 p., https://doi.org/10.1186/s42408-023-00196-1.","productDescription":"37, 20 p.","ipdsId":"IP-146903","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":442947,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1186/s42408-023-00196-1","text":"Publisher Index Page"},{"id":418583,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"Altar Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -111.68342763370987,\n 31.524152730957113\n ],\n [\n -111.07689163856048,\n 31.33347646138226\n ],\n [\n -110.93146487948965,\n 31.49996137458362\n ],\n [\n -110.95629383835528,\n 32.06679730274084\n ],\n [\n -110.97757580309751,\n 32.114877905907576\n ],\n [\n -111.07334464443704,\n 32.27096495459102\n ],\n [\n -111.10526759154996,\n 32.3728769856678\n ],\n [\n -111.4209500685577,\n 32.39084955148782\n ],\n [\n -111.68342763370987,\n 31.524152730957113\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"19","noUsgsAuthors":false,"publicationDate":"2023-06-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Wells, Adam Gerhard 0000-0001-9675-4963","orcid":"https://orcid.org/0000-0001-9675-4963","contributorId":270137,"corporation":false,"usgs":true,"family":"Wells","given":"Adam","email":"","middleInitial":"Gerhard","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":876400,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Munson, Seth M. 0000-0002-2736-6374 smunson@usgs.gov","orcid":"https://orcid.org/0000-0002-2736-6374","contributorId":1334,"corporation":false,"usgs":true,"family":"Munson","given":"Seth","email":"smunson@usgs.gov","middleInitial":"M.","affiliations":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true},{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":876401,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Villarreal, Miguel L. 0000-0003-0720-1422 mvillarreal@usgs.gov","orcid":"https://orcid.org/0000-0003-0720-1422","contributorId":1424,"corporation":false,"usgs":true,"family":"Villarreal","given":"Miguel","email":"mvillarreal@usgs.gov","middleInitial":"L.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":876402,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sesnie, Steven E.","contributorId":315379,"corporation":false,"usgs":false,"family":"Sesnie","given":"Steven E.","affiliations":[{"id":68297,"text":"U.S. Fish and Wildlife Service, Division of Biological Sciences, Albuquerque, NM 87102, USA","active":true,"usgs":false}],"preferred":false,"id":876403,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Laushman, Katherine M.","contributorId":315380,"corporation":false,"usgs":false,"family":"Laushman","given":"Katherine M.","affiliations":[{"id":68299,"text":"Washington Department of Fish and Wildlife, 7801 Phillips Road SW, Lakewood, WA 98498, USA","active":true,"usgs":false}],"preferred":false,"id":876404,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70256499,"text":"70256499 - 2023 - Migration, breeding location, and seascape shape seabird assemblages in the northern Gulf of Mexico","interactions":[],"lastModifiedDate":"2024-08-19T23:48:40.813272","indexId":"70256499","displayToPublicDate":"2023-06-23T18:38:14","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Migration, breeding location, and seascape shape seabird assemblages in the northern Gulf of Mexico","docAbstract":"

The Gulf of Mexico supports many seabird species, yet data gaps describing species composition and habitat use are prevalent. We used vessel-based observations from the Gulf of Mexico Marine Assessment Program for Protected Species to identify and characterize distinct seabird assemblages in the northern Gulf of Mexico (within the U.S. Exclusive Economic Zone; nGoM). Using cluster analysis of 17 seabird species, we identified assemblages based on seabird relative density. Vessel-based surveys documented the location, species, and number of seabirds across the nGoM between 2017–2019. For each assemblage, we identified the (co-)dominant species, spatial distribution, and areas of greater relative density. We also assessed the relationship of the total relative density within each assemblage with environmental, spatial, and temporal covariates. Of the species assessed, 76% (n = 13) breed predominantly outside the nGoM basin. We identified four seabird assemblages. Two assemblages, one dominated by black tern and the other co-dominated by northern gannet/laughing gull, occurred on the continental shelf. An assemblage dominated by sooty tern occurred along the continental slope into pelagic waters. The fourth assemblage had no dominant species, was broadly distributed, and was composed of observations with low relative density (‘singles’ assemblage). Differentiation of assemblages was linked to migratory patterns, residency, and breeding location. The spatial distributions and relationships of the black tern and northern gannet/laughing gull assemblages with environmental covariates indicate associations with river outflows and ports. The sooty tern assemblage overlapped an area prone to mesoscale feature formation. The singles assemblage may reflect commuting and dispersive behaviors. These findings highlight the importance of seasonal migrations and dynamic features across the seascape, shaping seabird assemblages. Considering the potential far-ranging effects of interactions with seabirds in the nGoM, awareness of these unique patterns and potential links with other fauna could inform future monitoring, research, restoration, offshore energy, and aquaculture development in this highly industrialized sea.

","language":"English","publisher":"PLoS","doi":"10.1371/journal.pone.0287316","usgsCitation":"Michael, P., Hixson, K.M., Gleason, J.S., Haney, C., Satgé, Y., and Jodice, P.G., 2023, Migration, breeding location, and seascape shape seabird assemblages in the northern Gulf of Mexico: PLoS ONE, v. 18, no. 6, e0287316, 26 p., https://doi.org/10.1371/journal.pone.0287316.","productDescription":"e0287316, 26 p.","ipdsId":"IP-144222","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":442961,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0287316","text":"Publisher Index Page"},{"id":432903,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Gulf of Mexico","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -101.24612521060158,\n 31.579440148930942\n ],\n [\n -101.24612521060158,\n 24.287994854244246\n ],\n [\n -80.06448458560156,\n 24.287994854244246\n ],\n [\n -80.06448458560156,\n 31.579440148930942\n ],\n [\n -101.24612521060158,\n 31.579440148930942\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"18","issue":"6","noUsgsAuthors":false,"publicationDate":"2023-06-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Michael, Pamela E.","contributorId":340919,"corporation":false,"usgs":false,"family":"Michael","given":"Pamela E.","affiliations":[{"id":7084,"text":"Clemson University","active":true,"usgs":false}],"preferred":false,"id":907682,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hixson, Kathy M.","contributorId":340920,"corporation":false,"usgs":false,"family":"Hixson","given":"Kathy","email":"","middleInitial":"M.","affiliations":[{"id":7084,"text":"Clemson University","active":true,"usgs":false}],"preferred":false,"id":907683,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gleason, Jeffery S.","contributorId":340921,"corporation":false,"usgs":false,"family":"Gleason","given":"Jeffery","email":"","middleInitial":"S.","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":907684,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Haney, Christopher","contributorId":340922,"corporation":false,"usgs":false,"family":"Haney","given":"Christopher","email":"","affiliations":[{"id":61685,"text":"Terra Mar Applied Sciences","active":true,"usgs":false}],"preferred":false,"id":907685,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Satgé, Yvan","contributorId":340923,"corporation":false,"usgs":false,"family":"Satgé","given":"Yvan","affiliations":[{"id":7084,"text":"Clemson University","active":true,"usgs":false}],"preferred":false,"id":907686,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Jodice, Patrick G.R. 0000-0001-8716-120X","orcid":"https://orcid.org/0000-0001-8716-120X","contributorId":219852,"corporation":false,"usgs":true,"family":"Jodice","given":"Patrick","middleInitial":"G.R.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":907687,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70247138,"text":"70247138 - 2023 - Evaluating deep learning architecture and data assimilation for improving water temperature forecasts at unmonitored locations","interactions":[],"lastModifiedDate":"2023-11-08T16:50:55.631264","indexId":"70247138","displayToPublicDate":"2023-06-23T09:45:00","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7170,"text":"Frontiers in Water","active":true,"publicationSubtype":{"id":10}},"title":"Evaluating deep learning architecture and data assimilation for improving water temperature forecasts at unmonitored locations","docAbstract":"

Deep learning (DL) models are increasingly used to forecast water quality variables for use in decision making. Ingesting recent observations of the forecasted variable has been shown to greatly increase model performance at monitored locations; however, observations are not collected at all locations, and methods are not yet well developed for DL models for optimally ingesting recent observations from other sites to inform focal sites. In this paper, we evaluate two different DL model structures, a long short-term memory neural network (LSTM) and a recurrent graph convolutional neural network (RGCN), both with and without data assimilation for forecasting daily maximum stream temperature 7 days into the future at monitored and unmonitored locations in a 70-segment stream network. All our DL models performed well when forecasting stream temperature as the root mean squared error (RMSE) across all models ranged from 2.03 to 2.11°C for 1-day lead times in the validation period, with substantially better performance at gaged locations (RMSE = 1.45–1.52°C) compared to ungaged locations (RMSE = 3.18–3.27°C). Forecast uncertainty characterization was near-perfect for gaged locations but all DL models were overconfident (i.e., uncertainty bounds too narrow) for ungaged locations. Our results show that the RGCN with data assimilation performed best for ungaged locations and especially at higher temperatures (>18°C) which is important for management decisions in our study location. This indicates that the networked model structure and data assimilation techniques may help borrow information from nearby monitored sites to improve forecasts at unmonitored locations. Results from this study can help guide DL modeling decisions when forecasting other important environmental variables.

","language":"English","publisher":"Frontiers Media","doi":"10.3389/frwa.2023.1184992","usgsCitation":"Zwart, J.A., Diaz, J.A., Hamshaw, S.D., Oliver, S.K., Ross, J.C., Sleckman, M.J., Appling, A.P., Corson-Dosch, H.R., Jia, X., Read, J.S., Sadler, J., Thompson, T.P., Watkins, D., and White, E., 2023, Evaluating deep learning architecture and data assimilation for improving water temperature forecasts at unmonitored locations: Frontiers in Water, v. 5, 1184992, 18 p., https://doi.org/10.3389/frwa.2023.1184992.","productDescription":"1184992, 18 p.","ipdsId":"IP-151646","costCenters":[{"id":37273,"text":"Advanced Research Computing (ARC)","active":true,"usgs":true},{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"links":[{"id":442963,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/frwa.2023.1184992","text":"Publisher Index Page"},{"id":419304,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"5","noUsgsAuthors":false,"publicationDate":"2023-06-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Zwart, Jacob Aaron 0000-0002-3870-405X","orcid":"https://orcid.org/0000-0002-3870-405X","contributorId":237809,"corporation":false,"usgs":true,"family":"Zwart","given":"Jacob","email":"","middleInitial":"Aaron","affiliations":[{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"preferred":true,"id":879014,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Diaz, Jeremy Alejandro 0000-0001-7087-7949","orcid":"https://orcid.org/0000-0001-7087-7949","contributorId":302986,"corporation":false,"usgs":true,"family":"Diaz","given":"Jeremy","email":"","middleInitial":"Alejandro","affiliations":[{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"preferred":true,"id":879015,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hamshaw, Scott Douglas 0000-0002-0583-4237","orcid":"https://orcid.org/0000-0002-0583-4237","contributorId":305601,"corporation":false,"usgs":true,"family":"Hamshaw","given":"Scott","email":"","middleInitial":"Douglas","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":879016,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Oliver, Samantha K. 0000-0001-5668-1165","orcid":"https://orcid.org/0000-0001-5668-1165","contributorId":211886,"corporation":false,"usgs":true,"family":"Oliver","given":"Samantha","email":"","middleInitial":"K.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":879017,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ross, Jesse Cleveland 0000-0002-5422-8284","orcid":"https://orcid.org/0000-0002-5422-8284","contributorId":304193,"corporation":false,"usgs":true,"family":"Ross","given":"Jesse","email":"","middleInitial":"Cleveland","affiliations":[{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"preferred":true,"id":879018,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Sleckman, Margaux Jeanne 0000-0002-1843-6932","orcid":"https://orcid.org/0000-0002-1843-6932","contributorId":295257,"corporation":false,"usgs":true,"family":"Sleckman","given":"Margaux","email":"","middleInitial":"Jeanne","affiliations":[{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"preferred":true,"id":879019,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Appling, Alison P. 0000-0003-3638-8572 aappling@usgs.gov","orcid":"https://orcid.org/0000-0003-3638-8572","contributorId":150595,"corporation":false,"usgs":true,"family":"Appling","given":"Alison","email":"aappling@usgs.gov","middleInitial":"P.","affiliations":[{"id":5054,"text":"Office of Water Information","active":true,"usgs":true}],"preferred":true,"id":879020,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Corson-Dosch, Hayley R. 0000-0001-8695-1584","orcid":"https://orcid.org/0000-0001-8695-1584","contributorId":244707,"corporation":false,"usgs":true,"family":"Corson-Dosch","given":"Hayley","middleInitial":"R.","affiliations":[{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"preferred":true,"id":879021,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Jia, Xiaowei 0000-0001-8544-5233","orcid":"https://orcid.org/0000-0001-8544-5233","contributorId":237807,"corporation":false,"usgs":false,"family":"Jia","given":"Xiaowei","email":"","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":879022,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Read, Jordan S 0000-0002-3888-6631","orcid":"https://orcid.org/0000-0002-3888-6631","contributorId":305964,"corporation":false,"usgs":false,"family":"Read","given":"Jordan","email":"","middleInitial":"S","affiliations":[{"id":12701,"text":"US Geological Survey","active":true,"usgs":false}],"preferred":false,"id":879023,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Sadler, Jeffrey M 0000-0001-8776-4844","orcid":"https://orcid.org/0000-0001-8776-4844","contributorId":302989,"corporation":false,"usgs":false,"family":"Sadler","given":"Jeffrey M","affiliations":[{"id":7249,"text":"Oklahoma State University","active":true,"usgs":false}],"preferred":false,"id":879024,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Thompson, Theodore Paul 0000-0001-7373-314X","orcid":"https://orcid.org/0000-0001-7373-314X","contributorId":295258,"corporation":false,"usgs":true,"family":"Thompson","given":"Theodore","email":"","middleInitial":"Paul","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":879025,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Watkins, David 0000-0002-7544-0700","orcid":"https://orcid.org/0000-0002-7544-0700","contributorId":317375,"corporation":false,"usgs":true,"family":"Watkins","given":"David","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":879026,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"White, Elaheh 0000-0003-1248-5247","orcid":"https://orcid.org/0000-0003-1248-5247","contributorId":295260,"corporation":false,"usgs":true,"family":"White","given":"Elaheh","email":"","affiliations":[{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"preferred":true,"id":879027,"contributorType":{"id":1,"text":"Authors"},"rank":14}]}} ,{"id":70246674,"text":"70246674 - 2023 - Monazite and xenotime petrochronologic constraints on four Proterozoic tectonic episodes and ca. 1705 Ma age of the Uncompahgre Formation, southwestern Colorado, USA","interactions":[],"lastModifiedDate":"2023-08-23T16:46:14.525465","indexId":"70246674","displayToPublicDate":"2023-06-23T07:16:01","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1820,"text":"Geosphere","active":true,"publicationSubtype":{"id":10}},"title":"Monazite and xenotime petrochronologic constraints on four Proterozoic tectonic episodes and ca. 1705 Ma age of the Uncompahgre Formation, southwestern Colorado, USA","docAbstract":"

The Proterozoic tectonic evolution of the south-western USA remains incompletely understood due to limited constraints on the timing and conditions of the tectono-metamorphic phases and depositional age of metasedimentary successions. We integrated multi-scale compositional mapping, petrologic modeling, and in situ geochronology to constrain pressure-temperature-time paths from samples of Paleoproterozoic basement gneisses and overlying quartzites in southwestern Colorado, USA. Basement gneiss from the western Needle Mountains records metamorphic conditions of 600 °C at 0.75 GPa at 1764 ± 9 Ma and ~575 °C at 1741 ± 10 Ma. Gneiss sampled from drill core near Pagosa Springs, Colorado, records conditions of 700 °C at 1748 ± 9 Ma, 800 °C at 1.1 GPa at 1650 ± 40 Ma, 540 °C at 1570 ± 36 Ma, and 440 °C at 1424 ± 12 Ma. The Uncompahgre Formation was deposited at ca. 1705 Ma, as constrained by detrital monazite (1707 ± 8 Ma) and xenotime (1692 ± 40, 1725 ± 50 Ma), metamorphic xenotime (1650 ± 10 Ma), and published 40Ar/39Ar and detrital zircon data. Compositions of ca. 1705 Ma detrital monazite and xenotime are consistent with derivation from a garnet-bearing source in the Yavapai orogenic hinterland. The Vallecito Conglomerate and Uncompahgre Formation record macroscopic folding and greenschist-facies metamorphism at 1650 ± 10 Ma and temperatures of 270 °C to >570 °C at 1470–1400 Ma. Laser ablation–inductively coupled plasma–mass spectrometry (LA-ICP-MS) zircon geochronology yielded dates of 1775 ± 18 Ma from the Twilight Gneiss and 1696 ± 7 Ma from the Bakers Bridge Granite, supporting previous isotope dilution–thermal ionization mass spectrometry (ID-TIMS) dates. The Eolus Granite yielded a date of 1463 ± 6 Ma, which is older than previous 1.44–1.43 Ga ID-TIMS dates. The newly dated granite of Cataract Gulch is 1421 ± 12 Ma. In situ analysis of detrital and metamorphic monazite and xenotime, igneous zircon, and quantitative thermobarometry, integrated with previously published constraints, indicate multiple tectonic episodes after the emplacement of 1800–1760 Ma arc-related rocks. The region experienced greenschist- to amphibolite-facies metamorphism (M1) from 1760 Ma to 1740 Ma, which was followed by the intrusion of granites at 1730–1695 Ma and deposition of the Uncompahgre Formation at ca. 1705 Ma, contemporaneous with the Yavapai orogeny. Metamorphism at 1680–1600 Ma was characterized by greenschist-facies conditions near Ouray, Colorado, and granulite-facies conditions near Pagosa Springs (M2) during the Mazatzal orogeny. From 1470 Ma to 1400 Ma, greenschist- to amphibolite-facies metamorphism (M3) and largely granitic plutonism occurred during the protracted Picuris orogeny. These results demonstrate the power of monazite and xenotime analyses to constrain depositional ages, provenance, and pressure-temperature-time (P-T-t) paths to resolve the compound orogenic history that is characteristic of most mountain belts.

","language":"English","publisher":"Geological Society of America","doi":"10.1130/GES02631.1","usgsCitation":"Hillenbrand, I.W., Williams, M.L., Karlstrom, K.E., Gilmer, A.K., Lowers, H.A., Jercinovic, M.J., Suarez, K., and Souders, A., 2023, Monazite and xenotime petrochronologic constraints on four Proterozoic tectonic episodes and ca. 1705 Ma age of the Uncompahgre Formation, southwestern Colorado, USA: Geosphere, v. 19, no. 4, p. 1057-1079, https://doi.org/10.1130/GES02631.1.","productDescription":"23 p.","startPage":"1057","endPage":"1079","ipdsId":"IP-147636","costCenters":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":442976,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/ges02631.1","text":"Publisher Index Page"},{"id":435277,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9IXUBGV","text":"USGS data release","linkHelpText":"Zircon U-Pb data for Proterozoic rocks in southwestern Colorado and rocks from drill core from Wyoming, Montana, and Nebraska"},{"id":435276,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P90IZUDS","text":"USGS data release","linkHelpText":"Data release of geochemistry and geochronology for Proterozoic rocks in southwestern Colorado and rocks from drill core from Colorado, North Dakota, Nevada, Wyoming, Montana, and Nebraska"},{"id":418924,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -107.5,\n 38.0\n ],\n [\n -107.5,\n 37.3\n ],\n [\n -107.2,\n 37.3\n ],\n [\n -107.2,\n 38.0\n ],\n [\n -107.5,\n 38.0\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"19","issue":"4","noUsgsAuthors":false,"publicationDate":"2023-06-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Hillenbrand, Ian William 0000-0003-2801-3674","orcid":"https://orcid.org/0000-0003-2801-3674","contributorId":299032,"corporation":false,"usgs":true,"family":"Hillenbrand","given":"Ian","email":"","middleInitial":"William","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":877871,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Williams, Michael L.","contributorId":215495,"corporation":false,"usgs":false,"family":"Williams","given":"Michael","email":"","middleInitial":"L.","affiliations":[{"id":37201,"text":"UMass Amherst","active":true,"usgs":false}],"preferred":false,"id":877872,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Karlstrom, Karl E.","contributorId":228844,"corporation":false,"usgs":false,"family":"Karlstrom","given":"Karl","email":"","middleInitial":"E.","affiliations":[{"id":36307,"text":"University of New Mexico","active":true,"usgs":false}],"preferred":false,"id":877873,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gilmer, Amy K. 0000-0001-5038-8136","orcid":"https://orcid.org/0000-0001-5038-8136","contributorId":218307,"corporation":false,"usgs":true,"family":"Gilmer","given":"Amy","email":"","middleInitial":"K.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":877874,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lowers, Heather A. 0000-0001-5360-9264 hlowers@usgs.gov","orcid":"https://orcid.org/0000-0001-5360-9264","contributorId":191307,"corporation":false,"usgs":true,"family":"Lowers","given":"Heather","email":"hlowers@usgs.gov","middleInitial":"A.","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":877875,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Jercinovic, Michael J.","contributorId":316620,"corporation":false,"usgs":false,"family":"Jercinovic","given":"Michael","email":"","middleInitial":"J.","affiliations":[{"id":68659,"text":"University of Massachusetts - Amherst","active":true,"usgs":false}],"preferred":false,"id":877876,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Suarez, Kaitlyn","contributorId":316621,"corporation":false,"usgs":false,"family":"Suarez","given":"Kaitlyn","email":"","affiliations":[{"id":68659,"text":"University of Massachusetts - Amherst","active":true,"usgs":false}],"preferred":false,"id":877877,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Souders, Amanda 0000-0002-1367-8924","orcid":"https://orcid.org/0000-0002-1367-8924","contributorId":296423,"corporation":false,"usgs":true,"family":"Souders","given":"Amanda","email":"","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":877878,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70243136,"text":"70243136 - 2023 - A 1300-year microfaunal record from the Beaufort Sea shelf indicates exceptional climate-related environmental changes over the last two centuries","interactions":[],"lastModifiedDate":"2023-07-19T15:55:47.363433","indexId":"70243136","displayToPublicDate":"2023-06-22T10:49:15","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2996,"text":"Palaeogeography, Palaeoclimatology, Palaeoecology","printIssn":"0031-0182","active":true,"publicationSubtype":{"id":10}},"title":"A 1300-year microfaunal record from the Beaufort Sea shelf indicates exceptional climate-related environmental changes over the last two centuries","docAbstract":"

The environments of Arctic Ocean nearshore areas experience high intra- and inter-annual variability, making it difficult to evaluate the impact of anthropogenic warming. However, a sediment record from the southern Canadian Beaufort Sea allowed us to reconstruct the impacts of climate and environmental changes over the last 1300 years along the northern Yukon coast, Canada. The coring site (PG2303; 69.513°N, 138.895°W; water depth 32 m) is located in the Herschel Basin, where high sedimentation rates (0.1–0.5 cm a−1) allowed analyses at sub-centennial to decadal resolutions. Benthic foraminiferal, ostracod, and tintinnid assemblages, as well as the stable isotope composition of the foraminifera Elphidium clavatum and Cassidulina reniforme were used as paleoclimatic and ecological indicators, while the age model was based on the combined radiometric data of 14C, 210Pb and 137Cs. From ca 700 to 1050 CE, our data suggest penetration of offshore shelf-break waters inferred by the dominance of C. reniforme followed by the relatively abundant Triloculina trihedra in the foraminiferal assemblages as both species are associated with stable saline conditions. Afterwards, the occurrence of ostracods Kotoracythere arctoborealis and Normanicythere leioderma suggests influx of Pacific-sourced waters until ca. 1150 CE. From ∼1150–1650 CE, persistent frigid waters, limited sediment supply, and low abundances of microfossils suggest cold conditions with pervasive annual sea-ice cover that may have restricted upwelling of oceanic waters. After ∼1800 CE, the co-occurrence of Tintinnopsis fimbriata and bacterial/complex organic carbon feeder foraminifera (Quinqueloculina stalkeri, Textularia earlandi and Stetsonia horvathi), suggest an increased influence of freshwater rich in particulate organic matter, which may be related to the spreading of the Mackenzie River plume and/or increased coastal permafrost erosion during longer ice-free seasons. Based on these proxy data, the shift at ∼1800 CE marks the onset of regional warming, which further intensified after ∼1955 CE, likely in response to the anthropogenic forcing.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.palaeo.2023.111670","usgsCitation":"Falardeau, J., de Vernal, A., Seidenkrantz, M., Fritz, M., Cronin, T.M., Gemery, L., Rochon, A., Carnero-Bravo, V., Hillaire-Marcel, C., Pearce, C., and Archambault, P., 2023, A 1300-year microfaunal record from the Beaufort Sea shelf indicates exceptional climate-related environmental changes over the last two centuries: Palaeogeography, Palaeoclimatology, Palaeoecology, v. 625, 111670, 18 p., https://doi.org/10.1016/j.palaeo.2023.111670.","productDescription":"111670, 18 p.","ipdsId":"IP-146909","costCenters":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":442984,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://orcid.org/0000-0003-4591-7325","text":"External Repository"},{"id":419154,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","state":"Alaska, Yukon","otherGeospatial":"Beaufort Sea","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -145.2665658621064,\n 71.13218589622568\n ],\n [\n -145.2665658621064,\n 68.83512392360717\n ],\n [\n -136.49812630673208,\n 68.83512392360717\n ],\n [\n -136.49812630673208,\n 71.13218589622568\n ],\n [\n -145.2665658621064,\n 71.13218589622568\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"625","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Falardeau, Jade","contributorId":304651,"corporation":false,"usgs":false,"family":"Falardeau","given":"Jade","affiliations":[{"id":66141,"text":"1. Geotop and Département des sciences de la Terre et de l’atmosphère, Université du Québec à Montréal, Montréal, Canada","active":true,"usgs":false}],"preferred":false,"id":871236,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"de Vernal, Anne","contributorId":304652,"corporation":false,"usgs":false,"family":"de Vernal","given":"Anne","affiliations":[{"id":66142,"text":"Geotop","active":true,"usgs":false}],"preferred":false,"id":871237,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Seidenkrantz, Marit-Solveig","contributorId":304650,"corporation":false,"usgs":false,"family":"Seidenkrantz","given":"Marit-Solveig","affiliations":[{"id":49183,"text":"Department of Geoscience, Aarhus University, Aarhus, Denmark","active":true,"usgs":false}],"preferred":false,"id":871238,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fritz, Michael","contributorId":176701,"corporation":false,"usgs":false,"family":"Fritz","given":"Michael","email":"","affiliations":[],"preferred":false,"id":871239,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cronin, Thomas M. 0000-0001-9522-3992 tcronin@usgs.gov","orcid":"https://orcid.org/0000-0001-9522-3992","contributorId":304640,"corporation":false,"usgs":true,"family":"Cronin","given":"Thomas","email":"tcronin@usgs.gov","middleInitial":"M.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":871240,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Gemery, Laura 0000-0003-1966-8732","orcid":"https://orcid.org/0000-0003-1966-8732","contributorId":245413,"corporation":false,"usgs":true,"family":"Gemery","given":"Laura","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":871241,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Rochon, Andre","contributorId":316792,"corporation":false,"usgs":false,"family":"Rochon","given":"Andre","email":"","affiliations":[],"preferred":false,"id":878327,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Carnero-Bravo, Vladislav","contributorId":304655,"corporation":false,"usgs":false,"family":"Carnero-Bravo","given":"Vladislav","email":"","affiliations":[],"preferred":false,"id":878328,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Hillaire-Marcel, Claude","contributorId":304656,"corporation":false,"usgs":false,"family":"Hillaire-Marcel","given":"Claude","email":"","affiliations":[],"preferred":false,"id":878329,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Pearce, Christof","contributorId":197126,"corporation":false,"usgs":false,"family":"Pearce","given":"Christof","email":"","affiliations":[{"id":25421,"text":"Department of Geological Sciences, Stockholm University, Sweden","active":true,"usgs":false}],"preferred":false,"id":878330,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Archambault, Philippe","contributorId":304657,"corporation":false,"usgs":false,"family":"Archambault","given":"Philippe","email":"","affiliations":[],"preferred":false,"id":878331,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70263629,"text":"70263629 - 2023 - Uncertainties in intensity-based earthquake magnitude estimates","interactions":[],"lastModifiedDate":"2025-02-18T15:46:50.341945","indexId":"70263629","displayToPublicDate":"2023-06-22T09:43:58","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3372,"text":"Seismological Research Letters","onlineIssn":"1938-2057","printIssn":"0895-0695","active":true,"publicationSubtype":{"id":10}},"title":"Uncertainties in intensity-based earthquake magnitude estimates","docAbstract":"

Estimating the magnitude of historical earthquakes is crucial for assessing seismic hazard. Magnitudes of early‐instrumental earthquakes can be inferred using a combination of instrumental records, field observations, and the observed distribution of shaking intensity determined from macroseismic observations. For earthquakes before 1900, shaking intensity distributions often provide the only information to constrain earthquake magnitude. Considerable effort has been made to develop methods to estimate the magnitude of moderate‐to‐large historical earthquakes using shaking intensities derived from macroseismic data. In this study, we consider earthquakes in California with known instrumental magnitudes to explore uncertainties in estimating the magnitude of historical earthquakes from intensity information alone. We use three California‐specific intensity prediction equations (IPEs) and an IPE based on a global ground‐motion model (GMM) to determine optimum intensity‐based magnitudes for 33 moderate‐to‐large California earthquakes between 1979 and 2021. Intensity‐based magnitudes are close to instrumental magnitudes on average. However, intensity‐based magnitudes for individual events differ by as much as 2.2 magnitude units from instrumental magnitudes. This result reflects the weak dependence of ground motions and shaking intensities on moment magnitude and their strong dependence on stress drop. Considering the intensity distributions of the 1906 San Francisco and 1989 Loma Prieta earthquakes, we show that information that could constrain rupture length is discarded when considering only the 2D decay of intensity with distance. We also show that ground‐motion intensity conversion equations used in a GMM‐based approach may cause a systematic overestimation of large historical earthquake magnitudes. This study underscores both the reducible and potentially irreducible uncertainties associated with using intensity data to estimate magnitudes of historical earthquakes using IPEs and highlights the value of using additional information to constrain rupture dimensions. Using intensity observations alone, moment magnitude uncertainties are typically on the order of a full unit.

","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0220230030","usgsCitation":"Lucas, M.C., Hough, S.E., Stein, S., Salditch, L.M., Gallahue, M.M., Neely, J.S., and Abrahamson, N., 2023, Uncertainties in intensity-based earthquake magnitude estimates: Seismological Research Letters, v. 94, no. 5, p. 2202-2214, https://doi.org/10.1785/0220230030.","productDescription":"13 p.","startPage":"2202","endPage":"2214","ipdsId":"IP-153047","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":482162,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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\"}}]}","volume":"94","issue":"5","noUsgsAuthors":false,"publicationDate":"2023-06-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Lucas, Madeleine C.","contributorId":263451,"corporation":false,"usgs":false,"family":"Lucas","given":"Madeleine","email":"","middleInitial":"C.","affiliations":[{"id":25254,"text":"Northwestern University","active":true,"usgs":false}],"preferred":false,"id":927607,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hough, Susan E. 0000-0002-5980-2986","orcid":"https://orcid.org/0000-0002-5980-2986","contributorId":263442,"corporation":false,"usgs":true,"family":"Hough","given":"Susan","email":"","middleInitial":"E.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":927608,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stein, Seth","contributorId":263457,"corporation":false,"usgs":false,"family":"Stein","given":"Seth","affiliations":[{"id":25254,"text":"Northwestern University","active":true,"usgs":false}],"preferred":false,"id":927609,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Salditch, Leah Marschall 0000-0002-4478-1836","orcid":"https://orcid.org/0000-0002-4478-1836","contributorId":297144,"corporation":false,"usgs":true,"family":"Salditch","given":"Leah","email":"","middleInitial":"Marschall","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":927610,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gallahue, Molly M.","contributorId":263448,"corporation":false,"usgs":false,"family":"Gallahue","given":"Molly","email":"","middleInitial":"M.","affiliations":[{"id":25254,"text":"Northwestern University","active":true,"usgs":false}],"preferred":false,"id":927611,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Neely, James S.","contributorId":263454,"corporation":false,"usgs":false,"family":"Neely","given":"James","email":"","middleInitial":"S.","affiliations":[{"id":25254,"text":"Northwestern University","active":true,"usgs":false}],"preferred":false,"id":927612,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Abrahamson, Norman A.","contributorId":45202,"corporation":false,"usgs":false,"family":"Abrahamson","given":"Norman A.","affiliations":[{"id":13174,"text":"Pacific Gas & Electric","active":true,"usgs":false}],"preferred":false,"id":927613,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70243992,"text":"sir20235021 - 2023 - Application of surrogate technology to predict real-time metallic-contaminant concentrations and loads in the Clark Fork near Grant-Kohrs Ranch National Historic Site, Montana, water years 2019–20","interactions":[],"lastModifiedDate":"2026-03-02T22:18:37.300537","indexId":"sir20235021","displayToPublicDate":"2023-06-22T08:47:18","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2023-5021","displayTitle":"Application of Surrogate Technology to Predict Real-Time Metallic-Contaminant Concentrations and Loads in the Clark Fork near Grant-Kohrs Ranch National Historic Site, Montana, Water Years 2019–20","title":"Application of surrogate technology to predict real-time metallic-contaminant concentrations and loads in the Clark Fork near Grant-Kohrs Ranch National Historic Site, Montana, water years 2019–20","docAbstract":"

Grant-Kohrs Ranch National Historic Site (GRKO) in southwestern Montana commemorates the frontier cattle era and its formative role in shaping the culture and history of the Western United States. The ranch was designated a national historic landmark in 1960 and a unit of the National Park Service (NPS) by Congress in 1972. The GRKO is unique because of its proximity to large-scale extraction, milling, and smelting of gold, silver, copper, and lead ore from the 1860s to the 1980s in the Butte mining district. During this time, mining and milling wastes were discarded in the upper Clark Fork Basin, resulting in the deposition of large amounts of waste materials (tailings) enriched with metallic contaminants (including cadmium, copper, iron, lead, manganese, zinc, and the metalloid trace element arsenic) in soils and in nearby streams and floodplains. Denuded vegetation and fish kills attributed to large concentrations of heavy metals caused the U.S. Environmental Protection Agency to designate a 120-mile section of the Clark Fork River (hereafter referred to as the “Clark Fork”), including GRKO, to be included on the National Priority List for Superfund cleanup in 1989. In 2018, with oversight from the Montana Department of Environmental Quality, the NPS began remediation of 2.6 miles of the Clark Fork as it flows through GRKO property.

In 2019, the U.S. Geological Survey (USGS), in collaboration with the NPS, conducted a study using time-series data from backscatter signals from fixed-point turbidity and acoustic sensors with the intent to provide a high-resolution monitoring tool to estimate metallic-contaminant concentrations (MCCs) and loads during NPS remediation of the Clark Fork. Two monitoring sites at USGS streamgages on the Clark Fork on either side of GRKO property were instrumented with turbidity and acoustic sensors and surrogate relations were developed among time-series data and MCCs. The application of high-resolution surrogate data was used to infer contaminant source and fate and evaluate MCC values relative to aquatic-life standards. Using high-resolution surrogate data, it was determined that during spring runoff and storm-related runoff events, MCCs peaked at their highest values at streamflows markedly lower and prior to peak streamflow. Because MCCs peaked prior to streamflow peaks, it could be inferred that the source of MCCs originated from channel bed sediments in close spatial proximity to the monitoring site or from nearby streambanks and floodplains. High-resolution surrogate data revealed that copper concentrations in the Clark Fork exceeded chronic aquatic-life standards 90 percent of the time when streamflow exceeded 200 cubic feet per second (ft3/s) and exceeded acute aquatic-life standards 85 percent of the time when streamflow exceeded 260 ft3/s. These data helped support NPS management goals for evaluating variation in water quality during remediation of GRKO property, evaluating MCC values relative to aquatic-life standards, and quantifying benefits from Superfund remediation activities.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235021","collaboration":"Prepared in cooperation with the National Park Service","usgsCitation":"Ellison, C.A., Sando, S.K., and Cleasby, T.E., 2023, Application of surrogate technology to predict real-time metallic-contaminant concentrations and loads in the Clark Fork near Grant-Kohrs Ranch National Historic Site, Montana, water years 2019–20: U.S. Geological Survey Scientific Investigations Report 2023–5021, 70 p., https://doi.org/10.3133/sir20235021.","productDescription":"Report: x, 70 p.; Data Release; Dataset","numberOfPages":"84","onlineOnly":"Y","ipdsId":"IP-133560","costCenters":[{"id":685,"text":"Wyoming-Montana Water Science Center","active":false,"usgs":true}],"links":[{"id":417541,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9330BXM","text":"USGS data release","linkHelpText":"Water quality and streamflow data for the Clark Fork near Grant-Kohrs Ranch National Historic Site in southwestern Montana, water years 2019–20"},{"id":500715,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114935.htm","linkFileType":{"id":5,"text":"html"}},{"id":417543,"rank":6,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2023/5021/images"},{"id":417542,"rank":5,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"—USGS water data for the Nation"},{"id":417540,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2023/5021/sir20235021.XML","text":"Report","linkFileType":{"id":8,"text":"xml"},"description":"SIR 2023–5021 XML"},{"id":417539,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2023/5021/sir20235021.pdf","text":"Report","size":"8.46 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2023–5021"},{"id":418358,"rank":7,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.er.usgs.gov/publication/sir20235021/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2023–5021"},{"id":417538,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2023/5021/coverthb.jpg"}],"country":"United States","state":"Montana","otherGeospatial":"Clark Fork, Grant-Kohrs Ranch National Historic Site","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -113.99863083744248,\n 47.014564748966194\n ],\n [\n -113.99863083744248,\n 45.54540728416404\n ],\n [\n -112.31070324373364,\n 45.54540728416404\n ],\n [\n -112.31070324373364,\n 47.014564748966194\n ],\n [\n -113.99863083744248,\n 47.014564748966194\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"

Director, Wyoming-Montana Water Science Center
U.S. Geological Survey
3162 Bozeman Avenue
Helena, MT 59601

Contact Pubs Warehouse

","tableOfContents":"","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2023-06-22","noUsgsAuthors":false,"publicationDate":"2023-06-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Ellison, Christopher A. 0000-0002-5886-6654 cellison@usgs.gov","orcid":"https://orcid.org/0000-0002-5886-6654","contributorId":4891,"corporation":false,"usgs":true,"family":"Ellison","given":"Christopher","email":"cellison@usgs.gov","middleInitial":"A.","affiliations":[{"id":685,"text":"Wyoming-Montana Water Science Center","active":false,"usgs":true}],"preferred":true,"id":874088,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sando, Steven K. 0000-0003-1206-1030 sksando@usgs.gov","orcid":"https://orcid.org/0000-0003-1206-1030","contributorId":1016,"corporation":false,"usgs":true,"family":"Sando","given":"Steven","email":"sksando@usgs.gov","middleInitial":"K.","affiliations":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"preferred":true,"id":874089,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cleasby, Tom E. 0000-0003-0694-1541 tcleasby@usgs.gov","orcid":"https://orcid.org/0000-0003-0694-1541","contributorId":139625,"corporation":false,"usgs":true,"family":"Cleasby","given":"Tom","email":"tcleasby@usgs.gov","middleInitial":"E.","affiliations":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"preferred":true,"id":874090,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70245777,"text":"70245777 - 2023 - Mapping abandoned uranium mine features using Worldview-3 imagery in portions of Karnes, Atascosa and Live Oak Counties, Texas","interactions":[],"lastModifiedDate":"2023-06-27T12:00:36.399687","indexId":"70245777","displayToPublicDate":"2023-06-22T06:54:49","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":15678,"text":"MDPI-Minerals","active":true,"publicationSubtype":{"id":10}},"title":"Mapping abandoned uranium mine features using Worldview-3 imagery in portions of Karnes, Atascosa and Live Oak Counties, Texas","docAbstract":"
Worldview-3 (WV3) 16-band multispectral data were used to map exposed bedrock and mine waste piles associated with legacy open-pit mining of sandstone-hosted roll-front uranium deposits along the South Texas Coastal Plain. We used the “spectral hourglass” approach to extract spectral endmembers representative of these features from the image. This approach first requires calibrating the imagery to reflectance, then masking for vegetation, followed by spatial and spectral data reduction using a principal component analysis-based procedure that reduces noise and identifies homogeneous targets which are “pure” enough to be considered spectral endmembers. In this case, we used a single WV3 image which covered an ~11.5 km by ~19.5 km area of Karnes, Atascosa and Live Oak Counties, underlain by mined rocks from the Jackson Group and Catahoula Formation. Up to 58 spectral endmembers were identified using a further multi-dimensional class segregation method and were used as inputs for spectral angle mapper (SAM) classification. SAM classification resulted in the identification of at least 117 mine- and mine waste-related features, most of which were previously unknown. Class similarity was further evaluated, and the dominant minerals in each class were identified by comparison to spectral libraries and measured samples of actual Jackson Group uranium host rocks. Redundant classes were eliminated, and SAM was run a second time using a reduced set of 23 endmembers, which were found to map these same features as effectively as using the full 58 set of endmembers, but with significantly reduced noise and spectral outliers. Our classification results were validated by evaluating detailed scale mapping of three known mine sites (Esse-Spoonamore, Wright-McCrady and Garbysch-Thane) with published ground truth information about the vegetation cover, extent of erosion and exposure of waste pile materials and/or geologic information about host lithology and mineralization. Despite successful demonstration of the utility of WV3 data for inventorying mine features, additional landscape features such as bare agricultural fields and oil and gas drill pads were also identified. The elimination of such features will require combining the spectral classification maps presented in this study with high-quality topographic data. Also, the spectral endmembers identified during the course of this study could be useful for larger-scale mapping efforts using additional well-calibrated WV3 images beyond the coverage of our initial study area.
","language":"English","publisher":"MDPI","doi":"10.3390/min13070839","usgsCitation":"Hubbard, B.E., Gallegos, T., and Stengel, V.G., 2023, Mapping abandoned uranium mine features using Worldview-3 imagery in portions of Karnes, Atascosa and Live Oak Counties, Texas: MDPI-Minerals, v. 13, no. 7, 839, 30 p., https://doi.org/10.3390/min13070839.","productDescription":"839, 30 p.","ipdsId":"IP-136838","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true},{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true},{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"links":[{"id":442989,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/min13070839","text":"Publisher Index Page"},{"id":418499,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Texas","county":"Karnes County, Atascosa County, Live Oak County","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-98.4083,29.1104],[-98.2809,28.9878],[-98.1879,28.8807],[-97.7292,29.224],[-97.6145,29.1096],[-97.755,29.0056],[-97.5693,28.8157],[-97.7706,28.6717],[-97.7743,28.669],[-97.7812,28.6646],[-97.7847,28.6688],[-97.7882,28.6716],[-97.7929,28.6721],[-97.8267,28.6715],[-97.8276,28.6742],[-97.8291,28.6761],[-97.8353,28.679],[-97.8461,28.6824],[-97.8538,28.6839],[-97.859,28.6845],[-97.8637,28.6841],[-97.8641,28.6874],[-97.8682,28.6902],[-97.8795,28.6932],[-97.8913,28.6998],[-97.8954,28.7013],[-97.8975,28.7032],[-97.8995,28.7055],[-97.8989,28.7073],[-97.8999,28.7092],[-97.9035,28.7116],[-97.9127,28.7168],[-97.9189,28.7187],[-98.0037,28.6896],[-98.0894,28.6599],[-98.0167,28.5323],[-97.8084,28.1788],[-97.8136,28.1757],[-97.8896,28.1253],[-97.8991,28.1185],[-97.9007,28.1167],[-97.9018,28.1135],[-97.9008,28.1108],[-97.9009,28.1071],[-97.902,28.1048],[-97.9047,28.0998],[-97.9059,28.0934],[-97.9041,28.0846],[-97.9021,28.079],[-97.9013,28.0726],[-97.8988,28.0684],[-97.8963,28.0646],[-97.8943,28.0609],[-97.8923,28.0595],[-98.2338,28.0607],[-98.3343,28.06],[-98.3358,28.4775],[-98.336,28.4982],[-98.3363,28.6117],[-98.3372,28.6443],[-98.8035,28.645],[-98.8039,29.0884],[-98.8042,29.2513],[-98.4083,29.1104]]]},\"properties\":{\"name\":\"Atascosa\",\"state\":\"TX\"}}]}","volume":"13","issue":"7","noUsgsAuthors":false,"publicationDate":"2023-06-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Hubbard, Bernard E. 0000-0002-9315-2032","orcid":"https://orcid.org/0000-0002-9315-2032","contributorId":213146,"corporation":false,"usgs":true,"family":"Hubbard","given":"Bernard","email":"","middleInitial":"E.","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":876302,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gallegos, Tanya J. 0000-0003-3350-6473","orcid":"https://orcid.org/0000-0003-3350-6473","contributorId":206859,"corporation":false,"usgs":true,"family":"Gallegos","given":"Tanya J.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":876303,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stengel, Victoria G. 0000-0003-0481-3159 vstengel@usgs.gov","orcid":"https://orcid.org/0000-0003-0481-3159","contributorId":5932,"corporation":false,"usgs":true,"family":"Stengel","given":"Victoria","email":"vstengel@usgs.gov","middleInitial":"G.","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":876304,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70244892,"text":"dr1177 - 2023 - Least Bell’s Vireo (Vireo bellii pusillus) and Southwestern Willow Flycatcher (Empidonax traillii extimus) surveys in the Sepulveda Dam Basin, Los Angeles County, California—2022 data summary","interactions":[],"lastModifiedDate":"2023-06-22T11:11:23.303027","indexId":"dr1177","displayToPublicDate":"2023-06-21T14:29:56","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":9318,"text":"Data Report","code":"DR","onlineIssn":"2771-9448","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1177","displayTitle":"Least Bell’s Vireo (Vireo bellii pusillus) and Southwestern Willow Flycatcher (Empidonax traillii extimus) Surveys in the Sepulveda Dam Basin, Los Angeles County, California—2022 Data Summary","title":"Least Bell’s Vireo (Vireo bellii pusillus) and Southwestern Willow Flycatcher (Empidonax traillii extimus) surveys in the Sepulveda Dam Basin, Los Angeles County, California—2022 data summary","docAbstract":"

Executive Summary

We surveyed for Least Bell’s Vireos (Vireo bellii pusillus; vireo) and Southwestern Willow Flycatchers (Empidonax traillii extimus; flycatcher) along Bull Creek, Haskell Creek, and the Los Angeles River (Sepulveda Dam project area) in Los Angeles County, California, in 2022. Four vireo surveys were completed from April 26 to July 14, and three flycatcher surveys were completed from May 19 to July 14. We detected 10 territorial male vireos, 5 of which were confirmed as paired, and 2 transient vireos. Of the 10 territorial vireos, 70 percent were detected along the Los Angeles River, 20 percent along Bull Creek, and 10 percent along Haskell Creek. Of the vireos detected, 80 percent were in habitats characterized as mixed willow, and most vireos were detected in habitats with greater than 50-percent native plant cover. One transient flycatcher was observed in the survey area in 2022.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/dr1177","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers","programNote":"Ecosystems Mission Area—Species Management Research Program","usgsCitation":"Pottinger, R.E., and Kus, B.E., 2023, Least Bell’s Vireo (Vireo bellii pusillus) and Southwestern Willow Flycatcher (Empidonax traillii extimus) surveys in the Sepulveda Dam Basin, Los Angeles County, California—2022 data summary: U.S. Geological Survey Data Report 1177, 8 p., https://doi.org/10.3133/dr1177.","productDescription":"vii, 8 p.","numberOfPages":"8","onlineOnly":"Y","ipdsId":"IP-147329","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":418110,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/preview/dr1177/full"},{"id":418109,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/dr/1177/images"},{"id":418108,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/dr/1177/dr1177.xml"},{"id":418107,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/dr/1177/dr1177.pdf","size":"6 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":418106,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/dr/1177/covrthb.jpg"}],"country":"United States","state":"California","county":"Los Angeles County","otherGeospatial":"Sepulveda Dam project area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -118.53187344095177,\n 34.199920176198304\n ],\n [\n -118.53187344095177,\n 34.137737606736394\n ],\n [\n -118.42583220728267,\n 34.137737606736394\n ],\n [\n -118.42583220728267,\n 34.199920176198304\n ],\n [\n -118.53187344095177,\n 34.199920176198304\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"

Western Ecological Research Center
U.S. Geological Survey
3020 State University Drive East
Sacramento, California 95819

","tableOfContents":"","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"publishedDate":"2023-06-21","noUsgsAuthors":false,"publicationDate":"2023-06-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Pottinger, Ryan E. 0000-0002-0263-0300","orcid":"https://orcid.org/0000-0002-0263-0300","contributorId":212869,"corporation":false,"usgs":true,"family":"Pottinger","given":"Ryan","email":"","middleInitial":"E.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":875420,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kus, Barbara E. 0000-0002-3679-3044 barbara_kus@usgs.gov","orcid":"https://orcid.org/0000-0002-3679-3044","contributorId":3026,"corporation":false,"usgs":true,"family":"Kus","given":"Barbara E.","email":"barbara_kus@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":875421,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70256429,"text":"70256429 - 2023 - Exposure to risk factors experienced during migration is not associated with recent Vermivora warbler population trends","interactions":[],"lastModifiedDate":"2024-08-01T16:17:18.454766","indexId":"70256429","displayToPublicDate":"2023-06-21T11:11:40","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2602,"text":"Landscape Ecology","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Exposure to risk factors experienced during migration is not associated with recent Vermivora warbler population trends","title":"Exposure to risk factors experienced during migration is not associated with recent Vermivora warbler population trends","docAbstract":"

Context

Understanding the factors limiting populations of animals is critical for effective conservation. Determining which factors limit populations of migratory species can be especially challenging because of their reliance on multiple, often geographically distant regions during their annual cycles.

Objectives

We investigated whether distribution-wide variation in recent breeding population trends was more strongly associated with exposure to risk factors experienced during migration (i.e., natural and anthropogenic threats often associated with increased mortality or carry-over effects) or factors associated with breeding and nonbreeding areas in golden-winged warblers (Vermivora chrysoptera) and blue-winged warblers (V. cyanoptera), two Nearctic-Neotropical migrants experiencing regionally variable population trends.

Methods

We used geolocator data from 85 Vermivora warblers (n = 90 geolocator tracks) tracked from North American breeding locations and Central American nonbreeding locations from 2013 to 2017 to determine variation in space use among populations. We assessed whether differences in space use among populations of Vermivora warblers during migration were associated with exposure to migration risk-factors and whether increased relative exposure to migration risk factors was associated with population declines at regional and subregional scales.

Results

Regional and subregional populations of Vermivora warblers exhibited variation in space use and exposure to anthropogenic and natural risk-factors. However, we found no evidence that recent variation in population trends of Vermivora warblers was associated with risk-factors experienced by different populations during migration. Instead, factors associated with land cover-types in breeding and nonbreeding areas were more strongly associated with recent population trends.

Conclusions

Understanding how populations of migratory birds are affected by factors experienced during migration is critical for their conservation. We did not find evidence that variation in exposure to migration risk-factors is associated with recent regional or subregional variation in Vermivora warbler population trends. Consequently, our results suggest that efforts to reverse ongoing population declines of Vermivora warblers may be more effective if directed toward conservation actions targeting limiting factors within the breeding and nonbreeding periods versus those directed at conditions encountered during migration. We caution that geographic variation in projected land-use change may differentially affect areas used by different populations of Vermivora warblers during migration, posing a potential threat to these species in the future.

","language":"English","publisher":"Springer Link","doi":"10.1007/s10980-023-01701-2","usgsCitation":"Kramer, G., Andersen, D.E., Buehler, D., Wood, P.B., Peterson, S.M., Lehman, J., Aldinger, K.R., Bulluck, L.P., Harding, S., Jones, J.A., Loegering, J.P., Smalling, C., Vallender, R., and Streby, H.M., 2023, Exposure to risk factors experienced during migration is not associated with recent Vermivora warbler population trends: Landscape Ecology, v. 38, p. 2357-2380, https://doi.org/10.1007/s10980-023-01701-2.","productDescription":"24 p.","startPage":"2357","endPage":"2380","ipdsId":"IP-145286","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":502557,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://open-science.canada.ca/handle/123456789/2861","text":"External Repository"},{"id":432039,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"38","noUsgsAuthors":false,"publicationDate":"2023-06-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Kramer, Gunnar R.","contributorId":276165,"corporation":false,"usgs":false,"family":"Kramer","given":"Gunnar R.","affiliations":[{"id":12455,"text":"University of Toledo","active":true,"usgs":false}],"preferred":false,"id":907335,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Andersen, David E. 0000-0001-9535-3404 dea@usgs.gov","orcid":"https://orcid.org/0000-0001-9535-3404","contributorId":199408,"corporation":false,"usgs":true,"family":"Andersen","given":"David","email":"dea@usgs.gov","middleInitial":"E.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":907336,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Buehler, David A.","contributorId":274719,"corporation":false,"usgs":false,"family":"Buehler","given":"David A.","affiliations":[{"id":56640,"text":"University of Tennesse","active":true,"usgs":false}],"preferred":false,"id":907337,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wood, Petra B. 0000-0002-8575-1705 pbwood@usgs.gov","orcid":"https://orcid.org/0000-0002-8575-1705","contributorId":199090,"corporation":false,"usgs":true,"family":"Wood","given":"Petra","email":"pbwood@usgs.gov","middleInitial":"B.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":907339,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Peterson, Sean M.","contributorId":9354,"corporation":false,"usgs":false,"family":"Peterson","given":"Sean","email":"","middleInitial":"M.","affiliations":[{"id":34539,"text":"Minnesota Cooperative Fish and Wildlife Research Unit","active":true,"usgs":false},{"id":13013,"text":"Department of Environmental Science, Policy and Management, University of California, Berkeley","active":true,"usgs":false}],"preferred":false,"id":907340,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lehman, J.A.","contributorId":340532,"corporation":false,"usgs":false,"family":"Lehman","given":"J.A.","email":"","affiliations":[{"id":12716,"text":"University of Tennessee","active":true,"usgs":false}],"preferred":false,"id":907338,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Aldinger, Kyle R.","contributorId":171892,"corporation":false,"usgs":false,"family":"Aldinger","given":"Kyle","email":"","middleInitial":"R.","affiliations":[{"id":34541,"text":"West Virginia Cooperative Fish and Wildlife Research Unit","active":true,"usgs":false},{"id":12432,"text":"West Virginia University","active":true,"usgs":false}],"preferred":false,"id":907341,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Bulluck, Lesley P.","contributorId":204987,"corporation":false,"usgs":false,"family":"Bulluck","given":"Lesley","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":907342,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Harding, Sergio","contributorId":340539,"corporation":false,"usgs":false,"family":"Harding","given":"Sergio","affiliations":[{"id":56188,"text":"Virginia Department of Wildlife Resources","active":true,"usgs":false}],"preferred":false,"id":907343,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Jones, John A.","contributorId":200310,"corporation":false,"usgs":false,"family":"Jones","given":"John","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":907344,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Loegering, John P.","contributorId":166933,"corporation":false,"usgs":false,"family":"Loegering","given":"John","email":"","middleInitial":"P.","affiliations":[{"id":33353,"text":"University of Minnesota, Crookston","active":true,"usgs":false}],"preferred":false,"id":907345,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Smalling, Curtis","contributorId":340542,"corporation":false,"usgs":false,"family":"Smalling","given":"Curtis","affiliations":[{"id":33352,"text":"Audubon North Carolina","active":true,"usgs":false}],"preferred":false,"id":907346,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Vallender, Rachel","contributorId":194966,"corporation":false,"usgs":false,"family":"Vallender","given":"Rachel","email":"","affiliations":[{"id":27312,"text":"Canadian Wildlife Service, Environment and Climate Change Canada, 6 Bruce Street, Mount","active":true,"usgs":false},{"id":34540,"text":"Canadian Museum of Nature","active":true,"usgs":false}],"preferred":false,"id":907347,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Streby, Henry M.","contributorId":11024,"corporation":false,"usgs":false,"family":"Streby","given":"Henry","email":"","middleInitial":"M.","affiliations":[{"id":12455,"text":"University of Toledo","active":true,"usgs":false}],"preferred":false,"id":907348,"contributorType":{"id":1,"text":"Authors"},"rank":14}]}} ,{"id":70244248,"text":"ofr20231041 - 2023 - Ecological effects of pinyon-juniper removal in the Western United States—A synthesis of scientific research, January 2014–March 2021","interactions":[],"lastModifiedDate":"2023-09-18T19:47:43.622569","indexId":"ofr20231041","displayToPublicDate":"2023-06-21T09:08:44","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2023-1041","displayTitle":"Ecological Effects of Pinyon-Juniper Removal in the Western United States—A Synthesis of Scientific Research, January 2014–March 2021","title":"Ecological effects of pinyon-juniper removal in the Western United States—A synthesis of scientific research, January 2014–March 2021","docAbstract":"

Executive Summary

Increasing density of pinyon (Pinus spp.) and juniper (Juniperus spp.) woodlands (hereinafter “pinyon-juniper”), as well as expansion of these woodlands into adjacent shrublands and grasslands, has altered ecosystem function and wildlife habitat across large areas of the interior western United States. Although there are many natural and human-caused drivers of woodland infilling and expansion, restoration of sagebrush (Artemisia spp.) habitat through removal of pinyon-juniper is considered an urgent management objective in many locations, particularly in support of sagebrush-dependent wildlife species of conservation concern. In December 2020, the Bureau of Land Management (BLM) established the Pinyon-Juniper Management Categorical Exclusion (PJCX) to expedite the regulatory process for pinyon-juniper removal projects on public lands, largely intended to benefit mule deer (Odocoileus hemionus) and greater sage-grouse (Centrocercus urophasianus) habitats. During final preparation of this report, the BLM discontinued use of the PJCX (as of November, 2022), but the pinyon-juniper tree removal techniques assessed in this report are commonly used and understanding their effects remains relevant to land use planning.

To address areas of uncertainty relative to potential ecological effects of the PJCX, we conducted a review of the peer-reviewed science literature to better understand the likely responses of vegetation, environmental (for example, soils), and wildlife variables to specific tree removal techniques permitted by the PJCX. In brief, the PJCX permitted removal of trees by either manual cutting, mechanical cutting, or mastication; allowed certain methods to redistribute or remove resulting tree biomass after treatment; and prohibited broadcast burning, roadbuilding, removal of old-growth, and seeding of non-native species. Specifically, we conducted our review to address the following questions:

  1. How will PJCX removal techniques affect plant communities, soils, and abiotic resources?
  2. How do these pinyon-juniper removal techniques affect wildlife communities, including both woodland- and sagebrush-dependent species?
  3. What are the potential ecological implications of different pinyon-juniper removal treatment types and implementation strategies (for example, treatment sizes) over time?
  4. What are the most important gaps in our scientific understanding of how treatments might affect targeted ecosystems over space and time (for example, potential effects of climate change)?

To answer these questions, we considered studies related to pinyon-juniper ecosystems, focusing on research that occurred over a large portion of the interior western United States that is the primary focus of the PJCX. We also focused on papers published from 2014 onward, to avoid excessive overlap with other recent reviews on pinyon-juniper management effects. Using strict criteria, including only considering research that tested responses for statistical significance, we identified 48 papers that primarily examined treatment effects on vegetation and other environmental variables (1,709 responses), and 11 papers that addressed effects on wildlife (132 responses). Responses to the PJCX-permitted treatments were summarized as either positive (that is, a significant increase), negative (that is, a significant decrease), or non-significant (that is, no significant difference). Responses were assigned to categories (for example, Native Annual Grass/Forb Abundance) and hierarchical treatment levels.

We found that there were large proportions of non-significant responses among all categories combined, with roughly half or more of all responses non-significant (48 percent for wildlife, 60 percent for vegetation-environmental), comparable to other recent systematic reviews of pinyon-juniper treatment effects. However, we also found that when there were significant responses, some important trends potentially emerged. Important undesirable outcomes included far more positive than negative responses of exotic grass and forb abundance among nearly all treatment types. Cutting treatments were also more likely to decrease biocrust cover and microbial activity. Potentially beneficial outcomes included mostly positive responses among sagebrush obligate species, including more positive than negative responses for mule deer and sage-grouse. Some treatment types (for example, mastication) also resulted in more positive than negative responses for native grasses and forbs (although, non-significant responses were the majority). We also highlighted many limitations of this review, including how responses often come from few studies, and how some response-treatment category combinations lack adequate response data. Moreover, the existing research is often insufficient to address many key questions about treatment effects, largely owing to short time-scales and limited spatial extents of observations, which do not match the size of treatments being implemented by land managers, nor capture long-term, post-treatment ecological dynamics. We also identify a lack of research that addresses key interactions that could undermine restoration objectives, including potential effects of climate change and grazing on post-treatment environments. Thus, we emphasize the importance of integrating these factors into future pinyon-juniper treatment research, and we stress the need for use of monitoring programs and research studies that partake in data collection and analysis over long durations and broad spatial scales.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20231041","collaboration":"Prepared in cooperation with the Bureau of Land Management","usgsCitation":"Shinneman, D.J., McIlroy, S.K., Poessel, S.A., Downing, R.L., Johnson, T.N., Young, A.C., and Katzner, T.E., 2023, Ecological effects of pinyon-juniper removal in the Western United States—A synthesis of scientific research, January 2014–March 2021: U.S. Geological Survey Open-File Report 2023–1041, 56 p., https://doi.org/10.3133/ofr20231041.","productDescription":"viii, 56 p.","onlineOnly":"Y","ipdsId":"IP-147314","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":417951,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2023/1041/images"},{"id":417950,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20231041/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2023-1041"},{"id":417949,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2023/1041/ofr20231041.pdf","text":"Report","size":"96 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2023-1041"},{"id":417948,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2023/1041/coverthb.jpg"},{"id":417952,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2023/1041/ofr20231041.XML"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -127.07350481470358,\n 50.40448106244946\n ],\n [\n -127.07350481470358,\n 30.159124183877992\n ],\n [\n -101.68400762449346,\n 30.159124183877992\n ],\n [\n -101.68400762449346,\n 50.40448106244946\n ],\n [\n -127.07350481470358,\n 50.40448106244946\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"

Director, Forest and Rangeland Ecosystem Science Center
777 NW 9th Street, Suite 400
Corvallis, OR 97330

","tableOfContents":"","publishedDate":"2023-06-21","noUsgsAuthors":false,"publicationDate":"2023-06-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Shinneman, Douglas J. 0000-0002-4909-5181 dshinneman@usgs.gov","orcid":"https://orcid.org/0000-0002-4909-5181","contributorId":147745,"corporation":false,"usgs":true,"family":"Shinneman","given":"Douglas","email":"dshinneman@usgs.gov","middleInitial":"J.","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":874999,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McIlroy, Susan K. 0000-0001-5088-3700 smcilroy@usgs.gov","orcid":"https://orcid.org/0000-0001-5088-3700","contributorId":4649,"corporation":false,"usgs":true,"family":"McIlroy","given":"Susan","email":"smcilroy@usgs.gov","middleInitial":"K.","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":false,"id":875000,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Poessel, Sharon A 0000-0002-0283-627X spoessel@usgs.gov","orcid":"https://orcid.org/0000-0002-0283-627X","contributorId":127029,"corporation":false,"usgs":false,"family":"Poessel","given":"Sharon","email":"spoessel@usgs.gov","middleInitial":"A","affiliations":[{"id":6737,"text":"Colorado State University, Department of Ecosystem Science and Sustainability, and Natural Resource Ecology Laboratory","active":true,"usgs":false}],"preferred":false,"id":875001,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Downing, Rosemary L. 0000-0003-1890-5919 rdowning@usgs.gov","orcid":"https://orcid.org/0000-0003-1890-5919","contributorId":306195,"corporation":false,"usgs":false,"family":"Downing","given":"Rosemary","email":"rdowning@usgs.gov","middleInitial":"L.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":false,"id":875002,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Johnson, Tracey N. 0000-0003-3480-8596","orcid":"https://orcid.org/0000-0003-3480-8596","contributorId":223735,"corporation":false,"usgs":false,"family":"Johnson","given":"Tracey","email":"","middleInitial":"N.","affiliations":[{"id":40761,"text":"Department of Fish and Wildlife Sciences, University of Idaho, Moscow, ID 83844","active":true,"usgs":false}],"preferred":false,"id":875003,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Young, Aaron C. 0000-0002-7577-4081","orcid":"https://orcid.org/0000-0002-7577-4081","contributorId":306196,"corporation":false,"usgs":false,"family":"Young","given":"Aaron","email":"","middleInitial":"C.","affiliations":[{"id":33345,"text":" University of Idaho","active":true,"usgs":false}],"preferred":false,"id":875004,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Katzner, Todd E. 0000-0003-4503-8435 tkatzner@usgs.gov","orcid":"https://orcid.org/0000-0003-4503-8435","contributorId":191353,"corporation":false,"usgs":true,"family":"Katzner","given":"Todd E.","email":"tkatzner@usgs.gov","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":875005,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70259717,"text":"70259717 - 2023 - Cooperative joint inversion of magnetotelluric and microseismic data for imaging the Geysers geothermal field, California, USA","interactions":[],"lastModifiedDate":"2024-10-19T13:08:45.132149","indexId":"70259717","displayToPublicDate":"2023-06-21T08:07:03","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1808,"text":"Geophysics","active":true,"publicationSubtype":{"id":10}},"title":"Cooperative joint inversion of magnetotelluric and microseismic data for imaging the Geysers geothermal field, California, USA","docAbstract":"

The Geysers geothermal field located in northern California, USA, is the world’s largest electricity-generating geothermal facility. To delineate the spatio-temporal distribution of reservoir steam and recharge water, we have collected microseismic and magnetotelluric (MT) data using a dense array of stations in 2021. The microseismic and MT data have been inverted together using a 3D cooperative joint inversion workflow. The joint inversion exploits a cross-gradient structural constraint because electrical conductivity structures observed in the geothermal field are strongly correlated with 

","language":"English","publisher":"Society of Exploration Geophysicists","doi":"10.1190/geo2022-0521.1","usgsCitation":"Um, E., Commer, M., Gritto, R., Peacock, J., Alumbaugh, D., Jarpe, S.P., and Hartline, C., 2023, Cooperative joint inversion of magnetotelluric and microseismic data for imaging the Geysers geothermal field, California, USA: Geophysics, v. 88, no. 5, p. WB45-WB54, https://doi.org/10.1190/geo2022-0521.1.","productDescription":"10 p.","startPage":"WB45","endPage":"WB54","ipdsId":"IP-147160","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":467106,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://escholarship.org/uc/item/64g3h0k7","text":"External Repository"},{"id":463039,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Geysers geothermal field","volume":"88","issue":"5","noUsgsAuthors":false,"publicationDate":"2023-06-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Um, Evan","contributorId":345396,"corporation":false,"usgs":false,"family":"Um","given":"Evan","email":"","affiliations":[{"id":39617,"text":"Lawrence Berkeley National Lab","active":true,"usgs":false}],"preferred":false,"id":916421,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Commer, Michael","contributorId":345398,"corporation":false,"usgs":false,"family":"Commer","given":"Michael","email":"","affiliations":[{"id":39617,"text":"Lawrence Berkeley National Lab","active":true,"usgs":false}],"preferred":false,"id":916422,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gritto, Roland","contributorId":194798,"corporation":false,"usgs":false,"family":"Gritto","given":"Roland","email":"","affiliations":[],"preferred":false,"id":916423,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Peacock, Jared R. 0000-0002-0439-0224","orcid":"https://orcid.org/0000-0002-0439-0224","contributorId":210082,"corporation":false,"usgs":true,"family":"Peacock","given":"Jared R.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":916424,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Alumbaugh, David 0000-0002-6975-7197","orcid":"https://orcid.org/0000-0002-6975-7197","contributorId":299109,"corporation":false,"usgs":false,"family":"Alumbaugh","given":"David","email":"","affiliations":[{"id":64775,"text":"Berkeley National Lab","active":true,"usgs":false}],"preferred":false,"id":916425,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Jarpe, Steve P.","contributorId":345402,"corporation":false,"usgs":false,"family":"Jarpe","given":"Steve","email":"","middleInitial":"P.","affiliations":[{"id":38755,"text":"Calpine","active":true,"usgs":false}],"preferred":false,"id":916426,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hartline, Craig","contributorId":213429,"corporation":false,"usgs":false,"family":"Hartline","given":"Craig","email":"","affiliations":[{"id":38755,"text":"Calpine","active":true,"usgs":false}],"preferred":false,"id":916427,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70244155,"text":"sir20235036 - 2023 - Simulation of future streamflow and irrigation demand based on climate and urban growth projections in the Cape Fear and Pee Dee River Basins, North Carolina and South Carolina, 2055–65","interactions":[],"lastModifiedDate":"2026-03-06T21:18:08.428516","indexId":"sir20235036","displayToPublicDate":"2023-06-21T07:56:13","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2023-5036","displayTitle":"Simulation of Future Streamflow and Irrigation Demand Based on Climate and Urban Growth Projections in the Cape Fear and Pee Dee River Basins, North Carolina and South Carolina, 2055–65","title":"Simulation of future streamflow and irrigation demand based on climate and urban growth projections in the Cape Fear and Pee Dee River Basins, North Carolina and South Carolina, 2055–65","docAbstract":"

Water resources in the coastal region of North Carolina and South Carolina (Coastal Carolinas) are currently under stress from competing ecological and societal needs. Projected changes in climate and population are expected to place even more stress on water resources in the region. The Coastal Carolinas Focus Area Study was initiated by the U.S. Geological Survey Water Availability and Use Science Program’s National Water Census to investigate these stressors and their effects on water resources for the Coastal Carolinas. As part of that study, the Soil and Water Assessment Tool (SWAT) model was used to investigate future streamflow and irrigation demand under six scenarios for the Cape Fear and Pee Dee River Basins, which flow through the Coastal Carolinas and into the Atlantic Ocean.

For each river basin, historical (2000 through 2014) Soil and Water Assessment Tool models were minimally calibrated, and future (2055 through 2065) scenario models were developed based on three alternative global climate models, two alternative urban growth projections, and water-use projections that correspond to each global climate model and urban growth projection pair. The river basins were delineated into 2,928 and 5,678 subbasins for the Cape Fear and Pee Dee, respectively, each approximately 2.6 square miles (mi2) in size. The best available water-use and wastewater discharge data were used for historical model calibration. The models simulated monthly mean streamflow with median Nash-Sutcliffe efficiency values of 0.53 (n = 36) and 0.61 (n = 33) in the Cape Fear and Pee Dee River Basins, respectively. Average percent bias was −4.8 percent for the Cape Fear River Basin and −1.2 percent for the Pee Dee River Basin. Catchments for streamgages chosen for model calibration that were small (less than 100 mi2) to medium (100–1,000 mi2) in area tended to perform better than larger catchments (greater than 1,000 mi2).

Historical models were used to develop future model scenarios by replacing historical weather, land-use, and water-use input datasets with projected datasets. One small, gaged catchment was selected to illustrate how the models can be used to evaluate the relative differences in simulated streamflow resulting from alternative global climate models and urban growth projections. For the selected catchment, future climate projections had a much greater influence on simulated streamflow than urban growth projections. Simulated cumulative monthly mean streamflow results for this catchment differed by 26 percent under alternative global climate models and differed by 2.4 percent under alternative urban growth projections.

Irrigation demand was modeled for subbasins with cropland. Simulated differences in irrigation demand were more pronounced and widespread across the model domain under the alternative future climate scenarios compared to alternative urban growth scenarios.

The calibrated and future scenario models have the capability to run on a daily time step and simulate streamflow and irrigation demand for thousands of small subbasins in the Cape Fear and Pee Dee River Basins. The models and underlying datasets enable future analyses for large and small areas within the basins.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235036","issn":"2328-0328","programNote":"Water Availability and Use Science Program","usgsCitation":"Gurley, L.N., García, A.M., Pfeifle, C.A., and Sanchez, G.M., 2023, Simulation of future streamflow and irrigation demand based on climate and urban growth projections in the Cape Fear and Pee Dee River Basins, North Carolina and South Carolina, 2055–65: U.S. Geological Survey Scientific Investigations Report 2023–5036, 23 p., https://doi.org/10.3133/sir20235036.","productDescription":"Report: viii, 23 p.; 2 Data Releases","numberOfPages":"36","onlineOnly":"Y","ipdsId":"IP-118241","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":417754,"rank":7,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P951VE5P","text":"USGS Data Release—Soil and Water Assessment Tool (SWAT) models for the Pee Dee River Basin used to simulate future streamflow and irrigation demand based on climate and urban growth projections"},{"id":417749,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2023/5036/sir20235036.pdf","size":"12.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2023-5036"},{"id":500906,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114934.htm","linkFileType":{"id":5,"text":"html"}},{"id":417753,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P98PVDBW","text":"USGS Data Release—Soil and Water Assessment Tool (SWAT) models for the Cape Fear River Basin used to simulate future streamflow and irrigation demand based on climate and urban growth projections"},{"id":417752,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2023/5036/images/"},{"id":417751,"rank":4,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20235036/full","linkFileType":{"id":5,"text":"html"},"description":"SIR 2023-5036 HTML"},{"id":417750,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2023/5036/sir20235036.XML","linkFileType":{"id":8,"text":"xml"},"description":"SIR 2023-5036 XML"},{"id":417748,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2023/5036/coverthb.jpg"}],"country":"United States","state":"North Carolina, South Carolina","otherGeospatial":"Cape Fear and Pee Dee River Basins","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -79.57121892850378,\n 32.91032390352079\n ],\n [\n -79.1296411830063,\n 33.177656538712625\n ],\n [\n -78.78619182539771,\n 33.72348311575605\n ],\n [\n -77.91939106571822,\n 33.920494939888584\n ],\n [\n -77.52687751416516,\n 34.40766001221573\n ],\n [\n -76.77455987368852,\n 35.02604160967191\n ],\n [\n -78.54904822133423,\n 36.169665661169745\n ],\n [\n -79.23594693655193,\n 36.51875607367013\n ],\n [\n -80.06186086794473,\n 36.51218395574713\n ],\n [\n -81.09220894077154,\n 36.66976065554749\n ],\n [\n -81.87723604387764,\n 35.792485806453826\n ],\n [\n -80.6996953892185,\n 34.985853498019594\n ],\n [\n -80.79782377710687,\n 34.42115219807647\n ],\n [\n -80.72422748619073,\n 33.5123831107352\n ],\n [\n -79.57121892850378,\n 32.91032390352079\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"

For more information about this publication, contact
Program Coordinator
U.S. Geological Survey
Water Availability and Use Science Program
National Water Quality Program
Email: wausp-info@usgs.gov

For additional information, visit
https://www.usgs.gov/programs/national-water-quality-program

Contact Pubs Warehouse
","tableOfContents":"","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"publishedDate":"2023-06-21","noUsgsAuthors":false,"publicationDate":"2023-06-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Gurley, Laura N. 0000-0002-2881-1038","orcid":"https://orcid.org/0000-0002-2881-1038","contributorId":93834,"corporation":false,"usgs":true,"family":"Gurley","given":"Laura N.","affiliations":[{"id":476,"text":"North Carolina Water Science Center","active":true,"usgs":true}],"preferred":true,"id":874651,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Garcia, Ana Maria 0000-0002-5388-1281 agarcia@usgs.gov","orcid":"https://orcid.org/0000-0002-5388-1281","contributorId":2035,"corporation":false,"usgs":true,"family":"Garcia","given":"Ana","email":"agarcia@usgs.gov","middleInitial":"Maria","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":874652,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pfeifle, Cassandra A. 0000-0001-5002-1625 cmendoza@usgs.gov","orcid":"https://orcid.org/0000-0001-5002-1625","contributorId":198960,"corporation":false,"usgs":true,"family":"Pfeifle","given":"Cassandra","email":"cmendoza@usgs.gov","middleInitial":"A.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":874653,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sanchez, Georgina M. 0000-0002-2365-6200","orcid":"https://orcid.org/0000-0002-2365-6200","contributorId":303829,"corporation":false,"usgs":false,"family":"Sanchez","given":"Georgina","email":"","middleInitial":"M.","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":true,"id":874654,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70245174,"text":"ofr20231049 - 2023 - Age-0 sablefish size and growth indices from seabird diets at Middleton Island, Gulf of Alaska","interactions":[],"lastModifiedDate":"2023-09-18T19:48:30.761903","indexId":"ofr20231049","displayToPublicDate":"2023-06-21T07:48:16","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2023-1049","displayTitle":"Age-0 Sablefish Size and Growth Indices from Seabird Diets at Middleton Island, Gulf of Alaska","title":"Age-0 sablefish size and growth indices from seabird diets at Middleton Island, Gulf of Alaska","docAbstract":"

Sablefish (Anoplopoma fimbria) is a commercially valuable groundfish species in Alaska, with the population assessed annually by the National Oceanic and Atmospheric Administration Alaska Fisheries Science Center. Sablefish recruit into the commercially fished population at 2 years old and are poorly sampled by most surveys before that age. However, information on the abundance, distribution, and size of pre-recruitment age fish is valuable as an ecosystem indicator for older fish. Size and an index of growth rate of age-0 sablefish were quantified using samples from seabird diets at Middleton Island, Alaska, an island in the northern Gulf of Alaska. Age-0 sablefish information may serve as an indicator for potential recruitment into older age populations. This report (1) provides information on the data collection for age-0 sablefish from seabird diets at Middleton Island, Alaska from 1978 to 2022, (2) describes a method for quantifying age-0 sablefish size and growth rate, and (3) describes the size and growth rate of sablefish sampled over time. An annual release of age-0 sablefish size and growth data by U.S. Geological Survey based on continued collections on Middleton Island, Alaska, may be used to assess ecosystem status and as a recruitment indicator for sablefish.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20231049","collaboration":"Prepared in cooperation with National Oceanic and Atmospheric Administration Alaska Fisheries Science Center","usgsCitation":"Arimitsu, M.L., and Hatch, S.A., 2023, Age-0 sablefish size and growth indices from seabird diets at Middleton Island, Gulf of Alaska: U.S. Geological Survey Open-File Report 2023–1049, 4 p., https://doi.org/10.3133/ofr20231049.","productDescription":"Report: v, 4 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-151412","costCenters":[{"id":65299,"text":"Alaska Science Center Ecosystems","active":true,"usgs":true}],"links":[{"id":418265,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P94KVH9X","text":"USGS data release","description":"USGS data release","linkHelpText":"Age-0 Sablefish size and growth indices from seabird diets at Middleton Island, Alaska"},{"id":418263,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2023/1049/ofr20231049.pdf","text":"Report","size":"2.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2023-1049"},{"id":418262,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2023/1049/coverthb.jpg"},{"id":418267,"rank":6,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2023/1049/ofr20231049.XML"},{"id":418266,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2023/1049/images"},{"id":418264,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.er.usgs.gov/publication/ofr20231049/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2023-1049"}],"country":"United States","state":"Alaska","otherGeospatial":"Middleton Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -147.10005001165774,\n 59.77785521975687\n ],\n [\n -147.10005001165774,\n 58.9779941146154\n ],\n [\n -145.39789946473627,\n 58.9779941146154\n ],\n [\n -145.39789946473627,\n 59.77785521975687\n ],\n [\n -147.10005001165774,\n 59.77785521975687\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"

Director, Alaska Science Center
U.S. Geological Survey
4210 University Drive
Anchorage, Alaska 99508

","tableOfContents":"","publishedDate":"2023-06-21","noUsgsAuthors":false,"publicationDate":"2023-06-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Arimitsu, Mayumi L. 0000-0001-6982-2238 marimitsu@usgs.gov","orcid":"https://orcid.org/0000-0001-6982-2238","contributorId":140501,"corporation":false,"usgs":true,"family":"Arimitsu","given":"Mayumi","email":"marimitsu@usgs.gov","middleInitial":"L.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":875761,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hatch, Scott A. 0000-0002-0064-8187 shatch@usgs.gov","orcid":"https://orcid.org/0000-0002-0064-8187","contributorId":2625,"corporation":false,"usgs":true,"family":"Hatch","given":"Scott","email":"shatch@usgs.gov","middleInitial":"A.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":875762,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70245377,"text":"70245377 - 2023 - Dispersive currents explain patterns of population connectivity in an ecologically and economically important fish","interactions":[],"lastModifiedDate":"2023-07-26T14:44:15.125668","indexId":"70245377","displayToPublicDate":"2023-06-21T07:25:23","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1601,"text":"Evolutionary Applications","active":true,"publicationSubtype":{"id":10}},"title":"Dispersive currents explain patterns of population connectivity in an ecologically and economically important fish","docAbstract":"

How to identify the drivers of population connectivity remains a fundamental question in ecology and evolution. Answering this question can be challenging in aquatic environments where dynamic lake and ocean currents coupled with high levels of dispersal and gene flow can decrease the utility of modern population genetic tools. To address this challenge, we used RAD-Seq to genotype 959 yellow perch (Perca flavescens), a species with an ~40-day pelagic larval duration (PLD), collected from 20 sites circumscribing Lake Michigan. We also developed a novel, integrative approach that couples detailed biophysical models with eco-genetic agent-based models to generate “predictive” values of genetic differentiation. By comparing predictive and empirical values of genetic differentiation, we estimated the relative contributions for known drivers of population connectivity (e.g., currents, behavior, PLD). For the main basin populations (i.e., the largest contiguous portion of the lake), we found that high gene flow led to low overall levels of genetic differentiation among populations (FST = 0.003). By far the best predictors of genetic differentiation were connectivity matrices that were derived from periods of time when there were strong and highly dispersive currents. Thus, these highly dispersive currents are driving the patterns of population connectivity in the main basin. We also found that populations from the northern and southern main basin are slightly divergent from one another, while those from Green Bay and the main basin are highly divergent (FST = 0.11). By integrating biophysical and eco-genetic models with genome-wide data, we illustrate that the drivers of population connectivity can be identified in high gene flow systems.

","language":"English","publisher":"Wiley","doi":"10.1111/eva.13567","usgsCitation":"Schraidt, C., Ackiss, A.S., Larson, W.A., Rowe, M.D., Hook, T.O., and Christie, M.R., 2023, Dispersive currents explain patterns of population connectivity in an ecologically and economically important fish: Evolutionary Applications, v. 16, no. 7, p. 1284-1301, https://doi.org/10.1111/eva.13567.","productDescription":"18 p.","startPage":"1284","endPage":"1301","ipdsId":"IP-147062","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":442996,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/eva.13567","text":"Publisher Index Page"},{"id":418356,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Lake Michigan","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -88.99318380021634,\n 41.1537248915464\n ],\n [\n -84.5566107617885,\n 41.1537248915464\n ],\n [\n -84.5566107617885,\n 46.29159809742305\n ],\n [\n -88.99318380021634,\n 46.29159809742305\n ],\n [\n -88.99318380021634,\n 41.1537248915464\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"16","issue":"7","noUsgsAuthors":false,"publicationDate":"2023-06-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Schraidt, Claire","contributorId":311102,"corporation":false,"usgs":false,"family":"Schraidt","given":"Claire","email":"","affiliations":[{"id":13186,"text":"Purdue University","active":true,"usgs":false}],"preferred":false,"id":875915,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ackiss, Amanda Susanne 0000-0002-8726-7423","orcid":"https://orcid.org/0000-0002-8726-7423","contributorId":272165,"corporation":false,"usgs":true,"family":"Ackiss","given":"Amanda","email":"","middleInitial":"Susanne","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":875916,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Larson, Wesley Alan","contributorId":311103,"corporation":false,"usgs":false,"family":"Larson","given":"Wesley","email":"","middleInitial":"Alan","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":875917,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rowe, Mark D","contributorId":293584,"corporation":false,"usgs":false,"family":"Rowe","given":"Mark","email":"","middleInitial":"D","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":875918,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hook, Tomas O","contributorId":292058,"corporation":false,"usgs":false,"family":"Hook","given":"Tomas","email":"","middleInitial":"O","affiliations":[{"id":13186,"text":"Purdue University","active":true,"usgs":false}],"preferred":false,"id":875919,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Christie, Mark R.","contributorId":191035,"corporation":false,"usgs":false,"family":"Christie","given":"Mark","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":875920,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70246267,"text":"70246267 - 2023 - Linear and landscape disturbances alter Mojave desert tortoise movement behavior","interactions":[],"lastModifiedDate":"2023-06-29T12:18:20.963691","indexId":"70246267","displayToPublicDate":"2023-06-21T07:12:07","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3910,"text":"Frontiers in Ecology and Evolution","onlineIssn":"2296-701X","active":true,"publicationSubtype":{"id":10}},"title":"Linear and landscape disturbances alter Mojave desert tortoise movement behavior","docAbstract":"

Introduction: Animal movements are influenced by landscape features; disturbances to the landscape can alter movements, dispersal, and ultimately connectivity among populations. Faster or longer movements adjacent to a localized disturbance or within disturbed areas could indicate reduced habitat quality whereas slower or shorter movements and reduced movements may indicate greater availability of resources. The Mojave desert tortoise (Gopherus agassizii) is a threatened species that is challenged by anthropogenic disturbances.

Methods: We studied tortoise movements using Global Positioning System (GPS) loggers at multiple sites in the Mojave Desert of Nevada and California. Tortoises at our sites encountered localized, linear human infrastructure, including paved roads, dirt roads, and fences, as well as landscape-scale disturbances [wildfire, off highway vehicle use (OHV), livestock grazing area]. We fit two-state (moving and encamped) Hidden Markov models to GPS logger data to infer how tortoise movement behavior relates to anthropogenic and natural features.

Results: We found that temporal covariates, individual-level random effects (intercepts), and sex best explained state transition probability in all sites. We compared relationships between tortoise movement and linear disturbances, which varied depending on site and context. Tortoises made longer movements within the OHV recreation area, near most dirt roads, and near a low-traffic paved road, indicating that tortoises avoid these habitat disturbances. Conversely, tortoises made shorter movements in areas of higher slope and near highways, suggesting that these features may restrict movement or provide resources that result in prolonged use (e.g., forage or drinking locations). Tortoises that encountered fences around utility-scale solar installations were more active and made longer movements near fences, indicative of pacing behavior.

Discussion: These results provide insight into how different disturbances alter tortoise movement behavior and modify tortoise habitat use, providing information that can be used to manage tortoise habitat.

","language":"English","publisher":"Frontiers","doi":"10.3389/fevo.2023.971337","usgsCitation":"Hromada, S.J., Esque, T., Vandergast, A.G., Drake, K.K., Chen, F., Gottsacker, B.O., Swart, J.A., and Nussear, K., 2023, Linear and landscape disturbances alter Mojave desert tortoise movement behavior: Frontiers in Ecology and Evolution, v. 11, 971337, 14 p., https://doi.org/10.3389/fevo.2023.971337.","productDescription":"971337, 14 p.","ipdsId":"IP-144743","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":442999,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fevo.2023.971337","text":"Publisher Index Page"},{"id":418620,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Nevada","otherGeospatial":"Mojave Desert","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -116.85708110970195,\n 36.70940504207991\n ],\n [\n -116.85708110970195,\n 34.67613588087687\n ],\n [\n -114.55094165903384,\n 34.67613588087687\n ],\n [\n -114.55094165903384,\n 36.70940504207991\n ],\n [\n -116.85708110970195,\n 36.70940504207991\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"11","noUsgsAuthors":false,"publicationDate":"2023-06-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Hromada, Steven J.","contributorId":245147,"corporation":false,"usgs":false,"family":"Hromada","given":"Steven","email":"","middleInitial":"J.","affiliations":[{"id":16686,"text":"University of Nevada, Reno","active":true,"usgs":false}],"preferred":false,"id":876504,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Esque, Todd 0000-0002-4166-6234 tesque@usgs.gov","orcid":"https://orcid.org/0000-0002-4166-6234","contributorId":195896,"corporation":false,"usgs":true,"family":"Esque","given":"Todd","email":"tesque@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":876505,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Vandergast, Amy G. 0000-0002-7835-6571","orcid":"https://orcid.org/0000-0002-7835-6571","contributorId":57201,"corporation":false,"usgs":true,"family":"Vandergast","given":"Amy","middleInitial":"G.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":876506,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Drake, K. Kristina 0000-0003-0711-7634 kdrake@usgs.gov","orcid":"https://orcid.org/0000-0003-0711-7634","contributorId":3799,"corporation":false,"usgs":true,"family":"Drake","given":"K.","email":"kdrake@usgs.gov","middleInitial":"Kristina","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":876507,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Chen, Felicia 0000-0002-7408-5946","orcid":"https://orcid.org/0000-0002-7408-5946","contributorId":210469,"corporation":false,"usgs":true,"family":"Chen","given":"Felicia","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":876508,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Gottsacker, Benjamin O 0000-0002-9481-6267","orcid":"https://orcid.org/0000-0002-9481-6267","contributorId":315424,"corporation":false,"usgs":true,"family":"Gottsacker","given":"Benjamin","email":"","middleInitial":"O","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":876509,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Swart, Jordan Andrew 0000-0002-3348-4721","orcid":"https://orcid.org/0000-0002-3348-4721","contributorId":315425,"corporation":false,"usgs":true,"family":"Swart","given":"Jordan","email":"","middleInitial":"Andrew","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":876510,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Nussear, Ken E","contributorId":221816,"corporation":false,"usgs":false,"family":"Nussear","given":"Ken E","affiliations":[{"id":16686,"text":"University of Nevada, Reno","active":true,"usgs":false}],"preferred":false,"id":876511,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70246266,"text":"70246266 - 2023 - Putting down roots: Afforestation and bank cohesion of Icelandic Rivers","interactions":[],"lastModifiedDate":"2023-11-07T15:07:54.763698","indexId":"70246266","displayToPublicDate":"2023-06-21T07:04:07","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3301,"text":"River Research and Applications","active":true,"publicationSubtype":{"id":10}},"title":"Putting down roots: Afforestation and bank cohesion of Icelandic Rivers","docAbstract":"

Riparian vegetation is widely recognized as a critical component of functioning fluvial systems. Human pressures on woody vegetation including riparian areas have had lasting effects, especially at high latitude. In Iceland, prior to human settlement, native downy birch woodlands covered approximately 15%–40% of the land area compared to 1%–2% today. Afforestation efforts include planting seedlings, protecting native forest remnants, and acquiring land areas as national forests. The planted and protected nature of vegetation along rivers within forests provides a unique opportunity to evaluate the various taxa within riparian zones and the channel stabilizing characteristics of the vegetation used in afforestation. We investigated bank properties, sediment textures, and root characteristics within riparian zones along four rivers in forests in Iceland. Bank sediment textures are dominantly sandy loam overlying coarser textures. Undercut banks are common because of erosion of the less cohesive subsurface layer. Quantitative root data indicate that the woody taxa have greater root densities, rooting depths, and more complex root structures than forbs or graminoids. The native downy birch has the highest root densities, with <1 mm roots most abundant. Modeling of added bank cohesion indicates that willow provides up to six times and birch up to four times more added cohesion to the coarse sediment textures comprising stream banks compared to no vegetation. We conclude that planting and protecting the native birch and willow helps to reduce bank erosion, especially where long-term grazing exclusion can be maintained.

","language":"English","publisher":"Wiley","doi":"10.1002/rra.4172","usgsCitation":"Rathburn, S.L., Eysteinsson, P., Saemundsson, T., Kemper, J.T., Wieting, C.D., and Friedman, J.M., 2023, Putting down roots: Afforestation and bank cohesion of Icelandic Rivers: River Research and Applications, v. 39, no. 9, p. 1669-1681, https://doi.org/10.1002/rra.4172.","productDescription":"13 p.","startPage":"1669","endPage":"1681","ipdsId":"IP-150313","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":443001,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/rra.4172","text":"Publisher Index Page"},{"id":418619,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Iceland","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -26.16947229895635,\n 67.00386623509442\n ],\n [\n -26.16947229895635,\n 62.80275798176817\n ],\n [\n -10.970915157411696,\n 62.80275798176817\n ],\n [\n -10.970915157411696,\n 67.00386623509442\n ],\n [\n -26.16947229895635,\n 67.00386623509442\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"39","issue":"9","noUsgsAuthors":false,"publicationDate":"2023-06-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Rathburn, Sara L.","contributorId":140606,"corporation":false,"usgs":false,"family":"Rathburn","given":"Sara","email":"","middleInitial":"L.","affiliations":[{"id":13539,"text":"Department of Geosciences, Colorado State University, Fort Collins, Colorado","active":true,"usgs":false}],"preferred":false,"id":876498,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Eysteinsson, Prostur","contributorId":315421,"corporation":false,"usgs":false,"family":"Eysteinsson","given":"Prostur","email":"","affiliations":[{"id":68314,"text":"Icelandic Forest Service","active":true,"usgs":false}],"preferred":false,"id":876499,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Saemundsson, Thorsteinn","contributorId":315422,"corporation":false,"usgs":false,"family":"Saemundsson","given":"Thorsteinn","email":"","affiliations":[{"id":68315,"text":"University of Iceland, Reykjavik","active":true,"usgs":false}],"preferred":false,"id":876500,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kemper, John T.","contributorId":270040,"corporation":false,"usgs":false,"family":"Kemper","given":"John","email":"","middleInitial":"T.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":876501,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wieting, Celeste D.","contributorId":315423,"corporation":false,"usgs":false,"family":"Wieting","given":"Celeste","email":"","middleInitial":"D.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":876502,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Friedman, Jonathan M. 0000-0002-1329-0663 friedmanj@usgs.gov","orcid":"https://orcid.org/0000-0002-1329-0663","contributorId":2473,"corporation":false,"usgs":true,"family":"Friedman","given":"Jonathan","email":"friedmanj@usgs.gov","middleInitial":"M.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":876503,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70256517,"text":"70256517 - 2023 - Wetland management practices and secretive marsh bird habitat in the Mississippi Flyway: A review","interactions":[],"lastModifiedDate":"2024-08-21T11:08:28.450043","indexId":"70256517","displayToPublicDate":"2023-06-21T06:06:05","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":16872,"text":"The Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Wetland management practices and secretive marsh bird habitat in the Mississippi Flyway: A review","docAbstract":"

Management regimes on publicly owned freshwater wetlands in the Mississippi Flyway of North America (i.e., Flyway) have historically emphasized waterfowl, but there is limited information on how waterfowl-focused wetland management affects other wetland-dependent wildlife. Secretive marsh birds (SMBs) depend on wetlands with emergent vegetation throughout their migratory life cycle and often encounter vegetation and water conditions resulting from waterfowl-focused management regimes. Thus, there is a need for better understanding of how SMBs are affected by wetland management and the extent to which waterfowl-focused management regimes provide habitat for SMBs. In this review, we identify the vegetation and water conditions resulting from typical management objectives on freshwater emergent wetlands in the Flyway, review and qualitatively synthesize results from studies that directly evaluate how wetland management practices affect SMBs or their habitat, and assess how the vegetation and water conditions being produced for target species (mainly waterfowl) align with SMB habitat requirements. We searched online databases and used Google Scholar to locate peer-reviewed literature, technical reports, and graduate theses that pertained to responses of SMBs or their habitat to water-level manipulation, herbicide application, prescribed fire, disking, mowing, and planting crops. There are several management strategies that complement SMBs and waterfowl, such as reducing cover of woody species and providing flooded emergent vegetation. We also highlight management strategies that may not currently align with SMB life-cycle needs and suggest adjustments that might promote habitat for SMBs while still achieving waterfowl population objectives. For example, adjusting the dates and duration of spring water-level drawdowns on a portion of wetlands within a larger complex can provide for spring migrating waterfowl and ensure habitat for migrating and nesting SMBs. Ideally, future studies would address how modifications to management practices affect SMBs and monitor potential effects on waterfowl, resulting in a more holistic approach to wetland management.

","language":"English","publisher":"Wiley","doi":"10.1002/jwmg.22451","usgsCitation":"Malone, K.M., Webb, E.B., Mengel, D., Kearns, L., McKellar, A.E., Matteson, S.W., and Williams, B.R., 2023, Wetland management practices and secretive marsh bird habitat in the Mississippi Flyway: A review: The Journal of Wildlife Management, v. 87, no. 7, e22451, https://doi.org/10.1002/jwmg.22451.","productDescription":"e22451","ipdsId":"IP-145590","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":499237,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/jwmg.22451","text":"Publisher Index Page"},{"id":432973,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"87","issue":"7","noUsgsAuthors":false,"publicationDate":"2023-06-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Malone, Kristen M.","contributorId":340994,"corporation":false,"usgs":false,"family":"Malone","given":"Kristen","email":"","middleInitial":"M.","affiliations":[{"id":6754,"text":"University of Missouri","active":true,"usgs":false}],"preferred":false,"id":907776,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Webb, Elisabeth B. 0000-0003-3851-6056 ewebb@usgs.gov","orcid":"https://orcid.org/0000-0003-3851-6056","contributorId":3981,"corporation":false,"usgs":true,"family":"Webb","given":"Elisabeth","email":"ewebb@usgs.gov","middleInitial":"B.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":907777,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mengel, Doreen C.","contributorId":340995,"corporation":false,"usgs":false,"family":"Mengel","given":"Doreen C.","affiliations":[{"id":16971,"text":"Missouri Department of Conservation","active":true,"usgs":false}],"preferred":false,"id":907778,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kearns, Laura","contributorId":340996,"corporation":false,"usgs":false,"family":"Kearns","given":"Laura","email":"","affiliations":[{"id":81690,"text":"Ohio Department of Natural Resources – Division of Wildlife","active":true,"usgs":false}],"preferred":false,"id":907779,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McKellar, Ann E.","contributorId":340997,"corporation":false,"usgs":false,"family":"McKellar","given":"Ann","email":"","middleInitial":"E.","affiliations":[{"id":36681,"text":"Environment and Climate Change Canada","active":true,"usgs":false}],"preferred":false,"id":907780,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Matteson, Sumner W.","contributorId":340998,"corporation":false,"usgs":false,"family":"Matteson","given":"Sumner","email":"","middleInitial":"W.","affiliations":[{"id":6913,"text":"Wisconsin Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":907781,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Williams, Benjamin R.","contributorId":340999,"corporation":false,"usgs":false,"family":"Williams","given":"Benjamin","email":"","middleInitial":"R.","affiliations":[{"id":33955,"text":"Illinois Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":907782,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70245601,"text":"70245601 - 2023 - A body composition model with multiple storage compartments for polar bears (Ursus maritimus)","interactions":[],"lastModifiedDate":"2023-06-26T13:27:30.871321","indexId":"70245601","displayToPublicDate":"2023-06-20T08:23:18","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"displayTitle":"A body composition model with multiple storage compartments for polar bears (Ursus maritimus)","title":"A body composition model with multiple storage compartments for polar bears (Ursus maritimus)","docAbstract":"

Climate warming is rapidly altering Arctic ecosystems. Polar bears (Ursus maritimus) need sea ice as a platform from which to hunt seals, but increased sea-ice loss is lengthening periods when bears are without access to primary hunting habitat. During periods of food scarcity, survival depends on the energy that a bear has stored in body reserves, termed storage energy, making this a key metric in predictive models assessing climate change impacts on polar bears. Here, we developed a body composition model for polar bears that estimates storage energy while accounting for changes in storage tissue composition. We used data of dissected polar bears (n = 31) to link routinely collected field measures of total body mass and straight-line body length to the body composition of individual bears, described in terms of structural mass and two storage compartments, adipose and muscle. We then estimated the masses of metabolizable proteins and lipids within these storage compartments, giving total storage energy. We tested this multi-storage model by using it to predict changes in the lipid stores from an independent dataset of wild polar bears (n = 36) that were recaptured 8–200 days later. Using length and mass measurements, our model successfully predicted direct measurements of lipid changes via isotopic dilutions (root mean squared error of 14.5 kg). Separating storage into two compartments, and allowing the molecular composition of storage to vary, provides new avenues for quantifying energy stores of individuals across their life cycle. The multi-storage body composition model thus provides a basis for further exploring energetic costs of physiological processes that contribute to individual survival and reproductive success. Given bioenergetic models are increasingly used as a tool to predict individual fitness and population dynamics, our approach for estimating individual energy stores could be applicable to a wide range of species.

","language":"English","publisher":"Oxford Academic","doi":"10.1093/conphys/coad043","usgsCitation":"Penk, S.R., Sadana, P., Archer, L.C., Pagano, A.M., Cattet, M.R., Lunn, N.J., Thiemann, G.W., and Molnar, P.K., 2023, A body composition model with multiple storage compartments for polar bears (Ursus maritimus), v. 11, no. 1, coad043, 20 p., https://doi.org/10.1093/conphys/coad043.","productDescription":"coad043, 20 p.","ipdsId":"IP-142122","costCenters":[{"id":65299,"text":"Alaska Science Center Ecosystems","active":true,"usgs":true}],"links":[{"id":443007,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/conphys/coad043","text":"Publisher Index Page"},{"id":418459,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"11","issue":"1","noUsgsAuthors":false,"publicationDate":"2023-06-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Penk, Stephanie R. 0000-0002-8027-4372","orcid":"https://orcid.org/0000-0002-8027-4372","contributorId":312472,"corporation":false,"usgs":false,"family":"Penk","given":"Stephanie","email":"","middleInitial":"R.","affiliations":[{"id":67687,"text":"University of Toronto Scarborough","active":true,"usgs":false}],"preferred":false,"id":876207,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sadana, Pranav","contributorId":312473,"corporation":false,"usgs":false,"family":"Sadana","given":"Pranav","email":"","affiliations":[{"id":16930,"text":"University of Winnipeg","active":true,"usgs":false}],"preferred":false,"id":876208,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Archer, Louise C. 0000-0002-1983-3825","orcid":"https://orcid.org/0000-0002-1983-3825","contributorId":312474,"corporation":false,"usgs":false,"family":"Archer","given":"Louise","email":"","middleInitial":"C.","affiliations":[{"id":67687,"text":"University of Toronto Scarborough","active":true,"usgs":false}],"preferred":false,"id":876209,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pagano, Anthony M. 0000-0003-2176-0909 apagano@usgs.gov","orcid":"https://orcid.org/0000-0003-2176-0909","contributorId":3884,"corporation":false,"usgs":true,"family":"Pagano","given":"Anthony","email":"apagano@usgs.gov","middleInitial":"M.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":876210,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cattet, Marc R. L. 0000-0002-2318-1452","orcid":"https://orcid.org/0000-0002-2318-1452","contributorId":312475,"corporation":false,"usgs":false,"family":"Cattet","given":"Marc","email":"","middleInitial":"R. L.","affiliations":[{"id":13248,"text":"University of Saskatchewan","active":true,"usgs":false}],"preferred":false,"id":876211,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lunn, Nicholas J. 0000-0003-0189-5494","orcid":"https://orcid.org/0000-0003-0189-5494","contributorId":312476,"corporation":false,"usgs":false,"family":"Lunn","given":"Nicholas","email":"","middleInitial":"J.","affiliations":[{"id":36681,"text":"Environment and Climate Change Canada","active":true,"usgs":false}],"preferred":false,"id":876212,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Thiemann, Gregory W.","contributorId":83023,"corporation":false,"usgs":false,"family":"Thiemann","given":"Gregory","email":"","middleInitial":"W.","affiliations":[{"id":27291,"text":"York University, Toronto, ON","active":true,"usgs":false}],"preferred":false,"id":876213,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Molnar, Peter K. 0000-0001-7260-2674","orcid":"https://orcid.org/0000-0001-7260-2674","contributorId":312477,"corporation":false,"usgs":false,"family":"Molnar","given":"Peter","email":"","middleInitial":"K.","affiliations":[{"id":67687,"text":"University of Toronto Scarborough","active":true,"usgs":false}],"preferred":false,"id":876214,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70245787,"text":"70245787 - 2023 - Ensemble estimation of historical evapotranspiration for the conterminous U.S.","interactions":[],"lastModifiedDate":"2023-06-27T11:48:52.454255","indexId":"70245787","displayToPublicDate":"2023-06-20T06:45:54","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Ensemble estimation of historical evapotranspiration for the conterminous U.S.","docAbstract":"

Evapotranspiration (ET) is the largest component of the water budget, accounting for the majority of the water available from precipitation. ET is challenging to quantify because of the uncertainties associated with the many ET equations currently in use, and because observations of ET are uncertain and sparse. In this study, we combine information provided by available ET data and equations to produce a new monthly data set for ET for the conterminous U.S. (CONUS). These maps are produced from 1895 to 2018 at an 800 m spatial scale, marking a finer resolution than currently available products over this time period. In our approach, the relative performance of a suite of ET equations is assessed using water balance, flux tower, and remotely sensed ET estimates. At the observation locations, we use error distributions to quantify relative weights for the equations and use these in a modified Bayesian model averaging weighted ensemble approach. The relative weights are spatially generalized using a random forest regression, which is applied to wall-to-wall explanatory variable maps to generate CONUS-wide relative weight maps and ensemble estimates. We assess the performance of the ensemble using a reserved subset of the observations and compare this performance against other national-scale map products for historical to modern ET. The ensemble ET maps are shown to provide an improved accuracy over the alternative comparison products. These ET maps could be useful for a variety of hydrologic modeling and assessment applications that benefit from a long record, such as the study of periods of water scarcity through time.

","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2022WR034012","usgsCitation":"Reitz, M., Sanford, W.E., and Saxe, S., 2023, Ensemble estimation of historical evapotranspiration for the conterminous U.S.: Water Resources Research, v. 59, no. 6, e2022WR034012, 23 p., https://doi.org/10.1029/2022WR034012.","productDescription":"e2022WR034012, 23 p.","ipdsId":"IP-150947","costCenters":[{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true}],"links":[{"id":498673,"rank":1,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1029/2022wr034012","text":"External Repository"},{"id":435279,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9EZ3VAS","text":"USGS data release","linkHelpText":"Historical Evapotranspiration for the Conterminous U.S."},{"id":418497,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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- Eastern Branch","active":true,"usgs":true},{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true}],"preferred":true,"id":876330,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sanford, Ward E. 0000-0002-6624-0280 wsanford@usgs.gov","orcid":"https://orcid.org/0000-0002-6624-0280","contributorId":2268,"corporation":false,"usgs":true,"family":"Sanford","given":"Ward","email":"wsanford@usgs.gov","middleInitial":"E.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":876331,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Saxe, Samuel 0000-0003-1151-8908","orcid":"https://orcid.org/0000-0003-1151-8908","contributorId":218991,"corporation":false,"usgs":false,"family":"Saxe","given":"Samuel","affiliations":[{"id":6606,"text":"Colorado School of Mines","active":true,"usgs":false}],"preferred":false,"id":876332,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70245610,"text":"70245610 - 2023 - The influence of vegetated marshes on wave transformation in sheltered estuaries","interactions":[],"lastModifiedDate":"2023-06-26T11:38:14.031057","indexId":"70245610","displayToPublicDate":"2023-06-20T06:35:45","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1262,"text":"Coastal Engineering","active":true,"publicationSubtype":{"id":10}},"title":"The influence of vegetated marshes on wave transformation in sheltered estuaries","docAbstract":"

Assessing the influence of marshes on mitigating flooding along estuarine shorelines under the pressures of sea level rise requires understanding wave transformation across the marsh. A numerical model was applied to investigate how vegetated marshes influence wave transformation. XBeach non-hydrostatic (XB-NH) was calibrated and validated with high frequency pressure data from the marsh at China Camp State Park in San Pablo Bay, California (USA). The model was used to examine how marsh and hydrodynamic characteristics change the potential for marshes to mitigate wave driven flooding. Model results demonstrate that hydrodynamics, vegetation, and marsh width influence wave transformation most, while marsh morphology parameters such as elevation and slope had least effect. Results suggest that in the range of settings explored here (incident wave heights ranging from 0.5 to 3 m and water levels ranging from current mean higher high water to 3 m above current mean higher high water), in comparison to wave propagation over an unvegetated mudflat, marsh vegetation reduces runup by a median of 40 cm and wave height by a median of 35 cm. Results illustrate how marshes can be strategically utilized to provide flood reduction benefits.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.coastaleng.2023.104346","usgsCitation":"Taylor-Burns, R.M., Nederhoff, C.M., Lacy, J.R., and Barnard, P.L., 2023, The influence of vegetated marshes on wave transformation in sheltered estuaries: Coastal Engineering, v. 184, 104346, 17 p., https://doi.org/10.1016/j.coastaleng.2023.104346.","productDescription":"104346, 17 p.","ipdsId":"IP-137013","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":443009,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.coastaleng.2023.104346","text":"Publisher Index Page"},{"id":418451,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"184","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Taylor-Burns, Rae M. 0000-0003-4963-6643","orcid":"https://orcid.org/0000-0003-4963-6643","contributorId":312507,"corporation":false,"usgs":false,"family":"Taylor-Burns","given":"Rae","email":"","middleInitial":"M.","affiliations":[{"id":6949,"text":"University of California, Santa Cruz","active":true,"usgs":false}],"preferred":false,"id":876241,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nederhoff, Cornelis M. 0000-0003-0552-3428","orcid":"https://orcid.org/0000-0003-0552-3428","contributorId":265889,"corporation":false,"usgs":false,"family":"Nederhoff","given":"Cornelis","email":"","middleInitial":"M.","affiliations":[{"id":33886,"text":"Deltares USA","active":true,"usgs":false}],"preferred":true,"id":876242,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lacy, Jessica R. 0000-0002-2797-6172","orcid":"https://orcid.org/0000-0002-2797-6172","contributorId":201703,"corporation":false,"usgs":true,"family":"Lacy","given":"Jessica","email":"","middleInitial":"R.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":876243,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Barnard, Patrick L. 0000-0003-1414-6476 pbarnard@usgs.gov","orcid":"https://orcid.org/0000-0003-1414-6476","contributorId":140982,"corporation":false,"usgs":true,"family":"Barnard","given":"Patrick","email":"pbarnard@usgs.gov","middleInitial":"L.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":876244,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ]}