Aquatic insects exhibit complex life cycles that include egg, larval, adult, and, in some instances, pupal stages. Disturbances at any of these life stages can affect overall population dynamics. Yet, efforts to understand the effects of disturbances, such as hydrologic alterations, overwhelmingly focus on the larval life stage of aquatic insects. We evaluated the potential for load-following flows associated with hydroelectric power production to act as a population bottleneck for aquatic insects via reductions in the availability and temporal persistence of optimal oviposition habitats. Specifically, we quantified the oviposition habitat selectivity of Baetis spp. (Baetidae), Brachycentrus occidentalis (Brachycentridae), Chironomidae (Diptera), and Hydropsyche occidentalis (Hydropsychidae) downstream of Flaming Gorge Dam, Utah, USA. We found that all taxa except H. occidentalis preferentially laid eggs on large emergent substrates located along the river edge. Peak discharge associated with load-following flows substantially reduced the number of emergent substrates available for oviposition, and daily low flows exposed eggs in these habitats to desiccation and drying. When subjected to experimental drying, both Baetis and H. occidentalis eggs experienced nearly 100% mortality after 2 h, whereas most B. occidentalis remained viable after 8 h. Our paired field and experimental results are consistent with the hypothesis that load-following flows from hydroelectric dams produce a population bottleneck for aquatic insects by short circuiting recruitment processes. Environmental flows that seek to improve the health of tailwater aquatic insect populations would benefit from consideration of habitat requirements for all life stages of aquatic insects.
","language":"English","publisher":"University of Chicago Press Journals","doi":"10.1086/710237","usgsCitation":"Miller, S.W., Schroer, M., Fleri, J.R., and Kennedy, T.A., 2020, Macroinvertebrate oviposition habitat selectivity and egg-mass desiccation tolerances: Implications for population dynamics in large regulated rivers: Freshwater Science, v. 39, no. 3, p. 584-599, https://doi.org/10.1086/710237.","productDescription":"16 p.","startPage":"584","endPage":"599","onlineOnly":"N","ipdsId":"IP-112469","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":455768,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1086/710237","text":"Publisher Index Page"},{"id":377107,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Utah","otherGeospatial":"Green River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -109.52407836914062,\n 40.84706035607122\n ],\n [\n -109.10659790039062,\n 40.84706035607122\n ],\n [\n -109.10659790039062,\n 40.93841495689795\n ],\n [\n -109.52407836914062,\n 40.93841495689795\n ],\n [\n -109.52407836914062,\n 40.84706035607122\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"39","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Miller, Scott W.","contributorId":237002,"corporation":false,"usgs":false,"family":"Miller","given":"Scott","email":"","middleInitial":"W.","affiliations":[{"id":6682,"text":"Utah State University","active":true,"usgs":false}],"preferred":false,"id":794962,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schroer, Matt","contributorId":237003,"corporation":false,"usgs":false,"family":"Schroer","given":"Matt","email":"","affiliations":[{"id":6682,"text":"Utah State University","active":true,"usgs":false}],"preferred":false,"id":794963,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fleri, Jesse R.","contributorId":237004,"corporation":false,"usgs":false,"family":"Fleri","given":"Jesse","email":"","middleInitial":"R.","affiliations":[{"id":6682,"text":"Utah State University","active":true,"usgs":false}],"preferred":false,"id":794964,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kennedy, Theodore A. 0000-0003-3477-3629 tkennedy@usgs.gov","orcid":"https://orcid.org/0000-0003-3477-3629","contributorId":167537,"corporation":false,"usgs":true,"family":"Kennedy","given":"Theodore","email":"tkennedy@usgs.gov","middleInitial":"A.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":794965,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70209146,"text":"fs20203020 - 2020 - Water resources of Evangeline Parish, Louisiana","interactions":[],"lastModifiedDate":"2020-08-04T20:20:14.724487","indexId":"fs20203020","displayToPublicDate":"2020-08-04T09:02:52","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2020-3020","displayTitle":"Water Resources of Evangeline Parish, Louisiana","title":"Water resources of Evangeline Parish, Louisiana","docAbstract":"Information concerning the availability, use, and quality of water in Evangeline Parish, Louisiana, is critical for proper water-supply management. The purpose of this fact sheet is to present information that can be used by water managers, parish residents, and others for stewardship of this vital resource. In 2014, about 282.66 million gallons per day (Mgal/d) of water were withdrawn in Evangeline Parish, including about 122.05 Mgal/d from groundwater sources and 160.61 Mgal/d from surface-water sources. Withdrawals for agricultural use, composed of aquaculture, general irrigation, livestock, and rice irrigation, accounted for 45 percent (126.86 Mgal/d) of the total water withdrawn. Withdrawals for power-generation use accounted for about 52 percent (146.33 Mgal/d) of the total water withdrawn. Other categories of use included public supply, industry, and rural domestic. Water-use data collected at 5-year intervals from 1960 to 2010 and again in 2014 indicated that water withdrawals peaked in 1980.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20203020","collaboration":"Prepared in cooperation with the Louisiana Department of Transportation and Development","usgsCitation":"Murphy, C.J., and White, V.E., 2020, Water resources of Evangeline Parish, Louisiana: U.S. Geological Survey Fact Sheet 2020–3020, 6 p., https://doi.org/10.3133/fs20203020.","productDescription":"Report: 6 p.; Data Release","numberOfPages":"6","onlineOnly":"N","ipdsId":"IP-103346","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":376884,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F78051VM","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Water withdrawals by source and category in Louisiana Parishes, 2014–2015"},{"id":376882,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2020/3020/coverthb.jpg"},{"id":376883,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2020/3020/fs20203020.pdf","text":"Report","size":"1.04 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2020–3020"}],"country":"United States","state":"Louisiana","county":"Evangeline Parish","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-92.2809,30.9653],[-92.2811,30.9365],[-92.2381,30.8924],[-92.2377,30.8486],[-92.2132,30.8487],[-92.2127,30.7948],[-92.2079,30.7889],[-92.2073,30.7848],[-92.1977,30.7798],[-92.1918,30.7785],[-92.187,30.7758],[-92.1816,30.7694],[-92.1774,30.7685],[-92.1694,30.7677],[-92.1729,30.6758],[-92.175,30.6762],[-92.1797,30.6661],[-92.1861,30.667],[-92.1887,30.6647],[-92.1945,30.6596],[-92.2009,30.6564],[-92.2008,30.6477],[-92.205,30.639],[-92.2034,30.6372],[-92.2055,30.6353],[-92.2044,30.6331],[-92.206,30.6299],[-92.2038,30.6257],[-92.2064,30.6216],[-92.2107,30.6198],[-92.2117,30.6129],[-92.2113,30.569],[-92.2622,30.5682],[-92.263,30.5385],[-92.2795,30.5388],[-92.4148,30.5405],[-92.4227,30.5386],[-92.4285,30.5363],[-92.4397,30.5362],[-92.4508,30.532],[-92.4592,30.5246],[-92.4622,30.5163],[-92.4659,30.5108],[-92.4637,30.5008],[-92.4657,30.4967],[-92.471,30.4939],[-92.4805,30.4924],[-92.4874,30.4878],[-92.4942,30.4818],[-92.6304,30.4827],[-92.6305,30.4859],[-92.6284,30.4896],[-92.6237,30.4929],[-92.6232,30.4974],[-92.618,30.5021],[-92.6165,30.5067],[-92.6176,30.5135],[-92.6246,30.5185],[-92.6241,30.5208],[-92.6162,30.5259],[-92.6051,30.531],[-92.6,30.5434],[-92.5958,30.5457],[-92.5948,30.5517],[-92.5932,30.5554],[-92.588,30.5559],[-92.5859,30.5618],[-92.5844,30.5683],[-92.5871,30.5719],[-92.5903,30.5732],[-92.593,30.5796],[-92.5979,30.5832],[-92.5986,30.8726],[-92.5989,30.8945],[-92.5658,30.8948],[-92.5605,30.899],[-92.5537,30.9031],[-92.5484,30.9032],[-92.5451,30.9009],[-92.5366,30.8978],[-92.5275,30.8997],[-92.5253,30.8943],[-92.5142,30.8953],[-92.4961,30.9037],[-92.484,30.9138],[-92.4798,30.9226],[-92.4861,30.9536],[-92.484,30.9559],[-92.4728,30.9587],[-92.4664,30.9574],[-92.4568,30.9589],[-92.451,30.9626],[-92.4404,30.9686],[-92.4271,30.9733],[-92.4154,30.9788],[-92.4123,30.9853],[-92.405,30.994],[-92.3948,30.9968],[-92.3869,31.0033],[-92.3784,31.0029],[-92.3746,30.9974],[-92.3676,30.9916],[-92.3606,30.9925],[-92.3601,30.9898],[-92.3611,30.988],[-92.3579,30.9848],[-92.3419,30.9817],[-92.3408,30.9794],[-92.3418,30.9758],[-92.345,30.9739],[-92.3439,30.9703],[-92.3316,30.9736],[-92.3252,30.9704],[-92.331,30.9635],[-92.3171,30.9636],[-92.315,30.9655],[-92.2809,30.9653]]]},\"properties\":{\"name\":\"Evangeline\",\"state\":\"LA\"}}]}","contact":"Director, Lower Mississippi-Gulf Water Science Center
U.S. Geological Survey
3535 S. Sherwood Forest Blvd., Suite 120
Baton Rouge, LA 70816
Information concerning the availability, use, and quality of water in Avoyelles Parish, Louisiana, is critical for proper water-supply management. The purpose of this fact sheet is to present information that can be used by water managers, parish residents, and others for stewardship of this vital resource. In 2014, about 70 million gallons per day (Mgal/d) of water were withdrawn in Avoyelles Parish, including about 59.27 Mgal/d from groundwater sources and 10.95 Mgal/d from surface-water sources. Withdrawals for agricultural use—composed of aquaculture, general irrigation, livestock, and rice irrigation—accounted for 93 percent (65.59 Mgal/d) of the total water withdrawn. Other categories of use included public supply and rural domestic. Water-use data collected at 5-year intervals from 1960 to 2010 and again in 2014 indicated that water withdrawals peaked in 2014.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20203011","collaboration":"Prepared in cooperation with the Louisiana Department of Transportation and Development","usgsCitation":"White, V.E., 2020, Water resources of Avoyelles Parish, Louisiana: U.S. Geological Survey Fact Sheet 2020–3011, 6 p., https://doi.org/10.3133/fs20203011.","productDescription":"Report: 6 p.; Data Release","numberOfPages":"6","onlineOnly":"N","ipdsId":"IP-102165","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":376881,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F78051VM","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Water withdrawals by source and category in Louisiana Parishes, 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Lower Mississippi-Gulf Water Science Center
U.S. Geological Survey
3535 S. Sherwood Forest Blvd., Suite 120
Baton Rouge, LA 70816
Passive acoustic monitoring using autonomous recording units (ARUs) is a fast-growing area of wildlife research especially for rare, cryptic species that vocalize. Northern Spotted Owl (Strix occidentalis caurina) populations have been monitored since the mid-1980s using mark–recapture methods. To evaluate an alternative survey method, we used ARUs to detect calls of Northern Spotted Owls and Barred Owls (S. varia), a congener that has expanded its range into the Pacific Northwest and threatens Northern Spotted Owl persistence. We set ARUs at 30 500-ha hexagons (150 ARU stations) with recent Northern Spotted Owl activity and high Barred Owl density within Northern Spotted Owl demographic study areas in Oregon and Washington, and set ARUs to record continuously each night from March to July, 2017. We reviewed spectrograms (visual representations of sound) and tagged target vocalizations to extract calls from ~160,000 hr of recordings. Even in a study area with low occupancy rates on historical territories (Washington’s Olympic Peninsula), the probability of detecting a Northern Spotted Owl when it was present in a hexagon exceeded 0.95 after 3 weeks of recording. Environmental noise, mainly from rain, wind, and streams, decreased detection probabilities for both species over all study areas. Using demographic information about known Northern Spotted Owls, we found that weekly detection probabilities of Northern Spotted Owls were higher when ARUs were closer to known nests and activity centers and when owls were paired, suggesting passive acoustic data alone could help locate Northern Spotted Owl pairs on the landscape. These results demonstrate that ARUs can effectively detect Northern Spotted Owls when they are present, even in a landscape with high Barred Owl density, thereby facilitating the use of passive, occupancy-based study designs to monitor Northern Spotted Owl populations.
","language":"English","publisher":"Oxford Academic","doi":"10.1093/condor/duaa017","usgsCitation":"Duchac, L.S., Lesmeister, D., Dugger, K.M., Ruff, Z.J., and Davis, R.J., 2020, Passive acoustic monitoring effectively detects Northern Spotted Owls and Barred Owls over a range of forest conditions: Condor, v. 122, no. 3, duaa017, 22 p., https://doi.org/10.1093/condor/duaa017.","productDescription":"duaa017, 22 p.","ipdsId":"IP-113895","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":455771,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/condor/duaa017","text":"Publisher Index Page"},{"id":396168,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon, Washington","otherGeospatial":"Klamath Mountains, Olympic Peninsula, Oregon Coast Range","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124.51904296875,\n 47.24194882163242\n ],\n [\n -122.838134765625,\n 47.24194882163242\n ],\n [\n -122.838134765625,\n 48.23199134320962\n ],\n [\n -124.51904296875,\n 48.23199134320962\n ],\n [\n -124.51904296875,\n 47.24194882163242\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124.12353515624999,\n 43.731414013769\n ],\n [\n -123.321533203125,\n 43.731414013769\n ],\n [\n -123.321533203125,\n 44.6061127451739\n ],\n [\n -124.12353515624999,\n 44.6061127451739\n ],\n [\n -124.12353515624999,\n 43.731414013769\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.64013671874999,\n 42.415346114253616\n ],\n [\n -122.64038085937499,\n 42.415346114253616\n ],\n [\n -122.64038085937499,\n 43.004647127794435\n ],\n [\n -123.64013671874999,\n 43.004647127794435\n ],\n [\n -123.64013671874999,\n 42.415346114253616\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"122","issue":"3","noUsgsAuthors":false,"publicationDate":"2020-04-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Duchac, Leila S.","contributorId":279674,"corporation":false,"usgs":false,"family":"Duchac","given":"Leila","email":"","middleInitial":"S.","affiliations":[{"id":7134,"text":"USFS","active":true,"usgs":false}],"preferred":false,"id":835345,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lesmeister, Damon B.","contributorId":279675,"corporation":false,"usgs":false,"family":"Lesmeister","given":"Damon B.","affiliations":[{"id":7134,"text":"USFS","active":true,"usgs":false}],"preferred":false,"id":835346,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dugger, Katie M. 0000-0002-4148-246X","orcid":"https://orcid.org/0000-0002-4148-246X","contributorId":36037,"corporation":false,"usgs":true,"family":"Dugger","given":"Katie","email":"","middleInitial":"M.","affiliations":[{"id":517,"text":"Oregon Cooperative Fish and Wildlife Research Unit","active":false,"usgs":true}],"preferred":false,"id":835344,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ruff, Zachary J.","contributorId":279676,"corporation":false,"usgs":false,"family":"Ruff","given":"Zachary","email":"","middleInitial":"J.","affiliations":[{"id":7134,"text":"USFS","active":true,"usgs":false}],"preferred":false,"id":835347,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Davis, Raymond J.","contributorId":279677,"corporation":false,"usgs":false,"family":"Davis","given":"Raymond","email":"","middleInitial":"J.","affiliations":[{"id":7134,"text":"USFS","active":true,"usgs":false}],"preferred":false,"id":835348,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70211424,"text":"ofr20201073 - 2020 - Ecological forecasting—21st century science for 21st century management","interactions":[],"lastModifiedDate":"2024-03-04T18:30:12.945694","indexId":"ofr20201073","displayToPublicDate":"2020-08-04T07:20:00","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":"2020-1073","displayTitle":"Ecological Forecasting—21st Century Science for 21st Century Management","title":"Ecological forecasting—21st century science for 21st century management","docAbstract":"Natural resource managers are coping with rapid changes in both environmental conditions and ecosystems. Enabled by recent advances in data collection and assimilation, short-term ecological forecasting may be a powerful tool to help resource managers anticipate impending near-term changes in ecosystem conditions or dynamics. Managers may use the information in forecasts to minimize the adverse effects of ecological stressors and optimize the effectiveness of management actions. To explore the potential for ecological forecasting to enhance natural resource management, the U.S. Geological Survey (USGS) convened a workshop titled \"Building Capacity for Applied Short-Term Ecological Forecasting\" on May 29—31, 2019, with participants from several Federal agencies, including the Bureau of Land Management, the U.S. Fish and Wildlife Service, the National Park Service, and the National Oceanic and Atmospheric Administration as well as all mission areas within the USGS.
Participants broadly agreed that short-term ecological forecasting—on the order of days to years into the future—has tremendous potential to improve the quality and timeliness of information available to guide resource management decisions. Participants considered how ecological forecasting could directly affect their agency missions and specified numerous critical tools for addressing natural resource management concerns in the 21st century that could be enhanced by ecological forecasting. Given this breadth of possible applications for forecast products, participants developed a repeatable framework for evaluating potential value of a forecast product for enhancing resource management. Applying that process to a large list of forecast ideas that were developed in a brainstorming session, participants identified a small set of promising forecast products that illustrate the value of ecological forecasting for informing resource management. Workshop outcomes also include insights about important likely obstacles and next steps. In particular, reliable production and delivery of operational ecological forecasts will require a sustained commitment by research agencies, in partnership with resource management agencies, to maintain and improve forecasting tools and capabilities.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201073","usgsCitation":"Bradford, J.B., Weltzin, J.F., McCormick, M., Baron, J., Bowen, Z., Bristol, S., Carlisle, D., Crimmins, T., Cross, P., DeVivo, J., Dietze, M., Freeman, M., Goldberg, J., Hooten, M., Hsu, L., Jenni, K., Keisman, J., Kennen, J., Lee, K., Lesmes, D., Loftin, K., Miller, B.W., Murdoch, P., Newman, J., Prentice, K.L., Rangwala, I., Read, J., Sieracki, J., Sofaer, H., Thur, S., Toevs, G., Werner, F., White, C.L., White, T., and Wiltermuth, M., 2020, Ecological forecasting—21st century science for 21st century management: U.S. Geological Survey Open-File Report 2020–1073, 54 p., https://doi.org/10.3133/ofr20201073.","productDescription":"vii, 54 p.","numberOfPages":"54","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-114740","costCenters":[{"id":208,"text":"Core Science Analytics and Synthesis","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true},{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true},{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true},{"id":433,"text":"National Phenology Network","active":true,"usgs":true},{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true},{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true},{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true},{"id":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":376787,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1073/ofr20201073.pdf","text":"Report","size":"598 KB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020-1073"},{"id":376786,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1073/coverthb.jpg"}],"contact":"Director, Southwest Biological Science Center
U.S. Geological Survey
2255 N. Gemini Drive
Flagstaff, AZ 86001
The accurate mapping of streams and their streamflow conditions in terms of presence or absence of surface water is important to both understanding physical, chemical, and biological processes in streams and to managing land, water, and ecological resources. This document describes a field form, FLOwPER (FLOw PERmanence), available within a mobile application (app), for standardized data collection of the presence or absence of surface flow in streams. The FLOwPER Database is a publicly available geodataset that can be used for research and management applications. This document provides instructions on how to (1) access and download the FLOwPER field form within the mobile app service, (2) use and complete a FLOwPER field form, and (3) view and download data from the FLOwPER Database.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201075","collaboration":"Prepared in cooperation with the United States Forest Service and the Bureau of Land Management","usgsCitation":"Jaeger, K.L., Burnett, J., Heaston, E.D., Wondzell, S.M., Chelgren, N., Dunham, J.B., Johnson, S., and Brown, M., 2020, FLOwPER user guide—For collection of FLOw PERmanence field observations: U.S. Geological Survey Open-File Report 2020–1075, 40 p., https://doi.org/10.3133/ofr20201075.","productDescription":"Report: vi, 40 p.; Appendix","onlineOnly":"Y","ipdsId":"IP-118616","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":436839,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P13WFKYW","text":"USGS data release","linkHelpText":"FLOwPER Database: StreamFLOw PERmanence field observations, Jan 2021 - Dec 2021"},{"id":407336,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://www.sciencebase.gov/catalog/item/5edea67582ce7e579c6e5845","text":"USGS data release","description":"USGS data release","linkHelpText":"FLOwPER Database: StreamFLOw PERmanence Field Observations"},{"id":376985,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1075/coverthb.jpg"},{"id":377862,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2020/1075/ofr20201075_appendix01.pdf","text":"Appendix 1","size":"507 KB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020-1075 Appendix 1"},{"id":376986,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1075/ofr20201075.pdf","text":"Report","size":"5.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020-1075"}],"contact":"Director, Washington Water Science Center
U.S. Geological Survey
934 Broadway, Suite 300
Tacoma, Washington 98402
The Midcontinent Rift System (MRS) of North America is one of the world’s largest continental rifts and has an age of 1.1 Ga (giga-annum). The MRS hosts a diverse suite of magmatic and hydrothermal mineral deposits in the Lake Superior region where rift rocks are exposed at or near the surface. As part of the construction of a database summarizing information on mineral deposits in the MRS, data from regional mineral deposits were downloaded from the U.S. Geological Survey (USGS) Mineral Resources Data System (MRDS), the USGS Mineral Deposit Database (USMIN), and the Ontario Ministry of Energy, Northern Development and Mines Mineral Deposit Inventory (MDI). Deposits related to MRS rocks or mineralizing events were identified and compiled into a database to develop a space/time classification for MRS-related mineral deposits. Information from MRDS, USMIN, and MDI records and from the extensive literature describing MRS mineral deposits was used to classify each entry by deposit type, host rock age and type, and estimated mineralization age. Most deposits were readily classified because of unique mineralogy, location, or well-constrained host rock. These deposits were then put into a tectonic evolutionary framework for the MRS, which showed that many deposits formed within discrete spatial and temporal stages of rift evolution.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201069","usgsCitation":"Woodruff, L.G., Schulz, K.J., Dicken, C.L., and Nicholson, S.W., 2020, Mineral resource database for deposits related to the Mesoproterozoic Midcontinent Rift System, United States and Canada: U.S. Geological Survey Open-File Report 2020–1069, 20 p., https://doi.org/10.3133/ofr20201069.","productDescription":"Report: vi, 20 p.; 2 Tables","numberOfPages":"20","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-113694","costCenters":[{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true}],"links":[{"id":436840,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9HTATKY","text":"USGS data release","linkHelpText":"Database of mineral deposits related to the Mesoproterozoic Midcontinent Rift System (MRS) in the northern United States and northern Ontario, Canada"},{"id":376912,"rank":4,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/of/2020/1069/ofr20201069_table1.csv","text":"Table 1","size":"171 KB","linkFileType":{"id":7,"text":"csv"},"linkHelpText":"- Database of mineral deposits related to the Mesoproterozoic Midcontinent Rift System (MRS) in the northern United States and northern Ontario, Canada"},{"id":376911,"rank":3,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/of/2020/1069/ofr20201069_table1.xlsx","text":"Table 1","size":"124 KB","linkFileType":{"id":3,"text":"xlsx"},"linkHelpText":"- Database of mineral deposits related to the Mesoproterozoic Midcontinent Rift System (MRS) in the northern United States and northern Ontario, Canada"},{"id":376909,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1069/coverthb.jpg"},{"id":376910,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1069/ofr20201069.pdf","text":"Report","size":"13.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020-1069"}],"country":"United States, Canada","otherGeospatial":"Mesoproterozoic Midcontinent Rift System","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -82.2216796875,\n 40.245991504199026\n ],\n [\n -81.8701171875,\n 50.792047064406866\n ],\n [\n -96.6357421875,\n 51.23440735163459\n ],\n [\n -96.1083984375,\n 43.45291889355465\n ],\n [\n -97.5146484375,\n 43.739352079154706\n ],\n [\n -97.55859375,\n 41.541477666790286\n ],\n [\n -99.931640625,\n 41.376808565702355\n ],\n [\n -100.1513671875,\n 37.16031654673677\n ],\n [\n -94.7021484375,\n 37.09023980307208\n ],\n [\n -94.833984375,\n 39.53793974517628\n ],\n [\n -82.2216796875,\n 40.245991504199026\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Coordinator, Mineral Resources Program
U.S. Geological Survey
913 National Center
Reston, VA 20192
Impacts of land use, specifically soil disturbance, are linked to reductions of soil organic carbon (SOC) stocks. Correspondingly, ecosystem restoration is promoted to sequester SOC to mitigate anthropogenic greenhouse gas emissions, which are exacerbating global climate change. Restored wetlands have relatively high potential to sequester carbon compared to other ecosystems, but SOC accumulation rates are variable, which leads to high uncertainty in sequestration rates. To assess soil properties and carbon sequestration rates of freshwater mineral soil wetlands, we analyzed an extensive database of SOC concentrations from the Prairie Pothole Region (549 wetlands over 160,000 km2), which is considered one of the largest wetland ecosystems in North America. We demonstrate that SOC of wetland catchments varies among inner, transition, toe slope, and upland landscape positions (LSPs), as well as among land uses and soil depth segments. Soil organic carbon concentrations were greatest in the inner portion of the catchment (66 Mg ha−1) and progressively decrease towards the upland LSP (43 Mg ha−1). We also conducted a regional extrapolation based on LSP- and land-use-specific SOC stocks, and estimated that wetland and upland areas of PPR wetland catchments contain 141 and 178 Tg of SOC in the upper 15 cm of the soil profile, respectively. Regressing SOC by restoration age (years restored) showed that sequestration rates, which differ by LSP and depth, ranged from 0.35 to 1.10 Mg ha−1 year−1. Using these SOC sequestration rates, along with data from natural and cropland reference sites, we estimated that it takes 20 to 64 years for SOC levels of restored wetlands to return to natural reference conditions, depending on LSP and depth segment. Accounting for LSP reduces uncertainty and should refine future assessments of the greenhouse gas mitigation potential from wetland restoration.
Globally accelerating frequency and extent of wildfire threatens the persistence of specialist wildlife species through direct loss of habitat and indirect facilitation of exotic invasive species. Habitat specialists may be especially prone to rapidly changing environmental conditions because their ability to adapt lags behind the rate of habitat alteration. As a result, these populations may become increasingly susceptible to ecological traps by returning to suboptimal breeding habitats that were dramatically altered by disturbance. We demonstrate a multistage modeling approach that integrates habitat selection and survival during the key nesting life‐stage of a bird species of high conservation concern, the greater sage‐grouse (Centrocercus urophasianus; hereafter, sage‐grouse). We applied these spatially explicit models to a spatiotemporally robust dataset of sage‐grouse nest locations and fates across wildfire‐altered sagebrush ecosystems of the Great Basin ecoregion, western United States. Female sage‐grouse exhibited intricate habitat selection patterns that varied across regional gradients of ecological productivity among sagebrush communities, but often selected nest sites that disproportionately resulted in nest failure. For example, 23% of nests occurred in wildfire‐affected habitats characterized by reduced sagebrush cover and greater composition of invasive annual grasses. We found survival of nests was negatively associated with wildfire‐affected areas, but positively associated with higher elevations with increased ruggedness and overall shrub cover. Strong site fidelity likely drove sage‐grouse to continue nesting in habitats degraded by wildfire. Hence, increasing frequency and extent of wildfire may contribute disproportionately to reduced reproductive success by creating ecological traps that act as population sinks. Identifying such habitat mismatches between selection and survival facilitates deeper understanding of the mechanisms driving reduced geographic niche space and population decline at broad spatiotemporal scales, while guiding management actions to areas that would be most beneficial to the species.
The St. Marys River connects Lake Superior to Lake Huron, comprising the international border between Michigan, United States, and Ontario, Canada. This Great Lakes connecting channel naturally encompasses various habitats including lakes, wetlands, islands, tributaries, side channels, and main channels. The St. Marys River Rapids are shallow rock areas with high flow velocities (>1 m/s) in the upper river adjacent to the navigation locks and electric power generating stations, while the Little Rapids are shallow, recently restored rocky areas with lower velocities located about 7 km downstream. The St. Marys River Rapids provide important spawning habitat for several native and introduced fishes, but spawning by lake sturgeon (Acipenser fulvescens) was not previously documented. We sampled for lake sturgeon eggs and larvae in both locations during June and July 2018–2019 using weekly benthic egg mat lifts and overnight D-frame larval fish drift nets. Viable lake sturgeon eggs (11 in 2018, 45 in 2019) were collected in the tailrace of a hydroelectric power facility adjacent to the St. Marys River Rapids. Larval lake sturgeon (21 in 2018, 1 in 2019) were collected in the same area as the eggs. Neither lake sturgeon eggs nor larvae were collected at Little Rapids in either year. Our results are the first documentation of successful lake sturgeon spawning and larval drift in the upper St. Marys River. While our observations showed spawning in a human-made tailrace area, the fate of larvae produced here is unknown and warrants further research.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jglr.2020.07.005","usgsCitation":"Roseman, E., Adams, E.J., DeBruyne, R.L., Gostiaux, J., Harrington, H., Kapuscinski, K., Moerke, A., and Olds, C., 2020, Lake sturgeon (Acipenser fulvescens) spawn in the St. Marys River Rapids, Michigan: Journal of Great Lakes Research, v. 46, no. 5, p. 1479-1484, https://doi.org/10.1016/j.jglr.2020.07.005.","productDescription":"6 p.","startPage":"1479","endPage":"1484","ipdsId":"IP-115133","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":436842,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9VJMIPO","text":"USGS data release","linkHelpText":"Fish eggs collected in the St. Clair, Detroit, and St. Marys rivers, 2005-2018"},{"id":382461,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","state":"Michigan, Ontario","otherGeospatial":"St. Marys River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -84.49722290039062,\n 46.44069599413034\n ],\n [\n -84.1827392578125,\n 46.44069599413034\n ],\n [\n -84.1827392578125,\n 46.54091587805394\n ],\n [\n -84.49722290039062,\n 46.54091587805394\n ],\n [\n -84.49722290039062,\n 46.44069599413034\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"46","issue":"5","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Roseman, Edward F. 0000-0002-5315-9838","orcid":"https://orcid.org/0000-0002-5315-9838","contributorId":217909,"corporation":false,"usgs":true,"family":"Roseman","given":"Edward F.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":808630,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Adams, Eric John 0000-0001-9695-9483","orcid":"https://orcid.org/0000-0001-9695-9483","contributorId":248219,"corporation":false,"usgs":true,"family":"Adams","given":"Eric","email":"","middleInitial":"John","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":808631,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"DeBruyne, Robin L. 0000-0002-9232-7937 rdebruyne@usgs.gov","orcid":"https://orcid.org/0000-0002-9232-7937","contributorId":4936,"corporation":false,"usgs":true,"family":"DeBruyne","given":"Robin","email":"rdebruyne@usgs.gov","middleInitial":"L.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":808632,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gostiaux, J.","contributorId":248221,"corporation":false,"usgs":false,"family":"Gostiaux","given":"J.","affiliations":[{"id":6983,"text":"Michigan DNR","active":true,"usgs":false}],"preferred":false,"id":808633,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Harrington, H.","contributorId":248222,"corporation":false,"usgs":false,"family":"Harrington","given":"H.","email":"","affiliations":[{"id":13502,"text":"US Army Corps of Engineers","active":true,"usgs":false}],"preferred":false,"id":808634,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kapuscinski, K.","contributorId":247567,"corporation":false,"usgs":false,"family":"Kapuscinski","given":"K.","email":"","affiliations":[{"id":49581,"text":"Lake Superior State Univ.","active":true,"usgs":false}],"preferred":false,"id":808635,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Moerke, A.","contributorId":247569,"corporation":false,"usgs":false,"family":"Moerke","given":"A.","affiliations":[{"id":49581,"text":"Lake Superior State Univ.","active":true,"usgs":false}],"preferred":false,"id":808636,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Olds, C.","contributorId":248227,"corporation":false,"usgs":false,"family":"Olds","given":"C.","email":"","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":808637,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70212762,"text":"70212762 - 2020 - Procedures for developing multi-period response spectra at non-conterminous United States sites","interactions":[],"lastModifiedDate":"2021-01-22T18:10:01.008346","indexId":"70212762","displayToPublicDate":"2020-08-01T11:57:53","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"seriesNumber":"P-2078","title":"Procedures for developing multi-period response spectra at non-conterminous United States sites","docAbstract":"This study complements proposals to the Provisions Update Committee of the Building Seismic Safety Council that would incorporate multi-period response spectra (MPRS) in the 2020 edition of the NEHRP Recommended Seismic Provisions for New Buildings and Other Structures (2020 NEHRP Provisions) and related proposals to the ASCE 7-22 Seismic Subcommittee of the American Society of Civil Engineers for incorporation of MPRS in ASCE Standard, ASCE/SEI 7-22, Minimum Design Loads and Associated Criteria for Buildings and Other Structures (ASCE 7-22). Ultimately, the intent is that the proposed MPRS and related design requirements of ASCE 7-22 would be adopted, by reference, as part of the 2024 International Building Code.
The technical basis and associated methods herein enable the U.S. Geological Survey (USGS) to develop MPRS for sites in non-conterminous U.S. regions for which seismic hazard analyses have not yet been updated by the USGS to fully define all 22 periods and eight site classes of interest in the MPRS related proposals for the 2020 NEHRP Provisions and ASCE 7-22. These regions include Alaska, Hawaii, Guam and the Northern Mariana Islands, Puerto Rico and the U.S. Virgin Islands, and American Samoa.
The methods developed can be used to derive MPRS using only the three currently available ground motion parameters SS, S1, and TL for all nonconterminous United States regions of interest. The methods include models that characterize generic shapes of Risk-Targeted Maximum Considered Earthquake (MCER) ground motions as a function of these three parameters. For deriving MPRS that represent probabilistic MCER ground motions, models are based on statistical analyses of large sample sets of probabilistic MCER response spectra for Western United States (WUS) and Cascadia sites in California, Oregon, Washington (including Puget Sound), Idaho, and Nevada. For deriving MPRS that represent deterministic MCER ground motions, models are based on sets of deterministic MCER response spectra calculated using WUS shallow crustal ground motion models for earthquake magnitudes and shaking levels typical of sites governed by deterministic
MCER ground motions.
Temporal and spatial distribution of niclosamide in the water column and sediment were evaluated after the application of granular Bayluscide in six lentic sea lamprey (Petromyzon marinus) larval assessment plots. Water and sediment were collected 0.25, 1, 3, 5, and 7 hours after application and were analyzed for niclosamide, the active ingredient in granular Bayluscide. Water samples were collected from five heights in the water column (1 cm, 13 cm, 26 cm, 1/2 water column, and water surface) at five locations inside and four locations 10 m outside of each assessment plot. Sediment was collected from 18 locations within each plot. Niclosamide water concentrations inside and outside of the plots did not vary by depth but did vary between plots and by time. Niclosamide water concentrations also varied by sampler location outside of the plots. Following granular Bayluscide applications the mean niclosamide concentration in water for all levels, within the plots, decreased from 0.12 mgL-1 (SD = 0.12 mgL-1) at 15 minutes to 0.061 mgL-1 (SD = 0.040 mgL-1) at hour 1. The mean niclosamide concentration in the top 4 cm of sediment was 2.9 mgkg-1 (SD = 2.4 mgkg-1) 15 minutes after application and was 1.3 mgkg-1 (SD = 1.8 mgkg-1) at hour 7. Concentrations in all sediment samples ranged from < 0.001 to 30.730 mgkg-1 and varied between the six plots. Niclosamide concentrations measured in sediment samples were more than 1 order of magnitude greater than in the water and varied spatially by over 4 orders of magnitude.
","language":"English","publisher":"Great Lakes Fishery Commission","usgsCitation":"Bernardy, J., Kaye, C., Schloesser, N., and Schueller, J., 2020, Distribution of niclosamide following granular Bayer applications in lentic environments: Project Completion Report, 30 p.","productDescription":"30 p.","ipdsId":"IP-107424","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":399095,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":377968,"type":{"id":15,"text":"Index Page"},"url":"https://www.glfc.org/"}],"country":"United States","state":"Michigan, Wisconsin","county":"Mackinac County, Marinette County","otherGeospatial":"Hog Island Creek, Lake Michigan, Peshtigo Harbor","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -87.66952514648438,\n 44.96832008904543\n ],\n [\n -87.64514923095703,\n 44.96832008904543\n ],\n [\n -87.64514923095703,\n 44.98568481264677\n ],\n [\n -87.66952514648438,\n 44.98568481264677\n ],\n [\n -87.66952514648438,\n 44.96832008904543\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -85.28724074363708,\n 46.07139217240364\n ],\n [\n -85.28464436531067,\n 46.07139217240364\n ],\n [\n -85.28464436531067,\n 46.07282125858186\n ],\n [\n -85.28724074363708,\n 46.07282125858186\n ],\n [\n -85.28724074363708,\n 46.07139217240364\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Bernardy, Jeffry 0000-0001-7443-1995","orcid":"https://orcid.org/0000-0001-7443-1995","contributorId":213528,"corporation":false,"usgs":true,"family":"Bernardy","given":"Jeffry","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":797469,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kaye, Cheryl","contributorId":167292,"corporation":false,"usgs":false,"family":"Kaye","given":"Cheryl","affiliations":[{"id":6599,"text":"U.S. Fish and Wildlife Service, Marquette Biological Station","active":true,"usgs":false}],"preferred":false,"id":797470,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schloesser, Nicholas 0000-0002-3815-5302","orcid":"https://orcid.org/0000-0002-3815-5302","contributorId":237025,"corporation":false,"usgs":true,"family":"Schloesser","given":"Nicholas","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":797471,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schueller, Justin R. 0000-0002-7102-3889","orcid":"https://orcid.org/0000-0002-7102-3889","contributorId":213527,"corporation":false,"usgs":true,"family":"Schueller","given":"Justin","middleInitial":"R.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":797472,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70228560,"text":"70228560 - 2020 - Spatiotemporal variation in occurrence and co-occurrence of pesticides, hormones, and other organic contaminants in rivers in the Chesapeake Bay Watershed, United States","interactions":[],"lastModifiedDate":"2022-02-15T12:22:36.066283","indexId":"70228560","displayToPublicDate":"2020-08-01T09:59:30","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":"Spatiotemporal variation in occurrence and co-occurrence of pesticides, hormones, and other organic contaminants in rivers in the Chesapeake Bay Watershed, United States","docAbstract":"Investigating the spatiotemporal dynamics of contaminants in surface water is crucial to better understand how introduced chemicals are interacting with and potentially influencing aquatic organisms and environments. Within the Chesapeake Bay Watershed, USA, there are concerns about the potential role of contaminant exposure on fish health. Evidence suggests that exposure to contaminants in surface water is causing immunosuppression and intersex in freshwater fish species. Despite these concerns, there is a paucity of information regarding the complex dynamics of contaminant occurrence and co-occurrence in surface water across both space and time. To address these concerns, we applied a Bayesian hierarchical joint-contaminant model to describe the occurrence and co-occurrence patterns of 28 contaminants and total estrogenicity across six river sites and over three years. We found that seasonal occurrence patterns varied by contaminant, with the highest occurrence probabilities during the spring and summer months. Additionally, we found that the proportion of agricultural landcover in the immediate catchment, as well as stream discharge, did not have a significant effect on the occurrence probabilities of most compounds. Four pesticides (atrazine, metolachlor, fipronil and simazine) co-occurred across sites after accounting for environmental covariates. These results provide baseline information on the contaminant occurrence patterns of several classes of compounds within the Chesapeake Bay Watershed. Understanding the spatiotemporal dynamics of contaminants in surface water is the first step in investigating the effects of contaminant exposure on fisheries and aquatic environments.","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2020.138765","usgsCitation":"McClure, C.M., Smalling, K., Blazer, V.S., Sperry, A., Schall, M.K., Kolpin, D., Phillips, P.J., Hladik, M.L., and Wagner, T., 2020, Spatiotemporal variation in occurrence and co-occurrence of pesticides, hormones, and other organic contaminants in rivers in the Chesapeake Bay Watershed, United States: Science of the Total Environment, v. 728, p. 1-13, https://doi.org/10.1016/j.scitotenv.2020.138765.","productDescription":"138765, 13 p.","startPage":"1","endPage":"13","ipdsId":"IP-117478","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true},{"id":365,"text":"Leetown Science 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snapping turtles in southwest Louisiana","interactions":[],"lastModifiedDate":"2021-03-05T21:31:13.265943","indexId":"70213082","displayToPublicDate":"2020-08-01T09:37:20","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2287,"text":"Journal of Fish and Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"A trapping survey targeting head-started alligator snapping turtles in southwest Louisiana","docAbstract":"The alligator snapping turtle Macrochelys temminckii is the largest freshwater turtle in North America and is sought after as a food source, primarily in Louisiana. Decades of intensive commercial harvest of alligator snapping turtles has been implicated in population declines. The Louisiana Department of Wildlife and Fisheries initiated a head-start program for alligator snapping turtles and released 53 head-started juveniles at seven sites along an approximately 5.7-km stretch of Bundick Creek in southwest Louisiana between November 2015 and October 2016. Before release, all alligator snapping turtles were measured, weighed, and marked with both an internal passive integrated transponder tag and a numbered external tag. In 2018, the U.S. Geological Survey initiated a turtle trapping survey at those seven release sites targeting the head-started alligator snapping turtles. In one week of trapping effort at each site, we recorded 69 turtle captures comprising seven species, including 15 alligator snapping turtles (representing 12 individuals). Of those 12 individuals, 8 were head-started juveniles and 4 were native to the creek. An additional head-started juvenile alligator snapping turtle was captured by a landowner during our trapping and measurements were taken before release. A minimum of 17% of head-started alligator snapping turtles survived since release, and most captured head-started individuals were trapped near their release site and exhibited growth consistent with other studies, indicating acclimatization to their new environment. Three head-started alligator snapping turtles had their external tags entangled in the net mesh, and two of these turtles drowned. An additional two head-started individuals lost their external tags in the natural environment prior to their capture in this study. The use of external tags was discontinued by the Louisiana Department of Wildlife and Fisheries based on our findings, as they were detrimental to the health of head-started turtles.
","language":"English","publisher":"Allen Press","doi":"10.3996/JFWM-20-009","usgsCitation":"Glorioso, B., Muse, L.J., Hillard, C.J., Maldonado, B.R., Streeter, J., Battaglia, C.D., and Waddle, J.H., 2020, A trapping survey targeting head-started alligator snapping turtles in southwest Louisiana: Journal of Fish and Wildlife Management, v. 11, no. 2, p. 572-582, https://doi.org/10.3996/JFWM-20-009.","productDescription":"11 p.","startPage":"572","endPage":"582","ipdsId":"IP-108013","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":455791,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3996/jfwm-20-009","text":"Publisher Index Page"},{"id":436844,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9G9BR1D","text":"USGS data release","linkHelpText":"Data from a turtle trapping effort at a release site of head-started alligator snapping turtles, 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Its evolution through time is commonly reconstructed using the oxygen isotope and the clumped isotope compositions of carbonate archives. However, reaction kinetics involved in the precipitation of carbonates can introduce inaccuracies in the derived temperatures. Here, we show that dual clumped isotope analyses, i.e., simultaneous Δ47 and Δ48 measurements on the single carbonate phase, can identify the origin and quantify the extent of these kinetic biases. Our results verify theoretical predictions and evidence that the isotopic disequilibrium commonly observed in speleothems and scleractinian coral skeletons is inherited from the dissolved inorganic carbon pool of their parent solutions. Further, we show that dual clumped isotope thermometry can achieve reliable palaeotemperature reconstructions, devoid of kinetic bias. Analysis of a belemnite rostrum implies that it precipitated near isotopic equilibrium and confirms the warmer-than-present temperatures during the Early Cretaceous at southern high latitudes.
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These changes started in 2005, when disease was documented in young-of-the-year (age-0) Smallmouth Bass. Shortly thereafter, declines in abundance of both juveniles and adults were observed. These declines in abundance coincided with disease infections in age-0, intersex in adults, and concerns regarding contaminant exposure. Natural mortality rates, particularly for age-0, increased during this period (2005–2011), and there were concerns for the overall health of this world-class fishery. However, in recent years (2012–2017), there have been decreases in both mortality rates and external observations of disease and increases in abundance across multiple size-classes. Recent changes are encouraging for the future of the Smallmouth Bass fishery in the Susquehanna River. Yet, in light of the ever changing environmental, social, and anthropogenic influences on aquatic ecosystems, there remain concerns for Smallmouth Bass health and management. Because of this, ongoing research efforts are needed to monitor population and health changes and to conduct integrative research that considers complex relationships between organisms and their environments.
","language":"English","publisher":"Wiley","doi":"10.1002/fsh.10491","usgsCitation":"Schall, M., Smith, G., Blazer, V., Walsh, H.L., Li, Y., and Wagner, T., 2020, A fishery after the decline: The Susquehanna River Smallmouth Bass story: Fisheries Magazine, v. 45, no. 11, p. 576-584, https://doi.org/10.1002/fsh.10491.","productDescription":"9 p.","startPage":"576","endPage":"584","ipdsId":"IP-113869","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true},{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"links":[{"id":395618,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Pennsylvania","otherGeospatial":"Susquehanna River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -76.629638671875,\n 39.73253798438173\n ],\n [\n -75.95947265625,\n 39.73253798438173\n ],\n [\n -76.102294921875,\n 40.65563874006118\n ],\n [\n -75.498046875,\n 41.3850519497068\n ],\n [\n -76.04736328125,\n 42.01665183556825\n ],\n [\n -77.750244140625,\n 42.01665183556825\n ],\n [\n -77.618408203125,\n 40.371658891506094\n ],\n [\n -76.629638671875,\n 39.73253798438173\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"45","issue":"11","noUsgsAuthors":false,"publicationDate":"2020-08-31","publicationStatus":"PW","contributors":{"authors":[{"text":"Schall, Megan K.","contributorId":264767,"corporation":false,"usgs":false,"family":"Schall","given":"Megan K.","affiliations":[{"id":36985,"text":"Penn State University","active":true,"usgs":false}],"preferred":false,"id":833481,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Smith, Geoffrey D.","contributorId":224595,"corporation":false,"usgs":false,"family":"Smith","given":"Geoffrey D.","affiliations":[{"id":40898,"text":"Pennsylvania Fish & Boat Commission","active":true,"usgs":false}],"preferred":false,"id":833482,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Blazer, Vicki S. 0000-0001-6647-9614 vblazer@usgs.gov","orcid":"https://orcid.org/0000-0001-6647-9614","contributorId":150384,"corporation":false,"usgs":true,"family":"Blazer","given":"Vicki S.","email":"vblazer@usgs.gov","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":833483,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Walsh, Heather L. 0000-0001-6392-4604 hwalsh@usgs.gov","orcid":"https://orcid.org/0000-0001-6392-4604","contributorId":4696,"corporation":false,"usgs":true,"family":"Walsh","given":"Heather","email":"hwalsh@usgs.gov","middleInitial":"L.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":833484,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Li, Yan","contributorId":264515,"corporation":false,"usgs":false,"family":"Li","given":"Yan","affiliations":[{"id":6738,"text":"The Pennsylvania State University","active":true,"usgs":false}],"preferred":false,"id":833485,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wagner, Tyler 0000-0003-1726-016X twagner@usgs.gov","orcid":"https://orcid.org/0000-0003-1726-016X","contributorId":1050,"corporation":false,"usgs":true,"family":"Wagner","given":"Tyler","email":"twagner@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":833480,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70237801,"text":"70237801 - 2020 - f. Glaciers and ice caps outside Greenland","interactions":[],"lastModifiedDate":"2022-10-31T15:13:54.989407","indexId":"70237801","displayToPublicDate":"2020-08-01T08:56:53","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1112,"text":"Bulletin of the American Meteorological Society","onlineIssn":"1520-0477","printIssn":"0003-0007","active":true,"publicationSubtype":{"id":10}},"title":"f. Glaciers and ice caps outside Greenland","docAbstract":"No abstract available.
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For decades, ecologists have been calling for research to understand parasites' important ecological role, and increasingly, to protect as many species from extinction as possible. However, most conservationists still work within priority systems for funding and effort that exclude or ignore parasites, or treat parasites as an obstacle to be overcome. Our working group identified 12 goals for the next decade that could advance parasite biodiversity conservation through an ambitious mix of research, advocacy, and management.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.biocon.2020.108596","usgsCitation":"Carlson, C.J., Hopkins, S.R., Bell, K.C., Dona, J., Godfrey, S.S., Kwak, M.L., Lafferty, K.D., Moir, M.L., Speer, K., Strona, G., Torchin, M., and Wood, C.L., 2020, A global parasite conservation plan: Biological Conservation, v. 250, 108596, 12 p., https://doi.org/10.1016/j.biocon.2020.108596.","productDescription":"108596, 12 p.","ipdsId":"IP-117834","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":455804,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.biocon.2020.108596","text":"Publisher Index Page"},{"id":377168,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"250","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Carlson, Colin 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Article"},"seriesTitle":{"id":1820,"text":"Geosphere","active":true,"publicationSubtype":{"id":10}},"title":"Three-dimensional shape and structure of the Susitna basin, south-central Alaska, from geophysical data","docAbstract":"We use gravity, magnetic, seismic reflection, well, and outcrop data to determine the three-dimensional shape and structural features of south-central Alaska’s Susitna basin. This basin is located within the Aleutian-Alaskan convergent margin region and is expected to show effects of regional subduction zone processes. Aeromagnetic data, when filtered to highlight anomalies associated with sources within the upper few kilometers, show numerous linear northeast-trending highs and some linear north-trending highs. Comparisons to seismic reflection and well data show that these highs correspond to areas where late Paleocene to early Eocene volcanic layers have been locally uplifted due to folding and/or faulting. The combined magnetic and seismic reflection data suggest that the linear highs represent northeast-trending folds and north-striking faults. Several lines of evidence suggest that the northeast-trending folds formed during the middle Eocene to early Miocene and may have continued to be active in the Pliocene. The north-striking faults, which in some areas appear to cut the northeast-trending folds, show evidence of Neogene and probable modern movement. Gravity data facilitate estimates of the shape and depth of the basin. This was accomplished by separating the observed gravity anomaly into two components—one representing low-density sedimentary fill within the basin and one representing density heterogeneities within the underlying crystalline basement. We then used the basin anomaly, seismic reflection data, and well data to estimate the depth of the basin. Together, the magnetic, gravity, and reflection seismic analyses reveal an asymmetric basin comprising sedimentary rock over 4 km thick with steep, fault-bounded sides to the southwest, west, and north and a mostly gentle rise toward the east. Relations to the broader tectonic regime are suggested by fold axis orientations within the Susitna basin and neighboring Cook Inlet basin, which are roughly parallel to the easternmost part of the Alaska-Aleutian trench and associated Wadati-Benioff zone as it trends from northeast to north-northeast to northeast. An alignment between forearc basin folds and the subduction zone trench has been observed at other convergent margins, attributed to strain partitioning generated by regional rheologic variations that are associated with the subducting plate and arc magmatism. The asymmetric shape of the basin, especially its gentle rise to the east, may reflect uplift associated with flat-slab subduction of the Yakutat microplate, consistent with previous work that suggested Yakutat influence on the nearby Talkeetna Mountains and western Alaska Range. Yakutat subduction may also have contributed to Neogene and later reverse slip along north-striking faults within the Susitna basin.
","language":"English","publisher":"Geological Society of America","doi":"10.1130/GES02165.1","usgsCitation":"Shah, A.K., Phillips, J., Lewis, K.A., Stanley, R.G., Haeussler, P., and Potter, C.J., 2020, Three-dimensional shape and structure of the Susitna basin, south-central Alaska, from geophysical data: Geosphere, v. 16, no. 4, p. 969-990, https://doi.org/10.1130/GES02165.1.","productDescription":"22 p.","startPage":"969","endPage":"990","ipdsId":"IP-103718","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":455808,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/ges02165.1","text":"Publisher Index Page"},{"id":380589,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","city":"South Central Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -154.775390625,\n 57.844750992891\n ],\n [\n -145.634765625,\n 57.844750992891\n ],\n [\n -145.634765625,\n 62.71446210149774\n ],\n [\n -154.775390625,\n 62.71446210149774\n ],\n [\n -154.775390625,\n 57.844750992891\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"16","issue":"4","noUsgsAuthors":false,"publicationDate":"2020-06-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Shah, Anjana K. 0000-0002-3198-081X ashah@usgs.gov","orcid":"https://orcid.org/0000-0002-3198-081X","contributorId":2297,"corporation":false,"usgs":true,"family":"Shah","given":"Anjana","email":"ashah@usgs.gov","middleInitial":"K.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":805103,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Phillips, Jeffrey 0000-0002-6459-2821 jeff@usgs.gov","orcid":"https://orcid.org/0000-0002-6459-2821","contributorId":127453,"corporation":false,"usgs":true,"family":"Phillips","given":"Jeffrey","email":"jeff@usgs.gov","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":805104,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lewis, Kristen A. 0000-0003-4991-3399 klewis@usgs.gov","orcid":"https://orcid.org/0000-0003-4991-3399","contributorId":4120,"corporation":false,"usgs":true,"family":"Lewis","given":"Kristen","email":"klewis@usgs.gov","middleInitial":"A.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":805105,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stanley, Richard G. 0000-0001-6192-8783 rstanley@usgs.gov","orcid":"https://orcid.org/0000-0001-6192-8783","contributorId":1832,"corporation":false,"usgs":true,"family":"Stanley","given":"Richard","email":"rstanley@usgs.gov","middleInitial":"G.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":805106,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Haeussler, Peter J. 0000-0002-1503-6247","orcid":"https://orcid.org/0000-0002-1503-6247","contributorId":219956,"corporation":false,"usgs":true,"family":"Haeussler","given":"Peter J.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"preferred":true,"id":805107,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Potter, Christopher J. 0000-0002-2300-6670 cpotter@usgs.gov","orcid":"https://orcid.org/0000-0002-2300-6670","contributorId":1026,"corporation":false,"usgs":true,"family":"Potter","given":"Christopher","email":"cpotter@usgs.gov","middleInitial":"J.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":805108,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70212896,"text":"70212896 - 2020 - Genomes reveal genetic diversity of Piscine orthoreovirus in farmed and free-ranging salmonids from Canada and USA","interactions":[],"lastModifiedDate":"2020-10-28T15:59:41.808411","indexId":"70212896","displayToPublicDate":"2020-07-31T18:44:38","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5051,"text":"Virus Evolution","onlineIssn":"2057-1577","active":true,"publicationSubtype":{"id":10}},"title":"Genomes reveal genetic diversity of Piscine orthoreovirus in farmed and free-ranging salmonids from Canada and USA","docAbstract":"Piscine orthoreovirus (PRV-1) is a segmented RNA virus which is commonly found in salmonids in the Atlantic and Pacific Oceans. PRV-1 causes the Heart and Skeletal Muscle Inflammation (HSMI) disease in Atlantic salmon and is associated with several other disease conditions. Previous phylogenetic studies of genome segment 1 (S1) identified four main genogroups of PRV-1 (S1 genogroups I – IV). The goal of the present study was to use Bayesian phylogenetic inference to expand our understanding of the spatial, temporal and host patterns of PRV-1 from the waters of the northeast Pacific. To that end, we determined the coding genome sequences of 14 PRV-1 samples that were selected to improve our knowledge of genetic diversity across a broader temporal, geographic and host range, including the first reported genome sequences from the northwest Atlantic (Eastern Canada). Nucleotide and amino acid sequences of the concatenated genomes and their individual segments revealed that established sequences from the northeast Pacific were monophyletic in all analyses. Bayesian inference phylogenetic trees of S1 sequences using BEAST and MrBayes also found that sequences from the northeast Pacific grouped separately from sequences from other areas. One PRV-1 sample (WCAN_BC17_AS_2017) from an escaped Atlantic salmon, collected in British Columbia but derived from Icelandic broodstock, grouped with other S1 sequences from Iceland. Our concatenated genome and S1 analysis demonstrated that PRV-1 from the northeast Pacific is genetically distinct but descended from PRV-1 from the North Atlantic. However, the analyses were inconclusive as to the timing and exact source of introduction into the northeast Pacific, either from eastern North America or European waters of the North Atlantic. There was no evidence that PRV-1 was evolving differently between free-ranging Pacific Salmon and farmed Atlantic Salmon. The northeast Pacific PRV-1 sequences fall within genogroup II based on the classification of Garseth et al. (2013), which also includes North Atlantic sequences from Eastern Canada, Iceland and Norway. The additional full genome sequences herein strengthen our understanding of phylogeographical patterns related to the northeast Pacific, but a more balanced representation of full PRV-1 genomes from across its range, as well additional sequencing of archived samples, are still needed to better understand global relationships including potential transmission links among regions.
","language":"English","publisher":"Oxford Academic Journals","doi":"10.1093/ve/veaa054","usgsCitation":"Siah, A., Breyta, B.R., Warheit, K.I., Gagne, N., Purcell, M.K., Morrison, D.B., Powell, J.F., and Johnson, S., 2020, Genomes reveal genetic diversity of Piscine orthoreovirus in farmed and free-ranging salmonids from Canada and USA: Virus Evolution, v. 6, no. 2, veaa054, 15 p., https://doi.org/10.1093/ve/veaa054.","productDescription":"veaa054, 15 p.","ipdsId":"IP-118186","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":455811,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/ve/veaa054","text":"Publisher Index Page"},{"id":378077,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, Chile, Norway, United States","otherGeospatial":"Faroe Islands","volume":"6","issue":"2","noUsgsAuthors":false,"publicationDate":"2020-07-31","publicationStatus":"PW","contributors":{"authors":[{"text":"Siah, Ahmed","contributorId":149983,"corporation":false,"usgs":false,"family":"Siah","given":"Ahmed","email":"","affiliations":[{"id":17874,"text":"British Columbia Centre for Aquatic Health Sciences, BC Canada","active":true,"usgs":false}],"preferred":false,"id":797785,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Breyta, B. R.","contributorId":239729,"corporation":false,"usgs":false,"family":"Breyta","given":"B.","email":"","middleInitial":"R.","affiliations":[{"id":47991,"text":"University of Washington, School of Aquatic Fisheries Sciences, Seattle, WA","active":true,"usgs":false}],"preferred":false,"id":797786,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Warheit, K. I.","contributorId":239730,"corporation":false,"usgs":false,"family":"Warheit","given":"K.","email":"","middleInitial":"I.","affiliations":[{"id":47993,"text":"Washington Department of Fish and Wildlife, Olympia WA, USA","active":true,"usgs":false}],"preferred":false,"id":797787,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gagne, N","contributorId":239731,"corporation":false,"usgs":false,"family":"Gagne","given":"N","email":"","affiliations":[{"id":47994,"text":"Fisheries & Oceans Canada, Gulf Fisheries Center, Moncton, NB, Canada","active":true,"usgs":false}],"preferred":false,"id":797788,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Purcell, Maureen K. 0000-0003-0154-8433 mpurcell@usgs.gov","orcid":"https://orcid.org/0000-0003-0154-8433","contributorId":168475,"corporation":false,"usgs":true,"family":"Purcell","given":"Maureen","email":"mpurcell@usgs.gov","middleInitial":"K.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":797789,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Morrison, Diane B.","contributorId":149984,"corporation":false,"usgs":false,"family":"Morrison","given":"Diane","email":"","middleInitial":"B.","affiliations":[{"id":17875,"text":"Marine Harvest Canada, Campbell River, BC, Canada","active":true,"usgs":false}],"preferred":false,"id":797790,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Powell, J. F. F.","contributorId":239732,"corporation":false,"usgs":false,"family":"Powell","given":"J.","email":"","middleInitial":"F. F.","affiliations":[{"id":47996,"text":"British Columbia Centre for Aquatic Health Sciences, Campbell River BC, Canada","active":true,"usgs":false}],"preferred":false,"id":797791,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Johnson, S. C.","contributorId":239733,"corporation":false,"usgs":false,"family":"Johnson","given":"S. C.","affiliations":[{"id":47997,"text":"Fisheries & Oceans Canada, Nanaimo, British Columbia, Canada","active":true,"usgs":false}],"preferred":false,"id":797792,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70211518,"text":"sir20205069 - 2020 - Incipient bed-movement and flood-frequency analysis using hydrophones to estimate flushing flows on the upper Colorado River, Colorado, 2019","interactions":[],"lastModifiedDate":"2020-08-05T18:38:22.157905","indexId":"sir20205069","displayToPublicDate":"2020-07-31T18:00:00","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2020-5069","displayTitle":"Incipient Bed-Movement and Flood-Frequency Analysis using Hydrophones to Estimate Flushing Flows on the Upper Colorado River, Colorado, 2019","title":"Incipient bed-movement and flood-frequency analysis using hydrophones to estimate flushing flows on the upper Colorado River, Colorado, 2019","docAbstract":"In 2019, the U.S. Geological Survey, in cooperation with the Upper Colorado River Wild and Scenic Stakeholder Group, studied the magnitude and recurrence interval of streamflow (discharge) needed to initiate bed movement of gravel-sized and finer sediment in a segment of the Colorado River in Colorado to better understand sediment movement and its relation to flow regimes of the river. The study area extended from the confluence of the Blue and Colorado Rivers near Kremmling, Colorado, downstream to the confluence of the Eagle and Colorado Rivers near Dotsero, Colo. Bed movement occurred more frequently and at lower streamflows from State Bridge to Catamount Bridge compared to the study area upstream from State Bridge. As a result, the flushing flow was characterized in the study area using two definitions: the “upstream flushing flow” for locations above State Bridge and the “downstream flushing flow” for locations below State Bridge.
Acoustic data from stationary hydrophones continuously deployed in the spring and summer of 2019 and longitudinal hydrophone acoustic profiles manually collected in summer 2019 were used to identify the streamflow needed for incipient gravel-bed movement and establish flushing flows defined for this study. The upstream flushing flow was defined as 3,000 cubic feet per second (ft3/s) at streamgage 09058000 Colorado River near Kremmling, Colo. (the Kremmling streamgage) based on the underwater acoustic data from the downstream location at the Radium stationary site (2,950 ft3/s at the Kremmling streamgage which was rounded to 3,000 ft3/s). The downstream flushing flow was defined as 2,400 ft3/s at the Kremmling streamgage or 3,100 ft3/s at streamgage 09060799 Colorado River at Catamount Bridge, Colo. (the Catamount Bridge streamgage) based on the more conservative streamflow associated with the flushing flow defined using underwater acoustic data from the downstream location at the above Catamount Bridge stationary site (2,310 ft3/s at the Kremmling streamgage which was rounded to 2,400 ft3/s and 3,040 ft3/s at the Catamount Bridge streamgage which was rounded to 3,100 ft3/s).
The annual series of peak-streamflow data at the Kremmling streamgage were used to estimate annual exceedance probability (AEP) streamflows to compare to the flushing flow. Results from the Denver Water Platte and Colorado Simulation Model were used to generate daily peak-streamflows for a future conditions scenario provided for this report. The upstream flushing flow of approximately 3,000 ft3/s at the Kremmling streamgage has an AEP near 0.50 (2-year return period) depending on the period of historical record and an AEP near 0.43 (2.33-year return period) for the future period. The downstream flushing flow of approximately 2,400 ft3/s at the Kremmling streamgage has an AEP near 0.67 (1.5-year return period) depending on the period of historical record and an AEP near 0.67 (1.5-year return period) for the future period.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205069","collaboration":"Prepared in cooperation with the Upper Colorado River Wild and Scenic Stakeholder Group and the Colorado River Water Conservation District","usgsCitation":"Kohn, M.S., Marineau, M.D., Hempel, L.A., and McDonald, R.R., 2020, Incipient bed-movement and flood-frequency analysis using hydrophones to estimate flushing flows on the upper Colorado River, Colorado, 2019: U.S. Geological Survey Scientific Investigations Report 2020–5069, 39 p., https://doi.org/10.3133/sir20205069.","productDescription":"Report: viii, 39 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-114386","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":376916,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9J5L78O","text":"USGS data release","linkHelpText":"Acoustic, Spatial, and Sediment Size Data 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Colorado Water Science Center
U.S. Geological Survey
Box 25046, MS 415
Denver, CO 80225