The Florida Coastal Mapping Program is a nascent but highly relevant program that has the potential to greatly enhance the “Blue Economy” of Florida by coordinating and facilitating sea-floor mapping efforts and aligning partner and stakeholder activities for increased efficiency and cost reduction. Sustained acquisition of modern coastal mapping information for Florida may improve management of resources and reduce costs by eliminating redundancy. Economic growth could be aided by improved data to support emerging sectors such as aquaculture and renewable energy.
The present focus of the Florida Coastal Mapping Program is on modern, high-resolution bathymetric and coastal topobathymetric data, which can be immediately used to update navigational charts and identify navigation hazards, provide fundamental baseline data for scientific research, and provide information for use by emergency managers and responders. Derivative products include identifying sand resources for beach nourishment, creating vastly improved models for coastal erosion and flooding, identifying coastal springs, and creating benthic habitat maps. The uses and applications of the data generated could grow over time. The process of creating a steering committee and technical team, conducting an inventory and gaps analysis, soliciting feedback from the stakeholder and partner communities, and developing a prioritization process has provided a framework on which a successful program can develop a sustainable funding strategy that may be an investment the citizens of Florida could benefit from for decades.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191017","collaboration":"Prepared in cooperation with the Florida Institute of Oceanography, Florida Fish and Wildlife Research Institute, and Florida Department of Environmental Protection","usgsCitation":"Hapke, C.J., Kramer, P.A., Fetherston-Resch, E.H., Baumstark, R.D., Druyor, R., Fredericks, X., and Fitos, E., 2019, Florida Coastal Mapping Program—Overview and 2018 workshop report: U.S. Geological Survey Open-File Report 2019–1017, 19 p., https://doi.org/10.3133/ofr20191017.","productDescription":"vii, 19 p.","numberOfPages":"28","ipdsId":"IP-099357","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":361829,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1017/ofr20191017.pdf","text":"Report","size":"5.02 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019-1017"},{"id":361828,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1017/coverthb.jpg"}],"country":"United States","state":"Florida","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.00,\n 24.5\n ],\n [\n -80,\n 24.5\n ],\n [\n -80,\n 30.75\n ],\n [\n -88.00,\n 30.75\n ],\n [\n -88.00,\n 24.5\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, St. Petersburg Coastal and Marine Science Center
U.S. Geological Survey
600 Fourth Street South
St. Petersburg, FL 33701
We mapped yearly (2000–2016) estimates of annual grass percent cover for much of the sagebrush ecosystem of the western United States using remotely sensed, climate, and geophysical data in regression-tree models. Annual grasses senesce and cure by early summer and then become beds of fine fuel that easily ignite and spread fire through rangeland systems. Our annual maps estimate the extent of these fuels and can serve as a tool to assist land managers and scientists in understanding the ecosystem’s response to weather variations, disturbances, and management. Validating the time series of annual maps is important for determining the usefulness of the data. To validate these maps, we compare Bureau of Land Management Assessment Inventory and Monitoring (AIM) data to mapped estimates and use a leave-one-out spatial assessment technique that is effective for validating maps that cover broad geographical extents. We hypothesize that the time series of annual maps exhibits high spatiotemporal variability because precipitation is highly variable in arid and semiarid environments where sagebrush is native, and invasive annual grasses respond to precipitation. The remotely sensed data that help drive our regression-tree model effectively measures annual grasses’ response to precipitation. The mean absolute error (MAE) rate varied depending on the validation data and technique used for comparison. The AIM plot data and our maps had substantial spatial incongruence, but despite this, the MAE rate for the assessment equaled 12.62%. The leave-one-out accuracy assessment had an MAE of 8.43%. We quantified bias, and bias was more substantial at higher percent cover. These annual maps can help management identify actions that may alleviate the current cycle of invasive grasses because it enables the assessment of the variability of annual grass − percent cover distribution through space and time, as part of dynamic systems rather than static systems.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.rama.2018.09.004","usgsCitation":"Boyte, S.P., Wylie, B.K., and Major, D.J., 2019, Validating a time series of annual grass percent cover in the sagebrush ecosystem: Rangeland Ecology and Management, v. 72, no. 2, p. 347-359, https://doi.org/10.1016/j.rama.2018.09.004.","productDescription":"13 p.","startPage":"347","endPage":"359","ipdsId":"IP-101002","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":467831,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.rama.2018.09.004","text":"Publisher Index Page"},{"id":437546,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F71J98QK","text":"USGS data release","linkHelpText":"A Time Series of Herbaceous Annual Cover in the Sagebrush Ecosystem"},{"id":361853,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"72","issue":"2","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Boyte, Stephen P. 0000-0002-5462-3225 sboyte@usgs.gov","orcid":"https://orcid.org/0000-0002-5462-3225","contributorId":139238,"corporation":false,"usgs":true,"family":"Boyte","given":"Stephen","email":"sboyte@usgs.gov","middleInitial":"P.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":758988,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wylie, Bruce K. 0000-0002-7374-1083 wylie@usgs.gov","orcid":"https://orcid.org/0000-0002-7374-1083","contributorId":750,"corporation":false,"usgs":true,"family":"Wylie","given":"Bruce","email":"wylie@usgs.gov","middleInitial":"K.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":758989,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Major, Donald J.","contributorId":83405,"corporation":false,"usgs":false,"family":"Major","given":"Donald","email":"","middleInitial":"J.","affiliations":[{"id":7217,"text":"Bureau of Land Management","active":true,"usgs":false}],"preferred":false,"id":758990,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70205225,"text":"70205225 - 2019 - Dark halos produced by current impact cratering on Mars","interactions":[],"lastModifiedDate":"2019-09-09T12:04:09","indexId":"70205225","displayToPublicDate":"2019-03-07T12:01:25","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1963,"text":"Icarus","active":true,"publicationSubtype":{"id":10}},"title":"Dark halos produced by current impact cratering on Mars","docAbstract":"Hundreds of new impact craters have been observed to form on Mars since spacecraft began imaging that planet. New impact craters produced visible ejecta deposits and many of them also have visible rays, similar to lunar and mercurian craters. However, some of the new martian impact craters have a circular feature of relatively low reflectance that we call a “halo.” This feature is distinct from the usual visible ejecta deposits or ray patterns. In this paper we present an observational study of this halo feature and we discuss the results of this study with respect to the nature of the halos: what they are and how they may have formed. To address these questions, we measured diameters of both halos and their central craters. We found a strong correlation between halo diameter and crater diameter, which indicates that the nature of the halos is fundamentally governed by the amount of impact energy available at their formation. Specifically, halo size is controlled by impact energy according to the non-linear relationship DH ∝ E2/3, where DH is the diameter of the halo and E is the impact energy. We also found that certain factors may influence the formation of the halos: a thicker dust layer and lower elevations are both correlated with larger halos. From these correlations we conclude that the local surface characteristics as well as local atmospheric pressure influence the formation of the halos. Our description and analysis of the martian halo features provide a framework upon which specific halo formation mechanisms can be developed and tested in the future.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.icarus.2019.03.004","usgsCitation":"Bart, G.D., Daubar, I.J., Ivanov, B.A., Dundas, C.M., and McEwen, A.S., 2019, Dark halos produced by current impact cratering on Mars: Icarus, v. 328, p. 45-57, https://doi.org/10.1016/j.icarus.2019.03.004.","productDescription":"13 p.","startPage":"45","endPage":"57","ipdsId":"IP-102841","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":467832,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.icarus.2019.03.004","text":"Publisher Index Page"},{"id":367289,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Mars","volume":"328","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Bart, Gwendolyn D.","contributorId":210489,"corporation":false,"usgs":false,"family":"Bart","given":"Gwendolyn","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":770448,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Daubar, Ingrid J.","contributorId":204233,"corporation":false,"usgs":false,"family":"Daubar","given":"Ingrid","email":"","middleInitial":"J.","affiliations":[{"id":7023,"text":"Jet Propulsion Laboratory, California Institute of Technology","active":true,"usgs":false}],"preferred":false,"id":770449,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ivanov, Boris A","contributorId":218831,"corporation":false,"usgs":false,"family":"Ivanov","given":"Boris","email":"","middleInitial":"A","affiliations":[{"id":39920,"text":"Institute for Dynamics of Geospheres","active":true,"usgs":false}],"preferred":false,"id":770450,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dundas, Colin M. 0000-0003-2343-7224 cdundas@usgs.gov","orcid":"https://orcid.org/0000-0003-2343-7224","contributorId":2937,"corporation":false,"usgs":true,"family":"Dundas","given":"Colin","email":"cdundas@usgs.gov","middleInitial":"M.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":770447,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McEwen, Alfred S.","contributorId":61657,"corporation":false,"usgs":false,"family":"McEwen","given":"Alfred","email":"","middleInitial":"S.","affiliations":[{"id":7042,"text":"University of Arizona","active":true,"usgs":false}],"preferred":false,"id":770451,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70202528,"text":"70202528 - 2019 - Evidence for plunging river plume deposits in the Pahrump Hills member of the Murray formation, Gale crater, Mars","interactions":[],"lastModifiedDate":"2019-07-23T12:29:25","indexId":"70202528","displayToPublicDate":"2019-03-07T11:15:41","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3369,"text":"Sedimentology","active":true,"publicationSubtype":{"id":10}},"title":"Evidence for plunging river plume deposits in the Pahrump Hills member of the Murray formation, Gale crater, Mars","docAbstract":"Recent robotic missions to Mars have offered new insights into the extent, diversity and habitability of the Martian sedimentary rock record. Since the Curiosity rover landed in Gale crater in August 2012, the Mars Science Laboratory Science Team has explored the origins and habitability of ancient fluvial, deltaic, lacustrine and aeolian deposits preserved within the crater. This study describes the sedimentology of a ca 13 m thick succession named the Pahrump Hills member of the Murray formation, the first thick fine‐grained deposit discovered in situ on Mars. This work evaluates the depositional processes responsible for its formation and reconstructs its palaeoenvironmental setting. The Pahrump Hills succession can be sub‐divided into four distinct sedimentary facies: (i) thinly laminated mudstone; (ii) low‐angle cross‐stratified mudstone; (iii) cross‐stratified sandstone; and (iv) thickly laminated mudstone–sandstone. The very fine grain size of the mudstone facies and abundant millimetre‐scale and sub‐millimetre‐scale laminations exhibiting quasi‐uniform thickness throughout the Pahrump Hills succession are most consistent with lacustrine deposition. Low‐angle geometric discordances in the mudstone facies are interpreted as ‘scour and drape’ structures and suggest the action of currents, such as those associated with hyperpycnal river‐generated plumes plunging into a lake. Observation of an overall upward coarsening in grain size and thickening of laminae throughout the Pahrump Hills succession is consistent with deposition from basinward progradation of a fluvial‐deltaic system derived from the northern crater rim into the Gale crater lake. Palaeohydraulic modelling constrains the salinity of the ancient lake in Gale crater: assuming river sediment concentrations typical of floods on Earth, plunging river plumes and sedimentary structures like those observed at Pahrump Hills would have required lake densities near freshwater to form. The depositional model for the Pahrump Hills member presented here implies the presence of an ancient sustained, habitable freshwater lake in Gale crater for at least ca 103 to 107 Earth years.
","language":"English","publisher":"Wiley","doi":"10.1111/sed.12558","usgsCitation":"Stack, K.M., Grotzinger, J.P., Lamb, M.P., Gupta, S., Rubin, D.M., Kah, L.C., Edgar, L.A., Fey, D.M., Hurowitz, J.A., McBride, M.J., Rivera-Hernandez, F., Sumner, D.Y., Van Beek, J.K., Williams, R.M., and Yingst, R.A., 2019, Evidence for plunging river plume deposits in the Pahrump Hills member of the Murray formation, Gale crater, Mars: Sedimentology, v. 66, no. 5, p. 1768-1801, https://doi.org/10.1111/sed.12558.","productDescription":"34 p.","startPage":"1768","endPage":"1801","ipdsId":"IP-101054","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":467833,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/sed.12558","text":"Publisher Index Page"},{"id":361830,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"66","issue":"5","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2019-02-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Stack, Kathryn M. 0000-0003-3444-6695","orcid":"https://orcid.org/0000-0003-3444-6695","contributorId":146791,"corporation":false,"usgs":false,"family":"Stack","given":"Kathryn","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":758957,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Grotzinger, John P.","contributorId":181502,"corporation":false,"usgs":false,"family":"Grotzinger","given":"John","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":758958,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lamb, Michael P.","contributorId":214027,"corporation":false,"usgs":false,"family":"Lamb","given":"Michael","email":"","middleInitial":"P.","affiliations":[{"id":13711,"text":"Caltech","active":true,"usgs":false}],"preferred":false,"id":758959,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gupta, Sanjeev","contributorId":172302,"corporation":false,"usgs":false,"family":"Gupta","given":"Sanjeev","email":"","affiliations":[{"id":24608,"text":"Imperial College London","active":true,"usgs":false}],"preferred":false,"id":758960,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rubin, David M.","contributorId":206587,"corporation":false,"usgs":false,"family":"Rubin","given":"David","email":"","middleInitial":"M.","affiliations":[{"id":32898,"text":"U.C. Santa Cruz","active":true,"usgs":false}],"preferred":false,"id":758961,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kah, Linda C.","contributorId":181497,"corporation":false,"usgs":false,"family":"Kah","given":"Linda","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":758962,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Edgar, Lauren A. 0000-0001-7512-7813 ledgar@usgs.gov","orcid":"https://orcid.org/0000-0001-7512-7813","contributorId":167501,"corporation":false,"usgs":true,"family":"Edgar","given":"Lauren","email":"ledgar@usgs.gov","middleInitial":"A.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":758956,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Fey, Deirdra M.","contributorId":214028,"corporation":false,"usgs":false,"family":"Fey","given":"Deirdra","email":"","middleInitial":"M.","affiliations":[{"id":36716,"text":"Malin Space Science Systems","active":true,"usgs":false}],"preferred":false,"id":758963,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Hurowitz, Joel A.","contributorId":200390,"corporation":false,"usgs":false,"family":"Hurowitz","given":"Joel","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":758964,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"McBride, Marie J.","contributorId":167693,"corporation":false,"usgs":false,"family":"McBride","given":"Marie","email":"","middleInitial":"J.","affiliations":[{"id":24734,"text":"Malin Space Science Systems, San Diego","active":true,"usgs":false}],"preferred":false,"id":758965,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Rivera-Hernandez, Frances","contributorId":203793,"corporation":false,"usgs":false,"family":"Rivera-Hernandez","given":"Frances","email":"","affiliations":[{"id":16975,"text":"University of California Davis","active":true,"usgs":false}],"preferred":false,"id":758966,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Sumner, Dawn Y.","contributorId":200403,"corporation":false,"usgs":false,"family":"Sumner","given":"Dawn","email":"","middleInitial":"Y.","affiliations":[],"preferred":false,"id":758967,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Van Beek, Jason K.","contributorId":200399,"corporation":false,"usgs":false,"family":"Van Beek","given":"Jason","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":758968,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Williams, Rebecca M. E.","contributorId":214029,"corporation":false,"usgs":false,"family":"Williams","given":"Rebecca","email":"","middleInitial":"M. E.","affiliations":[{"id":13179,"text":"Planetary Science Institute","active":true,"usgs":false}],"preferred":false,"id":758969,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Yingst, R. Aileen","contributorId":214030,"corporation":false,"usgs":false,"family":"Yingst","given":"R.","email":"","middleInitial":"Aileen","affiliations":[{"id":13179,"text":"Planetary Science Institute","active":true,"usgs":false}],"preferred":false,"id":758970,"contributorType":{"id":1,"text":"Authors"},"rank":15}]}} ,{"id":70202351,"text":"sim3427 - 2019 - Structure contour and overburden maps of the Niobrara interval of the Upper Cretaceous Cody Shale in the Wind River Basin, Wyoming","interactions":[],"lastModifiedDate":"2019-03-11T13:15:55","indexId":"sim3427","displayToPublicDate":"2019-03-07T11:15:00","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3427","displayTitle":"Structure Contour and Overburden Maps of the Niobrara Interval of the Upper Cretaceous Cody Shale in the Wind River Basin, Wyoming","title":"Structure contour and overburden maps of the Niobrara interval of the Upper Cretaceous Cody Shale in the Wind River Basin, Wyoming","docAbstract":"The Wind River Basin in central Wyoming is one of many structural and sedimentary basins that formed in the Rocky Mountain foreland during the Laramide orogeny. The basin is bounded by the Washakie, Owl Creek, and southern Bighorn uplifts on the north, the Casper arch on the east, the Granite Mountains uplift on the south, and Wind River uplift on the west.
The first commercial oil well in Wyoming was drilled at Dallas dome near an oil seep along the southwestern edge of the Wind River Basin in 1884. Since then, many important conventional oil and gas fields, that produce from reservoirs ranging in age from Mississippian through Tertiary, have been discovered in this basin. In addition, an extensive unconventional (continuous) overpressured basin-centered gas accumulation has been identified in Cretaceous and Tertiary strata in the deeper parts of the basin. It has been suggested that various Upper Cretaceous marine shales, including the Cody Shale, are the principal hydrocarbon source rocks for many of these accumulations. With recent advances in horizontal drilling and multistage fracture stimulation, there has been an increase in exploration and completion of wells in equivalent marine shales in other Rocky Mountain Laramide basins that were traditionally thought of only as hydrocarbon source rocks. The maps presented in this report were constructed as part of a project carried out by the U.S. Geological Survey to characterize the geologic framework of potential undiscovered continuous (unconventional) oil and gas resources of the Niobrara interval of the Upper Cretaceous Cody Shale in the Wind River Basin in central Wyoming.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3427","usgsCitation":"Finn, T.M., 2019, Structure contour and overburden maps of the Niobrara interval of the Upper Cretaceous Cody Shale in the Wind River Basin, Wyoming: U.S. Geological Survey Scientific Investigations Map 3427, pamphlet 9 p., 2 sheets, scale 1:500,000, https://doi.org/10.3133/sim3427","productDescription":"Report: iii, 9 p.; 2 Sheets: 32.0 x 22.0 inches and 32.01 x 22.0 inches; Database release; Read Me","onlineOnly":"Y","ipdsId":"IP-094046","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":361865,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7BZ65CN","text":"USGS data release","linkHelpText":"Tops file for the Niobrara interval of the Upper Cretaceous Cody Shale and associated strata in the Wind River Basin, Wyoming"},{"id":361751,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3427/coverthb_sheet1.jpg"},{"id":361752,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3427/sim3427_pamphlet.pdf","text":"Report","size":"3.11 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3427 Pamphlet"},{"id":361754,"rank":4,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3427/sim3427_sheet2.pdf","text":"Sheet 2—Map Showing Depth to the Base of the Niobrara Interval of the Upper Cretaceous Cody Shale in the Wind River Basin, Wyoming ","size":"1.38 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3427 Sheet 2"},{"id":361755,"rank":5,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/sim/3427/sim3427_Readme.txt","text":"Read Me","size":"8.00 kB","linkFileType":{"id":2,"text":"txt"},"description":"SIM 3427 Read Me"},{"id":361753,"rank":3,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3427/sim3427_sheet1.pdf","text":"Sheet 1—Structure Contour Map of the Niobrara Interval of the Upper Cretaceous Cody Shale in the Wind River Basin, Wyoming ","size":"1.45 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3427 Sheet 1"}],"country":"United States","state":"Wyoming","otherGeospatial":"Wind River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -110,\n 42.5\n ],\n [\n -110,\n 43.75\n ],\n [\n -106.5,\n 43.75\n ],\n [\n -106.5,\n 42.5\n ],\n [\n -110,\n 42.5\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Central Energy Resources Science Center
U.S. Geological Survey
Box 25046, MS-939
Denver, CO 80225-0046
A decline in submerged aquatic vegetation (SAV) within Florida’s spring-fed thermal refuges raises questions about how these systems support winter foraging of Florida manatees Trichechus manatus latirostris. We analyzed telemetry data for 12 manatees over 7 yr to assess their use of Kings Bay, a winter refuge with diminished SAV. After accounting for the effect of water temperature, we hypothesized that the number of trips out of Kings Bay would increase and the time wintering manatees spent in Kings Bay would decrease. Trips out of and into Kings Bay were also compared to assess potential influences on exiting or entering. There were no detectable differences in the number of trips out of the bay or overall time manatees spent in Kings Bay across winters. The percentage of time water temperatures were below 20°C was the single best predictor of increased time spent in Kings Bay. Trips out of Kings Bay were more likely than trips into the bay to occur after 12:00 h and during a high but ebbing tide. Nine manatees tracked for longer than 75 d in winter spent 7 to 57% of their time in the Gulf of Mexico, and 3 of these manatees spent 7 to 65% of the winter >80 km from the mouth of Kings Bay. Results suggest the low amount of SAV in Kings Bay does not obviate its use by manatees, though there are likely tradeoffs for manatees regularly foraging elsewhere. Accounting for movements of Florida manatees through a network of habitats may improve management strategies and facilitate desirable conservation outcomes.
","language":"English","publisher":"Inter-Research","doi":"10.3354/esr00933","usgsCitation":"Littles, C.J., Bonde, R.K., Butler, S.M., Jacoby, C.A., Notestein, S.K., Reid, J.P., Slone, D.H., and Frazer, T.K., 2019, Coastal habitat change and marine megafauna behavior: Florida manatees encountering reduced food provisions in a prominent winter refuge: Endangered Species Research, v. 38, p. 29-43, https://doi.org/10.3354/esr00933.","productDescription":"15 p.","startPage":"29","endPage":"43","ipdsId":"IP-088011","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":467834,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3354/esr00933","text":"Publisher Index Page"},{"id":361825,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -82.80258178710938,\n 28.5941685062326\n ],\n [\n -82.56912231445312,\n 28.5941685062326\n ],\n [\n -82.56912231445312,\n 29.039361975917828\n ],\n [\n -82.80258178710938,\n 29.039361975917828\n ],\n [\n -82.80258178710938,\n 28.5941685062326\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"38","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Littles, Chanda J.","contributorId":214014,"corporation":false,"usgs":false,"family":"Littles","given":"Chanda","email":"","middleInitial":"J.","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":758925,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bonde, Robert K. 0000-0001-9179-4376 rbonde@usgs.gov","orcid":"https://orcid.org/0000-0001-9179-4376","contributorId":2675,"corporation":false,"usgs":true,"family":"Bonde","given":"Robert","email":"rbonde@usgs.gov","middleInitial":"K.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":758924,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Butler, Susan M. 0000-0003-3676-9332 sbutler@usgs.gov","orcid":"https://orcid.org/0000-0003-3676-9332","contributorId":195796,"corporation":false,"usgs":true,"family":"Butler","given":"Susan","email":"sbutler@usgs.gov","middleInitial":"M.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":758926,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jacoby, Charles A.","contributorId":214015,"corporation":false,"usgs":false,"family":"Jacoby","given":"Charles","email":"","middleInitial":"A.","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":758927,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Notestein, Sky K.","contributorId":214017,"corporation":false,"usgs":false,"family":"Notestein","given":"Sky","email":"","middleInitial":"K.","affiliations":[{"id":35620,"text":"Southwest Florida Water Management District","active":true,"usgs":false}],"preferred":false,"id":758931,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Reid, James P. 0000-0002-8497-1132 jreid@usgs.gov","orcid":"https://orcid.org/0000-0002-8497-1132","contributorId":3460,"corporation":false,"usgs":true,"family":"Reid","given":"James","email":"jreid@usgs.gov","middleInitial":"P.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":758928,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Slone, Daniel H. 0000-0002-9903-9727 dslone@usgs.gov","orcid":"https://orcid.org/0000-0002-9903-9727","contributorId":205617,"corporation":false,"usgs":true,"family":"Slone","given":"Daniel","email":"dslone@usgs.gov","middleInitial":"H.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":758929,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Frazer, Thomas K.","contributorId":214016,"corporation":false,"usgs":false,"family":"Frazer","given":"Thomas","email":"","middleInitial":"K.","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":758930,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70202522,"text":"70202522 - 2019 - The past and future roles of competition and habitat in the range‐wide occupancy dynamics of Northern Spotted Owls","interactions":[],"lastModifiedDate":"2019-07-23T12:27:49","indexId":"70202522","displayToPublicDate":"2019-03-07T10:05:45","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1450,"text":"Ecological Applications","active":true,"publicationSubtype":{"id":10}},"title":"The past and future roles of competition and habitat in the range‐wide occupancy dynamics of Northern Spotted Owls","docAbstract":"Slow ecological processes challenge conservation. Short‐term variability can obscure the importance of slower processes that may ultimately determine the state of a system. Furthermore, management actions with slow responses can be hard to justify. One response to slow processes is to explicitly concentrate analysis on state dynamics. Here, we focus on identifying drivers of Northern Spotted Owl (Strix occidentalis caurina) territorial occupancy dynamics across 11 study areas spanning their geographic range and forecasting response to potential management actions. Competition with Barred Owls (Strix varia) has increased Spotted Owl territory extinction probabilities across all study areas and driven recent declines in Spotted Owl populations. Without management intervention, the Northern Spotted Owl subspecies will be extirpated from parts of its current range within decades. In the short term, Barred Owl removal can be effective. Over longer time spans, however, maintaining or improving habitat conditions can help promote the persistence of northern spotted owl populations. In most study areas, habitat effects on expected Northern Spotted Owl territorial occupancy are actually greater than the effects of competition from Barred Owls. This study suggests how intensive management actions (removal of a competitor) with rapid results can complement a slower management action (i.e., promoting forest succession).
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/eap.1861","usgsCitation":"Yackulic, C.B., Bailey, L.L., Dugger, K., Davis, R.J., Franklin, A.B., Forsman, E.D., Ackers, S.H., Andrews, L.S., Diller, L.V., Gremel, S.A., Hamm, K.A., Herter, D.R., Higley, J.M., Horn, R.B., McCafferty, C., Reid, J.A., Rockweit, J.T., and Sovern, S.G., 2019, The past and future roles of competition and habitat in the range‐wide occupancy dynamics of Northern Spotted Owls: Ecological Applications, v. 29, no. 3, e01861, https://doi.org/10.1002/eap.1861.","productDescription":"e01861","ipdsId":"IP-101277","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":437547,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9O0IIRH","text":"USGS data release","linkHelpText":"Northern spotted owl data and analysis code, Cascade Range, Pacific Northwest, USA"},{"id":361824,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"29","issue":"3","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2019-03-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Yackulic, Charles B. 0000-0001-9661-0724 cyackulic@usgs.gov","orcid":"https://orcid.org/0000-0001-9661-0724","contributorId":4662,"corporation":false,"usgs":true,"family":"Yackulic","given":"Charles","email":"cyackulic@usgs.gov","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":758916,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bailey, Larissa L. 0000-0002-5959-2018","orcid":"https://orcid.org/0000-0002-5959-2018","contributorId":189578,"corporation":false,"usgs":false,"family":"Bailey","given":"Larissa","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":758917,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dugger, Katie M. 0000-0002-4148-246X cdugger@usgs.gov","orcid":"https://orcid.org/0000-0002-4148-246X","contributorId":4399,"corporation":false,"usgs":true,"family":"Dugger","given":"Katie","email":"cdugger@usgs.gov","middleInitial":"M.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":758919,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Davis, Raymond J.","contributorId":150574,"corporation":false,"usgs":false,"family":"Davis","given":"Raymond","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":758918,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Franklin, Alan B.","contributorId":101999,"corporation":false,"usgs":false,"family":"Franklin","given":"Alan","email":"","middleInitial":"B.","affiliations":[{"id":12434,"text":"USDA, Wildlife Services, National Wildlife Research Center","active":true,"usgs":false}],"preferred":false,"id":758942,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Forsman, Eric D.","contributorId":96792,"corporation":false,"usgs":false,"family":"Forsman","given":"Eric","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":758943,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ackers, Steven H.","contributorId":36065,"corporation":false,"usgs":true,"family":"Ackers","given":"Steven","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":758944,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Andrews, Lawrence S.","contributorId":40526,"corporation":false,"usgs":true,"family":"Andrews","given":"Lawrence","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":758945,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Diller, Lowell V.","contributorId":65394,"corporation":false,"usgs":true,"family":"Diller","given":"Lowell","email":"","middleInitial":"V.","affiliations":[],"preferred":false,"id":758946,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Gremel, Scott A.","contributorId":23075,"corporation":false,"usgs":true,"family":"Gremel","given":"Scott","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":758947,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Hamm, Keith A.","contributorId":167062,"corporation":false,"usgs":false,"family":"Hamm","given":"Keith","email":"","middleInitial":"A.","affiliations":[{"id":24606,"text":"Green Diamond Resource Company","active":true,"usgs":false}],"preferred":false,"id":758948,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Herter, Dale R.","contributorId":206141,"corporation":false,"usgs":false,"family":"Herter","given":"Dale","email":"","middleInitial":"R.","affiliations":[{"id":37257,"text":"Raedeke Associates, Inc","active":true,"usgs":false}],"preferred":false,"id":758949,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Higley, J. Mark","contributorId":91029,"corporation":false,"usgs":true,"family":"Higley","given":"J.","email":"","middleInitial":"Mark","affiliations":[],"preferred":false,"id":758950,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Horn, Rob B.","contributorId":150583,"corporation":false,"usgs":false,"family":"Horn","given":"Rob","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":758951,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"McCafferty, Christopher","contributorId":150584,"corporation":false,"usgs":false,"family":"McCafferty","given":"Christopher","email":"","affiliations":[],"preferred":false,"id":758952,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Reid, Janice A.","contributorId":98034,"corporation":false,"usgs":true,"family":"Reid","given":"Janice","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":758953,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Rockweit, Jeremy T.","contributorId":202538,"corporation":false,"usgs":false,"family":"Rockweit","given":"Jeremy","email":"","middleInitial":"T.","affiliations":[{"id":36473,"text":"Colorado Cooperative Fish and Wildlife Unit","active":true,"usgs":false}],"preferred":false,"id":758954,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Sovern, Stan G.","contributorId":44084,"corporation":false,"usgs":true,"family":"Sovern","given":"Stan","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":758955,"contributorType":{"id":1,"text":"Authors"},"rank":18}]}} ,{"id":70200357,"text":"sir20185141 - 2019 - Spatial distribution of nutrients, chloride, and suspended sediment concentrations and loads determined by using different sampling methods in a cross section of the Trenton Channel of the Detroit River, Michigan, November 2014–November 2015","interactions":[],"lastModifiedDate":"2019-03-08T10:17:20","indexId":"sir20185141","displayToPublicDate":"2019-03-07T10:00:00","publicationYear":"2019","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":"2018-5141","displayTitle":"Spatial Distribution of Nutrients, Chloride, and Suspended Sediment Concentrations and Loads Determined by Using Different Sampling Methods in a Cross Section of the Trenton Channel of the Detroit River, Michigan, November 2014–November 2015","title":"Spatial distribution of nutrients, chloride, and suspended sediment concentrations and loads determined by using different sampling methods in a cross section of the Trenton Channel of the Detroit River, Michigan, November 2014–November 2015","docAbstract":"The Detroit River separates the United States and Canada as it flows from Lake St. Clair to Lake Erie. The Trenton Channel is a 13-kilometer-long branch of the Detroit River that flows to the west of Grosse Ile before rejoining the Detroit River near its mouth, just before the Detroit River flows into Lake Erie. The U.S. Environmental Protection Agency has listed both the Trenton Channel and Detroit River as Areas of Concern because of a list of Beneficial Use Impairments such as interrupted drinking-water services, loss of aquatic life, and reduced recreational use. Phosphorus loading from tributaries such as the Trenton Channel is one of the primary drivers of eutrophication in Lake Erie. The complex flow patterns and variable distribution of chemical constituents in the Trenton Channel make it difficult to accurately characterize the concentrations and loads of nutrients and other constituents conveyed through the channel to Lake Erie.
In order to better understand the Trenton Channel’s contributions of nutrients (total phosphorus, orthophosphate, total nitrogen, and ammonia), chloride, and suspended sediment to Lake Erie and evaluate differences in results obtained by using different sample methodologies, the U.S. Geological Survey, in cooperation with the U.S. Environmental Protection Agency and Environment Canada, completed 12 sampling campaigns on the Trenton Channel in Detroit, Michigan, from November 2014 through November 2015.
Acoustic Doppler current profiler (ADCP) techniques were used to characterize the distribution of velocity components within a cross section corresponding to a transect of the Trenton Channel at U.S. Geological Survey station 041686401 Trenton Channel of Detroit River at Grosse Ile, Mich. Three methods of collecting water-quality data at the same transect of the Trenton Channel were used: multiple-vertical depth-integrated (MVDI), fixed-point, and discrete samples. Horizontal and vertical variations in concentrations of nutrients, chloride, and suspended sediment were analyzed from discrete samples to better understand distributions of these constituents throughout the channel. Constituent loads were calculated by using individual sample concentrations and ADCP measurements for discharge made on the same day that the water-quality samples were collected. Constituent loads calculated from MVDI and fixed-point sampling methods were compared. The relation between MVDI and fixed-point samples helped quantify the differences between the sampling methods. Linear regression equations depicting the relation between concentrations measured by using MVDI and fixed-point samples were prepared.
ADCP data indicates that velocities throughout the sampled transect remain uniform except for one location around 200 meters from the west bank of the channel. Secondary flow vectors suggest the presence of counter-rotating helical flow cells, and these helical flow cells could affect the mixing of constituents in transport by preventing cross-channel mixing. Flow discharges throughout the sampling campaign showed small variations, although lower flow rates were observed in the early winter months than in the summer months. Discrete sampling methods results displayed both heterogeneity throughout the channel horizontally, representing limited horizontal mixing in the channel, and displayed homogeneity throughout vertical transects, indicating mixing vertically. Comparisons between MVDI and fixed-point methods found consistently higher concentrations were measured in MVDI samples compared to concentrations measured in fixed-point samples. To correct for this bias between MVDI and fixed-point sample results, simple linear-regression equations were developed for all major constituents to help estimate constituent concentrations from fixed-point samples equivalent to those measured by using MVDI sampling techniques. Instantaneous constituent loads were developed by using velocity and discharge data obtained from ADCPs and constituent concentrations obtained from MVDI and fixed-point samples.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185141","collaboration":"Prepared in cooperation with the United States Environmental Protection Agency and Environment and Climate Change Canada","usgsCitation":"Totten, A.R., and Duris, J.W., 2019, Spatial distribution of nutrients, chloride, and suspended sediment concentrations and loads determined by using different sampling methods in a cross section of the Trenton Channel of the Detroit River, Michigan, November 2014–November 2015: U.S. Geological Survey Scientific Investigations Report 2018–5141, 25 p., https://doi.org/10.3133/sir20185141.","productDescription":"viii, 25 p.","numberOfPages":"38","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-091065","costCenters":[{"id":382,"text":"Michigan Water Science Center","active":true,"usgs":true},{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":361790,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5141/sir20185141.pdf","text":"Report","size":"4.63 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018-5141"},{"id":361789,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5141/coverthb.jpg"}],"country":"Canada, United States","state":"Michigan","otherGeospatial":"Detroit River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -83.26263427734375,\n 41.97174336327968\n ],\n [\n -82.78884887695312,\n 41.97174336327968\n ],\n [\n -82.78884887695312,\n 42.40622065620649\n ],\n [\n -83.26263427734375,\n 42.40622065620649\n ],\n [\n -83.26263427734375,\n 41.97174336327968\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Upper Midwest Water Science Center
U.S. Geological Survey
6520 Mercantile Way, Suite 5
Lansing, MI 48911
Over 9000 articles have been published on turtles and tortoises (excluding sea turtles) since 1950 according to the Web of Science, including over 8000 contained in a personal bibliography that we analyze in this paper. Research had a slow start from 1900 to 1950, with mostly anecdotal additions to our knowledge until the contributions of F. Cagle and A. Carr took turtle research to new levels as the cofathers of turtle ecology in the middle of the last century. Books written in 1939, 1952, and 1972 that compiled existing literature on turtles in the United States and Canada set the stage for growing interest in turtles. The first global compilation of turtle species did not become available until 1961. Publication frequency increased in the 1960s and especially the 1970s as interest in turtles grew, and a wave of turtle biologists emerged from doctoral degree programs. We briefly review the contributions of scientists who published extensively on turtle ecology in those and later decades up to the present. We also review advances in our knowledge of various topics, including the global distribution of turtle research efforts; changes in our perceptions of turtle species diversity over time; turtle community ecology; sex ratios, sex-determination, and climate change; overwintering behavior; sexual size dimorphism and sexual dichromatism; analyses of population genetics; turtles and vocalization; and the emergence of turtle conservation biology efforts. We conclude with a discussion of future opportunities and challenges for working with turtles.
","language":"English","publisher":"Herpetologists’ League","doi":"10.1655/0018-0831-075.1.4","usgsCitation":"Gibbons, J.W., and Lovich, J.E., 2019, Where has turtle ecology been, and where is it going?: Herpetologica, v. 75, no. 1, p. 4-20, https://doi.org/10.1655/0018-0831-075.1.4.","productDescription":"17 p.","startPage":"4","endPage":"20","ipdsId":"IP-102682","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":361818,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"75","issue":"1","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Gibbons, J. Whitfield","contributorId":198690,"corporation":false,"usgs":false,"family":"Gibbons","given":"J.","email":"","middleInitial":"Whitfield","affiliations":[],"preferred":false,"id":758898,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lovich, Jeffrey E. 0000-0002-7789-2831 jeffrey_lovich@usgs.gov","orcid":"https://orcid.org/0000-0002-7789-2831","contributorId":458,"corporation":false,"usgs":true,"family":"Lovich","given":"Jeffrey","email":"jeffrey_lovich@usgs.gov","middleInitial":"E.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true},{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":758897,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70215588,"text":"70215588 - 2019 - Age of the dacite of Sunset Amphitheater, a voluminous Pleistocene tephra from Mount Rainier (USA), and implications for Cascade glacial stratigraphy","interactions":[],"lastModifiedDate":"2020-10-26T12:36:38.044988","indexId":"70215588","displayToPublicDate":"2019-03-07T07:31:29","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2499,"text":"Journal of Volcanology and Geothermal Research","active":true,"publicationSubtype":{"id":10}},"title":"Age of the dacite of Sunset Amphitheater, a voluminous Pleistocene tephra from Mount Rainier (USA), and implications for Cascade glacial stratigraphy","docAbstract":"The dacite of Sunset Amphitheater, Mount Rainier (USA), illustrates the difficulties in establishing accurate ages of Pleistocene tephra eruptions. Nearly uniform whole-rock, glass, and mineral compositions, texture, and phenocryst assemblage establish that certain conspicuous dissected pumice exposures scattered from Mount Rainier to southern Puget Sound are products of the same Pleistocene Plinian eruption. Deposit thicknesses and pumice sizes support an eruption on the order of low Volcanic Explosivity Index (VEI) 5, atypically explosive for dominantly lava-producing Mount Rainier. Statistically permissible 40Ar/39Ar plateau ages of plagioclase phenocryst separates are 138 ± 20 ka and 101 ± 11 ka (2σ). A previously published result of 206 ± 11 ka is herein shown to result from a sample selection error. Zircon from the pumice yields a U-Th crystallization age of 147 ± 8 ka if the isochron is required to pass through the tephra U-Th isotopic composition. In contrast, pooled (U-Th)/He measurements on the zircon yield an age of 85 ± 6 ka (2σ), which accords with well-behaved 40Ar/39Ar ages of stratigraphically associated lavas high on Mount Rainier, and is the best estimate of the pumice's true eruption age. Inclusions of undegassed melt (glass) in the plagioclase separates are proposed as biasing apparent 40Ar/39Ar plateau ages to old values through coupling of undegassed magmatic excess Ar with radiogenic Ar that accumulated post-eruptively from relatively K-rich glass. U-Th ages record zircon growth prior to eruption, consistent with a possible complex history of advanced solidification followed by remobilization. The ca. 85 ka eruption age confirms that bracketing glacial tills on the flanks of Mount Rainier were products of the Penultimate Glaciation (MIS 6) and Last Glacial Maximum (MIS 2). This eruption age also provides an important time marker for glacial and other sedimentary deposits in southern Puget Sound lowland that, excepting the Vashon Drift (MIS 2), generally lack reliable age determinations.
Viral hemorrhagic septicemia virus (VHSV), a fish rhabdovirus belonging to the Novirhabdovirus genus, causes severe disease and mortality in many marine and freshwater fish species worldwide. VHSV isolates are classified into four genotypes and each group is endemic to specific geographic regions in the north Atlantic and Pacific Oceans. Most viruses in the European VHSV genotype Ia are highly virulent for rainbow trout (Oncorhynchus mykiss), whereas, VHSV genotype IVb viruses from the Great Lakes region in the United States, which caused high mortality in wild freshwater fish species, are avirulent for trout. This study describes molecular characterization and construction of an infectious clone of the virulent VHSV-Ia strain DK-3592B from Denmark, and application of the clone in reverse genetics to investigate the role of selected VHSV protein(s) in host-specific virulence in rainbow trout (referred to as trout-virulence).
","language":"English","publisher":"BMC part of Springer Nature","doi":"10.1186/s12985-019-1139-3","usgsCitation":"Yusuff, S., Kurath, G., Kim, M., Tesfaye, T.M., Liu, J., Mckenney, D., and Vakharia, V.N., 2019, The glycoprotein, non-virion protein, and polymerase of viral hemorrhagic septicemia virus are not determinants of host-specific virulence in rainbow trout: Virology Journal, v. 16, no. 31, p. 1-16, https://doi.org/10.1186/s12985-019-1139-3.","productDescription":"16 p.","startPage":"1","endPage":"16","ipdsId":"IP-105277","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":460447,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1186/s12985-019-1139-3","text":"Publisher Index Page"},{"id":363412,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"16","issue":"31","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2019-03-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Yusuff, Shamila","contributorId":215222,"corporation":false,"usgs":false,"family":"Yusuff","given":"Shamila","email":"","affiliations":[{"id":39208,"text":"GeneDX 207 Perry Parkway, Gaithersburg, MD 20877 USA","active":true,"usgs":false}],"preferred":false,"id":761853,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kurath, Gael 0000-0003-3294-560X gkurath@usgs.gov","orcid":"https://orcid.org/0000-0003-3294-560X","contributorId":215223,"corporation":false,"usgs":true,"family":"Kurath","given":"Gael","email":"gkurath@usgs.gov","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":761854,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kim, Min Sun","contributorId":215224,"corporation":false,"usgs":false,"family":"Kim","given":"Min Sun","affiliations":[{"id":39209,"text":"Department of Integrative Bio-Industrial Engineering, Sejong University, Seoul, Republic of South Korea","active":true,"usgs":false}],"preferred":false,"id":761855,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Tesfaye, Tarin M","contributorId":215227,"corporation":false,"usgs":false,"family":"Tesfaye","given":"Tarin","email":"","middleInitial":"M","affiliations":[{"id":37814,"text":"Former USGS","active":true,"usgs":false}],"preferred":false,"id":761859,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Liu, Jie","contributorId":201274,"corporation":false,"usgs":false,"family":"Liu","given":"Jie","email":"","affiliations":[],"preferred":false,"id":761856,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Mckenney, Douglas","contributorId":215225,"corporation":false,"usgs":true,"family":"Mckenney","given":"Douglas","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":761857,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Vakharia, Vikram N","contributorId":215226,"corporation":false,"usgs":false,"family":"Vakharia","given":"Vikram","email":"","middleInitial":"N","affiliations":[{"id":39210,"text":"Institute of Marine & Environmental Technology, University of Maryland Baltimore County, 701 E. Pratt Street, Baltimore, MD 21202 USA","active":true,"usgs":false}],"preferred":false,"id":761858,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70202489,"text":"70202489 - 2019 - Modelling sea lice control by lumpfish on Atlantic salmon farms: interactions with mate limitation, temperature, and treatment rules","interactions":[],"lastModifiedDate":"2019-06-18T10:39:36","indexId":"70202489","displayToPublicDate":"2019-03-06T11:26:48","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1396,"text":"Diseases of Aquatic Organisms","active":true,"publicationSubtype":{"id":10}},"title":"Modelling sea lice control by lumpfish on Atlantic salmon farms: interactions with mate limitation, temperature, and treatment rules","docAbstract":"Atlantic salmon farming is one of the largest aquaculture sectors in the world. A major impact on farm economics, fish welfare, and potentially nearby wild salmonid populations, is the sea louse ectoparasite Lepeophtheirus salmonis. Sea louse infestations are most often controlled through application of chemicals, but in most farming regions sea lice have evolved resistance to the small set of available chemicals. Therefore, alternative treatment methodologies are becoming more widely used. One increasingly common alternative treatment involves the co-culture of farmed salmon with cleaner fish, which prey on sea lice. However, despite their wide use, little is understood about the situations in which cleaner fish are most effective. For example, previous work suggests that a low parasite density results in sea lice finding it difficult to acquire mates, reducing fecundity and population growth. Other work suggests that environmental conditions such as temperature and external sea louse pressure have substantial impact on this mate limitation threshold and may even remove the effect entirely. We use an Agent-Based Model (ABM) to simulate cleaner fish on a salmon farm to explore interactions between sea louse mating behaviour, cleaner fish feeding rate, temperature, and external sea lice pressure. We found that sea louse mating has a substantial effect on sea louse infestations under a variety of environmental conditions. Our results suggest that cleaner fish can control sea louse infestations most effectively by maintaining the population below critical density thresholds.
","language":"English","publisher":"Inter-Research","doi":"10.3354/dao03329","usgsCitation":"McEwan, G.F., Groner, M.L., Cohen, A.A., Imsland, A.K., and Revie, C.W., 2019, Modelling sea lice control by lumpfish on Atlantic salmon farms: interactions with mate limitation, temperature, and treatment rules: Diseases of Aquatic Organisms, v. 133, no. 1, p. 69-82, https://doi.org/10.3354/dao03329.","productDescription":"14 p.","startPage":"69","endPage":"82","ipdsId":"IP-099338","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":467835,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://strathprints.strath.ac.uk/68921/1/McEwan_etal_DoAO_2019_Modelling_sea_lice_control.pdf","text":"External Repository"},{"id":361798,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"133","issue":"1","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"McEwan, Gregor F.","contributorId":213961,"corporation":false,"usgs":false,"family":"McEwan","given":"Gregor","email":"","middleInitial":"F.","affiliations":[{"id":38940,"text":"Department of Health Management, University of Prince Edward Island, Charlottetown, PE, Canada, C1A 4P3","active":true,"usgs":false}],"preferred":false,"id":758813,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Groner, Maya L. 0000-0002-3381-6415","orcid":"https://orcid.org/0000-0002-3381-6415","contributorId":213541,"corporation":false,"usgs":true,"family":"Groner","given":"Maya","email":"","middleInitial":"L.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":758814,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cohen, Allegra A. B.","contributorId":213963,"corporation":false,"usgs":false,"family":"Cohen","given":"Allegra","email":"","middleInitial":"A. B.","affiliations":[{"id":38941,"text":"Department of Agricultural and Biological Engineering, University of Florida, Gainesville, FL, USA 32611-0570","active":true,"usgs":false}],"preferred":false,"id":758815,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Imsland, Albert K. D.","contributorId":213964,"corporation":false,"usgs":false,"family":"Imsland","given":"Albert","email":"","middleInitial":"K. D.","affiliations":[{"id":38942,"text":"Akvaplan-niva Iceland Office, Akralind 4, 201 Kópavogur, Iceland","active":true,"usgs":false}],"preferred":false,"id":758816,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Revie, Crawford W.","contributorId":213965,"corporation":false,"usgs":false,"family":"Revie","given":"Crawford","email":"","middleInitial":"W.","affiliations":[{"id":38940,"text":"Department of Health Management, University of Prince Edward Island, Charlottetown, PE, Canada, C1A 4P3","active":true,"usgs":false}],"preferred":false,"id":758817,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70202490,"text":"70202490 - 2019 - Not so normal normals: Species distribution model results are sensitive to choice of climate normals and model type","interactions":[],"lastModifiedDate":"2019-03-06T11:22:40","indexId":"70202490","displayToPublicDate":"2019-03-06T11:22:37","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5811,"text":"Climate","active":true,"publicationSubtype":{"id":10}},"title":"Not so normal normals: Species distribution model results are sensitive to choice of climate normals and model type","docAbstract":"Species distribution models have many applications in conservation and ecology, and climate data are frequently a key driver of these models. Often, correlative modeling approaches are developed with readily available climate data; however, the impacts of the choice of climate normals is rarely considered. Here, we produced species distribution models for five disparate species using four different modeling algorithms and compared results between two different, but overlapping, climate normals time periods. Although the correlation structure among climate predictors did not change between the time periods, model results were sensitive to both baseline climate period and model method, even with model parameters specifically tuned to a species. Each species and each model type had at least one difference in variable retention or relative ranking with the change in climate time period. Pairwise comparisons of spatial predictions were also different, ranging from a low of 1.6% for climate period differences to a high of 25% for algorithm differences. While uncertainty from model algorithm selection is recognized as an important source of uncertainty, the impact of climate period is not commonly assessed. These uncertainties may affect conservation decisions, especially when projecting to future climates, and should be evaluated during model development.
","language":"English","publisher":"MDPI","doi":"10.3390/cli7030037","usgsCitation":"Jarnevich, C.S., and Young, N.E., 2019, Not so normal normals: Species distribution model results are sensitive to choice of climate normals and model type: Climate, v. 7, no. 3, p. 1-15, https://doi.org/10.3390/cli7030037.","productDescription":"Article 37; 15 p.","startPage":"1","endPage":"15","ipdsId":"IP-073502","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":467836,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/cli7030037","text":"Publisher Index Page"},{"id":361797,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"7","issue":"3","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2019-02-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Jarnevich, Catherine S. 0000-0002-9699-2336 jarnevichc@usgs.gov","orcid":"https://orcid.org/0000-0002-9699-2336","contributorId":3424,"corporation":false,"usgs":true,"family":"Jarnevich","given":"Catherine","email":"jarnevichc@usgs.gov","middleInitial":"S.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":758818,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Young, Nicholas E.","contributorId":189060,"corporation":false,"usgs":false,"family":"Young","given":"Nicholas","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":758819,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70202492,"text":"70202492 - 2019 - Patterns of mercury and selenium exposure in Minnesota common loons","interactions":[],"lastModifiedDate":"2019-03-06T11:18:40","indexId":"70202492","displayToPublicDate":"2019-03-06T11:18:38","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1571,"text":"Environmental Toxicology and Chemistry","active":true,"publicationSubtype":{"id":10}},"title":"Patterns of mercury and selenium exposure in Minnesota common loons","docAbstract":"Common loons (Gavia immer) are at risk of elevated dietary mercury (Hg) exposure in portions of their breeding range. To assess the level of risk among loons in Minnesota (USA), we investigated loon blood Hg concentrations in breeding lakes across Minnesota. Loon blood Hg concentrations were regressed on predicted Hg concentrations in standardized 12‐cm whole‐organism yellow perch (Perca flavescens), based on fish Hg records from Minnesota lakes, using the US Geological Survey National Descriptive Model for Mercury in Fish. A linear model, incorporating common loon sex, age, body mass, and log‐transformed standardized perch Hg concentration representative of each study lake, was associated with 83% of the variability in observed common loon blood Hg concentrations. Loon blood Hg concentration was positively related to standardized perch Hg concentrations; juvenile loons had lower blood Hg concentrations than adult females, and blood Hg concentrations of juveniles increased with body mass. Blood Hg concentrations of all adult common loons and associated standardized prey Hg for all loon capture lakes included in the study were well below proposed thresholds for adverse effects on loon behavior, physiology, survival, and reproductive success. The fish Hg modeling approach provided insights into spatial patterns of dietary Hg exposure risk to common loons across Minnesota. We also determined that loon blood selenium (Se) concentrations were positively correlated with Hg concentration. Average common loon blood Se concentrations exceeded the published provisional threshold.
","language":"English","publisher":"Society for Environmental Toxicology and Chemistry (SETAC)","doi":"10.1002/etc.4331","usgsCitation":"Kenow, K.P., Houdek, S.C., Fara, L., Erickson, R.A., Gray, B.R., Harrison, T.J., Monson, B., and Henderson, C.L., 2019, Patterns of mercury and selenium exposure in Minnesota common loons: Environmental Toxicology and Chemistry, v. 38, no. 3, p. 524-532, https://doi.org/10.1002/etc.4331.","productDescription":"9 p.","startPage":"524","endPage":"532","ipdsId":"IP-099038","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":437550,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9QHT2DG","text":"USGS data release","linkHelpText":"Code to analyze loon blood mercury"},{"id":437549,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P96XLGLP","text":"USGS data release","linkHelpText":"Loon mercury models"},{"id":437548,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9TDCH3F","text":"USGS data release","linkHelpText":"Patterns of mercury and selenium exposure in Minnesota common loons: Data"},{"id":361796,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"38","issue":"3","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationDate":"2018-12-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Kenow, Kevin P. 0000-0002-3062-5197 kkenow@usgs.gov","orcid":"https://orcid.org/0000-0002-3062-5197","contributorId":3339,"corporation":false,"usgs":true,"family":"Kenow","given":"Kevin","email":"kkenow@usgs.gov","middleInitial":"P.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":758823,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Houdek, Steven C. 0000-0001-9452-6596 shoudek@usgs.gov","orcid":"https://orcid.org/0000-0001-9452-6596","contributorId":4423,"corporation":false,"usgs":true,"family":"Houdek","given":"Steven","email":"shoudek@usgs.gov","middleInitial":"C.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":758824,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fara, Luke J. 0000-0002-1143-4395","orcid":"https://orcid.org/0000-0002-1143-4395","contributorId":202973,"corporation":false,"usgs":true,"family":"Fara","given":"Luke J.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":758825,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Erickson, Richard A. 0000-0003-4649-482X rerickson@usgs.gov","orcid":"https://orcid.org/0000-0003-4649-482X","contributorId":5455,"corporation":false,"usgs":true,"family":"Erickson","given":"Richard","email":"rerickson@usgs.gov","middleInitial":"A.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":758826,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gray, Brian R. 0000-0001-7682-9550 brgray@usgs.gov","orcid":"https://orcid.org/0000-0001-7682-9550","contributorId":2615,"corporation":false,"usgs":true,"family":"Gray","given":"Brian","email":"brgray@usgs.gov","middleInitial":"R.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":758827,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Harrison, Travis J. 0000-0002-9195-738X","orcid":"https://orcid.org/0000-0002-9195-738X","contributorId":213966,"corporation":false,"usgs":true,"family":"Harrison","given":"Travis","email":"","middleInitial":"J.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":758828,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Monson, Bruce 0000-0002-3632-2875","orcid":"https://orcid.org/0000-0002-3632-2875","contributorId":211998,"corporation":false,"usgs":false,"family":"Monson","given":"Bruce","email":"","affiliations":[{"id":13330,"text":"Minnesota Pollution Control Agency","active":true,"usgs":false}],"preferred":false,"id":758829,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Henderson, Carrol L.","contributorId":213967,"corporation":false,"usgs":false,"family":"Henderson","given":"Carrol","email":"","middleInitial":"L.","affiliations":[{"id":6964,"text":"Minnesota Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":758830,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70202493,"text":"70202493 - 2019 - The area under the precision‐recall curve as a performance metric for rare binary events","interactions":[],"lastModifiedDate":"2019-06-18T10:36:48","indexId":"70202493","displayToPublicDate":"2019-03-06T11:16:23","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2717,"text":"Methods in Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"The area under the precision‐recall curve as a performance metric for rare binary events","docAbstract":"Background
Information about contemporary fire regimes across the Sky Island mountain ranges of the Madrean Archipelago Ecoregion in the southwestern United States and northern Mexico can provide insight into how historical fire management and land use have influenced fire regimes, and can be used to guide fuels management, ecological restoration, and habitat conservation. To contribute to a better understanding of spatial and temporal patterns of fires in the region relative to environmental and anthropogenic influences, we augmented existing fire perimeter data for the US by mapping wildfires that occurred in the Mexican Sky Islands from 1985 to 2011.
Results
A total of 254 fires were identified across the region: 99 fires in Mexico (μ = 3901 ha, σ = 5066 ha) and 155 in the US (μ = 3808 ha, σ = 8368 ha). The Animas, Chiricahua, Huachuca-Patagonia, and Santa Catalina mountains in the US, and El Pinito in Mexico had the highest proportion of total area burned (>50%) relative to Sky Island size. Sky Islands adjacent to the border had the greatest number of fires, and many of these fires were large with complex shapes. Wildfire occurred more often in remote biomes, characterized by evergreen woodlands and conifer forests with cooler, wetter conditions. The five largest fires (>25 000 ha) all occurred during twenty-first century droughts (2002 to 2003 and 2011); four of these were in the US and one in Mexico. Overall, high variation in fire shape and size were observed in both wetter and drier years, contributing to landscape heterogeneity across the region.
Conclusions
Future research on regional fire patterns, including fire severity, will enhance opportunities for collaborative efforts between countries, improve knowledge about ecological patterns and processes in the borderlands, and support long-term planning and restoration efforts.
Fire has a diverse range of impacts on Earth's physical and social systems. Accurate and up to date information on areas affected by fire is critical to better understand drivers of fire activity, as well as its relevance for biogeochemical cycles, climate, air quality, and to aid fire management. Mapping burned areas was traditionally done from field sketches. With the launch of the first Earth observation satellites, remote sensing quickly became a more practical alternative to detect burned areas, as they provide timely regional and global coverage of fire occurrence. This review paper explores the physical basis to detect burned area from satellite observations, describes the historical trends of using satellite sensors to monitor burned areas, summarizes the most recent approaches to map burned areas and evaluates the existing burned area products (both at global and regional scales). Finally, it identifies potential future opportunities to further improve burned area detection from Earth observation satellites.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.rse.2019.02.013","usgsCitation":"Chuvieco, E., Mouillot, F., van der Werf, G.R., San Miguel, J., Tanasse, M., Koutsias, N., Garcia, M., Yebra, M., Padilla, M., Heil, A., Hawbaker, T., and Giglio, L., 2019, Historical background and current developments for mapping burned area from satellite Earth observation: Remote Sensing of Environment, v. 225, p. 45-64, https://doi.org/10.1016/j.rse.2019.02.013.","productDescription":"20 p.","startPage":"45","endPage":"64","ipdsId":"IP-102158","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":467839,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.rse.2019.02.013","text":"Publisher Index Page"},{"id":361792,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"225","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Chuvieco, Emilio","contributorId":213978,"corporation":false,"usgs":false,"family":"Chuvieco","given":"Emilio","email":"","affiliations":[{"id":38949,"text":"Environmental Remote Sensing Research Group, Department of Geology, Geography and the Environment, Universidad de Alcalá. Calle Colegios 2, Alcalá de Henares, 28801, Spain","active":true,"usgs":false}],"preferred":false,"id":758859,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mouillot, Flourent","contributorId":213980,"corporation":false,"usgs":false,"family":"Mouillot","given":"Flourent","email":"","affiliations":[{"id":38951,"text":"Centre National de la Recherche Scientifique (CNRS), Université de Montpellier, Université Paul-Valery Montpellier, Ecole pratique des hautes etudes (EPHE), Institut de Recherche pour le Développement (IRD)","active":true,"usgs":false}],"preferred":false,"id":758861,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"van der Werf, Guido R.","contributorId":213979,"corporation":false,"usgs":false,"family":"van der Werf","given":"Guido","email":"","middleInitial":"R.","affiliations":[{"id":38950,"text":"Department of Earth Sciences, Faculty of Science, Vrije Universiteit Amsterdam, De Boelelaan 1085, 1081HV Amsterdam, the Netherlands","active":true,"usgs":false}],"preferred":false,"id":758860,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"San Miguel, Jesus","contributorId":213981,"corporation":false,"usgs":false,"family":"San Miguel","given":"Jesus","email":"","affiliations":[{"id":38952,"text":"European Commission Joint Research Centre, Directorate D – Space, Security and Migration, Via Fermi 2749, Ispra, I-21027, Italy","active":true,"usgs":false}],"preferred":false,"id":758862,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Tanasse, Mihai","contributorId":213982,"corporation":false,"usgs":false,"family":"Tanasse","given":"Mihai","email":"","affiliations":[{"id":38953,"text":"Department of Environmental and Natural Resources Management, University of Patras, G. Seferi 2, Agrinio, GR-30100, Greece","active":true,"usgs":false}],"preferred":false,"id":758863,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Koutsias, Nikos","contributorId":213983,"corporation":false,"usgs":false,"family":"Koutsias","given":"Nikos","email":"","affiliations":[{"id":38954,"text":"Fenner School of Environment and Society, The Australian National University, Acton, ACT, Australia, and Bushfire and Natural Hazards Cooperative Research Centre, Melbourne, Australia","active":true,"usgs":false}],"preferred":false,"id":758864,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Garcia, Mariano","contributorId":213984,"corporation":false,"usgs":false,"family":"Garcia","given":"Mariano","email":"","affiliations":[{"id":38949,"text":"Environmental Remote Sensing Research Group, Department of Geology, Geography and the Environment, Universidad de Alcalá. Calle Colegios 2, Alcalá de Henares, 28801, Spain","active":true,"usgs":false}],"preferred":false,"id":758865,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Yebra, Marta","contributorId":213985,"corporation":false,"usgs":false,"family":"Yebra","given":"Marta","email":"","affiliations":[{"id":38954,"text":"Fenner School of Environment and Society, The Australian National University, Acton, ACT, Australia, and Bushfire and Natural Hazards Cooperative Research Centre, Melbourne, Australia","active":true,"usgs":false}],"preferred":false,"id":758866,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Padilla, Marc","contributorId":213986,"corporation":false,"usgs":false,"family":"Padilla","given":"Marc","email":"","affiliations":[{"id":38955,"text":"Centre for Landscape & Climate Research, Leicester Institute for Space and Earth Observation, School of Geography, University of Leicester, Leicester LE1 7RH, United Kingdom","active":true,"usgs":false}],"preferred":false,"id":758867,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Heil, Angelika","contributorId":213987,"corporation":false,"usgs":false,"family":"Heil","given":"Angelika","email":"","affiliations":[{"id":38956,"text":"Max Planck Institute for Meteorology, Environmental Modeling, Hamburg, Germany","active":true,"usgs":false}],"preferred":false,"id":758868,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Hawbaker, Todd 0000-0003-0930-9154 tjhawbaker@usgs.gov","orcid":"https://orcid.org/0000-0003-0930-9154","contributorId":568,"corporation":false,"usgs":true,"family":"Hawbaker","given":"Todd","email":"tjhawbaker@usgs.gov","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":547,"text":"Rocky Mountain Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":758869,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Giglio, Louis","contributorId":213989,"corporation":false,"usgs":false,"family":"Giglio","given":"Louis","email":"","affiliations":[{"id":38957,"text":"Department of Geographical Sciences, University of Maryland, College Park, MD, USA","active":true,"usgs":false}],"preferred":false,"id":758870,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70224544,"text":"70224544 - 2019 - Managing dams for energy and fish tradeoffs: What does a win-win solution take?","interactions":[],"lastModifiedDate":"2021-09-27T14:14:22.922021","indexId":"70224544","displayToPublicDate":"2019-03-06T09:05:28","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Managing dams for energy and fish tradeoffs: What does a win-win solution take?","docAbstract":"Management activities to restore endangered fish species, such as dam removals, fishway installations, and periodic turbine shutdowns, usually decrease hydropower generation capacities at dams. Quantitative analysis of the tradeoffs between energy production and fish population recovery related to dam decision-making is still lacking. In this study, an integrated hydropower generation and age-structured fish population model was developed using a system dynamics modeling method to assess basin-scale energy-fish tradeoffs under eight dam management scenarios. This model ran across 150 years on a daily time step, applied to five hydroelectric dams located in the main stem of the Penobscot River, Maine. We used alewife (Alosa pseudoharengus) to be representative of the local diadromous fish populations to link projected hydropower production with theoretical influences on migratory fish populations on the model river system. Our results show that while the five dams can produce around 427 GWh/year of energy, without fishway installations they would contribute to a 90% reduction in the alewife spawner abundance. The effectiveness of fishway installations is largely influenced by the size of reopened habitat areas and the actual passage rate of the fishways. Homing to natal habitat has an insignificant effect on the growth of the simulated spawner abundance. Operating turbine shutdowns during alewives' peak downstream migration periods, in addition to other dam management strategies, can effectively increase the spawner abundance by 480–550% while also preserving 65% of the hydropower generation capacity. These data demonstrate that in a river system where active hydropower dams operate, a combination of dam management strategies at the basin scale can best balance the tradeoff between energy production and the potential for migratory fish population recovery.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2019.03.042","usgsCitation":"Song, C., O’Malley, A., Roy, S.G., Zydlewski, J.D., Barber, B.L., and Mo, W., 2019, Managing dams for energy and fish tradeoffs: What does a win-win solution take?: Science of the Total Environment, v. 669, p. 833-843, https://doi.org/10.1016/j.scitotenv.2019.03.042.","productDescription":"11 p.","startPage":"833","endPage":"843","ipdsId":"IP-105717","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":467840,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2019.03.042","text":"Publisher Index Page"},{"id":389809,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Maine","otherGeospatial":"Penobscot River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -68.7744140625,\n 44.53959000445632\n ],\n [\n -68.3184814453125,\n 44.69599298172069\n ],\n [\n -68.2635498046875,\n 44.883120442385646\n ],\n [\n -68.1317138671875,\n 45.20913363773731\n ],\n [\n -68.18115234375,\n 45.38301927899065\n ],\n [\n -68.40087890624999,\n 45.57175504130605\n ],\n [\n -68.54919433593749,\n 45.69850658738846\n ],\n [\n -68.97216796875,\n 45.67932023569538\n ],\n [\n -69.01611328125,\n 45.57944511437787\n ],\n [\n -69.14794921875,\n 45.17041997262664\n ],\n [\n -69.169921875,\n 44.94536144236941\n ],\n [\n -69.41162109375,\n 44.68818283842486\n ],\n [\n -69.12597656249999,\n 44.453388800301774\n ],\n [\n -68.9117431640625,\n 44.469071224701096\n ],\n [\n -68.7744140625,\n 44.52392653654213\n ],\n [\n -68.7744140625,\n 44.53959000445632\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"669","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Song, Cuihong","contributorId":265998,"corporation":false,"usgs":false,"family":"Song","given":"Cuihong","email":"","affiliations":[{"id":12667,"text":"University of New Hampshire","active":true,"usgs":false}],"preferred":false,"id":824000,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"O’Malley, Andrew","contributorId":169716,"corporation":false,"usgs":false,"family":"O’Malley","given":"Andrew","email":"","affiliations":[],"preferred":false,"id":824001,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Roy, Samuel G.","contributorId":266000,"corporation":false,"usgs":false,"family":"Roy","given":"Samuel","email":"","middleInitial":"G.","affiliations":[{"id":7063,"text":"University of Maine","active":true,"usgs":false}],"preferred":false,"id":824002,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Zydlewski, Joseph D. 0000-0002-2255-2303 jzydlewski@usgs.gov","orcid":"https://orcid.org/0000-0002-2255-2303","contributorId":2004,"corporation":false,"usgs":true,"family":"Zydlewski","given":"Joseph","email":"jzydlewski@usgs.gov","middleInitial":"D.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":false,"id":824003,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Barber, Betsy L.","contributorId":207173,"corporation":false,"usgs":false,"family":"Barber","given":"Betsy","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":824004,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Mo, Weiwei","contributorId":266002,"corporation":false,"usgs":false,"family":"Mo","given":"Weiwei","affiliations":[{"id":12667,"text":"University of New Hampshire","active":true,"usgs":false}],"preferred":false,"id":824005,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70202336,"text":"sir20185166 - 2019 - Spatial and temporal variability of harmful algal blooms in Milford Lake, Kansas, May through November 2016","interactions":[],"lastModifiedDate":"2019-03-06T14:01:08","indexId":"sir20185166","displayToPublicDate":"2019-03-06T07:46:29","publicationYear":"2019","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":"2018-5166","displayTitle":"Spatial and Temporal Variability of Harmful Algal Blooms in Milford Lake, Kansas, May through November 2016","title":"Spatial and temporal variability of harmful algal blooms in Milford Lake, Kansas, May through November 2016","docAbstract":"The U.S. Geological Survey, in cooperation with the Kansas Department of Health and Environment (KDHE), completed a study to quantify the spatial and temporal variability of cyanobacterial blooms in Milford Lake, Kansas, over a range of environmental conditions at various time scales (hours to months). A better understanding of the spatial and temporal variability of cyanobacteria and microcystin will inform sampling and management strategies for Milford Lake and for other lakes with cyanobacterial harmful algal bloom (CyanoHAB) issues throughout the Nation. Spatial and temporal variability were assessed in the upstream one-third of Milford Lake (designated as “Zone C” by KDHE) during May through November 2016 using a combination of time-lapse photography, continuous water-quality monitors, discrete phytoplankton, chlorophyll, and microcystin samples, and spatially dense near-surface data. Combined, these data were used to characterize variability of cyanobacterial abundance, algal biomass, and microcystin concentrations in Zone C of Milford Lake before, during, and after cyanobacterial blooms in 2016.
Temporal patterns were evaluated during May through November 2016 using time-lapse photography at six locations in Zone C and at a single point location (the Wakefield site) using a combination of discrete and continuously measured water-quality data (including the cyanobacterial pigment phycocyanin). Based on time-lapse photography, CyanoHABs developed in Zone C of Milford Lake in early July and persisted through the end of November. Bloom accumulations at individual sites were dependent on wind direction. After a change in wind direction, it would take about 1 day for accumulations to become visible at different locations. During periods with low wind, accumulations were widespread and visible at all sites. Cyanobacteria were absent from the algal community at the Wakefield site in late May and were a minor component of the community in June; however, by mid-July the cyanobacteria were dominant and remained dominant until early November.
Chlorophyll and microcystin concentrations at the Wakefield site were estimated using sensor-measured phycocyanin based on regression models developed for Zone C. Regression-estimated concentrations likely are more indicative of seasonal patterns in algal biomass (as indicated by chlorophyll concentrations) and microcystin than discretely collected samples because regression-estimated data have a much higher temporal resolution. Based on regression estimates, algal biomass and microcystin concentrations at the Wakefield site steadily increased from May through August. After August, concentrations decreased but remained relatively high compared to May and June. Daily chlorophyll maxima were as much as 400 times higher than daily minima, and daily microcystin maxima were as many as several orders of magnitude higher than daily minima. The extreme variability in algal biomass and microcystin concentrations at the Wakefield site reflects the development and dissipation of blooms, as indicated by the time-lapse cameras.
Based on regression-estimated microcystin concentrations, the KDHE watch and warning thresholds for microcystin were exceeded during mid-June through late November. Exceedance of KDHE advisory thresholds often changed from no advisory to watch or warning over the course of the day because of the variability in algal biomass and microcystin concentrations caused by bloom development and dissipation. Continuous water-quality monitors may be useful in informing public-health decisions in lakes with variable CyanoHAB conditions; however, site-specific models need to be developed, and best practices for using continuous water-quality monitors to inform CyanoHAB management strategies need to be established.
Spatial data were collected on May 26, July 21, and September 15, 2016, using a combination of a boat-mounted array and discrete water-quality samples analyzed for phytoplankton community composition and chlorophyll and microcystin concentrations. Spatial patterns were described using regression-estimated chlorophyll and microcystin concentrations. During the May 26, 2016, spatial surveys, cyanobacterial abundances were relatively low throughout Zone C and did not exceed KDHE guidance values compared to spatial surveys on July 21 and September 15. Regression-estimated chlorophyll concentrations were indicative of higher algal biomass uplake in Zone C, and decreases in the downlake direction towards Zone B. Regression-estimated chlorophyll concentrations also were more variable uplake than downlake. Based on regression estimates, microcystin concentrations did not exceed KDHE guidance values anywhere in Zone C on May 26. Spatial patterns in microcystin throughout Zone C did not match patterns in regression-estimated chlorophyll concentrations, likely because the algal community was not dominated by cyanobacteria at most locations in May.
During the July 21, 2016, spatial surveys, cyanobacterial abundances in Zone C exceeded KDHE guidance values in 50 percent of samples. The algal community in Zone C was dominated by cyanobacteria at all locations except two, where cyanobacteria codominated with diatoms. Both locations where cyanobacteria and diatoms codominated were north of the causeway. Regression-estimated chlorophyll concentrations were indicative of higher algal biomass north of the causeway and on the eastern shore of Zone C. On July 21, algal biomass did not always decrease in the downlake direction. There was a decrease just south of the causeway but an increase shortly after with higher concentrations into Zone B. Spatial maps indicated changes in algal distribution at a 0.5-meter depth, with algae moving to the central part of the lake north of the causeway and along the eastern shore south of the causeway. Most regression-estimated microcystin concentrations on July 21 exceeded KDHE guidance values, reflecting the pervasive bloom conditions in Zone C during this period. Spatial patterns in regression-estimated microcystin concentrations throughout Zone C were similar to patterns seen in discrete samples and regression-estimated chlorophyll concentrations, with higher concentrations north of the causeway and on the east shore of Zone C.
During the September 15, 2016, spatial surveys, cyanobacterial abundances did not exceed KDHE guidance values. The algal community north of the causeway was dominated by diatoms. The algal community throughout the rest of Zone C was dominated by cyanobacteria. Of regression-estimated microcystin concentrations on September 15, 80 percent did not exceed KDHE guidance values. Spatial patterns indicated northward movement of the cyanobacterial bloom consistent with a wind shift noted the previous day. On September 14, winds were generally from the north to northwest, shifting to the south by September 15. There was a northward progression of chlorophyll and microcystin during the spatial surveys. These data, along with the camera data and spatial and wind data from May and July, indicate that wind can be a major driver of the spatial and temporal variability of cyanobacterial blooms in Milford Lake and likely plays a role in the extent and duration of near-shore accumulations.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185166","collaboration":"Prepared in cooperation with the Kansas Department of Health and Environment","usgsCitation":"Foster, G.M., Graham, J.L., and King, L.R., 2019, Spatial and temporal variability of harmful algal blooms in Milford Lake, Kansas, May through November 2016: U.S. Geological Survey Scientific Investigations Report 2018–5166, 36 p., https://doi.org/10.3133/sir20185166.","productDescription":"Report: vi, 36 p.; Appendixes: 28 p.; Data Releases: 4","numberOfPages":"46","onlineOnly":"Y","ipdsId":"IP-093516","costCenters":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"links":[{"id":361764,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F78S4P4M","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Water-quality data from two sites on Milford Lake, Kansas, May 25–26, June 8–10, July 20–21, and September 14–15, 2016"},{"id":361765,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7JH3KCV","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Time-lapse photography of Milford Lake, Kansas, June through November 2016"},{"id":361760,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5166/coverthb.jpg"},{"id":361763,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7DJ5DVX","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Milford Lake, Kansas spatial water-quality data, May 26, June 9, July 14, July 21, and September 15, 2016"},{"id":361761,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5166/sir20185166.PDF","text":"Report","size":"13.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018–5166"},{"id":361762,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2018/5166/sir20185166_appendixes.pdf","text":"Appendix 1 and 2","size":"571 kB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018–5166 Appendixes 1 and 2"},{"id":361766,"rank":7,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7513XFN","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Phytoplankton data for Milford Lake, Kansas, May through November 2016"}],"country":"United States","state":"Kansas","otherGeospatial":"Milford Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -97.1630859375,\n 38.982897808179985\n ],\n [\n -97.1630859375,\n 39.38526381099774\n ],\n [\n -96.49017333984375,\n 39.38526381099774\n ],\n [\n -96.49017333984375,\n 38.982897808179985\n ],\n [\n -97.1630859375,\n 38.982897808179985\n ]\n ]\n ]\n }\n }\n ]\n}\n\n\n\n","contact":"Director, Kansas Water Science Center
U.S. Geological Survey
1217 Biltmore Drive
Lawrence, KS 66049
The chaparral-dominated national forests of southern California were in part established to provide water provision services to the surrounding urban populations and irrigation for agriculture. However, water provision in the form of groundwater recharge and surface runoff depends on the climatological conditions of any given year and also landscape-scale disturbances such as fire. Fire is increasing in frequency in southern California and understanding its impacts both immediately postfire and as vegetation recovers, and the interactions between fire and hydrology, are key components to managing federal lands effectively. In this study we focus on nine fires in a study area that encompasses the four southern California national forests (Los Padres, Angeles, San Bernardino, and Cleveland) and use a water balance model to investigate the effects of water provision services post-fire at a regional scale. We found that runoff and recharge increased post-fire, with increases in recharge being greater with recovery times ranging from 2 to 4 y post-fire. Vegetation recovery occurred 2 y post-fire for all basins as indicated by remotely sensed imagery measuring vegetation greenness having returned to or exceeded pre-fire values for the basin. We found that runoff and recharge were more sensitive to the effects of climate than to length of time post-fire. Findings from these modeling tools allow users to anticipate the impact of fire on water provision services in the region and develop management strategies that help reduce the impacts of wildfire.
In the U.S., about 44 million people rely on self-supplied groundwater for drinking water. Because most self-supplied homeowners do not treat their water to control corrosion, drinking water can be susceptible to lead (Pb) contamination from metal plumbing. To assess the types and locations of susceptible groundwater, a geochemical reaction model that included pure Pb minerals and solid solutions of calcite (CaxPb1–xCO3) and apatite [CaxPb5-x(PO4)3(OH; Cl; F)] was developed to estimate the lead solubility potential (LSP) for over 8300 untreated groundwater samples collected from domestic and public-supply sites between 2000 and 2016 in the U.S. The LSP is the calculated amount of Pb metal that could dissolve at 25 °C before a Pb-bearing mineral precipitates. About 33% of untreated groundwater samples had LSP greater than 15 μg/L—the USEPA action level for dissolved plus particulate forms of Pb. Five percent of samples had high LSP (above 300 μg/L) and tended to occur in the eastern and southeastern U.S. Measured Pb concentrations above 15 μg/L were rarely detected (<1%) but always coincided with high LSP values. Future work will provide a better understanding of the relation between water chemistry, Pb-mineral formation, and dissolved Pb concentrations in tap water.
","language":"English","publisher":"ACS Publications","doi":"10.1021/acs.est.8b04475","usgsCitation":"Jurgens, B., Parkhurst, D.L., and Belitz, K., 2019, Assessing the lead solubility potential of untreated groundwater of the United States: Environmental Science & Technology, v. 53, no. 6, p. 3095-3103, https://doi.org/10.1021/acs.est.8b04475.","productDescription":"Article: 9 p.; Data Release ","startPage":"3095","endPage":"3103","ipdsId":"IP-083634","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":467842,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1021/acs.est.8b04475","text":"Publisher Index 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]\n}","volume":"53","issue":"6","noUsgsAuthors":false,"publicationDate":"2019-03-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Jurgens, Bryant 0000-0002-1572-113X","orcid":"https://orcid.org/0000-0002-1572-113X","contributorId":203430,"corporation":false,"usgs":true,"family":"Jurgens","given":"Bryant","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":770836,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Parkhurst, David L. 0000-0003-3348-1544 dlpark@usgs.gov","orcid":"https://orcid.org/0000-0003-3348-1544","contributorId":1088,"corporation":false,"usgs":true,"family":"Parkhurst","given":"David","email":"dlpark@usgs.gov","middleInitial":"L.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":770837,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Belitz, Kenneth 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differences on cellulose oxygen isotopes from two Kenai Peninsula, Alaska peatlands: Implications for hydroclimatic reconstructions","docAbstract":"Peat cores are valuable archives of past environmental change because they accumulate plant organic matter over millennia. While studies have primarily focused on physical, ecological, and some biogeochemical proxies, cores from peatlands have increasingly been used to interpret hydroclimatic change using stable isotope analyses of cellulose preserved in plant remains. Previous studies indicate that the stable oxygen isotope compositions (δ18O) preserved in alpha cellulose extracted from specific plant macrofossils reflect the δ18O values of past peatland water and thereby provide information on long-term changes in hydrology in response to climate. Oxygen isotope analyses of peat cellulose (δ18Ocellulose) have been successfully developed from peat cores that accumulate the same species for millennia. However, to fully exploit the potential of this proxy in species-diverse fens, studies are needed that account for the isotopic variations caused by changes in dominant species composition. This study assesses variation in δ18O values among peatland plant species and how they relate to environmental waters in two fens informally named Horse Trail and Goldfin, located on the leeward (dry) and windward (wet) side, respectively, of the climatic gradient across the Kenai Peninsula, Alaska. Environmental water δ18O values at both fens reflect unmodified δ18O values of mean annual precipitation, although at Goldfin standing pools were slightly influenced by evaporation. Modern plant [mosses and Carex spp. (sedges)] δ18Ocellulose values indicate that all Carex spp. are higher (~2.5‰) than those of mosses, likely driven by their vascular structure and ecophysiological difference from non-vascular mosses. Moss δ18Ocellulose values within each peatland are similar among the species, and differences appear related to evaporation effects on environmental waters within hummocks and hollows. The plant taxa-environmental water δ18O differences are applied to the previously determined Horse Trail Fen untreated bulk δ18O record. Results include significant changes to inferred millennial-to-centennial scale hydroclimatic trends where dominant taxa shift from moss to Carex spp., indicating that modern calibration datasets are necessary for interpreting stable isotopes from fens, containing a mix of vascular and nonvascular plants. Accounting for isotopic offsets through macrofossil analysis and modern plant-water isotope measurements opens new opportunities for hydroclimatic reconstructions from fen peatlands.
","language":"English","publisher":"Frontiers Media","doi":"10.3389/feart.2019.00025","usgsCitation":"Jones, M., Anderson, L., Keller, K., Nash, B., Littell, V., Wooller, M.J., and Jolley, C., 2019, An assessment of plant species differences on cellulose oxygen isotopes from two Kenai Peninsula, Alaska peatlands: Implications for hydroclimatic reconstructions: Frontiers in Earth Science, v. 7, 25, 16 p., https://doi.org/10.3389/feart.2019.00025.","productDescription":"25, 16 p.","ipdsId":"IP-102651","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":467843,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/feart.2019.00025","text":"Publisher Index Page"},{"id":368887,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Arc Lake, Bear Lake, Bear Mountain Lake, Browse Lake, Headquarters Lake, Horse Trail clearing, Kenai Lake, Lower Ohmer Lake, Portage Lake, Skilak Lake, Summit Lake, Tern Lake, Upper Ohmer Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -151.578369140625,\n 59.9274956808828\n ],\n [\n -149.04052734375,\n 59.9274956808828\n ],\n [\n -149.04052734375,\n 60.919754532399686\n ],\n [\n -151.578369140625,\n 60.919754532399686\n ],\n [\n -151.578369140625,\n 59.9274956808828\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -173.485107421875,\n 60.10319489936693\n ],\n [\n -171.826171875,\n 60.10319489936693\n ],\n [\n -171.826171875,\n 60.925093815014655\n ],\n [\n -173.485107421875,\n 60.925093815014655\n ],\n [\n -173.485107421875,\n 60.10319489936693\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"7","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2019-03-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Jones, Miriam 0000-0002-6650-7619","orcid":"https://orcid.org/0000-0002-6650-7619","contributorId":201994,"corporation":false,"usgs":true,"family":"Jones","given":"Miriam","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":false,"id":774422,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Anderson, Lesleigh 0000-0002-5264-089X land@usgs.gov","orcid":"https://orcid.org/0000-0002-5264-089X","contributorId":436,"corporation":false,"usgs":true,"family":"Anderson","given":"Lesleigh","email":"land@usgs.gov","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":774423,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Keller, Katherine 0000-0001-6915-5455","orcid":"https://orcid.org/0000-0001-6915-5455","contributorId":218048,"corporation":false,"usgs":false,"family":"Keller","given":"Katherine","email":"","affiliations":[{"id":39732,"text":"Natural Systems Analysts, Harvard University","active":true,"usgs":false}],"preferred":false,"id":774424,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Nash, Bailey 0000-0001-6423-2773 bnash@usgs.gov","orcid":"https://orcid.org/0000-0001-6423-2773","contributorId":220192,"corporation":false,"usgs":true,"family":"Nash","given":"Bailey","email":"bnash@usgs.gov","affiliations":[{"id":40146,"text":"Iowa State University, Ames, IA","active":true,"usgs":false},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":774425,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Littell, Virginia","contributorId":220193,"corporation":false,"usgs":false,"family":"Littell","given":"Virginia","email":"","affiliations":[{"id":40147,"text":"University of Washington, Seattle, WA","active":true,"usgs":false}],"preferred":false,"id":774426,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wooller, Matthew J.","contributorId":192799,"corporation":false,"usgs":false,"family":"Wooller","given":"Matthew","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":774427,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Jolley, Chelsea","contributorId":220194,"corporation":false,"usgs":false,"family":"Jolley","given":"Chelsea","email":"","affiliations":[{"id":26916,"text":"Brigham Young University, Provo, UT","active":true,"usgs":false}],"preferred":false,"id":774428,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70205300,"text":"70205300 - 2019 - Hormones and pharmaceuticals in groundwater used as a source of drinking water across the United States","interactions":[],"lastModifiedDate":"2019-09-13T15:11:37","indexId":"70205300","displayToPublicDate":"2019-03-05T10:44:53","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1565,"text":"Environmental Science & Technology","onlineIssn":"1520-5851","printIssn":"0013-936X","active":true,"publicationSubtype":{"id":10}},"title":"Hormones and pharmaceuticals in groundwater used as a source of drinking water across the United States","docAbstract":"This is the first large-scale, systematic assessment of hormone and pharmaceutical occurrence in groundwater used for drinking across the United States. Samples from 1091 sites in Principal Aquifers representing 60% of the volume pumped for drinking-water supply had final data for 21 hormones and 103 pharmaceuticals. At least one compound was detected at 5.9% of 844 sites representing the resource used for public supply across the entirety of 15 Principal Aquifers, and at 11.3% of 247 sites representing the resource used for domestic supply over subareas of nine Principal Aquifers. Of 34 compounds detected, one plastics component (bisphenol A), three pharmaceuticals (carbamazepine, sulfamethoxazole, and meprobamate), and the caffeine degradate 1,7-dimethylxanthine were detected in more than 0.5% of samples. Hydrocortisone had a concentration greater than a human-health benchmark at 1 site. Compounds with high solubility and low Koc were most likely to be detected. Detections were most common in shallow wells with a component of recent recharge, particularly in crystalline-rock and mixed land-use settings. Results indicate vulnerability of groundwater used for drinking water in the U.S. to contamination by these compounds is generally limited, and exposure to these compounds at detected concentrations is unlikely to have adverse effects on human health.
","language":"English","publisher":"ACS Publications","doi":"10.1021/acs.est.8b05592","usgsCitation":"Bexfield, L.M., Toccalino, P., Belitz, K., Foreman, W.T., and Furlong, E., 2019, Hormones and pharmaceuticals in groundwater used as a source of drinking water across the United States: Environmental Science & Technology, v. 53, no. 6, p. 2950-2960, https://doi.org/10.1021/acs.est.8b05592.","productDescription":"Article: 11 p.; 3 Data Releases ","startPage":"2950","endPage":"2960","ipdsId":"IP-076014","costCenters":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":5046,"text":"Branch of Analytical Serv (NWQL)","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true}],"links":[{"id":460449,"rank":5,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1021/acs.est.8b05592","text":"Publisher Index 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]\n}","volume":"53","issue":"6","noUsgsAuthors":false,"publicationDate":"2019-03-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Bexfield, Laura M. 0000-0002-1789-654X bexfield@usgs.gov","orcid":"https://orcid.org/0000-0002-1789-654X","contributorId":1273,"corporation":false,"usgs":true,"family":"Bexfield","given":"Laura","email":"bexfield@usgs.gov","middleInitial":"M.","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":770810,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Toccalino, Patricia 0000-0003-1066-1702","orcid":"https://orcid.org/0000-0003-1066-1702","contributorId":213736,"corporation":false,"usgs":true,"family":"Toccalino","given":"Patricia","affiliations":[{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true}],"preferred":true,"id":770811,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Belitz, Kenneth 0000-0003-4481-2345 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Services Division","active":true,"usgs":true},{"id":503,"text":"Office of Water Quality","active":true,"usgs":true},{"id":5046,"text":"Branch of Analytical Serv (NWQL)","active":true,"usgs":true}],"preferred":true,"id":770813,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Furlong, Edward 0000-0002-7305-4603","orcid":"https://orcid.org/0000-0002-7305-4603","contributorId":213730,"corporation":false,"usgs":true,"family":"Furlong","given":"Edward","affiliations":[{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true},{"id":503,"text":"Office of Water Quality","active":true,"usgs":true},{"id":5046,"text":"Branch of Analytical Serv (NWQL)","active":true,"usgs":true}],"preferred":true,"id":770814,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70215498,"text":"70215498 - 2019 - Modeling connectivity of non‐floodplain wetlands: Insights, approaches, and recommendations","interactions":[],"lastModifiedDate":"2020-10-21T15:39:49.079734","indexId":"70215498","displayToPublicDate":"2019-03-05T10:36:56","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7168,"text":"Journal of the American Water Resources Association (JAWRA)","active":true,"publicationSubtype":{"id":10}},"title":"Modeling connectivity of non‐floodplain wetlands: Insights, approaches, and recommendations","docAbstract":"Representing hydrologic connectivity of non‐floodplain wetlands (NFWs) to downstream waters in process‐based models is an emerging challenge relevant to many research, regulatory, and management activities. We review four case studies that utilize process‐based models developed to simulate NFW hydrology. Models range from a simple, lumped parameter model to a highly complex, fully distributed model. Across case studies, we highlight appropriate application of each model, emphasizing spatial scale, computational demands, process representation, and model limitations. We end with a synthesis of recommended “best modeling practices” to guide model application. These recommendations include: (1) clearly articulate modeling objectives, and revisit and adjust those objectives regularly; (2) develop a conceptualization of NFW connectivity using qualitative observations, empirical data, and process‐based modeling; (3) select a model to represent NFW connectivity by balancing both modeling objectives and available resources; (4) use innovative techniques and data sources to validate and calibrate NFW connectivity simulations; and (5) clearly articulate the limits of the resulting NFW connectivity representation. Our review and synthesis of these case studies highlights modeling approaches that incorporate NFW connectivity, demonstrates tradeoffs in model selection, and ultimately provides actionable guidance for future model application and development.