{"pageNumber":"394","pageRowStart":"9825","pageSize":"25","recordCount":165227,"records":[{"id":70228162,"text":"70228162 - 2022 - The role of hydraulic and geomorphic complexity in predicting invasive carp spawning potential: St. Croix River, Minnesota and Wisconsin, United States","interactions":[],"lastModifiedDate":"2022-02-07T18:02:04.365799","indexId":"70228162","displayToPublicDate":"2022-02-03T11:55:43","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"The role of hydraulic and geomorphic complexity in predicting invasive carp spawning potential: St. Croix River, Minnesota and Wisconsin, United States","docAbstract":"

Since they were first introduced to the United States more than 50 years ago, invasive carp have rapidly colonized rivers of the Mississippi River Basin, with detrimental effects on native aquatic species. Their continued range expansion, and potential for subsequent invasion of the Great Lakes, has led to increased concern for the susceptibility of as-yet uncompromised lotic and lentic systems in the central United States. Because invasive carp eggs and larvae must drift in the river current for the first several days following spawning, numerical drift modeling has emerged as a useful technique for determining whether certain river systems and reaches have the potential to support suspension-to-hatching survival of invasive carp eggs, a critical first step in recruitment. Here we use one such numerical modeling approach, the Fluvial Egg Drift Simulator (FluEgg), to estimate bighead carp (Hypophthalmichthys nobilis) egg hatching success and larval retention in a 47.8-kilometer (km) reach of the multi-thread St. Croix River, Minnesota and Wisconsin, United States. We explore three approaches for obtaining the hydraulic data required by FluEgg, parameterizing the model with either (a) field hydraulic data collected within the main channel during a high-flow event, or hydraulic data output from a one-dimensional hydrodynamic model with both (b) steady, and (c) unsteady flows. We find that the three approaches, along with the range of water temperatures and discharge used in simulations, produce vastly different predictions of streamwise transport and in-river egg hatching probability (0% for field data, 0 to 96% for steady-state hydraulic modeling, and 1.8 to 65% for unsteady modeling). However, all FluEgg simulations, regardless of the source of hydraulic data, predicted that no larvae reach the gas bladder inflation stage within the study reach where nursery habitat is abundant. Overall, these results indicate that the lower St. Croix River is suitable for invasive carp spawning and egg suspension until hatching for a range of discharge and water temperatures. These results highlight the role of complex channel hydraulics and morphology, particularly multi-thread reaches, and their inclusion in ecohydraulic-suitability modeling to determine susceptibility of river systems for invasive carp reproduction. Our work also emphasizes the scientific value of multi-dimensional hydrodynamic models that can capture the spatial heterogeneity of flow fields in geomorphically complex rivers. This work may help to guide management efforts based on the targeted monitoring and control and improve invasive carp egg and larvae sampling efficiency.

","language":"English","publisher":"Public Library of Science (PLOS)","doi":"10.1371/journal.pone.0263052","usgsCitation":"Kasprak, A., Jackson, P.R., Lindroth, E.M., Lund, J.W., and Ziegeweid, J.R., 2022, The role of hydraulic and geomorphic complexity in predicting invasive carp spawning potential: St. Croix River, Minnesota and Wisconsin, United States: PLoS ONE, v. 17, no. 2, e0263052, 25 p., https://doi.org/10.1371/journal.pone.0263052.","productDescription":"e0263052, 25 p.","ipdsId":"IP-128244","costCenters":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true},{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":448898,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0263052","text":"Publisher Index Page"},{"id":435980,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P93K0UUI","text":"USGS data release","linkHelpText":"Bathymetric, water velocity, and water temperature data on the St. Croix River between St. Croix Falls, Wisconsin, and Stillwater, Minnesota, June 19-22, 2018"},{"id":395554,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Minnesota, Wisconsin","otherGeospatial":"St Croix River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -92.84408569335938,\n 44.98714175309689\n ],\n [\n -92.59552001953125,\n 44.98714175309689\n ],\n [\n -92.59552001953125,\n 45.42062422307843\n ],\n [\n -92.84408569335938,\n 45.42062422307843\n ],\n [\n -92.84408569335938,\n 44.98714175309689\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"17","issue":"2","noUsgsAuthors":false,"publicationDate":"2022-02-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Kasprak, Alan 0000-0001-8184-6128","orcid":"https://orcid.org/0000-0001-8184-6128","contributorId":245742,"corporation":false,"usgs":false,"family":"Kasprak","given":"Alan","affiliations":[{"id":49307,"text":"Current: Utah State University. Former: Southwest Biological Science Center, Grand Canyon Monitoring and Research Center, U.S. Geological Survey, Flagstaff, AZ 86001, USA","active":true,"usgs":false}],"preferred":false,"id":833274,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jackson, P. Ryan 0000-0002-3154-6108 pjackson@usgs.gov","orcid":"https://orcid.org/0000-0002-3154-6108","contributorId":194529,"corporation":false,"usgs":true,"family":"Jackson","given":"P.","email":"pjackson@usgs.gov","middleInitial":"Ryan","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true},{"id":35680,"text":"Illinois-Iowa-Missouri Water Science Center","active":true,"usgs":true},{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"preferred":true,"id":833275,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lindroth, Evan M. 0000-0002-9746-4359 elindroth@usgs.gov","orcid":"https://orcid.org/0000-0002-9746-4359","contributorId":264885,"corporation":false,"usgs":true,"family":"Lindroth","given":"Evan","email":"elindroth@usgs.gov","middleInitial":"M.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":833276,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lund, J. William 0000-0002-8830-4468","orcid":"https://orcid.org/0000-0002-8830-4468","contributorId":211157,"corporation":false,"usgs":true,"family":"Lund","given":"J.","email":"","middleInitial":"William","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":833277,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ziegeweid, Jeffrey R. 0000-0001-7797-3044 jrziege@usgs.gov","orcid":"https://orcid.org/0000-0001-7797-3044","contributorId":4166,"corporation":false,"usgs":true,"family":"Ziegeweid","given":"Jeffrey","email":"jrziege@usgs.gov","middleInitial":"R.","affiliations":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":833278,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70230108,"text":"70230108 - 2022 - The occurrence of large floods in the United States in the modern hydroclimate regime: Seasonality, trends, and large-scale climate associations","interactions":[],"lastModifiedDate":"2022-03-30T16:33:28.393017","indexId":"70230108","displayToPublicDate":"2022-02-03T11:32:58","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"The occurrence of large floods in the United States in the modern hydroclimate regime: Seasonality, trends, and large-scale climate associations","docAbstract":"

Many studies investigate river floods by analyzing annual maximum series that record the largest flow of each year, including many within-bank events inconsequential for human communities. Fewer focus on larger floods, especially at the continental scale. Using 473 streamgages across the conterminous United States with near-natural flow from 1966 to 2015, we characterized the seasonality, occurrence, and climatic associations of the 10 largest and 2 largest floods at each site. These are often overbank events that have ecosystem functions and pose risks to humans. We grouped sites into 14 clusters corresponding to climatic and physiographic regions and characterized their flood seasonality at a monthly resolution using a probabilistic method. We then evaluated annual occurrence regionally and nationally, and seasonal occurrence regionally, by complementing a traditional approach to trend analyses with a novel method based on expected occurrence. Relationships between flood occurrence and climate indices were also investigated. Large floods have strong seasonality in some regions, but in areas with numerous flood-generating mechanisms, seasonality is more complex. There is little evidence nationally that large riverine floods are more or less frequent than expected in recent years and only two regions show significant trends in annual counts; few show seasonal trends. We found some regional relationships between flood counts and climate indices, annually and seasonally; nationally the Pacific North American pattern is related to annual counts of the 2 largest floods. Large-flood occurrence was generally stable across the United States in the last five decades; this may or may not continue with projected warming.

","language":"English","publisher":"Wiley","doi":"10.1029/2021WR030480","usgsCitation":"Collins, M., Hodgkins, G.A., Archfield, S.A., and Hirsch, R.M., 2022, The occurrence of large floods in the United States in the modern hydroclimate regime: Seasonality, trends, and large-scale climate associations: Water Resources Research, v. 58, e2021WR030480, 22 p., https://doi.org/10.1029/2021WR030480.","productDescription":"e2021WR030480, 22 p.","ipdsId":"IP-128386","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":435981,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9QYR28M","text":"USGS data release","linkHelpText":"Ten Largest Annual Instantaneous Floods and Seasonal Signal for Reference Streamgages in the United States, Water Years 1966-2015"},{"id":397871,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":839065,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hirsch, Robert M. 0000-0002-4534-075X rhirsch@usgs.gov","orcid":"https://orcid.org/0000-0002-4534-075X","contributorId":2005,"corporation":false,"usgs":true,"family":"Hirsch","given":"Robert","email":"rhirsch@usgs.gov","middleInitial":"M.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":502,"text":"Office of Surface Water","active":true,"usgs":true},{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"preferred":true,"id":839066,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70228699,"text":"70228699 - 2022 - Use of riparian spiders as sentinels of persistent and bioavailable chemical contaminants in aquatic ecosystems: A review","interactions":[],"lastModifiedDate":"2022-03-17T16:58:18.718539","indexId":"70228699","displayToPublicDate":"2022-02-03T10:57:24","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1571,"text":"Environmental Toxicology and Chemistry","active":true,"publicationSubtype":{"id":10}},"title":"Use of riparian spiders as sentinels of persistent and bioavailable chemical contaminants in aquatic ecosystems: A review","docAbstract":"

Aquatic ecosystems around the world are contaminated with a wide range of anthropogenic chemicals, including metals and organic pollutants, that originate from point and nonpoint sources. Many of these chemical contaminants have complex environmental cycles, are persistent and bioavailable, can be incorporated into aquatic food webs, and pose a threat to the health of wildlife and humans. Identifying appropriate sentinels that reflect bioavailability is critical to assessing and managing aquatic ecosystems impacted by contaminants. The objective of the present study is to review research on riparian spiders as sentinels of persistent and bioavailable chemical contaminants in aquatic ecosystems. Our review of the literature on riparian spiders as sentinels suggests that significant progress has been made during the last two decades of research. We identified 55 published studies conducted around the world in which riparian spiders (primarily of the families Tetragnathidae, Araneidae, Lycosidae, and Pisauridae) were used as sentinels of chemical contamination of lotic, lentic, and estuarine systems. For several contaminants, such as polychlorinated biphenyls (PCBs), Hg, and Se, it is now clear that riparian spiders are appropriate sentinels. However, many contaminants and factors that could impact chemical concentrations in riparian spiders have not been well characterized. Further study of riparian spiders and their potential role as sentinels is critical because it would allow for development of national-scale programs that utilize riparian spiders as sentinels to monitor chemical contaminants in aquatic ecosystems. A riparian spider sentinel program in the United States would be complementary to existing national sentinel programs, including those for fish and immature dragonflies. 

","language":"English","publisher":"Society of Environmental Toxicology and Chemistry (SETAC)","doi":"10.1002/etc.5267","usgsCitation":"Chumchal, M., Beaubien, G.B., Drenner, R., Hannappel, M.P., Mills, M.A., Olson, C.I., Otter, R.R., Todd, A.C., and Walters, D., 2022, Use of riparian spiders as sentinels of persistent and bioavailable chemical contaminants in aquatic ecosystems: A review: Environmental Toxicology and Chemistry, v. 41, no. 3, p. 499-514, https://doi.org/10.1002/etc.5267.","productDescription":"16 p.","startPage":"499","endPage":"514","ipdsId":"IP-131503","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":448902,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/etc.5267","text":"Publisher Index Page"},{"id":396115,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"41","issue":"3","noUsgsAuthors":false,"publicationDate":"2022-03-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Chumchal, Matthew M.","contributorId":279539,"corporation":false,"usgs":false,"family":"Chumchal","given":"Matthew M.","affiliations":[{"id":25471,"text":"Texas Christian University","active":true,"usgs":false}],"preferred":false,"id":835110,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Beaubien, Gale B.","contributorId":244596,"corporation":false,"usgs":false,"family":"Beaubien","given":"Gale","email":"","middleInitial":"B.","affiliations":[{"id":37193,"text":"Middle Tennessee State University","active":true,"usgs":false}],"preferred":false,"id":835111,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Drenner, Ray W.","contributorId":279540,"corporation":false,"usgs":false,"family":"Drenner","given":"Ray W.","affiliations":[{"id":25471,"text":"Texas Christian University","active":true,"usgs":false}],"preferred":false,"id":835112,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hannappel, Madeline P.","contributorId":279542,"corporation":false,"usgs":false,"family":"Hannappel","given":"Madeline","email":"","middleInitial":"P.","affiliations":[{"id":34637,"text":"University of North Texas","active":true,"usgs":false}],"preferred":false,"id":835113,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mills, Marc A.","contributorId":141085,"corporation":false,"usgs":false,"family":"Mills","given":"Marc","email":"","middleInitial":"A.","affiliations":[{"id":12772,"text":"USEPA","active":true,"usgs":false}],"preferred":false,"id":835114,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Olson, Connor I.","contributorId":244597,"corporation":false,"usgs":false,"family":"Olson","given":"Connor","email":"","middleInitial":"I.","affiliations":[{"id":37193,"text":"Middle Tennessee State University","active":true,"usgs":false}],"preferred":false,"id":835115,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Otter, Ryan R.","contributorId":205916,"corporation":false,"usgs":false,"family":"Otter","given":"Ryan","email":"","middleInitial":"R.","affiliations":[{"id":37193,"text":"Middle Tennessee State University","active":true,"usgs":false}],"preferred":false,"id":835116,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Todd, Andrew C.","contributorId":279545,"corporation":false,"usgs":false,"family":"Todd","given":"Andrew","email":"","middleInitial":"C.","affiliations":[{"id":25471,"text":"Texas Christian University","active":true,"usgs":false}],"preferred":false,"id":835117,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Walters, David 0000-0002-4237-2158","orcid":"https://orcid.org/0000-0002-4237-2158","contributorId":203410,"corporation":false,"usgs":true,"family":"Walters","given":"David","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":835118,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70230954,"text":"70230954 - 2022 - Silicate volcanism on Europa’s seafloor and implications for habitability","interactions":[],"lastModifiedDate":"2022-04-29T12:10:55.639334","indexId":"70230954","displayToPublicDate":"2022-02-03T07:09:25","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Silicate volcanism on Europa’s seafloor and implications for habitability","docAbstract":"

Habitable ocean environments on Europa require an influx of reactants to maintain chemical disequilibrium. One possible source of reactants is seafloor volcanism. Modeling has shown that dissipation of tidal energy in Europa's asthenosphere can generate melt, but melt formation cannot be equated with volcanism. Melt must also be transported through Europa's cold lithosphere to erupt at the seafloor. Here, we use two models of dike propagation to show that dikes can only traverse the lithosphere if either the fracture toughness of the lithosphere or the flux into the dike is large (>500 MPa m1/2 or ∼1 m2 s−1, respectively). We conclude that cyclic volcanic episodes might provide reactants to Europa's ocean if magma accumulates at the base of the lithosphere for several thousand years. However, if dikes form too frequently, or are too numerous, the magma flux into each will be insufficient, and volcanism cannot support a habitable ocean environment.

","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2021GL096939","usgsCitation":"Bland, M.T., and Elder, C., 2022, Silicate volcanism on Europa’s seafloor and implications for habitability: Geophysical Research Letters, v. 49, no. 5, e96939, 9 p., https://doi.org/10.1029/2021GL096939.","productDescription":"e96939, 9 p.","ipdsId":"IP-133512","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":448905,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2021gl096939","text":"Publisher Index Page"},{"id":399884,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"49","issue":"5","noUsgsAuthors":false,"publicationDate":"2022-03-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Bland, Michael T. 0000-0001-5543-1519 mbland@usgs.gov","orcid":"https://orcid.org/0000-0001-5543-1519","contributorId":146287,"corporation":false,"usgs":true,"family":"Bland","given":"Michael","email":"mbland@usgs.gov","middleInitial":"T.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":841703,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Elder, Catherine","contributorId":237916,"corporation":false,"usgs":false,"family":"Elder","given":"Catherine","email":"","affiliations":[{"id":36276,"text":"JPL","active":true,"usgs":false}],"preferred":false,"id":841704,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70229652,"text":"70229652 - 2022 - Deconstructing the microbial necromass continuum to inform soil carbon sequestration","interactions":[],"lastModifiedDate":"2022-06-16T15:19:09.106557","indexId":"70229652","displayToPublicDate":"2022-02-03T06:46:26","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1711,"text":"Functional Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Deconstructing the microbial necromass continuum to inform soil carbon sequestration","docAbstract":"
  1. Microbial necromass is a large, dynamic and persistent component of soil organic carbon, the dominant terrestrial carbon pool. Quantification of necromass carbon stocks and its susceptibility to global change is becoming standard practice in soil carbon research. However, the typical proxies used for necromass carbon do not reveal the dynamic nature of necromass carbon flows and transformations within soil that ultimately determine necromass persistence. In this review, we define and deconstruct four stages of the necromass continuum: production, recycling, stabilization and destabilization.
  2. Current understanding of necromass dynamics is described for each continuum stage. We highlight recent advances, methodological limitations and knowledge gaps which need to be addressed to determine necromass pool sizes and transformations. We discuss the dominant controls on necromass process rates and aspects of soil microscale structure including biofilms and food web interactions. The relative importance of each stage of the continuum is then compared in contrasting ecosystems and for climate change drivers.
  3. From the perspective of the continuum, we draw three conclusions to inform future research. First, controls on necromass persistence are more clearly defined when viewed through the lens of the continuum; second, destabilization is the least understood stage of the continuum with recycling also poorly evidenced outside of a few ecosystems; and third, the response of necromass process rates to climate change is unresolved for most continuum stages and ecosystems.
  4. Future mechanistic research focused on the role of biotic and abiotic soil microscale structure in determining necromass process rates and the relative importance of organo–mineral and organo–organo interactions can inform necromass persistence in different climate change scenarios. Our review demonstrates that deconstructing the necromass continuum is key to predicting the vulnerability and persistence of necromass carbon in a changing world.
","language":"English","publisher":"British Ecological Society","doi":"10.1111/1365-2435.14014","usgsCitation":"Buckeridge, K.M., Creamer, C., and Whitaker, J., 2022, Deconstructing the microbial necromass continuum to inform soil carbon sequestration: Functional Ecology, v. 36, no. 6, p. 1396-1410, https://doi.org/10.1111/1365-2435.14014.","productDescription":"15 p.","startPage":"1396","endPage":"1410","ipdsId":"IP-133529","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":448908,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1111/1365-2435.14014","text":"External Repository"},{"id":397012,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"36","issue":"6","noUsgsAuthors":false,"publicationDate":"2022-02-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Buckeridge, Kate M 0000-0002-3267-4216","orcid":"https://orcid.org/0000-0002-3267-4216","contributorId":288379,"corporation":false,"usgs":false,"family":"Buckeridge","given":"Kate","email":"","middleInitial":"M","affiliations":[{"id":61743,"text":"Luxembourg Institute of Science and Technology","active":true,"usgs":false}],"preferred":false,"id":837818,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Creamer, Courtney 0000-0001-8270-9387","orcid":"https://orcid.org/0000-0001-8270-9387","contributorId":201952,"corporation":false,"usgs":true,"family":"Creamer","given":"Courtney","email":"","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":837819,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Whitaker, Jeanette 0000-0001-8824-471X","orcid":"https://orcid.org/0000-0001-8824-471X","contributorId":288380,"corporation":false,"usgs":false,"family":"Whitaker","given":"Jeanette","email":"","affiliations":[{"id":61746,"text":"UK Centre for Hydrology & Ecology","active":true,"usgs":false}],"preferred":false,"id":837820,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70264967,"text":"70264967 - 2022 - Evaluation of electrical and electromagnetic geophysical techniques to inspect earthen dam and levee structures in Arkansas","interactions":[],"lastModifiedDate":"2025-03-27T15:34:18.439831","indexId":"70264967","displayToPublicDate":"2022-02-03T00:00:00","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":9128,"text":"Journal of Environmental and Engineering Geophysics","active":true,"publicationSubtype":{"id":10}},"title":"Evaluation of electrical and electromagnetic geophysical techniques to inspect earthen dam and levee structures in Arkansas","docAbstract":"Within the state of Arkansas there is an increasing number of aging dams and levees that have little to no documentation concerning their construction or composition. Surface geophysical surveys offer a non-intrusive method for investigating these structures: To describe their lithologic makeup, to evaluate the materials that they were constructed upon, and to identify potential flow paths through them. Techniques such as electrical resistivity tomography, seismic refraction, and electromagnetic induction have all been used to image dams and levees and require additional information from geologic outcrops, geotechnical borings, or drill cores in order to make informed geologic interpretations of the geophysical models. These geologic models then allow the owners of these structures to make more informed decisions about their operation and maintenance. Between 2011 and 2018, the U.S. Geological Survey conducted geophysical and geotechnical investigations of three earthen structures within the state of Arkansas. Electrical and electromagnetic geophysical data were used to develop lithologic models of these structures and the underlying geology. Self-potential surveys were utilized to detect the movement of water through these structures indicating possible seepage pathways. Geotechnical methods such as electric and hydraulic direct-push well logs and cores acted as both a control on the geophysical interpretations and a confirmation of anomalies. This integrated approach detected the lack of an impermeable core within a levee, imaged a change in lithology of the bedrock forming the seal beneath a gravity dam, and identified a potential seepage feature within the core of an earthen dam. These results further support that this method of extending known lithologic features via surface and borehole geophysics is a useful approach for characterizing earthen water control structures.","language":"English","publisher":"GeoScienceWorld","doi":"10.32389/JEEG20-063","usgsCitation":"Adams, R.F., Miller, B., Kress, W., Ikard, S., Payne, J.D., and Killion, W., 2022, Evaluation of electrical and electromagnetic geophysical techniques to inspect earthen dam and levee structures in Arkansas: Journal of Environmental and Engineering Geophysics, v. 26, no. 4, p. 287-303, https://doi.org/10.32389/JEEG20-063.","productDescription":"17 p.","startPage":"287","endPage":"303","ipdsId":"IP-116502","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":483950,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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Science Center","active":true,"usgs":true}],"preferred":true,"id":932119,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kress, Wade 0000-0002-6833-028X","orcid":"https://orcid.org/0000-0002-6833-028X","contributorId":203539,"corporation":false,"usgs":true,"family":"Kress","given":"Wade","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":932120,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ikard, Scott 0000-0002-8304-4935","orcid":"https://orcid.org/0000-0002-8304-4935","contributorId":212256,"corporation":false,"usgs":true,"family":"Ikard","given":"Scott","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":932121,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Payne, Jason D. 0000-0003-4294-7924","orcid":"https://orcid.org/0000-0003-4294-7924","contributorId":257453,"corporation":false,"usgs":true,"family":"Payne","given":"Jason","email":"","middleInitial":"D.","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":932122,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Killion, Walter 0000-0002-5653-8489","orcid":"https://orcid.org/0000-0002-5653-8489","contributorId":214713,"corporation":false,"usgs":true,"family":"Killion","given":"Walter","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":932123,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70229525,"text":"70229525 - 2022 - Human-in-the-Loop segmentation of earth surface imagery","interactions":[],"lastModifiedDate":"2022-03-10T21:47:50.876493","indexId":"70229525","displayToPublicDate":"2022-02-02T15:44:05","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5026,"text":"Earth and Space Science","active":true,"publicationSubtype":{"id":10}},"title":"Human-in-the-Loop segmentation of earth surface imagery","docAbstract":"

Segmentation, or the classification of pixels (grid cells) in imagery, is ubiquitously applied in the natural sciences. Manual methods are often prohibitively time-consuming, especially those images consisting of small objects and/or significant spatial heterogeneity of colors or textures. Labeling complicated regions of transition that in Earth surface imagery are represented by collections of mixed-pixels, -textures, and -spectral signatures, can be especially error-prone because it is difficult to reliably unmix, identify and delineate consistently. However, the success of supervised machine learning (ML) approaches is entirely dependent on good label data. We describe a fast, semi-automated, method for interactive segmentation of N-dimensional (x, y, N) images into two-dimensional (x, y) label images. It uses human-in-the-loop ML to achieve consensus between the labeler and a model in an iterative workflow. The technique is reproducible; the sequence of decisions made by human labeler and ML algorithms can be encoded to file, so the entire process can be played back and new outputs generated with alternative decisions and/or algorithms. We illustrate the scientific potential of segmentation of imagery of diverse settings and image types using six case studies from river, estuarine, and open coast environments. These photographic and non-photographic imagery consist of 1- and 3-bands on regular and irregular grids ranging from centimeters to tens of meters. We demonstrate high levels of agreement in label images generated by several labelers on the same imagery, and make suggestions to achieve consensus and measure uncertainty, ideal for widespread application in training supervised ML for image segmentation.

","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2021EA002085","usgsCitation":"Buscombe, D., Goldstein, E.B., Sherwood, C.R., Bodine, C.S., Brown, J., Favela, J., Fitzpatrick, S., Kranenburg, C.J., Over, J.R., Ritchie, A.C., Warrick, J.A., and Wernette, P., 2022, Human-in-the-Loop segmentation of earth surface imagery: Earth and Space Science, v. 9, e2021EA002085, 31 p., https://doi.org/10.1029/2021EA002085.","productDescription":"e2021EA002085, 31 p.","ipdsId":"IP-132726","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true},{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true},{"id":680,"text":"Woods Hole Science Center","active":false,"usgs":true}],"links":[{"id":448911,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2021ea002085","text":"Publisher Index Page"},{"id":397005,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"9","noUsgsAuthors":false,"publicationDate":"2022-03-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Buscombe, Daniel D. 0000-0001-6217-5584","orcid":"https://orcid.org/0000-0001-6217-5584","contributorId":240661,"corporation":false,"usgs":true,"family":"Buscombe","given":"Daniel D.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":837749,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Goldstein, Evan B. 0000-0001-9358-1016","orcid":"https://orcid.org/0000-0001-9358-1016","contributorId":184210,"corporation":false,"usgs":false,"family":"Goldstein","given":"Evan","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":837750,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sherwood, Christopher R. 0000-0001-6135-3553 csherwood@usgs.gov","orcid":"https://orcid.org/0000-0001-6135-3553","contributorId":2866,"corporation":false,"usgs":true,"family":"Sherwood","given":"Christopher","email":"csherwood@usgs.gov","middleInitial":"R.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":837751,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bodine, Cameron S 0000-0002-1623-3920","orcid":"https://orcid.org/0000-0002-1623-3920","contributorId":288327,"corporation":false,"usgs":false,"family":"Bodine","given":"Cameron","email":"","middleInitial":"S","affiliations":[{"id":61729,"text":"School of Informatics, Computing and Cybersystems, Northern Arizona University","active":true,"usgs":false}],"preferred":false,"id":837752,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Brown, Jenna A. 0000-0003-3137-7073","orcid":"https://orcid.org/0000-0003-3137-7073","contributorId":208564,"corporation":false,"usgs":true,"family":"Brown","given":"Jenna A.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":837753,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Favela, Jaycee 0000-0001-9175-8324","orcid":"https://orcid.org/0000-0001-9175-8324","contributorId":288328,"corporation":false,"usgs":false,"family":"Favela","given":"Jaycee","email":"","affiliations":[{"id":27155,"text":"University of California Santa Cruz","active":true,"usgs":false}],"preferred":false,"id":837754,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Fitzpatrick, Sharon 0000-0001-6513-9132","orcid":"https://orcid.org/0000-0001-6513-9132","contributorId":288329,"corporation":false,"usgs":false,"family":"Fitzpatrick","given":"Sharon","email":"","affiliations":[{"id":39151,"text":"California State University Sacramento","active":true,"usgs":false}],"preferred":false,"id":837755,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Kranenburg, Christine J. 0000-0002-2955-0167 ckranenburg@usgs.gov","orcid":"https://orcid.org/0000-0002-2955-0167","contributorId":169234,"corporation":false,"usgs":true,"family":"Kranenburg","given":"Christine","email":"ckranenburg@usgs.gov","middleInitial":"J.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":837756,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Over, Jin-Si R. 0000-0001-6753-7185 jover@usgs.gov","orcid":"https://orcid.org/0000-0001-6753-7185","contributorId":260178,"corporation":false,"usgs":true,"family":"Over","given":"Jin-Si","email":"jover@usgs.gov","middleInitial":"R.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":837757,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Ritchie, Andrew C. aritchie@usgs.gov","contributorId":4984,"corporation":false,"usgs":true,"family":"Ritchie","given":"Andrew","email":"aritchie@usgs.gov","middleInitial":"C.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":837758,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Warrick, Jonathan A. 0000-0002-0205-3814 jwarrick@usgs.gov","orcid":"https://orcid.org/0000-0002-0205-3814","contributorId":167736,"corporation":false,"usgs":true,"family":"Warrick","given":"Jonathan","email":"jwarrick@usgs.gov","middleInitial":"A.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":837759,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Wernette, Phillipe Alan 0000-0002-8902-5575","orcid":"https://orcid.org/0000-0002-8902-5575","contributorId":259274,"corporation":false,"usgs":true,"family":"Wernette","given":"Phillipe Alan","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":837760,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70228127,"text":"70228127 - 2022 - Conservation under uncertainty: Innovations in participatory climate change scenario planning from U.S. national parks","interactions":[],"lastModifiedDate":"2022-03-28T16:48:06.539021","indexId":"70228127","displayToPublicDate":"2022-02-02T10:41:27","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5803,"text":"Conservation Science and Practice","active":true,"publicationSubtype":{"id":10}},"title":"Conservation under uncertainty: Innovations in participatory climate change scenario planning from U.S. national parks","docAbstract":"

The impacts of climate change (CC) on natural and cultural resources are far-reaching and complex. A major challenge facing resource managers is not knowing the exact timing and nature of those impacts. To confront this problem, scientists, adaptation specialists, and resource managers have begun to use scenario planning (SP). This structured process identifies a small set of scenarios—descriptions of potential future conditions that encompass the range of critical uncertainties—and uses them to inform planning. We reflect on a series of five recent participatory CC SP projects at four US National Park Service units and derive guidelines for using CC SP to support natural and cultural resource conservation. Specifically, we describe how these engagements affected management, present a generalized CC SP approach grounded in management priorities, and share key insights and innovations that (1) fostered participant confidence and deep engagement in the participatory CC SP process, (2) shared technical information in a way that encouraged informed, effective participation, (3) contextualized CC SP in the broader picture of relevant longstanding or emerging nonclimate stressors, (4) incorporated quantitative approaches to expand analytical capacity and assess qualitative findings, and (5) translated scenarios and all their complexity into strategic action.

","language":"English","publisher":"Society for Conservation Biology","doi":"10.1111/csp2.12633","usgsCitation":"Miller, B.W., Schuurman, G.W., Symstad, A., Runyon, A.C., and Robb, B.C., 2022, Conservation under uncertainty: Innovations in participatory climate change scenario planning from U.S. national parks: Conservation Science and Practice, v. 4, no. 3, e12633, 15 p., https://doi.org/10.1111/csp2.12633.","productDescription":"e12633, 15 p.","ipdsId":"IP-132976","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true},{"id":40927,"text":"North Central Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":448914,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/csp2.12633","text":"Publisher Index Page"},{"id":395439,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"4","issue":"3","noUsgsAuthors":false,"publicationDate":"2022-02-02","publicationStatus":"PW","contributors":{"authors":[{"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":833177,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schuurman, Gregor W. 0000-0002-9304-7742","orcid":"https://orcid.org/0000-0002-9304-7742","contributorId":147698,"corporation":false,"usgs":false,"family":"Schuurman","given":"Gregor","email":"","middleInitial":"W.","affiliations":[{"id":16909,"text":"U.S. National Park Service, Natural Resource Stewardship and Science, Fort Collins, CO, 80525, USA","active":true,"usgs":false}],"preferred":false,"id":833178,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Symstad, Amy 0000-0003-4231-2873 asymstad@usgs.gov","orcid":"https://orcid.org/0000-0003-4231-2873","contributorId":201095,"corporation":false,"usgs":true,"family":"Symstad","given":"Amy","email":"asymstad@usgs.gov","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":833179,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Runyon, Amber C 0000-0002-7282-1217","orcid":"https://orcid.org/0000-0002-7282-1217","contributorId":274643,"corporation":false,"usgs":false,"family":"Runyon","given":"Amber","email":"","middleInitial":"C","affiliations":[{"id":56633,"text":"U.S. National Park Service Climate Change Response Program","active":true,"usgs":false}],"preferred":false,"id":833180,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Robb, Brecken C. 0000-0001-9016-249X","orcid":"https://orcid.org/0000-0001-9016-249X","contributorId":274644,"corporation":false,"usgs":true,"family":"Robb","given":"Brecken","email":"","middleInitial":"C.","affiliations":[{"id":40927,"text":"North Central Climate Adaptation Science Center","active":true,"usgs":true}],"preferred":true,"id":833181,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70256710,"text":"70256710 - 2022 - Tidally-driven gas exchange in beaches: Implications for sea turtle nest success","interactions":[],"lastModifiedDate":"2024-09-03T15:25:54.568198","indexId":"70256710","displayToPublicDate":"2022-02-02T10:20:35","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2220,"text":"Journal of Coastal Research","active":true,"publicationSubtype":{"id":10}},"title":"Tidally-driven gas exchange in beaches: Implications for sea turtle nest success","docAbstract":"

The success of individual sea turtle nests is influenced by nest location on the beach and the resulting incubation environment. Several abiotic factors affect nest incubation, and thus nest success, but tides and gas exchange are two of the most important. The effects of tides on nest success have been well documented in regard to overwash and inundation events. However, the possible effect of tidally-driven gas exchange has received little attention. The incursion and retreat of the saltwater wedge may cause substantial movement of gases through the beach during the tidal cycle. This study quantifies the differences in tidally-driven gas exchange among beach types and shoreline elevation levels. Carbon dioxide (CO2) efflux was used as a means of measuring gas movement through the beach to examine tidal effects across different beach zones and among different beach types. CO2 efflux was measured throughout the tidal cycle at three distinct beaches (accreting, eroding, and nourished) at Cape San Blas, Florida. There was a general pattern of CO2 efflux rising and falling throughout the tidal cycle on each beach and a difference in the CO2 efflux observed among beaches and beach zones. Efflux patterns at the nourished and eroding beaches were similar, but the nourished beach exhibited a decreased and dampened CO2 efflux pattern throughout the course of the tidal cycle. Analyses of the hatchling turtle emergence success data from 2011 to 2014 for the three beaches found that emergence success differed among the three beaches. The highest emergence success was on the nourished beach, which exhibited a relatively consistent efflux pattern. These results suggest that tidally-driven gas exchange may have implications on nest incubation and survival and are a consideration in beach restoration management and best practices for coastline conservation.

","language":"English","publisher":"Coastal Education and Research Foundation, Inc.","doi":"10.2112/JCOASTRES-D-21-00082.1","usgsCitation":"Goforth, K., and Carthy, R., 2022, Tidally-driven gas exchange in beaches: Implications for sea turtle nest success: Journal of Coastal Research, v. 38, no. 3, p. 523-537, https://doi.org/10.2112/JCOASTRES-D-21-00082.1.","productDescription":"15 p.","startPage":"523","endPage":"537","ipdsId":"IP-130877","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":433408,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","county":"Gulf County","otherGeospatial":"Eglin Air Force Base–CSB, and Rish Park, Salinas Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -85.40572058069057,\n 29.74177252032031\n ],\n [\n -85.37633878087428,\n 29.664358173736517\n ],\n [\n -85.3489157677126,\n 29.658826431928226\n ],\n [\n -85.32541032785983,\n 29.663507352511033\n ],\n [\n -85.35087455436684,\n 29.69243951475036\n ],\n [\n -85.37927696085592,\n 29.739645420414227\n ],\n [\n -85.40572058069057,\n 29.74177252032031\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"38","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Goforth, K.M.","contributorId":341648,"corporation":false,"usgs":false,"family":"Goforth","given":"K.M.","email":"","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":908739,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Carthy, Raymond 0000-0001-8978-5083","orcid":"https://orcid.org/0000-0001-8978-5083","contributorId":219303,"corporation":false,"usgs":true,"family":"Carthy","given":"Raymond","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":908740,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70227958,"text":"70227958 - 2022 - Poor relationships between NEON Airborne Observation Platform data and field-based vegetation traits at a mesic grassland","interactions":[],"lastModifiedDate":"2022-02-02T15:10:24.469421","indexId":"70227958","displayToPublicDate":"2022-02-02T09:04:27","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1465,"text":"Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Poor relationships between NEON Airborne Observation Platform data and field-based vegetation traits at a mesic grassland","docAbstract":"Understanding spatial and temporal variation in plant traits is needed to accurately predict how communities and ecosystems will respond to global change. The National Observatory Ecological Network (NEON) Airborne Observation Platform (AOP) provides hyperspectral images and associated data products at numerous field sites at 1 m spatial resolution, potentially allowing high-resolution trait mapping. We tested the accuracy of NEON’s readily available AOP derived data products – Leaf Area Index, Total biomass, Ecosystem structure (Canopy height model; CHM), and Canopy Nitrogen by comparing them to spatially extensive field measurements from a mesic tallgrass prairie. Correlations with AOP data products exhibited generally weak or no relationships with corresponding field measurements. The strongest relationships were between AOP LAI and ground-measured LAI (r = 0.32) and AOP Total biomass and ground-measured biomass (r = 0.23). We also examined how well the full reflectance spectra (380-2500 nm), as opposed to derived products, could predict vegetation traits using partial least-squares regression models. Only one of the eight traits examined, Nitrogen, had a validation R2 of more than 0.25. For all vegetation traits, validation R2 ranged from 0.08-0.29 and the root mean square error of prediction ranged from 14-64%. Our results suggest that currently available AOP derived data products should not be used without extensive ground-based validation. Relationships using the full reflectance spectra may be more promising, although careful consideration of field and AOP data mismatches in space and/or time, biases in field-based measurements or AOP algorithms, and model uncertainty are needed. Finally, grassland sites may be especially challenging for airborne spectroscopy because of their high species diversity within a small area, mixed functional types of plant communities, and heterogenous mosaics of disturbance and resource availability. Remote sensing observations are one of the most promising approaches to understanding ecological patterns across space and time, yet the opportunity to engage a diverse community of NEON data users will depend on establishing rigorous links with in-situ field measurements across a diversity of sites.","language":"English","publisher":"Wiley","doi":"10.1002/ecy.3590","usgsCitation":"Pau, S., Nippert, J., Slapikas, R., Griffith, D.M., Bachle, S., Helliker, B., O’Connor, R., Riley, W.J., Still, C.J., and Zaricor, M., 2022, Poor relationships between NEON Airborne Observation Platform data and field-based vegetation traits at a mesic grassland: Ecology, v. 103, no. 2, e03590, https://doi.org/10.1002/ecy.3590.","productDescription":"e03590","ipdsId":"IP-123791","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":395269,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"103","issue":"2","noUsgsAuthors":false,"publicationDate":"2021-12-16","publicationStatus":"PW","contributors":{"editors":[{"text":"Borer, Elizabeth T.","contributorId":45049,"corporation":false,"usgs":false,"family":"Borer","given":"Elizabeth","email":"","middleInitial":"T.","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":832742,"contributorType":{"id":2,"text":"Editors"},"rank":1}],"authors":[{"text":"Pau, Stephanie","contributorId":190208,"corporation":false,"usgs":false,"family":"Pau","given":"Stephanie","email":"","affiliations":[],"preferred":false,"id":832703,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nippert, Jesse","contributorId":273240,"corporation":false,"usgs":false,"family":"Nippert","given":"Jesse","affiliations":[],"preferred":false,"id":832704,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Slapikas, Ryan","contributorId":273467,"corporation":false,"usgs":false,"family":"Slapikas","given":"Ryan","email":"","affiliations":[{"id":7092,"text":"Florida State University","active":true,"usgs":false}],"preferred":false,"id":832741,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Griffith, Daniel Mark 0000-0001-7463-4004","orcid":"https://orcid.org/0000-0001-7463-4004","contributorId":271033,"corporation":false,"usgs":true,"family":"Griffith","given":"Daniel","email":"","middleInitial":"Mark","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":832705,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bachle, Seton","contributorId":273242,"corporation":false,"usgs":false,"family":"Bachle","given":"Seton","email":"","affiliations":[],"preferred":false,"id":832706,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Helliker, Brent","contributorId":273243,"corporation":false,"usgs":false,"family":"Helliker","given":"Brent","email":"","affiliations":[],"preferred":false,"id":832707,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"O’Connor, Rory","contributorId":273244,"corporation":false,"usgs":false,"family":"O’Connor","given":"Rory","affiliations":[],"preferred":false,"id":832708,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Riley, William J. 0000-0002-4615-2304","orcid":"https://orcid.org/0000-0002-4615-2304","contributorId":194645,"corporation":false,"usgs":false,"family":"Riley","given":"William","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":832709,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Still, Christopher J.","contributorId":167581,"corporation":false,"usgs":false,"family":"Still","given":"Christopher","email":"","middleInitial":"J.","affiliations":[{"id":24761,"text":"University of California, Santa Barbara; Oregon State University","active":true,"usgs":false}],"preferred":false,"id":832710,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Zaricor, Marissa","contributorId":273245,"corporation":false,"usgs":false,"family":"Zaricor","given":"Marissa","email":"","affiliations":[],"preferred":false,"id":832711,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70230063,"text":"70230063 - 2022 - Rainfall an unlikely trigger of Kilauea’s 2018 rift eruption","interactions":[],"lastModifiedDate":"2022-03-28T13:47:26.611874","indexId":"70230063","displayToPublicDate":"2022-02-02T08:34:06","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2840,"text":"Nature","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Rainfall an unlikely trigger of Kīlauea’s 2018 rift eruption","title":"Rainfall an unlikely trigger of Kilauea’s 2018 rift eruption","docAbstract":"

If volcanic eruptions could be forecast from the occurrence of some external process, it might be possible to better mitigate risk and protect lives and livelihoods. Farquharson and Amelung1 suggested that the 2018 lower East Rift Zone (ERZ) eruption of Kīlauea Volcano—the most destructive eruption in Hawai‘i in at least 200 years2—was triggered by extreme precipitation, which caused increased pore pressure that resulted in mechanical weakening of the volcano. Here we argue that Kīlauea’s 2018 eruption was instead caused by significant pre-eruptive pressurization, that pre-eruptive rainfall was not extreme, and that there is no significant correlation between rain and eruptions at Kīlauea. Understanding the causal mechanisms of volcanic eruptions is vital for hazard assessment and mitigation, and misattribution may compromise monitoring, preparedness, communication and response efforts.

","language":"English","publisher":"Springer","doi":"10.1038/s41586-021-04163-1","usgsCitation":"Poland, M., Hurwitz, S., Kauahikaua, J.P., Montgomery-Brown, E.K., Anderson, K.R., Johanson, I.A., Patrick, M.R., and Neal, C.A., 2022, Rainfall an unlikely trigger of Kilauea’s 2018 rift eruption: Nature, v. 602, no. 7895, p. E7-E10, https://doi.org/10.1038/s41586-021-04163-1.","productDescription":"4 p.","startPage":"E7","endPage":"E10","ipdsId":"IP-119030","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":397697,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"Kilauea Volcano","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -155.511474609375,\n 19.21780295966795\n ],\n [\n -154.8,\n 19.21780295966795\n ],\n [\n -154.8,\n 19.6\n ],\n [\n -155.511474609375,\n 19.6\n ],\n [\n -155.511474609375,\n 19.21780295966795\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"602","issue":"7895","noUsgsAuthors":false,"publicationDate":"2022-02-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Poland, Michael 0000-0001-5240-6123","orcid":"https://orcid.org/0000-0001-5240-6123","contributorId":49920,"corporation":false,"usgs":true,"family":"Poland","given":"Michael","affiliations":[{"id":336,"text":"Hawaiian Volcano Observatory","active":false,"usgs":true}],"preferred":true,"id":838933,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hurwitz, Shaul 0000-0001-5142-6886 shaulh@usgs.gov","orcid":"https://orcid.org/0000-0001-5142-6886","contributorId":2169,"corporation":false,"usgs":true,"family":"Hurwitz","given":"Shaul","email":"shaulh@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":438,"text":"National Research Program - 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2022 - Operational assessment tool for forest carbon dynamics for the United States: A new spatially explicit approach linking the LUCAS and CBM-CFS3 models","interactions":[],"lastModifiedDate":"2023-09-22T13:35:38.842499","indexId":"70248850","displayToPublicDate":"2022-02-02T08:26:38","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1183,"text":"Carbon Balance and Management","active":true,"publicationSubtype":{"id":10}},"title":"Operational assessment tool for forest carbon dynamics for the United States: A new spatially explicit approach linking the LUCAS and CBM-CFS3 models","docAbstract":"

Background

Quantifying the carbon balance of forested ecosystems has been the subject of intense study involving the development of numerous methodological approaches. Forest inventories, processes-based biogeochemical models, and inversion methods have all been used to estimate the contribution of U.S. forests to the global terrestrial carbon sink. However, estimates have ranged widely, largely based on the approach used, and no single system is appropriate for operational carbon quantification and forecasting. We present estimates obtained using a new spatially explicit modeling framework utilizing a “gain–loss” approach, by linking the LUCAS model of land-use and land-cover change with the Carbon Budget Model of the Canadian Forest Sector (CBM-CFS3).

Results

We estimated forest ecosystems in the conterminous United States stored 52.0 Pg C across all pools. Between 2001 and 2020, carbon storage increased by 2.4 Pg C at an annualized rate of 126 Tg C year−1. Our results broadly agree with other studies using a variety of other methods to estimate the forest carbon sink. Climate variability and change was the primary driver of annual variability in the size of the net carbon sink, while land-use and land-cover change and disturbance were the primary drivers of the magnitude, reducing annual sink strength by 39%. Projections of carbon change under climate scenarios for the western U.S. find diverging estimates of carbon balance depending on the scenario. Under a moderate emissions scenario we estimated a 38% increase in the net sink of carbon, while under a high emissions scenario we estimated a reversal from a net sink to net source.

Conclusions

The new approach provides a fully coupled modeling framework capable of producing spatially explicit estimates of carbon stocks and fluxes under a range of historical and/or future socioeconomic, climate, and land management futures.

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the effects of hydrology on fish populations is essential to managing for native fish conservation. However, despite decades of research illustrating streamflow influences on fish habitat, reproduction and survival, biologists remain challenged when tasked with predicting how fish populations will respond to changes in flow regimes. This uncertainty stems from insufficient understanding of the context-dependent mechanisms underlying fish responses to, for example, periods of reduced flow or altered frequency of high-flow events. We aim to address this gap by drawing on previous research to hypothesize mechanisms by which low- and high-flows influence fish populations and communities, identifying challenges that stem from data limitations and ecological complexity, and outlining research directions that can advance an empirical basis for prediction. Focusing flow-ecology research on testing and refining mechanistic hypotheses can help narrow management uncertainties and better support species conservation in changing flow regimes.","language":"English","publisher":"Wiley","doi":"10.1002/fsh.10731","usgsCitation":"Freeman, M., Bestgen, K., Carlisle, D.M., Frimpong, E.A., Franssen, N.R., Gido, K.B., Irwin, E.R., Kanno, Y., Luce, C.H., McKay, S.K., Mims, M.C., Olden, J., Poff, N.L., Propst, D.L., Rack, L., Roy, A.H., Stowe, E.S., Walters, A.W., and Wenger, S., 2022, Toward improved prediction of streamflow effects on freshwater fishes: Fisheries Magazine, v. 47, no. 7, p. 290-298, https://doi.org/10.1002/fsh.10731.","productDescription":"9 p.","startPage":"290","endPage":"298","ipdsId":"IP-128605","costCenters":[{"id":683,"text":"Wyoming Cooperative Fish and Wildlife Research Unit","active":false,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":448921,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/fsh.10731","text":"Publisher Index Page"},{"id":395266,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"47","issue":"7","noUsgsAuthors":false,"publicationDate":"2022-03-09","publicationStatus":"PW","contributors":{"authors":[{"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":832721,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bestgen, Kevin R.","contributorId":264509,"corporation":false,"usgs":false,"family":"Bestgen","given":"Kevin R.","affiliations":[{"id":13606,"text":"CSU","active":true,"usgs":false}],"preferred":false,"id":832722,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Carlisle, Daren M. 0000-0002-7367-348X dcarlisle@usgs.gov","orcid":"https://orcid.org/0000-0002-7367-348X","contributorId":513,"corporation":false,"usgs":true,"family":"Carlisle","given":"Daren","email":"dcarlisle@usgs.gov","middleInitial":"M.","affiliations":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":503,"text":"Office of Water Quality","active":true,"usgs":true},{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":832723,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Frimpong, Emmanuel A.","contributorId":273251,"corporation":false,"usgs":false,"family":"Frimpong","given":"Emmanuel","email":"","middleInitial":"A.","affiliations":[{"id":12694,"text":"Virginia Tech","active":true,"usgs":false}],"preferred":false,"id":832724,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Franssen, Nathan R.","contributorId":273252,"corporation":false,"usgs":false,"family":"Franssen","given":"Nathan","email":"","middleInitial":"R.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":832725,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Gido, Ketih B.","contributorId":273253,"corporation":false,"usgs":false,"family":"Gido","given":"Ketih","email":"","middleInitial":"B.","affiliations":[{"id":12661,"text":"Kansas State University","active":true,"usgs":false}],"preferred":false,"id":832726,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Irwin, Elise R. 0000-0002-6866-4976 eirwin@usgs.gov","orcid":"https://orcid.org/0000-0002-6866-4976","contributorId":2588,"corporation":false,"usgs":true,"family":"Irwin","given":"Elise","email":"eirwin@usgs.gov","middleInitial":"R.","affiliations":[{"id":506,"text":"Office of the AD Ecosystems","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":832727,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Kanno, Yoichiro","contributorId":210653,"corporation":false,"usgs":false,"family":"Kanno","given":"Yoichiro","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":832728,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Luce, Charles H.","contributorId":177837,"corporation":false,"usgs":false,"family":"Luce","given":"Charles","email":"","middleInitial":"H.","affiliations":[{"id":37389,"text":"U.S. Forest Service","active":true,"usgs":false}],"preferred":false,"id":832729,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"McKay, S. Kyle","contributorId":169086,"corporation":false,"usgs":false,"family":"McKay","given":"S.","email":"","middleInitial":"Kyle","affiliations":[],"preferred":false,"id":832730,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Mims, Meryl C. 0000-0003-0570-988X","orcid":"https://orcid.org/0000-0003-0570-988X","contributorId":209951,"corporation":false,"usgs":false,"family":"Mims","given":"Meryl","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":832731,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Olden, Julian D.","contributorId":202893,"corporation":false,"usgs":false,"family":"Olden","given":"Julian D.","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":832732,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Poff, N. LeRoy","contributorId":261271,"corporation":false,"usgs":false,"family":"Poff","given":"N.","email":"","middleInitial":"LeRoy","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":832733,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Propst, David L.","contributorId":273254,"corporation":false,"usgs":false,"family":"Propst","given":"David","email":"","middleInitial":"L.","affiliations":[{"id":36307,"text":"University of New Mexico","active":true,"usgs":false}],"preferred":false,"id":832734,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Rack, Laura","contributorId":273255,"corporation":false,"usgs":false,"family":"Rack","given":"Laura","email":"","affiliations":[{"id":12697,"text":"University of Georgia","active":true,"usgs":false}],"preferred":false,"id":832735,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Roy, Allison H. 0000-0002-8080-2729 aroy@usgs.gov","orcid":"https://orcid.org/0000-0002-8080-2729","contributorId":4240,"corporation":false,"usgs":true,"family":"Roy","given":"Allison","email":"aroy@usgs.gov","middleInitial":"H.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":832736,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Stowe, Edward S.","contributorId":273256,"corporation":false,"usgs":false,"family":"Stowe","given":"Edward","email":"","middleInitial":"S.","affiliations":[{"id":12697,"text":"University of Georgia","active":true,"usgs":false}],"preferred":false,"id":832737,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Walters, Annika W. 0000-0002-8638-6682 awalters@usgs.gov","orcid":"https://orcid.org/0000-0002-8638-6682","contributorId":4190,"corporation":false,"usgs":true,"family":"Walters","given":"Annika","email":"awalters@usgs.gov","middleInitial":"W.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":832738,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Wenger, Seth J.","contributorId":177838,"corporation":false,"usgs":false,"family":"Wenger","given":"Seth J.","affiliations":[],"preferred":false,"id":832739,"contributorType":{"id":1,"text":"Authors"},"rank":19}]}} ,{"id":70241786,"text":"70241786 - 2022 - The role of monitoring and research in the Greater Yellowstone Ecosystem in framing our understanding of the effects of disease on amphibians","interactions":[],"lastModifiedDate":"2023-03-27T12:13:51.160574","indexId":"70241786","displayToPublicDate":"2022-02-02T07:12:03","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1456,"text":"Ecological Indicators","active":true,"publicationSubtype":{"id":10}},"title":"The role of monitoring and research in the Greater Yellowstone Ecosystem in framing our understanding of the effects of disease on amphibians","docAbstract":"

Emerging infectious disease threatens amphibian biodiversity worldwide, including in landscapes that are protected from many anthropogenic stressors. We summarized data from studies in the Greater Yellowstone Ecosystem (GYE), one of the largest and most complete temperate-zone ecosystems on Earth, to assess the current state of knowledge about ranaviruses and the novel amphibian chytrid fungus (Bd) in this landscape, and to provide insight into future threats and conservation strategies. Our comprehension of these amphibian diseases in the GYE is based on >20 years of monitoring, surveys, population studies, and opportunistic observations of mortality events. Research indicates that local species are affected differently, depending on temperature, community structure, and location in the GYE. Bd has not been linked to die-offs in the GYE but evidence for ongoing reductions in survival contributes to foundational data about the effects of this pathogen in North America. Localized mortality events attributed to, or consistent with, disease from ranaviruses, are widespread in the GYE, but there is less information on how ranaviruses affect amphibian vital rates. The significance of disease in the long-term persistence of amphibians in the GYE is linked to anticipated changes in climate, especially drought. Additionally, expected increases in visitor use, and its associated impacts, have the potential to exacerbate the effects of disease. Long-term information from this large, intact landscape helps to frame our understanding of the effects of disease on amphibians and provides data that can contribute to management decisions, mitigation strategies, and forecasting efforts.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolind.2022.108577","usgsCitation":"Muths, E.L., and Hossack, B.R., 2022, The role of monitoring and research in the Greater Yellowstone Ecosystem in framing our understanding of the effects of disease on amphibians: Ecological Indicators, v. 136, 108577, 10 p., https://doi.org/10.1016/j.ecolind.2022.108577.","productDescription":"108577, 10 p.","ipdsId":"IP-132880","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":448923,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecolind.2022.108577","text":"Publisher Index Page"},{"id":414770,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wyoming","otherGeospatial":"Greater Yellowstone Ecosystem","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -111.28035985446333,\n 45.220187202284905\n ],\n [\n -111.28035985446333,\n 42.77976798388039\n ],\n [\n -108.9412781432977,\n 42.77976798388039\n ],\n [\n -108.9412781432977,\n 45.220187202284905\n ],\n [\n -111.28035985446333,\n 45.220187202284905\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"136","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Muths, Erin L. 0000-0002-5498-3132 muthse@usgs.gov","orcid":"https://orcid.org/0000-0002-5498-3132","contributorId":1260,"corporation":false,"usgs":true,"family":"Muths","given":"Erin","email":"muthse@usgs.gov","middleInitial":"L.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":867562,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hossack, Blake R. 0000-0001-7456-9564 blake_hossack@usgs.gov","orcid":"https://orcid.org/0000-0001-7456-9564","contributorId":1177,"corporation":false,"usgs":true,"family":"Hossack","given":"Blake","email":"blake_hossack@usgs.gov","middleInitial":"R.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":867563,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70234356,"text":"70234356 - 2022 - Activity patterns of Hawaiian forest birds in a fragmented and continuous landscape","interactions":[],"lastModifiedDate":"2022-08-09T12:13:46.931348","indexId":"70234356","displayToPublicDate":"2022-02-02T07:11:43","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2190,"text":"Journal of Avian Biology","active":true,"publicationSubtype":{"id":10}},"title":"Activity patterns of Hawaiian forest birds in a fragmented and continuous landscape","docAbstract":"

Activity patterns are a key component of avian life history and behavior, and decisions about how activity periods are structured can have important fitness implications. Despite the importance of activity patterns, individual variability in activity is poorly studied in small birds. We used automated radio telemetry to track Hawaiian forest birds from three dietary guilds in a continuous forest, and in a similar forest that was naturally fragmented in the 1800s by lava flows but supports stable populations of native birds. We generated kernel density profiles of activity (KDEs) over the full tracking period of each bird and used the KDEs to derive seven activity metrics that characterized daily activity patterns. We identified three distinct activity strategies using a cluster analysis of the activity metrics and assessed day-to-day variability in activity strategy to understand intraindividual consistency in activity behavior. We also evaluated the influence of landscape structure, dietary guild and sex on the suite of activity metrics using constrained ordination. Most birds (61%) exhibited high levels of sustained activity throughout the day, while 23% showed irregular activity most of the day followed by a peak in the late afternoon, and 16% were mainly active in the morning. Though activity patterns varied by sex and dietary guild, landscape structure had the strongest influence on activity patterns. Birds sustained high levels of activity throughout the day in the fragmented landscape regardless of dietary guild, suggesting they needed to be more active to obtain necessary resources. However, activity patterns of birds in the fragmented landscape varied more day-to-day, indicating they retained a method for adjusting behavior to match internal and external conditions. This study reveals how a diverse suite of tropical birds has adapted to long-term fragmentation in Hawaiʻi and demonstrates the utility of automated radio telemetry for studying the activity strategies of birds.

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Mississippi","active":true,"usgs":false}],"preferred":false,"id":848631,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hart, Patrick J.","contributorId":147728,"corporation":false,"usgs":false,"family":"Hart","given":"Patrick","email":"","middleInitial":"J.","affiliations":[{"id":6977,"text":"University of Hawai`i at Hilo","active":true,"usgs":false}],"preferred":false,"id":848632,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Paxton, Eben H. 0000-0001-5578-7689","orcid":"https://orcid.org/0000-0001-5578-7689","contributorId":19640,"corporation":false,"usgs":true,"family":"Paxton","given":"Eben","email":"","middleInitial":"H.","affiliations":[{"id":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true}],"preferred":true,"id":848633,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70241787,"text":"70241787 - 2022 - Context-dependent variation in persistence of host populations in the face of disease","interactions":[],"lastModifiedDate":"2023-03-27T12:07:35.971729","indexId":"70241787","displayToPublicDate":"2022-02-02T07:06:33","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2158,"text":"Journal of Animal Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Context-dependent variation in persistence of host populations in the face of disease","docAbstract":"

Research Highlight: Valenzuela-Sánchez, A., Azat, C., Cunningham, A. A., Delgado, S., Bacigalupe, L. D., Beltrand, J., Serrano, J. M., Sentenac, H., Haddow, N., Toledo, V., Schmidt, B. R., & Cayuela, H. (2022). Interpopulation differences in male reproductive effort drive the population dynamics of a host exposed to an emerging fungal pathogen. Journal of Animal Ecology, 00, 1– 12. https://doi.org/10.1111/1365-2656.13603. Understanding the nuances of population persistence in the face of a stressor can help predict extinction risk and guide conservation actions. However, the exact mechanisms driving population stability may not always be known. In this paper, Valenzuela-Sánchez et al. (2022) integrate long-term mark–recapture data, focal measurements of reproductive effort, a population matrix model and inferences on life-history variation to reveal differences in demographic response to disease in a susceptible frog species (Rhinoderma darwinii). Valenzuela-Sánchez et al. found that demographic compensation via recruitment explained the positive population growth rate in their high disease prevalence population whereas the low disease prevalence population did not compensate and thus had decreasing population growth. Compensatory recruitment was likely due to the high probability of males brooding, and the high number of brooded larvae in the high prevalence population compared to low prevalence and disease-free populations. Valenzuela-Sánchez et al. also document faster generation times in the high prevalence population, which may indicate a faster life history that may be contributing to the population's ability to compensate for reduced survival. Lastly, the authors find a positive relationship between disease prevalence and the proportion of juveniles in a given population that suggest that there may be a threshold for disease prevalence that triggers increased reproductive effort. Altogether, their study provides novel support for increased reproductive effort as the pathway for compensatory recruitment leading to increasing population growth despite strong negative effects of disease on adult survival. Their results also caution the overgeneralization of the effects of stressors (e.g. disease) on population dynamics, where context-dependent responses may differ among host populations of a given species.

","language":"English","publisher":"British Ecological Society","doi":"10.1111/1365-2656.13654","usgsCitation":"Hardy, B., Muths, E.L., and Koons, D.N., 2022, Context-dependent variation in persistence of host populations in the face of disease: Journal of Animal Ecology, v. 91, no. 2, p. 282-286, https://doi.org/10.1111/1365-2656.13654.","productDescription":"5 p.","startPage":"282","endPage":"286","ipdsId":"IP-135071","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":414767,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"91","issue":"2","noUsgsAuthors":false,"publicationDate":"2022-02-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Hardy, Bennett","contributorId":303568,"corporation":false,"usgs":false,"family":"Hardy","given":"Bennett","email":"","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":867564,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Muths, Erin L. 0000-0002-5498-3132 muthse@usgs.gov","orcid":"https://orcid.org/0000-0002-5498-3132","contributorId":1260,"corporation":false,"usgs":true,"family":"Muths","given":"Erin","email":"muthse@usgs.gov","middleInitial":"L.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":867565,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Koons, David N.","contributorId":28137,"corporation":false,"usgs":false,"family":"Koons","given":"David","email":"","middleInitial":"N.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":867566,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70241895,"text":"70241895 - 2022 - Quantifying streamflow depletion from groundwater pumping: A practical review of past and emerging approaches for water management","interactions":[],"lastModifiedDate":"2023-03-30T11:53:25.809423","indexId":"70241895","displayToPublicDate":"2022-02-02T06:51:42","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2529,"text":"Journal of the American Water Resources Association","active":true,"publicationSubtype":{"id":10}},"title":"Quantifying streamflow depletion from groundwater pumping: A practical review of past and emerging approaches for water management","docAbstract":"

Groundwater pumping can cause reductions in streamflow (“streamflow depletion”) that must be quantified for conjunctive management of groundwater and surface water resources. However, streamflow depletion cannot be measured directly and is challenging to estimate because pumping impacts are masked by streamflow variability due to other factors. Here, we conduct a management-focused review of analytical, numerical, and statistical models for estimating streamflow depletion and highlight promising emerging approaches. Analytical models are easy to implement, but include many assumptions about the stream and aquifer. Numerical models are widely used for streamflow depletion assessment and can represent many processes affecting streamflow, but have high data, expertise, and computational needs. Statistical approaches are a historically underutilized tool due to difficulty in attributing causality, but emerging causal inference techniques merit future research and development. We propose that streamflow depletion-related management questions can be divided into three broad categories (attribution, impacts, and mitigation) that influence which methodology is most appropriate. We then develop decision criteria for method selection based on suitability for local conditions and the management goal, actionability with current or obtainable data and resources, transparency with respect to process and uncertainties, and reproducibility.

","language":"English","publisher":"Wiley","doi":"10.1111/1752-1688.12998","usgsCitation":"Zipper, S., Farmer, W., Brookfield, A.E., Ajami, H., Reeves, H.W., Wardropper, C., Hammond, J., Gleeson, T., and Deines, J.M., 2022, Quantifying streamflow depletion from groundwater pumping: A practical review of past and emerging approaches for water management: Journal of the American Water Resources Association, v. 58, no. 2, p. 289-312, https://doi.org/10.1111/1752-1688.12998.","productDescription":"24 p.","startPage":"289","endPage":"312","ipdsId":"IP-126304","costCenters":[{"id":382,"text":"Michigan Water Science Center","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":448929,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1111/1752-1688.12998","text":"External Repository"},{"id":414952,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"58","issue":"2","noUsgsAuthors":false,"publicationDate":"2022-02-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Zipper, Samuel 0000-0002-8735-5757","orcid":"https://orcid.org/0000-0002-8735-5757","contributorId":225160,"corporation":false,"usgs":false,"family":"Zipper","given":"Samuel","email":"","affiliations":[{"id":41056,"text":"Kansas Geological Survey, University of Kansas, Lawrence KS 66047, USA","active":true,"usgs":false}],"preferred":false,"id":868129,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Farmer, William H. 0000-0002-2865-2196","orcid":"https://orcid.org/0000-0002-2865-2196","contributorId":223181,"corporation":false,"usgs":true,"family":"Farmer","given":"William H.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":868130,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brookfield, Andrea E.","contributorId":202677,"corporation":false,"usgs":false,"family":"Brookfield","given":"Andrea","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":868131,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ajami, Hoori 0000-0001-6883-7630","orcid":"https://orcid.org/0000-0001-6883-7630","contributorId":303806,"corporation":false,"usgs":false,"family":"Ajami","given":"Hoori","email":"","affiliations":[{"id":36629,"text":"University of California","active":true,"usgs":false}],"preferred":false,"id":868132,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Reeves, Howard W. 0000-0001-8057-2081 hwreeves@usgs.gov","orcid":"https://orcid.org/0000-0001-8057-2081","contributorId":2307,"corporation":false,"usgs":true,"family":"Reeves","given":"Howard","email":"hwreeves@usgs.gov","middleInitial":"W.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":868133,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wardropper, Chloe 0000-0002-0652-2315","orcid":"https://orcid.org/0000-0002-0652-2315","contributorId":303807,"corporation":false,"usgs":false,"family":"Wardropper","given":"Chloe","email":"","affiliations":[{"id":36394,"text":"University of Idaho","active":true,"usgs":false}],"preferred":false,"id":868134,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hammond, John C. 0000-0002-4935-0736","orcid":"https://orcid.org/0000-0002-4935-0736","contributorId":223108,"corporation":false,"usgs":true,"family":"Hammond","given":"John C.","affiliations":[{"id":41514,"text":"Maryland-Delaware-District of Columbia Water Science Center","active":true,"usgs":true}],"preferred":true,"id":868135,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Gleeson, Tom","contributorId":42694,"corporation":false,"usgs":false,"family":"Gleeson","given":"Tom","affiliations":[{"id":6646,"text":"McGill University","active":true,"usgs":false}],"preferred":false,"id":868136,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Deines, Jillian M. 0000-0002-4279-8765","orcid":"https://orcid.org/0000-0002-4279-8765","contributorId":303808,"corporation":false,"usgs":false,"family":"Deines","given":"Jillian","email":"","middleInitial":"M.","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":868137,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70262534,"text":"70262534 - 2022 - Mark-recapture models accurately predict growth trajectories of known-age Muskellunge in Green Bay, Lake Michigan","interactions":[],"lastModifiedDate":"2025-01-21T18:57:53.395514","indexId":"70262534","displayToPublicDate":"2022-02-01T12:32:43","publicationYear":"2022","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":"Mark-recapture models accurately predict growth trajectories of known-age Muskellunge in Green Bay, Lake Michigan","docAbstract":"

Length-at-age data are commonly used to describe growth of fish, and obtaining these data typically involves estimating ages from calcified structures (e.g., fin spines or rays, otoliths, or cleithra). Verifying the accuracy of age and growth estimates for long-lived fish is often difficult because known-age fish are not available for all ages in a population. Mark–recapture methods offer nonlethal alternatives for estimating growth of fish that do not require age data. However, few studies have compared growth trajectories estimated from mark–recapture data with trajectories estimated using the standard von Bertalanffy growth function (VBGF) incorporating length-at-age data from known-age fish. We used a robust data set of Muskellunge Esox masquinongy sampled from Green Bay, Lake Michigan, during 1990–2018 to compare growth trajectories estimated from three mark–recapture models and a VBGF fitted to length-at-age data from known-age individuals. Growth trajectories estimated with mark–recapture models were similar to trajectories estimated with a VBGF using known-age fish. Our results suggest that using recapture of tagged fish provides a viable alternative for describing Muskellunge growth trajectories compared with using ages estimated from calcified structures, where incorrect age estimates represent an additional source of error.

","language":"English","publisher":"American Fisheries Society","doi":"10.1002/nafm.10757","usgsCitation":"Sheffer, R., Hogler, S., and Isermann, D.A., 2022, Mark-recapture models accurately predict growth trajectories of known-age Muskellunge in Green Bay, Lake Michigan: North American Journal of Fisheries Management, v. 42, no. 2, p. 410-424, https://doi.org/10.1002/nafm.10757.","productDescription":"15 p.","startPage":"410","endPage":"424","ipdsId":"IP-129450","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":480851,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wisconsin","otherGeospatial":"Green Bay, Lake Michigan, Sturgeon Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -88.27706007733632,\n 44.35374357415128\n ],\n [\n -86.88196993224543,\n 44.35374357415128\n ],\n [\n -86.88196993224543,\n 45.190198563184424\n ],\n [\n -88.27706007733632,\n 45.190198563184424\n ],\n [\n -88.27706007733632,\n 44.35374357415128\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"42","issue":"2","noUsgsAuthors":false,"publicationDate":"2022-02-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Sheffer, Robert J.","contributorId":349585,"corporation":false,"usgs":false,"family":"Sheffer","given":"Robert J.","affiliations":[{"id":17613,"text":"University of Wisconsin - Stevens Point","active":true,"usgs":false}],"preferred":false,"id":924493,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hogler, Steven R.","contributorId":349586,"corporation":false,"usgs":false,"family":"Hogler","given":"Steven R.","affiliations":[{"id":16117,"text":"Wisconsin DNR","active":true,"usgs":false}],"preferred":false,"id":924494,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Isermann, Daniel A. 0000-0003-1151-9097 disermann@usgs.gov","orcid":"https://orcid.org/0000-0003-1151-9097","contributorId":5167,"corporation":false,"usgs":true,"family":"Isermann","given":"Daniel","email":"disermann@usgs.gov","middleInitial":"A.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":924492,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70227605,"text":"cir1489 - 2022 - National assessment of carbon dioxide enhanced oil recovery and associated carbon dioxide retention resources — Results","interactions":[],"lastModifiedDate":"2026-03-16T19:44:20.869218","indexId":"cir1489","displayToPublicDate":"2022-02-01T12:00:00","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":307,"text":"Circular","code":"CIR","onlineIssn":"2330-5703","printIssn":"1067-084X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1489","displayTitle":"National Assessment of Carbon Dioxide Enhanced Oil Recovery and Associated Carbon Dioxide Retention Resources—Results","title":"National assessment of carbon dioxide enhanced oil recovery and associated carbon dioxide retention resources — Results","docAbstract":"

In 2020, the U.S. Geological Survey (USGS) completed a probabilistic assessment of the volume of technically recoverable oil resources available if current carbon dioxide enhanced oil recovery (CO2-EOR) technologies were applied to amenable oil reservoirs underlying the onshore and State waters areas of the conterminous United States. The assessment also includes estimates of the mass of CO2 that could be stored (retained) as a result of CO2-EOR activities. The USGS assessment team evaluated more than 3,500 oil reservoirs that were miscible to injected CO2. The assessed reservoirs are in 185 previously defined USGS plays in 33 petroleum provinces of 7 national regions. The assessment team estimated that the technically recoverable oil associated with CO2-EOR ranges from approximately 25,000 million barrels (MMbbl) at the P5 percentile to as much as 32,000 MMbbl at the P95 percentile, with a mean of 29,000 MMbbl. The associated CO2 retention ranges from approximately 7,400 million metric tons (Mt) at the P5 percentile to as much as 9,500 Mt at the P95 percentile, with a mean of 8,400 Mt. The West Texas and Eastern New Mexico region and the Gulf Coast region together contain 60 percent of the mean assessed CO2-EOR oil potential and 61 percent of the mean assessed CO2 retention. Other regions with significant resource potential include the Midcontinent region and Rocky Mountains and Northern Great Plains region.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/cir1489","programNote":"Energy Resources Program","usgsCitation":"Warwick, P.D., Attanasi, E.D., Blondes, M.S., Brennan, S.T., Buursink, M.L., Cahan, S.M., Doolan, C.A., Freeman, P.A., Karacan, C.Ö., Lohr, C.D., Merrill, M.D., Olea, R.A., Shelton, J.L., Slucher, E.R., and Varela, B.A., 2022, National assessment of carbon dioxide enhanced oil recovery and associated carbon dioxide retention resources—Results: U.S. Geological Survey Circular 1489, 39 p., https://doi.org/10.3133/cir1489.","productDescription":"Report: viii, 39 p.; Data release","numberOfPages":"39","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-122375","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true},{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"links":[{"id":501193,"rank":5,"type":{"id":36,"text":"NGMDB 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Program Coordinator, Energy Resources Program
U.S. Geological Survey
12201 Sunrise Valley Drive
Reston, VA 20192
Telephone: 703–648–6470

Contact Pubs Warehouse

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Introduction

In 2020, the U.S. Geological Survey (USGS) completed a probabilistic assessment of the volume of technically recoverable oil resources that might be produced by using current carbon dioxide enhanced oil recovery (CO2-EOR) technologies in amenable conventional oil reservoirs underlying the onshore and State waters areas of the conterminous United States. The assessment also includes estimates of the mass of CO2 that could be stored (retained) in the assessed oil reservoirs following the application of the CO2-EOR process. The USGS assessment team evaluated more than 3,500 oil reservoirs that were miscible to injected CO2. The assessed reservoirs are in 185 previously defined USGS plays in 33 petroleum provinces of 7 national regions. The team estimated that the total technically recoverable oil resulting from the application of the CO2-EOR process ranges from approximately 25,000 million barrels (MMbbl) at the P5 percentile to as much as 32,000 MMbbl at the P95 percentile, with a mean of 29,000 MMbbl. The associated CO2 retention ranges from approximately 7,400 million metric tons (Mt) at the P5 percentile to as much as 9,500 Mt at the P95 percentile, with a mean of 8,400 Mt. The results are summarized in this fact sheet and are provided in more detail in the companion data release and circular.

The West Texas and Eastern New Mexico region (primarily its Permian Basin) and the Gulf Coast region together contain 60 percent of the mean assessed CO2-EOR oil potential and 61 percent of the mean assessed CO2 retention. Other regions with significant resource potential include the Midcontinent region and the Rocky Mountains and Northern Great Plains region.

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Program Coordinator, Energy Resources Program
U.S. Geological Survey
12201 Sunrise Valley Drive
Reston, VA 20192
Telephone: 703–648–6470

Contact Pubs Warehouse

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The Living Shoreline Demonstration Project (PO-148) used five bio-engineered reef technologies (Reef Balls in two configurations; Figure 1) acting as breakwaters to protect vulnerable shorelines. While the primary goal is to attenuate wave energy, the sustainability and success of these products as “living” shorelines are based on their ability to enhance oyster habitat, enabling the reef to maintain elevation within the rapidly changing environment (i.e., sea level rise, subsidence). This report documents the recruitment, survival, and growth of the living components of the reef – oysters and other encrusting organisms (e.g. mussels, barnacles). This final technical report provides data from five years of monitoring (November 2017 – December 2021) of reefs located along the western side of Eloi Bay in Pontchartrain Basin (Figure 2). Monitoring goals included assessment of (1) annual oyster densities and population dynamics on the reefs, (2) annual density and diversity of other encrusting organisms, and (3) comparisons of outcomes by reef technology, exposure, and water quality. Detailed information on technologies used, construction design, as-built elevations are available in Coast & Harbor Engineering (2016) Design Memorandum dated March 25, 2016, submitted to Louisiana Coastal Protection and Restoration Authority.

","language":"English","publisher":"U.S. Fish & Wildlife Service","doi":"10.3996/css70529922","usgsCitation":"Swam, L.M., Marshall, D.A., and La Peyre, M., 2022, Five years of monitoring a bio-engineered living shoreline: Comparison of oyster population development by reef technology.: Cooperator Science Series 139-2022, ii, 19 p., https://doi.org/10.3996/css70529922.","productDescription":"ii, 19 p.","ipdsId":"IP-137095","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":433383,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Louisiana","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -89.38780223527601,\n 29.790840321829222\n ],\n [\n -89.42069143656458,\n 29.790840321829222\n ],\n [\n -89.42069143656458,\n 29.750906524072846\n ],\n [\n -89.38780223527601,\n 29.750906524072846\n ],\n [\n -89.38780223527601,\n 29.790840321829222\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationDate":"2022-02-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Swam, Lauren M.","contributorId":341585,"corporation":false,"usgs":false,"family":"Swam","given":"Lauren","email":"","middleInitial":"M.","affiliations":[{"id":32913,"text":"Louisiana State University Agricultural Center","active":true,"usgs":false}],"preferred":false,"id":908644,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Marshall, Danielle Aguilar","contributorId":341509,"corporation":false,"usgs":false,"family":"Marshall","given":"Danielle","email":"","middleInitial":"Aguilar","affiliations":[{"id":32913,"text":"Louisiana State University Agricultural Center","active":true,"usgs":false}],"preferred":false,"id":908645,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"La Peyre, Megan K. 0000-0001-9936-2252","orcid":"https://orcid.org/0000-0001-9936-2252","contributorId":264343,"corporation":false,"usgs":true,"family":"La Peyre","given":"Megan K.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":908646,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70249400,"text":"70249400 - 2022 - Comment on ‘Evidence for a large strike-slip component during the 1960 Chilean earthquake’ by H. Kanamori, L. Rivera, and S. Lambotte","interactions":[],"lastModifiedDate":"2023-10-05T15:52:18.805799","indexId":"70249400","displayToPublicDate":"2022-02-01T10:40:16","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1803,"text":"Geophysical Journal International","active":true,"publicationSubtype":{"id":10}},"title":"Comment on ‘Evidence for a large strike-slip component during the 1960 Chilean earthquake’ by H. Kanamori, L. Rivera, and S. Lambotte","docAbstract":"

Based on numerous studies of the relevant geodetic data, a low-angle thrusting mechanism has been assigned to the 1960 Chile earthquake. Kanamori, Rivera and Lambotte recently suggested that a component of dextral slip comparable to the thrusting be included in the mechanism to satisfy long-period, teleseismic observations. The absence of geodetic evidence for that huge strike-slip component is the subject of this comment. The geodetic data are largely measurements of coseismic uplift associated with the earthquake but include eight measurements of the coseismic change in shear strain. Because strike-slip produces relatively little uplift except near the end points of the rupture, identification of that strike-slip component in the geodetic data depends upon the measured, shear-strain change. I consider elastic, half-space models of oblique slip on the plate interface possibly supplemented by simultaneous dextral slip on the nearby, intra-arc Liquiñe-Ofqui Fault Zone. Slip is assumed to be uniform along strike. The best fits to the geodetic data for these models furnish little evidence for strike-slip on those structures. To satisfy the long-period, teleseismic data, Kanamori et al. proposed six examples, each of which requires a large amount of dextral slip. Because the long-period, teleseismic data do not define the slip distributions, I have used the best fits of those examples to the geodetic data to define those distributions. The large thrusting near the deformation front required by those slip distributions implies large uplift there, contrary to the uplift inferred from the inversion of tsunami data. However, an acceptable fit to the geodetic data and the tsunami data for the six examples suggested by Kanamori et al. can be obtained if the seismic moments specified by them are reduced by a factor ∼1.8, a factor within the uncertainties in estimating seismic moments of the 1960 Chile earthquake. The presence of strike-slip in those reduced-moment examples despite the lack of geodetic evidence for strike-slip is due to a remarkable coincidence that requires careful balancing of contributions from the shallower (depths < 70 km) coseismic sources against those from the deeper coseismic sources to nullify the geodetic evidence for strike-slip. Such balancing is possible, but it is remarkable that the balancing is so nearly perfect that it nullifies the geodetic evidence for strike-slip and thereby confounds the interpretation of the geodetic data.

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surveillance of a potential bridge host: Pathogen exposure risks posed to avian populations augmented with captive-bred pheasants","interactions":[],"lastModifiedDate":"2022-05-13T14:39:58.812289","indexId":"70227892","displayToPublicDate":"2022-02-01T10:17:04","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3849,"text":"Transboundary and Emerging Diseases","active":true,"publicationSubtype":{"id":10}},"title":"Health surveillance of a potential bridge host: Pathogen exposure risks posed to avian populations augmented with captive-bred pheasants","docAbstract":"

Augmentation of wild populations with captive-bred individuals presents an inherent risk of co-introducing novel pathogens to naïve species, but it can be an important tool for supplementing small or declining populations. Game species used for human enterprise and recreation such as the ring-necked pheasant (Phasianus colchicus) are commonly raised in captivity and released onto public and private wildlands as a method of augmenting naturalized pheasant populations. This study presents findings on pathogen exposure from three sources of serological data collected in California during 2014–2017 including (a) 71 pen-reared pheasants sampled across seven game bird breeding farms, (b) six previously released pen-reared pheasants captured at two study sites where wild pheasants occurred and (c) 79 wild pheasants captured across six study sites. In both pen-reared and wild pheasants, antibodies were detected against haemorrhagic enteritis virus (HEV), infectious laryngotracheitis (ILT), infectious bursal disease virus (IBDV), paramyxovirus type 1 (PMV-1) and Pasteurella multocida (PM). Previously released pen-reared pheasants were seropositive for HEV, ILT, and PM. Generalized linear mixed models accounting for intraclass correlation within groups indicated that pen-reared pheasants were more than twice as likely to test positive for HEV antibodies. Necropsy and ancillary diagnostics were performed in addition to serological testing on 40 pen-reared pheasants sampled from five of the seven farms. Pheasants from three of these farms tested positive by PCR for Siadenovirus, the causative agent of both haemorrhagic enteritis in turkeys and marble spleen disease of pheasants, which are serologically indistinguishable. Following necropsy, owners from the five farms were surveyed regarding husbandry and biosecurity practices. Farms ranged in size from 10,000 to more than 100,000 birds, two farms raised other game bird species on premises, and two farms used some form of vaccination. Biosecurity practices varied by farm, but the largest farm implemented the strictest practices.

","language":"English","publisher":"Wiley","doi":"10.1111/tbed.14068","usgsCitation":"Dwight, I., Coates, P.S., Stoute, S.T., and Pitesky, M.E., 2022, Health surveillance of a potential bridge host: Pathogen exposure risks posed to avian populations augmented with captive-bred pheasants: Transboundary and Emerging Diseases, v. 69, no. 3, p. 1095-1107, https://doi.org/10.1111/tbed.14068.","productDescription":"13 p.","startPage":"1095","endPage":"1107","ipdsId":"IP-119580","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":448936,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/tbed.14068","text":"Publisher Index Page"},{"id":395209,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Sacramento and San Joaquin Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -119.33349609375,\n 34.88593094075317\n ],\n [\n -118.71826171875,\n 35.191766965947394\n ],\n [\n -118.41064453125,\n 35.871246850027966\n ],\n [\n -119.44335937499999,\n 37.3002752813443\n ],\n [\n -120.80566406250001,\n 39.14710270770074\n ],\n [\n -121.53076171875,\n 40.51379915504413\n ],\n [\n -120.43212890625,\n 41.244772343082076\n ],\n [\n -120.4541015625,\n 42.01665183556825\n ],\n [\n -122.32177734375,\n 42.032974332441405\n ],\n [\n -122.9150390625,\n 41.07935114946899\n ],\n [\n -122.87109375,\n 39.26628442213066\n ],\n [\n -121.88232421875,\n 37.75334401310656\n ],\n [\n -120.73974609374999,\n 36.155617833818525\n ],\n [\n -119.33349609375,\n 34.88593094075317\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"69","issue":"3","noUsgsAuthors":false,"publicationDate":"2021-05-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Dwight, Ian 0000-0002-8393-5391 idwight@usgs.gov","orcid":"https://orcid.org/0000-0002-8393-5391","contributorId":192077,"corporation":false,"usgs":true,"family":"Dwight","given":"Ian","email":"idwight@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":832482,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Coates, Peter S. 0000-0003-2672-9994 pcoates@usgs.gov","orcid":"https://orcid.org/0000-0003-2672-9994","contributorId":3263,"corporation":false,"usgs":true,"family":"Coates","given":"Peter","email":"pcoates@usgs.gov","middleInitial":"S.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":832483,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stoute, Simone T.","contributorId":202770,"corporation":false,"usgs":false,"family":"Stoute","given":"Simone","email":"","middleInitial":"T.","affiliations":[{"id":36526,"text":"California Animal Health and Food Safety Laboratory","active":true,"usgs":false}],"preferred":false,"id":832484,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pitesky, Maurice E.","contributorId":176920,"corporation":false,"usgs":false,"family":"Pitesky","given":"Maurice","email":"","middleInitial":"E.","affiliations":[{"id":7214,"text":"University of California, Davis","active":true,"usgs":false}],"preferred":false,"id":832485,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70227893,"text":"70227893 - 2022 - Management foundations for navigating ecological transformation by resisting, accepting, or directing social-ecological change","interactions":[],"lastModifiedDate":"2022-02-02T14:24:42.435166","indexId":"70227893","displayToPublicDate":"2022-02-01T09:58:04","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":997,"text":"BioScience","active":true,"publicationSubtype":{"id":10}},"title":"Management foundations for navigating ecological transformation by resisting, accepting, or directing social-ecological change","docAbstract":"Despite striking global change, management to ensure healthy landscapes and sustained natural resources has tended to set objectives on the basis of the historical range of variability in stationary ecosystems. Many social–ecological systems are moving into novel conditions that can result in ecological transformation. We present four foundations to enable a transition to future-oriented conservation and management that increases capacity to manage change. The foundations are to identify plausible social–ecological trajectories, to apply upstream and deliberate engagement and decision-making with stakeholders, to formulate management pathways to desired futures, and to consider a portfolio approach to manage risk and account for multiple preferences across space and time. 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