{"pageNumber":"128","pageRowStart":"3175","pageSize":"25","recordCount":40783,"records":[{"id":70246323,"text":"70246323 - 2023 - Sediment and nutrient deposition over a reconnected floodplain during large-scale river diversions, the Bonnet Carré spillway in 2011, 2016, and 2019","interactions":[],"lastModifiedDate":"2023-07-05T14:13:25.298908","indexId":"70246323","displayToPublicDate":"2023-04-12T08:52:27","publicationYear":"2023","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Sediment and nutrient deposition over a reconnected floodplain during large-scale river diversions, the Bonnet Carré spillway in 2011, 2016, and 2019","docAbstract":"<p>In hopes of reversing or slowing the decline of the river delta, water diversions have been built and planned, and natural diversions have formed and been allowed to develop along the lower Mississippi River. In addition to the possibility of building land, these diversions allow for the storage of nutrients within the deposited sediments and provide a buffer from coastal storm surge flooding. Deposition from diversions reduces nutrient loading to the receiving waterbodies. Along the Mississippi River delta in Louisiana, modern planned diversions after 2017 (CPRA 2017) seek to bring sediment-laden water from the river to a receiving area that may once have been part of the historic delta floodplain. Many of the existing diversions discharge directly into open-water bays of the subaqueous delta, however some flood diversions outflow to the subaerial floodplain (Kroes et al. 2015). The effects of diversion outflows to bays are difficult to physically analyze and quantify due to the complex hydrodynamics of subaqueous sites, such as storm-driven resuspension, and tidal currents that mobilize deposited fine sediments downcoast or off the continental shelf. In contrast, flood diversions that outflow to subaerial floodplains offer clear and numerous sediment deposition measurement opportunities and clearly identifiable material to analyze. Flood diversions, while similar, may not exhibit identical depositional environments due to hydraulic gradient and vegetation differences. Because flood diversions draw water from the river at a greater height above the riverbed, they may entrain less bed sediment than non-flood diversions (Karmaker et al. 2010). Previous studies indicate that the large discharges through flood diversion control structures deposit large masses of sediment (Nittrouer et al. 2012) and nutrients and can provide depositional curves that may be extrapolated to other diversions (Kroes et al. 2015).</p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of SEDHYD2023","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"SEDHYD2023: The sedimentation and hydrologic modeling conference","conferenceDate":"May 8-12, 2023","conferenceLocation":"St. Louis, MO","language":"English","publisher":"SEDHYD","usgsCitation":"Kroes, D., Noe, G.E., Ramirez, D., and Vosburg, B., 2023, Sediment and nutrient deposition over a reconnected floodplain during large-scale river diversions, the Bonnet Carré spillway in 2011, 2016, and 2019, <i>in</i> Proceedings of SEDHYD2023, St. Louis, MO, May 8-12, 2023, 11 p.","productDescription":"11 p.","ipdsId":"IP-151842","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":418678,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":418675,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://www.sedhyd.org/2023Program/s68.html","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Louisiana","otherGeospatial":"Bonnet Carré spillway, Lake Pontchartrain, Mississippi River","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -90.42757540318235,\n              30.082894344072514\n            ],\n            [\n              -90.42757540318235,\n              30.01150844828244\n            ],\n            [\n              -90.3745696787966,\n              30.01150844828244\n            ],\n            [\n              -90.3745696787966,\n              30.082894344072514\n            ],\n            [\n              -90.42757540318235,\n              30.082894344072514\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Kroes, Daniel 0000-0001-9104-9077 dkroes@usgs.gov","orcid":"https://orcid.org/0000-0001-9104-9077","contributorId":3830,"corporation":false,"usgs":true,"family":"Kroes","given":"Daniel","email":"dkroes@usgs.gov","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":369,"text":"Louisiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":876812,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Noe, Gregory E. 0000-0002-6661-2646 gnoe@usgs.gov","orcid":"https://orcid.org/0000-0002-6661-2646","contributorId":139100,"corporation":false,"usgs":true,"family":"Noe","given":"Gregory","email":"gnoe@usgs.gov","middleInitial":"E.","affiliations":[{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":876813,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ramirez, David","contributorId":315549,"corporation":false,"usgs":false,"family":"Ramirez","given":"David","email":"","affiliations":[{"id":12537,"text":"USACE","active":true,"usgs":false}],"preferred":false,"id":876814,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Vosburg, Brian","contributorId":315550,"corporation":false,"usgs":false,"family":"Vosburg","given":"Brian","email":"","affiliations":[{"id":68350,"text":"Grey Boat Group","active":true,"usgs":false}],"preferred":false,"id":876815,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70242901,"text":"70242901 - 2023 - Coupling large-spatial scale larval dispersal modelling with barcoding to refine the amphi-Atlantic connectivity hypothesis in deep-sea seep mussels","interactions":[],"lastModifiedDate":"2023-04-21T11:43:51.591272","indexId":"70242901","displayToPublicDate":"2023-04-12T06:41:36","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3912,"text":"Frontiers in Marine Science","onlineIssn":"2296-7745","active":true,"publicationSubtype":{"id":10}},"title":"Coupling large-spatial scale larval dispersal modelling with barcoding to refine the amphi-Atlantic connectivity hypothesis in deep-sea seep mussels","docAbstract":"<div class=\"JournalAbstract\"><p>In highly fragmented and relatively stable cold-seep ecosystems, species are expected to exhibit high migration rates and long-distance dispersal of long-lived pelagic larvae to maintain genetic integrity over their range. Accordingly, several species inhabiting cold seeps are widely distributed across the whole Atlantic Ocean, with low genetic divergence between metapopulations on both sides of the Atlantic Equatorial Belt (AEB, i.e. Barbados and African/European margins). Two hypotheses may explain such patterns: (i) the occurrence of present-day gene flow or (ii) incomplete lineage sorting due to large population sizes and low mutation rates. Here, we evaluated the first hypothesis using the cold seep mussels<span>&nbsp;</span><i>Gigantidas childressi, G. mauritanicus, Bathymodiolus heckerae</i><span>&nbsp;</span>and<span>&nbsp;</span><i>B. boomerang</i>. We combined COI barcoding of 763 individuals with VIKING20X larval dispersal modelling at a large spatial scale not previously investigated. Population genetics supported the parallel evolution of<span>&nbsp;</span><i>Gigantidas</i><span>&nbsp;</span>and<span>&nbsp;</span><i>Bathymodiolus</i><span>&nbsp;</span>genera in the Atlantic Ocean and the occurrence of a 1-3 Million-year-old vicariance effect that isolated populations across the Caribbean Sea. Both population genetics and larval dispersal modelling suggested that contemporary gene flow and larval exchanges are possible across the AEB and the Caribbean Sea, although probably rare. When occurring, larval flow was eastward (AEB - only for<span>&nbsp;</span><i>B. boomerang</i>) or northward (Caribbean Sea - only for<span>&nbsp;</span><i>G. mauritanicus</i>). Caution is nevertheless required since we focused on only one mitochondrial gene, which may underestimate gene flow if a genetic barrier exists. Non-negligible genetic differentiation occurred between Barbados and African populations, so we could not discount the incomplete lineage sorting hypothesis. Larval dispersal modelling simulations supported the genetic findings along the American coast with high amounts of larval flow between the Gulf of Mexico (GoM) and the US Atlantic Margin, although the Blake Ridge population of<span>&nbsp;</span><i>B. heckerae</i><span>&nbsp;</span>appeared genetically differentiated. Overall, our results suggest that additional studies using nuclear genetic markers and population genomics approaches are needed to clarify the evolutionary history of the Atlantic bathymodioline mussels and to distinguish between ongoing and past processes.</p></div>","language":"English","publisher":"Frontiers","doi":"10.3389/fmars.2023.1122124","usgsCitation":"Portanier, E., Nicolle, A., Rath, W., Monnet, L., Le Goff, G., Le Port, A., Daguin-Thiebaut, C., Morrison, C., Cunha, M., Betters, M., Young, C.M., Van Dover, C., Biastoch, A., Thiebaut, E., and Jollivet, D., 2023, Coupling large-spatial scale larval dispersal modelling with barcoding to refine the amphi-Atlantic connectivity hypothesis in deep-sea seep mussels: Frontiers in Marine Science, v. 10, 1122124, 29 p., https://doi.org/10.3389/fmars.2023.1122124.","productDescription":"1122124, 29 p.","ipdsId":"IP-147936","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":443874,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fmars.2023.1122124","text":"Publisher Index Page"},{"id":416110,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"10","noUsgsAuthors":false,"publicationDate":"2023-04-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Portanier, Elodie","contributorId":304320,"corporation":false,"usgs":false,"family":"Portanier","given":"Elodie","email":"","affiliations":[{"id":66024,"text":"Sorbonne Université, CNRS, UMR 7144, Adaptation et Diversité en Milieu Marin, Station Biologique de Roscoff, Place Georges Teissier, F-29680 Roscoff, France","active":true,"usgs":false}],"preferred":false,"id":870139,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nicolle, A.","contributorId":304321,"corporation":false,"usgs":false,"family":"Nicolle","given":"A.","email":"","affiliations":[{"id":66025,"text":"École nationale supérieure de techniques avancées (ENSTA) Bretagne, Pôle STIC/HOP, Brest, France","active":true,"usgs":false}],"preferred":false,"id":870140,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rath, W.","contributorId":304322,"corporation":false,"usgs":false,"family":"Rath","given":"W.","email":"","affiliations":[{"id":62473,"text":"GEOMAR Helmholtz Centre for Ocean Research Kiel, Kiel, Germany","active":true,"usgs":false}],"preferred":false,"id":870141,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Monnet, L.","contributorId":304323,"corporation":false,"usgs":false,"family":"Monnet","given":"L.","email":"","affiliations":[{"id":66024,"text":"Sorbonne Université, CNRS, UMR 7144, Adaptation et Diversité en Milieu Marin, Station Biologique de Roscoff, Place Georges Teissier, F-29680 Roscoff, France","active":true,"usgs":false}],"preferred":false,"id":870142,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Le Goff, G.","contributorId":304324,"corporation":false,"usgs":false,"family":"Le Goff","given":"G.","email":"","affiliations":[{"id":66025,"text":"École nationale supérieure de techniques avancées (ENSTA) Bretagne, Pôle STIC/HOP, Brest, France","active":true,"usgs":false}],"preferred":false,"id":870143,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Le Port, A.-S.","contributorId":304325,"corporation":false,"usgs":false,"family":"Le Port","given":"A.-S.","email":"","affiliations":[{"id":66024,"text":"Sorbonne Université, CNRS, UMR 7144, Adaptation et Diversité en Milieu Marin, Station Biologique de Roscoff, Place Georges Teissier, F-29680 Roscoff, France","active":true,"usgs":false}],"preferred":false,"id":870144,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Daguin-Thiebaut, C.","contributorId":304326,"corporation":false,"usgs":false,"family":"Daguin-Thiebaut","given":"C.","email":"","affiliations":[{"id":66024,"text":"Sorbonne Université, CNRS, UMR 7144, Adaptation et Diversité en Milieu Marin, Station Biologique de Roscoff, Place Georges Teissier, F-29680 Roscoff, France","active":true,"usgs":false}],"preferred":false,"id":870145,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Morrison, Cheryl L. 0000-0001-9425-691X","orcid":"https://orcid.org/0000-0001-9425-691X","contributorId":239844,"corporation":false,"usgs":true,"family":"Morrison","given":"Cheryl","middleInitial":"L.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":870146,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Cunha, M.R.","contributorId":304327,"corporation":false,"usgs":false,"family":"Cunha","given":"M.R.","email":"","affiliations":[{"id":66026,"text":"Department of Biology, University of Aveiro, 3810-193, Aveiro, Portugal","active":true,"usgs":false}],"preferred":false,"id":870147,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Betters, M.","contributorId":304328,"corporation":false,"usgs":false,"family":"Betters","given":"M.","affiliations":[{"id":66027,"text":"Department of Biology, Temple University, Philadelphia, Pennsylvania, USA","active":true,"usgs":false}],"preferred":false,"id":870148,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Young, Craig M.","contributorId":304329,"corporation":false,"usgs":false,"family":"Young","given":"Craig","email":"","middleInitial":"M.","affiliations":[{"id":66028,"text":"Oregon Institute of Marine Biology, University of Oregon, Eugene, Oregon, USA","active":true,"usgs":false}],"preferred":false,"id":870149,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Van Dover, Cindy L.","contributorId":304330,"corporation":false,"usgs":false,"family":"Van Dover","given":"Cindy L.","affiliations":[{"id":66029,"text":"Division of Marine Science and Conservation, Nicholas School of the Environment, Duke University, Beaufort, NC, USA","active":true,"usgs":false}],"preferred":false,"id":870150,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Biastoch, A.","contributorId":304332,"corporation":false,"usgs":false,"family":"Biastoch","given":"A.","email":"","affiliations":[{"id":62473,"text":"GEOMAR Helmholtz Centre for Ocean Research Kiel, Kiel, Germany","active":true,"usgs":false}],"preferred":false,"id":870151,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Thiebaut, E.","contributorId":304333,"corporation":false,"usgs":false,"family":"Thiebaut","given":"E.","email":"","affiliations":[{"id":66024,"text":"Sorbonne Université, CNRS, UMR 7144, Adaptation et Diversité en Milieu Marin, Station Biologique de Roscoff, Place Georges Teissier, F-29680 Roscoff, France","active":true,"usgs":false}],"preferred":false,"id":870152,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Jollivet, Didier","contributorId":304334,"corporation":false,"usgs":false,"family":"Jollivet","given":"Didier","email":"","affiliations":[{"id":66024,"text":"Sorbonne Université, CNRS, UMR 7144, Adaptation et Diversité en Milieu Marin, Station Biologique de Roscoff, Place Georges Teissier, F-29680 Roscoff, France","active":true,"usgs":false}],"preferred":false,"id":870153,"contributorType":{"id":1,"text":"Authors"},"rank":15}]}}
,{"id":70257317,"text":"70257317 - 2023 - Estimates of predator densities using mobile DIDSON surveys: Implications for survival of Central Valley Chinook Salmon","interactions":[],"lastModifiedDate":"2024-08-28T15:48:16.370501","indexId":"70257317","displayToPublicDate":"2023-04-11T10:32:38","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2886,"text":"North American Journal of Fisheries Management","active":true,"publicationSubtype":{"id":10}},"title":"Estimates of predator densities using mobile DIDSON surveys: Implications for survival of Central Valley Chinook Salmon","docAbstract":"<p><span>The Sacramento–San Joaquin Delta (hereafter, “the Delta”) is one of the estuaries with the most invasive species in the world, and nonnative predators may be a major factor in the observed decline of Central Valley Chinook Salmon&nbsp;</span><i>Oncorhynchus tshawytscha</i><span>&nbsp;over recent decades. In order for managers to take actions that might reduce predation-related mortality for these ecologically, culturally, and economically valuable fish, it is important to understand the factors influencing the distribution and abundance of piscivores in the Delta. In this study, we used a dual-frequency identification sonar (i.e., DIDSON) to conduct mobile surveys to quantify the abundances of piscivores in the Delta. We then used these data to identify the habitat features that are correlated with the abundance of piscivores. Prior to conducting the surveys, we used DIDSON data from captured fish to develop an algorithm to distinguish piscivores from nonpiscivores with high confidence (98% accuracy). A generalized linear mixed-effects model fit to these survey data indicated that predator abundances were most associated with areas of increased submerged aquatic vegetation patches, and channels&nbsp;that are straighter, with increased bathymetric complexity. When applied to the entire survey area, this model was successfully able to predict known areas of high predator densities. These results indicate that one approach to reduce predator densities in key locations throughout the Delta, and improve juvenile salmonid outmigration survival, is to reduce the extent of invasive submerged aquatic vegetation. Because experimental predator removals have been largely ineffective in the Delta, efforts to manipulate habitat to discourage nonnative predator recruitment and favor native species recruitment may provide a more effective solution to improve salmonid survival rates.</span></p>","language":"English","publisher":"American Fisheries Society","doi":"10.1002/nafm.10873","usgsCitation":"Henderson, M., Loomis, C., Michel, C., Smith, J., Iglesias, I., Lehman, B., and Huff, D., 2023, Estimates of predator densities using mobile DIDSON surveys: Implications for survival of Central Valley Chinook Salmon: North American Journal of Fisheries Management, v. 43, no. 3, p. 628-645, https://doi.org/10.1002/nafm.10873.","productDescription":"18 p.","startPage":"628","endPage":"645","ipdsId":"IP-145482","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":443880,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/nafm.10873","text":"Publisher Index Page"},{"id":433250,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Sacramento–San Joaquin Delta","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -122,\n              38.5\n            ],\n            [\n              -122,\n              37.25\n            ],\n            [\n              -121,\n              37.25\n            ],\n            [\n              -121,\n              38.5\n            ],\n            [\n              -122,\n              38.5\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"43","issue":"3","noUsgsAuthors":false,"publicationDate":"2023-04-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Henderson, Mark J. 0000-0002-2861-8668 mhenderson@usgs.gov","orcid":"https://orcid.org/0000-0002-2861-8668","contributorId":198609,"corporation":false,"usgs":true,"family":"Henderson","given":"Mark J.","email":"mhenderson@usgs.gov","affiliations":[],"preferred":false,"id":909952,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Loomis, Chris","contributorId":342274,"corporation":false,"usgs":false,"family":"Loomis","given":"Chris","email":"","affiliations":[{"id":26936,"text":"Humbolt State University","active":true,"usgs":false}],"preferred":false,"id":909953,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Michel, Cyril","contributorId":342275,"corporation":false,"usgs":false,"family":"Michel","given":"Cyril","affiliations":[{"id":81849,"text":"NOAA-SWFSC Fisheries Ecology Division","active":true,"usgs":false}],"preferred":false,"id":909954,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Smith, Joe","contributorId":342276,"corporation":false,"usgs":false,"family":"Smith","given":"Joe","affiliations":[{"id":81850,"text":"NOAA-NWFSC Fish Ecology Division","active":true,"usgs":false}],"preferred":false,"id":909955,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Iglesias, Ilysa","contributorId":342277,"corporation":false,"usgs":false,"family":"Iglesias","given":"Ilysa","affiliations":[{"id":36629,"text":"University of California","active":true,"usgs":false}],"preferred":false,"id":909956,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lehman, Brendan","contributorId":342279,"corporation":false,"usgs":false,"family":"Lehman","given":"Brendan","affiliations":[{"id":81849,"text":"NOAA-SWFSC Fisheries Ecology Division","active":true,"usgs":false}],"preferred":false,"id":909957,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Huff, David","contributorId":342281,"corporation":false,"usgs":false,"family":"Huff","given":"David","affiliations":[{"id":81850,"text":"NOAA-NWFSC Fish Ecology Division","active":true,"usgs":false}],"preferred":false,"id":909958,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70243983,"text":"70243983 - 2023 - Using neutral landscape models to evaluate the umbrella species concept in an ecotone","interactions":[],"lastModifiedDate":"2023-05-30T14:51:00.989431","indexId":"70243983","displayToPublicDate":"2023-04-11T09:36:40","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2602,"text":"Landscape Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Using neutral landscape models to evaluate the umbrella species concept in an ecotone","docAbstract":"<h3 class=\"c-article__sub-heading\" data-test=\"abstract-sub-heading\">Context</h3><p>Steep declines in North American rangeland biodiversity have prompted researchers and managers to use umbrella species as a tool to manage diverse suites of co-occurring wildlife, but efficacy of this method has been variable. Evaluation of prairie and shrubland grouse as umbrellas is typically restricted to observed overlap between umbrella and background species, but this approach does not distinguish between overlap due to ubiquity or niche overlap.</p><h3 class=\"c-article__sub-heading\" data-test=\"abstract-sub-heading\">Objectives</h3><p>We demonstrate a novel application of neutral landscape models (NLMs) to test the effectiveness of greater sage-grouse (<i>Centrocercus urophasianus</i>) as an umbrella species for grassland songbirds at a grassland-sagebrush ecotone in northeastern Wyoming, USA.</p><h3 class=\"c-article__sub-heading\" data-test=\"abstract-sub-heading\">Methods</h3><p>We leveraged existing spatial data representing sage-grouse habitat in two distinct seasons (nesting and late brood-rearing) and density and distribution of eight grassland songbirds. We applied a permutation-based analysis using NLMs to determine whether overlap between background species and greater sage-grouse was greater than expected by chance.</p><h3 class=\"c-article__sub-heading\" data-test=\"abstract-sub-heading\">Results</h3><p>Three species (western meadowlark<span>&nbsp;</span><i>Sturnella neglecta</i>, loggerhead shrike<span>&nbsp;</span><i>Lanius ludovicianus</i>, and lark bunting<span>&nbsp;</span><i>Calamospiza melanocorys</i>) had greater overlap than expected with at least one type of greater sage-grouse habitat, while western kingbirds (<i>Tyrannus verticalis</i>) indicated avoidance of all sage-grouse habitat assessed.</p><h3 class=\"c-article__sub-heading\" data-test=\"abstract-sub-heading\">Conclusions</h3><p>NLMs provided a more nuanced evaluation of the umbrella species concept than previously available and allowed us to differentiate between overlap due to ubiquity (e.g., vesper sparrow;<span>&nbsp;</span><i>Pooecetes gramineus</i>) rather than overlap in habitat use. All grassland passerine species with greater than expected overlap with sage-grouse habitat either nest in sagebrush (loggerhead shrike) or often select nest locations underneath small shrubs (western meadowlark, lark bunting). These results indicate that nesting substrate is a potential niche axis to consider when evaluating the umbrella species concept, especially within sagebrush-grassland ecotones.</p>","language":"English","publisher":"Springer","doi":"10.1007/s10980-022-01586-7","usgsCitation":"Duchardt, C.J., Monroe, A., Edmunds, D.R., Holloran, M.J., Holloran, A.G., and Aldridge, C.L., 2023, Using neutral landscape models to evaluate the umbrella species concept in an ecotone: Landscape Ecology, v. 38, p. 1447-1462, https://doi.org/10.1007/s10980-022-01586-7.","productDescription":"16 p.","startPage":"1447","endPage":"1462","ipdsId":"IP-135208","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":435377,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9MLURH7","text":"USGS data release","linkHelpText":"A neutral landscape approach to evaluating the umbrella species concept for greater sage-grouse in northeast Wyoming, USA"},{"id":417531,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wyoming","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -111.00304481605505,\n              44.99130028797805\n            ],\n            [\n              -111.00304481605505,\n              40.92596776661196\n            ],\n            [\n              -104.05240845017104,\n              40.92596776661196\n            ],\n            [\n              -104.05240845017104,\n              44.99130028797805\n            ],\n            [\n              -111.00304481605505,\n              44.99130028797805\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"38","noUsgsAuthors":false,"publicationDate":"2023-04-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Duchardt, Courtney J. 0000-0003-4563-0199","orcid":"https://orcid.org/0000-0003-4563-0199","contributorId":239754,"corporation":false,"usgs":false,"family":"Duchardt","given":"Courtney","middleInitial":"J.","affiliations":[{"id":48000,"text":"U Wyoming","active":true,"usgs":false}],"preferred":false,"id":874007,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Monroe, Adrian P. 0000-0003-0934-8225 amonroe@usgs.gov","orcid":"https://orcid.org/0000-0003-0934-8225","contributorId":152209,"corporation":false,"usgs":true,"family":"Monroe","given":"Adrian P.","email":"amonroe@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":874008,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Edmunds, David R. 0000-0002-5212-8271 dedmunds@usgs.gov","orcid":"https://orcid.org/0000-0002-5212-8271","contributorId":152210,"corporation":false,"usgs":true,"family":"Edmunds","given":"David","email":"dedmunds@usgs.gov","middleInitial":"R.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":874009,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Holloran, Matthew James 0000-0001-5244-770X","orcid":"https://orcid.org/0000-0001-5244-770X","contributorId":305854,"corporation":false,"usgs":true,"family":"Holloran","given":"Matthew","email":"","middleInitial":"James","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":874010,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Holloran, Alison G.","contributorId":305855,"corporation":false,"usgs":false,"family":"Holloran","given":"Alison","email":"","middleInitial":"G.","affiliations":[{"id":51369,"text":"Audubon Rockies","active":true,"usgs":false}],"preferred":false,"id":874011,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Aldridge, Cameron L. 0000-0003-3926-6941 aldridgec@usgs.gov","orcid":"https://orcid.org/0000-0003-3926-6941","contributorId":191773,"corporation":false,"usgs":true,"family":"Aldridge","given":"Cameron","email":"aldridgec@usgs.gov","middleInitial":"L.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":false,"id":874012,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70242849,"text":"70242849 - 2023 - A conceptual framework for estimation of initial emergency food and water resource requirements in disasters","interactions":[],"lastModifiedDate":"2023-04-20T12:10:06.454803","indexId":"70242849","displayToPublicDate":"2023-04-11T07:05:24","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2036,"text":"International Journal of Disaster Risk Reduction","active":true,"publicationSubtype":{"id":10}},"title":"A conceptual framework for estimation of initial emergency food and water resource requirements in disasters","docAbstract":"<div id=\"abstracts\" class=\"Abstracts u-font-gulliver text-s\"><div id=\"abs0010\" class=\"abstract author\" lang=\"en\"><div id=\"abssec0010\"><p id=\"abspara0010\">Many households lack the necessary food and water supplies to sustain themselves for more than three days during a disaster. Community vulnerability assessments can be used to identify households with more pressing needs for emergency food and water resources. It is critical that these assessments include the interaction between physical impacts to lifeline infrastructure and the social vulnerabilities of food and water insecurity to prioritize, allocate, and distribute emergency resources. In this paper, we review and synthesize relevant literature to propose a new multidisciplinary conceptual framework of community vulnerability assessment for estimating initial emergency food and water resource requirements in a developed country. Using the framework as a guide, we illustrate its practical application through a simplified, deterministic model of initial resource requirements in disaster response, and offer a quantitative, comprehensive description of its application within the geophysical hazard context of the “ShakeOut” scenario—a major<span>&nbsp;</span><i>M</i><sub>w</sub><span>&nbsp;7.8 earthquake on California's&nbsp;<a class=\"topic-link\" title=\"Learn more about San Andreas fault from ScienceDirect's AI-generated Topic Pages\" href=\"https://www.sciencedirect.com/topics/earth-and-planetary-sciences/san-andreas-fault\" data-mce-href=\"https://www.sciencedirect.com/topics/earth-and-planetary-sciences/san-andreas-fault\">San Andreas fault</a>, occurring within the&nbsp;<a class=\"topic-link\" title=\"Learn more about Los Angeles from ScienceDirect's AI-generated Topic Pages\" href=\"https://www.sciencedirect.com/topics/earth-and-planetary-sciences/los-angeles\" data-mce-href=\"https://www.sciencedirect.com/topics/earth-and-planetary-sciences/los-angeles\">Los Angeles</a>&nbsp;Basin, CA (USA) region. Model results estimate that 999,027 households (2,947,130 residents) will require initial emergency food and water resource requirements. Estimates include about 6 million meals and 9 million liters of water, concentrated in Lancaster-Palmdale, El Monte-Baldwin Park, East Los Angeles-Downey in Los Angeles County, the Coachella Valley (Riverside County), and in populated areas of San Bernardino County. A sensitivity analysis of social vulnerability interactions with utility service outages investigates the influence of food insecurity on the amplification of resource needs. This study establishes fundamental knowledge at the nexus of natural hazards, critical infrastructure disruptions, and social vulnerability by providing initial estimates of emergency resource demand while advancing the understanding of social inequity in emergency resource access.</span></p></div></div></div>","language":"English","publisher":"Elsevier","doi":"10.1016/j.ijdrr.2023.103661","usgsCitation":"Toland, J.C., Wein, A., Wu, A., and Spearing, L., 2023, A conceptual framework for estimation of initial emergency food and water resource requirements in disasters: International Journal of Disaster Risk Reduction, v. 90, 103661, 28 p., https://doi.org/10.1016/j.ijdrr.2023.103661.","productDescription":"103661, 28 p.","ipdsId":"IP-140475","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":443884,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ijdrr.2023.103661","text":"Publisher Index Page"},{"id":435378,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9FIJCCF","text":"USGS data release","linkHelpText":"Data Release&amp;amp;amp;amp;ndash;A Conceptual Framework for Estimation of Initial Emergency Food and Water Resource Requirements in Disasters"},{"id":416050,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"90","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Toland, Joseph Charles 0000-0002-0092-0320","orcid":"https://orcid.org/0000-0002-0092-0320","contributorId":265976,"corporation":false,"usgs":true,"family":"Toland","given":"Joseph","email":"","middleInitial":"Charles","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":869990,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wein, Anne 0000-0002-5516-3697 awein@usgs.gov","orcid":"https://orcid.org/0000-0002-5516-3697","contributorId":589,"corporation":false,"usgs":true,"family":"Wein","given":"Anne","email":"awein@usgs.gov","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":869991,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wu, An-Min","contributorId":304268,"corporation":false,"usgs":false,"family":"Wu","given":"An-Min","email":"","affiliations":[{"id":13249,"text":"University of Southern California","active":true,"usgs":false}],"preferred":false,"id":869992,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Spearing, Lauryn","contributorId":304269,"corporation":false,"usgs":false,"family":"Spearing","given":"Lauryn","email":"","affiliations":[{"id":18133,"text":"University of Illinois Chicago","active":true,"usgs":false}],"preferred":false,"id":869993,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70243529,"text":"70243529 - 2023 - Inferring pathogen presence when sample misclassification and partial observation occur","interactions":[],"lastModifiedDate":"2023-05-11T11:57:40.081025","indexId":"70243529","displayToPublicDate":"2023-04-11T06:55:13","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2717,"text":"Methods in Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Inferring pathogen presence when sample misclassification and partial observation occur","docAbstract":"<ol class=\"\"><li>Surveillance programmes are essential for detecting emerging pathogens and often rely on molecular methods to make inference about the presence of a target disease agent. However, molecular methods rarely detect target DNA perfectly. For example, molecular pathogen detection methods can result in misclassification (i.e. false positives and false negatives) or partial detection errors (i.e. detections with ‘ambiguous’, ‘uncertain’ or ‘equivocal’ results). Then, when data are to be analysed, these partial observations are either discarded or censored; this, however, disregards information that could be used to make inference about the true state of the system. There is a critical need for more direction and guidance related to how many samples are enough to declare a unit of interest ‘pathogen free’.</li><li>Here, we develop a Bayesian hierarchal framework that accommodates false negative, false positive and uncertain detections to improve inference related to the occupancy of a pathogen. We apply our modelling framework to a case study of the fungal pathogen<span>&nbsp;</span><i>Pseudogymnoascus destructans</i><span>&nbsp;</span>(Pd) identified in Texas bats at the invasion front of white-nose syndrome. To improve future surveillance programmes, we provide guidance on sample sizes required to be 95% certain a target organism is absent from a site.</li><li>We found that the presence of uncertain detections increased the variability of resulting posterior probability distributions of pathogen occurrence, and that our estimates of required sample size were very sensitive to prior information about pathogen occupancy, pathogen prevalence and diagnostic test specificity. In the Pd case study, we found that the posterior probability of occupancy was very low in 2018, but occupancy probability approached 1 in 2020, reflecting increasing prior probabilities of occupancy and prevalence elicited from the site manager.</li><li>Our modelling framework provides the user a posterior probability distribution of pathogen occurrence, which allows for subjective interpretation by the decision-maker. To help readers apply and use the methods we developed, we provide an interactive RShiny app that generates target species occupancy estimation and sample size estimates to make these methods more accessible to the scientific community (<a class=\"linkBehavior\" href=\"https://rmummah.shinyapps.io/ambigDetect_sampleSize\" data-mce-href=\"https://rmummah.shinyapps.io/ambigDetect_sampleSize\">https://rmummah.shinyapps.io/ambigDetect_sampleSize</a>). This modelling framework and sample size guide may be useful for improving inferences from molecular surveillance data about emerging pathogens, non-native invasive species and endangered species where misclassifications and ambiguous detections occur.</li></ol>","language":"English","publisher":"British Ecological Society","doi":"10.1111/2041-210X.14102","usgsCitation":"Campbell Grant, E.H., Mummah, R.O., Mosher, B.A., Evans, J., and DiRenzo, G.V., 2023, Inferring pathogen presence when sample misclassification and partial observation occur: Methods in Ecology and Evolution, v. 14, no. 5, p. 1299-1311, https://doi.org/10.1111/2041-210X.14102.","productDescription":"13 p.","startPage":"1299","endPage":"1311","ipdsId":"IP-148152","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":443886,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/2041-210x.14102","text":"Publisher Index Page"},{"id":435379,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9PDV4LV","text":"USGS data release","linkHelpText":"Inferring pathogen presence when sample misclassification and partial observation occur"},{"id":416954,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"14","issue":"5","noUsgsAuthors":false,"publicationDate":"2023-04-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Campbell Grant, Evan H. 0000-0003-4401-6496 ehgrant@usgs.gov","orcid":"https://orcid.org/0000-0003-4401-6496","contributorId":150443,"corporation":false,"usgs":true,"family":"Campbell Grant","given":"Evan","email":"ehgrant@usgs.gov","middleInitial":"H.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":872230,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mummah, Riley O.","contributorId":305294,"corporation":false,"usgs":false,"family":"Mummah","given":"Riley","email":"","middleInitial":"O.","affiliations":[{"id":66204,"text":"Massachusetts Cooperative Fish and Wildlife Research Unit, University of Massachusetts, Department of Environmental Conservation, 160 Holdsworth Way, Amherst, Massachusetts 01003","active":true,"usgs":false}],"preferred":false,"id":872231,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mosher, Brittany A.","contributorId":189579,"corporation":false,"usgs":false,"family":"Mosher","given":"Brittany","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":872232,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Evans, Jonah","contributorId":239062,"corporation":false,"usgs":false,"family":"Evans","given":"Jonah","email":"","affiliations":[{"id":27442,"text":"Texas parks and Wildlife Department","active":true,"usgs":false}],"preferred":false,"id":872233,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"DiRenzo, Graziella Vittoria 0000-0001-5264-4762","orcid":"https://orcid.org/0000-0001-5264-4762","contributorId":243404,"corporation":false,"usgs":true,"family":"DiRenzo","given":"Graziella","email":"","middleInitial":"Vittoria","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":872234,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70243190,"text":"70243190 - 2023 - Model-based assessment and mapping of total phosphorus enrichment in rivers with sparse reference data","interactions":[],"lastModifiedDate":"2023-05-12T15:04:48.978919","indexId":"70243190","displayToPublicDate":"2023-04-11T06:52:09","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Model-based assessment and mapping of total phosphorus enrichment in rivers with sparse reference data","docAbstract":"<div id=\"ab0005\" class=\"abstract author\" lang=\"en\"><div id=\"as0005\"><p id=\"sp0045\">Water nutrient management efforts are frequently coordinated across thousands of water bodies, leading to a need for spatially extensive information to facilitate decision making. Here we explore potential applications of a machine learning model of river low-flow total phosphorus (TP) concentrations to support landscape nutrient management. The model was trained, validated, and then applied for all rivers of Michigan, USA to identify potential drivers of nutrient variation, predict alteration in nutrient concentrations from minimally disturbed conditions, and explore reach specific sensitivity to riparian agricultural change. A boosted regression tree model of low-flow TP concentrations trained on natural and anthropogenic landscape predictors accounted for 53 % of variation in cross-validation data, had good accuracy, little bias, and plausible relationships between predictors and response. Percent riparian agricultural cover accounted for the greatest root mean square error reduction in the modeled response (33.2 %), followed by riparian soil permeability (12.9 %), watershed slope (9.6 %), and percent urban cover (9.6 %). An apparent non-linear relationship between TP concentrations and percent riparian agricultural cover suggested steep positive increases in stream TP concentrations between 10 and 30 % upstream riparian agricultural cover. Predicted minimally disturbed TP concentrations were spatially variable and ranged from 7.0 to 48.5 μg l<sup>−1</sup>, with the highest concentrations in watersheds draining low-permeability lake plain soils. Comparison of minimally disturbed predictions to those from the early 2000s suggested that much of northern Michigan existed close to the reference condition, while lower Michigan streams were often substantially enriched. Our predicted values of minimally disturbed condition generally agree with previous studies but offer greater geographic specificity. Expanded application of machine learning modeling with landscape predictor data have great potential to inform large scale strategy development in landscapes with sparse reference data.</p></div></div>","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2023.163418","usgsCitation":"Esselman, P.C., and Stevenson, R.J., 2023, Model-based assessment and mapping of total phosphorus enrichment in rivers with sparse reference data: Science of the Total Environment, v. 884, 163418, 13 p., https://doi.org/10.1016/j.scitotenv.2023.163418.","productDescription":"163418, 13 p.","ipdsId":"IP-132079","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":416652,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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 \"}}]}","volume":"884","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Esselman, Peter C. 0000-0002-0085-903X pesselman@usgs.gov","orcid":"https://orcid.org/0000-0002-0085-903X","contributorId":5965,"corporation":false,"usgs":true,"family":"Esselman","given":"Peter","email":"pesselman@usgs.gov","middleInitial":"C.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":871416,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stevenson, R Jan","contributorId":304704,"corporation":false,"usgs":false,"family":"Stevenson","given":"R","email":"","middleInitial":"Jan","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":871417,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70242670,"text":"70242670 - 2023 - Climate change and the global redistribution of biodiversity: Substantial variation in empirical support for expected range shifts","interactions":[],"lastModifiedDate":"2023-04-12T11:52:12.574367","indexId":"70242670","displayToPublicDate":"2023-04-11T06:50:09","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":14239,"text":"Journal of Environmental Evidence","active":true,"publicationSubtype":{"id":10}},"title":"Climate change and the global redistribution of biodiversity: Substantial variation in empirical support for expected range shifts","docAbstract":"<h3 class=\"c-article__sub-heading\" data-test=\"abstract-sub-heading\">Background</h3><p>Among the most widely predicted climate change-related impacts to biodiversity are geographic range shifts, whereby species shift their spatial distribution to track their climate niches. A series of commonly articulated hypotheses have emerged in the scientific literature suggesting species are expected to shift their distributions to higher latitudes, greater elevations, and deeper depths in response to rising temperatures associated with climate change. Yet, many species are not demonstrating range shifts consistent with these expectations. Here, we evaluate the impact of anthropogenic climate change (specifically, changes in temperature and precipitation) on species’ ranges, and assess whether expected range shifts are supported by the body of empirical evidence.</p><h3 class=\"c-article__sub-heading\" data-test=\"abstract-sub-heading\">Methods</h3><p>We conducted a Systematic Review, searching online databases and search engines in English. Studies were screened in a two-stage process (title/abstract review, followed by full-text review) to evaluate whether they met a list of eligibility criteria. Data coding, extraction, and study validity assessment was completed by a team of trained reviewers and each entry was validated by at least one secondary reviewer. We used logistic regression models to assess whether the direction of shift supported common range-shift expectations (i.e., shifts to higher latitudes and elevations, and deeper depths). We also estimated the magnitude of shifts for the subset of available range-shift data expressed in distance per time (i.e., km/decade). We accounted for methodological attributes at the study level as potential sources of variation. This allowed us to answer two questions: (1) are most species shifting in the direction we expect (i.e., each observation is assessed as support/fail to support our expectation); and (2) what is the average speed of range shifts?</p><h3 class=\"c-article__sub-heading\" data-test=\"abstract-sub-heading\">Review findings</h3><p>We found that less than half of all range-shift observations (46.60%) documented shifts towards higher latitudes, higher elevations, and greater marine depths, demonstrating significant variation in the empirical evidence for general range shift expectations. For the subset of studies looking at range shift rates, we found that species demonstrated significant average shifts towards higher latitudes (average = 11.8&nbsp;km/dec) and higher elevations (average = 9&nbsp;m/dec), although we failed to find significant evidence for shifts to greater marine depths. We found that methodological factors in individual range-shift studies had a significant impact on the reported direction and magnitude of shifts. Finally, we identified important variation across dimensions of range shifts (e.g., greater support for latitude and elevation shifts than depth), parameters (e.g., leading edge shifts faster than trailing edge for latitude), and taxonomic groups (e.g., faster latitudinal shifts for insects than plants).</p><h3 class=\"c-article__sub-heading\" data-test=\"abstract-sub-heading\">Conclusions</h3><p>Despite growing evidence that species are shifting their ranges in response to climate change, substantial variation exists in the extent to which definitively empirical observations confirm these expectations. Even though on average, rates of shift show significant movement to higher elevations and latitudes for many taxa, most species are not shifting in expected directions. Variation across dimensions and parameters of range shifts, as well as differences across taxonomic groups and variation driven by methodological factors, should be considered when assessing overall confidence in range-shift hypotheses. In order for managers to effectively plan for species redistribution, we need to better account for and predict which species will shift and by how much. The dataset produced for this analysis can be used for future research to explore additional hypotheses to better understand species range shifts.</p>","language":"English","publisher":"Springer Nature","doi":"10.1186/s13750-023-00296-0","usgsCitation":"Rubenstein, M.A., Weiskopf, S.R., Bertrand, R., Carter, S., Comte, L., Eaton, M.J., Johnson, C.G., Lenoir, J., Lynch, A., Miller, B.W., Morelli, T.L., Rodriguez, M.A., Terando, A., and Thompson, L., 2023, Climate change and the global redistribution of biodiversity: Substantial variation in empirical support for expected range shifts: Journal of Environmental Evidence, v. 12, 7, 21 p., https://doi.org/10.1186/s13750-023-00296-0.","productDescription":"7, 21 p.","ipdsId":"IP-138082","costCenters":[{"id":565,"text":"Southeast Climate Science Center","active":true,"usgs":true},{"id":36940,"text":"National Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":443888,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1186/s13750-023-00296-0","text":"Publisher Index Page"},{"id":435380,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P99VP2TW","text":"USGS data release","linkHelpText":"CoRE (Contractions or Range Expansions) Database: Global Database of Species Range Shifts from 1802-2019"},{"id":415647,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"12","noUsgsAuthors":false,"publicationDate":"2023-04-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Rubenstein, Madeleine A. 0000-0001-8569-781X mrubenstein@usgs.gov","orcid":"https://orcid.org/0000-0001-8569-781X","contributorId":203206,"corporation":false,"usgs":true,"family":"Rubenstein","given":"Madeleine","email":"mrubenstein@usgs.gov","middleInitial":"A.","affiliations":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true}],"preferred":true,"id":869279,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Weiskopf, Sarah R. 0000-0002-5933-8191","orcid":"https://orcid.org/0000-0002-5933-8191","contributorId":207699,"corporation":false,"usgs":true,"family":"Weiskopf","given":"Sarah","email":"","middleInitial":"R.","affiliations":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true}],"preferred":true,"id":869278,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bertrand, Romain","contributorId":304118,"corporation":false,"usgs":false,"family":"Bertrand","given":"Romain","email":"","affiliations":[{"id":65973,"text":"Universitéde Toulouse 3, Toulouse, France","active":true,"usgs":false}],"preferred":false,"id":869280,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Carter, Shawn 0000-0002-0045-4681","orcid":"https://orcid.org/0000-0002-0045-4681","contributorId":216490,"corporation":false,"usgs":true,"family":"Carter","given":"Shawn","affiliations":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true}],"preferred":true,"id":869281,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Comte, Lise","contributorId":304119,"corporation":false,"usgs":false,"family":"Comte","given":"Lise","email":"","affiliations":[{"id":65974,"text":"College of Arts and Sciences, Illinois State University","active":true,"usgs":false}],"preferred":false,"id":869282,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Eaton, Mitchell J. 0000-0001-7324-6333","orcid":"https://orcid.org/0000-0001-7324-6333","contributorId":213526,"corporation":false,"usgs":true,"family":"Eaton","given":"Mitchell","middleInitial":"J.","affiliations":[{"id":565,"text":"Southeast Climate Science Center","active":true,"usgs":true}],"preferred":true,"id":869283,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Johnson, Ciara G.","contributorId":271273,"corporation":false,"usgs":false,"family":"Johnson","given":"Ciara","email":"","middleInitial":"G.","affiliations":[{"id":12909,"text":"George Mason University","active":true,"usgs":false}],"preferred":false,"id":869284,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Lenoir, Jonathan","contributorId":167876,"corporation":false,"usgs":false,"family":"Lenoir","given":"Jonathan","email":"","affiliations":[{"id":24849,"text":"Université de Picardie Jules Verne","active":true,"usgs":false}],"preferred":false,"id":869285,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Lynch, Abigail 0000-0001-8449-8392","orcid":"https://orcid.org/0000-0001-8449-8392","contributorId":216203,"corporation":false,"usgs":true,"family":"Lynch","given":"Abigail","affiliations":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true}],"preferred":true,"id":869286,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Miller, Brian W. 0000-0003-1716-1161","orcid":"https://orcid.org/0000-0003-1716-1161","contributorId":196603,"corporation":false,"usgs":true,"family":"Miller","given":"Brian","email":"","middleInitial":"W.","affiliations":[{"id":36940,"text":"National Climate Adaptation Science Center","active":true,"usgs":true}],"preferred":true,"id":869287,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Morelli, Toni Lyn 0000-0001-5865-5294 tmorelli@usgs.gov","orcid":"https://orcid.org/0000-0001-5865-5294","contributorId":197458,"corporation":false,"usgs":true,"family":"Morelli","given":"Toni","email":"tmorelli@usgs.gov","middleInitial":"Lyn","affiliations":[{"id":5080,"text":"Northeast Climate Adaptation Science Center","active":true,"usgs":true},{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true}],"preferred":true,"id":869288,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Rodriguez, Mari Angel 0000-0002-3372-1897","orcid":"https://orcid.org/0000-0002-3372-1897","contributorId":224776,"corporation":false,"usgs":true,"family":"Rodriguez","given":"Mari","email":"","middleInitial":"Angel","affiliations":[{"id":36940,"text":"National Climate Adaptation Science Center","active":true,"usgs":true}],"preferred":true,"id":869289,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Terando, Adam 0000-0002-9280-043X","orcid":"https://orcid.org/0000-0002-9280-043X","contributorId":205908,"corporation":false,"usgs":true,"family":"Terando","given":"Adam","affiliations":[{"id":565,"text":"Southeast Climate Science Center","active":true,"usgs":true}],"preferred":true,"id":869290,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Thompson, Laura 0000-0002-7884-6001","orcid":"https://orcid.org/0000-0002-7884-6001","contributorId":207364,"corporation":false,"usgs":true,"family":"Thompson","given":"Laura","affiliations":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true}],"preferred":true,"id":869291,"contributorType":{"id":1,"text":"Authors"},"rank":14}]}}
,{"id":70248875,"text":"70248875 - 2023 - Shorebird monitoring using spatially explicit occupancy and abundance","interactions":[],"lastModifiedDate":"2023-09-25T11:49:53.727957","indexId":"70248875","displayToPublicDate":"2023-04-11T06:46:23","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2596,"text":"Land","active":true,"publicationSubtype":{"id":10}},"title":"Shorebird monitoring using spatially explicit occupancy and abundance","docAbstract":"<div class=\"html-p\">Loss of habitat and human disturbance are major factors in the worldwide decline of shorebird populations, including that of the threatened migratory piping plover (<span class=\"html-italic\">Charadrius melodus</span>). From 2013 to 2018, we conducted land-based surveys of the shorebird community every other week during the peak piping plover season (September to March). We assessed the ability of a thin plate spline occupancy model to identify hotspot locations on Whiskey Island, Louisiana, for the piping plover and four additional shorebird species (Wilson’s plover (<span class=\"html-italic\">Charadrius wilsonia</span>), snowy plover (<span class=\"html-italic\">Charadrius nivosus</span>), American oystercatcher (<span class=\"html-italic\">Haematopus palliatus</span>), and red knot (<span class=\"html-italic\">Calidris canutus</span>)). By fitting single-species occupancy models with geographic thin plate spline parameters, hotspot priority regions for conserving piping plovers and the multispecies shorebird assemblage were identified on the island. The occupancy environmental covariate, distance to the coastline, was weakly fitting, where the spatially explicit models were heavily dependent on the spatial spline parameter for distribution estimation. Additionally, the detectability parameters for Julian date and tide stage affected model estimations, resulting in seemingly inflated estimates compared to assuming perfect detection. The models predicted species distributions, biodiversity, high-use habitats for conservation, and multispecies conservation areas using a thin-plate spline for spatially explicit estimation without significant landscape variables, demonstrating the applicability of this modeling approach for defining areas on a landscape that are more heavily used by a species or multiple species.</div>","language":"English","publisher":"MDPI","doi":"10.3390/land12040863","usgsCitation":"Bohnett, E., Schulz, J., Dobbs, R., Hoctor, T., Hulse, D., Ahmad, B., Rashid, W., and Waddle, H., 2023, Shorebird monitoring using spatially explicit occupancy and abundance: Land, v. 12, no. 4, 863, 15 p., https://doi.org/10.3390/land12040863.","productDescription":"863, 15 p.","ipdsId":"IP-146627","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":443891,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/land12040863","text":"Publisher Index Page"},{"id":435382,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P93MVS0S","text":"USGS data release","linkHelpText":"Evaluating if abundance and behavior of shorebird species are related to restoration and habitat at Whiskey Island and Caminada Headland, Louisiana from 2012 to 2020"},{"id":421119,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Louisiana","otherGeospatial":"Whiskey Island","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -90.64800967611227,\n              29.110571625127676\n            ],\n            [\n              -90.64800967611227,\n              29.07849153917428\n            ],\n            [\n              -90.56579430804571,\n              29.07849153917428\n            ],\n            [\n              -90.56579430804571,\n              29.110571625127676\n            ],\n            [\n              -90.64800967611227,\n              29.110571625127676\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"12","issue":"4","noUsgsAuthors":false,"publicationDate":"2023-04-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Bohnett, Eve","contributorId":272548,"corporation":false,"usgs":false,"family":"Bohnett","given":"Eve","email":"","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":884011,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schulz, Jessica","contributorId":330111,"corporation":false,"usgs":false,"family":"Schulz","given":"Jessica","affiliations":[{"id":52994,"text":"New Hampshire Department of Environmental Services","active":true,"usgs":false}],"preferred":false,"id":884012,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dobbs, Robert C. 0000-0002-9079-7249 rdobbs@usgs.gov","orcid":"https://orcid.org/0000-0002-9079-7249","contributorId":200300,"corporation":false,"usgs":false,"family":"Dobbs","given":"Robert C.","email":"rdobbs@usgs.gov","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":false,"id":884013,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hoctor, Thomas","contributorId":330115,"corporation":false,"usgs":false,"family":"Hoctor","given":"Thomas","email":"","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":884014,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hulse, Dave","contributorId":330116,"corporation":false,"usgs":false,"family":"Hulse","given":"Dave","email":"","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":884015,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ahmad, Bilal","contributorId":330120,"corporation":false,"usgs":false,"family":"Ahmad","given":"Bilal","email":"","affiliations":[{"id":78816,"text":"University of Swat, Pakistan","active":true,"usgs":false}],"preferred":false,"id":884016,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Rashid, Wajid","contributorId":330121,"corporation":false,"usgs":false,"family":"Rashid","given":"Wajid","email":"","affiliations":[{"id":78816,"text":"University of Swat, Pakistan","active":true,"usgs":false}],"preferred":false,"id":884017,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Waddle, Hardin 0000-0003-1940-2133","orcid":"https://orcid.org/0000-0003-1940-2133","contributorId":222187,"corporation":false,"usgs":true,"family":"Waddle","given":"Hardin","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":884018,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70256519,"text":"70256519 - 2023 - Evaluating regional length limits in freshwater fisheries","interactions":[],"lastModifiedDate":"2024-08-21T11:10:11.652094","indexId":"70256519","displayToPublicDate":"2023-04-11T06:09:18","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":6455,"text":"Canadian Journal Fisheries and Aquatic Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Evaluating regional length limits in freshwater fisheries","docAbstract":"<div id=\"abstracts\" data-extent=\"frontmatter\"><div class=\"core-container\"><div>Length limits are often used in recreational fisheries management to prevent overharvest and manipulate fish size distributions. These regulations are ideally customized to meet water-specific stock dynamics and fishery objectives. However, in districts with numerous discrete waters, fisheries are commonly managed with a universal regional regulation. Evaluating alternative regional length limits requires consideration of management objectives that may not be important at the single-system level but that emerge as relevant at the regional scale, such as uniformity of regional harvest, diversity of average catch sizes, and opportunity to harvest. We developed a flexible tool for evaluating regional length limits. The tool joins the well-established Beverton–Holt yield-per-recruit model with elements of decision-support methods. The model quantifies regional management objectives as utility functions that are weighted and summed into a single value used to evaluate alternative length limits. The flexibility of the tool stems from its capacity to consider a mixture of stock parameters and associated uncertainty to evaluate multiple length limits, weighting an array of regional fishery objectives quantified by various performance metrics. This adjustability affords flexibility to consider a diversity of options that can stimulate innovation in setting regional length limits. We demonstrate the model by evaluating varying length limits on fishery objectives related to the management of hypothetical yellow perch (<i>Perca flavescens</i>) populations and real black crappie (<i>Pomoxis nigromaculatus</i>) populations.</div></div></div>","language":"English","publisher":"Canadian Science Publishing","doi":"10.1139/cjfas-2022-0179","usgsCitation":"Shamaskin, A.C., Colvin, M., and Miranda, L.E., 2023, Evaluating regional length limits in freshwater fisheries: Canadian Journal Fisheries and Aquatic Sciences, v. 80, no. 8, https://doi.org/10.1139/cjfas-2022-0179.","ipdsId":"IP-142911","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":501068,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/1807/127338","text":"External Repository"},{"id":432974,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"80","issue":"8","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Shamaskin, Andrew C.","contributorId":341003,"corporation":false,"usgs":false,"family":"Shamaskin","given":"Andrew","email":"","middleInitial":"C.","affiliations":[{"id":17848,"text":"Mississippi State University","active":true,"usgs":false}],"preferred":false,"id":907787,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Colvin, Michael E.","contributorId":264842,"corporation":false,"usgs":false,"family":"Colvin","given":"Michael E.","affiliations":[{"id":17848,"text":"Mississippi State University","active":true,"usgs":false}],"preferred":false,"id":907788,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Miranda, Leandro E. 0000-0002-2138-7924 smiranda@usgs.gov","orcid":"https://orcid.org/0000-0002-2138-7924","contributorId":531,"corporation":false,"usgs":true,"family":"Miranda","given":"Leandro","email":"smiranda@usgs.gov","middleInitial":"E.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":907789,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70266239,"text":"70266239 - 2023 - Laying sequence and oceanographic factors affect egg size in Scripps's Murrelets Synthliboramphus scrippsi at Santa Barbara Island","interactions":[],"lastModifiedDate":"2025-08-04T15:40:52.782654","indexId":"70266239","displayToPublicDate":"2023-04-10T00:00:00","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2675,"text":"Marine Ornithology: Journal of Seabird Research and Conservation","onlineIssn":"2074-1235","printIssn":"1018-3337","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Laying sequence and oceanographic factors affect egg size in Scripps's Murrelets <i>Synthliboramphus scrippsi</i> at Santa Barbara Island","title":"Laying sequence and oceanographic factors affect egg size in Scripps's Murrelets Synthliboramphus scrippsi at Santa Barbara Island","docAbstract":"<p><span>Egg size is an important avian life history parameter, with larger eggs indicating greater investment of resources in the chick. Prey availability can affect such investment. We investigated the effects of oceanographic conditions and laying sequence on Scripps's Murrelet&nbsp;</span><i>Synthliboramphus scrippsi</i><span>&nbsp;egg size at Santa Barbara Island, California during 2009-2017. We evaluated oceanographic covariates characterizing marine productivity for their effect on egg size, including large-scale oceanographic indices such as the Pacific Decadal Oscillation (PDO) index, Oceanic Niño Index (ONI), and North Pacific Gyre Oscillation (NPGO) index. We also evaluated a larval anchovy catch-per-unit-effort (ANCHL) index and the Biologically Effective Upwelling Transport Index (BEUTI) as region-wide indices, and sea surface temperature (SST) as a local index. We evaluated oceanographic conditions over the entire year and during the breeding season only. We also considered the contribution of lagged effects to oceanographic conditions. Our results generally ran counter to our hypothesis that increased ocean productivity should increase egg size. Based on Akaike's Information Criterion, the four top-ranked models provided support for an association between larger eggs and conditions indicative of lower oceanographic productivity, including lower values of BEUTI and NPGO, and higher values of ONI, PDO, and SST. The only result that supported our hypothesis was a positive relationship between ANCHL and egg size, although the 95% confidence interval for the effect included 0. The strongest relationship detected was between laying sequence and egg size, as second eggs were considerably larger than first eggs. Our results indicate substantial complexity in the relationship between ocean productivity and seabird demography. A better understanding of how ocean productivity affects seabird breeding outcomes through multiple mechanisms will help improve predictions of how seabirds will respond to changing ocean conditions.</span></p>","language":"English","publisher":"Marine Ornithology","doi":"10.5038/2074-1235.51.1.1503","usgsCitation":"Zaragoza, M., DuVall, A., Howard, J., Mazurkiewicz, D., and Converse, S.J., 2023, Laying sequence and oceanographic factors affect egg size in Scripps's Murrelets Synthliboramphus scrippsi at Santa Barbara Island: Marine Ornithology: Journal of Seabird Research and Conservation, v. 51, p. 1-9, https://doi.org/10.5038/2074-1235.51.1.1503.","productDescription":"9 p.","startPage":"1","endPage":"9","ipdsId":"IP-136381","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":494434,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5038/2074-1235.51.1.1503","text":"Publisher Index Page"},{"id":485392,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Santa Barbara Island","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -119.05661717686746,\n              33.49341793309826\n            ],\n            [\n              -119.05661717686746,\n              33.45600358149278\n            ],\n            [\n              -119.0156631801566,\n              33.45600358149278\n            ],\n            [\n              -119.0156631801566,\n              33.49341793309826\n            ],\n            [\n              -119.05661717686746,\n              33.49341793309826\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"51","noUsgsAuthors":false,"publicationDate":"2025-03-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Zaragoza, Marcela I. Todd","contributorId":354067,"corporation":false,"usgs":false,"family":"Zaragoza","given":"Marcela I. Todd","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":935058,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"DuVall, Amelia J.","contributorId":354068,"corporation":false,"usgs":false,"family":"DuVall","given":"Amelia J.","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":935059,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Howard, Jim A.","contributorId":354073,"corporation":false,"usgs":false,"family":"Howard","given":"Jim A.","affiliations":[{"id":84544,"text":"California Institute of Environmental","active":true,"usgs":false}],"preferred":false,"id":935060,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mazurkiewicz, David M.","contributorId":354074,"corporation":false,"usgs":false,"family":"Mazurkiewicz","given":"David M.","affiliations":[{"id":6993,"text":"Channel Islands National Park","active":true,"usgs":false}],"preferred":false,"id":935061,"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":935062,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70245407,"text":"70245407 - 2023 - Evaluating and mitigating the impact of systematic geolocation error on canopy height measurement performance of GEDI","interactions":[],"lastModifiedDate":"2023-06-23T13:33:45.396836","indexId":"70245407","displayToPublicDate":"2023-04-08T08:30:43","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3254,"text":"Remote Sensing of Environment","printIssn":"0034-4257","active":true,"publicationSubtype":{"id":10}},"title":"Evaluating and mitigating the impact of systematic geolocation error on canopy height measurement performance of GEDI","docAbstract":"<p><span>NASA's Global Ecosystem Dynamics Investigation (GEDI) is designed to provide high-resolution measurements of forest structure and topography between 52° N and S. However, current geolocation accuracy may limit further science applications of footprint-level products as early adopters have found it difficult to align with in-situ forestry inventory data and high-resolution imagery for calibration and validation purpose. Here we developed a new means to rapidly evaluate and mitigate the impact of systematic geolocation error on the performance of GEDI's forest height estimates in the US. By integrating nationwide high-resolution airborne&nbsp;</span>lidar<span>&nbsp;data collected through the 3D Elevation Program of the&nbsp;USGS, we provided optimal geolocation adjustments of GEDI at per beam level and tracked their performances over the first 18-mo. Our results suggest that the first release of GEDI product (R01) can have large systematic geolocation errors at beam level (i.e., 50.5% of beams with an error&nbsp;&gt;&nbsp;20&nbsp;m). Its impact on canopy height measurement could drastically vary in space and time, which in turn also offers a separate indirect method to evaluate and track geolocation performance. The second release of GEDI data (R02) has achieved a much-improved systematic geolocation accuracy which is shown to meet the mission requirement (0.2% beams &gt;20&nbsp;m and 80.8% beams &lt;10&nbsp;m) and should be able to meet requirements from many practical science applications tolerant to moderate geolocation errors. In sum, our approach has provided a short-term solution for an enhanced Cal/Val strategy for GEDI. While further improvements will certainly be made in future releases, it can potentially create an alternative pathway to generate and validate biomass products by linking GEDI footprint samples directly with in-situ data collections.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.rse.2023.113571","usgsCitation":"Tang, H., Stoker, J.M., Luthcke, S., Armston, J., Lee, K., Blair, B., and Hofton, M., 2023, Evaluating and mitigating the impact of systematic geolocation error on canopy height measurement performance of GEDI: Remote Sensing of Environment, v. 291, 113571, 13 p., https://doi.org/10.1016/j.rse.2023.113571.","productDescription":"113571, 13 p.","ipdsId":"IP-144120","costCenters":[{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"links":[{"id":443909,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.rse.2023.113571","text":"Publisher Index Page"},{"id":418400,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":418399,"rank":1,"type":{"id":12,"text":"Errata"},"url":"https://doi.org/10.1016/j.rse.2023.113663"}],"volume":"291","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Tang, Hao","contributorId":311206,"corporation":false,"usgs":false,"family":"Tang","given":"Hao","email":"","affiliations":[{"id":67355,"text":"Department of Geography, National University of Singapore, 117570, Singapore","active":true,"usgs":false}],"preferred":false,"id":876037,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stoker, Jason M. 0000-0003-2455-0931 jstoker@usgs.gov","orcid":"https://orcid.org/0000-0003-2455-0931","contributorId":3021,"corporation":false,"usgs":true,"family":"Stoker","given":"Jason","email":"jstoker@usgs.gov","middleInitial":"M.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"preferred":true,"id":876038,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Luthcke, Scott","contributorId":311207,"corporation":false,"usgs":false,"family":"Luthcke","given":"Scott","affiliations":[{"id":67357,"text":"NASA Goddard Space Flight Center, Greenbelt, MD 20771, USA","active":true,"usgs":false}],"preferred":false,"id":876039,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Armston, John","contributorId":311208,"corporation":false,"usgs":false,"family":"Armston","given":"John","email":"","affiliations":[{"id":67358,"text":"Department of Geographical Sciences, University of Maryland, College Park, MD 20770, USA","active":true,"usgs":false}],"preferred":false,"id":876040,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lee, Kyungtae","contributorId":311209,"corporation":false,"usgs":false,"family":"Lee","given":"Kyungtae","email":"","affiliations":[{"id":67358,"text":"Department of Geographical Sciences, University of Maryland, College Park, MD 20770, USA","active":true,"usgs":false}],"preferred":false,"id":876042,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Blair, Bryan","contributorId":311210,"corporation":false,"usgs":false,"family":"Blair","given":"Bryan","email":"","affiliations":[{"id":67357,"text":"NASA Goddard Space Flight Center, Greenbelt, MD 20771, USA","active":true,"usgs":false}],"preferred":false,"id":876043,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hofton, Michelle","contributorId":311211,"corporation":false,"usgs":false,"family":"Hofton","given":"Michelle","email":"","affiliations":[{"id":67358,"text":"Department of Geographical Sciences, University of Maryland, College Park, MD 20770, USA","active":true,"usgs":false}],"preferred":false,"id":876044,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70255158,"text":"70255158 - 2023 - Impact of wastewater treatment plant effluent on the winter thermal regime of two urban Colorado South Platte tributaries","interactions":[],"lastModifiedDate":"2024-06-14T13:57:55.896167","indexId":"70255158","displayToPublicDate":"2023-04-07T08:49:59","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":16456,"text":"Frontiers in Enviornmental Science","active":true,"publicationSubtype":{"id":10}},"title":"Impact of wastewater treatment plant effluent on the winter thermal regime of two urban Colorado South Platte tributaries","docAbstract":"<p><span>Wastewater treatment plant effluent can increase stream water temperature from near freezing to 5°C–12°C in winter months. Recent research in the South Platte River Basin in Colorado showed that this warming alters the reproductive timing of some fishes. However, the spatial extent and magnitude of this warming are unknown. Thus, we created winter water temperature models both upstream and downstream of effluent inputs for two urban tributaries of the South Platte River, the Big Thompson River, and St. Vrain Creek. We examined the influence of air temperature, discharge, effluent temperature, and distance downstream on water temperature over the winter period (December–February). The models were also used to predict water temperature in the absence of effluent and based on air temperature predictions in 2052 and 2082. Effluent temperature was the largest driver of water temperature downstream of the effluent, while the impact of air temperature was comparatively small. Streams cooled after an initially sharp temperature increase, though were still predicted to be ∼2°C greater than they would be in the absence of effluent at ∼0.5&nbsp;km. Predicted air temperatures in 2052 and 2082 had a negligible effect on water temperature, suggesting that mitigating effluent temperature is key to protecting the winter thermal regimes of effluent-impacted rivers. Our models can be used to gain insight into the magnitude and downstream extent of the impact of effluent temperature on small urban streams in winter and provide a baseline for models in other watersheds and at larger scales.</span></p>","language":"English","publisher":"Frontiers Media","doi":"10.3389/fenvs.2023.1120412","usgsCitation":"Adams, C., Winkelman, D.L., and Fitzpatrick, R., 2023, Impact of wastewater treatment plant effluent on the winter thermal regime of two urban Colorado South Platte tributaries: Frontiers in Enviornmental Science, v. 11, 1120412, 10 p., https://doi.org/10.3389/fenvs.2023.1120412.","productDescription":"1120412, 10 p.","ipdsId":"IP-149443","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":443916,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fenvs.2023.1120412","text":"Publisher Index Page"},{"id":430205,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"Big Thompson River","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -105.47113160280938,\n              40.490008852821404\n            ],\n            [\n              -105.47113160280938,\n              40.37392612322179\n            ],\n            [\n              -105.18090980925777,\n              40.37392612322179\n            ],\n            [\n              -105.18090980925777,\n              40.490008852821404\n            ],\n            [\n              -105.47113160280938,\n              40.490008852821404\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"11","noUsgsAuthors":false,"publicationDate":"2023-04-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Adams, Catherine M.","contributorId":338827,"corporation":false,"usgs":false,"family":"Adams","given":"Catherine M.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":903627,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Winkelman, Dana L. 0000-0002-5247-0114 danaw@usgs.gov","orcid":"https://orcid.org/0000-0002-5247-0114","contributorId":4141,"corporation":false,"usgs":true,"family":"Winkelman","given":"Dana","email":"danaw@usgs.gov","middleInitial":"L.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":903628,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fitzpatrick, Ryan M.","contributorId":338828,"corporation":false,"usgs":false,"family":"Fitzpatrick","given":"Ryan M.","affiliations":[{"id":39887,"text":"Colorado Parks and Wildlife","active":true,"usgs":false}],"preferred":false,"id":903629,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70242108,"text":"70242108 - 2023 - Predicting methane emissions and developing reduction strategies for a Central Appalachian Basin, USA, longwall mine through analysis and modeling of geology and degasification system performance","interactions":[],"lastModifiedDate":"2023-04-07T13:49:09.661815","indexId":"70242108","displayToPublicDate":"2023-04-07T08:41:52","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2033,"text":"International Journal of Coal Geology","active":true,"publicationSubtype":{"id":10}},"title":"Predicting methane emissions and developing reduction strategies for a Central Appalachian Basin, USA, longwall mine through analysis and modeling of geology and degasification system performance","docAbstract":"<p id=\"sp0175\">Coal mine methane is a safety concern in active mines due to explosion risk and an environmental concern due to the greenhouse gas (GHG) properties of methane emissions to the atmosphere. Depending on the mine design and operation, structural and stratigraphic characteristics of the geology, and the properties of coal beds affected by mining, a significant amount of methane can be released during coal extraction. These emissions may be low and uniform, but they also can be high and abrupt, if not captured by using pre- and post-mining methods of degasification or not controlled by ventilation during mining. Therefore, emissions should be monitored and predicted accurately for underground safety and GHG reduction. Ventilation and degasification systems should be designed accordingly by taking into account the mine geological properties and the degasification system's performance.</p><p id=\"sp0180\">This paper presents a comprehensive study to predict emissions and proposes alternatives to reduce emissions in a longwall mine extracting metallurgical coal from the Pocahontas No. 3 coal bed in Virginia (Central Appalachian Basin),<span>&nbsp;</span>USA. The work focused on mining activity in four adjacent panels through analysis and modeling of geology and evaluation of the performance of the methane control system. Results showed that the mine geology contained a significant amount of gas within and around the panel areas, which was controlled by utilizing different degasification methods besides ventilation during mining. The study showed that after pre-mining degasification using fractured vertical wells and in-seam horizontal wells, each panel potentially contained ∼19 MMscf and&nbsp;∼&nbsp;2 MMscf of gas remaining to be handled by the gob gas ventholes (GGVs) and the ventilation, respectively, per acre of mining. It was shown that extending the pre-mining degasification duration of vertical wells by as much as 4&nbsp;years or drilling more horizontal wells with closer spacing could significantly reduce ventilation and gob emissions during the mining of coal.</p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.coal.2023.104234","usgsCitation":"Karacan, C.O., 2023, Predicting methane emissions and developing reduction strategies for a Central Appalachian Basin, USA, longwall mine through analysis and modeling of geology and degasification system performance: International Journal of Coal Geology, v. 270, 104234, 25 p., https://doi.org/10.1016/j.coal.2023.104234.","productDescription":"104234, 25 p.","ipdsId":"IP-142173","costCenters":[{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"links":[{"id":415414,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Kentucky, Virginia, West Virginia","county":"Buchanan County","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -82.686048242248,\n              36.57702911764123\n            ],\n            [\n              -79.95590318884388,\n              36.57702911764123\n            ],\n            [\n              -79.95590318884388,\n              38.35520774391128\n            ],\n            [\n              -82.686048242248,\n              38.35520774391128\n            ],\n            [\n              -82.686048242248,\n              36.57702911764123\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"270","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Karacan, C. Ozgen 0000-0002-0947-8241","orcid":"https://orcid.org/0000-0002-0947-8241","contributorId":201991,"corporation":false,"usgs":true,"family":"Karacan","given":"C.","email":"","middleInitial":"Ozgen","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":868913,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70242136,"text":"70242136 - 2023 - Predicted aquatic exposure effects from a national urban stormwater study","interactions":[],"lastModifiedDate":"2023-12-04T16:57:15.989156","indexId":"70242136","displayToPublicDate":"2023-04-07T08:18:09","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":13794,"text":"Environmental Science: Water Research and Technology","active":true,"publicationSubtype":{"id":10}},"title":"Predicted aquatic exposure effects from a national urban stormwater study","docAbstract":"<p><span>A multi-agency study of 438 organic and 62 inorganic chemicals measured in urban stormwater during 50 total runoff events at 21 sites across the United States demonstrated that stormwater discharges can generate localized, aquatic exposures to extensive contaminant mixtures, including organics suspected to cause adverse aquatic-health effects. The aggregated risks to multiple aquatic trophic levels (fish, invertebrates, plants) of the stormwater mixture exposures, which were documented in the national study, were explored herein by calculating cumulative ratios of organic-contaminant&nbsp;</span><i>in vitro</i><span>&nbsp;exposure–activity cutoffs (∑</span><small><sub>EAR</sub></small><span>) and health-benchmark-weighted cumulative toxicity quotients (∑</span><small><sub>TQ</sub></small><span>). Both risk assessment approaches indicated substantial (moderate to high) risk for acute adverse effects to aquatic organisms across multiple trophic levels (fish, macroinvertebrates, non-vascular/vascular plants) at or near stormwater discharge points across the United States. The results are interpreted as potential orders of magnitude underestimates of actual aquatic risk in stormwater control wetlands or in the immediate vicinity of such discharges to surface-water receptors, because the 438 organic-compound analytical space assessed in this study is orders of magnitude less than the 350 000 parent compounds estimated to be in current commercial use globally and the incalculable chemical-space of potential metabolites and degradates.</span></p>","language":"English","publisher":"Royal Society of Chemistry","doi":"10.1039/D2EW00933A","usgsCitation":"Bradley, P., Romanok, K., Smalling, K., Masoner, J.R., Kolpin, D., and Gordon, S.E., 2023, Predicted aquatic exposure effects from a national urban stormwater study: Environmental Science: Water Research and Technology, v. 9, p. 3191-3199, https://doi.org/10.1039/D2EW00933A.","productDescription":"9 p.","startPage":"3191","endPage":"3199","ipdsId":"IP-124205","costCenters":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true},{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true},{"id":516,"text":"Oklahoma Water Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":35680,"text":"Illinois-Iowa-Missouri Water Science Center","active":true,"usgs":true}],"links":[{"id":443921,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"http://dx.doi.org/10.1039/d2ew00933a","text":"Publisher Index Page"},{"id":415409,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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States\"}}]}","volume":"9","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Bradley, Paul M. 0000-0001-7522-8606","orcid":"https://orcid.org/0000-0001-7522-8606","contributorId":221226,"corporation":false,"usgs":true,"family":"Bradley","given":"Paul M.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":559,"text":"South Carolina Water Science Center","active":true,"usgs":true}],"preferred":true,"id":868974,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Romanok, Kristin M. 0000-0002-8472-8765","orcid":"https://orcid.org/0000-0002-8472-8765","contributorId":221227,"corporation":false,"usgs":true,"family":"Romanok","given":"Kristin M.","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":868975,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"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":868976,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Masoner, Jason R. 0000-0002-4829-6379 jmasoner@usgs.gov","orcid":"https://orcid.org/0000-0002-4829-6379","contributorId":3193,"corporation":false,"usgs":true,"family":"Masoner","given":"Jason","email":"jmasoner@usgs.gov","middleInitial":"R.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":516,"text":"Oklahoma Water Science Center","active":true,"usgs":true}],"preferred":true,"id":868977,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kolpin, Dana W. 0000-0002-3529-6505","orcid":"https://orcid.org/0000-0002-3529-6505","contributorId":204154,"corporation":false,"usgs":true,"family":"Kolpin","given":"Dana W.","affiliations":[{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true},{"id":35680,"text":"Illinois-Iowa-Missouri Water Science Center","active":true,"usgs":true}],"preferred":true,"id":868978,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Gordon, Stephanie E. 0000-0002-6292-2612 sgordon@usgs.gov","orcid":"https://orcid.org/0000-0002-6292-2612","contributorId":200931,"corporation":false,"usgs":true,"family":"Gordon","given":"Stephanie","email":"sgordon@usgs.gov","middleInitial":"E.","affiliations":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":868979,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70244272,"text":"70244272 - 2023 - Assessing large landscape patterns of potential fire connectivity using circuit methods","interactions":[],"lastModifiedDate":"2023-06-12T11:24:05.990292","indexId":"70244272","displayToPublicDate":"2023-04-07T06:17:36","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2602,"text":"Landscape Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Assessing large landscape patterns of potential fire connectivity using circuit methods","docAbstract":"<h3 class=\"c-article__sub-heading\" data-test=\"abstract-sub-heading\">Context</h3><p>Minimizing negative impacts of wildfire is a major societal objective in fire-prone landscapes. Models of fire connectivity can aid in understanding and managing wildfires by analyzing potential fire spread and conductance patterns. We define ‘fire connectivity’ as the landscape’s capacity to facilitate fire transmission from one point on the landscape to another.</p><h3 class=\"c-article__sub-heading\" data-test=\"abstract-sub-heading\">Objectives</h3><p>Our objective was to develop an approach for modeling fire connectivity patterns representing potential fire spread and relative flow across a broad landscape extent, particularly in the management-relevant context of fuel breaks.</p><h3 class=\"c-article__sub-heading\" data-test=\"abstract-sub-heading\">Methods</h3><p>We applied an omnidirectional circuit theory algorithm to model fire connectivity in the Great Basin of the western United States. We used predicted rates of fire spread to approximate conductance and calculated current densities to identify connections among areas with high spread rates. We compared existing and planned fuel breaks with fire connectivity patterns.</p><h3 class=\"c-article__sub-heading\" data-test=\"abstract-sub-heading\">Results</h3><p>Fire connectivity and relative flow outputs were characterized by spatial heterogeneity in the landscape’s capacity to transmit fire. We found that existing fuel break networks were denser in areas with relatively diffuse and impeded flow patterns, rather than in locations with channelized flow.</p><h3 class=\"c-article__sub-heading\" data-test=\"abstract-sub-heading\">Conclusions</h3><p>This approach could be paired with traditional fire behavior and risk analyses to better understand wildfire spread as well as direct strategic placement of individual fuel breaks within larger networks to constrain fire spread. Thus, our findings may offer local- to landscape-level support for management actions that aim to disrupt fire spread and mitigate the costs of fire on the landscape.</p>","language":"English","publisher":"Springer","doi":"10.1007/s10980-022-01581-y","usgsCitation":"Buchholtz, E.K., Kreitler, J.R., Shinneman, D.J., Crist, M., and Heinrichs, J., 2023, Assessing large landscape patterns of potential fire connectivity using circuit methods: Landscape Ecology, v. 38, p. 1663-1676, https://doi.org/10.1007/s10980-022-01581-y.","productDescription":"14 p.","startPage":"1663","endPage":"1676","ipdsId":"IP-138309","costCenters":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":443924,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10980-022-01581-y","text":"Publisher Index Page"},{"id":435384,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9EA3E00","text":"USGS data release","linkHelpText":"Circuit-based potential fire connectivity and relative flow patterns in the Great Basin, United States, 270 meters"},{"id":417995,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Idaho, Nevada, Oregon, Utah","otherGeospatial":"Great Basin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -121.51991830833018,\n              44.189247821751025\n            ],\n            [\n              -121.51991830833018,\n              37.1713133111553\n            ],\n            [\n              -110.58222834230502,\n              37.1713133111553\n            ],\n            [\n              -110.58222834230502,\n              44.189247821751025\n            ],\n            [\n              -121.51991830833018,\n              44.189247821751025\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"38","noUsgsAuthors":false,"publicationDate":"2023-04-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Buchholtz, Erin K. 0000-0002-1985-9531","orcid":"https://orcid.org/0000-0002-1985-9531","contributorId":300162,"corporation":false,"usgs":true,"family":"Buchholtz","given":"Erin","middleInitial":"K.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":875111,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kreitler, Jason R. 0000-0002-0243-5281 jkreitler@usgs.gov","orcid":"https://orcid.org/0000-0002-0243-5281","contributorId":4050,"corporation":false,"usgs":true,"family":"Kreitler","given":"Jason","email":"jkreitler@usgs.gov","middleInitial":"R.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":875112,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shinneman, Douglas J. 0000-0002-4909-5181 dshinneman@usgs.gov","orcid":"https://orcid.org/0000-0002-4909-5181","contributorId":147745,"corporation":false,"usgs":true,"family":"Shinneman","given":"Douglas","email":"dshinneman@usgs.gov","middleInitial":"J.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":true,"id":875113,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Crist, Michele R.","contributorId":178453,"corporation":false,"usgs":false,"family":"Crist","given":"Michele R.","affiliations":[],"preferred":false,"id":875114,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Heinrichs, Julie A. 0000-0001-7733-5034","orcid":"https://orcid.org/0000-0001-7733-5034","contributorId":240888,"corporation":false,"usgs":false,"family":"Heinrichs","given":"Julie A.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":875115,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70243875,"text":"70243875 - 2023 - Time-lapse seafloor surveys reveal how turbidity currents and internal tides in Monterey Canyon interact with the seabed at centimeter-scale","interactions":[],"lastModifiedDate":"2023-05-24T17:02:25.974335","indexId":"70243875","displayToPublicDate":"2023-04-06T11:56:41","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5739,"text":"Journal of Geophysical Research: Earth Surface","onlineIssn":"2169-9011","active":true,"publicationSubtype":{"id":10}},"title":"Time-lapse seafloor surveys reveal how turbidity currents and internal tides in Monterey Canyon interact with the seabed at centimeter-scale","docAbstract":"<p><span>Here we show how ultra-high resolution seabed mapping using new technology can help to understand processes that sculpt submarine canyons. Time-lapse seafloor surveys were conducted in the axis of Monterey Canyon, ∼50&nbsp;km from the canyon head (∼1,840&nbsp;m water depth) over an 18-month period. These surveys comprised 5-cm resolution multibeam bathymetry, 1-cm resolution lidar bathymetry, and 2-mm resolution stereophotographic imagery. Bathymetry data reveal centimeter-scale textures that would be undetectable by more traditional survey methods. Upward-looking Acoustic Doppler Current Profilers at the site recorded the flow character of internal tides and the passage of three turbidity currents, while sediment cores collected from the site record flow deposits. Combined with flow and core data, the bathymetry shows how turbidity currents and internal tides modify the seabed. The turbidity currents drape sediment across the site, infilling bedform troughs and smoothing erosional features carved by the internal tides (e.g., rippled scours). Turbidity currents with speeds of 0.9–3.3&nbsp;m/s failed to cause notable bedform movement, which is surprising given that flows with similar speeds produced rapid bedform migration elsewhere, including the upper Monterey Canyon. The lack of migration may be related to the character of the underlying substrate or indicate that turbidity currents at the site lack dense, near-bed layers. The scale of scours produced by the internal tides (≤0.7&nbsp;m/s) approaches the scale of features recorded in the ancient rock record. Thus, these results illustrate how the scale gap between seabed mapping technology and the rock record may eventually be bridged.</span></p>","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2022JF006705","usgsCitation":"Wolfson-Schwehr, M., Paull, C.K., Caress, D.W., Gwiazda, R., Nieminski, N.M., Talling, P.J., Carvajal, C., Simmons, S.M., and Troni, G., 2023, Time-lapse seafloor surveys reveal how turbidity currents and internal tides in Monterey Canyon interact with the seabed at centimeter-scale: Journal of Geophysical Research: Earth Surface, v. 128, no. 4, e2022JF006705, 22 p., https://doi.org/10.1029/2022JF006705.","productDescription":"e2022JF006705, 22 p.","ipdsId":"IP-136210","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":443928,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2022jf006705","text":"Publisher Index Page"},{"id":417402,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Monterey Canyon","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -122.095833,\n              36.704167\n            ],\n            [\n              -122.095833,\n              36.7\n            ],\n            [\n              -122.0875,\n              36.7\n            ],\n            [\n              -122.0875,\n              36.704167\n            ],\n            [\n              -122.095833,\n              36.704167\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"128","issue":"4","noUsgsAuthors":false,"publicationDate":"2023-04-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Wolfson-Schwehr, Monica","contributorId":175112,"corporation":false,"usgs":false,"family":"Wolfson-Schwehr","given":"Monica","email":"","affiliations":[],"preferred":false,"id":873579,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Paull, Charles K. 0000-0001-5940-3443","orcid":"https://orcid.org/0000-0001-5940-3443","contributorId":55825,"corporation":false,"usgs":false,"family":"Paull","given":"Charles","email":"","middleInitial":"K.","affiliations":[{"id":7043,"text":"University of North Carolina","active":true,"usgs":false}],"preferred":true,"id":873580,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Caress, David W.","contributorId":147392,"corporation":false,"usgs":false,"family":"Caress","given":"David","email":"","middleInitial":"W.","affiliations":[{"id":16837,"text":"MBARI","active":true,"usgs":false}],"preferred":false,"id":873581,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gwiazda, Roberto","contributorId":147193,"corporation":false,"usgs":false,"family":"Gwiazda","given":"Roberto","email":"","affiliations":[{"id":13620,"text":"Monterey Bay Aquarium Research Institute, Moss Landing, California","active":true,"usgs":false}],"preferred":false,"id":873582,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Nieminski, Nora Maria 0000-0002-4465-8731","orcid":"https://orcid.org/0000-0002-4465-8731","contributorId":279764,"corporation":false,"usgs":true,"family":"Nieminski","given":"Nora","email":"","middleInitial":"Maria","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":873583,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Talling, Peter J.","contributorId":195515,"corporation":false,"usgs":false,"family":"Talling","given":"Peter","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":873584,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Carvajal, Cristian","contributorId":204133,"corporation":false,"usgs":false,"family":"Carvajal","given":"Cristian","email":"","affiliations":[{"id":16837,"text":"MBARI","active":true,"usgs":false}],"preferred":false,"id":873585,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Simmons, Stephen M.","contributorId":305699,"corporation":false,"usgs":false,"family":"Simmons","given":"Stephen","email":"","middleInitial":"M.","affiliations":[{"id":40174,"text":"University of Hull","active":true,"usgs":false}],"preferred":false,"id":873586,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Troni, Giancarlo","contributorId":305700,"corporation":false,"usgs":false,"family":"Troni","given":"Giancarlo","email":"","affiliations":[{"id":66274,"text":"Pontifica Universidad Catolica de Chile","active":true,"usgs":false}],"preferred":false,"id":873587,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70242689,"text":"70242689 - 2023 - Planktic foraminifera","interactions":[],"lastModifiedDate":"2023-04-18T13:28:58.734306","indexId":"70242689","displayToPublicDate":"2023-04-06T08:27:29","publicationYear":"2023","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Planktic foraminifera","docAbstract":"<p><span>Planktic foraminifera are single-celled marine organisms that secrete&nbsp;calcium carbonate&nbsp;tests. They live in the ocean's&nbsp;photic zone, and when they die, their tests, each about the size of a grain of sand, collect on the ocean floor. The geographic distribution of planktic foraminifera is mostly governed by the temperature and salinity of the ocean surface, and species assemblages are generally arranged in latitudinal bands from polar to tropical, with more species occupying warmer waters. Their ubiquity in the world's oceans since the&nbsp;</span>Cretaceous Period<span>&nbsp;makes them ideal biostratigraphic markers, and their sensitivity to environmental changes makes them excellent proxies of past ecological, oceanographic and climatic history.</span></p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Reference module in earth systems and environmental sciences","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Elsevier","doi":"10.1016/B978-0-323-99931-1.00041-6","usgsCitation":"Dowsett, H., and Robinson, M., 2023, Planktic foraminifera, chap. <i>of</i> Reference module in earth systems and environmental sciences, HTML Document, https://doi.org/10.1016/B978-0-323-99931-1.00041-6.","productDescription":"HTML Document","ipdsId":"IP-149364","costCenters":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":415912,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Dowsett, Harry J. 0000-0003-1983-7524","orcid":"https://orcid.org/0000-0003-1983-7524","contributorId":261665,"corporation":false,"usgs":true,"family":"Dowsett","given":"Harry J.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":869378,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Robinson, Marci M. 0000-0002-9200-4097","orcid":"https://orcid.org/0000-0002-9200-4097","contributorId":261664,"corporation":false,"usgs":true,"family":"Robinson","given":"Marci M.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":869379,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70242657,"text":"70242657 - 2023 - Knowledge coproduction on the impact of decisions for waterbird habitat in a changing climate","interactions":[],"lastModifiedDate":"2023-10-11T15:17:00.654848","indexId":"70242657","displayToPublicDate":"2023-04-06T06:58:42","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1321,"text":"Conservation Biology","active":true,"publicationSubtype":{"id":10}},"title":"Knowledge coproduction on the impact of decisions for waterbird habitat in a changing climate","docAbstract":"<p>Scientists, resource managers, and decision-makers increasingly use knowledge co-production to guide the stewardship of future landscapes under climate change. This process was applied in the California Central Valley, USA to solve complex conservation problems, where managed wetlands and croplands are flooded between fall and spring to support some of the largest concentrations of shorebirds and waterfowl in the world. We co-produced scenario narratives, spatially-explicit flooded waterbird habitat models, data products, and new knowledge about climate adaptation potential. We document our co-production process, and using the co-produced models, we ask: “when and where do management actions make a difference?” and “when does climate override these actions?” The outcomes of this process provide lessons learned on how to co-create usable information and how to increase climate adaptive capacity in a highly managed landscape. We found that: 1) actions to restore wetlands and prioritize their water supply create habitat outcomes resilient to climate change impacts particularly in March, when habitat is most limited, 2) land protection combined with management can increase the ecosystem's resilience to climate change, and 3) the uptake and use of this information was influenced by the roles of different stakeholders, plus rapidly changing water policies, discrepancies in decision-making time frames, and immediate crises of extreme drought. While a broad stakeholder group contributed knowledge to scenario narratives and model development, to co-produce usable information, data products were tailored to a small set of decision contexts, leading to fewer stakeholder participants over time. A boundary organization convened stakeholders across a large landscape, and early adopters helped to build legitimacy, yet broad-scale use of climate adaptation knowledge will depend on state and local policies, engagement with decision-makers that have legislative and budgetary authority, and the capacity to fit data products to specific decision needs.</p>","language":"English","publisher":"Society for Conservation Biology","doi":"10.1111/cobi.14089","usgsCitation":"Byrd, K.B., Matchett, E., Mengelt, C., Wilson, T., DiPietro, D., Moritsch, M., Conlisk, E., Veloz, S., Casazza, M.L., and Reiter, M., 2023, Knowledge coproduction on the impact of decisions for waterbird habitat in a changing climate: Conservation Biology, v. 37, no. 5, e14089, 12 p., https://doi.org/10.1111/cobi.14089.","productDescription":"e14089, 12 p.","ipdsId":"IP-145413","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":499259,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/cobi.14089","text":"Publisher Index Page"},{"id":415649,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Central Valley","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -122.5,\n              39.75\n            ],\n            [\n              -122.5,\n              35.5\n            ],\n            [\n              -118.5,\n              35.5\n            ],\n            [\n              -118.5,\n              39.75\n            ],\n            [\n              -122.5,\n              39.75\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"37","issue":"5","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Byrd, Kristin B. 0000-0002-5725-7486 kbyrd@usgs.gov","orcid":"https://orcid.org/0000-0002-5725-7486","contributorId":3814,"corporation":false,"usgs":true,"family":"Byrd","given":"Kristin","email":"kbyrd@usgs.gov","middleInitial":"B.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":869232,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Matchett, Elliott 0000-0001-5095-2884 ematchett@usgs.gov","orcid":"https://orcid.org/0000-0001-5095-2884","contributorId":5541,"corporation":false,"usgs":true,"family":"Matchett","given":"Elliott","email":"ematchett@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":869233,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mengelt, Claudia 0000-0001-7869-5170","orcid":"https://orcid.org/0000-0001-7869-5170","contributorId":304087,"corporation":false,"usgs":true,"family":"Mengelt","given":"Claudia","email":"","affiliations":[{"id":506,"text":"Office of the AD Ecosystems","active":true,"usgs":true}],"preferred":true,"id":869234,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wilson, Tamara 0000-0001-7399-7532 tswilson@usgs.gov","orcid":"https://orcid.org/0000-0001-7399-7532","contributorId":2975,"corporation":false,"usgs":true,"family":"Wilson","given":"Tamara","email":"tswilson@usgs.gov","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":869235,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"DiPietro, Deanne","contributorId":304089,"corporation":false,"usgs":false,"family":"DiPietro","given":"Deanne","email":"","affiliations":[{"id":38279,"text":"Conservation Biology Institute","active":true,"usgs":false}],"preferred":false,"id":869236,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Moritsch, Monica","contributorId":304091,"corporation":false,"usgs":false,"family":"Moritsch","given":"Monica","affiliations":[{"id":65966,"text":"EDF","active":true,"usgs":false}],"preferred":false,"id":869237,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Conlisk, Erin","contributorId":304092,"corporation":false,"usgs":false,"family":"Conlisk","given":"Erin","affiliations":[{"id":17734,"text":"Point Blue Conservation Science","active":true,"usgs":false}],"preferred":false,"id":869238,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Veloz, Sam","contributorId":304093,"corporation":false,"usgs":false,"family":"Veloz","given":"Sam","affiliations":[{"id":17734,"text":"Point Blue Conservation Science","active":true,"usgs":false}],"preferred":false,"id":869239,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Casazza, Michael L. 0000-0002-5636-735X mike_casazza@usgs.gov","orcid":"https://orcid.org/0000-0002-5636-735X","contributorId":2091,"corporation":false,"usgs":true,"family":"Casazza","given":"Michael","email":"mike_casazza@usgs.gov","middleInitial":"L.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":869240,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Reiter, Matthew","contributorId":304094,"corporation":false,"usgs":false,"family":"Reiter","given":"Matthew","affiliations":[{"id":17734,"text":"Point Blue Conservation 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,{"id":70258667,"text":"70258667 - 2023 - Subsurface porewater flow accelerates talik development under the Alaska Highway, Yukon: A prelude to road collapse and permafrost thaw?","interactions":[],"lastModifiedDate":"2024-09-20T11:45:49.293096","indexId":"70258667","displayToPublicDate":"2023-04-06T06:42:01","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":11438,"text":"Water Resource Research","active":true,"publicationSubtype":{"id":10}},"title":"Subsurface porewater flow accelerates talik development under the Alaska Highway, Yukon: A prelude to road collapse and permafrost thaw?","docAbstract":"<div class=\"article-section__content en main\"><p>The presence of taliks (perennially unfrozen zones in permafrost areas) adversely affects the thermal stability of infrastructure in cold regions, including roads. The role of heat advection on talik development and feedback on permafrost degradation has not been quantified methodically in this context. We incorporate a surface energy balance model into a coupled groundwater flow and energy transport numerical model (SUTRA-ice). The model, calibrated with long-term observations (1997–2018 on the Alaska Highway), is used to investigate and quantify the role of heat advection on talik initiation and development under a road embankment. Over the 25-year simulation period, the new model is driven by reconstructed meteorological data and has a good agreement with near surface soil temperatures. The model successfully reproduces the increasing depth to the permafrost table (mean absolute error &lt;0.2&nbsp;m), and talik development. The results demonstrate that heat advection provides an additional energy source that expedites the rate of permafrost thaw and roughly doubles the rate of permafrost table deepening, compared to purely conductive thawing. Talik initially formed and grew over time under the combined effect of water flow, snow insulation, road construction and climate warming. Talik formation creates a new thermal state under the road embankment, resulting in acceleration of underlying permafrost degradation, due to the positive feedback of heat accumulation created by trapped unfrozen water. In a changing climate, mobile water flow will play a more important role in permafrost thaw and talik development under road embankments, and is likely to significantly increase maintenance costs and reduce the long-term stability of the infrastructure.</p></div>","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2022WR032578","usgsCitation":"Chen, L., Fortier, D., McKenzie, J.M., Voss, C., and Lamontagne-Halle, P., 2023, Subsurface porewater flow accelerates talik development under the Alaska Highway, Yukon: A prelude to road collapse and permafrost thaw?: Water Resource Research, v. 59, no. 4, e2022WR032578, 21 p., https://doi.org/10.1029/2022WR032578.","productDescription":"e2022WR032578, 21 p.","ipdsId":"IP-144274","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":467115,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2022wr032578","text":"Publisher Index Page"},{"id":462119,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada","otherGeospatial":"Yukon","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            -141.53437844422567,\n            69.80626078042113\n          ],\n          [\n            -141.35859719422575,\n            60.10426959701812\n          ],\n          [\n            -138.1945346942257,\n            59.663280929580196\n          ],\n          [\n            -122.7257846942255,\n            59.663280929580196\n          ],\n          [\n            -124.4835971942257,\n            61.30821251748273\n          ],\n          [\n            -125.88984719422555,\n            61.30821251748273\n          ],\n          [\n            -127.82344094422567,\n            62.0173853261021\n          ],\n          [\n            -128.8781284442257,\n            62.99114869965834\n          ],\n          [\n            -129.5812534442256,\n            63.894845633989036\n          ],\n          [\n            -130.98750344422547,\n            64.9197990155574\n          ],\n          [\n            -131.16328469422564,\n            65.39976918418793\n          ],\n          [\n            -131.7785190692255,\n            66.26330212065466\n          ],\n          [\n            -132.39375344422558,\n            66.54474901496525\n          ],\n          [\n            -133.09687844422552,\n            67.23464489690826\n          ],\n          [\n            -135.38203469422572,\n            67.3025687364092\n          ],\n          [\n            -135.64570656922572,\n            68.68531115379355\n          ],\n          [\n            -136.26094094422555,\n            69.22186457595464\n          ],\n          [\n            -138.54609719422552,\n            69.68455292065909\n          ],\n          [\n            -139.95234719422564,\n            69.95741322614839\n          ],\n          [\n            -141.53437844422567,\n            69.86685241644281\n          ]\n        ],\n        \"type\": \"LineString\"\n      }\n    }\n  ]\n}","volume":"59","issue":"4","noUsgsAuthors":false,"publicationDate":"2023-04-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Chen, Lin","contributorId":299914,"corporation":false,"usgs":false,"family":"Chen","given":"Lin","email":"","affiliations":[],"preferred":false,"id":913604,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fortier, Daniel","contributorId":194641,"corporation":false,"usgs":false,"family":"Fortier","given":"Daniel","email":"","affiliations":[],"preferred":false,"id":913605,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McKenzie, Jeffrey M.","contributorId":176299,"corporation":false,"usgs":false,"family":"McKenzie","given":"Jeffrey","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":913606,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Voss, Clifford I. 0000-0001-5923-2752","orcid":"https://orcid.org/0000-0001-5923-2752","contributorId":211844,"corporation":false,"usgs":true,"family":"Voss","given":"Clifford I.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":913607,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lamontagne-Halle, Pierrick","contributorId":344355,"corporation":false,"usgs":false,"family":"Lamontagne-Halle","given":"Pierrick","email":"","affiliations":[{"id":6730,"text":"Department of Earth and Planetary Sciences, McGill University, Montreal, QC, Canada","active":true,"usgs":false}],"preferred":false,"id":913608,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70243528,"text":"70243528 - 2023 - Environmental factors influencing detection efficiency of an acoustic telemetry array and consequences for data interpretation","interactions":[],"lastModifiedDate":"2023-05-11T11:47:29.744393","indexId":"70243528","displayToPublicDate":"2023-04-06T06:40:51","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":773,"text":"Animal Biotelemetry","active":true,"publicationSubtype":{"id":10}},"title":"Environmental factors influencing detection efficiency of an acoustic telemetry array and consequences for data interpretation","docAbstract":"<h3 class=\"c-article__sub-heading\" data-test=\"abstract-sub-heading\">Background</h3><p>Acoustic telemetry is a commonly used technology to monitor animal occupancy and infer movement in aquatic environments. The information that acoustic telemetry provides is vital for spatial planning and management decisions concerning aquatic and coastal environments by characterizing behaviors and habitats&nbsp;such as spawning aggregations, migrations, corridors, and&nbsp;nurseries,&nbsp;among others. However, performance of acoustic telemetry equipment and resulting detection ranges and efficiencies can vary as a function of environmental conditions, leading to potentially biased interpretations of telemetry data. Here, we characterize variation in detection performance using an acoustic telemetry receiver array deployed in Wellfleet Harbor, Massachusetts, USA from 2015 to 2017. The array was designed to study benthic invertebrate movements and provided an in situ opportunity to identify factors driving variation in detection probability.</p><h3 class=\"c-article__sub-heading\" data-test=\"abstract-sub-heading\">Results</h3><p>The near-shore location proximate to environmental monitoring allowed for a detailed examination of factors influencing detection efficiency in a range-testing experiment. Detection ranges varied from &lt; 50 to 1,500&nbsp;m and efficiencies varied from 0 to 100% within those detection ranges. Detection efficiency was affected by distance, wind speed and direction, wave height and direction, water temperature, water depth, and water quality.</p><h3 class=\"c-article__sub-heading\" data-test=\"abstract-sub-heading\">Conclusions</h3><p>Performance of acoustic telemetry systems is strongly contingent on environmental conditions. Our study found that wind, waves, water temperature, water quality, and depth all affected performance to an extent that could seriously compromise a study if these effects were not taken into consideration. Other unmeasured factors may also be important, depending on the characteristics of each site. This information can help guide future telemetry study designs by helping researchers anticipate the density of receivers required to achieve study objectives. Researchers can further refine and document the reliability of&nbsp;their data by incorporating continuously deployed range-testing tags and prior knowledge on varying detection efficiency into movement and occupancy models.</p>","language":"English","publisher":"Springer","doi":"10.1186/s40317-023-00317-2","usgsCitation":"Long, M., Jordaan, A., and Castro-Santos, T.R., 2023, Environmental factors influencing detection efficiency of an acoustic telemetry array and consequences for data interpretation: Animal Biotelemetry, v. 11, 18, 13 p., https://doi.org/10.1186/s40317-023-00317-2.","productDescription":"18, 13 p.","ipdsId":"IP-141767","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":443940,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1186/s40317-023-00317-2","text":"Publisher Index Page"},{"id":416951,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Massachusetts","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -70.12152378095689,\n              41.97721573790295\n            ],\n            [\n              -70.12152378095689,\n              41.80349781857885\n            ],\n            [\n              -69.90189169540182,\n              41.80349781857885\n            ],\n            [\n              -69.90189169540182,\n              41.97721573790295\n            ],\n            [\n              -70.12152378095689,\n              41.97721573790295\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"11","noUsgsAuthors":false,"publicationDate":"2023-04-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Long, Michael 0000-0001-6735-6878","orcid":"https://orcid.org/0000-0001-6735-6878","contributorId":261905,"corporation":false,"usgs":false,"family":"Long","given":"Michael","email":"","affiliations":[{"id":34616,"text":"University of Massachusetts Amherst","active":true,"usgs":false}],"preferred":false,"id":872227,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jordaan, Adrian","contributorId":257709,"corporation":false,"usgs":false,"family":"Jordaan","given":"Adrian","affiliations":[{"id":37201,"text":"UMass Amherst","active":true,"usgs":false}],"preferred":false,"id":872228,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Castro-Santos, Theodore R. 0000-0003-2575-9120 tcastrosantos@usgs.gov","orcid":"https://orcid.org/0000-0003-2575-9120","contributorId":3321,"corporation":false,"usgs":true,"family":"Castro-Santos","given":"Theodore","email":"tcastrosantos@usgs.gov","middleInitial":"R.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":872229,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70242660,"text":"70242660 - 2023 - Observed and projected functional reorganization of riverine fish assemblages from global change","interactions":[],"lastModifiedDate":"2023-06-09T15:14:17.319867","indexId":"70242660","displayToPublicDate":"2023-04-06T06:34:06","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1837,"text":"Global Change Biology","active":true,"publicationSubtype":{"id":10}},"title":"Observed and projected functional reorganization of riverine fish assemblages from global change","docAbstract":"<div class=\"abstract-group  metis-abstract\"><div class=\"article-section__content en main\"><p>Climate and land-use/land-cover change (‘global change’) are restructuring biodiversity, globally. Broadly, environmental conditions are expected to become warmer, potentially drier (particularly in arid regions), and more anthropogenically developed in the future, with spatiotemporally complex effects on ecological communities. We used functional traits to inform Chesapeake Bay Watershed fish responses to future climate and land-use scenarios (2030, 2060, and 2090). We modelled the future habitat suitability of focal species representative of key trait axes (substrate, flow, temperature, reproduction, and trophic) and used functional and phylogenetic metrics to assess variable assemblage responses across physiographic regions and habitat sizes (headwaters through large rivers). Our focal species analysis projected future habitat suitability gains for carnivorous species with preferences for warm water, pool habitats, and fine or vegetated substrates. At the assemblage level, models projected decreasing habitat suitability for cold-water, rheophilic, and lithophilic individuals but increasing suitability for carnivores in the future across all regions. Projected responses of functional and phylogenetic diversity and redundancy differed among regions. Lowland regions were projected to become less functionally and phylogenetically diverse and more redundant while upland regions (and smaller habitat sizes) were projected to become more diverse and less redundant. Next, we assessed how this model projected assemblage changes 2005-2030 related to observed time-series trends (1999–2016). Halfway through the initial projecting period (2005–2030), we found observed trends broadly followed modelled patterns of increasing proportions of carnivorous and lithophilic individuals in lowland regions but showed opposing patterns for functional and phylogenetic metrics. Leveraging observed and predicted analyses simultaneously helps elucidate the instances and causes of discrepancies between model predictions and ongoing observed changes. Collectively, results highlight the complexity of global change impacts across broad landscapes that likely relate to differences in assemblages’ intrinsic sensitivities and external exposure to stressors.</p></div></div>","language":"English","publisher":"Wiley","doi":"10.1111/gcb.16707","usgsCitation":"Woods, T., Freeman, M., Krause, K.P., and Maloney, K.O., 2023, Observed and projected functional reorganization of riverine fish assemblages from global change: Global Change Biology, v. 29, no. 13, p. 3759-3780, https://doi.org/10.1111/gcb.16707.","productDescription":"22 p.","startPage":"3759","endPage":"3780","ipdsId":"IP-146780","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true},{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":443943,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/gcb.16707","text":"Publisher Index Page"},{"id":415644,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"29","issue":"13","noUsgsAuthors":false,"publicationDate":"2023-04-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Woods, Taylor 0000-0002-6277-1260","orcid":"https://orcid.org/0000-0002-6277-1260","contributorId":304097,"corporation":false,"usgs":true,"family":"Woods","given":"Taylor","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":869250,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Freeman, Mary 0000-0001-7615-6923 mcfreeman@usgs.gov","orcid":"https://orcid.org/0000-0001-7615-6923","contributorId":3528,"corporation":false,"usgs":true,"family":"Freeman","given":"Mary","email":"mcfreeman@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":869251,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Krause, Kevin P. 0000-0002-0255-7027","orcid":"https://orcid.org/0000-0002-0255-7027","contributorId":304098,"corporation":false,"usgs":false,"family":"Krause","given":"Kevin","email":"","middleInitial":"P.","affiliations":[{"id":65969,"text":"Minnesota Department of Natural Resource","active":true,"usgs":false}],"preferred":false,"id":869252,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Maloney, Kelly O. 0000-0003-2304-0745 kmaloney@usgs.gov","orcid":"https://orcid.org/0000-0003-2304-0745","contributorId":4636,"corporation":false,"usgs":true,"family":"Maloney","given":"Kelly","email":"kmaloney@usgs.gov","middleInitial":"O.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":869253,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70242000,"text":"sir20235013 - 2023 - Salinity and selenium yield maps derived from geostatistical modeling in the lower Gunnison River Basin, western Colorado, 1992–2013","interactions":[],"lastModifiedDate":"2026-03-02T21:57:03.940791","indexId":"sir20235013","displayToPublicDate":"2023-04-05T10:35:01","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":"2023-5013","displayTitle":"Salinity and Selenium Yield Maps Derived from Geostatistical Modeling in the Lower Gunnison River Basin, Western Colorado, 1992–2013","title":"Salinity and selenium yield maps derived from geostatistical modeling in the lower Gunnison River Basin, western Colorado, 1992–2013","docAbstract":"<p>Salinity is known to affect drinking-water supplies and damage irrigated agricultural lands. Selenium in high concentrations is harmful to fish and other wildlife. Land managers, water providers, and agricultural producers in the lower Gunnison River Basin in western Colorado expend resources mitigating the effects of these constituents. The U.S. Geological Survey revised existing salinity (total dissolved solids) and selenium models for the lower Gunnison River Basin in an attempt to better identify areas of greatest salinity and selenium yield. This effort developed maps of yields predicted from multiple linear regression (MLR) models for the lower Gunnison River Basin. The models included data for irrigation and nonirrigation seasons and two periods, 1992–2004 and 2005–13.</p><p>Concentrations of salinity and selenium and discharge measurements made at the time of sampling were used to compute loads for subbasins (component drainages of the larger lower Gunnison River Basin study area), which were adjusted for inflows and outflows of canal loads. Load regression equations were determined from explanatory basin characteristics that included physical properties, precipitation, land use and cover, surficial deposits (soil and unconsolidated geologic materials), and bedrock geology. Loads of salinity and selenium were converted to yields by using the subbasin drainage areas, and an empirical Bayesian kriging procedure was used to produce robust grids of yields for salinity and selenium.</p><p>Salinity yields ranged from 0.00667 to 6.564 tons per year per acre. The highest salinity yields, greater than about 5.0 tons per year per acre, are predicted on the western side of the Uncompahgre River upstream from Delta, Colorado, an area with a high density of irrigated land. The selenium yield map shows a similar pattern, but the highest yields are somewhat more confined to the eastern side of the lower Uncompahgre River and south of the Gunnison River near the confluence with the Uncompahgre River at Delta, Colorado. Selenium yields ranged from 2.6888 x 10<sup>-10</sup> to 0.000445 pounds per day per acre. The highest predicted selenium yields, greater than 0.0003 pounds per day per acre, were in the area downstream from Montrose, Colorado, on the eastern side of the Uncompahgre River.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/sir20235013","collaboration":"Prepared in cooperation with the Bureau of Reclamation and the Colorado Water Conservation Board","usgsCitation":"Williams, C.A., Gidley, R.G., and Stevens, M.R., 2023, Salinity and selenium yield maps derived from geostatistical modeling in the lower Gunnison River Basin, western Colorado, 1992–2013: U.S. Geological Survey Scientific Investigations Report 2023–5013, 37 p., https://doi.org/10.3133/sir20235013.","productDescription":"Report: vi, 37 p.; 2 Data Releases","onlineOnly":"Y","ipdsId":"IP-127438","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":415136,"rank":3,"type":{"id":30,"text":"Data 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2023-5013"},{"id":415134,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2023/5013/coverthb.jpg"},{"id":415137,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS data release","linkHelpText":"USGS water data for the Nation: U.S. Geological Survey National Water Information System database"},{"id":500707,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114651.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Colorado","otherGeospatial":"Lower Gunnison River basin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -108.66041487616633,\n              38.99638415429618\n            ],\n            [\n              -108.6616273692395,\n              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href=\"https://www.usgs.gov/centers/colorado-water-science-center/\" data-mce-href=\"https://www.usgs.gov/centers/colorado-water-science-center/\">Colorado Water Science Center</a><br>U.S. Geological Survey<br>Box 25046, Mail Stop 415<br>Denver, CO 80225</p>","tableOfContents":"<ul><li>Abstract</li><li>Introduction</li><li>Previous Investigations</li><li>Methods</li><li>Salinity and Selenium Yield Maps</li><li>Summary</li><li>Acknowledgments</li><li>References Cited</li></ul>","publishedDate":"2023-04-05","noUsgsAuthors":false,"publicationDate":"2023-04-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Williams, Cory A. 0000-0003-1461-7848 cawillia@usgs.gov","orcid":"https://orcid.org/0000-0003-1461-7848","contributorId":689,"corporation":false,"usgs":true,"family":"Williams","given":"Cory","email":"cawillia@usgs.gov","middleInitial":"A.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":868486,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gidley, Rachel G. 0000-0002-9840-8252","orcid":"https://orcid.org/0000-0002-9840-8252","contributorId":259315,"corporation":false,"usgs":true,"family":"Gidley","given":"Rachel","email":"","middleInitial":"G.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":868487,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stevens, Michael R. 0000-0002-9476-6335","orcid":"https://orcid.org/0000-0002-9476-6335","contributorId":303903,"corporation":false,"usgs":false,"family":"Stevens","given":"Michael R.","affiliations":[{"id":37196,"text":"Retired USGS employee","active":true,"usgs":false}],"preferred":false,"id":868488,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70241590,"text":"sir20235010 - 2023 - Visualization of petroleum exploration maturity for six petroleum provinces outside the United States and Canada","interactions":[],"lastModifiedDate":"2023-04-05T14:53:25.369229","indexId":"sir20235010","displayToPublicDate":"2023-04-05T09:55:00","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":"2023-5010","displayTitle":"Visualization of Petroleum Exploration Maturity for Six Petroleum Provinces Outside the United States and Canada","title":"Visualization of petroleum exploration maturity for six petroleum provinces outside the United States and Canada","docAbstract":"<p>Outside the United States and Canada, most of the world’s supplies of oil and natural gas are recovered from conventional (or discrete) oil and gas accumulations. This type of hydrocarbon accumulation remains a target for exploration. In this report, exploration and discovery data are used to visually assist in describing the exploration maturity of selected petroleum provinces with respect to conventional oil and natural gas accumulations. The specific provinces are the Campos Basin (Brazil), the Santos Basin (Brazil), the North Sea Graben (northwestern Europe), the Middle Magdelena Basin (Colombia), the Sirte Basin (Libya), and the Kutei Basin (Indonesia). For each province, discovery data and well data through October 2019 are reported; from these data, depth distributions of the oil in oil fields and natural gas in gas fields were computed.</p><p>The concepts of delineated prospective area and explored area include elements of geographic spatial information and statistical data analytics. Graphs showing dynamic growth of discoveries that are tied to the delineated prospective area provide a means of grading prospective area. Visualizations put the results of exploration in the context of geographic and geologic features of the play or basin and can be a tool to assist geologists with the appraisal of the number and sizes of undiscovered petroleum accumulations. Visualizations of exploration drilling and discoveries can (1) assist in conceptualizing a geologic model of the basin, (2) highlight relations among discovered accumulations in different plays or assessment units within the basin, and (3) allow the geologist to identify the missing information needed to complete the geologic model of a basin. Further, if visualization attributes can be quantified, they may be used for formulating quantitative models that predict numbers and sizes of undiscovered oil and gas accumulations. Such modeling approaches include discovery process models, Bayesian network models that characterize play or assessment unit dependencies, and innovative applications of machine learning to complement standard geologic assessments.</p><p>The purpose of this report is to show how visualizations can further the understanding of exploration maturity for the six selected petroleum provinces. It also shows how the geologic framework, geologic data, and drilling and discovery trends can give context to the interpretation of the visualizations that lead to appraisal of exploration maturity.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235010","usgsCitation":"Attanasi, E.D., and Freeman, P.A., 2023, Visualization of petroleum exploration maturity for six petroleum provinces outside the United States and Canada: U.S. Geological Survey Scientific Investigations Report 2023–5010, 38 p., https://doi.org/10.3133/sir20235010.","productDescription":"viii, 38 p.","numberOfPages":"38","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-119047","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":414671,"rank":3,"type":{"id":39,"text":"HTML 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}\n    }\n  ]\n}","contact":"<p>Program Coordinator, <a href=\"https://www.usgs.gov/energy-and-minerals/energy-resources-program/connect\" data-mce-href=\"https://www.usgs.gov/energy-and-minerals/energy-resources-program/connect\">Energy Resources Program</a><br>U.S. Geological Survey<br>12201 Sunrise Valley Drive<br>Reston, VA 20192</p><p><a href=\"mailto:AskEnergyProgram@usgs.gov\" data-mce-href=\"mailto:AskEnergyProgram@usgs.gov\">AskEnergyProgram@usgs.gov</a></p>","tableOfContents":"<ul><li>Abstract</li><li>Introduction</li><li>Methodology</li><li>Summary Description of the Six Petroleum Provinces</li><li>Explanation of Tabular Data and Figures</li><li>Provisional Evaluation of Exploration Maturity</li><li>Implications and Conclusions</li><li>References Cited</li><li>Appendix 1. Mean Volume Estimates of the Undiscovered, Technically Recoverable, and Conventional Petroleum Resources for the Six Provinces in This Study</li></ul>","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"publishedDate":"2023-04-05","noUsgsAuthors":false,"publicationDate":"2023-04-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Attanasi, Emil D. 0000-0001-6845-7160 attanasi@usgs.gov","orcid":"https://orcid.org/0000-0001-6845-7160","contributorId":198728,"corporation":false,"usgs":true,"family":"Attanasi","given":"Emil D.","email":"attanasi@usgs.gov","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":867400,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Freeman, Philip A. 0000-0002-0863-7431","orcid":"https://orcid.org/0000-0002-0863-7431","contributorId":206294,"corporation":false,"usgs":true,"family":"Freeman","given":"Philip A.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":867398,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70247680,"text":"70247680 - 2023 - Nonlinear radiation damping: A new method for dissipating energy in dynamic earthquake rupture simulations","interactions":[],"lastModifiedDate":"2023-08-11T14:01:19.125829","indexId":"70247680","displayToPublicDate":"2023-04-05T08:59:47","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":10542,"text":"The Seismic Record","active":true,"publicationSubtype":{"id":10}},"title":"Nonlinear radiation damping: A new method for dissipating energy in dynamic earthquake rupture simulations","docAbstract":"<p><span>Dynamic earthquake rupture simulations are used to understand earthquake mechanics and the ground shaking that earthquakes produce. These simulations can help diagnose past earthquake behavior and are also used to generate scenarios of possible future earthquakes. Traditional dynamic rupture models generally assume elastic rock response, but this can lead to peak on‐fault slip rates and ground shaking that are higher than those inferred from seismological observations. Some have approached this challenge using inelastic off‐fault rock behavior to dissipate energy, but the addition of inelasticity can make it difficult to select parameters and establish suitable initial conditions, and increases the model’s complexity and computational cost. We propose a new method that works by adding a nonlinear radiation damping term to the friction law, with the surrounding rocks remaining linear elastic. Our new method results in lower peak slip rates, reduced seismic radiation, and an increasing slip‐weakening critical distance with increasing rupture propagation distance, all within a linear elastic model. In addition, it is easy to implement.</span></p>","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0320230001","usgsCitation":"Barall, M., and Harris, R.A., 2023, Nonlinear radiation damping: A new method for dissipating energy in dynamic earthquake rupture simulations: The Seismic Record, v. 3, no. 2, p. 69-76, https://doi.org/10.1785/0320230001.","productDescription":"8 p.","startPage":"69","endPage":"76","ipdsId":"IP-144269","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":443944,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1785/0320230001","text":"Publisher Index Page"},{"id":419736,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"3","issue":"2","noUsgsAuthors":false,"publicationDate":"2023-04-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Barall, Michael 0000-0001-7724-8563 mbarall@usgs.gov","orcid":"https://orcid.org/0000-0001-7724-8563","contributorId":271197,"corporation":false,"usgs":true,"family":"Barall","given":"Michael","email":"mbarall@usgs.gov","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":880016,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Harris, Ruth A. 0000-0002-9247-0768 harris@usgs.gov","orcid":"https://orcid.org/0000-0002-9247-0768","contributorId":786,"corporation":false,"usgs":true,"family":"Harris","given":"Ruth","email":"harris@usgs.gov","middleInitial":"A.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":880017,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
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