Many metrics exist for quantifying the relative value of habitats and pathways used by highly mobile species. Properly selecting and applying such metrics requires substantial background in mathematics and understanding the relevant management arena. To address this multidimensional challenge, we demonstrate and compare three measurements of habitat quality: graph-, occupancy-, and demographic-based metrics. Each metric provides insights into system dynamics, at the expense of increasing amounts and complexity of data and models. Our descriptions and comparisons of diverse habitat-quality metrics provide means for practitioners to overcome the modeling challenges associated with management or conservation of such highly mobile species. Whereas previous guidance for applying habitat-quality metrics has been scattered in diversified tracks of literature, we have brought this information together into an approachable format including accessible descriptions and a modeling case study for a typical example that conservation professionals can adapt for their own decision contexts and focal populations.
Considerations for Resource Managers
Globally, hydrologic modifications such as ditching and subsurface drainage have significantly reduced wetland water storage capacity (i.e., volume of surface water a wetland can retain) and consequent wetland functions. While wetland area has been well documented across many landscapes and used to guide restoration efforts, few studies have directly quantified the associated wetland storage capacity. Here, we present a novel raster-based approach to quantify both contemporary and potential (i.e., restorable) storage capacities of individual depressional basins across landscapes. We demonstrate the utility of this method by applying it to the Delmarva Peninsula, a region punctuated by both depressional wetlands and drainage ditches. Across the entire peninsula, we estimated that restoration (i.e., plugging ditches) could increase storage capacity by 80%. Focusing on an individual watershed, we found that over 59% of restorable storage capacity occurs within 20 m of the drainage network, and that 93% occurs within 1 m elevation of the drainage network. Our demonstration highlights widespread ditching in this landscape, spatial patterns of both contemporary and potential storage capacities, and clear opportunities for hydrologic restoration. In Delmarva and more broadly, our novel approach can inform targeted landscape-scale conservation and restoration efforts to optimize hydrologically mediated wetland functions.
","language":"English","publisher":"Wiley","doi":"10.1002/hyp.11405","usgsCitation":"Jones, C.N., Evenson, G.R., McLaughlin, D.L., Vanderhoof, M.K., Lang, M.W., McCarty, G.W., Golden, H.E., Lane, C., and Alexander, L., 2018, Estimating restorable wetland water storage at landscape scales: Hydrological Processes, v. 32, no. 2, p. 305-313, https://doi.org/10.1002/hyp.11405.","productDescription":"9 p.","startPage":"305","endPage":"313","ipdsId":"IP-088286","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":29789,"text":"John Wesley Powell Center for Analysis and Synthesis","active":true,"usgs":true}],"links":[{"id":461079,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/5907502","text":"External Repository"},{"id":351516,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"32","issue":"2","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2017-12-13","publicationStatus":"PW","scienceBaseUri":"5afee751e4b0da30c1bfc22a","contributors":{"authors":[{"text":"Jones, Charles Nathan","contributorId":202421,"corporation":false,"usgs":false,"family":"Jones","given":"Charles","email":"","middleInitial":"Nathan","affiliations":[{"id":36428,"text":"The National Socio-Environmental Synthesis Center, University of Maryland","active":true,"usgs":false}],"preferred":false,"id":728374,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Evenson, Grey R.","contributorId":202422,"corporation":false,"usgs":false,"family":"Evenson","given":"Grey","email":"","middleInitial":"R.","affiliations":[{"id":12694,"text":"Virginia Tech","active":true,"usgs":false}],"preferred":false,"id":728375,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McLaughlin, Daniel L.","contributorId":156435,"corporation":false,"usgs":false,"family":"McLaughlin","given":"Daniel","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":728376,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Vanderhoof, Melanie K. 0000-0002-0101-5533 mvanderhoof@usgs.gov","orcid":"https://orcid.org/0000-0002-0101-5533","contributorId":168395,"corporation":false,"usgs":true,"family":"Vanderhoof","given":"Melanie","email":"mvanderhoof@usgs.gov","middleInitial":"K.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":728373,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lang, Megan W.","contributorId":196284,"corporation":false,"usgs":false,"family":"Lang","given":"Megan","email":"","middleInitial":"W.","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":728377,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"McCarty, Greg W.","contributorId":143675,"corporation":false,"usgs":false,"family":"McCarty","given":"Greg","email":"","middleInitial":"W.","affiliations":[{"id":15298,"text":"USDA-ARS Hydrology and Remote Sensing Laboratory, Bldg 007, BARC-W, 10300 Baltimore Avenue, Beltsville, Maryland 20705, United States","active":true,"usgs":false}],"preferred":false,"id":728378,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Golden, Heather E.","contributorId":202423,"corporation":false,"usgs":false,"family":"Golden","given":"Heather","email":"","middleInitial":"E.","affiliations":[{"id":36429,"text":"USEPA ORD","active":true,"usgs":false}],"preferred":false,"id":728379,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Lane, Charles R.","contributorId":138991,"corporation":false,"usgs":false,"family":"Lane","given":"Charles R.","affiliations":[{"id":6914,"text":"U.S. Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":728380,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Alexander, Laurie C.","contributorId":138989,"corporation":false,"usgs":false,"family":"Alexander","given":"Laurie C.","affiliations":[{"id":6914,"text":"U.S. Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":728381,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70195316,"text":"70195316 - 2018 - Beyond the edge: Linking agricultural landscapes, stream networks, and best management practices","interactions":[],"lastModifiedDate":"2018-02-08T14:48:57","indexId":"70195316","displayToPublicDate":"2018-01-15T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2262,"text":"Journal of Environmental Quality","active":true,"publicationSubtype":{"id":10}},"title":"Beyond the edge: Linking agricultural landscapes, stream networks, and best management practices","docAbstract":"Despite much research and investment into understanding and managing nutrients across agricultural landscapes, nutrient runoff to freshwater ecosystems is still a major concern. We argue there is currently a disconnect between the management of watershed surfaces (agricultural landscape) and river networks (riverine landscape). These landscapes are commonly managed separately, but there is limited cohesiveness between agricultural landscape-focused research and river science, despite similar end goals. Interdisciplinary research into stream networks that drain agricultural landscapes is expanding but is fraught with problems. Conceptual frameworks are useful tools to order phenomena, reveal patterns and processes, and in interdisciplinary river science, enable the joining of multiple areas of understanding into a single conceptual–empirical structure. We present a framework for the interdisciplinary study and management of agricultural and riverine landscapes. The framework includes components of an ecosystems approach to the study of catchment–stream networks, resilience thinking, and strategic adaptive management. Application of the framework is illustrated through a study of the Fox Basin in Wisconsin, USA. To fully realize the goal of nutrient reduction in the basin, we suggest that greater emphasis is needed on where best management practices (BMPs) are used within the spatial context of the combined watershed–stream network system, including BMPs within the river channel. Targeted placement of BMPs throughout the riverine landscape would increase the overall buffering capacity of the system to nutrient runoff and thus its resilience to current and future disturbances.
","language":"English","publisher":"American Society of Agronomy, Crop Science Society of America, & Soil Science Society of America","doi":"10.2134/jeq2017.08.0319","usgsCitation":"Kreiling, R.M., Thoms, M.C., and Richardson, W.B., 2018, Beyond the edge: Linking agricultural landscapes, stream networks, and best management practices: Journal of Environmental Quality, v. 47, p. 42-53, https://doi.org/10.2134/jeq2017.08.0319.","productDescription":"12 p.","startPage":"42","endPage":"53","ipdsId":"IP-088966","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":351379,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"47","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a7d6ffde4b00f54eb2441a3","contributors":{"authors":[{"text":"Kreiling, Rebecca M. 0000-0002-9295-4156 rkreiling@usgs.gov","orcid":"https://orcid.org/0000-0002-9295-4156","contributorId":4234,"corporation":false,"usgs":true,"family":"Kreiling","given":"Rebecca","email":"rkreiling@usgs.gov","middleInitial":"M.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":false,"id":727805,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thoms, Martin C. 0000-0002-8074-0476","orcid":"https://orcid.org/0000-0002-8074-0476","contributorId":145710,"corporation":false,"usgs":false,"family":"Thoms","given":"Martin","email":"","middleInitial":"C.","affiliations":[{"id":16205,"text":"Riverine Landscapes Research Laboratory, University of New England, NSW, Australia","active":true,"usgs":false}],"preferred":false,"id":727806,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Richardson, William B. 0000-0002-7471-4394 wrichardson@usgs.gov","orcid":"https://orcid.org/0000-0002-7471-4394","contributorId":3277,"corporation":false,"usgs":true,"family":"Richardson","given":"William","email":"wrichardson@usgs.gov","middleInitial":"B.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":727807,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70194647,"text":"ofr20171159 - 2018 - Processing of next generation weather radar-multisensor precipitation estimates and quantitative precipitation forecast data for the DuPage County streamflow simulation system","interactions":[],"lastModifiedDate":"2018-01-25T15:19:19","indexId":"ofr20171159","displayToPublicDate":"2018-01-12T13:45:00","publicationYear":"2018","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":"2017-1159","title":"Processing of next generation weather radar-multisensor precipitation estimates and quantitative precipitation forecast data for the DuPage County streamflow simulation system","docAbstract":"The U.S. Geological Survey, in cooperation with DuPage County Stormwater Management Department, is testing a near real-time streamflow simulation system that assists in the management and operation of reservoirs and other flood-control structures in the Salt Creek and West Branch DuPage River drainage basins in DuPage County, Illinois. As part of this effort, the U.S. Geological Survey maintains a database of hourly meteorological and hydrologic data for use in this near real-time streamflow simulation system. Among these data are next generation weather radar-multisensor precipitation estimates and quantitative precipitation forecast data, which are retrieved from the North Central River Forecasting Center of the National Weather Service. The DuPage County streamflow simulation system uses these quantitative precipitation forecast data to create streamflow predictions for the two simulated drainage basins. This report discusses in detail how these data are processed for inclusion in the Watershed Data Management files used in the streamflow simulation system for the Salt Creek and West Branch DuPage River drainage basins.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171159","collaboration":"Prepared in cooperation with the DuPage County Stormwater Management Department","usgsCitation":"Bera, Maitreyee, and Ortel, T.W., 2018, Processing of next generation weather radar-multisensor precipitation estimates and quantitative precipitation forecast data for the DuPage County streamflow simulation system: \nU.S. Geological Survey Open-File Report 2017–1159, 16 p., https://doi.org/10.3133/ofr20171159.","productDescription":"iv, 15 p.","numberOfPages":"24","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-087229","costCenters":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"links":[{"id":350409,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1159/coverthb.jpg"},{"id":350410,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1159/ofr20171159.pdf","text":"Report","size":"3.64 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1159"}],"country":"United States","state":"Illinois","county":"DuPage County","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-88.2634,41.9876],[-88.1473,41.9883],[-88.0342,41.9925],[-87.9175,41.9938],[-87.9188,41.9076],[-87.9178,41.8185],[-87.9142,41.7318],[-87.9139,41.7172],[-87.9438,41.7017],[-87.9482,41.694],[-87.9674,41.6879],[-87.9883,41.6877],[-88.0013,41.6874],[-88.0308,41.6868],[-88.0317,41.7295],[-88.1499,41.7272],[-88.2625,41.7251],[-88.2628,41.811],[-88.2632,41.8623],[-88.2631,41.9],[-88.2634,41.9876]]]},\"properties\":{\"name\":\"Dupage\",\"state\":\"IL\"}}]}","contact":"Director, Illinois-Iowa Water Science Center
U.S. Geological Survey
405 North Goodwin Avenue
Urbana, IL 61801
Snake fungal disease (SFD) results from a skin infection that has been documented only in snakes. Historically, reports of snakes with skin infections of unknown origin have been sporadic. Recently, the number of reported cases of skin infections in snakes has increased substantially. This emerging infectious disease, confirmed in numerous species of snakes, is caused by the fungus Ophidiomyces ophiodiicola. As of August 2017, O. ophiodiicola has been detected in at least 23 States and one Canadian Province. However, researchers suspect that SFD may be more widely distributed than these documented cases suggest, because efforts to monitor the health of many snake populations are limited. Snake fungal disease may also be underreported in populations where it affects snakes infrequently or in species that develop less severe illness. Signs of SFD include crusted or ulcerated scales, nodules (that is, abnormal bumps) under the skin, and facial disfiguration that can be quite severe, leading to emaciation and death. Many snake populations are already in decline due to habitat loss and dwindling prey populations, and the recent emergence of SFD may accelerate this decline, causing certain species to disappear entirely from some locations.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20173064","usgsCitation":"Thompson, N.E., Lankau, E.W., and Rogall, G.M., 2018, Snake fungal disease in North America—U.S. Geological Survey updates: U.S. Geological Survey Fact Sheet 2017–3064, 4 p., https://doi.org/10.3133/fs20173064.","productDescription":"4 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-086524","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":350374,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2017/3064/coverthb1.jpg"},{"id":350375,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2017/3064/fs20173064.pdf","text":"Report","size":"9.57 MB","linkFileType":{"id":1,"text":"pdf"}}],"contact":"Director, National Wildlife Health Center
U.S. Geological Survey
6006 Schroeder Road
Madison, WI 53711
Remote camera trapping is an efficient noninvasive technique for monitoring rare and elusive species, such as cheetahs. The unique pelage pattern of cheetahs allows for identification of individuals from photographs, providing detection histories that are naturally suited for abundance estimation using capture–recapture methods. Furthermore, the spatial location of photographic detections allows for the use of spatial capture–recapture models, which provide estimates of density. In this chapter, we describe aspects of cheetah ecology that should be considered when designing camera trapping surveys (e.g., social structure, natural densities, and home range size) to estimate cheetah density and provide guidance for future camera trap sampling and analysis.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Cheetahs: Biology and Conservation","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Elsevier","doi":"10.1016/B978-0-12-804088-1.00029-0","usgsCitation":"Ezequiel Fabiano, Boast, L., Fuller, A.K., and Chris Sutherland, 2018, The use of remote camera trapping to study cheetahs, chap. 29 of Cheetahs: Biology and Conservation, p. 415-425, https://doi.org/10.1016/B978-0-12-804088-1.00029-0.","productDescription":"11 p.","startPage":"415","endPage":"425","ipdsId":"IP-080279","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":367608,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Ezequiel Fabiano","contributorId":217268,"corporation":false,"usgs":false,"family":"Ezequiel Fabiano","affiliations":[{"id":39588,"text":"University of Namibia","active":true,"usgs":false}],"preferred":false,"id":766480,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Boast, Lorraine","contributorId":217269,"corporation":false,"usgs":false,"family":"Boast","given":"Lorraine","email":"","affiliations":[{"id":39589,"text":"Cheetah Conservation Botswana","active":true,"usgs":false}],"preferred":false,"id":766481,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fuller, Angela K. 0000-0002-9247-7468 afuller@usgs.gov","orcid":"https://orcid.org/0000-0002-9247-7468","contributorId":3984,"corporation":false,"usgs":true,"family":"Fuller","given":"Angela","email":"afuller@usgs.gov","middleInitial":"K.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":766479,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Chris Sutherland","contributorId":196873,"corporation":false,"usgs":false,"family":"Chris Sutherland","affiliations":[],"preferred":false,"id":766482,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70190434,"text":"sir20175094 - 2018 - Nutrient and metal loads estimated by using discrete, automated, and continuous water-quality monitoring techniques for the Blackstone River at the Massachusetts-Rhode Island State line, water years 2013–14","interactions":[],"lastModifiedDate":"2018-01-10T16:40:29","indexId":"sir20175094","displayToPublicDate":"2018-01-10T17:20:00","publicationYear":"2018","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":"2017-5094","title":"Nutrient and metal loads estimated by using discrete, automated, and continuous water-quality monitoring techniques for the Blackstone River at the Massachusetts-Rhode Island State line, water years 2013–14","docAbstract":"Flow-proportional composite water samples were collected in water years 2013 and 2014 by the U.S. Geological Survey, in cooperation with the Massachusetts Department of Environmental Protection, from the Blackstone River at Millville, Massachusetts (U.S. Geological Survey station 01111230), about 0.5 mile from the border with Rhode Island. Samples were collected in order to better understand the dynamics of selected nutrient and metal constituents, assist with planning, guide activities to meet water-quality goals, and provide real-time water-quality information to the public. An automated system collected the samples at 14-day intervals to determine total and dissolved nitrogen and phosphorus concentrations, to provide accurate monthly nutrient concentration data, and to calculate monthly load estimates. Concentrations of dissolved trace metals and total aluminum were determined from 4-day composite water samples that were collected twice monthly by the automated system. Results from 4-day composites provide stakeholders with information to evaluate trace metals on the basis of chronic 4-day exposure criteria for aquatic life, and the potential to use the biotic ligand model to evaluate copper concentrations. Nutrient, trace metal, suspended sediment, dissolved organic carbon, and chlorophyll a concentrations were determined from discrete samples collected at the Millville station and from across the stream transect at the upstream railroad bridge, and these concentrations served as a means to evaluate the representativeness of the Millville point location.
Analytical results from samples collected with the automated flow-proportional sampling system provided the means to calculate monthly and annual loading data. Total nitrogen and total phosphorus loads in water year (WY) 2013 were about 447,000 and 36,000 kilograms (kg), respectively. In WY 2014, annual loads of total nitrogen and total phosphorus were about 342,000 and 21,000 kg, respectively. Total nitrogen and total phosphorus loads from WYs 2013 and 2014 were about 56 and 65 percent lower than those reported for WYs 2008 and 2009. The higher loads in 2008 and 2009 may be explained by the higher than average flows in WY 2009 and by facility upgrades made by wastewater treatment facilities in the basin.
Median loads were determined from composite samples collected with the automated system between October 2012 and October 2014. Median dissolved cadmium and chromium 4-day loads were 0.55 and 0.84 kg, respectively. Dissolved copper and total lead median 4-day loads were 8.02 and 1.42 kg, respectively. The dissolved nickel median 4-day load was 5.45 kg, and the dissolved zinc median 4-day load was 36 kg. Median total aluminum 4-day loads were about 197 kg.
Spearman’s rank correlation analyses were used with discrete sample concentrations and continuous records of temperature, specific conductance, turbidity, and chlorophyll a to identify correlations between variables that could be used to develop regression equations for estimating real-time concentrations of constituents. Correlation coefficients were generated for flow, precipitation, antecedent precipitation, physical parameters, and chemical constituents. A 95-percent confidence limit for each value of Spearman’s rho was calculated, and multiple linear regression analysis using ordinary least squares regression techniques was used to develop regression equations for concentrations of total phosphorus, total nitrogen, suspended sediment concentration, total copper, and total aluminum. Although the correlations are based on the limited amount of data collected as part of this study, the potential to monitor water-quality changes in real time may be of value to resource managers and decision makers.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175094","isbn":"ISBN 978-1-4113-4181-4","collaboration":"Prepared in cooperation with the Massachusetts Department of Environmental Protection","usgsCitation":"Sorenson, J.R., Granato, G.E., and Smith, K.P., 2018, Nutrient and metal loads estimated by using discrete, automated, and continuous water-quality monitoring techniques for the Blackstone River at the Massachusetts-Rhode Island State line, water years 2013–14: U.S. Geological Survey Scientific Investigations Report 2017–5094, 41 p., https://doi.org/10.3133/sir20175094.","productDescription":"Report: ix, 41 p.; 4 Tables","onlineOnly":"N","additionalOnlineFiles":"Y","ipdsId":"IP-079789","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":350359,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5094/sir20175094.pdf","text":"Report","size":"4.05 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017-5094"},{"id":350366,"rank":8,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2017/5094/tables/sir20175094_table6.csv","text":"Table 6","size":"19.4 csv","linkHelpText":"- Concentrations of nutrients, trace metals, and suspended sediment in manually collected samples from the upstream railroad bridge and from the collection point at the Blackstone River at Millville, Massachusetts, station (01111230) during water years 2013 and 2014."},{"id":350368,"rank":10,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2017/5094/tables/sir20175094_table7.csv","text":"Table 7","size":"13.1 KB csv","linkHelpText":"- Loads of nutrients based on 14-day nutrient composite samples, and loads of dissolved trace metals and total aluminum based on 4-day metal composite samples collected by the automated sampling system from the point location at the Blackstone River at Millville, Massachusetts, station (01111230) during water years 2013 and 2014."},{"id":350361,"rank":3,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2017/5094/tables/sir20175094_table4.xlsx","text":"Table 4 (Microsoft Excel)","size":"48.5 KB"},{"id":350358,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5094/coverthb.jpg"},{"id":350360,"rank":4,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2017/5094/tables/sir20175094_table4.csv","text":"Table 4","size":"15 KB csv","linkHelpText":"- Concentrations of nutrients, trace metals, and suspended sediment in sample pairs collected from the upstream railroad bridge and from the point location at the Blackstone River at Millville, Massachusetts, station (01111230)."},{"id":350367,"rank":9,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2017/5094/tables/sir20175094_table7.xlsx","text":"Table 7 (Microsoft Excel)","size":"44 KB","linkFileType":{"id":3,"text":"xlsx"}},{"id":350364,"rank":6,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2017/5094/tables/sir20175094_table5.csv","text":"Table 5","size":"13.7 KB csv","linkHelpText":"- Concentrations of nutrients, total aluminum, and dissolved trace metals in 14-day nutrient composite samples and 4-day metal composite samples collected by using the automated sampling system from the point location at the Blackstone River at Millville, Massachusetts, station (01111230) during water years 2013 and 2014."},{"id":350365,"rank":7,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2017/5094/tables/sir20175094_table6.xlsx","text":"Table 6 (Microsoft Excel)","size":"46.7 KB","linkFileType":{"id":3,"text":"xlsx"}},{"id":350363,"rank":5,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2017/5094/tables/sir20175094_table5.xlsx","text":"Table 5 (Microsoft Excel)","size":"39.6 KB","linkFileType":{"id":3,"text":"xlsx"}}],"country":"United States","state":"Massachusetts, Rhode Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -71.9167,\n 41.8333\n ],\n [\n -71.3333,\n 41.8333\n ],\n [\n -71.3333,\n 42.3333\n ],\n [\n -71.9167,\n 42.3333\n ],\n [\n -71.9167,\n 41.8333\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New England Water Science Center
U.S. Geological Survey
10 Bearfoot Road
Northborough, MA 01532
","tableOfContents":"
The Geospatial Semantic Web (GSW) is an emerging technology that uses the Internet for more effective knowledge engineering and information extraction. Among the aims of the GSW are to structure the semantic specifications of data to reduce ambiguity and to link those data more efficiently. The data are stored as triples, the basic data unit in graph databases, which are similar to the vector data model of geographic information systems (GIS); that is, a node-edge-node model that forms a graph of semantically related information. The GSW is supported by emerging technologies such as linked geospatial data, described below, that enable it to store and manage geographical data that require new cartographic methods for visualization. This report describes a map that can interact with linked geospatial data using a simulation of a data query approach called the browsable graph to find information that is semantically related to a subject of interest, visualized using the Data Driven Documents (D3) library. Such a semantically enabled map functions as a map knowledge base (MKB) (Varanka and Usery, 2017).
A MKB differs from a database in an important way. The central element of a triple, alternatively called the edge or property, is composed of a logic formalization that structures the relation between the first and third parts, the nodes or objects. Node-edge-node represents the graphic form of the triple, and the subject-property-object terms represent the data structure. Object classes connect to build a federated graph, similar to a network in visual form. Because the triple property is a logical statement (a predicate), the data graph represents logical propositions or assertions accepted to be true about the subject matter. These logical formalizations can be manipulated to calculate new triples, representing inferred logical assertions, from the existing data.
To demonstrate a MKB system, a technical proof-of-concept is developed that uses geographically attributed Resource Description Framework (RDF) serializations of linked data for mapping. The proof-of-concept focuses on accessing triple data from visual elements of a geographic map as the interface to the MKB. The map interface is embedded with other essential functions such as SPARQL Protocol and RDF Query Language (SPARQL) data query endpoint services and reasoning capabilities of Apache Marmotta (Apache Software Foundation, 2017). An RDF database of the Geographic Names Information System (GNIS), which contains official names of domestic feature in the United States, was linked to a county data layer from The National Map of the U.S. Geological Survey. The county data are part of a broader Government Units theme offered to the public as Esri shapefiles. The shapefile used to draw the map itself was converted to a geographic-oriented JavaScript Object Notation (JSON) (GeoJSON) format and linked through various properties with a linked geodata version of the GNIS database called “GNIS–LD” (Butler and others, 2016; B. Regalia and others, University of California-Santa Barbara, written commun., 2017). The GNIS–LD files originated in Terse RDF Triple Language (Turtle) format but were converted to a JSON format specialized in linked data, “JSON–LD” (Beckett and Berners-Lee, 2011; Sorny and others, 2014). The GNIS–LD database is composed of roughly three predominant triple data graphs: Features, Names, and History. The graphs include a set of namespace prefixes used by each of the attributes. Predefining the prefixes made the conversion to the JSON–LD format simple to complete because Turtle and JSON–LD are variant specifications of the basic RDF concept.
To convert a shapefile into GeoJSON format to capture the geospatial coordinate geometry objects, an online converter, Mapshaper, was used (Bloch, 2013). To convert the Turtle files, a custom converter written in Java reconstructs the files by parsing each grouping of attributes belonging to one subject and pasting the data into a new file that follows the syntax of JSON–LD. Additionally, the Features file contained its own set of geometries, which was exported into a separate JSON–LD file along with its elevation value to form a fourth file, named “features-geo.json.” Extracted data from external files can be represented in HyperText Markup Language (HTML) path objects. The goal was to import multiple JSON–LD files using this approach.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171150","usgsCitation":"Powell, L.J., and Varanka, D.E., 2018, A linked GeoData map for enabling information access: U.S. Geological Survey Open–File Report 2017–1150, 6 p, https://doi.org/10.3133/ofr20171150.","productDescription":"iv, 6 p.","numberOfPages":"14","onlineOnly":"Y","ipdsId":"IP-090452","costCenters":[{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"links":[{"id":350413,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1150/coverthb.jpg"},{"id":350414,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1150/ofr20171150.pdf","text":"Report","size":"376 kB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1150"}],"contact":"Director, National Geospatial Technical Operations Center
U.S. Geological Survey
1400 Independence Road
Rolla, MO 65401
Agricultural activities can affect water quality and the health of aquatic ecosystems; many water-quality issues originate with the movement of water, agricultural chemicals, and eroded soil from agricultural areas to streams and groundwater. Most agricultural activities are designed to sustain or increase crop production, while some are designed to protect soil and water resources. Numerous soil- and water-protection practices are designed to reduce the volume and velocity of runoff and increase infiltration. This report presents a conceptual framework that combines generalized concepts on the movement of water, the environmental behavior of chemicals and eroded soil, and the designed functions of various agricultural activities, as they relate to hydrology, to create attainable expectations for the protection of—with the goal of improving—water quality through changes in an agricultural activity.
The framework presented uses two types of decision trees to guide decision making toward attainable expectations regarding the effectiveness of changing agricultural activities to protect and improve water quality in streams. One decision tree organizes decision making by considering the hydrologic setting and chemical behaviors, largely at the field scale. This decision tree can help determine which agricultural activities could effectively protect and improve water quality in a stream from the movement of chemicals, or sediment, from a field. The second decision tree is a chemical fate accounting tree. This decision tree helps set attainable expectations for the permanent removal of sediment, elements, and organic chemicals—such as herbicides and insecticides—through trapping or conservation tillage practices. Collectively, this conceptual framework consolidates diverse hydrologic settings, chemicals, and agricultural activities into a single, broad context that can be used to set attainable expectations for agricultural activities. This framework also enables better decision making for future agricultural activities as a means to reduce current, and prevent new, water-quality issues.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175095","usgsCitation":"Capel, P.D., Wolock, D.M., Coupe, R.H., and Roth, J.L., 2018, A conceptual framework for effectively anticipating water-quality changes resulting from changes in agricultural activities: U.S. Geological Survey Scientific Investigations Report 2017–5095, 35 p., https://doi.org/10.3133/sir20175095.","productDescription":"Report: viii, 35 p.; Data release","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-071052","costCenters":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"links":[{"id":350408,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F75T3HN9","text":"USGS data release","description":"USGS data release","linkHelpText":"Data set used to develop a conceptual framework for effectively anticipating water-quality changes resulting from changes in agricultural activities"},{"id":349840,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5095/coverthb.jpg"},{"id":349841,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5095/sir20175095.pdf","text":"Report","size":"2.14 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017-5095"}],"contact":"National Water-Quality Program
U.S. Geological Survey
12201 Sunrise Valley Drive
Reston, VA 20192
PDEPTH is an interactive, graphical computer program used to construct interpreted geological source models for observed potential-field geophysical profile data. The current version of PDEPTH has been adapted to the Windows platform from an earlier DOS-based version. The input total-field magnetic anomaly and vertical gravity anomaly profiles can be filtered to produce derivative products such as reduced-to-pole magnetic profiles, pseudogravity profiles, pseudomagnetic profiles, and upward-or-downward-continued profiles. A variety of source-location methods can be applied to the original and filtered profiles to estimate (and display on a cross section) the locations and physical properties of contacts, sheet edges, horizontal line sources, point sources, and interface surfaces. Two-and-a-half-dimensional source bodies having polygonal cross sections can be constructed using a mouse and keyboard. These bodies can then be adjusted until the calculated gravity and magnetic fields of the source bodies are close to the observed profiles. Auxiliary information such as the topographic surface, bathymetric surface, seismic basement, and geologic contact locations can be displayed on the cross section using optional input files. Test data files, used to demonstrate the source location methods in the report, and several utility programs are included.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Section C: Computer programs in Book 7: Automated data processing and computations","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/tm7C17","collaboration":"Prepared in cooperation with the U.S. Department of Energy, National Nuclear Security Administration Nevada Site Office under Interagency Agreement number IAG DE-AI52-12NA30865/DE-NA0001654. The USGS does not provide technical support for the software associated with this publication.","usgsCitation":"Phillips, J.D., 2018, PDEPTH—A computer program for the geophysical interpretation of magnetic and gravity profiles through Fourier filtering, source-depth analysis, and forward modeling: U.S. Geological Survey Techniques and Methods, book 7, chap. C17, 23 p., https://doi.org/10.3133/tm7C17.","productDescription":"viii, 23 p.","numberOfPages":"36","onlineOnly":"Y","ipdsId":"IP-032003","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":425658,"rank":4,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/tm/07/c17/readme.txt","text":"Read Me","size":"4.00 KB","linkFileType":{"id":2,"text":"txt"}},{"id":425657,"rank":3,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/tm/07/c17/PDepthDataFiles.zip","size":"2.21 MB","linkFileType":{"id":6,"text":"zip"}},{"id":350415,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/tm/07/c17/coverthb.jpg"},{"id":350416,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/tm/07/c17/tm7c17.pdf","text":"Report","size":"776 kB","linkFileType":{"id":1,"text":"pdf"},"description":"TM 7-C17"}],"publicComments":"This report is Chapter 17 of Section C: Computer programs in Book 7: Automated data processing and computations.","contact":"Director, Geology, Geophysics, and Geochemistry Science Center
U.S. Geological Survey
Box 25046, MS 973
Denver, CO 80225
Impact crater populations crucially help us to understand solar system dynamics, planetary surface histories, and surface modification processes. A single previous effort to standardize how crater data are displayed in graphs, tables, and archives, was in a 1978 NASA report by the Crater Analysis Techniques Working Group, published in 1979 in Icarus. The report had a significant lasting effect, but later decades brought major advances in statistical and computer sciences while the crater field has remained fairly stagnant. In this new work, we revisit the fundamental techniques for displaying and analyzing crater population data and demonstrate better statistical methods that can be used. Specifically, we address (1) how crater size-frequency distributions (SFDs) are constructed, (2) how error bars are assigned to SFDs, and (3) how SFDs are fit to power laws and other models. We show how the new methods yield results similar to those of previous techniques in that the SFDs have familiar shapes but better account for multiple sources of uncertainty. We also recommend graphic, display, and archiving methods that reflect computers' capabilities and fulfill NASA's current requirements for Data Management Plans.
","language":"English","publisher":"The Meteoritical Society","doi":"10.1111/maps.12990","usgsCitation":"Robbins, S.J., Riggs, J.D., Weaver, B.P., Bierhaus, E.B., Chapman, C.R., Kirchoff, M.R., Singer, K.N., and Gaddis, L., 2018, Revised recommended methods for analyzing crater size-frequency distributions: Meteoritics and Planetary Science, v. 53, no. 4, p. 891-931, https://doi.org/10.1111/maps.12990.","productDescription":"41 p.","startPage":"891","endPage":"931","ipdsId":"IP-080708","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":469097,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/maps.12990","text":"Publisher Index Page"},{"id":355669,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"53","issue":"4","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-01-10","publicationStatus":"PW","scienceBaseUri":"5b6fc4bbe4b0f5d57878eac6","contributors":{"authors":[{"text":"Robbins, Stuart J.","contributorId":204229,"corporation":false,"usgs":false,"family":"Robbins","given":"Stuart","email":"","middleInitial":"J.","affiliations":[{"id":36712,"text":"Southwest Research Institute","active":true,"usgs":false}],"preferred":false,"id":739951,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Riggs, Jamie D.","contributorId":204236,"corporation":false,"usgs":false,"family":"Riggs","given":"Jamie","email":"","middleInitial":"D.","affiliations":[{"id":25254,"text":"Northwestern University","active":true,"usgs":false}],"preferred":false,"id":739952,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Weaver, Brian P.","contributorId":204237,"corporation":false,"usgs":false,"family":"Weaver","given":"Brian","email":"","middleInitial":"P.","affiliations":[{"id":36891,"text":"Statistical Sciences, CCS-6, Los Alamos National Laboratory","active":true,"usgs":false}],"preferred":false,"id":739953,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bierhaus, Edward B.","contributorId":206277,"corporation":false,"usgs":false,"family":"Bierhaus","given":"Edward","email":"","middleInitial":"B.","affiliations":[{"id":37297,"text":"Lockheed Martin Space Systems Company","active":true,"usgs":false}],"preferred":false,"id":739954,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Chapman, Clark R.","contributorId":206278,"corporation":false,"usgs":false,"family":"Chapman","given":"Clark","email":"","middleInitial":"R.","affiliations":[{"id":37298,"text":"Southwest Research Institute, Boulder, CO","active":true,"usgs":false}],"preferred":false,"id":739955,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kirchoff, Michelle R.","contributorId":206279,"corporation":false,"usgs":false,"family":"Kirchoff","given":"Michelle","email":"","middleInitial":"R.","affiliations":[{"id":37298,"text":"Southwest Research Institute, Boulder, CO","active":true,"usgs":false}],"preferred":false,"id":739956,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Singer, Kelsi N.","contributorId":196151,"corporation":false,"usgs":false,"family":"Singer","given":"Kelsi","email":"","middleInitial":"N.","affiliations":[{"id":7037,"text":"Southwest Research Institute, Boulder, Colorado","active":true,"usgs":false}],"preferred":false,"id":739957,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Gaddis, Lisa 0000-0001-9953-5483 lgaddis@usgs.gov","orcid":"https://orcid.org/0000-0001-9953-5483","contributorId":206276,"corporation":false,"usgs":true,"family":"Gaddis","given":"Lisa","email":"lgaddis@usgs.gov","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":739950,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70196290,"text":"70196290 - 2018 - International migration patterns of Red-throated Loons (Gavia stellata) from four breeding populations in Alaska","interactions":[],"lastModifiedDate":"2018-03-30T14:00:16","indexId":"70196290","displayToPublicDate":"2018-01-10T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"displayTitle":"International migration patterns of Red-throated Loons (Gavia stellata) from four breeding populations in Alaska","title":"International migration patterns of Red-throated Loons (Gavia stellata) from four breeding populations in Alaska","docAbstract":"Identifying post-breeding migration and wintering distributions of migratory birds is important for understanding factors that may drive population dynamics. Red-throated Loons (Gavia stellata) are widely distributed across Alaska and currently have varying population trends, including some populations with recent periods of decline. To investigate population differentiation and the location of migration pathways and wintering areas, which may inform population trend patterns, we used satellite transmitters (n = 32) to describe migration patterns of four geographically separate breeding populations of Red-throated Loons in Alaska. On average (± SD) Red-throated Loons underwent long (6,288 ± 1,825 km) fall and spring migrations predominantly along coastlines. The most northern population (Arctic Coastal Plain) migrated westward to East Asia and traveled approximately 2,000 km farther to wintering sites than the three more southerly populations (Seward Peninsula, Yukon-Kuskokwim Delta, and Copper River Delta) which migrated south along the Pacific coast of North America. These migration paths are consistent with the hypothesis that Red-throated Loons from the Arctic Coastal Plain are exposed to contaminants in East Asia. The three more southerly breeding populations demonstrated a chain migration pattern in which the more northerly breeding populations generally wintered in more northerly latitudes. Collectively, the migration paths observed in this study demonstrate that some geographically distinct breeding populations overlap in wintering distribution while others use highly different wintering areas. Red-throated Loon population trends in Alaska may therefore be driven by a wide range of effects throughout the annual cycle.
","language":"English","publisher":"PLOS","doi":"10.1371/journal.pone.0189954","usgsCitation":"McCloskey, S., Uher-Koch, B.D., Schmutz, J.A., and Fondell, T., 2018, International migration patterns of Red-throated Loons (Gavia stellata) from four breeding populations in Alaska: PLoS ONE, v. 13, no. 1, p. 1-15, https://doi.org/10.1371/journal.pone.0189954.","productDescription":"e0189954; 15 p.","startPage":"1","endPage":"15","ipdsId":"IP-090249","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":469099,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0189954","text":"Publisher Index Page"},{"id":438057,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7TH8KVH","text":"USGS data release","linkHelpText":" Tracking data for Red-throated Loons (Gavia stellata)"},{"id":353018,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","volume":"13","issue":"1","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2018-01-10","publicationStatus":"PW","scienceBaseUri":"5afee751e4b0da30c1bfc22c","contributors":{"authors":[{"text":"McCloskey, Sarah E. smccloskey@usgs.gov","contributorId":4850,"corporation":false,"usgs":true,"family":"McCloskey","given":"Sarah E.","email":"smccloskey@usgs.gov","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":false,"id":732175,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Uher-Koch, Brian D. 0000-0002-1885-0260 buher-koch@usgs.gov","orcid":"https://orcid.org/0000-0002-1885-0260","contributorId":5117,"corporation":false,"usgs":true,"family":"Uher-Koch","given":"Brian","email":"buher-koch@usgs.gov","middleInitial":"D.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":732174,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schmutz, Joel A. 0000-0002-6516-0836 jschmutz@usgs.gov","orcid":"https://orcid.org/0000-0002-6516-0836","contributorId":1805,"corporation":false,"usgs":true,"family":"Schmutz","given":"Joel","email":"jschmutz@usgs.gov","middleInitial":"A.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":732176,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fondell, Thomas F. tfondell@usgs.gov","contributorId":139310,"corporation":false,"usgs":true,"family":"Fondell","given":"Thomas F.","email":"tfondell@usgs.gov","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":false,"id":732177,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70237797,"text":"70237797 - 2018 - The Polar WRF downscaled historical and projected twenty-first century climate for the coast and foothills of Arctic Alaska","interactions":[],"lastModifiedDate":"2022-10-24T15:50:49.887876","indexId":"70237797","displayToPublicDate":"2018-01-09T10:44:46","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":12790,"text":"Frontiers in Earth Science: Atmospheric Science","active":true,"publicationSubtype":{"id":10}},"title":"The Polar WRF downscaled historical and projected twenty-first century climate for the coast and foothills of Arctic Alaska","docAbstract":"Climate change is most pronounced in the northern high latitude region. Yet, climate observations are unable to fully capture regional-scale dynamics due to the sparse weather station coverage, which limits our ability to make reliable climate-based assessments. A set of simulated data products was therefore developed for the North Slope of Alaska through a dynamical downscaling approach. The polar-optimized Weather Research and Forecast (Polar WRF) model was forced by three sources: The ERA-interim reanalysis data (for 1979–2014), the Community Earth System Model 1.0 (CESM1.0) historical simulation (for 1950–2005), and the CESM1.0 projected (for 2006–2100) simulations in two Representative Concentration Pathways (RCP4.5 and RCP8.5) scenarios. Climatic variables were produced in a 10-km grid spacing and a 3-h interval. The ERA-interim forced WRF (ERA-WRF) proves the value of dynamical downscaling, which yields more realistic topographical-induced precipitation and air temperature, as well as corrects underestimations in observed precipitation. In summary, dry and cold biases to the north of the Brooks Range are presented in ERA-WRF, while CESM forced WRF (CESM-WRF) holds wet and warm biases in its historical period. A linear scaling method allowed for an adjustment of the biases, while keeping the majority of the variability and extreme values of modeled precipitation and air temperature. CESM-WRF under RCP 4.5 scenario projects smaller increase in precipitation and air temperature than observed in the historical CESM-WRF product, while the CESM-WRF under RCP 8.5 scenario shows larger changes. The fine spatial and temporal resolution, long temporal coverage, and multi-scenario projections jointly make the dataset appropriate to address a myriad of physical and biological changes occurring on the North Slope of Alaska.
","language":"English","publisher":"Frontiers Media","doi":"10.3389/feart.2017.00111","usgsCitation":"Cai, L., Alexeev, V.A., Arp, C.D., Jones, B.M., Liljedahl, A.K., and Gadeke, A., 2018, The Polar WRF downscaled historical and projected twenty-first century climate for the coast and foothills of Arctic Alaska: Frontiers in Earth Science: Atmospheric Science, v. 5, 111, 15 p., https://doi.org/10.3389/feart.2017.00111.","productDescription":"111, 15 p.","ipdsId":"IP-091773","costCenters":[{"id":118,"text":"Alaska Science Center Geography","active":true,"usgs":true}],"links":[{"id":469100,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/feart.2017.00111","text":"Publisher Index Page"},{"id":408650,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -133.9309914494186,\n 76.57231802755655\n ],\n [\n -169.1576427848962,\n 76.57231802755655\n ],\n [\n -169.1576427848962,\n 66.53960949503181\n ],\n [\n -133.9309914494186,\n 66.53960949503181\n ],\n [\n -133.9309914494186,\n 76.57231802755655\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"5","noUsgsAuthors":false,"publicationDate":"2018-01-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Cai, Lei","contributorId":173394,"corporation":false,"usgs":false,"family":"Cai","given":"Lei","email":"","affiliations":[{"id":6695,"text":"UAF","active":true,"usgs":false}],"preferred":false,"id":855661,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Alexeev, Vladimir A","contributorId":298469,"corporation":false,"usgs":false,"family":"Alexeev","given":"Vladimir","email":"","middleInitial":"A","affiliations":[{"id":6695,"text":"UAF","active":true,"usgs":false}],"preferred":false,"id":855662,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Arp, Christopher D.","contributorId":17330,"corporation":false,"usgs":false,"family":"Arp","given":"Christopher","email":"","middleInitial":"D.","affiliations":[{"id":6752,"text":"University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":855663,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jones, Benjamin M. 0000-0002-1517-4711 bjones@usgs.gov","orcid":"https://orcid.org/0000-0002-1517-4711","contributorId":2286,"corporation":false,"usgs":true,"family":"Jones","given":"Benjamin","email":"bjones@usgs.gov","middleInitial":"M.","affiliations":[{"id":118,"text":"Alaska Science Center Geography","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":855664,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Liljedahl, Anna K. 0000-0001-7114-6443","orcid":"https://orcid.org/0000-0001-7114-6443","contributorId":150135,"corporation":false,"usgs":false,"family":"Liljedahl","given":"Anna","email":"","middleInitial":"K.","affiliations":[{"id":6695,"text":"UAF","active":true,"usgs":false}],"preferred":false,"id":855665,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Gadeke, Anne","contributorId":191059,"corporation":false,"usgs":false,"family":"Gadeke","given":"Anne","email":"","affiliations":[],"preferred":false,"id":855666,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70195317,"text":"70195317 - 2018 - Managing individual nests promotes population recovery of a top predator","interactions":[],"lastModifiedDate":"2018-04-17T12:27:38","indexId":"70195317","displayToPublicDate":"2018-01-09T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2163,"text":"Journal of Applied Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Managing individual nests promotes population recovery of a top predator","docAbstract":"This report documents several components of the U.S. Geological Survey National Hydrologic Model of the conterminous United States for use with the Precipitation-Runoff Modeling System (PRMS). It provides descriptions of the (1) National Hydrologic Model, (2) Geospatial Fabric for National Hydrologic Modeling, (3) PRMS hydrologic simulation code, (4) parameters and estimation methods used to compute spatially and temporally distributed default values as required by PRMS, (5) National Hydrologic Model Parameter Database, and (6) model extraction tool named Bandit. The National Hydrologic Model Parameter Database contains values for all PRMS parameters used in the National Hydrologic Model. The methods and national datasets used to estimate all the PRMS parameters are described. Some parameter values are derived from characteristics of topography, land cover, soils, geology, and hydrography using traditional Geographic Information System methods. Other parameters are set to long-established default values and computation of initial values. Additionally, methods (statistical, sensitivity, calibration, and algebraic) were developed to compute parameter values on the basis of a variety of nationally-consistent datasets. Values in the National Hydrologic Model Parameter Database can periodically be updated on the basis of new parameter estimation methods and as additional national datasets become available. A companion ScienceBase resource provides a set of static parameter values as well as images of spatially-distributed parameters associated with PRMS states and fluxes for each Hydrologic Response Unit across the conterminuous United States.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Section B: Surface water in Book 6: Modeling techniques","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/tm6B9","usgsCitation":"Regan, R.S., Markstrom, S.L., Hay, L.E., Viger, R.J., Norton, P.A., Driscoll, J.M., LaFontaine, J.H., 2018, Description of the National Hydrologic Model for use with the Precipitation-Runoff Modeling System (PRMS): U.S. Geological Survey Techniques and Methods, book 6, chap B9, 38 p., https://doi.org/10.3133/tm6B9.","productDescription":"vii, 38 p.","onlineOnly":"Y","ipdsId":"IP-084916","costCenters":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"links":[{"id":438059,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9TYOJKN","text":"USGS data release","linkHelpText":"National Hydrologic Model v1.0 water budget components aggregated to 10 and 12-digit Hydrologic Unit Code boundaries"},{"id":350326,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/tm/06/b09/coverthb.jpg"},{"id":350327,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/tm/06/b09/tm6b9.pdf","text":"Report","size":"5.96 MB","linkFileType":{"id":1,"text":"pdf"},"description":"TM 6-B9"}],"publicComments":"This report is Chapter 9 of Section B: Surface Water in Book 6 Modeling Techniques.","contact":"Director, Integrated Modeling and Prediction Division
U.S. Geological Survey
Mail Stop 415
12201 Sunrise Valley Drive
Reston, VA 20192
The analysis described in this report is part of a longterm project monitoring the biological communities, habitat, and water quality of the Fountain Creek Basin. Biology, habitat, and water-quality data have been collected at 10 sites since 2003. These data include annual samples of aquatic invertebrate communities, fish communities, water quality, and quantitative riverine habitat. This report examines trends in biological communities from 2003 to 2016 and explores relationships between biological communities and abiotic variables (antecedent streamflow, physical habitat, and water quality). Six biological metrics (three invertebrate and three fish) and four individual fish species were used to examine trends in these data and how streamflow, habitat, and (or) water quality may explain these trends. The analysis of 79 trends shows that the majority of significant trends decreased over the trend period. Overall, 19 trends before adjustments for streamflow in the fish (12) and invertebrate (7) metrics were all decreasing except for the metric Invertebrate Species Richness at the most upstream site in Monument Creek. Seven of these trends were explained by streamflow and four trends were revealed that were originally masked by variability in antecedent streamflow. Only two sites (Jimmy Camp Creek at Fountain, CO and Fountain Creek near Pinon, CO) had no trends in the fish or invertebrate metrics. Ten of the streamflow-adjusted trends were explained by habitat, one was explained by water quality, and five were not explained by any of the variables that were tested. Overall, from 2003 to 2016, all the fish metric trends were decreasing with an average decline of 40 percent, and invertebrate metrics decreased on average by 9.5 percent. A potential peak streamflow threshold was identified above which there is severely limited production of age-0 flathead chub (Platygobio gracilis).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175162","collaboration":"Prepared in cooperation with the City of Colorado Springs, Water Resources Engineering Division, Public Works Department and Colorado Springs Utilities","usgsCitation":"Roberts, J.J., Bruce, J.F., and Zuellig, R.E., 2018, Changes in biological communities of the Fountain Creek Basin, Colorado, 2003–2016, in relation to antecedent streamflow, water quality, and habitat: U.S. Geological Survey Scientific Investigations Report 2017–5162, 20 p., https://doi.org/10.3133/sir20175162.","productDescription":"Report: vi, 20 p.; Data Release","numberOfPages":"30","onlineOnly":"Y","ipdsId":"IP-088880","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":350235,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/f747493V","text":"USGS data release","linkHelpText":"Datasets of ecological communities (invertebrates and fish), streamflow, habitat, and water quality to examine the presence of trends in ecological communities from the Fountain Creek Basin, Colorado, USA, 2003-2016"},{"id":438060,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F747493V","text":"USGS data release","linkHelpText":"Datasets of ecological communities (invertebrates and fish), streamflow, habitat, and water quality to examine the presence of trends in ecological communities from the Fountain Creek basin, Colorado, USA, 2003-2016."},{"id":350234,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5162/sir20175162.pdf","text":"Report","size":"5.63 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017–5162"},{"id":350233,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5162/coverthb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"Fountain Creek Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -105,\n 38.25\n ],\n [\n -104.5,\n 38.25\n ],\n [\n -104.5,\n 39\n ],\n [\n -105,\n 39\n ],\n [\n -105,\n 38.25\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Colorado Water Science Center
U.S. Geological Survey
Box 25046, MS 415
Denver, CO 80225
Fugitive dust from unpaved roads creates human health hazards, degrades road surfaces, and increases the cost of road maintenance. As a result, many different chemical treatments are applied to unpaved roads in an attempt to control dust and stabilize the wearing course. However, investigations of the effectiveness of these treatments have often been poorly planned or executed. The objective of this study was to use a combination of real-time dust monitoring and objective road condition evaluations to assess the success of two chemical treatments for a period of 19?months post-application, to provide quantitative information in support of road management decisions. Dust production from road sections treated with calcium chloride-based durablend-C™ or the synthetic fluid EnviroKleen® was monitored on five dates using a vehicle-mounted particulate matter meter. Both products reduced dust by up to 99% relative to an untreated control section during the monitoring period, and quantitative data from the meter were consistent with qualitative observations of dust conditions. Linear models of dust production indicated that road treatment and humidity explained 69% of the variation in dust over time. Road sections treated with either product developed less rutting and fewer potholes than the untreated control. Overall, the combination of real-time dust monitoring and surface condition evaluation was an effective approach for generating quantitative data on endpoints of interest to road managers.
","language":"English","publisher":"Sage Publications","doi":"10.1177/0361198118799167","usgsCitation":"Kunz, B.K., Green, N., Albers, J.L., Wildhaber, M.L., and Little, E.E., 2018, Use of real-time dust monitoring and surface condition to evaluate success of unpaved road treatments: Transportation Research Record, v. 2672, no. 52, p. 195-204, https://doi.org/10.1177/0361198118799167.","productDescription":"10 p.","startPage":"195","endPage":"204","ipdsId":"IP-092378","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":362798,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Missouri","otherGeospatial":"Loess Bluffs National Wildlife Refuge","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -95.26691436767577,\n 40.096457912121444\n ],\n [\n -95.26811599731445,\n 40.07491896000657\n ],\n [\n -95.25678634643555,\n 40.05219060659433\n ],\n [\n -95.2488899230957,\n 40.051665005850715\n ],\n [\n -95.24940490722656,\n 40.05337319344778\n ],\n [\n -95.24614334106445,\n 40.053898781018304\n ],\n [\n -95.23086547851562,\n 40.07386810509482\n ],\n [\n -95.22897720336914,\n 40.10315461168825\n ],\n [\n -95.23721694946289,\n 40.110638378278054\n ],\n [\n -95.24288177490234,\n 40.110638378278054\n ],\n [\n -95.26691436767577,\n 40.096457912121444\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"2672","issue":"52","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2018-10-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Kunz, Bethany K. 0000-0002-7193-9336 bkunz@usgs.gov","orcid":"https://orcid.org/0000-0002-7193-9336","contributorId":3798,"corporation":false,"usgs":true,"family":"Kunz","given":"Bethany","email":"bkunz@usgs.gov","middleInitial":"K.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":760470,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Green, Nicholas S. 0000-0002-8538-4191","orcid":"https://orcid.org/0000-0002-8538-4191","contributorId":202040,"corporation":false,"usgs":true,"family":"Green","given":"Nicholas S.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":760471,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Albers, Janice L. 0000-0002-6312-8269 jalbers@usgs.gov","orcid":"https://orcid.org/0000-0002-6312-8269","contributorId":3972,"corporation":false,"usgs":true,"family":"Albers","given":"Janice","email":"jalbers@usgs.gov","middleInitial":"L.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":760472,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wildhaber, Mark L. 0000-0002-6538-9083 mwildhaber@usgs.gov","orcid":"https://orcid.org/0000-0002-6538-9083","contributorId":1386,"corporation":false,"usgs":true,"family":"Wildhaber","given":"Mark","email":"mwildhaber@usgs.gov","middleInitial":"L.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":760473,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Little, Edward E. 0000-0003-0034-3639 elittle@usgs.gov","orcid":"https://orcid.org/0000-0003-0034-3639","contributorId":1746,"corporation":false,"usgs":true,"family":"Little","given":"Edward","email":"elittle@usgs.gov","middleInitial":"E.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":760474,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70194663,"text":"ofr20171162 - 2018 - Groundwater quality in the shallow aquifers of the Madera–Chowchilla and Kings subbasins, San Joaquin Valley, California","interactions":[],"lastModifiedDate":"2018-01-09T09:52:21","indexId":"ofr20171162","displayToPublicDate":"2018-01-08T00:00:00","publicationYear":"2018","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":"2017-1162","title":"Groundwater quality in the shallow aquifers of the Madera–Chowchilla and Kings subbasins, San Joaquin Valley, California","docAbstract":"Groundwater provides more than 40 percent of California’s drinking water. To protect this vital resource, the State of California created the Groundwater Ambient Monitoring and Assessment (GAMA) Program. The GAMA Program’s Priority Basin Project assesses the quality of groundwater resources used for drinking-water supply and increases public access to groundwater-quality information. Many households and small communities in the Madera– Chowchilla and Kings subbasins of the San Joaquin Valley rely on private domestic wells for their drinking-water supplies.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171162","collaboration":"Prepared in cooperation with the California State Water Resources Control Board","usgsCitation":"Fram, M.S. and Shelton, J.L., 2018, Groundwater Quality in the Shallow Aquifers of the Madera–Chowchilla and Kings Subbasins, San Joaquin Valley, California: U.S. Geological Survey Open-File Report 2017–1162, 4 p., https://doi.org/10.3133/ofr20171162.","productDescription":"4 p.","ipdsId":"IP-089766","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":350380,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1162/ofr20171162.pdf","text":"Report","size":"1.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1162"},{"id":350379,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1162/coverthb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Madera– Chowchilla Subbasin, Kings Subbasin, San Joaquin Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -120.5,\n 36.25\n ],\n [\n -119.25,\n 36.25\n ],\n [\n -119.25,\n 37.25\n ],\n [\n -120.5,\n 37.25\n ],\n [\n -120.5,\n 36.25\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"California Water Science Center
California GAMA
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, California 95819
The river otter (Lontra canadensis) was extirpated from Nebraska, USA, in the early 1900s and reintroduced starting in 1986. Information is needed regarding the distribution of river otters in Nebraska before decisions can be made regarding its conservation status. Understanding distribution of a species is critically important for effective management. We investigated river otter distribution in Nebraska with occupancy modeling and maximum entropy (Maxent) modeling using 190 otter sign observations on Nebraska's navigable rivers and 380 historical otter records from November 1977 to April 2014. Both methods identified the Platte River, Elkhorn River, central and eastern Niobrara River, and southern Loup River system as core areas within the distribution of otters in Nebraska. The Maxent model provided more liberal estimates of site occupancy and identified some smaller rivers as being within the distribution of otters in Nebraska, which were not identified using occupancy modeling. We recommend that multiple data sets and analysis methods be used to estimate species distribution because this allows for the broadest geographical coverage and decreases the likelihood of overlooking areas with fewer animal records. If further reintroduction efforts or translocation efforts are to take place in the future, we recommend focusing on areas with high modeled occupancy but few historical and survey records
","language":"English","publisher":"Wildlife Society","doi":"10.1002/wsb.843","usgsCitation":"Bieber, N.R., Wilson, S.P., and Allen, C.R., 2018, River otter distribution in Nebraska: Wildlife Society Bulletin, v. 42, no. 1, p. 136-143, https://doi.org/10.1002/wsb.843.","productDescription":"8 p.","startPage":"136","endPage":"143","ipdsId":"IP-094064","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":500069,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doaj.org/article/08bde403cf22458cbb0e4cf09a97b49e","text":"External Repository"},{"id":395281,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nebraska","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-104.053249,41.001406],[-104.053127,43.000585],[-101.849982,42.999329],[-101.625424,42.996238],[-100.472742,42.999288],[-98.49855,42.99856],[-98.490483,42.977948],[-98.467356,42.947556],[-98.448309,42.936428],[-98.444145,42.929242],[-98.437285,42.928393],[-98.430934,42.931504],[-98.42074,42.931924],[-98.34623,42.902747],[-98.325864,42.8865],[-98.280007,42.874996],[-98.25181,42.872824],[-98.219826,42.853157],[-98.189765,42.841628],[-98.167523,42.836925],[-98.14806,42.840013],[-98.137912,42.832728],[-98.127489,42.820127],[-98.107688,42.810633],[-98.094574,42.799309],[-98.067388,42.784759],[-98.062913,42.781119],[-98.059838,42.772772],[-98.056625,42.770781],[-98.035034,42.764205],[-98.013046,42.762299],[-98.005739,42.764167],[-98.000348,42.763256],[-97.977588,42.769923],[-97.950147,42.769619],[-97.936716,42.775754],[-97.921434,42.788352],[-97.908983,42.794909],[-97.888562,42.817251],[-97.879878,42.835395],[-97.878976,42.843673],[-97.875849,42.847725],[-97.877003,42.854394],[-97.875345,42.858724],[-97.84527,42.867734],[-97.828496,42.868797],[-97.817075,42.861781],[-97.774456,42.849774],[-97.72045,42.847439],[-97.686506,42.842435],[-97.657846,42.844626],[-97.611811,42.858367],[-97.603762,42.858329],[-97.591916,42.853837],[-97.561928,42.847552],[-97.531867,42.850105],[-97.504847,42.858477],[-97.49149,42.851625],[-97.470529,42.850455],[-97.452177,42.846048],[-97.442279,42.846224],[-97.431951,42.851542],[-97.417066,42.865918],[-97.408315,42.868334],[-97.393966,42.86425],[-97.376695,42.865195],[-97.368643,42.858419],[-97.359569,42.854816],[-97.336156,42.856802],[-97.306677,42.867604],[-97.289859,42.855499],[-97.267946,42.852583],[-97.248556,42.855386],[-97.218825,42.845848],[-97.217411,42.843519],[-97.218269,42.829561],[-97.213957,42.820143],[-97.213084,42.813007],[-97.210126,42.809296],[-97.200431,42.805485],[-97.166978,42.802087],[-97.150763,42.795566],[-97.138216,42.783428],[-97.134461,42.774494],[-97.131331,42.771929],[-97.096128,42.76934],[-97.065592,42.772189],[-97.033229,42.765904],[-97.02485,42.76243],[-96.99282,42.759481],[-96.97912,42.76009],[-96.96888,42.754278],[-96.96123,42.740623],[-96.965833,42.727096],[-96.964776,42.722455],[-96.961576,42.719841],[-96.948902,42.719465],[-96.924156,42.730327],[-96.906797,42.7338],[-96.886845,42.725222],[-96.860436,42.720797],[-96.843419,42.712024],[-96.806223,42.704154],[-96.801652,42.698774],[-96.800485,42.692466],[-96.802178,42.672237],[-96.800986,42.669758],[-96.793238,42.666024],[-96.76406,42.661985],[-96.746949,42.666223],[-96.728024,42.666882],[-96.691269,42.6562],[-96.687669,42.653126],[-96.687788,42.645992],[-96.709485,42.621932],[-96.711546,42.614758],[-96.7093,42.603753],[-96.681369,42.574486],[-96.658754,42.566426],[-96.643589,42.557604],[-96.63533,42.54764],[-96.632882,42.528987],[-96.628179,42.516963],[-96.625958,42.513576],[-96.611489,42.506088],[-96.603468,42.50446],[-96.591121,42.50541],[-96.567896,42.517877],[-96.548791,42.520547],[-96.538036,42.518131],[-96.528753,42.513273],[-96.520683,42.504761],[-96.515891,42.49427],[-96.508587,42.486691],[-96.501321,42.482749],[-96.478792,42.479635],[-96.443408,42.489495],[-96.423892,42.48898],[-96.396107,42.484095],[-96.386007,42.474495],[-96.381307,42.461694],[-96.380707,42.446394],[-96.387608,42.432494],[-96.413609,42.407894],[-96.41498,42.393442],[-96.408436,42.376092],[-96.417093,42.361443],[-96.417786,42.351449],[-96.413895,42.343393],[-96.407998,42.337408],[-96.384169,42.325874],[-96.375307,42.318339],[-96.369212,42.308344],[-96.368454,42.291848],[-96.365792,42.285875],[-96.356406,42.276493],[-96.336003,42.264806],[-96.328905,42.254734],[-96.327706,42.249992],[-96.330004,42.240224],[-96.322868,42.233637],[-96.323723,42.229887],[-96.336323,42.218922],[-96.356591,42.215182],[-96.35987,42.210545],[-96.348066,42.194747],[-96.347243,42.186721],[-96.350323,42.17744],[-96.347752,42.166806],[-96.33798,42.157197],[-96.319528,42.146647],[-96.310085,42.132523],[-96.301023,42.128042],[-96.279203,42.12348],[-96.2689,42.11359],[-96.266594,42.103262],[-96.267636,42.096177],[-96.276758,42.081416],[-96.279079,42.074026],[-96.278445,42.060399],[-96.275548,42.051976],[-96.271427,42.044988],[-96.263886,42.039858],[-96.256087,42.03808],[-96.246832,42.041616],[-96.238392,42.041088],[-96.225656,42.035217],[-96.221901,42.029558],[-96.223611,42.022652],[-96.238859,42.012315],[-96.241932,42.006965],[-96.240713,41.999351],[-96.236487,41.996428],[-96.225463,41.994734],[-96.215225,42.006701],[-96.206083,42.009267],[-96.194556,42.008662],[-96.188067,42.006323],[-96.183568,41.999987],[-96.192141,41.984461],[-96.186265,41.977417],[-96.177203,41.976325],[-96.156538,41.980137],[-96.141228,41.978063],[-96.129505,41.971673],[-96.129186,41.965136],[-96.133318,41.955732],[-96.144583,41.941544],[-96.136613,41.927167],[-96.136743,41.920826],[-96.142265,41.915379],[-96.159098,41.910057],[-96.161988,41.905553],[-96.161756,41.90182],[-96.148826,41.888132],[-96.146083,41.874988],[-96.142045,41.868865],[-96.135253,41.863128],[-96.116202,41.854869],[-96.110246,41.84885],[-96.107911,41.840339],[-96.11081,41.828172],[-96.107592,41.820685],[-96.09827,41.814206],[-96.075548,41.807811],[-96.069662,41.803509],[-96.064879,41.79623],[-96.066413,41.788913],[-96.077543,41.777824],[-96.079915,41.757895],[-96.084673,41.753314],[-96.102772,41.746339],[-96.106425,41.73789],[-96.105582,41.731647],[-96.10261,41.728016],[-96.079682,41.717962],[-96.073376,41.710674],[-96.073063,41.705004],[-96.082429,41.698159],[-96.090579,41.697425],[-96.105119,41.699917],[-96.111968,41.697773],[-96.117751,41.694221],[-96.121401,41.688522],[-96.120983,41.677861],[-96.114978,41.67122],[-96.099837,41.66103],[-96.095415,41.652736],[-96.095046,41.647365],[-96.100701,41.635507],[-96.116233,41.621574],[-96.117558,41.609999],[-96.109387,41.596871],[-96.101496,41.59158],[-96.085771,41.585746],[-96.081152,41.577289],[-96.082406,41.571229],[-96.093613,41.558271],[-96.096186,41.547192],[-96.09409,41.539265],[-96.08822,41.530595],[-96.07307,41.525052],[-96.05369,41.508859],[-96.040701,41.507076],[-96.036603,41.509047],[-96.034305,41.512853],[-96.027289,41.541081],[-96.023182,41.544364],[-96.016474,41.546085],[-96.005079,41.544004],[-96.001161,41.541146],[-95.993891,41.523412],[-95.992833,41.512002],[-95.997903,41.504789],[-96.019224,41.489296],[-96.019542,41.486617],[-96.011757,41.476212],[-96.004708,41.472342],[-95.982962,41.469778],[-95.962329,41.46281],[-95.946465,41.466166],[-95.936801,41.46519],[-95.925713,41.459382],[-95.920281,41.451566],[-95.921833,41.442062],[-95.933169,41.42943],[-95.929721,41.411331],[-95.93749,41.393095],[-95.92879,41.370096],[-95.93099,41.364696],[-95.93549,41.360596],[-95.954891,41.351796],[-95.956691,41.345496],[-95.946891,41.334096],[-95.92569,41.322197],[-95.88869,41.319097],[-95.883089,41.316697],[-95.874689,41.307097],[-95.871489,41.295797],[-95.872889,41.289497],[-95.88239,41.281397],[-95.90249,41.273398],[-95.912491,41.279498],[-95.90429,41.293497],[-95.90429,41.299597],[-95.920291,41.301097],[-95.927491,41.298397],[-95.929591,41.292297],[-95.928691,41.281398],[-95.913991,41.271398],[-95.920391,41.268398],[-95.921891,41.264598],[-95.921291,41.258498],[-95.910891,41.233998],[-95.912591,41.226998],[-95.924891,41.211198],[-95.927491,41.202198],[-95.923219,41.191046],[-95.91459,41.185098],[-95.864789,41.188298],[-95.850188,41.184798],[-95.844088,41.180598],[-95.841288,41.174998],[-95.841888,41.171098],[-95.846188,41.166698],[-95.852788,41.165398],[-95.867344,41.168734],[-95.871912,41.168122],[-95.880936,41.160269],[-95.883489,41.154898],[-95.882088,41.143998],[-95.865888,41.117898],[-95.86545,41.101266],[-95.862587,41.088399],[-95.865463,41.080367],[-95.878103,41.069587],[-95.882415,41.060411],[-95.879487,41.053299],[-95.861782,41.039427],[-95.859654,41.035695],[-95.859918,41.025403],[-95.869486,41.009399],[-95.867286,41.001599],[-95.860116,40.995242],[-95.838908,40.986484],[-95.833537,40.98266],[-95.829074,40.975688],[-95.829829,40.963857],[-95.837951,40.950618],[-95.839743,40.93278],[-95.836438,40.921642],[-95.830699,40.915004],[-95.814302,40.902936],[-95.809775,40.895447],[-95.809474,40.891228],[-95.815933,40.879846],[-95.824989,40.875],[-95.838735,40.872191],[-95.844073,40.869248],[-95.847785,40.864328],[-95.847084,40.854174],[-95.837186,40.835347],[-95.838601,40.826175],[-95.843921,40.817686],[-95.845342,40.811324],[-95.843745,40.803783],[-95.834523,40.787778],[-95.835232,40.779151],[-95.84662,40.768619],[-95.869982,40.759645],[-95.883643,40.747831],[-95.888697,40.736292],[-95.885349,40.721093],[-95.883178,40.717579],[-95.859378,40.708055],[-95.852615,40.702262],[-95.847931,40.694197],[-95.846034,40.682605],[-95.842801,40.677496],[-95.822913,40.66724],[-95.804307,40.664886],[-95.786568,40.657253],[-95.772832,40.642496],[-95.768926,40.621264],[-95.749685,40.606842],[-95.748858,40.599965],[-95.753148,40.59284],[-95.768527,40.583296],[-95.773549,40.578205],[-95.774704,40.573574],[-95.763833,40.553873],[-95.763624,40.548298],[-95.769281,40.536656],[-95.76692,40.531563],[-95.762857,40.528371],[-95.74868,40.524275],[-95.73725,40.52393],[-95.725214,40.527773],[-95.714291,40.527208],[-95.708591,40.521551],[-95.69721,40.528477],[-95.69505,40.533124],[-95.697281,40.536985],[-95.694147,40.556942],[-95.678718,40.56256],[-95.671754,40.562626],[-95.665486,40.556686],[-95.662097,40.549959],[-95.655848,40.546609],[-95.652262,40.538114],[-95.655674,40.523557],[-95.661687,40.517309],[-95.699969,40.505275],[-95.694726,40.493602],[-95.696756,40.478849],[-95.694651,40.471452],[-95.671742,40.456695],[-95.65819,40.44188],[-95.65563,40.434736],[-95.661463,40.415947],[-95.659134,40.40869],[-95.643934,40.386849],[-95.641027,40.366399],[-95.627124,40.3528],[-95.623728,40.346567],[-95.622704,40.340856],[-95.625204,40.334288],[-95.633807,40.329297],[-95.653729,40.322582],[-95.657764,40.315788],[-95.657328,40.310856],[-95.651507,40.306684],[-95.645329,40.305693],[-95.617931,40.313728],[-95.610439,40.31397],[-95.598657,40.309809],[-95.581787,40.29958],[-95.562157,40.297359],[-95.55162,40.288666],[-95.551488,40.281061],[-95.556275,40.270761],[-95.552473,40.261904],[-95.521925,40.24947],[-95.490333,40.248966],[-95.477501,40.24272],[-95.472548,40.236078],[-95.469718,40.227908],[-95.471393,40.217333],[-95.482319,40.200667],[-95.48254,40.192283],[-95.479193,40.185652],[-95.460746,40.169173],[-95.442818,40.163261],[-95.436348,40.15872],[-95.432165,40.141025],[-95.428749,40.135577],[-95.419186,40.130586],[-95.409481,40.130052],[-95.398667,40.126419],[-95.393347,40.119212],[-95.394216,40.108263],[-95.407591,40.09803],[-95.410643,40.091531],[-95.408455,40.079158],[-95.409856,40.07432],[-95.418345,40.066509],[-95.42164,40.058952],[-95.41932,40.048442],[-95.413588,40.038424],[-95.402665,40.030567],[-95.391527,40.027058],[-95.382957,40.027112],[-95.363983,40.031498],[-95.348777,40.029297],[-95.336242,40.019104],[-95.315271,40.01207],[-95.311163,40.007806],[-95.30829,39.999998],[-98.193483,40.002614],[-99.756835,40.001342],[-102.051744,40.003078],[-102.051614,41.002377],[-104.053249,41.001406]]]},\"properties\":{\"name\":\"Nebraska\",\"nation\":\"USA \"}}]}","volume":"42","issue":"1","noUsgsAuthors":false,"publicationDate":"2018-01-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Bieber, N. R.","contributorId":273158,"corporation":false,"usgs":false,"family":"Bieber","given":"N.","email":"","middleInitial":"R.","affiliations":[{"id":36892,"text":"University of Nebraska","active":true,"usgs":false}],"preferred":false,"id":832635,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wilson, S. P.","contributorId":273159,"corporation":false,"usgs":false,"family":"Wilson","given":"S.","email":"","middleInitial":"P.","affiliations":[{"id":56368,"text":"Nebraska Game and Parks","active":true,"usgs":false}],"preferred":false,"id":832636,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Allen, Craig R. 0000-0001-8655-8272 allencr@usgs.gov","orcid":"https://orcid.org/0000-0001-8655-8272","contributorId":1979,"corporation":false,"usgs":true,"family":"Allen","given":"Craig","email":"allencr@usgs.gov","middleInitial":"R.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":832637,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70263443,"text":"70263443 - 2018 - River otter distribution in Nebraska","interactions":[],"lastModifiedDate":"2025-02-11T15:28:17.418219","indexId":"70263443","displayToPublicDate":"2018-01-07T09:25:34","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3779,"text":"Wildlife Society Bulletin","onlineIssn":"1938-5463","printIssn":"0091-7648","active":true,"publicationSubtype":{"id":10}},"title":"River otter distribution in Nebraska","docAbstract":"The river otter (Lontra canadensis) was extirpated from Nebraska, USA, in the early 1900s and reintroduced starting in 1986. Information is needed regarding the distribution of river otters in Nebraska before decisions can be made regarding its conservation status. Understanding distribution of a species is critically important for effective management. We investigated river otter distribution in Nebraska with occupancy modeling and maximum entropy (Maxent) modeling using 190 otter sign observations on Nebraska's navigable rivers and 380 historical otter records from November 1977 to April 2014. Both methods identified the Platte River, Elkhorn River, central and eastern Niobrara River, and southern Loup River system as core areas within the distribution of otters in Nebraska. The Maxent model provided more liberal estimates of site occupancy and identified some smaller rivers as being within the distribution of otters in Nebraska, which were not identified using occupancy modeling. We recommend that multiple data sets and analysis methods be used to estimate species distribution because this allows for the broadest geographical coverage and decreases the likelihood of overlooking areas with fewer animal records. If further reintroduction efforts or translocation efforts are to take place in the future, we recommend focusing on areas with high modeled occupancy but few historical and survey records.
","language":"English","publisher":"The Wildlife Society","doi":"10.1002/wsb.843","usgsCitation":"Bieber, N., Wilson, S., and Allen, C.R., 2018, River otter distribution in Nebraska: Wildlife Society Bulletin, v. 42, no. 1, p. 136-143, https://doi.org/10.1002/wsb.843.","productDescription":"8 p.","startPage":"136","endPage":"143","ipdsId":"IP-097555","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":499837,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doaj.org/article/08bde403cf22458cbb0e4cf09a97b49e","text":"External Repository"},{"id":481929,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nebraska","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-104.053249,41.001406],[-104.053127,43.000585],[-101.849982,42.999329],[-101.625424,42.996238],[-100.472742,42.999288],[-98.49855,42.99856],[-98.490483,42.977948],[-98.467356,42.947556],[-98.448309,42.936428],[-98.444145,42.929242],[-98.437285,42.928393],[-98.430934,42.931504],[-98.42074,42.931924],[-98.34623,42.902747],[-98.325864,42.8865],[-98.280007,42.874996],[-98.25181,42.872824],[-98.219826,42.853157],[-98.189765,42.841628],[-98.167523,42.836925],[-98.14806,42.840013],[-98.137912,42.832728],[-98.127489,42.820127],[-98.107688,42.810633],[-98.094574,42.799309],[-98.067388,42.784759],[-98.062913,42.781119],[-98.059838,42.772772],[-98.056625,42.770781],[-98.035034,42.764205],[-98.013046,42.762299],[-98.005739,42.764167],[-98.000348,42.763256],[-97.977588,42.769923],[-97.950147,42.769619],[-97.936716,42.775754],[-97.921434,42.788352],[-97.908983,42.794909],[-97.888562,42.817251],[-97.879878,42.835395],[-97.878976,42.843673],[-97.875849,42.847725],[-97.877003,42.854394],[-97.875345,42.858724],[-97.84527,42.867734],[-97.828496,42.868797],[-97.817075,42.861781],[-97.774456,42.849774],[-97.72045,42.847439],[-97.686506,42.842435],[-97.657846,42.844626],[-97.611811,42.858367],[-97.603762,42.858329],[-97.591916,42.853837],[-97.561928,42.847552],[-97.531867,42.850105],[-97.504847,42.858477],[-97.49149,42.851625],[-97.470529,42.850455],[-97.452177,42.846048],[-97.442279,42.846224],[-97.431951,42.851542],[-97.417066,42.865918],[-97.408315,42.868334],[-97.393966,42.86425],[-97.376695,42.865195],[-97.368643,42.858419],[-97.359569,42.854816],[-97.336156,42.856802],[-97.306677,42.867604],[-97.289859,42.855499],[-97.267946,42.852583],[-97.248556,42.855386],[-97.218825,42.845848],[-97.217411,42.843519],[-97.218269,42.829561],[-97.213957,42.820143],[-97.213084,42.813007],[-97.210126,42.809296],[-97.200431,42.805485],[-97.166978,42.802087],[-97.150763,42.795566],[-97.138216,42.783428],[-97.134461,42.774494],[-97.131331,42.771929],[-97.096128,42.76934],[-97.065592,42.772189],[-97.033229,42.765904],[-97.02485,42.76243],[-96.99282,42.759481],[-96.97912,42.76009],[-96.96888,42.754278],[-96.96123,42.740623],[-96.965833,42.727096],[-96.964776,42.722455],[-96.961576,42.719841],[-96.948902,42.719465],[-96.924156,42.730327],[-96.906797,42.7338],[-96.886845,42.725222],[-96.860436,42.720797],[-96.843419,42.712024],[-96.806223,42.704154],[-96.801652,42.698774],[-96.800485,42.692466],[-96.802178,42.672237],[-96.800986,42.669758],[-96.793238,42.666024],[-96.76406,42.661985],[-96.746949,42.666223],[-96.728024,42.666882],[-96.691269,42.6562],[-96.687669,42.653126],[-96.687788,42.645992],[-96.709485,42.621932],[-96.711546,42.614758],[-96.7093,42.603753],[-96.681369,42.574486],[-96.658754,42.566426],[-96.643589,42.557604],[-96.63533,42.54764],[-96.632882,42.528987],[-96.628179,42.516963],[-96.625958,42.513576],[-96.611489,42.506088],[-96.603468,42.50446],[-96.591121,42.50541],[-96.567896,42.517877],[-96.548791,42.520547],[-96.538036,42.518131],[-96.528753,42.513273],[-96.520683,42.504761],[-96.515891,42.49427],[-96.508587,42.486691],[-96.501321,42.482749],[-96.478792,42.479635],[-96.443408,42.489495],[-96.423892,42.48898],[-96.396107,42.484095],[-96.386007,42.474495],[-96.381307,42.461694],[-96.380707,42.446394],[-96.387608,42.432494],[-96.413609,42.407894],[-96.41498,42.393442],[-96.408436,42.376092],[-96.417093,42.361443],[-96.417786,42.351449],[-96.413895,42.343393],[-96.407998,42.337408],[-96.384169,42.325874],[-96.375307,42.318339],[-96.369212,42.308344],[-96.368454,42.291848],[-96.365792,42.285875],[-96.356406,42.276493],[-96.336003,42.264806],[-96.328905,42.254734],[-96.327706,42.249992],[-96.330004,42.240224],[-96.322868,42.233637],[-96.323723,42.229887],[-96.336323,42.218922],[-96.356591,42.215182],[-96.35987,42.210545],[-96.348066,42.194747],[-96.347243,42.186721],[-96.350323,42.17744],[-96.347752,42.166806],[-96.33798,42.157197],[-96.319528,42.146647],[-96.310085,42.132523],[-96.301023,42.128042],[-96.279203,42.12348],[-96.2689,42.11359],[-96.266594,42.103262],[-96.267636,42.096177],[-96.276758,42.081416],[-96.279079,42.074026],[-96.278445,42.060399],[-96.275548,42.051976],[-96.271427,42.044988],[-96.263886,42.039858],[-96.256087,42.03808],[-96.246832,42.041616],[-96.238392,42.041088],[-96.225656,42.035217],[-96.221901,42.029558],[-96.223611,42.022652],[-96.238859,42.012315],[-96.241932,42.006965],[-96.240713,41.999351],[-96.236487,41.996428],[-96.225463,41.994734],[-96.215225,42.006701],[-96.206083,42.009267],[-96.194556,42.008662],[-96.188067,42.006323],[-96.183568,41.999987],[-96.192141,41.984461],[-96.186265,41.977417],[-96.177203,41.976325],[-96.156538,41.980137],[-96.141228,41.978063],[-96.129505,41.971673],[-96.129186,41.965136],[-96.133318,41.955732],[-96.144583,41.941544],[-96.136613,41.927167],[-96.136743,41.920826],[-96.142265,41.915379],[-96.159098,41.910057],[-96.161988,41.905553],[-96.161756,41.90182],[-96.148826,41.888132],[-96.146083,41.874988],[-96.142045,41.868865],[-96.135253,41.863128],[-96.116202,41.854869],[-96.110246,41.84885],[-96.107911,41.840339],[-96.11081,41.828172],[-96.107592,41.820685],[-96.09827,41.814206],[-96.075548,41.807811],[-96.069662,41.803509],[-96.064879,41.79623],[-96.066413,41.788913],[-96.077543,41.777824],[-96.079915,41.757895],[-96.084673,41.753314],[-96.102772,41.746339],[-96.106425,41.73789],[-96.105582,41.731647],[-96.10261,41.728016],[-96.079682,41.717962],[-96.073376,41.710674],[-96.073063,41.705004],[-96.082429,41.698159],[-96.090579,41.697425],[-96.105119,41.699917],[-96.111968,41.697773],[-96.117751,41.694221],[-96.121401,41.688522],[-96.120983,41.677861],[-96.114978,41.67122],[-96.099837,41.66103],[-96.095415,41.652736],[-96.095046,41.647365],[-96.100701,41.635507],[-96.116233,41.621574],[-96.117558,41.609999],[-96.109387,41.596871],[-96.101496,41.59158],[-96.085771,41.585746],[-96.081152,41.577289],[-96.082406,41.571229],[-96.093613,41.558271],[-96.096186,41.547192],[-96.09409,41.539265],[-96.08822,41.530595],[-96.07307,41.525052],[-96.05369,41.508859],[-96.040701,41.507076],[-96.036603,41.509047],[-96.034305,41.512853],[-96.027289,41.541081],[-96.023182,41.544364],[-96.016474,41.546085],[-96.005079,41.544004],[-96.001161,41.541146],[-95.993891,41.523412],[-95.992833,41.512002],[-95.997903,41.504789],[-96.019224,41.489296],[-96.019542,41.486617],[-96.011757,41.476212],[-96.004708,41.472342],[-95.982962,41.469778],[-95.962329,41.46281],[-95.946465,41.466166],[-95.936801,41.46519],[-95.925713,41.459382],[-95.920281,41.451566],[-95.921833,41.442062],[-95.933169,41.42943],[-95.929721,41.411331],[-95.93749,41.393095],[-95.92879,41.370096],[-95.93099,41.364696],[-95.93549,41.360596],[-95.954891,41.351796],[-95.956691,41.345496],[-95.946891,41.334096],[-95.92569,41.322197],[-95.88869,41.319097],[-95.883089,41.316697],[-95.874689,41.307097],[-95.871489,41.295797],[-95.872889,41.289497],[-95.88239,41.281397],[-95.90249,41.273398],[-95.912491,41.279498],[-95.90429,41.293497],[-95.90429,41.299597],[-95.920291,41.301097],[-95.927491,41.298397],[-95.929591,41.292297],[-95.928691,41.281398],[-95.913991,41.271398],[-95.920391,41.268398],[-95.921891,41.264598],[-95.921291,41.258498],[-95.910891,41.233998],[-95.912591,41.226998],[-95.924891,41.211198],[-95.927491,41.202198],[-95.923219,41.191046],[-95.91459,41.185098],[-95.864789,41.188298],[-95.850188,41.184798],[-95.844088,41.180598],[-95.841288,41.174998],[-95.841888,41.171098],[-95.846188,41.166698],[-95.852788,41.165398],[-95.867344,41.168734],[-95.871912,41.168122],[-95.880936,41.160269],[-95.883489,41.154898],[-95.882088,41.143998],[-95.865888,41.117898],[-95.86545,41.101266],[-95.862587,41.088399],[-95.865463,41.080367],[-95.878103,41.069587],[-95.882415,41.060411],[-95.879487,41.053299],[-95.861782,41.039427],[-95.859654,41.035695],[-95.859918,41.025403],[-95.869486,41.009399],[-95.867286,41.001599],[-95.860116,40.995242],[-95.838908,40.986484],[-95.833537,40.98266],[-95.829074,40.975688],[-95.829829,40.963857],[-95.837951,40.950618],[-95.839743,40.93278],[-95.836438,40.921642],[-95.830699,40.915004],[-95.814302,40.902936],[-95.809775,40.895447],[-95.809474,40.891228],[-95.815933,40.879846],[-95.824989,40.875],[-95.838735,40.872191],[-95.844073,40.869248],[-95.847785,40.864328],[-95.847084,40.854174],[-95.837186,40.835347],[-95.838601,40.826175],[-95.843921,40.817686],[-95.845342,40.811324],[-95.843745,40.803783],[-95.834523,40.787778],[-95.835232,40.779151],[-95.84662,40.768619],[-95.869982,40.759645],[-95.883643,40.747831],[-95.888697,40.736292],[-95.885349,40.721093],[-95.883178,40.717579],[-95.859378,40.708055],[-95.852615,40.702262],[-95.847931,40.694197],[-95.846034,40.682605],[-95.842801,40.677496],[-95.822913,40.66724],[-95.804307,40.664886],[-95.786568,40.657253],[-95.772832,40.642496],[-95.768926,40.621264],[-95.749685,40.606842],[-95.748858,40.599965],[-95.753148,40.59284],[-95.768527,40.583296],[-95.773549,40.578205],[-95.774704,40.573574],[-95.763833,40.553873],[-95.763624,40.548298],[-95.769281,40.536656],[-95.76692,40.531563],[-95.762857,40.528371],[-95.74868,40.524275],[-95.73725,40.52393],[-95.725214,40.527773],[-95.714291,40.527208],[-95.708591,40.521551],[-95.69721,40.528477],[-95.69505,40.533124],[-95.697281,40.536985],[-95.694147,40.556942],[-95.678718,40.56256],[-95.671754,40.562626],[-95.665486,40.556686],[-95.662097,40.549959],[-95.655848,40.546609],[-95.652262,40.538114],[-95.655674,40.523557],[-95.661687,40.517309],[-95.699969,40.505275],[-95.694726,40.493602],[-95.696756,40.478849],[-95.694651,40.471452],[-95.671742,40.456695],[-95.65819,40.44188],[-95.65563,40.434736],[-95.661463,40.415947],[-95.659134,40.40869],[-95.643934,40.386849],[-95.641027,40.366399],[-95.627124,40.3528],[-95.623728,40.346567],[-95.622704,40.340856],[-95.625204,40.334288],[-95.633807,40.329297],[-95.653729,40.322582],[-95.657764,40.315788],[-95.657328,40.310856],[-95.651507,40.306684],[-95.645329,40.305693],[-95.617931,40.313728],[-95.610439,40.31397],[-95.598657,40.309809],[-95.581787,40.29958],[-95.562157,40.297359],[-95.55162,40.288666],[-95.551488,40.281061],[-95.556275,40.270761],[-95.552473,40.261904],[-95.521925,40.24947],[-95.490333,40.248966],[-95.477501,40.24272],[-95.472548,40.236078],[-95.469718,40.227908],[-95.471393,40.217333],[-95.482319,40.200667],[-95.48254,40.192283],[-95.479193,40.185652],[-95.460746,40.169173],[-95.442818,40.163261],[-95.436348,40.15872],[-95.432165,40.141025],[-95.428749,40.135577],[-95.419186,40.130586],[-95.409481,40.130052],[-95.398667,40.126419],[-95.393347,40.119212],[-95.394216,40.108263],[-95.407591,40.09803],[-95.410643,40.091531],[-95.408455,40.079158],[-95.409856,40.07432],[-95.418345,40.066509],[-95.42164,40.058952],[-95.41932,40.048442],[-95.413588,40.038424],[-95.402665,40.030567],[-95.391527,40.027058],[-95.382957,40.027112],[-95.363983,40.031498],[-95.348777,40.029297],[-95.336242,40.019104],[-95.315271,40.01207],[-95.311163,40.007806],[-95.30829,39.999998],[-98.193483,40.002614],[-99.756835,40.001342],[-102.051744,40.003078],[-102.051614,41.002377],[-104.053249,41.001406]]]},\"properties\":{\"name\":\"Nebraska\",\"nation\":\"USA \"}}]}","volume":"42","issue":"1","noUsgsAuthors":false,"publicationDate":"2018-01-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Bieber, N.R.","contributorId":350797,"corporation":false,"usgs":false,"family":"Bieber","given":"N.R.","affiliations":[{"id":36892,"text":"University of Nebraska","active":true,"usgs":false}],"preferred":false,"id":927011,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wilson, S.P.","contributorId":341215,"corporation":false,"usgs":false,"family":"Wilson","given":"S.P.","email":"","affiliations":[{"id":17640,"text":"Nebraska Game and Parks Commission","active":true,"usgs":false}],"preferred":false,"id":927012,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Allen, Craig R. 0000-0001-8655-8272 allencr@usgs.gov","orcid":"https://orcid.org/0000-0001-8655-8272","contributorId":1979,"corporation":false,"usgs":true,"family":"Allen","given":"Craig","email":"allencr@usgs.gov","middleInitial":"R.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":927013,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70194678,"text":"sir20175157 - 2018 - Simulation of hydrodynamics, water quality, and lake sturgeon habitat volumes in Lake St. Croix, Wisconsin and Minnesota, 2013","interactions":[],"lastModifiedDate":"2019-10-23T12:29:22","indexId":"sir20175157","displayToPublicDate":"2018-01-05T16:45:00","publicationYear":"2018","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":"2017-5157","title":"Simulation of hydrodynamics, water quality, and lake sturgeon habitat volumes in Lake St. Croix, Wisconsin and Minnesota, 2013","docAbstract":"Lake St. Croix is a naturally impounded, riverine lake that makes up the last 40 kilometers of the St. Croix River. Substantial land-use changes during the past 150 years, including increased agriculture and urban development, have reduced Lake St. Croix water-quality and increased nutrient loads delivered to Lake St. Croix. A recent (2012–13) total maximum daily load phosphorus-reduction plan set the goal to reduce total phosphorus loads to Lake St. Croix by 20 percent by 2020 and reduce Lake St. Croix algal bloom frequencies. The U.S. Geological Survey, in cooperation with the National Park Service, developed a two-dimensional, carbon-based, laterally averaged, hydrodynamic and water-quality model, CE–QUAL–W2, that addresses the interaction between nutrient cycling, primary production, and trophic dynamics to predict responses in the distribution of water temperature, oxygen, and chlorophyll a. Distribution is evaluated in the context of habitat for lake sturgeon, including a combination of temperature and dissolved oxygen conditions termed oxy-thermal habitat.
The Lake St. Croix CE–QUAL–W2 model successfully reproduced temperature and dissolved oxygen in the lake longitudinally (from upstream to downstream), vertically, and temporally over the seasons. The simulated water temperature profiles closely matched the measured water temperature profiles throughout the year, including the prediction of thermocline transition depths (often within 1 meter), the absolute temperature of the thermocline transitions (often within 1.0 degree Celsius), and profiles without a strong thermocline transition. Simulated dissolved oxygen profiles matched the trajectories of the measured dissolved oxygen concentrations at multiple depths over time, and the simulated concentrations matched the depth and slope of the measured concentrations.
Additionally, trends in the measured water-quality data were captured by the model simulation, gaining some potential insights into the underlying mechanisms of critical Lake St. Croix metabolic processes. The CE–QUAL–W2 model tracked nitrate plus nitrite, total nitrogen, and total phosphorus throughout the year. Inflow nutrient contributions (loads), largely dominated by upstream St. Croix River loads, were the most important controls on Lake St. Croix water quality. Close to 60 percent of total phosphorus to the lake was from phosphorus derived from organic matter, and about 89 percent of phosphorus to Lake St. Croix was delivered by St. Croix River inflows. The Lake St. Croix CE–QUAL–W2 model offered potential mechanisms for the effect of external and internal loadings on the biotic response regarding the modeled algal community types of diatoms, green algae, and blue-green algae. The model also suggested the seasonal dominance of blue-green algae in all four pools of the lake.
A sensitivity analysis was completed to test the total maximum daily load phosphorus-reduction scenario responses of total phosphorus and chlorophyll a. The modeling indicates that phosphorus reductions would result in similar Lake St. Croix reduced concentrations, although chlorophyll a concentrations did not decrease in the same proportional amounts as the total phosphorus concentrations had decreased. The smaller than expected reduction in algal growth rates highlighted that although inflow phosphorus loads are important, other constituents also can affect the algal response of the lake, such as changes in light penetration and the breakdown of organic matter releasing nutrients.
The available habitat suitable for lake sturgeon was evaluated using the modeling results to determine the total volume of good-growth habitat, optimal growth habitat, and lethal temperature habitat. Overall, with the calibrated model, the fish habitat volume in general contained a large proportion of good-growth habitat and a sustained period of optimal growth habitat in the summer. Only brief periods of lethal oxy-thermal habitat were present in Lake St. Croix during the model simulation.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175157","collaboration":"Prepared in cooperation with the National Park Service","usgsCitation":"Smith, E.A., Kiesling, R.L., Ziegeweid, J.R., Elliott, S.M., and Magdalene, Suzanne, 2018, Simulation of hydrodynamics, water quality, and lake sturgeon habitat volumes in Lake St. Croix, Wisconsin and Minnesota, 2013: U.S. Geological Survey Scientific Investigations Report 2017–5157, 60 p., https://doi.org/10.3133/sir20175157.","productDescription":"Report: ix, 60 p.; Data Release","numberOfPages":"74","onlineOnly":"Y","ipdsId":"IP-075804","costCenters":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"links":[{"id":350333,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7319V2J","text":"USGS data release","description":"USGS data release","linkHelpText":"CE–QUAL–W2 water-quality model and supporting LOADEST models for Lake St. Croix, Wisconsin and Minnesota, 2013"},{"id":350332,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5157/sir20175157.pdf","text":"Report","size":"3.30 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017–5157"},{"id":350331,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5157/coverthb.jpg"}],"country":"United States","state":"Minnesota, Wisconsin","otherGeospatial":"Lake St. Croix","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -92.81936645507811,\n 44.74136858658327\n ],\n [\n -92.73216247558594,\n 44.74136858658327\n ],\n [\n -92.73216247558594,\n 45.07352060670971\n ],\n [\n -92.81936645507811,\n 45.07352060670971\n ],\n [\n -92.81936645507811,\n 44.74136858658327\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Upper Midwest Water Science Center
U.S. Geological Survey
2280 Woodale Drive
Mounds View, MN 55112
Auklets (Aethia spp.) are small seabirds, endemic to the North Pacific Ocean, that nest in rock crevices on islands in Alaska and Russia. Nesting habitats for least (A. pusilla) and crested (A. cristatella) auklet colonies in the southern part of their range (Aleutian and Kuril Islands) are becoming overgrown by vegetation, which is fertilized by the auklets, making rock crevices unavailable for breeding. Colonization of newly created volcanic habitats suggests that auklets are habitat-limited in the southern range. The largest colonies there of least and crested auklets exist on lava slopes <100 years old. We propose that in the south, volcanic activity is required to maintain auklet populations. In contrast, colonies in the northern Bering Sea and Sea of Okhotsk show no indication of habitat limitation. They occur in more persistent talus slope habitats maintained by weathering, slumping, frost heaving, and tumbling. Biological processes there are slower and vegetation communities not as developed. We propose a conceptual model describing the interaction of geological and biological processes that influence auklet demography. We conclude that least and crested auklets require episodic disturbance (provided by volcanoes, earthquakes, and rock fall deposits) to maintain access to nest crevices. Auklets thereby provide an example of disturbance-adapted, early successional species that self-inhibit if their habitat is not regularly disturbed.
From August 2016 to March 2017, the U.S. Geological Survey (USGS) collected representative samples of filtered and unfiltered water and suspended sediment (including the colloidal fraction) at USGS streamgage 12113390 (Duwamish River at Golf Course, at Tukwila, Washington) during 13 periods of differing flow conditions. Samples were analyzed by Washington-State-accredited laboratories for a large suite of compounds, including metals, dioxins/furans, semivolatile compounds including polycyclic aromatic hydrocarbons, butyltins, the 209 polychlorinated biphenyl (PCB) congeners, and total and dissolved organic carbon. Concurrent with the chemistry sampling, water-quality field parameters were measured, and representative water samples were collected and analyzed for river suspended-sediment concentration and particle-size distribution. The results provide new data that can be used to estimate sediment and chemical loads transported by the Green River to the Lower Duwamish Waterway.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds1073","collaboration":"Prepared in cooperation with the Washington State Department of Ecology","usgsCitation":"Conn, K.E., Black, R.W., Peterson, N.T., Senter, C.A., and Chapman, E.A., 2018, Chemical concentrations in water and\nsuspended sediment, Green River to Lower Duwamish Waterway near Seattle, Washington, 2016–17: U.S. Geological\nSurvey Data Series 1073, 17 p., https://doi.org/10.3133/ds1073.","productDescription":"Report: v, 17 p.; Appendix","numberOfPages":"28","onlineOnly":"Y","ipdsId":"IP-091233","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":350280,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/ds/1073/ds1073_appendixa.xlsx","text":"Appendix A","size":"259 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"DS 1073 Appendix A"},{"id":350278,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/1073/coverthb.jpg"},{"id":350279,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/1073/ds1073.pdf","text":"Report","size":"1.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DS 1073"}],"country":"United States","state":"Washington","city":"Seattle","otherGeospatial":"Green River, Lower Duwamish Waterway","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.35507965087889,\n 47.50931654292719\n ],\n [\n -122.29499816894531,\n 47.50931654292719\n ],\n [\n -122.29499816894531,\n 47.572124991940015\n ],\n [\n -122.35507965087889,\n 47.572124991940015\n ],\n [\n -122.35507965087889,\n 47.50931654292719\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Washington Water Science Center
U.S. Geological Survey
934 Broadway, Suite 300
Tacoma, Washington 98402
Liming techniques are being explored as a means to accelerate the recovery of aquatic biota from decades of acid deposition in many regions. The preservation or restoration of native sportfish populations has typically been the impetus for liming programs, and as such, less attention has been given to its effects on other biological assemblages such as macroinvertebrates. Furthermore, the differing effects of various lime application strategies such as in-stream and watershed applications are not well understood. In 2012, a program was initiated using in-stream and aerial (whole-watershed) liming to improve water quality and Brook Trout (Salvelinus fontinalis) recruitment in three acidified tributaries of a high-elevation Adirondack lake in New York State. Concurrently, macroinvertebrates were sampled annually between 2013 and 2016 at 3 treated sites and 3 untreated reference sites to assess the effects of each liming technique on this community. Despite improvements in water chemistry in all three limed streams, our results generally suggest that neither liming technique succeeded in improving the condition of macroinvertebrate communities. The watershed application caused an immediate and unsustained decrease in the density of macroinvertebrates and increase in the proportion of sensitive taxa. These changes were driven primarily by a one-year 71 percent reduction of the acid-tolerant Leuctra stoneflies and likely represent an initial chemistry shock from the lime application rather than a recovery response. The in-stream applications appeared to reduce the density of macroinvertebrates, particularly in one stream where undissolved lime covered the natural substrate. The close proximity of our study sites to the in-stream application points (50 and 1230 m) may partly explain these negative effects. Our results are consistent with prior studies of in-stream liming which indicate that this technique often fails to restore macroinvertebrate communities to a pre-acidification condition, especially at distances <1.5 km downstream of the lime application point. The inability of either liming technique to improve the condition of macroinvertebrate communities may be partly explained by the persistence of acidic episodes in all three streams. This suggests that in order to be effective, liming programs should attempt to eliminate even temporary episodes of unsuitable water chemistry rather than just meeting minimal criteria the majority of the time. Because watershed liming produced a more stable water chemistry regime than in-stream liming, this technique may have greater future potential to eliminate toxic episodes and accelerate the recovery of acid-impacted macroinvertebrate communities.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolind.2017.11.048","usgsCitation":"George, S.D., Baldigo, B.P., Lawrence, G.B., and Fuller, R.L., 2018, Effects of watershed and in-stream liming on macroinvertebrate communities in acidified tributaries to an Adirondack lake: Ecological Indicators, v. 85, no. February 2018, p. 1058-1067, https://doi.org/10.1016/j.ecolind.2017.11.048.","productDescription":"10 p.","startPage":"1058","endPage":"1067","ipdsId":"IP-080307","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":350330,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New York","otherGeospatial":"Honnedaga Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -74.88006591796874,\n 43.50174856516506\n ],\n [\n -74.76848602294922,\n 43.50174856516506\n ],\n [\n -74.76848602294922,\n 43.55203173091177\n ],\n [\n -74.88006591796874,\n 43.55203173091177\n ],\n [\n -74.88006591796874,\n 43.50174856516506\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"85","issue":"February 2018","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a60fad1e4b06e28e9c22727","contributors":{"authors":[{"text":"George, Scott D. 0000-0002-8197-1866 sgeorge@usgs.gov","orcid":"https://orcid.org/0000-0002-8197-1866","contributorId":3014,"corporation":false,"usgs":true,"family":"George","given":"Scott","email":"sgeorge@usgs.gov","middleInitial":"D.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":724815,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Baldigo, Barry P. 0000-0002-9862-9119 bbaldigo@usgs.gov","orcid":"https://orcid.org/0000-0002-9862-9119","contributorId":1234,"corporation":false,"usgs":true,"family":"Baldigo","given":"Barry","email":"bbaldigo@usgs.gov","middleInitial":"P.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":724816,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lawrence, Gregory B. 0000-0002-8035-2350 glawrenc@usgs.gov","orcid":"https://orcid.org/0000-0002-8035-2350","contributorId":867,"corporation":false,"usgs":true,"family":"Lawrence","given":"Gregory","email":"glawrenc@usgs.gov","middleInitial":"B.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":724818,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fuller, Randall L.","contributorId":196969,"corporation":false,"usgs":false,"family":"Fuller","given":"Randall","email":"","middleInitial":"L.","affiliations":[{"id":35994,"text":"Colgate University, Hamilton, NY","active":true,"usgs":false}],"preferred":false,"id":724817,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ]}