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Biological communities in freshwater streams are often impaired by multiple stressors (e.g., flow or water quality) originating from anthropogenic activities such as urbanization, agriculture, or energy extraction. Restoration efforts in the Chesapeake Bay watershed, USA seek to improve biological conditions in 10% of freshwater tributaries and to protect the biological integrity of existing healthy watersheds. To achieve these goals, resource managers need to better understand which stressors are most likely driving biological impairment. Our study addressed this knowledge gap through two approaches: 1) reviewing and synthesizing published multi-stressor studies, and 2) examining 303(d) listed impairments linked to biological impairment as identified by jurisdiction regulatory agencies (the states within the watershed and the District of Columbia). Results identified geomorphology (i.e., physical habitat), salinity, and toxic contaminants as important for explaining variability in benthic community metrics in the literature review. Geomorphology (i.e., physical habitat and sediment), salinity, and nutrients were the most reported stressors in the jurisdictional impairment analysis. Salinity is likely a major stressor in urban and mining settings, whereas geomorphology was commonly reported in agricultural settings. Toxic contaminants, such as pesticides, were rarely measured; more research is needed to quantify the extent of their effects in the region. Flow alteration was also highlighted as an important urban stressor in the literature review but was rarely measured in the literature or reported by jurisdictions as a cause of impairment. These results can be used to prioritize stressor monitoring by managers, and to improve stressor identification methods for identifying causes of biological impairment.

","language":"English","publisher":"Springer","doi":"10.1007/s00267-022-01723-7","usgsCitation":"Fanelli, R., Cashman, M.J., and Porter, A.J., 2022, Identifying key stressors driving biological impairment in freshwater streams in the Chesapeake Bay watershed, USA: Environmental Management, v. 70, p. 926-949, https://doi.org/10.1007/s00267-022-01723-7.","productDescription":"24 p.","startPage":"926","endPage":"949","ipdsId":"IP-138853","costCenters":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":446195,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s00267-022-01723-7","text":"Publisher Index Page"},{"id":435662,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9DHJSLF","text":"USGS data release","linkHelpText":"Literature review results and regulatory summaries of freshwater 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Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":856424,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cashman, Matthew J. 0000-0002-6635-4309","orcid":"https://orcid.org/0000-0002-6635-4309","contributorId":203315,"corporation":false,"usgs":true,"family":"Cashman","given":"Matthew","middleInitial":"J.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":856425,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Porter, Aaron J. 0000-0002-0781-3309","orcid":"https://orcid.org/0000-0002-0781-3309","contributorId":239980,"corporation":false,"usgs":true,"family":"Porter","given":"Aaron","email":"","middleInitial":"J.","affiliations":[{"id":37759,"text":"VA/WV Water Science Center","active":true,"usgs":true}],"preferred":true,"id":856426,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70266449,"text":"70266449 - 2022 - Temporal variation in capture efficiency underrepresents spring out-migrating Bull Trout in a trap-and-haul program","interactions":[],"lastModifiedDate":"2025-05-07T15:54:50.252734","indexId":"70266449","displayToPublicDate":"2022-10-07T00:00:00","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":"Temporal variation in capture efficiency underrepresents spring out-migrating Bull Trout in a trap-and-haul program","docAbstract":"

Trap-and-haul programs can maintain connection among habitats for migratory salmonids in fragmented systems. To conserve diversity within and among life history strategies, downstream trap and transport of juvenile salmonids could ideally mimic the natural, underlying out-migration dynamics of the population. A two-way trap-and-haul program is implemented in the lower Clark Fork River, Montana, to conserve adfluvial Bull Trout Salvelinus confluentus. We used PIT technology to assess whether downstream trapping efforts are effectively capturing variation in the out-migration dynamics of juvenile Bull Trout in Graves Creek, a key spawning and rearing tributary in the system. We tagged 821 juvenile Bull Trout in Graves Creek and used these tagged Bull Trout in conjunction with stationary PIT antennas to monitor out-migration and evaluate efficiency of the downstream trapping program. Capture efficiency in Graves Creek varied substantially from autumn to spring, with 89–96% of autumn out-migrating Bull Trout captured and 5–10% of spring out-migrating Bull Trout captured. Overall, we found that Bull Trout transported during the autumn out-migration periods generally reflect the natural out-migration dynamics of the population; however, Bull Trout that out-migrate in the spring are currently underrepresented in the downstream transport program. By understanding the underlying out-migration dynamics of the Bull Trout population in Graves Creek, management of the downstream trapping efforts can focus on minimizing potential selection for or against out-migrants based on timing and age at out-migration. Minimizing selection will conserve variation within the adfluvial life history strategy and therefore maximize resilience of the adfluvial Bull Trout populations.

","language":"English","publisher":"Wiley","doi":"10.1002/nafm.10817","usgsCitation":"Lewis, M., Guy, C.S., Oldenburg, E., and McMahon, T., 2022, Temporal variation in capture efficiency underrepresents spring out-migrating Bull Trout in a trap-and-haul program: North American Journal of Fisheries Management, v. 42, no. 5, p. 1237-1249, https://doi.org/10.1002/nafm.10817.","productDescription":"13 p.","startPage":"1237","endPage":"1249","ipdsId":"IP-139824","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":485511,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho, Montana","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -116.33181112337759,\n 48.716602752324974\n ],\n [\n -116.33181112337759,\n 48.106842812139405\n ],\n [\n -115.54832319686268,\n 48.106842812139405\n ],\n [\n -115.54832319686268,\n 48.716602752324974\n ],\n [\n -116.33181112337759,\n 48.716602752324974\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"42","issue":"5","noUsgsAuthors":false,"publicationDate":"2022-09-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Lewis, Madeline C.","contributorId":354619,"corporation":false,"usgs":false,"family":"Lewis","given":"Madeline C.","affiliations":[{"id":36555,"text":"Montana State University","active":true,"usgs":false}],"preferred":false,"id":936002,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Guy, Christopher S. 0000-0002-9936-4781 cguy@usgs.gov","orcid":"https://orcid.org/0000-0002-9936-4781","contributorId":2876,"corporation":false,"usgs":true,"family":"Guy","given":"Christopher","email":"cguy@usgs.gov","middleInitial":"S.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":5062,"text":"Office of the Chief Scientist for Ecosystems","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":936003,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Oldenburg, Eric W.","contributorId":354620,"corporation":false,"usgs":false,"family":"Oldenburg","given":"Eric W.","affiliations":[{"id":84641,"text":"Noxon Natural Resources Office","active":true,"usgs":false}],"preferred":false,"id":936004,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McMahon, Thomas E.","contributorId":354621,"corporation":false,"usgs":false,"family":"McMahon","given":"Thomas E.","affiliations":[{"id":36555,"text":"Montana State University","active":true,"usgs":false}],"preferred":false,"id":936005,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70255211,"text":"70255211 - 2022 - Industrial energy development decouples ungulate migration from the green wave","interactions":[],"lastModifiedDate":"2024-06-13T16:04:59.632829","indexId":"70255211","displayToPublicDate":"2022-10-06T10:58:02","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":6505,"text":"Nature Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Industrial energy development decouples ungulate migration from the green wave","docAbstract":"

The ability to freely move across the landscape to track the emergence of nutritious spring green-up (termed ‘green-wave surfing’) is key to the foraging strategy of migratory ungulates. Across the vast landscapes traversed by many migratory herds, habitats are being altered by development with unknown consequences for surfing. Using a unique long-term tracking dataset, we found that when energy development occurs within mule deer (Odocoileus hemionus) migration corridors, migrating animals become decoupled from the green wave. During the early phases of a coalbed natural gas development, deer synchronized their movements with peak green-up. But faced with increasing disturbance as development expanded, deer altered their movements by holding up at the edge of the gas field and letting the green wave pass them by. Development often modified only a small portion of the migration corridor but had far-reaching effects on behaviour before and after migrating deer encountered it, thus reducing surfing along the entire route by 38.65% over the 14-year study period. Our study suggests that industrial development within migratory corridors can change the behaviour of migrating ungulates and diminish the benefits of migration. Such disruptions to migratory behaviour present a common mechanism whereby corridors become unprofitable and could ultimately be lost on highly developed landscapes.

","language":"English","publisher":"Nature","doi":"10.1038/s41559-022-01887-9","collaboration":"Western EcoSystems, INC","usgsCitation":"Aikens, E.O., Wyckoff, T., Sawyer, H., and Kauffman, M., 2022, Industrial energy development decouples ungulate migration from the green wave: Nature Ecology and Evolution, v. 6, p. 1733-1741, https://doi.org/10.1038/s41559-022-01887-9.","productDescription":"9 p.","startPage":"1733","endPage":"1741","ipdsId":"IP-136329","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":430147,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wyoming","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -108.50057122965278,\n 41.908308585415085\n ],\n [\n -108.50057122965278,\n 40.99058578879266\n ],\n [\n -107.30804228444518,\n 40.99058578879266\n ],\n [\n -107.30804228444518,\n 41.908308585415085\n ],\n [\n -108.50057122965278,\n 41.908308585415085\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"6","noUsgsAuthors":false,"publicationDate":"2022-10-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Aikens, Ellen O.","contributorId":272241,"corporation":false,"usgs":false,"family":"Aikens","given":"Ellen","email":"","middleInitial":"O.","affiliations":[{"id":40829,"text":"uwy","active":true,"usgs":false}],"preferred":false,"id":903738,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wyckoff, Teal B.","contributorId":339010,"corporation":false,"usgs":false,"family":"Wyckoff","given":"Teal B.","affiliations":[{"id":36628,"text":"University of Wyoming","active":true,"usgs":false}],"preferred":false,"id":903739,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sawyer, Hall","contributorId":287880,"corporation":false,"usgs":false,"family":"Sawyer","given":"Hall","affiliations":[{"id":61660,"text":"Western Ecosystems Technology, Inc., Laramie, WY","active":true,"usgs":false}],"preferred":false,"id":903740,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kauffman, Matthew J. 0000-0003-0127-3900","orcid":"https://orcid.org/0000-0003-0127-3900","contributorId":202921,"corporation":false,"usgs":true,"family":"Kauffman","given":"Matthew","middleInitial":"J.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":903741,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70237280,"text":"70237280 - 2022 - Immunogenicity, safety, and anti-viral efficacy of a subunit SARS-CoV-2 vaccine candidate in captive black-footed ferrets (Mustela nigripes) and their susceptibility to viral challenge","interactions":[],"lastModifiedDate":"2022-10-17T16:41:14.433649","indexId":"70237280","displayToPublicDate":"2022-10-06T09:33:35","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3700,"text":"Viruses","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Immunogenicity, safety, and anti-viral efficacy of a subunit SARS-CoV-2 vaccine candidate in captive black-footed ferrets (Mustela nigripes) and their susceptibility to viral challenge","title":"Immunogenicity, safety, and anti-viral efficacy of a subunit SARS-CoV-2 vaccine candidate in captive black-footed ferrets (Mustela nigripes) and their susceptibility to viral challenge","docAbstract":"

A preliminary vaccination trial against the emergent pathogen, SARS-CoV-2, was completed in captive black-footed ferrets (Mustela nigripes; BFF) to assess safety, immunogenicity, and anti-viral efficacy. Vaccination and boosting of 15 BFF with purified SARS-CoV-2 S1 subunit protein produced a nearly 150-fold increase in mean antibody titers compared to pre-vaccination titers. Serum antibody responses were highest in young animals, but in all vaccinees, antibody response declined rapidly. Anti-viral activity from vaccinated and unvaccinated BFF was determined in vitro, as well as in vivo with a passive serum transfer study in mice. Transgenic mice that received BFF serum transfers and were subsequently challenged with SARS-CoV-2 had lung viral loads that negatively correlated (p < 0.05) with the BFF serum titer received. Lastly, an experimental challenge study in a small group of BFF was completed to test susceptibility to SARS-CoV-2. Despite viral replication and shedding in the upper respiratory tract for up to 7 days post-challenge, no clinical disease was observed in either vaccinated or naive animals. The lack of morbidity or mortality observed indicates SARS-CoV-2 is unlikely to affect wild BFF populations, but infected captive animals pose a potential risk, albeit low, for humans and other animals.

","language":"English","publisher":"MDPI","doi":"10.3390/v14102188","usgsCitation":"Leon, A.E., Garelle, D., Hartwig, A., Falendysz, E., Ip, H., Lankton, J.S., Tretten, T., Spraker, T., Bowen, R., and Rocke, T.E., 2022, Immunogenicity, safety, and anti-viral efficacy of a subunit SARS-CoV-2 vaccine candidate in captive black-footed ferrets (Mustela nigripes) and their susceptibility to viral challenge: Viruses, v. 14, no. 10, 2188, 15 p., https://doi.org/10.3390/v14102188.","productDescription":"2188, 15 p.","ipdsId":"IP-144258","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":446199,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/v14102188","text":"Publisher Index Page"},{"id":435663,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9GZEXN9","text":"USGS data release","linkHelpText":"Viral loads, histology, and adverse events in transgenic mice after passive transfer of serum from black-footed ferrets (Mustela nigripes) used to assess the anti-viral efficacy of a subunit SARS-CoV-2 vaccine candidate"},{"id":408037,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"14","issue":"10","noUsgsAuthors":false,"publicationDate":"2022-10-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Leon, Ariel Elizabeth 0000-0001-9246-4619","orcid":"https://orcid.org/0000-0001-9246-4619","contributorId":247573,"corporation":false,"usgs":true,"family":"Leon","given":"Ariel","email":"","middleInitial":"Elizabeth","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":853959,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Garelle, Della","contributorId":297372,"corporation":false,"usgs":false,"family":"Garelle","given":"Della","email":"","affiliations":[{"id":64382,"text":"US Fish and Wildlife Service, National Black-Footed Ferret Conservation Center, P.O. Box 190, Wellington, Colorado","active":true,"usgs":false}],"preferred":false,"id":853960,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hartwig, Airn","contributorId":297373,"corporation":false,"usgs":false,"family":"Hartwig","given":"Airn","email":"","affiliations":[{"id":64383,"text":"Colorado State University, Department of Biomedical Sciences, 3107 Rampart Road, Fort Collins, Colorado","active":true,"usgs":false}],"preferred":false,"id":853961,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Falendysz, Elizabeth 0000-0003-2895-8918 efalendysz@usgs.gov","orcid":"https://orcid.org/0000-0003-2895-8918","contributorId":127751,"corporation":false,"usgs":true,"family":"Falendysz","given":"Elizabeth","email":"efalendysz@usgs.gov","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":853962,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ip, Hon S. 0000-0003-4844-7533","orcid":"https://orcid.org/0000-0003-4844-7533","contributorId":126815,"corporation":false,"usgs":true,"family":"Ip","given":"Hon S.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":853963,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lankton, Julia S. 0000-0002-6843-4388 jlankton@usgs.gov","orcid":"https://orcid.org/0000-0002-6843-4388","contributorId":5888,"corporation":false,"usgs":true,"family":"Lankton","given":"Julia","email":"jlankton@usgs.gov","middleInitial":"S.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":853964,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Tretten, Tyler","contributorId":297374,"corporation":false,"usgs":false,"family":"Tretten","given":"Tyler","affiliations":[{"id":64384,"text":"US Fish and Wildlife Service, National Black-Footed Ferret Conservation Center","active":true,"usgs":false}],"preferred":false,"id":853965,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Spraker, Terry","contributorId":297375,"corporation":false,"usgs":false,"family":"Spraker","given":"Terry","affiliations":[{"id":64385,"text":"Colorado State University, Department of Microbiology, Immunology and Pathology, 2450 Gillette Dr, Fort Collins, CO 80526","active":true,"usgs":false}],"preferred":false,"id":853966,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Bowen, Richard","contributorId":297376,"corporation":false,"usgs":false,"family":"Bowen","given":"Richard","affiliations":[{"id":64386,"text":"Colorado State University, Department of Biomedical Sciences, 3107 Rampart Road, Fort Collins, Colorado 80523 USA","active":true,"usgs":false}],"preferred":false,"id":853967,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Rocke, Tonie E. 0000-0003-3933-1563 trocke@usgs.gov","orcid":"https://orcid.org/0000-0003-3933-1563","contributorId":2665,"corporation":false,"usgs":true,"family":"Rocke","given":"Tonie","email":"trocke@usgs.gov","middleInitial":"E.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":853968,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70237277,"text":"70237277 - 2022 - Absolute accuracy assessment of lidar point cloud using amorphous objects","interactions":[],"lastModifiedDate":"2022-10-06T14:30:04.492861","indexId":"70237277","displayToPublicDate":"2022-10-06T09:26:08","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3250,"text":"Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Absolute accuracy assessment of lidar point cloud using amorphous objects","docAbstract":"

The accuracy assessment of airborne lidar point cloud typically estimates vertical accuracy by computing RMSEz (root mean square error of the z coordinate) from ground check points (GCPs). Due to the low point density of the airborne lidar point cloud, there is often not enough accurate semantic context to find an accurate conjugate point. To advance the accuracy assessment in full three-dimensional (3D) context, geometric features, such as the three-plane intersection point or two-line intersection point, are often used. Although the point density is still low, geometric features are mathematically modeled from many points. Thus, geometric features provide a robust determination of the intersection point, and the point is considered as a GCP. When no regular built objects are available, we describe the process of utilizing features of irregular shape called amorphous natural objects, such as a tree or a rock. When scanned to a high-density point cloud, an amorphous natural object can be used as ground truth reference data to estimate 3D georeferencing errors of the airborne lidar point cloud. The algorithm to estimate 3D accuracy is the optimization that minimizes the sum of the distance between the airborne lidar points to the ground scanned data. The search volume partitioning was the most important procedure to improve the computational efficiency. We also performed an extensive study to address the external uncertainty associated with the amorphous object method. We describe an accuracy assessment using amorphous objects (108 trees) spread over the project area. The accuracy results for ∆x, ∆y, and ∆z obtained using the amorphous object method were 3.1 cm, 3.6 cm, and 1.7 cm RMSE, along with a mean error of 0.1 cm, 0.1 cm, and 4.5 cm, respectively, satisfying the accuracy requirement of U.S. Geological Survey lidar base specification. This approach shows strong promise as an alternative to geometric feature methods when artificial targets are scarce. The relative convenience and advantages of using amorphous targets, along with its good performance shown here, make this amorphous object method a practical way to perform 3D accuracy assessment.

","language":"English","publisher":"MDPI","doi":"10.3390/rs14194767","usgsCitation":"Kim, M., Stoker, J.M., Irwin, J., Danielson, J.J., and Park, S., 2022, Absolute accuracy assessment of lidar point cloud using amorphous objects: Remote Sensing, v. 14, no. 19, 4767, 18 p., https://doi.org/10.3390/rs14194767.","productDescription":"4767, 18 p.","ipdsId":"IP-145321","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"links":[{"id":446201,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs14194767","text":"Publisher Index Page"},{"id":408035,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"14","issue":"19","noUsgsAuthors":false,"publicationDate":"2022-09-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Kim, Minsu 0000-0003-4472-0926","orcid":"https://orcid.org/0000-0003-4472-0926","contributorId":297371,"corporation":false,"usgs":false,"family":"Kim","given":"Minsu","affiliations":[{"id":54490,"text":"KBR, Inc., under contract to USGS","active":true,"usgs":false}],"preferred":false,"id":853945,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stoker, Jason M. 0000-0003-2455-0931 jstoker@usgs.gov","orcid":"https://orcid.org/0000-0003-2455-0931","contributorId":3021,"corporation":false,"usgs":true,"family":"Stoker","given":"Jason","email":"jstoker@usgs.gov","middleInitial":"M.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"preferred":true,"id":853946,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Irwin, Jeffrey 0000-0001-5828-0787 jrirwin@usgs.gov","orcid":"https://orcid.org/0000-0001-5828-0787","contributorId":222485,"corporation":false,"usgs":true,"family":"Irwin","given":"Jeffrey","email":"jrirwin@usgs.gov","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":853947,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Danielson, Jeffrey J. 0000-0003-0907-034X daniels@usgs.gov","orcid":"https://orcid.org/0000-0003-0907-034X","contributorId":3996,"corporation":false,"usgs":true,"family":"Danielson","given":"Jeffrey","email":"daniels@usgs.gov","middleInitial":"J.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":853948,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Park, Seonkyung 0000-0003-3203-1998 seonkyungpark@contractor.usgs.gov","orcid":"https://orcid.org/0000-0003-3203-1998","contributorId":222488,"corporation":false,"usgs":false,"family":"Park","given":"Seonkyung","email":"seonkyungpark@contractor.usgs.gov","affiliations":[{"id":40547,"text":"United Support Services, Contractor to the USGS Earth Resources Observation and Science (EROS) Center","active":true,"usgs":false}],"preferred":false,"id":853949,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70237290,"text":"70237290 - 2022 - Sediment source fingerprinting as an aid to large-scale landscape conservation and restoration: A review for the Mississippi River Basin","interactions":[],"lastModifiedDate":"2022-10-06T14:25:24.776873","indexId":"70237290","displayToPublicDate":"2022-10-06T09:19:21","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2258,"text":"Journal of Environmental Management","active":true,"publicationSubtype":{"id":10}},"title":"Sediment source fingerprinting as an aid to large-scale landscape conservation and restoration: A review for the Mississippi River Basin","docAbstract":"Reliable quantitative information on sediment sources to rivers is critical to mitigate contamination and target conservation and restoration actions. However, the determination of the relative importance of sediment sources is complicated at the scale of large river basins by immense variability in erosional processes and sediment sources over space and time, heterogeneity in sediment transport and deposition, and a paucity of sediment monitoring data. Sediment source fingerprinting is an increasingly adopted field-based technique that identifies the nature and relative source contribution of sediment transported in waterways. Notably, sediment source fingerprinting provides information that is independent of other field, modeling, or remotely sensed techniques. However, the diversity in sediment fingerprinting sampling, analytical, and interpretive methods has been recognized as a problem in terms of developing standardized procedures for its application at the scale of large river basins. Accordingly, this review focuses on established sediment source fingerprinting studies conducted within the Mississippi River Basin (MRB), summarizes unique information provided by sediment source fingerprinting that is distinct from traditional monitoring techniques, evaluates consistency and reliability of methodological approaches among MRB studies, and provides prospects for the use of the sediment source fingerprinting technique as an aid to large-scale landscape conservation and restoration under current management frameworks. Most established MRB studies got creditable fingerprinting results and considered near-channel sources as the dominant sediment sources in most cases, while the comparability of their results suffers from a lack of standardization in procedural steps. Findings from MRB studies demonstrate that sediment source fingerprinting is a highly valuable and reliable sediment source assessment approach to assist land and water resource management under current management frameworks, but efforts are still needed to make this technique ready to be used in a more predominant way in large-scale landscape conservation and restoration efforts. We summarized research needs and suggested the best fingerprinting practices for management purposes with the aim of ensuring that this technique is as robust and reliable as it moves forward.","language":"English","publisher":"Elsevier","doi":"10.1016/j.jenvman.2022.116260","usgsCitation":"Xu, Z., Belmont, P., Brahney, J., and Gellis, A.C., 2022, Sediment source fingerprinting as an aid to large-scale landscape conservation and restoration: A review for the Mississippi River Basin: Journal of Environmental Management, v. 324, 116260, 20 p., https://doi.org/10.1016/j.jenvman.2022.116260.","productDescription":"116260, 20 p.","ipdsId":"IP-141762","costCenters":[{"id":41514,"text":"Maryland-Delaware-District of Columbia Water Science Center","active":true,"usgs":true}],"links":[{"id":446204,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jenvman.2022.116260","text":"Publisher Index Page"},{"id":408033,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Mississippi River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -94.0869140625,\n 29.57345707301757\n ],\n [\n -89.7802734375,\n 28.729130483430154\n ],\n [\n -89.20898437499999,\n 29.34387539941801\n ],\n [\n -89.5166015625,\n 30.107117887092357\n ],\n [\n -89.384765625,\n 33.65120829920497\n ],\n [\n -82.8369140625,\n 34.77771580360469\n ],\n [\n -79.40917968749999,\n 36.59788913307022\n ],\n [\n -77.6953125,\n 42.391008609205045\n ],\n [\n -79.365234375,\n 42.4234565179383\n ],\n [\n -81.9580078125,\n 41.31082388091818\n ],\n [\n -87.099609375,\n 41.0130657870063\n ],\n [\n -87.62695312499999,\n 41.672911819602085\n ],\n [\n -88.2861328125,\n 43.229195113965005\n ],\n [\n -90.1318359375,\n 46.49839225859763\n ],\n [\n -92.021484375,\n 46.558860303117164\n ],\n [\n -93.8232421875,\n 47.54687159892238\n ],\n [\n -95.00976562499999,\n 47.54687159892238\n ],\n [\n -98.61328125,\n 47.100044694025215\n ],\n [\n -104.0185546875,\n 49.009050809382046\n ],\n [\n -115.00488281250001,\n 49.03786794532644\n ],\n [\n -114.60937499999999,\n 46.92025531537451\n ],\n [\n -114.521484375,\n 45.85941212790755\n ],\n [\n -112.8076171875,\n 44.62175409623324\n ],\n [\n -111.1376953125,\n 44.99588261816546\n ],\n [\n -109.2919921875,\n 44.715513732021336\n ],\n [\n -108.896484375,\n 42.65012181368022\n ],\n [\n -106.12792968749999,\n 40.88029480552824\n ],\n [\n -105.3369140625,\n 39.26628442213066\n ],\n [\n -105.29296874999999,\n 37.16031654673677\n ],\n [\n -105.29296874999999,\n 34.92197103616377\n ],\n [\n -103.0517578125,\n 34.23451236236987\n ],\n [\n -97.646484375,\n 33.46810795527896\n ],\n [\n -93.955078125,\n 31.353636941500987\n ],\n [\n -94.0869140625,\n 29.57345707301757\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"324","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Xu, Zhen","contributorId":297389,"corporation":false,"usgs":false,"family":"Xu","given":"Zhen","affiliations":[{"id":6682,"text":"Utah State University","active":true,"usgs":false}],"preferred":false,"id":853997,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Belmont, Patrick","contributorId":275033,"corporation":false,"usgs":false,"family":"Belmont","given":"Patrick","affiliations":[{"id":28050,"text":"USU","active":true,"usgs":false}],"preferred":false,"id":853998,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brahney, Janice","contributorId":269810,"corporation":false,"usgs":false,"family":"Brahney","given":"Janice","email":"","affiliations":[{"id":6682,"text":"Utah State University","active":true,"usgs":false}],"preferred":false,"id":853999,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gellis, Allen C. 0000-0002-3449-2889 agellis@usgs.gov","orcid":"https://orcid.org/0000-0002-3449-2889","contributorId":197684,"corporation":false,"usgs":true,"family":"Gellis","given":"Allen","email":"agellis@usgs.gov","middleInitial":"C.","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":true,"id":854000,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70237272,"text":"70237272 - 2022 - Simple statistical models can be sufficient for testing hypotheses with population time series data","interactions":[],"lastModifiedDate":"2022-10-06T14:10:39.16442","indexId":"70237272","displayToPublicDate":"2022-10-06T08:52:34","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Simple statistical models can be sufficient for testing hypotheses with population time series data","docAbstract":"

Time-series data offer wide-ranging opportunities to test hypotheses about the physical and biological factors that influence species abundances. Although sophisticated models have been developed and applied to analyze abundance time series, they require information about species detectability that is often unavailable. We propose that in many cases, simpler models are adequate for testing hypotheses. We consider three relatively simple regression models for time series, using simulated and empirical (fish and mammal) datasets. Model A is a conventional generalized linear model of abundance, model B adds a temporal autoregressive term, and model C uses an estimate of population growth rate as a response variable, with the option of including a term for density dependence. All models can be fit using Bayesian and non-Bayesian methods. Simulation results demonstrated that model C tended to have greater support for long-lived, lower-fecundity organisms (K life-history strategists), while model A, the simplest, tended to be supported for shorter-lived, high-fecundity organisms (r life-history strategists). Analysis of real-world fish and mammal datasets found that models A, B, and C each enjoyed support for at least some species, but sometimes yielded different insights. In particular, model C indicated effects of predictor variables that were not evident in analyses with models A and B. Bayesian and frequentist models yielded similar parameter estimates and performance. We conclude that relatively simple models are useful for testing hypotheses about the factors that influence abundance in time-series data, and can be appropriate choices for datasets that lack the information needed to fit more complicated models. When feasible, we advise fitting datasets with multiple models because they can provide complementary information.

","language":"English","publisher":"Wiley","doi":"10.1002/ece3.9339","usgsCitation":"Wenger, S., Stowe, E.S., Gido, K.B., Freeman, M., Kanno, Y., Franssen, N.R., Olden, J., Poff, N.L., Walters, A.W., Bumpers, P.M., Mims, M.C., Hooten, M.B., and Lu, X., 2022, Simple statistical models can be sufficient for testing hypotheses with population time series data: Ecology and Evolution, v. 12, no. 9, e9339, 13 p., https://doi.org/10.1002/ece3.9339.","productDescription":"e9339, 13 p.","ipdsId":"IP-133439","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":446206,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1002/ece3.9339","text":"External Repository"},{"id":408029,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"12","issue":"9","noUsgsAuthors":false,"publicationDate":"2022-09-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Wenger, Seth J.","contributorId":177838,"corporation":false,"usgs":false,"family":"Wenger","given":"Seth J.","affiliations":[],"preferred":false,"id":853925,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"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":853926,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gido, Keith B.","contributorId":198487,"corporation":false,"usgs":false,"family":"Gido","given":"Keith","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":853927,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"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":853928,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"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":853929,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"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":853930,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Olden, Julian 0000-0003-2143-1187","orcid":"https://orcid.org/0000-0003-2143-1187","contributorId":296007,"corporation":false,"usgs":false,"family":"Olden","given":"Julian","email":"","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":853931,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"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":853932,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"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":853933,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Bumpers, Phillip M.","contributorId":203871,"corporation":false,"usgs":false,"family":"Bumpers","given":"Phillip","email":"","middleInitial":"M.","affiliations":[{"id":12697,"text":"University of Georgia","active":true,"usgs":false}],"preferred":false,"id":853934,"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":853935,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Hooten, Mevin B. 0000-0002-1614-723X","orcid":"https://orcid.org/0000-0002-1614-723X","contributorId":292295,"corporation":false,"usgs":false,"family":"Hooten","given":"Mevin","email":"","middleInitial":"B.","affiliations":[{"id":12430,"text":"University of Texas at Austin","active":true,"usgs":false}],"preferred":false,"id":853936,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Lu, Xinyi","contributorId":279368,"corporation":false,"usgs":false,"family":"Lu","given":"Xinyi","affiliations":[{"id":13606,"text":"CSU","active":true,"usgs":false}],"preferred":false,"id":853937,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}} ,{"id":70237276,"text":"70237276 - 2022 - Range-wide population projections for Northern Red-Bellied Cooters (Pseudemys rubriventris)","interactions":[],"lastModifiedDate":"2022-10-06T13:47:45.013432","indexId":"70237276","displayToPublicDate":"2022-10-06T08:35:56","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2334,"text":"Journal of Herpetology","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Range-wide population projections for Northern Red-Bellied Cooters (Pseudemys rubriventris)","title":"Range-wide population projections for Northern Red-Bellied Cooters (Pseudemys rubriventris)","docAbstract":"

Northern Red-Bellied Cooters (Pseudemys rubriventris) have a disjunct distribution with a relictual population in southeastern Massachusetts and a larger range across the mid-Atlantic United States. The relictual population is currently listed with protections under the U.S. Endangered Species Act but the status of the population in the remainder of the species' range has not been assessed, and there is concern that it may be at risk of extinction without protection. The U.S. Fish and Wildlife Service requires scientific information of the species' status to inform conservation decisions. There is little empirical information available from P. rubriventris populations and, furthermore, the majority of what exists comes from the disjunct northern subpopulation. To fill data gaps in the species' life history and reduce geographic bias, we supplement available data from P. rubriventris with demographic rate estimates from other Pseudemys species to parameterize an age-structured population projection model. Our estimate of mean population growth rate was 0.987 (0.92–1.04), indicating that P. rubriventris populations may be in decline. However, there was considerable uncertainty in our results, with 35% of projections resulting in stable or increasing populations. Additional uncertainty about parameter values, geographic variation, and current threats limit the assessment. We discuss the merits and limitations of our population projection modeling (PPM) approach where other analytical methods are precluded by lack of available data.

","language":"English","publisher":"Society for the Study of Amphibians and Reptiles","doi":"10.1670/21-065","usgsCitation":"Fleming, J.E., Moore, J.F., Waddle, H., Martin, J., and Campbell Grant, E.H., 2022, Range-wide population projections for Northern Red-Bellied Cooters (Pseudemys rubriventris): Journal of Herpetology, v. 56, no. 3, p. 362-369, https://doi.org/10.1670/21-065.","productDescription":"8 p.","startPage":"362","endPage":"369","ipdsId":"IP-130062","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":408028,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Maryland, Massachusetts, New Jersey, North Carolina, Pennsylvania, Virginia, West Virginia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -77.332763671875,\n 34.551811369170494\n ],\n [\n -76.607666015625,\n 34.6241677899049\n ],\n [\n -76.201171875,\n 34.831841149828655\n ],\n [\n -75.399169921875,\n 35.23664622093195\n ],\n [\n -75.322265625,\n 35.47856499535729\n ],\n [\n -75.377197265625,\n 35.84453450421662\n ],\n [\n -75.83862304687499,\n 37.046408899699564\n ],\n [\n -74.970703125,\n 38.26406296833961\n ],\n [\n -74.981689453125,\n 38.65119833229951\n ],\n [\n -74.827880859375,\n 38.8824811975508\n ],\n [\n -74.168701171875,\n 39.58029027440865\n ],\n [\n -73.80615234375,\n 40.33817045213394\n ],\n [\n -74.1357421875,\n 40.49709237269567\n ],\n [\n -77.750244140625,\n 40.75557964275589\n ],\n [\n -79.332275390625,\n 39.715638134796336\n ],\n [\n -79.595947265625,\n 38.59970036588819\n ],\n [\n -78.134765625,\n 35.71975793933433\n ],\n [\n -77.332763671875,\n 34.551811369170494\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -71.202392578125,\n 41.72213058512578\n ],\n [\n -70.499267578125,\n 41.72213058512578\n ],\n [\n -70.499267578125,\n 42.27730877423709\n ],\n [\n -71.202392578125,\n 42.27730877423709\n ],\n [\n -71.202392578125,\n 41.72213058512578\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"56","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Fleming, Jillian Elizabeth 0000-0003-2570-914X","orcid":"https://orcid.org/0000-0003-2570-914X","contributorId":238931,"corporation":false,"usgs":true,"family":"Fleming","given":"Jillian","email":"","middleInitial":"Elizabeth","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":853940,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Moore, Jennifer F.","contributorId":189122,"corporation":false,"usgs":false,"family":"Moore","given":"Jennifer","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":853941,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Waddle, Hardin 0000-0003-1940-2133","orcid":"https://orcid.org/0000-0003-1940-2133","contributorId":206866,"corporation":false,"usgs":true,"family":"Waddle","given":"Hardin","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":853942,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Martin, Julien 0000-0002-7375-129X","orcid":"https://orcid.org/0000-0002-7375-129X","contributorId":216734,"corporation":false,"usgs":true,"family":"Martin","given":"Julien","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":853943,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Campbell Grant, Evan H. 0000-0003-4401-6496 ehgrant@usgs.gov","orcid":"https://orcid.org/0000-0003-4401-6496","contributorId":150443,"corporation":false,"usgs":true,"family":"Campbell Grant","given":"Evan","email":"ehgrant@usgs.gov","middleInitial":"H.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":853944,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70238817,"text":"70238817 - 2022 - Post-fire seed dispersal of a wind-dispersed shrub declined with distance to seed source, yet had high levels of unexplained variation","interactions":[],"lastModifiedDate":"2022-12-13T13:40:55.160716","indexId":"70238817","displayToPublicDate":"2022-10-06T07:10:53","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5538,"text":"AoB PLANTS","active":true,"publicationSubtype":{"id":10}},"title":"Post-fire seed dispersal of a wind-dispersed shrub declined with distance to seed source, yet had high levels of unexplained variation","docAbstract":"

Plant-population recovery across large disturbance areas is often seed-limited. An understanding of seed dispersal patterns is fundamental for determining natural-regeneration potential. However, forecasting seed dispersal rates across heterogeneous landscapes remains a challenge. Our objectives were to determine (i) the landscape patterning of post-disturbance seed dispersal, and underlying sources of variation and the scale at which they operate, and (ii) how the natural seed dispersal patterns relate to a seed augmentation strategy. Vertical seed trapping experiments were replicated across 2 years and five burned and/or managed landscapes in sagebrush steppe. Multi-scale sampling and hierarchical Bayesian models were used to determine the scale of spatial variation in seed dispersal. We then integrated an empirical and mechanistic dispersal kernel for wind-dispersed species to project rates of seed dispersal and compared natural seed arrival to typical post-fire aerial seeding rates. Seeds were captured across the range of tested dispersal distances, up to a maximum distance of 26 m from seed-source plants, although dispersal to the furthest traps was variable. Seed dispersal was better explained by transect heterogeneity than by patch or site heterogeneity (transects were nested within patch within site). The number of seeds captured varied from a modelled mean of ~13 m−2 adjacent to patches of seed-producing plants, to nearly none at 10 m from patches, standardized over a 49-day period. Maximum seed dispersal distances on average were estimated to be 16 m according to a novel modelling approach using a ‘latent’ variable for dispersal distance based on seed trapping heights. Surprisingly, statistical representation of wind did not improve model fit and seed rain was not related to the large variation in total available seed of adjacent patches. The models predicted severe seed limitations were likely on typical burned areas, especially compared to the mean 95–250 seeds per m2 that previous literature suggested were required to generate sagebrush recovery. More broadly, our Bayesian data fusion approach could be applied to other cases that require quantitative estimates of long-distance seed dispersal across heterogeneous landscapes.

","language":"English","publisher":"Oxford Academic","doi":"10.1093/aobpla/plac045","usgsCitation":"Applestein, C., Caughlin, T., and Germino, M., 2022, Post-fire seed dispersal of a wind-dispersed shrub declined with distance to seed source, yet had high levels of unexplained variation: AoB PLANTS, v. 14, no. 6, plac045, 13 p., https://doi.org/10.1093/aobpla/plac045.","productDescription":"plac045, 13 p.","ipdsId":"IP-127630","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":446211,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/aobpla/plac045","text":"Publisher Index Page"},{"id":410359,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -117.2526670227266,\n 45.4\n ],\n [\n -117.2526670227266,\n 43.21761290801206\n ],\n [\n -113.74569616023115,\n 43.21761290801206\n ],\n [\n -113.74569616023115,\n 45.4\n ],\n [\n -117.2526670227266,\n 45.4\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"14","issue":"6","noUsgsAuthors":false,"publicationDate":"2022-10-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Applestein, Cara 0000-0002-7923-8526","orcid":"https://orcid.org/0000-0002-7923-8526","contributorId":218003,"corporation":false,"usgs":true,"family":"Applestein","given":"Cara","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":858780,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Caughlin, Trevor 0000-0001-6752-2055","orcid":"https://orcid.org/0000-0001-6752-2055","contributorId":256964,"corporation":false,"usgs":false,"family":"Caughlin","given":"Trevor","email":"","affiliations":[{"id":16201,"text":"Boise State University","active":true,"usgs":false}],"preferred":false,"id":858781,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Germino, Matthew J. 0000-0001-6326-7579","orcid":"https://orcid.org/0000-0001-6326-7579","contributorId":251901,"corporation":false,"usgs":true,"family":"Germino","given":"Matthew J.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":858782,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70240117,"text":"70240117 - 2022 - Antecedent climatic conditions spanning several years influence multiple land-surface phenology events in semi-arid environments","interactions":[],"lastModifiedDate":"2023-01-27T13:09:43.480884","indexId":"70240117","displayToPublicDate":"2022-10-06T07:02:49","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3910,"text":"Frontiers in Ecology and Evolution","onlineIssn":"2296-701X","active":true,"publicationSubtype":{"id":10}},"title":"Antecedent climatic conditions spanning several years influence multiple land-surface phenology events in semi-arid environments","docAbstract":"

Ecological processes are complex, often exhibiting non-linear, interactive, or hierarchical relationships. Furthermore, models identifying drivers of phenology are constrained by uncertainty regarding predictors, interactions across scales, and legacy impacts of prior climate conditions. Nonetheless, measuring and modeling ecosystem processes such as phenology remains critical for management of ecological systems and the social systems they support. We used random forest models to assess which combination of climate, location, edaphic, vegetation composition, and disturbance variables best predict several phenological responses in three dominant land cover types in the U.S. Northwestern Great Plains (NWP). We derived phenological measures from the 25-year series of AVHRR satellite data and characterized climatic predictors (i.e., multiple moisture and/or temperature based variables) over seasonal and annual timeframes within the current year and up to 4 years prior. We found that antecedent conditions, from seasons to years before the current, were strongly associated with phenological measures, apparently mediating the responses of communities to current-year conditions. For example, at least one measure of antecedent-moisture availability [precipitation or vapor pressure deficit (VPD)] over multiple years was a key predictor of all productivity measures. Variables including longer-term lags or prior year sums, such as multi-year-cumulative moisture conditions of maximum VPD, were top predictors for start of season. Productivity measures were also associated with contextual variables such as soil characteristics and vegetation composition. Phenology is a key process that profoundly affects organism-environment relationships, spatio-temporal patterns in ecosystem structure and function, and other ecosystem dynamics. Phenology, however, is complex, and is mediated by lagged effects, interactions, and a diversity of potential drivers; nonetheless, the incorporation of antecedent conditions and contextual variables can improve models of phenology.

","language":"English","publisher":"Frontiers","doi":"10.3389/fevo.2022.1007010","usgsCitation":"Wood, D.J., Stoy, P.C., Powell, S., and Beever, E.A., 2022, Antecedent climatic conditions spanning several years influence multiple land-surface phenology events in semi-arid environments: Frontiers in Ecology and Evolution, v. 10, 1007010, 16 p., https://doi.org/10.3389/fevo.2022.1007010.","productDescription":"1007010, 16 p.","ipdsId":"IP-143541","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":446214,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fevo.2022.1007010","text":"Publisher Index Page"},{"id":435664,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9Z47EWL","text":"USGS data release","linkHelpText":"Model performance and output variables for phenological events across land cover types in the Northwestern Plains, 1989-2014"},{"id":412401,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho, Montana, Nebraska, North Dakota, South Dakota, Wyoming","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -116.36446840224696,\n 49.041849451282246\n ],\n [\n -116.36446840224696,\n 42.4957242202581\n ],\n [\n -99.3648518667362,\n 42.4957242202581\n ],\n [\n -99.3648518667362,\n 49.041849451282246\n ],\n [\n -116.36446840224696,\n 49.041849451282246\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"10","noUsgsAuthors":false,"publicationDate":"2022-10-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Wood, David J. A. 0000-0003-4315-5160 dwood@usgs.gov","orcid":"https://orcid.org/0000-0003-4315-5160","contributorId":177588,"corporation":false,"usgs":true,"family":"Wood","given":"David","email":"dwood@usgs.gov","middleInitial":"J. A.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":862633,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stoy, Paul C.","contributorId":204157,"corporation":false,"usgs":false,"family":"Stoy","given":"Paul","email":"","middleInitial":"C.","affiliations":[{"id":36555,"text":"Montana State University","active":true,"usgs":false}],"preferred":false,"id":862634,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Powell, Scott","contributorId":192347,"corporation":false,"usgs":false,"family":"Powell","given":"Scott","affiliations":[],"preferred":false,"id":862635,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Beever, Erik A. 0000-0002-9369-486X ebeever@usgs.gov","orcid":"https://orcid.org/0000-0002-9369-486X","contributorId":2934,"corporation":false,"usgs":true,"family":"Beever","given":"Erik","email":"ebeever@usgs.gov","middleInitial":"A.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":862636,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70237313,"text":"70237313 - 2022 - Nonlinear multidecadal trends in organic matter dynamics in Midwest reservoirs are a function of variable hydroclimate","interactions":[],"lastModifiedDate":"2022-11-16T17:11:50.804997","indexId":"70237313","displayToPublicDate":"2022-10-06T06:38:10","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2620,"text":"Limnology and Oceanography","active":true,"publicationSubtype":{"id":10}},"title":"Nonlinear multidecadal trends in organic matter dynamics in Midwest reservoirs are a function of variable hydroclimate","docAbstract":"

Dissolved organic matter (DOM) and particulate organic matter (POM) can influence biogeochemical processes in aquatic systems. An understanding, however, of the source, composition, and processes driving inland reservoir organic matter (OM) cycling at a regional scale over the long term is currently unexplored. Here, we quantify decadal patterns (> 20 yr) of DOM quantity and composition and POM in 40 reservoirs in the midcontinent United States. We built 184 Random Forest models to identify how the relative influence of watershed characteristics and limnological parameters on OM dynamics may vary over time and in synchrony with hydroclimatic anomalies. The reservoir OM quantity and composition varied nonmonotonically through time and in contrast to lake browning observed in the northern hemisphere. Reservoir DOM composition switched from humic and aromatic during wet summers to aliphatic, potentially autochthonous DOM during particularly prolonged dry summers in the mid-2000s. The shift in reservoir DOM quantity and composition could be attributed to the change in time-varying control of watershed and limnological factors mediated by the hydroclimatic conditions. Watershed control (e.g., percent crops) was predominant during wet summers, while the effect of reservoir morphology (e.g., maximum depth) and water quality parameters (e.g., Secchi depth, chlorophyll a) were evident during dry summers. Thus, future predictions of drier conditions may promote “greening” with negative implications for reservoir water quality and treated drinking water. Considering the nonlinear nature of reservoir OM dynamics and its controls will help to better mitigate water quality issues in these constructed systems increasingly impacted by global changes.

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D.","contributorId":297416,"corporation":false,"usgs":false,"family":"Harlan","given":"James","email":"","middleInitial":"D.","affiliations":[{"id":6754,"text":"University of Missouri","active":true,"usgs":false}],"preferred":false,"id":854111,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"North, Rebecca L.","contributorId":297417,"corporation":false,"usgs":false,"family":"North","given":"Rebecca L.","affiliations":[{"id":6754,"text":"University of Missouri","active":true,"usgs":false}],"preferred":false,"id":854112,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70237558,"text":"70237558 - 2022 - Multispecies approaches to status assessments in support of endangered species classifications","interactions":[],"lastModifiedDate":"2022-11-16T17:13:33.687452","indexId":"70237558","displayToPublicDate":"2022-10-05T11:53:40","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":"Multispecies approaches to status assessments in support of endangered species classifications","docAbstract":"

Multispecies risk assessments have developed within many international conservation programs, reflecting a widespread need for efficiency. Under the United States Endangered Species Act (ESA), multispecies assessments ultimately lead to species-level listing decisions. Although this approach provides opportunities for improved efficiency, it also risks overwhelming or biasing the assessment process and would benefit from clear guidance for practitioners. We reviewed multispecies assessments conducted between 1993 and 2019 for ESA listing decisions to identify the ecological basis for combining species, the assessment approach used, and the policy factors influencing their efficacy. We identified 42 cases covering 359 species. Most assessments (81%) included two to five species, although the maximum was 82. A common theme involved grouping narrow endemics or habitat specialists based on taxonomic relatedness, similar distributions, and common threats to persistence. All assessments included a combined threats analysis, but few employed a common species' response model or expert elicitation process. Although ESA risk assessments are distinct from policy decisions, most assessments (50%) supported decisions that all species warranted endangered status. Available guidance has generally emphasized ecological similarity as the key attribute leading to successful multispecies assessments. The challenge with consistently selecting species based on qualitative proxies such as common distributions or threats to persistence is that ecological patterns and processes are scale dependent. Focusing instead on the assessment methods and their potential for bias and increased efficiency may provide a stronger basis for developing consistent and transparent guidance.

","language":"English","publisher":"Society for Conservation Biology","doi":"10.1111/csp2.12825","usgsCitation":"Fitzgerald, D.B., Freeman, M., Maloney, K.O., Young, J.A., Rosenberger, A.E., Kazyak, D., and Smith, D.R., 2022, Multispecies approaches to status assessments in support of endangered species classifications: Conservation Science and Practice, v. 4, no. 11, e12825, 11 p., https://doi.org/10.1111/csp2.12825.","productDescription":"e12825, 11 p.","ipdsId":"IP-127956","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":446217,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/csp2.12825","text":"Publisher Index Page"},{"id":408261,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"4","issue":"11","noUsgsAuthors":false,"publicationDate":"2022-10-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Fitzgerald, Daniel Bruce 0000-0002-3254-7428","orcid":"https://orcid.org/0000-0002-3254-7428","contributorId":245718,"corporation":false,"usgs":true,"family":"Fitzgerald","given":"Daniel","email":"","middleInitial":"Bruce","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":854454,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Freeman, Mary 0000-0001-7615-6923 mcfreeman@usgs.gov","orcid":"https://orcid.org/0000-0001-7615-6923","contributorId":3528,"corporation":false,"usgs":true,"family":"Freeman","given":"Mary","email":"mcfreeman@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":854455,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Maloney, Kelly O. 0000-0003-2304-0745 kmaloney@usgs.gov","orcid":"https://orcid.org/0000-0003-2304-0745","contributorId":4636,"corporation":false,"usgs":true,"family":"Maloney","given":"Kelly","email":"kmaloney@usgs.gov","middleInitial":"O.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":854456,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Young, John A. 0000-0002-4500-3673 jyoung@usgs.gov","orcid":"https://orcid.org/0000-0002-4500-3673","contributorId":3777,"corporation":false,"usgs":true,"family":"Young","given":"John","email":"jyoung@usgs.gov","middleInitial":"A.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":854457,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rosenberger, Amanda E. 0000-0002-5520-8349 arosenberger@usgs.gov","orcid":"https://orcid.org/0000-0002-5520-8349","contributorId":5581,"corporation":false,"usgs":true,"family":"Rosenberger","given":"Amanda","email":"arosenberger@usgs.gov","middleInitial":"E.","affiliations":[{"id":396,"text":"Missouri Water Science Center","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":854458,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kazyak, David C. 0000-0001-9860-4045","orcid":"https://orcid.org/0000-0001-9860-4045","contributorId":202481,"corporation":false,"usgs":true,"family":"Kazyak","given":"David C.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":854459,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Smith, David R. 0000-0001-6074-9257 drsmith@usgs.gov","orcid":"https://orcid.org/0000-0001-6074-9257","contributorId":168442,"corporation":false,"usgs":true,"family":"Smith","given":"David","email":"drsmith@usgs.gov","middleInitial":"R.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":854460,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70263564,"text":"70263564 - 2022 - Creep rate models for the 2023 US National Seismic Hazard Model: Physically constrained inversions for the distribution of creep on California faults","interactions":[],"lastModifiedDate":"2025-02-13T17:17:51.912547","indexId":"70263564","displayToPublicDate":"2022-10-05T11:16:08","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3372,"text":"Seismological Research Letters","onlineIssn":"1938-2057","printIssn":"0895-0695","active":true,"publicationSubtype":{"id":10}},"title":"Creep rate models for the 2023 US National Seismic Hazard Model: Physically constrained inversions for the distribution of creep on California faults","docAbstract":"

Widespread surface creep is observed across a number of active faults included in the United States (US) National Seismic Hazard Model (NSHM). In northern California, creep occurs on the central section of the San Andreas fault, along the Hayward and Calaveras faults through the San Francisco Bay Area, and to the north coast region along the Maacama and Bartlett Springs faults. In southern California, creep is observed across the Coachella segment of the San Andreas fault, through the Brawley Seismic Zone, and along the Imperial and Superstition Hills faults. Seismic hazard assessments for California have accounted for creep using various data and methods, including the most recent Uniform California Earthquake Rupture Forecast, Version 3 (UCERF3) in 2013. The purpose of this study is to expand and update the UCERF3 creep rate data set for the 2023 release of the US NSHM and to invert geodetic data and the surface creep rate data for the spatial distribution of interseismic fault creep on California faults using an elastic model with physical creep constraints. The updated surface creep rate compilation consists of a variety of data types including alignment arrays, offset cultural markers, creepmeters, Interferometric Synthetic Aperture Radar, and Global Positioning System data. We compile a total of 497 surface creep rate measurements, 400 of which are new and 97 of which appear in the UCERF3 compilation. We compute creep rate distributions for each of the five 2023 NSHM geodetic‐based and geologic‐based deformation models. Computed creep rates are used to reduce the total fault moment rate available for earthquake sequences in the NSHM model. We find that, despite relatively large variability in model long‐term slip rates across all five deformation models, the variability in depth‐averaged creep rate across all models is relatively small, typically 5–10 mm/yr along the creeping San Andreas fault section and only 2–4 mm/yr along the Maacama and Rodgers Creek‐Hayward faults.

","language":"English","publisher":"Seismological Society of America","doi":"10.1785/ 0220220186","usgsCitation":"Johnson, K., Murray, J.R., and Wespestad, C., 2022, Creep rate models for the 2023 US National Seismic Hazard Model: Physically constrained inversions for the distribution of creep on California faults: Seismological Research Letters, v. 93, no. 6, p. 3151-3169, https://doi.org/10.1785/ 0220220186.","productDescription":"19 p.","startPage":"3151","endPage":"3169","ipdsId":"IP-142160","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":482046,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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M.","affiliations":[{"id":37145,"text":"Indiana University","active":true,"usgs":false}],"preferred":false,"id":927345,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Murray, Jessica R. 0000-0002-6144-1681 jrmurray@usgs.gov","orcid":"https://orcid.org/0000-0002-6144-1681","contributorId":2759,"corporation":false,"usgs":true,"family":"Murray","given":"Jessica","email":"jrmurray@usgs.gov","middleInitial":"R.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":927346,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wespestad, Crystal","contributorId":296055,"corporation":false,"usgs":false,"family":"Wespestad","given":"Crystal","email":"","affiliations":[{"id":37145,"text":"Indiana University","active":true,"usgs":false}],"preferred":false,"id":927347,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70256624,"text":"70256624 - 2022 - Genomic divergence, local adaptation, and complex demographic history may inform management of a popular sportfish species complex","interactions":[],"lastModifiedDate":"2024-08-27T15:29:22.998417","indexId":"70256624","displayToPublicDate":"2022-10-05T10:24:52","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Genomic divergence, local adaptation, and complex demographic history may inform management of a popular sportfish species complex","docAbstract":"

The Neosho Bass (Micropterus velox), a former subspecies of the keystone top-predator and globally popular Smallmouth Bass (M. dolomieu), is endemic and narrowly restricted to small, clear streams of the Arkansas River Basin in the Central Interior Highlands (CIH) ecoregion, USA. Previous studies have detected some morphological, genetic, and genomic differentiation between the Neosho and Smallmouth Basses; however, the extent of neutral and adaptive divergence and patterns of intraspecific diversity are poorly understood. Furthermore, lineage diversification has likely been impacted by gene flow in some Neosho populations, which may be due to a combination of natural biogeographic processes and anthropogenic introductions. We assessed: (1) lineage divergence, (2) local directional selection (adaptive divergence), and (3) demographic history among Smallmouth Bass populations in the CIH using population genomic analyses of 50,828 single-nucleotide polymorphisms (SNPs) obtained through ddRAD-seq. Neosho and Smallmouth Bass formed monophyletic clades with 100% bootstrap support. We identified two major lineages within each species. We discovered six Neosho Bass populations (two nonadmixed and four admixed) and three nonadmixed Smallmouth Bass populations. We detected 29 SNPs putatively under directional selection in the Neosho range, suggesting populations may be locally adapted. Two populations were admixed via recent asymmetric secondary contact, perhaps after anthropogenic introduction. Two other populations were likely admixed via combinations of ancient and recent processes. These species comprise independently evolving lineages, some having experienced historical and natural admixture. These results may be critical for management of Neosho Bass as a distinct species and may aid in the conservation of other species with complex biogeographic histories.

","language":"English","publisher":"Wiley","doi":"10.1002/ece3.9370","usgsCitation":"Gunn, J., Berkman, L., Kopplelman, J., Taylor, A., Brewer, S.K., Long, J.M., and Eggert, L., 2022, Genomic divergence, local adaptation, and complex demographic history may inform management of a popular sportfish species complex: Ecology and Evolution, v. 12, no. 10, e9370, 19 p., https://doi.org/10.1002/ece3.9370.","productDescription":"e9370, 19 p.","ipdsId":"IP-131849","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":446220,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.9370","text":"Publisher Index Page"},{"id":433201,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"12","issue":"10","noUsgsAuthors":false,"publicationDate":"2022-10-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Gunn, J.C.","contributorId":341410,"corporation":false,"usgs":false,"family":"Gunn","given":"J.C.","email":"","affiliations":[{"id":6754,"text":"University of Missouri","active":true,"usgs":false}],"preferred":false,"id":908366,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Berkman, L.K.","contributorId":341411,"corporation":false,"usgs":false,"family":"Berkman","given":"L.K.","affiliations":[{"id":16971,"text":"Missouri Department of Conservation","active":true,"usgs":false}],"preferred":false,"id":908367,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kopplelman, J.","contributorId":341412,"corporation":false,"usgs":false,"family":"Kopplelman","given":"J.","email":"","affiliations":[{"id":16971,"text":"Missouri Department of Conservation","active":true,"usgs":false}],"preferred":false,"id":908368,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Taylor, A.T.","contributorId":286995,"corporation":false,"usgs":false,"family":"Taylor","given":"A.T.","email":"","affiliations":[{"id":54572,"text":"University of Central Oklahoma","active":true,"usgs":false}],"preferred":false,"id":908369,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Brewer, Shannon K. 0000-0002-1537-3921 skbrewer@usgs.gov","orcid":"https://orcid.org/0000-0002-1537-3921","contributorId":2252,"corporation":false,"usgs":true,"family":"Brewer","given":"Shannon","email":"skbrewer@usgs.gov","middleInitial":"K.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":908370,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Long, James M. 0000-0002-8658-9949 jmlong@usgs.gov","orcid":"https://orcid.org/0000-0002-8658-9949","contributorId":3453,"corporation":false,"usgs":true,"family":"Long","given":"James","email":"jmlong@usgs.gov","middleInitial":"M.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":908371,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Eggert, L.S.","contributorId":341413,"corporation":false,"usgs":false,"family":"Eggert","given":"L.S.","email":"","affiliations":[{"id":6754,"text":"University of Missouri","active":true,"usgs":false}],"preferred":false,"id":908372,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70256651,"text":"70256651 - 2022 - Next-generation technologies unlock new possibilities to track rangeland productivity and quantify multi-scale conservation outcomes","interactions":[],"lastModifiedDate":"2024-08-29T14:42:33.295584","indexId":"70256651","displayToPublicDate":"2022-10-05T09:34:54","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2258,"text":"Journal of Environmental Management","active":true,"publicationSubtype":{"id":10}},"title":"Next-generation technologies unlock new possibilities to track rangeland productivity and quantify multi-scale conservation outcomes","docAbstract":"

Historically, relying on plot-level inventories impeded our ability to quantify large-scale change in plant biomass, a key indicator of conservation practice outcomes in rangeland systems. Recent technological advances enable assessment at scales appropriate to inform management by providing spatially comprehensive estimates of productivity that are partitioned by plant functional group across all contiguous US rangelands. We partnered with the Sage Grouse and Lesser Prairie-Chicken Initiatives and the Nebraska Natural Legacy Project to demonstrate the ability of these new datasets to quantify multi-scale changes and heterogeneity in plant biomass following mechanical tree removal, prescribed fire, and prescribed grazing. In Oregon's sagebrush steppe, for example, juniper tree removal resulted in a 21% increase in one pasture's productivity and an 18% decline in another. In Nebraska's Loess Canyons, perennial grass productivity initially declined 80% at sites invaded by trees that were prescriptively burned, but then fully recovered post-fire, representing a 492% increase from nadir. In Kansas' Shortgrass Prairie, plant biomass increased 4-fold (966,809 kg/ha) in pastures that were prescriptively grazed, with gains highly dependent upon precipitation as evidenced by sensitivity of remotely sensed estimates (SD ± 951,308 kg/ha). Our results emphasize that next-generation remote sensing datasets empower land managers to move beyond simplistic control versus treatment study designs to explore nuances in plant biomass in unprecedented ways. The products of new remote sensing technologies also accelerate adaptive management and help communicate wildlife and livestock forage benefits from management to diverse stakeholders.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.jenvman.2022.116359","usgsCitation":"Roberts, C.P., Naugle, D., Allred, B.W., Donovan, V.M., Fogarty, D.T., Jones, M., Maestas, J., Olsen, A.C., and Twidwell, D., 2022, Next-generation technologies unlock new possibilities to track rangeland productivity and quantify multi-scale conservation outcomes: Journal of Environmental Management, v. 324, 116359, 8 p., https://doi.org/10.1016/j.jenvman.2022.116359.","productDescription":"116359, 8 p.","ipdsId":"IP-137365","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":446222,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jenvman.2022.116359","text":"Publisher Index Page"},{"id":433304,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Kansas, Nebraska, Oregon","geographicExtents":"{\n \"type\": 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Montana","active":true,"usgs":false}],"preferred":false,"id":908492,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Allred, Brady W.","contributorId":341485,"corporation":false,"usgs":false,"family":"Allred","given":"Brady","email":"","middleInitial":"W.","affiliations":[{"id":36523,"text":"University of Montana","active":true,"usgs":false}],"preferred":false,"id":908493,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Donovan, Victoria M.","contributorId":341486,"corporation":false,"usgs":false,"family":"Donovan","given":"Victoria","email":"","middleInitial":"M.","affiliations":[{"id":16610,"text":"University of Nebraska-Lincoln","active":true,"usgs":false}],"preferred":false,"id":908494,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fogarty, Dillon T.","contributorId":341487,"corporation":false,"usgs":false,"family":"Fogarty","given":"Dillon","email":"","middleInitial":"T.","affiliations":[{"id":16610,"text":"University of Nebraska-Lincoln","active":true,"usgs":false}],"preferred":false,"id":908495,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Jones, Matthew O.","contributorId":341488,"corporation":false,"usgs":false,"family":"Jones","given":"Matthew O.","affiliations":[{"id":36523,"text":"University of Montana","active":true,"usgs":false}],"preferred":false,"id":908496,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Maestas, Jeremy D.","contributorId":341489,"corporation":false,"usgs":false,"family":"Maestas","given":"Jeremy D.","affiliations":[{"id":65354,"text":"USDA Natural Resources Conservation Service","active":true,"usgs":false}],"preferred":false,"id":908497,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Olsen, Andrew C.","contributorId":341490,"corporation":false,"usgs":false,"family":"Olsen","given":"Andrew","email":"","middleInitial":"C.","affiliations":[{"id":7041,"text":"The Nature 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Technology","active":true,"publicationSubtype":{"id":10}},"title":"Exposure to 17α-ethinylestradiol results in differential susceptibility of largemouth bass (Micropterus salmoides) to bacterial infection","docAbstract":"

Disease outbreaks, skin lesions, mortality events, and reproductive abnormalities have been observed in wild populations of centrarchids. The presence of estrogenic endocrine disrupting compounds (EEDCs) has been implicated as a potential causal factor for these effects. The effects of prior EEDC exposure on immune response were examined in juvenile largemouth bass (Micropterus salmoides) exposed to a potent synthetic estrogen (17α-ethinylestradiol, EE2) at a low (EE2Low, 0.87 ng/L) or high (EE2High, 9.08 ng/L) dose for 4 weeks, followed by transfer to clean water and injection with an LD40 dose of the Gram-negative bacteria Edwardsiella piscicida. Unexpectedly, this prior exposure to EE2High significantly increased survivorship at 10 d post-infection compared to solvent control or EE2Low-exposed, infected fish. Both prior exposure and infection with E. piscicida led to significantly reduced hepatic glycogen levels, indicating a stress response resulting in depletion of energy stores. Additionally, pathway analysis for liver and spleen indicated differentially expressed genes associated with immunometabolic processes in the mock-injected EE2High treatment that could underlie the observed protective effect and metabolic shift in EE2High-infected fish. Our results demonstrate that exposure to a model EEDC alters metabolism and immune function in a fish species that is ecologically and economically important in North America.

","language":"English","publisher":"ACS Publications","doi":"10.1021/acs.est.2c02250","usgsCitation":"Leet, J.K., Greer, J., Richter, C.A., Iwanowicz, L., Spinard, E., McDonald, J., Conway, C.M., Gale, R.W., Tillitt, D.E., and Hansen, J.D., 2022, Exposure to 17α-ethinylestradiol results in differential susceptibility of largemouth bass (Micropterus salmoides) to bacterial infection: Environmental Science and Technology, v. 56, no. 20, p. 14375-14386, https://doi.org/10.1021/acs.est.2c02250.","productDescription":"12 p.","startPage":"14375","endPage":"14386","ipdsId":"IP-139357","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true},{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":446225,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1021/acs.est.2c02250","text":"Publisher Index Page"},{"id":435665,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P93OHUUS","text":"USGS data release","linkHelpText":"Physiological and molecular endpoints observed in juvenile largemouth bass in response to an estrogen (17&amp;amp;amp;alpha;-ethinylestradiol) and subsequently a bacterial challenge (Edwardsiella piscicida) exposure under laboratory conditions."},{"id":408607,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"56","issue":"20","noUsgsAuthors":false,"publicationDate":"2022-10-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Leet, Jessica Kristin 0000-0001-8142-6043","orcid":"https://orcid.org/0000-0001-8142-6043","contributorId":225505,"corporation":false,"usgs":true,"family":"Leet","given":"Jessica","email":"","middleInitial":"Kristin","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":855378,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Greer, Justin","contributorId":298316,"corporation":false,"usgs":false,"family":"Greer","given":"Justin","affiliations":[{"id":24583,"text":"former USGS employee","active":true,"usgs":false}],"preferred":false,"id":855379,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Richter, Cathy A. 0000-0001-7322-4206 crichter@usgs.gov","orcid":"https://orcid.org/0000-0001-7322-4206","contributorId":1878,"corporation":false,"usgs":true,"family":"Richter","given":"Cathy","email":"crichter@usgs.gov","middleInitial":"A.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":855380,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Iwanowicz, Luke R. 0000-0002-1197-6178","orcid":"https://orcid.org/0000-0002-1197-6178","contributorId":79382,"corporation":false,"usgs":true,"family":"Iwanowicz","given":"Luke R.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":855381,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Spinard, Edward","contributorId":298319,"corporation":false,"usgs":false,"family":"Spinard","given":"Edward","email":"","affiliations":[{"id":24583,"text":"former USGS employee","active":true,"usgs":false}],"preferred":false,"id":855382,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"McDonald, Jacquelyn","contributorId":298321,"corporation":false,"usgs":false,"family":"McDonald","given":"Jacquelyn","email":"","affiliations":[{"id":24583,"text":"former USGS employee","active":true,"usgs":false}],"preferred":false,"id":855383,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Conway, Carla M. 0000-0002-3851-3616 cmconway@usgs.gov","orcid":"https://orcid.org/0000-0002-3851-3616","contributorId":2946,"corporation":false,"usgs":true,"family":"Conway","given":"Carla","email":"cmconway@usgs.gov","middleInitial":"M.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":855384,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Gale, Robert W. 0000-0002-8533-141X rgale@usgs.gov","orcid":"https://orcid.org/0000-0002-8533-141X","contributorId":2808,"corporation":false,"usgs":true,"family":"Gale","given":"Robert","email":"rgale@usgs.gov","middleInitial":"W.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":855385,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Tillitt, Donald E. 0000-0002-8278-3955 dtillitt@usgs.gov","orcid":"https://orcid.org/0000-0002-8278-3955","contributorId":1875,"corporation":false,"usgs":true,"family":"Tillitt","given":"Donald","email":"dtillitt@usgs.gov","middleInitial":"E.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":855386,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Hansen, John D. 0000-0002-3006-2734","orcid":"https://orcid.org/0000-0002-3006-2734","contributorId":220725,"corporation":false,"usgs":true,"family":"Hansen","given":"John","middleInitial":"D.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":855387,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70237281,"text":"70237281 - 2022 - Evolutionary dynamics inform management interventions of a hanging garden obligate, Carex specuicola","interactions":[],"lastModifiedDate":"2022-10-06T14:37:55.932771","indexId":"70237281","displayToPublicDate":"2022-10-05T09:31:01","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":9319,"text":"Frontiers in Conservation Science","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Evolutionary dynamics inform management interventions of a hanging garden obligate, Carex specuicola","title":"Evolutionary dynamics inform management interventions of a hanging garden obligate, Carex specuicola","docAbstract":"

Uncovering the historical and contemporary processes shaping rare species with complex distributions is of growing importance due to threats such as habitat destruction and climate change. Species restricted to specialized, patchy habitat may persist by virtue of life history characteristics facilitating ongoing gene flow and dispersal, but they could also reflect the remnants of formerly widespread, suitable habitat that existed during past climate regimes. If formerly widespread species did not rely upon traits facilitating high dispersibility to persist, contemporary populations could be at high risk of extirpation or extinction. Fortunately, genomic investigations provide an opportunity to illuminate such alternative scenarios while simultaneously offering guidance for future management interventions. Herein, we test the role of these mechanisms in shaping patterns of genomic diversity and differentiation across a highly restricted and rare ecosystem: desert hanging gardens. We focus on Carex specuicola (Cyperaceae), a hanging garden obligate narrowly distributed in the Four Corners region of the southwestern United States that is listed as Threatened under the United States Endangered Species Act. Population structure and diversity analyses reveal that hanging garden populations are shaped by strong genetic drift, but that individuals in gardens are occasionally more closely related to individuals at other gardens than to individuals within the same garden. Similarly, gardens separated by long geographic distances may contain individuals that are more closely related compared to individuals in gardens separated by short geographic distances. Demographic modeling supports historical gene flow between some contemporary garden pairs, which is corroborated by low estimates of inbreeding coefficients and recent divergence times. As such, multiple lines of evidence support dispersal and gene flow across C. specuicola populations at both small and large spatial scales, indicating that even if C. specuicola was formerly more widespread, it may be well suited to persist in hanging gardens so long as suitable habitat remains available. Analyses like those demonstrated herein may be broadly applicable for understanding the short- and long-term evolutionary processes influencing rare species, and especially those having complex distributions across heterogeneous landscapes.

","language":"English","publisher":"Frontiers Media","doi":"10.3389/fcosc.2022.941002","usgsCitation":"Chapin, K.J., Jones, M.R., Winkler, D.E., Rink, G., and Massatti, R., 2022, Evolutionary dynamics inform management interventions of a hanging garden obligate, Carex specuicola: Frontiers in Conservation Science, v. 3, 941002, 15 p., https://doi.org/10.3389/fcosc.2022.941002.","productDescription":"941002, 15 p.","ipdsId":"IP-141134","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":446227,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fcosc.2022.941002","text":"Publisher Index Page"},{"id":435666,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9LLZ1XD","text":"USGS data release","linkHelpText":"Carex specuicola genomic data for the southern Colorado Plateau Desert"},{"id":408036,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona, Utah","otherGeospatial":"southern Colorado Plateau Desert","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -110.478515625,\n 35.88905007936091\n ],\n [\n -109.072265625,\n 35.88905007936091\n ],\n [\n -109.072265625,\n 37.75334401310656\n ],\n [\n -110.478515625,\n 37.75334401310656\n ],\n [\n -110.478515625,\n 35.88905007936091\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"3","noUsgsAuthors":false,"publicationDate":"2022-10-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Chapin, Kenneth James 0000-0002-8382-4050","orcid":"https://orcid.org/0000-0002-8382-4050","contributorId":297377,"corporation":false,"usgs":true,"family":"Chapin","given":"Kenneth","email":"","middleInitial":"James","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":853969,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jones, Matthew R","contributorId":297378,"corporation":false,"usgs":false,"family":"Jones","given":"Matthew","email":"","middleInitial":"R","affiliations":[{"id":64389,"text":"formerly: USGS Southwest Biological Science Center, Flagstaff, AZ","active":true,"usgs":false}],"preferred":false,"id":853970,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Winkler, Daniel E. 0000-0003-4825-9073","orcid":"https://orcid.org/0000-0003-4825-9073","contributorId":206786,"corporation":false,"usgs":true,"family":"Winkler","given":"Daniel","email":"","middleInitial":"E.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":853971,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rink, Glenn","contributorId":297379,"corporation":false,"usgs":false,"family":"Rink","given":"Glenn","affiliations":[{"id":64390,"text":"Deaver Herbarium, Northern Arizona University, Flagstaff, AZ","active":true,"usgs":false}],"preferred":false,"id":853972,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Massatti, Robert 0000-0001-5854-5597","orcid":"https://orcid.org/0000-0001-5854-5597","contributorId":207294,"corporation":false,"usgs":true,"family":"Massatti","given":"Robert","email":"","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":853973,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70237282,"text":"70237282 - 2022 - A fault‐based crustal deformation model with deep driven dislocation sources for the 2023 update to the U.S. National Seismic Hazard Model","interactions":[],"lastModifiedDate":"2022-10-31T14:50:23.413345","indexId":"70237282","displayToPublicDate":"2022-10-05T09:12:43","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3372,"text":"Seismological Research Letters","onlineIssn":"1938-2057","printIssn":"0895-0695","active":true,"publicationSubtype":{"id":10}},"title":"A fault‐based crustal deformation model with deep driven dislocation sources for the 2023 update to the U.S. National Seismic Hazard Model","docAbstract":"

A fault‐based crustal deformation model with deep driven dislocation sources is applied to estimate long‐term on‐fault slip rates and off‐fault moment rate distribution in the western United States (WUS) for the 2023 update to the National Seismic Hazard Model (NSHM). This model uses the method of Zeng and Shen (2017) to invert for slip rate and strain‐rate parameters based on inputs from Global Positioning System (GPS) velocities and geologic slip‐rate constraints. The model connects adjacent major fault segments in California and the Cascadia subduction zone to form blocks that extend to the boundaries of the study area. Faults within the blocks are obtained from the NSHM geologic fault section database. The model slip rates are determined using a least‐squares inversion with a normalized chi‐square of 6.6. I also apply a time‐dependent correction called “ghost transient” effect to account for the viscoelastic responses from large historic earthquakes along the San Andreas fault and Cascadia subduction zone. Major discrepancies between model slip rates and geologic slip rates along the San Andreas fault, for example, from the Cholame to the Mojave and San Bernardino segments of the San Andreas, are well reduced after the ghost transient correction is applied to GPS velocities. The off‐fault moment rate distribution is consistent with regional tectonics and seismicity patterns with a total rate of 1.6&#xD7;1019&#x2009;&#x2009;N&#xB7;m/yr\">1.6×1019  N⋅m/yr for the WUS.

","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0220220209","usgsCitation":"Zeng, Y., 2022, A fault‐based crustal deformation model with deep driven dislocation sources for the 2023 update to the U.S. National Seismic Hazard Model: Seismological Research Letters, v. 93, no. 6, p. 3170-3185, https://doi.org/10.1785/0220220209.","productDescription":"16 p.","startPage":"3170","endPage":"3185","ipdsId":"IP-142327","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":408032,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"western United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -126.7822265625,\n 31.80289258670676\n ],\n [\n -105,\n 31.80289258670676\n ],\n [\n -105,\n 48.922499263758255\n ],\n [\n -126.7822265625,\n 48.922499263758255\n ],\n [\n -126.7822265625,\n 31.80289258670676\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"93","issue":"6","noUsgsAuthors":false,"publicationDate":"2022-10-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Zeng, Yuehua 0000-0003-1161-1264 zeng@usgs.gov","orcid":"https://orcid.org/0000-0003-1161-1264","contributorId":145693,"corporation":false,"usgs":true,"family":"Zeng","given":"Yuehua","email":"zeng@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":853974,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70237593,"text":"70237593 - 2022 - Ocean acidification in the Gulf of Mexico: Drivers, impacts, and unknowns","interactions":[],"lastModifiedDate":"2022-10-31T14:53:37.328533","indexId":"70237593","displayToPublicDate":"2022-10-04T14:10:31","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3194,"text":"Progress in Oceanography","active":true,"publicationSubtype":{"id":10}},"title":"Ocean acidification in the Gulf of Mexico: Drivers, impacts, and unknowns","docAbstract":"Ocean acidification (OA) has resulted in global-scale changes in ocean chemistry, which can disturb marine organisms and ecosystems. Despite its extensively populated coastline, many marine-dependent communities, and valuable economies, the Gulf of Mexico (GOM) remains a relatively understudied region with respect to acidification. In general, the warm waters of the GOM are better buffered from acidification compared to higher latitude seas, yet long-term acidification has been documented in several GOM regions. OA within the GOM is recognized as spatially variable, particularly within the coastal zone where numerous physical and biogeochemical processes contribute to carbonate chemistry dynamics. The historical progression of OA within the entire GOM is difficult to assess because only a few dedicated long-term monitoring sites have recently been established, and full-water column observations are limited. However, environmental drivers on smaller scales that affect GOM acidification were found to include freshwater, nutrient, and carbonate discharge from large rivers; ocean warming, circulation and residence times; and episodic extreme weather events. GOM marine ecosystems provide essential services, including coastline protection and carbon dioxide removal, and habitats for many marine species that are economically and ecologically important. However, organismal and ecosystem responses to OA are not well constrained for the GOM due to a lack of studies examining the specific effects of OA on regionally relevant species under contemporary and projected conditions. Tackling the vast number of remaining scientific unknowns in this region can be best coordinated through regional capacity networks, such as the Gulf of Mexico Coastal Acidification Network (GCAN), working to achieve a system-wide understanding of Gulf OA and its impacts. Here we synthesize the current peer-reviewed literature on GOM acidification across the ocean-estuarine continuum and identify critical knowledge, research, and monitoring gaps that require future attention.","language":"English","publisher":"Elsevier","doi":"10.1016/j.pocean.2022.102882","usgsCitation":"Osborne, E., Hu, X., Hall, E.R., Yates, K.K., Vreeland-Dawson, J., Shamberger, K., Barbero, L., Hernandez-Ayon, J., Gomez, F., Hicks, T., Xu, Y., McCutcheon, M.R., Acquafredda, M., Chapa-Balcorta, C., Norzagaray, O., Pierrot, D., Munoz-Caravaca, A., Dobson, K.L., Williams, N., Rabalais, N.N., and Dash, P., 2022, Ocean acidification in the Gulf of Mexico: Drivers, impacts, and unknowns: Progress in Oceanography, v. 209, 102882, 23 p., https://doi.org/10.1016/j.pocean.2022.102882.","productDescription":"102882, 23 p.","ipdsId":"IP-135936","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":446231,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.pocean.2022.102882","text":"Publisher Index Page"},{"id":408276,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Gulf of Mexico","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -89.82421875,\n 21.207458730482642\n ],\n [\n -87.099609375,\n 21.779905342529645\n ],\n [\n -83.935546875,\n 22.59372606392931\n ],\n [\n -80.947265625,\n 24.926294766395593\n ],\n [\n -82.265625,\n 27.137368359795584\n ],\n [\n -82.705078125,\n 28.38173504322308\n ],\n [\n -83.75976562499999,\n 30.06909396443887\n ],\n [\n -84.990234375,\n 29.53522956294847\n ],\n [\n -86.484375,\n 30.372875188118016\n ],\n [\n -87.978515625,\n 30.372875188118016\n ],\n [\n -90.087890625,\n 30.14512718337613\n ],\n [\n -89.384765625,\n 29.6880527498568\n ],\n [\n -90.263671875,\n 28.998531814051795\n ],\n [\n -91.23046875,\n 29.22889003019423\n ],\n [\n -92.021484375,\n 29.76437737516313\n ],\n [\n -93.8671875,\n 29.53522956294847\n ],\n [\n -95.537109375,\n 28.844673680771795\n ],\n [\n -96.85546875,\n 27.994401411046148\n ],\n [\n -97.646484375,\n 26.980828590472107\n ],\n [\n -97.3828125,\n 25.24469595130604\n ],\n [\n -97.55859375,\n 22.836945920943855\n ],\n [\n -97.3828125,\n 20.96143961409684\n ],\n [\n -96.328125,\n 19.476950206488414\n ],\n [\n -94.21875,\n 18.396230138028827\n ],\n [\n -92.28515625,\n 18.396230138028827\n ],\n [\n -91.0546875,\n 18.979025953255267\n ],\n [\n -90.3515625,\n 21.207458730482642\n ],\n [\n -89.82421875,\n 21.207458730482642\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"209","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Osborne, Emily","contributorId":279621,"corporation":false,"usgs":false,"family":"Osborne","given":"Emily","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":854555,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hu, Xinping 0000-0002-0613-6545","orcid":"https://orcid.org/0000-0002-0613-6545","contributorId":297889,"corporation":false,"usgs":false,"family":"Hu","given":"Xinping","email":"","affiliations":[{"id":64434,"text":"Harte Research Institute for Gulf of Mexico Studies, Texas A&M University-Corpus Christi, US","active":true,"usgs":false}],"preferred":false,"id":854556,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hall, E. 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Martin 0000-0001-6869-6225","orcid":"https://orcid.org/0000-0001-6869-6225","contributorId":297892,"corporation":false,"usgs":false,"family":"Hernandez-Ayon","given":"J. Martin","affiliations":[{"id":64439,"text":"Autonomous University of Baja California, Mexico","active":true,"usgs":false}],"preferred":false,"id":854562,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Gomez, Fabian 0000-0002-2335-478X","orcid":"https://orcid.org/0000-0002-2335-478X","contributorId":297893,"corporation":false,"usgs":false,"family":"Gomez","given":"Fabian","email":"","affiliations":[{"id":64440,"text":"Cooperative Institute for Marine and Atmospheric Studies, Rosenstiel School for Marine and Atmospheric Science, University of Miami, Miami, FL","active":true,"usgs":false}],"preferred":false,"id":854563,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Hicks, Tacey 0000-0002-4064-7496","orcid":"https://orcid.org/0000-0002-4064-7496","contributorId":297894,"corporation":false,"usgs":false,"family":"Hicks","given":"Tacey","email":"","affiliations":[{"id":34980,"text":"Department of Oceanography, Texas A&M University","active":true,"usgs":false}],"preferred":false,"id":854564,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Xu, Yuan-Yuan 0000-0001-5103-468X","orcid":"https://orcid.org/0000-0001-5103-468X","contributorId":297895,"corporation":false,"usgs":false,"family":"Xu","given":"Yuan-Yuan","email":"","affiliations":[{"id":64440,"text":"Cooperative Institute for Marine and Atmospheric Studies, Rosenstiel School for Marine and Atmospheric Science, University of Miami, Miami, FL","active":true,"usgs":false}],"preferred":false,"id":854565,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"McCutcheon, Melissa R. 0000-0003-1289-9191","orcid":"https://orcid.org/0000-0003-1289-9191","contributorId":297896,"corporation":false,"usgs":false,"family":"McCutcheon","given":"Melissa","email":"","middleInitial":"R.","affiliations":[{"id":64434,"text":"Harte Research Institute for Gulf of Mexico Studies, Texas A&M University-Corpus Christi, US","active":true,"usgs":false}],"preferred":false,"id":854566,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Acquafredda, Michael 0000-0003-2006-6026","orcid":"https://orcid.org/0000-0003-2006-6026","contributorId":297897,"corporation":false,"usgs":false,"family":"Acquafredda","given":"Michael","email":"","affiliations":[{"id":64441,"text":"Ocean Acidification Program, National Oceanographic and Atmospheric Administration, Silver Spring, MD, US","active":true,"usgs":false}],"preferred":false,"id":854567,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Chapa-Balcorta, Cecilia 0000-0001-8305-0844","orcid":"https://orcid.org/0000-0001-8305-0844","contributorId":297898,"corporation":false,"usgs":false,"family":"Chapa-Balcorta","given":"Cecilia","email":"","affiliations":[{"id":64442,"text":"Instituto de Recursos, Universidad del Mar. Puerto Angel, Oaxaca, Mexico","active":true,"usgs":false}],"preferred":false,"id":854568,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Norzagaray, Orion 0000-0002-9769-0030","orcid":"https://orcid.org/0000-0002-9769-0030","contributorId":297899,"corporation":false,"usgs":false,"family":"Norzagaray","given":"Orion","email":"","affiliations":[{"id":64439,"text":"Autonomous University of Baja California, Mexico","active":true,"usgs":false}],"preferred":false,"id":854569,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Pierrot, Denis","contributorId":176446,"corporation":false,"usgs":false,"family":"Pierrot","given":"Denis","email":"","affiliations":[],"preferred":false,"id":854570,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Munoz-Caravaca, Alain 0000-0003-1261-0159","orcid":"https://orcid.org/0000-0003-1261-0159","contributorId":297900,"corporation":false,"usgs":false,"family":"Munoz-Caravaca","given":"Alain","email":"","affiliations":[{"id":64443,"text":"Center for Environmental Studies in Cienfuegos, Cuba","active":true,"usgs":false}],"preferred":false,"id":854571,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Dobson, Kerri L. 0000-0003-1363-4195","orcid":"https://orcid.org/0000-0003-1363-4195","contributorId":297901,"corporation":false,"usgs":false,"family":"Dobson","given":"Kerri","email":"","middleInitial":"L.","affiliations":[{"id":64441,"text":"Ocean Acidification Program, National Oceanographic and Atmospheric Administration, Silver Spring, MD, US","active":true,"usgs":false}],"preferred":false,"id":854572,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Williams, N. 0000-0002-6541-9385","orcid":"https://orcid.org/0000-0002-6541-9385","contributorId":297902,"corporation":false,"usgs":false,"family":"Williams","given":"N.","email":"","affiliations":[{"id":64444,"text":"College of Marine Science, University of South Florida, Saint Petersburg, FL","active":true,"usgs":false}],"preferred":false,"id":854573,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Rabalais, N. N.","contributorId":198497,"corporation":false,"usgs":false,"family":"Rabalais","given":"N.","email":"","middleInitial":"N.","affiliations":[{"id":12699,"text":"Louisiana Universities Marine Consortium","active":true,"usgs":false}],"preferred":false,"id":854574,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"Dash, Padmanava 0000-0003-3851-6830","orcid":"https://orcid.org/0000-0003-3851-6830","contributorId":297903,"corporation":false,"usgs":false,"family":"Dash","given":"Padmanava","email":"","affiliations":[{"id":64445,"text":"Department of Geosciences, Mississippi State University, Mississippi State, MS, US","active":true,"usgs":false}],"preferred":false,"id":854575,"contributorType":{"id":1,"text":"Authors"},"rank":21}]}} ,{"id":70237137,"text":"fs20223069 - 2022 - Assessment of undiscovered conventional oil and gas resources in Mesozoic total petroleum systems of the Central European Basin system, 2019","interactions":[],"lastModifiedDate":"2022-10-05T10:54:58.073609","indexId":"fs20223069","displayToPublicDate":"2022-10-04T11:45:00","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2022-3069","displayTitle":"Assessment of Undiscovered Conventional Oil and Gas Resources in Mesozoic Total Petroleum Systems of the Central European Basin System, 2019","title":"Assessment of undiscovered conventional oil and gas resources in Mesozoic total petroleum systems of the Central European Basin system, 2019","docAbstract":"

Using a geology-based assessment methodology, the U.S. Geological Survey estimated mean undiscovered, technically recoverable continuous resources of 5.8 billion barrels of oil and 22.4 trillion cubic feet of gas in the Mesozoic Total Petroleum Systems of the Central European Basin.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20223069","usgsCitation":"Schenk, C.J., Mercier, T.J., Woodall, C.A., Leathers-Miller, H.M., Le, P.A., Drake, R.M., II, Kinney, S.A., and Brownfield, M.E., 2022, Assessment of undiscovered conventional oil and gas resources in Mesozoic total petroleum systems of the Central European Basin system, 2019: U.S. Geological Survey Fact Sheet 2022–3069, 4 p., https://doi.org/10.3133/fs20223069.","productDescription":"Report: 4 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-115545","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":407698,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9N5F8XY","text":"USGS data release","linkHelpText":"USGS National and Global Oil and Gas Assessment Project-Mesozoic Petroleum Systems of Central European Basin System: Assessment Unit Boundaries, Assessment Input Data, and Fact Sheet Data Tables"},{"id":407696,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2022/3069/coverthb.jpg"},{"id":407697,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2022/3069/fs20223069.pdf","text":"Report","size":"1.03 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2022-3069"}],"otherGeospatial":"Central European Basin system","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -9.667968749999975,\n 50.2893392532918\n ],\n [\n 9.93164062500003,\n 50.2893392532918\n ],\n [\n 9.93164062500003,\n 63.11463763252086\n ],\n [\n -9.667968749999975,\n 63.11463763252086\n ],\n [\n -9.667968749999975,\n 50.2893392532918\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"

Director, Central Energy Resources Science Center
U.S. Geological Survey
Box 25046, MS-939
Denver, CO 80225-0046

","tableOfContents":"","publishedDate":"2022-10-04","noUsgsAuthors":false,"publicationDate":"2022-10-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Schenk, Christopher J. 0000-0002-0248-7305 schenk@usgs.gov","orcid":"https://orcid.org/0000-0002-0248-7305","contributorId":826,"corporation":false,"usgs":true,"family":"Schenk","given":"Christopher","email":"schenk@usgs.gov","middleInitial":"J.","affiliations":[{"id":255,"text":"Energy Resources Program","active":true,"usgs":true},{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":853462,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mercier, Tracey J. 0000-0002-8232-525X","orcid":"https://orcid.org/0000-0002-8232-525X","contributorId":255366,"corporation":false,"usgs":true,"family":"Mercier","given":"Tracey J.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":853463,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Woodall, Cheryl A. 0000-0002-4844-5768 cwoodall@usgs.gov","orcid":"https://orcid.org/0000-0002-4844-5768","contributorId":194924,"corporation":false,"usgs":true,"family":"Woodall","given":"Cheryl","email":"cwoodall@usgs.gov","middleInitial":"A.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":853464,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Leathers-Miller, Heidi M. 0000-0001-5208-9906","orcid":"https://orcid.org/0000-0001-5208-9906","contributorId":210000,"corporation":false,"usgs":true,"family":"Leathers-Miller","given":"Heidi M.","affiliations":[{"id":5078,"text":"Southwest Regional Director's Office","active":true,"usgs":true},{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":853467,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Le, Phuong A. 0000-0003-2477-509X","orcid":"https://orcid.org/0000-0003-2477-509X","contributorId":255367,"corporation":false,"usgs":true,"family":"Le","given":"Phuong A.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":853466,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Drake, Ronald M. II 0000-0002-1770-4667","orcid":"https://orcid.org/0000-0002-1770-4667","contributorId":206291,"corporation":false,"usgs":true,"family":"Drake","given":"Ronald M.","suffix":"II","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":853468,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kinney, Scott A. 0000-0001-5008-5813 skinney@usgs.gov","orcid":"https://orcid.org/0000-0001-5008-5813","contributorId":1395,"corporation":false,"usgs":true,"family":"Kinney","given":"Scott","email":"skinney@usgs.gov","middleInitial":"A.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":853469,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Brownfield, Michael E. 0000-0003-3633-1138 mbrownfield@usgs.gov","orcid":"https://orcid.org/0000-0003-3633-1138","contributorId":1548,"corporation":false,"usgs":true,"family":"Brownfield","given":"Michael","email":"mbrownfield@usgs.gov","middleInitial":"E.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":853470,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70238634,"text":"70238634 - 2022 - Regional models do not outperform continental models for invasive species","interactions":[],"lastModifiedDate":"2022-12-02T13:01:29.078063","indexId":"70238634","displayToPublicDate":"2022-10-04T07:00:10","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5071,"text":"NeoBiota","active":true,"publicationSubtype":{"id":10}},"title":"Regional models do not outperform continental models for invasive species","docAbstract":"

Aim: Species distribution models can guide invasive species prevention and management by characterizing invasion risk across space. However, extrapolation and transferability issues pose challenges for developing useful models for invasive species. Previous work has emphasized the importance of including all available occurrences in model estimation, but managers attuned to local processes may be skeptical of models based on a broad spatial extent if they suspect the captured responses reflect those of other regions where data are more numerous. We asked whether species distribution models for invasive plants performed better when developed at national versus regional extents.

Location: Continental United States.

Methods: We developed ensembles of species distribution models trained nationally, on sagebrush habitat, or on sagebrush habitat within three ecoregions (Great Basin, eastern sagebrush, and Great Plains) for nine invasive plants of interest for early detection and rapid response at local or regional scales. We compared the performance of national versus regional models using spatially independent withheld test data from each of the three ecoregions.

Results: We found that models trained using a national spatial extent tended to perform better than regionally trained models. Regional models did not outperform national ones even when considerable occurrence data were available for model estimation within the focal region. Information was often unavailable to fit informative regional models precisely in those areas of greatest interest for early detection and rapid response.

Main conclusions: Habitat suitability models for invasive plant species trained at a continental extent can reduce extrapolation while maximizing information on species’ responses to environmental variation. Standard modeling methods can capture spatially varying limiting factors, while regional or hierarchical models may only be advantageous when populations differ in their responses to environmental conditions, a condition expected to be relatively rare at the expanding boundaries of invasive species’ distributions.

","language":"English","publisher":"NeoBiota","doi":"10.3897/neobiota.77.86364","usgsCitation":"Jarnevich, C.S., Sofaer, H., Engelstad, P., and Belamaric, P., 2022, Regional models do not outperform continental models for invasive species: NeoBiota, v. 77, https://doi.org/10.3897/neobiota.77.86364.","productDescription":"22 p.","startPage":"1-22","ipdsId":"IP-137001","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":446233,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3897/neobiota.77.86364","text":"Publisher Index Page"},{"id":435667,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P90AL0PN","text":"USGS data release","linkHelpText":"Data to create and evaluate distribution models for invasive species for different geographic extents"},{"id":409981,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"77","noUsgsAuthors":false,"publicationDate":"2022-10-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Jarnevich, Catherine S. 0000-0002-9699-2336 jarnevichc@usgs.gov","orcid":"https://orcid.org/0000-0002-9699-2336","contributorId":3424,"corporation":false,"usgs":true,"family":"Jarnevich","given":"Catherine","email":"jarnevichc@usgs.gov","middleInitial":"S.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":858156,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sofaer, Helen 0000-0002-9450-5223","orcid":"https://orcid.org/0000-0002-9450-5223","contributorId":216681,"corporation":false,"usgs":true,"family":"Sofaer","given":"Helen","email":"","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":858157,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Engelstad, Peder","contributorId":238758,"corporation":false,"usgs":false,"family":"Engelstad","given":"Peder","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":858158,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Belamaric, Pairsa 0000-0001-7529-0370","orcid":"https://orcid.org/0000-0001-7529-0370","contributorId":299593,"corporation":false,"usgs":false,"family":"Belamaric","given":"Pairsa","affiliations":[{"id":64897,"text":"Student Contractor to the USGS Fort Collins Science Center","active":true,"usgs":false}],"preferred":false,"id":858159,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70237881,"text":"70237881 - 2022 - Hurdles to developing quantitative decision support for Endangered Species Act resource allocation","interactions":[],"lastModifiedDate":"2022-10-31T12:01:40.279728","indexId":"70237881","displayToPublicDate":"2022-10-04T06:58:37","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":9319,"text":"Frontiers in Conservation Science","active":true,"publicationSubtype":{"id":10}},"title":"Hurdles to developing quantitative decision support for Endangered Species Act resource allocation","docAbstract":"

The U.S. Fish and Wildlife Service oversees the recovery of many species protected by the U.S. Endangered Species Act (ESA). Recent research suggests that a structured approach to allocating conservation resources could increase recovery outcomes for ESA listed species. Quantitative approaches to decision support can efficiently allocate limited financial resources and maximize desired outcomes. Yet, developing quantitative decision support under real-world constraints is challenging. Approaches that pair research teams and end-users are generally the most effective. However, co-development requires overcoming “hurdles” that can arise because of differences in the mental models of the co-development team. These include perceptions that: (1) scarce funds should be spent on action, not decision support; (2) quantitative approaches are only useful for simple decisions; (3) quantitative tools are inflexible and prescriptive black boxes; (4) available data are not good enough to support decisions; and (5) prioritization means admitting defeat. Here, we describe how we addressed these misperceptions during the development of a prototype resource allocation decision support tool for understanding trade-offs in U.S. endangered species recovery. We describe how acknowledging these hurdles and identifying solutions enabled us to progress with development. We believe that our experience can assist other applications of developing quantitative decision support for resource allocation.

","language":"English","publisher":"Frontiers","doi":"10.3389/fcosc.2022.1002804","usgsCitation":"Iacona, G.D., Avery-Gomm, S., Maloney, R.F., Brazill-Boast, J., Crouse, D.T., Drew, C., Epanchin-Niell, R.S., Hall, S.B., Maguire, L.A., Male, T., Newman, J., Possingham, H.P., Rumpff, L., Runge, M.C., Weiss, K.C., Wilson, R.S., Zablan, M.A., and Gerber, L.R., 2022, Hurdles to developing quantitative decision support for Endangered Species Act resource allocation: Frontiers in Conservation Science, v. 3, 1002804, 9 p., https://doi.org/10.3389/fcosc.2022.1002804.","productDescription":"1002804, 9 p.","ipdsId":"IP-114585","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":446236,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fcosc.2022.1002804","text":"Publisher Index Page"},{"id":408877,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"3","noUsgsAuthors":false,"publicationDate":"2022-10-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Iacona, Gwenllian D.","contributorId":213094,"corporation":false,"usgs":false,"family":"Iacona","given":"Gwenllian","email":"","middleInitial":"D.","affiliations":[{"id":12552,"text":"University of Queensland","active":true,"usgs":false}],"preferred":false,"id":856069,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Avery-Gomm, Stephanie","contributorId":213093,"corporation":false,"usgs":false,"family":"Avery-Gomm","given":"Stephanie","email":"","affiliations":[{"id":12552,"text":"University of Queensland","active":true,"usgs":false}],"preferred":false,"id":856070,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Maloney, Richard F.","contributorId":213091,"corporation":false,"usgs":false,"family":"Maloney","given":"Richard","email":"","middleInitial":"F.","affiliations":[{"id":38703,"text":"New Zealand Department of Conservation","active":true,"usgs":false}],"preferred":false,"id":856071,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brazill-Boast, James","contributorId":213095,"corporation":false,"usgs":false,"family":"Brazill-Boast","given":"James","email":"","affiliations":[{"id":38705,"text":"New South Wales Office of Environment and Heritage","active":true,"usgs":false}],"preferred":false,"id":856072,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Crouse, Deborah T.","contributorId":173709,"corporation":false,"usgs":false,"family":"Crouse","given":"Deborah","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":856073,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Drew, C Ashton","contributorId":298628,"corporation":false,"usgs":false,"family":"Drew","given":"C Ashton","affiliations":[{"id":64631,"text":"KDV Decision Analysis LLC","active":true,"usgs":false}],"preferred":false,"id":856074,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Epanchin-Niell, Rebecca S.","contributorId":175364,"corporation":false,"usgs":false,"family":"Epanchin-Niell","given":"Rebecca","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":856075,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Hall, Sarah B.","contributorId":213157,"corporation":false,"usgs":false,"family":"Hall","given":"Sarah","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":856076,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Maguire, Lynn A.","contributorId":213097,"corporation":false,"usgs":false,"family":"Maguire","given":"Lynn","email":"","middleInitial":"A.","affiliations":[{"id":12643,"text":"Duke University","active":true,"usgs":false}],"preferred":false,"id":856077,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Male, Tim","contributorId":213158,"corporation":false,"usgs":false,"family":"Male","given":"Tim","email":"","affiliations":[],"preferred":false,"id":856078,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Newman, Jeff","contributorId":213099,"corporation":false,"usgs":false,"family":"Newman","given":"Jeff","email":"","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":856079,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Possingham, Hugh P.","contributorId":20882,"corporation":false,"usgs":false,"family":"Possingham","given":"Hugh","email":"","middleInitial":"P.","affiliations":[{"id":12552,"text":"University of Queensland","active":true,"usgs":false}],"preferred":false,"id":856080,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Rumpff, Libby","contributorId":197117,"corporation":false,"usgs":false,"family":"Rumpff","given":"Libby","email":"","affiliations":[],"preferred":false,"id":856081,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Runge, Michael C. 0000-0002-8081-536X mrunge@usgs.gov","orcid":"https://orcid.org/0000-0002-8081-536X","contributorId":3358,"corporation":false,"usgs":true,"family":"Runge","given":"Michael","email":"mrunge@usgs.gov","middleInitial":"C.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":856082,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Weiss, Katherine C B","contributorId":298629,"corporation":false,"usgs":false,"family":"Weiss","given":"Katherine","email":"","middleInitial":"C B","affiliations":[{"id":6607,"text":"Arizona State University","active":true,"usgs":false}],"preferred":false,"id":856083,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Wilson, Robyn S.","contributorId":175362,"corporation":false,"usgs":false,"family":"Wilson","given":"Robyn","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":856084,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Zablan, Marilet A.","contributorId":175046,"corporation":false,"usgs":false,"family":"Zablan","given":"Marilet","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":856085,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Gerber, Leah R.","contributorId":147236,"corporation":false,"usgs":false,"family":"Gerber","given":"Leah","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":856086,"contributorType":{"id":1,"text":"Authors"},"rank":18}]}} ,{"id":70246290,"text":"70246290 - 2022 - Use of regional breeding bird surveys to estimate bird populations in Big Thicket National Preserve","interactions":[],"lastModifiedDate":"2023-06-30T11:51:09.714357","indexId":"70246290","displayToPublicDate":"2022-10-04T06:49:09","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5991,"text":"The Southwestern Naturalist","active":true,"publicationSubtype":{"id":10}},"title":"Use of regional breeding bird surveys to estimate bird populations in Big Thicket National Preserve","docAbstract":"

We used data collected during surveys of seven North American Breeding Bird Survey routes in eastern Texas to estimate avian populations within Big Thicket National Preserve. On only 61 of the 350 count locations located along these routes did observers monitor birds within the boundaries of this preserve. On selected routes, we recorded initial bird detections during the 3-min bird count within 1-min time intervals and within two distance classes (≤50 or >50 m). We used these data, combined with data collected using standard Breeding Bird Survey protocols during 2009–2016, to estimate detection probabilities and effective detection radii for commonly detected species. For species often detected in flocks, we estimated these parameters for group detections. From these parameters, we estimated regional densities for 60 species. Because habitat within Big Thicket National Preserve differed from habitat along surveyed routes, for each species we adjusted the projected population estimate to account for the relationship between density of detected birds and habitat descriptors from the National Land Cover database. On the basis of our estimates of regional density of each species, and accounting for differences in habitat availability, we estimated that commonly detected avian species comprises a population of 192,201 breeding birds (95% confidence interval = 144,269–340,790) within Big Thicket National Preserve.

","language":"English","publisher":"BioOne","doi":"10.1894/0038-4909-66.3.240","usgsCitation":"Twedt, D.J., and Shackelford, C.E., 2022, Use of regional breeding bird surveys to estimate bird populations in Big Thicket National Preserve: The Southwestern Naturalist, v. 66, no. 3, p. 240-249, https://doi.org/10.1894/0038-4909-66.3.240.","productDescription":"10 p.","startPage":"240","endPage":"249","ipdsId":"IP-065568","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":418650,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Texas","otherGeospatial":"Big Thicket National Preserve","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -94.4910453710765,\n 30.60117874378041\n ],\n [\n -94.4910453710765,\n 30.35392517388506\n ],\n [\n -94.20415064179676,\n 30.35392517388506\n ],\n [\n -94.20415064179676,\n 30.60117874378041\n ],\n [\n -94.4910453710765,\n 30.60117874378041\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"66","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Twedt, Daniel J. 0000-0003-1223-5045 dtwedt@usgs.gov","orcid":"https://orcid.org/0000-0003-1223-5045","contributorId":398,"corporation":false,"usgs":true,"family":"Twedt","given":"Daniel","email":"dtwedt@usgs.gov","middleInitial":"J.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":876669,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Shackelford, Clifford E.","contributorId":315488,"corporation":false,"usgs":false,"family":"Shackelford","given":"Clifford","email":"","middleInitial":"E.","affiliations":[{"id":68340,"text":"Texas Parks and Wildlife Department, 506 Hayter St., Nacogdoches, Texas 75965","active":true,"usgs":false}],"preferred":false,"id":876670,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70237237,"text":"70237237 - 2022 - Wildfire imagery reduces risk information-seeking among homeowners as property wildfire risk increases","interactions":[],"lastModifiedDate":"2022-10-05T11:43:40.442998","indexId":"70237237","displayToPublicDate":"2022-10-04T06:40:49","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":8956,"text":"Communications Earth & Environment","active":true,"publicationSubtype":{"id":10}},"title":"Wildfire imagery reduces risk information-seeking among homeowners as property wildfire risk increases","docAbstract":"

Negative imagery of destruction may induce or inhibit action to reduce risks from climate-exacerbated hazards, such as wildfires. This has generated conflicting assumptions among experts who communicate with homeowners: half of surveyed wildfire practitioners perceive a lack of expert agreement about the effect of negative imagery (a burning house) on homeowner behavior, yet most believe negative imagery is more engaging. We tested whether this expectation matched homeowner response in the United States. In an online experiment, homeowners who viewed negative imagery reported more negative emotions but the same behavioral intentions compared to those who viewed status-quo landscape photos. In a pre-registered field experiment, homeowners who received a postcard showing negative imagery were equally likely, overall, to visit a wildfire risk webpage as those whose postcard showed a status quo photo. However, the negative imagery decreased webpage visits as homeowners’ wildfire risk increased. These results illustrate the importance of testing assumptions to encourage behavioral adaptation to climate change.

","language":"English","publisher":"Nature","doi":"10.1038/s43247-022-00505-7","usgsCitation":"Byerly Flint, H., Champ, P.A., Meldrum, J., and Brenkert-Smith, H., 2022, Wildfire imagery reduces risk information-seeking among homeowners as property wildfire risk increases: Communications Earth & Environment, v. 3, 229, 8 p., https://doi.org/10.1038/s43247-022-00505-7.","productDescription":"229, 8 p.","ipdsId":"IP-129193","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":446238,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s43247-022-00505-7","text":"Publisher Index Page"},{"id":407950,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"3","noUsgsAuthors":false,"publicationDate":"2022-10-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Byerly Flint, Hilary 0000-0002-7445-2099","orcid":"https://orcid.org/0000-0002-7445-2099","contributorId":297251,"corporation":false,"usgs":false,"family":"Byerly Flint","given":"Hilary","email":"","affiliations":[{"id":36621,"text":"University of Colorado","active":true,"usgs":false}],"preferred":false,"id":853706,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Champ, Patricia A.","contributorId":195486,"corporation":false,"usgs":false,"family":"Champ","given":"Patricia","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":853707,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Meldrum, James R. 0000-0001-5250-3759 jmeldrum@usgs.gov","orcid":"https://orcid.org/0000-0001-5250-3759","contributorId":195484,"corporation":false,"usgs":true,"family":"Meldrum","given":"James","email":"jmeldrum@usgs.gov","middleInitial":"R.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":853708,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brenkert-Smith, Hannah 0000-0001-6117-8863","orcid":"https://orcid.org/0000-0001-6117-8863","contributorId":195485,"corporation":false,"usgs":false,"family":"Brenkert-Smith","given":"Hannah","email":"","affiliations":[],"preferred":false,"id":853709,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70237176,"text":"cir1500 - 2022 - 2022 Joint Agency Commercial Imagery Evaluation—Remote sensing satellite compendium","interactions":[{"subject":{"id":70212975,"text":"cir1468 - 2020 - 2020 Joint Agency Commercial Imagery Evaluation—Remote sensing satellite compendium","indexId":"cir1468","publicationYear":"2020","noYear":false,"displayTitle":"2020 Joint Agency Commercial Imagery Evaluation—Remote Sensing Satellite Compendium","title":"2020 Joint Agency Commercial Imagery Evaluation—Remote sensing satellite compendium"},"predicate":"SUPERSEDED_BY","object":{"id":70237176,"text":"cir1500 - 2022 - 2022 Joint Agency Commercial Imagery Evaluation—Remote sensing satellite compendium","indexId":"cir1500","publicationYear":"2022","noYear":false,"title":"2022 Joint Agency Commercial Imagery Evaluation—Remote sensing satellite compendium"},"id":1}],"lastModifiedDate":"2022-10-04T19:55:21.162292","indexId":"cir1500","displayToPublicDate":"2022-10-03T17:23:03","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":"1500","displayTitle":"2022 Joint Agency Commercial Imagery Evaluation—Remote Sensing Satellite Compendium","title":"2022 Joint Agency Commercial Imagery Evaluation—Remote sensing satellite compendium","docAbstract":"

The Joint Agency Commercial Imagery Evaluation (JACIE) is a collaboration between six Federal agencies that are major users and producers of satellite land remote sensing data. In recent years, the JACIE group has observed ever-increasing numbers of remote sensing satellites being launched. This rapidly growing wave of new systems creates a need for a single reference for land remote sensing satellites that provides basic system specifications and linkage to any JACIE assessment that may have been completed on existing systems. This volume has been assembled by the Requirements, Capabilities, and Analysis for Earth Observation Project under the U.S. Geological Survey National Land Imaging Program as a contribution to the JACIE community. This is the third edition of the JACIE compendium, which is planned to be updated and released annually.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/cir1500","usgsCitation":"Ramaseri Chandra, S.N., Christopherson, J.B., Casey, K.A., Lawson, J., and Sampath, A., 2022, 2022 Joint Agency Commercial Imagery Evaluation—Remote sensing satellite compendium: U.S. Geological Survey Circular 1500, 279 p., https://doi.org/10.3133/cir1500. [Supersedes USGS Circular 1468.]","productDescription":"xiii, 279 p.","numberOfPages":"298","onlineOnly":"N","ipdsId":"IP-139076","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":407832,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/circ/1500/circ1500.pdf","text":"Report","size":"21.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Circular 1500"},{"id":407831,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/circ/1500/coverthb.jpg"}],"contact":"

Director, Earth Resources Observation and Science Center
U.S. Geological Survey
47914 252nd Street
Sioux Falls, SD 57198

Contact Pubs Warehouse

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