Limited data, time, and funding lead conservation managers to make difficult choices in managing species recovery. Coupled dynamical models are relied upon for decision support, but their application to empirical predator-prey systems has generally been restricted to small, tractable species. To broaden their use in conservation decision-making, we developed a model suitable for predicting the population dynamics of a larger apex carnivore and its prey. We selected southern sea otters (Enhydra lutris nereis) and their primary estuarine prey as our case study and parameterized the dynamical model with data on sea otter, clam, and crab abundances; predator-prey interactions; and sea otter bioenergetics collected from Elkhorn Slough, CA. Our model, having integrated all these salient factors, was able to successfully reproduce trends in taxa abundance as well as shifts in sea otter diet composition and energy intake rates. Rich data inputs allow the model to predict population dynamics over realistic temporal scales not only for the site of data collection, but also for similar estuaries uncolonized by sea otters. Based on model projections parameterized with prey survey data from two such estuaries, Tomales Bay and Drakes Estero, we predict the sites could support over 160 sea otters and may hold potential to further species recovery. In systems with good data availability, the model has high predictive power and can provide multi-taxa projections useful for making informed management decisions.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.biocon.2024.110623","usgsCitation":"Hamilton, S.N., Tinker, M.T., Jackson, J., Tomoleoni, J.A., Kenner, M.C., Yee, J.L., Bell, T., Castorani, M.C., Becker, B.H., and Hughes, B.B., 2024, Modeling coupled dynamics of an empirical predator-prey system to predict top predator recovery: Biological Conservation, v. 294, https://doi.org/10.1016/j.biocon.2024.110623.","productDescription":"110623, 10 p.","startPage":"110623","ipdsId":"IP-161954","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":439583,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.biocon.2024.110623","text":"Publisher Index Page"},{"id":429752,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Drakes Estero, Tomales Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.74955788944419,\n 38.00758882778453\n ],\n [\n -122.74955788944419,\n 38.30127856996327\n ],\n [\n -123.07749717586825,\n 38.30127856996327\n ],\n [\n -123.07749717586825,\n 38.00758882778453\n ],\n [\n -122.74955788944419,\n 38.00758882778453\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"294","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Hamilton, Samantha N. M.","contributorId":337990,"corporation":false,"usgs":false,"family":"Hamilton","given":"Samantha","email":"","middleInitial":"N. M.","affiliations":[{"id":81062,"text":"Sonoma State University and Johns Hopkins University","active":true,"usgs":false}],"preferred":false,"id":902846,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tinker, M. T. 0000-0002-3314-839X","orcid":"https://orcid.org/0000-0002-3314-839X","contributorId":54152,"corporation":false,"usgs":false,"family":"Tinker","given":"M.","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":902847,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jackson, Joseph","contributorId":337995,"corporation":false,"usgs":false,"family":"Jackson","given":"Joseph","email":"","affiliations":[],"preferred":false,"id":902848,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"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":902849,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"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":902850,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"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":902851,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bell, Tomoko","contributorId":211310,"corporation":false,"usgs":false,"family":"Bell","given":"Tomoko","email":"","affiliations":[{"id":7267,"text":"University of Tokyo","active":true,"usgs":false}],"preferred":false,"id":902852,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Castorani, Max C. N.","contributorId":337991,"corporation":false,"usgs":false,"family":"Castorani","given":"Max","email":"","middleInitial":"C. N.","affiliations":[{"id":25492,"text":"University of Virginia","active":true,"usgs":false}],"preferred":false,"id":902853,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Becker, Benjamin H.","contributorId":207275,"corporation":false,"usgs":false,"family":"Becker","given":"Benjamin","email":"","middleInitial":"H.","affiliations":[{"id":37509,"text":"Point Reyes National Seashore, Point Reyes Station, CA","active":true,"usgs":false}],"preferred":true,"id":902854,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Hughes, Brent B.","contributorId":201240,"corporation":false,"usgs":false,"family":"Hughes","given":"Brent","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":902855,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70254909,"text":"70254909 - 2024 - Tool use increases mechanical foraging success and tooth health in southern sea otters (Enhydra lutris nereis)","interactions":[],"lastModifiedDate":"2024-09-16T15:30:09.8264","indexId":"70254909","displayToPublicDate":"2024-05-16T09:06:20","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3338,"text":"Science","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Tool use increases mechanical foraging success and tooth health in southern sea otters (Enhydra lutris nereis)","title":"Tool use increases mechanical foraging success and tooth health in southern sea otters (Enhydra lutris nereis)","docAbstract":"Although tool use may enhance resource utilization, its fitness benefits are difficult to measure. By examining longitudinal data from 196 radio-tagged southern sea otters (Enhydra lutris nereis), we found that tool-using individuals, particularly females, gained access to larger and/or harder-shelled prey. These mechanical advantages translated to reduced tooth damage during food processing. We also found that tool use diminishes trade-offs between access to different prey, tooth condition, and energy intake, all of which are dependent on the relative prey availability in the environment. Tool use allowed individuals to maintain energetic requirements through the processing of alternative prey that are typically inaccessible with biting alone, suggesting that this behavior is a necessity for the survival of some otters in environments where preferred prey are depleted.
","language":"English","publisher":"American Association for the Advancement of Science","doi":"10.1126/science.adj6608","usgsCitation":"Law, C.J., Tinker, M., Fujii, J.A., Nicholson, T., Staedler, M.M., Tomoleoni, J.A., Young, C., and Mehta, R.S., 2024, Tool use increases mechanical foraging success and tooth health in southern sea otters (Enhydra lutris nereis): Science, v. 384, no. 6697, p. 798-802, https://doi.org/10.1126/science.adj6608.","productDescription":"5 p.","startPage":"798","endPage":"802","ipdsId":"IP-162451","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":429739,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"384","issue":"6697","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Law, Chris J.","contributorId":337988,"corporation":false,"usgs":false,"family":"Law","given":"Chris","email":"","middleInitial":"J.","affiliations":[{"id":81059,"text":"University of Washington, University of Texas","active":true,"usgs":false}],"preferred":false,"id":902838,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tinker, M. Tim 0000-0002-3314-839X","orcid":"https://orcid.org/0000-0002-3314-839X","contributorId":221787,"corporation":false,"usgs":false,"family":"Tinker","given":"M. Tim","affiliations":[{"id":40428,"text":"University of California, Santa Cruz; former USGS PI","active":true,"usgs":false}],"preferred":false,"id":902839,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"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":902840,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Nicholson, Teri","contributorId":214308,"corporation":false,"usgs":false,"family":"Nicholson","given":"Teri","affiliations":[{"id":6953,"text":"Monterey Bay Aquarium","active":true,"usgs":false}],"preferred":false,"id":902841,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Staedler, Michelle M. 0000-0002-1101-6580","orcid":"https://orcid.org/0000-0002-1101-6580","contributorId":213742,"corporation":false,"usgs":false,"family":"Staedler","given":"Michelle","email":"","middleInitial":"M.","affiliations":[{"id":6953,"text":"Monterey Bay Aquarium","active":true,"usgs":false}],"preferred":false,"id":902842,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"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":902843,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Young, Colleen","contributorId":337989,"corporation":false,"usgs":false,"family":"Young","given":"Colleen","affiliations":[{"id":6952,"text":"California Department of Fish and Wildlife","active":true,"usgs":false}],"preferred":false,"id":902844,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Mehta, Rita S.","contributorId":189577,"corporation":false,"usgs":false,"family":"Mehta","given":"Rita","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":902845,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70254369,"text":"70254369 - 2024 - Considerations and challenges in support of science and communication of fish consumption advisories for per- and polyfluoroalkyl substances","interactions":[],"lastModifiedDate":"2024-10-23T15:53:19.947813","indexId":"70254369","displayToPublicDate":"2024-05-16T06:48:04","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2006,"text":"Integrated Environmental Assessment and Management","active":true,"publicationSubtype":{"id":10}},"title":"Considerations and challenges in support of science and communication of fish consumption advisories for per- and polyfluoroalkyl substances","docAbstract":"Federal, state, tribal, or local entities in the United States issue fish consumption advisories (FCAs) as guidance for safer consumption of locally caught fish containing contaminants. Fish consumption advisories have been developed for commonly detected compounds such as mercury and polychlorinated biphenyls. The existing national guidance does not specifically address the unique challenges associated with bioaccumulation and consumption risk related to per- and polyfluoroalkyl substances (PFAS). As a result, several states have derived their own PFAS-related consumption guidelines, many of which focus on one frequently detected PFAS, known as perfluorooctane sulfonic acid (PFOS). However, there can be significant variation between tissue concentrations or trigger concentrations (TCs) of PFOS that support the individual state-issued FCAs. This variation in TCs can create challenges for risk assessors and risk communicators in their efforts to protect public health. The objective of this article is to review existing challenges, knowledge gaps, and needs related to issuing PFAS-related FCAs and to provide key considerations for the development of protective fish consumption guidance. The current state of the science and variability in FCA derivation, considerations for sampling and analytical methodologies, risk management, risk communication, and policy challenges are discussed. How to best address PFAS mixtures in the development of FCAs, in risk assessment, and establishment of effect thresholds remains a major challenge, as well as a source of uncertainty and scrutiny. This includes developments better elucidating toxicity factors, exposures to PFAS mixtures, community fish consumption behaviors, and evolving technology and analytical instrumentation, methods, and the associated detection limits. Given the evolving science and public interests informing PFAS-related FCAs, continued review and revision of FCA approaches and best practices are vital. Nonetheless, consistent, widely applicable, PFAS-specific approaches informing methods, critical concentration thresholds, and priority compounds may assist practitioners in PFAS-related FCA development and possibly reduce variability between states and jurisdictions. Integr Environ Assess Manag 2024;00:1–20. © 2024 SETAC
The U.S. Geological Survey (USGS) has long recognized the strategic importance and value of well-managed data assets as an integral component of scientific integrity and foundational to the advancement of scientific research, decision making, and public safety. The USGS investment in the science lifecycle, including collection of unbiased data assets, interpretation, peer review, interpretive publications, and data release, ultimately contributes to the transparency and availability of science. Foundational Government directives and laws, such as the Foundations for Evidence-Based Policymaking Act of 2018 (Public Law 115–435, 132 Stat. 5529) as well as Executive Order 13642, “Making Open and Machine Readable the New Default for Government Information,” provide a framework for addressing strategic data management. The USGS Data Strategy builds on that framework by outlining high-level goals and objectives that serve as a long-term, decadal guide toward achieving a broad, data-focused vision.
Benefits of the USGS Data Strategy are many. The USGS will contribute to open science by increasing efficiencies in the consistent management of valuable data assets; driving innovation that results in modernized capabilities to ensure data are analysis ready; increasing data skills across the Bureau to enhance workforce data literacy; broadening capacity to understand and address needs of stakeholders; and measuring progress in producing findable, accessible, interoperable, and reusable (FAIR) data products.
The major goals and objectives of the USGS Data Strategy promote maximizing the utility of USGS data based on stakeholder needs, promoting data innovation, coordinating common data practices, modernizing our USGS enterprise data architecture, and enhancing our data-centric culture. The goals and objectives in the strategy align with other Bureau strategic plans, guidance, and directives from the Department of the Interior and the Federal Government. This strategy is a key component to strengthen the Bureau’s data ecosystem to ensure a relevant, long-term capacity that supports internal needs and achieves its scientific mission in the most efficient and effective manner.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/cir1517","usgsCitation":"Hutchison, V.B., Burley, T.E., Blasch, K.W., Exter, P.E., Gunther, G.L., Shipman, A.J., Kelley, C.M., and Morris, C.A., 2024, U.S. Geological Survey data strategy 2023–33: U.S. Geological Survey Circular 1517, 7 p., https://doi.org/10.3133/cir1517.","productDescription":"v, 7 p.","onlineOnly":"Y","ipdsId":"IP-154183","costCenters":[{"id":5071,"text":"Office of Administration","active":true,"usgs":true},{"id":5077,"text":"Northwest Regional Director's Office","active":true,"usgs":true},{"id":38128,"text":"Science Analytics and Synthesis","active":true,"usgs":true},{"id":80860,"text":"Office of the Associate Chief Information Officer","active":true,"usgs":true}],"links":[{"id":428771,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/cir1517/full"},{"id":428770,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/circ/1517/cir1517.xml"},{"id":428769,"rank":3,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/circ/1517/images"},{"id":428707,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/circ/1517/cir1517.pdf","text":"Report","size":"5.51 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Circular 1517"},{"id":428706,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/circ/1517/coverthb.jpg"}],"contact":"Director, USGS Science Analytics and Synthesis
U.S. Geological Survey
Box 25046, MS 302
Denver, CO 80225
Eye loss has been a long-standing interest in evolutionary biology. Many organisms that inhabit environments without light penetration, for example the deep sea, exhibit eye loss and thus become blind. However, water-depth distribution of eyes in marine organisms is poorly understood. Ostracods are widely distributed crustaceans, and many sighted marine ostracods have eye tubercles (lenses) on their shells. Since eye tubercles are visible on the shells illustrated in much literature, it is easy to determine their presence or absence via a literature survey. Here, we used a large Arctic-wide ostracod census dataset (Arctic Ostracode Database) to calculate the eye index (the percentage of species with eyes), and compare them with water depth and light availability. As water depth increases, eye index values decrease and become constantly zero in water deeper than 1000 m. Similar decline of sighted species with increasing depth is also known in isopods and amphipods, suggesting that it may be common in other crustaceans and perhaps in deep-sea organisms in general. We also show that eye index values increase as light availability increases. This study is the first to quantify how distributions of sighted and blind species change with light availability, giving baseline information on vision in the deep sea.
","language":"English","publisher":"Association for the Sciences of Limnology and Oceanography","doi":"10.1002/lno.12584","usgsCitation":"Zhang, J., Yasuhara, M., Wei, C., Tian, S.Y., Aye, K.K., Gemery, L., Cronin, T.M., Frenzel, P., and Horne, D.J., 2024, Sight and blindness: The relationship between ostracod eyes, water depth, and light availability in the Arctic Ocean: Limnology and Oceanography, v. 69, no. 6, p. 1418-1428, https://doi.org/10.1002/lno.12584.","productDescription":"11 p.","startPage":"1418","endPage":"1428","ipdsId":"IP-159915","costCenters":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":439590,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/lno.12584","text":"Publisher Index Page"},{"id":428845,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"69","issue":"6","noUsgsAuthors":false,"publicationDate":"2024-05-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Zhang, Jingwen","contributorId":336196,"corporation":false,"usgs":false,"family":"Zhang","given":"Jingwen","email":"","affiliations":[{"id":55550,"text":"University of Hong Kong","active":true,"usgs":false}],"preferred":false,"id":900116,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Yasuhara, Moriaki","contributorId":178705,"corporation":false,"usgs":false,"family":"Yasuhara","given":"Moriaki","email":"","affiliations":[],"preferred":false,"id":900117,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wei, Chih-Lin","contributorId":336198,"corporation":false,"usgs":false,"family":"Wei","given":"Chih-Lin","email":"","affiliations":[{"id":55550,"text":"University of Hong Kong","active":true,"usgs":false}],"preferred":false,"id":900118,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Tian, Skye Yunshu","contributorId":336200,"corporation":false,"usgs":false,"family":"Tian","given":"Skye","email":"","middleInitial":"Yunshu","affiliations":[{"id":55550,"text":"University of Hong Kong","active":true,"usgs":false}],"preferred":false,"id":900119,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Aye, Kyawt K. T.","contributorId":336202,"corporation":false,"usgs":false,"family":"Aye","given":"Kyawt","email":"","middleInitial":"K. T.","affiliations":[{"id":55550,"text":"University of Hong Kong","active":true,"usgs":false}],"preferred":false,"id":900120,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Gemery, Laura 0000-0003-1966-8732","orcid":"https://orcid.org/0000-0003-1966-8732","contributorId":245413,"corporation":false,"usgs":true,"family":"Gemery","given":"Laura","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":900121,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Cronin, Thomas M. 0000-0001-9522-3992 tcronin@usgs.gov","orcid":"https://orcid.org/0000-0001-9522-3992","contributorId":304640,"corporation":false,"usgs":true,"family":"Cronin","given":"Thomas","email":"tcronin@usgs.gov","middleInitial":"M.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":900122,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Frenzel, Peter","contributorId":336790,"corporation":false,"usgs":false,"family":"Frenzel","given":"Peter","affiliations":[],"preferred":false,"id":901050,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Horne, David J.","contributorId":113597,"corporation":false,"usgs":true,"family":"Horne","given":"David","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":901051,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70266507,"text":"70266507 - 2024 - On the survival and habitat use of hatchery-reared cisco (Coregonus artedi) in Lake Erie","interactions":[],"lastModifiedDate":"2025-05-09T15:12:50.835095","indexId":"70266507","displayToPublicDate":"2024-05-15T10:02:44","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2330,"text":"Journal of Great Lakes Research","active":true,"publicationSubtype":{"id":10}},"displayTitle":"On the survival and habitat use of hatchery-reared cisco (Coregonus artedi) in Lake Erie","title":"On the survival and habitat use of hatchery-reared cisco (Coregonus artedi) in Lake Erie","docAbstract":"Cisco (Coregonus artedi) have been extirpated from Lake Erie in North America since the 1960s, but they once supported one of the largest Laurentian Great Lakes fisheries. Numerous potential impediments to rehabilitation have been identified, including summer habitat refugia and predation. We used acoustic telemetry to investigate the thermal habitat use and survival of hatchery-reared adult cisco in Lake Erie. Fish were experimentally released (n = 50 per site) offshore at Dunkirk, New York, in the eastern basin and Huron, Ohio, in the central basin. Cisco in both basins found suitable summer oxythermal habitat in the metalimnion, suggesting that coldwater habitat availability is likely not an impediment for reestablishment. However, track end dates or predation dates were distributed across only four months with the last detection at 155 days. Predation sensors combined with temperature values during digestion indicated different potential predators: lake trout (Salvelinus namaycush) for the Dunkirk group and walleye (Sander vitreus) for the Huron group. Additionally, digestion temperatures of two tags indicated bird predation was also important, likely underestimated and suggested substantial use of the epilimnion by tagged fish. The results highlight the need for additional studies to address stocking optimization questions in support of future reintroduction experiments and related cisco conservation efforts.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jglr.2024.102343","usgsCitation":"Kraus, R., Markham, J., Robinson, J., MacDougall, T., Faust, M., Schmitt, J., Vandergoot, C., McKenna, J., and Gorsky, D., 2024, On the survival and habitat use of hatchery-reared cisco (Coregonus artedi) in Lake Erie: Journal of Great Lakes Research, v. 50, 102343, 8 p., https://doi.org/10.1016/j.jglr.2024.102343.","productDescription":"102343, 8 p.","ipdsId":"IP-159579","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":488295,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jglr.2024.102343","text":"Publisher Index Page"},{"id":485649,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","otherGeospatial":"Lake Erie","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -78.90437674926393,\n 42.88573072124271\n ],\n [\n -79.52141499356523,\n 42.87769210959476\n ],\n [\n -80.22678399206747,\n 42.79281581499302\n ],\n [\n -80.51880625151767,\n 42.57814946253396\n ],\n [\n -81.02026663661093,\n 42.67543230196293\n ],\n [\n -81.30128454543694,\n 42.67543535756306\n ],\n [\n -81.53822853578485,\n 42.56596464399709\n ],\n [\n -81.9019334399238,\n 42.33014170165541\n ],\n [\n -81.95153424579222,\n 42.26492779780335\n ],\n [\n -82.12236039987853,\n 42.236375180224144\n ],\n [\n -82.45298532777961,\n 42.08524033767702\n ],\n [\n -82.5191058069868,\n 41.92964634487325\n ],\n [\n -82.61828632462084,\n 42.04024072452731\n ],\n [\n -82.91034362126736,\n 41.987015817617134\n ],\n [\n -83.11972864041921,\n 42.077062926530004\n ],\n [\n -83.10317152070901,\n 42.24453450962994\n ],\n [\n -83.29610139408294,\n 41.9419412108324\n ],\n [\n -83.3622121286252,\n 41.92964573816295\n ],\n [\n -83.51644448225035,\n 41.69555451568095\n ],\n [\n -82.9488535420495,\n 41.41103910261083\n ],\n [\n -82.71193183972241,\n 41.41929329585025\n ],\n [\n -82.47491670465367,\n 41.35733064230888\n ],\n [\n -81.99008606791249,\n 41.477110666960954\n ],\n [\n -81.70899983775189,\n 41.46067864477564\n ],\n [\n -81.25720217469238,\n 41.736707291689584\n ],\n [\n -80.6842102922714,\n 41.88460348122109\n ],\n [\n -79.96258495960994,\n 42.16700280222196\n ],\n [\n -79.42295622097835,\n 42.38302164176207\n ],\n [\n -79.37861904307078,\n 42.4440510296389\n ],\n [\n -79.15795348814065,\n 42.52534601120243\n ],\n [\n -79.00930804606551,\n 42.69563463834368\n ],\n [\n -78.83853732874603,\n 42.76038448982763\n ],\n [\n -78.84931646792415,\n 42.86956831700121\n ],\n [\n -78.90437674926393,\n 42.88573072124271\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"50","noUsgsAuthors":false,"publicationDate":"2024-05-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Kraus, Richard 0000-0003-4494-1841","orcid":"https://orcid.org/0000-0003-4494-1841","contributorId":216548,"corporation":false,"usgs":true,"family":"Kraus","given":"Richard","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":936397,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Markham, James","contributorId":354791,"corporation":false,"usgs":false,"family":"Markham","given":"James","affiliations":[{"id":84661,"text":"New York State Dept. of Env. 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Jr. 0000-0002-1428-7597 jemckenna@usgs.gov","orcid":"https://orcid.org/0000-0002-1428-7597","contributorId":190798,"corporation":false,"usgs":true,"family":"McKenna","given":"James E.","suffix":"Jr.","email":"jemckenna@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":936404,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Gorsky, Dimitri","contributorId":354793,"corporation":false,"usgs":false,"family":"Gorsky","given":"Dimitri","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":936405,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70255975,"text":"70255975 - 2024 - Atlas of microscopic images of biochar using reflected light microscopy in biochar characterization","interactions":[],"lastModifiedDate":"2024-07-11T13:27:32.525256","indexId":"70255975","displayToPublicDate":"2024-05-15T08:21:53","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":18004,"text":"Indiana Journal of Earth Sciences","onlineIssn":"2642-1550","active":true,"publicationSubtype":{"id":10}},"title":"Atlas of microscopic images of biochar using reflected light microscopy in biochar characterization","docAbstract":"Derived through the thermochemical conversion of biomass, biochar is a carbon-rich substance recognized for its significance in environmental applications and sustainable agriculture. As interest in its utilization continues to rise, it becomes crucial to comprehend how the source material and pyrolysis parameters influence the properties of biochar and, consequently, to research the suitability of various analytical methods for characterizing it. Despite the current utilization of numerous physical and chemical methods, the untapped potential of reflected light microscopy warrants further exploration.
While a few recent studies suggest a correlation between certain microscopic characteristics and selected physical and chemical properties of biochar, the data are limited and difficult to compare. This is primarily due to variations in the types of original biomass used and lack of information about pyrolysis conditions. Moreover, because only a limited number of photographs taken under a reflected light microscope are publicly available to-date, it is difficult to evaluate morphological differences between various biochars and other organic materials such as inertinites from coal, charcoal, etc.
To address limited availability of publicly available data, this “Atlas of Microscopic Images of Biochar” presents a collection of more than 300 images contributed by researchers from Poland, the United States, Canada, Australia, Brazil, and Denmark. These photomicrographs capture optical characteristics of a diverse array of biochar, demonstrating its unique morphological and structural features. This visual documentation can serve as a valuable resource for researchers, industry professionals, educators, and enthusiasts interested in investigating the complexities of biochar forms.
","language":"English","publisher":"Indiana Geological and Water Survey at Indiana University","doi":"10.14434/ijes.v6i1.37623","usgsCitation":"Drobniak, A., Mastalerz, M., Knauth, W., Adarkani, O., dos Santos, T.A., de Faria, V.C., Congo, T., Hackley, P.C., Hatcherian, J.J., Hower, J.C., Petersen, H.I., Reyes, J., and Sanei, H., 2024, Atlas of microscopic images of biochar using reflected light microscopy in biochar characterization: Indiana Journal of Earth Sciences, v. 6, 9 p., https://doi.org/10.14434/ijes.v6i1.37623.","productDescription":"9 p.","ipdsId":"IP-162580","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"links":[{"id":439591,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.14434/ijes.v6i1.37623","text":"Publisher Index Page"},{"id":430954,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"6","noUsgsAuthors":false,"publicationDate":"2024-05-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Drobniak, Agnieszka","contributorId":330811,"corporation":false,"usgs":false,"family":"Drobniak","given":"Agnieszka","affiliations":[{"id":79025,"text":"University of Silesia in Katowice, Faculty of Natural Sciences, ul. Będzińska 60, 41-200 Sosnowiec, Poland","active":true,"usgs":false}],"preferred":false,"id":906217,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mastalerz, Maria","contributorId":330812,"corporation":false,"usgs":false,"family":"Mastalerz","given":"Maria","affiliations":[{"id":79026,"text":"Indiana University, Indiana Geological and Water Survey, 1001 E. 10th St., Bloomington, IN 47405, United States","active":true,"usgs":false}],"preferred":false,"id":906218,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Knauth, Will","contributorId":340115,"corporation":false,"usgs":false,"family":"Knauth","given":"Will","email":"","affiliations":[{"id":81483,"text":"Centre for Biomass Energy Research and Education, University of Silesia in Katowice","active":true,"usgs":false}],"preferred":false,"id":906219,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Adarkani, Omid","contributorId":340116,"corporation":false,"usgs":false,"family":"Adarkani","given":"Omid","email":"","affiliations":[{"id":13092,"text":"Geological Survey of Canada","active":true,"usgs":false}],"preferred":false,"id":906220,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"dos Santos, Telma Ataide","contributorId":340117,"corporation":false,"usgs":false,"family":"dos Santos","given":"Telma","email":"","middleInitial":"Ataide","affiliations":[{"id":81486,"text":"TAS Petrographic Consulting & Auditing","active":true,"usgs":false}],"preferred":false,"id":906221,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"de Faria, Valdeci Caio","contributorId":340118,"corporation":false,"usgs":false,"family":"de Faria","given":"Valdeci","email":"","middleInitial":"Caio","affiliations":[{"id":81487,"text":"Gerdau Ouro Branco","active":true,"usgs":false}],"preferred":false,"id":906222,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Congo, Tara","contributorId":330818,"corporation":false,"usgs":false,"family":"Congo","given":"Tara","email":"","affiliations":[{"id":79031,"text":"The University of Queensland, Australia","active":true,"usgs":false}],"preferred":false,"id":906223,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Hackley, Paul C. 0000-0002-5957-2551 phackley@usgs.gov","orcid":"https://orcid.org/0000-0002-5957-2551","contributorId":592,"corporation":false,"usgs":true,"family":"Hackley","given":"Paul","email":"phackley@usgs.gov","middleInitial":"C.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true}],"preferred":true,"id":906224,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Hatcherian, Javin J. 0000-0001-9151-6798 jhatcherian@usgs.gov","orcid":"https://orcid.org/0000-0001-9151-6798","contributorId":195770,"corporation":false,"usgs":true,"family":"Hatcherian","given":"Javin","email":"jhatcherian@usgs.gov","middleInitial":"J.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":906225,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Hower, James C.","contributorId":330827,"corporation":false,"usgs":false,"family":"Hower","given":"James","email":"","middleInitial":"C.","affiliations":[{"id":79038,"text":"University of Kentucky Center for Applied Energy Research, USA","active":true,"usgs":false}],"preferred":false,"id":906226,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Petersen, Henrik I.","contributorId":330843,"corporation":false,"usgs":false,"family":"Petersen","given":"Henrik","email":"","middleInitial":"I.","affiliations":[{"id":79049,"text":"Geological Survey of Denmark and Greenland, Denmark","active":true,"usgs":false}],"preferred":false,"id":906227,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Reyes, Julito","contributorId":330844,"corporation":false,"usgs":false,"family":"Reyes","given":"Julito","affiliations":[{"id":79030,"text":"Geological Survey of Canada-Calgary","active":true,"usgs":false}],"preferred":false,"id":906228,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Sanei, Hamed","contributorId":168753,"corporation":false,"usgs":false,"family":"Sanei","given":"Hamed","email":"","affiliations":[{"id":13092,"text":"Geological Survey of Canada","active":true,"usgs":false}],"preferred":false,"id":906229,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}} ,{"id":70256186,"text":"70256186 - 2024 - Species richness and distribution of Sphaeriidae surveyed with Environmental DNA metabarcoding","interactions":[],"lastModifiedDate":"2024-07-25T12:26:53.798491","indexId":"70256186","displayToPublicDate":"2024-05-15T07:26:00","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5254,"text":"Freshwater Mollusk Biology and Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Species richness and distribution of Sphaeriidae surveyed with Environmental DNA metabarcoding","docAbstract":"Freshwater bivalves of the family Sphaeriidae (fingernail, pea, and pill clams) are difficult to survey and identify due to their small size and overlapping morphological traits. Environmental DNA (eDNA) metabarcoding offers a cost-effective method for assessing species richness and distributional patterns at large scales. We evaluated sphaeriid species richness and distribution at 15 sites in the Maumee River, Ohio, USA, based on two eDNA metabarcoding assays (broad and targeted), and we compared our results with those from a traditional benthic macroinvertebrate survey. We detected seven molecular operational taxonomic units (MOTUs) in the Maumee River, including Sphaerium transversum, five MOTUs representing Euglesa spp., and one MOTU representing Odhneripisidum sp. Sphaerium transversum was widely distributed, occurring at 10 sites, but Euglesa and Odhneripisidum were restricted to one to four sites in the upper river. Distributional patterns were broadly similar between both metabarcoding assays and benthic surveys. However, eDNA metabarcoding provided species-level identifications, resulting in higher species richness. Environmental DNA sampling augments and enhances traditional benthic surveys, but greater eDNA sample replication is needed to improve detection, and additional sphaeriid reference sequences are needed to improve species-level identification.
The mission of Northern Prairie Wildlife Research Center is to provide scientific information needed to conserve and manage the Nation’s natural capital for current and future generations, with an emphasis on migratory birds, Department of the Interior trust resources, and ecosystems of the Nation’s interior. This report provides an overview of the studies conducted at Northern Prairie during fiscal years 2021–23 in pursuit of this mission. Studies are organized under a framework developed by the U.S. Geological Survey Ecosystems Mission Area, identifying primary and secondary alignment with focal areas of research, and summarizing recent scientific products resulting from these studies. Partnerships with Federal, State, and non-Governmental organizations are essential to a robust program of applied ecological research, and we thank our many collaborators and colleagues whose contributions made this work possible.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/cir1512","usgsCitation":"Sherfy, M.H., ed., 2024, U.S. Geological Survey—Northern Prairie Wildlife Research Center 2021–23 research activity report: U.S. Geological Survey Circular 1512, 96 p., https://doi.org/10.3133/cir1512.","productDescription":"xi, 96 p.","numberOfPages":"112","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-135399","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":428702,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/circ/1512/coverthb.jpg"},{"id":428703,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/circ/1512/cir1512.pdf","text":"Report","size":"34 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Cir 1512"},{"id":428704,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/circ/1512/cir1512.XML"}],"contact":"Director, Northern Prairie Wildlife Research Center
U.S. Geological Survey
8711 37th Street Southeast
Jamestown, ND 58401
In 2012, a platform at the approximate center of Lake Okeechobee in central Florida was instrumented to continuously measure evaporation with the Bowen-ratio energy-budget method as part of a long-term partnership between the South Florida Water Management District and the U.S. Geological Survey. The primary goal for the study was to quantify daily rates of open-water evaporation. A secondary goal was to assess differences in evaporation rates among alternate methods and determine if instrumentation and operational expenses associated with the Bowen-ratio method could be reduced.
Mean annual evaporation from Lake Okeechobee for 2013–16 was about 1,825 millimeters per year. Annual evaporation from 2013 to 2016 was 1,760, 1,840, 1,810, and 1,890 millimeters per year, respectively. These evaporation rates are among the highest rates observed in Florida based on scientifically vetted methods such as evaporation pans, lysimeters, eddy-covariance, or Bowen-ratio methods. The high evaporation rates are largely a result of frequent clear-sky conditions over the interior of Lake Okeechobee, which allows solar radiation to reach the water surface and drive open-water evaporation. Cloud formation over the interior of Lake Okeechobee is suppressed because of a relatively large heat capacity for water that buffers convective fluxes of air that form clouds while rising and cooling.
Estimated evaporation rates obtained using five alternative methods were compared to measured Bowen-ratio energy-budget daily, monthly, and annual evaporation: the Penman, Priestly-Taylor, Mass-Transfer, Simple, and Turc equations. All five methods performed relatively well (within 10 percent of the Bowen ratio annual totals). The Penman, Priestley-Taylor, and Mass-Transfer methods captured relatively large evaporation rates that occurred in the winter due to cold fronts, because these methods account for large wind speeds and vapor pressure deficits associated with the regional cold fronts. For operational implementation, the Simple, Mass-Transfer, or Turc methods are likely preferable because of their simplicity, limited data requirements, and improved accuracy for computing monthly and annual evaporation totals. The Turc equation computed monthly evaporation within 8 percent of the Bowen-ratio method, while requiring only air temperature and solar radiation data. The Simple equation achieved similar accuracy while requiring only solar radiation data.
Director, Caribbean-Florida Water Science Center
U.S. Geological Survey
4446 Pet Lane, Suite 108
Lutz, FL 33559
Groundwater quality in the western part of the Mojave Desert in San Bernardino County, California, was investigated in 2018 as part of the California State Water Resources Control Board Groundwater Ambient Monitoring and Assessment Program Priority Basin Project. The Mojave Basin Domestic-Supply Aquifer study unit (MOBS) region was divided into two study areas—floodplain and regional—to assess differences between the two major aquifers used for drinking water supply in the area. This assessment characterized the quality of ambient groundwater and not the quality of treated drinking water.
The study included three components: (1) a status assessment, which characterized the quality of groundwater resources used for domestic drinking-water supply in the floodplain and regional study areas; (2) a brief understanding assessment, which evaluated factors that could potentially affect the quality of groundwater used by domestic wells in the region; and (3) a comparative assessment between the groundwater resources used by domestic wells and public-supply wells in the two study areas. The domestic-well assessment was based on data collected by the U.S. Geological Survey from 48 domestic wells in January–May 2018. The public-supply assessment was based on data for samples from 322 public-supply wells in 2008–18, either collected by the U.S. Geological Survey or compiled from the California State Water Resources Control Boards Division of Drinking Water publicly available database.
Concentrations of water-quality constituents in ambient groundwater were compared to regulatory and non-regulatory benchmarks typically used by the State of California and Federal agencies as health-based or aesthetic standards for public drinking water. Relative concentrations, defined as the measured concentration divided by the benchmark concentration, were classified as high (greater than 1.0), moderate (greater than 0.5 for inorganic constituents or 0.1 for organic and special-interest constituents, and not high), or low (concentrations lower than moderate). The floodplain and regional study areas were divided into 15 and 35 grid cells, respectively, and grid-based methods were used to compute the areal proportions of the two study areas with high, moderate, or low relative concentrations of individual constituents and classes of constituents.
For the domestic-supply assessment, one or more inorganic constituents with health-based benchmarks were detected at high relative concentrations in 58 percent of the regional study area and 13 percent of the floodplain study area. The inorganic constituents with health-based benchmarks detected at high relative concentrations in the regional study area were arsenic, chromium and hexavalent chromium, fluoride, adjusted gross alpha particle activity, uranium, molybdenum, strontium, and nitrate; only arsenic was detected at high relative concentrations in the floodplain study area. One or more inorganic constituents with secondary maximum contaminant level benchmarks were detected at high concentrations in 15 and 6.7 percent of the regional and floodplain study areas, respectively. The constituents detected at high relative concentrations in the regional study area were total dissolved solids, chloride, sulfate, and iron; only total dissolved solids and sulfate were detected at high relative concentrations in the floodplain study area.
Organic constituents were not detected at moderate or high relative concentrations in either the regional or floodplain study areas. Volatile organic compounds were detected at low relative concentrations in 21 and 27 percent of the regional and floodplain study areas, respectively, and pesticides were detected at low relative concentrations in 9.1 and 20 percent of the regional and floodplain study areas, respectively. The only individual organic constituent detected in more than 10 percent of either study area was the trihalomethane trichloromethane. Total coliform bacteria were detected in 15 and 27 percent of the grid wells in the regional and floodplain study areas, respectively.
The greater prevalence of high relative concentrations of many inorganic constituents in the regional study area compared to the floodplain area likely indicates the greater diversity of geologic material at depth in aquifer material and generally finer-grained alluvium compared to the floodplain study area combined with generally older groundwater that has had more contact time with aquifer materials. In general, trace element concentrations (1) increased with increasing groundwater age, (2) increased with distance from recharge sources in the mountains, and (3) increased with closer proximity to some types of geological units. In general, groundwater from domestic wells in the floodplain study area is young, with most samples containing a component of modern groundwater based on tritium and unadjusted carbon-14 activities, whereas groundwater from domestic wells in the regional study area generally is old, with most samples having unadjusted carbon-14 ages of 5,000–40,000 years.
Public-supply wells in MOBS generally were deeper than domestic wells and presumably are in contact with older, more weathered alluvium that may have more mobile trace elements, such as arsenic or uranium. However, only 26 percent of the public-supply regional study area had high relative concentrations of inorganic constituents, compared to 58 percent for the domestic regional study area. The percentages of the public-supply and domestic floodplain study areas with high relative concentrations of inorganic constituents were 11 and 13 percent, respectively. The ages of groundwater used by public-supply and domestic wells in each study area were similar, which was not expected given the greater depth of the public-supply wells. Three potential factors may contribute to these results: (1) greater spatial footprint of domestic well network, which may result in domestic wells pumping groundwater from fractured bedrock or mineralized areas not used by public-supply wells; (2) greater pumping rates in public-supply wells, resulting in more water being withdrawn from coarse-grained, heterogeneous alluvium than finer-grained layers, which may have higher concentrations of (or more mobile) inorganic constituents; and (3) a greater degree of well management with public-supply wells, which may include pausing use of or decommissioning wells if treating or blending water is not feasible to lower constituent concentrations.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20245019","collaboration":"Prepared in cooperation with the California State Water Resources Control Board","programNote":"A product of the California Groundwater Ambient Monitoring and Assessment (GAMA) Program","usgsCitation":"Groover, K.D., Fram, M.S., and Levy, Z.F., 2024, Status and understanding of groundwater quality in the Mojave Basin Domestic-Supply Aquifer study unit, 2018—California GAMA Priority Basin Project: U.S. Geological Survey Scientific Investigations Report 2024–5019, 62 p., https://doi.org/10.3133/sir20245019.","productDescription":"x, 62 p.","numberOfPages":"62","onlineOnly":"Y","ipdsId":"IP-110004","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":499448,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_116979.htm","linkFileType":{"id":5,"text":"html"}},{"id":428611,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2024/5019/sir20245019.XML"},{"id":428610,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2024/5019/images"},{"id":428608,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20245019/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2024-5019"},{"id":428607,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2024/5019/sir20245019.pdf","text":"Report","size":"14.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2024-5019"},{"id":428606,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2024/5019/sir20245019.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 -117.51859835894652,\n 35.183647408915874\n ],\n [\n -117.51859835894652,\n 34.28986048082601\n ],\n [\n -116.15629367144663,\n 34.28986048082601\n ],\n [\n -116.15629367144663,\n 35.183647408915874\n ],\n [\n -117.51859835894652,\n 35.183647408915874\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director,
California Water Science Center
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, California 95819
In a laboratory experiment, we quantified microhabitat use of small yellow-phase American eels (Anguilla rostrata, n = 130, 224–338 mm TL) conditional on five benthic substrate types common to rivers within their geographic range. During nine, 4-day trials replicated with three aquaria, American eels were given a choice to burrow into five equally available benthic substrates: cobble (90–256 mm), gravel (4–16 mm), sand (0.125–1 mm), silt/clay (< 0.0625 mm), and leaf pack. Five American eels were used per aquarium for each trial, and individuals were used one time only. All eels were injected with PIT tags prior to the study, which allowed for determination of lengths and otolith-based ages of each individual following each trial. Leaf pack was selected with a significantly higher probability than other substrates (63 of 130 individuals). However, other substrates were also used (cobble, 21 of 130; silt/clay, 18 of 130; gravel, 16 of 130; and sand, 12 of 130). Length and age covariates were not associated with substrate selection. Selection of leaf pack habitat supports the importance of forested riparian zones and terrestrial organic material to yellow-phase American eels in riverine systems.
","language":"English","publisher":"Springer Link","doi":"10.1007/s10641-024-01544-z","usgsCitation":"Braham, M., Welsh, S., and Smith, D., 2024, An experimental study of benthic habitat selection in yellow-phase American eels (Anguilla rostrata): Environmental Biology of Fishes, v. 107, p. 513-522, https://doi.org/10.1007/s10641-024-01544-z.","productDescription":"10 p.","startPage":"513","endPage":"522","ipdsId":"IP-127663","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":433566,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"West Virginia","otherGeospatial":"Millville hydroelectric dam, Shenandoah River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -78.25894317307947,\n 39.22638050030608\n ],\n [\n -78.25894317307947,\n 38.94086151879799\n ],\n [\n -77.75103536336908,\n 38.94086151879799\n ],\n [\n -77.75103536336908,\n 39.22638050030608\n ],\n [\n -78.25894317307947,\n 39.22638050030608\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"107","noUsgsAuthors":false,"publicationDate":"2024-05-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Braham, Melissa","contributorId":343003,"corporation":false,"usgs":false,"family":"Braham","given":"Melissa","affiliations":[{"id":12432,"text":"West Virginia University","active":true,"usgs":false}],"preferred":false,"id":910571,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Welsh, S.A. 0000-0003-0362-054X","orcid":"https://orcid.org/0000-0003-0362-054X","contributorId":10191,"corporation":false,"usgs":true,"family":"Welsh","given":"S.A.","affiliations":[],"preferred":false,"id":910570,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Smith, Dustin M.","contributorId":272979,"corporation":false,"usgs":false,"family":"Smith","given":"Dustin M.","affiliations":[{"id":56173,"text":"West Virginia DNR","active":true,"usgs":false}],"preferred":false,"id":912567,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70258121,"text":"70258121 - 2024 - Site response in the Walnut Creek–Concord region of the San Francisco Bay, California: Ground motion amplification in a fault-bounded basin","interactions":[],"lastModifiedDate":"2024-10-07T16:22:14.75653","indexId":"70258121","displayToPublicDate":"2024-05-14T08:50:01","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"Site response in the Walnut Creek–Concord region of the San Francisco Bay, California: Ground motion amplification in a fault-bounded basin","docAbstract":"Thirty‐seven portable accelerometers were deployed in the eastern San Francisco Bay communities of Walnut Creek and Concord to study site response in a fault‐bounded, urban, sedimentary basin. Local earthquakes were recorded for a period of two years from 2017 to 2019 resulting in 101 well‐recorded events. Site response is estimated by two methods: the reference site spectral ratio method and a source‐site spectral inversion method. The reference site spectral ratio method allows investigation of the variability of site amplification with source azimuth and frequency. The source‐site spectral inversion method yields the best least‐squares fit to site response for a database of ground‐motion records. Both methods show substantial amplification in the Walnut Creek–Concord basin below 2 Hz indicating strong surface‐wave development. Greater amplification is seen for sources aligned along the long axis of the basin. Inversion using close‐in sources at short distances yields lower amplification at longer periods than the entire data set due to reduced surface‐wave generation for steeper angles of incidence. Inversion of site response spectra for shallow shear‐wave velocity using a global search algorithm yields VS30 values consistent with generalized mapping results based on geology and topography but with greater variability due to local site variations. 3D finite‐element modeling shows greater amplification in the Walnut Creek–Concord basin with a basin‐edge effect likely contributing to higher ground motions. Topography is also seen to lead to increased scattering and shadowing effects.
","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120230309","usgsCitation":"Hartzell, S.H., Leeds, A.L., Ramirez-Guzman, L., Langenheim, V., and Schmitt, R.G., 2024, Site response in the Walnut Creek–Concord region of the San Francisco Bay, California: Ground motion amplification in a fault-bounded basin: Bulletin of the Seismological Society of America, v. 114, no. 5, p. 2668-2686, https://doi.org/10.1785/0120230309.","productDescription":"18 p.","startPage":"2668","endPage":"2686","ipdsId":"IP-156595","costCenters":[{"id":78686,"text":"Geologic Hazards Science Center - Seismology / Geomagnetism","active":true,"usgs":true}],"links":[{"id":433493,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Walnut Creek–Concord region of San Francisco Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.15,\n 38.1\n ],\n [\n -122.15,\n 37.85\n ],\n [\n -121.85,\n 37.85\n ],\n [\n -121.85,\n 38.1\n ],\n [\n -122.15,\n 38.1\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"114","issue":"5","noUsgsAuthors":false,"publicationDate":"2024-05-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Hartzell, Stephen H. 0000-0003-0858-9043 shartzell@usgs.gov","orcid":"https://orcid.org/0000-0003-0858-9043","contributorId":2594,"corporation":false,"usgs":true,"family":"Hartzell","given":"Stephen","email":"shartzell@usgs.gov","middleInitial":"H.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":912261,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Leeds, Alena L. 0000-0002-8756-3687 aleeds@usgs.gov","orcid":"https://orcid.org/0000-0002-8756-3687","contributorId":4077,"corporation":false,"usgs":true,"family":"Leeds","given":"Alena","email":"aleeds@usgs.gov","middleInitial":"L.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":912262,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ramirez-Guzman, Leonardo","contributorId":175444,"corporation":false,"usgs":false,"family":"Ramirez-Guzman","given":"Leonardo","email":"","affiliations":[],"preferred":false,"id":912263,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Langenheim, Victoria 0000-0003-2170-5213","orcid":"https://orcid.org/0000-0003-2170-5213","contributorId":206990,"corporation":false,"usgs":true,"family":"Langenheim","given":"Victoria","affiliations":[],"preferred":true,"id":912264,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Schmitt, Robert G. 0000-0001-8060-1954 rschmitt@usgs.gov","orcid":"https://orcid.org/0000-0001-8060-1954","contributorId":5611,"corporation":false,"usgs":true,"family":"Schmitt","given":"Robert","email":"rschmitt@usgs.gov","middleInitial":"G.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":912265,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70254331,"text":"70254331 - 2024 - Translocation in a fragmented river provides demographic benefits for imperiled fishes","interactions":[],"lastModifiedDate":"2024-05-17T13:52:52.822292","indexId":"70254331","displayToPublicDate":"2024-05-14T08:47:45","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Translocation in a fragmented river provides demographic benefits for imperiled fishes","docAbstract":"Fragmentation isolates individuals and restricts access to valuable habitat with severe consequences for populations, such as reduced gene flow, disruption of recolonization dynamics, reduced resiliency to disturbance, and changes in aquatic community structure. Translocations to mitigate the effects of fragmentation and habitat loss are common, but few are rigorously evaluated, particularly for fishes. Over six years, we translocated 1215 individuals of four species of imperiled fish isolated below a barrier on the San Juan River, Utah, USA, that restricts access to upstream habitat. We used re-encounter data (both passive integrated transponder tag and telemetry detections and physical recaptures) collected between 2016 and 2023, to inform a spatially explicit multistate mark–recapture model that estimated survival and transition probabilities of translocated and non-translocated individuals, both below and above the barrier. Individuals of all four species moved large (>200 km) distances upstream following translocation, with the maximum upstream encounter distance varying by species. Results from the multistate mark–recapture model suggested translocated fish survived at a higher rate compared with non-translocated fish below the barrier for three of the four species. Above the barrier, translocated individuals survived at similar rates as non-translocated fish for bluehead sucker (Catostomus discobolus) and flannelmouth sucker (Catostomus latipinnis), while survival rates of translocated endangered Colorado pikeminnow (Ptychocheilus lucius; mean, 95% CI: 0.75, 0.55–0.88) and endangered razorback sucker (Xyrauchen texanus; 0.86, 0.75–0.92) were higher relative to non-translocated individuals (Colorado pikeminnow: 0.52, 0.51–0.54; razorback sucker: 0.75, 0.74–0.75). Transition probabilities from above the barrier to below the barrier were generally low for three of the four species (all upper 95% CI ≤ 0.23), but they were substantially higher for razorback sucker. Our results suggest translocation to mitigate fragmentation and habitat loss can have demographic benefits for large-river fish species by allowing movements necessary to complete their life history in heterogeneous riverscapes. Further, given the costs or delays in providing engineered fish passage structures or in achieving dam removal, we suggest translocations may provide an alternative conservation strategy in fragmented river systems.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.4874","usgsCitation":"Pennock, C., Healy, B.D., Bogaard, M.R., McKinstry, M.C., Gido, K.B., Cathcart, C.N., and Hines, B., 2024, Translocation in a fragmented river provides demographic benefits for imperiled fishes: Ecosphere, v. 15, no. 5, e4874, 18 p., https://doi.org/10.1002/ecs2.4874.","productDescription":"e4874, 18 p.","ipdsId":"IP-157286","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":439600,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.4874","text":"Publisher Index Page"},{"id":428797,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado, New Mexico, Utah","otherGeospatial":"San Juan River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -107.19795244457669,\n 37.464337921724805\n ],\n [\n -110.39339902199882,\n 37.464337921724805\n ],\n [\n -110.39339902199882,\n 36.58940165978096\n ],\n [\n -107.19795244457669,\n 36.58940165978096\n ],\n [\n -107.19795244457669,\n 37.464337921724805\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"15","issue":"5","noUsgsAuthors":false,"publicationDate":"2024-05-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Pennock, Casey A.","contributorId":287044,"corporation":false,"usgs":false,"family":"Pennock","given":"Casey A.","affiliations":[{"id":28050,"text":"USU","active":true,"usgs":false}],"preferred":false,"id":900989,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Healy, Brian D. 0000-0002-4402-638X","orcid":"https://orcid.org/0000-0002-4402-638X","contributorId":304257,"corporation":false,"usgs":true,"family":"Healy","given":"Brian","middleInitial":"D.","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":900990,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bogaard, Matthew R.","contributorId":317815,"corporation":false,"usgs":false,"family":"Bogaard","given":"Matthew","email":"","middleInitial":"R.","affiliations":[{"id":12438,"text":"Washington Department of Fish and Wildlife","active":true,"usgs":false}],"preferred":false,"id":900991,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McKinstry, Mark C.","contributorId":301155,"corporation":false,"usgs":false,"family":"McKinstry","given":"Mark","email":"","middleInitial":"C.","affiliations":[{"id":65322,"text":"Upper Colorado Regional Office","active":true,"usgs":false}],"preferred":false,"id":900992,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gido, Keith B.","contributorId":198487,"corporation":false,"usgs":false,"family":"Gido","given":"Keith","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":900993,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Cathcart, C. Nathan","contributorId":214105,"corporation":false,"usgs":false,"family":"Cathcart","given":"C.","email":"","middleInitial":"Nathan","affiliations":[{"id":7058,"text":"Alaska Department of Fish and Game","active":true,"usgs":false}],"preferred":false,"id":900994,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hines, Brian","contributorId":336773,"corporation":false,"usgs":false,"family":"Hines","given":"Brian","email":"","affiliations":[{"id":80857,"text":"U.S. Bureau of Reclamation, Upper Colorado Regional Office, Salt Lake City, Utah, USA","active":true,"usgs":false}],"preferred":false,"id":900995,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70261914,"text":"70261914 - 2024 - Estimating price elasticity of demand for mineral commodities used in lithium-ion batteries in the face of surging demand","interactions":[],"lastModifiedDate":"2025-01-03T14:47:53.520255","indexId":"70261914","displayToPublicDate":"2024-05-14T08:31:18","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3267,"text":"Resources, Conservation and Recycling","active":true,"publicationSubtype":{"id":10}},"title":"Estimating price elasticity of demand for mineral commodities used in lithium-ion batteries in the face of surging demand","docAbstract":"The accelerating adoption of clean energy technologies is driving demand for certain mineral commodities like lithium, essential for electric vehicle batteries. Understanding the influence of the energy transition on each market requires examining their supply and demand price elasticities. However, there have only been a limited number of studies that have estimated mineral demand price elasticities in emerging technologies. We empirically estimate the price elasticity demand (PEDs) for mineral commodities used in lithium-ion battery cathodes and anodes—cobalt, graphite, lithium, manganese, and nickel. We also test whether the price elasticities of these mineral commodities have changed due to any structural changes in recent years, given the recent expansion in the sales of electric vehicles. Using Two Stage Least Squared (2SLS) econometric techniques, we find that demand has become less elastic for lithium (-0.11), cobalt (-0.45), nickel (-0.09), and manganese (-0.04) after structural breaks in 2020, 2013, 2009, and 2014, respectively. In contrast, demand for natural amorphous graphite (-0.36), and natural flake graphite (-0.58) remains relatively stable over the time period assessed.","language":"English","publisher":"Elsevier","doi":"10.1016/j.resconrec.2024.107664","usgsCitation":"Shojaeddini, E., Alonso, E., and Nassar, N.T., 2024, Estimating price elasticity of demand for mineral commodities used in lithium-ion batteries in the face of surging demand: Resources, Conservation and Recycling, v. 207, 107664, 9 p., https://doi.org/10.1016/j.resconrec.2024.107664.","productDescription":"107664, 9 p.","ipdsId":"IP-154682","costCenters":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"links":[{"id":467008,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.resconrec.2024.107664","text":"Publisher Index Page"},{"id":465625,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"207","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Shojaeddini, Ensieh 0000-0001-9584-6399","orcid":"https://orcid.org/0000-0001-9584-6399","contributorId":345023,"corporation":false,"usgs":false,"family":"Shojaeddini","given":"Ensieh","affiliations":[{"id":82464,"text":"Akima System Engineering","active":true,"usgs":false}],"preferred":false,"id":922263,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Alonso, Elisa 0000-0002-0090-8284","orcid":"https://orcid.org/0000-0002-0090-8284","contributorId":223015,"corporation":false,"usgs":true,"family":"Alonso","given":"Elisa","email":"","affiliations":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"preferred":true,"id":922264,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nassar, Nedal T. 0000-0001-8758-9732 nnassar@usgs.gov","orcid":"https://orcid.org/0000-0001-8758-9732","contributorId":197864,"corporation":false,"usgs":true,"family":"Nassar","given":"Nedal","email":"nnassar@usgs.gov","middleInitial":"T.","affiliations":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"preferred":true,"id":922265,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70258633,"text":"70258633 - 2024 - Infectivity of wild-bird origin Influenza A viruses in Minnesota wetlands across seasons","interactions":[],"lastModifiedDate":"2024-09-19T12:09:47.45247","indexId":"70258633","displayToPublicDate":"2024-05-14T07:07:08","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":9113,"text":"Pathogens","active":true,"publicationSubtype":{"id":10}},"title":"Infectivity of wild-bird origin Influenza A viruses in Minnesota wetlands across seasons","docAbstract":"Image-based algorithms have become a powerful tool for estimating flow velocities in rivers. In this study, we generalize the space-time image velocimetry (STIV) framework for reach-scale application rather than along a cross section. The new algorithm provides information on both the magnitude and orientation of velocity vectors, and we refer to the algorithm as two-dimensional STIV, or 2D-STIV. The workflow involves setting up a grid, using centreline tangent vectors as initial estimates of flow direction, and then extracting space-time images (STIs) along search lines radiating from each grid node. The autocorrelation function is used to infer the inclination of streak lines present in STIs, which represents the advection of water surface features. Information on flow direction is obtained by evaluating various candidate search lines and identifying that which yields the highest velocity. This search can be performed exhaustively or via optimization. We applied the new 2D-STIV algorithm to three test cases, one simulated data set and two natural channels, and compared image-derived velocities to modelled or measured values. We also applied two established particle image velocimetry (PIV) algorithms to the same data sets. 2D-STIV performed as well as the two PIV algorithms for simulated images. For a natural river with distinct water surface features, 2D-STIV was effective for much of the channel but also led to a more patchy, irregular velocity field than the two PIV algorithms. For a site lacking obvious surface features, exhaustive 2D-STIV led to velocity estimates uncorrelated with field data while the optimization-based version produced erratic flow directions. 2D-STIV also required greater image sequence durations, higher frame rates, and generally longer computational run times. Overall, ensemble PIV was the most reliable algorithm.
Freshwater mussels (Bivalvia: Unionida) are an ecologically important faunal group. Excessive sediments, both in suspended and deposited formats, are believed to have negative effects on survival of freshwater mussels. However, there is a lack of quantitative tools for assessing the impact of abrupt and excessive sedimentation on freshwater mussel habitats. This gap in knowledge poses challenges for construction planning that necessitates evaluating sedimentation effects on mussels. In this paper, we present a simple Lagrangian particle tracking (LPT) model designed to investigate the downstream distances from the sediment release point where mussels may face risks of sediment exposure and burial during episodic sedimentation events. We validated the model in predicting the deposition of sands ranging from 125 to
Shallow, tropical coral reefs face compounding threats from climate change, habitat degradation due to coastal development and pollution, impacts from storms and sea-level rise, and pulse disturbances like blast fishing, mining, dredging, and ship groundings that reduce reef height and complexity. One approach toward restoring coral reef physical structure from such impacts is deploying built structures of artificial, natural, or hybrid (both artificial and natural) origin. Built structures range from designed modules and repurposed materials to underwater sculptures and intentionally placed natural rocks. Restoration practitioners and coastal managers increasingly consider incorporating – and in many cases have already begun to incorporate – built structures into coral reef-related applications, yet synthesized evidence on the ecological (coral-related; e.g., coral growth, coral survival) and physical performance of built structures in coral ecosystems across a variety of contexts (e.g., restoration, coastal protection, mitigation, tourism) is not readily available to guide decisions. To help fill this gap and inform management decisions, we systematically mapped the global distribution and abundance of published evidence on the ecological (coral-related) and physical performance of built structure interventions in shallow (≤ 30 m), tropical (35°N to 35°S) coral ecosystems.
","language":"English","publisher":"Springer Nature","doi":"10.1186/s13750-024-00336-3","usgsCitation":"Paxton, A., Foxfoot, I.R., Cutshaw, C., Steward, D., Poussard, L., Riley, T., Swannack, T.M., Piercy, C., Altman, S., Puckett, B., Storlazzi, C.D., and Viehman, S., 2024, Evidence on the ecological and physical effects of built structures in shallow, tropical coral reefs: A systematic map: Environmental Evidence, v. 13, 12, 26 p., https://doi.org/10.1186/s13750-024-00336-3.","productDescription":"12, 26 p.","ipdsId":"IP-161299","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":439609,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1186/s13750-024-00336-3","text":"Publisher Index Page"},{"id":428970,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"13","noUsgsAuthors":false,"publicationDate":"2024-05-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Paxton, Avery 0000-0002-4871-9167","orcid":"https://orcid.org/0000-0002-4871-9167","contributorId":331325,"corporation":false,"usgs":false,"family":"Paxton","given":"Avery","email":"","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":901087,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Foxfoot, Iris R.","contributorId":336806,"corporation":false,"usgs":false,"family":"Foxfoot","given":"Iris","middleInitial":"R.","affiliations":[{"id":12537,"text":"USACE","active":true,"usgs":false}],"preferred":false,"id":901088,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cutshaw, Christina","contributorId":336808,"corporation":false,"usgs":false,"family":"Cutshaw","given":"Christina","email":"","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":901089,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Steward, D’amy","contributorId":336809,"corporation":false,"usgs":false,"family":"Steward","given":"D’amy","email":"","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":901090,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Poussard, Leanne","contributorId":331346,"corporation":false,"usgs":false,"family":"Poussard","given":"Leanne","email":"","affiliations":[],"preferred":false,"id":901091,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Riley, Trevor","contributorId":336811,"corporation":false,"usgs":false,"family":"Riley","given":"Trevor","email":"","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":901092,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Swannack, Todd M.","contributorId":336813,"corporation":false,"usgs":false,"family":"Swannack","given":"Todd","middleInitial":"M.","affiliations":[{"id":12537,"text":"USACE","active":true,"usgs":false}],"preferred":false,"id":901093,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Piercy, Candice","contributorId":331327,"corporation":false,"usgs":false,"family":"Piercy","given":"Candice","email":"","affiliations":[{"id":12537,"text":"USACE","active":true,"usgs":false}],"preferred":false,"id":901094,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Altman, Safra","contributorId":331328,"corporation":false,"usgs":false,"family":"Altman","given":"Safra","email":"","affiliations":[{"id":12537,"text":"USACE","active":true,"usgs":false}],"preferred":false,"id":901095,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Puckett, Brandon 0000-0001-9615-6242","orcid":"https://orcid.org/0000-0001-9615-6242","contributorId":331329,"corporation":false,"usgs":false,"family":"Puckett","given":"Brandon","email":"","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":901096,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Storlazzi, Curt D. 0000-0001-8057-4490","orcid":"https://orcid.org/0000-0001-8057-4490","contributorId":213610,"corporation":false,"usgs":true,"family":"Storlazzi","given":"Curt","middleInitial":"D.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":901097,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Viehman, Shay","contributorId":336815,"corporation":false,"usgs":false,"family":"Viehman","given":"Shay","email":"","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":901098,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70254203,"text":"ofr20241023 - 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These agencies are large consumers of remotely sensed data and bring extensive experience in the assessment and use of these data. The six agencies are as follows: National Aeronautics and Space Administration, National Geospatial-Intelligence Agency, National Oceanic and Atmospheric Administration, U.S. Department of Agriculture, U.S. Geological Survey, and National Reconnaissance Office.
JACIE was formed in 2001 to assess the quality of data from the nascent commercial high-resolution satellite industry. Since then, JACIE has expanded its purview to include data at various resolutions, including commercial and civil.
The processes and techniques used by the JACIE agencies to assess data quality have been compiled within this report to share them across the agencies and with others who want to assess remotely sensed imagery data or understand how data are assessed and reported by JACIE.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20241023","usgsCitation":"Cantrell, S.J., and Christopherson, J.B., 2024, Joint Agency Commercial Imagery Evaluation (JACIE) best practices for remote sensing system evaluation and reporting: U.S. Geological Survey Open-File Report 2024–1023, 26 p., https://doi.org/10.3133/ofr20241023.","productDescription":"vi, 26 p.","numberOfPages":"36","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-153510","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":428638,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20241023/full"},{"id":428637,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2024/1023/images/"},{"id":428636,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2024/1023/ofr20241023.XML"},{"id":428635,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2024/1023/ofr20241023.pdf","text":"Report","size":"2.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2024–1023"},{"id":428634,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2024/1023/coverthb.jpg"}],"contact":"Director, Earth Resources Observation and Science Center
U.S. Geological Survey
47914 252nd Street
Sioux Falls, SD 57198
Waterfowl population recruitment is sensitive to duckling survival. We quantified predator types and survival rates for Anas platyrhynchos (Mallard) and Mareca strepera (Gadwall) ducklings in one of the largest brackish water marshes in western North America (Suisun Marsh, California) using 556 radio-tagged ducklings from 284 broods tracked during the 2016 to 2019 breeding seasons. Overall, 78% of ducklings died and 84% of mortalities occurred < 7 days after hatch. After hatching in upland fields, survival was greater for broods that hatched closer to flooded wetlands; broods had a ≥ 75% chance of surviving the move from the nest to water when nests were located ≤ 140 m from the nearest wetland and ≤ 50% chance of surviving when nests were located ≥ 970 m from the nearest wetland. Predation accounted for 91% of mortalities and was attributed to mammals (27.6%), birds (22.0%), snakes (4.4%), and unknown predators (46.0%). Anas platyrhynchos survival to fledging (54 days) was only 3.2% and 0.9% during 2 drier years and 11.7% and 16.7% during 2 wetter years. Mareca strepera survival to fledging was 9.4% to 11.2% among years. Daily survival rates for ducklings generally increased with the amount of flooded wetlands within 0.5 km (A. platyrhynchos) and 1.0 km (M. strepera) of the nest at hatch. Additionally, survival rates increased with duckling age and body mass at hatch for both species and decreased with hatch date for A. platyrhynchos but not M. strepera, which may be partially due to the earlier onset of A. platyrhynchos nesting. For ducklings that survived the initial move to water, survival rates were negatively correlated with salinity and this effect was more pronounced for younger ducklings. Anas platyrhynchos survival to 7 days post hatch decreased by 9.1% (wetter year) to 31.4% (drier year) when ducklings were in 12 ppt water (99th quantile of cumulative salinity concentrations experienced by ducklings) versus 0.5 ppt water. Mareca strepera survival to 7 days decreased by 7.4% when ducklings were in 12 ppt vs. 0.5 ppt water. Our results suggest that maintaining a network of low salinity wetlands within 1 km of upland nesting sites would likely improve duckling survival rates, especially during the critical 7-day period after hatch.
","language":"English","publisher":"Oxford Academic","doi":"10.1093/ornithapp/duae017","collaboration":"CDFW, DWR, BOR","usgsCitation":"Peterson, S.H., Ackerman, J.T., Hartman, C.A., Greenawalt, A.C., Casazza, M.L., and Herzog, M.P., 2024, Duckling survival increased with availability of flooded wetland habitat and decreased with salinity concentrations in a brackish marsh: Ornithological Applications, v. 126, no. 3, duae017, 18 p., https://doi.org/10.1093/ornithapp/duae017.","productDescription":"duae017, 18 p.","ipdsId":"IP-161682","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":498275,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/ornithapp/duae017","text":"Publisher Index Page"},{"id":498159,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Suisan Marsh","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.02904038945182,\n 38.15034309532726\n ],\n [\n -122.02904038945182,\n 38.04476134451929\n ],\n [\n -121.83322632092529,\n 38.04476134451929\n ],\n [\n -121.83322632092529,\n 38.15034309532726\n ],\n [\n -122.02904038945182,\n 38.15034309532726\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"126","issue":"3","noUsgsAuthors":false,"publicationDate":"2024-05-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Peterson, Sarah H. 0000-0003-2773-3901 sepeterson@usgs.gov","orcid":"https://orcid.org/0000-0003-2773-3901","contributorId":167181,"corporation":false,"usgs":true,"family":"Peterson","given":"Sarah","email":"sepeterson@usgs.gov","middleInitial":"H.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":952997,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ackerman, Joshua T. 0000-0002-3074-8322","orcid":"https://orcid.org/0000-0002-3074-8322","contributorId":202848,"corporation":false,"usgs":true,"family":"Ackerman","given":"Joshua","middleInitial":"T.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":952998,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hartman, C. Alex 0000-0002-7222-1633 chartman@usgs.gov","orcid":"https://orcid.org/0000-0002-7222-1633","contributorId":131157,"corporation":false,"usgs":true,"family":"Hartman","given":"C.","email":"chartman@usgs.gov","middleInitial":"Alex","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":952999,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Greenawalt, Andrew C. 0000-0003-4443-9528","orcid":"https://orcid.org/0000-0003-4443-9528","contributorId":364649,"corporation":false,"usgs":false,"family":"Greenawalt","given":"Andrew","middleInitial":"C.","affiliations":[{"id":63051,"text":"previously WERC","active":true,"usgs":false}],"preferred":false,"id":953000,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Casazza, Michael L. 0000-0002-5636-735X mike_casazza@usgs.gov","orcid":"https://orcid.org/0000-0002-5636-735X","contributorId":2091,"corporation":false,"usgs":true,"family":"Casazza","given":"Michael","email":"mike_casazza@usgs.gov","middleInitial":"L.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":953001,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Herzog, Mark P. 0000-0002-5203-2835 mherzog@usgs.gov","orcid":"https://orcid.org/0000-0002-5203-2835","contributorId":131158,"corporation":false,"usgs":true,"family":"Herzog","given":"Mark","email":"mherzog@usgs.gov","middleInitial":"P.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":953002,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ]}