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Recent declines of grassland bird populations in North America are linked to habitat loss and fragmentation associated with agricultural practices. One tool used to conserve soil, water and wildlife habitat on agricultural fields is the U.S. Department of Agriculture’s Conservation Reserve Program (CRP), the largest agricultural conservation program in the United States. Managers and conservationists recognize CRP as an important component of conserving grassland birds in the central portion of the United States. However, recent widespread expiration of CRP contracts could negatively influence grassland bird populations. Few studies have evaluated how former CRP-enrolled fields may function as grassland bird habitat. In this paper, we analyzed data from a long-term (1990–2017) study aimed at comparing grassland bird abundance (24 species) between idled CRP grasslands and fields where the CRP contracts expired. Some of these fields where contracts expired were maintained as pasture or hayland, and others were converted back to cropland. Estimated abundances of most species were considerably higher in idled CRP than in fields with expired CRP contracts. Post-CRP land use also appeared to affect most bird abundances, with lower abundance in grazed grasslands and haylands relative to idled CRP, but higher abundance than cropland. The responses of obligate and facultative grassland specialists to post-CRP management varied among species, with some being negative and some being positive depending on post-CRP land use, which is unsurprising given the variable habitat requirements of grassland birds. Our results have implications for wildlife managers who must design conservation strategies around the land use decisions of private landowners. Our results support the idea of maintaining a mosaic of undisturbed CRP grasslands and post-CRP grasslands that are hayed or grazed, which should guarantee some undisturbed nesting cover in the landscape for some bird species and some disturbed grasslands that may have long-term benefits for other species.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.gecco.2023.e02629","usgsCitation":"Igl, L., Buhl, D.A., Post van der Burg, M., and Johnson, D., 2023, Converting CRP grasslands to cropland, grazing land, or hayland: Effects on breeding bird abundances in the northern Great Plains of the United States: Global Ecology and Conservation, v. 46, https://doi.org/10.1016/j.gecco.2023.e02629.","productDescription":"e02629, 13 p.","startPage":"13 pages","ipdsId":"IP-149095","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":442119,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.gecco.2023.e02629","text":"Publisher Index Page"},{"id":421165,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Minnesota, Montana, North Dakota, South 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\"}}]}","volume":"46","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Igl, Lawrence 0000-0003-0530-7266","orcid":"https://orcid.org/0000-0003-0530-7266","contributorId":217211,"corporation":false,"usgs":true,"family":"Igl","given":"Lawrence","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":884160,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Buhl, Deborah A. 0000-0002-8563-5990 dbuhl@usgs.gov","orcid":"https://orcid.org/0000-0002-8563-5990","contributorId":146226,"corporation":false,"usgs":true,"family":"Buhl","given":"Deborah","email":"dbuhl@usgs.gov","middleInitial":"A.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":884161,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Post van der Burg, Max 0000-0002-3943-4194","orcid":"https://orcid.org/0000-0002-3943-4194","contributorId":219400,"corporation":false,"usgs":true,"family":"Post van der Burg","given":"Max","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":884162,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Johnson, Douglas H. 0000-0002-7778-6641","orcid":"https://orcid.org/0000-0002-7778-6641","contributorId":221269,"corporation":false,"usgs":true,"family":"Johnson","given":"Douglas H.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":884163,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70248743,"text":"70248743 - 2023 - Native amphibian toxin reduces invasive crayfish feeding with potential benefits to stream biodiversity","interactions":[],"lastModifiedDate":"2023-09-19T11:58:48.720642","indexId":"70248743","displayToPublicDate":"2023-09-13T06:55:27","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":16865,"text":"BMC Ecological Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Native amphibian toxin reduces invasive crayfish feeding with potential benefits to stream biodiversity","docAbstract":"

Background

Biodiversity is generally reduced when non-native species invade an ecosystem. Invasive crayfish, Procambarus clarkii, populate California freshwater streams, and in the Santa Monica Mountains (Los Angeles, USA), their introduction has led to trophic cascades due to omnivorous feeding behavior and a rapid rate of population growth. The native California newt, Taricha torosa, possesses a neurotoxin, tetrodotoxin (TTX), that affects freshwater animal behavior. Given P. clarkii has a limited evolutionary history with TTX, we hypothesized that TTX may affect crayfish feeding behaviors. To determine if TTX affects P. clarkii behavior, we measured cumulative movement and various feeding behaviors of P. clarkii exposed to (i) waterborne, ecologically realistic concentrations of TTX (~ 3.0 × 10− 8 moles/L), (ii) an anuran chemical cue to account for intraguild cues, or (iii) a T. torosa chemical cue with quantitated TTX in it (~ 6.2 × 10− 8 moles/L).

Results

We found that the presence of TTX in any form significantly reduced crayfish movement and decreased the amount of food consumed over time. Crayfish responses to the anuran treatment did not significantly differ from controls.

Conclusion

Our laboratory results show that naturally occurring neurotoxin from native California newts limits invasive crayfish foraging and feeding rates, which may play a role in preserving local stream ecosystems by limiting invasive crayfish behaviors that are detrimental to biodiversity.

","language":"English","publisher":"Springer","doi":"10.1186/s12862-023-02162-6","usgsCitation":"Bucciarelli, G.M., Smith, S.J., Choe, J.J., Shin, P.D., Fisher, R., and Kats, L.B., 2023, Native amphibian toxin reduces invasive crayfish feeding with potential benefits to stream biodiversity: BMC Ecological Evolution, v. 23, 51, 10 p., https://doi.org/10.1186/s12862-023-02162-6.","productDescription":"51, 10 p.","ipdsId":"IP-153361","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":442121,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1186/s12862-023-02162-6","text":"Publisher Index Page"},{"id":420942,"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 -119.10835949859933,\n 34.24972494086572\n ],\n [\n -119.10835949859933,\n 33.95419558307488\n ],\n [\n -118.36160958124017,\n 33.95419558307488\n ],\n [\n -118.36160958124017,\n 34.24972494086572\n ],\n [\n -119.10835949859933,\n 34.24972494086572\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"23","noUsgsAuthors":false,"publicationDate":"2023-09-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Bucciarelli, Gary M.","contributorId":209642,"corporation":false,"usgs":false,"family":"Bucciarelli","given":"Gary","email":"","middleInitial":"M.","affiliations":[{"id":13399,"text":"UCLA","active":true,"usgs":false}],"preferred":false,"id":883402,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Smith, Sierra J.","contributorId":329828,"corporation":false,"usgs":false,"family":"Smith","given":"Sierra","email":"","middleInitial":"J.","affiliations":[{"id":37949,"text":"Pepperdine University","active":true,"usgs":false}],"preferred":false,"id":883403,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Choe, Justin J.","contributorId":329829,"corporation":false,"usgs":false,"family":"Choe","given":"Justin","email":"","middleInitial":"J.","affiliations":[{"id":37949,"text":"Pepperdine University","active":true,"usgs":false}],"preferred":false,"id":883404,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Shin, Phoebe D.","contributorId":329831,"corporation":false,"usgs":false,"family":"Shin","given":"Phoebe","email":"","middleInitial":"D.","affiliations":[{"id":37949,"text":"Pepperdine University","active":true,"usgs":false}],"preferred":false,"id":883405,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fisher, Robert N. 0000-0002-2956-3240","orcid":"https://orcid.org/0000-0002-2956-3240","contributorId":51675,"corporation":false,"usgs":true,"family":"Fisher","given":"Robert N.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":883406,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kats, Lee B.","contributorId":208330,"corporation":false,"usgs":false,"family":"Kats","given":"Lee","email":"","middleInitial":"B.","affiliations":[{"id":37783,"text":"Seaver College, Pepperdine University","active":true,"usgs":false}],"preferred":false,"id":883407,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70248277,"text":"sir20235087 - 2023 - Approaches for assessing flows, concentrations, and loads of highway and urban runoff and receiving-stream stormwater in southern New England with the Stochastic Empirical Loading and Dilution Model (SELDM)","interactions":[],"lastModifiedDate":"2026-03-12T21:08:34.632448","indexId":"sir20235087","displayToPublicDate":"2023-09-12T19:46:00","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2023-5087","displayTitle":"Approaches for Assessing Flows, Concentrations, and Loads of Highway and Urban Runoff and Receiving-Stream Stormwater in Southern New England With the Stochastic Empirical Loading and Dilution Model (SELDM)","title":"Approaches for assessing flows, concentrations, and loads of highway and urban runoff and receiving-stream stormwater in southern New England with the Stochastic Empirical Loading and Dilution Model (SELDM)","docAbstract":"

The Stochastic Empirical Loading and Dilution Model (SELDM) was designed to help quantify the risk of adverse effects of runoff on receiving waters, the potential need for mitigation measures, and the potential effectiveness of such management measures for reducing these risks. SELDM is calibrated using representative hydrological and water-quality input statistics. This report by the U.S. Geological Survey, in cooperation with the Federal Highway Administration and the Connecticut, Massachusetts, and Rhode Island Departments of Transportation, documents approaches for assessing flows, concentrations, and loads of highway- and urban-runoff and receiving-stream stormwater in southern New England with SELDM. In this report, the term “urban runoff” is used to identify stormwater flows from developed areas with impervious fractions ranging from 10 to 100 percent without regard to the U.S. Census Bureau designation for any given location. There are more than 48,000 delineated road-stream crossings in southern New England, but because there are relatively few precipitation, streamflow, and water-quality monitoring sites in this area, methods were needed to simulate conditions at unmonitored sites. This report documents simulation methods, methods for interpreting stochastic model results, sensitivity analyses to identify the most critical variables of concern, and examples demonstrating how simulation results can be used to inform scientific decision-making processes. Results of 7,511 SELDM simulations were used to do the sensitivity analyses and provide information decisionmakers can use to address runoff-quality issues in southern New England and other areas of the Nation.

The sensitivity analyses indicate the relatively strong effect of input variables on variations in output results. These analyses indicate that highway and urban runoff quality and upstream water-quality statistics that vary considerably from site to site have the greatest effect on simulated results. Further data are needed to improve available water-quality statistics, and because the number of monitored sites will never approach the number of sites of interest for water-quality management, research is needed to identify methods to select statistics for unmonitored sites and quantify the uncertainties in the selection process. Hydrologically, prestorm streamflows with and without zero flows are the most sensitive and therefore the most important hydrologic variables to quantify. Results of analyses also are sensitive to statistics used for simulating structural best management practices.

Although the focus of the report is on data, statistics, simulation methods, and methods to interpret stochastic simulations, the examples in this report provide results that can be used to inform scientific decision-making processes. The results of 441 simulations that provide regional and site-specific highway and urban runoff yields across southern New England can be used for total maximum daily load analyses. The example stormwater load analysis done for 16 tributaries of the Narragansett Bay demonstrates that highway nitrogen loads are a small fraction of stormwater loads (about 3.6 percent), and a much smaller fraction of all nitrogen loads to the bay, primarily because highways have a small footprint on the land. Examples evaluating the potential effectiveness of end-of-pipe treatment indicate that offsite treatment is warranted in developed areas, and land conservation may be an effective mitigation strategy. The results of these analyses are consistent with conclusions from other simulation and monitoring studies.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235087","collaboration":"Prepared in cooperation with the Federal Highway Administration and the Connecticut, Massachusetts, and Rhode Island Departments of Transportation","usgsCitation":"Granato, G.E., Spaetzel, A.B., and Jeznach, L.C., 2023, Approaches for assessing flows, concentrations, and loads of highway and urban runoff and receiving-stream stormwater in southern New England with the Stochastic Empirical Loading and Dilution Model (SELDM): U.S. Geological Survey Scientific Investigations Report 2023–5087, 152 p., https://doi.org/10.3133/sir20235087.","productDescription":"Report: xii, 152 p.; Software Release; 4 Data Releases","numberOfPages":"152","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-133112","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":501050,"rank":12,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_115402.htm","linkFileType":{"id":5,"text":"html"}},{"id":420555,"rank":8,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9K0Y7XR","text":"USGS data release","linkHelpText":"Model archive for analysis of the effects of impervious cover on receiving-water quality with the Stochastic Empirical Loading Dilution Model (SELDM)"},{"id":420556,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9CZNIH5","text":"USGS data release","linkHelpText":"Model archive for analysis of flows, concentrations, and loads of highway and urban runoff and receiving-stream stormwater in southern New England with the Stochastic Empirical Loading and Dilution Model (SELDM)"},{"id":420554,"rank":7,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9B02EUZ","text":"USGS data release","linkHelpText":"Model archive for analysis of long-term annual yields of highway and urban runoff in selected areas of California with the Stochastic Empirical Loading Dilution Model (SELDM)"},{"id":420557,"rank":9,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9VK1MCG","text":"USGS data release","linkHelpText":"Basin characteristics and point locations of road crossings in Connecticut, Massachusetts, and Rhode Island for highway-runoff mitigation analyses using the Stochastic Empirical Loading and Dilution Model"},{"id":420548,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2023/5087/coverthb.jpg"},{"id":420549,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2023/5087/sir20235087.pdf","text":"Report","size":"8.64 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2023-5087"},{"id":420552,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2023/5087/images/"},{"id":420887,"rank":11,"type":{"id":35,"text":"Software Release"},"url":"https://doi.org/10.5066/P9PYG7T5","text":"USGS software release","linkHelpText":"- Stochastic Empirical Loading and Dilution Model (SELDM) software archive"},{"id":420551,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2023/5087/sir20235087.XML"},{"id":420553,"rank":10,"type":{"id":35,"text":"Software Release"},"url":"https://doi.org/10.5066/P9XBPIOB","text":"USGS software release","linkHelpText":"- Best management practices statistical estimator (BMPSE) version 1.2.0"},{"id":420550,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20235087/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2023-5087"}],"country":"United States","state":"Connecticut, Massachusetts, New Hampshire, Rhode Island, Vermont","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -73.28249194123347,\n 42.97558594616143\n ],\n [\n -73.81823969745555,\n 41.00628384122689\n ],\n [\n -69.72117184187273,\n 40.9949482400483\n ],\n [\n -69.72117184187273,\n 42.97558594616143\n ],\n [\n -73.28249194123347,\n 42.97558594616143\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"

Director, New England Water Science Center
U.S. Geological Survey
10 Bearfoot Road
Northborough, MA 01532

","tableOfContents":"","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"publishedDate":"2023-09-12","noUsgsAuthors":false,"publicationDate":"2023-09-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Granato, Gregory E. 0000-0002-2561-9913","orcid":"https://orcid.org/0000-0002-2561-9913","contributorId":203250,"corporation":false,"usgs":true,"family":"Granato","given":"Gregory E.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":882225,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Spaetzel, Alana B. 0000-0002-9871-812X","orcid":"https://orcid.org/0000-0002-9871-812X","contributorId":240935,"corporation":false,"usgs":true,"family":"Spaetzel","given":"Alana","email":"","middleInitial":"B.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":882226,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jeznach, Lillian C. 0000-0002-5476-9232","orcid":"https://orcid.org/0000-0002-5476-9232","contributorId":297153,"corporation":false,"usgs":true,"family":"Jeznach","given":"Lillian","email":"","middleInitial":"C.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":882227,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70248428,"text":"ofr20231071 - 2023 - Southern (California) sea otter population status and trends at San Nicolas Island, 2020–2023","interactions":[],"lastModifiedDate":"2023-09-13T13:50:49.576331","indexId":"ofr20231071","displayToPublicDate":"2023-09-12T12:49:56","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2023-1071","displayTitle":"Southern (California) Sea Otter Population Status and Trends at San Nicolas Island, 2020–2023","title":"Southern (California) sea otter population status and trends at San Nicolas Island, 2020–2023","docAbstract":"

The population of southern sea otters (Enhydra lutris nereis) at San Nicolas Island, California, has been monitored annually since the translocation of 140 southern sea otters to the island was completed in 1990. Monitoring efforts have varied in frequency and type across years. In 2017, the U.S. Navy and the U.S. Fish and Wildlife Service initiated a southern sea otter monitoring and research plan to determine the effects of military readiness activities on the growth or decline of the southern sea otter population at San Nicolas Island. The southern sea otter is the only subspecies of sea otter in California (hereafter, “sea otter\"). The monitoring program, at its basic level, includes seasonal surveys of population abundance, distribution, and foraging activity. From 2020 to 2023, we measured a 10-percent per annum increase in population abundance (95-percent confidence interval =0–20 percent), with 146 total individuals as of April 2023. Coinciding with the recent population growth, the sea otter distribution, which previously tended to concentrate on the island’s west end during 2003–2006 before shifting toward more use in the north and south sides during 2017–2019, appears to have shifted again during 2020–2023 to concentrate at the island’s east end. Forage data were collected between February 2020 and April 2023. There was a total of 773 forage dives in 60 forage bouts, with most of the identified prey on successful dives (n=401) recorded as sea urchins (66 percent), followed by bivalves (15 percent), snails (12 percent), and crabs (5.2 percent). Two lobsters and three abalone also were identified among the sea otter prey. Estimates of energy intake rates averaged 14.0 kilocalories per minute (95-percent confidence interval =10.8–17.2 kilocalories per minute). Monitoring data from the past two decades indicate that sea otters at San Nicolas Island have maintained a steady pattern of energy intake and population growth characteristic of a robust population, including a sixfold growth between 2000 and 2023. There was no conclusive evidence of density-dependent effects based on these patterns; however, estimates of energy intake rates for 2020–2023 were slightly lower than previous estimates from 2017 to 2019. Additionally, subtidal monitoring results at four sites around San Nicolas Island indicated that counts of purple sea urchins (Strongylocentrotus purpuratus) have increased between 2003 and 2023, whereas sea otter foraging surveys completed during the same period revealed that some sea otters have shifted toward higher consumption of purple sea urchins and bivalves compared to red sea urchins (S. fransicanus), which generally are the preferred larger prey of sea otters. These results contribute to the understanding of population dynamics and to the conservation and planning of future monitoring and research of sea otters at San Nicolas Island.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20231071","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service and the U.S. Navy","programNote":"Ecosystems Mission Area—Species Management Research Program","usgsCitation":"Yee, J.L., Tomoleoni, J.A., Kenner, M.C., Fujii, J.A., Bentall, G.B., Staedler, M.M., and Hatfield, B.B., 2023, Southern (California) sea otter population status and trends at San Nicolas Island, 2020–2023: U.S. Geological Survey Open-File Report 2023–1071, 37 p., https://doi.org/10.3133/ofr20231071.","productDescription":"vii, 37 p.","numberOfPages":"37","onlineOnly":"Y","ipdsId":"IP-155128","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":420734,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20231071/full"},{"id":420730,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2023/1071/covrthb.jpg"},{"id":420731,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2023/1071/ofr20231071.pdf","text":"Report","size":"11 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":420732,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2023/1071/ofr20231071.xml"},{"id":420733,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2023/1071/images"}],"country":"United States","state":"California","otherGeospatial":"San Nicolas Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -119.41914133101146,\n 33.23095571590274\n ],\n [\n -119.5256785251456,\n 33.28967086732948\n ],\n [\n -119.583789721946,\n 33.28157457228808\n ],\n [\n -119.57410452247933,\n 33.24816941739742\n ],\n [\n -119.54504892407897,\n 33.22791765206338\n ],\n [\n -119.47119927814498,\n 33.20867413062352\n ],\n [\n -119.43730108001157,\n 33.21576434144701\n ],\n [\n -119.41914133101146,\n 33.23095571590274\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"

Western Ecological Research Center
U.S. Geological Survey
3020 State University Drive East
Sacramento, California 95819

","tableOfContents":"","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"publishedDate":"2023-09-12","noUsgsAuthors":false,"publicationDate":"2023-09-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Yee, Julie L. 0000-0003-1782-157X julie_yee@usgs.gov","orcid":"https://orcid.org/0000-0003-1782-157X","contributorId":3246,"corporation":false,"usgs":true,"family":"Yee","given":"Julie","email":"julie_yee@usgs.gov","middleInitial":"L.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":882886,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tomoleoni, Joseph A. 0000-0001-6980-251X jtomoleoni@usgs.gov","orcid":"https://orcid.org/0000-0001-6980-251X","contributorId":167551,"corporation":false,"usgs":true,"family":"Tomoleoni","given":"Joseph","email":"jtomoleoni@usgs.gov","middleInitial":"A.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":882887,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kenner, Michael C. 0000-0003-4659-461X","orcid":"https://orcid.org/0000-0003-4659-461X","contributorId":208151,"corporation":false,"usgs":true,"family":"Kenner","given":"Michael","email":"","middleInitial":"C.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":882888,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fujii, Jessica A. 0000-0003-4794-479X","orcid":"https://orcid.org/0000-0003-4794-479X","contributorId":196602,"corporation":false,"usgs":false,"family":"Fujii","given":"Jessica","email":"","middleInitial":"A.","affiliations":[],"preferred":true,"id":882889,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bentall, Gena B. 0000-0001-5448-1573","orcid":"https://orcid.org/0000-0001-5448-1573","contributorId":43103,"corporation":false,"usgs":true,"family":"Bentall","given":"Gena","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":882890,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Staedler, Michelle M. 0000-0002-1101-6580","orcid":"https://orcid.org/0000-0002-1101-6580","contributorId":222317,"corporation":false,"usgs":true,"family":"Staedler","given":"Michelle","email":"","middleInitial":"M.","affiliations":[{"id":6953,"text":"Monterey Bay Aquarium","active":true,"usgs":false}],"preferred":true,"id":882891,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hatfield, Brian B. 0000-0003-1432-2660 brian_hatfield@usgs.gov","orcid":"https://orcid.org/0000-0003-1432-2660","contributorId":147917,"corporation":false,"usgs":true,"family":"Hatfield","given":"Brian","email":"brian_hatfield@usgs.gov","middleInitial":"B.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":882892,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70250212,"text":"70250212 - 2023 - Transferring deep learning models for hydrographic feature extraction from IfSAR data in Alaska","interactions":[],"lastModifiedDate":"2023-11-28T17:24:31.851807","indexId":"70250212","displayToPublicDate":"2023-09-12T11:18:25","publicationYear":"2023","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Transferring deep learning models for hydrographic feature extraction from IfSAR data in Alaska","docAbstract":"The National Hydrography Dataset (NHD) managed by the U.S. Geological Survey (USGS) is being updated with higher-quality feature representations through efforts that derive hydrography from 3DEP HR elevation datasets. Deriving hydrography from elevation through traditional flow routing and interactive methods is a complex, time-consuming process that must be tailored for different hydrogeomorphic conditions. The large volume of surface water features and HR remote sensing data make manual annotation of the water features over the entire nation infeasible. Furthermore, annual and seasonal variations of surface waters warrant some level of periodic updates to hydrography. Advances in deep learning technologies provide an opportunity to automate hydrography extraction and scale up the process to a nationwide level. One major challenge, however, is the effect of spatial heterogeneity due to the wide variety of hydrogeomorphic conditions in the United States. In other words, it is unclear how a deep learning model pre-trained in one set of hydrogeomorphic conditions can be effectively applied to other conditions for hydrographic feature extraction. This paper aims to provide some clarity in this regard by testing automated deep learning and its transferability to the extraction of hydrography from digital elevation model (DEM) data spanning a range of hydrogeomorphic conditions in Alaska. In transfer learning, the knowledge (e.g., neural network weights) from one domain is transferred to other domains and thereby decrease training requirements in the target domain.","conferenceTitle":"GIScience 2023 Workshop on CartoAI: AI for cartography","conferenceDate":"September 12-15, 2023","conferenceLocation":"Leeds, United Kingdom","language":"English","publisher":"ICA Commission on Multiscale Cartography","usgsCitation":"Stanislawski, L.V., Jaroenchai, N., Wang, S., Shavers, E.J., Duffy, A., Thiem, P.T., Jiang, Z., and Camerer, A., 2023, Transferring deep learning models for hydrographic feature extraction from IfSAR data in Alaska, GIScience 2023 Workshop on CartoAI: AI for cartography, Leeds, United Kingdom, September 12-15, 2023, 3 p.","productDescription":"3 p.","ipdsId":"IP-156657","costCenters":[{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"links":[{"id":423015,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":423004,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://cartoai.github.io/giscience2023/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -154.78252936612796,\n 71.06703147535433\n ],\n [\n -160.1834860755645,\n 68.98584856236955\n ],\n [\n -158.7680908656647,\n 63.65325869193444\n ],\n [\n -142.69648224587866,\n 62.32431074447908\n ],\n [\n -142.64727236190666,\n 70.42721281931796\n ],\n [\n -154.78252936612796,\n 71.06703147535433\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Stanislawski, Larry V. 0000-0002-9437-0576 lstan@usgs.gov","orcid":"https://orcid.org/0000-0002-9437-0576","contributorId":3386,"corporation":false,"usgs":true,"family":"Stanislawski","given":"Larry","email":"lstan@usgs.gov","middleInitial":"V.","affiliations":[{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true},{"id":404,"text":"NGTOC Rolla","active":true,"usgs":true}],"preferred":true,"id":888921,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jaroenchai, Nattapon","contributorId":267318,"corporation":false,"usgs":false,"family":"Jaroenchai","given":"Nattapon","email":"","affiliations":[{"id":38021,"text":"University of Illinois Urbana-Champaign","active":true,"usgs":false}],"preferred":false,"id":888922,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wang, Shaowen","contributorId":198966,"corporation":false,"usgs":false,"family":"Wang","given":"Shaowen","email":"","affiliations":[],"preferred":false,"id":888923,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Shavers, Ethan J. 0000-0001-9470-5199 eshavers@usgs.gov","orcid":"https://orcid.org/0000-0001-9470-5199","contributorId":206890,"corporation":false,"usgs":true,"family":"Shavers","given":"Ethan","email":"eshavers@usgs.gov","middleInitial":"J.","affiliations":[{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"preferred":true,"id":888924,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Duffy, Alexander 0000-0001-6036-0583","orcid":"https://orcid.org/0000-0001-6036-0583","contributorId":299070,"corporation":false,"usgs":false,"family":"Duffy","given":"Alexander","email":"","affiliations":[{"id":64752,"text":"University of Missouri Science & Technology","active":true,"usgs":false}],"preferred":false,"id":888925,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Thiem, Philip T. 0000-0002-3324-2589","orcid":"https://orcid.org/0000-0002-3324-2589","contributorId":287990,"corporation":false,"usgs":true,"family":"Thiem","given":"Philip","email":"","middleInitial":"T.","affiliations":[{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"preferred":true,"id":888926,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Jiang, Zhe","contributorId":267317,"corporation":false,"usgs":false,"family":"Jiang","given":"Zhe","email":"","affiliations":[{"id":36730,"text":"University of Alabama","active":true,"usgs":false}],"preferred":false,"id":888927,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Camerer, Adam","contributorId":331850,"corporation":false,"usgs":false,"family":"Camerer","given":"Adam","email":"","affiliations":[{"id":26996,"text":"Missouri University of Science & Technology","active":true,"usgs":false}],"preferred":false,"id":888928,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70248283,"text":"cir1510 - 2023 - Colorado River Basin Actionable and Strategic Integrated Science and Technology (ASIST) pilot project progress toward an information management and technology plan","interactions":[],"lastModifiedDate":"2023-09-12T18:55:36.46567","indexId":"cir1510","displayToPublicDate":"2023-09-12T10:25:00","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":307,"text":"Circular","code":"CIR","onlineIssn":"2330-5703","printIssn":"1067-084X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1510","displayTitle":"Colorado River Basin Actionable and Strategic Integrated Science and Technology (ASIST) Pilot Project Progress Toward an Information Management and Technology Plan","title":"Colorado River Basin Actionable and Strategic Integrated Science and Technology (ASIST) pilot project progress toward an information management and technology plan","docAbstract":"

Executive Summary

The U.S. Geological Survey carries out a wide variety of multidisciplinary science projects through the Bureau’s regions, mission areas, programs, and science centers. However, this structure can limit interactions among individual scientists, segregate data holdings, and make it difficult to apply holistic, interdisciplinary science. In addition, technological advances in sensors, data storage and analysis, computing power, and networking have resulted in an exponential growth in the volume, variety, and complexity of data. To address some of these challenges, the U.S. Geological Survey initiated the Colorado River Basin Actionable and Strategic Integrated Science and Technology (ASIST) pilot project to facilitate interdisciplinary science in the drought-stricken basin and apply information management and technology (IMT) resources that can be used to deliver actionable science efficiently and effectively.

In fiscal year 2021, the Data Management and Advanced Technology subgroup of the ASIST pilot project worked toward developing an IMT plan that includes several advanced IMT solutions that are being implemented Bureau-wide by the Office of the Associate Chief Information Officer. This plan identifies applications, opportunities, and steps to leverage new and existing technologies, data, models, and knowledge to support integrated science projects across the Colorado River Basin. The subgroup also created an inventory of available IMT resources and their locations. The Colorado River Basin ASIST pilot project also developed a multiyear approach to build capacity for supporting integrated science projects in the Colorado River Basin, which provides an advanced IMT framework for expediting the production of interdisciplinary science related to the basin.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/cir1510","usgsCitation":"Anderson, E.D., Erxleben, J.R., Qi, S.L., Monroe, A.P., and Dahm, K.G., 2023, Colorado River Basin Actionable and Strategic Integrated Science and Technology (ASIST) pilot project progress toward an information management and technology plan: U.S. Geological Survey Circular 1510, 11 p., https://doi.org/10.3133/cir1510.","productDescription":"viii, 10 p.","onlineOnly":"Y","ipdsId":"IP-131022","costCenters":[{"id":64844,"text":"Rocky Mountain Region Director’s Office","active":true,"usgs":true}],"links":[{"id":420721,"rank":9,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/circ/1510/images"},{"id":420626,"rank":8,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20221040","text":"USGS Open-File Report 2022-1040","linkHelpText":"Presented Abstracts from the U.S. Geological Survey 2020 Rocky Mountain Region Science Exchange (September 15–17, 2020)"},{"id":420625,"rank":7,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/fs20223051","text":"USGS Fact Sheet 2022-3051","linkHelpText":"U.S. Geological Survey Colorado River Basin Actionable and Strategic Integrated Science and Technology (ASIST)—Information Management Technology Plan"},{"id":420590,"rank":6,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/fs20223016","text":"USGS Fact Sheet 2022-3016","linkHelpText":"Colorado River Basin Actionable and Strategic Integrated Science and Technology (ASIST)"},{"id":420589,"rank":5,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/fs20223010","text":"USGS Fact Sheet 2022-3010","linkHelpText":"Addressing Stakeholder Science Needs for Integrated Drought Science in the Colorado River Basin"},{"id":420624,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/cir1502","text":"USGS Circular 1502","linkHelpText":"Colorado River Basin Actionable and Strategic Integrated Science and Technology Project—Science Strategy"},{"id":420627,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/cir1483","text":"USGS Circular 1483","linkHelpText":"Rocky Mountain Region Science Exchange 2020—EarthMAP and the Colorado River Basin"},{"id":420588,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/circ/1510/cir1510.pdf","text":"Report","size":"4.12 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Circular 1510"},{"id":420587,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/circ/1510/coverthb.jpg"},{"id":420735,"rank":11,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/cir1510/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"Circular 1510"},{"id":420722,"rank":10,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/circ/1510/cir1510.xml"}],"country":"United States","otherGeospatial":"Colorado River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -107.50163992210821,\n 41.074060046257415\n ],\n [\n -117.48373547769216,\n 41.074060046257415\n ],\n [\n -117.48373547769216,\n 30.63237394457815\n ],\n [\n -107.50163992210821,\n 30.63237394457815\n ],\n [\n -107.50163992210821,\n 41.074060046257415\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"

Director, Region 7 - Upper Colorado Basin
U.S. Geological Survey
Box 25046, MS 911
Denver, CO 80225

","tableOfContents":"","publishedDate":"2023-09-12","noUsgsAuthors":false,"publicationDate":"2023-09-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Anderson, Eric D. 0000-0002-0138-6166","orcid":"https://orcid.org/0000-0002-0138-6166","contributorId":202072,"corporation":false,"usgs":true,"family":"Anderson","given":"Eric D.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":882263,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Erxleben, Jennifer R. 0000-0002-4060-0241","orcid":"https://orcid.org/0000-0002-4060-0241","contributorId":299423,"corporation":false,"usgs":true,"family":"Erxleben","given":"Jennifer","email":"","middleInitial":"R.","affiliations":[{"id":5066,"text":"Office of the Director USGS","active":true,"usgs":true}],"preferred":true,"id":882264,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Qi, Sharon L. 0000-0001-7278-4498 slqi@usgs.gov","orcid":"https://orcid.org/0000-0001-7278-4498","contributorId":1130,"corporation":false,"usgs":true,"family":"Qi","given":"Sharon","email":"slqi@usgs.gov","middleInitial":"L.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true},{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":882265,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Monroe, Adrian P. 0000-0003-0934-8225 amonroe@usgs.gov","orcid":"https://orcid.org/0000-0003-0934-8225","contributorId":152209,"corporation":false,"usgs":true,"family":"Monroe","given":"Adrian P.","email":"amonroe@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":882266,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dahm, Katharine G. 0000-0002-4024-8110","orcid":"https://orcid.org/0000-0002-4024-8110","contributorId":299422,"corporation":false,"usgs":true,"family":"Dahm","given":"Katharine","email":"","middleInitial":"G.","affiliations":[{"id":64844,"text":"Rocky Mountain Region Director’s Office","active":true,"usgs":true}],"preferred":true,"id":882267,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70248757,"text":"70248757 - 2023 - Application of a catch multiple survey analysis for Atlantic horseshoe crab Limulus polyphemus in the Delaware Bay","interactions":[],"lastModifiedDate":"2023-09-20T15:08:03.924703","indexId":"70248757","displayToPublicDate":"2023-09-12T07:03:22","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2680,"text":"Marine and Coastal Fisheries: Dynamics, Management, and Ecosystem Science","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Application of a catch multiple survey analysis for Atlantic horseshoe crab Limulus polyphemus in the Delaware Bay","title":"Application of a catch multiple survey analysis for Atlantic horseshoe crab Limulus polyphemus in the Delaware Bay","docAbstract":"

Objective

This paper applies a catch multiple survey analysis (CMSA) to Atlantic horseshoe crabs Limulus polyphemus in the Delaware Bay to generate robust population estimates for harvest management. Currently, horseshoe crabs along the U.S. Atlantic coast are harvested as bait for other fisheries and collected for their blood, which is used in a biomedical industry. The Delaware Bay is home to the largest population of horseshoe crabs and is a significant stopover for shorebirds to rebuild energy by consuming horseshoe crab eggs prior to completing their northward migration. To address this interrelationship, the Adaptive Resource Management (ARM) Framework has been used since 2013 to ensure that horseshoe crab harvest within the region takes into account the forage needs of migratory birds. Since its inception, the ARM Framework has used a single trawl survey's swept area-based population estimates of horseshoe crab relative abundance and a theoretical population model developed primarily from literature-derived values. With more data collected in the region in recent years and other sources of mortality that can now be quantified, a catch survey model can provide horseshoe crab population estimates going forward.

Methods

A CMSA was used to estimate male and female horseshoe crab population size for 2003–2021 using all quantifiable sources of mortality and three fishery-independent indices of abundance.

Result

The CMSA results indicated that adult abundance of male and female horseshoe crabs was stable from 2003 to 2013 and then began to increase through 2017, a result that is consistent with stock rebuilding following a period of harvest restrictions as recommended by the ARM Framework. Population estimates were lower in recent years but remained above the levels estimated before implementation of the ARM Framework. In 2021, the CMSA estimated that there were over 6 million mature females and nearly 16 million mature male horseshoe crabs in the region.

Conclusion

The CMSA provides the best and most comprehensive population estimates of horseshoe crabs in Delaware Bay and will improve modeling efforts within the ARM Framework going forward.

","language":"English","publisher":"American Fisheries Society","doi":"10.1002/mcf2.10250","usgsCitation":"Anstead, K.A., Sweka, J., Barry, L., Hallerman, E., Smith, D.R., Ameral, N., Schmidtke, M., and Wong, R.A., 2023, Application of a catch multiple survey analysis for Atlantic horseshoe crab Limulus polyphemus in the Delaware Bay: Marine and Coastal Fisheries: Dynamics, Management, and Ecosystem Science, v. 15, no. 5, e10250, 16 p., https://doi.org/10.1002/mcf2.10250.","productDescription":"e10250, 16 p.","ipdsId":"IP-154235","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":442129,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/mcf2.10250","text":"Publisher Index Page"},{"id":420973,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Delaware, Maryland, New Jersey","otherGeospatial":"Delaware Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -76.0255903899312,\n 40.963933240903344\n ],\n [\n -76.0255903899312,\n 37.040030719320384\n ],\n [\n -73.65356124067296,\n 37.040030719320384\n ],\n [\n -73.65356124067296,\n 40.963933240903344\n ],\n [\n -76.0255903899312,\n 40.963933240903344\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"15","issue":"5","noUsgsAuthors":false,"publicationDate":"2023-09-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Anstead, Kristen A.","contributorId":329847,"corporation":false,"usgs":false,"family":"Anstead","given":"Kristen","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":883459,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sweka, John A.","contributorId":288581,"corporation":false,"usgs":false,"family":"Sweka","given":"John A.","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":883460,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Barry, Linda","contributorId":329848,"corporation":false,"usgs":false,"family":"Barry","given":"Linda","email":"","affiliations":[],"preferred":false,"id":883461,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hallerman, Eric M.","contributorId":279474,"corporation":false,"usgs":false,"family":"Hallerman","given":"Eric M.","affiliations":[{"id":36967,"text":"Virginia Tech University","active":true,"usgs":false}],"preferred":false,"id":883462,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Smith, David R. 0000-0001-9560-5210 dvsmith@usgs.gov","orcid":"https://orcid.org/0000-0001-9560-5210","contributorId":329849,"corporation":false,"usgs":true,"family":"Smith","given":"David","email":"dvsmith@usgs.gov","middleInitial":"R.","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":883463,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ameral, Natalie","contributorId":329850,"corporation":false,"usgs":false,"family":"Ameral","given":"Natalie","email":"","affiliations":[],"preferred":false,"id":883464,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Schmidtke, Michael","contributorId":329851,"corporation":false,"usgs":false,"family":"Schmidtke","given":"Michael","email":"","affiliations":[],"preferred":false,"id":883465,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Wong, Richard A.","contributorId":329852,"corporation":false,"usgs":false,"family":"Wong","given":"Richard","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":883466,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70256430,"text":"70256430 - 2023 - Prioritization of species status assessments for decision support","interactions":[],"lastModifiedDate":"2024-08-01T16:21:36.448455","indexId":"70256430","displayToPublicDate":"2023-09-11T11:17:56","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":14243,"text":"Decision Analysis","active":true,"publicationSubtype":{"id":10}},"title":"Prioritization of species status assessments for decision support","docAbstract":"

Species status assessments are used to inform U.S. Fish and Wildlife Service (USFWS) decision making for Endangered Species Act (ESA) classification decisions, recovery planning, and more. The large number of species that require assessment and uncertainty in the data available impede the process of assigning and completing the assessments, which makes creating a multiyear work plan extremely difficult. An optimized triaging system that maximizes the use of the best available information while managing the complex ESA workload and meeting deadlines is necessary. We used a structured decision-making framework to approach the problem with the goal of creating a prioritization tool that would be effective at scheduling assessments, given the best information available and priorities of the USFWS. We collected data on the species awaiting assessment and developed a value function that incorporates existing deadlines, taxonomic uncertainty, controversy of the species, and population and habitat data availability and quality. We used a constrained linear optimization algorithm to maximize the value function and ensure that workload capacity was not exceeded. A comparison of model scenarios indicates that imposed deadlines impact the model more than capacity constraints. Additionally, differential weighting of the metrics significantly affected the outcome of the model. In the future, elicitation of metric weights should be done routinely before the model is run for use in official planning to ensure alignment with current USFWS priorities. Output from this optimization can be used to inform a five-year work plan, allocate resources, and discuss workforce decisions.

","language":"English","publisher":"Informs","doi":"10.1287/deca.2023.0026","usgsCitation":"Goode, A.B., Rivenbark, E., Gilbert, J.A., and McGowan, C., 2023, Prioritization of species status assessments for decision support: Decision Analysis, v. 20, no. 4, p. 311-325, https://doi.org/10.1287/deca.2023.0026.","productDescription":"15 p.","startPage":"311","endPage":"325","ipdsId":"IP-151407","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":432041,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"20","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Goode, Ashley B.C.","contributorId":332463,"corporation":false,"usgs":false,"family":"Goode","given":"Ashley","middleInitial":"B.C.","affiliations":[{"id":33268,"text":"USDA-ARS Aquatic Weed Research Laboratory","active":true,"usgs":false}],"preferred":false,"id":907349,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rivenbark, Erin","contributorId":340546,"corporation":false,"usgs":false,"family":"Rivenbark","given":"Erin","email":"","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":907350,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gilbert, Jessica A.","contributorId":340547,"corporation":false,"usgs":false,"family":"Gilbert","given":"Jessica","email":"","middleInitial":"A.","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":907351,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McGowan, Conor P. 0000-0002-7330-9581 cmcgowan@usgs.gov","orcid":"https://orcid.org/0000-0002-7330-9581","contributorId":3381,"corporation":false,"usgs":true,"family":"McGowan","given":"Conor P.","email":"cmcgowan@usgs.gov","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":false,"id":907352,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70248917,"text":"70248917 - 2023 - The diversity of volcanic hazard maps around the world: Insights from map makers","interactions":[],"lastModifiedDate":"2023-09-26T11:43:01.626685","indexId":"70248917","displayToPublicDate":"2023-09-11T06:41:16","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3841,"text":"Journal of Applied Volcanology","active":true,"publicationSubtype":{"id":10}},"title":"The diversity of volcanic hazard maps around the world: Insights from map makers","docAbstract":"

The IAVCEI Working Group on Hazard Mapping has been active since 2014 and has facilitated several activities to enable sharing of experiences of how volcanic hazard maps are developed and used around the world. One key activity was a global survey of 90 map makers and practitioners to collect data about official, published volcanic hazard maps and how they were developed. The survey asked questions about map content, design, and input data, as well as about the map development process and key lessons learned. Here we present the results of this global survey, which are then used to quantitatively describe and summarise current practices in volcanic hazard map development.

We received entries related to 89 volcanic hazard maps (78% long-term/background maps and 22% short-term/crisis hazard maps), covering a total of 80 volcanoes across 28 countries. Although most maps captured in the survey are volcano-scale maps of stratovolcanoes that show similar types of content, such as primary hazard footprints or zones, they vary greatly in input data, communication style, format, appearance, scale, content, and visual design. This diversity stems from a range of factors, including differences in map purpose, the methodology used, the level of understanding of past eruptive history, the prevailing scientific and cartographic practice at the time, the state of volcanic activity, and variations in culture, national map standards and legal requirements.

Experiences and lessons shared by our respondents can be divided into six main themes: map design considerations; the process of map development; map audience and map user needs; hazard assessment approach; map availability and accessibility; and external (e.g., political) influences. Insights shared included the importance of: visual design elements, map testing and evaluation, working with stakeholders and end users to improve a map’s efficacy and relevance, and considering possible unanticipated uses of hazard maps. These free-form text insights (i.e., responses to open-ended questions) from map makers and practitioners familiar with the maps lend depth and clarity to our results. They provide a rich complement to our more quantitative analysis of design elements and of approaches used to determine and delineate map zones.

Results from our global survey of hazard map makers and practitioners, together with insights from other key initiatives of the Working Group on Hazard Mapping such as the Volcanic Hazard Maps Database (VHMD; https://volcanichazardmaps.org/), provide a snapshot of the wide variety of volcanic hazard maps generated over the past decades, and improve our understanding of the diversity across volcanic hazard mapping practices. These initiatives represent important steps towards fulfilling the aims of the Working Group, namely, to construct a framework for a classification scheme for volcanic hazard maps and to promote harmonized terminology, as well as to identify and categorise good practices and considerations for volcanic hazard mapping.

","language":"English","publisher":"Springer","doi":"10.1186/s13617-023-00134-5","usgsCitation":"Lindsay, J., Charlton, D., Clive, M.A., Bertin, D., Ogburn, S.E., Wright, H.M., Ewert, J., Calder, E.S., and Steinke, B., 2023, The diversity of volcanic hazard maps around the world: Insights from map makers: Journal of Applied Volcanology, v. 12, 8, 26 p., https://doi.org/10.1186/s13617-023-00134-5.","productDescription":"8, 26 p.","ipdsId":"IP-152936","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":442134,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1186/s13617-023-00134-5","text":"Publisher Index Page"},{"id":421158,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"12","noUsgsAuthors":false,"publicationDate":"2023-09-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Lindsay, Jan 0000-0002-8591-3399","orcid":"https://orcid.org/0000-0002-8591-3399","contributorId":302369,"corporation":false,"usgs":false,"family":"Lindsay","given":"Jan","email":"","affiliations":[{"id":38833,"text":"University of Auckland","active":true,"usgs":false}],"preferred":false,"id":884195,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Charlton, Danielle 0000-0002-7837-514X","orcid":"https://orcid.org/0000-0002-7837-514X","contributorId":302366,"corporation":false,"usgs":false,"family":"Charlton","given":"Danielle","email":"","affiliations":[{"id":36277,"text":"GNS Science","active":true,"usgs":false}],"preferred":false,"id":884196,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Clive, Mary Ann T.","contributorId":330167,"corporation":false,"usgs":false,"family":"Clive","given":"Mary","email":"","middleInitial":"Ann T.","affiliations":[{"id":78832,"text":"Waipapa Taumata Rau University of Auckland; GNS Science Te Pū Ao, New Zealand","active":true,"usgs":false}],"preferred":false,"id":884197,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bertin, Daniel","contributorId":173512,"corporation":false,"usgs":false,"family":"Bertin","given":"Daniel","email":"","affiliations":[{"id":27236,"text":"SERNAGEOMIN","active":true,"usgs":false}],"preferred":false,"id":884198,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ogburn, Sarah E. 0000-0002-4734-2118","orcid":"https://orcid.org/0000-0002-4734-2118","contributorId":204751,"corporation":false,"usgs":true,"family":"Ogburn","given":"Sarah","email":"","middleInitial":"E.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":884199,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wright, Heather M. 0000-0001-9013-507X hwright@usgs.gov","orcid":"https://orcid.org/0000-0001-9013-507X","contributorId":3949,"corporation":false,"usgs":true,"family":"Wright","given":"Heather","email":"hwright@usgs.gov","middleInitial":"M.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":884200,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ewert, John W. 0000-0003-2819-4057","orcid":"https://orcid.org/0000-0003-2819-4057","contributorId":204745,"corporation":false,"usgs":true,"family":"Ewert","given":"John W.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":884201,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Calder, Eliza S. 0000-0002-1644-2087","orcid":"https://orcid.org/0000-0002-1644-2087","contributorId":302368,"corporation":false,"usgs":false,"family":"Calder","given":"Eliza","email":"","middleInitial":"S.","affiliations":[{"id":25497,"text":"University of Edinburgh","active":true,"usgs":false}],"preferred":false,"id":884202,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Steinke, Bastian","contributorId":330168,"corporation":false,"usgs":false,"family":"Steinke","given":"Bastian","email":"","affiliations":[{"id":78834,"text":"Waipapa Taumata Rau University of Auckland","active":true,"usgs":false}],"preferred":false,"id":884203,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70262059,"text":"70262059 - 2023 - Pardus in the press: Drivers of leopard (Panthera pardus fusca) attack occurrence on humans in Nepal","interactions":[],"lastModifiedDate":"2025-01-10T18:31:23.287244","indexId":"70262059","displayToPublicDate":"2023-09-10T11:42:06","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5936,"text":"People and Nature","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Pardus in the press: Drivers of leopard (Panthera pardus fusca) attack occurrence on humans in Nepal","title":"Pardus in the press: Drivers of leopard (Panthera pardus fusca) attack occurrence on humans in Nepal","docAbstract":"
  1. The negative impact of large carnivore presence in human-dominated landscapes manifests as livestock depredation and in extreme cases as attacks on humans. In the case of conflict with leopards in Nepal, attacks resulting in human fatality have become more frequent over time, thus creating an urgent socio-ecological and management issue.
  2. We estimated the occurrence of leopard attacks in Nepal from human-leopard conflict cases reported in the media. We used occupancy models to analyse data collected from online news reports on incidents of leopard attacks on humans to explore drivers of leopard attacks on a landscape scale. Our results suggest that the probability of occurrence of leopard attack is associated with human population density, terrain ruggedness and livestock density.
  3. The human population density effect may be indicative of a density-dependent relationship, where attacks are more likely in areas where an increased abundance of humans increases encounter rates with leopards. The positive effect of livestock density suggests that livestock may be drawing leopards into human settlements, and consequently increasing the likelihood of attacks on humans. Terrain ruggedness might be offering ideal conditions to facilitate attacks on humans, for example remoteness and high amounts of cover to launch ambush attacks.
  4. We provide inference and insights into key determinants of leopard attacks on humans on a landscape scale. These insights can be used to guide future research, inform mitigation measures to reduce leopard attacks and foster a better understanding of the interaction between people and leopards.
  5. This study demonstrates the applicability and novelty of using a hierarchical modelling framework applied to freely and publicly available media reports to inform the applied management of human-wildlife conflict at a national scale.
","language":"English","publisher":"British Ecological Society","doi":"10.1002/pan3.10536","usgsCitation":"Poudel, S., Twining, J., Stedman, R., Ghimire, S., and Fuller, A.K., 2023, Pardus in the press: Drivers of leopard (Panthera pardus fusca) attack occurrence on humans in Nepal: People and Nature, v. 5, no. 6, p. 177-188, https://doi.org/10.1002/pan3.10536.","productDescription":"12 p.","startPage":"177","endPage":"188","ipdsId":"IP-130714","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":467093,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/pan3.10536","text":"Publisher Index Page"},{"id":466016,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Nepal","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 79.92780335815291,\n 28.803692392786957\n ],\n [\n 82.71145675855735,\n 27.422532855103327\n ],\n [\n 85.79994047161551,\n 26.519692535546156\n ],\n [\n 88.21732200599081,\n 26.28592528048857\n ],\n [\n 88.23034164615058,\n 28.015630040007878\n ],\n [\n 86.47325630501331,\n 28.11386705824934\n ],\n [\n 82.25297495008891,\n 30.33864883355747\n ],\n [\n 81.61483198209362,\n 30.552482869451012\n ],\n [\n 80.31771509103879,\n 29.885911968905162\n ],\n [\n 79.92780335815291,\n 28.803692392786957\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"5","issue":"6","noUsgsAuthors":false,"publicationDate":"2023-09-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Poudel, Shashank","contributorId":348087,"corporation":false,"usgs":false,"family":"Poudel","given":"Shashank","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":922928,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Twining, Joshua P.","contributorId":342747,"corporation":false,"usgs":false,"family":"Twining","given":"Joshua P.","affiliations":[{"id":81920,"text":"Cornell Universtity","active":true,"usgs":false}],"preferred":false,"id":922997,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stedman, Richard C.","contributorId":348088,"corporation":false,"usgs":false,"family":"Stedman","given":"Richard C.","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":922929,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ghimire, Shravan Kumar","contributorId":348089,"corporation":false,"usgs":false,"family":"Ghimire","given":"Shravan Kumar","affiliations":[{"id":32415,"text":"Chinese Academy of Sciences","active":true,"usgs":false}],"preferred":false,"id":922930,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fuller, Angela K. 0000-0002-9247-7468 afuller@usgs.gov","orcid":"https://orcid.org/0000-0002-9247-7468","contributorId":3984,"corporation":false,"usgs":true,"family":"Fuller","given":"Angela","email":"afuller@usgs.gov","middleInitial":"K.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":922927,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70252983,"text":"70252983 - 2023 - a-positive: A robust estimator of the earthquake rate in incomplete or saturated catalogs","interactions":[],"lastModifiedDate":"2024-04-15T11:30:46.628935","indexId":"70252983","displayToPublicDate":"2023-09-09T06:28:26","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7501,"text":"JGR Solid Earth","active":true,"publicationSubtype":{"id":10}},"title":"a-positive: A robust estimator of the earthquake rate in incomplete or saturated catalogs","docAbstract":"

Detection thresholds in earthquake catalogs frequently change in time due to station coverage improvements and network saturation effects during active periods such as mainshock-aftershock cascades. This presents a challenge to seismicity-rate estimation; there is a tradeoff between using as low a minimum magnitude as possible to maximize data while not undercounting the rate due to catalog incompleteness. Here we present a simple method, “a-positive,” which makes use of differential statistics to robustly estimate the seismicity rate in catalogs with time-varying detection thresholds. We demonstrate the effectiveness of this method for a centuries-long, hybrid earthquake catalog with both historical and instrumentally-detected earthquakes in the Central and Eastern U.S., as well as for the 2019 Ridgecrest aftershock sequence in California, which has rapid changes in completeness due to network saturation. We find that the a-positive method leads to more precise and less biased estimates of seismicity rate than traditional methods. In addition, with our improved estimate of earthquake rate early in the aftershock cascade, we find no evidence of rate-saturation at short times from the mainshock; that is, the Omori c-value is not distinguishable from zero.

","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2023JB027089","usgsCitation":"van der Elst, N., and Page, M.T., 2023, a-positive: A robust estimator of the earthquake rate in incomplete or saturated catalogs: JGR Solid Earth, v. 128, no. 10, e2023JB027089, https://doi.org/10.1029/2023JB027089.","productDescription":"e2023JB027089","ipdsId":"IP-153135","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":497986,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2023jb027089","text":"Publisher Index Page"},{"id":427778,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"128","issue":"10","noUsgsAuthors":false,"publicationDate":"2023-09-30","publicationStatus":"PW","contributors":{"authors":[{"text":"van der Elst, Nicholas 0000-0002-3812-1153 nvanderelst@usgs.gov","orcid":"https://orcid.org/0000-0002-3812-1153","contributorId":147858,"corporation":false,"usgs":true,"family":"van der Elst","given":"Nicholas","email":"nvanderelst@usgs.gov","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true}],"preferred":true,"id":898855,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Page, Morgan T. 0000-0001-9321-2990 mpage@usgs.gov","orcid":"https://orcid.org/0000-0001-9321-2990","contributorId":3762,"corporation":false,"usgs":true,"family":"Page","given":"Morgan","email":"mpage@usgs.gov","middleInitial":"T.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true}],"preferred":true,"id":898856,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70249288,"text":"70249288 - 2023 - Polar bear's range dynamics and survival in the Holocene","interactions":[],"lastModifiedDate":"2023-10-03T12:16:58.922015","indexId":"70249288","displayToPublicDate":"2023-09-08T07:11:59","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3219,"text":"Quaternary Science Reviews","active":true,"publicationSubtype":{"id":10}},"title":"Polar bear's range dynamics and survival in the Holocene","docAbstract":"

Polar bear (Ursus maritimus) is the apex predator of the Arctic, largely dependent on sea-ice. The expected disappearance of the ice cover of the Arctic seas by the mid 21st century is predicted to cause a dramatic decrease in the global range and population size of the species. To place this scenario against the backdrop of past distribution changes and their causes, we use a fossil dataset to investigate the polar bear's past distribution dynamics during the Late Glacial and the Holocene. Fossil results indicate that during the last deglaciation, polar bears were present at the southwestern margin of the Scandinavian Ice Sheet, surviving until the earliest Holocene. There are no Arctic polar bear findings from 8000–6000 years ago (8–6 ka), the Holocene's warmest period. However, fossils that date from 8-9 ka and 5–6 ka suggest that the species likely survived this period in cold refugia located near the East Siberian Sea, northern Greenland and the Canadian Archipelago. Polar bear range expansion is documented by an increase in fossils during the last 4000 years in tandem with cooling climate and expanding Arctic sea ice. The results document changes in polar bear's distribution in response to Late Glacial and Holocene Arctic temperature and sea ice trends.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.quascirev.2023.108277","usgsCitation":"Seppa, H., Seidenkrantz, M., Caissie, B.E., and Fauria, M.M., 2023, Polar bear's range dynamics and survival in the Holocene: Quaternary Science Reviews, v. 317, 108277, 6 p., https://doi.org/10.1016/j.quascirev.2023.108277.","productDescription":"108277, 6 p.","ipdsId":"IP-144338","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":442145,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://escholarship.org/uc/item/85s714tb","text":"External Repository"},{"id":421531,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"317","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Seppa, Heikki","contributorId":330467,"corporation":false,"usgs":false,"family":"Seppa","given":"Heikki","email":"","affiliations":[{"id":18162,"text":"University of Helsinki","active":true,"usgs":false}],"preferred":false,"id":885004,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Seidenkrantz, Marit-Solveig","contributorId":304650,"corporation":false,"usgs":false,"family":"Seidenkrantz","given":"Marit-Solveig","affiliations":[{"id":49183,"text":"Department of Geoscience, Aarhus University, Aarhus, Denmark","active":true,"usgs":false}],"preferred":false,"id":885005,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Caissie, Beth Elaine 0000-0001-9587-1842","orcid":"https://orcid.org/0000-0001-9587-1842","contributorId":292500,"corporation":false,"usgs":true,"family":"Caissie","given":"Beth","email":"","middleInitial":"Elaine","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":885006,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fauria, Marc Macias","contributorId":330469,"corporation":false,"usgs":false,"family":"Fauria","given":"Marc","email":"","middleInitial":"Macias","affiliations":[{"id":30742,"text":"University of Oxford, UK","active":true,"usgs":false}],"preferred":false,"id":885007,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70249974,"text":"70249974 - 2023 - Local topography and streambed hydraulic conductivity influence riparian groundwater age and groundwater-surface water connection","interactions":[],"lastModifiedDate":"2023-11-09T12:54:40.111463","indexId":"70249974","displayToPublicDate":"2023-09-08T06:51:22","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Local topography and streambed hydraulic conductivity influence riparian groundwater age and groundwater-surface water connection","docAbstract":"

The western U.S. is experiencing increasing rain to snow ratios due to climate change, and scientists are uncertain how changing recharge patterns will affect future groundwater-surface water connection. We examined how watershed topography and streambed hydraulic conductivity impact groundwater age and stream discharge at eight sites along a headwater stream within the Manitou Experimental Forest, CO USA. To do so, we measured: (a) continuous stream and groundwater discharge/level and specific conductivity from April to November 2021; (b) biweekly stream and groundwater chemistry; (c) groundwater chlorofluorocarbons and tritium in spring and fall; (d) streambed hydraulic conductivity; and (e) local slope. We used the chemistry data to calculate fluorite saturation states that were used to inform end-member mixing analysis of streamflow source. We then combined chlorofluorocarbon and tritium data to estimate the age composition of riparian groundwater. Our data suggest that future stream drying is more probable where local slope is steep and streambed hydraulic conductivity is high. In these areas, groundwater source shifted seasonally, as indicated by age increases, and we observed a high fraction of groundwater in streamflow, primarily interflow from adjacent hillslopes. In contrast, where local slope is flat and streambed hydraulic conductivity is low, streamflow is more likely to persist as groundwater age was seasonally constant and buffered by storage in alluvial sediments. Groundwater age and streamflow paired with characterization of watershed topography and subsurface characteristics enabled identification of likely controls on future stream drying patterns.

","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2023WR035044","usgsCitation":"Warix, S.R., Navarre-Sitchler, A., Manning, A.H., and Singha, K., 2023, Local topography and streambed hydraulic conductivity influence riparian groundwater age and groundwater-surface water connection: Water Resources Research, v. 59, no. 9, e2023WR035044, 22 p., https://doi.org/10.1029/2023WR035044.","productDescription":"e2023WR035044, 22 p.","ipdsId":"IP-146499","costCenters":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":442149,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2023wr035044","text":"Publisher Index Page"},{"id":422473,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"Manitou Experimental Forest","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -105.19601263225407,\n 39.19295829401517\n ],\n [\n -105.19601263225407,\n 38.9626869460493\n ],\n [\n -104.87878240764469,\n 38.9626869460493\n ],\n [\n -104.87878240764469,\n 39.19295829401517\n ],\n [\n -105.19601263225407,\n 39.19295829401517\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"59","issue":"9","noUsgsAuthors":false,"publicationDate":"2023-09-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Warix, Sara R.","contributorId":331499,"corporation":false,"usgs":false,"family":"Warix","given":"Sara","email":"","middleInitial":"R.","affiliations":[{"id":6606,"text":"Colorado School of Mines","active":true,"usgs":false}],"preferred":false,"id":887877,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Navarre-Sitchler, Alexis","contributorId":190441,"corporation":false,"usgs":false,"family":"Navarre-Sitchler","given":"Alexis","email":"","affiliations":[],"preferred":false,"id":887878,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Manning, Andrew H. 0000-0002-6404-1237 amanning@usgs.gov","orcid":"https://orcid.org/0000-0002-6404-1237","contributorId":1305,"corporation":false,"usgs":true,"family":"Manning","given":"Andrew","email":"amanning@usgs.gov","middleInitial":"H.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":887879,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Singha, Kamini","contributorId":331170,"corporation":false,"usgs":false,"family":"Singha","given":"Kamini","affiliations":[{"id":6606,"text":"Colorado School of Mines","active":true,"usgs":false}],"preferred":false,"id":887880,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70248238,"text":"sir20235086 - 2023 - Characterization of peak streamflows and flooding in select areas of Pennsylvania from the remnants of Hurricane Ida, September 1–2, 2021","interactions":[],"lastModifiedDate":"2026-03-12T21:06:52.59464","indexId":"sir20235086","displayToPublicDate":"2023-09-07T12:00:00","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2023-5086","displayTitle":"Characterization of Peak Streamflows and Flooding in Select Areas of Pennsylvania from the Remnants of Hurricane Ida, September 1–2, 2021","title":"Characterization of peak streamflows and flooding in select areas of Pennsylvania from the remnants of Hurricane Ida, September 1–2, 2021","docAbstract":"

Pennsylvania experienced heavy rainfall on September 1 and 2, 2021, as the remnants of Hurricane Ida swept over parts of the State. Much of eastern and south-central Pennsylvania received 5 to 10 inches of rain, and most of the rainfall fell within little more than 6 hours. Southeastern Pennsylvania experienced widespread, substantial flooding, and the city of Philadelphia and surrounding areas were particularly affected by the flooding. U.S. Geological Survey (USGS) streamgages registered peak streamflows of record at 19 locations, and 52 locations experienced top 5 peak streamflows for the period of record and an annual exceedance probability estimate of at least 10 percent. During this September 2021 flood event, USGS personnel made over 60 streamflow measurements at streamgages in Pennsylvania using direct and indirect methods. Many of those streamflow measurements were made to verify or improve the accuracy, extent, or development of new stage-streamflow relations at streamgages operated by the USGS. After the floodwaters receded, USGS personnel identified and documented a total of 338 high-water marks in Pennsylvania, noting such things as their general description, location, height above land surface, and quality. Many of these high-water marks were used to create five flood-documentation maps for selected communities in southeastern Pennsylvania that experienced substantial flooding because of the remnants of Hurricane Ida. Digital datasets of the inundated areas, mapped boundaries, and water depth are available (Stuckey and Conlon, 2023).

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235086","collaboration":"Prepared in cooperation with the Federal Emergency Management Agency","usgsCitation":"Stuckey, M.H., Conlon, M.D., and Weaver, M.R., 2023, Characterization of peak streamflows and flooding in select areas of Pennsylvania from the remnants of Hurricane Ida, September 1–2, 2021 (ver. 1.1, September 28, 2023): U.S. Geological Survey Scientific Investigations Report 2023–5086, 28 p., https://doi.org/10.3133/sir20235086.","productDescription":"Report: vii, 28 p.; Data Release","numberOfPages":"40","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-145111","costCenters":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"links":[{"id":501049,"rank":8,"type":{"id":36,"text":"NGMDB Index 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\"}}]}","edition":"Version 1.0: September 7, 2023; Version 1.1: September 28, 2023","contact":"

Director, Pennsylvania Water Science Center
U.S. Geological Survey
215 Limekiln Road
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","tableOfContents":"","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"publishedDate":"2023-09-07","revisedDate":"2023-09-28","noUsgsAuthors":false,"publicationDate":"2023-09-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Stuckey, Marla H. 0000-0002-5211-8444","orcid":"https://orcid.org/0000-0002-5211-8444","contributorId":329365,"corporation":false,"usgs":true,"family":"Stuckey","given":"Marla H.","affiliations":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"preferred":true,"id":882066,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Conlon, Matthew D. 0000-0001-8266-9610 mconlon@usgs.gov","orcid":"https://orcid.org/0000-0001-8266-9610","contributorId":201291,"corporation":false,"usgs":true,"family":"Conlon","given":"Matthew","email":"mconlon@usgs.gov","middleInitial":"D.","affiliations":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"preferred":true,"id":882067,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Weaver, Mitchell R. 0000-0003-3099-2285","orcid":"https://orcid.org/0000-0003-3099-2285","contributorId":329366,"corporation":false,"usgs":true,"family":"Weaver","given":"Mitchell","email":"","middleInitial":"R.","affiliations":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"preferred":true,"id":882068,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70251451,"text":"70251451 - 2023 - Leveraging multimission satellite data for spatiotemporally coherent cyanoHAB monitoring","interactions":[],"lastModifiedDate":"2024-02-13T12:44:53.978846","indexId":"70251451","displayToPublicDate":"2023-09-07T06:40:23","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":17157,"text":"Frontiers in Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Leveraging multimission satellite data for spatiotemporally coherent cyanoHAB monitoring","docAbstract":"

Cyanobacteria harmful algal blooms (cyanoHABs) present a critical public health challenge for aquatic resource and public health managers. Satellite remote sensing is well-positioned to aid in the identification and mapping of cyanoHABs and their dynamics, giving freshwater resource managers a tool for both rapid and long-term protection of public health. Monitoring cyanoHABs in lakes and reservoirs with remote sensing requires robust processing techniques for generating accurate and consistent products across local and global scales at high revisit rates. We leveraged the high spatial and temporal resolution chlorophyll-a (Chla) and phycocyanin (PC) maps from two multispectral satellite sensors, the Sentinel-2 (S2) MultiSpectral Instrument (MSI) and the Sentinel-3 (S3) Ocean Land Colour Instrument (OLCI) respectively, to study bloom dynamics in Utah Lake, United States, for 2018. We used established Mixture Density Networks (MDNs) to map Chla from MSI and train new MDNs for PC retrieval from OLCI, using the same architecture and training dataset previously proven for PC retrieval from hyperspectral imagery. Our assessment suggests lower median uncertainties and biases (i.e., 42% and -4%, respectively) than that of existing top-performing PC algorithms. Additionally, we compared bloom trends in MDN-based PC and Chla products to those from a satellite-derived cyanobacteria cell density estimator, the cyanobacteria index (CI-cyano), to evaluate their utility in the context of public health risk management. Our comprehensive analyses indicate increased spatiotemporal coherence of bloom magnitude, frequency, occurrence, and extent of MDN-based maps compared to CI-cyano and potential for use in cyanoHAB monitoring for public health and aquatic resource managers.

","language":"English","publisher":"Froniters","doi":"10.3389/frsen.2023.1157609","usgsCitation":"Fickas, K.C., O’Shea, R., Pahlevan, N., Smith, B., Bartlett, S., and Wolny, J.L., 2023, Leveraging multimission satellite data for spatiotemporally coherent cyanoHAB monitoring: Frontiers in Remote Sensing, v. 4, 1157609, 24 p., https://doi.org/10.3389/frsen.2023.1157609.","productDescription":"1157609, 24 p.","ipdsId":"IP-142409","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":442159,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/frsen.2023.1157609","text":"Publisher Index Page"},{"id":425598,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Utah","otherGeospatial":"Utah Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -112.10203383155128,\n 40.45613437617996\n ],\n [\n -112.10203383155128,\n 39.962431675009014\n ],\n [\n -111.55417471255357,\n 39.962431675009014\n ],\n [\n -111.55417471255357,\n 40.45613437617996\n ],\n [\n -112.10203383155128,\n 40.45613437617996\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"4","noUsgsAuthors":false,"publicationDate":"2023-09-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Fickas, Kate Colleen 0000-0002-6617-2441","orcid":"https://orcid.org/0000-0002-6617-2441","contributorId":304194,"corporation":false,"usgs":true,"family":"Fickas","given":"Kate","email":"","middleInitial":"Colleen","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":894612,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"O’Shea, Ryan","contributorId":334049,"corporation":false,"usgs":false,"family":"O’Shea","given":"Ryan","email":"","affiliations":[{"id":7049,"text":"NASA Goddard Space Flight Center","active":true,"usgs":false}],"preferred":false,"id":894613,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pahlevan, Nima","contributorId":328507,"corporation":false,"usgs":false,"family":"Pahlevan","given":"Nima","affiliations":[{"id":78385,"text":"NASA GSFC/ SSAI","active":true,"usgs":false}],"preferred":false,"id":894614,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Smith, Brandon","contributorId":334050,"corporation":false,"usgs":false,"family":"Smith","given":"Brandon","email":"","affiliations":[{"id":7049,"text":"NASA Goddard Space Flight Center","active":true,"usgs":false}],"preferred":false,"id":894615,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bartlett, Sarah","contributorId":190422,"corporation":false,"usgs":false,"family":"Bartlett","given":"Sarah","affiliations":[],"preferred":false,"id":894616,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wolny, Jennifer L.","contributorId":195447,"corporation":false,"usgs":false,"family":"Wolny","given":"Jennifer","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":894617,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70248279,"text":"ofr20231064 - 2023 - California State waters map series—Benthic habitat characterization in the region offshore of Morro Bay, California","interactions":[],"lastModifiedDate":"2026-02-11T21:39:00.871652","indexId":"ofr20231064","displayToPublicDate":"2023-09-06T15:22:48","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2023-1064","displayTitle":"California State Waters Map Series—Benthic Habitat Characterization in the Region Offshore of Morro Bay, California","title":"California State waters map series—Benthic habitat characterization in the region offshore of Morro Bay, California","docAbstract":"

Coastal and Marine Ecological Classification Standard geoform, substrate, and biotic component geographic information system products were developed for the California State waters of south-central California in the region offshore of Morro Bay. The study was motivated by interest in development of offshore wind-energy capacity and infrastructure in Federal waters offshore. The Bureau of Ocean Energy Management, in coordination with the State of California and many other members of the California Intergovernmental Renewable Energy Task Force, issued calls for information in 2018 for the study area offshore of Morro Bay, California. The study area is adjacent to a nuclear power plant (currently scheduled for decommissioning) with a developed electric grid connection, and in an area of high wind resource potential. The Bureau of Ocean Energy Management is the lead agency responsible for planning and leasing in the U.S. Exclusive Economic Zone and funded this project to assess baseline conditions of, and the potential effects on, the seafloor environment. This project, carried out by the U.S. Geological Survey, resulted in three data releases for individual map blocks that are part of the California State Waters Map Series: (1) Offshore of Point Estero, (2) Offshore of Morro Bay, and (3) Offshore of Point Buchon. The study area consists of 341 square kilometers (km2) of multibeam echo sounder (MBES) data acquired by Fugro, Inc., in 2010. Towed camera-sled video was acquired in 2012 to supervise the classification of the MBES data into habitats. There were 935 annotations of organisms and habitat made from 22 video transects. Using video observations of habitat as ground truth, derivatives of the MBES data were classified into 3 seafloor character types (hard-rugged, hard-flat, and soft-flat), 25 modifier groups, and 9 geoforms. The study area substrate is predominantly soft-flat sediment (mud and fine sand) covering 191.3 km2 (56.1 percent) of the area. Hard-flat substrate areas, predominantly coarse sediment in scour depressions, cover 52.2 km2 (15.3 percent) of the study area. The hard-rugged substrate areas are primarily outcrops of layered sedimentary bedrock and constitute 97.5 km2 of the study area (28.6 percent). After classification of bathymetry and backscatter raster images according to substrate, false-positive hard areas produced by noise artifacts were removed by manual editing. Nine geoforms were then identified in the analysis. The predominant geoforms mirror the seafloor character results, shelf geoforms (flat areas covered in soft sediment), rock outcrop geoforms (hard, rugged areas), and scour depression geoforms (flat areas covered in coarse sediment formed by bottom currents).

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20231064","collaboration":"Prepared in cooperation with California State University Monterey Bay, University of California Santa Cruz, the Bureau of Ocean Energy Management, and the California Ocean Protection Council","usgsCitation":"Cochrane, G.R., Kvitek, R., Cole, A., Sherrier, M., Roca-Lezra, A., Hallahan, S., and Dartnell, P., 2023, California State waters map series—Benthic habitat characterization in the region offshore of Morro Bay, California: U.S. Geological Survey Open-File Report 2023–1064, 14 p., https://doi.org/10.3133/ofr20231064.","productDescription":"Report: vii, 14 p.; 3 Data Releases","numberOfPages":"14","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-142408","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":420580,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9ZSTUK1","text":"USGS Data Release","description":"Cochrane, G.R., Cole, A., Sherrier, M., and Hallahan, S., 2022, Bathymetry, backscatter intensity, and benthic habitat offshore of Point Estero, California: U.S. Geological Survey data release, https://doi.org/10.5066/P9ZSTUK1.","linkHelpText":"Bathymetry, backscatter intensity, and benthic habitat offshore of Point Estero, California"},{"id":420579,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9HEZNRO","text":"USGS Data Release","description":"Cochrane, G.R., Cole, A., Sherrier, M., and Roca-Lezra, A., 2022, Bathymetry, backscatter intensity, and benthic habitat offshore of Morro Bay, California: U.S. Geological Survey data release, https://doi.org/10.5066/P9HEZNRO.","linkHelpText":"Bathymetry, backscatter intensity, and benthic habitat offshore of Morro Bay, California"},{"id":499787,"rank":9,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_115244.htm","linkFileType":{"id":5,"text":"html"}},{"id":420582,"rank":8,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20231064/full"},{"id":420581,"rank":7,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9KBGELE","text":"USGS Data Release","description":"Cochrane, G.R., Cole, A., and Sherrier, M., 2022, Bathymetry, backscatter intensity, and benthic habitat offshore of Point Buchon, California: U.S. Geological Survey data release, https://doi.org/10.5066/P9KBGELE.","linkHelpText":"Bathymetry, backscatter intensity, and benthic habitat offshore of Point Buchon, California"},{"id":420575,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2023/1064/covrthb.jpg"},{"id":420576,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2023/1064/ofr20231064.pdf","text":"Report","size":"5 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":420577,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2023/1064/ofr20231064.xml"},{"id":420578,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2023/1064/images"}],"country":"United States","state":"California","otherGeospatial":"Morro Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -121.14748785119099,\n 35.56953868165078\n ],\n [\n -121.14748785119099,\n 35.15085512961322\n ],\n [\n -120.69449617338131,\n 35.15085512961322\n ],\n [\n -120.69449617338131,\n 35.56953868165078\n ],\n [\n -121.14748785119099,\n 35.56953868165078\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"

Pacific Coastal and Marine Science Center
U.S. Geological Survey
2885 Mission St.
Santa Cruz, CA 95060

","tableOfContents":"","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"publishedDate":"2023-09-06","noUsgsAuthors":false,"publicationDate":"2023-09-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Cochrane, Guy R. 0000-0002-8094-4583 gcochrane@usgs.gov","orcid":"https://orcid.org/0000-0002-8094-4583","contributorId":2870,"corporation":false,"usgs":true,"family":"Cochrane","given":"Guy","email":"gcochrane@usgs.gov","middleInitial":"R.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true}],"preferred":true,"id":882231,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kvitek, Rikk","contributorId":203977,"corporation":false,"usgs":false,"family":"Kvitek","given":"Rikk","affiliations":[{"id":36778,"text":"California State University at Monterey Bay","active":true,"usgs":false}],"preferred":false,"id":882232,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cole, Aaron","contributorId":214198,"corporation":false,"usgs":false,"family":"Cole","given":"Aaron","email":"","affiliations":[{"id":17620,"text":"UCSC","active":true,"usgs":false}],"preferred":false,"id":882233,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sherrier, Meghan 0000-0002-7857-7737","orcid":"https://orcid.org/0000-0002-7857-7737","contributorId":292303,"corporation":false,"usgs":false,"family":"Sherrier","given":"Meghan","email":"","affiliations":[{"id":17620,"text":"UCSC","active":true,"usgs":false}],"preferred":false,"id":882234,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Roca-Lezra, Alia 0000-0001-6450-3684","orcid":"https://orcid.org/0000-0001-6450-3684","contributorId":329415,"corporation":false,"usgs":false,"family":"Roca-Lezra","given":"Alia","email":"","affiliations":[{"id":6949,"text":"University of California, Santa Cruz","active":true,"usgs":false}],"preferred":true,"id":882235,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hallahan, Sean","contributorId":292304,"corporation":false,"usgs":false,"family":"Hallahan","given":"Sean","email":"","affiliations":[{"id":17620,"text":"UCSC","active":true,"usgs":false}],"preferred":false,"id":882236,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Dartnell, Peter 0000-0002-9554-729X pdartnell@usgs.gov","orcid":"https://orcid.org/0000-0002-9554-729X","contributorId":2688,"corporation":false,"usgs":true,"family":"Dartnell","given":"Peter","email":"pdartnell@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":882237,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70247999,"text":"cir1511 - 2023 - U.S. Geological Survey science vision for native freshwater mussel research in the United States","interactions":[],"lastModifiedDate":"2023-10-17T13:27:30.861769","indexId":"cir1511","displayToPublicDate":"2023-09-06T10:45:00","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":307,"text":"Circular","code":"CIR","onlineIssn":"2330-5703","printIssn":"1067-084X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1511","displayTitle":"U.S. Geological Survey Science Vision for Native Freshwater Mussel Research in the United States","title":"U.S. Geological Survey science vision for native freshwater mussel research in the United States","docAbstract":"

Executive Summary

North America is a global center for native freshwater mussel (order Unionida, hereinafter “mussels”) diversity, with more than 350 species. Mussels are among the most imperiled fauna on the planet. Reasons for both local and widespread declines in mussels are mostly unknown, although the threats may include habitat loss and fragmentation, diseases, environmental contaminants, altered flow regimes, migration barriers to larval hosts, non-native species, and climate change.

Over the past three decades, research on mussels has been substantial. Nevertheless, current conservation and management efforts are limited by significant information gaps. For example, the effects of emerging stressors on mussels are largely unknown and identifying when habitats are rehabilitated and suitable for reestablishment of mussels remains challenging. Additionally, historical and current information on the distribution, taxonomy, and life histories are often unreliable or lacking altogether, and more reliable information is needed for many species.

We identified focal research themes, goals, and objectives where research on mussels is needed based on information gaps identified through conversations with resource partners across local, regional, and national organizations. Research on biodiversity seeks to enhance the diversity of mussel species and populations to support healthy aquatic ecosystems. Research on emerging stressors seeks to improve the understanding of how mussel species, populations, and communities respond to emerging stressors, including environmental contaminants and climate change. Research on conservation seeks to enhance the recovery of species and populations and to identify data gaps limiting the conservation of mussels and their habitats. Mussels are in urgent need of proactive conservation because they are an integral part of our natural heritage, enhance biodiversity, and provide vital ecological services that support freshwater ecosystems.

The U.S. Geological Survey (USGS) has been, and continues to be, a leader in mussel research. Although the USGS is well suited to address the broad-scale multidisciplinary research needed to conserve mussels, the USGS has had substantial loss of scientists with mussel expertise over the past 20 years. However, the breadth of the USGS expertise on mussels can be leveraged internally across other USGS mission and program areas and externally across research partners. Given the breadth and scope of the issues facing mussels across the United States, the research themes outlined in this science vision can only be accomplished through extensive collaborations between the USGS and the full spectrum of natural resource partners, including other Federal and State agencies, Tribal organizations, universities, industries, and nongovernmental organizations.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/cir1511","isbn":"978-1-4113-4537-9","programNote":"Ecosystems Mission Area—Species Management Research Program","usgsCitation":"Newton, T.J., Johnson, N.A., and Hu, D.H., 2023, U.S. Geological Survey science vision for native freshwater mussel research in the United States: U.S. Geological Survey Circular 1511, 15 p., https://doi.org/10.3133/cir1511.","productDescription":"vi, 15 p.","numberOfPages":"15","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-147504","costCenters":[{"id":506,"text":"Office of the AD Ecosystems","active":true,"usgs":true}],"links":[{"id":420318,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/circ/1511/cir1511.XML"},{"id":420317,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/circ/1511/images/"},{"id":420316,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/cir1511/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"CIR 1511"},{"id":420329,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/circ/1511/cir1511.pdf","text":"Report","size":"29.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"CIR 1511"},{"id":420328,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/circ/1511/coverthb.jpg"}],"contact":"

Program Coordinator, Species Management Research Program
Ecosystems Mission Area
U.S. Geological Survey
12201 Sunrise Valley Drive, Mail Stop 415
Reston, VA 20192

Contact Pubs Warehouse

","tableOfContents":"","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"publishedDate":"2023-09-06","noUsgsAuthors":false,"publicationDate":"2023-09-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Newton, Teresa J. 0000-0001-9351-5852","orcid":"https://orcid.org/0000-0001-9351-5852","contributorId":78696,"corporation":false,"usgs":true,"family":"Newton","given":"Teresa J.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":881469,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Johnson, Nathan A. 0000-0001-5167-1988","orcid":"https://orcid.org/0000-0001-5167-1988","contributorId":218986,"corporation":false,"usgs":true,"family":"Johnson","given":"Nathan A.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":881470,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hu, David H. 0000-0002-5676-5649","orcid":"https://orcid.org/0000-0002-5676-5649","contributorId":292473,"corporation":false,"usgs":true,"family":"Hu","given":"David","email":"","middleInitial":"H.","affiliations":[{"id":506,"text":"Office of the AD Ecosystems","active":true,"usgs":true}],"preferred":true,"id":881471,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70256523,"text":"70256523 - 2023 - An agent-based model to quantify energetics, movement and habitat selection of mid-continent mallards in the Mississippi Alluvial Valley","interactions":[],"lastModifiedDate":"2024-08-07T12:17:58.180684","indexId":"70256523","displayToPublicDate":"2023-09-06T07:15:27","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}},"title":"An agent-based model to quantify energetics, movement and habitat selection of mid-continent mallards in the Mississippi Alluvial Valley","docAbstract":"

The dynamics of wintering waterfowl populations at the landscape scale are the result of complex interactions of environmental, behavioral and energetic drivers. Agent-based models provide a method to directly link these factors in a spatially explicit framework and allow the emergence of patterns from the aggregation of individual agent actions. We adapted the Spatially-explicit Waterbird Agent-based Model Program (SWAMP), originally developed for waterfowl in central California, to simulate a basin-scale population of mallards (A. platyrhynchos) wintering in the Mississippi Alluvial Valley over a four-month period (November–February). Simulated agents move within the landscape, foraging on areas made available based on a probabilistic inundation status, and converting food resources to endogenous energy. The model uses a high-resolution map of eastern Arkansas waterfowl habitats and incorporates a hierarchical habitat selection system that enables mallards to relocate at increasing scales in response to changing food availability. We validated the performance of modeled mallard body condition and behavioral metrics under a range of environmental conditions against expected outcomes derived from empirical data and found that the simulation produced realistic representations of changes in flight distances, energy expenditure, lipid storage, and foraging habitat use in response to depleting food resources over time. We discuss the model's applicability as a tool to quantify waterfowl response to a range of environmental conditions and to evaluate scenarios of landscape composition and configuration in the context of waterfowl population management.


","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolmodel.2023.110488","usgsCitation":"Weller, F.G., Webb, E.B., Fogenburg, S., Beatty, W., Kesler, D., Blenk, R.H., Ringelman, K.M., Miller, M.L., and Eadie, J., 2023, An agent-based model to quantify energetics, movement and habitat selection of mid-continent mallards in the Mississippi Alluvial Valley: Ecological Modelling, v. 485, 110488, https://doi.org/10.1016/j.ecolmodel.2023.110488.","productDescription":"110488","ipdsId":"IP-151506","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":442176,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://repository.lsu.edu/agrnr_pubs/679","text":"Publisher Index Page"},{"id":432333,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"485","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Weller, Florian G.","contributorId":341013,"corporation":false,"usgs":false,"family":"Weller","given":"Florian","email":"","middleInitial":"G.","affiliations":[{"id":6754,"text":"University of Missouri","active":true,"usgs":false}],"preferred":false,"id":907803,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Webb, Elisabeth B. 0000-0003-3851-6056 ewebb@usgs.gov","orcid":"https://orcid.org/0000-0003-3851-6056","contributorId":3981,"corporation":false,"usgs":true,"family":"Webb","given":"Elisabeth","email":"ewebb@usgs.gov","middleInitial":"B.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":907804,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fogenburg, Sean","contributorId":341014,"corporation":false,"usgs":false,"family":"Fogenburg","given":"Sean","email":"","affiliations":[{"id":7214,"text":"University of California, Davis","active":true,"usgs":false}],"preferred":false,"id":907805,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Beatty, William S. 0000-0003-0013-3113","orcid":"https://orcid.org/0000-0003-0013-3113","contributorId":224795,"corporation":false,"usgs":true,"family":"Beatty","given":"William S.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":907806,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kesler, Dylan","contributorId":341015,"corporation":false,"usgs":false,"family":"Kesler","given":"Dylan","affiliations":[{"id":37290,"text":"The Institute for Bird Populations","active":true,"usgs":false}],"preferred":false,"id":907807,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Blenk, Robert H.","contributorId":341016,"corporation":false,"usgs":false,"family":"Blenk","given":"Robert","email":"","middleInitial":"H.","affiliations":[{"id":7214,"text":"University of California, Davis","active":true,"usgs":false}],"preferred":false,"id":907808,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ringelman, Kevin M.","contributorId":341017,"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":907809,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Miller, Matt L.","contributorId":341018,"corporation":false,"usgs":false,"family":"Miller","given":"Matt","email":"","middleInitial":"L.","affiliations":[{"id":7214,"text":"University of California, Davis","active":true,"usgs":false}],"preferred":false,"id":907810,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Eadie, John M.","contributorId":341020,"corporation":false,"usgs":false,"family":"Eadie","given":"John M.","affiliations":[{"id":7214,"text":"University of California, Davis","active":true,"usgs":false}],"preferred":false,"id":907811,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70248027,"text":"sir20235085 - 2023 - Updates to CE-QUAL-W2 models for select U.S. Army Corps of Engineers reservoirs in the Willamette Valley Project and an inter-reservoir reach of the Middle Fork Willamette River, northwestern Oregon","interactions":[],"lastModifiedDate":"2025-08-14T19:42:16.158318","indexId":"sir20235085","displayToPublicDate":"2023-09-05T09:38:18","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2023-5085","displayTitle":"Updates to CE-QUAL-W2 Models for Select U.S. Army Corps of Engineers Reservoirs in the Willamette Valley Project and an Inter-Reservoir Reach of the Middle Fork Willamette River, Northwestern Oregon","title":"Updates to CE-QUAL-W2 models for select U.S. Army Corps of Engineers reservoirs in the Willamette Valley Project and an inter-reservoir reach of the Middle Fork Willamette River, northwestern Oregon","docAbstract":"

Mechanistic models capable of simulating hydrodynamics and water temperature in rivers and reservoirs are valuable tools for investigating thermal conditions and their relation to dam operations and streamflow in river basins where upstream water storage and management decisions have an important influence on river reaches with threatened fish populations. In particular, models allow managers to investigate how new, untried operations or hypothetical structures might influence streamflow and temperature conditions downstream. CE-QUAL-W2 is a two-dimensional (laterally averaged) hydrodynamic water-quality model that has previously been used to investigate the downstream effects of dam operations and other anthropogenic influences on stream temperature in the Willamette River Basin in northwestern Oregon, a region with two populations of fish species designated as threatened under the Endangered Species Act. By linking CE-QUAL-W2 river models to models of upstream, large Willamette Valley Project dams and reservoirs, these models can be used to investigate how dam operations at individual dams can influence streamflow and thermal conditions in downstream river reaches as an integrated system. Integrated model simulations that include the large dams and reservoirs linked to downstream river reaches can help managers develop a better understanding of tradeoffs associated with potential retrofits or operational changes across the multipurpose dams in the Willamette Valley Project, the effect of dam management on downstream tributaries and the Willamette River, and the resulting potential effect on threatened fish populations and habitat conditions.

River models capable of simulating river corridors downstream from U.S. Army Corps of Engineers dams were previously updated and integrated to simulate conditions that occurred from March through October of 2011 (a cool and wet year), 2015 (a hot and dry year), and 2016 (a moderately hot and dry year) using CE-QUAL-W2 version 4.2. These river models encompass the following:

This report documents model modifications, boundary condition data sources or estimation methods, and goodness-of-fit statistics for six CE-QUAL-W2 reservoir models and one river model upstream from the existing river models. These models simulate (1) Hills Creek Lake; (2) Lookout Point Lake and Dexter Reservoir on the Middle Fork Willamette River; (3) the Middle Fork Willamette River reach between Hills Creek Dam upstream and Lookout Point Lake downstream; (4) Cougar Reservoir on the South Fork McKenzie River; (5) Green Peter Lake on the Middle Santiam River and Foster Lake on the South Santiam River; and (6) Detroit Lake and (7) Big Cliff Reservoir on the North Santiam River. These CE-QUAL-W2 models were built by a variety of researchers to simulate a range of conditions in past years; this report documents their upgrade to U.S. Geological Survey (USGS) edition 7 of version 4.2 of CE-QUAL-W2 and updates each model to simulate conditions from January through December of 2011, 2015, and 2016. Also included in this report is an explanation of modifications to the CE-QUAL-W2 source code that constitute USGS edition 7 of CE-QUAL-W2 version 4.2. Each of the models described in this report can be run in isolation or linked to downstream models as a “system model” to simulate conditions in tributaries and (or) in the Willamette Valley Project as a whole.

As part of the model updates described in this report, some model parameters were adjusted to improve stability or decrease model error, and boundary conditions including meteorological, hydrologic, and temperature inputs were developed and updated for model years 2011, 2015, and 2016, as necessary. In some cases, the data sources used to drive previous model versions were no longer available, which required the development and checking of new data sources or estimation techniques. Goodness-of-fit statistics for outflow from the dams and in simulated river reaches generally show a good model fit, with the models simulating subdaily water temperatures at most comparable locations with a mean absolute error of generally less than 1 degree Celsius (°C) and a reasonably low bias. Model simulation of the thermal vertical profiles in each reservoir also produced an overall mean absolute error of generally less than 1 °C for all 3 years, with the exception of the Hills Creek Lake Model and the Cougar Reservoir Model in years when the reservoirs did not fill (2015 and 2016). Both of these models have known calibration issues and tend to be sensitive to the choice of certain structural parameters in the model. Overall, the calibration process was focused on obtaining model settings that led to realistic water temperature predictions in all 3 years (2011, 2015, and 2016) without over-calibrating specifically to any single year. A complete investigation of model error for these reservoir submodels was beyond the scope of this investigation but could be undertaken in the future if better model performance for these two reservoirs is desired.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235085","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers, Portland District","usgsCitation":"Stratton Garvin, L.E., Buccola, N.L., and Rounds, S.A., 2023, Updates to CE-QUAL-W2 models for select U.S. Army Corps of Engineers reservoirs in the Willamette Valley Project and an inter-reservoir reach of the Middle Fork Willamette River, northwestern Oregon (ver. 1.1, June 2025): U.S. Geological Survey Scientific Investigations Report 2023–5085, 89 p., https://doi.org/10.3133/sir20235085.","productDescription":"Report: xii, 89 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-141377","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":494149,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_115245.htm","linkFileType":{"id":5,"text":"html"}},{"id":420372,"rank":6,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2023/5085/sir20235085.XML"},{"id":420371,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2023/5085/images"},{"id":420373,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9UJFXA5","text":"USGS data release","description":"USGS data release","linkHelpText":"CE-QUAL-W2 models for select U.S. Army Corps of Engineers reservoirs in the Willamette Valley Project and an inter-reservoir reach of the Middle Fork Willamette River, northwestern Oregon, 2011, 2015, and 2016 (ver. 1.1, May 2025)"},{"id":491287,"rank":3,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sir/2023/5085/versionHist.txt","size":"2 KB","linkFileType":{"id":2,"text":"txt"}},{"id":420368,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2023/5085/coverthb2.jpg"},{"id":420369,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2023/5085/sir20235085.pdf","text":"Report","size":"24 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2023-5085"}],"country":"United States","state":"Oregon","otherGeospatial":"Willamette River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.45633507532085,\n 45.58946612874976\n ],\n [\n -122.9361641346579,\n 46.04098363545978\n ],\n [\n -123.5145410212395,\n 45.5627587310459\n ],\n [\n -123.63148629596873,\n 44.60670825289975\n ],\n [\n -123.5623951104441,\n 43.59496378124939\n ],\n [\n -123.05635970383773,\n 43.13379451064938\n ],\n [\n -121.74055049946932,\n 42.79157283626091\n ],\n [\n -121.20756798908744,\n 43.3534143414802\n ],\n [\n -121.15566880710551,\n 44.42799279254055\n ],\n [\n -121.3336847614029,\n 45.19900479802473\n ],\n [\n -121.88806972979938,\n 45.53916954884161\n ],\n [\n -122.45633507532085,\n 45.58946612874976\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","edition":"Version 1.0: September 5, 2023; Version 1.1: June 27, 2025","contact":"

Director, Oregon Water Science Center
U.S. Geological Survey
601 SW Second Avenue, Suite 1950
Portland, Oregon 97204

","tableOfContents":"","publishedDate":"2023-09-05","revisedDate":"2025-06-27","noUsgsAuthors":false,"publicationDate":"2023-09-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Stratton Garvin, Laurel E. 0000-0001-8567-8619 lstratton@usgs.gov","orcid":"https://orcid.org/0000-0001-8567-8619","contributorId":270182,"corporation":false,"usgs":true,"family":"Stratton Garvin","given":"Laurel","email":"lstratton@usgs.gov","middleInitial":"E.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":881555,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Buccola, Norman L. 0000-0002-9590-2458 nbuccola@usgs.gov","orcid":"https://orcid.org/0000-0002-9590-2458","contributorId":139096,"corporation":false,"usgs":true,"family":"Buccola","given":"Norman","email":"nbuccola@usgs.gov","middleInitial":"L.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":881556,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rounds, Stewart A. 0000-0002-8540-2206 sarounds@usgs.gov","orcid":"https://orcid.org/0000-0002-8540-2206","contributorId":905,"corporation":false,"usgs":true,"family":"Rounds","given":"Stewart","email":"sarounds@usgs.gov","middleInitial":"A.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":881557,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70248263,"text":"70248263 - 2023 - Prioritizing science efforts to inform decision making on public lands","interactions":[],"lastModifiedDate":"2023-12-04T17:05:49.12494","indexId":"70248263","displayToPublicDate":"2023-09-05T08:24:53","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1701,"text":"Frontiers in Ecology and the Environment","active":true,"publicationSubtype":{"id":10}},"title":"Prioritizing science efforts to inform decision making on public lands","docAbstract":"

Public land management agencies in the US are committed to using science-informed decision making, but there has been little research on the types and topics of science that managers need most to inform their decisions. We used the National Environmental Policy Act to identify four types of science information needed for making decisions relevant to public lands: (1) data on resources of concern, (2) scientific studies relevant to potential effects of proposed actions, (3) methods for quantifying potential effects of proposed actions, and (4) effective mitigation measures. We then used this framework to analyze 70 Environmental Assessments completed by the Bureau of Land Management in Colorado. Commonly proposed actions were oil and gas development, livestock grazing, land transactions, and recreation. Commonly analyzed resources included terrestrial wildlife, protected birds, vegetation, and soils. Focusing research efforts on the intersection of these resources and actions, and on developing and evaluating the effectiveness of mitigation measures to protect these resources, could strengthen the science foundation for public lands decision making.

","language":"English","publisher":"Wiley","doi":"10.1002/fee.2672","usgsCitation":"Carter, S.K., Haby, T., Meineke, J.K., Foster, A.C., McCall, L.E., Espy, L., Gilbert, M., Herrick, J.E., and Prentice, K., 2023, Prioritizing science efforts to inform decision making on public lands: Frontiers in Ecology and the Environment, v. 21, no. 10, p. 453-460, https://doi.org/10.1002/fee.2672.","productDescription":"8 p.","startPage":"453","endPage":"460","ipdsId":"IP-134196","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":442187,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/fee.2672","text":"Publisher Index Page"},{"id":420558,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"21","issue":"10","noUsgsAuthors":false,"publicationDate":"2023-09-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Carter, Sarah K. 0000-0003-3778-8615","orcid":"https://orcid.org/0000-0003-3778-8615","contributorId":192418,"corporation":false,"usgs":true,"family":"Carter","given":"Sarah","email":"","middleInitial":"K.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":882143,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Haby, Travis","contributorId":202409,"corporation":false,"usgs":false,"family":"Haby","given":"Travis","affiliations":[{"id":36421,"text":"Bureau of Land Management National Operations Center","active":true,"usgs":false}],"preferred":false,"id":882144,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Meineke, Jennifer K. 0000-0002-7136-5854","orcid":"https://orcid.org/0000-0002-7136-5854","contributorId":275418,"corporation":false,"usgs":true,"family":"Meineke","given":"Jennifer","email":"","middleInitial":"K.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":882145,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Foster, Alison C. 0000-0002-6659-2120","orcid":"https://orcid.org/0000-0002-6659-2120","contributorId":260599,"corporation":false,"usgs":true,"family":"Foster","given":"Alison","email":"","middleInitial":"C.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":882146,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McCall, Laine E. 0000-0003-2624-8453","orcid":"https://orcid.org/0000-0003-2624-8453","contributorId":275417,"corporation":false,"usgs":true,"family":"McCall","given":"Laine","email":"","middleInitial":"E.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":882228,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Espy, Leigh","contributorId":329383,"corporation":false,"usgs":false,"family":"Espy","given":"Leigh","email":"","affiliations":[{"id":7217,"text":"Bureau of Land Management","active":true,"usgs":false}],"preferred":false,"id":882147,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Gilbert, Megan A.","contributorId":329384,"corporation":false,"usgs":false,"family":"Gilbert","given":"Megan A.","affiliations":[{"id":7217,"text":"Bureau of Land Management","active":true,"usgs":false}],"preferred":false,"id":882148,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Herrick, Jeffrey E.","contributorId":26054,"corporation":false,"usgs":false,"family":"Herrick","given":"Jeffrey","email":"","middleInitial":"E.","affiliations":[{"id":12627,"text":"USDA-ARS Jornada Experimental Range, New Mexico State University, Las Cruces, NM 88003-8003, USA","active":true,"usgs":false}],"preferred":false,"id":882149,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Prentice, Karen","contributorId":177304,"corporation":false,"usgs":false,"family":"Prentice","given":"Karen","affiliations":[],"preferred":false,"id":882150,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70248272,"text":"70248272 - 2023 - Wind-modulated groundwater discharge along a microtidal Arctic coastline","interactions":[],"lastModifiedDate":"2023-09-06T11:47:24.361413","indexId":"70248272","displayToPublicDate":"2023-09-05T06:35:48","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1562,"text":"Environmental Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Wind-modulated groundwater discharge along a microtidal Arctic coastline","docAbstract":"

Groundwater discharge transports dissolved constituents to the ocean, affecting coastal carbon budgets and water quality. However, the magnitude and mechanisms of groundwater exchange along rapidly transitioning Arctic coastlines are largely unknown due to limited observations. Here, using first-of-its-kind coastal Arctic groundwater timeseries data, we evaluate the magnitude and drivers of groundwater discharge to Alaska's Beaufort Sea coast. Darcy flux calculations reveal temporally variable groundwater fluxes, ranging from −6.5 cm d−1 (recharge) to 14.1 cm d−1 (discharge), with fluctuations in groundwater discharge or aquifer recharge over diurnal and multiday timescales during the open-water season. The average flux during the monitoring period of 4.9 cm d−1 is in line with previous estimates, but the maximum discharge exceeds previous estimates by over an order-of-magnitude. While the diurnal fluctuations are small due to the microtidal conditions, multiday variability is large and drives sustained periods of aquifer recharge and groundwater discharge. Results show that wind-driven lagoon water level changes are the dominant mechanism of fluctuations in land–sea hydraulic head gradients and, in turn, groundwater discharge. Given the microtidal conditions, low topographic relief, and limited rainfall along the Beaufort Sea coast, we identify wind as an important forcing mechanism of coastal groundwater discharge and aquifer recharge with implications for nearshore biogeochemistry. This study provides insights into groundwater flux dynamics along this coastline over time and highlights an oft overlooked discharge and circulation mechanism with implications towards refining solute export estimates to coastal Arctic waters.

","language":"English","publisher":"IOP Publishing","doi":"10.1088/1748-9326/acf0d8","usgsCitation":"Guimond, J., Demir, C., Kurylyk, B.L., Walvoord, M.A., McClelland, J., and Cardenas, M.B., 2023, Wind-modulated groundwater discharge along a microtidal Arctic coastline: Environmental Research Letters, v. 18, 094042, 10 p., https://doi.org/10.1088/1748-9326/acf0d8.","productDescription":"094042, 10 p.","ipdsId":"IP-155579","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":442198,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1088/1748-9326/acf0d8","text":"Publisher Index Page"},{"id":420538,"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 -149.8787190288838,\n 70.63569535875706\n ],\n [\n -149.8787190288838,\n 70.39401335666025\n ],\n [\n -148.90750421618975,\n 70.39401335666025\n ],\n [\n -148.90750421618975,\n 70.63569535875706\n ],\n [\n -149.8787190288838,\n 70.63569535875706\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"18","noUsgsAuthors":false,"publicationDate":"2023-09-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Guimond, Julia","contributorId":266043,"corporation":false,"usgs":false,"family":"Guimond","given":"Julia","email":"","affiliations":[{"id":24650,"text":"Dalhousie University","active":true,"usgs":false}],"preferred":false,"id":882179,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Demir, Casu","contributorId":329392,"corporation":false,"usgs":false,"family":"Demir","given":"Casu","email":"","affiliations":[{"id":29861,"text":"The University of Texas at Austin","active":true,"usgs":false}],"preferred":false,"id":882180,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kurylyk, Barret L.","contributorId":176296,"corporation":false,"usgs":false,"family":"Kurylyk","given":"Barret","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":882181,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Walvoord, Michelle A. 0000-0003-4269-8366","orcid":"https://orcid.org/0000-0003-4269-8366","contributorId":211843,"corporation":false,"usgs":true,"family":"Walvoord","given":"Michelle","email":"","middleInitial":"A.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":882182,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McClelland, James W.","contributorId":255074,"corporation":false,"usgs":false,"family":"McClelland","given":"James W.","affiliations":[{"id":36422,"text":"University of Texas","active":true,"usgs":false}],"preferred":false,"id":882183,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Cardenas, M. Bayani","contributorId":181932,"corporation":false,"usgs":false,"family":"Cardenas","given":"M.","email":"","middleInitial":"Bayani","affiliations":[],"preferred":false,"id":882184,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70248362,"text":"70248362 - 2023 - Sharing FAIR monitoring program data improves discoverability and reuse","interactions":[],"lastModifiedDate":"2023-09-12T19:06:42.996433","indexId":"70248362","displayToPublicDate":"2023-09-04T07:18:04","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":16706,"text":"Enviornmental Monitoring and Assessment","active":true,"publicationSubtype":{"id":10}},"title":"Sharing FAIR monitoring program data improves discoverability and reuse","docAbstract":"

Data resulting from environmental monitoring programs are valuable assets for natural resource managers, decision-makers, and researchers. These data are often collected to inform specific reporting needs or decisions with a specific timeframe. While program-oriented data and related publications are effective for meeting program goals, sharing well-documented data and metadata allows users to research aspects outside initial program intentions. As part of an effort to integrate data from four long-term large-scale US aquatic monitoring programs, we evaluated the original datasets against the FAIR (Findable, Accessible, Interoperable, Reusable) data principles and offer recommendations and lessons learned. Differences in data governance across these programs resulted in considerable effort to access and reuse the original datasets. Requirements, guidance, and resources available to support data publishing and documentation are inconsistent across agencies and monitoring programs, resulting in various data formats and storage locations that are not easily found, accessed, or reused. Making monitoring data FAIR will reduce barriers to data discovery and reuse. Programs are continuously striving to improve data management, data products, and metadata; however, provision of related tools, consistent guidelines and standards, and more resources to do this work is needed. Given the value of these data and the significant effort required to access and reuse them, actions and steps intended on improving data documentation and accessibility are described.

","language":"English","publisher":"Springer","doi":"10.1007/s10661-023-11788-4","usgsCitation":"Bayer, J.M., Scully, R., Dlabola, E.K., Courtwright, J., Hirsch, C.L., Hockman-Wert, D.P., Miller, S.W., Roper, B.B., Saunders, W.C., and Snyder, M.N., 2023, Sharing FAIR monitoring program data improves discoverability and reuse: Enviornmental Monitoring and Assessment, v. 195, 1141, 12 p., https://doi.org/10.1007/s10661-023-11788-4.","productDescription":"1141, 12 p.","ipdsId":"IP-146005","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":420657,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"http://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"195","noUsgsAuthors":false,"publicationDate":"2023-09-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Bayer, Jennifer M. 0000-0001-9564-3110 jbayer@usgs.gov","orcid":"https://orcid.org/0000-0001-9564-3110","contributorId":3393,"corporation":false,"usgs":true,"family":"Bayer","given":"Jennifer","email":"jbayer@usgs.gov","middleInitial":"M.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true},{"id":5067,"text":"Northeast Regional Director's Office","active":true,"usgs":true},{"id":5077,"text":"Northwest Regional Director's Office","active":true,"usgs":true}],"preferred":true,"id":882683,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Scully, Rebecca A 0000-0003-0704-8907","orcid":"https://orcid.org/0000-0003-0704-8907","contributorId":329593,"corporation":false,"usgs":false,"family":"Scully","given":"Rebecca A","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":882684,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dlabola, Erin K. 0000-0002-2510-9948","orcid":"https://orcid.org/0000-0002-2510-9948","contributorId":329594,"corporation":false,"usgs":false,"family":"Dlabola","given":"Erin","email":"","middleInitial":"K.","affiliations":[{"id":20304,"text":"Pacific States Marine Fisheries Commission","active":true,"usgs":false}],"preferred":false,"id":882685,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Courtwright, Jennifer L","contributorId":328473,"corporation":false,"usgs":false,"family":"Courtwright","given":"Jennifer L","affiliations":[],"preferred":false,"id":882687,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hirsch, Christine L","contributorId":329599,"corporation":false,"usgs":false,"family":"Hirsch","given":"Christine","email":"","middleInitial":"L","affiliations":[{"id":7134,"text":"USFS","active":true,"usgs":false}],"preferred":false,"id":882688,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hockman-Wert, David P 0000-0003-2436-6237","orcid":"https://orcid.org/0000-0003-2436-6237","contributorId":228969,"corporation":false,"usgs":false,"family":"Hockman-Wert","given":"David","email":"","middleInitial":"P","affiliations":[{"id":37389,"text":"U.S. Forest Service","active":true,"usgs":false}],"preferred":false,"id":882689,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Miller, Scott W.","contributorId":237002,"corporation":false,"usgs":false,"family":"Miller","given":"Scott","email":"","middleInitial":"W.","affiliations":[{"id":6682,"text":"Utah State University","active":true,"usgs":false}],"preferred":false,"id":882690,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Roper, Brett B.","contributorId":120701,"corporation":false,"usgs":false,"family":"Roper","given":"Brett","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":882691,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Saunders, W. Carl 0000-0002-2066-9276","orcid":"https://orcid.org/0000-0002-2066-9276","contributorId":328474,"corporation":false,"usgs":false,"family":"Saunders","given":"W.","email":"","middleInitial":"Carl","affiliations":[{"id":36493,"text":"USDA Forest Service","active":true,"usgs":false}],"preferred":false,"id":882692,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Snyder, Marcia N","contributorId":329601,"corporation":false,"usgs":false,"family":"Snyder","given":"Marcia","email":"","middleInitial":"N","affiliations":[{"id":7134,"text":"USFS","active":true,"usgs":false}],"preferred":false,"id":882693,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70249565,"text":"70249565 - 2023 - Positioning aquatic animals with acoustic transmitters","interactions":[],"lastModifiedDate":"2023-10-17T11:55:31.610527","indexId":"70249565","displayToPublicDate":"2023-09-04T06:49:17","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2717,"text":"Methods in Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Positioning aquatic animals with acoustic transmitters","docAbstract":"
  1. Geolocating aquatic animals with acoustic tags has been ongoing for decades, relying on the detection of acoustic signals at multiple receivers with known positions to calculate a 2D or 3D position, and ultimately recreate the path of an aquatic animal from detections at fixed stations.
  2. This method of underwater geolocation is evolving with new software and hardware options available to help investigators design studies and calculate positions using solvers based predominantly on time-difference-of-arrival and time-of-arrival.
  3. We provide an overview of the considerations necessary to implement positioning in aquatic acoustic telemetry studies, including how to design arrays of receivers, test performance, synchronize receiver clocks and calculate positions from the detection data. We additionally present some common positioning algorithms, including both the free open-source solvers and the ‘black-box’ methods provided by some manufacturers for calculating positions.
  4. This paper is the first to provide a comprehensive overview of methods and considerations for designing and implementing better positioning studies that will support users, and encourage further knowledge advances in aquatic systems.
","language":"English","publisher":"British Ecological Society","doi":"10.1111/2041-210X.14191","usgsCitation":"Lennox, R.J., Aarestrup, K., Alos, J., Arlinghaus, R., Aspillaga, E., Bertram, M.G., Birnie-Gauvin, K., Brodin, T., Cooke, S., Dahlmo, L.S., Dhellemmes, F., Gjelland, K.O., Hellstrom, G., Hershey, H., Holbrook, C., Klefoth, T., Lowerre-Barbieri, S.K., Monk, C.T., Nilsen, C.I., Pauwels, I., Pickholtz, R., Prchalova, M., Reubens, J., Říha, M., Villegas-Rios, D., Vollset, K.W., Westrelin, S., and Baktoft, H., 2023, Positioning aquatic animals with acoustic transmitters: Methods in Ecology and Evolution, v. 14, no. 10, p. 2514-2530, https://doi.org/10.1111/2041-210X.14191.","productDescription":"17 p.","startPage":"2514","endPage":"2530","ipdsId":"IP-153443","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":442208,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/2041-210x.14191","text":"Publisher Index Page"},{"id":421937,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"14","issue":"10","noUsgsAuthors":false,"publicationDate":"2023-09-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Lennox, Robert J.","contributorId":198273,"corporation":false,"usgs":false,"family":"Lennox","given":"Robert","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":886222,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Aarestrup, Kim","contributorId":203992,"corporation":false,"usgs":false,"family":"Aarestrup","given":"Kim","email":"","affiliations":[{"id":36789,"text":"Danmarks Tekniske Universitet","active":true,"usgs":false}],"preferred":false,"id":886223,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Alos, Josep","contributorId":330921,"corporation":false,"usgs":false,"family":"Alos","given":"Josep","email":"","affiliations":[{"id":79064,"text":"Instituto Mediterráneo de Estudios Avanzados","active":true,"usgs":false}],"preferred":false,"id":886224,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Arlinghaus, Robert","contributorId":32425,"corporation":false,"usgs":false,"family":"Arlinghaus","given":"Robert","email":"","affiliations":[{"id":17980,"text":"Leibniz-Institute of Freshwater Ecology and Inland Fisheries, Berlin, Germany","active":true,"usgs":false}],"preferred":false,"id":886225,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Aspillaga, Eneko","contributorId":330922,"corporation":false,"usgs":false,"family":"Aspillaga","given":"Eneko","email":"","affiliations":[{"id":79064,"text":"Instituto Mediterráneo de Estudios Avanzados","active":true,"usgs":false}],"preferred":false,"id":886226,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bertram, Michael G.","contributorId":257463,"corporation":false,"usgs":false,"family":"Bertram","given":"Michael","email":"","middleInitial":"G.","affiliations":[{"id":52030,"text":"Swedish University of Agricultural Sciences, Umeå, Sweden","active":true,"usgs":false}],"preferred":false,"id":886227,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Birnie-Gauvin, Kim","contributorId":272554,"corporation":false,"usgs":false,"family":"Birnie-Gauvin","given":"Kim","email":"","affiliations":[],"preferred":false,"id":886228,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Brodin, Tomas","contributorId":212851,"corporation":false,"usgs":false,"family":"Brodin","given":"Tomas","email":"","affiliations":[{"id":24847,"text":"Umea University","active":true,"usgs":false}],"preferred":false,"id":886229,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Cooke, Steven J.","contributorId":56132,"corporation":false,"usgs":false,"family":"Cooke","given":"Steven J.","affiliations":[{"id":36574,"text":"Carleton University, Ottawa, Ontario","active":true,"usgs":false}],"preferred":false,"id":886230,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Dahlmo, Lotte S.","contributorId":330923,"corporation":false,"usgs":false,"family":"Dahlmo","given":"Lotte","email":"","middleInitial":"S.","affiliations":[{"id":79065,"text":"NORCE Norwegian Research Centre; 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Expansion of exotic annual grass (EAG), such as cheatgrass (Bromus tectorum L.) and medusahead (Taeniatherum caput-medusae [L.] Nevski), could cause irreversible changes to arid and semiarid rangeland ecosystems in the western United States. The distribution and abundance of EAG species are highly affected by weather variables such as temperature and precipitation. The study's goal is to understand how different precipitation scenarios affect EAG abundance estimates and dynamics, and we develop a machine learning modeling approach to predict how changes in annual and immediate past precipitation patterns could affect the abundance of EAG. The machine learning predictive model used seed source from previous years, weather variables, and soil profiles to drive its predictions. We achieved excellent training accuracy (r = 0.95 and median absolute error [MdAE] = 2.36% cover) and strong test accuracy (r = 0.79 and MdAE = 4.54% cover). We developed five versions of EAG abundance maps for 2022 with different precipitation scenarios: 9 yr of average precipitation, half of the average, three-fourths of the average, one and one-half times the average, and two times the average. The approach presented can be replicated to new study domains and easily modified for use with other precipitation scenarios. Developing multiple versions of a year's EAG spatially explicit abundance dataset predictions from multiple weather-based scenarios can provide important information to land managers as they prepare for variable EAG dynamics each year. Informed annual predictions based on weather scenario−driven models have the potential to improve fire preparation decisions.

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This report describes work carried out under the U.S. Nuclear Regulatory Commission (NRC) Interagency Agreement to the U.S. Geological Survey (USGS) “Research to Support NRC’s Seismic Hazard Analyses” for Task 3, “Seismic Hazard and Ground Motion Models.” The focus of this work has been on evaluation of the Next Generation Attenuation (NGA)-East groundmotion models (GMMs) with available ground-motion data and evaluation of alternative methods for characterizing epistemic uncertainty for probabilistic seismic hazard analysis (PSHA).  

When the Interagency Agreement commenced, the USGS’s National Seismic Hazard Model (NSHM) was being updated, and a significant part of the update for the 2018 NSHM included the introduction of new GMMs for the central and eastern United States (CEUS) (Petersen et al., 2020). In addition to the implementation of the then-recently developed NGA-East GMMs (Goulet et al., 2018), the ground-motion characterization for the CEUS in the 2018 NSHM also included a logic-tree branch with weights applied to the updated “adjusted seed” models that were developed as part of the NGA-East process and in updates by the GMM developers.  

The Statement of Work for Task 3 of the NRC Interagency Agreement to the USGS included the following parts: (1) Describe technically acceptable approaches in combining GMMs for use in PSHA calculations; (2) Evaluate the effect of using different sets of GMMs (NGA-East SSHAC versus NGA-East USGS) on PSHA calculations; (3) Describe the results of the GMM testing against recorded data, and provide a recommendation on the GMMs application for use in the PSHA; (4) Evaluate the impacts of recently updated individual GMMs on the published NGAEast models; and (5) Submit a final Technical Letter Report documenting results of this task.

We present results from this work in two sections: (Chapter 1) Updated Central and Eastern United States Ground Motions and Ground-Motion Analyses; and (Chapter 2) Approaches to Combining Ground-Motion Models for Probabilistic Seismic Hazard Analysis in the Central and Eastern United States.

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