{"pageNumber":"219","pageRowStart":"5450","pageSize":"25","recordCount":184617,"records":[{"id":70250603,"text":"70250603 - 2023 - Using a coupled integral projection model to investigate interspecific competition during an invasion: An application to silver carp (Hypophthalmichthys molitrix) and gizzard shad (Dorosoma cepedianum)","interactions":[],"lastModifiedDate":"2023-12-19T12:50:26.049418","indexId":"70250603","displayToPublicDate":"2023-12-19T06:32:31","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3824,"text":"Letters in Biomathematics","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Using a coupled integral projection model to investigate interspecific competition during an invasion: An application to silver carp (<i>Hypophthalmichthys molitrix</i>) and gizzard shad (<i>Dorosoma cepedianum</i>)","title":"Using a coupled integral projection model to investigate interspecific competition during an invasion: An application to silver carp (Hypophthalmichthys molitrix) and gizzard shad (Dorosoma cepedianum)","docAbstract":"<p><span>As a generalization of stage-based matrix models, integral projection models&nbsp;(IPMs) have been used to describe the size-based dynamics of wildlife and fisheries populations. Although some matrix models have explicitly included species interactions, few IPMs have expanded beyond single species, which limits their ability to describe the competitive dynamics of co-occuring taxa. We present a coupled system of IPMs where intra- and inter-specific competition may reciprocally affect the life-histories of two species. We investigated the potential role that competition has on two overlapping fish species in the upper Mississippi River system: the native gizzard shad (</span><i>Dorosoma cepedianum</i><span>) and the invasive silver carp (</span><i>Hypophthalmichthys molitrix</i><span>). Numerical simulations of this system indicated that the coupled IPMs could exhibit asymptotic behaviors similar to traditional, non-linear competition models. Specifically, by altering the competition coefficients, we demonstrate this model's ability to detect competitive exclusion, species coexistence, and dual extinction outcomes.</span></p>","language":"English","publisher":"Intercollegiate Biomathematics Alliance","usgsCitation":"Peirce, J.P., Sandland, G., Schumann, D., Thompson, H.M., and Erickson, R.A., 2023, Using a coupled integral projection model to investigate interspecific competition during an invasion: An application to silver carp (Hypophthalmichthys molitrix) and gizzard shad (Dorosoma cepedianum): Letters in Biomathematics, v. 10, no. 1, p. 175-184.","productDescription":"10 p.","startPage":"175","endPage":"184","ipdsId":"IP-156781","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":423743,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":423740,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://lettersinbiomath.journals.publicknowledgeproject.org/index.php/lib/article/view/645"}],"volume":"10","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Peirce, James P 0000-0002-7147-3695","orcid":"https://orcid.org/0000-0002-7147-3695","contributorId":316559,"corporation":false,"usgs":false,"family":"Peirce","given":"James","email":"","middleInitial":"P","affiliations":[{"id":47908,"text":"University of Wisconsin - La Crosse","active":true,"usgs":false}],"preferred":false,"id":890531,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sandland, Gregory","contributorId":332579,"corporation":false,"usgs":false,"family":"Sandland","given":"Gregory","email":"","affiliations":[{"id":12793,"text":"University of Wisconsin-La Crosse","active":true,"usgs":false}],"preferred":false,"id":890532,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schumann, David","contributorId":199504,"corporation":false,"usgs":false,"family":"Schumann","given":"David","affiliations":[{"id":5089,"text":"South Dakota State University","active":true,"usgs":false}],"preferred":false,"id":890533,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Thompson, Hannah Mann 0000-0001-8316-3232","orcid":"https://orcid.org/0000-0001-8316-3232","contributorId":316560,"corporation":false,"usgs":true,"family":"Thompson","given":"Hannah","email":"","middleInitial":"Mann","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":890534,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Erickson, Richard A. 0000-0003-4649-482X rerickson@usgs.gov","orcid":"https://orcid.org/0000-0003-4649-482X","contributorId":5455,"corporation":false,"usgs":true,"family":"Erickson","given":"Richard","email":"rerickson@usgs.gov","middleInitial":"A.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":890535,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70259695,"text":"70259695 - 2023 - Two-dimensional inverse energy cascade in a laboratory surf zone for varying wave directional spread","interactions":[],"lastModifiedDate":"2024-10-21T11:29:40.817354","indexId":"70259695","displayToPublicDate":"2023-12-19T06:26:39","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3070,"text":"Physics of Fluids","active":true,"publicationSubtype":{"id":10}},"title":"Two-dimensional inverse energy cascade in a laboratory surf zone for varying wave directional spread","docAbstract":"<p><span>Surfzone eddies enhance the dispersion and transport of contaminants, bacteria, and larvae across the nearshore, altering coastal water quality and ecosystem health. During directionally spread wave conditions, vertical vortices (horizontal eddies) are injected near the ends of breaking crests. Energy associated with these eddies may be transferred to larger-scale, low-frequency rotational motions through an inverse energy cascade, consistent with two-dimensional turbulence. However, our understanding of the relationships between the wave conditions and the dynamics and energetics of low-frequency surfzone eddies are largely based on numerical modeling. Here, we test these relationships with remotely sensed and&nbsp;</span><i>in situ</i><span>&nbsp;observations from large-scale directional wave basin experiments with varying wave conditions over alongshore-uniform barred bathymetry. Surface velocities derived with particle image velocimetry were employed to assess the spatial scales of low-frequency surfzone eddies and compute structure functions with alongshore velocities. Second-order structure functions for directionally spread waves (</span><span class=\"inline-formula no-formula-id\">⁠<span>&nbsp;</span></span></p>","language":"English","publisher":"AIP Publishing","doi":"10.1063/5.0169895","usgsCitation":"Baker, C., Moulton, M., Chickadel, C.C., Nuss, E., Palmsten, M.L., and Brodie, K.L., 2023, Two-dimensional inverse energy cascade in a laboratory surf zone for varying wave directional spread: Physics of Fluids, v. 35, 125140, 18 p., https://doi.org/10.1063/5.0169895.","productDescription":"125140, 18 p.","ipdsId":"IP-156274","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":467067,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1063/5.0169895","text":"Publisher Index Page"},{"id":463055,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"35","noUsgsAuthors":false,"publicationDate":"2023-12-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Baker, Christine","contributorId":305678,"corporation":false,"usgs":false,"family":"Baker","given":"Christine","email":"","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":916354,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Moulton, Melissa","contributorId":194341,"corporation":false,"usgs":false,"family":"Moulton","given":"Melissa","email":"","affiliations":[],"preferred":false,"id":916355,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Chickadel, C Chris 0000-0002-0770-7725","orcid":"https://orcid.org/0000-0002-0770-7725","contributorId":221998,"corporation":false,"usgs":false,"family":"Chickadel","given":"C","email":"","middleInitial":"Chris","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":916356,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Nuss, Emma","contributorId":305681,"corporation":false,"usgs":false,"family":"Nuss","given":"Emma","email":"","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":916357,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Palmsten, Margaret L. 0000-0002-6424-2338","orcid":"https://orcid.org/0000-0002-6424-2338","contributorId":239955,"corporation":false,"usgs":true,"family":"Palmsten","given":"Margaret","email":"","middleInitial":"L.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":916358,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Brodie, Katherine L.","contributorId":345330,"corporation":false,"usgs":false,"family":"Brodie","given":"Katherine","email":"","middleInitial":"L.","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":916359,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70250567,"text":"ofr20231077 - 2023 - Applying intrinsic potential models to evaluate salmon (Oncorhynchus spp.) introduction into main-stem and tributary habitats upstream from the Skagit River Hydroelectric Project, northern Washington","interactions":[],"lastModifiedDate":"2024-12-03T19:37:33.744214","indexId":"ofr20231077","displayToPublicDate":"2023-12-18T14:53:20","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":"2023-1077","displayTitle":"Applying Intrinsic Potential Models to Evaluate Salmon (<em>Oncorhynchus spp.</em>) Introduction into Main-Stem and Tributary Habitats Upstream from the Skagit River Hydroelectric Project, Northern Washington","title":"Applying intrinsic potential models to evaluate salmon (Oncorhynchus spp.) introduction into main-stem and tributary habitats upstream from the Skagit River Hydroelectric Project, northern Washington","docAbstract":"<p>We assessed habitat suitability for salmonids across selected tributaries upstream from three hydroelectric dams on the upper Skagit River in Whatcom County, northern Washington. We used NetMap, a commercial toolset within the ArcMap geographic information system (GIS), to analyze stream attributes based upon a synthetic stream channel network derived from digital elevation models. The GIS-derived stream attributes—including gradient, bankfull width, valley width index, elevation, and stream flow—allowed us to examine the spatial distribution and relative quality of spawning and rearing habitat for salmonids based on existing intrinsic potential (IP) models. As a first step, we created maps of potential anadromous fish distribution by identifying potential migration barriers within the synthetic stream network. Next, we applied a suite of existing IP models for steelhead, coho, and Chinook salmon (<i>Oncorhynchus mykiss</i>, <i>O. kisutch</i>, and <i>O. tshawytscha</i>, respectively) to estimate low, medium, and high IP habitat for each species. Three different IP models were used for each species, based on species preference curves from populations from coastal Oregon, northern California, Alaska, and western Washington. We found that at least 25 tributaries that were greater than third order and contained habitat with the potential for anadromous fish, totaling about 470 river kilometers in 4,453 synthetic stream reaches averaging about 100 meters (m) in length. The IP of each of these reaches was calculated and placed into low, medium, and high IP categories. For Chinook salmon, the only stream with significantly (in other words, greater than 1 kilometer [km]) high IP reaches was the upper Skagit River upstream from Ross Lake reservoir in Canada, upstream from the third dam in the hydroelectric system. There were differences among the three models evaluated, with the model derived for the lower Skagit River showing more high and medium IP habitat than the other two models that were designed for the Columbia River Basin. For coho salmon, all three models showed similar results favoring medium IP over low and high IP habitat. Of the 3 species examined with existing IP models, steelhead had the most habitat rated as high IP with 19 targeted tributaries showing greater than 1 km of high intrinsic potential habitat.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20231077","collaboration":"Prepared in cooperation with Seattle City Light","usgsCitation":"Duda, J.J., and Hardiman, J.M., 2023, Applying intrinsic potential models to evaluate salmon (Oncorhynchus spp.) introduction into main-stem and tributary habitats upstream from the Skagit River Hydroelectric Project, northern Washington: U.S. Geological Survey Open-File Report 2023-1077, 44 p. https://doi.org/10.3133/ofr20231077.","productDescription":"Report: viii, 44 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-147497","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":423653,"rank":6,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2023/1077/ofr20231077.XML"},{"id":423733,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9MKQ2UK","text":"USGS data release","description":"USGS data release","linkHelpText":"Upper Skagit River intrinsic potential results"},{"id":423650,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2023/1077/ofr20231077.pdf"},{"id":423649,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2023/1077/ofr20231077.jpg"},{"id":423652,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2023/1077/Images"},{"id":423651,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20231077/full"}],"country":"Canada, United States","state":"Washington","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -121.3,\n              49.3\n            ],\n            [\n              -121.3,\n              48.3\n            ],\n            [\n              -120.3,\n              48.3\n            ],\n            [\n               -120.3,\n              49.3\n            ],\n            [\n              -121.3,\n              49.3\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","contact":"<p>Director, <a href=\"https://www.usgs.gov/centers/wfrc\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://www.usgs.gov/centers/wfrc\">Western Fisheries Research Center</a><br>U.S. Geological Survey<br>6505 NE 65th Street<br>Seattle, Washington 98115-5016</p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Purpose and Scope</li><li>Methodology</li><li>Results and Interpretations</li><li>Summary</li><li>References Cited</li></ul>","publishedDate":"2023-12-18","noUsgsAuthors":false,"publicationDate":"2023-12-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Duda, Jeffrey J. 0000-0001-7431-8634 jduda@usgs.gov","orcid":"https://orcid.org/0000-0001-7431-8634","contributorId":148954,"corporation":false,"usgs":true,"family":"Duda","given":"Jeffrey","email":"jduda@usgs.gov","middleInitial":"J.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":890407,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hardiman, Jill M. 0000-0002-3661-9695 jhardiman@usgs.gov","orcid":"https://orcid.org/0000-0002-3661-9695","contributorId":2672,"corporation":false,"usgs":true,"family":"Hardiman","given":"Jill","email":"jhardiman@usgs.gov","middleInitial":"M.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":890408,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70256475,"text":"70256475 - 2023 - The context dependency of fish-habitat associations in separated karst ecoregions","interactions":[],"lastModifiedDate":"2024-08-07T16:04:22.691671","indexId":"70256475","displayToPublicDate":"2023-12-18T10:54:40","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"The context dependency of fish-habitat associations in separated karst ecoregions","docAbstract":"<p><span>Fish populations may be isolated via natural conditions in geographically separated ecoregions. Although reconnecting these populations is not a management goal, we need to understand how these populations persist across landscapes to develop meaningful conservation actions, particularly for species occupying sensitive karst ecosystems. Our study objective was to determine the physicochemical factors related to the occurrence of four spring-associated fishes. Arbuckle Uplift and Ozark Highlands ecoregions, USA. We used a hierarchical approach to identify habitat relationships at multiple spatial scales. We collected detection data using snorkeling and seining. We examined the physicochemical relationships related to the detection and occurrence of four spring-associated fishes using occupancy modeling in a Bayesian framework. We found physicochemical relationships that differed and were similar between ecoregions for several fishes. For three species, we found different water temperature relationships between ecoregions. Smallmouth bass were ubiquitous in their use of drainage areas in the Ozark Highlands but only associated with the lower network of the Arbuckle Uplift. There were several mirrored relationships between ecoregions, including an interaction between residual pool depth and water temperature, where sites with deeper pools were more likely to be occupied during warmer water temperatures. There were single-species occurrence relationships with percent vegetation and percent agriculture. Lastly, snorkeling was a more efficient sampling method compared to seining for all fishes. Our results indicate stream temperature mitigation may be possible via the maintenance of key channel morphologies, and we identify shared stressors between ecoregions. Channel mitigation to maintain reaches with deeper pools may be an important strategy for maintaining thermal refugia, particularly when considering climate change. Identifying the mechanistic underpinning of other multiscale ecological relationships would be helpful to discern if some of the different ecoregion relationships represent warning signals or interactions with unmeasured biotic or abiotic factors.</span></p>","language":"English","publisher":"Wiley","doi":"10.1002/ece3.10701","usgsCitation":"Swedberg, D.A., Mollenhauer, R.M., and Brewer, S.K., 2023, The context dependency of fish-habitat associations in separated karst ecoregions: Ecology and Evolution, v. 13, no. 12, e10701, 18 p., https://doi.org/10.1002/ece3.10701.","productDescription":"e10701, 18 p.","ipdsId":"IP-146272","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":441399,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.10701","text":"Publisher Index Page"},{"id":432361,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oklahoma","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -94.6056935051375,\n              36.99095780343694\n            ],\n            [\n              -95.25818479665297,\n              36.77262795781087\n            ],\n            [\n              -95.51281809235115,\n              35.597221761955254\n            ],\n            [\n              -94.4536118118592,\n              35.530687987028585\n            ],\n            [\n              -94.6056935051375,\n              36.99095780343694\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    },\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -97.16528274367352,\n              34.594939532905144\n            ],\n            [\n              -97.44206576958777,\n              33.94434112413069\n            ],\n            [\n              -96.10069816898147,\n              33.94433280692786\n            ],\n            [\n              -96.13328126204877,\n              34.75563707296074\n            ],\n            [\n              -97.16528274367352,\n              34.594939532905144\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"13","issue":"12","noUsgsAuthors":false,"publicationDate":"2023-12-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Swedberg, Dusty A.","contributorId":340779,"corporation":false,"usgs":false,"family":"Swedberg","given":"Dusty","email":"","middleInitial":"A.","affiliations":[{"id":7249,"text":"Oklahoma State University","active":true,"usgs":false}],"preferred":false,"id":907545,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mollenhauer, Robert M.","contributorId":340780,"corporation":false,"usgs":false,"family":"Mollenhauer","given":"Robert","email":"","middleInitial":"M.","affiliations":[{"id":7249,"text":"Oklahoma State University","active":true,"usgs":false}],"preferred":false,"id":907546,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brewer, Shannon K. 0000-0002-1537-3921 skbrewer@usgs.gov","orcid":"https://orcid.org/0000-0002-1537-3921","contributorId":2252,"corporation":false,"usgs":true,"family":"Brewer","given":"Shannon","email":"skbrewer@usgs.gov","middleInitial":"K.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":907547,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70254772,"text":"70254772 - 2023 - Forage senescence and disease influence elk pregnancy across the Greater Yellowstone Ecosystem","interactions":[],"lastModifiedDate":"2024-06-07T15:57:01.046173","indexId":"70254772","displayToPublicDate":"2023-12-18T10:45:58","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Forage senescence and disease influence elk pregnancy across the Greater Yellowstone Ecosystem","docAbstract":"<p><span>For various temperate ungulate species, recent research has highlighted the potential for spring vegetation phenology (“green-up”) to influence individual condition, with purported benefits to population productivity. However, few studies have been able to measure the benefit on vital rates directly, and fewer still have investigated the comparative influence of other phenological periods on ungulate vital rates. In this study, we tracked phenological changes throughout the duration of the growing season and examined how their timing affected the probability of pregnancy in an ungulate population. We did this for elk (</span><i>Cervus canadensis</i><span>) across the Greater Yellowstone Ecosystem (GYE) by sampling 1106 adult females in winter at 25 sites over a 13-year period and assessing sources of variation in pregnancy using a Bayesian hierarchical model. Pregnancy rates were generally high across the GYE (82.4%), and the primary influences on probability of pregnancy were the timing of vegetation senescence (“brown-down”) in autumn and exposure to the reproductive disease brucellosis. Earlier forage brown-down in fall negatively influenced the probability of pregnancy of elk aged 6–9 years by an estimated 17.2% within the range (ca. 32 days) of observed brown-down end dates. While summer habitat quality has been inferred to influence elk pregnancy previously, our findings specify the key influence of foraging conditions later in the seasonal cycle, immediately before the breeding season. The reproductive disease brucellosis was also an important factor, reducing the probability of pregnancy by 12.4% in elk in the 6- to 9-year age class. Because pregnancy was tested before most disease-induced abortions occur, the apparent mechanism for this effect is a prolonged reduction in fertility beyond the period of initial exposure in which fetal mortality is typically expected. Our results prompt greater scrutiny of the combined effects of late-season phenology and disease on reproductive rates and population productivity in temperate ungulates.</span></p>","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.4694","usgsCitation":"Bidder, O.R., Connor, T., Morales, J.M., Rickbeil, G.J., Merkle, J., Fuda, R.K., Rogerson, J., Scurlock, B.M., Edwards, W.H., Cole, E., McWhirter, D.E., Courtemanch, A.B., Dewey, S., Kauffman, M., MacNulty, D.R., du Toit, J., Stahler, D., and Middleton, A.D., 2023, Forage senescence and disease influence elk pregnancy across the Greater Yellowstone Ecosystem: Ecosphere, v. 14, e4694, 14 p., https://doi.org/10.1002/ecs2.4694.","productDescription":"e4694, 14 p.","ipdsId":"IP-157765","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":441401,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.4694","text":"Publisher Index Page"},{"id":429652,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho, Montana, Wyoming","otherGeospatial":"Greater Yellowstone Ecosystem","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -114.01112913216181,\n              46.437409339504086\n            ],\n            [\n              -114.01112913216181,\n              42.020821465341925\n            ],\n            [\n              -105.94049421049453,\n              42.020821465341925\n            ],\n            [\n              -105.94049421049453,\n              46.437409339504086\n            ],\n            [\n              -114.01112913216181,\n              46.437409339504086\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"14","noUsgsAuthors":false,"publicationDate":"2023-12-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Bidder, Owen R.","contributorId":337529,"corporation":false,"usgs":false,"family":"Bidder","given":"Owen","email":"","middleInitial":"R.","affiliations":[{"id":6643,"text":"University of California - Berkeley","active":true,"usgs":false}],"preferred":false,"id":902480,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Connor, Thomas","contributorId":337530,"corporation":false,"usgs":false,"family":"Connor","given":"Thomas","email":"","affiliations":[{"id":6643,"text":"University of California - Berkeley","active":true,"usgs":false}],"preferred":false,"id":902481,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Morales, Juan M.","contributorId":171521,"corporation":false,"usgs":false,"family":"Morales","given":"Juan","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":902482,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rickbeil, Gregory J.M.","contributorId":270401,"corporation":false,"usgs":false,"family":"Rickbeil","given":"Gregory","email":"","middleInitial":"J.M.","affiliations":[{"id":54468,"text":"uc","active":true,"usgs":false}],"preferred":false,"id":902483,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Merkle, Jerod A.","contributorId":264421,"corporation":false,"usgs":false,"family":"Merkle","given":"Jerod A.","affiliations":[{"id":40829,"text":"uwy","active":true,"usgs":false}],"preferred":false,"id":902484,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Fuda, Rebecca K.","contributorId":203303,"corporation":false,"usgs":false,"family":"Fuda","given":"Rebecca","email":"","middleInitial":"K.","affiliations":[{"id":36596,"text":"Wyoming Game and Fish Department","active":true,"usgs":false}],"preferred":false,"id":902485,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Rogerson, Jared D.","contributorId":106401,"corporation":false,"usgs":true,"family":"Rogerson","given":"Jared D.","affiliations":[],"preferred":false,"id":902486,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Scurlock, Brandon M.","contributorId":93788,"corporation":false,"usgs":false,"family":"Scurlock","given":"Brandon","email":"","middleInitial":"M.","affiliations":[{"id":6917,"text":"Wyoming Game and Fish Department, Laramie, USA","active":true,"usgs":false}],"preferred":false,"id":902487,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Edwards, William H","contributorId":189799,"corporation":false,"usgs":false,"family":"Edwards","given":"William","email":"","middleInitial":"H","affiliations":[],"preferred":false,"id":902488,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Cole, Eric K.","contributorId":337540,"corporation":false,"usgs":false,"family":"Cole","given":"Eric K.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":902489,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"McWhirter, Douglas E.","contributorId":264424,"corporation":false,"usgs":false,"family":"McWhirter","given":"Douglas","email":"","middleInitial":"E.","affiliations":[{"id":54471,"text":"wyfg","active":true,"usgs":false}],"preferred":false,"id":902490,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Courtemanch, Alyson B.","contributorId":198651,"corporation":false,"usgs":false,"family":"Courtemanch","given":"Alyson","email":"","middleInitial":"B.","affiliations":[{"id":35682,"text":"Wyoming Game and Fish Department, Jackson, WY","active":true,"usgs":false}],"preferred":false,"id":902491,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Dewey, Sarah","contributorId":337547,"corporation":false,"usgs":false,"family":"Dewey","given":"Sarah","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":902492,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Kauffman, Matthew J. 0000-0003-0127-3900","orcid":"https://orcid.org/0000-0003-0127-3900","contributorId":202921,"corporation":false,"usgs":true,"family":"Kauffman","given":"Matthew","middleInitial":"J.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":902493,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"MacNulty, Daniel R.","contributorId":210842,"corporation":false,"usgs":false,"family":"MacNulty","given":"Daniel","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":902494,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"du Toit, Johan T.","contributorId":86583,"corporation":false,"usgs":true,"family":"du Toit","given":"Johan T.","affiliations":[],"preferred":false,"id":902495,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Stahler, Daniel R.","contributorId":337554,"corporation":false,"usgs":false,"family":"Stahler","given":"Daniel R.","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":902496,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Middleton, Arthur D.","contributorId":210264,"corporation":false,"usgs":false,"family":"Middleton","given":"Arthur","email":"","middleInitial":"D.","affiliations":[{"id":33770,"text":"University of California at Berkeley","active":true,"usgs":false}],"preferred":false,"id":902497,"contributorType":{"id":1,"text":"Authors"},"rank":18}]}}
,{"id":70250712,"text":"70250712 - 2023 - Bayesian hierarchical modeling for probabilistic estimation of tsunami amplitude from far-field earthquake sources","interactions":[],"lastModifiedDate":"2023-12-28T12:44:48.760618","indexId":"70250712","displayToPublicDate":"2023-12-18T06:36:38","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2321,"text":"Journal of Geophysical Research: Oceans","active":true,"publicationSubtype":{"id":10}},"title":"Bayesian hierarchical modeling for probabilistic estimation of tsunami amplitude from far-field earthquake sources","docAbstract":"<div class=\"article-section__content en main\"><p>Evaluation of tsunami disaster risk for a coastal region requires reliable estimation of tsunami hazard, for example, wave amplitude close to the shore. Observed tsunami data are scarce and have poor spatial coverage, and for this reason probabilistic tsunami hazard analysis (PTHA) traditionally relies on numerical simulation of “synthetic” tsunami generation and propagation toward the coast. Such an approach has been extensively studied in the past and it is widely recognized as an important disaster-risk mitigation tool. PTHA can not only provide less uncertain and spatially coherent hazard estimates in comparison with classical empirical data analysis which is restricted at the tide gauge stations, but also local inundation information. In this paper, we explore a purely statistical alternative to traditional PTHA for evaluation of tsunami amplitude hazard. Here, we use tide gauge measurements of tsunami amplitude along the western United States, specifically California and Oregon, and develop a spatial Bayesian hierarchical model (BHM) to assess tsunami hazard from far-field earthquake sources at various recurrence intervals. The configuration of our model incorporates latent Gaussian fields that utilize information on the distance between tide gauges as well as on the continental shelf width, that is, a covariate linked to potential dissipative effects on wave energy as the tsunami travels over shallow water. Through our BHM, we produce spatially continuous probabilistic maps of far-field tsunami hazard which can aid comprehensive tsunami disaster risk reduction and management.</p></div>","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2023JC020002","usgsCitation":"Boumis, G., Geist, E.L., and Lee, D., 2023, Bayesian hierarchical modeling for probabilistic estimation of tsunami amplitude from far-field earthquake sources: Journal of Geophysical Research: Oceans, v. 128, no. 12, e2023JC020002, 16 p., https://doi.org/10.1029/2023JC020002.","productDescription":"e2023JC020002, 16 p.","ipdsId":"IP-151939","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":499265,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2023jc020002","text":"Publisher Index Page"},{"id":423956,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Oregon, Washington","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -122.89613542356796,\n              48.497460056867624\n            ],\n            [\n              -126.0601979235679,\n              49.01892139292943\n            ],\n            [\n              -126.0601979235679,\n              44.94434930821649\n            ],\n            [\n              -126.41176042356773,\n              40.75865742539179\n            ],\n            [\n              -125.35707292356773,\n              38.45677055335565\n            ],\n            [\n              -123.24769792356778,\n              34.64558981782825\n            ],\n            [\n              -120.61097917356783,\n              33.0397043679928\n            ],\n            [\n              -118.32582292356796,\n              32.0767084901876\n            ],\n            [\n              -115.33754167356793,\n              32.37411455892672\n            ],\n            [\n              -120.17152604856793,\n              36.78614622387245\n            ],\n            [\n              -122.80824479856787,\n              39.95497361468907\n            ],\n            [\n              -122.80824479856787,\n              43.94038749428063\n            ],\n            [\n              -122.89613542356796,\n              48.497460056867624\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"128","issue":"12","noUsgsAuthors":false,"publicationDate":"2023-12-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Boumis, Georgios 0000-0001-7825-5239","orcid":"https://orcid.org/0000-0001-7825-5239","contributorId":332846,"corporation":false,"usgs":false,"family":"Boumis","given":"Georgios","email":"","affiliations":[{"id":79664,"text":"Center for Complex Hydrosystems Research, University of Alabama","active":true,"usgs":false}],"preferred":false,"id":891060,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Geist, Eric L. 0000-0003-0611-1150","orcid":"https://orcid.org/0000-0003-0611-1150","contributorId":15543,"corporation":false,"usgs":true,"family":"Geist","given":"Eric","email":"","middleInitial":"L.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":891061,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lee, Danhyang","contributorId":332847,"corporation":false,"usgs":false,"family":"Lee","given":"Danhyang","email":"","affiliations":[{"id":36730,"text":"University of Alabama","active":true,"usgs":false}],"preferred":false,"id":891062,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70254899,"text":"70254899 - 2023 - Backpack satellite transmitters reduce survival but not nesting propensity or success of greater sage-grouse","interactions":[],"lastModifiedDate":"2024-06-11T11:18:44.083911","indexId":"70254899","displayToPublicDate":"2023-12-18T06:12:57","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Backpack satellite transmitters reduce survival but not nesting propensity or success of greater sage-grouse","docAbstract":"<div class=\"abstract-group  metis-abstract\"><div class=\"article-section__content en main\"><p>Telemetry technology is ubiquitous for studying the behavior and demography of wildlife, including the use of traditional very high frequency (VHF) radio telemetry and more recent methods that record animal locations using global positioning systems (GPS). Satellite-based GPS telemetry allows researchers to collect high spatial–temporal resolution data remotely but may also come with additional costs. For example, recent studies from the southern Great Basin suggested GPS transmitters attached via backpacks may reduce the survival of greater sage-grouse (<i>Centrocercus urophasianus</i>) relative to VHF transmitters attached via collars that have been in use for decades. While some evidence suggests GPS backpacks reduce survival, no studies have examined the effects of GPS backpacks on breeding behavior and success. Therefore, we compared survival, breeding behavior, and nest success of sage-grouse hens marked with both VHF collars and GPS backpack transmitter over a 7-year period in central Idaho, USA. GPS backpacks reduced spring–summer survival of sage-grouse hens relative to hens with VHF collars, where daily mortality probability was 68%–82% higher from March 1 to August 1. Yet satellite GPS backpacks did not consistently affect nest success or the likelihood or timing of nest initiation relative to VHF collars. Daily nest survival varied annually and with timing of nest initiation and nest age, but marginal effects of transmitter type were statistically insignificant and interactions between transmitter type and study year produced no meaningful patterns. Our results corroborate recent studies for the effect of satellite GPS backpacks on sage-grouse survival, but also suggest that these transmitters do not appear to affect components of fecundity. Our results therefore add important context to recent debate surrounding the effects of GPS backpacks on sage-grouse, and the relative strengths and weaknesses of different transmitter types for understanding behavior and population dynamics.</p></div></div>","language":"English","publisher":"Wiley","doi":"10.1002/ece3.10820","usgsCitation":"Stevens, B., Conway, C.J., Tisdale, C.A., Denny, K.N., Meyers, A., and Makela, P., 2023, Backpack satellite transmitters reduce survival but not nesting propensity or success of greater sage-grouse: Ecology and Evolution, v. 13, no. 12, e10820, 13 p., https://doi.org/10.1002/ece3.10820.","productDescription":"e10820, 13 p.","ipdsId":"IP-155346","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":441404,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.10820","text":"Publisher Index Page"},{"id":429808,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -114.45000480079682,\n              44.653208889001206\n            ],\n            [\n              -114.45000480079682,\n              43.85056176698046\n            ],\n            [\n              -113.18657706642185,\n              43.85056176698046\n            ],\n            [\n              -113.18657706642185,\n              44.653208889001206\n            ],\n            [\n              -114.45000480079682,\n              44.653208889001206\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"13","issue":"12","noUsgsAuthors":false,"publicationDate":"2023-12-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Stevens, Bryan S.","contributorId":275853,"corporation":false,"usgs":false,"family":"Stevens","given":"Bryan S.","affiliations":[{"id":39599,"text":"ui","active":true,"usgs":false}],"preferred":false,"id":902808,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Conway, Courtney J. 0000-0003-0492-2953 cconway@usgs.gov","orcid":"https://orcid.org/0000-0003-0492-2953","contributorId":2951,"corporation":false,"usgs":true,"family":"Conway","given":"Courtney","email":"cconway@usgs.gov","middleInitial":"J.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":902809,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tisdale, Cody A.","contributorId":337968,"corporation":false,"usgs":false,"family":"Tisdale","given":"Cody","email":"","middleInitial":"A.","affiliations":[{"id":36394,"text":"University of Idaho","active":true,"usgs":false}],"preferred":false,"id":902810,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Denny, Kylie N.","contributorId":337969,"corporation":false,"usgs":false,"family":"Denny","given":"Kylie","email":"","middleInitial":"N.","affiliations":[{"id":36394,"text":"University of Idaho","active":true,"usgs":false}],"preferred":false,"id":902811,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Meyers, Andrew","contributorId":337999,"corporation":false,"usgs":false,"family":"Meyers","given":"Andrew","email":"","affiliations":[],"preferred":false,"id":902891,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Makela, Paul","contributorId":338000,"corporation":false,"usgs":false,"family":"Makela","given":"Paul","email":"","affiliations":[],"preferred":false,"id":902892,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70256182,"text":"70256182 - 2023 - Maps of active layer thickness in northern Alaska by upscaling P-band polarimetric synthetic aperture radar retrievals","interactions":[],"lastModifiedDate":"2024-07-25T23:58:14.226325","indexId":"70256182","displayToPublicDate":"2023-12-15T18:56:14","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1562,"text":"Environmental Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Maps of active layer thickness in northern Alaska by upscaling P-band polarimetric synthetic aperture radar retrievals","docAbstract":"<div class=\"article-text wd-jnl-art-abstract cf\"><p>Extensive, detailed information on the spatial distribution of active layer thickness (ALT) in northern Alaska and how it evolves over time could greatly aid efforts to assess the effects of climate change on the region and also help to quantify greenhouse gas emissions generated due to permafrost thaw. For this reason, we have been developing high-resolution maps of ALT throughout northern Alaska. The maps are produced by upscaling from high-resolution swaths of estimated ALT retrieved from airborne P-band synthetic aperture radar (SAR) images collected for three different years. The upscaling was accomplished by using hundreds of thousands of randomly selected samples from the SAR-derived swaths of ALT to train a machine learning regression algorithm supported by numerous spatial data layers. In order to validate the maps, thousands of randomly selected samples of SAR-derived ALT were excluded from the training in order to serve as validation pixels; error performance calculations relative to these samples yielded root-mean-square errors (RMSEs) of 7.5–9.1 cm, with bias errors of magnitude under 0.1 cm. The maps were also compared to ALT measurements collected at a number of<span>&nbsp;</span><i>in situ</i><span>&nbsp;</span>test sites; error performance relative to the site measurements yielded RMSEs of approximately 11–12 cm and bias of 2.7–6.5 cm. These data are being used to investigate regional patterns and underlying physical controls affecting permafrost degradation in the tundra biome.</p></div>","language":"English","publisher":"IOP Publishing","doi":"10.1088/1748-9326/ad127f","usgsCitation":"Whitcomb, J., Chen, R., Clewley, D., Kimball, J.S., Pastick, N., Yi, Y., and Moghaddam, M., 2023, Maps of active layer thickness in northern Alaska by upscaling P-band polarimetric synthetic aperture radar retrievals: Environmental Research Letters, v. 19, 014046, 14 p., https://doi.org/10.1088/1748-9326/ad127f.","productDescription":"014046, 14 p.","ipdsId":"IP-157950","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":441407,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"http://dx.doi.org/10.1088/1748-9326/ad127f","text":"Publisher Index Page"},{"id":431453,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"19","noUsgsAuthors":false,"publicationDate":"2023-12-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Whitcomb, Jane 0000-0002-2919-7260","orcid":"https://orcid.org/0000-0002-2919-7260","contributorId":340381,"corporation":false,"usgs":false,"family":"Whitcomb","given":"Jane","email":"","affiliations":[{"id":81594,"text":"University of Southern California, Dept. of Electrical Engineering","active":true,"usgs":false}],"preferred":false,"id":907011,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chen, Richard","contributorId":340382,"corporation":false,"usgs":false,"family":"Chen","given":"Richard","email":"","affiliations":[{"id":7023,"text":"Jet Propulsion Laboratory, California Institute of Technology","active":true,"usgs":false}],"preferred":false,"id":907012,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Clewley, Daniel 0000-0003-1243-3711","orcid":"https://orcid.org/0000-0003-1243-3711","contributorId":340383,"corporation":false,"usgs":false,"family":"Clewley","given":"Daniel","email":"","affiliations":[{"id":81595,"text":"Plymouth Marine Laboratory, Centre for Geospatial Applications,","active":true,"usgs":false}],"preferred":false,"id":907013,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kimball, John S. 0000-0002-5493-5878","orcid":"https://orcid.org/0000-0002-5493-5878","contributorId":244377,"corporation":false,"usgs":false,"family":"Kimball","given":"John","email":"","middleInitial":"S.","affiliations":[{"id":48908,"text":"U Montana","active":true,"usgs":false}],"preferred":false,"id":907014,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Pastick, Neal 0000-0002-4321-6739","orcid":"https://orcid.org/0000-0002-4321-6739","contributorId":222683,"corporation":false,"usgs":true,"family":"Pastick","given":"Neal","email":"","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":false,"id":907015,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Yi, Yonghong 0000-0002-0039-0462","orcid":"https://orcid.org/0000-0002-0039-0462","contributorId":340384,"corporation":false,"usgs":false,"family":"Yi","given":"Yonghong","email":"","affiliations":[{"id":81596,"text":"University of California, Joint Institute for Regional Earth System Science and Engineering","active":true,"usgs":false}],"preferred":false,"id":907016,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Moghaddam, Mahta","contributorId":267922,"corporation":false,"usgs":false,"family":"Moghaddam","given":"Mahta","email":"","affiliations":[{"id":13249,"text":"University of Southern California","active":true,"usgs":false}],"preferred":false,"id":907017,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70253565,"text":"70253565 - 2023 - Designation of a composite-stratotype section for the lower Paleocene (Danian) Brightseat Formation in Prince George’s County, Maryland, U.S.A.","interactions":[],"lastModifiedDate":"2024-05-02T14:03:53.184557","indexId":"70253565","displayToPublicDate":"2023-12-15T08:52:03","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3481,"text":"Stratigraphy","active":true,"publicationSubtype":{"id":10}},"title":"Designation of a composite-stratotype section for the lower Paleocene (Danian) Brightseat Formation in Prince George’s County, Maryland, U.S.A.","docAbstract":"<p><span>The lower Paleocene (Danian) Brightseat Formation consists of fine-grained, dark-gray, micaceous sand and silty clay, with glauconite and abundant, but generally poorly preserved, fossils. The Brightseat Formation represents deposition of lower, but not lowermost, Paleocene sediments that were deposited on the middle to outer shelf of what is now the Atlantic Coastal Plain. A basal disconformity separates the Brightseat from the underlying Upper Cretaceous Severn Formation, and it is disconformably overlain by the middle to upper Paleocene Aquia Formation. The type locality of the Brightseat Formation, previously exposed approximately 1 mile (1.6 km) west-southwest of the former village of Brightseat in Prince George’s County, Maryland, just outside ofWashington, D.C., has been destroyed by urban development, prompting the establishment of a composite-stratotype section from nearby outcrops approximately a half mile to the south-southwest of the original location. The outcrop at Cabin Branch is hereby designated as the principal reference section for the Brightseat Formation and the “Cabin Creek” outcrop (an informally designated tributary of Cabin Branch) is designated as a supplementary reference section that illustrates the boundary of the Brightseat with the overlying Aquia Formation. Paleontological analyses, grain-size analyses, and petrographic techniques are used to document this new stratotype section and to correlate and contrast it with underlying and overlying sediments. This composite-stratotype section is designated using the guidelines outlined in Article 8, remarks (d) and (e) of the North American Code of Stratigraphic Nomenclature.</span></p>","language":"English","publisher":"Micropaleontology Press","doi":"10.29041/strat.20.4.01","usgsCitation":"Self-Trail, J., Parker, M., Govoni, D.L., Bybell, L.M., Gardner, K.F., and Gohn, G., 2023, Designation of a composite-stratotype section for the lower Paleocene (Danian) Brightseat Formation in Prince George’s County, Maryland, U.S.A.: Stratigraphy, v. 20, no. 4, p. 237-258, https://doi.org/10.29041/strat.20.4.01.","productDescription":"22 p.","startPage":"237","endPage":"258","ipdsId":"IP-152111","costCenters":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":428323,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Maryland","county":"Prince Georges County","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -76.92,\n              38.9\n            ],\n            [\n              -76.92,\n              38.75\n            ],\n            [\n              -76.88,\n              38.75\n            ],\n            [\n              -76.88,\n              38.9\n            ],\n            [\n              -76.92,\n              38.9\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"20","issue":"4","noUsgsAuthors":false,"publicationDate":"2023-12-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Self-Trail, Jean 0000-0002-3018-4985 jstrail@usgs.gov","orcid":"https://orcid.org/0000-0002-3018-4985","contributorId":147370,"corporation":false,"usgs":true,"family":"Self-Trail","given":"Jean","email":"jstrail@usgs.gov","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":899910,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Parker, Mercer 0000-0001-6683-6458 mercerparker@usgs.gov","orcid":"https://orcid.org/0000-0001-6683-6458","contributorId":203174,"corporation":false,"usgs":true,"family":"Parker","given":"Mercer","email":"mercerparker@usgs.gov","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":899911,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Govoni, David L. 0000-0002-2707-0098 dgovoni@usgs.gov","orcid":"https://orcid.org/0000-0002-2707-0098","contributorId":292463,"corporation":false,"usgs":true,"family":"Govoni","given":"David","email":"dgovoni@usgs.gov","middleInitial":"L.","affiliations":[{"id":5071,"text":"Office of Administration","active":true,"usgs":true}],"preferred":true,"id":899912,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bybell, Laurel M. 0000-0002-4760-7542 lbybell@usgs.gov","orcid":"https://orcid.org/0000-0002-4760-7542","contributorId":1760,"corporation":false,"usgs":true,"family":"Bybell","given":"Laurel","email":"lbybell@usgs.gov","middleInitial":"M.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":899913,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gardner, Kristina Frank 0000-0001-9872-9294","orcid":"https://orcid.org/0000-0001-9872-9294","contributorId":297849,"corporation":false,"usgs":true,"family":"Gardner","given":"Kristina","email":"","middleInitial":"Frank","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":899914,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Gohn, Gregory S.","contributorId":297850,"corporation":false,"usgs":false,"family":"Gohn","given":"Gregory S.","affiliations":[],"preferred":false,"id":899915,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70262288,"text":"70262288 - 2023 - Observed impacts of large wind farms on grassland carbon cycling","interactions":[],"lastModifiedDate":"2025-01-16T15:58:01.645734","indexId":"70262288","displayToPublicDate":"2023-12-15T00:00:00","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5802,"text":"Science Bulletin","active":true,"publicationSubtype":{"id":10}},"title":"Observed impacts of large wind farms on grassland carbon cycling","docAbstract":"<p>No abstract available.&nbsp;</p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.scib.2023.10.016","usgsCitation":"Wu, D., Grodsky, S.M., Xu, W., Liu, N., Almeida, R.M., Zhou, L., Miller, L., Roy, S., Xia, G., Agrawal, A., Houlton, B.Z., Flecker, A.S., and Xu, X., 2023, Observed impacts of large wind farms on grassland carbon cycling: Science Bulletin, v. 68, no. 23, p. 2889-2892, https://doi.org/10.1016/j.scib.2023.10.016.","productDescription":"4 p.","startPage":"2889","endPage":"2892","ipdsId":"IP-139072","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":467068,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.osti.gov/biblio/2222420","text":"External Repository"},{"id":466634,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"68","issue":"23","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Wu, Donghai","contributorId":348756,"corporation":false,"usgs":false,"family":"Wu","given":"Donghai","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":923742,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Grodsky, Steven Mark 0000-0003-0846-7230","orcid":"https://orcid.org/0000-0003-0846-7230","contributorId":328517,"corporation":false,"usgs":true,"family":"Grodsky","given":"Steven","email":"","middleInitial":"Mark","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":923744,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Xu, Wenfang","contributorId":348761,"corporation":false,"usgs":false,"family":"Xu","given":"Wenfang","affiliations":[{"id":37968,"text":"Sun Yat-Sen University","active":true,"usgs":false}],"preferred":false,"id":923748,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Liu, Naijing","contributorId":348757,"corporation":false,"usgs":false,"family":"Liu","given":"Naijing","affiliations":[{"id":16866,"text":"Beijing Normal University","active":true,"usgs":false}],"preferred":false,"id":923743,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Almeida, Rafael M.","contributorId":269683,"corporation":false,"usgs":false,"family":"Almeida","given":"Rafael","email":"","middleInitial":"M.","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":924111,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Zhou, Liming","contributorId":34939,"corporation":false,"usgs":false,"family":"Zhou","given":"Liming","email":"","affiliations":[],"preferred":false,"id":924112,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Miller, Lee M.","contributorId":349176,"corporation":false,"usgs":false,"family":"Miller","given":"Lee M.","affiliations":[],"preferred":false,"id":924113,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Roy, Somnath Baidya","contributorId":349177,"corporation":false,"usgs":false,"family":"Roy","given":"Somnath Baidya","affiliations":[],"preferred":false,"id":924114,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Xia, Geng","contributorId":348762,"corporation":false,"usgs":false,"family":"Xia","given":"Geng","affiliations":[{"id":83407,"text":"7National Wind Technology Center/National Renewable Energy Laboratory","active":true,"usgs":false}],"preferred":false,"id":923749,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Agrawal, A.","contributorId":43601,"corporation":false,"usgs":true,"family":"Agrawal","given":"A.","email":"","affiliations":[],"preferred":false,"id":924115,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Houlton, Benjamin Z.","contributorId":9553,"corporation":false,"usgs":true,"family":"Houlton","given":"Benjamin","email":"","middleInitial":"Z.","affiliations":[],"preferred":false,"id":924116,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Flecker, Alexander S.","contributorId":216523,"corporation":false,"usgs":false,"family":"Flecker","given":"Alexander","email":"","middleInitial":"S.","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":924117,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Xu, Xiangtao","contributorId":348758,"corporation":false,"usgs":false,"family":"Xu","given":"Xiangtao","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":923745,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}}
,{"id":70250474,"text":"sir20235121 - 2023 - Hydrogeology, karst, and groundwater availability of Monroe County, West Virginia","interactions":[],"lastModifiedDate":"2026-03-13T15:40:20.136121","indexId":"sir20235121","displayToPublicDate":"2023-12-14T07:40:00","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":"2023-5121","displayTitle":"Hydrogeology, Karst, and Groundwater Availability of Monroe County, West Virginia","title":"Hydrogeology, karst, and groundwater availability of Monroe County, West Virginia","docAbstract":"<p>Monroe County is in southeastern West Virginia, encompassing an area of 474 square miles. The area consists of karst and siliciclastic aquifers of Ordovician, Silurian, Devonian, and Mississippian age and is in parts of two physiographic provinces: the Valley and Ridge Province to the east of Peters Mountain, and the Appalachian Plateau Province to the west of Peters Mountain. This study was developed in response to inquiries from the Monroe County Commission requesting assessment of the water resources of the county to better understand the quantity of the county’s groundwater resources, for both current [2023] and future demand, and to provide information to support protection and management of the county’s valuable groundwater resources.</p><p>Various products were developed for this study that provide knowledge with respect to water availability and contamination susceptibility of the karst aquifers within the county. U.S. Geological Survey (USGS) geologists conducted extensive geologic mapping in support of the project, producing (1) a countywide bedrock geologic map, (2) a countywide hydrogeologic map, and (3) a light detection and ranging (lidar)-derived countywide digital elevation model and associated sinkhole map. A significant part of this work was to map in detail the Greenbrier Group at the formation level, which prior to this study had only partially been completed. The report also includes (4) a description of the lithologic units identified as part of the geologic mapping process.</p><p>U.S. Geological Survey hydrologists completed several additional products for the hydrology part of the effort, including development of (1) a countywide potentiometric surface (water-table) map, (2) a countywide base-flow stream assessment, (3) countywide water-budget estimates, (4) well log surveys for 15 wells to better understand subsurface controls on groundwater flow within the study area, (5) two groundwater tracer tests to better refine the groundwater divide from the northern and southern parts of the karst aquifer in Monroe County; and finally, based on all available data collected for the study including the potentiometric surface map, geologic map, current [2023] and legacy fluorometric groundwater tracer tests, and base-flow stream assessments, (6) groundwater-basin delineations were reassessed for principal groundwater basins within the Greenbrier aquifer.</p><p>In Monroe County, four principal hydrogeologic settings produce large yields of water for residential, agricultural, and other uses. The most relied upon water-bearing zone with respect to current [2023] public water supply is from springs along Peters Mountain. These springs are derived from intervals of fractured sandstone and resultant alluvial deposits. Groundwater flows downslope through these permeable alluvial deposits and discharges at the contact with less permeable strata, such as the Reedsville Shale. The second most relied upon water-bearing zone in Monroe County is within the karstic Greenbrier Group aquifer, in which the basal Hillsdale Limestone overlies the less permeable Maccrady Shale. This geologic contact between the Hillsdale Limestone and Maccrady Shale is not only targeted as a source of water for agricultural supply but also is targeted as a source of water for residential supply. The third most relied upon water-bearing zone is composed of shallow perched aquifers within the Greenbrier Group. The discontinuous nature of these perched aquifers makes mapping their extent impossible, but they are related to permeable geologic strata, such as karstified limestones with solutionally enhanced permeability that overlies less permeable shale or chert bedrock. During geologic mapping of the county, several of these perched aquifers were documented in the Pickaway, Union, and Alderson Limestones. A fourth zone consists of springs from Ordovician carbonates at the base of Peters Mountain, which are influenced by sinking streams as well as upwelling along faults. In terms of water quantity, the most sustainable springs are those having deeper-sourced flows.</p><p>Public supplies are a principal source of water used for residential and commercial supply in the region, accounting for 0.49 million gallons per day (Mgal/d) of fresh-water withdrawals (0.14 Mgal/d of groundwater and 0.35 Mgal/d of surface water) for residential and commercial use and serving 6,645 individuals (49.2 percent of the population). An estimated 6,861 people, (50.8 percent of the population) primarily rely on private wells or other unregulated sources, such as springs, and withdraw 0.55 Mgal/d of groundwater for their residential use. Public water supply in the region is primarily (71.4 percent) derived from springs and augmented by stream withdrawals (backup sources mainly during low-flow periods), with the remaining portion (28.6 percent) derived from groundwater withdrawals from wells. For rural residents, however, 100 percent of their withdrawals are derived from groundwater (wells or springs).</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235121","isbn":"978-1-4113-4541-6","collaboration":"Prepared in cooperation with the West Virginia Department of Environmental Protection, the West Virginia Department of Health & Human Resources, and the Monroe County Commission","usgsCitation":"Kozar, M.D., Doctor, D.H., Jones, W.K., Chien, N., Cox, C.E., Orndorff, R.C., Weary, D.J., Weaver, M.R., McAdoo, M.A., and Parker, M., 2023, Hydrogeology, karst, and groundwater availability of Monroe County, West Virginia: U.S. Geological Survey Scientific Investigations Report 2023–5121, 82 p., https://doi.org/10.3133/sir20235121.","productDescription":"Report: xii, 81 p.; 4 Appendixes, 5 Data 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release","linkHelpText":"Density raster of caves in Monroe County, West Virginia"},{"id":426143,"rank":15,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sir/2023/5121/sir20235121_fig04_plate.pdf","text":"Plate of Figure 4","size":"19.7 MB","linkHelpText":"- Hydrogeologic Map of Monroe County, West Virginia"},{"id":426144,"rank":16,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sir/2023/5121/sir20235121_fig05_plate.pdf","text":"Plate of Figure 5","size":"10.7 MB","linkHelpText":"- Geologic Map of Monroe County, West Virginia"},{"id":423485,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20235121/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2023-5121"},{"id":426145,"rank":17,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sir/2023/5121/sir20235121_fig25_plate.pdf","text":"Plate of Figure 25","size":"1.98 MB","linkHelpText":"- Potentiometric-Surface Map of Monroe County, West Virginia"},{"id":423488,"rank":6,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2023/5121/sir20235121_appendix1.csv","text":"Appendix 1","size":"15.6 KB","linkFileType":{"id":7,"text":"csv"},"linkHelpText":"- Well Depth, Casing, Yield, Water Level, and Specific Capacity Data From County Health Department Well Completion Reports"},{"id":423489,"rank":7,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2023/5121/sir20235121_appendix2.csv","text":"Appendix 2","size":"17.3 KB","linkFileType":{"id":7,"text":"csv"},"linkHelpText":"- Base-flow Data for 83 Sites Measured in September 2019 in Monroe County, West Virginia"},{"id":501160,"rank":18,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_115685.htm","linkFileType":{"id":5,"text":"html"}},{"id":423496,"rank":14,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9TFAN5X","text":"USGS data release","linkHelpText":"Interpolated groundwater levels and altitudes for Monroe County, West Virginia, 2017–2019"},{"id":423495,"rank":13,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9KF9FD2","text":"USGS data release","linkHelpText":"Fluorescein and Rhodamine WT concentration and recovery data for select samples collected in Monroe County, West Virginia, in August and September 2019"},{"id":423491,"rank":9,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2023/5121/sir20235121_appendix4.zip","text":"Appendix 4","size":"14.9 KB","linkFileType":{"id":6,"text":"zip"},"linkHelpText":"- Results of Annual Hydrograph Analyses for Four Major Watersheds in Monroe County and for the Greenbrier River at Alderson, West Virginia"}],"country":"United States","state":"West Virginia","county":"Monroe County","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-80.3074,37.6895],[-80.2773,37.6581],[-80.2649,37.649],[-80.2215,37.6282],[-80.2248,37.6242],[-80.2295,37.6186],[-80.2365,37.6126],[-80.2479,37.6045],[-80.2611,37.5958],[-80.2751,37.5885],[-80.2828,37.5853],[-80.2959,37.5799],[-80.326,37.5667],[-80.3127,37.5463],[-80.3338,37.5368],[-80.307,37.5287],[-80.2946,37.54],[-80.2878,37.5371],[-80.2821,37.5344],[-80.2894,37.5228],[-80.2945,37.5159],[-80.2998,37.5103],[-80.3036,37.5072],[-80.3062,37.5053],[-80.3066,37.505],[-80.3125,37.502],[-80.3183,37.4997],[-80.3293,37.4964],[-80.3437,37.4927],[-80.3518,37.4909],[-80.3553,37.4895],[-80.3594,37.4881],[-80.3646,37.4849],[-80.3663,37.4822],[-80.3662,37.479],[-80.368,37.4768],[-80.3689,37.4759],[-80.3702,37.4749],[-80.3739,37.4731],[-80.3761,37.4722],[-80.3811,37.4703],[-80.3883,37.4676],[-80.4033,37.4617],[-80.4163,37.4559],[-80.4262,37.45],[-80.4357,37.443],[-80.4414,37.4394],[-80.4438,37.4378],[-80.4461,37.4362],[-80.4501,37.4333],[-80.4549,37.4317],[-80.4611,37.4302],[-80.4651,37.4293],[-80.4704,37.4275],[-80.4727,37.427],[-80.4761,37.4269],[-80.4802,37.4283],[-80.4831,37.4319],[-80.486,37.4333],[-80.4884,37.4356],[-80.4901,37.4374],[-80.4905,37.4379],[-80.4919,37.4396],[-80.4936,37.4419],[-80.4942,37.4446],[-80.4939,37.4467],[-80.4937,37.4487],[-80.4931,37.4528],[-80.4932,37.4596],[-80.4954,37.4666],[-80.4984,37.473],[-80.5002,37.4761],[-80.5026,37.4789],[-80.5054,37.4802],[-80.5083,37.481],[-80.5124,37.4806],[-80.5156,37.48],[-80.5182,37.4796],[-80.5309,37.4768],[-80.5407,37.4752],[-80.55,37.4729],[-80.5563,37.4707],[-80.5673,37.4661],[-80.5732,37.4628],[-80.5807,37.4583],[-80.5899,37.4523],[-80.5986,37.4473],[-80.603,37.445],[-80.6052,37.4439],[-80.6077,37.4427],[-80.613,37.4404],[-80.6176,37.4385],[-80.6219,37.4361],[-80.6276,37.4328],[-80.6363,37.4282],[-80.6518,37.4199],[-80.6696,37.4116],[-80.684,37.4056],[-80.7048,37.396],[-80.7052,37.3958],[-80.7198,37.3895],[-80.7248,37.3874],[-80.7307,37.3849],[-80.7423,37.3812],[-80.7507,37.3784],[-80.7531,37.3776],[-80.7629,37.3748],[-80.7709,37.3729],[-80.7757,37.382],[-80.7793,37.3878],[-80.7834,37.3923],[-80.7864,37.3936],[-80.7899,37.3945],[-80.7934,37.3945],[-80.7939,37.3946],[-80.7963,37.3948],[-80.7968,37.395],[-80.7986,37.3954],[-80.8004,37.3963],[-80.8021,37.3981],[-80.8051,37.4012],[-80.8097,37.4062],[-80.8157,37.4115],[-80.8244,37.4168],[-80.8321,37.4222],[-80.8367,37.4248],[-80.842,37.4257],[-80.8451,37.4257],[-80.8484,37.4256],[-80.853,37.4278],[-80.8575,37.4304],[-80.8547,37.4349],[-80.8467,37.4458],[-80.8404,37.4545],[-80.8399,37.4554],[-80.7965,37.5259],[-80.7559,37.5774],[-80.7467,37.5924],[-80.686,37.6798],[-80.6704,37.699],[-80.6688,37.7058],[-80.6625,37.7244],[-80.6631,37.728],[-80.6637,37.7303],[-80.6474,37.729],[-80.6253,37.7219],[-80.6159,37.7201],[-80.5401,37.7005],[-80.5104,37.6929],[-80.507,37.6925],[-80.5029,37.6948],[-80.5006,37.6952],[-80.4982,37.6943],[-80.4959,37.6921],[-80.4924,37.6939],[-80.4883,37.693],[-80.4849,37.6939],[-80.4808,37.6926],[-80.4756,37.6958],[-80.4721,37.6949],[-80.4674,37.694],[-80.4628,37.6927],[-80.4575,37.6877],[-80.4476,37.6868],[-80.4337,37.6928],[-80.4238,37.7005],[-80.4168,37.7019],[-80.414,37.7055],[-80.4093,37.7065],[-80.4053,37.7106],[-80.3971,37.716],[-80.3948,37.716],[-80.3925,37.7133],[-80.3953,37.7056],[-80.3942,37.7047],[-80.3878,37.7079],[-80.382,37.7034],[-80.3825,37.6997],[-80.3831,37.6925],[-80.3778,37.688],[-80.3743,37.6884],[-80.3697,37.6925],[-80.3679,37.693],[-80.3627,37.6907],[-80.3604,37.6921],[-80.354,37.6998],[-80.3523,37.7103],[-80.3518,37.7125],[-80.35,37.7121],[-80.3436,37.7067],[-80.3447,37.6994],[-80.347,37.6953],[-80.3406,37.6894],[-80.326,37.6868],[-80.3156,37.6872],[-80.3139,37.6878],[-80.3115,37.6886],[-80.3094,37.6891],[-80.3074,37.6895]]]},\"properties\":{\"name\":\"Monroe\",\"state\":\"WV\"}}]}","contact":"<p>Director, <a href=\"https://www.usgs.gov/centers/va-wv-water\" data-mce-href=\"https://www.usgs.gov/centers/va-wv-water\">Virginia and West Virginia Water Science Center</a><br>U.S. Geological Survey<br>1730 East Parham Road<br>Richmond, Virginia 23228</p><p><a href=\"https://pubs.er.usgs.gov/contact\" data-mce-href=\"https://pubs.er.usgs.gov/contact\">Contact Pubs Warehouse</a></p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Hydrogeology</li><li>Karst Features</li><li>Groundwater Availability</li><li>Summary</li><li>References Cited</li><li>Appendix 1. Well Depth, Casing, Yield, Water Level, and Specific Capacity Data From County Health Department Well Completion Reports</li><li>Appendix 2. Base-flow Data for 83 Sites Measured in September 2019 in Monroe County, West Virginia</li><li>Appendix 3. Results of Monthly Hydrograph Analyses for Four Major Watersheds in Monroe County and for the Greenbrier River at Alderson, West Virginia</li><li>Appendix 4. Results of Annual Hydrograph Analyses for Four Major Watersheds in Monroe County and for the Greenbrier River at Alderson, West Virginia</li></ul>","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"publishedDate":"2023-12-14","noUsgsAuthors":false,"publicationDate":"2023-12-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Kozar, Mark D. 0000-0001-7755-7657 mdkozar@usgs.gov","orcid":"https://orcid.org/0000-0001-7755-7657","contributorId":1963,"corporation":false,"usgs":true,"family":"Kozar","given":"Mark","email":"mdkozar@usgs.gov","middleInitial":"D.","affiliations":[{"id":37280,"text":"Virginia and West Virginia Water Science Center ","active":true,"usgs":true}],"preferred":true,"id":890052,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Doctor, Daniel H. 0000-0002-8338-9722 dhdoctor@usgs.gov","orcid":"https://orcid.org/0000-0002-8338-9722","contributorId":2037,"corporation":false,"usgs":true,"family":"Doctor","given":"Daniel","email":"dhdoctor@usgs.gov","middleInitial":"H.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":890053,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jones, William K. 0009-0000-9851-3514","orcid":"https://orcid.org/0009-0000-9851-3514","contributorId":332334,"corporation":false,"usgs":false,"family":"Jones","given":"William","email":"","middleInitial":"K.","affiliations":[{"id":79454,"text":"Environmental Data LLC, Warm Springs, VA","active":true,"usgs":false}],"preferred":false,"id":890054,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Chien, Nathan 0009-0001-2274-9085","orcid":"https://orcid.org/0009-0001-2274-9085","contributorId":332335,"corporation":false,"usgs":false,"family":"Chien","given":"Nathan","email":"","affiliations":[{"id":79455,"text":"Previous employee USGS VA-WV WSC","active":true,"usgs":false}],"preferred":false,"id":890055,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cox, Cheyenne E. 0000-0002-5213-7880","orcid":"https://orcid.org/0000-0002-5213-7880","contributorId":332336,"corporation":false,"usgs":false,"family":"Cox","given":"Cheyenne","email":"","middleInitial":"E.","affiliations":[{"id":79456,"text":"former USGS Employee (Florence Bascom)","active":true,"usgs":false}],"preferred":false,"id":890056,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Orndorff, Randall C. 0000-0002-8956-5803 rorndorf@usgs.gov","orcid":"https://orcid.org/0000-0002-8956-5803","contributorId":2739,"corporation":false,"usgs":true,"family":"Orndorff","given":"Randall","email":"rorndorf@usgs.gov","middleInitial":"C.","affiliations":[{"id":501,"text":"Office of Science Quality and Integrity","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":890057,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Weary, David J. 0000-0002-6115-6397 dweary@usgs.gov","orcid":"https://orcid.org/0000-0002-6115-6397","contributorId":545,"corporation":false,"usgs":true,"family":"Weary","given":"David","email":"dweary@usgs.gov","middleInitial":"J.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":890058,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Weaver, Mitchell R. 0000-0003-3099-2285","orcid":"https://orcid.org/0000-0003-3099-2285","contributorId":329366,"corporation":false,"usgs":true,"family":"Weaver","given":"Mitchell","email":"","middleInitial":"R.","affiliations":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"preferred":true,"id":890059,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"McAdoo, Mitchell A. 0000-0002-3895-0816 mmcadoo@usgs.gov","orcid":"https://orcid.org/0000-0002-3895-0816","contributorId":200287,"corporation":false,"usgs":true,"family":"McAdoo","given":"Mitchell","email":"mmcadoo@usgs.gov","middleInitial":"A.","affiliations":[{"id":37280,"text":"Virginia and West Virginia Water Science Center ","active":true,"usgs":true}],"preferred":true,"id":890060,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Parker, Mercer 0000-0001-6683-6458 mercerparker@usgs.gov","orcid":"https://orcid.org/0000-0001-6683-6458","contributorId":203174,"corporation":false,"usgs":true,"family":"Parker","given":"Mercer","email":"mercerparker@usgs.gov","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":890061,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}}
,{"id":70250658,"text":"70250658 - 2023 - Inundation tolerance, rather than drought tolerance, predicts riparian plant distributions along a local hydrologic gradient","interactions":[],"lastModifiedDate":"2023-12-22T13:05:59.003272","indexId":"70250658","displayToPublicDate":"2023-12-14T07:04:44","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3750,"text":"Wetlands","onlineIssn":"1943-6246","printIssn":"0277-5212","active":true,"publicationSubtype":{"id":10}},"title":"Inundation tolerance, rather than drought tolerance, predicts riparian plant distributions along a local hydrologic gradient","docAbstract":"<div id=\"Abs1-section\" class=\"c-article-section\"><div id=\"Abs1-content\" class=\"c-article-section__content\"><p>Riparian vegetation varies along hydrologic gradients, along which inundation and drought tend to be inversely correlated. Differentiating effects of inundation and drought on plant distributions is critical for predicting impacts of changes to baseflows and designing flow patterns to achieve vegetation objectives in regulated river systems. To this end, we conducted a greenhouse experiment where we decreased, increased, or maintained constant water levels experienced by a suite of riparian plant species. We related changes in new root growth and stomatal conductance under experimental conditions to species hydrologic niches in the field, specifically the median elevation at which they occur above the channel, along the regulated Colorado River in Grand Canyon. We found a significant negative relationship between root growth response to experimental inundation with increasing elevation above the channel in the field, and a negative response of stomatal conductance to inundation among the most xeric-adapted species. Drought responses were idiosyncratic with respect to hydrologic niche, and instead seemed to vary in relation to clonality and rooting depth. Several Salicaceae tree species that are uncommon along regulated rivers exhibited consistently negative responses to both drought and inundation relative to other species, which may explain their rarity. The results of this study suggest that riparian plant distributions along hydrologic gradients have been shaped primarily by current and past levels of inundation. However, future anticipated declines in the water table are likely to produce species-specific responses based on drought tolerance that may in part be predicted from the results of this experiment.</p></div></div>","language":"English","publisher":"Springer","doi":"10.1007/s13157-023-01730-2","usgsCitation":"Butterfield, B.J., and Palmquist, E.C., 2023, Inundation tolerance, rather than drought tolerance, predicts riparian plant distributions along a local hydrologic gradient: Wetlands, v. 44, no. 6, 6, 12 p., https://doi.org/10.1007/s13157-023-01730-2.","productDescription":"6, 12 p.","ipdsId":"IP-152535","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":423861,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"44","issue":"6","noUsgsAuthors":false,"publicationDate":"2023-12-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Butterfield, Bradley J. 0000-0003-0974-9811","orcid":"https://orcid.org/0000-0003-0974-9811","contributorId":167009,"corporation":false,"usgs":false,"family":"Butterfield","given":"Bradley","email":"","middleInitial":"J.","affiliations":[{"id":24591,"text":"Merriam-Powell Center for Environmental Research and Department of Biological Sciences, Northern Arizona University, Flagstaff, AZ, USA","active":true,"usgs":false}],"preferred":false,"id":890907,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Palmquist, Emily C. 0000-0003-1069-2154 epalmquist@usgs.gov","orcid":"https://orcid.org/0000-0003-1069-2154","contributorId":5669,"corporation":false,"usgs":true,"family":"Palmquist","given":"Emily","email":"epalmquist@usgs.gov","middleInitial":"C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":890906,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70251283,"text":"70251283 - 2023 - Unprecedented distribution data for Joshua trees (Yucca brevifolia and Y. jaegeriana) reveal contemporary climate associations of a Mojave Desert icon","interactions":[],"lastModifiedDate":"2024-02-02T12:42:56.771463","indexId":"70251283","displayToPublicDate":"2023-12-14T06:37:17","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":17146,"text":"Frontiers Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Unprecedented distribution data for Joshua trees (Yucca brevifolia and Y. jaegeriana) reveal contemporary climate associations of a Mojave Desert icon","docAbstract":"<div class=\"JournalAbstract\"><p><strong>Introduction:</strong><span>&nbsp;</span>Forecasting range shifts in response to climate change requires accurate species distribution models (SDMs), particularly at the margins of species' ranges. However, most studies producing SDMs rely on sparse species occurrence datasets from herbarium records and public databases, along with random pseudoabsences. While environmental covariates used to fit SDMS are increasingly precise due to satellite data, the availability of species occurrence records is still a large source of bias in model predictions. We developed distribution models for hybridizing sister species of western and eastern Joshua trees (<i>Yucca brevifolia</i><span>&nbsp;</span>and<span>&nbsp;</span><i>Y. jaegeriana</i>, respectively), iconic Mojave Desert species that are threatened by climate change and habitat loss.</p><p><strong>Methods:</strong><span>&nbsp;</span>We conducted an intensive visual grid search of online satellite imagery for 672,043 0.25 km<sup>2</sup><span>&nbsp;</span>grid cells to identify the two species' presences and absences on the landscape with exceptional resolution, and field validated 29,050 cells in 15,001 km of driving. We used the resulting presence/absence data to train SDMs for each Joshua tree species, revealing the contemporary environmental gradients (during the past 40 years) with greatest influence on the current distribution of adult trees.</p><p><strong>Results:</strong><span>&nbsp;</span>While the environments occupied by<span>&nbsp;</span><i>Y. brevifolia</i><span>&nbsp;</span>and<span>&nbsp;</span><i>Y. jaegeriana</i><span>&nbsp;</span>were similar in total aridity, they differed with respect to seasonal precipitation and temperature ranges, suggesting the two species may have differing responses to climate change. Moreover, the species showed differing potential to occupy each other's geographic ranges: modeled potential habitat for<span>&nbsp;</span><i>Y. jaegeriana</i><span>&nbsp;</span>extends throughout the range of<span>&nbsp;</span><i>Y. brevifolia</i>, while potential habitat for<span>&nbsp;</span><i>Y. brevifolia</i><span>&nbsp;</span>is not well represented within the range of<span>&nbsp;</span><i>Y. jaegeriana</i>.</p><p><strong>Discussion:</strong><span>&nbsp;</span>By reproducing the current range of the Joshua trees with high fidelity, our dataset can serve as a baseline for future research, monitoring, and management of this species, including an increased understanding of dynamics at the trailing and leading margins of the species' ranges and potential for climate refugia.</p></div>","language":"English","publisher":"Frontiers","doi":"10.3389/fevo.2023.1266892","usgsCitation":"Esque, T., Shryock, D., Berr, G.A., Chen, F., DeFalco, L., Lewicki, S.M., Cunningham, B.L., Gaylord, E.J., Poage, C.S., Gantz, G.E., Van Gaalen, R.A., Gottsacker, B.O., Mcdonald, A.M., Yoder, J., Smith, C., and Nussear, K., 2023, Unprecedented distribution data for Joshua trees (Yucca brevifolia and Y. jaegeriana) reveal contemporary climate associations of a Mojave Desert icon: Frontiers Ecology and Evolution, v. 11, 1266892, 20 p., https://doi.org/10.3389/fevo.2023.1266892.","productDescription":"1266892, 20 p.","ipdsId":"IP-159615","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":441412,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fevo.2023.1266892","text":"Publisher Index Page"},{"id":425278,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -120.58014768204356,\n              38.89373609553763\n            ],\n            [\n              -120.58014768204356,\n              32.02965081218825\n            ],\n            [\n              -111.08796018204377,\n              32.02965081218825\n            ],\n            [\n              -111.08796018204377,\n              38.89373609553763\n            ],\n            [\n              -120.58014768204356,\n              38.89373609553763\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"11","noUsgsAuthors":false,"publicationDate":"2023-12-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Esque, Todd 0000-0002-4166-6234 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0009-0004-1531-7761","orcid":"https://orcid.org/0009-0004-1531-7761","contributorId":333759,"corporation":false,"usgs":false,"family":"Berr","given":"Gabrielle","email":"","middleInitial":"A.","affiliations":[{"id":24583,"text":"former USGS employee","active":true,"usgs":false}],"preferred":false,"id":893851,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"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":893852,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"DeFalco, Lesley A. 0000-0002-7542-9261","orcid":"https://orcid.org/0000-0002-7542-9261","contributorId":208658,"corporation":false,"usgs":true,"family":"DeFalco","given":"Lesley A.","affiliations":[{"id":651,"text":"Western Ecological Research 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,{"id":70251037,"text":"70251037 - 2023 - Identifying invasive species threats, pathways, and impacts to improve biosecurity","interactions":[],"lastModifiedDate":"2024-01-18T12:39:27.872516","indexId":"70251037","displayToPublicDate":"2023-12-14T06:36:39","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Identifying invasive species threats, pathways, and impacts to improve biosecurity","docAbstract":"<div class=\"abstract-group  metis-abstract\"><div class=\"article-section__content en main\"><p>Managing invasive species with prevention and early-detection strategies can avert severe ecological and economic impacts. Horizon scanning, an evidence-based process combining risk screening and consensus building to identify threats, has become a valuable tool for prioritizing invasive species management and prevention. We assembled a working group of experts from academic, government, and nonprofit agencies and organizations, and conducted a multi-taxa horizon scan for Florida, USA, the first of its kind in North America. Our primary objectives were to identify high-risk species and their introduction pathways, to detail the magnitude and mechanism of potential impacts, and, more broadly, to demonstrate the utility of horizon scanning. As a means to facilitate future horizon scans, we document the process used to generate the list of taxa for screening. We evaluated 460 taxa for their potential to arrive, establish, and cause negative ecological and socioeconomic impacts, and identified 40 potential invaders, including alewife, zebra mussel, crab-eating macaque, and red swamp crayfish. Vertebrates and aquatic invertebrates posed the greatest invasion threat, over half of the high-risk taxa were omnivores, and there was high confidence in the scoring of high-risk taxa. Common arrival pathways were ballast water, biofouling of vessels, and escape from the pet/aquarium/horticulture trade. Competition, predation, and damage to agriculture/forestry/aquaculture were common impact mechanisms. We recommend full risk analysis for the high-risk taxa; increased surveillance at Florida's ports, state borders, and high-risk pathways; and periodic review and revision of the list. Few horizon scans detail the comprehensive methodology (including list-building), certainty estimates for all scoring categories and the final score, detailed pathways, and the magnitude and mechanism of impact. Providing this information can further inform prevention efforts and can be efficiently replicated in other regions. Moreover, harmonizing methodology can facilitate data sharing and enhance interpretation of results for stakeholders and the general public.</p></div></div>","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.4711","usgsCitation":"Lieurance, D., Canavan, S., Behringer, D.C., Kendig, A., Minteer, C.R., Reisinger, L.S., Romagosa, C.M., Flory, S., Lockwood, J.L., Anderson, P., Baker, S.M., Bojko, J., Bowers, K.E., Canavan, K., Carruthers, K., Daniel, W., Gordon, D.R., Hill, J.E., Howeth, J., Iannone, B., Jennings, L., Gettys, L., Kariuki, E.M., Kunzer, J.M., Laughinghouse, H.D., Mandrak, N.E., McCann, S., Morawo, T., Morningstar, C.R., Neilson, M., Petri, T., Pfingsten, I., Reed, R., Walters, L., and Wanamaker, C., 2023, Identifying invasive species threats, pathways, and impacts to improve biosecurity: Ecosphere, v. 14, no. 12, e4711, 16 p., https://doi.org/10.1002/ecs2.4711.","productDescription":"e4711, 16 p.","ipdsId":"IP-156894","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":441415,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.4711","text":"Publisher Index Page"},{"id":424583,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"14","issue":"12","noUsgsAuthors":false,"publicationDate":"2023-12-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Lieurance, Deah 0000-0001-8176-3146","orcid":"https://orcid.org/0000-0001-8176-3146","contributorId":293605,"corporation":false,"usgs":false,"family":"Lieurance","given":"Deah","email":"","affiliations":[{"id":63333,"text":"Agronomy Department, University of Florida","active":true,"usgs":false}],"preferred":false,"id":892816,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Canavan, Susan 0000-0002-7972-7928","orcid":"https://orcid.org/0000-0002-7972-7928","contributorId":293598,"corporation":false,"usgs":false,"family":"Canavan","given":"Susan","email":"","affiliations":[{"id":63333,"text":"Agronomy Department, University of Florida","active":true,"usgs":false}],"preferred":false,"id":892817,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Behringer, Donald C.","contributorId":333440,"corporation":false,"usgs":false,"family":"Behringer","given":"Donald","email":"","middleInitial":"C.","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":892818,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kendig, Amy E.","contributorId":333442,"corporation":false,"usgs":false,"family":"Kendig","given":"Amy E.","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":892819,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Minteer, Carey R.","contributorId":333444,"corporation":false,"usgs":false,"family":"Minteer","given":"Carey","email":"","middleInitial":"R.","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":892820,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Reisinger, Lindsey S.","contributorId":333446,"corporation":false,"usgs":false,"family":"Reisinger","given":"Lindsey","email":"","middleInitial":"S.","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":892821,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Romagosa, Christina M.","contributorId":200925,"corporation":false,"usgs":false,"family":"Romagosa","given":"Christina","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":892822,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Flory, S. 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,{"id":70256559,"text":"70256559 - 2023 - Effect of straying, reproductive strategies, and ocean distribution on the structure of American shad populations","interactions":[],"lastModifiedDate":"2024-08-16T11:38:31.421824","indexId":"70256559","displayToPublicDate":"2023-12-14T06:17:46","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Effect of straying, reproductive strategies, and ocean distribution on the structure of American shad populations","docAbstract":"<div class=\"abstract-group  metis-abstract\"><div class=\"article-section__content en main\"><p>The use of species distribution models has proliferated, providing insights for sustainable management of migratory species in a globally changing environment. However, many of these models are based on statistical relationships developed from historical conditions that may not perform well under changing or even analogous conditions caused by climate change. In this paper, we used a mechanistic species distribution model called GR3D (Global Repositioning Dynamics for Diadromous Fish Distribution) to examine the integrated dynamics of American shad (<i>Alosa sapidissima</i>) populations across their native range along the Eastern U.S. coast, where the species demonstrates latitudinal variations in life histories and reproductive strategies. The initial design of the model was adapted to incorporate region-specific parameterization to fit the species ecology. Then, a sensitivity analysis was performed to test the influences of uncertain processes regarding American shad distribution at sea, straying and reproduction on key characteristics of the species distribution. The sensitivity analysis showed the influence of the Allee effect (i.e., “depensatory” process) and the homing rate (i.e., fidelity to the breeding sites) on the probability of presence and abundances among catchments and metapopulations estimated by the model. Contrary to the homing rate, the distance of straying did not change the estimated number of metapopulations or abundances. Homing strength, however, was quite influential. The integration of complex migration patterns during the marine phase (i.e., wintering and summering offshore areas) provided more likely estimates of the species' overall distribution. Overall, our study illustrated the utility of incorporating factors governing the large-scale distribution of migratory species to improve local management.</p></div></div>","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.4712","usgsCitation":"Poulet, C., Lassalle, G., Jordaan, A., Limburg, K., Nack, C.C., Nye, J.A., O’Malley, A., O’Malley-Barber, B., Stich, D.S., Waldman, J., Zydlewski, J.D., and Lambert, P., 2023, Effect of straying, reproductive strategies, and ocean distribution on the structure of American shad populations: Ecosphere, v. 14, no. 12, e4712, 21 p., https://doi.org/10.1002/ecs2.4712.","productDescription":"e4712, 21 p.","ipdsId":"IP-147500","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":441419,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.4712","text":"Publisher Index Page"},{"id":432849,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -85.25384275260296,\n              23.589986588351152\n            ],\n            [\n              -59.41399900260346,\n              23.589986588351152\n            ],\n            [\n              -59.41399900260346,\n              51.4169004286193\n            ],\n            [\n              -85.25384275260296,\n              51.4169004286193\n            ],\n            [\n              -85.25384275260296,\n              23.589986588351152\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  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Amherst","active":true,"usgs":false}],"preferred":false,"id":907980,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Limburg, Karin E.","contributorId":341130,"corporation":false,"usgs":false,"family":"Limburg","given":"Karin E.","affiliations":[{"id":12623,"text":"State University of New York College of Environmental Science and Forestry","active":true,"usgs":false}],"preferred":false,"id":907981,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Nack, Christopher C.","contributorId":341131,"corporation":false,"usgs":false,"family":"Nack","given":"Christopher","email":"","middleInitial":"C.","affiliations":[{"id":62153,"text":"Ramboll","active":true,"usgs":false}],"preferred":false,"id":907982,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Nye, Janet A.","contributorId":341132,"corporation":false,"usgs":false,"family":"Nye","given":"Janet","email":"","middleInitial":"A.","affiliations":[{"id":55603,"text":"University of North Carolina Chapel Hill","active":true,"usgs":false}],"preferred":false,"id":907983,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"O’Malley, Andrew","contributorId":341133,"corporation":false,"usgs":false,"family":"O’Malley","given":"Andrew","affiliations":[{"id":81706,"text":"Gomez and Sullivan Engineers","active":true,"usgs":false}],"preferred":false,"id":907984,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"O’Malley-Barber, Betsy","contributorId":341134,"corporation":false,"usgs":false,"family":"O’Malley-Barber","given":"Betsy","email":"","affiliations":[{"id":81706,"text":"Gomez and Sullivan Engineers","active":true,"usgs":false}],"preferred":false,"id":907985,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Stich, Dan S.","contributorId":341135,"corporation":false,"usgs":false,"family":"Stich","given":"Dan","email":"","middleInitial":"S.","affiliations":[{"id":81707,"text":"State University of New York Oneonta","active":true,"usgs":false}],"preferred":false,"id":907986,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Waldman, John R.","contributorId":341136,"corporation":false,"usgs":false,"family":"Waldman","given":"John R.","affiliations":[{"id":32856,"text":"Queens College","active":true,"usgs":false}],"preferred":false,"id":907987,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Zydlewski, Joseph D. 0000-0002-2255-2303 jzydlewski@usgs.gov","orcid":"https://orcid.org/0000-0002-2255-2303","contributorId":2004,"corporation":false,"usgs":true,"family":"Zydlewski","given":"Joseph","email":"jzydlewski@usgs.gov","middleInitial":"D.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":false,"id":907988,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Lambert, Patrick","contributorId":341137,"corporation":false,"usgs":false,"family":"Lambert","given":"Patrick","affiliations":[{"id":81705,"text":"INRAe","active":true,"usgs":false}],"preferred":false,"id":907989,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}}
,{"id":70266207,"text":"70266207 - 2023 - Examining the effect of environmental variability on the viability of endangered Steller sea lions using an integrated population model","interactions":[],"lastModifiedDate":"2025-04-30T15:45:29.630755","indexId":"70266207","displayToPublicDate":"2023-12-14T00:00:00","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1497,"text":"Endangered Species Research","active":true,"publicationSubtype":{"id":10}},"title":"Examining the effect of environmental variability on the viability of endangered Steller sea lions using an integrated population model","docAbstract":"Understanding spatio-temporal variability in demography and the influence of environmental conditions offers insight into the factors underlying population dynamics. This is particularly true for species with divergent demographic patterns across large geographic areas. The contrasting abundance trends observed across the range of Steller sea lions (Eumetopias jubatus) have been studied extensively, with research suggesting that the primary drivers of localized population dynamics vary over time and space. We developed a Bayesian integrated population model for the endangered western distinct population segment of Steller sea lions that combines mark-recapture and count data from 2000-2021 to estimate demographic rates, abundance trends, and the effects of environmental variability on population growth. Our results highlight subregional demographic differences, including reduced pup survival in the central Aleutian Islands and reduced yearling survival west of Samalga Pass. Range-wide abundance increased by 1.7% yr-1 (95% credible interval: 0.14; 3.4%) over the study period, with a positive annual growth rate of 3.0% (1.1; 5.1%) yr-1 east of Samalga Pass, a negative growth rate of -2.1% (-4.6; 0.5%) yr-1 west of Samalga Pass, and an overall low probability of local extirpation (<2%) in 100 years even in subregions experiencing continued decline. The effect of environmental variability on population growth varied depending on subpopulation size and vital rates and was strongest in the area of greatest decline. Our model improves upon existing approaches for estimating abundance, accounts for environmental variability within the viability analysis, and can facilitate evaluating the efficacy of conservation actions and progress toward recovery goals.","language":"English","publisher":"Inter-Research","doi":"10.3354/esr01282","usgsCitation":"Warlick, A., Johnson, D., Sweeney, K., Gelatt, T., and Converse, S.J., 2023, Examining the effect of environmental variability on the viability of endangered Steller sea lions using an integrated population model: Endangered Species Research, v. 52, p. 343-361, https://doi.org/10.3354/esr01282.","productDescription":"19 p.","startPage":"343","endPage":"361","ipdsId":"IP-151798","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":487889,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3354/esr01282","text":"Publisher Index Page"},{"id":485208,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -192.3038114894406,\n              57.51067207764723\n            ],\n            [\n              -192.3038114894406,\n              51.43442138881829\n            ],\n            [\n              -154.88087376804862,\n              51.43442138881829\n            ],\n            [\n              -154.88087376804862,\n              57.51067207764723\n            ],\n            [\n              -192.3038114894406,\n              57.51067207764723\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"52","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Warlick, Amanda J.","contributorId":353988,"corporation":false,"usgs":false,"family":"Warlick","given":"Amanda J.","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":934927,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Johnson, Devin S.","contributorId":353989,"corporation":false,"usgs":false,"family":"Johnson","given":"Devin S.","affiliations":[{"id":36612,"text":"National Marine Fisheries Service","active":true,"usgs":false}],"preferred":false,"id":934928,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sweeney, Katie L.","contributorId":353990,"corporation":false,"usgs":false,"family":"Sweeney","given":"Katie L.","affiliations":[{"id":36612,"text":"National Marine Fisheries Service","active":true,"usgs":false}],"preferred":false,"id":934929,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gelatt, Tom S.","contributorId":353991,"corporation":false,"usgs":false,"family":"Gelatt","given":"Tom S.","affiliations":[{"id":36612,"text":"National Marine Fisheries Service","active":true,"usgs":false}],"preferred":false,"id":934930,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Converse, Sarah J. 0000-0002-3719-5441 sconverse@usgs.gov","orcid":"https://orcid.org/0000-0002-3719-5441","contributorId":173772,"corporation":false,"usgs":true,"family":"Converse","given":"Sarah","email":"sconverse@usgs.gov","middleInitial":"J.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":934931,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70250431,"text":"sir20235120 - 2023 - Assessment of prerestoration water quality in the Herring River to support adaptive management at the Cape Cod National Seashore","interactions":[],"lastModifiedDate":"2026-03-13T15:38:37.170287","indexId":"sir20235120","displayToPublicDate":"2023-12-13T11:20:00","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":"2023-5120","displayTitle":"Assessment of Prerestoration Water Quality in the Herring River To Support Adaptive Management at the Cape Cod National Seashore","title":"Assessment of prerestoration water quality in the Herring River to support adaptive management at the Cape Cod National Seashore","docAbstract":"<p>In 2020 and 2021, the U.S. Geological Survey, Cape Cod National Seashore of the National Park Service, and Friends of Herring River cooperated to assess nutrient and suspended sediment concentrations across the ocean-estuary boundary at a dike on the Herring River on Chequessett Neck Road in Wellfleet, Massachusetts, that has restricted saltwater inputs by regulating water inflow through three culverts or sluiceways into the watershed for more than 100 years. The dike is slated to be removed, and the purpose of this project was to characterize natural variability of nutrient and suspended sediment concentration during flood tide and ebb tide conditions at the dike based on seasonal and environmental variables. This baseline can be used to assess if removal of the dike is likely to result in measurable changes in water quality.</p><p>Data from the current [2023] study were aggregated with previously published data from November 2015 through September 2018 to provide a long-term record. Samples for the current [2023] study were collected from flood and following ebb tides approximately twice per month from June 2020 through December 2021 at fixed time intervals after the beginning of the tides. Samples were analyzed for nitrate plus nitrite, ammonium, total dissolved nitrogen, total nitrogen, orthophosphate, total dissolved phosphorus, total phosphorus, silica, dissolved organic carbon, and suspended sediment. Constituent concentrations generally were lower using fixed time sampling than in previous studies that used flow-weighted composite sampling, except for nitrate plus nitrite and orthophosphate. Concentrations of nitrate plus nitrite, ammonium, total nitrogen, total dissolved nitrogen, silica, and dissolved organic nitrogen generally were higher on the ebb tide than on the flood tide. By contrast, concentrations of orthophosphate, total phosphorus, and total dissolved phosphorus were generally similar between flood and ebb tides.</p><p>Most nutrient concentrations except silica and ammonium varied seasonally on flood and ebb tides. Phosphorus species, total nitrogen, and dissolved organic carbon concentrations generally peaked in mid- to late summer and were lowest in winter. For nitrate, the reverse was true. Nutrient concentrations generally were higher on the ebb tide than on the flood tide except for total dissolved phosphorus and total phosphorus where differences between flood and ebb tide depended on season. Constituent concentrations were similar between spring, neap, and midamplitude tides on both the flood and ebb tides.</p><p>Nitrate, ammonium, total nitrogen, and silica concentrations were positively correlated with precipitation and runoff. Orthophosphate, total dissolved phosphorus, total phosphorus, and dissolved organic carbon were positively correlated with surface air temperature, downwelling shortwave radiation, and ocean water temperature. Nitrate, ammonium, and silica concentration were negatively correlated with surface air temperature and ocean water temperature. Orthophosphate and total dissolved phosphorus were negatively correlated with runoff. Nitrate plus nitrite, ammonium, and silica concentrations were negatively correlated with downwelling shortwave radiation.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235120","collaboration":"Prepared in cooperation with the National Park Service and the Friends of Herring River","usgsCitation":"Huntington, T.G., 2023, Assessment of prerestoration water quality in the Herring River to support adaptive management at the Cape Cod National Seashore: U.S. Geological Survey Scientific Investigations Report 2023–5120, 51 p., https://doi.org/10.3133/sir20235120.","productDescription":"Report: viii, 51 p.; Data Release; 2 Appendixes","numberOfPages":"51","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-143243","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":501158,"rank":9,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_115686.htm","linkFileType":{"id":5,"text":"html"}},{"id":423334,"rank":8,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9ZU5YHW","text":"USGS data release","linkHelpText":"Data supporting analysis of relations between nutrient concentrations in the Herring River on the ebb tide, near Wellfleet, Massachusetts, and environmental conditions, 2015–2022"},{"id":423333,"rank":7,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2023/5120/sir20235120_appendix3.pdf","text":"Appendix 3","size":"96.1 KB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Alert and Preliminary Guidance for Addressing Nitrogen Contamination of Pall Versapor GWV High-Capacity Capsule Filters"},{"id":423332,"rank":6,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2023/5120/sir20235120_appendix2.pdf","text":"Appendix 2","size":"19.3 KB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Field Methods—Interim Announcement for Change in Capsule-Filter Type, Supplier, and Instructions for Use"},{"id":423331,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2023/5120/images/"},{"id":423330,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2023/5120/sir20235120.XML"},{"id":423329,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20235120/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2023-5120"},{"id":423328,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2023/5120/sir20235120.pdf","text":"Report","size":"6.34 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2023-5120"},{"id":423327,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2023/5120/coverthb.jpg"}],"country":"United States","state":"Massachusetts","otherGeospatial":"Herring River","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -70.07530273023929,\n              41.972935131526725\n            ],\n            [\n              -70.07530273023929,\n              41.92351733741285\n            ],\n            [\n              -70.00976667801922,\n              41.92351733741285\n            ],\n            [\n              -70.00976667801922,\n              41.972935131526725\n            ],\n            [\n              -70.07530273023929,\n              41.972935131526725\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","contact":"<p><a href=\"mailto:dc_nweng@usgs.gov\" data-mce-href=\"mailto:dc_nweng@usgs.gov\">Director</a>, <a href=\"https://www.usgs.gov/centers/new-england-water\" data-mce-href=\"https://www.usgs.gov/centers/new-england-water\">New England Water Science Center</a><br>U.S. Geological Survey<br>10 Bearfoot Road<br>Northborough, MA 01532</p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Methods</li><li>Results</li><li>Summary</li><li>References Cited</li><li>Appendix 1. Monthly Average Concentrations of Contaminants and Climatic Conditions on the Herring River at Near Wellfleet, Massachusetts</li><li>Appendix 2. Field Methods—Interim Announcement for Change in Capsule-Filter Type, Supplier, and Instructions for Use</li><li>Appendix 3. Alert and Preliminary Guidance for Addressing Nitrogen Contamination of Pall Versapor GWV High-Capacity Capsule Filters</li></ul>","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"publishedDate":"2023-12-13","noUsgsAuthors":false,"publicationDate":"2023-12-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Huntington, Thomas G. 0000-0002-9427-3530","orcid":"https://orcid.org/0000-0002-9427-3530","contributorId":218737,"corporation":false,"usgs":true,"family":"Huntington","given":"Thomas G.","affiliations":[{"id":371,"text":"Maine Water Science Center","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":889897,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70249975,"text":"fs20233048 - 2023 - Characterizing urban heat islands across 50 major cities in the United States","interactions":[],"lastModifiedDate":"2026-02-09T17:51:15.965521","indexId":"fs20233048","displayToPublicDate":"2023-12-13T10:29:45","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2023-3048","displayTitle":"Characterizing Urban Heat Islands Across 50 Major Cities in the United States","title":"Characterizing urban heat islands across 50 major cities in the United States","docAbstract":"<p><span data-ogsb=\"white\" data-ogsc=\"black\">Urban development and associated land-cover and land-use change alters the environment. The continued increase of developed land changes the Earth’s ecosystems and affects the resources provided to society. During the last 40 years, urban population in the United States has increased by more than 6.3 percent, and more than 80 percent of the U.S. population resides in urban areas. One of the changes associated with urbanization is the change of landscape features to structures such as buildings, roads, and other infrastructure that absorb and re-emit the heat of the sun more than natural landscapes such as forests and water bodies. This land-cover transition can result in an urban surface temperature that is higher than in a non-urban area, which is defined as a surface urban heat island (SUHI). A SUHI has a profound effect on the lives of urban residents and can exacerbate the risk of heat-related mortality associated with global climate change. The change of urban landscapes and climate conditions can affect the SUHI intensity. The U.S. Geological Survey (USGS) has developed a dataset of SUHI intensity and change from 1985 to 2020 over 50 cities in the United States using Landsat surface temperature (ST) and land</span><span data-ogsb=\"white\" data-ogsc=\"black\">-</span><span data-ogsb=\"white\" data-ogsc=\"black\">cover data. The data</span><span data-ogsb=\"white\" data-ogsc=\"black\">&nbsp;</span><span data-ogsb=\"white\" data-ogsc=\"black\">reveal</span><span data-ogsb=\"white\" data-ogsc=\"black\">&nbsp;SUHI spatial distributions and temporal trends in these cities. The 50-city mean SUHI intensity</span><span data-ogsb=\"white\" data-ogsc=\"black\">&nbsp;</span><span data-ogsb=\"white\" data-ogsc=\"black\">reaches</span><span data-ogsb=\"rgb(255, 128, 0)\" data-ogsc=\"black\">&nbsp;</span><span data-ogsb=\"white\" data-ogsc=\"black\">2.88 degrees Celsius (°C) (5.19 degrees Fahrenheit [°F]) and an</span><span data-ogsb=\"white\" data-ogsc=\"black\">&nbsp;</span><span data-ogsb=\"white\" data-ogsc=\"black\">average</span><span data-ogsb=\"white\" data-ogsc=\"black\">&nbsp;trend of 0.32 °C per decade (0.58 °F per decade). The data also provide spatial distributions of hotspots where annual mean ST is higher than in the surrounding areas that have the same urban land-cover type and high ST that repeated more than 50 percent of the time during 1985–2020 for 50 cities.</span></p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20233048","usgsCitation":"Xian, G.Z., 2023, Characterizing urban heat islands across 50 major cities in the United States: U.S. Geological Survey Fact Sheet 2023–3048, 4 p., https://doi.org/10.3133/fs20233048.","productDescription":"Report: 4 p.; Data Release","numberOfPages":"4","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-156869","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":422482,"rank":6,"type":{"id":39,"text":"HTML 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       [\n                -76.82003,\n                43.62878\n              ],\n              [\n                -76.5,\n                44.01846\n              ],\n              [\n                -76.375,\n                44.09631\n              ],\n              [\n                -75.31821,\n                44.81645\n              ],\n              [\n                -74.867,\n                45.00048\n              ],\n              [\n                -73.34783,\n                45.00738\n              ],\n              [\n                -71.50506,\n                45.0082\n              ],\n              [\n                -71.405,\n                45.255\n              ],\n              [\n                -71.08482,\n                45.30524\n              ],\n              [\n                -70.66,\n                45.46\n              ],\n              [\n                -70.305,\n                45.915\n              ],\n              [\n                -69.99997,\n                46.69307\n              ],\n              [\n                -69.23722,\n                47.44778\n              ],\n              [\n                -68.905,\n                47.185\n              ],\n              [\n                -68.23444,\n                47.35486\n              ],\n              [\n                -67.79046,\n                47.06636\n              ],\n              [\n                -67.79134,\n                45.70281\n              ],\n              [\n                -67.13741,\n                45.13753\n              ],\n              [\n                -66.96466,\n                44.8097\n              ],\n              [\n                -68.03252,\n                44.3252\n              ],\n              [\n                -69.06,\n                43.98\n              ],\n              [\n                -70.11617,\n                43.68405\n              ],\n              [\n                -70.64548,\n                43.09024\n              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        41.22065\n              ],\n              [\n                -73.71,\n                40.9311\n              ],\n              [\n                -72.24126,\n                41.11948\n              ],\n              [\n                -71.945,\n                40.93\n              ],\n              [\n                -73.345,\n                40.63\n              ],\n              [\n                -73.982,\n                40.628\n              ],\n              [\n                -73.95232,\n                40.75075\n              ],\n              [\n                -74.25671,\n                40.47351\n              ],\n              [\n                -73.96244,\n                40.42763\n              ],\n              [\n                -74.17838,\n                39.70926\n              ],\n              [\n                -74.90604,\n                38.93954\n              ],\n              [\n                -74.98041,\n                39.1964\n              ],\n              [\n                -75.20002,\n                39.24845\n              ],\n              [\n                -75.52805,\n                39.4985\n              ],\n              [\n                -75.32,\n                38.96\n              ],\n              [\n                -75.07183,\n                38.78203\n              ],\n              [\n                -75.05673,\n                38.40412\n              ],\n              [\n                -75.37747,\n                38.01551\n              ],\n              [\n                -75.94023,\n                37.21689\n              ],\n              [\n                -76.03127,\n                37.2566\n              ],\n              [\n                -75.72205,\n                37.93705\n              ],\n              [\n                -76.23287,\n                38.31921\n              ],\n              [\n                -76.35,\n                39.15\n              ],\n              [\n                -76.54272,\n                38.71762\n              ],\n              [\n                -76.32933,\n                38.08326\n              ],\n              [\n                -76.99,\n                38.23999\n              ],\n              [\n                -76.30162,\n                37.91794\n              ],\n              [\n                -76.25874,\n                36.9664\n              ],\n              [\n                -75.9718,\n                36.89726\n              ],\n              [\n                -75.86804,\n                36.55125\n              ],\n              [\n                -75.72749,\n                35.55074\n              ],\n              [\n                -76.36318,\n                34.80854\n              ],\n              [\n                -77.39763,\n                34.51201\n              ],\n              [\n                -78.05496,\n                33.92547\n              ],\n              [\n                -78.55435,\n                33.86133\n              ],\n              [\n                -79.06067,\n                33.49395\n              ],\n              [\n                -79.20357,\n                33.15839\n              ],\n              [\n                -80.30132,\n                32.50935\n              ],\n              [\n                -80.86498,\n                32.0333\n              ],\n              [\n                -81.33629,\n                31.44049\n              ],\n              [\n                -81.49042,\n                30.72999\n              ],\n              [\n                -81.31371,\n                30.03552\n              ],\n              [\n                -80.98,\n                29.18\n              ],\n              [\n                -80.53558,\n                28.47213\n              ],\n              [\n                -80.53,\n                28.04\n              ],\n              [\n                -80.05654,\n                26.88\n              ],\n              [\n                -80.08801,\n                26.20576\n              ],\n              [\n                -80.13156,\n                25.81677\n              ],\n              [\n                -80.38103,\n                25.20616\n              ],\n              [\n                -80.68,\n                25.08\n              ],\n              [\n                -81.17213,\n                25.20126\n              ],\n              [\n                -81.33,\n                25.64\n              ],\n              [\n                -81.71,\n                25.87\n              ],\n              [\n                -82.24,\n                26.73\n              ],\n              [\n                -82.70515,\n                27.49504\n              ],\n              [\n                -82.85526,\n                27.88624\n              ],\n              [\n                -82.65,\n                28.55\n              ],\n              [\n                -82.93,\n                29.1\n              ],\n              [\n                -83.70959,\n                29.93656\n              ],\n              [\n                -84.1,\n                30.09\n              ],\n              [\n                -85.10882,\n                29.63615\n              ],\n              [\n                -85.28784,\n                29.68612\n              ],\n              [\n                -85.7731,\n                30.15261\n              ],\n              [\n                -86.4,\n                30.4\n              ],\n              [\n                -87.53036,\n                30.27433\n              ],\n              [\n                -88.41782,\n                30.3849\n              ],\n              [\n                -89.18049,\n                30.31598\n              ],\n              [\n                -89.59383,\n                30.15999\n              ],\n              [\n                -89.41373,\n                29.89419\n              ],\n              [\n                -89.43,\n                29.48864\n              ],\n              [\n                -89.21767,\n                29.29108\n              ],\n              [\n                -89.40823,\n                29.15961\n              ],\n              [\n                -89.77928,\n                29.30714\n              ],\n              [\n                -90.15463,\n                29.11743\n              ],\n              [\n                -90.88022,\n                29.14854\n              ],\n              [\n                -91.62678,\n                29.677\n              ],\n              [\n                -92.49906,\n                29.5523\n              ],\n              [\n                -93.22637,\n                29.78375\n              ],\n              [\n                -93.84842,\n                29.71363\n              ],\n              [\n                -94.69,\n                29.48\n              ],\n              [\n                -95.60026,\n                28.73863\n              ],\n              [\n                -96.59404,\n                28.30748\n              ],\n              [\n                -97.14,\n                27.83\n              ],\n              [\n                -97.37,\n                27.38\n              ],\n              [\n                -97.38,\n                26.69\n              ],\n              [\n                -97.33,\n                26.21\n              ],\n              [\n                -97.14,\n                25.87\n              ],\n              [\n                -97.53,\n                25.84\n              ],\n              [\n                -98.24,\n                26.06\n              ],\n              [\n                -99.02,\n                26.37\n              ],\n              [\n                -99.3,\n                26.84\n              ],\n              [\n                -99.52,\n                27.54\n              ],\n              [\n                -100.11,\n                28.11\n              ],\n              [\n                -100.45584,\n                28.69612\n              ],\n              [\n                -100.9576,\n                29.38071\n              ],\n              [\n                -101.6624,\n                29.7793\n              ],\n              [\n                -102.48,\n                29.76\n              ],\n              [\n                -103.11,\n                28.97\n              ],\n              [\n                -103.94,\n                29.27\n              ],\n              [\n                -104.45697,\n                29.57196\n              ],\n              [\n                -104.70575,\n                30.12173\n              ],\n              [\n                -105.03737,\n                30.64402\n              ],\n              [\n                -105.63159,\n                31.08383\n              ],\n              [\n                -106.1429,\n                31.39995\n              ],\n              [\n                -106.50759,\n                31.75452\n              ],\n              [\n                -108.24,\n                31.75485\n              ],\n              [\n                -108.24194,\n                31.34222\n              ],\n              [\n                -109.035,\n                31.34194\n              ],\n              [\n                -111.02361,\n                31.33472\n              ],\n              [\n                -113.30498,\n                32.03914\n              ],\n              [\n                -114.815,\n                32.52528\n              ],\n              [\n                -114.72139,\n                32.72083\n              ],\n              [\n                -115.99135,\n                32.61239\n              ],\n              [\n                -117.12776,\n                32.53534\n              ],\n              [\n                -117.29594,\n                33.04622\n              ],\n              [\n                -117.944,\n                33.62124\n              ],\n              [\n                -118.4106,\n                33.74091\n              ],\n              [\n                -118.51989,\n                34.02778\n              ],\n              [\n                -119.081,\n                34.078\n              ],\n              [\n                -119.43884,\n                34.34848\n              ],\n              [\n                -120.36778,\n                34.44711\n              ],\n              [\n                -120.62286,\n                34.60855\n              ],\n              [\n                -120.74433,\n                35.15686\n              ],\n              [\n                -121.71457,\n                36.16153\n              ],\n              [\n                -122.54747,\n                37.55176\n              ],\n              [\n                -122.51201,\n                37.78339\n              ],\n              [\n                -122.95319,\n                38.11371\n              ],\n              [\n                -123.7272,\n                38.95166\n              ],\n              [\n                -123.86517,\n                39.76699\n              ],\n              [\n                -124.39807,\n                40.3132\n              ],\n              [\n                -124.17886,\n                41.14202\n              ],\n              [\n                -124.2137,\n                41.99964\n              ],\n              [\n                -124.53284,\n                42.76599\n              ],\n              [\n                -124.14214,\n                43.70838\n              ],\n              [\n                -124.02053,\n                44.6159\n              ],\n              [\n                -123.89893,\n                45.52341\n              ],\n              [\n                -124.07963,\n                46.86475\n              ],\n              [\n                -124.39567,\n                47.72017\n              ],\n              [\n                -124.68721,\n                48.18443\n              ],\n              [\n                -124.5661,\n                48.37971\n              ],\n              [\n                -123.12,\n                48.04\n              ],\n              [\n                -122.58736,\n                47.096\n              ],\n              [\n                -122.34,\n                47.36\n              ],\n              [\n                -122.5,\n                48.18\n              ],\n              [\n                -122.84,\n                49\n              ],\n              [\n                -120,\n                49\n              ],\n              [\n                -117.03121,\n                49\n              ],\n              [\n                -116.04818,\n                49\n              ],\n              [\n                -113,\n                49\n              ],\n              [\n                -110.05,\n                49\n              ],\n              [\n                -107.05,\n                49\n              ],\n              [\n                -104.04826,\n                48.99986\n              ],\n              [\n                -100.65,\n                49\n              ],\n              [\n                -97.22872,\n                49.0007\n              ],\n              [\n                -95.15907,\n                49\n              ],\n              [\n                -95.15609,\n                49.38425\n              ],\n              [\n                -94.81758,\n                49.38905\n              ]\n            ]\n          ]\n        ]\n      },\n      \"properties\": {\n        \"name\": \"United States\"\n      }\n    }\n  ]\n}","contact":"<p>Director, <a href=\"https://www.usgs.gov/centers/eros\" data-mce-href=\"https://www.usgs.gov/centers/eros\">Earth Resources Observation and Science Center</a><br>U.S. Geological Survey<br>47914 252nd Street<br>Sioux Falls, SD 57198</p><p><a href=\"https://pubs.usgs.gov/contact\" data-mce-href=\"../contact\">Contact Pubs Warehouse</a></p>","tableOfContents":"<ul><li>Background</li><li>Methods and Data</li><li>Results and Products</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2023-12-12","noUsgsAuthors":false,"publicationDate":"2023-12-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Xian, George Z. 0000-0001-5674-2204 xian@usgs.gov","orcid":"https://orcid.org/0000-0001-5674-2204","contributorId":2263,"corporation":false,"usgs":true,"family":"Xian","given":"George","email":"xian@usgs.gov","middleInitial":"Z.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":887881,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70250479,"text":"70250479 - 2023 - Critical review of the phytohemagglutinin assay for assessing amphibian immunity","interactions":[],"lastModifiedDate":"2023-12-13T12:34:49.424681","indexId":"70250479","displayToPublicDate":"2023-12-13T06:31:11","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3919,"text":"Conservation Physiology","onlineIssn":"2051-1434","active":true,"publicationSubtype":{"id":10}},"title":"Critical review of the phytohemagglutinin assay for assessing amphibian immunity","docAbstract":"<p><span>Infectious diseases are a major driver of the global amphibian decline. In addition, many factors, including genetics, stress, pollution, and climate change can influence the response to pathogens. Therefore, it is important to be able to evaluate amphibian immunity in the laboratory and in the field. The phytohemagglutinin (PHA) assay is an inexpensive and relatively non-invasive tool that has been used extensively to assess immunocompetence, especially in birds, and more recently in amphibians. However, there is substantial variation in experimental methodology among amphibian PHA studies in terms of species and life stages, PHA doses and injection sites, and use of experimental controls. Here, we compile and compare all known PHA studies in amphibians to identify knowledge gaps and develop best practices for future work. We found that research has only been conducted on a limited number of species, which may not reflect the diversity of amphibians. There is also a lack of validation studies in most species, so that doses and timing of PHA injection and subsequent swelling measurements may not effectively evaluate immunocompetence. Based on these and other findings, we put forward a set of recommendations to make future PHA studies more consistent and improve the ability to utilize this assay in wild populations, where immune surveillance is greatly needed.</span></p>","language":"English","publisher":"Oxford Academic Press","doi":"10.1093/conphys/coad090","usgsCitation":"Hawley, L., Smalling, K., and Glaberman, S., 2023, Critical review of the phytohemagglutinin assay for assessing amphibian immunity: Conservation Physiology, v. 11, no. 1, coad090, 23 p., https://doi.org/10.1093/conphys/coad090.","productDescription":"coad090, 23 p.","ipdsId":"IP-150838","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"links":[{"id":441422,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/conphys/coad090","text":"Publisher Index Page"},{"id":423506,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"11","issue":"1","noUsgsAuthors":false,"publicationDate":"2023-12-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Hawley, Lauren","contributorId":332337,"corporation":false,"usgs":false,"family":"Hawley","given":"Lauren","email":"","affiliations":[{"id":12909,"text":"George Mason University","active":true,"usgs":false}],"preferred":false,"id":890070,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Smalling, Kelly L. 0000-0002-1214-4920","orcid":"https://orcid.org/0000-0002-1214-4920","contributorId":214623,"corporation":false,"usgs":true,"family":"Smalling","given":"Kelly L.","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":890071,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Glaberman, Scott 0000-0003-0594-4732","orcid":"https://orcid.org/0000-0003-0594-4732","contributorId":266060,"corporation":false,"usgs":false,"family":"Glaberman","given":"Scott","email":"","affiliations":[{"id":12909,"text":"George Mason University","active":true,"usgs":false}],"preferred":false,"id":890072,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70250987,"text":"70250987 - 2023 - Saproxylic beetles' morphological traits and higher trophic guilds indicate boreal forest naturalness","interactions":[],"lastModifiedDate":"2024-01-18T11:56:09.015378","indexId":"70250987","displayToPublicDate":"2023-12-13T05:55:16","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Saproxylic beetles' morphological traits and higher trophic guilds indicate boreal forest naturalness","docAbstract":"<div class=\"abstract-group  metis-abstract\"><div class=\"article-section__content en main\"><p>Forests contribute to numerous ecosystem functions and services and contain a large proportion of terrestrial biodiversity, but they are being negatively impaced by anthropogenic activities. Forests that have never been clear-cut and have old growth characteristics, termed “near-natural,” often harbor different and richer species assemblages than managed forests. Alternative management strategies may be able to balance the needs of biodiversity with the demands of forestry, but evaluation efforts are limited by the challenges of measuring biodiversity. Species richness is frequently used as a simple measure of biodiversity, but research indicates that it may not adequately capture community-level changes. Alternatively, trait-based measures of biodiversity may prove to be useful, but research is lacking. In this paper, we use a large dataset that includes 339 obligate saproxylic beetle species collected over a decade in the boreal region throughout southern Norway to: (1) establish if there is a difference in beetle community composition between near-natural and managed forests; and (2) determine which measures of beetle biodiversity best indicate forest naturalness. We arranged the sites in an ordination space and tested for differences in community composition between these forest types. We also tested different measures of biodiversity to determine which were the most predictive of forest naturalness. We found a clear difference in community composition between near-natural and managed forests. Additionally, three measures of biodiversity were most predictive of forest naturalness: proportional abundance of predators, community weighted mean (CWM) of wing length, and CWM of body roundness. The probability that a forest was near-natural increased with the proportional abundance of predators but decreased with CWM wing length and body roundness. Although species richness was higher in near-natural forests, the effect was not significant. Overall, our findings underscore the conservation value of near-natural forests and highlight the potential of several measures of biodiversity for determining forest quality.</p></div></div>","language":"English","publisher":"Wiley","doi":"10.1002/ece3.10739","usgsCitation":"Wetherbee, R., Birkemoe, T., Burner, R.C., and Sverdrup-Thygeson, A., 2023, Saproxylic beetles' morphological traits and higher trophic guilds indicate boreal forest naturalness: Ecology and Evolution, v. 13, no. 12, e10739, 12 p., https://doi.org/10.1002/ece3.10739.","productDescription":"e10739, 12 p.","ipdsId":"IP-152931","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":441423,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.10739","text":"Publisher Index Page"},{"id":424556,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"13","issue":"12","noUsgsAuthors":false,"publicationDate":"2023-12-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Wetherbee, Ross","contributorId":333397,"corporation":false,"usgs":false,"family":"Wetherbee","given":"Ross","email":"","affiliations":[{"id":79864,"text":"Department of Environmental Sciences, Western Norway University of Applied Sciences, Sogndal, Norway","active":true,"usgs":false}],"preferred":false,"id":892669,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Birkemoe, Tone","contributorId":304154,"corporation":false,"usgs":false,"family":"Birkemoe","given":"Tone","email":"","affiliations":[{"id":40295,"text":"Norwegian University of Life Sciences","active":true,"usgs":false}],"preferred":false,"id":892670,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Burner, Ryan C. 0000-0002-7314-9506","orcid":"https://orcid.org/0000-0002-7314-9506","contributorId":304152,"corporation":false,"usgs":true,"family":"Burner","given":"Ryan","email":"","middleInitial":"C.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":892671,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sverdrup-Thygeson, Anne 0000-0002-3122-2250","orcid":"https://orcid.org/0000-0002-3122-2250","contributorId":304161,"corporation":false,"usgs":false,"family":"Sverdrup-Thygeson","given":"Anne","email":"","affiliations":[{"id":40295,"text":"Norwegian University of Life Sciences","active":true,"usgs":false}],"preferred":false,"id":892672,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70250472,"text":"ofr20231091 - 2023 - Assessing the use of long-term lek survey data to evaluate the effect of landscape characteristics and wind facilities on sharp-tailed grouse lek dynamics in North Dakota and South Dakota","interactions":[],"lastModifiedDate":"2026-02-18T22:05:08.82409","indexId":"ofr20231091","displayToPublicDate":"2023-12-12T14:58:13","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":"2023-1091","displayTitle":"Assessing the Use of Long-Term Lek Survey Data to Evaluate the Effect of Landscape Characteristics and Wind Facilities on Sharp-Tailed Grouse Lek Dynamics in North Dakota and South Dakota","title":"Assessing the use of long-term lek survey data to evaluate the effect of landscape characteristics and wind facilities on sharp-tailed grouse lek dynamics in North Dakota and South Dakota","docAbstract":"<p>The contribution of renewable energy to meet worldwide demand continues to grow. In the United States, wind energy is one of the fastest growing renewable energy sectors. Throughout the Great Plains of the United States, wind facilities often are placed in open landscapes of high-elevation grasslands, and those same habitats support sharp-tailed grouse (<i>Tympanuchus phasianellus</i>), a resident gamebird species. To assess the feasibility of using independently derived, long-term datasets gathered in North Dakota and South Dakota to determine whether wind facilities affected lek metrics, the U.S. Geological Survey obtained six datasets and identified 37 study sites, 9 of which contained wind turbines at varying densities. The association between explanatory variables that described geographic, landscape, and climatic attributes with two primary response metrics that described lekking activity within study sites—lek density (leks per square kilometer) and mean number of males per lek—was examined. The explanatory variables included number of turbines, geographic location, elevation, land-cover attributes available from satellite-derived land-cover data, soil moisture, precipitation, and temperature. Sampling units consisted of township-sized blocks, and lek information came from roadside surveys. Low sample sizes of constructed wind facilities available at the time of analysis did not lend itself to advanced statistical techniques, such as employing a rigorous design structure or assessing accuracy on landscape, geographic, or climatic variables. Given the quality of the data, the estimates obtained for lek density and mean number of males per lek should be considered approximations; however, these estimates have value in designing future studies, such as providing estimates for power analyses to determine sufficient sample size. No strong associations were found between the included explanatory variables and response variables (when these variables were measured as described in this report for township-sized blocks). The strongest association was that lek density and mean number of males per lek increased from South Dakota to North Dakota. Owing to the highly unbalanced distribution of turbine and nonturbine study sites across the study area, the analysis with wind turbines was inconclusive. The constraints under which the analysis can be used and the limitations of the independently derived datasets in attempted applications are discussed.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20231091","usgsCitation":"Shaffer, J.A., Buhl, D.A., and Newton, W.E., 2023, Assessing the use of long-term lek survey data to evaluate the effect of landscape characteristics and wind facilities on sharp-tailed grouse lek dynamics in North Dakota and South Dakota: U.S. Geological Survey Open-File Report 2023–1091, 33 p., https://doi.org/10.3133/ofr20231091.","productDescription":"Report: v, 33 p.; Data Release","numberOfPages":"42","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-154704","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":500155,"rank":7,"type":{"id":36,"text":"NGMDB Index 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Dakota\",\"nation\":\"USA  \"}}]}","contact":"<p>Director, <a href=\"https://www.usgs.gov/centers/npwrc\" data-mce-href=\"https://www.usgs.gov/centers/npwrc\">Northern Prairie Wildlife Research Center</a><br>U.S. Geological Survey<br>8711 37th Street Southeast<br>Jamestown, ND 58401</p><p><a href=\"https://pubs.usgs.gov/contact\" data-mce-href=\"../contact\">Contact Pubs Warehouse</a></p>","tableOfContents":"<ul><li>Abstract</li><li>Introduction</li><li>Study Area</li><li>Methods</li><li>Data Analysis</li><li>Results</li><li>Discussion</li><li>Summary</li><li>Acknowledgments</li><li>References Cited</li><li>Appendix 1. Correlation Tables of Explanatory Variables</li></ul>","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2023-12-12","noUsgsAuthors":false,"publicationDate":"2023-12-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Shaffer, Jill A. 0000-0003-3172-0708","orcid":"https://orcid.org/0000-0003-3172-0708","contributorId":214803,"corporation":false,"usgs":true,"family":"Shaffer","given":"Jill A.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":890046,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Buhl, Deborah A. 0000-0002-8563-5990 dbuhl@usgs.gov","orcid":"https://orcid.org/0000-0002-8563-5990","contributorId":146226,"corporation":false,"usgs":true,"family":"Buhl","given":"Deborah","email":"dbuhl@usgs.gov","middleInitial":"A.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":890047,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Newton, Wesley E. 0000-0002-1377-043X wnewton@usgs.gov","orcid":"https://orcid.org/0000-0002-1377-043X","contributorId":3661,"corporation":false,"usgs":true,"family":"Newton","given":"Wesley","email":"wnewton@usgs.gov","middleInitial":"E.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":890048,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
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,{"id":70256496,"text":"70256496 - 2023 - Decision analysis to advance environmental sustainability","interactions":[],"lastModifiedDate":"2024-08-07T16:25:02.875582","indexId":"70256496","displayToPublicDate":"2023-12-12T11:19:11","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":14243,"text":"Decision Analysis","active":true,"publicationSubtype":{"id":10}},"title":"Decision analysis to advance environmental sustainability","docAbstract":"<p><span>Decision analysis provides a robust framework for complex decisions related to environmental sustainability and conservation, including for energy and water, fisheries and wildlife management, agriculture, and climate change response. The complexities of these problems stem from their large scope and scale, which leads to multiple decision makers, stakeholders, rightsholders, and other entities with potentially competing objectives. These problems often are time limited (e.g., urgent action is required to prevent species’ extinction), involve management interventions over long time scales and delayed responses to management (deep uncertainty), and are impeded by limited resources (funding, capacity, etc.). In this Special Issue on “Decision Analysis to Advance Environmental Sustainability,” we present five case studies of applications of decision analysis to complex problems in environmental sustainability and conservation. These case studies incorporate multiple objectives related to ecological and environmental sustainability, economic and social concerns, and logistics of implementation. They showcase a wide range of tools and applications to these problems. We also provide suggestions for new avenues of research and application of decision analysis to problems of environmental sustainability and conservation, including how to incorporate other decision-making tools into decision analysis processes, how to broaden the reach of decision analysis to other sustainability problems, how to incorporate more stakeholders and rightsholders into the decision process, the potential to incorporate new technology into these processes, identifying more creative alternatives, how to secure more funding, ways to move from decision to action, and how to move beyond status quo to make big transitions necessary to achieve sustainability.</span></p>","language":"English","publisher":"Informs","doi":"10.1287/deca.2023.intro.v20.n4","usgsCitation":"Robinson, K.F., Baker, E., Ewing, E., Hemming, V., Kenney, M.A., and Runge, M.C., 2023, Decision analysis to advance environmental sustainability: Decision Analysis, v. 20, no. 4, p. 243-251, https://doi.org/10.1287/deca.2023.intro.v20.n4.","productDescription":"9 p.","startPage":"243","endPage":"251","ipdsId":"IP-156978","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":441426,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.31219/osf.io/qxcaj","text":"External Repository"},{"id":432363,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"20","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Robinson, Kelly Filer 0000-0001-8109-9492","orcid":"https://orcid.org/0000-0001-8109-9492","contributorId":340631,"corporation":false,"usgs":true,"family":"Robinson","given":"Kelly","email":"","middleInitial":"Filer","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":907663,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Baker, Erin","contributorId":340905,"corporation":false,"usgs":false,"family":"Baker","given":"Erin","affiliations":[{"id":36396,"text":"University of Massachusetts","active":true,"usgs":false}],"preferred":false,"id":907664,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ewing, Elizabeth","contributorId":340906,"corporation":false,"usgs":false,"family":"Ewing","given":"Elizabeth","email":"","affiliations":[{"id":81676,"text":"Ewing Smith Consulting LLC","active":true,"usgs":false}],"preferred":false,"id":907665,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hemming, Victoria","contributorId":340907,"corporation":false,"usgs":false,"family":"Hemming","given":"Victoria","email":"","affiliations":[{"id":36972,"text":"University of British Columbia","active":true,"usgs":false}],"preferred":false,"id":907666,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kenney, Melissa A.","contributorId":340908,"corporation":false,"usgs":false,"family":"Kenney","given":"Melissa","email":"","middleInitial":"A.","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":907667,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Runge, Michael C. 0000-0002-8081-536X mrunge@usgs.gov","orcid":"https://orcid.org/0000-0002-8081-536X","contributorId":3358,"corporation":false,"usgs":true,"family":"Runge","given":"Michael","email":"mrunge@usgs.gov","middleInitial":"C.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":907668,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70256411,"text":"70256411 - 2023 - Artisanal mining river dredge detection using SAR: A method comparison","interactions":[],"lastModifiedDate":"2024-08-01T14:14:12.206707","indexId":"70256411","displayToPublicDate":"2023-12-12T09:11:13","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3250,"text":"Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Artisanal mining river dredge detection using SAR: A method comparison","docAbstract":"<p><span>Challenges exist in monitoring artisanal and small-scale mining (ASM) activities, given their dynamic and often informal nature. ASM takes form through various techniques and scales, including riverine dredging, which often targets the abundant alluvial gold deposits in South America. Remote sensing offers a solution to improve data collection, regulation, and monitoring of the more mobile and elusive ASM activities and their impacts. Mapping ASM riverine dredges using Synthetic Aperture Radar (SAR) is one of the application areas least explored. Three semi-automated detection approaches using Sentinel-1 SAR are compared on their ability to identify dredges with minimal false positives. The methods are: (i) Search for Unidentified Maritime Objects (SUMO), an established method for large ocean ship detection; and two techniques specifically developed for riverine environments that are introduced in this paper: (ii) a local detection method; and (iii) a global threshold method. A visual interpretation of SAR data with the inclusion of optical high-resolution data are used to generate a validation dataset. Results show it is possible to semi-automatically detect riverine dredge using SAR and that a local detection method provides the best balance between sensitivity and precision and has the lowest risk of error. Future improvements may consider further automation, more discriminatory variables, and analyzing the methods in different environments and at higher spatial resolutions.</span></p>","language":"English","publisher":"MDPI","doi":"10.3390/rs15245701","usgsCitation":"Alessi, M.A., Chirico, P.G., and Millones, M., 2023, Artisanal mining river dredge detection using SAR: A method comparison: Remote Sensing, v. 15, no. 24, 5701, 18 p., https://doi.org/10.3390/rs15245701.","productDescription":"5701, 18 p.","ipdsId":"IP-155957","costCenters":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":441429,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs15245701","text":"Publisher Index Page"},{"id":432025,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"15","issue":"24","noUsgsAuthors":false,"publicationDate":"2023-12-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Alessi, Marissa Ann 0000-0002-1251-3108","orcid":"https://orcid.org/0000-0002-1251-3108","contributorId":244628,"corporation":false,"usgs":true,"family":"Alessi","given":"Marissa","email":"","middleInitial":"Ann","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":907299,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chirico, Peter G. 0000-0001-8375-5342","orcid":"https://orcid.org/0000-0001-8375-5342","contributorId":63838,"corporation":false,"usgs":true,"family":"Chirico","given":"Peter","email":"","middleInitial":"G.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":907300,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Millones, Marco 0009-0003-8572-0313","orcid":"https://orcid.org/0009-0003-8572-0313","contributorId":340502,"corporation":false,"usgs":false,"family":"Millones","given":"Marco","email":"","affiliations":[{"id":52557,"text":"University of Mary Washington","active":true,"usgs":false}],"preferred":false,"id":907301,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70255632,"text":"70255632 - 2023 - Feasibility of implementing a long-term plan to monitor the Arctic Basin polar bear subpopulation","interactions":[],"lastModifiedDate":"2024-06-27T14:23:19.203493","indexId":"70255632","displayToPublicDate":"2023-12-12T09:10:29","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"title":"Feasibility of implementing a long-term plan to monitor the Arctic Basin polar bear subpopulation","docAbstract":"<p><span>The Arctic Basin (AB) polar bear subpopulation is the least studied of the 19 global polar bear&nbsp;subpopulations. The Polar Bear Specialist Group (PBSG) recognizes the AB subpopulation as a&nbsp;regional grouping intended to include bears that do not belong to any of the remaining&nbsp;subpopulations that have data to support boundary delineations. Very little is currently known&nbsp;about the AB subpopulation including information on its size, genetic uniqueness, or movement&nbsp;patterns, most likely due to its remote range, and uncertainty about whether the AB&nbsp;subpopulation represents a true subpopulation. We provide an overview on the minimum&nbsp;requirements needed to monitor the AB subpopulation; challenges for establishing and&nbsp;implementing a monitoring program; feasibility of different monitoring techniques; alternative&nbsp;sources of inference; and general suggestions for moving forward.</span></p>","language":"English","publisher":"Polar Bear Range States","usgsCitation":"Wilson, R.H., Aars, J., Atwood, T.C., and Richardson, E., 2023, Feasibility of implementing a long-term plan to monitor the Arctic Basin polar bear subpopulation, 12 p.","productDescription":"12 p.","ipdsId":"IP-152119","costCenters":[{"id":65299,"text":"Alaska Science Center Ecosystems","active":true,"usgs":true}],"links":[{"id":430570,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":430549,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.polarbearagreement.org/resources/circumpolar-action-plan/cap-2020-2023-implementation-plan/objective-7-plan/objective-7-final-papers/rmv-a1-feasibility-of-implementing-a-long-term-plan-to-monitor-the-arctic-basin-polar-bear-subpopulation"}],"country":"Canada, Greenland, Norway, Russia, United States","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              0.6021951119280118,\n              82.00587311860781\n            ],\n            [\n              14.554236193208169,\n              58.83017304437573\n            ],\n            [\n              179.9,\n              53.347998970191185\n            ],\n            [\n              179.9,\n              76.31551663782366\n            ],\n            [\n              0.6021951119280118,\n              82.00587311860781\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    },\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -179.9,\n              77.41222161200673\n            ],\n            [\n              -179.9,\n              52.376980362713766\n            ],\n            [\n              -24.54619193353716,\n              52.376980362713766\n            ],\n            [\n              -9.77958939997336,\n              84.0635093320891\n            ],\n            [\n              -99.66600125197836,\n              82.267807345001\n            ],\n            [\n              -179.9,\n              77.41222161200673\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Wilson, Ryan H. 0000-0001-7740-7771","orcid":"https://orcid.org/0000-0001-7740-7771","contributorId":130989,"corporation":false,"usgs":false,"family":"Wilson","given":"Ryan","email":"","middleInitial":"H.","affiliations":[{"id":6987,"text":"U.S. Fish and Wildlife Sevice","active":true,"usgs":false}],"preferred":false,"id":904996,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Aars, Jon","contributorId":91338,"corporation":false,"usgs":false,"family":"Aars","given":"Jon","email":"","affiliations":[{"id":7238,"text":"Norwegian Polar Institute","active":true,"usgs":false}],"preferred":false,"id":904997,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Atwood, Todd C. 0000-0002-1971-3110 tatwood@usgs.gov","orcid":"https://orcid.org/0000-0002-1971-3110","contributorId":4368,"corporation":false,"usgs":true,"family":"Atwood","given":"Todd","email":"tatwood@usgs.gov","middleInitial":"C.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":904998,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Richardson, Evan","contributorId":194428,"corporation":false,"usgs":false,"family":"Richardson","given":"Evan","affiliations":[],"preferred":false,"id":904999,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
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