A new data layer provides Coastal and Marine Ecological Classification Standard (CMECS) labels for global coastal segments at 1 km or shorter resolution. These characteristics are summarized for six US Marine Biodiversity Observation Network (MBON) sites and one MBON Pole to Pole of the Americas site in Argentina. The global coastlines CMECS classifications were produced from a partitioning of a 30 m Landsat-derived shoreline vector that was segmented into 4 million 1 km or shorter segments. Each segment was attributed with values from 10 variables that represent the ecological settings in which the coastline occurs, including properties of the adjacent water, adjacent land, and coastline itself. The 4 million segments were classified into 81,000 coastal segment units (CSUs) as unique combinations of variable classes. We summarize the process to develop the CSUs and derive summary descriptions for the seven MBON case study sites. We discuss the intended application of the new CSU data for research and management in coastal areas.
","language":"English","publisher":"The Oceanography Society","doi":"10.5670/oceanog.2021.219","usgsCitation":"Sayre, R., Butler, K., Van Graafeiland, K., Breyer, S., Wright, D., Frye, C., Karagulle, D., Martin, M.T., Cress, J.J., Allen, T., Allee, R., Parsons, R., Nyberg, B., Costello, M., Harris, P., and Muller-Karger, F., 2021, A global ecological classification of coastal segment units to complement marine biodiversity observation network assessments: Oceanography, v. 34, no. 2, 10 p., https://doi.org/10.5670/oceanog.2021.219.","productDescription":"10 p.","ipdsId":"IP-129029","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":5055,"text":"Land Change Science","active":true,"usgs":true}],"links":[{"id":450534,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5670/oceanog.2021.219","text":"Publisher Index Page"},{"id":436173,"rank":0,"type":{"id":30,"text":"Data 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Arendal","active":true,"usgs":false}],"preferred":false,"id":825193,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Muller-Karger, Frank","contributorId":267728,"corporation":false,"usgs":false,"family":"Muller-Karger","given":"Frank","affiliations":[{"id":7163,"text":"University of South Florida","active":true,"usgs":false}],"preferred":false,"id":825192,"contributorType":{"id":1,"text":"Authors"},"rank":16}]}} ,{"id":70224917,"text":"sir20215073 - 2021 - Cimarron River alluvial aquifer hydrogeologic framework, water budget, and implications for future water availability in the Pawnee Nation Tribal jurisdictional area, Payne County, Oklahoma, 2016–18","interactions":[],"lastModifiedDate":"2021-10-06T11:55:47.832961","indexId":"sir20215073","displayToPublicDate":"2021-10-05T16:57:57","publicationYear":"2021","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":"2021-5073","displayTitle":"Cimarron River Alluvial Aquifer Hydrogeologic Framework, Water Budget, and Implications for Future Water Availability in the Pawnee Nation Tribal Jurisdictional Area, Payne County, Oklahoma, 2016–18","title":"Cimarron River alluvial aquifer hydrogeologic framework, water budget, and implications for future water availability in the Pawnee Nation Tribal jurisdictional area, Payne County, Oklahoma, 2016–18","docAbstract":"The Cimarron River is a free-flowing river and is a major source of water as it flows across Oklahoma. Increased demand for water resources within the Cimarron River alluvial aquifer in north-central Oklahoma (primarily in Payne County) has led to increases in groundwater withdrawals for agriculture, public, irrigation, industrial, and domestic supply purposes. The Pawnee Nation of Oklahoma (Pawnee Nation) is particularly concerned about the sustainability of the Cimarron River alluvial aquifer and whether the aquifer will continue to be a viable water resource for future generations of Tribal members and residents. To better understand current (2021) water resources and possible future water availability in the Pawnee Nation Tribal jurisdictional area, the U.S. Geological Survey, in cooperation with the Bureau of Indian Affairs and the Pawnee Nation of Oklahoma, compiled available hydrogeologic data and developed conceptual and numerical groundwater-flow models for the Cimarron River alluvial aquifer in Payne County, north-central Oklahoma, including a focus area in the Pawnee Nation Tribal jurisdictional area for the 2016–18 study period.
A conceptual water budget was created to establish estimates of groundwater fluxes into and out of the aquifer through hydrologic boundaries and groundwater withdrawals for use in the numerical groundwater-flow model. The conceptual water budget focuses on the alluvial aquifer, meaning that inflows include sources of water to the aquifer and that outflows include sources of water out of the aquifer, such as base-flow contributions to the Cimarron River. The conceptual water budget was constructed by using data from 2017 (the most complete year of record for each data type included in the model) for the Pawnee Nation subdomain of the Cimarron River alluvial aquifer model extent (Pawnee Nation subdomain).
Groundwater withdrawals were estimated from groundwater-withdrawal rate information for permanent and temporary permitted wells that was obtained from the Oklahoma Water Resources Board. One-half of each annual permitted groundwater-withdrawal rate allotted was used as the estimated annual groundwater-withdrawal amount. Halving the permitted groundwater-withdrawal rate was done because permitted withdrawal rates are the maximum permitted rate and actual groundwater withdrawals are generally appreciably lower than the maximum permitted rate. Total groundwater withdrawals were estimated as 1,300 acre-feet per year for the Pawnee Nation subdomain. Various hydrogeologic data were measured to assist with model development, including depth to bedrock and water-table altitude data. In support of the model development, analyses pertaining to groundwater flow, groundwater/surface-water interactions, base flows in the Cimarron River, and lithological interpretations in the Pawnee Nation Tribal jurisdictional area were used to compute a conceptual water budget applicable to the 2016–18 study period. A numerical groundwater-flow model was developed using the hydrogeologic framework of the Cimarron River alluvial aquifer and the conceptual water budget. The numerical model consists of a single layer representing alluvium and terrace deposits within the alluvial aquifer model area. Hydraulic conductivities were estimated and modeled for the alluvium and terrace deposits in the alluvial aquifer. Base-flow values were estimated using the base-flow index from streamflow data collected at U.S. Geological Survey streamgages. Stream seepage values were derived from the mean 2017 base-flow index between certain streamgages. Hydraulic conductivities were specified an initial (before calibration) value of 120 feet per day for the alluvium deposits and 16 feet per day for the terrace deposits.
The simulated inflows in the numerical groundwater-flow model of the Pawnee Nation subdomain were higher than the inflows of conceptual water budget, and the simulated outflows were lower than the outflows of the conceptual water budget. Overall, simulated base flows matched closely to observed base flows for the 2016 and 2017 stress periods. Simulated streamflow tended to match better with the observed streamflow for 2017, which was the period with the most data for the Cimarron River alluvial aquifer model.
Streamflow capture analysis was applied to the steady-state simulation to identify areas of the aquifer where base flows in the Cimarron River were most sensitive to groundwater withdrawals. The initial base-flow value was assigned the value obtained from streamflow-routing software used to simulate stream outflow for the calibrated steady-state base model. Subsequent simulations were run in each active cell in the Pawnee Nation subdomain for a specified groundwater-withdrawal rate of 180,000 cubic feet per day. The study area that includes the Pawnee Nation subdomain is in the upper Arkansas River Basin. A groundwater-withdrawal rate of 180,000 cubic feet per second per day represents a 34 percent increase compared to the highest permitted groundwater-withdrawal rate for the study area, which corresponds to the estimated 34 percent increase in groundwater withdrawals predicted by 2060 for the upper Arkansas River Basin. Simulated streamflow capture was highest in the alluvium deposits adjacent to the Cimarron River; that is, base flow in the Cimarron River decreased the most for simulated groundwater withdrawals in the alluvium deposits adjacent to the Cimarron River. Streamflow capture increased as the distance of a well from the Cimarron River decreased in the simulation. The northeastern part of the Pawnee Nation subdomain showed greater streamflow capture in a broader area; streamflow in that part of the Pawnee Nation subdomain is likely more sensitive to groundwater withdrawals compared to other parts of the Pawnee Nation subdomain.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215073","collaboration":"Prepared in cooperation with the Bureau of Indian Affairs and the Pawnee Nation of Oklahoma","usgsCitation":"Paizis, N.C., and Trevisan, A.R., 2021, Cimarron River alluvial aquifer hydrogeologic framework, water budget, and implications for future water availability in the Pawnee Nation Tribal jurisdictional area, Payne County, Oklahoma, 2016–18: U.S. Geological Survey Scientific Investigations Report 2021–5073, 49 p., https://doi.org/10.3133/sir20215073.","productDescription":"Report: x, 49 p.; Data Release; Dataset","numberOfPages":"64","onlineOnly":"Y","ipdsId":"IP-119627","costCenters":[{"id":48595,"text":"Oklahoma-Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":390181,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5073/coverthb.jpg"},{"id":390182,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5073/sir20215073.pdf","text":"Report","size":"7.46 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021–5073"},{"id":390184,"rank":4,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"U.S. Geological Survey National Water Information System database","description":"USGS Dataset","linkHelpText":"— USGS water data for the Nation"},{"id":390183,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9WZGYQF","text":"USGS Data Release","description":"USGS Data Release","linkHelpText":"MODFLOW-NWT model used for the simulation of the Cimarron River alluvial aquifer in the Pawnee Nation Tribal jurisdictional area in Payne County, Oklahoma, 2016–17"}],"country":"United States","state":"Oklahoma","county":"Payne County","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-96.9277,36.246],[-96.8216,36.245],[-96.8212,36.1593],[-96.6245,36.1605],[-96.6228,35.9427],[-97.1428,35.9442],[-97.1423,35.9641],[-97.1557,35.9485],[-97.1729,35.9428],[-97.1872,35.9426],[-97.2013,35.9469],[-97.2163,35.9576],[-97.2252,35.9677],[-97.236,35.9683],[-97.2461,35.9721],[-97.2523,35.9744],[-97.2734,35.9734],[-97.2841,35.9767],[-97.2863,35.9795],[-97.2862,35.9835],[-97.2883,35.9931],[-97.2927,36.0004],[-97.2982,36.0091],[-97.3055,36.011],[-97.3203,36.0108],[-97.3329,36.0078],[-97.3359,36.0024],[-97.34,35.9947],[-97.3475,35.9885],[-97.3556,35.9841],[-97.3569,36.1583],[-97.1426,36.1588],[-97.1417,36.245],[-96.9277,36.246]]]},\"properties\":{\"name\":\"Payne\",\"state\":\"OK\"}}]}","contact":"Director, Oklahoma-Texas Water Science Center
U.S. Geological Survey
1505 Ferguson Lane
Austin, TX 78754-4501
School Branch in Hendricks County in central Indiana, is a small stream with a variety of agricultural and suburban land uses that drains into the Eagle Creek Reservoir, a major source of drinking water for Indianapolis, Indiana. The School Branch watershed has become the focus of a collaborative partnership of Federal, State, and local agencies; a university research center; and agricultural producers to understand the effects of land use and management practices on water quality and water quantity in the watershed. The U.S. Geological Survey, in cooperation with the Indiana Department of Environmental Management, contributed to the School Branch partnership with the operation of three streamgages (03353415 School Branch at Maloney Road near Brownsburg, Indiana; 03353420 School Branch at County Road 750 North at Brownsburg, Indiana; and 03353430 School Branch at Noble Drive at Brownsburg, Indiana) and the operation of a continuous water-quality gage (also known as a supergage) at County Road 750 North that measured dissolved oxygen, pH, temperature, specific conductance, turbidity, nitrate, and orthophosphate. Additional efforts included the use of passive samplers to identify wastewater indicators; assessment of fish and macroinvertebrate communities and stream habitat to identify ecological impairment; sampling for nutrients and sediment to estimate loads; and using major ions, stable isotopes and nested groundwater monitoring wells at County Road 750 North to determine hydrologic connectivity between the groundwater and surface water. The objectives of this study were to collect surface and groundwater data to analyze the hydrology and water quality within the watershed. Total nitrogen yields were highest at the upstream site, Maloney Road, and indicated a mixture of nitrogen sources in the watershed. Differences found in total nitrogen loading patterns throughout the watershed may be linked to differences in hydrology and land-use management from site to site. The groundwater and surface water were shown to be highly connected, and except for some low-flow periods, the water was flowing from groundwater to the stream for most of the study period. Fish and macroinvertebrate communities show improvement from upstream to downstream, with increases in diversity, richness, and species sensitive to poor water quality and habitat. These increases were most likely due to improved habitat quality at the downstream station.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215061","collaboration":"Prepared in cooperation with the Indiana Department of Environmental Management","usgsCitation":"Bunch, A.R., McCausland, D.R., and Bayless, E.R., 2021, Hydrologic and ecological investigations in the School Branch watershed, Hendricks County, Indiana—Water years 2016–2018: U.S. Geological Survey Scientific Investigations Report 2021–5061, 61 p., https://doi.org/10.3133/sir20215061.","productDescription":"Report: x, 61 p.; Data Release","numberOfPages":"74","onlineOnly":"Y","ipdsId":"IP-114931","costCenters":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"links":[{"id":390195,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5061/coverthb.jpg"},{"id":390196,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5061/sir20215061.pdf","text":"Report","size":"4.62 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021–5061"},{"id":390197,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9QCIDBV","text":"USGS Data Release","description":"USGS Data Release","linkHelpText":"Data and rloadest models for daily total nitrogen load for the School Branch watershed, Hendricks County, Indiana—Water years 2016–2018"}],"country":"United States","state":"Indiana","county":"Hendricks County","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-86.3267,39.9238],[-86.325,39.8662],[-86.328,39.8662],[-86.3281,39.8526],[-86.3268,39.6318],[-86.4648,39.6297],[-86.4642,39.6006],[-86.574,39.6002],[-86.6546,39.6001],[-86.6522,39.6087],[-86.6463,39.6128],[-86.6403,39.6201],[-86.6404,39.6305],[-86.6654,39.6305],[-86.6858,39.63],[-86.6853,39.6884],[-86.6849,39.7773],[-86.6845,39.8648],[-86.6929,39.8643],[-86.6937,39.9228],[-86.3267,39.9238]]]},\"properties\":{\"name\":\"Hendricks\",\"state\":\"IN\"}}]}","contact":"Director, Ohio-Kentucky-Indiana Water Science Center
U.S. Geological Survey
5957 Lakeside Boulevard
Indianapolis, IN 46278
On March 12, 2019, Congress passed the John D. Dingell, Jr., Conservation, Management, and Recreation Act (Public Law 116–9; 133 Stat. 580), in which Title V, §5001 (43 U.S.C. 31k) authorized the establishment of the National Volcano Early Warning and Monitoring System (NVEWS) within the U.S. Geological Survey (USGS). Conceived by the USGS Volcano Hazards Program in 2005, NVEWS is designed to be a proactive, fully integrated national-scale volcano monitoring system to ensure that the 161 potentially active volcanoes in the United States and its territories are monitored at levels commensurate with the threat they pose. The core of this report is the first USGS NVEWS five-year management plan, which was presented to Congress on March 12, 2020, and which details the principal elements of NVEWS that will be developed over the next five years, pending sufficient funding. These elements are improvements and enhancements to the monitoring network, a National Volcano Data Center, an external grants activity, an Advisory Committee, an Implementation Committee, and partnerships, with estimated cost projections and annual milestones.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211092","usgsCitation":"Cervelli, P.F., Mandeville, C.W., Avery, V.F., and Wilkins, A.M., 2021, Five-year management plan for establishing and operating NVEWS—The National Volcano Early Warning System: U.S. Geological Survey Open-File Report 2021–1092, 11 p., https://doi.org/10.3133/ofr20211092.","productDescription":"iv, 11 p.","numberOfPages":"11","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-117913","costCenters":[{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":390179,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1092/coverthb.jpg"},{"id":390180,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1092/ofr20211092.pdf","text":"Report","size":"2.37 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2021-1092"}],"country":"United States","otherGeospatial":"Northern Mariana Islands","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 143.08593749999997,\n 13.410994034321702\n ],\n [\n 146.513671875,\n 13.410994034321702\n ],\n [\n 146.513671875,\n 16.720385051694\n ],\n [\n 143.08593749999997,\n 16.720385051694\n ],\n [\n 143.08593749999997,\n 13.410994034321702\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -158.55468749999997,\n 17.476432197195518\n ],\n [\n -153.28125,\n 17.476432197195518\n ],\n [\n -153.28125,\n 22.755920681486405\n ],\n [\n -158.55468749999997,\n 22.755920681486405\n ],\n [\n -158.55468749999997,\n 17.476432197195518\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -125.5078125,\n 31.20340495091737\n ],\n [\n -105.1171875,\n 31.20340495091737\n ],\n [\n -105.1171875,\n 48.922499263758255\n ],\n [\n -125.5078125,\n 48.922499263758255\n ],\n [\n -125.5078125,\n 31.20340495091737\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -141.328125,\n 69.83962194067463\n ],\n [\n -149.765625,\n 70.95969716686398\n ],\n [\n -155.91796874999997,\n 71.30079291637452\n ],\n [\n -162.94921875,\n 70.4367988185464\n ],\n [\n -166.640625,\n 68.52823492039876\n ],\n [\n -167.34375,\n 65.6582745198266\n ],\n [\n -165.41015625,\n 62.186013857194226\n ],\n [\n -165.41015625,\n 60.23981116999893\n ],\n [\n -164.00390625,\n 58.53959476664049\n ],\n [\n -164.53125,\n 56.07203547180089\n ],\n [\n -164.35546875,\n 53.85252660044951\n ],\n [\n -152.75390624999997,\n 56.84897198026975\n ],\n [\n -149.4140625,\n 59.62332522313024\n ],\n [\n -143.96484375,\n 59.62332522313024\n ],\n [\n -137.4609375,\n 57.42129439209407\n ],\n [\n -131.66015625,\n 52.3755991766591\n ],\n [\n -130.60546875,\n 53.4357192066942\n ],\n [\n -131.66015625,\n 57.326521225217064\n ],\n [\n -136.58203125,\n 59.88893689676585\n ],\n [\n -140.625,\n 60.50052541051131\n ],\n [\n -141.328125,\n 69.83962194067463\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Volcano Hazards Program
U.S. Geological Survey
12201 Sunrise Valley Drive
Reston, VA 20192
Contact Volcano Hazards Program
","tableOfContents":"Retaliatory killing of large carnivores due to livestock predation is one of the major threats for the conservation of many declining populations of predators. According to empirical observations, there is a higher incidence of livestock predation when native prey abundance is low. In this study, we applied a treatment consisting of augmentation of prey abundance by translocation of peccaries (Pecari tajacu) and placement of four feed stations for white-tailed deer (Odocoileus virginianus) on a cattle ranch in Sonora, Mexico, with verified calf predation by puma (Puma concolor) and jaguar (Panthera onca). We quantified and compared consumed prey over two periods—phase I (8 months before the augmentation of prey) and phase II (8 months after the augmentation of prey)—through investigation of kill sites from Global Positioning System–collared jaguar and puma, prey identification from analyzed scat using molecular DNA techniques, and opportunistic discoveries of recently killed animal remains by either predator. We calculated the relative abundance of species (17 mammals [one species with two distinct age classes] and 1 bird species) through camera traps and for the most relevant prey species for this study (deer, calf, and peccary), we also estimated prey use by the predator, based on their availability during each period (prey preference). In the prey composition analyses of scat, we observed a significant reduction in the consumption of bovids and a significant increase in the consumption of peccaries during phase II. In the analyses of prey use, during phase I, predators consumed peccaries and calves at a higher proportion in relation to their availability. During phase II, consumption of calves declined from being preferred, to being consumed at the same proportion as their availability. Application of these results can contribute to the decrease of livestock predation and therefore conservation of pumas and jaguars.
","language":"English","publisher":"Southwestern Association of Naturalists","doi":"10.1894/0038-4909-65.2.123","usgsCitation":"Cassaigne, I., Thompson, R.W., Medellin, R., Culver, M., Ochoa, A., Vargas, K., Childs, J.L., Galaz, M., and Sanderson, J., 2021, Augmentation of natural prey reduces cattle predation by puma (Puma concolor) and jaguar (Panthera onca) on a ranch in Sonora, Mexico: Southwestern Naturalist, v. 65, no. 2, p. 123-130, https://doi.org/10.1894/0038-4909-65.2.123.","productDescription":"8 p.","startPage":"123","endPage":"130","ipdsId":"IP-130984","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":397185,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Mexico","state":"Sonora","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -109.55429077148438,\n 29.545982511818\n ],\n [\n -109.42588806152342,\n 29.545982511818\n ],\n [\n -109.42588806152342,\n 29.656432596919352\n ],\n [\n -109.55429077148438,\n 29.656432596919352\n ],\n [\n -109.55429077148438,\n 29.545982511818\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"65","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Cassaigne, Ivonne","contributorId":287196,"corporation":false,"usgs":false,"family":"Cassaigne","given":"Ivonne","affiliations":[{"id":61499,"text":"pc","active":true,"usgs":false}],"preferred":false,"id":838082,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thompson, Ron W.","contributorId":170001,"corporation":false,"usgs":false,"family":"Thompson","given":"Ron","email":"","middleInitial":"W.","affiliations":[{"id":24784,"text":"Arizona Game and Fish Department, 5000 West Carefree Highway, Phoenix, Arizona 85086, United States","active":true,"usgs":false}],"preferred":false,"id":838083,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Medellin, Rodrigo A.","contributorId":77456,"corporation":false,"usgs":true,"family":"Medellin","given":"Rodrigo A.","affiliations":[],"preferred":false,"id":838084,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Culver, Melanie 0000-0001-5380-3059 mculver@usgs.gov","orcid":"https://orcid.org/0000-0001-5380-3059","contributorId":197693,"corporation":false,"usgs":true,"family":"Culver","given":"Melanie","email":"mculver@usgs.gov","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":838081,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ochoa, Alexander","contributorId":169994,"corporation":false,"usgs":false,"family":"Ochoa","given":"Alexander","email":"","affiliations":[{"id":17653,"text":"School of Natural Resources & the Environment, The University of Arizona, Tucson","active":true,"usgs":false}],"preferred":false,"id":838195,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Vargas, Karla","contributorId":173306,"corporation":false,"usgs":false,"family":"Vargas","given":"Karla","email":"","affiliations":[],"preferred":false,"id":838196,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Childs, Jack L.","contributorId":147124,"corporation":false,"usgs":false,"family":"Childs","given":"Jack","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":838197,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Galaz, Manuel","contributorId":288670,"corporation":false,"usgs":false,"family":"Galaz","given":"Manuel","email":"","affiliations":[],"preferred":false,"id":838198,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Sanderson, Jim","contributorId":173307,"corporation":false,"usgs":false,"family":"Sanderson","given":"Jim","email":"","affiliations":[],"preferred":false,"id":838199,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70225553,"text":"70225553 - 2021 - Evaluating lava flow propagation models with a case study from the 2018 eruption of Kīlauea Volcano, Hawai'i","interactions":[],"lastModifiedDate":"2021-10-22T12:33:32.523635","indexId":"70225553","displayToPublicDate":"2021-10-05T07:31:49","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1109,"text":"Bulletin of Volcanology","active":true,"publicationSubtype":{"id":10}},"title":"Evaluating lava flow propagation models with a case study from the 2018 eruption of Kīlauea Volcano, Hawai'i","docAbstract":"The 2018 lower East Rift Zone (LERZ) eruption of Kīlauea, Hawai’i, provides an excellent natural laboratory with which to test models of lava flow propagation. During early stages of eruption crises, the most useful lava flow propagation equations utilize readily determined parameters and require fewer a priori assumptions about future behavior of the flow. Here, we leverage the numerous observations of lava flows collected over the duration of the eruption crisis at Kīlauea in 2018 to test simple lava flow propagation models. These models track the one-dimensional propagation of the flows according to three main rheological restraining forces: bulk viscosity, yield strength, and growth of a surface crust. We calculate the predicted changes in length through time of three flows that vary in bulk composition, crystal content, and total flow length. Cooler flows that are more crystal-rich tend to be more dominated by crust growth, though early stages of propagation can be controlled by bulk viscosity. We find that variations in effusion rate significantly impact flows that are short-lived; flows that are produced during steady-state effusion are readily approximated by average values for the entire flow. Thus, accurate knowledge of variations in effusion rate are critical to accurate lava flow propagation forecasting.
Land-use land-cover change (LULCC) has become an important topic of research for the central United States because of the extensive conversion of the natural prairie into agricultural land, especially in the northern Great Plains. As a result, shifts in the natural climate (minimum/maximum temperature, precipitation, etc.) across the north-central United States have been observed, as noted within the Fourth National Climate Assessment (NCA4) report. Thus, it is necessary to understand how further LULCC will affect the near-surface atmosphere, the lower troposphere, and the planetary boundary layer (PBL) atmosphere over this region. The goal of this work was to investigate the utility of a new future land-use land-cover (LULC) dataset within the Weather Research and Forecasting (WRF) modeling system. The present study utilizes a modeled future land-use dataset developed by the Forecasting Scenarios of Land-Use Change (FORE-SCE) model to investigate the influence of future (2050) land use on a simulated PBL development within the WRF Model. Three primary areas of LULCC were identified within the FORE-SCE future LULC dataset across Nebraska and South Dakota. Variations in LULC between the 2005 LULC control simulation and four FORE-SCE simulations affected near-surface temperature (0.5°–1°C) and specific humidity (0.3–0.5 g kg−1). The differences noted in the temperature and moisture fields affected the development of the simulated PBL, leading to variations in PBL height and convective available potential energy. Overall, utilizing the FORE-SCE dataset within WRF produced notable differences relative to the control simulation over areas of LULCC represented in the FORE-SCE dataset.
Climate-influenced changes in hydrology affect water-food-energy security that may impact up to two billion people downstream of the High Mountain Asia (HMA) region. Changes in water supply affect energy, industry, transportation, and ecosystems (agriculture, fisheries) and as a result, also affect the region's social, environmental, and economic fabrics. Sustaining the highly interconnected food-energy-water nexus (FEWN) will be a fundamental and increasing challenge under a changing climate regime. High variability in topography and distribution of glaciated and snow-covered areas in the HMA region, and scarcity of high resolution (in-situ) data make it difficult to model and project climate change impacts on individual watersheds. We lack basic understanding of the spatial and temporal variations in climate, surface impurities in snow and ice such as black carbon and dust that alter surface albedo, and glacier mass balance and dynamics. These knowledge gaps create challenges in predicting where and when the impact of changes in river flow will be the most significant economically and ecologically. In response to these challenges, the United States National Aeronautics and Space Administration (NASA) established the High Mountain Asia Team (HiMAT) in 2016 to conduct research to address knowledge gaps. This paper summarizes some of the advances HiMAT made over the past 5 years, highlights the scientific challenges in improving our understanding of the hydrology of the HMA region, and introduces an integrated assessment framework to assess the impacts of climate changes on the FEWN for the HMA region. The framework, developed under a NASA HMA project, links climate models, hydrology, hydropower, fish biology, and economic analysis. The framework could be applied to develop scientific understanding of spatio-temporal variability in water availability and the resultant downstream impacts on the FEWN to support water resource management under a changing climate regime.
Groundwater depletion is a major threat to agricultural and municipal water supply in California's Central Valley. Recent droughts during 2007–2009 and 2012–2016 exacerbated chronic groundwater depletion. However, it is unclear how much groundwater storage recovered from drought-related overdrafts during post-drought years, and how climatic conditions and water management affected recovery times. We estimated groundwater storage change in the Central Valley for April 2002 through September 2019 using four methods: GRACE satellite data, a water balance approach, a hydrologic simulation model, and monitoring wells. We also evaluated the sensitivity of drought recovery to different climate scenarios (recent climate ± droughts and future climate change scenarios: 20 GCMs and 2 RCPs) using water balance method and statistical sampling of historical climate data. Estimated Central Valley groundwater loss during the two droughts ranged from 19 km3 (2007–2009) to 28 km3 (2012–2016) (median of four methods). Median aquifer storage recovery was 34% and 19% of the overdraft during the 2010–2011 and 2017–2019 post-drought years, respectively. Numerical experiments show that recovery times are sensitive to climate forcing, with longer recovery times for a future climate scenario that replicate historical climatology relative to historical forcing with no droughts. Overdraft recovery times decrease by ∼2× with implementation of pumping restrictions (30th to 50th percentiles of historical groundwater depletion) to constrain groundwater depletion relative to no restrictions with a no-drought future climatology. This study highlights the importance of considering water management implications for future drought recoveries within the context of climate change scenarios.
Successful wildlife management depends upon coordination and consultation with local communities. However, much of the research used to inform management is often derived solely from data collected directly from wildlife. Indigenous people living in the Arctic have a close connection to their environment, which provides unique opportunities to observe their environment and the ecology of Arctic species. Further, most northern Arctic communities occur within the range of polar bears (nanuq, Ursus maritimus) and have experienced significant climatic changes. Here, we used semi-structured interviews from 2017 to 2019 to document Iñupiaq knowledge of polar bears observed over four decades in four Alaskan communities in the range of the Southern Beaufort Sea polar bear subpopulation: Wainwright, Utqiaġvik, Nuiqsut, and Kaktovik. All but one of 47 participants described directional and notable changes in sea ice, including earlier ice breakup, later ice return, thinner ice, and less multiyear pack ice. These changes corresponded with observations of bears spending more time on land during the late summer and early fall in recent decades—observations consistent with scientific and Indigenous knowledge studies in Alaska, Canada, and Greenland. Participants noted that polar bear and seal body condition and local abundance either varied geographically or exhibited no patterns. However, participants described a recent phenomenon of bears being exhausted and lethargic when arriving on shore in the summer and fall after extensive swims from the pack ice. Further, several participants suggested that maternal denning is occurring more often on land than sea ice. Participants indicated that village and regional governments are increasingly challenged to obtain resources needed to keep their communities safe as polar bears spend more time on land, an issue that is likely to be exacerbated both in this region and elsewhere as sea ice loss continues.
The 2018 eruption of Kīlauea Volcano produced large and destructive lava flows from the fissure 8 (Ahu ‘aila ‘au) vent with flow velocities up to 17 m s−1, highly variable effusion rates over both short (minutes) and long (hours) time scales, and a proximal channel or spillway that displayed flow features similar to open channel flow in river systems. Monitoring such dynamic vent and lava flow systems is a challenge. Our results demonstrate that infrasound, combined with ground-based observations and imagery from unoccupied aircraft systems (UAS), can be used to distinguish vent degassing activity from high-speed lava flow activity. We use spectral characteristics and the infrasound frequency index (FI) to distinguish spillway infrasound from vent infrasound. Comparing FI with flow speeds derived from UAS videos reveals that spillway infrasound only occurs when flow speeds were sufficiently high to cause a supercritical flow state and breaking waves (Froude values > 1.7), and we propose that the spillway signals are produced primarily through the interaction of the turbulent lava-free surface with the atmosphere. We show that FI can also provide a means to track bulk effusion rate. Our results indicate that infrasound offers a new way to characterize lava flow channel hydraulics and is a powerful tool for monitoring effusive eruptions when high-speed flows are possible.
The spatial distribution and depth of permafrost are changing in response to warming and landscape disturbance across northern Arctic and boreal regions. This alters the infiltration, flow, surface and subsurface distribution, and hydrologic connectivity of inland waters. Such changes in the water cycle consequently alter the source, transport, and biogeochemical cycling of aquatic carbon (C), its role in the production and emission of greenhouse gases, and C delivery to inland waters and the Arctic Ocean. Responses to permafrost thaw across heterogeneous boreal landscapes will be neither spatially uniform nor synchronous, thus giving rise to expressions of low to medium confidence in predicting hydrologic and aquatic C response despite very high confidence in projections of widespread near-surface permafrost disappearance as described in the 2019 Intergovernmental Panel on Climate Change Special Report on the Ocean and Cryosphere in a Changing Climate: Polar Regions. Here, we describe the state of the science regarding mechanisms and factors that influence aquatic C and hydrologic responses to permafrost thaw. Through synthesis of recent topical field and modeling studies and evaluation of influential landscape characteristics, we present a framework for assessing vulnerabilities of northern permafrost landscapes to specific modes of thaw affecting local to regional hydrology and aquatic C biogeochemistry and transport. Lastly, we discuss scaling challenges relevant to model prediction of these impacts in heterogeneous permafrost landscapes.
","language":"English","publisher":"Frontiers Media","doi":"10.3389/fclim.2021.730402","usgsCitation":"Walvoord, M.A., and Striegl, R.G., 2021, Complex vulnerabilities of the water and aquatic carbon cycles to permafrost thaw: Frontiers in Climate, v. 3, 730402, 15 p., https://doi.org/10.3389/fclim.2021.730402.","productDescription":"730402, 15 p.","ipdsId":"IP-131645","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":450550,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fclim.2021.730402","text":"Publisher Index Page"},{"id":390316,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, Russia, United States","otherGeospatial":"Arctic","volume":"3","noUsgsAuthors":false,"publicationDate":"2021-10-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Walvoord, Michelle A. 0000-0003-4269-8366","orcid":"https://orcid.org/0000-0003-4269-8366","contributorId":211843,"corporation":false,"usgs":true,"family":"Walvoord","given":"Michelle","email":"","middleInitial":"A.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":824775,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Striegl, Robert G. 0000-0002-8251-4659 rstriegl@usgs.gov","orcid":"https://orcid.org/0000-0002-8251-4659","contributorId":1630,"corporation":false,"usgs":true,"family":"Striegl","given":"Robert","email":"rstriegl@usgs.gov","middleInitial":"G.","affiliations":[{"id":36183,"text":"Hydro-Ecological Interactions Branch","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},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":false,"id":824776,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70224912,"text":"sim3479 - 2021 - Vulnerability assessment in and near Theodore Roosevelt National Park, North Dakota","interactions":[],"lastModifiedDate":"2021-10-05T11:46:21.743463","indexId":"sim3479","displayToPublicDate":"2021-10-04T14:44:17","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3479","displayTitle":"Vulnerability Assessment in and near Theodore Roosevelt National Park, North Dakota","title":"Vulnerability assessment in and near Theodore Roosevelt National Park, North Dakota","docAbstract":"Theodore Roosevelt National Park is in western North Dakota and was established in 1978 under the National Wilderness Preservation system to preserve and protect the qualities of the North Dakota Badlands, including the wildlife, scenery, and wilderness. The park is made up of three units (North, Elkhorn Ranch, and South) that are connected by the Little Missouri River, which was identified by the National Park Service as a significant resource essential to fulfilling the park's purpose. The development of oil and gas (OG) resources has expanded in the past two decades in the region surrounding Theodore Roosevelt National Park. This expansion of OG development outside park boundaries increases the potential for adverse environmental and economic effects inside the park boundaries, especially for the hydrologic processes within Theodore Roosevelt National Park.
This report assesses the vulnerability of critical components that contribute to supporting plants and wildlife of the Northwestern Great Plains ecological region and Theodore Roosevelt National Park’s mission of preservation. Critical components include land cover, slope, soil saturated hydraulic conductivity, distance to Ovis canadensis (Shaw, 1804) (bighorn sheep) critical habitat, distance to springs, distance to rivers and streams, and distance to surficial aquifers. The study area included all the 12-digit hydrologic units within the watershed boundary dataset that intersect Theodore Roosevelt National Park or are within the 12-digit hydrologic units for Little Missouri River tributaries that flow into the park. Critical components that had existing publicly available geographic data were assessed and assigned vulnerability index values. These values were then summed to develop a vulnerability score and mapped. OG development and associated transportation infrastructure, referred to as “stressors” in this report, with publicly available geographic data were mapped, and then flow paths were generated starting from the stressor locations to assess their likelihood to contaminate vulnerable areas within the study area.
The North Unit had the most area with moderate, high, and very high vulnerability. These areas occurred all across the southern and eastern parts of the North Unit where the Little Missouri River, surficial aquifer, wetland type land covers, and bighorn sheep critical habitat are present. Several stressor flow paths from pipelines and highways cross these areas and may pose the most risk to the vulnerable areas identified. In the Elkhorn Ranch Unit, areas with moderate, high, and very high vulnerability were in the southeastern part of the unit, where the Little Missouri River, surficial aquifer, wetland type land covers, and bighorn sheep critical habitat are present. The stressor flow paths in the Elkhorn Ranch Unit follow the length of the Little Missouri River and all its tributaries in the study area. The stressor flow paths originated from crude oil wells and pipelines. In the South Unit, one area had moderate, high, and very high vulnerability. This area is where the Little Missouri River and bighorn sheep critical range are present. The stressor flow paths in the South Unit follow the length of the Little Missouri River and nearly all its tributaries in the study area. Several stressor flow paths cross the one identified vulnerable area that originated from crude oil wells.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3479","collaboration":"Prepared in cooperation with the Inland Oil Spill Preparedness Project","usgsCitation":"Valseth, K.J., 2021, Vulnerability assessment in and near Theodore Roosevelt National Park, North Dakota: U.S. Geological Survey Scientific Investigations Map 3479, pamphlet 9 p., 1 sheet, https://doi.org/10.3133/sim3479.","productDescription":"Pamphlet: vi, 9 p.; 1 Sheet: 23.50 x 31.10 inches; Dataset","numberOfPages":"18","onlineOnly":"Y","ipdsId":"IP-122274","costCenters":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"links":[{"id":390167,"rank":3,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3479/sim3479_sheet1.pdf","text":"Sheet 1","size":"9.56 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3479 Sheet 1"},{"id":390169,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sim/3479/sim3479.xml","size":"53.7 kB","linkFileType":{"id":8,"text":"xml"},"description":"SIM 3479 Pamphlet xml"},{"id":390165,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3479/coverthb.jpg"},{"id":390168,"rank":4,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"U.S. Geological Survey National Water Information System database","description":"USGS Dataset","linkHelpText":"— USGS water data for the Nation"},{"id":390166,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3479/sim3479_pamphlet.pdf","text":"Report","size":"2.50 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3479 Pamphlet"},{"id":390170,"rank":6,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sim/3479/images"}],"country":"United States","state":"North Dakota","otherGeospatial":"Theodore Roosevelt National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -103.72467041015625,\n 46.751153008636884\n ],\n [\n -103.14788818359375,\n 46.751153008636884\n ],\n [\n -103.14788818359375,\n 47.11873795272715\n ],\n [\n -103.72467041015625,\n 47.11873795272715\n ],\n [\n -103.72467041015625,\n 46.751153008636884\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Dakota Water Science Center
U.S. Geological Survey
821 East Interstate Avenue
Bismarck, ND 58503
1608 Mountain View Road
Rapid City, SD 57702
In 1999, a jet-fuels release was discovered at the Bulk Fuels Facility on Kirtland Air Force Base, Albuquerque, New Mexico. Contaminants had reached the water table and migrated north-northeast toward water-supply wells. Monitoring wells were installed downgradient from the facility to determine the primary zones of groundwater production for water-supply wells and assess contaminant presence. The monitoring wells are screened within the Santa Fe Group aquifer system, which includes clay units, at depths as great as 445 meters below land surface, and were categorized as water table, shallow, middle, deep, and aquifer-test pumping wells. Water-supply wells are screened across multiple water-bearing units within the aquifer system. All wells were sampled for major ions, trace elements, nutrients, stable isotopes, dissolved gases, tritium, carbon isotopes, and chlorofluorocarbons. The deeper and water-supply wells have evidence of longer groundwater residence times, as much as thousands of years, and water from the shallower wells shows evidence of anthropogenic nutrient inputs. Aquifer recharge is derived from either the mountain front or seepage from the Rio Grande. Dissolved-gas data indicate that the middle, deep, and aquifer-test pumping, and water-supply wells have cooler recharge temperatures than the shallower wells. Inferred groundwater age varies by method but indicates that the deeper, aquifer-test pumping, and water-supply wells have older water, as much as 15,000 years before present. Results indicate that the water-supply wells draw primarily from the middle and deeper portions of the aquifer system below the clay units and have not been affected by the contaminant plume, although some data indicate a potential for modern water entering some of the deeper and water-supply wells.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215076","collaboration":"Prepared in cooperation with the Air Force Civil Engineer Center","usgsCitation":"Travis, R.E., Bell, M.T., Linhoff, B.S., and Beisner, K.R., 2021, Utilizing multiple hydrogeologic and anthropogenic indicators to understand zones of groundwater contribution to water-supply wells near Kirtland Air Force Base Bulk Fuels Facility in southeast Albuquerque, New Mexico: U.S. Geological Survey Scientific Investigations Report 2021–5076, 28 p., https://doi.org/10.3133/sir20215076.","productDescription":"Report: viii, 28 p.; Data Release; Dataset","numberOfPages":"40","onlineOnly":"Y","ipdsId":"IP-120223","costCenters":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"links":[{"id":390163,"rank":5,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"U.S. Geological Survey National Water Information System database","description":"USGS Dataset","linkHelpText":"— USGS water data for the Nation"},{"id":389636,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5076/coverthb.jpg"},{"id":389637,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5076/sir20215076.pdf","text":"Report","size":"3.35 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021–5076"},{"id":389638,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7NV9HHG","text":"USGS Data Release","description":"USGS Data Release","linkHelpText":"Description of groundwater monitoring wells installed at and near Kirtland Air Force Base, Albuquerque, New Mexico, 2013–2016 (ver. 1.2, May 2019)"},{"id":389639,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2021/5076/images/"}],"country":"United States","state":"New Mexico","city":"Albuquerque","otherGeospatial":"Kirtland Air Force Base","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -106.69097900390625,\n 34.89156324823376\n ],\n [\n -106.43692016601562,\n 34.90170042871546\n ],\n [\n -106.4410400390625,\n 35.081707990840705\n ],\n [\n -106.68823242187499,\n 35.068221159859256\n ],\n [\n -106.69097900390625,\n 34.89156324823376\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New Mexico Water Science Center
U.S. Geological Survey
6700 Edith Blvd. NE
Albuquerque, NM 87113
The increasing incidence of wildfires across the southwestern United States (US) is altering the contemporary forest management template within historically frequent-fire conifer forests. An increasing fraction of southwestern conifer forests have recently burned, and many of these burned landscapes contain complex mosaics of surviving forest and severely burned patches without surviving conifer trees. These heterogeneous burned landscapes present unique social and ecological challenges. Severely burned patches can present numerous barriers to successful conifer regeneration, and often contain heavy downed fuels which have cascading effects on future fire behavior and conifer regeneration. Conversely, surviving forest patches are increasingly recognized for their value in postfire reforestation but often are overlooked from a management perspective.
Here we present a decision-making framework for landscape-scale management of complex postfire landscapes that allows for adaptation to a warming climate and future fire. We focus specifically on historically frequent-fire forests of the southwestern US but make connections to other forest types and other regions. Our framework depends on a spatially-explicit assessment of the mosaic of conifer forest and severely burned patches in the postfire landscape, evaluates likely vegetation trajectories, and identifies critical decision points to direct vegetation change via manipulations of fuels and live vegetation. This framework includes detailed considerations for postfire fuels management (e.g., edge hardening within live forest patches and repeat burning) and for reforestation (e.g., balancing tradeoffs between intensive and extensive planting strategies, establishing patches of seed trees, spatial planning to optimize reforestation success, and improving nursery capacity). In a future of increasing fire activity in forests where repeated low- to moderate-severity fire is essential to ecosystem resilience, the decision-making framework developed here can easily be integrated with existing postfire management strategies to optimize allocation of limited resources and more actively manage burned landscapes.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.foreco.2021.119678","usgsCitation":"Stevens, J., Haffey, C., Coop, J.D., Fornwalt, P.J., Yocom, L., Allen, C., Bradley, A., Burney, O.T., Carril, D., Chambers, M.E., Chapman, T.B., Haire, S.L., Hurteau, M., Iniguez, J.M., Margolis, E.Q., Marks, C., Marshall, L., Rodman, K., Stevens-Rumann, C.S., Thode, A., and Walker, J., 2021, Tamm review: Postfire landscape management in frequent-fire conifer forests of the southwestern United States: Forest Ecology and Management, v. 502, 119678, 21 p., https://doi.org/10.1016/j.foreco.2021.119678.","productDescription":"119678, 21 p.","ipdsId":"IP-130297","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":450553,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.foreco.2021.119678","text":"Publisher Index 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We investigated the effects of hypoxia, temperature (with acclimation), nitrogenous chemical compounds, and chloride on Topeka shiners (Notropis topeka) by monitoring behavioral responses to a reduction in oxygen and, using swimming speed, determining thermal optima and onset of effect for concentrations of nitrogenous compounds and chloride. We found ASR50 (i.e., dissolved oxygen concentrations where 50% of fish use aquatic surface respiration) to be 1.65 mg/L and ASR90 to be 1.08 mg/L of dissolved oxygen. Optimum temperatures for the species ranged from 17.7 to 28.0 °C, while predicted 100% mortality ranged from 33.7 to 40.3 °C, depending on the temperature at which fish were acclimated prior to experiments. Ammonia and sodium chloride reduced swimming speed at concentrations below known LC50 values, while nitrite concentrations did not correspond with swimming speed, but rather, post-experiment mortality. This provides insight into where Topeka shiners can not only persist, but also thrive. Although swimming speed may not be a suitable metric for determining the effects of all contaminants, our focus on optima and sub-lethal effects over tolerance allows selections of the most suitable reintroduction site matching the species’ physiological profile.
","language":"English","publisher":"Springer Link","doi":"10.1007/s10641-021-01148-x","usgsCitation":"Rosenberger, A.E., and Mott, R.T., 2021, Use of non-lethal endpoints to establish water quality requirements and optima of the endangered Topeka shiner (Notropis topeka): Environmental Biology of Fishes, v. 104, p. 1215-1233, https://doi.org/10.1007/s10641-021-01148-x.","productDescription":"19 p.","startPage":"1215","endPage":"1233","ipdsId":"IP-096850","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":450558,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10641-021-01148-x","text":"Publisher Index Page"},{"id":395357,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"104","noUsgsAuthors":false,"publicationDate":"2021-10-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Rosenberger, Amanda E. 0000-0002-5520-8349 arosenberger@usgs.gov","orcid":"https://orcid.org/0000-0002-5520-8349","contributorId":5581,"corporation":false,"usgs":true,"family":"Rosenberger","given":"Amanda","email":"arosenberger@usgs.gov","middleInitial":"E.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":396,"text":"Missouri Water Science Center","active":true,"usgs":true}],"preferred":true,"id":832952,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mott, Rory T.","contributorId":274385,"corporation":false,"usgs":false,"family":"Mott","given":"Rory","email":"","middleInitial":"T.","affiliations":[{"id":6754,"text":"University of Missouri","active":true,"usgs":false}],"preferred":false,"id":832953,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70231618,"text":"70231618 - 2021 - Fire and forests in the 21st century: Managing resilience under changing climates and fire regimes in USA forests","interactions":[],"lastModifiedDate":"2022-05-17T14:31:15.893631","indexId":"70231618","displayToPublicDate":"2021-10-02T09:25:04","publicationYear":"2021","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Fire and forests in the 21st century: Managing resilience under changing climates and fire regimes in USA forests","docAbstract":"Higher temperatures, lower snowpacks, drought, and extended dry periods have contributed to increased wildfire activity in recent decades. Climate change is expected to increase the frequency of large fires, the cumulative area burned, and fire suppression costs and risks in many areas of the USA. Fire regimes are likely to change due to interactions among climate, fire, and other stressors and disturbances; resulting in persistent changes in forest structure and function. The remainder of the twenty-first century will present substantial challenges, as natural resource managers are faced with higher fire risk and the difficult task of maintaining ecological function in a rapidly changing biophysical and social landscape. Fuel treatments will continue to be important for minimizing the undesirable ecological effects of fire, and for enhancing firefighter safety; however, treatments must be implemented strategically across large areas. Collaboration among agencies, private landowners, and other organizations will be critical for ensuring resilience and sustainable forest management.
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This survey was carried out to detect the distribution of faults near the gas hydrate research well (Stratigraphic Test Well: Hydrate-01) on the North Slope of Alaska within the Prudhoe Bay Unit (PBU). The data were recorded with a single-mode DAS cable which is permanently installed and cemented behind the casing of the Hydrate-01 well. A total of 1701 shot records were successfully acquired in 12 days using a DAS interrogator with two vibroseis sources. The data were converted from strain rate to a geophone equivalent for further data processing. Traveltime tomography was carried out using the first break of each shot and was used to build a 3D tilted transverse isotropy (TTI) velocity model. The data were processed with a sequence designed to produce a precise and high resolution P wave image, that included editing, redatum, band pass filtering, denoise, upgoing / downgoing wavefield separation, deconvolution and migration. Faults around the Hydrate-01 were interpreted using the 3DVSP volume and its attributes. These faults were clearly observed in the 3DVSP volume but they cannot be recognized by an existing 3D surface seismic volume.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of the 14th SEGJ International Symposium","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceDate":"October 18-21, 2021","language":"English","publisher":"SEG","doi":"10.1190/segj2021-006.1","usgsCitation":"Fujimoto, A., Lim, T.K., Tamaki, M., Kawaguchi, K., Kobayashi, T., Haines, S.S., Collett, T., and Boswell, R., 2021, DAS 3DVSP survey at Stratigraphic Test Well (Hydrate-01), in Proceedings of the 14th SEGJ International Symposium, October 18-21, 2021, p. 19-22, https://doi.org/10.1190/segj2021-006.1.","productDescription":"4 p.","startPage":"19","endPage":"22","ipdsId":"IP-129862","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":421461,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationDate":"2021-11-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Fujimoto, Akira","contributorId":330380,"corporation":false,"usgs":false,"family":"Fujimoto","given":"Akira","affiliations":[{"id":39359,"text":"JOGMEC","active":true,"usgs":false}],"preferred":false,"id":884811,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lim, Teck Kean","contributorId":330382,"corporation":false,"usgs":false,"family":"Lim","given":"Teck","email":"","middleInitial":"Kean","affiliations":[{"id":48092,"text":"TOYO Engineering","active":true,"usgs":false}],"preferred":false,"id":884812,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tamaki, Machiko","contributorId":330384,"corporation":false,"usgs":false,"family":"Tamaki","given":"Machiko","affiliations":[{"id":78875,"text":"JOE Co.","active":true,"usgs":false}],"preferred":false,"id":884813,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kawaguchi, Kyojiro","contributorId":330385,"corporation":false,"usgs":false,"family":"Kawaguchi","given":"Kyojiro","email":"","affiliations":[{"id":48092,"text":"TOYO Engineering","active":true,"usgs":false}],"preferred":false,"id":884814,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kobayashi, Toshiaki","contributorId":330387,"corporation":false,"usgs":false,"family":"Kobayashi","given":"Toshiaki","email":"","affiliations":[{"id":39359,"text":"JOGMEC","active":true,"usgs":false}],"preferred":false,"id":884815,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Haines, Seth S. 0000-0003-2611-8165 shaines@usgs.gov","orcid":"https://orcid.org/0000-0003-2611-8165","contributorId":1344,"corporation":false,"usgs":true,"family":"Haines","given":"Seth","email":"shaines@usgs.gov","middleInitial":"S.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":884816,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Collett, Timothy 0000-0002-7598-4708","orcid":"https://orcid.org/0000-0002-7598-4708","contributorId":220812,"corporation":false,"usgs":true,"family":"Collett","given":"Timothy","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":884817,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Boswell, Ray","contributorId":330389,"corporation":false,"usgs":false,"family":"Boswell","given":"Ray","affiliations":[{"id":78878,"text":"DOE NETL","active":true,"usgs":false}],"preferred":false,"id":884818,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70241791,"text":"70241791 - 2021 - Resilience of native amphibian communities following catastrophic drought: Evidence from a decade of regional-scale monitoring","interactions":[],"lastModifiedDate":"2023-03-27T12:05:50.759272","indexId":"70241791","displayToPublicDate":"2021-10-02T07:03:17","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1015,"text":"Biological Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Resilience of native amphibian communities following catastrophic drought: Evidence from a decade of regional-scale monitoring","docAbstract":"The increasing frequency and severity of drought may exacerbate ongoing global amphibian declines. However, interactions between drought and coincident stressors, coupled with high interannual variability in amphibian abundances, can mask the extent and underlying mechanisms of drought impacts. We synthesized a decade (2009–2019) of regional-scale amphibian monitoring data (2273 surveys, 233 ponds, and seven species) from across California's Bay Area and used dynamic occupancy modeling to estimate trends and drivers of species occupancy. An extreme drought during the study period resulted in substantial habitat loss, with 51% of ponds drying in the worst year of drought, compared to <20% in pre-drought years. Nearly every species exhibited reduced breeding activity during the drought, with the occupancy of some species (American bullfrogs and California newts) declining by >25%. Invasive fishes and bullfrogs were also associated with reduced amphibian occupancy, and these taxa were locally extirpated from numerous sites during drought, without subsequent recovery– suggesting that drought may present an opportunity to remove invaders. Despite a historic, multi-year drought, native amphibians rebounded quickly to pre-drought occupancy levels, demonstrating evidence of resilience. Permanent waterbodies supported higher persistence of native species during drought years than did temporary waterbodies, and we therefore highlight the value of hydroperiod diversity in promoting amphibian stability.
Migratory amphibians are at high risk of negative impacts when roads intersect their upland and breeding habitats. Road mortality can reduce population abundance, survivorship, breeding, recruitment, and probability of long-term persistence. Increasingly, environmental planners recommend installation of under-road tunnels with barrier fencing to reduce mortality and direct amphibians towards the passages. Often, the permeability of these barrier and passage systems to amphibian population movements are unknown. We studied the movements of California tiger salamanders (CTS: Ambystoma californiense) in relation to solid and mesh barrier fencing attached to a 3-tunnel system between upland and breeding habitats in Stanford, California. We deployed active-trigger cameras along the fencing, used pattern recognition software to identify individuals by their unique spot patterns, and calculated individual salamander movement distances, speed, direction changes, and “success” at reaching the tunnel system. We found that migrating adult CTS moved an average of 40 m along barrier fencing before turning back into the habitat or “giving-up”. This short distance, in comparison to long migratory movements, may be explained by the orientation mechanisms salamanders use to reach their breeding sites. The probability CTS found a passage decreased rapidly with increasing distance from the tunnel system, particularly if individuals turned the “wrong” way after encountering the fence. Salamanders changed directions more often and spent more time along mesh fencing. Our results suggest that a maximum of 12.5 m between passages along CTS migration routes should allow approximately 90% of adult salamanders to encounter road crossings. Additionally, use of solid fencing or a visual barrier on mesh fencing may help to lead salamanders to passages most efficiently. These considerations can assist those seeking to design effective road mitigation for CTS and other migratory amphibians.
No abstract available.
","language":"English","publisher":"The Denver Well Logging Society","usgsCitation":"Lagesse, J.H., 2021, The Denver Well Logging Society October 2021 Newsletter: From the VP - Technology: Denver Well Drilling Society Newsletter, no. October 2021, HTML Document.","productDescription":"HTML Document","ipdsId":"IP-133854","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":394319,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":394318,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://dwls.spwla.org/2021-10-Newsletter.html"}],"issue":"October 2021","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Lagesse, Jenny H. 0000-0002-3541-4751","orcid":"https://orcid.org/0000-0002-3541-4751","contributorId":248367,"corporation":false,"usgs":true,"family":"Lagesse","given":"Jenny","email":"","middleInitial":"H.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":825652,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70226666,"text":"70226666 - 2021 - Living with wildfire in Chalk Creek, Chaffee County, Colorado: 2019 data report","interactions":[],"lastModifiedDate":"2021-12-02T17:40:14.924197","indexId":"70226666","displayToPublicDate":"2021-10-01T11:39:36","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":72,"text":"Research Note","active":false,"publicationSubtype":{"id":1}},"seriesNumber":"90","title":"Living with wildfire in Chalk Creek, Chaffee County, Colorado: 2019 data report","docAbstract":"Wildfire affects many types of communities and is a particular concern for communities in the wildland urban interface (WUI), such as Chalk Creek in Chaffee County. The core intent of this project was to provide evidence to support Colorado State Forest Service (CSFS) Salida Field Office’s wildfire mitigation and education program. This report analyzes existing wildfire risk data collected in late 2017 through 2019 and pairs it with social data collected in the summer of 2019, in order to better understand Chalk Creek residents’ knowledge, experiences, and perceptions about wildfire risk. This greater understanding will help CSFS focus its programs and outreach and ultimately promote increased mitigation and reduced wildfire risk in Chalk Creek.
","language":"English","publisher":"USDA Forest Service, Rocky Mountain Research Station","doi":"10.2737/RMRS-RN-90","usgsCitation":"Champ, P.A., Goolsby, J.B., Shaver, J.T., Kuehn, J., Meldrum, J., Brenkert-Smith, H., Barth, C.M., Donovan, C., and Wagner, C., 2021, Living with wildfire in Chalk Creek, Chaffee County, Colorado: 2019 data report: Research Note 90, 81 p., https://doi.org/10.2737/RMRS-RN-90.","productDescription":"81 p.","ipdsId":"IP-126221","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":392385,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":392368,"type":{"id":15,"text":"Index Page"},"url":"https://www.fs.usda.gov/treesearch/pubs/63542"}],"country":"United States","state":"Colorado","county":"Chaffee County","otherGeospatial":"Chalk Creek","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -106.37683868408202,\n 38.67398509885878\n ],\n [\n -106.1282730102539,\n 38.67398509885878\n ],\n [\n -106.1282730102539,\n 38.75408327579141\n ],\n [\n -106.37683868408202,\n 38.75408327579141\n ],\n [\n -106.37683868408202,\n 38.67398509885878\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationDate":"2021-12-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Champ, Patricia A.","contributorId":195486,"corporation":false,"usgs":false,"family":"Champ","given":"Patricia","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":827607,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Goolsby, Julia B. 0000-0002-2229-5685","orcid":"https://orcid.org/0000-0002-2229-5685","contributorId":269631,"corporation":false,"usgs":true,"family":"Goolsby","given":"Julia","email":"","middleInitial":"B.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":827608,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shaver, J. T.","contributorId":269632,"corporation":false,"usgs":false,"family":"Shaver","given":"J.","email":"","middleInitial":"T.","affiliations":[{"id":56021,"text":"Colorado State Forest Service","active":true,"usgs":false}],"preferred":false,"id":827609,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kuehn, Josh","contributorId":269634,"corporation":false,"usgs":false,"family":"Kuehn","given":"Josh","email":"","affiliations":[{"id":56021,"text":"Colorado State Forest Service","active":true,"usgs":false}],"preferred":false,"id":827610,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Meldrum, James R. 0000-0001-5250-3759 jmeldrum@usgs.gov","orcid":"https://orcid.org/0000-0001-5250-3759","contributorId":195484,"corporation":false,"usgs":true,"family":"Meldrum","given":"James","email":"jmeldrum@usgs.gov","middleInitial":"R.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":827611,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Brenkert-Smith, Hannah 0000-0001-6117-8863","orcid":"https://orcid.org/0000-0001-6117-8863","contributorId":195485,"corporation":false,"usgs":false,"family":"Brenkert-Smith","given":"Hannah","email":"","affiliations":[],"preferred":false,"id":827612,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Barth, Christopher M.","contributorId":195487,"corporation":false,"usgs":false,"family":"Barth","given":"Christopher","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":827613,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Donovan, Colleen","contributorId":240586,"corporation":false,"usgs":false,"family":"Donovan","given":"Colleen","email":"","affiliations":[{"id":48103,"text":"Wildfire Research (WiRē) Center","active":true,"usgs":false}],"preferred":false,"id":827614,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Wagner, Carolyn","contributorId":240587,"corporation":false,"usgs":false,"family":"Wagner","given":"Carolyn","affiliations":[{"id":48103,"text":"Wildfire Research (WiRē) Center","active":true,"usgs":false}],"preferred":false,"id":827615,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70225661,"text":"70225661 - 2021 - Use of an artificial stream to monitor avoidance behavior of larval sea lamprey in response to TFM and niclosamide","interactions":[],"lastModifiedDate":"2022-04-21T16:24:56.291786","indexId":"70225661","displayToPublicDate":"2021-10-01T11:21:20","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":3,"text":"Organization Series"},"seriesTitle":{"id":7568,"text":"Project Completion Report","active":true,"publicationSubtype":{"id":3}},"title":"Use of an artificial stream to monitor avoidance behavior of larval sea lamprey in response to TFM and niclosamide","docAbstract":"The lampricide 3-trifluoromethyl-4-nitrophenol (TFM) has been used in liquid form to control larval sea lamprey (Petromyzon marinus) in Great Lakes tributaries since the late 1950s. In the 1980s a dissolvable TFM bar was developed as a supplemental tool for application to small tributaries as a deterrent to larvae seeking water not activated with TFM. The size, mass, and number of bars needed in some streams, as well as the location of the streams, limit the utility of a TFM bar. The development and use of an alternative niclosamide bar has the potential to use fewer bars to achieve similar results. However, the use of a niclosamide bar is dependent upon its larval deterrent capability compared to the TFM bar. In this study, we developed a laboratory-scale, simulated stream fluvarium with several avoidance areas including two side channels and a seep. The objective was to evaluate the deterrent capabilities of TFM and niclosamide. We found sea lamprey to have similar behavioral responses, with both TFM and niclosamide having similar capabilities to prevent sea lamprey from seeking refuge in side channels and seep avoidance areas. TFM-treated side channels and seep increased sea lamprey occupancy in the main channel 2.56 times more than the untreated-controls (95% CI 1.63 – 4.14) whereas niclosamide-treated side channels and seep increased sea lamprey occupancy of the main channel 2.68 times more than the untreated-controls (95% CI 1.72 – 4.32). These responses indicate a niclosamide bar would effectively prevent sea lamprey escapement into freshwater during a lampricide treatment at concentrations unlikely to harm aquatic organisms.
","language":"English","publisher":"Great Lakes Fishery Commission","usgsCitation":"Schloesser, N., Boogaard, M.A., Johnson, T., Kirkeeng, C., Schueller, J., and Erickson, R.A., 2021, Use of an artificial stream to monitor avoidance behavior of larval sea lamprey in response to TFM and niclosamide: Project Completion Report, 3 p.","productDescription":"3 p.","ipdsId":"IP-130111","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":399404,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":399403,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.glfc.org/"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"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":826092,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Boogaard, Michael A. 0000-0002-5192-8437 mboogaard@usgs.gov","orcid":"https://orcid.org/0000-0002-5192-8437","contributorId":865,"corporation":false,"usgs":true,"family":"Boogaard","given":"Michael","email":"mboogaard@usgs.gov","middleInitial":"A.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":826093,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Johnson, Todd 0000-0003-2152-8528","orcid":"https://orcid.org/0000-0003-2152-8528","contributorId":261519,"corporation":false,"usgs":true,"family":"Johnson","given":"Todd","email":"","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":826094,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kirkeeng, Courtney A. 0000-0002-7141-1216","orcid":"https://orcid.org/0000-0002-7141-1216","contributorId":237026,"corporation":false,"usgs":true,"family":"Kirkeeng","given":"Courtney","middleInitial":"A.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":826095,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"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":841215,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Erickson, Richard A. 0000-0003-4649-482X rerickson@usgs.gov","orcid":"https://orcid.org/0000-0003-4649-482X","contributorId":5455,"corporation":false,"usgs":true,"family":"Erickson","given":"Richard","email":"rerickson@usgs.gov","middleInitial":"A.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":826097,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70224571,"text":"sir20215047 - 2021 - Delineation of areas contributing groundwater and travel times to receiving waters in Kings, Queens, Nassau, and Suffolk Counties, New York","interactions":[],"lastModifiedDate":"2021-10-04T11:40:48.101196","indexId":"sir20215047","displayToPublicDate":"2021-10-01T11:00:00","publicationYear":"2021","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":"2021-5047","displayTitle":"Delineation of Areas Contributing Groundwater and Travel Times to Receiving Waters in Kings, Queens, Nassau, and Suffolk Counties, New York","title":"Delineation of areas contributing groundwater and travel times to receiving waters in Kings, Queens, Nassau, and Suffolk Counties, New York","docAbstract":"To assist resource managers and planners in developing informed strategies to address nitrogen loading to coastal water bodies of Long Island, New York, the U.S. Geological Survey and New York State Department of Environmental Conservation initiated a program to delineate areas contributing groundwater to coastal water bodies by assembling a comprehensive dataset of areas contributing groundwater, travel times, and groundwater discharges to streams, lakes, marine surface waters, and subsea discharge boundaries. Steady-state, 25-layer regional, three-dimensional finite-difference groundwater-flow models of average regional hydrologic conditions were used for particle-tracking analysis to delineate areas contributing groundwater to 843 water bodies. Two steady-state conditions were simulated: recent conditions from 2005 to 2015 and predevelopment conditions of about 1900. About 14 million particles were evenly distributed across the water table and tracked forward to discharge zones. Using a uniform porosity of 25 percent, simulated recent condition travel times ranged from less than 2 years to greater than 10,000 years and were visualized in 11 travel time intervals. About 85 percent of particle travel times from the water table to points of discharge are less than 100 years. Simulated particle-tracking ending zones represented 843 receiving water bodies, based on the New York State Department of Environmental Conservation water body inventory and priority water bodies list. Areal delineation of travel-time intervals and areas contributing groundwater to water bodies were generated and are summarized with total groundwater outflow for each water body.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215047","collaboration":"Prepared in cooperation with the New York State Department of Environmental Conservation","usgsCitation":"Misut, P.E., Casamassina, N.A., and Walter, D.A., 2021, Delineation of areas contributing groundwater and travel times to receiving waters in Kings, Queens, Nassau, and Suffolk Counties, New York: U.S. Geological Survey Scientific Investigations Report 2021–5047, 61 p., https://doi.org/10.3133/sir20215047.","productDescription":"Report: iv, 61 p.; 3 Tables; Data Release","numberOfPages":"61","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-108532","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":389890,"rank":8,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2021/5047/sir20215047_table1.3.csv","text":"Table 1.3","size":"27.5 KB","linkFileType":{"id":7,"text":"csv"},"linkHelpText":"- Marine subsystems, estuaries, and number of receiving water bodies on Long Island, New York, associated with New York State priority water bodies"},{"id":389888,"rank":6,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2021/5047/sir20215047_table1.1.csv","text":"Table 1.1","size":"12.2 KB","linkFileType":{"id":7,"text":"csv"},"linkHelpText":"- Association of receiving water body index to New York State priority water body list database for water bodies on Long Island, New York"},{"id":389874,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2021/5047/sir20215047.XML"},{"id":389876,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9DKILJY","text":"USGS data release","linkHelpText":"MODFLOW–NWT and MODPATH6 used to delineate areas contributing groundwater and travel times to receiving waters of Kings, Queens, Nassau, and Suffolk Counties, New York"},{"id":389889,"rank":7,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2021/5047/sir20215047_table1.2.csv","text":"Table 1.2","size":"9.48 KB","linkFileType":{"id":7,"text":"csv"},"linkHelpText":"- Sum of groundwater outflows to receiving water bodies simulated by a flow model of regional hydrologic conditions from 2005 to 2015 for Long Island, New York"},{"id":389875,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2021/5047/images/"},{"id":389872,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5047/sir20215047.pdf","text":"Report","size":"92.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021-5047"},{"id":389871,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5047/coverthb2.jpg"}],"country":"United States","state":"New York","county":"Kings County, Queens County, Nassau County, Suffolk County","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -74.20166015624999,\n 40.51379915504413\n ],\n [\n -71.7572021484375,\n 40.51379915504413\n ],\n [\n -71.7572021484375,\n 41.21998578493921\n ],\n [\n -74.20166015624999,\n 41.21998578493921\n ],\n [\n -74.20166015624999,\n 40.51379915504413\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New York Water Science Center
U.S. Geological Survey
425 Jordan Road
Troy, NY 12180–8349