{"pageNumber":"372","pageRowStart":"9275","pageSize":"25","recordCount":184776,"records":[{"id":70232696,"text":"70232696 - 2022 - The ice don’t lie","interactions":[],"lastModifiedDate":"2022-07-12T13:21:58.366807","indexId":"70232696","displayToPublicDate":"2022-07-01T08:14:16","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3587,"text":"The Wildlife Professional","active":true,"publicationSubtype":{"id":10}},"title":"The ice don’t lie","docAbstract":"<p>No abstract available.</p>","language":"English","publisher":"The Wildlife Society","usgsCitation":"Atwood, T.C., 2022, The ice don’t lie: The Wildlife Professional, p. 39-41.","productDescription":"3 p.","startPage":"39","endPage":"41","ipdsId":"IP-139708","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":403471,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":403453,"type":{"id":15,"text":"Index Page"},"url":"https://wildlife.org/the-july-august-issue-of-the-wildlife-professional-5/"}],"country":"Canada, United States","otherGeospatial":"southern Beaufort Sea","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -159.609375,\n              69.41124235697256\n            ],\n            [\n              -123.04687499999999,\n              69.41124235697256\n            ],\n            [\n              -123.04687499999999,\n              73.32785809840696\n            ],\n            [\n              -159.609375,\n              73.32785809840696\n            ],\n            [\n              -159.609375,\n              69.41124235697256\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Atwood, Todd C. 0000-0002-1971-3110 tatwood@usgs.gov","orcid":"https://orcid.org/0000-0002-1971-3110","contributorId":4368,"corporation":false,"usgs":true,"family":"Atwood","given":"Todd","email":"tatwood@usgs.gov","middleInitial":"C.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":846311,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70248034,"text":"70248034 - 2022 - New craters on Mars: An updated catalog","interactions":[],"lastModifiedDate":"2023-09-01T13:00:34.786362","indexId":"70248034","displayToPublicDate":"2022-07-01T07:53:03","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2317,"text":"Journal of Geophysical Research E: Planets","active":true,"publicationSubtype":{"id":10}},"title":"New craters on Mars: An updated catalog","docAbstract":"<p><span>We present a catalog of new impacts on Mars. These craters formed in the last few decades, constrained with repeat orbital imaging. Crater diameters range from 58&nbsp;m down to &lt;1&nbsp;m. For each impact, we report whether it formed a single crater or a cluster (58% clusters); albedo features of the blast zone (88% halos; 64% linear rays; 10% arcuate rays; majority dark-toned; 4% light-toned; 14% dual-toned); and exposures of ice (4% definite; 2% possible). We find no trends in the occurrences of clusters with latitude, elevation, or impact size. Albedo features do not depend on atmospheric fragmentation. Halos are more prevalent at lower elevations, indicating an atmospheric pressure dependence; and around smaller impacts, which could be an observational bias. Linear rays are more likely to form from larger impacts into more consolidated material and may be enhanced by lower atmospheric pressure at higher elevations. Light- and dual-toned blast zones occur in specific regions and more commonly around larger impacts, indicating excavation of compositionally distinct material. Surfaces covered with bright dust lacking cohesion are favored to form detectable surface features. The slope of the cumulative size frequency distribution for this data set is 2.2 for diameters &gt;8&nbsp;m (differential slope 2.9), significantly shallower than the slope of new lunar craters. We believe that no systematic biases exist in the Martian data set sufficient to explain the discrepancy. This catalog is complete at the time of writing, although observational biases exist, and new discoveries continue.</span></p>","language":"English","publisher":"Wiley","doi":"10.1029/2021JE007145","usgsCitation":"Daubar, I.J., Dundas, C., McEwen, A.S., Gao, A., Wexler, D., Piqueux, S., Collins, G.S., Miljkovic, K., Neidhart, T., Eschenfelder, J., Bart, G.D., Wagstaff, K.L., Doran, G., Posiolova, L., Malin, M.C., Speth, G., Susko, D., and Werynski, A., 2022, New craters on Mars: An updated catalog: Journal of Geophysical Research E: Planets, v. 127, no. 7, e2021JE007145, 21 p., https://doi.org/10.1029/2021JE007145.","productDescription":"e2021JE007145, 21 p.","ipdsId":"IP-135587","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":447259,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2021je007145","text":"Publisher Index Page"},{"id":420406,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Mars","volume":"127","issue":"7","noUsgsAuthors":false,"publicationDate":"2022-07-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Daubar, Ingrid J.","contributorId":204233,"corporation":false,"usgs":false,"family":"Daubar","given":"Ingrid","email":"","middleInitial":"J.","affiliations":[{"id":7023,"text":"Jet Propulsion Laboratory, California Institute of Technology","active":true,"usgs":false}],"preferred":false,"id":881570,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dundas, Colin M. 0000-0003-2343-7224","orcid":"https://orcid.org/0000-0003-2343-7224","contributorId":237028,"corporation":false,"usgs":true,"family":"Dundas","given":"Colin M.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":881571,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McEwen, Alfred S.","contributorId":61657,"corporation":false,"usgs":false,"family":"McEwen","given":"Alfred","email":"","middleInitial":"S.","affiliations":[{"id":7042,"text":"University of Arizona","active":true,"usgs":false}],"preferred":false,"id":881572,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gao, Annabelle","contributorId":328861,"corporation":false,"usgs":false,"family":"Gao","given":"Annabelle","email":"","affiliations":[{"id":16929,"text":"Brown University","active":true,"usgs":false}],"preferred":false,"id":881573,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wexler, D.","contributorId":328862,"corporation":false,"usgs":false,"family":"Wexler","given":"D.","email":"","affiliations":[{"id":16929,"text":"Brown University","active":true,"usgs":false}],"preferred":false,"id":881574,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Piqueux, Sylvain","contributorId":56986,"corporation":false,"usgs":false,"family":"Piqueux","given":"Sylvain","email":"","affiliations":[{"id":7023,"text":"Jet Propulsion Laboratory, California Institute of Technology","active":true,"usgs":false}],"preferred":false,"id":881575,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Collins, Gareth S.","contributorId":328863,"corporation":false,"usgs":false,"family":"Collins","given":"Gareth","email":"","middleInitial":"S.","affiliations":[{"id":24608,"text":"Imperial College London","active":true,"usgs":false}],"preferred":false,"id":881576,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Miljkovic, Katarina","contributorId":303375,"corporation":false,"usgs":false,"family":"Miljkovic","given":"Katarina","affiliations":[{"id":13639,"text":"Curtin University","active":true,"usgs":false}],"preferred":false,"id":881577,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Neidhart, T.","contributorId":328866,"corporation":false,"usgs":false,"family":"Neidhart","given":"T.","email":"","affiliations":[{"id":13639,"text":"Curtin University","active":true,"usgs":false}],"preferred":false,"id":881578,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Eschenfelder, J.","contributorId":328867,"corporation":false,"usgs":false,"family":"Eschenfelder","given":"J.","email":"","affiliations":[{"id":24608,"text":"Imperial College London","active":true,"usgs":false}],"preferred":false,"id":881579,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Bart, Gwen D.","contributorId":328869,"corporation":false,"usgs":false,"family":"Bart","given":"Gwen","email":"","middleInitial":"D.","affiliations":[{"id":36394,"text":"University of Idaho","active":true,"usgs":false}],"preferred":false,"id":881580,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Wagstaff, Kiri L.","contributorId":213351,"corporation":false,"usgs":false,"family":"Wagstaff","given":"Kiri","email":"","middleInitial":"L.","affiliations":[{"id":7023,"text":"Jet Propulsion Laboratory, California Institute of Technology","active":true,"usgs":false}],"preferred":false,"id":881581,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Doran, Gary","contributorId":297954,"corporation":false,"usgs":false,"family":"Doran","given":"Gary","email":"","affiliations":[{"id":36276,"text":"JPL","active":true,"usgs":false}],"preferred":false,"id":881582,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Posiolova, Liliya","contributorId":258278,"corporation":false,"usgs":false,"family":"Posiolova","given":"Liliya","affiliations":[{"id":36716,"text":"Malin Space Science Systems","active":true,"usgs":false}],"preferred":false,"id":881583,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Malin, Michael C.","contributorId":195300,"corporation":false,"usgs":false,"family":"Malin","given":"Michael","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":881584,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Speth, Gunnar","contributorId":258279,"corporation":false,"usgs":false,"family":"Speth","given":"Gunnar","email":"","affiliations":[{"id":36716,"text":"Malin Space Science Systems","active":true,"usgs":false}],"preferred":false,"id":881585,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Susko, David","contributorId":328873,"corporation":false,"usgs":false,"family":"Susko","given":"David","email":"","affiliations":[{"id":36716,"text":"Malin Space Science Systems","active":true,"usgs":false}],"preferred":false,"id":881586,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Werynski, A.","contributorId":328874,"corporation":false,"usgs":false,"family":"Werynski","given":"A.","email":"","affiliations":[{"id":36716,"text":"Malin Space Science Systems","active":true,"usgs":false}],"preferred":false,"id":881587,"contributorType":{"id":1,"text":"Authors"},"rank":18}]}}
,{"id":70232695,"text":"70232695 - 2022 - What is a stand? Assessing the variability of composition and structure in floodplain forest ecosystems across spatial scales in the Upper Mississippi River","interactions":[],"lastModifiedDate":"2022-07-12T12:27:03.988899","indexId":"70232695","displayToPublicDate":"2022-07-01T07:23:59","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1687,"text":"Forest Ecology and Management","active":true,"publicationSubtype":{"id":10}},"title":"What is a stand? Assessing the variability of composition and structure in floodplain forest ecosystems across spatial scales in the Upper Mississippi River","docAbstract":"<div id=\"abstracts\" class=\"Abstracts u-font-serif\"><div id=\"ab010\" class=\"abstract author\" lang=\"en\"><div id=\"as010\"><p id=\"sp0010\">The forest stand typically represents relatively homogenous forest conditions; the forest stand is generally the unit at which forest attributes are assessed, summarized, and subsequently managed. However, some ecosystems, such as the floodplain forests of the Upper Mississippi River (UMR), can exhibit high variability at fine spatial scales that can confound prescription development, implementation, and ultimate success of stand-level management actions. Here we assess how forest composition and structure vary within and across stand management units on the UMR and test at what spatial scale environmental variables relate to forest characteristics. We found that plot-level measures of composition, structure, and diversity were not well represented by site-level averages of these values. When basal area of all overstory species was combined, this variable was more closely related to “site” than to any of the environmental variables, but when analyzed by species, within-plot topographic variation (“microtopography”) was a significant positive predictor for both importance values of an individual species (swamp white oak (<i>Quercus bicolor</i><span>&nbsp;</span>Willd.)) as well as importance value of a specific group of species (oaks (Quercus spp.), bitternut hickory (<i>Carya cordiformis</i><span>&nbsp;</span>(Wangenh.) K. Koch), hackberry (<i>Celtis occidentalis</i><span>&nbsp;</span>L.), and American basswood (<i>Tilia americana</i><span>&nbsp;</span>L.)). This work highlights the challenges of using average stand conditions to summarize complex or heterogeneous systems and the need for flexibility and relaxed assumptions in defining management units in these forests.</p></div></div></div>","language":"English","publisher":"Elsevier","doi":"10.1016/j.foreco.2022.120385","usgsCitation":"Windmuller-Campione, M., Reuling, L.F., Van Appledorn, M., Nilesen, D.M., and Meier, A.R., 2022, What is a stand? Assessing the variability of composition and structure in floodplain forest ecosystems across spatial scales in the Upper Mississippi River: Forest Ecology and Management, v. 520, 120385, 19 p., https://doi.org/10.1016/j.foreco.2022.120385.","productDescription":"120385, 19 p.","ipdsId":"IP-137427","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":447262,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.foreco.2022.120385","text":"Publisher Index Page"},{"id":403467,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Iowa, Minnesota, Wisconsin","otherGeospatial":"Upper Mississippi River","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -94.1748046875,\n              42.5530802889558\n            ],\n            [\n              -89.7802734375,\n              42.5530802889558\n            ],\n            [\n              -89.7802734375,\n              45.69083283645816\n            ],\n            [\n              -94.1748046875,\n              45.69083283645816\n            ],\n            [\n              -94.1748046875,\n              42.5530802889558\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"520","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Windmuller-Campione, Marcella","contributorId":292936,"corporation":false,"usgs":false,"family":"Windmuller-Campione","given":"Marcella","email":"","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":846306,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Reuling, Laura F.","contributorId":292937,"corporation":false,"usgs":false,"family":"Reuling","given":"Laura","email":"","middleInitial":"F.","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":846307,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Van Appledorn, Molly 0000-0002-8029-0014","orcid":"https://orcid.org/0000-0002-8029-0014","contributorId":205785,"corporation":false,"usgs":true,"family":"Van Appledorn","given":"Molly","email":"","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":846308,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Nilesen, Daniel M.","contributorId":292938,"corporation":false,"usgs":false,"family":"Nilesen","given":"Daniel","email":"","middleInitial":"M.","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":846309,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Meier, Andrew R.","contributorId":215691,"corporation":false,"usgs":false,"family":"Meier","given":"Andrew","email":"","middleInitial":"R.","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":846310,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70233933,"text":"70233933 - 2022 - Functional composition of plant communities mediates biomass effects on ecosystem service recovery across an experimental dryland restoration network","interactions":[],"lastModifiedDate":"2022-09-15T14:18:48.828438","indexId":"70233933","displayToPublicDate":"2022-07-01T07:18:55","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1711,"text":"Functional Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Functional composition of plant communities mediates biomass effects on ecosystem service recovery across an experimental dryland restoration network","docAbstract":"<ol class=\"\"><li>Land degradation can result in a loss of critical ecosystem services that we often seek to restore through re-establishment of desired plant communities. Trait-based approaches have the potential to target specific ecosystem services based on associations between the functional composition of plant communities and ecosystem properties that serve as indicators of those services.</li><li>The effect of functional composition on ecosystem recovery may depend on the amount of restored plant biomass, itself a supporting service frequently targeted in restoration efforts. Yet, interactions between functional composition and biomass are not formally integrated into trait-based analytical frameworks.</li><li>We tested the hypothesis that functional composition of plant communities both drives, and interacts with, biomass production to influence indicators of soil functioning and weed suppression across a network of degraded dryland restoration experiments. This networked approach allowed us to identify generalized effects of functional composition on ecosystem recovery across a range of dryland climate conditions.</li><li>Climate had a substantial effect on ecosystem indicators, with weed cover and soil surface stability increasing in more arid climates, water infiltration increasing with precipitation, and aggregate structure increasing with less freezing. After accounting for climate effects across study sites, we found significant effects of community-weighted mean (CWM) trait values on biomass, particularly a positive effect of leaf carbon-to-nitrogen ratio, and of CWM-biomass interactions on other ecosystem indicators. Cover of exotic species was reduced in restored communities with a combination of low leaf dry matter content and high biomass, soil water infiltration increased with lower specific root length and high biomass, and soil aggregate stability increased with higher root dry matter content and high biomass, among other effects. Functional diversity had no significant effects on any ecosystem indicators.</li><li><i>Synthesis</i>: The influence of community functional composition on ecosystem properties increases with community biomass, particularly in disturbed or low productivity systems. This suggests that active management should not only focus on trait values that optimize individual ecosystem indicators but also how those functional strategies are complementary or counter to those that increase biomass.</li></ol>","language":"English","publisher":"British Ecological Society","doi":"10.1111/1365-2435.14129","usgsCitation":"Balazs, K.R., Munson, S.M., and Butterfield, B.J., 2022, Functional composition of plant communities mediates biomass effects on ecosystem service recovery across an experimental dryland restoration network: Functional Ecology, v. 36, no. 9, p. 2317-2330, https://doi.org/10.1111/1365-2435.14129.","productDescription":"14 p.","startPage":"2317","endPage":"2330","ipdsId":"IP-138753","costCenters":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true},{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":447265,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/1365-2435.14129","text":"Publisher Index Page"},{"id":404531,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"36","issue":"9","noUsgsAuthors":false,"publicationDate":"2022-07-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Balazs, Kathleen R.","contributorId":223214,"corporation":false,"usgs":false,"family":"Balazs","given":"Kathleen","email":"","middleInitial":"R.","affiliations":[{"id":24810,"text":"Department of Biological Sciences, Northern Arizona University, Flagstaff, Arizona, USA","active":true,"usgs":false}],"preferred":false,"id":847710,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"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":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true},{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":847711,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Butterfield, Bradley J. 0000-0003-0974-9811","orcid":"https://orcid.org/0000-0003-0974-9811","contributorId":167009,"corporation":false,"usgs":false,"family":"Butterfield","given":"Bradley","email":"","middleInitial":"J.","affiliations":[{"id":24591,"text":"Merriam-Powell Center for Environmental Research and Department of Biological Sciences, Northern Arizona University, Flagstaff, AZ, USA","active":true,"usgs":false}],"preferred":false,"id":847712,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70232548,"text":"70232548 - 2022 - Rapid implementation of high-frequency wastewater surveillance of SARS-CoV-2","interactions":[],"lastModifiedDate":"2022-11-16T16:57:27.039347","indexId":"70232548","displayToPublicDate":"2022-07-01T07:02:24","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":10957,"text":"ES&T: Water","active":true,"publicationSubtype":{"id":10}},"title":"Rapid implementation of high-frequency wastewater surveillance of SARS-CoV-2","docAbstract":"<div class=\"container container_scaled-down\"><div class=\"row\"><div class=\"col-xs-12\"><div id=\"abstractBox\" class=\"article_abstract-content hlFld-Abstract\"><p class=\"articleBody_abstractText\">There have been over 507 million cases of COVID-19, the disease caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), resulting in 6 million deaths globally. Wastewater surveillance has emerged as a valuable tool in understanding SARS-CoV-2 burden in communities. The National Wastewater Surveillance System (NWSS) partnered with the United States Geological Survey (USGS) to implement a high-frequency sampling program. This report describes basic surveillance and sampling statistics as well as a comparison of SARS-CoV-2 trends between high-frequency sampling 3–5 times per week, referred to as USGS samples, and routine sampling 1–2 times per week, referred to as NWSS samples. USGS samples provided a more nuanced impression of the changes in wastewater trends, which could be important in emergency response situations. Despite the rapid implementation time frame, USGS samples had similar data quality and testing turnaround times as NWSS samples. Ensuring there is a reliable sample collection and testing plan before an emergency arises will aid in the rapid implementation of a high-frequency sampling approach. High-frequency sampling requires a constant flow of information and supplies throughout sample collection, testing, analysis, and data sharing. High-frequency sampling may be a useful approach for increased resolution of disease trends in emergency response.</p></div></div></div></div>","language":"English","publisher":"American Chemical Society","doi":"10.1021/acsestwater.2c00094","usgsCitation":"Holst, M.M., Person, J., Jennings, W., Welsh, R.M., Focazio, M.J., Bradley, P., Schill, W., Kirby, A.E., and Marsh, Z.A., 2022, Rapid implementation of high-frequency wastewater surveillance of SARS-CoV-2: ES&T: Water, v. 2, no. 11, p. 2201-2210, https://doi.org/10.1021/acsestwater.2c00094.","productDescription":"10 p.","startPage":"2201","endPage":"2210","ipdsId":"IP-137069","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":403130,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"2","issue":"11","noUsgsAuthors":false,"publicationDate":"2022-07-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Holst, Meghan M. 0000-0002-9505-7282","orcid":"https://orcid.org/0000-0002-9505-7282","contributorId":292856,"corporation":false,"usgs":false,"family":"Holst","given":"Meghan","email":"","middleInitial":"M.","affiliations":[{"id":63044,"text":"Centers for Disease Control, National Center for Emerging and Zoonotic Infectious Diseases","active":true,"usgs":false}],"preferred":false,"id":845928,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Person, John","contributorId":292857,"corporation":false,"usgs":false,"family":"Person","given":"John","email":"","affiliations":[{"id":63044,"text":"Centers for Disease Control, National Center for Emerging and Zoonotic Infectious Diseases","active":true,"usgs":false}],"preferred":false,"id":845929,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jennings, Wiley 0000-0003-0596-2746","orcid":"https://orcid.org/0000-0003-0596-2746","contributorId":292858,"corporation":false,"usgs":false,"family":"Jennings","given":"Wiley","email":"","affiliations":[{"id":63044,"text":"Centers for Disease Control, National Center for Emerging and Zoonotic Infectious Diseases","active":true,"usgs":false}],"preferred":false,"id":845930,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Welsh, Rory M.","contributorId":292874,"corporation":false,"usgs":false,"family":"Welsh","given":"Rory","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":845978,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Focazio, Michael J. 0000-0003-0967-5576 mfocazio@usgs.gov","orcid":"https://orcid.org/0000-0003-0967-5576","contributorId":1276,"corporation":false,"usgs":true,"family":"Focazio","given":"Michael","email":"mfocazio@usgs.gov","middleInitial":"J.","affiliations":[{"id":5056,"text":"Office of the AD Energy and Minerals, and Environmental Health","active":true,"usgs":true},{"id":38175,"text":"Toxics Substances Hydrology Program","active":true,"usgs":true}],"preferred":true,"id":845931,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bradley, Paul M. 0000-0001-7522-8606","orcid":"https://orcid.org/0000-0001-7522-8606","contributorId":221226,"corporation":false,"usgs":true,"family":"Bradley","given":"Paul M.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":559,"text":"South Carolina Water Science Center","active":true,"usgs":true}],"preferred":true,"id":845927,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Schill, W. Bane 0000-0002-9217-984X","orcid":"https://orcid.org/0000-0002-9217-984X","contributorId":213903,"corporation":false,"usgs":true,"family":"Schill","given":"W. Bane","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":845932,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Kirby, Amy E. 0000-0002-6928-668X","orcid":"https://orcid.org/0000-0002-6928-668X","contributorId":292859,"corporation":false,"usgs":false,"family":"Kirby","given":"Amy","email":"","middleInitial":"E.","affiliations":[{"id":63044,"text":"Centers for Disease Control, National Center for Emerging and Zoonotic Infectious Diseases","active":true,"usgs":false}],"preferred":false,"id":845933,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Marsh, Zachary A. 0000-0002-4968-7427","orcid":"https://orcid.org/0000-0002-4968-7427","contributorId":292860,"corporation":false,"usgs":false,"family":"Marsh","given":"Zachary","email":"","middleInitial":"A.","affiliations":[{"id":63044,"text":"Centers for Disease Control, National Center for Emerging and Zoonotic Infectious Diseases","active":true,"usgs":false}],"preferred":false,"id":845934,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70240705,"text":"70240705 - 2022 - DevelNet: Earthquake detection on Develocorder films with deep learning: Application to the rangely earthquake control experiment","interactions":[],"lastModifiedDate":"2023-02-15T12:59:35.395969","indexId":"70240705","displayToPublicDate":"2022-07-01T06:58:39","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":"DevelNet: Earthquake detection on Develocorder films with deep learning: Application to the rangely earthquake control experiment","docAbstract":"<div id=\"134365686\" class=\"article-section-wrapper js-article-section js-content-section  \" data-section-parent-id=\"0\"><p>There exists over a century of instrumental seismic data; however, most seismograms recorded before the 1980s are only available in analog form. Although analog seismograms are of great value, they are underutilized due to the difficulties of making quantitative measurements on the original media and in converting them to digital time series. In this study, we present an alternative workflow, based on deep learning, to reconstruct an earthquake catalog from images of analog data without conversion to vector time series. We trained a convolutional neural network—DevelNet, using synthetic analog data to detect earthquakes on scanned multichannel Develocorder film images. We then developed an image‐based processing workflow to measure arrival times, locate, and determine the magnitudes of earthquakes in the data. We demonstrate the performance of this approach on two years of continuous Develocorder film recordings from the Rangely earthquake control experiment in the mid‐1970s. Our approach detects twice the number of events reported in the original catalog (<a class=\"link link-ref xref-bibr\" data-modal-source-id=\"rf17\">Raleigh<span>&nbsp;</span><i>et&nbsp;al.</i>, 1976</a>). This demonstrates that DevelNet efficiently detects earthquakes from Develocorder film scans, performs consistently over time, and is robust to changes in network geometry. Our locations generally agree with the original study, although the automatically measured arrival times are less precise than manual reading, leading to increased location scatter. Our automatic workflow of Develocorder films rivals the performance of skilled analysts in earthquake detection, but with minimal human intervention. This image‐based processing offers a new approach for effectively and efficiently extracting earthquake information from analog seismic data.</p></div>","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0220220066","usgsCitation":"Wang, K., Ellsworth, W.L., Beroza, G.C., Zhu, W., and Rubinstein, J., 2022, DevelNet: Earthquake detection on Develocorder films with deep learning: Application to the rangely earthquake control experiment: Bulletin of the Seismological Society of America, v. 93, no. 5, p. 2515-2528, https://doi.org/10.1785/0220220066.","productDescription":"14 p.","startPage":"2515","endPage":"2528","ipdsId":"IP-138495","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":413098,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"93","issue":"5","noUsgsAuthors":false,"publicationDate":"2022-07-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Wang, Kaiwen","contributorId":215275,"corporation":false,"usgs":false,"family":"Wang","given":"Kaiwen","email":"","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":864367,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ellsworth, William L","contributorId":302399,"corporation":false,"usgs":false,"family":"Ellsworth","given":"William","email":"","middleInitial":"L","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":864368,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Beroza, Gregory C.","contributorId":191201,"corporation":false,"usgs":false,"family":"Beroza","given":"Gregory","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":864369,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Zhu, Weiqiang","contributorId":302400,"corporation":false,"usgs":false,"family":"Zhu","given":"Weiqiang","email":"","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":864370,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rubinstein, Justin 0000-0003-1274-6785","orcid":"https://orcid.org/0000-0003-1274-6785","contributorId":215341,"corporation":false,"usgs":true,"family":"Rubinstein","given":"Justin","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":864371,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70234209,"text":"70234209 - 2022 - Over a third of groundwater in USA public-supply aquifers is Anthropocene-age and susceptible to surface contamination","interactions":[],"lastModifiedDate":"2022-08-03T11:53:39.776188","indexId":"70234209","displayToPublicDate":"2022-07-01T06:49:37","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":11444,"text":"Nature Communications Earth & Environment","active":true,"publicationSubtype":{"id":10}},"title":"Over a third of groundwater in USA public-supply aquifers is Anthropocene-age and susceptible to surface contamination","docAbstract":"<div id=\"Abs1-section\" class=\"c-article-section\"><div id=\"Abs1-content\" class=\"c-article-section__content\"><p>The distribution of groundwater age is useful for evaluating the susceptibility and sustainability of groundwater resources. Here, we compute the aquifer-scale cumulative distribution function to characterize the age distribution for 21 Principal Aquifers that account for ~80% of public-supply pumping in the United States. The aquifer-scale cumulative distribution function for each Principal Aquifer was derived from an ensemble of modeled age distributions (~60 samples per aquifer) based on multiple tracers: tritium, tritiogenic helium-3, sulfur hexafluoride, chlorofluorocarbons, carbon-14, and radiogenic helium-4. Nationally, the groundwater is 38% Anthropocene (since 1953), 34% Holocene (75 – 11,800 years ago), and 28% Pleistocene (&gt;11,800 years ago). The Anthropocene fraction ranges from &lt;5 to 100%, indicating a wide range in susceptibility to land-surface contamination. The Pleistocene fraction of groundwater exceeds 50% in 7 eastern aquifers that are predominately confined. The Holocene fraction of groundwater exceeds 50% in 5 western aquifers that are predominately unconfined. The sustainability of pumping from these Principal Aquifers depends on rates of recharge and release of groundwater stored in fine-grained layers.</p></div></div>","language":"English","publisher":"Springer Nature","doi":"10.1038/s43247-022-00473-y","usgsCitation":"Jurgens, B., Faulkner, K., McMahon, P.B., Hunt, A.G., Casile, G.C., Young, M.B., and Belitz, K., 2022, Over a third of groundwater in USA public-supply aquifers is Anthropocene-age and susceptible to surface contamination: Nature Communications Earth & Environment, v. 2, 153, 9 p., https://doi.org/10.1038/s43247-022-00473-y.","productDescription":"153, 9 p.","ipdsId":"IP-132959","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":447271,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s43247-022-00473-y","text":"Publisher Index 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,{"id":70232384,"text":"sir20225061 - 2022 - Characterization of and temporal changes in groundwater quality of the Upper Black Squirrel Creek Basin, El Paso County, Colorado, 2018–20","interactions":[],"lastModifiedDate":"2026-04-23T16:46:24.907999","indexId":"sir20225061","displayToPublicDate":"2022-06-30T16:00:00","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":"2022-5061","displayTitle":"Characterization of and Temporal Changes in Groundwater Quality of the Upper Black Squirrel Creek Basin, El Paso County, Colorado, 2018–20","title":"Characterization of and temporal changes in groundwater quality of the Upper Black Squirrel Creek Basin, El Paso County, Colorado, 2018–20","docAbstract":"<p>In 2018–20, the U.S. Geological Survey, in cooperation with Upper Black Squirrel Creek Ground Water Management District, sampled 48 wells for Phase III of a multiphase plan investigating groundwater quality in the alluvial aquifer of the Upper Black Squirrel Creek Basin (UBSB), El Paso County, Colorado. Results for samples collected from October to December each year were used to assess spatial and temporal changes in groundwater quality and to differentiate sources of nitrate. Groundwater was predominantly classified as mixed-cation and mixed-anion water type in the aquifer, with variable chemistry along the periphery. Concentrations of constituents in groundwater were generally less than regulatory standards, except for nitrate in four wells. Isotopes of nitrogen and oxygen in nitrate identified four different potential sources or processes affecting nitrate in the alluvial aquifer: naturally occurring nitrate from soils, nitrate from animal and (or) human waste, and an unknown source, along with evidence of denitrification. Pharmaceutical compounds and personal-care products were detected in seven wells, with three wells having multiple detections. Stable isotopes of water indicated variability in seasonality of recharge throughout the UBSB alluvial aquifer. Nitrate concentrations from the 1984 study and the 1996 study were compared to the more recent concentrations in the 2013 study and the 2018–20 study. The northern one-third of the UBSB alluvial aquifer had a statistically significant increase in nitrate concentration from the 2013 study to the 2018–20 study, but no change was shown from the 1984 study to the 1996 study. The opposite was found true for the southern two-thirds of the UBSB alluvial aquifer with no statistically significant difference in nitrate concentration from the 2013 study to the 2018–20 study. Analysis of temporal changes indicated an increase in median and maximum nitrate concentrations from the 2013 study to the 2018–20 study throughout the UBSB alluvial aquifer. Continued sampling of wells in the UBSB would be beneficial to better determine temporal changes in groundwater quality, characterize human effects on water quality, and understand characteristics of the alluvial aquifer pertaining to sustainability of the resource.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225061","collaboration":"Prepared in cooperation with Upper Black Squirrel Creek Ground Water Management District","usgsCitation":"Kisfalusi, Z.D., Bauch, N.J., and Bern, C.R., 2022, Characterization of and temporal changes in groundwater quality of the Upper Black Squirrel Creek Basin, El Paso County, Colorado, 2018–20: U.S. Geological Survey Scientific Investigations Report 2022–5061, 43 p., https://doi.org/10.3133/sir20225061.","productDescription":"viii, 43 p.","onlineOnly":"N","ipdsId":"IP-127190","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":402740,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5061/coverthb.jpg"},{"id":402741,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5061/sir20225061.pdf","text":"Report","size":"8.50 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2022-5061"},{"id":402743,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2022/5061/images"},{"id":503378,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113254.htm","linkFileType":{"id":5,"text":"html"}},{"id":402744,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2022/5061/sir20225061.xml"},{"id":402742,"rank":3,"type":{"id":9,"text":"Database"},"url":"https://doi.org/10.5066/F7P55KJN","linkHelpText":"USGS water data for the Nation: U.S. Geological Survey National Water Information System database"}],"country":"United States","state":"Colorado","county":"El Paso County","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-104.6642,39.1308],[-104.6072,39.1307],[-104.4958,39.1298],[-104.3854,39.1284],[-104.2733,39.1278],[-104.166,39.1277],[-104.0521,39.1264],[-104.0538,39.0407],[-104.0544,38.9528],[-104.0549,38.8666],[-104.0537,38.7801],[-104.0525,38.693],[-104.051,38.6585],[-104.0524,38.6069],[-104.054,38.523],[-104.1629,38.5215],[-104.2759,38.5204],[-104.2794,38.5205],[-104.2836,38.5201],[-104.3759,38.52],[-104.4971,38.5192],[-104.6071,38.5187],[-104.7171,38.5186],[-104.736,38.5183],[-104.8295,38.5183],[-104.943,38.5175],[-104.9432,38.5479],[-104.943,38.5624],[-104.9429,38.6041],[-104.9427,38.6186],[-104.9429,38.6467],[-104.9429,38.6503],[-104.9427,38.6621],[-104.9427,38.6648],[-104.9428,38.6938],[-104.9399,38.6938],[-104.9386,38.7808],[-104.939,38.7949],[-105.0671,38.7946],[-105.0674,38.8666],[-105.0502,38.8665],[-105.0296,38.8668],[-105.026,39.0413],[-105.032,39.1311],[-104.9371,39.1312],[-104.9175,39.131],[-104.8303,39.1311],[-104.6642,39.1308]]]},\"properties\":{\"name\":\"El Paso\",\"state\":\"CO\"}}]}","contact":"<p>Director, <a href=\"http://www.usgs.gov/centers/co-water/\" data-mce-href=\"http://www.usgs.gov/centers/co-water/\">Colorado Water Science Center</a><br>U.S. Geological Survey<br>Box 25046, MS-415<br>Denver, CO 80225</p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Methods</li><li>Groundwater Quality 2018–20</li><li>Temporal Changes in Groundwater Quality</li><li>Summary</li><li>References Cited</li></ul>","publishedDate":"2022-06-30","noUsgsAuthors":false,"publicationDate":"2022-06-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Kisfalusi, Zachary D. 0000-0001-6016-3213","orcid":"https://orcid.org/0000-0001-6016-3213","contributorId":222422,"corporation":false,"usgs":true,"family":"Kisfalusi","given":"Zachary","email":"","middleInitial":"D.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":845396,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bauch, Nancy J. 0000-0002-0302-2892","orcid":"https://orcid.org/0000-0002-0302-2892","contributorId":202707,"corporation":false,"usgs":true,"family":"Bauch","given":"Nancy J.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":845397,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"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":845398,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70232413,"text":"fs20223044 - 2022 - West Virginia and Landsat","interactions":[],"lastModifiedDate":"2024-08-19T14:31:50.253155","indexId":"fs20223044","displayToPublicDate":"2022-06-30T12:49:57","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":"2022-3044","displayTitle":"West Virginia and Landsat","title":"West Virginia and Landsat","docAbstract":"<p>Many may recall “Take Me Home, Country Roads,” made famous by John Denver, leads with the lyric “almost heaven, West Virginia, Blue Ridge Mountains, Shenandoah River.” The descriptors are apt. Nicknamed the “Mountain State,” West Virginia inspires thoughts of coal mining or logging in the Appalachian Mountains and valleys, or the leaping trout in the winding waters of <span>New River Gorge National Park &amp; Reserve</span>.</p><p>West Virginia is second only to Wyoming in coal production nationwide. Its mines produced more than 67 million tons of coal in 2020. Logging pumped about $3.4 billion into the State’s economy in 2019; tourist spending added another $4.6 billion.</p><p>Those industries are key for West Virginia, but agriculture and fisheries also play a role in the State's economic fortunes. Peaches and apples are major drivers of food production, as are beef and poultry. Trout, meanwhile, are caught and sold commercially, and are stocked throughout the State's rivers for local and visiting anglers.</p><p>Scientists, land managers, and others use imagery from the U.S. Geological Survey Landsat satellite program's deep historical archive to better understand and manage West Virginia’s storied forests, fields, mountains, and foothills.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20223044","usgsCitation":"U.S. Geological Survey, 2022, West Virginia and Landsat: U.S. Geological Survey Fact Sheet 2022–3044, 2 p., https://doi.org/10.3133/fs20223044.","productDescription":"2 p.","numberOfPages":"2","onlineOnly":"N","ipdsId":"IP-140321","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":402764,"rank":4,"type":{"id":34,"text":"Image 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Virginia\",\"nation\":\"USA  \"}}]}","contact":"<p>Program Coordinator, <a data-mce-href=\"https://www.usgs.gov/core-science-systems/national-land-imaging-program\" 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>Monitoring Surface Mines</li><li>Tracking Forest Change</li><li>Managing Aquatic Ecosystems</li><li>Landsat—Critical Information Infrastructure for the Nation</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2022-06-30","noUsgsAuthors":false,"publicationDate":"2022-06-30","publicationStatus":"PW","contributors":{"authors":[{"text":"U.S. Geological Survey","contributorId":147999,"corporation":true,"usgs":false,"organization":"U.S. Geological Survey","id":845466,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70242715,"text":"70242715 - 2022 - Book review: WIldflowers of the Indiana Dunes National Park by Nathanael Pilla and Scott Namestnik","interactions":[],"lastModifiedDate":"2023-04-18T14:04:43.281114","indexId":"70242715","displayToPublicDate":"2022-06-30T09:02:28","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":14250,"text":"Great Lakes Botanist","active":true,"publicationSubtype":{"id":10}},"title":"Book review: WIldflowers of the Indiana Dunes National Park by Nathanael Pilla and Scott Namestnik","docAbstract":"<p>No abstract available.</p>","language":"English","publisher":"Michigan Botanical Society","doi":"10.3998/glbot.3693","usgsCitation":"Pavlovic, N., 2022, Book review: WIldflowers of the Indiana Dunes National Park by Nathanael Pilla and Scott Namestnik: Great Lakes Botanist, v. 61, no. 1-2, p. 58-60, https://doi.org/10.3998/glbot.3693.","productDescription":"3 p.","startPage":"58","endPage":"60","ipdsId":"IP-144245","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":447272,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3998/glbot.3693","text":"Publisher Index Page"},{"id":415919,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"61","issue":"1-2","noUsgsAuthors":false,"publicationDate":"2022-12-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Pavlovic, Noel B. 0000-0002-2335-2274","orcid":"https://orcid.org/0000-0002-2335-2274","contributorId":266174,"corporation":false,"usgs":true,"family":"Pavlovic","given":"Noel B.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":869463,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70236303,"text":"70236303 - 2022 - Lake Tahoe clarity and associated conditions, 2022","interactions":[],"lastModifiedDate":"2022-09-01T12:23:09.591636","indexId":"70236303","displayToPublicDate":"2022-06-30T07:19:40","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"title":"Lake Tahoe clarity and associated conditions, 2022","docAbstract":"Lake Tahoe’s clarity remains a key indicator of overall ecosystem status, and scientific understanding about factors affecting lake clarity continues to evolve. The purpose of this briefing memorandum is to summarize the status of clarity metrics and drivers of change discussed in the 2022 TSAC Data Synthesis and Analysis report. \nConsistent with the Lake Tahoe Total Maximum Daily Load analyses, the concentrations of fine particles remain important to lake clarity. These include fine sediment particles from the watershed as well as small phytoplankton cells produced within the lake. This year, in addition to the analysis of Secchi depth clarity response to fine particle and small phytoplankton concentrations, we reviewed available data on fine sediment particles from streams and urban runoff. \nInformation summarized here is discussed further in the Tahoe Science Advisory Council (TSAC) Data Synthesis and Analysis reports (2022, 2021), the TSAC Lake Tahoe Seasonal and Long-Term Clarity Trend Analysis report (2020), and in annual State of the Lake reports produced by UC Davis Tahoe Environmental Research Center.","language":"English","publisher":"Tahoe Science Advisory Council","usgsCitation":"Heyvaert, A., Naranjo, R.C., Melack, J., Watanabe, S., Schladow, G., and Chandra, S., 2022, Lake Tahoe clarity and associated conditions, 2022, 22 p.","productDescription":"22 p.","ipdsId":"IP-142793","costCenters":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"links":[{"id":406062,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":406054,"type":{"id":15,"text":"Index Page"},"url":"https://www.tahoesciencecouncil.org/"}],"country":"United States","state":"California, Nevada","otherGeospatial":"Lake Tahoe","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -120.21514892578125,\n              38.8824811975508\n            ],\n            [\n              -119.85260009765624,\n              38.8824811975508\n            ],\n            [\n              -119.85260009765624,\n              39.317300373271024\n            ],\n            [\n              -120.21514892578125,\n              39.317300373271024\n            ],\n            [\n              -120.21514892578125,\n              38.8824811975508\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Heyvaert, Alan","contributorId":296065,"corporation":false,"usgs":false,"family":"Heyvaert","given":"Alan","affiliations":[{"id":16138,"text":"Desert Research Institute","active":true,"usgs":false}],"preferred":false,"id":850523,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Naranjo, Ramon C. 0000-0003-4469-6831 rnaranjo@usgs.gov","orcid":"https://orcid.org/0000-0003-4469-6831","contributorId":3391,"corporation":false,"usgs":true,"family":"Naranjo","given":"Ramon","email":"rnaranjo@usgs.gov","middleInitial":"C.","affiliations":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"preferred":true,"id":850524,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Melack, John","contributorId":296066,"corporation":false,"usgs":false,"family":"Melack","given":"John","affiliations":[{"id":37180,"text":"UC Santa Barbara","active":true,"usgs":false}],"preferred":false,"id":850525,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Watanabe, Shohei","contributorId":296067,"corporation":false,"usgs":false,"family":"Watanabe","given":"Shohei","affiliations":[{"id":12711,"text":"UC Davis","active":true,"usgs":false}],"preferred":false,"id":850526,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Schladow, Geoffrey","contributorId":296068,"corporation":false,"usgs":false,"family":"Schladow","given":"Geoffrey","affiliations":[{"id":12711,"text":"UC Davis","active":true,"usgs":false}],"preferred":false,"id":850527,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Chandra, Sudeep","contributorId":296069,"corporation":false,"usgs":false,"family":"Chandra","given":"Sudeep","affiliations":[{"id":38163,"text":"UNR","active":true,"usgs":false}],"preferred":false,"id":850528,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70246959,"text":"70246959 - 2022 - What’s It worth? Estimating the potential value of early warnings of cyanobacterial harmful algal blooms for managing freshwater reservoirs in Kansas, United States","interactions":[],"lastModifiedDate":"2023-12-04T14:26:21.87078","indexId":"70246959","displayToPublicDate":"2022-06-30T07:00:52","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":16456,"text":"Frontiers in Enviornmental Science","active":true,"publicationSubtype":{"id":10}},"title":"What’s It worth? Estimating the potential value of early warnings of cyanobacterial harmful algal blooms for managing freshwater reservoirs in Kansas, United States","docAbstract":"<div class=\"JournalAbstract\"><p class=\"mb15\">Cyanobacterial blooms are an issue drawing increasing concern in freshwater lakes and reservoirs in the United States due to the real and sometimes perceived harms they can cause through cyanotoxin production or other effects. These types of blooms are often referred to as cyanobacterial harmful algal blooms (cyanoHABs). Cyanotoxin exposure can potentially lead to human health effects through recreation and consumption of drinking water and may impact fisheries, wildlife, domestic pets, and livestock. Characterizing the societal impacts of cyanotoxin production, exposure, and effects and estimating the potential value of information of an early warning system can inform and support freshwater lake and reservoir management decisions and future research directions. A Bayesian decision tree analysis was utilized to identify uses, users, and benefits of the information provided by this research. Specifically, the potential value related to a cyanoHAB early warning system, based on potential toxicity, was analyzed that would provide information two additional days earlier relative to cyanoHAB toxicity. The evaluation considers the application of this information for freshwater lake management - whether or not to post an advisory or warning to avoid recreational water contact. The model was parameterized with data from the state of Kansas and the value of avoided foregone recreation and avoided health effects was derived. The estimated annual value of information ranges between \\$565 thousand to \\$2.3 million (2018 United States Dollars (USD)) for the state of Kansas alone based on provided assumptions. The results demonstrate a lower bound of the value of a cyanoHAB early warning system and suggest additional research to understand how the use and value of this information could support research prioritization and further illustrate the return on research investment. This analysis does not incorporate the full suite of potential societal costs that may be associated with a cyanoHAB event such as drinking water treatment, impacts to irrigation, or power generation.</p></div>","language":"English","publisher":"Frontiers","doi":"10.3389/fenvs.2022.805165","usgsCitation":"Pindilli, E., and Loftin, K.A., 2022, What’s It worth? 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,{"id":70232348,"text":"ofr20221061 - 2022 - Microplastic particles in dust-on-snow, Upper Colorado River Basin, Colorado Rocky Mountains, 2013–16","interactions":[],"lastModifiedDate":"2026-03-27T20:29:59.462926","indexId":"ofr20221061","displayToPublicDate":"2022-06-29T18:50:00","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2022-1061","displayTitle":"Microplastic Particles in Dust-on-Snow, Upper Colorado River Basin, Colorado Rocky Mountains, 2013–16","title":"Microplastic particles in dust-on-snow, Upper Colorado River Basin, Colorado Rocky Mountains, 2013–16","docAbstract":"<p>Atmospheric dust deposited to snow cover (dust-on-snow) diminishes snow-surface albedo (SSA) to result in early onset and accelerated rate of melting, effects that challenge management of downstream water resources. During ongoing investigations to identify the light-energy absorbing dust particles most responsible for diminished SSA in the Upper Colorado River Basin of the Colorado Rocky Mountains, we found microplastic particles, which are defined as those less than 5 millimeters in any dimension. In each of the 38 samples that represented the last remaining dust layer during melt seasons of 2013–16, microplastics were identified by size, shape, and color, and their relative amounts were visually estimated using stereomicroscopy. Considering the remote, high-elevation settings of the sample sites, the microplastic particles must have been deposited from the atmosphere. The possible role of microplastics for diminishing SSA of snow cover in the Upper Colorado River Basin may be linked to the solar-energy absorptive properties of polymers and is the subject of ongoing investigation.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221061","usgsCitation":"Reynolds, R.L., Goldstein, H.L., Kokaly, R.F., and Derry, J., 2022, Microplastic particles in dust-on-snow, Upper Colorado River Basin, Colorado Rocky Mountains, 2013–16: U.S. Geological Survey Open-File Report 2022–1061, 7 p.,  https://doi.org/10.3133/ofr20221061.","productDescription":"vi, 7 p.","onlineOnly":"Y","ipdsId":"IP-141503","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":501783,"rank":5,"type":{"id":36,"text":"NGMDB Index 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 \"}}]}","contact":"<p>Director, <a href=\"https://www.usgs.gov/centers/gecsc/\" data-mce-href=\"https://www.usgs.gov/centers/gecsc/\">Geosciences and Environmental Change Science Center</a><br>U.S. Geological Survey<br>P.O. Box 25046, Mail Stop 980<br>Denver, CO 80225</p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Identification of Microplastics</li><li>Is Microplastic Deposition Increasing in Upper Colorado River Basin DOS?</li><li>Regional and Global Context of Microplastics in Upper Colorado River Basin Snow</li><li>Summary</li><li>References Cited</li></ul>","publishedDate":"2022-06-29","noUsgsAuthors":false,"publicationDate":"2022-06-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Reynolds, Richard L. 0000-0002-4572-2942 rreynolds@usgs.gov","orcid":"https://orcid.org/0000-0002-4572-2942","contributorId":139068,"corporation":false,"usgs":true,"family":"Reynolds","given":"Richard","email":"rreynolds@usgs.gov","middleInitial":"L.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":845306,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Goldstein, Harland L. 0000-0002-6092-8818 hgoldstein@usgs.gov","orcid":"https://orcid.org/0000-0002-6092-8818","contributorId":807,"corporation":false,"usgs":true,"family":"Goldstein","given":"Harland","email":"hgoldstein@usgs.gov","middleInitial":"L.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":845307,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kokaly, Raymond F. 0000-0003-0276-7101","orcid":"https://orcid.org/0000-0003-0276-7101","contributorId":205165,"corporation":false,"usgs":true,"family":"Kokaly","given":"Raymond","email":"","middleInitial":"F.","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true},{"id":5078,"text":"Southwest Regional Director's Office","active":true,"usgs":true}],"preferred":true,"id":845308,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Derry, Jeff","contributorId":224402,"corporation":false,"usgs":false,"family":"Derry","given":"Jeff","email":"","affiliations":[{"id":40875,"text":"Center for Snow and Avalanche Studies","active":true,"usgs":false}],"preferred":false,"id":845309,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70232273,"text":"sir20225040 - 2022 - U.S. Geological Survey response to Hurricane Maria flooding in Puerto Rico and characterization of peak streamflows observed September 20–22, 2017","interactions":[],"lastModifiedDate":"2026-04-09T17:29:41.467573","indexId":"sir20225040","displayToPublicDate":"2022-06-29T11:51:42","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":"2022-5040","displayTitle":"U.S. Geological Survey Response to Hurricane Maria Flooding in Puerto Rico and Characterization of Peak Streamflows Observed September 20–22, 2017","title":"U.S. Geological Survey response to Hurricane Maria flooding in Puerto Rico and characterization of peak streamflows observed September 20–22, 2017","docAbstract":"<p>Hurricane Maria struck the island of Puerto Rico on September 20, 2017, as a Category 4 storm. The hurricane traversed the island from southeast to northwest and produced recorded 48-hour rainfall totals of up to 30.01 inches. Estimates of the human death toll range from 2,975 to 4,645, possibly more.</p><p>The U.S. Geological Survey (USGS) hydrologic monitoring network sustained substantial wind and flood damage during the hurricane. Eighty-five of the 300 hydrologic monitoring stations operating in Puerto Rico and the U.S. Virgin Islands prior to the passage of Hurricane Maria were destroyed or damaged. During the weeks and months after the hurricane, USGS field crews in Puerto Rico prioritized repair of the hydrologic monitoring network and collected hydrologic information to characterize the magnitude of observed peak streamflows at 20 streamgage and to develop new theoretical stage-streamflow relations for 58 streamgages where stream channels were substantially altered; the theoretical stage-streamflow relations were used to estimate Hurricane Maria peak streamflows for 39 of those sites. As part of a pilot program, USGS field crews installed continuous slope-area monitoring equipment at two remote streamgages to automate the collection of high-streamflow stage data.</p><p>Hurricane Maria peak streamflows and rankings were determined for 73 USGS streamgages in Puerto Rico. New rank 1 period-of-record peak streamflows occurred at 28 sites, rank 2 period-of-record peak streamflows occurred at 17 sites, and rank 3 period-of-record peak streamflows occurred at 9 sites; period-of-record peak streamflows at the remaining 19 sites either ranked from 4th to 20th or were not ranked. Annual exceedance probabilities for 53 unregulated peak streamflows ranged from greater than 50.0 percent (recurrence interval of less than 2 years) to 0.3 percent (recurrence interval of 333 years), with the majority (28 of 53) in the range of 10.0–2.1 percent (recurrence intervals of 10–48 years).</p><p>A comparison of period-of-record ranks for the largest flood events that have occurred in Puerto Rico since the 1960s indicated that Hurricane Maria produced more record peak streamflows than either Hurricane Hortense in 1996 or Hurricane Georges in 1998. Limited pre-1960s hydrologic data preclude quantitative comparison with earlier storms.</p><p>As part of this study, a maximum peak-streamflow envelope curve for Puerto Rico was developed using historical peak-streamflow information available through 2017. Other post-Hurricane Maria USGS activities summarized in this report include (1) Global Navigation Satellite System surveys at all stations in the USGS hydrologic monitoring network, used to tie the network to the Puerto Rico Vertical Datum of 2002; and (2) telemetered monitoring of the Lago Guajataca Dam in northwestern Puerto Rico, which was damaged and at risk of failure from October to December 2017.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225040","collaboration":"Prepared in collaboration with the U.S. Army Corps of Engineers, Federal Emergency Management Agency, National Oceanic and Atmospheric Administration, Puerto Rico Electric Power Authority, Puerto Rico Aqueduct and Sewer Authority, and Puerto Rico Department of Natural and Environmental Resources","usgsCitation":"Gómez-Fragoso, J., Smith, M., and Santiago, M., 2022, U.S. Geological Survey response to Hurricane Maria flooding in Puerto Rico and characterization of peak streamflows observed September 20–22, 2017 (ver. 1.1, July 2022): U.S. Geological Survey Scientific Investigations Report 2022–5040, 105 p., 6 app., 1 pl., https://doi.org/10.3133/sir20225040.","productDescription":"Report: ix, 105 p.; 6 Appendixes; 1 Plate: 33.08 × 18.40 inches; Data Release; Dataset","numberOfPages":"120","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-125005","costCenters":[{"id":27821,"text":"Caribbean-Florida Water Science Center","active":true,"usgs":true}],"links":[{"id":402425,"rank":13,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"—USGS water data for the Nation"},{"id":402421,"rank":9,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2022/5040/sir20225040_appendix5.csv","text":"Appendix 5","size":"41.3 kB","linkFileType":{"id":7,"text":"csv"},"description":"SIR 2022–5040, appendix 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Rico\",\"nation\":\"USA  \"}}]}","edition":"Version 1.0: June 29, 2022; Version 1.1: July 13, 2022","contact":"<p>Director, <a href=\"https://www.usgs.gov/centers/car-fl-water\" data-mce-href=\"https://www.usgs.gov/centers/car-fl-water\">Caribbean-Florida Water Science Center</a><br>U.S. Geological Survey<br>4446 Pet Lane, Suite 108<br>Lutz, FL 33559</p><p><a href=\"https://pubs.er.usgs.gov/contact\" data-mce-href=\"../contact\">Contact Pubs Warehouse</a></p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Methods</li><li>Results</li><li>Other USGS Activities in Response to Hurricane Maria</li><li>Summary and Conclusions</li><li>References Cited</li><li>Appendix 1. U.S. Geological Survey Hydrologic Monitoring Network in Puerto Rico in 2017, Prior to Hurricane Maria</li><li>Appendix 2. Indirect Measurements of Peak Streamflow, Made at Selected Sites in Puerto Rico After the Passage of Hurricane Maria</li><li>Appendix 3. Development of Stage-Streamflow Relations at Selected Sites in Puerto Rico, 2018</li><li>Appendix 4. 50093000 Río Marín Near Patillas (Case Study)—Continuous Slope Area Method to Determine Stage-Streamflow Relations</li><li>Appendix 5. Station Information, Peak Gage Height and Streamflow, Period of Record Rank, Number of Peak Streamflows, and Estimated Annual Exceedance Probability for Selected U.S. Geological Survey Streamgages in Puerto Rico, September 20–22, 2017</li><li>Appendix 6. Station Information, Period of Record, Number of Peak Streamflows, Historical Rank 1 Peak Streamflow and Date, and Operational Status of Site During Hurricane Maria for 181 Unregulated Sites in Puerto Rico</li></ul>","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"publishedDate":"2022-06-29","revisedDate":"2022-07-13","noUsgsAuthors":false,"publicationDate":"2022-06-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Gómez-Fragoso, Julieta M. 0000-0002-1080-2950","orcid":"https://orcid.org/0000-0002-1080-2950","contributorId":201641,"corporation":false,"usgs":true,"family":"Gómez-Fragoso","given":"Julieta M.","affiliations":[{"id":27821,"text":"Caribbean-Florida Water Science Center","active":true,"usgs":true}],"preferred":true,"id":844951,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Smith, Mark 0000-0003-3341-0594","orcid":"https://orcid.org/0000-0003-3341-0594","contributorId":292522,"corporation":false,"usgs":false,"family":"Smith","given":"Mark","email":"","affiliations":[],"preferred":false,"id":844952,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Santiago, Marilyn 0000-0002-2803-6799 msant@usgs.gov","orcid":"https://orcid.org/0000-0002-2803-6799","contributorId":5958,"corporation":false,"usgs":true,"family":"Santiago","given":"Marilyn","email":"msant@usgs.gov","affiliations":[{"id":156,"text":"Caribbean Water Science Center","active":true,"usgs":true}],"preferred":true,"id":844953,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70233417,"text":"70233417 - 2022 - Elevated nitrogen deposition to fire-prone forests adjacent to urban and agricultural areas, Colorado front range, USA","interactions":[],"lastModifiedDate":"2022-07-20T12:52:00.535042","indexId":"70233417","displayToPublicDate":"2022-06-29T07:48:39","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":11131,"text":"Earth’s Future","active":true,"publicationSubtype":{"id":10}},"title":"Elevated nitrogen deposition to fire-prone forests adjacent to urban and agricultural areas, Colorado front range, USA","docAbstract":"<div class=\"article-section__content en main\"><p>As humans increasingly dominate the nitrogen cycle, deposition of reactive nitrogen (Nr) will continue to have adverse consequences for ecosystems. In the Rocky Mountains, Nr deposition remains elevated and has become increasingly dominated by ammonium, despite efforts to reduce emissions. Currently, spatial models of Nr deposition do not fully account for urban and agricultural emissions, sources that contribute to the observed high rates of ammonium deposition in adjacent ecosystems. To address this gap in the Colorado Front Range, we measured Nr deposition along a transect from urban and agricultural plains to subalpine forests. We found elevated values of wet Nr deposition at the urban and foothill sites (4.7 and 4.4&nbsp;kg N ha<sup>−1</sup><span>&nbsp;</span>yr<sup>−1</sup>, respectively), and lower values at the montane and subalpine sites (2.5–2.8&nbsp;kg N ha<sup>−1</sup><span>&nbsp;</span>yr<sup>−1</sup>). Ammonium dominated wet and bulk Nr deposition, accounting for approximately 69% of bulk Nr deposition. Seasonally, bulk Nr deposition was highest in the spring months, when air masses from the plains are transported west into the mountains. Previous work has demonstrated that high elevations of the Colorado Front Range are especially sensitive to Nr deposition due to thin soil and minimal vegetation. Our results indicate that despite lower precipitation, the fire-prone forested foothills receive even greater Nr deposition than higher elevations, due to proximity to urban and agricultural Nr sources. The interaction between elevated Nr deposition and wildfire in this region may pose a risk to water supplies and ecosystems, and is an important topic for future research.</p></div>","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2021EF002373","usgsCitation":"Heindel, R.C., Murphy, S.F., Repert, D.A., Wetherbee, G.A., Liethen, A., Clow, D.W., and Halamka, T.A., 2022, Elevated nitrogen deposition to fire-prone forests adjacent to urban and agricultural areas, Colorado front range, USA: Earth’s Future, v. 10, no. 7, e2021EF002373, 17 p., https://doi.org/10.1029/2021EF002373.","productDescription":"e2021EF002373, 17 p.","ipdsId":"IP-126349","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":447277,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2021ef002373","text":"Publisher Index Page"},{"id":435790,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9XW4TM8","text":"USGS data release","linkHelpText":"Seasonal Atmospheric Nitrate and Ammonium Deposition along an Elevation Gradient in the Colorado Front Range using Ion Exchange Resin Columns (2018-2019)"},{"id":404108,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -106.4849853515625,\n              39.56758783088905\n            ],\n            [\n              -104.886474609375,\n              39.56758783088905\n            ],\n            [\n              -104.886474609375,\n              40.63479884404164\n            ],\n            [\n              -106.4849853515625,\n              40.63479884404164\n            ],\n            [\n              -106.4849853515625,\n              39.56758783088905\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"10","issue":"7","noUsgsAuthors":false,"publicationDate":"2022-07-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Heindel, Ruth C. 0000-0001-6292-2076","orcid":"https://orcid.org/0000-0001-6292-2076","contributorId":225133,"corporation":false,"usgs":false,"family":"Heindel","given":"Ruth","email":"","middleInitial":"C.","affiliations":[{"id":36621,"text":"University of Colorado","active":true,"usgs":false}],"preferred":false,"id":847046,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Murphy, Sheila F. 0000-0002-5481-3635 sfmurphy@usgs.gov","orcid":"https://orcid.org/0000-0002-5481-3635","contributorId":1854,"corporation":false,"usgs":true,"family":"Murphy","given":"Sheila","email":"sfmurphy@usgs.gov","middleInitial":"F.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":847047,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Repert, Deborah A. 0000-0001-7284-1456 darepert@usgs.gov","orcid":"https://orcid.org/0000-0001-7284-1456","contributorId":2578,"corporation":false,"usgs":true,"family":"Repert","given":"Deborah","email":"darepert@usgs.gov","middleInitial":"A.","affiliations":[{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true},{"id":38175,"text":"Toxics Substances Hydrology Program","active":true,"usgs":true}],"preferred":true,"id":847048,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wetherbee, Gregory A. 0000-0002-6720-2294","orcid":"https://orcid.org/0000-0002-6720-2294","contributorId":215100,"corporation":false,"usgs":true,"family":"Wetherbee","given":"Gregory","email":"","middleInitial":"A.","affiliations":[{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true}],"preferred":true,"id":847049,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Liethen, Alexander","contributorId":293479,"corporation":false,"usgs":false,"family":"Liethen","given":"Alexander","affiliations":[{"id":6606,"text":"Colorado School of Mines","active":true,"usgs":false}],"preferred":false,"id":847050,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Clow, David W. 0000-0001-6183-4824 dwclow@usgs.gov","orcid":"https://orcid.org/0000-0001-6183-4824","contributorId":1671,"corporation":false,"usgs":true,"family":"Clow","given":"David","email":"dwclow@usgs.gov","middleInitial":"W.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":847051,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Halamka, Toby A.","contributorId":293480,"corporation":false,"usgs":false,"family":"Halamka","given":"Toby","email":"","middleInitial":"A.","affiliations":[{"id":36621,"text":"University of Colorado","active":true,"usgs":false}],"preferred":false,"id":847052,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70233606,"text":"70233606 - 2022 - Migration and transformation of coastal wetlands in response to rising seas","interactions":[],"lastModifiedDate":"2023-06-09T13:37:38.92506","indexId":"70233606","displayToPublicDate":"2022-06-29T06:43:11","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":"Migration and transformation of coastal wetlands in response to rising seas","docAbstract":"<div id=\"abstracts\"><div class=\"core-container\"><div>Coastal wetlands are not only among the world’s most valued ecosystems but also among the most threatened by high greenhouse gas emissions that lead to accelerated sea level rise. There is intense debate regarding the extent to which landward migration of wetlands might compensate for seaward wetland losses. By integrating data from 166 estuaries across the conterminous United States, we show that landward migration of coastal wetlands will transform coastlines but not counter seaward losses. Two-thirds of potential migration is expected to occur at the expense of coastal freshwater wetlands, while the remaining one-third is expected to occur at the expense of valuable uplands, including croplands, forests, pastures, and grasslands. Our analyses underscore the need to better prepare for coastal transformations and net wetland loss due to rising seas.</div></div></div>","language":"English","publisher":"American Association for the Advancement of Science","doi":"10.1126/sciadv.abo5174","usgsCitation":"Osland, M., Chivoiu, B., Enwright, N., Thorne, K., Guntenspergen, G.R., Grace, J., Dale, L., Brooks, W., Herold, N., Day, J.W., Sklar, F.H., and Swarzenski, C.M., 2022, Migration and transformation of coastal wetlands in response to rising seas: Science Advances, v. 8, no. 26, eabo5174, 9 p.; Data Release, https://doi.org/10.1126/sciadv.abo5174.","productDescription":"eabo5174, 9 p.; Data Release","ipdsId":"IP-135577","costCenters":[{"id":369,"text":"Louisiana Water Science Center","active":true,"usgs":true},{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":447280,"rank":4,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1126/sciadv.abo5174","text":"External Repository"},{"id":435791,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P96D1J6Z","text":"USGS data release","linkHelpText":"Potential landward migration of coastal wetlands in response to sea-level rise within estuarine drainage areas and coastal states of the conterminous United States"},{"id":404479,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":417834,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9LPN3YY"}],"country":"United States","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n         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Center","active":true,"usgs":true}],"preferred":true,"id":847534,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chivoiu, Bogdan 0000-0002-4568-3496","orcid":"https://orcid.org/0000-0002-4568-3496","contributorId":206950,"corporation":false,"usgs":true,"family":"Chivoiu","given":"Bogdan","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":847535,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Enwright, Nicholas 0000-0002-7887-3261","orcid":"https://orcid.org/0000-0002-7887-3261","contributorId":201678,"corporation":false,"usgs":true,"family":"Enwright","given":"Nicholas","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":847536,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Thorne, Karen M. 0000-0002-1381-0657","orcid":"https://orcid.org/0000-0002-1381-0657","contributorId":204579,"corporation":false,"usgs":true,"family":"Thorne","given":"Karen M.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":847537,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Guntenspergen, Glenn R. 0000-0002-8593-0244 glenn_guntenspergen@usgs.gov","orcid":"https://orcid.org/0000-0002-8593-0244","contributorId":2885,"corporation":false,"usgs":true,"family":"Guntenspergen","given":"Glenn","email":"glenn_guntenspergen@usgs.gov","middleInitial":"R.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":847538,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Grace, James 0000-0001-6374-4726","orcid":"https://orcid.org/0000-0001-6374-4726","contributorId":206247,"corporation":false,"usgs":true,"family":"Grace","given":"James","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":847539,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Dale, Leah 0000-0002-3480-9954 ldale@usgs.gov","orcid":"https://orcid.org/0000-0002-3480-9954","contributorId":191022,"corporation":false,"usgs":true,"family":"Dale","given":"Leah","email":"ldale@usgs.gov","affiliations":[],"preferred":true,"id":847540,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Brooks, William","contributorId":287421,"corporation":false,"usgs":false,"family":"Brooks","given":"William","affiliations":[{"id":61577,"text":"NOAA NOS","active":true,"usgs":false}],"preferred":false,"id":847541,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Herold, Nathaniel","contributorId":140258,"corporation":false,"usgs":false,"family":"Herold","given":"Nathaniel","email":"","affiliations":[{"id":12641,"text":"NOAA NMFS","active":true,"usgs":false}],"preferred":false,"id":847542,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Day, John W.","contributorId":200323,"corporation":false,"usgs":false,"family":"Day","given":"John","email":"","middleInitial":"W.","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":847543,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Sklar, Fred H.","contributorId":195576,"corporation":false,"usgs":false,"family":"Sklar","given":"Fred","email":"","middleInitial":"H.","affiliations":[{"id":27553,"text":"South Florida Water Management District, West Palm Beach, FL","active":true,"usgs":false}],"preferred":false,"id":847544,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Swarzenski, Christopher M. 0000-0001-9843-1471 cswarzen@usgs.gov","orcid":"https://orcid.org/0000-0001-9843-1471","contributorId":656,"corporation":false,"usgs":true,"family":"Swarzenski","given":"Christopher","email":"cswarzen@usgs.gov","middleInitial":"M.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":369,"text":"Louisiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":847545,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}}
,{"id":70232349,"text":"sir20225048 - 2022 - Hydrogeology and simulation of groundwater flow in the Lucerne Valley groundwater basin, California","interactions":[],"lastModifiedDate":"2022-07-07T17:32:15.946418","indexId":"sir20225048","displayToPublicDate":"2022-06-28T14:08:07","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":"2022-5048","displayTitle":"Hydrogeology and Simulation of Groundwater Flow in the Lucerne Valley Groundwater Basin, California","title":"Hydrogeology and simulation of groundwater flow in the Lucerne Valley groundwater basin, California","docAbstract":"<p>The Lucerne Valley is in the southwestern part of the Mojave Desert and is about 75 miles northeast of Los Angeles, California. The Lucerne Valley groundwater basin encompasses about 230 square miles and is separated from the Upper Mojave Valley groundwater basin by splays of the Helendale Fault. Since its settlement, groundwater has been the primary source of water for agricultural, industrial, municipal, and domestic uses. Groundwater withdrawal from pumping has exceeded the amount of water recharged to the basin, causing groundwater declines of more than 100 feet between 1917 and 2016 in the center of the basin. The continued withdrawal has resulted in an increase in pumping costs, reduced well efficiency, and land subsidence near Lucerne Lake. Although the volume of pumping has declined in recent years, there is concern that new agricultural growth and limits on imported water will continue to strain the sustainability of the groundwater system.</p><p>To address these concerns, the U.S. Geological Survey entered into a cooperative agreement with the Mojave Water Agency to develop a better understanding of the Lucerne Valley hydrogeologic system and provide tools to help evaluate and manage the effects of future development in the Lucerne Valley. The objectives of this study were to (1) improve the understanding of the aquifer system, (2) improve the understanding of subsidence in the basin, and (3) incorporate the understanding into a groundwater-flow model that can be used to help manage the groundwater resources in the Lucerne Valley. The model developed for this study covers the period of 1942–2016 and can help evaluate various proposed water-management scenarios during different climatic and hydrologic conditions.</p><p>The aquifer system consists of a shallow aquifer, a confining unit, and middle and lower aquifers. These layered water-bearing units were identified based on geologic units of the mostly unconsolidated sediments and hydrologic properties. These alluvial deposits consist of clay, silt, sand, and gravel; some places also contain clay and silty clay lacustrine deposits. Several faults act, at least in part, as barriers to groundwater flow on the eastern, southern, and western edges of the basin. Present-day natural recharge is primarily from the infiltration of runoff from the San Bernardino Mountains to the south; however, stable and radioactive isotopes show that groundwater from the middle of the Lucerne Valley was older than about 10,000 years and probably was recharged as infiltration from streams draining the mountains in the Mojave Desert to the north, which probably does not occur under present-day climatic conditions. The annual average natural recharge for 1942–2016, estimated by a Basin Characterization Model, was about 635 acre-feet per year; the average amount of treated wastewater effluent transferred to the Lucerne Valley for artificial recharge annually ranged from about 1,500 to 4,000 acre-feet per year during 1980–2016. Pumpage estimates for 1942–2016 ranged from about 3,000 acre-feet in 1942 to about 18,300 acre-feet in 1984. The total cumulative amount of groundwater removed from the basin by pumping between 1942 and 2016 was estimated to be about 700,000 acre-feet, which was about 10 times greater than the cumulative amount of recharge to the entire Lucerne Valley groundwater basin. Before groundwater development, the direction of groundwater flow was from the southern part of the basin northward to discharge areas near Lucerne Lake, where it discharged through springs along the Helendale Fault and by evapotranspiration. Since the early 1900s, groundwater-level declines have mostly eliminated the areas where natural discharge occurred and exceeded 100 feet in the middle of the basin between the early 1950s and mid-1990s, and as much as 25 feet near the margins from about the mid-1950s to 2000s. A decrease in the rate of pumping after the mid-1990s lessened the hydraulic stress on the middle and lower aquifers and enabled hydraulic heads in the middle of the basin to recover slightly as groundwater near the margins of the basin moved toward the pumping depression. Although trends in groundwater levels in the center of the basin have reversed since the mid-1990s, levels at the basin margins continue to decline as the movement of groundwater from the margins fills the pumping depression and gradually flattens the groundwater table throughout the basin.</p><p>The long-term extraction of groundwater and associated dewatering of the fine-grained sediments present within the aquifer system has resulted in aquifer compaction and consequently land subsidence, primarily near Lucerne Lake. Analysis of interferometric synthetic aperture radar data shows that almost 11 inches of land subsidence has occurred south of Lucerne Lake between April 1992 and November 2009; less subsidence occurred elsewhere in the basin during this period. This differential land subsidence has caused fissures and cracks in the ground surface, which have buckled the pavement and undercut roads in several locations.</p><p>The Lucerne Valley Hydrologic Model was developed using the finite-difference groundwater modeling software One Water Hydrologic Model to represent the hydrologic conditions and stresses during 1942–2016. The model has a uniform grid of approximately 92 acres per cell (2,000 feet by 2,000 feet) and has four layers representing the water-bearing units. The results from the calibrated model simulations indicated that groundwater pumpage exceeded recharge, resulting in an estimated net cumulative depletion of groundwater storage (discharge minus recharge) of about 465,000 acre-feet from 1942 to 2016. The model simulated as much as 7.5 feet (90 inches; 2,286 millimeters) of aquifer compaction, which indicates the extensive fine-grained deposits and measured subsidence near Lucerne Lake.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225048","collaboration":"Prepared in cooperation with the Mojave Water Agency","usgsCitation":"Stamos, C.L., Larsen, J.D., Powell, R.E., Matti, J.C., and Martin, P., 2022, Hydrogeology and simulation of groundwater flow in the Lucerne Valley groundwater basin, California: U.S. Geological Survey Scientific Investigations Report 2022-5048, 120 p., https://doi.org/10.3133/sir20225048.","productDescription":"Report: xi, 120 p.; Appendix; Data Release","numberOfPages":"120","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-095487","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":403187,"rank":8,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20221063","text":"Open-File Report 2022-1063","description":"Fackrell, J.K., 2022, Groundwater quality of the Lucerne Valley groundwater basin, California: U.S. Geological Survey Open-File Report 2022-1063, 19 p., https://doi.org/10.3133/ofr20221063.","linkHelpText":"- Groundwater Quality of the Lucerne Valley Groundwater Basin, California"},{"id":402644,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P94W41EL","text":"MODFLOW-OWHM model used to simulate groundwater flow and evaluate storage in the Lucerne Valley Groundwater Basin, California","description":"Larsen, J.D., 2022, MODFLOW-OWHM model used to simulate groundwater flow and evaluate storage in the Lucerne Valley Groundwater Basin, California: U.S. Geological Survey data release, https://doi.org/10.5066/P94W41EL."},{"id":402643,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2022/5048/sir20225048_appendix1.txt","text":"Appendix 1","size":"27 KB","linkFileType":{"id":2,"text":"txt"},"linkHelpText":"- Sites with groundwater-level data available on the U. S. Geological Survey National Water Inventory System Web service (NWISWeb) from 1911-2016 within the Lucerne Valley, California"},{"id":402641,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2022/5048/sir20225048.xml"},{"id":402640,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5048/sir20225048.pdf","text":"Report","size":"20 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2022-5048"},{"id":402639,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5048/covrthb.jpg"},{"id":402695,"rank":7,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20225048/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2022-5048"},{"id":402642,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2022/5048/images"}],"country":"United States","state":"California","otherGeospatial":"Lucerne Valley Groundwater Basin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -116.666667,\n              34.266667\n            ],\n            [\n              -117.083333,\n              34.266667\n            ],\n            [\n              -117.083333,\n              34.666667\n            ],\n            [\n              -116.666667,\n              34.666667\n            ],\n            [\n              -116.666667,\n              34.266667\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p><a href=\"mailto:dc_ca@usgs.gov\" data-mce-href=\"mailto:dc_ca@usgs.gov\">Director</a>,<br><a href=\"https://ca.water.usgs.gov/\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://ca.water.usgs.gov\">California Water Science Center</a><br><a href=\"https://usgs.gov/\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://usgs.gov\">U.S. Geological Survey</a><br>6000 J Street, Placer Hall<br>Sacramento, California 95819</p>","tableOfContents":"<ul><li>Acknowledgments&nbsp;&nbsp;</li><li>Abstract&nbsp;&nbsp;</li><li>Introduction&nbsp;&nbsp;</li><li>Description of the Study Area&nbsp;&nbsp;</li><li>Hydrogeology&nbsp;&nbsp;</li><li>Lucerne Valley Hydrologic Model&nbsp;&nbsp;</li><li>Summary and Conclusions&nbsp;&nbsp;</li><li>References Cited&nbsp;&nbsp;</li><li>Appendix 1. Sites with Groundwater-Level Data Available on the U.S. Geological Survey National Water Inventory System Web System (NWISWeb) from 1911 to 2016, in the Lucerne Valley, California&nbsp;</li></ul>","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"publishedDate":"2022-06-28","noUsgsAuthors":false,"publicationDate":"2022-06-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Stamos-Pfeiffer, Christina 0000-0002-1007-9352 clstamos@usgs.gov","orcid":"https://orcid.org/0000-0002-1007-9352","contributorId":169089,"corporation":false,"usgs":true,"family":"Stamos-Pfeiffer","given":"Christina","email":"clstamos@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":845310,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Larsen, Joshua 0000-0002-1218-800X jlarsen@usgs.gov","orcid":"https://orcid.org/0000-0002-1218-800X","contributorId":272403,"corporation":false,"usgs":true,"family":"Larsen","given":"Joshua","email":"jlarsen@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":845311,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Powell, Robert E. 0000-0001-7682-1655 rpowell@usgs.gov","orcid":"https://orcid.org/0000-0001-7682-1655","contributorId":4210,"corporation":false,"usgs":true,"family":"Powell","given":"Robert","email":"rpowell@usgs.gov","middleInitial":"E.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":845312,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Matti, Jonathan C. 0000-0001-5961-9869 jmatti@usgs.gov","orcid":"https://orcid.org/0000-0001-5961-9869","contributorId":167192,"corporation":false,"usgs":true,"family":"Matti","given":"Jonathan","email":"jmatti@usgs.gov","middleInitial":"C.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":845313,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Martin, Peter pmmartin@usgs.gov","contributorId":799,"corporation":false,"usgs":true,"family":"Martin","given":"Peter","email":"pmmartin@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":845314,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70232320,"text":"sir20225020 - 2022 - Assessment of persistent chemicals of concern in white sturgeon (Acipenser transmontanus) in the Hanford Reach of the Columbia River, southeastern Washington, 2009","interactions":[],"lastModifiedDate":"2026-04-09T16:50:47.612392","indexId":"sir20225020","displayToPublicDate":"2022-06-28T11:04:42","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":"2022-5020","displayTitle":"Assessment of Persistent Chemicals of Concern in White Sturgeon (<em>Acipenser transmontanus</em>) in the Hanford Reach of the Columbia River, Southeastern Washington, 2009","title":"Assessment of persistent chemicals of concern in white sturgeon (Acipenser transmontanus) in the Hanford Reach of the Columbia River, southeastern Washington, 2009","docAbstract":"<p class=\"p1\">White sturgeon (<i>Acipenser transmontanus</i>) are long-lived, late-maturing, benthic-feeding fish that are ideal candidates for assessing the bioaccumulation of persistent chemicals. In this study, composite tissue samples of brain, liver, gonad, and fillet were collected from white sturgeon in 2009 from five sites in the Hanford Reach of the Columbia River near Hanford, Washington. The composite tissue samples at each site were analyzed for the concentrations of individual chemicals as well as the total concentrations of four chemical classes: (1) organochlorine (OC) pesticides, (2) industrial or personal care products, (3) polybrominated diphenyl ether (PBDE) congeners, and (4) polychlorinated biphenyl (PCB) congeners. The results showed that chemicals from all four classes were present in the fish, and that OC pesticides and degradation products (such as oxychlordane, fipronil sulfide, and dichlorodiphenyltrichloroethane (DDT) degradates, PBDE congeners, and PCB congeners) often were present in all tissues and at all sites. Gonad tissues generally had the highest total concentration of each chemical class, followed by brains, livers, and fillets. The concentrations of several chemicals or chemical classes exceeded many of the human health benchmarks for two different populations (general/recreational consumers and subsistence/Tribal consumers), and this was especially true for the total concentrations of DDT degradation products and PCB congeners. These results suggest that continued monitoring of resident fish in the Hanford Reach, as well as assessments of the health impacts on consumers of those fish, are warranted.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225020","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service","usgsCitation":"Payne, S.E., Wise, D.R., Davis, J.W., and Nilsen, E.B., 2022, Assessment of persistent chemicals of concern in white sturgeon (Acipenser transmontanus) in the Hanford Reach of the Columbia River, southeastern Washington, 2009: U.S. Geological Survey Scientific Investigations Report 2022–5020, 25 p., https://doi.org/10.3133/sir20225020.","productDescription":"vii, 25 p.","onlineOnly":"Y","ipdsId":"IP-113471","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":402577,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5020/coverthb.jpg"},{"id":402579,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2022/5020/images"},{"id":402580,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2022/5020/sir20225020.XML"},{"id":402578,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5020/sir20225020.pdf","text":"Report","size":"1.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2022-5020"},{"id":402624,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.er.usgs.gov/publication/sir20225020/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2022-5020"},{"id":502374,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113220.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Washington","otherGeospatial":"Columbia River","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -120.05859375,\n              46.13417004624326\n            ],\n            [\n              -118.89404296875,\n              46.13417004624326\n            ],\n            [\n              -118.89404296875,\n              46.95776134668866\n            ],\n            [\n              -120.05859375,\n              46.95776134668866\n            ],\n            [\n              -120.05859375,\n              46.13417004624326\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p><a href=\"mailto:dc_or@usgs.gov\" data-mce-href=\"mailto:dc_or@usgs.gov\">Director</a>, <a href=\"https://www.usgs.gov/centers/oregon-water-science-center\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://www.usgs.gov/centers/oregon-water-science-center\">Oregon Water Science Center</a><br>U.S. Geological Survey<br>2130 SW 5th Avenue<br>Portland, Oregon 97201</p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Methods</li><li>Results</li><li>Discussion</li><li>Conclusions</li><li>References Cited</li></ul>","publishedDate":"2022-06-28","noUsgsAuthors":false,"publicationDate":"2022-06-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Payne, Sean E. 0000-0003-1836-1886 spayne@usgs.gov","orcid":"https://orcid.org/0000-0003-1836-1886","contributorId":292581,"corporation":false,"usgs":true,"family":"Payne","given":"Sean","email":"spayne@usgs.gov","middleInitial":"E.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":845247,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wise, Daniel R. 0000-0002-1215-9612 dawise@usgs.gov","orcid":"https://orcid.org/0000-0002-1215-9612","contributorId":29891,"corporation":false,"usgs":true,"family":"Wise","given":"Daniel","email":"dawise@usgs.gov","middleInitial":"R.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":false,"id":845248,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Davis, Jay W.","contributorId":219459,"corporation":false,"usgs":false,"family":"Davis","given":"Jay","email":"","middleInitial":"W.","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":845249,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Nilsen, Elena B. 0000-0002-0104-6321 enilsen@usgs.gov","orcid":"https://orcid.org/0000-0002-0104-6321","contributorId":923,"corporation":false,"usgs":true,"family":"Nilsen","given":"Elena","email":"enilsen@usgs.gov","middleInitial":"B.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":845250,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70232319,"text":"ofr20221054 - 2022 - Potential effects of sea level rise on nearshore habitat availability for surf smelt (Hypomesus pretiosus) and eelgrass (Zostera marina), Puget Sound, Washington","interactions":[],"lastModifiedDate":"2026-03-27T20:25:13.436574","indexId":"ofr20221054","displayToPublicDate":"2022-06-28T09:59:47","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2022-1054","displayTitle":"Potential Effects of Sea Level Rise on Nearshore Habitat Availability for Surf Smelt (<em>Hypomesus pretiosus</em>) and Eelgrass (<em>Zostera marina</em>), Puget Sound, Washington","title":"Potential effects of sea level rise on nearshore habitat availability for surf smelt (Hypomesus pretiosus) and eelgrass (Zostera marina), Puget Sound, Washington","docAbstract":"<p class=\"p1\">In this study we examine the potential effects of three predicted sea level rise (SLR) scenarios on the nearshore eelgrass (<i>Zostera marina </i>L.) and surf smelt (<i>Hypomesus pretiosus</i>) spawning habitats along a beach on Bainbridge Island, Washington. Baseline bathymetric, geomorphological, and biological surveys were conducted to determine the existing conditions at the study site. The results of these surveys were coupled with a predictive model that estimates SLR-induced changes to coastal ecosystems based upon local topography and land-cover data. This model simulates the changes in nearshore habitat through time. The model inputs for SLR are probable values reported by the Intergovernmental Panel on Climate Change, and by user-defined values. The predicted effects of SLR are presented as (1) habitat type change and (2) the graphic response of developed dry land depicting the influence of shoreline armoring. This report describes the geophysical and biological characteristics at the Bainbridge Island study site, the modeling methods used to produce depictions of habitat changes, and a possible decrease in surf smelt spawning and an increase in eelgrass habitat availability in response to increases in sea level.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221054","usgsCitation":"Smith, C.D., and Liedtke, T.L., 2022, Potential effects of sea level rise on nearshore habitat availability for surf smelt (Hypomesus pretiosus) and eelgrass (Zostera marina), Puget Sound, Washington: U.S. Geological Survey Open-File Report 2022–1054, 17 p., https://doi.org/10.3133/ofr20221054.","productDescription":"Report: v, 17 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-117971","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":402574,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9HGJ3ZH","text":"USGS data release","description":"USGS Data Release.","linkHelpText":"Data collected in 2010 to evaluate habitat availability for surf smelt and eelgrass in response to sea level rise on Bainbridge Island, Puget Sound, Washington State, USA"},{"id":402572,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1054/coverthb.jpg"},{"id":402573,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1054/ofr20221054.pdf","text":"Report","size":"21.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022-1054"},{"id":402619,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.er.usgs.gov/publication/ofr20221054/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2022-1054"},{"id":402575,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1054/images"},{"id":402576,"rank":6,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1054/ofr20221054.XML"},{"id":501780,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113219.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Washington","otherGeospatial":"Puget Sound","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -122.6678466796875,\n              47.487513008956554\n            ],\n            [\n              -122.23937988281251,\n              47.487513008956554\n            ],\n            [\n              -122.23937988281251,\n              47.964180715412276\n            ],\n            [\n              -122.6678466796875,\n              47.964180715412276\n            ],\n            [\n              -122.6678466796875,\n              47.487513008956554\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p>Director, <a href=\"https://www.usgs.gov/centers/wfrc\" data-mce-href=\"https://www.usgs.gov/centers/wfrc\">Western Fisheries Research Center</a><br>U.S. Geological Survey<br>6505 NE 65th Street<br>Seattle, Washington 98115-5016</p>","tableOfContents":"<ul><li>Abstract</li><li>Introduction</li><li>Methods</li><li>Study Methods</li><li>Results of Data Analyses</li><li>Discussion—Current Status and Effects of Sea Level Rise on Changes in Nearshore Habitat</li><li>Acknowledgments</li><li>References Cited</li></ul>","publishedDate":"2022-06-28","noUsgsAuthors":false,"publicationDate":"2022-06-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Smith, Collin D. 0000-0003-4184-5686 cdsmith@usgs.gov","orcid":"https://orcid.org/0000-0003-4184-5686","contributorId":7915,"corporation":false,"usgs":true,"family":"Smith","given":"Collin D.","email":"cdsmith@usgs.gov","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":false,"id":845245,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Liedtke, Theresa L. 0000-0001-6063-9867 tliedtke@usgs.gov","orcid":"https://orcid.org/0000-0001-6063-9867","contributorId":2999,"corporation":false,"usgs":true,"family":"Liedtke","given":"Theresa","email":"tliedtke@usgs.gov","middleInitial":"L.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":845246,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70254547,"text":"70254547 - 2022 - Medium spatial resolution mapping of global land cover and land cover change across multiple decades from Landsat","interactions":[],"lastModifiedDate":"2024-05-31T14:27:00.972651","indexId":"70254547","displayToPublicDate":"2022-06-28T09:20:57","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":17157,"text":"Frontiers in Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Medium spatial resolution mapping of global land cover and land cover change across multiple decades from Landsat","docAbstract":"<p><span>Land cover maps are essential for characterizing the biophysical properties of the Earth’s land areas. Because land cover information synthesizes a rich array of information related to both the ecological condition of land areas and their exploitation by humans, they are widely used for basic and applied research that requires information related to land surface properties (e.g., terrestrial carbon models, water balance models, weather, and climate models) and are core inputs to models and analyses used by natural resource scientists and land managers. As the Earth’s global population has grown over the last several decades rates of land cover change have increased dramatically, with enormous impacts on ecosystem services (e.g., biodiversity, water supply, carbon sequestration, etc.). Hence, accurate information related to land cover is essential for both managing natural resources and for understanding society’s ecological, biophysical, and resource management footprint. To address the need for high-quality land cover information we are using the global record of Landsat observations to compile annual maps of global land cover from 2001 to 2020 at 30&nbsp;m spatial resolution. To create these maps we use features derived from time series of Landsat imagery in combination with ancillary geospatial data and a large database of training sites to classify land cover at annual time step. The algorithm that we apply uses temporal segmentation to identify periods with stable land cover that are separated by breakpoints in the time series. Here we provide an overview of the methods and data sets we are using to create global maps of land cover. We describe the algorithms used to create these maps and the core land cover data sets that we are creating through this effort, and we summarize our approach to accuracy assessment. We also present a synthesis of early results and discuss the strengths and weaknesses of our early map products and the challenges that we have encountered in creating global land cover data sets from Landsat. Initial accuracy assessment for North America shows good overall accuracy (77.0 ± 2.0% correctly classified) and 79.8% agreement with the European Space Agency (ESA) WorldCover product. The land cover mapping results we report provide the foundation for robust, repeatable, and accurate mapping of global land cover and land cover change across multiple decades at 30&nbsp;m spatial resolution from Landsat.</span></p>","language":"English","publisher":"Frontiers Media","doi":"10.3389/frsen.2022.894571","usgsCitation":"Friedl, M.A., Woodcock, C.E., Olofsson, P., Zhu, Z., Loveland, T., Stanimirova, R., Arevalo, P., Bullock, E.L., Hu, K., Zhang, Y., Turlej, K., Tarrio, K., Kristina, M., Gorelick, N., Wang, J.A., Barber, C., and Souza Jr., C., 2022, Medium spatial resolution mapping of global land cover and land cover change across multiple decades from Landsat: Frontiers in Remote Sensing, v. 3, 894571, 15 p., https://doi.org/10.3389/frsen.2022.894571.","productDescription":"894571, 15 p.","ipdsId":"IP-142442","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":447282,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/frsen.2022.894571","text":"Publisher Index Page"},{"id":429402,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"3","noUsgsAuthors":false,"publicationDate":"2022-06-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Friedl, Mark A.","contributorId":337043,"corporation":false,"usgs":false,"family":"Friedl","given":"Mark","email":"","middleInitial":"A.","affiliations":[{"id":80956,"text":"University of Boston","active":true,"usgs":false}],"preferred":false,"id":901837,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Woodcock, Curtis E.","contributorId":294423,"corporation":false,"usgs":false,"family":"Woodcock","given":"Curtis","email":"","middleInitial":"E.","affiliations":[{"id":13570,"text":"Boston University","active":true,"usgs":false}],"preferred":false,"id":901838,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Olofsson, Pontus","contributorId":131007,"corporation":false,"usgs":false,"family":"Olofsson","given":"Pontus","email":"","affiliations":[{"id":7208,"text":"Department of Earth and Environment, Boston University","active":true,"usgs":false}],"preferred":false,"id":901839,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Zhu, Zhe 0000-0003-4716-2309","orcid":"https://orcid.org/0000-0003-4716-2309","contributorId":272038,"corporation":false,"usgs":false,"family":"Zhu","given":"Zhe","affiliations":[{"id":36710,"text":"University of Connecticut","active":true,"usgs":false}],"preferred":false,"id":901840,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Loveland, Thomas R. 0000-0003-3114-6646","orcid":"https://orcid.org/0000-0003-3114-6646","contributorId":337044,"corporation":false,"usgs":false,"family":"Loveland","given":"Thomas R.","affiliations":[{"id":7248,"text":"emeritus USGS","active":true,"usgs":false}],"preferred":false,"id":901841,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Stanimirova, Radost","contributorId":337045,"corporation":false,"usgs":false,"family":"Stanimirova","given":"Radost","email":"","affiliations":[{"id":80956,"text":"University of Boston","active":true,"usgs":false}],"preferred":false,"id":901842,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Arevalo, Paulo","contributorId":337046,"corporation":false,"usgs":false,"family":"Arevalo","given":"Paulo","email":"","affiliations":[{"id":80956,"text":"University of Boston","active":true,"usgs":false}],"preferred":false,"id":901843,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Bullock, Eric L. 0000-0003-3279-6771","orcid":"https://orcid.org/0000-0003-3279-6771","contributorId":224710,"corporation":false,"usgs":false,"family":"Bullock","given":"Eric","email":"","middleInitial":"L.","affiliations":[{"id":40922,"text":"Department of Earth & Environment, Boston University","active":true,"usgs":false}],"preferred":false,"id":901844,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Hu, Kai-Ting","contributorId":337047,"corporation":false,"usgs":false,"family":"Hu","given":"Kai-Ting","email":"","affiliations":[{"id":80956,"text":"University of Boston","active":true,"usgs":false}],"preferred":false,"id":901845,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Zhang, Yingtong","contributorId":337048,"corporation":false,"usgs":false,"family":"Zhang","given":"Yingtong","email":"","affiliations":[{"id":80956,"text":"University of Boston","active":true,"usgs":false}],"preferred":false,"id":901846,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Turlej, Konrad","contributorId":337049,"corporation":false,"usgs":false,"family":"Turlej","given":"Konrad","email":"","affiliations":[{"id":78943,"text":"Jagiellonian University","active":true,"usgs":false}],"preferred":false,"id":901847,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Tarrio, Katelyn","contributorId":337050,"corporation":false,"usgs":false,"family":"Tarrio","given":"Katelyn","email":"","affiliations":[{"id":80956,"text":"University of Boston","active":true,"usgs":false}],"preferred":false,"id":901848,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Kristina, McAvoy","contributorId":337051,"corporation":false,"usgs":false,"family":"Kristina","given":"McAvoy","email":"","affiliations":[{"id":80956,"text":"University of Boston","active":true,"usgs":false}],"preferred":false,"id":901849,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Gorelick, Noel","contributorId":294417,"corporation":false,"usgs":false,"family":"Gorelick","given":"Noel","affiliations":[{"id":12484,"text":"Google","active":true,"usgs":false}],"preferred":false,"id":901850,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Wang, Jonathan A.","contributorId":337052,"corporation":false,"usgs":false,"family":"Wang","given":"Jonathan","email":"","middleInitial":"A.","affiliations":[{"id":6976,"text":"University of California, Irvine","active":true,"usgs":false}],"preferred":false,"id":901851,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Barber, Christopher P. 0000-0003-0570-1140","orcid":"https://orcid.org/0000-0003-0570-1140","contributorId":223102,"corporation":false,"usgs":true,"family":"Barber","given":"Christopher","middleInitial":"P.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":901852,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Souza Jr., Carlos","contributorId":337053,"corporation":false,"usgs":false,"family":"Souza Jr.","given":"Carlos","affiliations":[{"id":80958,"text":"IMAZON","active":true,"usgs":false}],"preferred":false,"id":901853,"contributorType":{"id":1,"text":"Authors"},"rank":17}]}}
,{"id":70232344,"text":"70232344 - 2022 - Biofilms in the Critical Zone: Distribution and mediation of processes","interactions":[],"lastModifiedDate":"2022-06-28T13:30:54.444935","indexId":"70232344","displayToPublicDate":"2022-06-28T08:24:40","publicationYear":"2022","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"4","title":"Biofilms in the Critical Zone: Distribution and mediation of processes","docAbstract":"Microbial biofilms occur in all levels of the Critical Zone (CZ); they are on and in the vegetation, throughout the soil-saprolite zone, and along fractures in deep subsurface. Here we discuss biofilms in each level of the CZ with a focus in the soil-saprolite continuum. We show how scanning electron microscope (SEM) images provide an appropriate scale to explore microbe mineral interactions in the CZ and can be used without extensive sample preparation. Through SEM imaging, we show that biofilms weather primary minerals, that macropores and fractures are hotspots of biofilm development, that biologic precipitation of short-range-order minerals (SROs) occurs in biofilms, and that biofilms are important in the process of organic matter stabilization.","largerWorkTitle":"Biogeochemistry of the Critical Zone","language":"English","publisher":"Springer","doi":"10.1007/978-3-030-95921-0_4","usgsCitation":"Schulz, M., and Manies, K.L., 2022, Biofilms in the Critical Zone: Distribution and mediation of processes, chap. 4 <i>of</i> Biogeochemistry of the Critical Zone, p. 89-119, https://doi.org/10.1007/978-3-030-95921-0_4.","productDescription":"31  p.","startPage":"89","endPage":"119","ipdsId":"IP-105346","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":402593,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Critical Zone, Earth","noUsgsAuthors":false,"publicationDate":"2022-05-17","publicationStatus":"PW","contributors":{"editors":[{"text":"Wymore, Adam S.","contributorId":243438,"corporation":false,"usgs":false,"family":"Wymore","given":"Adam","email":"","middleInitial":"S.","affiliations":[{"id":12667,"text":"University of New Hampshire","active":true,"usgs":false}],"preferred":false,"id":845300,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Yang, Wendy H.","contributorId":292622,"corporation":false,"usgs":false,"family":"Yang","given":"Wendy","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":845301,"contributorType":{"id":2,"text":"Editors"},"rank":2},{"text":"Silver, Whendee L.","contributorId":80998,"corporation":false,"usgs":true,"family":"Silver","given":"Whendee L.","affiliations":[],"preferred":false,"id":845302,"contributorType":{"id":2,"text":"Editors"},"rank":3},{"text":"McDowell, William H.","contributorId":97233,"corporation":false,"usgs":true,"family":"McDowell","given":"William","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":845303,"contributorType":{"id":2,"text":"Editors"},"rank":4},{"text":"Chorover, Jon 0000-0001-9497-0195","orcid":"https://orcid.org/0000-0001-9497-0195","contributorId":139472,"corporation":false,"usgs":false,"family":"Chorover","given":"Jon","email":"","affiliations":[],"preferred":false,"id":845304,"contributorType":{"id":2,"text":"Editors"},"rank":5}],"authors":[{"text":"Schulz, Marjorie S. 0000-0001-5597-6447 mschulz@usgs.gov","orcid":"https://orcid.org/0000-0001-5597-6447","contributorId":3720,"corporation":false,"usgs":true,"family":"Schulz","given":"Marjorie S.","email":"mschulz@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":845289,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Manies, Kristen L. 0000-0003-4941-9657 kmanies@usgs.gov","orcid":"https://orcid.org/0000-0003-4941-9657","contributorId":2136,"corporation":false,"usgs":true,"family":"Manies","given":"Kristen","email":"kmanies@usgs.gov","middleInitial":"L.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":845290,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70232351,"text":"70232351 - 2022 - Asking nicely: Best practices for requesting data","interactions":[],"lastModifiedDate":"2022-06-29T12:37:39.400674","indexId":"70232351","displayToPublicDate":"2022-06-28T07:35:37","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1456,"text":"Ecological Indicators","active":true,"publicationSubtype":{"id":10}},"title":"Asking nicely: Best practices for requesting data","docAbstract":"<div id=\"abstracts\" class=\"Abstracts u-font-serif\"><div id=\"ab0005\" class=\"abstract author\" lang=\"en\"><div id=\"as0005\"><p id=\"sp0055\">Compiling disparate datasets into publicly available composite databases helps natural resource communities explore ecological trends and effectively manage across spatiotemporal scales. Though some studies have reported on the database construction phase, fewer have evaluated the data acquisition and distribution process. To facilitate future data sharing collaborations, Louisiana State University surveyed data providers and requestors to understand the characteristics of effective data requests and sharing. Data providers were largely<span>&nbsp;</span>U.S.<span>&nbsp;</span>natural resource agency personnel, and they reported that unclear data requests, privacy issues, and rigid timelines and formats were the greatest barriers toward providing data, but that they were motivated by improving science and collaboration. Data requestors identified challenges such as evolving needs, standardization issues, and insufficient resources (time and funding) as barriers to compiling data for these types of efforts. In a time of big data, open access, and collaboration, significant scientific advances can be made with effective requests and inclusion of data sets into larger and more powerful databases.</p></div></div></div><ul id=\"issue-navigation\" class=\"issue-navigation u-margin-s-bottom u-bg-grey1\"></ul>","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecoinf.2022.101729","usgsCitation":"Midway, S.R., Sievert, N., Lynch, A., Whittier, J.B., and Pope, K.L., 2022, Asking nicely: Best practices for requesting data: Ecological Indicators, v. 70, 101729, 9 p., https://doi.org/10.1016/j.ecoinf.2022.101729.","productDescription":"101729, 9 p.","ipdsId":"IP-137497","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":36940,"text":"National Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":500794,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://repository.lsu.edu/oceanography_coastal_pubs/1066","text":"External Repository"},{"id":402673,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"70","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Midway, Steve R.","contributorId":292624,"corporation":false,"usgs":false,"family":"Midway","given":"Steve","email":"","middleInitial":"R.","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":845319,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sievert, Nicholas A. 0000-0003-3160-7596","orcid":"https://orcid.org/0000-0003-3160-7596","contributorId":177341,"corporation":false,"usgs":false,"family":"Sievert","given":"Nicholas A.","affiliations":[],"preferred":false,"id":845320,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lynch, Abigail 0000-0001-8449-8392","orcid":"https://orcid.org/0000-0001-8449-8392","contributorId":220490,"corporation":false,"usgs":true,"family":"Lynch","given":"Abigail","affiliations":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true}],"preferred":true,"id":845321,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Whittier, Joanna B.","contributorId":53151,"corporation":false,"usgs":false,"family":"Whittier","given":"Joanna","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":845322,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Pope, Kevin L. 0000-0003-1876-1687","orcid":"https://orcid.org/0000-0003-1876-1687","contributorId":270762,"corporation":false,"usgs":true,"family":"Pope","given":"Kevin","email":"","middleInitial":"L.","affiliations":[{"id":506,"text":"Office of the AD Ecosystems","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":845323,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70231886,"text":"70231886 - 2022 - The role of organic matter diversity on the Re-Os systematics of organic-rich sedimentary units: Insights into the controls of isochron age determinations from the lacustrine Green River Formation","interactions":[],"lastModifiedDate":"2022-06-01T12:22:53.418642","indexId":"70231886","displayToPublicDate":"2022-06-28T07:20:33","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1213,"text":"Chemical Geology","active":true,"publicationSubtype":{"id":10}},"title":"The role of organic matter diversity on the Re-Os systematics of organic-rich sedimentary units: Insights into the controls of isochron age determinations from the lacustrine Green River Formation","docAbstract":"<div id=\"abstracts\" class=\"Abstracts u-font-serif\"><div id=\"ab0005\" class=\"abstract author\" lang=\"en\"><div id=\"as0005\"><p id=\"sp0080\">The range of<span>&nbsp;</span><sup>187</sup>Re/<sup>188</sup><span>Os values measured from samples of five organic-rich lacustrine&nbsp;<a class=\"topic-link\" title=\"Learn more about mudstones from ScienceDirect's AI-generated Topic Pages\" href=\"https://www.sciencedirect.com/topics/earth-and-planetary-sciences/mudstone\" data-mce-href=\"https://www.sciencedirect.com/topics/earth-and-planetary-sciences/mudstone\">mudstones</a>&nbsp;units in the&nbsp;<a class=\"topic-link\" title=\"Learn more about Eocene from ScienceDirect's AI-generated Topic Pages\" href=\"https://www.sciencedirect.com/topics/earth-and-planetary-sciences/eocene\" data-mce-href=\"https://www.sciencedirect.com/topics/earth-and-planetary-sciences/eocene\">Eocene</a>&nbsp;Green River Formation in the easternmost Uinta Basin covaries with organic matter diversity driven by changing water column conditions. A set of samples from the Douglas Creek Member has the highest pristane/phytane ratio and lowest β-carotane/</span><i>n</i>-C<sub>30</sub><span>&nbsp;ratio compared to overlying units, indicating deposition in an oxic-anoxic environment with low&nbsp;<a class=\"topic-link\" title=\"Learn more about salinity from ScienceDirect's AI-generated Topic Pages\" href=\"https://www.sciencedirect.com/topics/earth-and-planetary-sciences/salinity\" data-mce-href=\"https://www.sciencedirect.com/topics/earth-and-planetary-sciences/salinity\">salinity</a>&nbsp;that would have allowed for the accumulation of a diverse assemblage of aquatic organisms. These samples define the broadest&nbsp;</span><sup>187</sup>Re/<sup>188</sup>Os range of 1504. In contrast, samples from the R6 and Mahogany zones possess lower pristane/phytane ratios and higher β-carotane/<i>n</i>-C<sub>30</sub><span>&nbsp;ratios indicating deposition in a more restricted&nbsp;<a class=\"topic-link\" title=\"Learn more about lacustrine environment from ScienceDirect's AI-generated Topic Pages\" href=\"https://www.sciencedirect.com/topics/earth-and-planetary-sciences/lacustrine-environment\" data-mce-href=\"https://www.sciencedirect.com/topics/earth-and-planetary-sciences/lacustrine-environment\">lacustrine environment</a>&nbsp;with elevated salinities and alkalinities that would have limited aquatic organic matter diversity. The R6 and Mahogany zones have the narrowest range of&nbsp;</span><sup>187</sup>Re/<sup>188</sup>Os values measured in this study of 254.9 and 154.6, respectively. As noted by previous workers, these results suggest that organic matter diversity plays a primary role in determining the range of<span>&nbsp;</span><sup>187</sup>Re/<sup>188</sup>Os ratios in a sample set, and in turn the uncertainty of Re-Os age determinations from organic-rich sedimentary rocks.</p><p id=\"sp0085\">The Re-Os data from the R3 zone and R6 zone yield ages of 49.7&nbsp;±&nbsp;3.4&nbsp;Ma and 42.0&nbsp;±&nbsp;18&nbsp;Ma, respectively, which are statistically indistinguishable based on 2σ uncertainty from three previously reported Re-Os age determinations and those provided by<span>&nbsp;</span><sup>40</sup>Ar/<sup>39</sup><span>Ar&nbsp;<a class=\"topic-link\" title=\"Learn more about geochronology from ScienceDirect's AI-generated Topic Pages\" href=\"https://www.sciencedirect.com/topics/earth-and-planetary-sciences/geochronology\" data-mce-href=\"https://www.sciencedirect.com/topics/earth-and-planetary-sciences/geochronology\">geochronology</a>&nbsp;of interbedded volcanic ash beds. Although the age uncertainty is high, these findings further highlight the importance of Re-Os geochronology in lacustrine basins, particularly those with thick mudstone successions that lack volcanic ash layers, reliable&nbsp;<a class=\"topic-link\" title=\"Learn more about biostratigraphy from ScienceDirect's AI-generated Topic Pages\" href=\"https://www.sciencedirect.com/topics/earth-and-planetary-sciences/biostratigraphy\" data-mce-href=\"https://www.sciencedirect.com/topics/earth-and-planetary-sciences/biostratigraphy\">biostratigraphy</a>, or magnetostratigraphic control. In these cases, even ages with large uncertainties can be useful to constrain burial history and thermal history models.</span></p><p id=\"sp0090\">Together, the initial<span>&nbsp;</span><sup>187</sup>Os/<sup>188</sup><span>Os ratios of five sets of samples analyzed from the Uinta Basin define the largest Os isotope&nbsp;<a class=\"topic-link\" title=\"Learn more about stratigraphic record from ScienceDirect's AI-generated Topic Pages\" href=\"https://www.sciencedirect.com/topics/earth-and-planetary-sciences/geological-record\" data-mce-href=\"https://www.sciencedirect.com/topics/earth-and-planetary-sciences/geological-record\">stratigraphic record</a>&nbsp;from any lacustrine basin compiled to date and record a shift from a value of 1.40 to 1.48 between the R3 and R4 zones in the lower part of the Parachute Creek Member. This small shift may signify a change in the chemical weathering products that entered the lake preserved 20 to 50&nbsp;m above the contact between the Douglas Creek and the lower Parachute Creek members during a period when the basin transitioned from a shallow lake with mostly open hydrology to an alkaline lake with more frequent basin restrictions.</span></p></div></div></div><ul id=\"issue-navigation\" class=\"issue-navigation u-margin-s-bottom u-bg-grey1\"></ul>","language":"English","publisher":"Elsevier","doi":"10.1016/j.chemgeo.2022.120939","usgsCitation":"Pietras, J.T., Dennett, A., Selby, D., and Birdwell, J.E., 2022, The role of organic matter diversity on the Re-Os systematics of organic-rich sedimentary units: Insights into the controls of isochron age determinations from the lacustrine Green River Formation: Chemical Geology, v. 604, 120939, 14 p., https://doi.org/10.1016/j.chemgeo.2022.120939.","productDescription":"120939, 14 p.","ipdsId":"IP-134923","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":447288,"rank":1,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://dro.dur.ac.uk/36549/","text":"External Repository"},{"id":435792,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9FOH9BV","text":"USGS data release","linkHelpText":"Geochemistry data for a Re-Os geochronology study of the Eocene Green River Formation in Uinta Basin, Utah"},{"id":401526,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado, Utah, Wyoming","otherGeospatial":"Uinta Basin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -111.796875,\n              39.16414104768742\n            ],\n            [\n              -107.0068359375,\n              39.16414104768742\n            ],\n            [\n              -107.0068359375,\n              41.96765920367816\n            ],\n            [\n              -111.796875,\n              41.96765920367816\n            ],\n            [\n              -111.796875,\n              39.16414104768742\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"604","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Pietras, Jeffrey T","contributorId":292193,"corporation":false,"usgs":false,"family":"Pietras","given":"Jeffrey","email":"","middleInitial":"T","affiliations":[{"id":37769,"text":"Binghamton University","active":true,"usgs":false}],"preferred":false,"id":844035,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dennett, Abby","contributorId":292194,"corporation":false,"usgs":false,"family":"Dennett","given":"Abby","email":"","affiliations":[{"id":37769,"text":"Binghamton University","active":true,"usgs":false}],"preferred":false,"id":844036,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Selby, David","contributorId":193460,"corporation":false,"usgs":false,"family":"Selby","given":"David","email":"","affiliations":[],"preferred":false,"id":844037,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Birdwell, Justin E. 0000-0001-8263-1452 jbirdwell@usgs.gov","orcid":"https://orcid.org/0000-0001-8263-1452","contributorId":3302,"corporation":false,"usgs":true,"family":"Birdwell","given":"Justin","email":"jbirdwell@usgs.gov","middleInitial":"E.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true},{"id":569,"text":"Southwest Climate Science Center","active":true,"usgs":true}],"preferred":true,"id":844038,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70232362,"text":"70232362 - 2022 - Evaluating the efficacy of aerial infrared surveys to detect artificial polar bear dens","interactions":[],"lastModifiedDate":"2022-08-02T14:52:50.849712","indexId":"70232362","displayToPublicDate":"2022-06-28T07:19:25","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3779,"text":"Wildlife Society Bulletin","onlineIssn":"1938-5463","printIssn":"0091-7648","active":true,"publicationSubtype":{"id":10}},"title":"Evaluating the efficacy of aerial infrared surveys to detect artificial polar bear dens","docAbstract":"<div class=\"abstract-group\"><div class=\"article-section__content en main\"><p>The need to balance economic development with impacts to Arctic wildlife has been a prominent subject since petroleum exploration began on the North Slope of Alaska, USA, in the late 1950s. The North Slope region includes polar bears (<i>Ursus maritimus</i>) of the southern Beaufort Sea subpopulation, which has experienced a long-term decline in abundance. Pregnant polar bears dig dens in snow drifts during winter and are vulnerable to disturbance, as den abandonment and mortality of neonates may result. Maternal denning coincides with the peak season of petroleum exploration and construction, raising concerns that human activities may disrupt denning. To minimize disturbance of denning polar bears, aerial infrared (AIR) surveys are routinely used to search for dens within planned industry activity areas and that information is used to implement mitigation. Aerial infrared surveys target the heat signature emanating from dens. Despite use by industry for &gt;15 years, the efficacy of AIR and the factors that impact its ability to detect dens remains uncertain. Here, we evaluate AIR using artificial dens and observers naïve to locations to estimate detection probability and its relationship with covariates including weather variables, den characteristics, infrared sensor and altitude, and survey order to identify potential evidence of in-flight observer learning occurring between surveys. In December 2019 we constructed 14 dens (each with an artificial heat source), and 11 control sites (disturbed sites without dens). Between December 2019 and January 2020, 3 survey crews flew 6 independent AIR surveys within the vicinity of dens and control sites and video-recorded AIR imagery. Observers identified putative dens either in flight or during post-flight review of recordings. We assessed detection probability with a simple Bayesian model using 3 subsets of data: 1) all detection/non-detection data; 2) detection/non-detection data restricted to instances where sample sites were confirmed to have been properly scanned by AIR during post-study verification (i.e., when den locations were known); and 3) all dens visible on the recorded imagery during post-study verification, even if they were not seen during the survey or during post-flight review. Subsets 1 and 2 most closely resembled den surveys flown for oil and gas industry and had detection probabilities of 0.15 (95% CI = 0.08–0.23) and 0.24 (95% CI = 0.13–0.37), respectively. Detection probability was 0.41 (95% CI = 0.25–0.58) for subset 3. Higher wind speeds and larger den volume negatively influenced detection probability. Our low detection rate compared to previous studies could partially be the result of differences in study design, such as survey flight patterns. Our results suggest that AIR, as it is currently used, is unlikely to detect most polar bear dens in surveyed areas. Resource managers who use AIR should consider a suite of additional methods (e.g., habitat mapping, probabilistic den distribution, AIR methodology improvements) for minimizing impacts of industry on denning polar bears.</p></div></div>","language":"English","publisher":"The Wildlife Society","doi":"10.1002/wsb.1324","usgsCitation":"Woodruff, S.P., Blank, J.J., Wisdom, S.S., Wilson, R.H., Durner, G.M., Atwood, T.C., Perham, C.J., and Pohl, C.H., 2022, Evaluating the efficacy of aerial infrared surveys to detect artificial polar bear dens: Wildlife Society Bulletin, v. 46, no. 3, e1324, 20 p., https://doi.org/10.1002/wsb.1324.","productDescription":"e1324, 20 p.","ipdsId":"IP-129400","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":402670,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -151.446533203125,\n              69.60737776178779\n            ],\n            [\n              -148.29345703124997,\n              69.60737776178779\n            ],\n            [\n              -148.29345703124997,\n              70.64541008235548\n            ],\n            [\n              -151.446533203125,\n              70.64541008235548\n            ],\n            [\n              -151.446533203125,\n              69.60737776178779\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"46","issue":"3","noUsgsAuthors":false,"publicationDate":"2022-06-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Woodruff, Susannah P.","contributorId":292629,"corporation":false,"usgs":false,"family":"Woodruff","given":"Susannah","email":"","middleInitial":"P.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":845345,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Blank, Justin J","contributorId":292631,"corporation":false,"usgs":false,"family":"Blank","given":"Justin","email":"","middleInitial":"J","affiliations":[{"id":62951,"text":"Environmental Research and Consulting, LLC","active":true,"usgs":false}],"preferred":false,"id":845346,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wisdom, Sheyna S","contributorId":292632,"corporation":false,"usgs":false,"family":"Wisdom","given":"Sheyna","email":"","middleInitial":"S","affiliations":[{"id":62953,"text":"Fairweather Science","active":true,"usgs":false}],"preferred":false,"id":845347,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wilson, Ryan H. 0000-0001-7740-7771","orcid":"https://orcid.org/0000-0001-7740-7771","contributorId":130989,"corporation":false,"usgs":false,"family":"Wilson","given":"Ryan","email":"","middleInitial":"H.","affiliations":[{"id":6987,"text":"U.S. Fish and Wildlife Sevice","active":true,"usgs":false}],"preferred":false,"id":845348,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Durner, George M. 0000-0002-3370-1191 gdurner@usgs.gov","orcid":"https://orcid.org/0000-0002-3370-1191","contributorId":3576,"corporation":false,"usgs":true,"family":"Durner","given":"George","email":"gdurner@usgs.gov","middleInitial":"M.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":845349,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Atwood, Todd C. 0000-0002-1971-3110 tatwood@usgs.gov","orcid":"https://orcid.org/0000-0002-1971-3110","contributorId":4368,"corporation":false,"usgs":true,"family":"Atwood","given":"Todd","email":"tatwood@usgs.gov","middleInitial":"C.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":845350,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Perham, Craig J","contributorId":292633,"corporation":false,"usgs":false,"family":"Perham","given":"Craig","email":"","middleInitial":"J","affiliations":[{"id":16722,"text":"US Bureau of Land Management","active":true,"usgs":false}],"preferred":false,"id":845351,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Pohl, Christina HM","contributorId":292634,"corporation":false,"usgs":false,"family":"Pohl","given":"Christina","email":"","middleInitial":"HM","affiliations":[{"id":62954,"text":"BP Exploration (Alaska), Inc.","active":true,"usgs":false}],"preferred":false,"id":845352,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
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