{"pageNumber":"388","pageRowStart":"9675","pageSize":"25","recordCount":184776,"records":[{"id":70231303,"text":"70231303 - 2022 - Toxicity of wildland fire-fighting chemicals in pulsed exposures to rainbow trout and fathead minnows","interactions":[],"lastModifiedDate":"2022-07-07T16:56:12.985464","indexId":"70231303","displayToPublicDate":"2022-05-06T08:43:40","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1571,"text":"Environmental Toxicology and Chemistry","active":true,"publicationSubtype":{"id":10}},"title":"Toxicity of wildland fire-fighting chemicals in pulsed exposures to rainbow trout and fathead minnows","docAbstract":"<p>Intrusions of fire-fighting chemicals in streams can result from containment and suppression of wildfires and may be harmful to native biota. We investigated the toxicity of seven current-use fire-fighting chemicals to juvenile rainbow trout (<i>Oncorhynchus mykiss</i>) and fathead minnows (<i>Pimephales promelas</i>) by simulating chemical intrusions under variable field conditions to provide insight on the potential damage these chemicals may cause in waterways. We manipulated water flow rate, water hardness, and concentration of the chemicals in three separate attenuated exposure assays where chemical concentrations decreased throughout the 96-hour exposure period. Concentration of retardant, temperature, duration of chemical exposure, and the number of exposures were manipulated in four pulsed assays where up to one-hour exposures were followed by an observation period in control water to determine delayed toxicity or recovery. Mortality of rainbow trout was higher across treatments at a warmer temperature and also increased with increasing concentration rate, increasing exposure duration, and with sequential exposures across assays. For fathead minnows, mortality increased with increasing concentration of fire retardant and longer exposure durations. Chemical exposure can exert additional stress during wildfire events that may impact stream fishes. Since the ratio of toxic unionized ammonia to ionized ammonia is greater with increasing temperature and pH, future studies could investigate the effects of water temperature and pH on native fishes under environmentally relevant concentrations of fire-fighting chemicals.</p>","language":"English","publisher":"John Wiley & Sons","doi":"10.1002/etc.5347","usgsCitation":"Puglis, H.J., Iacchetta, M.G., and Mackey, C.M., 2022, Toxicity of wildland fire-fighting chemicals in pulsed exposures to rainbow trout and fathead minnows: Environmental Toxicology and Chemistry, v. 41, no. 7, p. 1711-1720, https://doi.org/10.1002/etc.5347.","productDescription":"10 p.","startPage":"1711","endPage":"1720","ipdsId":"IP-132944","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":447890,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/etc.5347","text":"Publisher Index Page"},{"id":435855,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9TY8ZRG","text":"USGS data release","linkHelpText":"Biological and chemical data from attenuated and pulsed exposures of fire chemical to fish"},{"id":400277,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"41","issue":"7","noUsgsAuthors":false,"publicationDate":"2022-04-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Puglis, Holly J. 0000-0002-3090-6597 hpuglis@usgs.gov","orcid":"https://orcid.org/0000-0002-3090-6597","contributorId":4686,"corporation":false,"usgs":true,"family":"Puglis","given":"Holly","email":"hpuglis@usgs.gov","middleInitial":"J.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":842275,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Iacchetta, Michael G. 0000-0001-9459-1435","orcid":"https://orcid.org/0000-0001-9459-1435","contributorId":291394,"corporation":false,"usgs":true,"family":"Iacchetta","given":"Michael","email":"","middleInitial":"G.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":842276,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mackey, Christina M. 0000-0003-1737-2698","orcid":"https://orcid.org/0000-0003-1737-2698","contributorId":243574,"corporation":false,"usgs":true,"family":"Mackey","given":"Christina","email":"","middleInitial":"M.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":842277,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70231347,"text":"70231347 - 2022 - Microtremor array method using spatial autocorrelation  analysis of Rayleigh‑wave data","interactions":[],"lastModifiedDate":"2022-05-06T13:42:57.669261","indexId":"70231347","displayToPublicDate":"2022-05-06T08:33:57","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2453,"text":"Journal of Seismology","active":true,"publicationSubtype":{"id":10}},"title":"Microtremor array method using spatial autocorrelation  analysis of Rayleigh‑wave data","docAbstract":"Microtremor array measurements (MAM) and passive surface wave methods in general, have been increasingly used to non-invasively estimate shear-wave velocity structures (Vs) for various purposes. The methods estimate dispersion curves and invert them for retrieving S-wave velocity profiles. This paper summarizes principles, limitations, data collection and processing methods. It intends to enable students and practitioners to understand the principles needed to plan a microtremor array investigation, record and process the data, and evaluate the quality of investigation result. The paper focuses on the spatial autocorrelation (SPAC) processing method among microtremor array processing methods because of its relatively simple calculation and stable applicability.","language":"English","publisher":"Springer","doi":"10.1007/s10950-021-10051-y","usgsCitation":"Hayashi, K., Asten, M.W., Stephenson, W.J., Cornou, C., Hobiger, M., Pilz, M., and Yamanaka, H., 2022, Microtremor array method using spatial autocorrelation  analysis of Rayleigh‑wave data: Journal of Seismology, 27 p., https://doi.org/10.1007/s10950-021-10051-y.","productDescription":"27 p.","ipdsId":"IP-131758","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":447892,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10950-021-10051-y","text":"Publisher Index Page"},{"id":400275,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationDate":"2022-04-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Hayashi, Koichi","contributorId":291435,"corporation":false,"usgs":false,"family":"Hayashi","given":"Koichi","affiliations":[{"id":62705,"text":"Geometrics/OYO Corporation, San Jose, CA","active":true,"usgs":false}],"preferred":false,"id":842349,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Asten, Michael W.","contributorId":184065,"corporation":false,"usgs":false,"family":"Asten","given":"Michael","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":842350,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stephenson, William J. 0000-0001-8699-0786 wstephens@usgs.gov","orcid":"https://orcid.org/0000-0001-8699-0786","contributorId":695,"corporation":false,"usgs":true,"family":"Stephenson","given":"William","email":"wstephens@usgs.gov","middleInitial":"J.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":842351,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cornou, Cecile","contributorId":175495,"corporation":false,"usgs":false,"family":"Cornou","given":"Cecile","email":"","affiliations":[{"id":27334,"text":"Universite Grenoble Alpes","active":true,"usgs":false}],"preferred":false,"id":842352,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hobiger, Manuel","contributorId":291436,"corporation":false,"usgs":false,"family":"Hobiger","given":"Manuel","email":"","affiliations":[{"id":62706,"text":"Swiss Seismological Service (SED), ETH Zurich, Zurich, Switzerland / Federal Institute for Geosciences and Natural Resources (BGR), Hanover, Germany","active":true,"usgs":false}],"preferred":false,"id":842353,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Pilz, Marco","contributorId":264169,"corporation":false,"usgs":false,"family":"Pilz","given":"Marco","email":"","affiliations":[],"preferred":false,"id":842354,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Yamanaka, Hiroaki","contributorId":291437,"corporation":false,"usgs":false,"family":"Yamanaka","given":"Hiroaki","email":"","affiliations":[{"id":62709,"text":"Tokyo Institute of Technology, Yokohama, Kanagawa, Japan","active":true,"usgs":false}],"preferred":false,"id":842355,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70231342,"text":"70231342 - 2022 - Statewide quantitative microbial risk assessment for waterborne viruses, bacteria, and protozoa in public water supply wells in Minnesota","interactions":[],"lastModifiedDate":"2022-06-01T15:29:50.641732","indexId":"70231342","displayToPublicDate":"2022-05-06T08:22:50","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1565,"text":"Environmental Science & Technology","onlineIssn":"1520-5851","printIssn":"0013-936X","active":true,"publicationSubtype":{"id":10}},"title":"Statewide quantitative microbial risk assessment for waterborne viruses, bacteria, and protozoa in public water supply wells in Minnesota","docAbstract":"<p class=\"articleBody_abstractText\">Infection risk from waterborne pathogens can be estimated via quantitative microbial risk assessment (QMRA) and forms an important consideration in the management of public groundwater systems. However, few groundwater QMRAs use site-specific hazard identification and exposure assessment, so prevailing risks in these systems remain poorly defined. We estimated the infection risk for 9 waterborne pathogens based on a 2-year pathogen occurrence study in which 964 water samples were collected from 145 public wells throughout Minnesota, USA. Annual risk across all nine pathogens combined was 3.3 × 10<sup>–1</sup><span>&nbsp;</span>(95% CI: 2.3 × 10<sup>–1</sup><span>&nbsp;</span>to 4.2 × 10<sup>–1</sup>), 3.9 × 10<sup>–2</sup><span>&nbsp;</span>(2.3 × 10<sup>–2</sup><span>&nbsp;</span>to 5.4 × 10<sup>–2</sup>), and 1.2 × 10<sup>–1</sup><span>&nbsp;</span>(2.6 × 10<sup>–2</sup><span>&nbsp;</span>to 2.7 × 10<sup>–1</sup>) infections person<sup>–1</sup><span>&nbsp;</span>year<sup>–1</sup><span>&nbsp;</span>for noncommunity, nondisinfecting community, and disinfecting community wells, respectively. Risk estimates exceeded the U.S. benchmark of 10<sup>–4</sup><span>&nbsp;</span>infections person<sup>–1</sup><span>&nbsp;</span>year<sup>–1</sup><span>&nbsp;</span>in 59% of well-years, indicating that the risk was widespread. While the annual risk for all pathogens combined was relatively high, the average daily doses for individual pathogens were low, indicating that significant risk results from sporadic pathogen exposure.<span>&nbsp;</span><i>Cryptosporidium</i><span>&nbsp;</span>dominated annual risk, so improved identification of wells susceptible to<span>&nbsp;</span><i>Cryptosporidium</i><span>&nbsp;</span>contamination may be important for risk mitigation.</p>","language":"English","publisher":"ACS Publications","doi":"10.1021/acs.est.1c06472","usgsCitation":"Burch, T., Stokdyk, J.P., Rice, N., Anderson, A., Walsh, J.F., Spencer, S., Firnstahl, A.D., and Borchardt, M.A., 2022, Statewide quantitative microbial risk assessment for waterborne viruses, bacteria, and protozoa in public water supply wells in Minnesota: Environmental Science & Technology, v. 56, no. 10, p. 6315-6324, https://doi.org/10.1021/acs.est.1c06472.","productDescription":"10 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 \"}}]}","volume":"56","issue":"10","noUsgsAuthors":false,"publicationDate":"2022-05-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Burch, Tucker R.","contributorId":195801,"corporation":false,"usgs":false,"family":"Burch","given":"Tucker R.","affiliations":[],"preferred":false,"id":842329,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stokdyk, Joel P. 0000-0003-2887-6277 jstokdyk@usgs.gov","orcid":"https://orcid.org/0000-0003-2887-6277","contributorId":193848,"corporation":false,"usgs":true,"family":"Stokdyk","given":"Joel","email":"jstokdyk@usgs.gov","middleInitial":"P.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":842330,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rice, Nancy","contributorId":291417,"corporation":false,"usgs":false,"family":"Rice","given":"Nancy","email":"","affiliations":[],"preferred":false,"id":842331,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Anderson, Anita C.","contributorId":214336,"corporation":false,"usgs":false,"family":"Anderson","given":"Anita C.","affiliations":[],"preferred":false,"id":842332,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Walsh, James F.","contributorId":214333,"corporation":false,"usgs":false,"family":"Walsh","given":"James","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":842333,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Spencer, Sue","contributorId":291418,"corporation":false,"usgs":false,"family":"Spencer","given":"Sue","email":"","affiliations":[],"preferred":false,"id":842334,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Firnstahl, Aaron D. 0000-0003-2686-7596 afirnstahl@usgs.gov","orcid":"https://orcid.org/0000-0003-2686-7596","contributorId":168296,"corporation":false,"usgs":true,"family":"Firnstahl","given":"Aaron","email":"afirnstahl@usgs.gov","middleInitial":"D.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":842335,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Borchardt, Mark A. 0000-0002-6471-2627","orcid":"https://orcid.org/0000-0002-6471-2627","contributorId":151033,"corporation":false,"usgs":false,"family":"Borchardt","given":"Mark","email":"","middleInitial":"A.","affiliations":[{"id":6684,"text":"USDA Forest Service, Southern Research Station, Aiken, SC","active":true,"usgs":false}],"preferred":false,"id":842336,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70232355,"text":"70232355 - 2022 - Laboratory simulation of groundwater along uranium-mining-affected flow paths near the Grand Canyon, Arizona, USA","interactions":[],"lastModifiedDate":"2022-06-29T12:12:57.807473","indexId":"70232355","displayToPublicDate":"2022-05-06T07:09:25","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2745,"text":"Mine Water and the Environment","active":true,"publicationSubtype":{"id":10}},"title":"Laboratory simulation of groundwater along uranium-mining-affected flow paths near the Grand Canyon, Arizona, USA","docAbstract":"<div id=\"Abs1-section\" class=\"c-article-section\"><div id=\"Abs1-content\" class=\"c-article-section__content\"><p>Mining of volumetrically small, but relatively enriched (average 0.6% U<sub>3</sub>O<sub>8</sub>) breccia pipe uranium (BPU) deposits near the Grand Canyon, Arizona, USA has the potential to affect groundwater and springs in the area. Such deposits also contain base metal sulfides that can oxidize to generate acid mine drainage and release trace metals. In this study, sequential batch experiments were conducted to simulate the geochemistry of local shallow groundwater that contacts BPU ore and then moves downgradient through sedimentary strata. The experiments simulated shallow groundwater in a carbonate aquifer followed by contact with BPU ore. The experiments subsequently simulated contact with sedimentary rocks and changing oxygen availability. Concentrations of several contaminants of potential concern became substantially elevated in the waters exposed to BPU ore, including As, Co, Ni, U, and Zn, and to a lesser extent, Mo. Of these, Co, Mo, Ni, and U were minimally attenuated by downgradient processes, whereas Zn was partially attenuated. Sb and Tl concentrations were more moderately elevated but also generally minimally attenuated. Although the mixture of elements is particular to these BPU ore deposits, sulfide oxidation in the ore and carbonate buffering of pH by sedimentary rocks generates patterns of water chemistry common in acid mine drainage settings. Ultimately, downgradient concentrations of elements sourced from BPU ore will also be strongly influenced by non-geochemical factors such as the quantities of water contacting BPU materials, heterogeneity of materials along flow paths, and mixing with waters that have not contacted BPU materials.</p></div></div>","language":"English","publisher":"Springer","doi":"10.1007/s10230-022-00872-9","usgsCitation":"Bern, C.R., Campbell, K.M., Walton-Day, K., and Van Gosen, B.S., 2022, Laboratory simulation of groundwater along uranium-mining-affected flow paths near the Grand Canyon, Arizona, USA: Mine Water and the Environment, v. 41, p. 370-386, https://doi.org/10.1007/s10230-022-00872-9.","productDescription":"17 p.","startPage":"370","endPage":"386","ipdsId":"IP-125192","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":447894,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10230-022-00872-9","text":"Publisher Index Page"},{"id":402668,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"Grand Canyon","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -114.04907226562499,\n              35.69299463209881\n            ],\n            [\n              -111.324462890625,\n              35.69299463209881\n            ],\n            [\n              -111.324462890625,\n              36.98500309285596\n            ],\n            [\n              -114.04907226562499,\n              36.98500309285596\n            ],\n            [\n              -114.04907226562499,\n              35.69299463209881\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"41","noUsgsAuthors":false,"publicationDate":"2022-05-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Bern, Carleton R. 0000-0002-8980-1781 cbern@usgs.gov","orcid":"https://orcid.org/0000-0002-8980-1781","contributorId":201152,"corporation":false,"usgs":true,"family":"Bern","given":"Carleton","email":"cbern@usgs.gov","middleInitial":"R.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":845331,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Campbell, Kate M. 0000-0002-8715-5544 kcampbell@usgs.gov","orcid":"https://orcid.org/0000-0002-8715-5544","contributorId":1441,"corporation":false,"usgs":true,"family":"Campbell","given":"Kate","email":"kcampbell@usgs.gov","middleInitial":"M.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":845332,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Walton-Day, Katherine 0000-0002-9146-6193 kwaltond@usgs.gov","orcid":"https://orcid.org/0000-0002-9146-6193","contributorId":184043,"corporation":false,"usgs":true,"family":"Walton-Day","given":"Katherine","email":"kwaltond@usgs.gov","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":845333,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Van Gosen, Bradley S. 0000-0003-4214-3811 bvangose@usgs.gov","orcid":"https://orcid.org/0000-0003-4214-3811","contributorId":1174,"corporation":false,"usgs":true,"family":"Van Gosen","given":"Bradley","email":"bvangose@usgs.gov","middleInitial":"S.","affiliations":[{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":845334,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70231463,"text":"70231463 - 2022 - Presence of the herbaceous marsh species Schoenoplectus americanus enhances surface elevation gain in transitional coastal wetland communities exposed to elevated CO2 and sediment deposition events","interactions":[],"lastModifiedDate":"2023-06-09T13:46:36.60341","indexId":"70231463","displayToPublicDate":"2022-05-06T07:00:37","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":10760,"text":"Plants","active":true,"publicationSubtype":{"id":10}},"title":"Presence of the herbaceous marsh species Schoenoplectus americanus enhances surface elevation gain in transitional coastal wetland communities exposed to elevated CO2 and sediment deposition events","docAbstract":"<div class=\"art-abstract in-tab hypothesis_container\">Coastal wetlands are dynamic ecosystems that exist along a landscape continuum that can range from freshwater forested wetlands to tidal marsh to mudflat communities. Climate-driven stressors, such as sea-level rise, can cause shifts among these communities, resulting in changes to ecological functions and services. While a growing body of research has characterized the landscape-scale impacts of individual climate-driven stressors, little is known about how multiple stressors and their potential interactions will affect ecological functioning of these ecosystems. How will coastal wetlands respond to discrete climate disturbances, such as hurricane sediment deposition events, under future conditions of elevated atmospheric CO<sub>2</sub>? Will these responses vary among the different wetland communities? We conducted experimental greenhouse manipulations to simulate sediment deposition from a land-falling hurricane under future elevated atmospheric CO<sub>2</sub><span>&nbsp;</span>concentrations (720 ppm CO<sub>2</sub>). We measured responses of net primary production, decomposition, and elevation change in mesocosms representing four communities along a coastal wetland landscape gradient: freshwater forested wetland, forest/marsh mix, marsh, and mudflat. When<span>&nbsp;</span><span class=\"html-italic\">Schoenoplectus americanus</span><span>&nbsp;</span>was present, above- and belowground biomass production was highest, decomposition rates were lowest, and wetland elevation gain was greatest, regardless of CO<sub>2</sub><span>&nbsp;</span>and sediment deposition treatments. Sediment addition initially increased elevation capital in all communities, but post-deposition rates of elevation gain were lower than in mesocosms without added sediment. Together these results indicate that encroachment of oligohaline marshes into freshwater forested wetlands can enhance belowground biomass accumulation and resilience to sea-level rise, and these plant-mediated ecosystem services will be augmented by periodic sediment pulses from storms and restoration efforts.<span id=\"_mce_caret\" data-mce-bogus=\"1\" data-mce-type=\"format-caret\"><span></span></span></div>","language":"English","publisher":"MDPI","doi":"10.3390/plants11091259","usgsCitation":"Stagg, C.L., Laurenzano, C., Vervaeke, W.C., Krauss, K., and McKee, K.L., 2022, Presence of the herbaceous marsh species Schoenoplectus americanus enhances surface elevation gain in transitional coastal wetland communities exposed to elevated CO2 and sediment deposition events: Plants, v. 11, no. 9, 1259, 18 p.; Data Release, https://doi.org/10.3390/plants11091259.","productDescription":"1259, 18 p.; Data Release","ipdsId":"IP-136673","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":447896,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/plants11091259","text":"Publisher Index Page"},{"id":400500,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":417842,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P90JCZWU"}],"volume":"11","issue":"9","noUsgsAuthors":false,"publicationDate":"2022-05-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Stagg, Camille L. 0000-0002-1125-7253","orcid":"https://orcid.org/0000-0002-1125-7253","contributorId":214497,"corporation":false,"usgs":true,"family":"Stagg","given":"Camille","middleInitial":"L.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":842676,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Laurenzano, Claudia 0000-0003-1406-8658","orcid":"https://orcid.org/0000-0003-1406-8658","contributorId":218930,"corporation":false,"usgs":true,"family":"Laurenzano","given":"Claudia","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":842677,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Vervaeke, William C. 0000-0002-1518-5197","orcid":"https://orcid.org/0000-0002-1518-5197","contributorId":96613,"corporation":false,"usgs":false,"family":"Vervaeke","given":"William","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":842678,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Krauss, Ken 0000-0003-2195-0729","orcid":"https://orcid.org/0000-0003-2195-0729","contributorId":219804,"corporation":false,"usgs":true,"family":"Krauss","given":"Ken","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":842679,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McKee, Karen L. 0000-0001-7042-670X mckeek@usgs.gov","orcid":"https://orcid.org/0000-0001-7042-670X","contributorId":704,"corporation":false,"usgs":true,"family":"McKee","given":"Karen","email":"mckeek@usgs.gov","middleInitial":"L.","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":842680,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70231680,"text":"70231680 - 2022 - Major point and nonpoint sources of nutrient pollution to surface water have declined throughout the Chesapeake Bay watershed","interactions":[],"lastModifiedDate":"2022-05-20T11:55:42.439649","indexId":"70231680","displayToPublicDate":"2022-05-06T06:53:36","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":10763,"text":"Environmental Research Communications","active":true,"publicationSubtype":{"id":10}},"title":"Major point and nonpoint sources of nutrient pollution to surface water have declined throughout the Chesapeake Bay watershed","docAbstract":"<div class=\"article-text wd-jnl-art-abstract cf\"><p>Understanding drivers of water quality in local watersheds is the first step for implementing targeted restoration practices. Nutrient inventories can inform water quality management decisions by identifying shifts in nitrogen (N) and phosphorus (P) balances over space and time while also keeping track of the likely urban and agricultural point and nonpoint sources of pollution. The Chesapeake Bay Program's Chesapeake Assessment Scenario Tool (CAST) provides N and P balance data for counties throughout the Chesapeake Bay watershed, and these data were leveraged to create a detailed nutrient inventory for all the counties in the watershed from 1985–2019. This study focuses on three primary watershed nutrient balance components—agricultural surplus, atmospheric deposition, and point source loads—which are thought to be the leading anthropogenic drivers of nutrient loading trends across the watershed. All inputs, outputs, and derived metrics (n=53) like agricultural surplus and nutrient use efficiency, were subjected to short- and long-term trend analyses to discern how sources of pollution to surface water have changed over time. Across the watershed from 1985–2019, downward trends in atmospheric deposition were ubiquitous. Though there are varying effects, long-term declines in agricultural surplus were observed, likely because nutrients are being managed more efficiently. Multiple counties' point source loads declined, primarily associated with upgrades at major cities that discharge treated wastewater directly to tidal waters. Despite all of these positive developments, recent increases in agricultural surpluses from 2009–2019 highlight that water quality gains may soon be reversed in many agricultural areas of the basin. Besides tracking progress and jurisdictional influence on pollution sources, the nutrient inventory can be used for retrospective water quality analysis to highlight drivers of past improvement/degradation of water quality trends and for decision makers to develop and track their near- and long-term watershed restoration strategies.</p></div>","language":"English","publisher":"IOP Publishing","doi":"10.1088/2515-7620/ac5db6","usgsCitation":"Sabo, R.D., Sullivan, B.M., Wu, C., Trentacoste, E.M., Zhang, Q., Shenk, G.W., Bhatt, G., and Linker, L.C., 2022, Major point and nonpoint sources of nutrient pollution to surface water have declined throughout the Chesapeake Bay watershed: Environmental Research Communications, v. 4, no. 4, 045012, 11 p., https://doi.org/10.1088/2515-7620/ac5db6.","productDescription":"045012, 11 p.","ipdsId":"IP-139189","costCenters":[{"id":37759,"text":"VA/WV Water Science 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State University","active":true,"usgs":false}],"preferred":false,"id":843393,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Linker, Lewis C. 0000-0002-3456-3659","orcid":"https://orcid.org/0000-0002-3456-3659","contributorId":252964,"corporation":false,"usgs":false,"family":"Linker","given":"Lewis","email":"","middleInitial":"C.","affiliations":[{"id":6914,"text":"U.S. Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":843394,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70256662,"text":"70256662 - 2022 - Movement and habitat use by smallmouth bass Micropterus dolomieu velox in a dynamic Ozark Highlands riverscape","interactions":[],"lastModifiedDate":"2024-08-29T15:54:25.647648","indexId":"70256662","displayToPublicDate":"2022-05-05T10:48:11","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2285,"text":"Journal of Fish Biology","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Movement and habitat use by smallmouth bass <i>Micropterus dolomieu velox</i> in a dynamic Ozark Highlands riverscape","title":"Movement and habitat use by smallmouth bass Micropterus dolomieu velox in a dynamic Ozark Highlands riverscape","docAbstract":"<p><span>Stream fish movement in response to changing resource availability and habitat needs is important for fish growth, survival and reproduction. The authors used radio telemetry to evaluate individual movements, daily movement rates, home ranges and habitat-use characteristics of adult (278–464 mm&nbsp;</span><i>L</i><sub>T</sub><span>) Neosho smallmouth bass&nbsp;</span><i>Micropterus dolomieu velox</i><span>&nbsp;in three Ozark Highlands streams from June 2016 to February 2018. The authors quantified variation in movement and habitat use among seasons and streams and examined relations with select environmental cues (</span><i>i.e.</i><span>, temperature and discharge), fish size and sex. Maximum movement distances were an order of magnitude greater in the larger Elk River (17.0 km) and Buffalo Creek (12.9 km) than in the smaller Sycamore Creek (1.71 km), were similar in both upstream and downstream directions and typically occurred during the spring. Most movement rates were ≤10 m day</span><sup>−1</sup><span>&nbsp;in all streams and seasons, except for Elk River during spring. Ranking of linear mixed-effects models using AIC</span><sub><i>c</i></sub><span>&nbsp;supported that movement rates were much greater in spring and increased with stream size. Spring movement rate increased with discharge and water temperature; only weak relationships were apparent during other seasons. Increased variation in water temperature had a small negative effect on movement rate. Home range size was highly variable among individuals, ranging 45–15,061 m (median: 773 m), and was not related to fish size, sex, season or stream. Although some fish moved between rivers, this study's tagged fish did not use reservoir or associated interface habitat. Water temperatures used by this study's tagged fish followed seasonal patterns but indicated the use of thermal refugia during summer and winter. Deeper-water habitats were used in Buffalo Creek and in winter across all study streams, whereas greater velocities used in the Elk River likely reflect the increased use of run habitats. Use of pool habitats predominated among tagged fish, particularly in smaller streams. The results of this study indicate considerable heterogeneity in movement and habitat use within and among lotic populations of Neosho smallmouth bass. These findings suggest that population-specific management may be appropriate and highlight the importance of natural flow conditions (</span><i>i.e.</i><span>, spring high flows) and connected habitats for this endemic sport fish, particularly in smaller streams.</span></p>","language":"English","publisher":"Wiley","doi":"10.1111/jfb.15076","usgsCitation":"Miller, A., and Brewer, S.K., 2022, Movement and habitat use by smallmouth bass Micropterus dolomieu velox in a dynamic Ozark Highlands riverscape: Journal of Fish Biology, v. 101, no. 1, p. 100-114, https://doi.org/10.1111/jfb.15076.","productDescription":"15 p.","startPage":"100","endPage":"114","ipdsId":"IP-133584","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":447901,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1111/jfb.15076","text":"External Repository"},{"id":433317,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Missouri, Oklahoma","otherGeospatial":"Brush Creek, Elk River, Sycamore Creek","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -95.00337991937396,\n              36.9787447036027\n            ],\n            [\n              -95.00337991937396,\n              36.50639274310335\n            ],\n            [\n              -94.07756711091189,\n              36.50639274310335\n            ],\n            [\n              -94.07756711091189,\n              36.9787447036027\n            ],\n            [\n              -95.00337991937396,\n              36.9787447036027\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"101","issue":"1","noUsgsAuthors":false,"publicationDate":"2022-05-31","publicationStatus":"PW","contributors":{"authors":[{"text":"Miller, Andrew D.","contributorId":341518,"corporation":false,"usgs":false,"family":"Miller","given":"Andrew D.","affiliations":[{"id":7249,"text":"Oklahoma State University","active":true,"usgs":false}],"preferred":false,"id":908547,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brewer, Shannon K. 0000-0002-1537-3921 skbrewer@usgs.gov","orcid":"https://orcid.org/0000-0002-1537-3921","contributorId":2252,"corporation":false,"usgs":true,"family":"Brewer","given":"Shannon","email":"skbrewer@usgs.gov","middleInitial":"K.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":908548,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70231752,"text":"70231752 - 2022 - Structured elicitation of expert judgement in real-time eruption scenarios: An exercise for Piton de la Fournaise volcano, La Réunion island","interactions":[],"lastModifiedDate":"2022-05-25T15:19:27.635832","indexId":"70231752","displayToPublicDate":"2022-05-05T10:07:22","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7593,"text":"Volcanica","active":true,"publicationSubtype":{"id":10}},"title":"Structured elicitation of expert judgement in real-time eruption scenarios: An exercise for Piton de la Fournaise volcano, La Réunion island","docAbstract":"<p><span>Formalised elicitation of expert judgements has been used to help tackle several problematic societal&nbsp;issues, including volcanic crises and pandemic threats. We present an expert elicitation exercise for Piton de la&nbsp;Fournaise volcano, La Réunion island, held remotely in April 2021. This involved 28 experts from nine&nbsp;countries who considered a hypothetical effusive eruption crisis involving a new vent opening in a high-risk area.&nbsp;The tele-elicitation presented several challenges, but is a promising and workable option for application to future&nbsp;volcanic crises. Our exercise considered an “uncommon” eruptive scenario with a vent outside the present caldera&nbsp;and within inhabited areas, and provided uncertainty ranges for several hazard-related questions for such a scenario&nbsp;(e.g. probability of eruption within a defined timeframe; elapsed time until lava flow reaches a critical location, and&nbsp;other hazard management issues). Our exercise indicated that such a scenario would probably present very different&nbsp;characteristics compared to recent eruptions, and that it is fundamental to include well-prepared&nbsp;expert elicitations in updated civil protection evacuation plans to improve disaster response procedures.</span></p>","language":"English","publisher":"Presses Universitaires de Strasbourg","doi":"10.30909/vol.05.01.105131","usgsCitation":"Tadini, A., Harris, A.J., Morin, J., Bevilacqua, A., Peltier, A., Aspinall, W., Ciolli, S., Bachelery, P., Bernard, B., Biren, J., da Silveira, A.B., Cayol, V., Chevrel, O., Coppola, D., Dietterich, H., Donovan, A., Dorado, O., Drenne, S., Dupere, O., Gurioli, L., Kolzenburg, S., Komorowski, J., Labazuy, P., Mangione, D., Mannini, S., Martel-Asselin, F., Medard, E., Pailot-Bonnetat, S., Rafflin, V., Ramsey, M., Richter, N., Vallejo-Vargas, S., Villeneuve, N., and Zafrilla, S., 2022, Structured elicitation of expert judgement in real-time eruption scenarios: An exercise for Piton de la Fournaise volcano, La Réunion island: Volcanica, v. 5, no. 1, p. 105-131, https://doi.org/10.30909/vol.05.01.105131.","productDescription":"27 p.","startPage":"105","endPage":"131","ipdsId":"IP-138810","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":447906,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.30909/vol.05.01.105131","text":"Publisher Index Page"},{"id":401050,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"La Réunion Island, Piton de la Fournaise Volcano","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              55.15960693359375,\n              -21.423668314313243\n            ],\n            [\n              55.85723876953125,\n              -21.423668314313243\n            ],\n            [\n              55.85723876953125,\n              -20.820308271198467\n            ],\n            [\n              55.15960693359375,\n              -20.820308271198467\n            ],\n            [\n              55.15960693359375,\n              -21.423668314313243\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"5","issue":"1","noUsgsAuthors":false,"publicationDate":"2022-05-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Tadini, Alessandro","contributorId":292017,"corporation":false,"usgs":false,"family":"Tadini","given":"Alessandro","email":"","affiliations":[{"id":62801,"text":"Université Clermont Auvergne","active":true,"usgs":false}],"preferred":false,"id":843648,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Harris, Andrew J. L.","contributorId":169434,"corporation":false,"usgs":false,"family":"Harris","given":"Andrew","email":"","middleInitial":"J. L.","affiliations":[],"preferred":false,"id":843649,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Morin, Julie","contributorId":292018,"corporation":false,"usgs":false,"family":"Morin","given":"Julie","email":"","affiliations":[{"id":27136,"text":"University of Cambridge","active":true,"usgs":false}],"preferred":false,"id":843650,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bevilacqua, Andrea","contributorId":292019,"corporation":false,"usgs":false,"family":"Bevilacqua","given":"Andrea","email":"","affiliations":[{"id":39118,"text":"Istituto Nazionale di Geofisica e Vulcanologia","active":true,"usgs":false}],"preferred":false,"id":843651,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Peltier, Aline","contributorId":149410,"corporation":false,"usgs":false,"family":"Peltier","given":"Aline","email":"","affiliations":[],"preferred":false,"id":843652,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Aspinall, 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Benjamin","contributorId":178529,"corporation":false,"usgs":false,"family":"Bernard","given":"Benjamin","email":"","affiliations":[],"preferred":false,"id":843656,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Biren, Jonas","contributorId":292023,"corporation":false,"usgs":false,"family":"Biren","given":"Jonas","email":"","affiliations":[{"id":62801,"text":"Université Clermont Auvergne","active":true,"usgs":false}],"preferred":false,"id":843657,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"da Silveira, Antonio Brum","contributorId":193509,"corporation":false,"usgs":false,"family":"da Silveira","given":"Antonio","email":"","middleInitial":"Brum","affiliations":[],"preferred":false,"id":843658,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Cayol, Valery","contributorId":292024,"corporation":false,"usgs":false,"family":"Cayol","given":"Valery","email":"","affiliations":[{"id":62801,"text":"Université Clermont 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Pittsburgh","active":true,"usgs":false}],"preferred":false,"id":843678,"contributorType":{"id":1,"text":"Authors"},"rank":30},{"text":"Richter, Nicole","contributorId":292039,"corporation":false,"usgs":false,"family":"Richter","given":"Nicole","email":"","affiliations":[{"id":62807,"text":"Helmholtz-Zentrum Potsdam, Deutsches GeoForschungsZentrum GFZ","active":true,"usgs":false}],"preferred":false,"id":843679,"contributorType":{"id":1,"text":"Authors"},"rank":31},{"text":"Vallejo-Vargas, Silvia","contributorId":292040,"corporation":false,"usgs":false,"family":"Vallejo-Vargas","given":"Silvia","email":"","affiliations":[{"id":62808,"text":"Instituto Geofísico","active":true,"usgs":false}],"preferred":false,"id":843680,"contributorType":{"id":1,"text":"Authors"},"rank":32},{"text":"Villeneuve, Nicolas","contributorId":292041,"corporation":false,"usgs":false,"family":"Villeneuve","given":"Nicolas","email":"","affiliations":[{"id":30776,"text":"Institut de Physique du Globe de 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,{"id":70240353,"text":"70240353 - 2022 - Invasion of annual grasses following wildfire corresponds to maladaptive habitat selection by a sagebrush ecosystem indicator species","interactions":[],"lastModifiedDate":"2023-02-06T15:55:04.895367","indexId":"70240353","displayToPublicDate":"2022-05-05T09:50:54","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3871,"text":"Global Ecology and Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Invasion of annual grasses following wildfire corresponds to maladaptive habitat selection by a sagebrush ecosystem indicator species","docAbstract":"<p><span>Numerous wildlife species within semi-arid&nbsp;<a class=\"topic-link\" title=\"Learn more about shrubland from ScienceDirect's AI-generated Topic Pages\" href=\"https://www.sciencedirect.com/topics/agricultural-and-biological-sciences/shrubland\" data-mce-href=\"https://www.sciencedirect.com/topics/agricultural-and-biological-sciences/shrubland\">shrubland</a>&nbsp;ecosystems across western North America are experiencing substantial habitat loss and fragmentation. These changes in habitat are often attributed to a diverse suite of factors including prolonged and increasingly severe droughts, conifer expansion, anthropogenic development, domestic and feral livestock grazing, and invasion of exotic annual grasses, which promotes increased wildfire frequency and severity. Greater sage-grouse (</span><i>Centrocercus urophasianus</i><span>; hereafter, sage-grouse) are considered an indicator of sagebrush ecosystem health and have experienced widespread population decline associated with habitat loss and degradation, as well as changes in predator communities. Our objectives were to model and map sage-grouse habitat selection and survival during the important brood-rearing life stage in relation to landscape-scale environmental predictors. Furthermore, we sought to understand impacts of wildfire and annual grass invasion on brood habitat, as these accelerated disturbance regimes are a primary cause of habitat loss within the Great Basin region of the USA. We used a hierarchical Bayesian modeling framework to estimate resource selection functions and survival for early and late brood-rearing stages of sage-grouse in relation to a broad suite of habitat characteristics evaluated at multiple spatial scales within the Great Basin from 2009 to 2019. Sage-grouse selected for greater&nbsp;<a class=\"topic-link\" title=\"Learn more about perennial from ScienceDirect's AI-generated Topic Pages\" href=\"https://www.sciencedirect.com/topics/agricultural-and-biological-sciences/perennials\" data-mce-href=\"https://www.sciencedirect.com/topics/agricultural-and-biological-sciences/perennials\">perennial</a>&nbsp;grass cover, higher relative elevations, and areas closer to springs and&nbsp;<a class=\"topic-link\" title=\"Learn more about wet meadows from ScienceDirect's AI-generated Topic Pages\" href=\"https://www.sciencedirect.com/topics/agricultural-and-biological-sciences/wet-meadow\" data-mce-href=\"https://www.sciencedirect.com/topics/agricultural-and-biological-sciences/wet-meadow\">wet meadows</a>&nbsp;during both early and late brood-rearing. Terrain characteristics, including heat load and aspect, were important in survival models, as was variation in shrub height. We also found strong evidence for higher survival for both early and late broods within previously burned areas, but survival within burned areas decreased as annual grass cover (i.e.&nbsp;<a class=\"topic-link\" title=\"Learn more about cheatgrass from ScienceDirect's AI-generated Topic Pages\" href=\"https://www.sciencedirect.com/topics/agricultural-and-biological-sciences/bromus-tectorum\" data-mce-href=\"https://www.sciencedirect.com/topics/agricultural-and-biological-sciences/bromus-tectorum\">cheatgrass</a>,&nbsp;</span><i>Bromus tectorum</i><span>) increased. This interaction effect demonstrates how invasion of annual grasses into burned areas, which has become prevalent in Great Basin sagebrush ecosystems, can lead to maladaptive habitat selection by brood-rearing greater sage-grouse. Understanding these complex relationships aids wildlife conservation and habitat management as wildfire and annual grass cycles continue to accelerate across western ecosystems.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.gecco.2022.e02147","usgsCitation":"Brussee, B.E., Coates, P.S., O’Neil, S.T., Casazza, M.L., Espinosa, S.P., Boone, J., Ammon, E., Gardner, S.C., and Delehanty, D.J., 2022, Invasion of annual grasses following wildfire corresponds to maladaptive habitat selection by a sagebrush ecosystem indicator species: Global Ecology and Conservation, v. 37, e02147, 19 p., https://doi.org/10.1016/j.gecco.2022.e02147.","productDescription":"e02147, 19 p.","ipdsId":"IP-133908","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":447908,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.gecco.2022.e02147","text":"Publisher Index Page"},{"id":435856,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9B593DZ","text":"USGS data release","linkHelpText":"Spatially-Explicit Predictive Maps of Greater Sage-Grouse Brood Selection Integrated with Brood Survival in Nevada and Northeastern California, USA"},{"id":412740,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Nevada","otherGeospatial":"Great Basin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -115.11100469577016,\n              37.65679718030911\n            ],\n            [\n              -114.01367957532398,\n              37.81079149850166\n            ],\n            [\n              -114.06841886178916,\n              41.950546575009156\n          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bbrussee@usgs.gov","orcid":"https://orcid.org/0000-0002-2452-7101","contributorId":4249,"corporation":false,"usgs":true,"family":"Brussee","given":"Brianne","email":"bbrussee@usgs.gov","middleInitial":"E.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":863533,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Coates, Peter S. 0000-0003-2672-9994 pcoates@usgs.gov","orcid":"https://orcid.org/0000-0003-2672-9994","contributorId":3263,"corporation":false,"usgs":true,"family":"Coates","given":"Peter","email":"pcoates@usgs.gov","middleInitial":"S.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":863534,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"O’Neil, Shawn T. 0000-0002-0899-5220","orcid":"https://orcid.org/0000-0002-0899-5220","contributorId":206589,"corporation":false,"usgs":true,"family":"O’Neil","given":"Shawn","email":"","middleInitial":"T.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":863535,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"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":863536,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Espinosa, Shawn P.","contributorId":195583,"corporation":false,"usgs":false,"family":"Espinosa","given":"Shawn","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":863537,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Boone, John D.","contributorId":300334,"corporation":false,"usgs":false,"family":"Boone","given":"John D.","affiliations":[{"id":65087,"text":"Great Basin Bird Observatory, Reno, Nevada, USA","active":true,"usgs":false}],"preferred":false,"id":863538,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ammon, Elisabeth M.","contributorId":302116,"corporation":false,"usgs":false,"family":"Ammon","given":"Elisabeth M.","affiliations":[{"id":65418,"text":"Great Basin Bird Observatory, 1755 E. Plumb Ln Ste 256 A, Reno, NV 89502, USA","active":true,"usgs":false}],"preferred":false,"id":863539,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Gardner, Scott C.","contributorId":192081,"corporation":false,"usgs":false,"family":"Gardner","given":"Scott","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":863540,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Delehanty, David J.","contributorId":195584,"corporation":false,"usgs":false,"family":"Delehanty","given":"David","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":863541,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70231318,"text":"70231318 - 2022 - Hydroclimate response of spring ecosystems to a two-stage Younger Dryas event in western North America","interactions":[],"lastModifiedDate":"2022-05-06T14:29:19.84111","indexId":"70231318","displayToPublicDate":"2022-05-05T09:26:24","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3358,"text":"Scientific Reports","active":true,"publicationSubtype":{"id":10}},"title":"Hydroclimate response of spring ecosystems to a two-stage Younger Dryas event in western North America","docAbstract":"<p><span>The Younger Dryas (YD) climate event is the preeminent example of abrupt climate change in the recent geologic past. Climate conditions during the YD were spatially complex, and high-resolution sediment cores in the North Atlantic, western Europe, and East Asia have revealed it unfolded in two distinct stages, including an initial stable climatic period between ~ 12.9 and 12.2&nbsp;ka associated with a weakened Atlantic Meridional Overturning Circulation (AMOC) and a second phase characterized by variable conditions until 11.7&nbsp;ka as the AMOC recovered. Decades of investigations into the climate of western North America during the YD have failed to identify this stepped phenomenon. Here we present hydroclimate data from paleospring deposits in Death Valley National Park (California, USA) that demonstrate unequivocal evidence of two-stage partitioning within the YD event. High groundwater levels supported persistent and long-lived spring ecosystems between ~ 13.0 and 12.2&nbsp;ka, which were immediately replaced by alternating wet and dry environments until ~ 11.8&nbsp;ka. These results establish the mid-YD climate transition extended into western North America at approximately the same time it was recorded by hydrologic systems elsewhere in the Northern Hemisphere and show that even short-lived changes in the AMOC can have profound consequences for ecosystems worldwide.</span></p>","language":"English","publisher":"Nature Publications","doi":"10.1038/s41598-022-11377-4","usgsCitation":"Pigati, J.S., and Springer, K.B., 2022, Hydroclimate response of spring ecosystems to a two-stage Younger Dryas event in western North America: Scientific Reports, v. 12, 7373, 7 p., https://doi.org/10.1038/s41598-022-11377-4.","productDescription":"7373, 7 p.","ipdsId":"IP-122733","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":447910,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41598-022-11377-4","text":"Publisher Index Page"},{"id":435857,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9U5XSRY","text":"USGS data release","linkHelpText":"Data release for Hydroclimate response of spring ecosystems to a two-stage Younger Dryas event in western North America"},{"id":400284,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Nevada","otherGeospatial":"Death Valley","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -118.070068359375,\n              36.217687122250574\n            ],\n            [\n              -116.66931152343749,\n              36.217687122250574\n            ],\n            [\n              -116.66931152343749,\n              37.4356124041315\n            ],\n            [\n              -118.070068359375,\n              37.4356124041315\n            ],\n            [\n              -118.070068359375,\n              36.217687122250574\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"12","noUsgsAuthors":false,"publicationDate":"2022-05-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Pigati, Jeffrey S. 0000-0001-5843-6219 jpigati@usgs.gov","orcid":"https://orcid.org/0000-0001-5843-6219","contributorId":201167,"corporation":false,"usgs":true,"family":"Pigati","given":"Jeffrey","email":"jpigati@usgs.gov","middleInitial":"S.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":842301,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Springer, Kathleen B. 0000-0002-2404-0264 kspringer@usgs.gov","orcid":"https://orcid.org/0000-0002-2404-0264","contributorId":149826,"corporation":false,"usgs":true,"family":"Springer","given":"Kathleen","email":"kspringer@usgs.gov","middleInitial":"B.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":842302,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70232248,"text":"70232248 - 2022 - Supporting the development and use of native plant materials for restoration on the Colorado Plateau (Fiscal Year 2021 Report)","interactions":[],"lastModifiedDate":"2022-06-17T14:21:51.237888","indexId":"70232248","displayToPublicDate":"2022-05-05T09:21:04","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":10936,"text":"Fiscal Year Report","active":true,"publicationSubtype":{"id":1}},"title":"Supporting the development and use of native plant materials for restoration on the Colorado Plateau (Fiscal Year 2021 Report)","docAbstract":"<p>A primary focus of the Colorado Plateau Native Plant Program (CPNPP) is to identify and develop appropriate native plant materials (NPMs) for current and future restoration projects. Multiple efforts have characterized the myriad challenges inherent in providing appropriate seed resources to enable effective, widespread restoration and have identified a broad suite of research activities to provide the information necessary to overcome those challenges (e.g., Plant Conservation Alliance 2015; Breed et al. 2018; Winkler et al. 2018; McCormick et al. 2021). Many of the most complex information needs relate to identifying the appropriate sources of plant species that can successfully establish in dryland environments, like the Colorado Plateau, where low and highly variable precipitation is standard. Providing this information requires synergistic research efforts in which results from earlier investigations inform the design of subsequent investigations. The U.S. Geological Survey (USGS) Southwest Biological Science Center’s (SBSC’s) research activities to support CPNPP in FY21 followed the FY21 Statement of Work to support a research framework that is continually adapting based on the needs of the restoration community and results from previous investigations; the long-term research framework is outlined in the 2019-2023 5-Year Research Strategy (hereafter referred to as the 5-year plan). This research framework provides support for the National Seed Strategy for Rehabilitation and Restoration (Plant Conservation Alliance 2015), Biden-Harris Administration Executive Order 14008 (Tackling the Climate Crisis at Home and Abroad), and Department of Interior Priority #4 (Working to conserve at least 30% each of our lands and waters by the year 2030). </p><p>Research activities in FY21 centered on landscape genomics, implementing and monitoring a common garden experiment near Vernal, UT, conducting experimental treatments using the GRID (Germination for Restoration Information and Decision-making) framework, and initiating new genetics projects to investigate the impact of production techniques on plant materials and restoration treatments on native plant communities. These activities were supported by four biological science technicians. The SARS-CoV-2 pandemic delayed some aspects of the FY21 workplan, especially for outside laboratory services. However, goals were largely met, and the overall progress of research remains on track with respect to the 5-year plan. While Dr. Rob Massatti was the only scientist supported by the SBSC-CPNPP agreement in FY21, other scientists, including Drs. John Bradford, Seth Munson, Mike Duniway, Sasha Reed, and Daniel Winkler, spent a considerable amount of time providing expertise and support for individual projects. Work activities performed in support of each 5-year plan goal are discussed in turn. Products resulting from FY21 research activities are reported in Appendix 1.</p>","language":"English","publisher":"Bureau of Land Management","collaboration":"Bureau of Land Management","usgsCitation":"Massatti, R., Winkler, D.E., Reed, S., Duniway, M.C., Munson, S.M., and Bradford, J., 2022, Supporting the development and use of native plant materials for restoration on the Colorado Plateau (Fiscal Year 2021 Report): Fiscal Year Report, 19 p.","productDescription":"19 p.","ipdsId":"IP-139434","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":402326,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":402322,"type":{"id":15,"text":"Index Page"},"url":"https://www.blm.gov/sites/blm.gov/files/docs/2022-06/CPNPP_USGS_FY21_AnnualReport.pdf","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"Arizona, Colorado, New Mexico, Utah","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -113.02734374999999,\n              31.87755764334002\n            ],\n            [\n              -104.765625,\n              31.87755764334002\n            ],\n            [\n              -104.765625,\n              40.17887331434696\n            ],\n            [\n              -113.02734374999999,\n              40.17887331434696\n            ],\n            [\n              -113.02734374999999,\n              31.87755764334002\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Massatti, Robert 0000-0001-5854-5597","orcid":"https://orcid.org/0000-0001-5854-5597","contributorId":207294,"corporation":false,"usgs":true,"family":"Massatti","given":"Robert","email":"","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":844795,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Winkler, Daniel E. 0000-0003-4825-9073","orcid":"https://orcid.org/0000-0003-4825-9073","contributorId":206786,"corporation":false,"usgs":true,"family":"Winkler","given":"Daniel","email":"","middleInitial":"E.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":844796,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Reed, Sasha C. 0000-0002-8597-8619","orcid":"https://orcid.org/0000-0002-8597-8619","contributorId":205372,"corporation":false,"usgs":true,"family":"Reed","given":"Sasha C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":844797,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Duniway, Michael C. 0000-0002-9643-2785 mduniway@usgs.gov","orcid":"https://orcid.org/0000-0002-9643-2785","contributorId":4212,"corporation":false,"usgs":true,"family":"Duniway","given":"Michael","email":"mduniway@usgs.gov","middleInitial":"C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":844798,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Munson, Seth M. 0000-0002-2736-6374 smunson@usgs.gov","orcid":"https://orcid.org/0000-0002-2736-6374","contributorId":1334,"corporation":false,"usgs":true,"family":"Munson","given":"Seth","email":"smunson@usgs.gov","middleInitial":"M.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true},{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true}],"preferred":true,"id":844799,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bradford, John B. 0000-0001-9257-6303","orcid":"https://orcid.org/0000-0001-9257-6303","contributorId":219257,"corporation":false,"usgs":true,"family":"Bradford","given":"John B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":844800,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70236087,"text":"70236087 - 2022 - High‐frequency rupture processes of the 2014 Mw 8.2 Iquique and 2015 Mw 8.3 Illapel, Chile, earthquakes determined from strong‐motion recordings","interactions":[],"lastModifiedDate":"2022-08-29T12:07:32.607079","indexId":"70236087","displayToPublicDate":"2022-05-05T07:04:41","publicationYear":"2022","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":"High‐frequency rupture processes of the 2014 Mw 8.2 Iquique and 2015 Mw 8.3 Illapel, Chile, earthquakes determined from strong‐motion recordings","docAbstract":"<p><span>Strong‐motion recordings of the 2014&nbsp;</span><span class=\"inline-formula no-formula-id\"><span id=\"MathJax-Element-5-Frame\" class=\"MathJax\" data-mathml=\"<math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot;><msub xmlns=&quot;&quot;><mi>M</mi><mi mathvariant=&quot;normal&quot;>w</mi></msub></math>\"><span id=\"MathJax-Span-21\" class=\"math\"><span><span id=\"MathJax-Span-22\" class=\"mrow\"><span id=\"MathJax-Span-23\" class=\"msub\"><span id=\"MathJax-Span-24\" class=\"mi\">M</span><span id=\"MathJax-Span-25\" class=\"mi\">w</span></span></span></span></span><span class=\"MJX_Assistive_MathML\">Mw</span></span></span><span>&nbsp;8.2 Iquique and 2015&nbsp;</span><span class=\"inline-formula no-formula-id\"><span id=\"MathJax-Element-6-Frame\" class=\"MathJax\" data-mathml=\"<math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot;><msub xmlns=&quot;&quot;><mi>M</mi><mi mathvariant=&quot;normal&quot;>w</mi></msub></math>\"><span id=\"MathJax-Span-26\" class=\"math\"><span><span id=\"MathJax-Span-27\" class=\"mrow\"><span id=\"MathJax-Span-28\" class=\"msub\"><span id=\"MathJax-Span-29\" class=\"mi\">M</span><span id=\"MathJax-Span-30\" class=\"mi\">w</span></span></span></span></span><span class=\"MJX_Assistive_MathML\">Mw</span></span></span><span>&nbsp;8.3 Illapel, Chile, earthquakes were analyzed to determine rupture propagation and the location, timing, and strength of subevents that produce most of the high‐frequency (≥1&nbsp;Hz) ground motions. A moving window,cross‐correlation analysis of recordings from a local dense array, band‐pass filtered at 1&nbsp;Hz, directly shows that the Iquique earthquake ruptured to the southeast over a distance of about 60&nbsp;km. Array analysis of lower frequency energy (0.03–0.1&nbsp;Hz) indicates that it occurred updip of the high‐frequency rupture. A methodology was developed for inverting the envelopes of acceleration records (1–5&nbsp;Hz) to map high‐frequency source factors on the rupture zone and was applied to the two earthquakes. Waveforms of&nbsp;</span><span class=\"inline-formula no-formula-id\"><span id=\"MathJax-Element-7-Frame\" class=\"MathJax\" data-mathml=\"<math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot;><msub xmlns=&quot;&quot;><mi>M</mi><mi mathvariant=&quot;normal&quot;>w</mi></msub></math>\"><span id=\"MathJax-Span-31\" class=\"math\"><span><span id=\"MathJax-Span-32\" class=\"mrow\"><span id=\"MathJax-Span-33\" class=\"msub\"><span id=\"MathJax-Span-34\" class=\"mi\">M</span><span id=\"MathJax-Span-35\" class=\"mi\">w</span></span></span></span></span><span class=\"MJX_Assistive_MathML\">Mw</span></span></span><span>&nbsp;6 earthquakes were used as empirical Green’s functions in the inversions. High‐frequency subevents within the two&nbsp;</span><span class=\"inline-formula no-formula-id\"><span id=\"MathJax-Element-8-Frame\" class=\"MathJax\" data-mathml=\"<math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot;><msub xmlns=&quot;&quot;><mi>M</mi><mi mathvariant=&quot;normal&quot;>w</mi></msub></math>\"><span id=\"MathJax-Span-36\" class=\"math\"><span><span id=\"MathJax-Span-37\" class=\"mrow\"><span id=\"MathJax-Span-38\" class=\"msub\"><span id=\"MathJax-Span-39\" class=\"mi\">M</span><span id=\"MathJax-Span-40\" class=\"mi\">w</span></span></span></span></span><span class=\"MJX_Assistive_MathML\">Mw</span></span></span><span>&nbsp;8 earthquakes were located at depths ranging from 25 to 55&nbsp;km and mostly occurred downdip of the peak slip of these earthquakes. Fourier spectral ratios of the Iquique mainshock with respect to&nbsp;</span><span class=\"inline-formula no-formula-id\"><span id=\"MathJax-Element-9-Frame\" class=\"MathJax\" data-mathml=\"<math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot;><msub xmlns=&quot;&quot;><mi>M</mi><mi mathvariant=&quot;normal&quot;>w</mi></msub></math>\"><span id=\"MathJax-Span-41\" class=\"math\"><span><span id=\"MathJax-Span-42\" class=\"mrow\"><span id=\"MathJax-Span-43\" class=\"msub\"><span id=\"MathJax-Span-44\" class=\"mi\">M</span><span id=\"MathJax-Span-45\" class=\"mi\">w</span></span></span></span></span><span class=\"MJX_Assistive_MathML\">Mw</span></span></span><span>&nbsp;5–6 aftershocks were fit to determine their stress drops. The stress drops were roughly constant from&nbsp;</span><span class=\"inline-formula no-formula-id\"><span id=\"MathJax-Element-10-Frame\" class=\"MathJax\" data-mathml=\"<math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot;><msub xmlns=&quot;&quot;><mi>M</mi><mi mathvariant=&quot;normal&quot;>w</mi></msub></math>\"><span id=\"MathJax-Span-46\" class=\"math\"><span><span id=\"MathJax-Span-47\" class=\"mrow\"><span id=\"MathJax-Span-48\" class=\"msub\"><span id=\"MathJax-Span-49\" class=\"mi\">M</span><span id=\"MathJax-Span-50\" class=\"mi\">w</span></span></span></span></span><span class=\"MJX_Assistive_MathML\">Mw</span></span></span><span>&nbsp;5 to 8 at 10–20&nbsp;MPa. A compound rupture model is described in which subevents occur in areas of spatially heterogeneous strength and stress on the rupture, and produce the high‐frequency radiated energy of the overall earthquake, but are not located in the areas of peak slip. The stress drop of the overall earthquake is shown to equal the root mean square stress drop of subevents averaged over the rupture area.</span></p>","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120210331","usgsCitation":"Frankel, A.D., 2022, High‐frequency rupture processes of the 2014 Mw 8.2 Iquique and 2015 Mw 8.3 Illapel, Chile, earthquakes determined from strong‐motion recordings: Bulletin of the Seismological Society of America, v. 112, no. 4, p. 1832-1852, https://doi.org/10.1785/0120210331.","productDescription":"21 p.","startPage":"1832","endPage":"1852","ipdsId":"IP-136193","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":405784,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Chile","city":"Iquique, Illapel","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -70.5322265625,\n              -20.601936194281016\n            ],\n            [\n              -69.58740234375,\n              -20.601936194281016\n            ],\n            [\n              -69.58740234375,\n              -19.890723023996898\n            ],\n            [\n              -70.5322265625,\n              -19.890723023996898\n            ],\n            [\n              -70.5322265625,\n              -20.601936194281016\n            ]\n          ]\n        ]\n      }\n    },\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -71.3671875,\n              -31.802892586706747\n            ],\n            [\n              -70.894775390625,\n              -31.802892586706747\n            ],\n            [\n              -70.894775390625,\n              -31.475524020001796\n            ],\n            [\n              -71.3671875,\n              -31.475524020001796\n            ],\n            [\n              -71.3671875,\n              -31.802892586706747\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"112","issue":"4","noUsgsAuthors":false,"publicationDate":"2022-05-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Frankel, Arthur D. 0000-0001-9119-6106 afrankel@usgs.gov","orcid":"https://orcid.org/0000-0001-9119-6106","contributorId":146285,"corporation":false,"usgs":true,"family":"Frankel","given":"Arthur","email":"afrankel@usgs.gov","middleInitial":"D.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":849958,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70246533,"text":"70246533 - 2022 - Accounting for residual heterogeneity in double-observer sightability models decreases bias in burro abundance estimates","interactions":[],"lastModifiedDate":"2023-07-07T12:07:54.511452","indexId":"70246533","displayToPublicDate":"2022-05-05T06:54:35","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Accounting for residual heterogeneity in double-observer sightability models decreases bias in burro abundance estimates","docAbstract":"<div class=\"abstract-group  metis-abstract\"><div class=\"article-section__content en main\"><p>Feral burros (<i>Equus asinus</i>) and horses (<i>E. ferus caballus</i>) inhabiting public land in the western United States are intended to be managed at population levels established to promote a thriving, natural ecological balance. Double-observer sightability (M<sub>DS</sub>) models, which use detection records from multiple observers and sighting covariates, perform well for estimating feral horse abundances, but their effectiveness for use in burro populations is less understood. These M<sub>DS</sub><span>&nbsp;</span>models help minimize detection bias, yet bias can be further reduced with models that account for unmodeled variation, or residual heterogeneity, in detection probability. In populations containing radio-marked individuals, residual heterogeneity can be estimated with M<sub>DS</sub><span>&nbsp;</span>models by including a covariate that corresponds to the marked status of a group (M<sub>H</sub><span>&nbsp;</span>models). Another approach is to use information from detections missed by both observers to account for the characteristics that make groups more or less likely to be detected, or recaptured, by the second observer (M<sub>R</sub><span>&nbsp;</span>models). We used aerial survey data from 3 burro populations (Sinbad Herd Management Area, UT [2016–2018], Lake Pleasant Herd Management Area, AZ [2017], and Fort Irwin National Training Center, CA [2016–2017]) to develop M<sub>DS</sub><span>&nbsp;</span>models applicable for feral burros in the southwestern United States. Our objectives were to quantify precision and bias of standard M<sub>DS</sub><span>&nbsp;</span>surveys for feral burros and to examine which model type for incorporating residual heterogeneity (M<sub>H</sub><span>&nbsp;</span>or M<sub>R</sub>) would result in the least-biased estimates of burro populations relative to the minimum number known alive (MNKA) within the Sinbad Herd Management Area. Standard M<sub>DS</sub><span>&nbsp;</span>model estimates achieved a mean coefficient of variation of 0.08, while underestimating MNKA by an average of 27.1%. Accounting for residual heterogeneity through recapture probability in M<sub>R</sub><span>&nbsp;</span>models resulted in estimates closer to MNKA than M<sub>H</sub><span>&nbsp;</span>models (9.5% vs. 16.5% less than MNKA). Our results indicate that M<sub>DS</sub><span>&nbsp;</span>models can achieve precise enough estimates to monitor feral burro populations, but they routinely produce negatively biased estimates. We encourage the use of radio-collars to reduce bias in future burro surveys by accounting for residual heterogeneity through M<sub>R</sub><span>&nbsp;</span>models.</p></div></div>","language":"English","publisher":"The Wildlife Society","doi":"10.1002/jwmg.22239","usgsCitation":"Hennig, J.D., Schoenecker, K., Cain, J.W., Roemer, G., and Laake, J.L., 2022, Accounting for residual heterogeneity in double-observer sightability models decreases bias in burro abundance estimates: Journal of Wildlife Management, v. 86, no. 5, e22239, 17 p., https://doi.org/10.1002/jwmg.22239.","productDescription":"e22239, 17 p.","ipdsId":"IP-132644","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":447914,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/jwmg.22239","text":"Publisher Index Page"},{"id":435858,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9OAEATC","text":"USGS data release","linkHelpText":"Detections of burros from helicopter aerial surveys in the southwestern US, 2016-2018"},{"id":418742,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"86","issue":"5","noUsgsAuthors":false,"publicationDate":"2022-05-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Hennig, Jacob Daniel 0000-0001-6450-6906","orcid":"https://orcid.org/0000-0001-6450-6906","contributorId":264526,"corporation":false,"usgs":true,"family":"Hennig","given":"Jacob","email":"","middleInitial":"Daniel","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":877076,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schoenecker, Kathryn A. 0000-0001-9906-911X","orcid":"https://orcid.org/0000-0001-9906-911X","contributorId":202531,"corporation":false,"usgs":true,"family":"Schoenecker","given":"Kathryn A.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":877077,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cain, James W. III 0000-0003-4743-516X jwcain@usgs.gov","orcid":"https://orcid.org/0000-0003-4743-516X","contributorId":4063,"corporation":false,"usgs":true,"family":"Cain","given":"James","suffix":"III","email":"jwcain@usgs.gov","middleInitial":"W.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":877078,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Roemer, Gary W.","contributorId":276331,"corporation":false,"usgs":false,"family":"Roemer","given":"Gary W.","affiliations":[{"id":27575,"text":"NMSU","active":true,"usgs":false}],"preferred":false,"id":877079,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Laake, Jeffrey L.","contributorId":83851,"corporation":false,"usgs":false,"family":"Laake","given":"Jeffrey","email":"","middleInitial":"L.","affiliations":[{"id":6578,"text":"National Marine Fisheries Service, Seattle, WA 98112, USA","active":true,"usgs":false}],"preferred":false,"id":877080,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70232089,"text":"70232089 - 2022 - A future for the inland fish and fisheries hidden within the sustainable development goals","interactions":[],"lastModifiedDate":"2022-06-06T11:48:01.850001","indexId":"70232089","displayToPublicDate":"2022-05-05T06:43:29","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5738,"text":"Frontiers in Environmental Science","active":true,"publicationSubtype":{"id":10}},"title":"A future for the inland fish and fisheries hidden within the sustainable development goals","docAbstract":"<div class=\"JournalAbstract\"><p class=\"mb15\">The United Nations Sustainable Development Goals (SDGs) are a unifying call for change - guiding global actions at multiple levels of governance for a better planet and better lives. Consequently, achieving the “future we want” may be hindered by overlooking valuable natural resources and services that are not explicitly included in the SDGs. Not recognizing the direct, intrinsic value of some natural resources may threaten the sustainability of the services they provide and their contributions to the SDGs. Here, we use inland aquatic ecosystems, and the fish and fisheries therein, as an example to explore opportunities for recognition and inclusion of other natural resources that are missing from the SDGs. Key resources absent from the SDGs are less likely to be incorporated in global, national, and regional objectives, dialogues, and policies. We outline multiple potential pathways for better inclusion and capitalization of contributions from these overlooked natural resources during the operationalization of the SDGs and other global instruments.</p></div>","language":"English","publisher":"Frontiers","doi":"10.3389/fenvs.2022.756045","usgsCitation":"Elliott, V., Lynch, A., Phang, S.C., Cooke, S.J., Cowx, I.G., Claussen, J.E., Dalton, J., Darwall, W., Harrison, I., Murchie, K.J., Steel, E.A., and Stokes, G.L., 2022, A future for the inland fish and fisheries hidden within the sustainable development goals: Frontiers in Environmental Science, v. 10, 756045, 11 p., https://doi.org/10.3389/fenvs.2022.756045.","productDescription":"756045, 11 p.","ipdsId":"IP-124586","costCenters":[{"id":36940,"text":"National Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":447916,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fenvs.2022.756045","text":"Publisher Index Page"},{"id":401741,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"10","noUsgsAuthors":false,"publicationDate":"2022-05-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Elliott, Vittoria 0000-0001-8230-489X","orcid":"https://orcid.org/0000-0001-8230-489X","contributorId":216206,"corporation":false,"usgs":false,"family":"Elliott","given":"Vittoria","affiliations":[{"id":16938,"text":"Conservation International","active":true,"usgs":false}],"preferred":false,"id":844181,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lynch, Abigail J. 0000-0001-8449-8392","orcid":"https://orcid.org/0000-0001-8449-8392","contributorId":207361,"corporation":false,"usgs":true,"family":"Lynch","given":"Abigail","middleInitial":"J.","affiliations":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true}],"preferred":true,"id":844182,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Phang, Sui C.","contributorId":169462,"corporation":false,"usgs":false,"family":"Phang","given":"Sui","email":"","middleInitial":"C.","affiliations":[{"id":6714,"text":"Ohio State University, School of Earth Sciences, Columbus, Ohio, USA","active":true,"usgs":false}],"preferred":false,"id":844183,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cooke, Steve J.","contributorId":220492,"corporation":false,"usgs":false,"family":"Cooke","given":"Steve","email":"","middleInitial":"J.","affiliations":[{"id":17786,"text":"Carleton University","active":true,"usgs":false}],"preferred":false,"id":844184,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cowx, Ian. G.","contributorId":220479,"corporation":false,"usgs":false,"family":"Cowx","given":"Ian.","email":"","middleInitial":"G.","affiliations":[{"id":40174,"text":"University of Hull","active":true,"usgs":false}],"preferred":false,"id":844185,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Claussen, Julie E.","contributorId":292274,"corporation":false,"usgs":false,"family":"Claussen","given":"Julie","email":"","middleInitial":"E.","affiliations":[{"id":47804,"text":"Fisheries Conservation Foundation","active":true,"usgs":false}],"preferred":false,"id":844186,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Dalton, James","contributorId":292275,"corporation":false,"usgs":false,"family":"Dalton","given":"James","email":"","affiliations":[{"id":40831,"text":"IUCN","active":true,"usgs":false}],"preferred":false,"id":844187,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Darwall, William","contributorId":268101,"corporation":false,"usgs":false,"family":"Darwall","given":"William","affiliations":[{"id":40831,"text":"IUCN","active":true,"usgs":false}],"preferred":false,"id":844188,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Harrison, Ian ","contributorId":224161,"corporation":false,"usgs":false,"family":"Harrison","given":"Ian ","affiliations":[{"id":16938,"text":"Conservation International","active":true,"usgs":false}],"preferred":false,"id":844189,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Murchie, Karen J.","contributorId":216207,"corporation":false,"usgs":false,"family":"Murchie","given":"Karen","email":"","middleInitial":"J.","affiliations":[{"id":39376,"text":"Shedd Aquarium","active":true,"usgs":false}],"preferred":false,"id":844190,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Steel, E. Ashley","contributorId":192227,"corporation":false,"usgs":false,"family":"Steel","given":"E.","email":"","middleInitial":"Ashley","affiliations":[],"preferred":false,"id":844191,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Stokes, Gretchen L. 0000-0003-4202-6527","orcid":"https://orcid.org/0000-0003-4202-6527","contributorId":245640,"corporation":false,"usgs":false,"family":"Stokes","given":"Gretchen","email":"","middleInitial":"L.","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":844192,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}}
,{"id":70231182,"text":"tm4D3 - 2022 - U.S. Geological Survey Hydrologic Toolbox — A graphical and mapping interface for analysis of hydrologic data","interactions":[],"lastModifiedDate":"2022-05-05T13:50:19.759656","indexId":"tm4D3","displayToPublicDate":"2022-05-04T13:00:00","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":335,"text":"Techniques and Methods","code":"TM","onlineIssn":"2328-7055","printIssn":"2328-7047","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"4-D3","displayTitle":"U.S. Geological Survey Hydrologic Toolbox — A Graphical and Mapping Interface for Analysis of Hydrologic Data","title":"U.S. Geological Survey Hydrologic Toolbox — A graphical and mapping interface for analysis of hydrologic data","docAbstract":"<p>The Hydrologic Toolbox is a Windows-based desktop software program that provides a graphical and mapping interface for analysis of hydrologic time-series data with a set of widely used and standardized computational methods. The software combines the analytical and statistical functionality provided in the U.S. Geological Survey Groundwater and Surface-Water Toolboxes and provides several enhancements to these programs. The main analytical methods are the computation of hydrologic-frequency statistics such as the 7-day minimum flow that occurs on average only once every 10 years (7Q10); the computation of design flows, including biologically based flows; the computation of flow-duration curves and duration hydrographs; eight computer-programming methods for hydrograph separation of a streamflow time series, including the Base-Flow Index (BFI), HYSEP, PART, and SWAT Bflow methods and Eckhardt’s two-parameter digital-filtering method; and the RORA recession-curve displacement method and associated RECESS program to estimate groundwater-recharge values from streamflow data. Several of the statistical methods provided in the Hydrologic Toolbox are used primarily for computation of critical low-flow statistics. The Hydrologic Toolbox also facilitates retrieval of streamflow and groundwater-level time-series data from the U.S. Geological Survey National Water Information System and outputs text reports that describe their analyses.</p><p>The Hydrologic Toolbox was developed by use of the DotSpatial geographic information system (GIS) programming library, which is part of the MapWindow project. DotSpatial is a nonproprietary, open-source program written for the .NET framework that includes a spatial data viewer and GIS capabilities. Advantages of the DotSpatial system include its pure .NET implementation for both the user interface and the GIS mapping engine, and thus the DotSpatial system simplifies software deployment and installation. In addition to combining the functionality of the separate Groundwater and Surface-Water Toolboxes, the Hydrologic Toolbox also organizes the functionality by theme (Groundwater Tools, Surface-Water Tools, and general Time-Series Tools).</p><p>This report provides a description of how to build a Hydrologic Toolbox project and to download and manage hydrologic time-series data. It includes an overview of the analytical and statistical capabilities of the Hydrologic Toolbox and highlights the primary differences between the Hydrologic Toolbox and the Groundwater and Surface-Water Toolboxes. The report supplements information available in an extensive online Help manual and is intended to provide a set of instructions that will allow users to quickly develop skills to use the mapping, data-retrieval, and computational tools of the program.</p>","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Book 4, Hydrologic Analysis and Interpretation","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/tm4D3","programNote":"Water Availability and Use Science Program","usgsCitation":"Barlow, P.M., McHugh, A.R., Kiang, J.E., Zhai, T., Hummel, P., Duda, P., and Hinz, S., 2022, U.S. Geological Survey Hydrologic Toolbox — A graphical and mapping interface for analysis of hydrologic data: U.S. Geological Survey Techniques and Methods, book 4, chap. D3, 23 p., https://doi.org/10.3133/tm4D3.","productDescription":"Report: vi, 23 p.; Software release","numberOfPages":"23","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-130481","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":400024,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/tm/04/d03/tm4d3.pdf","text":"Report","size":"4.55 MB","linkFileType":{"id":1,"text":"pdf"},"description":"TM 4-D3"},{"id":400023,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/tm/04/d03/coverthb.jpg"},{"id":400027,"rank":3,"type":{"id":35,"text":"Software Release"},"url":"https://doi.org/10.5066/P9DBLL43","text":"USGS software release","linkHelpText":"- U.S. Geological Survey Hydrologic Toolbox software archive"}],"contact":"<p><a href=\"mailto:dc_nweng@usgs.gov\" data-mce-href=\"mailto:dc_nweng@usgs.gov\">Director</a>, <a href=\"https://www.usgs.gov/centers/new-england-water\" data-mce-href=\"https://www.usgs.gov/centers/new-england-water\">New England Water Science Center</a><br>U.S. Geological Survey<br>10 Bearfoot Road<br>Northborough, MA 01532</p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Building, Saving, and Reopening a Hydrologic Toolbox Project</li><li>Downloading, Opening, and Managing Data</li><li>Time-Series Tools</li><li>Groundwater (GW) Tools</li><li>Surface-Water (SW) Tools</li><li>Summary</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"publishedDate":"2022-05-04","noUsgsAuthors":false,"publicationDate":"2022-05-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Barlow, Paul M. 0000-0003-4247-6456 pbarlow@usgs.gov","orcid":"https://orcid.org/0000-0003-4247-6456","contributorId":1200,"corporation":false,"usgs":true,"family":"Barlow","given":"Paul","email":"pbarlow@usgs.gov","middleInitial":"M.","affiliations":[{"id":493,"text":"Office of Ground Water","active":true,"usgs":true}],"preferred":true,"id":841871,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McHugh, Amy R. 0000-0002-7745-9886","orcid":"https://orcid.org/0000-0002-7745-9886","contributorId":205491,"corporation":false,"usgs":true,"family":"McHugh","given":"Amy R.","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":841872,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kiang, Julie E. 0000-0003-0653-4225 jkiang@usgs.gov","orcid":"https://orcid.org/0000-0003-0653-4225","contributorId":2179,"corporation":false,"usgs":true,"family":"Kiang","given":"Julie","email":"jkiang@usgs.gov","middleInitial":"E.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"preferred":true,"id":841873,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Zhai, Tong","contributorId":291242,"corporation":false,"usgs":false,"family":"Zhai","given":"Tong","affiliations":[{"id":36536,"text":"RESPEC","active":true,"usgs":false}],"preferred":false,"id":841874,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hummel, Paul","contributorId":291243,"corporation":false,"usgs":false,"family":"Hummel","given":"Paul","affiliations":[{"id":36536,"text":"RESPEC","active":true,"usgs":false}],"preferred":false,"id":841875,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Duda, Paul","contributorId":291244,"corporation":false,"usgs":false,"family":"Duda","given":"Paul","email":"","affiliations":[{"id":36536,"text":"RESPEC","active":true,"usgs":false}],"preferred":false,"id":841876,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hinz, Scott","contributorId":291245,"corporation":false,"usgs":false,"family":"Hinz","given":"Scott","email":"","affiliations":[{"id":18005,"text":"LimnoTech","active":true,"usgs":false}],"preferred":false,"id":841877,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70231263,"text":"fs20223024 - 2022 - Hawaii and Landsat","interactions":[],"lastModifiedDate":"2022-09-27T12:12:48.835499","indexId":"fs20223024","displayToPublicDate":"2022-05-04T11:10:31","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2022-3024","displayTitle":"Hawaii and Landsat","title":"Hawaii and Landsat","docAbstract":"<p>Hawaii stands apart from the rest of the United States, literally and figuratively. The nearest of the eight islands that make up the Hawaiian archipelago is 2,000 miles from the U.S. mainland. Like every bit of land mass within the State, it emerged from the Pacific Ocean after thousands of years of undersea volcanic activity. Kona International Airport, on the “Big Island” of Hawai‘i, was built atop 220-year-old lava flows from the Hualālai volcano.</p><p>The volcanic soils and tropical vegetation that stretch across Hawaii’s postcard-perfect peaks and valleys, as well as the trade winds that blow precipitation northeast across the islands and the warm Kona winds that move in from the south, are among the factors that make the study of the State’s landscapes distinct from the rest of the Nation.</p><p>Six active volcanoes continue to alter the land surface. Some of them, like the constantly erupting Kīlauea or Mauna Loa, the world’s largest active volcano, can threaten human life and property. Man-made changes to the islands, such as the long-term agricultural production of sugar cane or pineapple, along with the introduction of non-native species, have also affected the health of the State’s ecosystems.</p><p>Landsat satellites, with 50 years of repeat Earth observations and decades of data from infrared and thermal instruments capable of tracking lava flows, can offer unique opportunities for the study of Hawaii’s ever-changing landscapes. Here are a few examples of how Landsat benefits the State.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20223024","usgsCitation":"U.S. Geological Survey, 2022, Hawaii and Landsat: U.S. Geological Survey Fact Sheet 2022–3024, 2 p., https://doi.org/10.3133/fs20223024.","productDescription":"2 p.","numberOfPages":"2","onlineOnly":"N","ipdsId":"IP-140071","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":400152,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/fs20223024/full","text":"Report","linkFileType":{"id":5,"text":"html"}},{"id":400123,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/fs/2022/3024/images"},{"id":400121,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2022/3024/fs20223024.pdf","text":"Report","size":"3.23 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 \"}}]}","contact":"<p>Program Coordinator, <a href=\"https://www.usgs.gov/core-science-systems/national-land-imaging-program\" data-mce-href=\"https://www.usgs.gov/core-science-systems/national-land-imaging-program\">National Land Imaging Program</a> <br>U.S. Geological Survey <br>12201 Sunrise Valley Drive <br>Reston, VA 20192</p><p><a href=\"https://pubs.er.usgs.gov/contact\" data-mce-href=\"../contact\">Contact Pubs Warehouse</a></p>","tableOfContents":"<ul><li>Tracking Lava Flows from Space</li><li>Monitoring Land Change Patterns</li><li>Mapping Land Conditions</li><li>Landsat—Critical Information Infrastructure for the Nation</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2022-05-04","noUsgsAuthors":false,"publicationDate":"2022-05-04","publicationStatus":"PW","contributors":{"authors":[{"text":"U.S. Geological Survey","contributorId":127955,"corporation":true,"usgs":false,"organization":"U.S. Geological Survey","id":842157,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70250315,"text":"70250315 - 2022 - Ignoring species availability biases occupancy estimates in single-scale occupancy models","interactions":[],"lastModifiedDate":"2023-12-07T14:08:48.423205","indexId":"70250315","displayToPublicDate":"2022-05-04T09:34:44","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2717,"text":"Methods in Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Ignoring species availability biases occupancy estimates in single-scale occupancy models","docAbstract":"<ol class=\"\"><li>Most applications of single-scale occupancy models do not differentiate between availability and detectability, even though species availability is rarely equal to one. Species availability can be estimated using multi-scale occupancy models; however, for the practical application of multi-scale occupancy models, it can be unclear what a robust sampling design looks like and what the statistical properties of the multi-scale and single-scale occupancy models are when availability is less than one.</li><li>Using simulations, we explore the following common questions asked by ecologists during the design phase of a field study: (Q1) what is a robust sampling design for the multi-scale occupancy model when there are a priori expectations of parameter estimates? (Q2) what is a robust sampling design when we have no expectations of parameter estimates? and (Q3) can a single-scale occupancy model with a random effects term adequately absorb the extra heterogeneity produced when availability is less than one and provide reliable estimates of occupancy probability?</li><li>Our results show that there is a tradeoff between the number of sites and surveys needed to achieve a specified level of acceptable error for occupancy estimates using the multi-scale occupancy model. We also document that when species availability is low (&lt;0.40 on the probability scale), then single-scale occupancy models underestimate occupancy by as much as 0.40 on the probability scale, produce overly precise estimates, and provide poor parameter coverage. This pattern was observed when a random effects term was and was not included in the single-scale occupancy model, suggesting that adding a random-effects term does not adequately absorb the extra heterogeneity produced by the availability process. In contrast, when species availability was high (&gt;0.60), single-scale occupancy models performed similarly to the multi-scale occupancy model.</li><li>Users can further explore our results and sampling designs across a number of different scenarios using the RShiny app<span>&nbsp;</span><a class=\"linkBehavior\" href=\"https://gdirenzo.shinyapps.io/multi-scale-occ/\" data-mce-href=\"https://gdirenzo.shinyapps.io/multi-scale-occ/\">https://gdirenzo.shinyapps.io/multi-scale-occ/</a>. Our results suggest that unaccounted for availability can lead to underestimating species distributions when using single-scale occupancy models, which can have large implications on inference and prediction, especially for those working in the fields of invasion ecology, disease emergence, and species conservation.</li></ol>","language":"English","publisher":"British Ecological Society","doi":"10.1111/2041-210X.13881","usgsCitation":"DiRenzo, G.V., David A. W. Miller, and Campbell Grant, E.H., 2022, Ignoring species availability biases occupancy estimates in single-scale occupancy models: Methods in Ecology and Evolution, v. 13, no. 8, p. 1790-1804, https://doi.org/10.1111/2041-210X.13881.","productDescription":"15 p.","startPage":"1790","endPage":"1804","ipdsId":"IP-130185","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true},{"id":37273,"text":"Advanced Research Computing (ARC)","active":true,"usgs":true}],"links":[{"id":502598,"rank":2,"type":{"id":41,"text":"Open Access External Repository Page"},"text":"External Repository"},{"id":423175,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"13","issue":"8","noUsgsAuthors":false,"publicationDate":"2022-05-17","publicationStatus":"PW","contributors":{"authors":[{"text":"DiRenzo, Graziella Vittoria 0000-0001-5264-4762","orcid":"https://orcid.org/0000-0001-5264-4762","contributorId":243404,"corporation":false,"usgs":true,"family":"DiRenzo","given":"Graziella","email":"","middleInitial":"Vittoria","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":889421,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"David A. W. Miller","contributorId":332097,"corporation":false,"usgs":false,"family":"David A. W. Miller","affiliations":[{"id":36985,"text":"Penn State University","active":true,"usgs":false}],"preferred":false,"id":889422,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Campbell Grant, Evan H. 0000-0003-4401-6496 ehgrant@usgs.gov","orcid":"https://orcid.org/0000-0003-4401-6496","contributorId":150443,"corporation":false,"usgs":true,"family":"Campbell Grant","given":"Evan","email":"ehgrant@usgs.gov","middleInitial":"H.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":889423,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70231288,"text":"70231288 - 2022 - Implementing landscape connectivity with topographic filtering model: A simulation of suspended sediment delivery in an agricultural watershed","interactions":[],"lastModifiedDate":"2022-05-13T15:24:40.403273","indexId":"70231288","displayToPublicDate":"2022-05-04T08:57:49","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Implementing landscape connectivity with topographic filtering model: A simulation of suspended sediment delivery in an agricultural watershed","docAbstract":"<p><span>The widespread availability of high-fidelity topography combined with advances in geospatial analysis offer the opportunity to reimagine approaches to the difficult problem of predicting sediment delivery from watersheds. Here we present a model that uses high-resolution topography to filter sediment sources to quantify sediment delivery to the watershed outlet. It is a reduced-complexity, top-down model that defines transfer functions—topographic filters—between spatially distributed sediment sources and spatially integrated sediment delivery. The goal of the model is to forecast changes in watershed suspended sediment delivery in response to spatially distributed changes in sediment source magnitude or delivery, whether a result of watershed drivers or intentional management actions. Such an application requires the context of a watershed model that accounts for all sediment sources, enforces sediment mass balance throughout the spatial domain, and accommodates sediment storage and delivery over time. The model is developed for a HUC-8 watershed with a flat upland dominated by corn-soybean agriculture and deeply incised valleys near the watershed outlet with large sediment contributions from near-channel sources. Topofilter computes delivery and storage of field-derived sediment according to its spatial and structural connectivity to the stream channel network; subsequently, delivery of both field- and near-channel-derived sediment along with floodplain storage are computed in the stream channel network to the watershed outlet. The model outputs provide a spatially rich representation of sediment delivery and storage on field and along the stream that is consistent with available independent information on sediment accumulations and fluxes. Rather than a single best-calibrated solution, Topofilter uses the Generalized Likelihood Uncertainty Estimate (GLUE) approach to develop many possible solutions with sediment delivery rates expressed as probability distributions across the watershed. The ensemble of simulation outputs provides a useful basis for estimating uncertainty in sediment delivery and the effectiveness of different landscape management allocation across a watershed.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2022.155701","usgsCitation":"Cho, J., Wilcock, P.R., and Gran, K.B., 2022, Implementing landscape connectivity with topographic filtering model: A simulation of suspended sediment delivery in an agricultural watershed: Science of the Total Environment, v. 836, 155701, 16 p., https://doi.org/10.1016/j.scitotenv.2022.155701.","productDescription":"155701, 16 p.","ipdsId":"IP-127448","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":447923,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2022.155701","text":"Publisher Index Page"},{"id":400202,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Minnesota","otherGeospatial":"Le Sueur River basin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -94.46868896484375,\n              43.61619382369185\n            ],\n            [\n              -93.087158203125,\n              43.61619382369185\n            ],\n            [\n              -93.087158203125,\n              44.27273816279087\n            ],\n            [\n              -94.46868896484375,\n              44.27273816279087\n            ],\n            [\n              -94.46868896484375,\n              43.61619382369185\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"836","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Cho, Jong 0000-0001-5514-6056","orcid":"https://orcid.org/0000-0001-5514-6056","contributorId":291384,"corporation":false,"usgs":true,"family":"Cho","given":"Jong","email":"","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":842241,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wilcock, Peter R 0000-0001-5756-9829","orcid":"https://orcid.org/0000-0001-5756-9829","contributorId":291385,"corporation":false,"usgs":false,"family":"Wilcock","given":"Peter","email":"","middleInitial":"R","affiliations":[{"id":6682,"text":"Utah State University","active":true,"usgs":false}],"preferred":false,"id":842242,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gran, Karen B.","contributorId":288093,"corporation":false,"usgs":false,"family":"Gran","given":"Karen","email":"","middleInitial":"B.","affiliations":[{"id":6915,"text":"University of Minnesota - Duluth","active":true,"usgs":false}],"preferred":true,"id":842243,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70231237,"text":"fs20223025 - 2022 - Pennsylvania and Landsat","interactions":[],"lastModifiedDate":"2022-09-27T12:13:22.17303","indexId":"fs20223025","displayToPublicDate":"2022-05-04T08:45:52","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2022-3025","displayTitle":"Pennsylvania and Landsat","title":"Pennsylvania and Landsat","docAbstract":"<p>The Commonwealth of Pennsylvania straddles an array of landscapes. From east to west, its 46,055 square miles connect the sea-level lowlands of the Atlantic seaboard with the rolling hills of the Midwest. It also acts as a bridge between regions from north to south, with the Appalachian Mountains swooping through its center from its northern border with New York to its southern borders with Maryland and West Virginia.</p><p>The Declaration of Independence and U.S. Constitution were signed in the Commonwealth’s largest city, Philadelphia, and it was the second of the original 13 colonies to ratify the Constitution. The pivotal Civil War battle of Gettysburg took place in the southern part of Pennsylvania. Western Pennsylvania was an early hub for the coal, oil, and steel industries that fueled the Nation’s growth in the 20th century and still factor into Pennsylvania’s economy. The varied natural features of Pennsylvania have been an important proving ground for the value of satellite imagery from the USGS Landsat Program. Scientists began to lean on Landsat observations early in the program’s history to map the effect of invasive moths on Commonwealth forests. That activity continues to this day. Space-based imagery has also contributed to the study and management of land change from energy development, urban growth, and shifting land use patterns.</p><p>The Landsat Program’s unparalleled 50-year archive of repeat Earth observations remains a critical public resource for Pennsylvania as climate change and land use patterns present new challenges to land managers and urban planners in the Keystone State.</p><p>Here are just a few examples of how Landsat has benefited Pennsylvania.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20223025","usgsCitation":"U.S. Geological Survey, 2022, Pennsylvania and Landsat: U.S. Geological Survey Fact Sheet 2022–3025, 2 p., https://doi.org/10.3133/fs20223025.","productDescription":"2 p.","numberOfPages":"2","onlineOnly":"N","ipdsId":"IP-140045","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) 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 \"}}]}","contact":"<p>Program Coordinator, <a href=\"https://www.usgs.gov/core-science-systems/national-land-imaging-program\" data-mce-href=\"https://www.usgs.gov/core-science-systems/national-land-imaging-program\">National Land Imaging Program</a> <br>U.S. Geological Survey <br>12201 Sunrise Valley Drive <br>Reston, VA 20192</p><p><a href=\"https://pubs.er.usgs.gov/contact\" data-mce-href=\"../contact\">Contact Pubs Warehouse</a></p>","tableOfContents":"<ul><li>Watching Over the Forests</li><li>Mapping the Past, Sketching the Future</li><li>Tracking Change from the Energy Industry</li><li>Landsat—Critical Information Infrastructure for the Nation</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2022-05-04","noUsgsAuthors":false,"publicationDate":"2022-05-04","publicationStatus":"PW","contributors":{"authors":[{"text":"U.S. Geological Survey","contributorId":147999,"corporation":true,"usgs":false,"organization":"U.S. Geological Survey","id":842114,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70231238,"text":"70231238 - 2022 - Amphibian mucus triggers a developmental transition in the frog-killing chytrid fungus","interactions":[],"lastModifiedDate":"2022-07-07T16:55:24.723137","indexId":"70231238","displayToPublicDate":"2022-05-04T08:40:27","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1352,"text":"Current Biology","active":true,"publicationSubtype":{"id":10}},"title":"Amphibian mucus triggers a developmental transition in the frog-killing chytrid fungus","docAbstract":"<p>The frog-killing chytrid fungus<span>&nbsp;</span><span><i>Batrachochytrium dendrobatidis</i></span><span>&nbsp;</span>(<i>Bd</i>) is decimating amphibian populations around the world.<span>&nbsp;</span><i>Bd</i><span>&nbsp;has a biphasic life cycle, alternating between motile&nbsp;zoospores&nbsp;that disperse within&nbsp;aquatic environments&nbsp;and sessile&nbsp;sporangia&nbsp;that grow within the mucus-coated skin of amphibians.</span><span>&nbsp;</span>Zoospores lack cell walls and swim rapidly through aquatic environments using a posterior flagellum and crawl across solid surfaces using actin structures similar to those of human cells.<span>&nbsp;</span><i>Bd</i><span>&nbsp;transitions from this motile dispersal form to its reproductive form by absorbing its flagellum, rearranging its&nbsp;actin cytoskeleton, and rapidly building a chitin-based cell wall—a process called “encystation.”</span><span>&nbsp;The resulting sporangium increases in volume by two or three orders of magnitude while undergoing rounds of mitosis without&nbsp;cytokinesis&nbsp;to form a large ceonocyte. The sporangium then cellurizes by dividing its cytoplasm into dozens of new zoospores. After exiting the sporangium through a discharge tube onto the amphibian skin, daughter zoospores can then reinfect the same individual or find a new host.</span><span>&nbsp;</span>Although encystation is critical to<span>&nbsp;</span><i>Bd</i><span>&nbsp;growth, whether and how this developmental transition is triggered by external signals was previously unknown. We discovered that exposure to amphibian mucus triggers rapid and reproducible encystation within minutes. This response can be recapitulated with purified mucin, the bulk component of mucus, but not by similarly viscous&nbsp;methylcellulose&nbsp;or&nbsp;simple sugars. Mucin-induced encystation does not require gene expression but does require surface adhesion,&nbsp;calcium signaling, and modulation of the actin cytoskeleton. Mucus-induced encystation may represent a key mechanism for synchronizing&nbsp;</span><i>Bd</i><span>&nbsp;</span>development with the arrival at the host.</p>","language":"English","publisher":"Cell Press","doi":"10.1016/j.cub.2022.04.006","usgsCitation":"Robinson, K.A., Prostak, S.M., Campbell Grant, E.H., and Fritz-Laylin, L.K., 2022, Amphibian mucus triggers a developmental transition in the frog-killing chytrid fungus: Current Biology, v. 32, no. 12, p. 2765-2771.e4, https://doi.org/10.1016/j.cub.2022.04.006.","productDescription":"12 p.","startPage":"2765","endPage":"2771.e4","ipdsId":"IP-139126","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":447925,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.cub.2022.04.006","text":"Publisher Index Page"},{"id":400128,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"32","issue":"12","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Robinson, Kristyn A.","contributorId":291342,"corporation":false,"usgs":false,"family":"Robinson","given":"Kristyn","email":"","middleInitial":"A.","affiliations":[{"id":6932,"text":"University of Massachusetts, Amherst","active":true,"usgs":false}],"preferred":false,"id":842115,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Prostak, Sarah M.","contributorId":291343,"corporation":false,"usgs":false,"family":"Prostak","given":"Sarah","email":"","middleInitial":"M.","affiliations":[{"id":6932,"text":"University of Massachusetts, Amherst","active":true,"usgs":false}],"preferred":false,"id":842116,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Campbell Grant, Evan H. 0000-0003-4401-6496 ehgrant@usgs.gov","orcid":"https://orcid.org/0000-0003-4401-6496","contributorId":150443,"corporation":false,"usgs":true,"family":"Campbell Grant","given":"Evan","email":"ehgrant@usgs.gov","middleInitial":"H.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":842117,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fritz-Laylin, Lillian K.","contributorId":291345,"corporation":false,"usgs":false,"family":"Fritz-Laylin","given":"Lillian","email":"","middleInitial":"K.","affiliations":[{"id":6932,"text":"University of Massachusetts, Amherst","active":true,"usgs":false}],"preferred":false,"id":842118,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70236140,"text":"70236140 - 2022 - Standard atomic weights of the elements 2021 (IUPAC Technical Report)","interactions":[],"lastModifiedDate":"2022-08-31T11:01:43.760813","indexId":"70236140","displayToPublicDate":"2022-05-04T08:13:46","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3207,"text":"Pure and Applied Chemistry","active":true,"publicationSubtype":{"id":10}},"title":"Standard atomic weights of the elements 2021 (IUPAC Technical Report)","docAbstract":"<p>Following the reviews of atomic-weight determinations and other cognate data in 2015, 2017, 2019 and 2021, the IUPAC (International Union of Pure and Applied Chemistry) Commission on Isotopic Abundances and Atomic Weights (CIAAW) reports changes of standard atomic weights. The symbol<span>&nbsp;</span><i>A</i><span>&nbsp;</span><sub>r</sub>°(E) was selected for standard atomic weight of an element to distinguish it from the atomic weight of an element E in a specific substance P, designated<span>&nbsp;</span><i>A</i><span>&nbsp;</span><sub>r</sub>(E, P). The CIAAW has changed the values of the standard atomic weights of five elements based on recent determinations of terrestrial isotopic abundances:</p><p><br></p><div id=\"j_pac-2019-0603_tab_101\" class=\"table-wrap\"><table class=\"content-table mce-item-table\" border=\"0\" frame=\"hsides\" rules=\"groups\"><colgroup><col align=\"left\"><col align=\"left\"><col align=\"left\"><col align=\"left\"></colgroup><tbody><tr><td>Ar (argon):</td><td>from 39.948&nbsp;±&nbsp;0.001</td><td>to</td><td>[39.792, 39.963]</td></tr><tr><td>Hf (hafnium):</td><td>from 178.49&nbsp;±&nbsp;0.02</td><td>to</td><td>178.486&nbsp;±&nbsp;0.006</td></tr><tr><td>Ir (iridium):</td><td>from 192.217&nbsp;±&nbsp;0.003</td><td>to</td><td>192.217&nbsp;±&nbsp;0.002</td></tr><tr><td>Pb (lead):</td><td>from 207.2&nbsp;±&nbsp;0.1</td><td>to</td><td>[206.14, 207.94]</td></tr><tr><td>Yb (ytterbium):</td><td>from 173.054&nbsp;±&nbsp;0.005</td><td>to</td><td>173.045&nbsp;±&nbsp;0.010</td></tr></tbody></table></div><p><br></p><p>The standard atomic weight of argon and lead have changed to an interval to reflect that the natural variation in isotopic composition exceeds the measurement uncertainty of<span>&nbsp;</span><i>A</i><span>&nbsp;</span><sub>r</sub>(Ar) and<span>&nbsp;</span><i>A</i><span>&nbsp;</span><sub>r</sub>(Pb) in a specific substance. The standard atomic weights and/or the uncertainties of fourteen elements have been changed based on the Atomic Mass Evaluations 2016 and 2020 accomplished under the auspices of the International Union of Pure and Applied Physics (IUPAP).<span>&nbsp;</span><i>A</i><span>&nbsp;</span><sub>r</sub>° of Ho, Tb, Tm and Y were changed in 2017 and again updated in 2021:</p><p><br></p><div id=\"j_pac-2019-0603_tab_102\" class=\"table-wrap\"><table class=\"content-table mce-item-table\" border=\"0\" frame=\"hsides\" rules=\"groups\"><colgroup><col align=\"left\"><col align=\"left\"><col align=\"left\"><col align=\"left\"></colgroup><tbody><tr><td>Al (aluminium), 2017:</td><td>from 26.981&nbsp;5385&nbsp;±&nbsp;0.000&nbsp;0007</td><td>to</td><td>26.981&nbsp;5384&nbsp;±&nbsp;0.000&nbsp;0003</td></tr><tr><td>Au (gold), 2017:</td><td>from 196.966&nbsp;569&nbsp;±&nbsp;0.000&nbsp;005</td><td>to</td><td>196.966&nbsp;570&nbsp;±&nbsp;0.000&nbsp;004</td></tr><tr><td>Co (cobalt), 2017:</td><td>from 58.933&nbsp;194&nbsp;±&nbsp;0.000&nbsp;004</td><td>to</td><td>58.933&nbsp;194&nbsp;±&nbsp;0.000&nbsp;003</td></tr><tr><td>F (fluorine), 2021:</td><td>from 18.998&nbsp;403&nbsp;163&nbsp;±&nbsp;0.000&nbsp;000&nbsp;006</td><td>to</td><td>18.998&nbsp;403&nbsp;162&nbsp;±&nbsp;0.000&nbsp;000&nbsp;005</td></tr><tr><td>(Ho (holmium), 2017:</td><td>from 164.930&nbsp;33&nbsp;±&nbsp;0.000&nbsp;02</td><td>to</td><td>164.930&nbsp;328&nbsp;±&nbsp;0.000&nbsp;007)</td></tr><tr><td>Ho (holmium), 2021:</td><td>from 164.930&nbsp;328&nbsp;±&nbsp;0.000&nbsp;007</td><td>to</td><td>164.930&nbsp;329&nbsp;±&nbsp;0.000&nbsp;005</td></tr><tr><td>Mn (manganese), 2017:</td><td>from 54.938&nbsp;044&nbsp;±&nbsp;0.000&nbsp;003</td><td>to</td><td>54.938&nbsp;043&nbsp;±&nbsp;0.000&nbsp;002</td></tr><tr><td>Nb (niobium), 2017:</td><td>from 92.906&nbsp;37&nbsp;±&nbsp;0.000&nbsp;02</td><td>to</td><td>92.906&nbsp;37&nbsp;±&nbsp;0.000&nbsp;01</td></tr><tr><td>Pa (protactinium), 2017:</td><td>from 231.035&nbsp;88&nbsp;±&nbsp;0.000&nbsp;02</td><td>to</td><td>231.035&nbsp;88&nbsp;±&nbsp;0.000&nbsp;01</td></tr><tr><td>Pr (praseodymium), 2017:</td><td>from 140.907&nbsp;66&nbsp;±&nbsp;0.000&nbsp;02</td><td>to</td><td>140.907&nbsp;66&nbsp;±&nbsp;0.000&nbsp;01</td></tr><tr><td>Rh (rhodium), 2017:</td><td>from 102.905&nbsp;50&nbsp;±&nbsp;0.000&nbsp;02</td><td>to</td><td>102.905&nbsp;49&nbsp;±&nbsp;0.000&nbsp;02</td></tr><tr><td>Sc (scandium), 2021:</td><td>from 44.955&nbsp;908&nbsp;±&nbsp;0.000&nbsp;005</td><td>to</td><td>44.955&nbsp;907&nbsp;±&nbsp;0.000&nbsp;004</td></tr><tr><td>(Tb (terbium), 2017:</td><td>from 158.925&nbsp;35&nbsp;±&nbsp;0.000&nbsp;02</td><td>to</td><td>158.925&nbsp;354&nbsp;±&nbsp;0.000&nbsp;008)</td></tr><tr><td>Tb (terbium), 2021:</td><td>from 158.925&nbsp;354&nbsp;±&nbsp;0.000&nbsp;008</td><td>to</td><td>158.925&nbsp;354&nbsp;±&nbsp;0.000&nbsp;007</td></tr><tr><td>(Tm (thulium), 2017:</td><td>from 168.934&nbsp;22&nbsp;±&nbsp;0.000&nbsp;02</td><td>to</td><td>168.934&nbsp;218&nbsp;±&nbsp;0.000&nbsp;006)</td></tr><tr><td>Tm (thulium), 2021:</td><td>from 168.934&nbsp;218&nbsp;±&nbsp;0.000&nbsp;006</td><td>to</td><td>168.934&nbsp;219&nbsp;±&nbsp;0.000&nbsp;005</td></tr><tr><td>(Y (yttrium), 2017:</td><td>from 88.905&nbsp;84&nbsp;±&nbsp;0.000&nbsp;02</td><td>to</td><td>88.905&nbsp;84&nbsp;±&nbsp;0.000&nbsp;01)</td></tr><tr><td>Y (yttrium), 2021:</td><td>from 88.905&nbsp;84&nbsp;±&nbsp;0.000&nbsp;01</td><td>to</td><td>88.905&nbsp;838&nbsp;±&nbsp;0.000&nbsp;002</td></tr></tbody></table></div>","language":"English","publisher":"De Gruyter","doi":"10.1515/pac-2019-0603","usgsCitation":"Prohaska, T., Irrgeher, J., Benefield, J., Bohlke, J., Chesson, L., Coplen, T.B., Ding, T., Dunn, P., Groning, M., Holden, N.E., Meijer, H.A., Moossen, H., Possolo, A., Takahashi, Y., Vogl, J., Walczyk, T., Wang, J., Wieser, M.E., Yoneda, S., Zhu, X., and Meija, J., 2022, Standard atomic weights of the elements 2021 (IUPAC Technical Report): Pure and Applied Chemistry, v. 94, no. 5, https://doi.org/10.1515/pac-2019-0603.","productDescription":"28 p.","endPage":"573","numberOfPages":"600","ipdsId":"IP-116706","costCenters":[{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true}],"links":[{"id":447928,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1515/pac-2019-0603","text":"Publisher Index Page"},{"id":405897,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"94","issue":"5","noUsgsAuthors":false,"publicationDate":"2022-05-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Prohaska, Thomas 0000-0001-9367-8141","orcid":"https://orcid.org/0000-0001-9367-8141","contributorId":295932,"corporation":false,"usgs":false,"family":"Prohaska","given":"Thomas","email":"","affiliations":[{"id":63944,"text":"Montanuniversität Leoben, Leoben, Austria","active":true,"usgs":false}],"preferred":false,"id":850207,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Irrgeher, Johanna","contributorId":176643,"corporation":false,"usgs":false,"family":"Irrgeher","given":"Johanna","email":"","affiliations":[],"preferred":false,"id":850208,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Benefield, Jacqueline 0000-0001-9124-2424 jbenefield@usgs.gov","orcid":"https://orcid.org/0000-0001-9124-2424","contributorId":190135,"corporation":false,"usgs":true,"family":"Benefield","given":"Jacqueline","email":"jbenefield@usgs.gov","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true}],"preferred":true,"id":850209,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bohlke, J.K. 0000-0001-5693-6455 jkbohlke@usgs.gov","orcid":"https://orcid.org/0000-0001-5693-6455","contributorId":191103,"corporation":false,"usgs":true,"family":"Bohlke","given":"J.K.","email":"jkbohlke@usgs.gov","affiliations":[{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":850210,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Chesson, Lesley 0000-0002-8457-9341","orcid":"https://orcid.org/0000-0002-8457-9341","contributorId":295933,"corporation":false,"usgs":false,"family":"Chesson","given":"Lesley","email":"","affiliations":[{"id":63945,"text":"PAE, contractor at the Defense POW/MIA Accounting Agency (DPAA) Laboratory, Joint Base Pearl Harbor-Hickam, HI","active":true,"usgs":false}],"preferred":false,"id":850211,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Coplen, Tyler B. 0000-0003-4884-6008 tbcoplen@usgs.gov","orcid":"https://orcid.org/0000-0003-4884-6008","contributorId":508,"corporation":false,"usgs":true,"family":"Coplen","given":"Tyler","email":"tbcoplen@usgs.gov","middleInitial":"B.","affiliations":[{"id":37277,"text":"WMA - 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J.","affiliations":[{"id":63918,"text":"University of Groningen, Groningen, The Netherlands","active":true,"usgs":false}],"preferred":false,"id":850217,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Moossen, Heiko","contributorId":260393,"corporation":false,"usgs":false,"family":"Moossen","given":"Heiko","email":"","affiliations":[{"id":52579,"text":"Max Planck Institute for Biogeochemistry, Jena, Germany","active":true,"usgs":false}],"preferred":false,"id":850218,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Possolo, Antonio 0000-0002-8691-4190","orcid":"https://orcid.org/0000-0002-8691-4190","contributorId":295934,"corporation":false,"usgs":false,"family":"Possolo","given":"Antonio","email":"","affiliations":[{"id":63946,"text":"National Institute of Standards and Technology, Gaithersburg, MD","active":true,"usgs":false}],"preferred":false,"id":850219,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Takahashi, Yoshio 0000-0003-0707-8954","orcid":"https://orcid.org/0000-0003-0707-8954","contributorId":295935,"corporation":false,"usgs":false,"family":"Takahashi","given":"Yoshio","email":"","affiliations":[{"id":34822,"text":"University of Tokyo, Tokyo, JAPAN","active":true,"usgs":false}],"preferred":false,"id":850220,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Vogl, Jochen 0000-0002-0104-748X","orcid":"https://orcid.org/0000-0002-0104-748X","contributorId":295712,"corporation":false,"usgs":false,"family":"Vogl","given":"Jochen","email":"","affiliations":[{"id":63919,"text":"Bundesanstalt für Materialforschung und -prüfung (BAM), 12489 Berlin, Germany","active":true,"usgs":false}],"preferred":false,"id":850221,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Walczyk, Thomas","contributorId":222032,"corporation":false,"usgs":false,"family":"Walczyk","given":"Thomas","email":"","affiliations":[{"id":40477,"text":"Department of Chemistry and Department of Biochemistry, National University of Singapore, Singapore","active":true,"usgs":false}],"preferred":false,"id":850222,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Wang, Jun","contributorId":97457,"corporation":false,"usgs":false,"family":"Wang","given":"Jun","email":"","affiliations":[],"preferred":false,"id":850223,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Wieser, Michael E.","contributorId":197949,"corporation":false,"usgs":false,"family":"Wieser","given":"Michael","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":850224,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Yoneda, Shigekazu","contributorId":222033,"corporation":false,"usgs":false,"family":"Yoneda","given":"Shigekazu","email":"","affiliations":[{"id":40478,"text":"National Museum of Nature and Science, Tokyo, Japan","active":true,"usgs":false}],"preferred":false,"id":850225,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Zhu, Xiang-Kun 0000-0002-8407-6883","orcid":"https://orcid.org/0000-0002-8407-6883","contributorId":248595,"corporation":false,"usgs":false,"family":"Zhu","given":"Xiang-Kun","email":"","affiliations":[{"id":49957,"text":"Institute of Geology, Chinese Academy of Geological Sciences, Beijing 100037, China","active":true,"usgs":false}],"preferred":false,"id":850226,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"Meija, Juris 0000-0002-3349-5535","orcid":"https://orcid.org/0000-0002-3349-5535","contributorId":295936,"corporation":false,"usgs":false,"family":"Meija","given":"Juris","email":"","affiliations":[{"id":63948,"text":"National Research Council of Canada, Ottawa, Canada","active":true,"usgs":false}],"preferred":false,"id":850227,"contributorType":{"id":1,"text":"Authors"},"rank":21}]}}
,{"id":70231257,"text":"70231257 - 2022 - Surface parameters and bedrock properties covary across a mountainous watershed: Insights from machine learning and geophysics","interactions":[],"lastModifiedDate":"2022-05-04T13:25:52.650064","indexId":"70231257","displayToPublicDate":"2022-05-04T08:09:12","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5010,"text":"Science Advances","active":true,"publicationSubtype":{"id":10}},"title":"Surface parameters and bedrock properties covary across a mountainous watershed: Insights from machine learning and geophysics","docAbstract":"<p>Bedrock property quantification is critical for predicting the hydrological response of watersheds to climate disturbances. Estimating bedrock hydraulic properties over watershed scales is inherently difficult, particularly in fracture-dominated regions. Our analysis tests the covariability of above- and belowground features on a watershed scale, by linking borehole geophysical data, near-surface geophysics, and remote sensing data. We use machine learning to quantify the relationships between bedrock geophysical/hydrological properties and geomorphological/vegetation indices and show that machine learning relationships can estimate most of their covariability. Although we can predict the electrical resistivity variation across the watershed, regions of lower variability in the input parameters are shown to provide better estimates, indicating a limitation of commonly applied geomorphological models. Our results emphasize that such an integrated approach can be used to derive detailed bedrock characteristics, allowing for identification of small-scale variations across an entire watershed that may be critical to assess the impact of disturbances on hydrological systems.</p>","language":"English","publisher":"American Association for the Advancement of Science","doi":"10.1126/sciadv.abj2479","usgsCitation":"Uhlemann, S., Dafflon, B., Wainwright, H.M., Williams, K.H., Minsley, B.J., Zamudio, K.D., Carr, B., Falco, N., Ulrich, C., and Hubbard, S.S., 2022, Surface parameters and bedrock properties covary across a mountainous watershed: Insights from machine learning and geophysics: Science Advances, v. 8, no. 12, 15 p., https://doi.org/10.1126/sciadv.abj2479.","productDescription":"15 p.","ipdsId":"IP-134172","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":447933,"rank":0,"type":{"id":41,"text":"Open 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,{"id":70231476,"text":"70231476 - 2022 - Determination of optimal set of spatio-temporal features for predicting burn probability in the state of California, USA","interactions":[],"lastModifiedDate":"2022-05-11T12:07:04.245455","indexId":"70231476","displayToPublicDate":"2022-05-04T07:03:53","publicationYear":"2022","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Determination of optimal set of spatio-temporal features for predicting burn probability in the state of California, USA","docAbstract":"<div class=\"hlFld-Abstract\"><div class=\"article__section article__abstract hlFld-Abstract\"><div class=\"abstractSection abstractInFull\"><p>Wildfires play a critical role in determining ecosystem structure and function and pose serious risks to human life, property and ecosystem services. Burn probability (BP) models the likelihood that a location could burn. Simulation models are typically used to predict BP but are computationally intensive. Machine learning (ML) pipelines can predict BP and reduce computational intensity. In this work, we tested approaches to reduce the set of input features used in an ML model to estimate BP for the state of California, USA, without loss of predictive performance. We used Principal Component Analysis (PCA) to determine the optimal set of features to use in our ML pipeline. Then, we mapped BP and compared model performance when using the reduced set and when using the whole set of features. 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Center","active":true,"usgs":true}],"preferred":true,"id":842740,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70255095,"text":"70255095 - 2022 - Management goals for conserving White Sturgeon in the Sacramento-San Joaquin River basin","interactions":[],"lastModifiedDate":"2024-06-12T23:41:55.201627","indexId":"70255095","displayToPublicDate":"2022-05-03T18:40:10","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2287,"text":"Journal of Fish and Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Management goals for conserving White Sturgeon in the Sacramento-San Joaquin River basin","docAbstract":"<div id=\"15050063\" class=\"article-section-wrapper js-article-section js-content-section  \" data-section-parent-id=\"0\"><p>Management objectives for long-lived species are difficult to define because many taxa have delayed maturity and variable recruitment. White Sturgeon<span>&nbsp;</span><i>Acipenser transmontanus</i><span>&nbsp;</span>is an example of a species with a complex life history that complicates long-term status monitoring and establishment of management objectives. Historically, White Sturgeon in the Sacramento–San Joaquin River basin have been monitored by tracking the abundance of age-15 individuals as outlined by the Central Valley Project Improvement Act. However, infrequent recruitment complicates progress toward Central Valley Project Improvement Act management objectives because abundance of a single cohort fails to represent overall population trends. By using a Leslie population matrix, we demonstrate that the probability of reaching the Central Valley Project Improvement Act objective of 11,000 age-15 White Sturgeon is highly unlikely. We propose an alternative metric of 155,000 adults, which better represents overall population trends of White Sturgeon in the Sacramento–San Joaquin River basin, can be efficiently monitored, and can support both the goal of the Central Valley Project Improvement Act and management objectives.</p></div>","language":"English","publisher":"Allen Press","doi":"10.3996/JFWM-21-070","usgsCitation":"Ulaski, M., Blackburn, S., Jackson, Z., and Quist, M.C., 2022, Management goals for conserving White Sturgeon in the Sacramento-San Joaquin River basin: Journal of Fish and Wildlife Management, v. 13, no. 2, p. 334-343, https://doi.org/10.3996/JFWM-21-070.","productDescription":"10 p.","startPage":"334","endPage":"343","ipdsId":"IP-131268","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":447939,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3996/jfwm-21-070","text":"Publisher Index Page"},{"id":430058,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"13","issue":"2","noUsgsAuthors":false,"publicationDate":"2022-05-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Ulaski, Marta","contributorId":338595,"corporation":false,"usgs":false,"family":"Ulaski","given":"Marta","email":"","affiliations":[{"id":36394,"text":"University of Idaho","active":true,"usgs":false}],"preferred":false,"id":903385,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Blackburn, Shannon","contributorId":338596,"corporation":false,"usgs":false,"family":"Blackburn","given":"Shannon","affiliations":[{"id":36394,"text":"University of Idaho","active":true,"usgs":false}],"preferred":false,"id":903386,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jackson, Zachary","contributorId":338597,"corporation":false,"usgs":false,"family":"Jackson","given":"Zachary","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":903387,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Quist, Michael C. 0000-0001-8268-1839","orcid":"https://orcid.org/0000-0001-8268-1839","contributorId":207142,"corporation":false,"usgs":true,"family":"Quist","given":"Michael","middleInitial":"C.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":903388,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70231037,"text":"sir20225012 - 2022 - Refining sources of polychlorinated biphenyls in the Back River watershed, Baltimore, Maryland, 2018–2020","interactions":[],"lastModifiedDate":"2026-04-08T17:25:50.545381","indexId":"sir20225012","displayToPublicDate":"2022-05-03T13:30:00","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2022-5012","displayTitle":"Refining Sources of Polychlorinated Biphenyls in the Back River Watershed, Baltimore, Maryland, 2018–2020","title":"Refining sources of polychlorinated biphenyls in the Back River watershed, Baltimore, Maryland, 2018–2020","docAbstract":"<p>Older urban landscapes present unique and complex stressors to urban streams and their habitats through the introduction of legacy and emerging toxic contaminants. Contaminant sources are often associated with various developed land uses such as older residential areas, active and former industrial sites, contaminated sites, and effluents from municipal wastewater treatment plant discharges. These landscapes have a history of legacy contaminant use such as polychlorinated biphenyls (PCBs) resulting in impacts to sediment and water in these complex environments. Despite the ban of PCBs in new commercial use in 1979, PCB contamination is still widespread in the environment, with many fish consumption advisories throughout the Chesapeake Bay region based on elevated PCBs. Several watersheds in the Baltimore region have mandated reductions in PCBs per total maximum daily loads in tidal waters of the watersheds in order to promote compliance with water quality standards. Some of these mandated reductions (for example, regulated watershed runoff) specified in the total maximum daily loads are the responsibility of the local jurisdictions as part of their phase 1 National Pollutant Discharge Elimination System municipal separate storm sewer system permit. In cooperation with the Baltimore City Department of Public Works and Maryland Department of the Environment, the U.S. Geological Survey and University of Maryland, Baltimore County conducted a study from 2018 to 2020 to refine the sources of PCBs from the City of Baltimore into Back River and to use the results to improve the conceptual site model of PCBs in the Back River watershed.</p><p>PCB concentrations in the water column of the nontidal streams in Back River watershed are relatively consistent throughout both tributaries, with greater concentrations detected in samples collected from Moores Run but greater loads estimated in samples collected from Herring Run. PCB concentrations measured in the bed sediments and analysis of the flux between sediment porewater (hereafter porewater) and surface water within the tributaries suggest that there are no stationary legacy sources within the stream channels.</p><p>The bulk of PCB mass entering the system from these nontidal tributaries appears to be introduced primarily during storm events. While only one storm event was sampled and concentrations were quantified only in Herring Run, solids captured during the storm were characterized by increases in PCB mass and overall suspended solids concentrations. Although the bioavailability of the PCB-associated sediment is unknown, this mechanism appears to warrant additional attention to better understand how concentrations vary under different storm conditions and temporally. The importance of contaminated stormwater in loading to Herring Run is further supported by the PCB concentrations in storm drain sediments collected near the tributary, which were present in higher concentrations and were characterized by different homolog signatures compared to that in bed sediments.</p><p>The observations in the tributaries differed from PCB concentrations and sediment characteristics downstream from the City of Baltimore boundary, in the upper tidal area of the main stem of Back River, particularly at the passive sampler locations BRT–1 and BRT–3. This depositional environment is characterized by higher organic content in sediments and higher concentrations of PCBs in porewater, which result in the possible flux of contaminants from sediment to the water column. This flux is generally opposite of that observed in the nontidal tributaries and the farthest upstream tidal site (BRT–2) and may be a result of the possible settling of sediment particles introduced via suspended solids in stormwater.</p><p>Despite an observed considerable reduction in overall PCB mass loading to and from the Back River Wastewater Treatment Plant (BRWWTP) (and similar reductions observed in biosolids) compared to the estimates previously reported from 2015, effluent from the BRWWTP continues to be a primary source of PCBs to Back River. The current study confirmed the likeliness of fat, oil, and grease deposits within the miles of sewer pipe as a source of PCBs to the BRWWTP influent. The differences between PCB concentrations in fat, oil, and grease deposits found in pipes (during replacement) compared to that of the BRWWTP suggest that legacy deposits may contain higher PCB concentrations and may act as a source of PCBs to passing sewage, eventually entering the BRWWTP. Variation in freely dissolved concentrations in the sewer system was apparent through the analysis of PCBs in the primary pump stations using passive sampling, with the largest contribution to the influent attributed to a single pump station and associated piping.</p><p>The contribution of PCBs to Herring Run and Moores Run via sanitary sewer overflows compared to the BRWWTP effluent is negligible, similar to reports from another large urban wastewater treatment plant. Therefore, decreased occurrence of sanitary sewer overflows is not expected to largely decrease PCB loads.</p><p>Results of this study suggest that targeted, sediment-capture best management practices in Back River watershed could be an effective way to reduce PCB mass loading assuming that deposited contaminated sediments are effectively isolated. Recent studies of some common urban best management practices such as bioretention have shown removal of PCBs within the stormwater control structures. In addition, appropriately timed street sweeping practices with appropriate collection equipment may be an effective way to reduce contaminants such as PCBs from road runoff sources. Reductions in concentrations and mass loading within the sewer system measured in this study compared to that estimated 5 years prior reflect the possible success of ongoing gray infrastructure management actions. Reductions may be attributable to enhanced nutrient reduction upgrades to the BRWWTP and extensive capital improvements and maintenance to the sewer system.</p><p>This study employed a combined sampling approach and a variety of sampling methods to include low-density polyethylene passive samplers, high-volume water samples, and grab samples of both water and sediment to characterize the PCB inputs to Herring Run, Moores Run, and Back River. Incorporating the passive samplers provided a time-weighted average of the freely dissolved concentration in the surface water, porewater, WWTP influent and effluent, and pump station influent over the deployment period with picogram per liter detection limits. A similar monitoring approach from this study could be implemented within other subwatersheds or municipal separate storm sewer system jurisdictions to assist in refining primary sources of PCBs in order to inform appropriate mitigation approaches.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225012","collaboration":"Prepared in cooperation with Baltimore City Department of Public Works and Maryland Department of the Environment","usgsCitation":"Majcher, E., Ghosh, U., Needham, T., Lombard, N., Foss, E., Bokare, M., Joshee, S., Cheung, L., Damond, J., and Lorah, M., 2022, Refining sources of polychlorinated biphenyls in the Back River watershed, Baltimore, Maryland, 2018–2020: U.S. Geological Survey Scientific Investigations Report 2022–5012, 58 p., https://doi.org/10.3133/sir20225012.","productDescription":"Report: x, 58 p.; Data Release","numberOfPages":"58","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-123587","costCenters":[{"id":41514,"text":"Maryland-Delaware-District of Columbia  Water Science Center","active":true,"usgs":true}],"links":[{"id":399906,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9WFDIBM","text":"USGS data release","linkHelpText":"Polychlorinated Biphenyl (PCB) Concentrations of Passive Samplers, Solids, Fat, Oil, and Greases (FOG), and Road Sediments; and Dissolved Organic Carbon (DOC), Total Suspended Solids (TSS), and Particulate Organic Carbon (POC) Concentrations in the Back River Watershed, Baltimore City, Maryland, 2018–2020"},{"id":399905,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5012/sir20225012.pdf","text":"Report","size":"79.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2022-5012"},{"id":399904,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5012/coverthb.jpg"},{"id":502298,"rank":4,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_112977.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Maryland","city":"Baltimore","otherGeospatial":"Back River watershed","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -76.84112548828125,\n              39.18969082109678\n            ],\n            [\n              -76.32202148437499,\n              39.18969082109678\n            ],\n            [\n              -76.32202148437499,\n              39.51675478434244\n            ],\n            [\n              -76.84112548828125,\n              39.51675478434244\n            ],\n            [\n              -76.84112548828125,\n              39.18969082109678\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p><a href=\"mailto:dc_md@usgs.gov\" data-mce-href=\"mailto:dc_md@usgs.gov\">Director</a>, <a href=\"https://www.usgs.gov/centers/md-de-dc-water\" data-mce-href=\"https://www.usgs.gov/centers/md-de-dc-water\">Maryland-Delaware-D.C. Water Science Center</a><br>U.S. Geological Survey<br>5522 Research Park Drive<br>Catonsville, MD 21228</p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Methods to Assess PCB Sources in Back River Watershed</li><li>Summary of Known PCB Sources to Back River</li><li>Assessment of PCBs Under Low-Flow Conditions</li><li>Assessment of PCBs Under Stormflow Conditions</li><li>Assessment of PCBs in Wastewater</li><li>Conceptual Model of PCBs in Back River and Implications for Management</li><li>Conclusions and Summary</li><li>References Cited</li><li>Appendix 1. Quality Assurance-Quality Control Discussion of Results</li></ul>","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"publishedDate":"2022-05-03","noUsgsAuthors":false,"publicationDate":"2022-05-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Majcher, Emily H. 0000-0001-7144-6809","orcid":"https://orcid.org/0000-0001-7144-6809","contributorId":203335,"corporation":false,"usgs":true,"family":"Majcher","given":"Emily","middleInitial":"H.","affiliations":[{"id":41514,"text":"Maryland-Delaware-District of Columbia  Water Science Center","active":true,"usgs":true}],"preferred":true,"id":841789,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ghosh, Upal","contributorId":290900,"corporation":false,"usgs":false,"family":"Ghosh","given":"Upal","email":"","affiliations":[{"id":62531,"text":"UMBC","active":true,"usgs":false}],"preferred":false,"id":841790,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Needham, Trevor P. 0000-0001-9356-4216","orcid":"https://orcid.org/0000-0001-9356-4216","contributorId":245024,"corporation":false,"usgs":true,"family":"Needham","given":"Trevor","email":"","middleInitial":"P.","affiliations":[{"id":41514,"text":"Maryland-Delaware-District of Columbia  Water Science Center","active":true,"usgs":true}],"preferred":true,"id":841791,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lombard, Nathalie","contributorId":290901,"corporation":false,"usgs":false,"family":"Lombard","given":"Nathalie","email":"","affiliations":[{"id":62531,"text":"UMBC","active":true,"usgs":false}],"preferred":false,"id":841792,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Foss, Ellie P. 0000-0001-9090-4617","orcid":"https://orcid.org/0000-0001-9090-4617","contributorId":290902,"corporation":false,"usgs":true,"family":"Foss","given":"Ellie","middleInitial":"P.","affiliations":[{"id":41514,"text":"Maryland-Delaware-District of Columbia  Water Science Center","active":true,"usgs":true}],"preferred":true,"id":841793,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bokare, Mandare","contributorId":290932,"corporation":false,"usgs":false,"family":"Bokare","given":"Mandare","email":"","affiliations":[{"id":62531,"text":"UMBC","active":true,"usgs":false}],"preferred":true,"id":841806,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Joshee, Sarahana","contributorId":290903,"corporation":false,"usgs":false,"family":"Joshee","given":"Sarahana","email":"","affiliations":[{"id":62531,"text":"UMBC","active":true,"usgs":false}],"preferred":false,"id":841794,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Cheung, Louis","contributorId":290933,"corporation":false,"usgs":false,"family":"Cheung","given":"Louis","email":"","affiliations":[{"id":62531,"text":"UMBC","active":true,"usgs":false}],"preferred":true,"id":841807,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Damond, Jada","contributorId":290934,"corporation":false,"usgs":false,"family":"Damond","given":"Jada","email":"","affiliations":[{"id":62531,"text":"UMBC","active":true,"usgs":false}],"preferred":true,"id":841808,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Lorah, Michelle M. 0000-0002-9236-587X","orcid":"https://orcid.org/0000-0002-9236-587X","contributorId":224040,"corporation":false,"usgs":true,"family":"Lorah","given":"Michelle","middleInitial":"M.","affiliations":[{"id":41514,"text":"Maryland-Delaware-District of Columbia  Water Science Center","active":true,"usgs":true}],"preferred":true,"id":841795,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}}
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