{"pageNumber":"151","pageRowStart":"3750","pageSize":"25","recordCount":41054,"records":[{"id":70252806,"text":"70252806 - 2023 - 2021–2022 Statewide Abundance Estimates for the Florida Manatee","interactions":[],"lastModifiedDate":"2024-04-05T14:14:20.517907","indexId":"70252806","displayToPublicDate":"2023-01-01T09:10:24","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":2,"text":"State or Local Government Series"},"seriesTitle":{"id":138,"text":"Technical Report","active":true,"publicationSubtype":{"id":2}},"seriesNumber":"TR-27","title":"2021–2022 Statewide Abundance Estimates for the Florida Manatee","docAbstract":"

Knowing the population size of Florida manatees (Trichechus manatus latirostris) is critical for conservation and management of this threatened species. Martin et al. (2015) and Hostetler et al. (2018) applied statistical models that incorporated multiple data sources to estimate the statewide abundance of manatees from aerial surveys f lown in 2011–2012 and 2015–2016. We conducted additional aerial surveys in 2021–2022 and applied similar models to provide an updated abundance estimate. This report serves as an update to Hostetler et al. (2018), with most of the text and methodology adapted from the previous report, and provides updated population estimates based on the newly available data. We estimate that the number of manatees in Florida in 2021–2022 was 9,790 (95% Bayesian credible interval 8,350–11,730), of which 4,630 (3,960–5,420) were on the west coast of Florida and 5,160 (3,940–6,980) were on the east coast. These estimates and the associated uncertainty, in addition to being of immediate value to wildlife managers, are essential new data for incorporation into integrated population models and population viability analyses. We also provide context for interpreting the new estimates and perspectives for future modeling improvements.

","language":"English","publisher":"Florida Fish and Wildlife Conservation Commission","usgsCitation":"Gowan, T., Edwards, H.H., Krzystan, A.M., Martin, J., and Hostetler, J.A., 2023, 2021–2022 Statewide Abundance Estimates for the Florida Manatee: Technical Report TR-27, 14 p.","productDescription":"14 p.","ipdsId":"IP-153497","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":427511,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":427508,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://myfwc.com/research/publications/technical-reports/"}],"country":"United States","state":"Florida","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"id\":10,\"properties\":{\"name\":\"Florida\",\"nation\":\"USA 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Commission","active":true,"usgs":false}],"preferred":false,"id":898280,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Martin, Julien 0000-0002-7375-129X","orcid":"https://orcid.org/0000-0002-7375-129X","contributorId":218445,"corporation":false,"usgs":true,"family":"Martin","given":"Julien","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":898281,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hostetler, J. A. 0000-0003-3669-1758","orcid":"https://orcid.org/0000-0003-3669-1758","contributorId":11319,"corporation":false,"usgs":true,"family":"Hostetler","given":"J.","middleInitial":"A.","affiliations":[],"preferred":true,"id":898282,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70241524,"text":"70241524 - 2023 - Comprehensive inventory of habitat assessment and evaluation datasets to support Deepwater Horizon mesophotic and deep benthic communities","interactions":[],"lastModifiedDate":"2023-03-22T13:52:48.219679","indexId":"70241524","displayToPublicDate":"2023-01-01T08:44:46","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":13626,"text":"DWH MDBC Data Report","active":true,"publicationSubtype":{"id":1}},"seriesNumber":"DR-23-01","title":"Comprehensive inventory of habitat assessment and evaluation datasets to support Deepwater Horizon mesophotic and deep benthic communities","docAbstract":"This report is part of the NOAA Mesophotic and Deep Benthic Communities (MDBC) Series of \npublications that share the results of work conducted by the Deepwater Horizon MDBC restoration projects.   \n \nThe 2010 Deepwater Horizon oil spill was an unprecedented event. Approximately 3.2 million barrels of oil were released into the deep ocean over nearly three months. The plume of oil moved throughout the water column, formed surface slicks that cumulatively covered an area the size of Virginia, and washed oil onto at least 1,300 miles of shoreline habitats. More than 770 square miles (2,000 square kilometers) of deep benthic habitat surrounding the Deepwater Horizon wellhead and 4-square miles of the Pinnacles mesophotic reef complex, located at the edge of the continental shelf, were injured by the oil spill. \n \nUnder the Oil Pollution Act, state and federal natural resource trustees conducted a Natural Resource Damage Assessment (NRDA). The Trustees assessed damages, quantifying the unprecedented injuries to natural resources and lost services. They also developed a programmatic restoration plan to restore injured resources and compensate the public for lost services. \n \nIn April 2016, a settlement was finalized that included up to $8.8 billion in funding for the Deepwater Horizon Trustees to restore the natural resource injuries caused by the oil spill as described in their programmatic restoration plan, Final Programmatic Damage Assessment and Restoration Plan and Final Programmatic Environmental Impact Statement. The Deepwater Horizon Open Ocean Trustee Implementation Group is responsible for restoring natural resources and their services within the Open Ocean Restoration Area that were injured by the oil spill. The Open Ocean Trustees include NOAA, Department of the Interior, U.S. Environmental Protection Agency, and U.S. Department of Agriculture. \n \nIn 2019, the Open Ocean Trustee Implementation Group committed more than $126 million to \nimplement four restoration projects to address the injury to MDBC. The MDBC projects are: mapping, Ground-truthing, and Predictive Habitat Modeling; Habitat Assessment and Evaluation; Coral Propagation Technique Development; and Active Management and Protection. NOAA and the Department of the Interior are implementing the projects, in cooperation with a range of partners, over eight years. \n \nTogether, the projects take a phased approach to meet the challenges involved in restoring deep-sea habitats. Challenges to restoration include a limited scientific understanding of these communities, limited experience with restoration at the depths at which these communities occur, and remote locations that limit accessibility. \n \nMore information about Deepwater Horizon restoration and the MDBC restoration projects is available at: www.gulfspillrestoration.noaa.gov.","language":"English","publisher":"NOAA","doi":"10.25923/kz7t-4674","usgsCitation":"Bassett, R., Herting, J., Frometa, J., Sharuga, S.M., Howell, J., Siceloff, L., Bourque, J.R., Cromwell, M., Francis, K., Clark, R., Demopoulos, A., David, A., Benson, K., and Harter, S.L., 2023, Comprehensive inventory of habitat assessment and evaluation datasets to support Deepwater Horizon mesophotic and deep benthic communities: DWH MDBC Data Report DR-23-01, 68 p., https://doi.org/10.25923/kz7t-4674.","productDescription":"68 p.","ipdsId":"IP-143985","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":414549,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Gulf of Mexico","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -91.4738402663695,\n 27.73976270326594\n ],\n [\n -88.43668753646247,\n 28.377487555215865\n ],\n [\n -87.08865291012629,\n 29.215833830999557\n ],\n [\n -87.79750143247816,\n 30.10517365534068\n ],\n [\n -88.52009799635897,\n 30.199023526767235\n ],\n [\n -89.11487834086316,\n 30.0687140895985\n ],\n [\n -89.42838914695855,\n 29.569401260101472\n ],\n [\n -89.06685117410953,\n 29.1845830007817\n ],\n [\n -89.02359871978788,\n 28.964173359471857\n ],\n [\n -89.57102082101116,\n 29.108470712158947\n ],\n [\n -91.61652997779979,\n 28.32580643304547\n ],\n [\n -92.09126902602307,\n 28.00138024651494\n 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Janessy","contributorId":200722,"corporation":false,"usgs":false,"family":"Frometa","given":"Janessy","email":"","affiliations":[],"preferred":false,"id":867104,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sharuga, Stephanie M.","contributorId":301148,"corporation":false,"usgs":false,"family":"Sharuga","given":"Stephanie","email":"","middleInitial":"M.","affiliations":[{"id":65319,"text":"Genwest Systems","active":true,"usgs":false}],"preferred":false,"id":867105,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Howell, Jacob","contributorId":218500,"corporation":false,"usgs":false,"family":"Howell","given":"Jacob","affiliations":[{"id":39855,"text":"NOAA contractor","active":true,"usgs":false}],"preferred":false,"id":867106,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Siceloff, Laughlin","contributorId":303301,"corporation":false,"usgs":false,"family":"Siceloff","given":"Laughlin","email":"","affiliations":[{"id":65431,"text":"CSS Inc, under contract to NOAA/NOS","active":true,"usgs":false}],"preferred":false,"id":867107,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bourque, Jill R. 0000-0003-3809-2601","orcid":"https://orcid.org/0000-0003-3809-2601","contributorId":215719,"corporation":false,"usgs":true,"family":"Bourque","given":"Jill","middleInitial":"R.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":867108,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Cromwell, Megan","contributorId":303303,"corporation":false,"usgs":false,"family":"Cromwell","given":"Megan","email":"","affiliations":[{"id":65754,"text":"NOAA/NCEI","active":true,"usgs":false}],"preferred":false,"id":867109,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Francis, Kirstie","contributorId":303304,"corporation":false,"usgs":false,"family":"Francis","given":"Kirstie","email":"","affiliations":[{"id":65754,"text":"NOAA/NCEI","active":true,"usgs":false}],"preferred":false,"id":867110,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Clark, Randy","contributorId":218497,"corporation":false,"usgs":false,"family":"Clark","given":"Randy","email":"","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":867111,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Demopoulos, Amanda 0000-0003-2096-4694","orcid":"https://orcid.org/0000-0003-2096-4694","contributorId":222192,"corporation":false,"usgs":true,"family":"Demopoulos","given":"Amanda","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":867112,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"David, Andy","contributorId":302199,"corporation":false,"usgs":false,"family":"David","given":"Andy","email":"","affiliations":[{"id":62397,"text":"NOAA/NMFS","active":true,"usgs":false}],"preferred":false,"id":867113,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Benson, Kristopher","contributorId":302200,"corporation":false,"usgs":false,"family":"Benson","given":"Kristopher","email":"","affiliations":[{"id":62397,"text":"NOAA/NMFS","active":true,"usgs":false}],"preferred":false,"id":867114,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Harter, Stacey L.","contributorId":302195,"corporation":false,"usgs":false,"family":"Harter","given":"Stacey","email":"","middleInitial":"L.","affiliations":[{"id":62397,"text":"NOAA/NMFS","active":true,"usgs":false}],"preferred":false,"id":867115,"contributorType":{"id":1,"text":"Authors"},"rank":14}]}} ,{"id":70240778,"text":"70240778 - 2023 - Skeletal indicators of locomotor adaptations in shrews","interactions":[],"lastModifiedDate":"2023-02-22T14:24:43.331761","indexId":"70240778","displayToPublicDate":"2023-01-01T08:21:19","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":13293,"text":"Therya","active":true,"publicationSubtype":{"id":10}},"title":"Skeletal indicators of locomotor adaptations in shrews","docAbstract":"

The Soricidae (Mammalia: Eulypotyphla) comprises more than 450 species inhabiting a variety of habitats on five continents.  As a family, shrews employ a variety of locomotor modes that incorporate ambulatory, fossorial, aquatic, and scansorial behaviors, illustrating an ability to exploit a variety of natural substrates and their associated resources.  In this study, the association of skeletal morphology and three of the dominant locomotor modes in the family—ambulatory, semi-fossorial, and semi-aquatic behaviors—was investigated in up to 52 species of 12 genera representing all three subfamilies of Soricidae.  From skeletal measures, 34 morphological indices were calculated, most of which have been used previously to characterize substrate use among shrews, rodents, and other mammals, and analyzed for their individual effectiveness for discriminating the three locomotory modes.  To assess their effectiveness in combination, subsets of locomotor indices were analyzed using 1) mean percentile ranks, 2) the first principal component from principal components analysis, and 3) plots and classifications from discriminant function analyses.  In general, the three methods effectively identified and grouped the three locomotor modes and identified smaller subsets.  Additional analyses were then used to classify the locomotor behaviors of five species whose locomotor modes were unknown or ambiguous.  The analyses reinforce and broaden the scope of a previously identified observation of the wide range of grades of morphological variation that may permit an equally diverse range of locomotor abilities among the Soricidae.

","language":"English","publisher":"Asociación Mexicana de Mastozoología A. C.","doi":"10.12933/therya-23-2218","usgsCitation":"Woodman, N., 2023, Skeletal indicators of locomotor adaptations in shrews: Therya, v. 14, no. 1, p. 15-37, https://doi.org/10.12933/therya-23-2218.","productDescription":"23 p.","startPage":"15","endPage":"37","ipdsId":"IP-147190","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":444989,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.12933/therya-23-2218","text":"Publisher Index Page"},{"id":413281,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"14","issue":"1","noUsgsAuthors":false,"publicationDate":"2023-01-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Woodman, Neal 0000-0003-2689-7373 nwoodman@usgs.gov","orcid":"https://orcid.org/0000-0003-2689-7373","contributorId":3547,"corporation":false,"usgs":true,"family":"Woodman","given":"Neal","email":"nwoodman@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":864803,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70239356,"text":"70239356 - 2023 - Improving the operational simplified surface energy balance evapotranspiration model using the forcing and normalizing operation","interactions":[],"lastModifiedDate":"2023-01-10T13:18:25.464452","indexId":"70239356","displayToPublicDate":"2023-01-01T07:17:05","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3250,"text":"Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Improving the operational simplified surface energy balance evapotranspiration model using the forcing and normalizing operation","docAbstract":"
Actual evapotranspiration modeling is providing useful information for researchers and resource managers in agriculture and water resources around the world. The performance of models depends on the accuracy of forcing inputs and model parameters. We developed an improved approach to the parameterization of the Operational Simplified Surface Energy Balance (SSEBop) model using the Forcing and Normalizing Operation (FANO). SSEBop has two key model parameters that define the model boundary conditions. The FANO algorithm computes the wet-bulb boundary condition using a linear FANO Equation relating surface temperature, surface psychrometric constant, and the Normalized Difference Vegetation Index (NDVI). The FANO parameterization was implemented on two computing platforms using Landsat and gridded meteorological datasets: (1) Google Earth Engine (GEE) and (2) Earth Resources Observation and Science (EROS) Center Science Processing Architecture (ESPA). Evaluation was conducted by comparing modeled actual evapotranspiration (ETa) estimates with AmeriFlux eddy covariance (EC) and water balance ETa from level-8 Hydrologic Unit Code sub-basins in the conterminous United States. FANO brought substantial improvements in model accuracy and operational implementation. Compared to the earlier version (v0.1.7), SSEBop FANO (v0.2.6) reduced grassland bias from 47% to −2% while maintaining comparable bias for croplands (11% versus −7%) against EC data. A water balance-based ETa bias evaluation showed an overall improvement from 7% to −1%. Climatology versus annual gridded reference evapotranspiration (ETr) produced comparable ETa results, justifying the use of climatology ETr for the global SSEBop Landsat ETa that is accessible through the ESPA website. Besides improvements in model accuracy, SSEBop FANO increases the spatiotemporal coverage of ET modeling due to the elimination of high NDVI requirements for model parameterization. Because of the existence of potential biases from forcing inputs and model parameters, continued evaluation and bias corrections are necessary to improve the absolute magnitude of ETa for localized water budget applications.
","language":"English","publisher":"MDPI","doi":"10.3390/rs15010260","usgsCitation":"Senay, G.B., Parrish, G.E., Schauer, M., Friedrichs, M., Khand, K., Boiko, O., Kagone, S., Dittmeier, R., Arab, S., and Ji, L., 2023, Improving the operational simplified surface energy balance evapotranspiration model using the forcing and normalizing operation: Remote Sensing, v. 15, no. 1, 260, 25 p., https://doi.org/10.3390/rs15010260.","productDescription":"260, 25 p.","ipdsId":"IP-146439","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":444995,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs15010260","text":"Publisher Index Page"},{"id":435525,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9NKWT3D","text":"USGS data release","linkHelpText":"Forcing and Normalizing Operation (FANO) method for the Operational Simplified Surface Energy Balance (SSEBop) ET model"},{"id":411621,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"15","issue":"1","noUsgsAuthors":false,"publicationDate":"2023-01-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Senay, Gabriel B. 0000-0002-8810-8539 senay@usgs.gov","orcid":"https://orcid.org/0000-0002-8810-8539","contributorId":3114,"corporation":false,"usgs":true,"family":"Senay","given":"Gabriel","email":"senay@usgs.gov","middleInitial":"B.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":861239,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Parrish, Gabriel Edwin Lee 0000-0003-4078-3516","orcid":"https://orcid.org/0000-0003-4078-3516","contributorId":267751,"corporation":false,"usgs":false,"family":"Parrish","given":"Gabriel","email":"","middleInitial":"Edwin Lee","affiliations":[{"id":55490,"text":"Innovate! Inc., Contractor to the USGS EROS Center","active":true,"usgs":false}],"preferred":false,"id":861240,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schauer, Matthew 0000-0002-4198-3379","orcid":"https://orcid.org/0000-0002-4198-3379","contributorId":181608,"corporation":false,"usgs":false,"family":"Schauer","given":"Matthew","affiliations":[],"preferred":false,"id":861241,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Friedrichs, MacKenzie 0000-0002-9602-321X","orcid":"https://orcid.org/0000-0002-9602-321X","contributorId":199093,"corporation":false,"usgs":false,"family":"Friedrichs","given":"MacKenzie","affiliations":[],"preferred":false,"id":861242,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Khand, Kul Bikram 0000-0002-1593-1508","orcid":"https://orcid.org/0000-0002-1593-1508","contributorId":259185,"corporation":false,"usgs":false,"family":"Khand","given":"Kul Bikram","affiliations":[{"id":52326,"text":"AFDS, Contractor to USGS ERSOS Center","active":true,"usgs":false}],"preferred":false,"id":861243,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Boiko, Olena 0000-0002-2007-7852","orcid":"https://orcid.org/0000-0002-2007-7852","contributorId":272079,"corporation":false,"usgs":false,"family":"Boiko","given":"Olena","email":"","affiliations":[{"id":56343,"text":"KBR, Contractor to USGS Earth Resources Observation and Science Center","active":true,"usgs":false}],"preferred":false,"id":861244,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kagone, Stefanie 0000-0002-2979-4655","orcid":"https://orcid.org/0000-0002-2979-4655","contributorId":199091,"corporation":false,"usgs":false,"family":"Kagone","given":"Stefanie","affiliations":[],"preferred":false,"id":861245,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Dittmeier, Ray","contributorId":299963,"corporation":false,"usgs":false,"family":"Dittmeier","given":"Ray","email":"","affiliations":[{"id":61731,"text":"KBR","active":true,"usgs":false}],"preferred":false,"id":861246,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Arab, Saeed 0000-0003-1602-8801","orcid":"https://orcid.org/0000-0003-1602-8801","contributorId":299964,"corporation":false,"usgs":false,"family":"Arab","given":"Saeed","email":"","affiliations":[{"id":61731,"text":"KBR","active":true,"usgs":false}],"preferred":false,"id":861247,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Ji, Lei 0000-0002-6133-1036","orcid":"https://orcid.org/0000-0002-6133-1036","contributorId":272078,"corporation":false,"usgs":false,"family":"Ji","given":"Lei","affiliations":[{"id":56342,"text":"ASRC Federal Data Solutions, Contractor to USGS Earth Resources Observation and Science Center","active":true,"usgs":false}],"preferred":false,"id":861248,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70229507,"text":"70229507 - 2023 - Vulnerable waters are essential to watershed resilience","interactions":[],"lastModifiedDate":"2024-05-20T13:45:00.529401","indexId":"70229507","displayToPublicDate":"2023-01-01T06:36:18","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1478,"text":"Ecosystems","active":true,"publicationSubtype":{"id":10}},"title":"Vulnerable waters are essential to watershed resilience","docAbstract":"

Watershed resilience is the ability of a watershed to maintain its characteristic system state while concurrently resisting, adapting to, and reorganizing after hydrological (for example, drought, flooding) or biogeochemical (for example, excessive nutrient) disturbances. Vulnerable waters include non-floodplain wetlands and headwater streams, abundant watershed components representing the most distal extent of the freshwater aquatic network. Vulnerable waters are hydrologically dynamic and biogeochemically reactive aquatic systems, storing, processing, and releasing water and entrained (that is, dissolved and particulate) materials along expanding and contracting aquatic networks. The hydrological and biogeochemical functions emerging from these processes affect the magnitude, frequency, timing, duration, storage, and rate of change of material and energy fluxes among watershed components and to downstream waters, thereby maintaining watershed states and imparting watershed resilience. We present here a conceptual framework for understanding how vulnerable waters confer watershed resilience. We demonstrate how individual and cumulative vulnerable-water modifications (for example, reduced extent, altered connectivity) affect watershed-scale hydrological and biogeochemical disturbance response and recovery, which decreases watershed resilience and can trigger transitions across thresholds to alternative watershed states (for example, states conducive to increased flood frequency or nutrient concentrations). We subsequently describe how resilient watersheds require spatial heterogeneity and temporal variability in hydrological and biogeochemical interactions between terrestrial systems and down-gradient waters, which necessitates attention to the conservation and restoration of vulnerable waters and their downstream connectivity gradients. To conclude, we provide actionable principles for resilient watersheds and articulate research needs to further watershed resilience science and vulnerable-water management.

","language":"English","publisher":"Springer","doi":"10.1007/s10021-021-00737-2","usgsCitation":"Lane, C., Creed, I., Golden, H.E., Leibowitz, S.G., Mushet, D., Rains, M.C., Wu, Q., D’Amico, E., Alexander, L., Ali, G.A., Basu, N.B., Bennett, M.G., Christensen, J.R., Cohen, M.J., Covino, T.P., DeVries, B., Hill, R.A., Jencso, K.G., Lang, M.W., McLaughlin, D.L., Rosenberry, D., Rover, J., and Vanderhoof, M.K., 2023, Vulnerable waters are essential to watershed resilience: Ecosystems, v. 26, p. 1-28, https://doi.org/10.1007/s10021-021-00737-2.","productDescription":"28 p.","startPage":"1","endPage":"28","ipdsId":"IP-126168","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":444998,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10021-021-00737-2","text":"Publisher Index Page"},{"id":396895,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"26","noUsgsAuthors":false,"publicationDate":"2022-02-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Lane, Charles R.","contributorId":138991,"corporation":false,"usgs":false,"family":"Lane","given":"Charles R.","affiliations":[{"id":6914,"text":"U.S. Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":837631,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Creed, Irena F.","contributorId":81209,"corporation":false,"usgs":false,"family":"Creed","given":"Irena F.","affiliations":[{"id":27655,"text":"Department of Biology, University of Western Ontario, London, ON Canada","active":true,"usgs":false}],"preferred":false,"id":837632,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Golden, Heather E.","contributorId":202423,"corporation":false,"usgs":false,"family":"Golden","given":"Heather","email":"","middleInitial":"E.","affiliations":[{"id":36429,"text":"USEPA ORD","active":true,"usgs":false}],"preferred":false,"id":837633,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Leibowitz, Scott G.","contributorId":156432,"corporation":false,"usgs":false,"family":"Leibowitz","given":"Scott","email":"","middleInitial":"G.","affiliations":[{"id":6914,"text":"U.S. Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":837634,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mushet, David M. 0000-0002-5910-2744","orcid":"https://orcid.org/0000-0002-5910-2744","contributorId":248468,"corporation":false,"usgs":true,"family":"Mushet","given":"David M.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":837635,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Rains, Mark C.","contributorId":138983,"corporation":false,"usgs":false,"family":"Rains","given":"Mark","email":"","middleInitial":"C.","affiliations":[{"id":12607,"text":"Univ of South florida, School of Geosciences, Tampa FL","active":true,"usgs":false}],"preferred":false,"id":837636,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Wu, Qiusheng","contributorId":208272,"corporation":false,"usgs":false,"family":"Wu","given":"Qiusheng","email":"","affiliations":[{"id":37769,"text":"Binghamton University","active":true,"usgs":false}],"preferred":false,"id":837637,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"D’Amico, 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B.","contributorId":288293,"corporation":false,"usgs":false,"family":"Basu","given":"Nandita","email":"","middleInitial":"B.","affiliations":[{"id":6655,"text":"University of Waterloo","active":true,"usgs":false}],"preferred":false,"id":837641,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Bennett, Micah G.","contributorId":288294,"corporation":false,"usgs":false,"family":"Bennett","given":"Micah","email":"","middleInitial":"G.","affiliations":[{"id":37230,"text":"EPA","active":true,"usgs":false}],"preferred":false,"id":837642,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Christensen, Jay R.","contributorId":179361,"corporation":false,"usgs":false,"family":"Christensen","given":"Jay","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":837643,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Cohen, Matthew J.","contributorId":138990,"corporation":false,"usgs":false,"family":"Cohen","given":"Matthew","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":837644,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Covino, Tim P.","contributorId":288295,"corporation":false,"usgs":false,"family":"Covino","given":"Tim","email":"","middleInitial":"P.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":837645,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"DeVries, Ben 0000-0003-2136-3401","orcid":"https://orcid.org/0000-0003-2136-3401","contributorId":198971,"corporation":false,"usgs":false,"family":"DeVries","given":"Ben","email":"","affiliations":[{"id":7261,"text":"Department of Geographical Sciences, University of Maryland, College Park, MD, 20742","active":true,"usgs":false}],"preferred":false,"id":837646,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Hill, Ryan A.","contributorId":198332,"corporation":false,"usgs":false,"family":"Hill","given":"Ryan","email":"","middleInitial":"A.","affiliations":[{"id":6682,"text":"Utah State University","active":true,"usgs":false}],"preferred":false,"id":837647,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Jencso, Kelsey G.","contributorId":32375,"corporation":false,"usgs":false,"family":"Jencso","given":"Kelsey","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":837648,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Lang, Megan W.","contributorId":131150,"corporation":false,"usgs":false,"family":"Lang","given":"Megan","email":"","middleInitial":"W.","affiliations":[{"id":7264,"text":"USDA Forest Service, Northern Research Station, Beltsville, MD 20705","active":true,"usgs":false}],"preferred":false,"id":837649,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"McLaughlin, Daniel L.","contributorId":156435,"corporation":false,"usgs":false,"family":"McLaughlin","given":"Daniel","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":837650,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"Rosenberry, Donald O. 0000-0003-0681-5641","orcid":"https://orcid.org/0000-0003-0681-5641","contributorId":257638,"corporation":false,"usgs":true,"family":"Rosenberry","given":"Donald O.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":837651,"contributorType":{"id":1,"text":"Authors"},"rank":21},{"text":"Rover, Jennifer 0000-0002-3437-4030","orcid":"https://orcid.org/0000-0002-3437-4030","contributorId":211850,"corporation":false,"usgs":true,"family":"Rover","given":"Jennifer","email":"","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":837652,"contributorType":{"id":1,"text":"Authors"},"rank":22},{"text":"Vanderhoof, Melanie K. 0000-0002-0101-5533 mvanderhoof@usgs.gov","orcid":"https://orcid.org/0000-0002-0101-5533","contributorId":168395,"corporation":false,"usgs":true,"family":"Vanderhoof","given":"Melanie","email":"mvanderhoof@usgs.gov","middleInitial":"K.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":837653,"contributorType":{"id":1,"text":"Authors"},"rank":23}]}} ,{"id":70248892,"text":"70248892 - 2023 - Causality-informed Bayesian inference for rapid seismic ground failure and building damage estimation","interactions":[],"lastModifiedDate":"2024-02-29T15:59:09.868044","indexId":"70248892","displayToPublicDate":"2022-12-31T09:57:57","publicationYear":"2023","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Causality-informed Bayesian inference for rapid seismic ground failure and building damage estimation","docAbstract":"Rapid and accurate estimates of seismic ground failure and building damage are beneficial to efficient emergency response and post-earthquake recovery. Traditional approaches, such as physical and geospatial models, have poor accuracy and resolution due to large uncertainties and the limited availability of informing geospatial layers. The introduction of remote sensing techniques has shown potential in providing supplementary information for rapid hazard estimation by analyzing earthquake-induced correlation changes between pre- and post-event satellite images. However, the changes in satellite images are the result of overlapping ground failure, building damage, and environmental noise, making it challenging to categorize and estimate different seismic hazards and impacts directly from satellite images.Here we design a novel causality-informed Bayesian network that continuously updates seismic ground failure and building damage estimates from satellite images by modeling the physical interdependencies between geospatial features, ground failure, building footprints, building damage, and satellite images. The incorporation of physical interdependencies allows an effective fusion of physical models and rich but noisy information from remote sensing observations and reduces bias and uncertainties in estimations. Our experiments show that integrating satellite images through our Bayesian network improves the accuracy of seismic ground failure and building damage estimations.","conferenceTitle":"12th National Conference on Earthquake Engineering","conferenceDate":"June 27-July 1, 2022","conferenceLocation":"Salt Lake City, UT","language":"English","publisher":"Earthquake Engineering Research Institute","usgsCitation":"Wald, D.J., Xu, S., Dimasaka, J., and Noh, H., 2023, Causality-informed Bayesian inference for rapid seismic ground failure and building damage estimation, 12th National Conference on Earthquake Engineering, Salt Lake City, UT, June 27-July 1, 2022, 5 p.","productDescription":"5 p.","ipdsId":"IP-134888","costCenters":[{"id":78686,"text":"Geologic Hazards Science Center - Seismology / Geomagnetism","active":true,"usgs":true}],"links":[{"id":426129,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":421114,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://12ncee.org/program/proceedings"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Wald, David J. 0000-0002-1454-4514 wald@usgs.gov","orcid":"https://orcid.org/0000-0002-1454-4514","contributorId":795,"corporation":false,"usgs":true,"family":"Wald","given":"David","email":"wald@usgs.gov","middleInitial":"J.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":884115,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Xu, Susu","contributorId":300127,"corporation":false,"usgs":false,"family":"Xu","given":"Susu","email":"","affiliations":[{"id":65025,"text":"Stony Brook University, NY, USA","active":true,"usgs":false}],"preferred":false,"id":884116,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dimasaka, J.","contributorId":330154,"corporation":false,"usgs":false,"family":"Dimasaka","given":"J.","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":884117,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Noh, H.","contributorId":330155,"corporation":false,"usgs":false,"family":"Noh","given":"H.","email":"","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":884118,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70254987,"text":"70254987 - 2023 - Relative-condition parameters for fishes of Montana, USA","interactions":[],"lastModifiedDate":"2024-06-11T14:47:25.713532","indexId":"70254987","displayToPublicDate":"2022-12-31T09:43:20","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":6476,"text":"Fishes","active":true,"publicationSubtype":{"id":10}},"title":"Relative-condition parameters for fishes of Montana, USA","docAbstract":"

Body condition indices are commonly used in the management of fish populations and are a surrogate to physiological attributes such as tissue-energy reserves. Relative condition factor (Kn) describes the condition of species relative to populations in a geographic area. We developed models to allow for the calculation of Kn in Montana, USA by using the weight–length data collected by Montana Fish, Wildlife & Parks. We generated log10weight–log10length relationships to obtain Montana specific parameter estimates for relative condition equations (W′) for 51 species and three subspecies. We developed separate models by water type (e.g., lotic and lentic) and sex for five species due to varying growth based on sexual dimorphism and varying ecosystem types. Relative condition offers the advantage of describing body condition relative to species in Montana, provides a condition index for species that do not have standard-weight models developed for relative weight (Wr), and affords more information for the global database on weight–length relationships of fishes.

","language":"English","publisher":"MDPI","doi":"10.3390/fishes8010028","usgsCitation":"Eckelbecker, R.W., Heili, N.M., Guy, C.S., and Schmetterling, D.A., 2023, Relative-condition parameters for fishes of Montana, USA: Fishes, v. 8, no. 1, 28, 8 p., https://doi.org/10.3390/fishes8010028.","productDescription":"28, 8 p.","ipdsId":"IP-139822","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":445003,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/fishes8010028","text":"Publisher Index Page"},{"id":429875,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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\"}}]}","volume":"8","issue":"1","noUsgsAuthors":false,"publicationDate":"2022-12-31","publicationStatus":"PW","contributors":{"authors":[{"text":"Eckelbecker, Robert W.","contributorId":338225,"corporation":false,"usgs":false,"family":"Eckelbecker","given":"Robert","email":"","middleInitial":"W.","affiliations":[{"id":36555,"text":"Montana State University","active":true,"usgs":false}],"preferred":false,"id":903026,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Heili, Nathaniel M.","contributorId":338227,"corporation":false,"usgs":false,"family":"Heili","given":"Nathaniel","email":"","middleInitial":"M.","affiliations":[{"id":36555,"text":"Montana State University","active":true,"usgs":false}],"preferred":false,"id":903027,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"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":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":5062,"text":"Office of the Chief Scientist for Ecosystems","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":903028,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schmetterling, David A.","contributorId":338230,"corporation":false,"usgs":false,"family":"Schmetterling","given":"David","email":"","middleInitial":"A.","affiliations":[{"id":52338,"text":"Montana Fish, Wildlife & Parks","active":true,"usgs":false}],"preferred":false,"id":903029,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70239219,"text":"70239219 - 2023 - Assessment of cropland inundation due to the operation of the Reelfoot Lake spillway in West Tennessee","interactions":[],"lastModifiedDate":"2023-08-07T16:55:22.918741","indexId":"70239219","displayToPublicDate":"2022-12-30T06:51:42","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2529,"text":"Journal of the American Water Resources Association","active":true,"publicationSubtype":{"id":10}},"title":"Assessment of cropland inundation due to the operation of the Reelfoot Lake spillway in West Tennessee","docAbstract":"

Running Reelfoot Bayou (RRB) is the outlet canal of Reelfoot Lake, the largest natural lake in Tennessee. RRB is not able to contain discharge from Reelfoot Lake greater than the bankfull discharge of 28 m3/s (1000 ft3/s), which typically occurs at the beginning of the growing season (April–June). Historically, the planting of crops has been delayed until flooding subsides and cropland has drained. The objective of this study is a preliminary quantification of cropland inundation to determine its spatial distribution in the RRB floodplain. Inundated croplands in the RRB floodplain were delineated over a range of spillway discharges from 2 to 57 m3/s (70–2000 ft3/s), using one-dimensional–two-dimensional hydrodynamic modeling and multispectral satellite images (Landsat 8 and Sentinel-2). The composite maps made by combining the simulated and image-derived flood maps were overlaid on the United States Department of Agriculture CropScape layer to determine the inundation of individual summer crops during the growing season. About 25% of the inundated croplands are flooded at discharges of RRB less than 28 m3/s, implying wetland hydrology. The results of this analysis can be used to inform operational management of the Reelfoot Lake spillway.

","language":"English","publisher":"Wiley","doi":"10.1111/1752-1688.13092","usgsCitation":"Bhuyian, N., Lahiri, C., Diehl, T.H., and Heal, E., 2023, Assessment of cropland inundation due to the operation of the Reelfoot Lake spillway in West Tennessee: Journal of the American Water Resources Association, v. 59, no. 4, p. 855-873, https://doi.org/10.1111/1752-1688.13092.","productDescription":"19 p.","startPage":"855","endPage":"873","ipdsId":"IP-124997","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":445008,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/1752-1688.13092","text":"Publisher Index Page"},{"id":411335,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Tennessee","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -89.58348471060779,\n 36.42528433341498\n ],\n [\n -89.58348471060779,\n 36.07800148864851\n ],\n [\n -89.2636166393048,\n 36.07800148864851\n ],\n [\n -89.2636166393048,\n 36.42528433341498\n ],\n [\n -89.58348471060779,\n 36.42528433341498\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"59","issue":"4","noUsgsAuthors":false,"publicationDate":"2022-12-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Bhuyian, N.M. 0000-0001-8101-8453","orcid":"https://orcid.org/0000-0001-8101-8453","contributorId":300553,"corporation":false,"usgs":false,"family":"Bhuyian","given":"N.M.","email":"","affiliations":[{"id":65197,"text":"Environmental Consultant 3, West Tennessee River Basin Authority","active":true,"usgs":false}],"preferred":false,"id":860798,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lahiri, Chayan 0000-0002-7454-4196","orcid":"https://orcid.org/0000-0002-7454-4196","contributorId":300554,"corporation":false,"usgs":false,"family":"Lahiri","given":"Chayan","email":"","affiliations":[{"id":65199,"text":"Assistant Professor, Department of Biology and Geosciences, Adams State University","active":true,"usgs":false}],"preferred":false,"id":860799,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Diehl, Timothy H. 0000-0001-9691-2212 thdiehl@usgs.gov","orcid":"https://orcid.org/0000-0001-9691-2212","contributorId":546,"corporation":false,"usgs":true,"family":"Diehl","given":"Timothy","email":"thdiehl@usgs.gov","middleInitial":"H.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":581,"text":"Tennessee Water Science Center","active":true,"usgs":true}],"preferred":true,"id":860800,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Heal, Elizabeth 0000-0002-1196-4708 eheal@usgs.gov","orcid":"https://orcid.org/0000-0002-1196-4708","contributorId":177003,"corporation":false,"usgs":true,"family":"Heal","given":"Elizabeth","email":"eheal@usgs.gov","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":860801,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70252813,"text":"70252813 - 2023 - An integral projection model for gizzard shad (Dorosoma cepedianum) utilizing density-dependent age-0 survival","interactions":[],"lastModifiedDate":"2024-04-08T23:52:55.748529","indexId":"70252813","displayToPublicDate":"2022-12-29T11:02:44","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1458,"text":"Ecological Modelling","active":true,"publicationSubtype":{"id":10}},"displayTitle":"An integral projection model for gizzard shad (Dorosoma cepedianum ) utilizing density-dependent age-0 survival","title":"An integral projection model for gizzard shad (Dorosoma cepedianum) utilizing density-dependent age-0 survival","docAbstract":"

Gizzard shad (Dorosoma cepedianum) is a common freshwater fish species found throughout the central and eastern portions of North America. Within these regions, gizzard shad play several critical roles in the freshwater community such as serving as prey for other fish species and translocating nutrients from substrates into the water column. Because of this, it is important to understand gizzard shad population dynamics. Here, we introduce an integral projection model (IPM) for gizzard shad that incorporates empirical information from sources including Long Term Resource Monitoring (LTRM) upper Mississippi River restoration data. IPMs are a generalization of stage-based, matrix population models that have been used to describe a wide range of organisms, and as such are a natural choice for gizzard shad because many aspects of their life cycle have been studied. We tested model outputs against empirical patterns reported for gizzard shad from a different location along the Illinois River (La Grange Reach). Results of our work indicate that our model could serve as an important tool for predicting patterns within gizzard shad populations. 

","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolmodel.2022.110260","usgsCitation":"Peirce, J.P., Sandland, G., Bennie, B., and Erickson, R.A., 2023, An integral projection model for gizzard shad (Dorosoma cepedianum) utilizing density-dependent age-0 survival: Ecological Modelling, v. 477, 110260, 7 p., https://doi.org/10.1016/j.ecolmodel.2022.110260.","productDescription":"110260, 7 p.","ipdsId":"IP-138963","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":445013,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecolmodel.2022.110260","text":"Publisher Index Page"},{"id":427558,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"477","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Peirce, James P 0000-0002-7147-3695","orcid":"https://orcid.org/0000-0002-7147-3695","contributorId":316559,"corporation":false,"usgs":false,"family":"Peirce","given":"James","email":"","middleInitial":"P","affiliations":[{"id":47908,"text":"University of Wisconsin - La Crosse","active":true,"usgs":false}],"preferred":false,"id":898309,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sandland, Gregory","contributorId":332579,"corporation":false,"usgs":false,"family":"Sandland","given":"Gregory","email":"","affiliations":[{"id":12793,"text":"University of Wisconsin-La Crosse","active":true,"usgs":false}],"preferred":false,"id":898310,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bennie, Barb","contributorId":244792,"corporation":false,"usgs":false,"family":"Bennie","given":"Barb","email":"","affiliations":[{"id":48977,"text":"UW-La Crosse","active":true,"usgs":false}],"preferred":false,"id":898311,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Erickson, Richard A. 0000-0003-4649-482X rerickson@usgs.gov","orcid":"https://orcid.org/0000-0003-4649-482X","contributorId":5455,"corporation":false,"usgs":true,"family":"Erickson","given":"Richard","email":"rerickson@usgs.gov","middleInitial":"A.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":898312,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70239211,"text":"70239211 - 2023 - Long-term monitoring in transition: Resolving spatial mismatch and integrating multistate occupancy data","interactions":[],"lastModifiedDate":"2023-01-04T13:31:11.765279","indexId":"70239211","displayToPublicDate":"2022-12-29T07:29:38","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1456,"text":"Ecological Indicators","active":true,"publicationSubtype":{"id":10}},"title":"Long-term monitoring in transition: Resolving spatial mismatch and integrating multistate occupancy data","docAbstract":"

The success of long-term wildlife monitoring programs can be influenced by many factors and study designs often represent compromises between spatial scales and costs. Adaptive monitoring programs can iteratively manage this tension by adopting new cost-efficient technologies, which can provide projects the opportunity to reallocate costs to address new hypotheses, adapt to changing ecological conditions, or adjust sampling scale or resolution. If there is interest in longer time series of monitoring data, methodological transitions may necessitate integrated models to link newer data with historical data. However, data integration can be difficult if spatial or temporal scales are mismatched. Here, we develop an integrated multistate site-occupancy model and resolve sample unit spatial mismatch to link datasets from two northern spotted owl (Strix occidentalis caurina) monitoring schemes that broadly overlapped during a methodological transition. The first dataset was obtained from a decades-long spotted owl monitoring program using call-playback and mark-resight surveys on historical territories of varying size and shape. This monitoring program has recently transitioned to passive acoustic monitoring of randomly selected 5-km2 hexagons over larger spatial extents. Both monitoring datasets overlapped with areas in which barred owl (Strix varia), an invasive competitor that has played an important role in northern spotted owl declines, were being removed experimentally. Reconciling spatial mismatch substantially increased the representation of the call-playback dataset and integrating the two datasets increased precision of spotted owl use and paired occupancy estimates relative to single dataset estimates. Estimates of spotted owl pair occupancy across the study area were lower than previous territory-based estimates based on call-playback surveys. Our integrated model further showed that a concurrent barred owl removal experiment increased landscape use and site occupancy by pairs of spotted owls. Our empirical application of an integrated modelling approach demonstrates a useful analytical framework for long-term monitoring efforts undergoing methodological transitions (e.g. mark-recapture to non-invasive population monitoring). This framework allows monitoring programs to maintain continuity of monitoring objectives across methodological transitions, rigorously incorporate previous findings, and adaptively respond to changing ecological conditions.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolind.2022.109815","usgsCitation":"Weldy, M.J., Lesmeister, D., Yackulic, C., Appel, C., McCafferty, C., and Wiens, D., 2023, Long-term monitoring in transition: Resolving spatial mismatch and integrating multistate occupancy data: Ecological Indicators, v. 146, 109815, 12 p., https://doi.org/10.1016/j.ecolind.2022.109815.","productDescription":"109815, 12 p.","ipdsId":"IP-141142","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":445014,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecolind.2022.109815","text":"Publisher Index Page"},{"id":411340,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -124.71472258149836,\n 45.51914910597108\n ],\n [\n -124.71472258149836,\n 42.32471741537614\n ],\n [\n -123.04550958834741,\n 42.32471741537614\n ],\n [\n -123.04550958834741,\n 45.51914910597108\n ],\n [\n -124.71472258149836,\n 45.51914910597108\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"146","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Weldy, Matthew J","contributorId":300545,"corporation":false,"usgs":false,"family":"Weldy","given":"Matthew","email":"","middleInitial":"J","affiliations":[{"id":65191,"text":"Pacific Northwest Research Station, USDA Forest Service, Corvallis, OR 97331, USA; Department of Forest Ecosystems and Society, Oregon State University, Corvallis, OR 97331, USA","active":true,"usgs":false}],"preferred":false,"id":860768,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lesmeister, Damon B.","contributorId":279675,"corporation":false,"usgs":false,"family":"Lesmeister","given":"Damon B.","affiliations":[{"id":7134,"text":"USFS","active":true,"usgs":false}],"preferred":false,"id":860769,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Yackulic, Charles B. 0000-0001-9661-0724","orcid":"https://orcid.org/0000-0001-9661-0724","contributorId":218825,"corporation":false,"usgs":true,"family":"Yackulic","given":"Charles","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":860770,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Appel, Cara L.","contributorId":265255,"corporation":false,"usgs":false,"family":"Appel","given":"Cara L.","affiliations":[{"id":54636,"text":"Graduate Research Assistant, USDA Forest Service, Pacific Northwest Research Station and Department of Fisheries and Wildlife, Oregon State University, Corvallis, OR.","active":true,"usgs":false}],"preferred":false,"id":860771,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McCafferty, Chris E.","contributorId":264230,"corporation":false,"usgs":false,"family":"McCafferty","given":"Chris E.","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":860772,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wiens, David 0000-0002-2020-038X","orcid":"https://orcid.org/0000-0002-2020-038X","contributorId":267230,"corporation":false,"usgs":true,"family":"Wiens","given":"David","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":860773,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70240234,"text":"70240234 - 2023 - The Sukari gold deposit, Egypt: Geochemical and geochronological constraints on the ore genesis and implications for regional exploration","interactions":[],"lastModifiedDate":"2023-05-15T13:12:40.265332","indexId":"70240234","displayToPublicDate":"2022-12-28T08:32:32","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1472,"text":"Economic Geology","active":true,"publicationSubtype":{"id":10}},"title":"The Sukari gold deposit, Egypt: Geochemical and geochronological constraints on the ore genesis and implications for regional exploration","docAbstract":"

The Sukari gold deposit (>15 Moz Au) in the Eastern Desert of Egypt is hosted by a deformed granitoid stock (Sukari tonalite-trondhjemite intrusion) and mainly occurs as a network of crosscutting sulfide-bearing quartz (± carbonate) veins and intensely sulfidized-silicified-sericitized wall rock. Emplacement of the Sukari intrusion into a tectonized Neoproterozoic accretionary complex was controlled by a system of NE- to NNE-trending oblique faults that are related to a deep-seated positive flower structure. A robust genetic model has been hampered by the poorly understood relationships between gold mineralization and host rocks. In this study, zircon U-Pb ages of three samples from the Sukari intrusion define a crystallization age of ~695 ± 2 Ma. In contrast, hydrothermal sericite from the ore zone yields an 40Ar/39Ar age of ~625 ± 3 Ma, which coincides with the onset of major sinistral transpression in the region.

Features including sigmoidal morphology of gold quartz veins and abundant subhorizontal tension gashes alongside widespread brecciation and recrystallization suggest that quartz veining occurred during renewed shortening and exhumation through the brittle-ductile transition. Petrographic and micro-X-ray fluorescence (µXRF) studies indicate that disseminated gold and sulfides, commonly associated with sericite and carbonate alteration, are mostly confined to stylolitic bands in the quartz veins. Oscillatory and sector zoning patterns, irregular As-rich bands, and truncations between early- and late-genetic pyrites reflect variations in temperature and mechanism of ore deposition, demonstrated by variable As/S and Co/Ni ratios in the different pyrite generations. Laser ablation-inductively coupled plasma-mass spectrometry analysis pinpoints the covariance of gold and arsenic contents in pyrite, but free milling gold inclusions in microfractures consistently have a mercury-bearing electrum composition, depicting different ore formation stages.

Ore fluids with δ34SH2s\">SH2s values of –1.9 to –3.0‰, modeled from gold-associated pyrite and arsenopyrite assemblages with nearly identical δ34S values, suggest a likely single source of sulfur. Alternatively, multisourced sulfur could have extensively mixed and equilibrated by fluid reaction with carbonaceous wall rock. Gold deposition was triggered by abrupt changes in fluid pH and ƒfO2\">O2⁠. As an implication for future exploration, sites of maximized strain gradients adjacent to granitoid bodies along extensive transpression zones in the district could be highly prospective targets, particularly where imprinted by sericite-carbonate ± graphite alteration.

","language":"English","publisher":"Society of Economic Geologists","doi":"10.5382/econgeo.4990","usgsCitation":"Zoheir, B., Holzheid, A., Zeh, A., McAleer, R.J., El-Behairy, M., Schwarz-Schampera, U., Graupner, T., Lentz, D., and Xiong, F., 2023, The Sukari gold deposit, Egypt: Geochemical and geochronological constraints on the ore genesis and implications for regional exploration: Economic Geology, v. 118, no. 4, p. 719-744, https://doi.org/10.5382/econgeo.4990.","productDescription":"26 p.","startPage":"719","endPage":"744","ipdsId":"IP-142063","costCenters":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":435528,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P954X51O","text":"USGS data release","linkHelpText":"40Ar/39Ar isotopic data and electron microprobe data from muscovite in the Sukari gold deposit, Egypt"},{"id":412615,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Egypt","otherGeospatial":"Sukari gold deposit","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 32.09840377670787,\n 29.776475305975993\n ],\n [\n 32.09840377670787,\n 28.340499887504606\n ],\n [\n 33.111689993290184,\n 28.340499887504606\n ],\n [\n 33.111689993290184,\n 29.776475305975993\n ],\n [\n 32.09840377670787,\n 29.776475305975993\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"118","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Zoheir, Basem 0000-0003-1792-9134","orcid":"https://orcid.org/0000-0003-1792-9134","contributorId":256944,"corporation":false,"usgs":false,"family":"Zoheir","given":"Basem","email":"","affiliations":[{"id":51910,"text":"Benha University","active":true,"usgs":false}],"preferred":false,"id":863036,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Holzheid, Astrid 0000-0001-5154-9886","orcid":"https://orcid.org/0000-0001-5154-9886","contributorId":299258,"corporation":false,"usgs":false,"family":"Holzheid","given":"Astrid","email":"","affiliations":[{"id":64799,"text":"Universität Kiel, Germany","active":true,"usgs":false}],"preferred":false,"id":863037,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Zeh, Armin 0000-0001-9476-8501","orcid":"https://orcid.org/0000-0001-9476-8501","contributorId":256945,"corporation":false,"usgs":false,"family":"Zeh","given":"Armin","email":"","affiliations":[{"id":51911,"text":"Karlsruher Institut für Technologie","active":true,"usgs":false}],"preferred":false,"id":863038,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McAleer, Ryan J. 0000-0003-3801-7441 rmcaleer@usgs.gov","orcid":"https://orcid.org/0000-0003-3801-7441","contributorId":215498,"corporation":false,"usgs":true,"family":"McAleer","given":"Ryan","email":"rmcaleer@usgs.gov","middleInitial":"J.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":863039,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"El-Behairy, Mohamed","contributorId":299259,"corporation":false,"usgs":false,"family":"El-Behairy","given":"Mohamed","email":"","affiliations":[{"id":64800,"text":"Centamin Egypt Ltd, Egypt","active":true,"usgs":false}],"preferred":false,"id":863040,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Schwarz-Schampera, Ulrich 0000-0002-6514-6233","orcid":"https://orcid.org/0000-0002-6514-6233","contributorId":299260,"corporation":false,"usgs":false,"family":"Schwarz-Schampera","given":"Ulrich","email":"","affiliations":[{"id":64801,"text":"Bundesanstalt für Geowissenschaften und Rohstoffe, Germany","active":true,"usgs":false}],"preferred":false,"id":863041,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Graupner, Torsten","contributorId":299261,"corporation":false,"usgs":false,"family":"Graupner","given":"Torsten","email":"","affiliations":[{"id":64801,"text":"Bundesanstalt für Geowissenschaften und Rohstoffe, Germany","active":true,"usgs":false}],"preferred":false,"id":863042,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Lentz, David","contributorId":299262,"corporation":false,"usgs":false,"family":"Lentz","given":"David","affiliations":[{"id":24781,"text":"University of New Brunswick, Canada","active":true,"usgs":false}],"preferred":false,"id":863043,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Xiong, Fahui","contributorId":299263,"corporation":false,"usgs":false,"family":"Xiong","given":"Fahui","email":"","affiliations":[{"id":64803,"text":"Chinese Academy of Geological Sciences, China","active":true,"usgs":false}],"preferred":false,"id":863044,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70239372,"text":"70239372 - 2023 - The over-prediction of seismically induced soil liquefaction during the 2016 Kumamoto, Japan earthquake sequence","interactions":[],"lastModifiedDate":"2023-01-11T12:48:02.805173","indexId":"70239372","displayToPublicDate":"2022-12-27T06:42:09","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1816,"text":"Geosciences","active":true,"publicationSubtype":{"id":10}},"title":"The over-prediction of seismically induced soil liquefaction during the 2016 Kumamoto, Japan earthquake sequence","docAbstract":"
Following the M7.0 strike-slip earthquake near Kumamoto, Japan, in April of 2016, most geotechnical engineering experts believed that there would be significant soil liquefaction and liquefaction-induced infrastructure damage observed in the densely populated city of Kumamoto during the post-event engineering reconnaissance. This belief was driven by several factors including the young geologic environment, alluvially deposited soils, a predominance of loose sandy soils documented in publicly available boring logs throughout the region, and the high intensity ground motions observed from the earthquake. To the surprise of many of the researchers, soil liquefaction occurred both less frequently and less severely than expected. This paper summarizes findings from our field, laboratory, and simplified analytical studies common to engineering practice to assess the lower occurrence of liquefaction. Measured in situ SPT and CPT resistance values were evaluated with current liquefaction triggering procedures. Minimally disturbed samples were subjected to cyclic triaxial testing. Furthermore, an extensive literature review on Kumamoto volcanic soils was performed. Our findings suggest that current liquefaction triggering procedures over-predict liquefaction frequency and effects in alluvially deposited volcanic soils. Volcanic soils were found to possess properties of soil crushability, high fines content, moderate plasticity, and unanticipated organic constituents. Cyclic triaxial tests confirm the high liquefaction resistance of these soils. Moving forward, geotechnical engineers should holistically consider the soil’s mineralogy and geology before relying solely on simplified liquefaction triggering procedures when evaluating volcanic soils for liquefaction.
","language":"English","publisher":"MDPI","doi":"10.3390/geosciences13010007","usgsCitation":"Anderson, D.J., Franke, K.W., Kayen, R., Dashti, S., and Badanagki, M., 2023, The over-prediction of seismically induced soil liquefaction during the 2016 Kumamoto, Japan earthquake sequence: Geosciences, v. 13, no. 1, 7, 28 p., https://doi.org/10.3390/geosciences13010007.","productDescription":"7, 28 p.","ipdsId":"IP-147235","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":445026,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/geosciences13010007","text":"Publisher Index Page"},{"id":411708,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Japan","otherGeospatial":"Mount Aso","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 130.37897745486168,\n 33.136385469043276\n ],\n [\n 130.37897745486168,\n 32.55051970765922\n ],\n [\n 131.50459805879575,\n 32.55051970765922\n ],\n [\n 131.50459805879575,\n 33.136385469043276\n ],\n [\n 130.37897745486168,\n 33.136385469043276\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"13","issue":"1","noUsgsAuthors":false,"publicationDate":"2022-12-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Anderson, Donald J.","contributorId":300727,"corporation":false,"usgs":false,"family":"Anderson","given":"Donald","email":"","middleInitial":"J.","affiliations":[{"id":65243,"text":"Utah-DOT","active":true,"usgs":false}],"preferred":false,"id":861311,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Franke, Kevin W.","contributorId":300728,"corporation":false,"usgs":false,"family":"Franke","given":"Kevin","email":"","middleInitial":"W.","affiliations":[{"id":48387,"text":"BYU","active":true,"usgs":false}],"preferred":false,"id":861312,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kayen, Robert 0000-0002-0356-072X","orcid":"https://orcid.org/0000-0002-0356-072X","contributorId":219065,"corporation":false,"usgs":true,"family":"Kayen","given":"Robert","email":"","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":861313,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dashti, Shideh","contributorId":189768,"corporation":false,"usgs":false,"family":"Dashti","given":"Shideh","email":"","affiliations":[],"preferred":false,"id":861314,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Badanagki, M","contributorId":300729,"corporation":false,"usgs":false,"family":"Badanagki","given":"M","email":"","affiliations":[{"id":65244,"text":"WSP, University of Colorado, Boulder","active":true,"usgs":false}],"preferred":false,"id":861315,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70256709,"text":"70256709 - 2023 - Multiple dimensions of functional diversity affect stream fish β-diversity","interactions":[],"lastModifiedDate":"2024-09-03T15:19:48.638587","indexId":"70256709","displayToPublicDate":"2022-12-26T10:12:08","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1696,"text":"Freshwater Biology","active":true,"publicationSubtype":{"id":10}},"title":"Multiple dimensions of functional diversity affect stream fish β-diversity","docAbstract":"
  1. When investigating metacommunity dynamics, functional differences among species are often assumed to be as important as environmental differences between sites in determining β-diversity. However, few studies have examined the influence of functional diversity on β-diversity. We examine the relative importance of regional functional diversity partitioned by niche dimensions and environmental variation in structuring taxonomic β-diversity of stream fishes using a large dataset of stream fish assemblages (hereafter, simply β-diversity). We predicted that both functional diversity and environmental variation play a role in determining β-diversity.
  2. We tested this prediction by modelling the patterns of stream fish β-diversity as a function of environmental variation, functional diversity and γ-richness across 10,220 sites for 329 fish species using a series of conceptual path models.
  3. Environmental variation consistently affected β-diversity across all models, whereas functional diversity and γ-richness influenced β-diversity only in some models. We show that including relevant trait differences among species in path models can improve their ability to explain β-diversity, suggesting that functional traits influence β-diversity.
  4. The ability of path models to explain β-diversity varied depending on the trait grouping included in the model, demonstrating that specific path models representing different niche dimensions can improve the ability of a model to explain β-diversity. In addition, parsing traits into different niche dimensions revealed alternative patterns of functional diversity–β-diversity relationships that otherwise would have been missed.
  5. The selection of relevant traits and linked niche dimensions is critical for detecting relationships between functional diversity and β-diversity. Using traits associated with different niche dimensions allows for the identification of niche dimensions most strongly associated with species sorting and the detection of patterns missed by focusing on a single niche dimension. Determining the niche dimensions that influence β-diversity could provide insights into the processes driving biodiversity and metacommunity dynamics, improving our ability to conserve or restore aquatic communities.
","language":"English","publisher":"Wiley","doi":"10.1111/fwb.14036","usgsCitation":"Bower, L.M., Stoczynski, L., Peoples, B.K., Patrick, C., and Brown, B.L., 2023, Multiple dimensions of functional diversity affect stream fish β-diversity: Freshwater Biology, v. 68, no. 3, p. 437-451, https://doi.org/10.1111/fwb.14036.","productDescription":"15 p.","startPage":"437","endPage":"451","ipdsId":"IP-134787","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":445030,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/fwb.14036","text":"Publisher Index Page"},{"id":433407,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Eastern United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -85.08254453558935,\n 29.663955568318002\n ],\n [\n -84.00353049201316,\n 31.24197817552016\n ],\n [\n -82.54620654241978,\n 29.549345286801383\n ],\n [\n -81.08225667140708,\n 30.220016244291074\n ],\n [\n -81.13068353501534,\n 32.32776358432194\n ],\n [\n -82.29417301039534,\n 34.379604334810125\n ],\n [\n -78.96528527688022,\n 33.925963218570786\n ],\n [\n -76.42910221157335,\n 34.602515517174\n ],\n [\n -75.69740219895765,\n 35.764395311405835\n ],\n [\n -75.05233402289387,\n 38.633501231022535\n ],\n [\n -75.10935092106094,\n 39.76556508592148\n ],\n [\n -73.50871658359135,\n 41.12478551758119\n ],\n [\n -69.73823459124182,\n 41.39849946093338\n ],\n [\n -70.56400501647666,\n 42.58101071327985\n ],\n [\n -66.53407606488797,\n 45.018393131168494\n ],\n [\n -67.98091085356586,\n 47.55537630125639\n ],\n [\n -69.25928679202123,\n 47.54170256695585\n ],\n [\n -71.21905272640619,\n 45.12756083037783\n ],\n [\n -74.09987276280616,\n 45.1570079552298\n ],\n [\n -74.83668470001416,\n 43.00167109657585\n ],\n [\n -78.7139760431753,\n 42.94670064885159\n ],\n [\n -82.49681964219468,\n 40.92727818455322\n ],\n [\n -80.23949798942652,\n 38.65161657169966\n ],\n [\n -82.81095598309338,\n 36.708283361840515\n ],\n [\n -87.42378197623401,\n 35.73782637186412\n ],\n [\n -86.2161486208606,\n 31.10920872480844\n ],\n [\n -85.08254453558935,\n 29.663955568318002\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"68","issue":"3","noUsgsAuthors":false,"publicationDate":"2022-12-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Bower, Luke Max 0000-0002-0739-858X","orcid":"https://orcid.org/0000-0002-0739-858X","contributorId":341034,"corporation":false,"usgs":true,"family":"Bower","given":"Luke","email":"","middleInitial":"Max","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":908734,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stoczynski, Lauren","contributorId":341643,"corporation":false,"usgs":false,"family":"Stoczynski","given":"Lauren","email":"","affiliations":[{"id":81766,"text":"Clemson University Clemson","active":true,"usgs":false}],"preferred":false,"id":908735,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Peoples, Brandon K.","contributorId":341644,"corporation":false,"usgs":false,"family":"Peoples","given":"Brandon","email":"","middleInitial":"K.","affiliations":[{"id":81766,"text":"Clemson University Clemson","active":true,"usgs":false}],"preferred":false,"id":908736,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Patrick, Christopher J.","contributorId":341645,"corporation":false,"usgs":false,"family":"Patrick","given":"Christopher J.","affiliations":[{"id":81768,"text":"Clemson University Clemson,","active":true,"usgs":false}],"preferred":false,"id":908737,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Brown, Bryan L.","contributorId":341646,"corporation":false,"usgs":false,"family":"Brown","given":"Bryan","email":"","middleInitial":"L.","affiliations":[{"id":6686,"text":"College of William and Mary","active":true,"usgs":false}],"preferred":false,"id":908738,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70241127,"text":"70241127 - 2023 - Divergent climate impacts on C3 versus C4 grasses imply widespread 21st century shifts in grassland functional composition","interactions":[],"lastModifiedDate":"2023-03-13T11:18:23.661025","indexId":"70241127","displayToPublicDate":"2022-12-26T06:16:01","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1399,"text":"Diversity and Distributions","active":true,"publicationSubtype":{"id":10}},"title":"Divergent climate impacts on C3 versus C4 grasses imply widespread 21st century shifts in grassland functional composition","docAbstract":"

Aim

Grasslands cover a third of Earth's landmass and provide critical ecosystem services. Anticipating how perennial C3 (cool-season) and C4 (warm-season) grasses respond to climate change will be key to predicting future composition and functioning of grasslands. Here, we evaluate environmental drivers of C3 and C4 perennial distributions and assess how C3 and C4 grass distributions shift in response to future climate change.

Location

Western United States.

Methods

We developed integrated species distribution models to identify climate and soil drivers of relative abundance of C3 and C4 perennial grasses. We then created projections of species abundances under future climate and evaluated when and where projected shifts in relative abundance were robust across climate models.

Results

Historically, C3 grasses occupied areas with lower temperature and more variable precipitation regimes, while C4 grasses occupied areas of higher temperature, greater temperature variability and greater warm-season precipitation. C4 species also occupied narrower soil texture niches. In response to future climate change, C3 grass abundance declined across 74% of areas, while C4 abundance increased across 66% of areas. C3 grasses expanded in mid- to higher-latitude areas with increasing temperature and decreasing seasonality of precipitation. In contrast, C4 grasses increased in higher-latitude regions, but declined in lower-latitude, dryer regions. Results were surprisingly robust across climate scenarios, suggesting high confidence in the direction of these future changes.

Main Conclusions

Findings imply C3 and C4 perennial grasses will have highly divergent responses to climate change that may result in grassland functional compositional changes. Increasing temperatures and precipitation variability may favour some C4 grasses, but C4 habitat expansion may be constrained by soil conditions in western USA. Results provide actionable insights for anticipating the impacts of climate change on grass-dominated and co-dominated ecosystems and improving large-scale conservation and restoration efforts.

","language":"English","publisher":"Wiley","doi":"10.1111/ddi.13669","usgsCitation":"Havrilla, C., Bradford, J., Yackulic, C., and Munson, S.M., 2023, Divergent climate impacts on C3 versus C4 grasses imply widespread 21st century shifts in grassland functional composition: Diversity and Distributions, v. 29, no. 3, p. 379-394, https://doi.org/10.1111/ddi.13669.","productDescription":"16 p.","startPage":"379","endPage":"394","ipdsId":"IP-143038","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":445039,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/ddi.13669","text":"Publisher Index Page"},{"id":435532,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P99EGD2E","text":"USGS data release","linkHelpText":"Bioclimatic suitability for 11 dominant Colorado Plateau perennial grass species (ver. 2.0, November 2022)"},{"id":413999,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -125.54030283521868,\n 49.526621871576566\n ],\n [\n -125.54030283521868,\n 28.895094929809844\n ],\n [\n -101.38064109224445,\n 28.895094929809844\n ],\n [\n -101.38064109224445,\n 49.526621871576566\n ],\n [\n -125.54030283521868,\n 49.526621871576566\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"29","issue":"3","noUsgsAuthors":false,"publicationDate":"2022-12-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Havrilla, Caroline A.","contributorId":303002,"corporation":false,"usgs":false,"family":"Havrilla","given":"Caroline A.","affiliations":[{"id":65592,"text":"Department of Forest and Rangeland Stewardship, Colorado State University, Fort Collins, CO 80524","active":true,"usgs":false}],"preferred":false,"id":866173,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bradford, John B. 0000-0001-9257-6303","orcid":"https://orcid.org/0000-0001-9257-6303","contributorId":219257,"corporation":false,"usgs":true,"family":"Bradford","given":"John B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":866174,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Yackulic, Charles B. 0000-0001-9661-0724","orcid":"https://orcid.org/0000-0001-9661-0724","contributorId":218825,"corporation":false,"usgs":true,"family":"Yackulic","given":"Charles","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":866175,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Munson, Seth M. 0000-0002-2736-6374 smunson@usgs.gov","orcid":"https://orcid.org/0000-0002-2736-6374","contributorId":1334,"corporation":false,"usgs":true,"family":"Munson","given":"Seth","email":"smunson@usgs.gov","middleInitial":"M.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true},{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true}],"preferred":true,"id":866176,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70240131,"text":"70240131 - 2023 - Borealization of nearshore fishes on an interior Arctic shelf over multiple decades","interactions":[],"lastModifiedDate":"2023-03-15T15:06:22.506747","indexId":"70240131","displayToPublicDate":"2022-12-24T06:37:51","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1837,"text":"Global Change Biology","active":true,"publicationSubtype":{"id":10}},"title":"Borealization of nearshore fishes on an interior Arctic shelf over multiple decades","docAbstract":"

Borealization is a type of community reorganization where Arctic specialists are replaced by species with more boreal distributions in response to climatic warming. The process of borealization is often exemplified by the northward range expansions and subsequent proliferation of boreal species on the Pacific and Atlantic inflow Arctic shelves (i.e., Bering/Chukchi and Barents seas, respectively). But the circumpolar nearshore distribution of Arctic-boreal fishes that predates recent warming suggests borealization is possible beyond inflow shelves. To examine this question, we revisited two nearshore lagoons in the eastern Alaska Beaufort Sea (Kaktovik and Jago lagoons, Arctic National Wildlife Refuge, Alaska, USA), a High Arctic interior shelf. We compared summer fish species assemblage, catch rate, and size distribution among three periods that spanned a 30-year record (baseline conditions, 1988–1991; moderate sea ice decline, 2003–2005; rapid sea ice decline, 2017–2019). Fish assemblages differed among periods in both lagoons, consistent with borealization. Among Arctic specialists, a clear decline in fourhorn sculpin (Myoxocephalus quadricornis, Kanayuq in Iñupiaq) occurred in both lagoons with 86%–90% lower catch rates compared with the baseline period. Among the Arctic-boreal species, a dramatic 18- to 19-fold increase in saffron cod (Eleginus gracilis, Uugaq) occurred in both lagoons. Fish size (length) distributions demonstrated increases in the proportion of larger fish for most species examined, consistent with increasing survival and addition of age-classes. These field data illustrate borealization of an Arctic nearshore fish community during a period of rapid warming. Our results agree with predictions that Arctic-boreal fishes (e.g., saffron cod) are well positioned to exploit the changing Arctic ecosystem. Another Arctic-boreal species, Dolly Varden (Salvelinus malma, Iqalukpik), appear to have already responded to warming by shifting from Arctic nearshore to shelf waters. More broadly, our findings suggest that areas of borealization could be widespread in the circumpolar nearshore.

","language":"English","publisher":"Wiley","doi":"10.1111/gcb.16576","usgsCitation":"von Biela, V.R., Laske, S.M., Stanek, A.E., Brown, R., and Dunton, K., 2023, Borealization of nearshore fishes on an interior Arctic shelf over multiple decades: Global Change Biology, v. 29, no. 7, p. 1822-1838, https://doi.org/10.1111/gcb.16576.","productDescription":"17 p.","startPage":"1822","endPage":"1838","ipdsId":"IP-140988","costCenters":[{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true}],"links":[{"id":445048,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/gcb.16576","text":"Publisher Index Page"},{"id":412437,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Arctic National Wildlife Refuge, Kaktovik and Jago lagoons","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -143.72717327290792,\n 70.14108904245526\n ],\n [\n -143.72717327290792,\n 70.05929996195823\n ],\n [\n -143.24258750157804,\n 70.05929996195823\n ],\n [\n -143.24258750157804,\n 70.14108904245526\n ],\n [\n -143.72717327290792,\n 70.14108904245526\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"29","issue":"7","noUsgsAuthors":false,"publicationDate":"2023-01-04","publicationStatus":"PW","contributors":{"authors":[{"text":"von Biela, Vanessa R. 0000-0002-7139-5981 vvonbiela@usgs.gov","orcid":"https://orcid.org/0000-0002-7139-5981","contributorId":3104,"corporation":false,"usgs":true,"family":"von Biela","given":"Vanessa","email":"vvonbiela@usgs.gov","middleInitial":"R.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true}],"preferred":true,"id":862727,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Laske, Sarah M. 0000-0002-6096-0420 slaske@usgs.gov","orcid":"https://orcid.org/0000-0002-6096-0420","contributorId":204872,"corporation":false,"usgs":true,"family":"Laske","given":"Sarah","email":"slaske@usgs.gov","middleInitial":"M.","affiliations":[{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":862728,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stanek, Ashley E. 0000-0001-5184-2126","orcid":"https://orcid.org/0000-0001-5184-2126","contributorId":290682,"corporation":false,"usgs":true,"family":"Stanek","given":"Ashley","email":"","middleInitial":"E.","affiliations":[{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true}],"preferred":true,"id":862729,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brown, Randy J","contributorId":243248,"corporation":false,"usgs":false,"family":"Brown","given":"Randy J","affiliations":[{"id":48666,"text":"USFWS, Fairbanks, Alaska","active":true,"usgs":false}],"preferred":false,"id":862730,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dunton, Kenneth H.","contributorId":171775,"corporation":false,"usgs":false,"family":"Dunton","given":"Kenneth H.","affiliations":[],"preferred":false,"id":862731,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70239202,"text":"70239202 - 2023 - Pesticide prioritization by potential biological effects in tributaries of the Laurentian Great Lakes","interactions":[],"lastModifiedDate":"2023-02-02T17:57:35.332175","indexId":"70239202","displayToPublicDate":"2022-12-23T07:07:29","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1571,"text":"Environmental Toxicology and Chemistry","active":true,"publicationSubtype":{"id":10}},"title":"Pesticide prioritization by potential biological effects in tributaries of the Laurentian Great Lakes","docAbstract":"

Watersheds of the Great Lakes Basin (USA/Canada) are highly modified and impacted by human activities including pesticide use. Despite labeling restrictions intended to minimize risks to nontarget organisms, concerns remain that environmental exposures to pesticides may be occurring at levels negatively impacting nontarget organisms. We used a combination of organismal-level toxicity estimates (in vivo aquatic life benchmarks) and data from high-throughput screening (HTS) assays (in vitro benchmarks) to prioritize pesticides and sites of concern in streams at 16 tributaries to the Great Lakes Basin. In vivo or in vitro benchmark values were exceeded at 15 sites, 10 of which had exceedances throughout the year. Pesticides had the greatest potential biological impact at the site with the greatest proportion of agricultural land use in its basin (the Maumee River, Toledo, OH, USA), with 72 parent compounds or transformation products being detected, 47 of which exceeded at least one benchmark value. Our risk-based screening approach identified multiple pesticide parent compounds of concern in tributaries of the Great Lakes; these compounds included: eight herbicides (metolachlor, acetochlor, 2,4-dichlorophenoxyacetic acid, diuron, atrazine, alachlor, triclopyr, and simazine), three fungicides (chlorothalonil, propiconazole, and carbendazim), and four insecticides (diazinon, fipronil, imidacloprid, and clothianidin). We present methods for reducing the volume and complexity of potential biological effects data that result from combining contaminant surveillance with HTS (in vitro) and traditional (in vivo) toxicity estimates. Environ Toxicol Chem 2022;00:1–18. Published 2022. This article is a U.S. Government work and is in the public domain in the USA. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

","language":"English","publisher":"Wiley","doi":"10.1002/etc.5522","usgsCitation":"Oliver, S.K., Corsi, S., Baldwin, A.K., Nott, M.A., Ankley, G., Blackwell, B., Villeneuve, D.L., Hladik, M.L., Kolpin, D., Loken, L.C., DeCicco, L.A., Meyer, M., and Loftin, K.A., 2023, Pesticide prioritization by potential biological effects in tributaries of the Laurentian Great Lakes: Environmental Toxicology and Chemistry, v. 42, no. 2, p. 367-384, https://doi.org/10.1002/etc.5522.","productDescription":"18 p.","startPage":"367","endPage":"384","ipdsId":"IP-137314","costCenters":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"links":[{"id":445058,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/etc.5522","text":"Publisher Index Page"},{"id":411338,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","otherGeospatial":"Great Lakes","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -91.41831603390857,\n 49.80549590740878\n ],\n [\n -91.41831603390857,\n 41.07851415036595\n ],\n [\n -74.90189273325733,\n 41.07851415036595\n ],\n [\n -74.90189273325733,\n 49.80549590740878\n ],\n [\n -91.41831603390857,\n 49.80549590740878\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"42","issue":"2","noUsgsAuthors":false,"publicationDate":"2023-02-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Oliver, Samantha K. 0000-0001-5668-1165","orcid":"https://orcid.org/0000-0001-5668-1165","contributorId":211886,"corporation":false,"usgs":true,"family":"Oliver","given":"Samantha","email":"","middleInitial":"K.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":860748,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Corsi, Steven R. 0000-0003-0583-5536 srcorsi@usgs.gov","orcid":"https://orcid.org/0000-0003-0583-5536","contributorId":172002,"corporation":false,"usgs":true,"family":"Corsi","given":"Steven R.","email":"srcorsi@usgs.gov","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":860749,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Baldwin, Austin K. 0000-0002-6027-3823 akbaldwi@usgs.gov","orcid":"https://orcid.org/0000-0002-6027-3823","contributorId":4515,"corporation":false,"usgs":true,"family":"Baldwin","given":"Austin","email":"akbaldwi@usgs.gov","middleInitial":"K.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":860750,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Nott, Michelle A. 0000-0003-3968-7586","orcid":"https://orcid.org/0000-0003-3968-7586","contributorId":221766,"corporation":false,"usgs":true,"family":"Nott","given":"Michelle","email":"","middleInitial":"A.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":860751,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ankley, Gerald T.","contributorId":177970,"corporation":false,"usgs":false,"family":"Ankley","given":"Gerald 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0000-0002-0891-2712","orcid":"https://orcid.org/0000-0002-0891-2712","contributorId":221229,"corporation":false,"usgs":true,"family":"Hladik","given":"Michelle","middleInitial":"L.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":860755,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Kolpin, Dana W. 0000-0002-3529-6505","orcid":"https://orcid.org/0000-0002-3529-6505","contributorId":205652,"corporation":false,"usgs":true,"family":"Kolpin","given":"Dana W.","affiliations":[{"id":35680,"text":"Illinois-Iowa-Missouri Water Science Center","active":true,"usgs":true},{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":860756,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Loken, Luke C. 0000-0003-3194-1498 lloken@usgs.gov","orcid":"https://orcid.org/0000-0003-3194-1498","contributorId":195600,"corporation":false,"usgs":true,"family":"Loken","given":"Luke","email":"lloken@usgs.gov","middleInitial":"C.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":860757,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"DeCicco, Laura A. 0000-0002-3915-9487 ldecicco@usgs.gov","orcid":"https://orcid.org/0000-0002-3915-9487","contributorId":174716,"corporation":false,"usgs":true,"family":"DeCicco","given":"Laura","email":"ldecicco@usgs.gov","middleInitial":"A.","affiliations":[{"id":160,"text":"Center for Integrated Data Analytics","active":false,"usgs":true},{"id":5054,"text":"Office of Water Information","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":860758,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Meyer, Michael T. 0000-0001-6006-7985","orcid":"https://orcid.org/0000-0001-6006-7985","contributorId":205665,"corporation":false,"usgs":true,"family":"Meyer","given":"Michael T.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":true,"id":860759,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Loftin, Keith A. 0000-0001-5291-876X","orcid":"https://orcid.org/0000-0001-5291-876X","contributorId":221964,"corporation":false,"usgs":true,"family":"Loftin","given":"Keith","middleInitial":"A.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":true,"id":860760,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}} ,{"id":70247139,"text":"70247139 - 2023 - Near-term forecasts of stream temperature using deep learning and data assimilation in support of management decisions","interactions":[],"lastModifiedDate":"2023-07-25T14:31:36.964032","indexId":"70247139","displayToPublicDate":"2022-12-22T09:14:29","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2529,"text":"Journal of the American Water Resources Association","active":true,"publicationSubtype":{"id":10}},"title":"Near-term forecasts of stream temperature using deep learning and data assimilation in support of management decisions","docAbstract":"

Deep learning (DL) models are increasingly used to make accurate hindcasts of management-relevant variables, but they are less commonly used in forecasting applications. Data assimilation (DA) can be used for forecasts to leverage real-time observations, where the difference between model predictions and observations today is used to adjust the model to make better predictions tomorrow. In this use case, we developed a process-guided DL and DA approach to make 7-day probabilistic forecasts of daily maximum water temperature in the Delaware River Basin in support of water management decisions. Our modeling system produced forecasts of daily maximum water temperature with an average root mean squared error (RMSE) from 1.1 to 1.4°C for 1-day-ahead and 1.4 to 1.9°C for 7-day-ahead forecasts across all sites. The DA algorithm marginally improved forecast performance when compared with forecasts produced using the process-guided DL model alone (0%–14% lower RMSE with the DA algorithm). Across all sites and lead times, 65%–82% of observations were within 90% forecast confidence intervals, which allowed managers to anticipate probability of exceedances of ecologically relevant thresholds and aid in decisions about releasing reservoir water downstream. The flexibility of DL models shows promise for forecasting other important environmental variables and aid in decision-making.

","language":"English","publisher":"Wiley","doi":"10.1111/1752-1688.13093","usgsCitation":"Zwart, J.A., Oliver, S.K., Watkins, W., Sadler, J.M., Appling, A.P., Corson-Dosch, H.R., Jia, X., Kumar, V., and Read, J., 2023, Near-term forecasts of stream temperature using deep learning and data assimilation in support of management decisions: Journal of the American Water Resources Association, v. 59, no. 2, p. 317-337, https://doi.org/10.1111/1752-1688.13093.","productDescription":"21 p.","startPage":"317","endPage":"337","ipdsId":"IP-135607","costCenters":[{"id":5054,"text":"Office of Water Information","active":true,"usgs":true},{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"links":[{"id":445061,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/1752-1688.13093","text":"Publisher Index Page"},{"id":419302,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"59","issue":"2","noUsgsAuthors":false,"publicationDate":"2022-12-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Zwart, Jacob Aaron 0000-0002-3870-405X","orcid":"https://orcid.org/0000-0002-3870-405X","contributorId":237809,"corporation":false,"usgs":true,"family":"Zwart","given":"Jacob","email":"","middleInitial":"Aaron","affiliations":[{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"preferred":true,"id":879028,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Oliver, Samantha K. 0000-0001-5668-1165","orcid":"https://orcid.org/0000-0001-5668-1165","contributorId":211886,"corporation":false,"usgs":true,"family":"Oliver","given":"Samantha","email":"","middleInitial":"K.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":879029,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Watkins, William 0000-0002-7544-0700 wwatkins@usgs.gov","orcid":"https://orcid.org/0000-0002-7544-0700","contributorId":178146,"corporation":false,"usgs":true,"family":"Watkins","given":"William","email":"wwatkins@usgs.gov","affiliations":[{"id":5054,"text":"Office of Water Information","active":true,"usgs":true}],"preferred":true,"id":879030,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sadler, Jeffrey Michael 0000-0001-8776-4844","orcid":"https://orcid.org/0000-0001-8776-4844","contributorId":260092,"corporation":false,"usgs":true,"family":"Sadler","given":"Jeffrey","email":"","middleInitial":"Michael","affiliations":[{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"preferred":true,"id":879031,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Appling, Alison P. 0000-0003-3638-8572 aappling@usgs.gov","orcid":"https://orcid.org/0000-0003-3638-8572","contributorId":150595,"corporation":false,"usgs":true,"family":"Appling","given":"Alison","email":"aappling@usgs.gov","middleInitial":"P.","affiliations":[{"id":5054,"text":"Office of Water Information","active":true,"usgs":true}],"preferred":true,"id":879032,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Corson-Dosch, Hayley R. 0000-0001-8695-1584","orcid":"https://orcid.org/0000-0001-8695-1584","contributorId":244707,"corporation":false,"usgs":true,"family":"Corson-Dosch","given":"Hayley","middleInitial":"R.","affiliations":[{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"preferred":true,"id":879033,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Jia, Xiaowei 0000-0001-8544-5233","orcid":"https://orcid.org/0000-0001-8544-5233","contributorId":237807,"corporation":false,"usgs":false,"family":"Jia","given":"Xiaowei","email":"","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":879034,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Kumar, Vipin","contributorId":237812,"corporation":false,"usgs":false,"family":"Kumar","given":"Vipin","email":"","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":879035,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Read, Jordan 0000-0002-3888-6631","orcid":"https://orcid.org/0000-0002-3888-6631","contributorId":221385,"corporation":false,"usgs":true,"family":"Read","given":"Jordan","affiliations":[{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"preferred":true,"id":879036,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70244195,"text":"70244195 - 2023 - Investigating effects of climate-induced changes in water temperature and diet on mercury concentrations in an Arctic freshwater forage fish","interactions":[],"lastModifiedDate":"2023-06-07T14:07:58.189314","indexId":"70244195","displayToPublicDate":"2022-12-22T09:02:04","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1561,"text":"Environmental Research","active":true,"publicationSubtype":{"id":10}},"title":"Investigating effects of climate-induced changes in water temperature and diet on mercury concentrations in an Arctic freshwater forage fish","docAbstract":"

The amount of mercury (Hg) in Arctic lake food webs is, and will continue to be, affected by rapid, ongoing climate change. At warmer temperatures, fish require more energy to sustain growth; changes in their metabolic rates and consuming prey with potentially higher Hg concentrations could result in increased Hg accumulation. To examine the potential implications of climate warming on forage fish Hg accumulation in Arctic lakes, we quantified growth and Hg accumulation in Ninespine Stickleback Pungitius pungitius under different temperature and diet scenarios using bioenergetics models. Four scenarios were considered that examined the role of climate, diet, climate × diet, and climate × diet × elevated prey Hg. As expected, annual fish growth increased with warmer temperatures, but growth rates and Hg accumulation were largely diet dependent. Compared to current growth rates of 0.3 g⋅y−1, fish growth increased at least 200% for fish consuming energy-dense benthic prey and decreased at least 40% for fish consuming pelagic prey. Compared to baseline levels, the Hg burden per kilocalorie of Ninespine Stickleback declined up to 43% with benthic consumption – indicating strong somatic growth dilution – but no more than 4% with pelagic consumption; elevated prey Hg concentrations led to moderate Hg declines in benthic-foraging fish and Hg increases in pelagic-foraging fish. Bioenergetics models demonstrated the complex interaction of water temperature, growth, prey proportions, and prey Hg concentrations that respond to climate change. Further work is needed to resolve mechanisms and rates linking climate change to Hg availability and uptake in Arctic freshwater systems.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.envres.2022.114851","usgsCitation":"Laske, S.M., Burke, S.M., Carey, M.P., Swanson, H.K., and Zimmerman, C.E., 2023, Investigating effects of climate-induced changes in water temperature and diet on mercury concentrations in an Arctic freshwater forage fish: Environmental Research, v. 218, 114851, 13 p., https://doi.org/10.1016/j.envres.2022.114851.","productDescription":"114851, 13 p.","ipdsId":"IP-144262","costCenters":[{"id":65299,"text":"Alaska Science Center Ecosystems","active":true,"usgs":true}],"links":[{"id":445064,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.envres.2022.114851","text":"Publisher Index Page"},{"id":417911,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -157.67980839183957,\n 70.52713703737254\n ],\n [\n -157.67980839183957,\n 70\n ],\n [\n -156.79804904275505,\n 70\n ],\n [\n -156.79804904275505,\n 70.52713703737254\n ],\n [\n -157.67980839183957,\n 70.52713703737254\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"218","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Laske, Sarah M. 0000-0002-6096-0420 slaske@usgs.gov","orcid":"https://orcid.org/0000-0002-6096-0420","contributorId":204872,"corporation":false,"usgs":true,"family":"Laske","given":"Sarah","email":"slaske@usgs.gov","middleInitial":"M.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true}],"preferred":true,"id":874844,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Burke, Samantha M.","contributorId":203348,"corporation":false,"usgs":false,"family":"Burke","given":"Samantha","email":"","middleInitial":"M.","affiliations":[{"id":6655,"text":"University of Waterloo","active":true,"usgs":false}],"preferred":false,"id":874845,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Carey, Michael P. 0000-0002-3327-8995 mcarey@usgs.gov","orcid":"https://orcid.org/0000-0002-3327-8995","contributorId":5397,"corporation":false,"usgs":true,"family":"Carey","given":"Michael","email":"mcarey@usgs.gov","middleInitial":"P.","affiliations":[{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":874846,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Swanson, Heidi K.","contributorId":203350,"corporation":false,"usgs":false,"family":"Swanson","given":"Heidi","email":"","middleInitial":"K.","affiliations":[{"id":6655,"text":"University of Waterloo","active":true,"usgs":false}],"preferred":false,"id":874847,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Zimmerman, Christian E. 0000-0002-3646-0688 czimmerman@usgs.gov","orcid":"https://orcid.org/0000-0002-3646-0688","contributorId":410,"corporation":false,"usgs":true,"family":"Zimmerman","given":"Christian","email":"czimmerman@usgs.gov","middleInitial":"E.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true}],"preferred":true,"id":874848,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70239217,"text":"70239217 - 2023 - Revised age and regional correlations of Cenozoic strata on Bat Mountain, Death Valley region, California, USA, from zircon U-Pb geochronology of sandstones and ash-fall tuffs","interactions":[],"lastModifiedDate":"2023-02-02T17:56:41.715738","indexId":"70239217","displayToPublicDate":"2022-12-22T08:57:39","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1820,"text":"Geosphere","active":true,"publicationSubtype":{"id":10}},"title":"Revised age and regional correlations of Cenozoic strata on Bat Mountain, Death Valley region, California, USA, from zircon U-Pb geochronology of sandstones and ash-fall tuffs","docAbstract":"

Basin analysis and tectonic reconstructions of the Cenozoic history of the Death Valley region, California, USA, are hindered by a lack of volcanic (tuff) age control in many stratigraphic successions exposed in the Grapevine and Funeral Mountains of California, USA. Although maximum depositional ages (MDAs) interpreted from detrital zircon U-Pb data may be a promising alternative to volcanic ages, arguments remain regarding the calculation of MDAs including, but not limited to, the number of “young” grains to consider (i.e., the spectrum of dates used to calculate the MDA); which grains, if any, should be ignored; which approaches yield results that are statistically rigorous; and ultimately, which approaches result in ages that are geologically reasonable. We compare commonly used metrics of detrital zircon MDA for five sandstone samples from the Cenozoic strata exposed on Bat Mountain in the southern Funeral Mountains of California—i.e., the youngest single grain (YSG), the weighted mean of the youngest grain cluster of two or more grains at 1σ uncertainty (YC1σ(2+)) and of three or more grains at 2σ uncertainty (YC2σ(3+)), the youngest graphical peak (YPP), and the maximum likelihood age (MLA). Every sandstone sample yielded abundant Cenozoic zircon U-Pb dates that formed unimodal, near-normal age distributions that were clearly distinguishable from the next-oldest grains in each sample and showed an apparent up-section decrease in peak age. Benchmarked against published K/Ar and 40Ar/39Ar ages and five new zircon U-Pb ages of ash-fall tuffs, our analysis parallels prior studies and demonstrates that many MDA metrics—YSG, YC1σ(2+), YC2σ(3+), and YPP—drift toward unreasonably young or old values. In contrast, the maximum likelihood estimation approach and the resulting MLA metric consistently produce geologically appropriate estimates of MDA without arbitrary omission of any young (or old) zircon dates. Using the MLAs of sandstones and zircon U-Pb ages of interbedded ash-fall tuffs, we develop a new age model for the Oligocene–Miocene Amargosa Valley Formation (deposited ca. 28.5–18.5 Ma) and the Miocene Bat Mountain Formation (deposited ca. 15.5–13.5 Ma) and revise correlations to Cenozoic strata across the eastern Death Valley region.

","language":"English","publisher":"Geological Society of America","doi":"10.1130/GES02543.1","usgsCitation":"Schwartz, T.M., Souders, A., Lundstern, J., Gilmer, A.K., and Thompson, R., 2023, Revised age and regional correlations of Cenozoic strata on Bat Mountain, Death Valley region, California, USA, from zircon U-Pb geochronology of sandstones and ash-fall tuffs: Geosphere, v. 19, no. 1, p. 235-257, https://doi.org/10.1130/GES02543.1.","productDescription":"23 p.","startPage":"235","endPage":"257","ipdsId":"IP-139248","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":445066,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/ges02543.1","text":"Publisher Index Page"},{"id":435534,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P982KK4D","text":"USGS data release","linkHelpText":"Zircon U-Pb data for ash-fall tuffs and sandstones of the Cenozoic Amargosa Valley and Bat Mountain Formations exposed on Bat Mountain, southern Funeral Mountains, California, USA"},{"id":411342,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Bat Mountain, Death Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -117.12127468750195,\n 37.16000456147583\n ],\n [\n -117.12127468750195,\n 35.551070951522945\n ],\n [\n -115.75746797181529,\n 35.551070951522945\n ],\n [\n -115.75746797181529,\n 37.16000456147583\n ],\n [\n -117.12127468750195,\n 37.16000456147583\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"19","issue":"1","noUsgsAuthors":false,"publicationDate":"2022-12-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Schwartz, Theresa Maude 0000-0001-6606-4072","orcid":"https://orcid.org/0000-0001-6606-4072","contributorId":245180,"corporation":false,"usgs":true,"family":"Schwartz","given":"Theresa","email":"","middleInitial":"Maude","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":860787,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Souders, Amanda Kate 0000-0002-1367-8924","orcid":"https://orcid.org/0000-0002-1367-8924","contributorId":296423,"corporation":false,"usgs":true,"family":"Souders","given":"Amanda Kate","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":860788,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lundstern, Jens-Erik 0000-0003-0000-8013","orcid":"https://orcid.org/0000-0003-0000-8013","contributorId":264189,"corporation":false,"usgs":true,"family":"Lundstern","given":"Jens-Erik","email":"","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":860789,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gilmer, Amy K. 0000-0001-5038-8136","orcid":"https://orcid.org/0000-0001-5038-8136","contributorId":218307,"corporation":false,"usgs":true,"family":"Gilmer","given":"Amy","email":"","middleInitial":"K.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":860790,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Thompson, Ren A. 0000-0002-3044-3043","orcid":"https://orcid.org/0000-0002-3044-3043","contributorId":207982,"corporation":false,"usgs":true,"family":"Thompson","given":"Ren A.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":860791,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70239141,"text":"70239141 - 2023 - Sharing land via keystone structure: Retaining naturally regenerated trees may efficiently benefit birds in plantations","interactions":[],"lastModifiedDate":"2023-04-11T16:56:36.003705","indexId":"70239141","displayToPublicDate":"2022-12-22T07:02:43","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1450,"text":"Ecological Applications","active":true,"publicationSubtype":{"id":10}},"title":"Sharing land via keystone structure: Retaining naturally regenerated trees may efficiently benefit birds in plantations","docAbstract":"

Meeting food/wood demands with increasing human population and per-capita consumption is a pressing conservation issue, and is often framed as a choice between land sparing and land sharing. Although most empirical studies comparing the efficacy of land sparing and sharing supported land sparing, land sharing may be more efficient if its performance is tested by rigorous experimental design and habitat structures providing crucial resources for various species––keystone structures––are clearly involved. We launched a manipulative experiment to retain naturally regenerated broad-leaved trees when harvesting conifer plantations in central Hokkaido, northern Japan. We surveyed birds in harvested treatments, unharvested plantation controls and natural forest references one-year before the harvest and for three consecutive post-harvest years. We developed a hierarchical community model separating abundance and space-use (territorial proportion overlapping treatment plots) subject to imperfect detection to assess population consequences of retention harvesting. Application of the model to our data showed that retaining some broad-leaved trees increased total abundance of forest birds over the harvest rotation cycle. Specifically, pre-harvest survey showed that the amount of broad-leaved trees increased forest bird abundance in a concave manner (i.e., in a form of diminishing-return). After harvesting, a small amount of retained broad-leaved trees mitigated negative harvesting impacts on abundance though retention harvesting reduced the space-use. Nevertheless, positive retention effects on the post-harvest bird density as the product of abundance and space-use exhibited a concave form. Thus, small profit reductions were shown to yield large increases in forest bird abundance. The difference in bird abundance between clear-cutting and low amounts of broad-leaved tree retention increased slightly from the first to second post-harvesting years. We conclude that retaining a small amount of broad-leaved trees may be a cost-effective on-site conservation approach for the management of conifer plantations. Retention of 20-30 broad-leaved trees per ha may be sufficient to maintain higher forest bird abundance than clear-cutting over the rotation cycle. Retention approaches can be incorporated into management systems using certification schemes and best management practices. Developing an awareness of the roles and values of naturally regenerated trees is needed to diversify plantations.

","language":"English","publisher":"Ecological Society of America","doi":"10.1002/eap.2802","usgsCitation":"Yamaura, Y., Unno, A., and Royle, A., 2023, Sharing land via keystone structure: Retaining naturally regenerated trees may efficiently benefit birds in plantations: Ecological Applications, v. 33, no. 3, e2802, https://doi.org/10.1002/eap.2802.","productDescription":"e2802","ipdsId":"IP-136595","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":445068,"rank":2,"type":{"id":41,"text":"Open Access External Repository Page"},"text":"External Repository"},{"id":411174,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"33","issue":"3","noUsgsAuthors":false,"publicationDate":"2023-02-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Yamaura, Yuichi","contributorId":300495,"corporation":false,"usgs":false,"family":"Yamaura","given":"Yuichi","affiliations":[{"id":65171,"text":"Shikoku Research Center, Forestry and Forest Products Research Institute","active":true,"usgs":false}],"preferred":false,"id":860324,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Unno, Akira","contributorId":300496,"corporation":false,"usgs":false,"family":"Unno","given":"Akira","email":"","affiliations":[{"id":65172,"text":"Fores try Research Institute, Hokkaido Research Organization, Koshunai, Bibai,","active":true,"usgs":false}],"preferred":false,"id":860325,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Royle, J. Andrew 0000-0003-3135-2167 aroyle@usgs.gov","orcid":"https://orcid.org/0000-0003-3135-2167","contributorId":146229,"corporation":false,"usgs":true,"family":"Royle","given":"J. Andrew","email":"aroyle@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":860326,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70242008,"text":"70242008 - 2023 - A genetic warning system for a hierarchically structured wildlife monitoring framework","interactions":[],"lastModifiedDate":"2023-04-04T12:00:53.306947","indexId":"70242008","displayToPublicDate":"2022-12-22T06:53:20","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1450,"text":"Ecological Applications","active":true,"publicationSubtype":{"id":10}},"title":"A genetic warning system for a hierarchically structured wildlife monitoring framework","docAbstract":"

Genetic variation is a well-known indicator of population fitness yet is not typically included in monitoring programs for sensitive species. Additionally, most programs monitor populations at one scale, which can lead to potential mismatches with ecological processes critical to species' conservation. Recently developed methods generating hierarchically nested population units (i.e., clusters of varying scales) for greater sage-grouse (Centrocercus urophasianus) have identified population trend declines across spatiotemporal scales to help managers target areas for conservation. The same clusters used as a proxy for spatial scale can alert managers to local units (i.e., neighborhood-scale) with low genetic diversity, further facilitating identification of management targets. We developed a genetic warning system utilizing previously developed hierarchical population units to identify management-relevant areas with low genetic diversity within the greater sage-grouse range. Within this warning system we characterized conservation concern thresholds based on values of genetic diversity and developed a statistical model for microsatellite data to robustly estimate these values for hierarchically nested populations. We found that 41 of 224 neighborhood-scale clusters had low genetic diversity, 23 of which were coupled with documented local population trend decline. We also found evidence of cross-scale low genetic diversity in the small and isolated Washington population, unlikely to be reversed through typical local management actions alone. The combination of low genetic diversity and a declining population suggests relatively high conservation concern. Our findings could further facilitate conservation action prioritization in combination with population trend assessments and (or) local information, and act as a base-line of genetic diversity for future comparison. Importantly, the approach we used is broadly applicable across taxa.

","language":"English","publisher":"Ecological Society of America","doi":"10.1002/eap.2787","usgsCitation":"Zimmerman, S.J., Aldridge, C.L., O’Donnell, M.S., Edmunds, D.R., Coates, P.S., Prochazka, B.G., Fike, J., Cross, T.B., Fedy, B.C., and Oyler-McCance, S.J., 2023, A genetic warning system for a hierarchically structured wildlife monitoring framework: Ecological Applications, v. 33, no. 3, e2787, 18 p., https://doi.org/10.1002/eap.2787.","productDescription":"e2787, 18 p.","ipdsId":"IP-133541","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":445071,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/eap.2787","text":"Publisher Index Page"},{"id":435536,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9FATNI9","text":"USGS data release","linkHelpText":"Greater sage-grouse genetic warning system, western United States (ver 1.1, January 2023)"},{"id":435535,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P98Q5F6R","text":"USGS data release","linkHelpText":"Genotypes and cluster definitions for a range-wide greater sage-grouse dataset collected 2005-2017 (ver 1.1, January 2023)"},{"id":415157,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -102.07344624886372,\n 49.512419389230956\n ],\n [\n -125.31052090062897,\n 49.512419389230956\n ],\n [\n -125.31052090062897,\n 35.5228832956214\n ],\n [\n -102.07344624886372,\n 35.5228832956214\n ],\n [\n -102.07344624886372,\n 49.512419389230956\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"33","issue":"3","noUsgsAuthors":false,"publicationDate":"2023-01-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Zimmerman, Shawna J 0000-0003-3394-6102 szimmerman@usgs.gov","orcid":"https://orcid.org/0000-0003-3394-6102","contributorId":238076,"corporation":false,"usgs":true,"family":"Zimmerman","given":"Shawna","email":"szimmerman@usgs.gov","middleInitial":"J","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":868512,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Aldridge, Cameron L. 0000-0003-3926-6941 aldridgec@usgs.gov","orcid":"https://orcid.org/0000-0003-3926-6941","contributorId":191773,"corporation":false,"usgs":true,"family":"Aldridge","given":"Cameron","email":"aldridgec@usgs.gov","middleInitial":"L.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":false,"id":868513,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"O’Donnell, Michael S. 0000-0002-3488-003X odonnellm@usgs.gov","orcid":"https://orcid.org/0000-0002-3488-003X","contributorId":140876,"corporation":false,"usgs":true,"family":"O’Donnell","given":"Michael","email":"odonnellm@usgs.gov","middleInitial":"S.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":868514,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Edmunds, David R. 0000-0002-5212-8271 dedmunds@usgs.gov","orcid":"https://orcid.org/0000-0002-5212-8271","contributorId":152210,"corporation":false,"usgs":true,"family":"Edmunds","given":"David","email":"dedmunds@usgs.gov","middleInitial":"R.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":868515,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Coates, Peter S. 0000-0003-2672-9994 pcoates@usgs.gov","orcid":"https://orcid.org/0000-0003-2672-9994","contributorId":3263,"corporation":false,"usgs":true,"family":"Coates","given":"Peter","email":"pcoates@usgs.gov","middleInitial":"S.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":868516,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Prochazka, Brian G. 0000-0001-7270-5550 bprochazka@usgs.gov","orcid":"https://orcid.org/0000-0001-7270-5550","contributorId":174839,"corporation":false,"usgs":true,"family":"Prochazka","given":"Brian","email":"bprochazka@usgs.gov","middleInitial":"G.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":868518,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Fike, Jennifer A. 0000-0001-8797-7823","orcid":"https://orcid.org/0000-0001-8797-7823","contributorId":207268,"corporation":false,"usgs":true,"family":"Fike","given":"Jennifer A.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":868519,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Cross, Todd B.","contributorId":189267,"corporation":false,"usgs":false,"family":"Cross","given":"Todd","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":868517,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Fedy, Bradley C.","contributorId":191347,"corporation":false,"usgs":false,"family":"Fedy","given":"Bradley","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":868520,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Oyler-McCance, Sara J. 0000-0003-1599-8769 sara_oyler-mccance@usgs.gov","orcid":"https://orcid.org/0000-0003-1599-8769","contributorId":1973,"corporation":false,"usgs":true,"family":"Oyler-McCance","given":"Sara","email":"sara_oyler-mccance@usgs.gov","middleInitial":"J.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":868521,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70241953,"text":"70241953 - 2023 - Estimating phosphorus retention capacity of flow-through wetlands","interactions":[],"lastModifiedDate":"2023-04-03T11:47:46.606064","indexId":"70241953","displayToPublicDate":"2022-12-21T06:44:20","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1454,"text":"Ecological Engineering","active":true,"publicationSubtype":{"id":10}},"title":"Estimating phosphorus retention capacity of flow-through wetlands","docAbstract":"

A Bayesian hierarchical modeling approach is introduced to pool data properly from multiple flow-through wetlands to estimate wetland-specific long-term phosphorus retention capacity. By pooling data from multiple wetlands, we overcome the difficulties in estimating the effectiveness of using constructed and natural wetlands for nutrient reduction. The Bayesian hierarchical modeling approach reduces estimation uncertainty by shrinking wetland-specific estimates towards the overall average of the same quantity from multiple wetlands, facilitating information sharing across sites, thereby reducing the demand on sample sizes from individual wetlands and avoiding several common pitfalls of using large data (i.e., from multiple systems) induced by Simpson's paradox. In this paper, we develop a sequential updating framework to alleviate the computational burden of compiling and modeling data from multiple wetlands. We then demonstrate the sequential updating process to estimate retention capacity of a suite of wetlands in Ohio, USA. A total of four wetlands, representing both natural and constructed wetlands, were used. The estimated total phosphorus retention capacities range less than 0.01 to well over 1 ton per year per system. As wetland restoration initiatives expand around the Laurentian Great Lakes and nationally, this model serves as an important initial step in developing tools to meet nutrient reduction goals and standards. Extending this work, we have developed a publicly accessible on-line open computation platform that can help natural resource specialists better plan for wetland efficacy in the future.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecoleng.2022.106869","usgsCitation":"Qian, S.S., Arend, K.K., Jacquemin, S.J., Sullivan, S.M., and Kowalski, K., 2023, Estimating phosphorus retention capacity of flow-through wetlands: Ecological Engineering, v. 187, 106869, 8 p., https://doi.org/10.1016/j.ecoleng.2022.106869.","productDescription":"106869, 8 p.","ipdsId":"IP-142368","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":445078,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecoleng.2022.106869","text":"Publisher Index Page"},{"id":415049,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"187","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Qian, Song S.","contributorId":198934,"corporation":false,"usgs":false,"family":"Qian","given":"Song","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":868364,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Arend, Kristi K.","contributorId":303882,"corporation":false,"usgs":false,"family":"Arend","given":"Kristi","email":"","middleInitial":"K.","affiliations":[{"id":16232,"text":"Ohio Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":868365,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jacquemin, Stephen J","contributorId":303884,"corporation":false,"usgs":false,"family":"Jacquemin","given":"Stephen","email":"","middleInitial":"J","affiliations":[{"id":13348,"text":"Wright State University","active":true,"usgs":false}],"preferred":false,"id":868366,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sullivan, S. Mazeika Patricio","contributorId":303885,"corporation":false,"usgs":false,"family":"Sullivan","given":"S.","email":"","middleInitial":"Mazeika Patricio","affiliations":[{"id":36630,"text":"Ohio State University","active":true,"usgs":false}],"preferred":false,"id":868367,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kowalski, Kurt P. 0000-0002-8424-4701 kkowalski@usgs.gov","orcid":"https://orcid.org/0000-0002-8424-4701","contributorId":3768,"corporation":false,"usgs":true,"family":"Kowalski","given":"Kurt P.","email":"kkowalski@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":868368,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70263896,"text":"70263896 - 2023 - Validation of earthquake ground-motion models in southern California, USA, using precariously balanced rocks","interactions":[],"lastModifiedDate":"2025-02-27T15:51:42.500906","indexId":"70263896","displayToPublicDate":"2022-12-20T09:47:18","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1723,"text":"GSA Bulletin","active":true,"publicationSubtype":{"id":10}},"title":"Validation of earthquake ground-motion models in southern California, USA, using precariously balanced rocks","docAbstract":"

Accurate estimates of earthquake ground shaking rely on uncertain ground-motion models derived from limited instrumental recordings of historical earthquakes. A critical issue is that there is currently no method to empirically validate the resultant ground-motion estimates of these models at the timescale of rare, large earthquakes; this lack of validation causes great uncertainty in ground-motion estimates. Here, we address this issue and validate ground-motion estimates for southern California utilizing the unexceeded ground motions recorded by 20 precariously balanced rocks. We used cosmogenic 10Be exposure dating to model the age of the precariously balanced rocks, which ranged from ca. 1 ka to ca. 50 ka, and calculated their probability of toppling at different ground-motion levels. With this rock data, we then validated the earthquake ground motions estimated by the Uniform California Earthquake Rupture Forecast, Version 3 (UCERF3) seismic-source characterization and the Next Generation Attenuation (NGA)-West2 ground-motion models. We found that no ground-motion model estimated levels of earthquake ground shaking consistent with the observed continued existence of all 20 precariously balanced rocks. The ground-motion model I14 estimated ground-motion levels that were inconsistent with the most rocks; therefore, I14 was invalidated and removed. At a 2475 year mean return period, the removal of this invalid ground-motion model resulted in a 2–7% reduction in the mean and a 10–36% reduction in the 5th–95th fractile uncertainty of the ground-motion estimates. Our findings demonstrate the value of empirical data from precariously balanced rocks as a validation tool for removing invalid ground-motion models and, in turn, reducing the uncertainty in earthquake ground-motion estimates.

","language":"English","publisher":"Geological Society of America","doi":"10.1130/B36484.1","usgsCitation":"Rood, A.H., Rood, D., Balco, G., Stafford, P.J., Grant Ludwig, L., Kendrick, K.J., and Wilcken, K., 2023, Validation of earthquake ground-motion models in southern California, USA, using precariously balanced rocks: GSA Bulletin, v. 135, no. 9-10, p. 2179-2199, https://doi.org/10.1130/B36484.1.","productDescription":"21 p.","startPage":"2179","endPage":"2199","ipdsId":"IP-143199","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":482565,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -118,\n 34.6\n ],\n [\n -118,\n 33.6\n ],\n [\n -116,\n 33.6\n ],\n [\n -116,\n 34.6\n ],\n [\n -118,\n 34.6\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"135","issue":"9-10","noUsgsAuthors":false,"publicationDate":"2022-12-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Rood, Anna H.","contributorId":245478,"corporation":false,"usgs":false,"family":"Rood","given":"Anna","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":928942,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rood, Dylan","contributorId":167067,"corporation":false,"usgs":false,"family":"Rood","given":"Dylan","email":"","affiliations":[{"id":24608,"text":"Imperial College London","active":true,"usgs":false}],"preferred":false,"id":928943,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Balco, Greg","contributorId":347027,"corporation":false,"usgs":false,"family":"Balco","given":"Greg","email":"","affiliations":[{"id":13621,"text":"Lawrence Livermore National Laboratory","active":true,"usgs":false}],"preferred":false,"id":928944,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stafford, Peter J.","contributorId":261918,"corporation":false,"usgs":false,"family":"Stafford","given":"Peter","email":"","middleInitial":"J.","affiliations":[{"id":24608,"text":"Imperial College London","active":true,"usgs":false}],"preferred":false,"id":928945,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Grant Ludwig, Lisa","contributorId":245422,"corporation":false,"usgs":false,"family":"Grant Ludwig","given":"Lisa","email":"","affiliations":[{"id":34134,"text":"UC Irvine","active":true,"usgs":false}],"preferred":false,"id":928946,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kendrick, Katherine J. 0000-0002-9839-6861","orcid":"https://orcid.org/0000-0002-9839-6861","contributorId":207907,"corporation":false,"usgs":true,"family":"Kendrick","given":"Katherine","email":"","middleInitial":"J.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":928947,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Wilcken, Klaus","contributorId":351569,"corporation":false,"usgs":false,"family":"Wilcken","given":"Klaus","affiliations":[{"id":84009,"text":"Australian Nuclear Science and Technology Organisation","active":true,"usgs":false}],"preferred":false,"id":928948,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70238993,"text":"70238993 - 2023 - Five year analyses of vegetation response to restoration using rock detention structures in southeastern Arizona, United States","interactions":[],"lastModifiedDate":"2023-05-01T15:34:08.422765","indexId":"70238993","displayToPublicDate":"2022-12-19T07:20:57","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1547,"text":"Environmental Management","active":true,"publicationSubtype":{"id":10}},"title":"Five year analyses of vegetation response to restoration using rock detention structures in southeastern Arizona, United States","docAbstract":"

Rock detention structures (RDS) are used in restoration of riparian areas around the world. The purpose of this study was to analyze the effect of RDS installation on vegetation in terms of species abundance and composition. We present the results from 5 years of annual vegetation sampling which focused on short term non-woody vegetation response within the riparian channel at 3 restoration sites across southeastern Arizona. We examined the potential ways that RDS can preserve native species, encourage wetland species, and/or introduce nonnative species using a Control-Impact-Paired-Series study design. Species composition and frequency were measured within quadrats and zones on an annual basis. Multivariate bootstrap analyses were performed, including Bray-Curtis dissimilarity index and non-metric multidimensional scaling ordination. We found that response to RDS was variable and could be related to the level of degradation or proximity to groundwater. The non-degraded site did not show a response to RDS and the severely degraded site showed a slight increase in vegetation frequency, but the moderately degraded site experienced a significant increase. At the moderately degraded site, located between two historic ciénegas (desert wetlands), species composition shifted and nonnative species invaded, dominating the vegetation increase at this location. At the severely degraded site, pre-existing wetland species frequency increased in response to the installation of RDS. These findings extend the understanding of RDS effects on vegetation, provide scenarios to help land and water resource managers understand potential outcomes, and can assist in optimizing success for restoration projects.

","language":"English","publisher":"Springer Nature","doi":"10.1007/s00267-022-01762-0","usgsCitation":"Wilson, N., and Norman, L., 2023, Five year analyses of vegetation response to restoration using rock detention structures in southeastern Arizona, United States: Environmental Management, v. 71, p. 921-939, https://doi.org/10.1007/s00267-022-01762-0.","productDescription":"19 p.","startPage":"921","endPage":"939","ipdsId":"IP-139780","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":445086,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s00267-022-01762-0","text":"Publisher Index Page"},{"id":410788,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -109.06809425904859,\n 31.39517669949646\n ],\n [\n -109.06809425904859,\n 32.671239706816536\n ],\n [\n -111.56747161928966,\n 32.671239706816536\n ],\n [\n -111.56747161928966,\n 31.39517669949646\n ],\n [\n -109.06809425904859,\n 31.39517669949646\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"71","noUsgsAuthors":false,"publicationDate":"2022-12-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Wilson, Natalie R. 0000-0001-5145-1221","orcid":"https://orcid.org/0000-0001-5145-1221","contributorId":202534,"corporation":false,"usgs":true,"family":"Wilson","given":"Natalie R.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":859556,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Norman, Laura M. 0000-0002-3696-8406","orcid":"https://orcid.org/0000-0002-3696-8406","contributorId":203300,"corporation":false,"usgs":true,"family":"Norman","given":"Laura M.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":859557,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70239789,"text":"70239789 - 2023 - Wetland occupancy by duck broods in cropland-dominated landscapes of the United States Prairie Pothole Region","interactions":[],"lastModifiedDate":"2023-01-20T13:03:06.231565","indexId":"70239789","displayToPublicDate":"2022-12-19T07:00:39","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Wetland occupancy by duck broods in cropland-dominated landscapes of the United States Prairie Pothole Region","docAbstract":"

The Prairie Pothole Region (PPR) is globally important for breeding waterfowl but has been altered via wetland drainage and grassland conversion to accommodate agricultural land use. Thus, understanding the ecology of waterfowl in these highly modified landscapes is essential for their conservation. Brood occurrence is the cumulative outcome of key life-history events including pair formation and territory establishment, nest success, and early brood survival. We applied new technological advances in brood surveying methods to understand brood use of wetlands and how land use and wetland-specific factors influenced brood use of 413 wetlands in crop-dominated landscapes in the PPR of Iowa, Minnesota, North Dakota, and South Dakota, USA, during summers of 2018–2020. Dynamic occupancy models combining information from 2 visits throughout the year revealed no difference among the 4 states or between private and public lands, resulting in a region-wide annual wetland occupancy estimate of 0.41 (95% credible interval [CrI] = 0.26, 0.58). We assessed aquatic invertebrate forage availability, wetland and upland vegetation communities, and various water chemistry metrics in a subset (n = 225) of these wetlands to evaluate how landscape and wetland-specific factors influenced occupancy. The amount of grassland surrounding wetlands was the only variable to influence occupancy at a landscape scale, while wetland size, invertebrates, fish, and vegetation communities influenced occupancy at finer scales. Closer scrutiny of wetland area revealed occupancy was greater in small wetlands after controlling for total wetland area. Our results indicate the greatest constraint on brood occupancy across crop-dominated landscapes of the PPR in the United States was the occurrence of semipermanent wetlands suitable for brood rearing. Other factors, such as wetland vegetation or surrounding land use, had minor intervening influences on duck brood use and ducks were distributed invariant of wetland ownership or broad spatial processes occurring among states. These results demonstrated wetland conservation and restoration strategies are likely to yield gains in annual duck broods across this vast, altered, and highly modified landscape.

","language":"English","publisher":"The Wildlife Society","doi":"10.1002/jwmg.22347","usgsCitation":"Mitchell, B.J., Terry, C.V., Ringelman, K.M., Kemink, K., Anteau, M.J., and Janke, A.K., 2023, Wetland occupancy by duck broods in cropland-dominated landscapes of the United States Prairie Pothole Region: Journal of Wildlife Management, v. 87, no. 2, e22347, 26 p., https://doi.org/10.1002/jwmg.22347.","productDescription":"e22347, 26 p.","ipdsId":"IP-140006","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":445089,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/jwmg.22347","text":"Publisher Index Page"},{"id":412114,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Iowa, Minnesota, North Dakota, South Dakota","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -96.29653960243344,\n 48.97443267103543\n ],\n [\n -103.81695065949702,\n 49.04648442059704\n ],\n [\n -100.56637798862401,\n 47.79300521453408\n ],\n [\n -99.68784483433396,\n 46.08364286612411\n ],\n [\n -99.16072494176002,\n 43.40115466919687\n ],\n [\n -97.57936526403823,\n 42.85616461776857\n ],\n [\n -96.17371221717424,\n 41.52182814884887\n ],\n [\n -93.7138193851624,\n 41.91528041046746\n ],\n [\n -93.18669949258846,\n 42.75948597666104\n ],\n [\n -95.43748196681628,\n 46.96875525238039\n ],\n [\n -96.29653960243344,\n 48.97443267103543\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"87","issue":"2","noUsgsAuthors":false,"publicationDate":"2022-12-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Mitchell, Blake J","contributorId":301081,"corporation":false,"usgs":false,"family":"Mitchell","given":"Blake","email":"","middleInitial":"J","affiliations":[{"id":6911,"text":"Iowa State University","active":true,"usgs":false}],"preferred":false,"id":861960,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Terry, Catrina V","contributorId":301082,"corporation":false,"usgs":false,"family":"Terry","given":"Catrina","email":"","middleInitial":"V","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":861961,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ringelman, Kevin M","contributorId":301083,"corporation":false,"usgs":false,"family":"Ringelman","given":"Kevin","email":"","middleInitial":"M","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":861962,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kemink, Kaylan M","contributorId":301084,"corporation":false,"usgs":false,"family":"Kemink","given":"Kaylan M","affiliations":[{"id":65300,"text":"Ducks Unlimited Inc","active":true,"usgs":false}],"preferred":false,"id":861963,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Anteau, Michael J. 0000-0002-5173-5870 manteau@usgs.gov","orcid":"https://orcid.org/0000-0002-5173-5870","contributorId":3427,"corporation":false,"usgs":true,"family":"Anteau","given":"Michael","email":"manteau@usgs.gov","middleInitial":"J.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":861964,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Janke, Adam K. 0000-0003-2781-7857","orcid":"https://orcid.org/0000-0003-2781-7857","contributorId":130959,"corporation":false,"usgs":false,"family":"Janke","given":"Adam","email":"","middleInitial":"K.","affiliations":[{"id":7176,"text":"Dept of Natl Res Mgmt, SDSU, Brookings, SD","active":true,"usgs":false}],"preferred":false,"id":861965,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ]}