{"pageNumber":"68","pageRowStart":"1675","pageSize":"25","recordCount":10450,"records":[{"id":70210502,"text":"70210502 - 2020 - Evaluating the potential role of bioactive chemicals on the distribution of invasive Asian carp upstream and downstream from river mile 278 in the Illinois waterway","interactions":[],"lastModifiedDate":"2020-06-05T12:39:41.761022","indexId":"70210502","displayToPublicDate":"2020-05-16T07:36:08","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Evaluating the potential role of bioactive chemicals on the distribution of invasive Asian carp upstream and downstream from river mile 278 in the Illinois waterway","docAbstract":"Two non-native carp species have invaded the Illinois Waterway and are a threat to Great Lakes ecosystems. Poor water quality in the upper Illinois Waterway, may be a factor contributing to the stalling of the carp population front near river mile 278. In 2015, the U.S. Geological Survey collected 4 sets of water samples from two sites upstream and 4 sites downstream from river mile 278, and one tributary. Each sample was analyzed for up to 649 unique parameters of which 287 were detected including 96 pesticides, 62 pharmaceuticals, 39 wastewater indicator compounds, 29 metals, 19 volatile organic compounds (VOCs), six disinfection by-products (DBPs), five hormones, and five carboxylic acids. Potential for bioactivity was estimated by comparing chemical concentrations to aquatic life or human health criteria and to in-vitro bioactivity screening results in the U.S EPA ToxCast™ database. The resulting hazard quotients and exposure-activity ratios (EARs) are toxicity indexes, that can be used to rank potential bioactivity of individual chemicals and chemical mixtures. This analysis indicates that several bioactive chemicals (BCs) including: carbendazim, 2,4-D, metolachlor, terbuthylazine, and acetochlor (pesticides); 1,4-dioxane (VOC); metformin, diphenhydramine, sulfamethoxazole, tramadol, fexofenadine, and the anti-depressants (pharmaceuticals); bisphenol A, 4-nonylphenol, galaxolide, 4-tert-octylphenol (wastewater indicator chemical); lead and boron (metals); and estrone (hormone) all occur in the upper Illinois Waterway at concentrations that produce elevated EARs values and may be adversely affecting carp reproduction and health. The clear differences in water quality upstream and downstream from river mile 278 with higher contaminant concentrations and potential bioactivity upstream could represent a barrier to carp range expansion.","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2020.139458","usgsCitation":"Battaglin, W., Duncker, J.J., Terrio, P.J., Bradley, P., Barber, L., and DeCicco, L.A., 2020, Evaluating the potential role of bioactive chemicals on the distribution of invasive Asian carp upstream and downstream from river mile 278 in the Illinois waterway: Science of the Total Environment, v. 735, 139458, 18 p., https://doi.org/10.1016/j.scitotenv.2020.139458.","productDescription":"139458, 18 p.","ipdsId":"IP-111948","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":456760,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2020.139458","text":"Publisher Index Page"},{"id":436985,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9V75F9Q","text":"USGS data release","linkHelpText":"Laboratory results for anthropogenic bioactive chemicals in the Illinois Waterway upstream and downstream of the bigheaded carp population front (2015; ver. 2.0, March 2020)"},{"id":375390,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Illinois","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.12408447265625,\n 41.539421883822854\n ],\n [\n -88.23944091796875,\n 41.46537017728069\n ],\n [\n -88.2696533203125,\n 41.43654942411456\n ],\n [\n -88.4674072265625,\n 41.393294288784865\n ],\n [\n -88.63220214843749,\n 41.335575973123916\n ],\n [\n -88.68988037109375,\n 41.36031866306708\n ],\n [\n -88.80523681640625,\n 41.395354710280166\n ],\n [\n -88.9178466796875,\n 41.37474755643594\n ],\n [\n -89.08538818359375,\n 41.37474755643594\n ],\n [\n -89.34906005859375,\n 41.35413387210046\n ],\n [\n -89.44244384765625,\n 41.27161384188987\n ],\n [\n -89.40673828125,\n 41.18485540813213\n ],\n [\n -89.44244384765625,\n 41.11660732012896\n ],\n [\n -89.50836181640625,\n 41.008920735004885\n ],\n [\n -89.59899902343749,\n 40.8595252289932\n ],\n [\n -89.6099853515625,\n 40.81380923056958\n ],\n [\n -89.60174560546875,\n 40.73268976628568\n ],\n [\n -89.5880126953125,\n 40.67438908251788\n ],\n [\n -89.53033447265625,\n 40.6723059714534\n ],\n [\n -89.50836181640625,\n 40.753499070431374\n ],\n [\n -89.5001220703125,\n 40.82835864973048\n ],\n [\n -89.40948486328125,\n 40.91973905106219\n ],\n [\n -89.26666259765625,\n 41.1290213474951\n ],\n [\n -89.307861328125,\n 41.18692242290296\n ],\n [\n -89.2913818359375,\n 41.265420628926684\n ],\n [\n -89.110107421875,\n 41.29431726315258\n ],\n [\n -88.90411376953125,\n 41.30050773444147\n ],\n [\n -88.7530517578125,\n 41.261291493919884\n ],\n [\n -88.5772705078125,\n 41.2509675141624\n ],\n [\n -88.38775634765625,\n 41.31494988250965\n ],\n [\n -88.29711914062499,\n 41.352072144512924\n ],\n [\n -88.20098876953125,\n 41.304634388885916\n ],\n [\n -88.154296875,\n 41.38299120166604\n ],\n [\n -88.0609130859375,\n 41.48800607185427\n ],\n [\n -88.12408447265625,\n 41.539421883822854\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"735","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Battaglin, William A. 0000-0001-7287-7096","orcid":"https://orcid.org/0000-0001-7287-7096","contributorId":204638,"corporation":false,"usgs":true,"family":"Battaglin","given":"William A.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":790408,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Duncker, James J. 0000-0001-5464-7991 jduncker@usgs.gov","orcid":"https://orcid.org/0000-0001-5464-7991","contributorId":4316,"corporation":false,"usgs":true,"family":"Duncker","given":"James","email":"jduncker@usgs.gov","middleInitial":"J.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true},{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true},{"id":35680,"text":"Illinois-Iowa-Missouri Water Science Center","active":true,"usgs":true}],"preferred":true,"id":790409,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Terrio, Paul J. 0000-0002-1515-9570 pjterrio@usgs.gov","orcid":"https://orcid.org/0000-0002-1515-9570","contributorId":3313,"corporation":false,"usgs":true,"family":"Terrio","given":"Paul","email":"pjterrio@usgs.gov","middleInitial":"J.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":790410,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"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":559,"text":"South Carolina Water Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":790411,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Barber, Larry B. 0000-0002-0561-0831","orcid":"https://orcid.org/0000-0002-0561-0831","contributorId":218953,"corporation":false,"usgs":true,"family":"Barber","given":"Larry B.","affiliations":[{"id":38175,"text":"Toxics Substances Hydrology Program","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":790412,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"DeCicco, Laura A. 0000-0002-3915-9487 ldecicco@usgs.gov","orcid":"https://orcid.org/0000-0002-3915-9487","contributorId":174716,"corporation":false,"usgs":true,"family":"DeCicco","given":"Laura","email":"ldecicco@usgs.gov","middleInitial":"A.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":5054,"text":"Office of Water Information","active":true,"usgs":true},{"id":160,"text":"Center for Integrated Data Analytics","active":false,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":790413,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70210145,"text":"70210145 - 2020 - Deep long-period earthquakes generated by second boiling beneath Mauna Kea volcano","interactions":[],"lastModifiedDate":"2020-05-15T13:33:24.671141","indexId":"70210145","displayToPublicDate":"2020-05-15T08:27:57","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3338,"text":"Science","active":true,"publicationSubtype":{"id":10}},"title":"Deep long-period earthquakes generated by second boiling beneath Mauna Kea volcano","docAbstract":"Deep long-period earthquakes (DLPs) are an enigmatic type of volcanic seismicity that sometimes precedes eruptions but mostly occurs at quiescent volcanoes. These earthquakes are depleted in high-frequency content and typically occur near the base of the crust. We observed a near-periodic, long- lived sequence of more than one million DLPs in the past 19 years beneath the dormant postshield Mauna Kea volcano in Hawai‘i. We argue that this DLP sequence was caused by repeated pressurization of volatiles exsolved through crystallization of cooling magma stalled beneath the crust. This “second boiling” of magma is a well-known process but has not previously been linked to DLP activity. Our observations suggest that, rather than portending eruptions, global DLP activity may more commonly be indicative of stagnant, cooling magma.","language":"English","publisher":"American Association for the Advancement of Science","doi":"10.1126/science.aba4798","collaboration":"","usgsCitation":"Wech, A., Thelen, W., and Thomas, A., 2020, Deep long-period earthquakes generated by second boiling beneath Mauna Kea volcano: Science, v. 368, p. 775-779, https://doi.org/10.1126/science.aba4798.","productDescription":"5 p.","startPage":"775","endPage":"779","ipdsId":"IP-116306","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":374868,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"Mauna Kea volcano","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -155.63987731933594,\n 19.70788973522166\n ],\n [\n -155.3473663330078,\n 19.70788973522166\n ],\n [\n -155.3473663330078,\n 19.938496312392708\n ],\n [\n -155.63987731933594,\n 19.938496312392708\n ],\n [\n -155.63987731933594,\n 19.70788973522166\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"368","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Wech, Aaron 0000-0003-4983-1991","orcid":"https://orcid.org/0000-0003-4983-1991","contributorId":202561,"corporation":false,"usgs":true,"family":"Wech","given":"Aaron","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":789295,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thelen, Weston 0000-0003-2534-5577","orcid":"https://orcid.org/0000-0003-2534-5577","contributorId":215530,"corporation":false,"usgs":true,"family":"Thelen","given":"Weston","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":789296,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Thomas, Amanda","contributorId":195086,"corporation":false,"usgs":false,"family":"Thomas","given":"Amanda","affiliations":[],"preferred":false,"id":789297,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70213698,"text":"70213698 - 2020 - Biological soil crusts in ecological restoration: Emerging research and perspectives","interactions":[],"lastModifiedDate":"2020-09-18T21:33:47.885725","indexId":"70213698","displayToPublicDate":"2020-05-14T16:31:02","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3271,"text":"Restoration Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Biological soil crusts in ecological restoration: Emerging research and perspectives","docAbstract":"

Drylands encompass over 40% of terrestrial ecosystems and face significant anthropogenic degradation causing a loss of ecosystem integrity, services, and deterioration of social‐ecological systems. To combat this degradation, some dryland restoration efforts have focused on the use of biological soil crusts (biocrusts): complex communities of cyanobacteria, algae, lichens, bryophytes, and other organisms living in association with the top millimeters of soil. Biocrusts are common in many ecosystems and especially drylands. They perform a suite of ecosystem functions: stabilizing soil surfaces to prevent erosion, contributing carbon through photosynthesis, fixing nitrogen, and mediating the hydrological cycle in drylands. Biocrusts have emerged as a potential tool in restoration; developing methods to implement effective biocrust restoration has the potential to return many ecosystem functions and services. Although culture‐based approaches have allowed researchers to learn about the biology, physiology, and cultivation of biocrusts, transferring this knowledge to field implementation has been more challenging. A large amount of research has amassed to improve our understanding of biocrust restoration, leaving us at an opportune time to learn from one another and to join approaches for maximum efficacy. The articles in this special issue improve the state of our current knowledge in biocrust restoration, highlighting efforts to effectively restore biocrusts through a variety of different ecosystems, across scales and utilizing a variety of lab and field methods. This collective work provides a useful resource for the scientific community as well as land managers.

","language":"English","doi":"10.1111/rec.13201","usgsCitation":"Antoninka, A., Faist, A.M., Rodriguez-Caballero, E., Young, K., Chaudhary, V., Condon, L.A., and Pyke, D.A., 2020, Biological soil crusts in ecological restoration: Emerging research and perspectives: Restoration Ecology, v. 28, no. S2, p. s3-s8, https://doi.org/10.1111/rec.13201.","productDescription":"6 p.","startPage":"s3","endPage":"s8","ipdsId":"IP-117103","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":29789,"text":"John Wesley Powell Center for Analysis and Synthesis","active":true,"usgs":true}],"links":[{"id":456772,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/rec.13201","text":"Publisher Index Page"},{"id":378584,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"28","issue":"S2","noUsgsAuthors":false,"publicationDate":"2020-06-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Antoninka, Anita","contributorId":166769,"corporation":false,"usgs":false,"family":"Antoninka","given":"Anita","affiliations":[{"id":24503,"text":"Northern Arizona University, School of Forestry, Flagstaff, AZ","active":true,"usgs":false}],"preferred":false,"id":799232,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Faist, Akasha M.","contributorId":193038,"corporation":false,"usgs":false,"family":"Faist","given":"Akasha","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":799233,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rodriguez-Caballero, Emilio 0000-0002-5934-3214","orcid":"https://orcid.org/0000-0002-5934-3214","contributorId":205639,"corporation":false,"usgs":false,"family":"Rodriguez-Caballero","given":"Emilio","email":"","affiliations":[{"id":37132,"text":"Multiphase Chemistry Department, Max Planck Institute for Chemistry, Hahn-Meitner-Weg 1, 55128 Mainz, Germany","active":true,"usgs":false}],"preferred":false,"id":799234,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Young, Kristina E.","contributorId":195945,"corporation":false,"usgs":false,"family":"Young","given":"Kristina E.","affiliations":[],"preferred":false,"id":799235,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Chaudhary, V Bala","contributorId":240984,"corporation":false,"usgs":false,"family":"Chaudhary","given":"V Bala","affiliations":[{"id":36623,"text":"DePaul University","active":true,"usgs":false}],"preferred":false,"id":799236,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Condon, Lea A. 0000-0002-9357-3881","orcid":"https://orcid.org/0000-0002-9357-3881","contributorId":202908,"corporation":false,"usgs":true,"family":"Condon","given":"Lea","email":"","middleInitial":"A.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":799237,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Pyke, David A. 0000-0002-4578-8335 david_a_pyke@usgs.gov","orcid":"https://orcid.org/0000-0002-4578-8335","contributorId":3118,"corporation":false,"usgs":true,"family":"Pyke","given":"David","email":"david_a_pyke@usgs.gov","middleInitial":"A.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":true,"id":799238,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70211827,"text":"70211827 - 2020 - Food web controls on mercury fluxes and fate in the Colorado River, Grand Canyon","interactions":[],"lastModifiedDate":"2020-08-07T21:59:17.624094","indexId":"70211827","displayToPublicDate":"2020-05-13T16:52:21","publicationYear":"2020","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":"Food web controls on mercury fluxes and fate in the Colorado River, Grand Canyon","docAbstract":"Mercury (Hg) biomagnification in aquatic food webs is a global concern; yet, the ways species traits and interactions mediate these fluxes remain poorly understood. Few pathways dominated Hg flux in the Colorado River despite large spatial differences in food web complexity, and fluxes were mediated by one functional trait, predation resistance. New Zealand mudsnails are predator resistant and a trophic dead end for Hg in food webs we studied. Fishes preferred blackflies, which accounted for 56 to 80% of Hg flux to fishes, even where blackflies were rare. Food web properties, i.e., match/mismatch between insect production and fish consumption, governed amounts of Hg retained in the river versus exported to land. An experimental flood redistributed Hg fluxes in the simplified tailwater food web, but not in complex downstream food webs. Recognizing that species traits, species interactions, and disturbance mediate contaminant exposure can improve risk management of linked aquatic-terrestrial ecosystems.","language":"English","publisher":"AAAS","doi":"10.1126/sciadv.aaz4880","usgsCitation":"Walters, D., Cross, W., Kennedy, T., Baxter, C., Hall, R., and Rosi, E.J., 2020, Food web controls on mercury fluxes and fate in the Colorado River, Grand Canyon: Science Advances, v. 6, no. 20, eaaz4880, 10 p., https://doi.org/10.1126/sciadv.aaz4880.","productDescription":"eaaz4880, 10 p.","ipdsId":"IP-111739","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":456788,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1126/sciadv.aaz4880","text":"Publisher Index Page"},{"id":436989,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9NBAHFF","text":"USGS data release","linkHelpText":"Consumption rates and total mercury concentration of food items and consumers collected at six sites on the Colorado River in the Grand Canyon, USA, 2007-2009"},{"id":377213,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona, Nevada","otherGeospatial":"Colorado River, Grand Canyon","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.39038085937499,\n 36.712467243386264\n ],\n [\n -112.313232421875,\n 36.60670888641815\n ],\n [\n -112.862548828125,\n 36.518465989675875\n ],\n [\n -113.741455078125,\n 36.36822190085111\n ],\n [\n -114.12597656249999,\n 36.217687122250574\n ],\n [\n -114.32373046875,\n 36.518465989675875\n ],\n [\n -114.949951171875,\n 36.1733569352216\n ],\n [\n -114.840087890625,\n 35.93354064249312\n ],\n [\n -114.554443359375,\n 35.96022296929667\n ],\n [\n -113.97216796875,\n 35.951329861522666\n ],\n [\n -113.291015625,\n 35.55010533588552\n ],\n [\n -113.126220703125,\n 35.951329861522666\n ],\n [\n -112.642822265625,\n 36.11125252076156\n ],\n [\n -111.895751953125,\n 35.782170703266075\n ],\n [\n -111.39038085937499,\n 36.712467243386264\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"6","issue":"20","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Walters, David 0000-0002-4237-2158 waltersd@usgs.gov","orcid":"https://orcid.org/0000-0002-4237-2158","contributorId":147135,"corporation":false,"usgs":true,"family":"Walters","given":"David","email":"waltersd@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":795260,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cross, Wyatt F.","contributorId":237773,"corporation":false,"usgs":false,"family":"Cross","given":"Wyatt F.","affiliations":[{"id":47607,"text":"Department of Ecology, Montana State University, Bozeman, MT","active":true,"usgs":false}],"preferred":false,"id":795261,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kennedy, Theodore 0000-0003-3477-3629","orcid":"https://orcid.org/0000-0003-3477-3629","contributorId":221741,"corporation":false,"usgs":true,"family":"Kennedy","given":"Theodore","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":795262,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Baxter, Colden V.","contributorId":47334,"corporation":false,"usgs":false,"family":"Baxter","given":"Colden V.","affiliations":[{"id":13656,"text":"Idaho State Univ.","active":true,"usgs":false}],"preferred":false,"id":795263,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hall, R. O. Jr.","contributorId":216427,"corporation":false,"usgs":false,"family":"Hall","given":"R. O.","suffix":"Jr.","affiliations":[{"id":39416,"text":"Flathead Lake Biological Station, University of Montana","active":true,"usgs":false}],"preferred":false,"id":795264,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Rosi, Emma J.","contributorId":201758,"corporation":false,"usgs":false,"family":"Rosi","given":"Emma","email":"","middleInitial":"J.","affiliations":[{"id":36248,"text":"Cary Institute of Ecosystem Studies","active":true,"usgs":false}],"preferred":false,"id":795265,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70210092,"text":"ofr20201040 - 2020 - Assessment of rangeland ecosystem conditions in Grand Canyon-Parashant National Monument, Arizona","interactions":[],"lastModifiedDate":"2020-05-14T11:55:22.364325","indexId":"ofr20201040","displayToPublicDate":"2020-05-13T13:43:13","publicationYear":"2020","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":"2020-1040","displayTitle":"Assessment of Rangeland Ecosystem Conditions in Grand Canyon-Parashant National Monument, Arizona","title":"Assessment of rangeland ecosystem conditions in Grand Canyon-Parashant National Monument, Arizona","docAbstract":"

Sustainability of dryland ecosystems depends on the functionality of soil-vegetation feedbacks that affect ecosystem processes, such as nutrient cycling, water capture and retention, soil erosion and deposition, and plant establishment and reproduction. Useful, common indicators can provide information on soil and site stability, hydrologic function, and biotic integrity. Evaluation of rangeland health thus relies on describing the condition and sustainability of these individual, measurable, and observable indicators that are linked to important ecosystem processes. This report focuses on the ~200,000 acres of the Grand Canyon-Parashant National Monument that is administered by the National Park Service (NPS)—one of the largest NPS units where livestock grazing is a permitted land-use activity. Many ecosystems in the monument are characterized by a low degree of resilience to improper grazing because of low and variable precipitation. The monument is marked by a high degree of environmental heterogeneity, including a large elevation gradient, widely differing precipitation patterns, a diversity of geologic substrates, and unique combinations of plant species.

The objective of this report is to (1) increase our understanding of the underlying landscape, soil, and climate setting factors that affect Grand Canyon-Parashant National Monument dryland ecosystem structure and function (also referred to as land potential) and (2) characterize the condition of monument ecosystems in relation to management concepts, such as rangeland health.

Data were analyzed by elevation zone using both univariate and multivariate approaches. Survey results document the high level of diversity within the study area, including 15 unique soil taxa and 271 species of plants. We collected three new plant species for Grand Canyon-Parashant National Monument and 17 new species for the NPS portion of the monument. Results also document a strong association between rangeland health indicators and elevation, topographic setting, and soils. Soil factors found to explain important variation across plots include the amount of exposed bedrock, soil rockiness, soil texture (and associated hydrologic properties), and soil depth. We also found that dominant species turnover across elevation may represent species’ differences in adaptation to climates, including Larrea tridentata, Coleogyne ramosissima, and Artemisia spp. Bromus rubens is the most common invasive species of concern recorded in this study, but other common invasive species are Bromus tectorum, Erodium cicutarium, and Schismus arabicus. Correlations between an index of cattle use and indicators of rangeland health suggest that areas with high cattle use have increased bare ground, decreased ground cover, increased frequency of Schismus arabicus, decreased cover of Coleogyne ramosissima and Ephedra spp., and increased cover of Gutierrezia spp. The few strong correlations observed between indicators of vascular plant community cover or abundance and indicators of cattle activity support rangeland assessment and monitoring strategies that do not rely solely on plant-based indicators are needed.

This work supports management of dryland ecosystems, including Grand Canyon-Parashant National Monument, using concepts of land potential. We conclude the report with recommendations on improving existing land-potential-based classification systems, associated interpretations, and methods for moving forward with a Grand Canyon-Parashant National Monument rangeland monitoring program.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201040","usgsCitation":"Duniway, M.C., and Palmquist, E.C., 2020, Assessment of rangeland ecosystem conditions in Grand Canyon-Parashant National Monument, Arizona: U.S. Geological Survey Open-File Report 2020–1040, 42 p., https://doi.org/10.3133/ofr20201040.","productDescription":"Report: viii, 42 p.; Data Release","numberOfPages":"42","onlineOnly":"Y","ipdsId":"IP-106479","costCenters":[{"id":569,"text":"Southwest Climate Science Center","active":true,"usgs":true}],"links":[{"id":374803,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9SJSJHT","linkHelpText":"Rangeland Ecosystem Data, Grand Canyon - Parashant National Monument, AZ, USA"},{"id":374801,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1040/coverthb.jpg"},{"id":374802,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1040/ofr20201040.pdf","text":"Report","size":"10 MB","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"Arizona","otherGeospatial":"Grand Canyon-Parashant National Monument","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -114.005126953125,\n 35.679609609368576\n ],\n [\n -111.57714843749999,\n 35.679609609368576\n ],\n [\n -111.57714843749999,\n 36.97622678464096\n ],\n [\n -114.005126953125,\n 36.97622678464096\n ],\n [\n -114.005126953125,\n 35.679609609368576\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"

Director, 
Southwest Biological Science Center
U.S. Geological Survey
2255 N. Gemini Drive
Flagstaff, AZ 86001

","tableOfContents":"","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"publishedDate":"2020-05-13","noUsgsAuthors":false,"publicationDate":"2020-05-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Duniway, Michael C. 0000-0002-9643-2785 mduniway@usgs.gov","orcid":"https://orcid.org/0000-0002-9643-2785","contributorId":4212,"corporation":false,"usgs":true,"family":"Duniway","given":"Michael","email":"mduniway@usgs.gov","middleInitial":"C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":789072,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Palmquist, Emily C. 0000-0003-1069-2154 epalmquist@usgs.gov","orcid":"https://orcid.org/0000-0003-1069-2154","contributorId":5669,"corporation":false,"usgs":true,"family":"Palmquist","given":"Emily","email":"epalmquist@usgs.gov","middleInitial":"C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":789073,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70210175,"text":"70210175 - 2020 - Fluoride occurrence in United States groundwater","interactions":[],"lastModifiedDate":"2020-05-19T13:38:58.950932","indexId":"70210175","displayToPublicDate":"2020-05-11T08:30:10","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Fluoride occurrence in United States groundwater","docAbstract":"Data from 38,105 wells were used to characterize fluoride (F) occurrence in untreated United States (U.S.) groundwater. For domestic wells (n = 11,032), water from which is generally not purposely fluoridated or monitored for quality, 10.9% of the samples have F concentrations >0.7 mg/L (U.S. Public Health Service recommended optimal F concentration in drinking water for preventing tooth decay) (87% are <0.7 mg/L); 2.6% have F > 2 mg/L (EPA Secondary Maximum Contaminant Level, SMCL); and 0.6% have F > 4 mg/L (EPA MCL). The data indicate the biggest concern with F in domestic wells at the national scale could be one of under consumption of F with respect to the oral-health benchmark (0.7 mg/L). Elevated F concentrations relative to the SMCL and MCL are regionally important, particularly in the western U.S. Statistical comparisons of potentially important controlling factors in four F-concentration categories (<0.1–0.7 mg/L; >0.7–2 mg/L; >2–4 mg/L; >4 mg/L) at the national scale indicate the highest F-concentration category is associated with groundwater that has significantly greater pH values, TDS and alkalinity concentrations, and well depths, and lower Ca/Na ratios and mean annual precipitation, than the lowest F-concentration category. The relative importance of the controlling factors appears to be regionally variable. Three case studies illustrate the spatial variability in controlling factors using groundwater-age (groundwater residence time), water-isotope (evaporative concentration), and water-temperature (geothermal processes) data. Populations potentially served by domestic wells with F concentrations <0.7, >0.7, >2, and >4 mg/L are estimated to be ~28,200,000, ~3,110,000; ~522,000; and ~172,000 people, respectively, in 40 principal aquifers with at least 25 F analyses per aquifer.","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2020.139217","collaboration":"","usgsCitation":"McMahon, P.B., Brown, C., Johnson, T., Belitz, K., and Lindsey, B.D., 2020, Fluoride occurrence in United States groundwater: Science of the Total Environment, v. 732, https://doi.org/10.1016/j.scitotenv.2020.139217.","productDescription":"139217, 15 p.","startPage":"","ipdsId":"IP-114693","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":466,"text":"New England Water Science 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Center","active":true,"usgs":true}],"preferred":true,"id":789428,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Johnson, Tyler D. 0000-0002-7334-9188","orcid":"https://orcid.org/0000-0002-7334-9188","contributorId":201888,"corporation":false,"usgs":true,"family":"Johnson","given":"Tyler D.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":789429,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Belitz, Kenneth 0000-0003-4481-2345","orcid":"https://orcid.org/0000-0003-4481-2345","contributorId":213728,"corporation":false,"usgs":true,"family":"Belitz","given":"Kenneth","affiliations":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"preferred":true,"id":789430,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lindsey, Bruce D. 0000-0002-7180-4319 blindsey@usgs.gov","orcid":"https://orcid.org/0000-0002-7180-4319","contributorId":175346,"corporation":false,"usgs":true,"family":"Lindsey","given":"Bruce","email":"blindsey@usgs.gov","middleInitial":"D.","affiliations":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":789431,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70210688,"text":"70210688 - 2020 - Projected impacts of climate change on the range and phenology of three culturally-important shrub species","interactions":[],"lastModifiedDate":"2020-06-17T13:34:51.108521","indexId":"70210688","displayToPublicDate":"2020-05-08T08:26:27","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Projected impacts of climate change on the range and phenology of three culturally-important shrub species","docAbstract":"

Climate change is shifting both the habitat suitability and the timing of critical biological events, such as flowering and fruiting, for plant species across the globe. Here, we ask how both the distribution and phenology of three food-producing shrubs native to northwestern North America might shift as the climate changes. To address this question, we compared gridded climate data with species location data to identify climate variables that best predicted the current bioclimatic niches of beaked hazelnut (Corylus cornuta), Oregon grape (Mahonia aquifolium), and salal (Gaultheria shallon). We also developed thermal-sum models for the timing of flowering and fruit ripening for these species. We then used multi-model ensemble future climate projections to estimate how species range and phenology may change under future conditions. Modelling efforts showed extreme minimum temperature, climate moisture deficit, and mean summer precipitation were predictive of climatic suitability across all three species. Future bioclimatic niche models project substantial reductions in habitat suitability across the lower elevation and southern portions of the species’ current ranges by the end of the 21st century. Thermal-sum phenology models for these species indicate that flowering and the ripening of fruits and nuts will advance an average of 25 days by the mid-21st century, and 36 days by the late-21st century under a high emissions scenario (RCP 8.5). Future changes in the climatic niche and phenology of these important food-producing species may alter trophic relationships, with cascading impacts on regional ecosystems.

","language":"English","publisher":"PLOS","doi":"10.1371/journal.pone.0232537","usgsCitation":"Prevey, J.S., Parker, L.E., and Harrington, C., 2020, Projected impacts of climate change on the range and phenology of three culturally-important shrub species: PLoS ONE, v. 15, no. 5, e0232537, 19 p., https://doi.org/10.1371/journal.pone.0232537.","productDescription":"e0232537, 19 p.","ipdsId":"IP-114286","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":456827,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0232537","text":"Publisher Index Page"},{"id":436996,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9G0UTKF","text":"USGS data release","linkHelpText":"Location and phenology observations for beaked hazelnut (Corylus cornuta), Oregon grape (Mahonia aquifolium), and salal (Gaultheria shallon) in western North America"},{"id":375664,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","state":"British, Columbia, California, Idaho, Montana, Nevada, Oregon, Washington","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -112.4560546875,\n 47.57652571374621\n ],\n [\n -117.333984375,\n 50.56928286558243\n ],\n [\n -121.5087890625,\n 52.32191088594773\n ],\n [\n -133.2421875,\n 54.34214886448341\n ],\n [\n -132.7587890625,\n 52.9883372533954\n ],\n [\n -126.60644531250001,\n 48.922499263758255\n ],\n [\n -124.541015625,\n 46.07323062540835\n ],\n [\n -125.0244140625,\n 42.22851735620852\n ],\n [\n -125.068359375,\n 39.80853604144591\n ],\n [\n -120.4541015625,\n 33.797408767572485\n ],\n [\n -117.333984375,\n 35.92464453144099\n ],\n [\n -120.32226562500001,\n 40.01078714046552\n ],\n [\n -119.00390625,\n 40.91351257612758\n ],\n [\n -112.32421875,\n 42.52069952914966\n ],\n [\n -111.357421875,\n 45.61403741135093\n ],\n [\n -111.8408203125,\n 47.100044694025215\n ],\n [\n -112.4560546875,\n 47.57652571374621\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"15","issue":"5","noUsgsAuthors":false,"publicationDate":"2020-05-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Prevey, Janet S. 0000-0003-2879-6453","orcid":"https://orcid.org/0000-0003-2879-6453","contributorId":222702,"corporation":false,"usgs":true,"family":"Prevey","given":"Janet","email":"","middleInitial":"S.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":790978,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Parker, Lauren E.","contributorId":225389,"corporation":false,"usgs":false,"family":"Parker","given":"Lauren","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":790979,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Harrington, Constance A","contributorId":167297,"corporation":false,"usgs":false,"family":"Harrington","given":"Constance A","affiliations":[{"id":24677,"text":"USDA Pacific Northwest Research Station, Olympia WA","active":true,"usgs":false}],"preferred":false,"id":790980,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70228787,"text":"70228787 - 2020 - Drivers and consequences of alternative landscape futures on wildlife distributions in New England, United States","interactions":[],"lastModifiedDate":"2022-02-21T15:46:27.686445","indexId":"70228787","displayToPublicDate":"2020-05-05T09:36:15","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3910,"text":"Frontiers in Ecology and Evolution","onlineIssn":"2296-701X","active":true,"publicationSubtype":{"id":10}},"title":"Drivers and consequences of alternative landscape futures on wildlife distributions in New England, United States","docAbstract":"In an era of rapid climate and land transformation, it is increasingly important to understand how future changes impact natural systems. Scenario studies can offer the structure and perspective needed to understand the impacts of change and help inform management and conservation decisions. We implemented a scenario-based approach to assess how two high impact drivers of landscape change influence the distributions of managed wildlife species (n = 10) in the New England region of the northeastern United States. We used expert derived species distribution models (SDMs) and scenarios developed by the New England Landscape Futures Project (NELFP) to estimate how species distributions change under various trajectories (n = 5) of landscape change. The NELFP scenarios were built around two primary drivers – Socio-Economic Connectedness (SEC) and Natural Resource Planning and Innovation (NRPI) – and provide plausible alternatives for how the New England region may change over fifty years (2010 to 2060). Our models generally resulted in species occurrence and richness declines by 2060. The majority of species (7 of 10) experienced declines in regional occurrence for all NELFP scenarios, and one species experienced a projected increase in mean regional occurrence for all scenarios. Our results indicate that the NRPI and SEC drivers strongly influenced projected distribution changes compared to baseline projections. NRPI had a greater impact on distribution change for five species (coyote, moose, striped skunk, white-tailed deer, and wild turkey), while SEC had a greater impact on four species (American black bear, bobcat, raccoon, and red fox); one species (gray fox) was equally influenced by both NRPI and SEC. These results emphasize the importance of integrating both natural resource planning and socio-economic factors when addressing issues of distribution change and offer insights that can inform proactive management and conservation planning.","language":"English","publisher":"Frontiers Media","doi":"10.3389/fevo.2020.00164","usgsCitation":"Pearman-Gillman, S., Duveneck, M.J., Murdoch, J.D., and Donovan, T.M., 2020, Drivers and consequences of alternative landscape futures on wildlife distributions in New England, United States: Frontiers in Ecology and Evolution, v. 8, p. 1-19, https://doi.org/10.3389/fevo.2020.00164.","productDescription":"164, 19 p.","startPage":"1","endPage":"19","ipdsId":"IP-114447","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":456846,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fevo.2020.00164","text":"Publisher Index 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Vermont","active":true,"usgs":false}],"preferred":false,"id":835484,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Duveneck, Matthew J.","contributorId":276073,"corporation":false,"usgs":false,"family":"Duveneck","given":"Matthew","email":"","middleInitial":"J.","affiliations":[{"id":16811,"text":"Harvard University","active":true,"usgs":false}],"preferred":false,"id":835485,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Murdoch, James D.","contributorId":276074,"corporation":false,"usgs":false,"family":"Murdoch","given":"James","email":"","middleInitial":"D.","affiliations":[{"id":13253,"text":"University of Vermont","active":true,"usgs":false}],"preferred":false,"id":835486,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Donovan, Therese M. 0000-0001-8124-9251 tdonovan@usgs.gov","orcid":"https://orcid.org/0000-0001-8124-9251","contributorId":204296,"corporation":false,"usgs":true,"family":"Donovan","given":"Therese","email":"tdonovan@usgs.gov","middleInitial":"M.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":835483,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70220547,"text":"70220547 - 2020 - Combining genetic and demographic monitoring better informs conservation of an endangered urban snake","interactions":[],"lastModifiedDate":"2025-04-16T13:18:39.30065","indexId":"70220547","displayToPublicDate":"2020-05-05T08:10:27","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Combining genetic and demographic monitoring better informs conservation of an endangered urban snake","docAbstract":"

Conversion and fragmentation of wildlife habitat often leads to smaller and isolated populations and can reduce a species’ ability to disperse across the landscape. As a consequence, genetic drift can quickly lower genetic variation and increase vulnerability to extirpation. For species of conservation concern, quantification of population size and connectivity can clarify the influence of genetic drift in local populations and provides important information for conservation management and recovery strategies. Here, we used genome-wide single nucleotide polymorphism (SNP) data and capture-mark-recapture methods to evaluate the genetic diversity and demography within seven focal sites of the endangered San Francisco gartersnake (Thamnophis sirtalis tetrataenia), a species affected by alteration and isolation of wetland habitats throughout its distribution. The primary goals were to determine the population structure and degree of genetic isolation among T. s. tetrataenia populations and estimate effective size and population abundance within sites to better understand the present and future importance of genetic drift. We also used temporally sampled datasets to examine the magnitude of genetic change over time. We found moderate population genetic structure throughout the San Francisco Peninsula that partitions sites into northern and southern regional clusters. Point estimates of both effective size and population abundance were generally small (≤ 100) for a majority of the sites, and estimates were particularly low in the northern populations. Genetic analyses of temporal datasets indicated an increase in genetic differentiation, especially for the most geographically isolated sites, and decreased genetic diversity over time in at least one site (Pacifica). Our results suggest that drift-mediated processes as a function of small population size and reduced connectivity from neighboring populations may decrease diversity and increase differentiation. Improving genetic diversity and connectivity among T. s. tetrataenia populations could promote persistence of this endangered snake.

","language":"English","publisher":"PLOS","doi":"10.1371/journal.pone.0231744","usgsCitation":"Wood, D.A., Rose, J.P., Halstead, B., Stoelting, R.E., Swaim, K.E., and Vandergast, A.G., 2020, Combining genetic and demographic monitoring better informs conservation of an endangered urban snake: PLoS ONE, v. 15, no. 5, e0231744, 27 p.; Data Release, https://doi.org/10.1371/journal.pone.0231744.","productDescription":"e0231744, 27 p.; Data Release","ipdsId":"IP-114654","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":458808,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0231744","text":"Publisher Index Page"},{"id":437231,"rank":1,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9YKLBB5","text":"USGS data release","linkHelpText":"San Francisco Gartersnake (Thamnophis sirtalis tetrataenia) Genomic and Demographic Data from San Mateo County and Northeastern Santa Cruz County Collected Between 2016 - 2018"},{"id":385763,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.62939453125001,\n 37.243448378654115\n ],\n [\n -122.05261230468751,\n 37.243448378654115\n ],\n [\n -122.05261230468751,\n 37.81846319511331\n ],\n [\n -122.62939453125001,\n 37.81846319511331\n ],\n [\n -122.62939453125001,\n 37.243448378654115\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"15","issue":"5","noUsgsAuthors":false,"publicationDate":"2020-05-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Wood, Dustin A. 0000-0002-7668-9911 dawood@usgs.gov","orcid":"https://orcid.org/0000-0002-7668-9911","contributorId":4179,"corporation":false,"usgs":true,"family":"Wood","given":"Dustin","email":"dawood@usgs.gov","middleInitial":"A.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":815967,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rose, Jonathan P. 0000-0003-0874-9166 jprose@usgs.gov","orcid":"https://orcid.org/0000-0003-0874-9166","contributorId":199339,"corporation":false,"usgs":true,"family":"Rose","given":"Jonathan","email":"jprose@usgs.gov","middleInitial":"P.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":815968,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Halstead, Brian J. 0000-0002-5535-6528 bhalstead@usgs.gov","orcid":"https://orcid.org/0000-0002-5535-6528","contributorId":3051,"corporation":false,"usgs":true,"family":"Halstead","given":"Brian J.","email":"bhalstead@usgs.gov","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":815969,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stoelting, Ricka E.","contributorId":171533,"corporation":false,"usgs":false,"family":"Stoelting","given":"Ricka","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":815970,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Swaim, Karen E","contributorId":258210,"corporation":false,"usgs":false,"family":"Swaim","given":"Karen","email":"","middleInitial":"E","affiliations":[{"id":52239,"text":"Swaim Biological Incorporated","active":true,"usgs":false}],"preferred":false,"id":815971,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Vandergast, Amy G. 0000-0002-7835-6571","orcid":"https://orcid.org/0000-0002-7835-6571","contributorId":57201,"corporation":false,"usgs":true,"family":"Vandergast","given":"Amy","middleInitial":"G.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":815972,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70209896,"text":"70209896 - 2020 - Ringed seal (Pusa hispida) seasonal movements, diving, and haul-out behavior in the Beaufort, Chukchi, and Bering Seas (2011–2017)","interactions":[],"lastModifiedDate":"2020-07-09T14:55:32.503474","indexId":"70209896","displayToPublicDate":"2020-05-05T07:05:05","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Ringed seal (Pusa hispida) seasonal movements, diving, and haul-out behavior in the Beaufort, Chukchi, and Bering Seas (2011–2017)","docAbstract":"Continued Arctic warming and sea-ice loss will have important implications for the conservation of ringed seals, a highly ice-dependent species. A better understanding of their spatial ecology will help characterize emerging ecological trends and inform management decisions. We deployed satellite transmitters on ringed seals in the summers of 2011, 2014, and 2016 near Utqiaġvik (formerly Barrow), Alaska to monitor their movements, diving, and haul-out behavior. We present analyses of tracking and dive data provided by 17 seals that were tracked until at least January of the following year. Seals mostly ranged north of Utqiaġvik in the Beaufort and Chukchi Seas during summer before moving into the southern Chukchi and Bering Seas during winter. In all seasons, ringed seals occupied a diversity of habitats and spatial distributions; from near shore and localized, to far offshore and wide-ranging in drifting sea-ice. Continental shelf waters were occupied for >96% of tracking-days, during which repetitive-diving (suggestive of foraging) primarily to the seafloor was the most frequent activity. From mid-summer to early-fall, 12 seals made ~ one-week forays off-shelf to the deep Arctic Basin, most reaching the retreating pack-ice, where they spent most of their time hauled out. Diel activity patterns suggested greater allocation of foraging efforts to midday hours. Haul-out patterns were complementary, occurring mostly at night until April-May when midday hours were preferred. Ringed seals captured in 2011—concurrent with an unusual mortality event (UME) that affected all ice seal species—differed morphologically and behaviorally from seals captured in other years. Speculations about the physiology of molting and its role in energetics, habitat use, and behavior are discussed; along with possible evidence of purported ringed seal ecotypes.","language":"English","publisher":"Wiley","doi":"10.1002/ece3.6302","usgsCitation":"Von Duyke, A.L., Douglas, D.C., Herreman, J.K., and Crawford, J.A., 2020, Ringed seal (Pusa hispida) seasonal movements, diving, and haul-out behavior in the Beaufort, Chukchi, and Bering Seas (2011–2017): Ecology and Evolution, v. 10, no. 12, p. 5595-5616, https://doi.org/10.1002/ece3.6302.","productDescription":"21 p.","startPage":"5595","endPage":"5616","ipdsId":"IP-102815","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":456850,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.6302","text":"Publisher Index Page"},{"id":374482,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Beaufort Sea, Chukchi Sea, Bering Sea","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -141.50390625,\n 69.59589006237648\n ],\n [\n -141.6796875,\n 70.67088107015755\n ],\n [\n -149.94140625,\n 73.32785809840696\n ],\n [\n -161.19140625,\n 73.02259157147301\n ],\n [\n -168.57421875,\n 71.24435551310674\n ],\n [\n -168.75,\n 64.92354174306496\n ],\n [\n -170.68359375,\n 53.330872983017066\n ],\n [\n -166.9921875,\n 51.6180165487737\n ],\n [\n -158.73046875,\n 55.07836723201515\n ],\n [\n -156.796875,\n 58.81374171570782\n ],\n [\n -158.55468749999997,\n 63.31268278043484\n ],\n [\n -161.89453125,\n 69.16255790810501\n ],\n [\n -157.32421875,\n 71.13098770917023\n ],\n [\n -141.50390625,\n 69.59589006237648\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"10","issue":"12","noUsgsAuthors":false,"publicationDate":"2020-05-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Von Duyke, Andrew L.","contributorId":214208,"corporation":false,"usgs":false,"family":"Von Duyke","given":"Andrew","email":"","middleInitial":"L.","affiliations":[{"id":38995,"text":"North Slope Borough Department of Wildlife Management","active":true,"usgs":false}],"preferred":false,"id":788535,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Douglas, David C. 0000-0003-0186-1104 ddouglas@usgs.gov","orcid":"https://orcid.org/0000-0003-0186-1104","contributorId":2388,"corporation":false,"usgs":true,"family":"Douglas","given":"David","email":"ddouglas@usgs.gov","middleInitial":"C.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":788536,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Herreman, Jason K","contributorId":224482,"corporation":false,"usgs":false,"family":"Herreman","given":"Jason","email":"","middleInitial":"K","affiliations":[{"id":7058,"text":"Alaska Department of Fish and Game","active":true,"usgs":false}],"preferred":false,"id":788537,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Crawford, Justin A.","contributorId":214225,"corporation":false,"usgs":false,"family":"Crawford","given":"Justin","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":788538,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70210795,"text":"70210795 - 2020 - Climate-induced abrupt shifts in structural states trigger delayed transitions in functional states","interactions":[],"lastModifiedDate":"2020-06-25T15:19:11.910151","indexId":"70210795","displayToPublicDate":"2020-05-01T09:45:05","publicationYear":"2020","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":"Climate-induced abrupt shifts in structural states trigger delayed transitions in functional states","docAbstract":"

Theoretical models suggest that ecosystems can be found in one of several possible alternative stable states, and a shift in structural stable state (SSS) can trigger a change in functional stable state (FSS). But we still lack the empirical evidence to confirm these states and transitions, and to inform the rates of change. Here, a 30-yr dataset from long-term ungrazed and grazed temperate grasslands was analyzed to determine whether abrupt transitions of SSS and FSS can occur. We found that the long-term ungrazed grassland experienced abrupt transitions in the dominant plant functional type (shift in SSS) that was followed by a transition between carbon sink and source 1–2 year later (shift in FSS). A directional shift in precipitation and temperature accounted for 40% of the variation in the SSS transition, while the SSS transition explained 20% of the variation in the FSS transition. In contrast, no abrupt transitions for SSS and FSS were observed in the long-term moderately grazed grassland. These findings provide important insight into the interacting effects of climate change and livestock grazing on ecosystem transitions in temperate grasslands. Moderate utilization of production in ecosystems that have co-evolved with herbivores can offset structural and functional transitions induced by climate change.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolind.2020.106468","usgsCitation":"Hao, Y., Liu, W., Xu, X., Munson, S.M., Cui, X., Kang, X., He, N., and Wang, Y., 2020, Climate-induced abrupt shifts in structural states trigger delayed transitions in functional states: Ecological Indicators, v. 115, 106468, 8 p., https://doi.org/10.1016/j.ecolind.2020.106468.","productDescription":"106468, 8 p.","ipdsId":"IP-115093","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":375918,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"China","otherGeospatial":"Xilin River watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 115.33172607421876,\n 43.058854606434494\n ],\n [\n 117.79266357421874,\n 43.058854606434494\n ],\n [\n 117.79266357421874,\n 44.05601169578525\n ],\n [\n 115.33172607421876,\n 44.05601169578525\n ],\n [\n 115.33172607421876,\n 43.058854606434494\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"115","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Hao, Yanbin","contributorId":225529,"corporation":false,"usgs":false,"family":"Hao","given":"Yanbin","email":"","affiliations":[],"preferred":false,"id":791454,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Liu, Wenjun","contributorId":225530,"corporation":false,"usgs":false,"family":"Liu","given":"Wenjun","email":"","affiliations":[],"preferred":false,"id":791455,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Xu, Xingliang","contributorId":225531,"corporation":false,"usgs":false,"family":"Xu","given":"Xingliang","email":"","affiliations":[],"preferred":false,"id":791456,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Munson, Seth M. 0000-0002-2736-6374 smunson@usgs.gov","orcid":"https://orcid.org/0000-0002-2736-6374","contributorId":1334,"corporation":false,"usgs":true,"family":"Munson","given":"Seth","email":"smunson@usgs.gov","middleInitial":"M.","affiliations":[{"id":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":791457,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cui, Xiaoyong","contributorId":225533,"corporation":false,"usgs":false,"family":"Cui","given":"Xiaoyong","email":"","affiliations":[],"preferred":false,"id":791461,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kang, Xiaoming","contributorId":225532,"corporation":false,"usgs":false,"family":"Kang","given":"Xiaoming","email":"","affiliations":[],"preferred":false,"id":791458,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"He, Nianpeng","contributorId":225534,"corporation":false,"usgs":false,"family":"He","given":"Nianpeng","affiliations":[],"preferred":false,"id":791459,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Wang, Yan","contributorId":225535,"corporation":false,"usgs":false,"family":"Wang","given":"Yan","email":"","affiliations":[],"preferred":false,"id":791460,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70228790,"text":"70228790 - 2020 - The relationship between biodiversity and wetland cover varies across regions of the conterminous United States","interactions":[],"lastModifiedDate":"2022-02-21T15:35:17.141252","indexId":"70228790","displayToPublicDate":"2020-05-01T09:21:56","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"The relationship between biodiversity and wetland cover varies across regions of the conterminous United States","docAbstract":"Identifying the factors that determine the spatial distribution of biodiversity is a major focus of ecological research. These factors vary with scale from interspecific interactions to global climatic cycles. Wetlands are important biodiversity hotspots and contributors of ecosystem services, but the association between proportional wetland cover and species richness has shown mixed results. It is not well known as to what extent there is a relationship between proportional wetland cover and species richness, especially at the sub-continental scale. We used the National Wetlands Inventory to model wetland cover for the conterminous United States and the National Land Cover Database to estimate wetland change between 2001 and 2011. We used a Bayesian spatial Poisson model to estimate a spatially varying coefficient surface describing the effect of proportional wetland cover on the distribution of amphibians, birds, mammals, and reptiles and the cumulative distribution of terrestrial endemic species. Species richness and wetland cover were significantly correlated, and this relationship varied both spatially and by taxonomic group. Rather than a continental-scale association, however, we found that this relationship changed more closely among ecoregions. The species richness of each of the five groups was positively associated with wetland cover in some or all of the Great Plains; additionally, a positive association was found for mammals in the Southeastern Plains and Piedmont of the eastern U.S. Model results indicated negative association especially in the Cold Deserts and Northern Lakes & Forests of Minnesota and Wisconsin, though these varied greatly between groups. Our results highlight the need for wetland conservation initiatives that focus efforts at the level II and III ecoregional scale rather than along political boundaries. ","language":"English","publisher":"Public Library of Science","doi":"10.1371/journal.pone.0232052","usgsCitation":"Dertien, J.S., Self, S., Ross, B., Barrett, K., and Baldwin, R.F., 2020, The relationship between biodiversity and wetland cover varies across regions of the conterminous United States: PLoS ONE, v. 15, no. 5, p. 1-18, https://doi.org/10.1371/journal.pone.0232052.","productDescription":"e0232052, 18 p.","startPage":"1","endPage":"18","ipdsId":"IP-114472","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":456890,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0232052","text":"Publisher Index 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S.","contributorId":279799,"corporation":false,"usgs":false,"family":"Dertien","given":"Jeremy","email":"","middleInitial":"S.","affiliations":[{"id":7084,"text":"Clemson University","active":true,"usgs":false}],"preferred":false,"id":835487,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Self, Stella","contributorId":279800,"corporation":false,"usgs":false,"family":"Self","given":"Stella","email":"","affiliations":[{"id":7084,"text":"Clemson University","active":true,"usgs":false}],"preferred":false,"id":835488,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ross, Beth 0000-0001-5634-4951 bross@usgs.gov","orcid":"https://orcid.org/0000-0001-5634-4951","contributorId":199242,"corporation":false,"usgs":true,"family":"Ross","given":"Beth","email":"bross@usgs.gov","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":835490,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Barrett, Kyle","contributorId":149401,"corporation":false,"usgs":false,"family":"Barrett","given":"Kyle","email":"","affiliations":[],"preferred":false,"id":835491,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Baldwin, Robert F.","contributorId":96415,"corporation":false,"usgs":true,"family":"Baldwin","given":"Robert","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":835489,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70222593,"text":"70222593 - 2020 - Risk-targeted alternatives to deterministic ground motion caps in U.S. seismic provisions","interactions":[],"lastModifiedDate":"2021-08-09T12:02:34.873846","indexId":"70222593","displayToPublicDate":"2020-05-01T06:57:57","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1436,"text":"Earthquake Spectra","active":true,"publicationSubtype":{"id":10}},"title":"Risk-targeted 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Since their inception over 20 years ago, the maximum considered earthquake ground motion maps in U.S. building codes have capped probabilistic values with deterministic ground motions from characteristic earthquakes on known active faults. This practice has increasingly been called into question both because of spatially non-uniform risk levels that are produced (risk being higher mainly in coastal California) and practical difficulties in defining characteristic earthquakes from recent earthquake rupture forecast models. We describe two proposals developed to enable phase-out of deterministic caps. One approach modestly increases collapse risk targets nationwide based on recent information on return periods of characteristic earthquakes on major central and eastern U.S. seismic sources; adoption of this approach would remove the perceived need for caps in California. The second approach uses geographically varying collapse risk targets, being higher near the highly active faults in California and unchanged elsewhere. Neither approach was adopted for the 2020 National Earthquake Hazards Reduction Program recommended seismic Provisions for new building structures, but they are described in a Part 3 document to accompany the Provisions and Commentary.

","language":"English","publisher":"Sage Publishing","doi":"10.1177/8755293019892010","usgsCitation":"Stewart, J.P., Luco, N., Hooper, J.D., and Crouse, C.B., 2020, Risk-targeted alternatives to deterministic ground motion caps in U.S. seismic provisions: Earthquake Spectra, v. 36, no. 2, p. 904-923, https://doi.org/10.1177/8755293019892010.","productDescription":"20 p.","startPage":"904","endPage":"923","ipdsId":"IP-114191","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":387757,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"geometry\": {\n \"type\": \"MultiPolygon\",\n \"coordinates\": [\n [\n [\n [\n -94.81758,\n 49.38905\n ],\n [\n -94.64,\n 48.84\n ],\n [\n -94.32914,\n 48.67074\n ],\n [\n -93.63087,\n 48.60926\n ],\n [\n -92.61,\n 48.45\n 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Center","active":true,"usgs":true}],"preferred":true,"id":820718,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hooper, John D","contributorId":261834,"corporation":false,"usgs":false,"family":"Hooper","given":"John","email":"","middleInitial":"D","affiliations":[{"id":40526,"text":"Magnusson Klemencic Associates","active":true,"usgs":false}],"preferred":false,"id":820719,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Crouse, C. B.","contributorId":199388,"corporation":false,"usgs":false,"family":"Crouse","given":"C.","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":820720,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70228793,"text":"70228793 - 2020 - High spatial fidelity among foraging trips of Masked Boobies from Pedro Cays, Jamaica","interactions":[],"lastModifiedDate":"2022-02-21T15:20:54.403267","indexId":"70228793","displayToPublicDate":"2020-04-27T09:07:26","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"High spatial fidelity among foraging trips of Masked Boobies from Pedro Cays, Jamaica","docAbstract":"In marine environments, tropical and subtropical habitats are considered to be inherently less productive than more temperate systems. As such, foraging site fidelity among vertebrate predators occupying low-latitude marine systems is generally low as a response to an increased unpredictability of resources. We investigated the foraging movements of Masked Boobies breeding on Middle Cay, Jamaica using GPS loggers to examine if the presence of a nearby bathymetric feature influenced foraging site fidelity in a tropical system, the Caribbean Sea. According to the movements of tracked individuals, this population of boobies shows a high degree of spatial fidelity in foraging site selection, concentrated on the northern edge of Pedro Bank. We suggest this feature as an important location for marine conservation in the region and demonstrate its utility to foraging boobies via habitat modeling using a maximum entropy approach of relevant habitat variables. Finally, we place this study into the global context of Masked Booby foraging by examining the published literature of relevant tracking studies for population-level similarity in foraging metrics. According to hierarchical clustering of foraging effort, Masked Boobies demonstrate a density-dependent response to foraging effort regardless of colony origin or oceanic basin consistent with the principles of Ashmole’s Halo.","language":"English","publisher":"Public Library of Science","doi":"10.1371/journal.pone.0231654","usgsCitation":"Wilkinson, B.P., Haynes-Sutton, A.M., Meggs, L., and Jodice, P.G., 2020, High spatial fidelity among foraging trips of Masked Boobies from Pedro Cays, Jamaica: PLoS ONE, v. 15, no. 4, p. 1-12, https://doi.org/10.1371/journal.pone.0231654.","productDescription":"e0231654, 12 p.","startPage":"1","endPage":"12","ipdsId":"IP-114475","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":456950,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0231654","text":"Publisher Index Page"},{"id":437012,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9AK95EG","text":"USGS data release","linkHelpText":"At-sea movements of Masked Boobies from Pedro Cays, Jamaica, 2012"},{"id":396222,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Jamaica","otherGeospatial":"Middle Cay, Pedro Bank","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -77.50730037689209,\n 17.039305995351352\n ],\n [\n -77.50489711761475,\n 17.04258848897172\n ],\n [\n -77.50009059906006,\n 17.047389032085324\n ],\n [\n -77.5001335144043,\n 17.051122702576645\n ],\n [\n -77.50197887420654,\n 17.053707507666026\n ],\n [\n -77.50927448272705,\n 17.0520253369896\n ],\n [\n -77.51197814941406,\n 17.04578886474929\n ],\n [\n -77.5120210647583,\n 17.041029311689186\n ],\n [\n -77.50730037689209,\n 17.039305995351352\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"15","issue":"4","noUsgsAuthors":false,"publicationDate":"2020-04-27","publicationStatus":"PW","contributors":{"editors":[{"text":"Halliday, William David","contributorId":279828,"corporation":false,"usgs":false,"family":"Halliday","given":"William","email":"","middleInitial":"David","affiliations":[{"id":36893,"text":"Wildlife Conservation Society Canada","active":true,"usgs":false}],"preferred":false,"id":835517,"contributorType":{"id":2,"text":"Editors"},"rank":1}],"authors":[{"text":"Wilkinson, Bradley P.","contributorId":219853,"corporation":false,"usgs":false,"family":"Wilkinson","given":"Bradley","email":"","middleInitial":"P.","affiliations":[{"id":40079,"text":"Clemson University & South Carolina Cooperative Fish and Wildlife Research Unit","active":true,"usgs":false}],"preferred":false,"id":835492,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Haynes-Sutton, Ann M.","contributorId":279809,"corporation":false,"usgs":false,"family":"Haynes-Sutton","given":"Ann","email":"","middleInitial":"M.","affiliations":[{"id":57362,"text":"Marshalls Pen, Jamaica","active":true,"usgs":false}],"preferred":false,"id":835493,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Meggs, Llewelyn","contributorId":279810,"corporation":false,"usgs":false,"family":"Meggs","given":"Llewelyn","email":"","affiliations":[{"id":57363,"text":"Yardie Environmental Conservationists Limited","active":true,"usgs":false}],"preferred":false,"id":835494,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jodice, Patrick G.R. 0000-0001-8716-120X pjodice@usgs.gov","orcid":"https://orcid.org/0000-0001-8716-120X","contributorId":200009,"corporation":false,"usgs":true,"family":"Jodice","given":"Patrick","email":"pjodice@usgs.gov","middleInitial":"G.R.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":835495,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70209823,"text":"70209823 - 2020 - The incubation environment of nests deposited by a genetically distinct group of loggerhead sea turtles in Northwest Florida","interactions":[],"lastModifiedDate":"2020-05-05T17:27:04.980551","indexId":"70209823","displayToPublicDate":"2020-04-25T06:58:06","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3871,"text":"Global Ecology and Conservation","active":true,"publicationSubtype":{"id":10}},"title":"The incubation environment of nests deposited by a genetically distinct group of loggerhead sea turtles in Northwest Florida","docAbstract":"The warming climate presents a challenge to conservation of all threatened and endangered species but particularly to those that exhibit temperature-dependent sex determination such as sea turtles. Changes in temperature may result in changes in the sex ratio of the population which can directly affect reproductive rate, abundance and population dynamics. The NW Atlantic loggerhead turtle population is listed as threatened under the U.S. Endangered Species Act, and one of the smallest subpopulations in this assemblage nests in the northern Gulf of Mexico. Here, we describe the incubation environment of northern Gulf of Mexico loggerheads nesting at several different beaches in Northwest Florida. Temperature dataloggers were placed inside and adjacent to nests on different nesting beaches across Northwest Florida. In addition, incubation durations were recorded from nests deposited on those same beaches. Internal nest temperatures were higher than those in the sand, however sand temperatures were correlated with incubation durations. Sand temperatures differed along the vertical beach profile and according to depth. Temperatures also differed along a geographic gradient across Northwest Florida and in relation to distance from the Apalachicola River. Incubation durations followed a similar pattern. Mean monthly temperatures at all sites were at or lower than 29 °C (range 23.1 °C–29.6 °C at the dunes; 23.8 °C–29.4 °C at mid-beach) which suggests nests in Northwest Florida may be producing a significant number of males, in contrast to the large number of females being produced on Florida's Atlantic coast. The temperatures and incubation durations on these nesting beaches may be regulated by differing sources of sand and beach orientations across Northwest Florida.","language":"English","publisher":"Elsevier ","doi":"10.1016/j.gecco.2020.e01070","collaboration":"","usgsCitation":"Lamont, M., Johnson, D., and Carthy, R., 2020, The incubation environment of nests deposited by a genetically distinct group of loggerhead sea turtles in Northwest Florida: Global Ecology and Conservation, v. 23, e01070, 49 p., https://doi.org/10.1016/j.gecco.2020.e01070.","productDescription":"e01070, 49 p.","ipdsId":"IP-113153","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":456956,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.gecco.2020.e01070","text":"Publisher Index Page"},{"id":374392,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Northwest Florida","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -86.72607421875,\n 29.57345707301757\n ],\n [\n -84.0234375,\n 29.57345707301757\n ],\n [\n -84.0234375,\n 30.65681556429287\n ],\n [\n -86.72607421875,\n 30.65681556429287\n ],\n [\n -86.72607421875,\n 29.57345707301757\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"23","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Lamont, Margaret 0000-0001-7520-6669","orcid":"https://orcid.org/0000-0001-7520-6669","contributorId":211374,"corporation":false,"usgs":true,"family":"Lamont","given":"Margaret","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":788172,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Johnson, Darren 0000-0002-0502-6045","orcid":"https://orcid.org/0000-0002-0502-6045","contributorId":203921,"corporation":false,"usgs":true,"family":"Johnson","given":"Darren","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":788173,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Carthy, Raymond 0000-0001-8978-5083","orcid":"https://orcid.org/0000-0001-8978-5083","contributorId":219303,"corporation":false,"usgs":true,"family":"Carthy","given":"Raymond","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":788174,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70211828,"text":"70211828 - 2020 - Salt flushing, salt storage, and controls on selenium: A 31-year mass-balance analysis of an irrigated, semiarid valley","interactions":[],"lastModifiedDate":"2020-08-26T19:33:17.012994","indexId":"70211828","displayToPublicDate":"2020-04-23T16:45:44","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2529,"text":"Journal of the American Water Resources Association","active":true,"publicationSubtype":{"id":10}},"title":"Salt flushing, salt storage, and controls on selenium: A 31-year mass-balance analysis of an irrigated, semiarid valley","docAbstract":"

Salinity, selenium, and uranium pose water‐quality challenges for the Arkansas River in southeastern Colorado and other rivers that support irrigation in semiarid regions. This study used 31 years of continuous discharge and specific conductance (SC) monitoring data to assess interannual patterns in water quality using mass balance on a 120‐km reach of river. Discrete sampling data were used to link the SC records to salinity, selenium, and uranium. Several important patterns emerged. Consumptive use reduced discharge by a median value of 33% and drove corresponding increases in salinity and uranium concentrations. Increased water availability for irrigation from rainfall and upstream snowpack in 1995–1999 flushed additional salinity and uranium into the river in 1996–2000; average annual total dissolved solids (salinity) concentrations increased 25%, and loads increased 131%. Smaller flushing events have occurred, sometimes lagging an increase in water availability by about one year. The pattern indicates flushing of salts temporarily stored, evaporatively concentrated, or of geologic origin. Mobilization of selenium from the reach was minor compared to salinity and uranium, and net selenium removal from the river was suggested in some years. Several processes related to irrigation could be removing selenium. The results provide context for efforts to improve water quality in the Arkansas River and rivers in other semiarid regions.

","language":"English","publisher":"American Water Resources Association","doi":"10.1111/1752-1688.12841","usgsCitation":"Bern, C.R., Holmberg, M.J., and Kisfalusi, Z.D., 2020, Salt flushing, salt storage, and controls on selenium: A 31-year mass-balance analysis of an irrigated, semiarid valley: Journal of the American Water Resources Association, v. 56, no. 4, p. 647-668, https://doi.org/10.1111/1752-1688.12841.","productDescription":"22 p.","startPage":"647","endPage":"668","ipdsId":"IP-102689","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":456966,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/1752-1688.12841","text":"Publisher Index Page"},{"id":377212,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"Arkansas River Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -102.06298828125,\n 38.62545397209084\n ],\n [\n -103.45275878906249,\n 39.104488809440475\n ],\n [\n -104.5074462890625,\n 39.35978526869001\n ],\n [\n -105.9906005859375,\n 39.29604824402406\n ],\n [\n -106.622314453125,\n 39.78321267821705\n ],\n [\n -107.13317871093749,\n 39.65222681530652\n ],\n [\n -105.58959960937499,\n 38.12159327165922\n ],\n [\n -105.3369140625,\n 37.85316995894978\n ],\n [\n -105.4852294921875,\n 37.592471511019085\n ],\n [\n -105.2105712890625,\n 37.61858263247881\n ],\n [\n -105.018310546875,\n 37.405073750176925\n ],\n [\n -105.16113281249999,\n 37.03325468997236\n ],\n [\n -102.041015625,\n 36.99816565700228\n ],\n [\n -102.06298828125,\n 38.62545397209084\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"56","issue":"4","noUsgsAuthors":false,"publicationDate":"2020-04-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Bern, Carleton R. 0000-0002-8980-1781 cbern@usgs.gov","orcid":"https://orcid.org/0000-0002-8980-1781","contributorId":201152,"corporation":false,"usgs":true,"family":"Bern","given":"Carleton","email":"cbern@usgs.gov","middleInitial":"R.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":795266,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Holmberg, Michael J. 0000-0002-1316-0412 mholmber@usgs.gov","orcid":"https://orcid.org/0000-0002-1316-0412","contributorId":190084,"corporation":false,"usgs":true,"family":"Holmberg","given":"Michael","email":"mholmber@usgs.gov","middleInitial":"J.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":795267,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"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":795268,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70211831,"text":"70211831 - 2020 - Model selection for the North American Breeding Bird Survey","interactions":[],"lastModifiedDate":"2020-09-10T20:29:14.489574","indexId":"70211831","displayToPublicDate":"2020-04-23T16:28:27","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1450,"text":"Ecological Applications","active":true,"publicationSubtype":{"id":10}},"title":"Model selection for the North American Breeding Bird Survey","docAbstract":"

The North American Breeding Bird Survey (BBS) provides data that can be used in complex, multiscale analyses of population change, while controlling for scale‐specific nuisance factors. Many alternative models can be fit to the data, but most model selection procedures are not appropriate for hierarchical models. Leave‐one‐out cross‐validation (LOOCV), in which relative model fit is assessed by omitting an observation and assessing the prediction of a model fit using the remainder of the data, provides a reasonable approach for assessing models, but is time consuming and not feasible to apply for all observations in large data sets. We report the first large‐scale formal model selection for BBS data, applying LOOCV to stratified random samples of observations from BBS data. Our results are for 548 species of North American birds, comparing the fit of four alternative models that differ in year effect structures and in descriptions of extra‐Poisson overdispersion. We use a hierarchical model among species to evaluate posterior probabilities that models are best for individual species. Models in which differences in year effects are conditionally independent (D models) were generally favored over models in which year effects are modeled by a slope parameter and a random year effect (S models), and models in which extra‐Poisson overdispersion effects are independent and t‐distributed (H models) tended to be favored over models where overdispersion was independent and normally distributed. Our conclusions lead us to recommend a change from the conventional S model to D and H models for the vast majority of species (544/548). Comparison of estimated population trends based on the favored model relative to the S model currently used for BBS summaries indicates no consistent differences in estimated trends. Of the 18 species that showed large differences in estimated trends between models, estimated trends from the default S model were more extreme, reflecting the influence of the slope parameter in that model for species that are undergoing large population changes. WAIC, a computationally simpler alternative to LOOCV, does not appear to be a reliable alternative to LOOCV.

","language":"English","publisher":"Ecological Society of America","doi":"10.1002/eap.2137","usgsCitation":"Link, W.A., Sauer, J.R., and Niven, D.K., 2020, Model selection for the North American Breeding Bird Survey: Ecological Applications, v. 30, no. 6, e2037, 10 p., https://doi.org/10.1002/eap.2137.","productDescription":"e2037, 10 p.","ipdsId":"IP-112644","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":377210,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"North America","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -81.2109375,\n 7.013667927566642\n ],\n [\n -71.015625,\n 20.3034175184893\n ],\n [\n -77.34374999999999,\n 28.92163128242129\n ],\n [\n -68.5546875,\n 40.713955826286046\n ],\n [\n -50.625,\n 49.15296965617042\n ],\n [\n -62.22656249999999,\n 68.65655498475735\n ],\n [\n -84.375,\n 76.67978490310692\n ],\n [\n -123.04687499999999,\n 77.61770905279676\n ],\n [\n -131.1328125,\n 71.52490903732816\n ],\n [\n -159.2578125,\n 71.85622888185527\n ],\n [\n -166.9921875,\n 69.03714171275197\n ],\n [\n -166.9921875,\n 62.75472592723178\n ],\n [\n -162.7734375,\n 58.07787626787517\n ],\n [\n -162.421875,\n 54.97761367069628\n ],\n [\n -148.0078125,\n 56.36525013685606\n ],\n [\n -141.328125,\n 57.326521225217064\n ],\n [\n -134.296875,\n 54.36775852406841\n ],\n [\n -127.265625,\n 47.040182144806664\n ],\n [\n -126.21093749999999,\n 37.16031654673677\n ],\n [\n -116.01562499999999,\n 26.43122806450644\n ],\n [\n -104.0625,\n 14.944784875088372\n ],\n [\n -81.2109375,\n 7.013667927566642\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"30","issue":"6","noUsgsAuthors":false,"publicationDate":"2020-06-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Link, William A. 0000-0002-9913-0256 wlink@usgs.gov","orcid":"https://orcid.org/0000-0002-9913-0256","contributorId":146920,"corporation":false,"usgs":true,"family":"Link","given":"William","email":"wlink@usgs.gov","middleInitial":"A.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":795277,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sauer, John R. 0000-0002-4557-3019 jrsauer@usgs.gov","orcid":"https://orcid.org/0000-0002-4557-3019","contributorId":146917,"corporation":false,"usgs":true,"family":"Sauer","given":"John","email":"jrsauer@usgs.gov","middleInitial":"R.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":795278,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Niven, Daniel K 0000-0002-3253-7211 dniven@usgs.gov","orcid":"https://orcid.org/0000-0002-3253-7211","contributorId":237775,"corporation":false,"usgs":true,"family":"Niven","given":"Daniel","email":"dniven@usgs.gov","middleInitial":"K","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":795279,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70217223,"text":"70217223 - 2020 - The Missoula and Bonneville floods—A review of ice-age megafloods in the Columbia River basin","interactions":[],"lastModifiedDate":"2021-01-13T13:59:28.598323","indexId":"70217223","displayToPublicDate":"2020-04-22T07:51:58","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1431,"text":"Earth-Science Reviews","active":true,"publicationSubtype":{"id":10}},"title":"The Missoula and Bonneville floods—A review of ice-age megafloods in the Columbia River basin","docAbstract":"

The Channeled Scabland of eastern Washington State, USA, brought megafloods to the scientific forefront. A 30,000-km2 landscape of coulees and cataracts carved into the region’s loess-covered basalt attests to overwhelming volumes of energetic water. The scarred landscape, garnished by huge boulder bars and far-travelled ice-rafted erratics, spurred J Harlen Bretz’s vigorously disputed flood hypothesis in the 1920s. First known as the Spokane flood, it was rebranded the Missoula flood once understood that the water came from glacial Lake Missoula, formed when the Purcell Trench lobe of the last-glacial Cordilleran ice sheet dammed the Clark Fork valley in northwestern Idaho with ice a kilometer thick. Bretz’s flood evidence in the once-remote Channeled Scabland, widely seen and elaborated by the 1950s, eventually swayed consensus for cataclysmic flooding. Missoula flood questions then turned to some that continue today: how many? when? how big? what routes? what processes?

The Missoula floods passed through eastern Washington by a multitude of valleys, coulees and scabland tracts, some contemporaneously, some sequentially. Which routings and their timing depended on the positions of various lobes of the multi-pronged Cordilleran ice sheet and the erosional development of the channels themselves. The first floods mostly followed the big bend of Columbia valley looping through north-central Washington. But the south-advancing Okanogan ice lobe soon blocked that path, forming long-lasting glacial Lake Columbia in the impounded Columbia valley. Missoula floods into this lake were diverted south out of the Columbia valley and into eastern Washington coulees and scabland tracts. At least four floods entered Moses Coulee, but then as the Okanogan lobe advanced over and blocked the head of that coulee, more eastern paths took the water, including Grand Coulee and the Telford-Crab-Creek and Cheney-Palouse scabland tracts. Flood routing also depended on the erosion of the coulees. At some point, headward erosion of upper Grand Coulee lowered the divide saddle between the west-running Columbia valley and the deep and wide Grand Coulee heading southwest. Still uncertain is when this happened and the consequences with respect to the stage and extent of glacial Lake Columbia and to flood access to the other, higher, flood routes. Downstream, all flood routes converged onto Pasco Basin, flowed through Wallula Gap and the Columbia River Gorge into the Pacific Ocean, following submarine canyons and depositing sediment layers on abyssal plains.

Stratigraphic studies indicate dozens—likely more than a hundred—separate Missoula floods during the last glacial period. Over the length of the flood route, backwater areas and depositional basins preserve multiple flood beds, many of which are separated by signs of time, including volcanic ash layers and soil development in subaerial environments; and varve-like beds and pelagic mud layers in lacustrine and marine settings. Evidence also comes from the glacial Lake Missoula basin, where stratigraphy indicates dozens of filling and emptying cycles. Varve counts in conjunction of radiocarbon dating and paleomagnetic secular variation show the repeated filling-and-release cycles of glacial Lake Missoula had intervals possibly as long as 100 years early in the lake’s history but diminished to just one or two years for the last few floods. This behavior accords with jökulhlaup-style floods released by subglacial drainage from a self-dumping ice-dammed lake. But not yet clear is whether such a mechanism applies to all the floods or if some emptied more cataclysmically as hypothesized by some.

Radiocarbon dating of sparse organic materials remains key to defining flood chronology but has been lately bolstered by analyses of terrestrial cosmogenic nuclides and optically stimulated luminescence. Varve counts and paleomagnetic secular variation studies help to define durations and intervals represented by sequences of flood beds. The ~16 ka Mount St. Helens Set S tephra is commonly interbedded within flood deposits, enabling correlation of deposits among sites. Tephra from the 13.7–13.4 ka eruption of Glacier Peak overlies all glacial Lake Missoula and Missoula flood deposits, defining an end time. Overall conclusions are that glacial Lake Missoula was extant and producing floods for at least 3–4 ky during 20–14 ka. At least ~75 floods preceded Mount St Helens Set S, followed by 30 or more after the tephra fall. Most floods entered glacial Lake Columbia, impounded by the Okanogan lobe, for 2–5 ky between about 18.5 and 15 ka. Glacial Lake Columbia outlived Lake Missoula by >200–400 yr but may have been born later since at least one flood came down the Columbia valley before the Okanogan ice lobe blocked the Columbia valley at 18.5–18 ka. The maximum extent of the Okanogan and Purcell Trench lobes, many Missoula floods, substantial erosion of upper Grand Coulee, and the widespread tephra falls from Mount St. Helens eruptions all happened about 17–15 ka. People, in the area since 16.6–15.3 ka, almost certainly witnessed the last of the Missoula floods and later large floods from other ice-dammed lakes in the Columbia River basin.

Quantitative flow analyses give peak discharge estimates and support understanding of erosional and depositional processes. The first flow assessments were simple cross-section calculations but recent assessments employ two-dimensional hydrodynamic models. The general finding is that emplacement of the maximum stage evidence requires about 20 million m3/s near the Lake Missoula outlet and about 5–15 million m3/s through Wallula Gap and downstream in the Columbia River Gorge. These hydraulic analyses raise still-unresolved questions regarding canyon erosion and possible additional water sources.

The large Pleistocene Bonneville flood entered the Columbia River system from the southeast from pluvial Lake Bonneville, the Pleistocene predecessor to Great Salt Lake in the eastern Great Basin. During the last glacial, the lake basin filled, covering >50,000 km2 with 10,400 km3 of water before reaching its maximum possible stage governed by Red Rock Pass, the lowest divide separating the basin from the Snake River basin to the north. The overtopping lake rapidly incised 108–125 m into the Red Rock Pass outlet, spilling half of its total lake volume. G.K. Gilbert described the essential sequence in the 1870s, but the flood was mostly forgotten until the late 1950s when Harold Malde linked the spectacular scabland topography and bouldery “melon gravel” on the Snake River Plain to the Lake Bonneville overflow. The Bonneville flood appears to have been a singular event at about 18 ka. No evidence of multiple or pre-last-glacial spillovers has yet been found. Its total volume was about twice that of a maximum Lake Missoula flood yet its peak discharge was ~1 million m3/s, less than a tenth of the largest Missoula floods. Its comparatively simple flow path and much steadier flow make the Bonneville flood ideal for new studies of erosional and depositional processes.

At least two floods seem to have passed down the Columbia valley after the last of the Missoula floods, including a large flood about ~14 ka likely from cataclysmic demise of the thinning Okanogan ice lobe dam impounding glacial Lake Columbia. Floods from earlier glacial ages left scant yet clear evidence in the Channeled Scabland and Columbia valley. But their source, timing, and magnitudes are little understood. Some deposits are paleomagnetically reversed, thus older than ~800 ka. Last-glacial floods and perhaps older ones affected the Snake River Plain, some likely sourced in lakes dammed by alpine glaciers in central Idaho.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.earscirev.2020.103181","usgsCitation":"O'Connor, J., Baker, V.R., Waitt, R.B., Smith, L.N., Cannon, C.M., George, D.L., and Denlinger, R.P., 2020, The Missoula and Bonneville floods—A review of ice-age megafloods in the Columbia River basin: Earth-Science Reviews, v. 208, 103181, 51 p., https://doi.org/10.1016/j.earscirev.2020.103181.","productDescription":"103181, 51 p.","ipdsId":"IP-117652","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":456992,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://archimer.ifremer.fr/doc/00624/73634/","text":"External Repository"},{"id":382128,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho, Oregon, Washington","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -120.76171875,\n 45.73685954736049\n ],\n [\n -116.4111328125,\n 45.73685954736049\n ],\n [\n -116.4111328125,\n 48.31242790407178\n ],\n [\n -120.76171875,\n 48.31242790407178\n ],\n [\n -120.76171875,\n 45.73685954736049\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"208","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"O'Connor, Jim E. 0000-0002-7928-5883 oconnor@usgs.gov","orcid":"https://orcid.org/0000-0002-7928-5883","contributorId":140771,"corporation":false,"usgs":true,"family":"O'Connor","given":"Jim E.","email":"oconnor@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":false,"id":808089,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Baker, Victor R.","contributorId":201141,"corporation":false,"usgs":false,"family":"Baker","given":"Victor","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":808090,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Waitt, Richard B. 0000-0002-6392-5604 waitt@usgs.gov","orcid":"https://orcid.org/0000-0002-6392-5604","contributorId":2343,"corporation":false,"usgs":true,"family":"Waitt","given":"Richard","email":"waitt@usgs.gov","middleInitial":"B.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":808091,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Smith, Larry N","contributorId":247679,"corporation":false,"usgs":false,"family":"Smith","given":"Larry","email":"","middleInitial":"N","affiliations":[{"id":49605,"text":"Montana Technological University","active":true,"usgs":false}],"preferred":false,"id":808092,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cannon, Charles M. 0000-0003-4136-2350 ccannon@usgs.gov","orcid":"https://orcid.org/0000-0003-4136-2350","contributorId":247680,"corporation":false,"usgs":true,"family":"Cannon","given":"Charles","email":"ccannon@usgs.gov","middleInitial":"M.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":808093,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"George, David L. 0000-0002-5726-0255 dgeorge@usgs.gov","orcid":"https://orcid.org/0000-0002-5726-0255","contributorId":3120,"corporation":false,"usgs":true,"family":"George","given":"David","email":"dgeorge@usgs.gov","middleInitial":"L.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":808094,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Denlinger, Roger P. 0000-0003-0930-0635 roger@usgs.gov","orcid":"https://orcid.org/0000-0003-0930-0635","contributorId":2679,"corporation":false,"usgs":true,"family":"Denlinger","given":"Roger","email":"roger@usgs.gov","middleInitial":"P.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true}],"preferred":true,"id":808095,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70215136,"text":"70215136 - 2020 - Post-fire management-scale trials of bacterial soil amendment MB906 show inconsistent control of invasive annual grasses","interactions":[],"lastModifiedDate":"2020-11-13T20:17:35.369323","indexId":"70215136","displayToPublicDate":"2020-04-21T07:51:50","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3228,"text":"Rangeland Ecology and Management","onlineIssn":"1551-5028","printIssn":"1550-7424","active":true,"publicationSubtype":{"id":10}},"title":"Post-fire management-scale trials of bacterial soil amendment MB906 show inconsistent control of invasive annual grasses","docAbstract":"

Rangeland managers need tools to control invasive annual grasses, particularly following wildfire. We assessed responses of native and invasive/exotic grasses to the MB906 soil amendment containing live cultures of a purportedly weed-suppressive strain of the bacterium Pseudomonas fluorescens (“WSB”). MB906 was applied alone and in combination with the pre-emergent herbicide imazapic on >3000 ha across three sagebrush-steppe landscapes burned several months prior. Replicate plots of each treatment type were established and plant cover was measured in the following three years. Cover of invasive-annual grasses (“IAG”) was not responsive to MB906 when all IAG species were considered (“IAG-All”). However, MB906 led to a 54% reduction in the IAG's that were previously reported to be controlled by WSB (“IAG-Target”) in the second year following application (IAG-Target = cheatgrass, Bromus tectorum and medusahead, Taeniatherum caput-medusae; IAG-All also includes Vulpia myuros and Bromus arvensis). MB906 reduced the effectiveness of co-applied imazapic: Imazapic alone reduced IAG-All by 83% and 68% in years 1 and 2, respectively, while imazapic+MB906 reduced IAG-All by 48% and 38% in years 1 and 2, respectively, across all landscapes, and a similar response pattern was observed for IAG-Target. Perennial grass cover was unaffected by the treatments except where it increased 4-fold in response to imazapic applied at a high rate (0.140 kg a.i. ha−1) in one of the landscapes. Tank mixing MB906 and herbicide may have lessened the biological activity of the herbicide by altering the pH or mineral content of the spray solution or by direct metabolism of the herbicide by the bacteria. These results do not provide strong support for MB906 as a tool for annual grass control, though they suggest further investigation may be warranted.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.rama.2020.03.005","usgsCitation":"Lazarus, B., Germino, M., Brabec, M., Peterson, L., Walker, R.N., and Moser, A., 2020, Post-fire management-scale trials of bacterial soil amendment MB906 show inconsistent control of invasive annual grasses: Rangeland Ecology and Management, v. 73, no. 6, p. 741-748, https://doi.org/10.1016/j.rama.2020.03.005.","productDescription":"8 p.","startPage":"741","endPage":"748","ipdsId":"IP-111914","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":456999,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.rama.2020.03.005","text":"Publisher Index Page"},{"id":379219,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"73","issue":"6","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Lazarus, Brynne E. 0000-0002-6352-486X","orcid":"https://orcid.org/0000-0002-6352-486X","contributorId":242732,"corporation":false,"usgs":true,"family":"Lazarus","given":"Brynne E.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":800973,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Germino, Matthew 0000-0001-6326-7579","orcid":"https://orcid.org/0000-0001-6326-7579","contributorId":218007,"corporation":false,"usgs":true,"family":"Germino","given":"Matthew","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":800974,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brabec, Martha mbrabec@usgs.gov","contributorId":242857,"corporation":false,"usgs":false,"family":"Brabec","given":"Martha","email":"mbrabec@usgs.gov","affiliations":[{"id":37341,"text":"City of Boise","active":true,"usgs":false}],"preferred":false,"id":800975,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Peterson, Logan","contributorId":242860,"corporation":false,"usgs":false,"family":"Peterson","given":"Logan","email":"","affiliations":[{"id":36224,"text":"Idaho Department of Fish and Game","active":true,"usgs":false}],"preferred":false,"id":800976,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Walker, Ryan N","contributorId":242863,"corporation":false,"usgs":false,"family":"Walker","given":"Ryan","email":"","middleInitial":"N","affiliations":[{"id":36224,"text":"Idaho Department of Fish and Game","active":true,"usgs":false}],"preferred":false,"id":800977,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Moser, Ann","contributorId":201657,"corporation":false,"usgs":false,"family":"Moser","given":"Ann","affiliations":[{"id":36224,"text":"Idaho Department of Fish and Game","active":true,"usgs":false}],"preferred":false,"id":800978,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70228644,"text":"70228644 - 2020 - Preliminary investigation of the critically imperiled Caney Mountain cave crayfish Orconectes stygocaneyi Hobbs III, 2001 (Decapoda: Cambaridae) in Missouri, USA","interactions":[],"lastModifiedDate":"2022-02-16T20:51:34.474746","indexId":"70228644","displayToPublicDate":"2020-04-17T14:43:19","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5290,"text":"Freshwater Crayfish","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Preliminary investigation of the critically imperiled Caney Mountain cave crayfish Orconectes stygocaneyi Hobbs III, 2001 (Decapoda: Cambaridae) in Missouri, USA","title":"Preliminary investigation of the critically imperiled Caney Mountain cave crayfish Orconectes stygocaneyi Hobbs III, 2001 (Decapoda: Cambaridae) in Missouri, USA","docAbstract":"

The Caney Mountain cave crayfish (Orconectes stygocaneyi) is one of North America's rarest crayfish, endemic to one cave in southern Missouri, USA. The species is listed as 'critically imperiled' by Missouri, and 'threatened' by the American Fisheries Society. Previously, only 15 crayfish have been observed in Mud Cave, and only two have been collected (for original species description). We aimed to collect the first natural history data on the species and search adjacent caves and springs for additional populations. Twelve visual searches and supplemental trapping over four years, in all seasons, yielded 69 O. stygocaneyi (including 11 young-of-year) observations and capture of 22 crayfish, including one ovigerous female. Visual searches of nearby caves and springs yielded no O. stygocaneyi records. However, multiple surveys of those caves and springs, using environmental DNA detected the species in one additional cave adjacent to Mud Cave, but only during spring high flow events when the caves may be ephemerally connected. Orconectes stygocaneyi's distribution is among the most restricted of any North American crayfish, and further evaluation of its conservation status designations might be warranted. Long term conservation of O. stygocaneyi would benefit from management practices promoting sustained, unimpacted surface runoff within Mud Cave's recharge area.

","language":"English","publisher":"International Association of Astacology","doi":"10.5869/fc.2020.v25-1.047","usgsCitation":"DiStefano, R., Ashley, D., Brewer, S.K., Mouser, J., and Neimiller, M., 2020, Preliminary investigation of the critically imperiled Caney Mountain cave crayfish Orconectes stygocaneyi Hobbs III, 2001 (Decapoda: Cambaridae) in Missouri, USA: Freshwater Crayfish, v. 25, no. 1, p. 47-57, https://doi.org/10.5869/fc.2020.v25-1.047.","productDescription":"11 p.","startPage":"47","endPage":"57","ipdsId":"IP-113351","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":396037,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Missouri","otherGeospatial":"Mud Lake","volume":"25","issue":"1","noUsgsAuthors":false,"publicationDate":"2020-04-15","publicationStatus":"PW","contributors":{"authors":[{"text":"DiStefano, Robert J.","contributorId":213268,"corporation":false,"usgs":false,"family":"DiStefano","given":"Robert J.","affiliations":[{"id":16971,"text":"Missouri Department of Conservation","active":true,"usgs":false}],"preferred":false,"id":834913,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ashley, D.C.","contributorId":244487,"corporation":false,"usgs":false,"family":"Ashley","given":"D.C.","email":"","affiliations":[{"id":48915,"text":"Missouri Western State University","active":true,"usgs":false}],"preferred":false,"id":834914,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brewer, Shannon K. 0000-0002-1537-3921 skbrewer@usgs.gov","orcid":"https://orcid.org/0000-0002-1537-3921","contributorId":2252,"corporation":false,"usgs":true,"family":"Brewer","given":"Shannon","email":"skbrewer@usgs.gov","middleInitial":"K.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":834915,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mouser, J.B.","contributorId":244447,"corporation":false,"usgs":false,"family":"Mouser","given":"J.B.","affiliations":[{"id":7249,"text":"Oklahoma State University","active":true,"usgs":false}],"preferred":false,"id":834916,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Neimiller, M.","contributorId":279385,"corporation":false,"usgs":false,"family":"Neimiller","given":"M.","email":"","affiliations":[{"id":36730,"text":"University of Alabama","active":true,"usgs":false}],"preferred":false,"id":834917,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70220209,"text":"70220209 - 2020 - Seasonal manganese transport in the hyporheic zone of a snowmelt-dominated river (East River, Colorado)","interactions":[],"lastModifiedDate":"2021-04-27T17:16:33.696458","indexId":"70220209","displayToPublicDate":"2020-04-17T12:10:10","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1923,"text":"Hydrogeology Journal","active":true,"publicationSubtype":{"id":10}},"title":"Seasonal manganese transport in the hyporheic zone of a snowmelt-dominated river (East River, Colorado)","docAbstract":"

Manganese (Mn) plays a critical role in river-water quality because Mn-oxides serve as sorption sites for contaminant metals. The aim of this study is to understand the seasonal cycling of Mn in an alpine streambed that experiences large spring snowmelt events and the potential responses to changes in snowmelt timing and magnitude. To address this goal, annual variations in river-water/groundwater interaction and Mn(aq) transport were measured and modeled in the bed of East River, Colorado, USA. In observations and numerical models, oxygenated river water containing dissolved organic carbon (DOC) mixes with groundwater rich in Mn(aq) in the streambed. The mixing depth increases during spring snowmelt when river discharge increases, leading to a greater DOC supply to the hyporheic zone and net respiration of Mn-oxides, despite an enhanced supply of oxygen. As groundwater upwelling resumes during the subsequent baseflow period, Mn(aq)-rich groundwater mixes with oxygenated river water, resulting in net accumulation of Mn-oxides until the bed freezes in winter. To explore potential responses of Mn transport to different climate-induced hydrological regimes, three hydrograph scenarios were numerically modeled (historic, low-snow, and storm) for the Rocky Mountain region. In a warming climate, Mn(aq) export to the river decreases, and Mn(aq) oxidation is favored in the upper streambed sediments over more of the year. One important implication is that the streambed may have an increased sorption capacity for metals over more of the year, leading to potential changes in river-water quality.

","language":"English","publisher":"Springer","doi":"10.1007/s10040-020-02146-6","usgsCitation":"Bryant, S., Sawyer, A., Briggs, M., Saup, C., Nelson, A.R., Wilkins, M.J., Christensen, J.R., and Williams, K.H., 2020, Seasonal manganese transport in the hyporheic zone of a snowmelt-dominated river (East River, Colorado): Hydrogeology Journal, v. 28, p. 1323-1341, https://doi.org/10.1007/s10040-020-02146-6.","productDescription":"19 p.","startPage":"1323","endPage":"1341","ipdsId":"IP-115069","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":385333,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"East River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -106.95238709449768,\n 38.92190699243362\n ],\n [\n -106.94936156272888,\n 38.92190699243362\n ],\n [\n -106.94936156272888,\n 38.923893566458055\n ],\n [\n -106.95238709449768,\n 38.923893566458055\n ],\n [\n -106.95238709449768,\n 38.92190699243362\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"28","noUsgsAuthors":false,"publicationDate":"2020-04-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Bryant, S.","contributorId":222764,"corporation":false,"usgs":false,"family":"Bryant","given":"S.","email":"","affiliations":[{"id":36630,"text":"Ohio State University","active":true,"usgs":false}],"preferred":false,"id":814777,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sawyer, A.","contributorId":222761,"corporation":false,"usgs":false,"family":"Sawyer","given":"A.","email":"","affiliations":[{"id":36630,"text":"Ohio State University","active":true,"usgs":false}],"preferred":false,"id":814778,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Briggs, Martin A. 0000-0003-3206-4132","orcid":"https://orcid.org/0000-0003-3206-4132","contributorId":257637,"corporation":false,"usgs":true,"family":"Briggs","given":"Martin A.","affiliations":[{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true}],"preferred":true,"id":814779,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Saup, C.","contributorId":222763,"corporation":false,"usgs":false,"family":"Saup","given":"C.","email":"","affiliations":[{"id":36630,"text":"Ohio State University","active":true,"usgs":false}],"preferred":false,"id":814780,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Nelson, A. R","contributorId":193402,"corporation":false,"usgs":false,"family":"Nelson","given":"A.","email":"","middleInitial":"R","affiliations":[],"preferred":false,"id":814781,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wilkins, M. J.","contributorId":176779,"corporation":false,"usgs":false,"family":"Wilkins","given":"M.","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":814782,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Christensen, J. R.","contributorId":204686,"corporation":false,"usgs":false,"family":"Christensen","given":"J.","email":"","middleInitial":"R.","affiliations":[{"id":36974,"text":"U.S. Environmental Protection Agency, National Exposure Research Laboratory, Las Vegas, NV","active":true,"usgs":false}],"preferred":false,"id":814783,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Williams, K. H.","contributorId":176777,"corporation":false,"usgs":false,"family":"Williams","given":"K.","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":814784,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70209899,"text":"70209899 - 2020 - Modeling the supporting ecosystem services of depressional wetlands","interactions":[],"lastModifiedDate":"2020-10-28T15:24:41.697512","indexId":"70209899","displayToPublicDate":"2020-04-17T07:09:36","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3750,"text":"Wetlands","onlineIssn":"1943-6246","printIssn":"0277-5212","active":true,"publicationSubtype":{"id":10}},"title":"Modeling the supporting ecosystem services of depressional wetlands","docAbstract":"We explored how a geographic information system modeling approach could be used to quantify supporting ecosystem services related to the type, abundance, and distribution of landscape components. Specifically, we use the Integrated Valuation of Ecosystem Services and Tradeoffs model to quantify habitats that support amphibians and birds, floral resources that support pollinators, native-plant communities that support regional biodiversity, and above- and below-ground carbon stores in the Des Moines Lobe ecoregion of the U.S. We quantified services under two scenarios, one that represented the 2012 Des Moines Lobe landscape, and one that simulated the conversion to crop production of wetlands and surrounding uplands conserved under the USDA Agricultural Conservation Easement Program (ACEP). While ACEP easements only covered 0.35% of the ecoregion, preserved wetlands and grasslands provided for 19,020 ha of amphibian habitat, 21,462 ha of grassland-bird habitat, 18,798 ha of high-quality native wetland plants, and 27,882 ha of floral resources for pollinators. Additionally, ACEP protected lands stored 257,722 tonnes of carbon that, if released, would result in costs in excess of 45-million USD. An integrated approach using results from a GIS-based model in combination with process-based model quantifications will facilitate more informed decisions related to ecosystem service tradeoffs.","language":"English","publisher":"Springer","doi":"10.1007/s13157-020-01297-2","usgsCitation":"Mushet, D.M., and Roth, C.L., 2020, Modeling the supporting ecosystem services of depressional wetlands: Wetlands, v. 40, p. 1061-1069, https://doi.org/10.1007/s13157-020-01297-2.","productDescription":"9 p.","startPage":"1061","endPage":"1069","ipdsId":"IP-108440","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":457054,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s13157-020-01297-2","text":"Publisher Index Page"},{"id":374483,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Iowa, Minnesota","otherGeospatial":"Prairie Pothole Region","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -95.9326171875,\n 43.34116005412307\n ],\n [\n -95.20751953125,\n 41.31082388091818\n ],\n [\n -93.84521484375,\n 41.09591205639546\n ],\n [\n -93.22998046875,\n 41.52502957323801\n ],\n [\n -94.02099609375,\n 43.50075243569041\n ],\n [\n -93.44970703125,\n 44.05601169578525\n ],\n [\n -93.7353515625,\n 44.55916341529182\n ],\n [\n -94.72412109375,\n 45.01141864227728\n ],\n [\n -95.82275390625,\n 44.793530904744074\n ],\n [\n -95.9326171875,\n 43.34116005412307\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"40","noUsgsAuthors":false,"publicationDate":"2020-04-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Mushet, David M. 0000-0002-5910-2744 dmushet@usgs.gov","orcid":"https://orcid.org/0000-0002-5910-2744","contributorId":1299,"corporation":false,"usgs":true,"family":"Mushet","given":"David","email":"dmushet@usgs.gov","middleInitial":"M.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":788546,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Roth, Cali L. 0000-0001-9077-2765 croth@usgs.gov","orcid":"https://orcid.org/0000-0001-9077-2765","contributorId":174422,"corporation":false,"usgs":true,"family":"Roth","given":"Cali","email":"croth@usgs.gov","middleInitial":"L.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true},{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":788547,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70227129,"text":"70227129 - 2020 - Methods for rapidly estimating velocity precision from GNSS time series in the presence of temporal correlation: A new method and comparison of existing methods","interactions":[],"lastModifiedDate":"2022-01-03T15:57:57.793919","indexId":"70227129","displayToPublicDate":"2020-04-15T08:04:06","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2312,"text":"Journal of Geophysical Research","active":true,"publicationSubtype":{"id":10}},"title":"Methods for rapidly estimating velocity precision from GNSS time series in the presence of temporal correlation: A new method and comparison of existing methods","docAbstract":"

Time series of position estimates from Global Navigational Satellite System (GNSS) are used to measure the velocities of points on the surface of the Earth. Along with the velocity estimates, a measure of the precision is needed to assess the quality of the velocity measurement. Here, I evaluate rate uncertainties provided by four different methods that have been applied to geodetic time series. The most rigorous approach uses a data covariance that incorporates a variety of noise processes relevant to geodetic time series but is computationally demanding. Two other approaches are efficient algorithms and are used widely, but both can provide less rigorous estimates of the rate uncertainty. I propose and evaluate a fourth method, which provides estimates of rate uncertainty closer to the rigorous approach but is significantly less computationally demanding. I have evaluated all three methods against the more rigorous method using both simulations and time series from 190 GNSS sites. For data best characterized as having a flicker type noise process, one of the widely used methods overestimates the uncertainty by up to a factor of 2, while the other widely used method underestimates the uncertainty by less than a factor of 2. For a random-walk process, both methods underestimate the rate uncertainty by a factor of 3 to 5.

","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2019JB019132","usgsCitation":"Langbein, J., 2020, Methods for rapidly estimating velocity precision from GNSS time series in the presence of temporal correlation: A new method and comparison of existing methods: Journal of Geophysical Research, v. 125, no. 7, p. 1-16, https://doi.org/10.1029/2019JB019132.","productDescription":"e2019JB019132, 16 p.","startPage":"1","endPage":"16","ipdsId":"IP-112015","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":457077,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2019jb019132","text":"Publisher Index Page"},{"id":393644,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"125","issue":"7","noUsgsAuthors":false,"publicationDate":"2020-07-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Langbein, John 0000-0002-7821-8101","orcid":"https://orcid.org/0000-0002-7821-8101","contributorId":212735,"corporation":false,"usgs":true,"family":"Langbein","given":"John","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":829747,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70219022,"text":"70219022 - 2020 - Sample mounting for organic petrology: No thermal effects from transient exposure to elevated temperatures","interactions":[],"lastModifiedDate":"2021-03-22T12:06:17.029941","indexId":"70219022","displayToPublicDate":"2020-04-15T07:17:53","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2033,"text":"International Journal of Coal Geology","active":true,"publicationSubtype":{"id":10}},"title":"Sample mounting for organic petrology: No thermal effects from transient exposure to elevated temperatures","docAbstract":"

For sample mounting, organic petrology laboratories typically use cold-setting epoxy-resin (e.g., 40 °C, used by Oklahoma Geological Survey, OGS) or heat-setting thermoplastic (e.g., 180 °C, used by U.S. Geological Survey, USGS). Previous workers have suggested a systematic huminite/vitrinite reflectance (VRo) increase was associated with the thermoplastic preparation process, relative to epoxy mounting, which was possibly attributed to moisture loss from organic matter due to the transient high temperatures of plastic mounting. In this study, we evaluated thermal effects to low thermal maturity organic matter from transient exposure to elevated temperatures. A subbituminous coal sample was subjected to long-term (4 to 38 weeks) exposure to temperatures of 85 to 120 °C and afterward evaluated by multiple approaches to test thermal advance [elemental analyses, Rock-Eval pyrolysis, Fourier transform infrared spectroscopy (FTIR), nuclear magnetic resonance (NMR), pyrolysis gas chromatography, and petrographic analyses, including huminite/vitrinite reflectance and spectral fluorescence], all of which showed no detectable systematic (statistically insignificant) changes between the original sample and its heat-treated products. We also compared huminite/vitrinite reflectance of six low thermal maturity samples (those most likely to react to transient heating) mounted via both cold-setting epoxy-resin and heat-setting thermoplastic. Results indicate measured VRo of a sample prepared by one mounting process was within the standard deviation of reflectance for the same sample prepared via the other process. Moreover, VRo results were not systematically higher in thermoplastic mounts. Contrary to previous work, these results suggest thermoplastic mounting or other transient exposure to elevated temperatures does not impact thermal maturity estimates from reflectance measurement for low thermal maturity organic samples. Furthermore, the average interlaboratory difference in measured VRo (between OGS and USGS) for the same sample prepared by either epoxy-resin or thermoplastic mounting was 0.038%, about double the average difference between VRo for the same sample prepared via epoxy-resin versus thermoplastic in a single laboratory (0.024%). This result indicates interlaboratory variability impacts VRo measurement reproducibility to the extent that systematic differences could not be observed between thermoplastic and cold-setting sample preparation approaches, even if such differences were present.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.coal.2020.103446","usgsCitation":"Hackley, P.C., and Cardott, B.J., 2020, Sample mounting for organic petrology: No thermal effects from transient exposure to elevated temperatures: International Journal of Coal Geology, v. 223, 103446, 12 p., https://doi.org/10.1016/j.coal.2020.103446.","productDescription":"103446, 12 p.","ipdsId":"IP-113691","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":457083,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.coal.2020.103446","text":"Publisher Index Page"},{"id":384526,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"223","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Hackley, Paul C. 0000-0002-5957-2551 phackley@usgs.gov","orcid":"https://orcid.org/0000-0002-5957-2551","contributorId":592,"corporation":false,"usgs":true,"family":"Hackley","given":"Paul","email":"phackley@usgs.gov","middleInitial":"C.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true}],"preferred":true,"id":812487,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cardott, Brian J.","contributorId":255079,"corporation":false,"usgs":false,"family":"Cardott","given":"Brian","email":"","middleInitial":"J.","affiliations":[{"id":51412,"text":"Oklahoma Geological Survey, USA","active":true,"usgs":false}],"preferred":false,"id":812488,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70221156,"text":"70221156 - 2020 - Genesis and evolution of ferromanganese crusts from the summit of Rio Grande Rise, southwest Atlantic Ocean","interactions":[],"lastModifiedDate":"2021-06-03T12:54:29.476362","indexId":"70221156","displayToPublicDate":"2020-04-14T07:45:03","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5207,"text":"Minerals","active":true,"publicationSubtype":{"id":10}},"title":"Genesis and evolution of ferromanganese crusts from the summit of Rio Grande Rise, southwest Atlantic Ocean","docAbstract":"
The Rio Grande Rise (RGR) is a large elevation in the Atlantic Ocean and known to host potential mineral resources of ferromanganese crusts (Fe–Mn), but no investigation into their general characteristics have been made in detail. Here, we investigate the chemical and mineralogical composition, growth rates and ages of initiation, and phosphatization of relatively shallow-water (650–825 m) Fe–Mn crusts dredged from the summit of RGR by using computed tomography, X-ray diffraction, 87Sr/86Sr ratios, U–Th isotopes, and various analytical techniques to determine their chemical composition. Fe–Mn crusts from RGR have two distinct generations. The older one has an estimated age of initiation around 48–55 Ma and was extensively affected by post-depositional processes under suboxic conditions resulting in phosphatization during the Miocene (from 20 to 6.8 Ma). As a result, the older generation shows characteristics of diagenetic Fe–Mn deposits, such as low Fe/Mn ratios (mean 0.52), high Mn, Ni, and Li contents and the presence of a 10 Å phyllomanganate, combined with the highest P content among crusts (up to 7.7 wt %). The younger generation is typical of hydrogenetic crusts formed under oxic conditions, with a mean Fe/Mn ratio of 0.75 and mean Co content of 0.66 wt %, and has the highest mean contents of Bi, Nb, Ni, Te, Rh, Ru, and Pt among crusts formed elsewhere. The regeneration of nutrients from local biological productivity in the water column is the main source of metals to crusts, providing mainly metals that regenerate rapidly in the water column and are made available at relatively shallow water depths (Ni, As, V, and Cd), at the expense of metals of slower regeneration (Si and Cu). Additionally, important contributions of nutrients may derive from various water masses, especially the South Atlantic Mode Water and Antarctic Intermediate Water (AAIW). Bulk Fe–Mn crusts from the summit of RGR plateau are generally depleted in metals considered of greatest economic interest in crusts like Co, REE, Mo, Te, and Zr, but are the most enriched in the critical metals Ni and Li compared to other crusts. Further investigations are warranted on Fe–Mn crusts from deeper-water depths along the RGR plateau and surrounding areas, which would less likely be affected by phosphatization.
","language":"English","publisher":"MDPI","doi":"10.3390/min10040349","usgsCitation":"Benites, M., Hein, J.R., Mizell, K., Blackburn, T., and Jovane, L., 2020, Genesis and evolution of ferromanganese crusts from the summit of Rio Grande Rise, southwest Atlantic Ocean: Minerals, v. 10, no. 4, 349, 36 p., https://doi.org/10.3390/min10040349.","productDescription":"349, 36 p.","ipdsId":"IP-117416","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":457096,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/min10040349","text":"Publisher Index Page"},{"id":386172,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Brazil","otherGeospatial":"Rio Grande Rise","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -42.5390625,\n -26.588527147308614\n ],\n [\n -31.552734374999996,\n -26.588527147308614\n ],\n [\n -31.552734374999996,\n -16.467694748288956\n ],\n [\n -42.5390625,\n -16.467694748288956\n ],\n [\n -42.5390625,\n -26.588527147308614\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"10","issue":"4","noUsgsAuthors":false,"publicationDate":"2020-04-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Benites, Mariana","contributorId":259240,"corporation":false,"usgs":false,"family":"Benites","given":"Mariana","email":"","affiliations":[{"id":48623,"text":"University of Sao Paulo","active":true,"usgs":false}],"preferred":false,"id":816881,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hein, James R. 0000-0002-5321-899X jhein@usgs.gov","orcid":"https://orcid.org/0000-0002-5321-899X","contributorId":140835,"corporation":false,"usgs":true,"family":"Hein","given":"James","email":"jhein@usgs.gov","middleInitial":"R.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":816882,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mizell, Kira 0000-0002-5066-787X kmizell@usgs.gov","orcid":"https://orcid.org/0000-0002-5066-787X","contributorId":4914,"corporation":false,"usgs":true,"family":"Mizell","given":"Kira","email":"kmizell@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":816883,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Blackburn, Terrence 0000-0003-0029-0709","orcid":"https://orcid.org/0000-0003-0029-0709","contributorId":259241,"corporation":false,"usgs":false,"family":"Blackburn","given":"Terrence","email":"","affiliations":[{"id":6949,"text":"University of California, Santa Cruz","active":true,"usgs":false}],"preferred":false,"id":816884,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jovane, Luigi 0000-0003-4348-4714","orcid":"https://orcid.org/0000-0003-4348-4714","contributorId":259243,"corporation":false,"usgs":false,"family":"Jovane","given":"Luigi","email":"","affiliations":[{"id":48623,"text":"University of Sao Paulo","active":true,"usgs":false}],"preferred":false,"id":816885,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ]}