At the Amazon estuary, the oldest logging frontier in the Amazon, no studies have comprehensively explored the potential long-term population and yield consequences of multiple timber harvests over time. Matrix population modeling is one way to simulate long-term impacts of tree harvests, but this approach has often ignored common impacts of tree harvests including incidental damage, changes in post-harvest demography, shifts in the distribution of merchantable trees, and shifts in stand composition. We designed a matrix-based forest management model that incorporates these harvest-related impacts so resulting simulations reflect forest stand dynamics under repeated timber harvests as well as the realities of local smallholder timber management systems. Using a wide range of values for management criteria (e.g., length of cutting cycle, minimum cut diameter), we projected the long-term population dynamics and yields of hundreds of timber management regimes in the Amazon estuary, where small-scale, unmechanized logging is an important economic activity. These results were then compared to find optimal stand-level and species-specific sustainable timber management (STM) regimes using a set of timber yield and population growth indicators. Prospects for STM in Amazonian tidal floodplain forests are better than for many other tropical forests. However, generally high stock recovery rates between harvests are due to the comparatively high projected mean annualized yields from fast-growing species that effectively counterbalance the projected yield declines from other species. For Amazonian tidal floodplain forests, national management guidelines provide neither the highest yields nor the highest sustained population growth for species under management. Our research shows that management guidelines specific to a region’s ecological settings can be further refined to consider differences in species demographic responses to repeated harvests. In principle, such fine-tuned management guidelines could make management more attractive, thus bridging the currently prevalent gap between tropical timber management practice and regulation.
","language":"English","publisher":"Public Library of Science","publisherLocation":"San Francisco, CA","doi":"10.1371/journal.pone.0136740","usgsCitation":"Fortini, L.B., Cropper, W.P., and Zarin, D.J., 2015, Modeling the complex impacts of timber harvests to find optimal management regimes for Amazon tidal floodplain forests: PLoS ONE, v. 10, no. 8, p. 1-17, https://doi.org/10.1371/journal.pone.0136740.","productDescription":"e0136740; 17 p.","startPage":"1","endPage":"17","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-066968","costCenters":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"links":[{"id":471846,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0136740","text":"Publisher Index Page"},{"id":312008,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Brazil","otherGeospatial":"Amazon River, Mazagão watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -51.6,\n -0.5\n ],\n [\n -51.6,\n -0.4 \n ],\n [\n -51.5,\n -0.4 \n ],\n [\n -51.5,\n -0.5\n ],\n [\n -51.6,\n -0.5\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"10","issue":"8","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2015-08-31","publicationStatus":"PW","scienceBaseUri":"5666bbe6e4b06a3ea36c8b3a","contributors":{"authors":[{"text":"Fortini, Lucas B. 0000-0002-5781-7295 lfortini@usgs.gov","orcid":"https://orcid.org/0000-0002-5781-7295","contributorId":4645,"corporation":false,"usgs":true,"family":"Fortini","given":"Lucas","email":"lfortini@usgs.gov","middleInitial":"B.","affiliations":[{"id":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true},{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"preferred":false,"id":581403,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cropper, Wendell P.","contributorId":150362,"corporation":false,"usgs":false,"family":"Cropper","given":"Wendell","email":"","middleInitial":"P.","affiliations":[{"id":12557,"text":"University of Florida, FLREC","active":true,"usgs":false}],"preferred":false,"id":581404,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Zarin, Daniel J.","contributorId":150363,"corporation":false,"usgs":false,"family":"Zarin","given":"Daniel","email":"","middleInitial":"J.","affiliations":[{"id":18011,"text":"Climate and Land Use Alliance","active":true,"usgs":false}],"preferred":false,"id":581405,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70157351,"text":"70157351 - 2015 - Controls on the breach geometry and flood hydrograph during overtopping of non-cohesive earthen dams","interactions":[],"lastModifiedDate":"2015-09-21T15:13:26","indexId":"70157351","displayToPublicDate":"2015-08-30T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Controls on the breach geometry and flood hydrograph during overtopping of non-cohesive earthen dams","docAbstract":"Overtopping failure of non-cohesive earthen dams was investigated in 13 large-scale experiments with dams built of compacted, damp, fine-grained sand. Breaching was initiated by cutting a notch across the dam crest and allowing water escaping from a finite upstream reservoir to form its own channel. The channel developed a stepped profile, and upstream migration of the steps, which coalesced into a headcut, led to the establishment of hydraulic control (critical flow) at the channel head, or breach crest, an arcuate erosional feature that functions hydraulically as a weir. Novel photogrammetric methods, along with underwater videography, revealed that the retreating headcut maintained a slope near the angle of friction of the sand, while the cross section at the breach crest maintained a geometrically similar shape through time. That cross-sectional shape was nearly unaffected by slope failures, contrary to the assumption in many models of dam breaching. Flood hydrographs were quite reproducible--for sets of dams ranging in height from 0.55 m to 0.98 m--when the time datum was chosen as the time that the migrating headcut intersected the breach crest. Peak discharge increased almost linearly as a function of initial dam height. Early-time variability between flood hydrographs for nominally identical dams is probably a reflection of subtle experiment-to-experiment differences in groundwater hydrology and the interaction between surface water and groundwater.
","language":"English","publisher":"American Geophysical Union","doi":"10.1002/2014WR016620","usgsCitation":"Walder, J.S., Iverson, R.M., Godt, J.W., Logan, M., and Solovitz, S.A., 2015, Controls on the breach geometry and flood hydrograph during overtopping of non-cohesive earthen dams: Water Resources Research, v. 51, no. 8, p. 6701-6724, https://doi.org/10.1002/2014WR016620.","productDescription":"24 p.","startPage":"6701","endPage":"6724","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-060938","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":308321,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"51","issue":"8","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2015-08-30","publicationStatus":"PW","scienceBaseUri":"56012a3ce4b03bc34f5443f3","chorus":{"doi":"10.1002/2014wr016620","url":"http://dx.doi.org/10.1002/2014wr016620","publisher":"Wiley-Blackwell","authors":"Walder Joseph S., Iverson Richard M., Godt Jonathan W., Logan Matthew, Solovitz Stephen A.","journalName":"Water Resources Research","publicationDate":"8/2015","auditedOn":"10/1/2015"},"contributors":{"authors":[{"text":"Walder, Joseph S. jswalder@usgs.gov","contributorId":2046,"corporation":false,"usgs":true,"family":"Walder","given":"Joseph","email":"jswalder@usgs.gov","middleInitial":"S.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":572808,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Iverson, Richard M. 0000-0002-7369-3819 riverson@usgs.gov","orcid":"https://orcid.org/0000-0002-7369-3819","contributorId":536,"corporation":false,"usgs":true,"family":"Iverson","given":"Richard","email":"riverson@usgs.gov","middleInitial":"M.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true}],"preferred":true,"id":572809,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Godt, Jonathan W. 0000-0002-8737-2493 jgodt@usgs.gov","orcid":"https://orcid.org/0000-0002-8737-2493","contributorId":1166,"corporation":false,"usgs":true,"family":"Godt","given":"Jonathan","email":"jgodt@usgs.gov","middleInitial":"W.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":508,"text":"Office of the AD Hazards","active":true,"usgs":true}],"preferred":true,"id":572810,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Logan, Matthew 0000-0002-3558-2405 mlogan@usgs.gov","orcid":"https://orcid.org/0000-0002-3558-2405","contributorId":638,"corporation":false,"usgs":true,"family":"Logan","given":"Matthew","email":"mlogan@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true}],"preferred":true,"id":572811,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Solovitz, Stephen A.","contributorId":21434,"corporation":false,"usgs":true,"family":"Solovitz","given":"Stephen","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":572812,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70148363,"text":"70148363 - 2015 - Predicting watershed post-fire sediment yield with the InVEST sediment retention model: Accuracy and uncertainties","interactions":[],"lastModifiedDate":"2022-02-07T18:09:46.569795","indexId":"70148363","displayToPublicDate":"2015-08-29T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Predicting watershed post-fire sediment yield with the InVEST sediment retention model: Accuracy and uncertainties","docAbstract":"Increased sedimentation following wildland fire can negatively impact water supply and water quality. Understanding how changing fire frequency, extent, and location will affect watersheds and the ecosystem services they supply to communities is of great societal importance in the western USA and throughout the world. In this work we assess the utility of the InVEST (Integrated Valuation of Ecosystem Services and Tradeoffs) Sediment Retention Model to accurately characterize erosion and sedimentation of burned watersheds. InVEST was developed by the Natural Capital Project at Stanford University (Tallis et al., 2014) and is a suite of GIS-based implementations of common process models, engineered for high-end computing to allow the faster simulation of larger landscapes and incorporation into decision-making. The InVEST Sediment Retention Model is based on common soil erosion models (e.g., USLE – Universal Soil Loss Equation) and determines which areas of the landscape contribute the greatest sediment loads to a hydrological network and conversely evaluate the ecosystem service of sediment retention on a watershed basis. In this study, we evaluate the accuracy and uncertainties for InVEST predictions of increased sedimentation after fire, using measured postfire sediment yields available for many watersheds throughout the western USA from an existing, published large database. We show that the model can be parameterized in a relatively simple fashion to predict post-fire sediment yield with accuracy. Our ultimate goal is to use the model to accurately predict variability in post-fire sediment yield at a watershed scale as a function of future wildfire conditions.
","conferenceTitle":"3rd Joint Federal Interagency Conference","conferenceDate":"April 19-23, 2015","conferenceLocation":"Reno, NV","language":"English","publisher":"Joint Federal Interagency Conference","usgsCitation":"Sankey, J.B., McVay, J., Kreitler, J.R., Hawbaker, T., Vaillant, N., and Lowe, S., 2015, Predicting watershed post-fire sediment yield with the InVEST sediment retention model: Accuracy and uncertainties, 3rd Joint Federal Interagency Conference, Reno, NV, April 19-23, 2015, p. 987-998.","productDescription":"12 p.","startPage":"987","endPage":"998","ipdsId":"IP-061071","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":342116,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":395555,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://acwi.gov/sos/pubs/3rdJFIC/Proceedings.pdf","linkFileType":{"id":1,"text":"pdf"}}],"publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59366daae4b0f6c2d0d7d630","contributors":{"authors":[{"text":"Sankey, Joel B. 0000-0003-3150-4992 jsankey@usgs.gov","orcid":"https://orcid.org/0000-0003-3150-4992","contributorId":3935,"corporation":false,"usgs":true,"family":"Sankey","given":"Joel","email":"jsankey@usgs.gov","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":547853,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McVay, Jason","contributorId":274867,"corporation":false,"usgs":false,"family":"McVay","given":"Jason","affiliations":[{"id":12698,"text":"Northern Arizona University","active":true,"usgs":false}],"preferred":false,"id":547854,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kreitler, Jason R. 0000-0002-0243-5281 jkreitler@usgs.gov","orcid":"https://orcid.org/0000-0002-0243-5281","contributorId":4050,"corporation":false,"usgs":true,"family":"Kreitler","given":"Jason","email":"jkreitler@usgs.gov","middleInitial":"R.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":547855,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"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":547856,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Vaillant, Nicole","contributorId":140987,"corporation":false,"usgs":false,"family":"Vaillant","given":"Nicole","affiliations":[{"id":13638,"text":"Western Wildland environmental threat assessment Center","active":true,"usgs":false}],"preferred":false,"id":547857,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lowe, Scott bslowe@usgs.gov","contributorId":3299,"corporation":false,"usgs":true,"family":"Lowe","given":"Scott","email":"bslowe@usgs.gov","affiliations":[],"preferred":true,"id":547858,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70155950,"text":"ofr20151146 - 2015 - Summary of oceanographic measurements for characterizing light attenuation and sediment resuspension in the Barnegat Bay-Little Egg Harbor Estuary, New Jersey, 2013","interactions":[],"lastModifiedDate":"2015-08-31T09:56:10","indexId":"ofr20151146","displayToPublicDate":"2015-08-28T13:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-1146","title":"Summary of oceanographic measurements for characterizing light attenuation and sediment resuspension in the Barnegat Bay-Little Egg Harbor Estuary, New Jersey, 2013","docAbstract":"The U.S. Geological Survey, in cooperation with the New Jersey Department of Environmental Protection, measured suspended-sediment concentrations, currents, waves, light attenuation, and a variety of other water-quality parameters in the summer of 2013 in Barnegat Bay-Little Egg Harbor, New Jersey. These measurements quantified light attenuation and sediment resuspension in three seagrass meadows. Data were acquired sequentially at three paired channel-shoal sites, as the equipment was moved from south to north in the estuary. Data were collected for approximately 3 weeks at each site.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151146","collaboration":"Prepared in cooperation with the New Jersey Department of Environmental Protection","usgsCitation":"Dickhudt, P.J., Ganju, N.K, and Montgomery, E.T., 2015, Summary of oceanographic measurements for characterizing light attenuation and sediment resuspension in the Barnegat Bay-Little Egg Harbor estuary, New Jersey, 2013: U.S. Geological Survey Open-File Report 2015–1146, 18 p., https://dx.doi.org/10.3133/ofr20151146.","productDescription":"Report: vi, 18 p.; Dataset","numberOfPages":"28","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-065792","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":307544,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1146/ofr20151146.pdf","text":"Report","size":"4.59 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2015-1146"},{"id":307640,"rank":3,"type":{"id":28,"text":"Dataset"},"url":"https://dx.doi.org/10.5066/F7GB224S","text":"Oceanographic measurements for characterizing light attenuation and sediment resuspension in the Barnegat Bay-Little Egg Harbor Estuary, New Jersey, 2013","linkFileType":{"id":5,"text":"html"}},{"id":307543,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2015/1146/coverthb.jpg"}],"country":"United States","state":"New Jersey","otherGeospatial":"Barnegat Bay-Little Egg Harbor Estuary","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -73.90228271484375,\n 40.29419163838167\n ],\n [\n -74.26483154296875,\n 40.3130432088809\n ],\n [\n -74.4598388671875,\n 39.84439484396462\n ],\n [\n -74.63836669921874,\n 39.53793974517628\n ],\n [\n -74.8114013671875,\n 39.3130504637139\n ],\n [\n -74.66033935546875,\n 39.179046210512645\n ],\n [\n -74.619140625,\n 39.17052936145295\n ],\n [\n -74.58343505859374,\n 39.18117526158749\n ],\n [\n -74.39666748046874,\n 39.29392267616436\n ],\n [\n -74.2510986328125,\n 39.442556532077376\n ],\n [\n -74.102783203125,\n 39.64165260123416\n ],\n [\n -74.0423583984375,\n 39.83174093314558\n ],\n [\n -73.90228271484375,\n 40.29419163838167\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Woods Hole Coastal and Marine Science Center
U.S. Geological Survey
384 Woods Hole Road
Quissett Campus
Woods Hole, MA 02543-1598
508-548-8700 or 508-457-2200
Or visit our Web site at:
http://woodshole.er.usgs.gov/
Hydrographic networks form an important data foundation for cartographic base mapping and for hydrologic analysis. Drainage density patterns for these networks can be derived to characterize local landscape, bedrock and climate conditions, and further inform hydrologic and geomorphological analysis by indicating areas where too few headwater channels have been extracted. But natural drainage density patterns are not consistently available in existing hydrographic data for the United States because compilation and capture criteria historically varied, along with climate, during the period of data collection over the various terrain types throughout the country. This paper demonstrates an automated workflow that is being tested in a high-performance computing environment by the U.S. Geological Survey (USGS) to map natural drainage density patterns at the 1:24,000-scale (24K) for the conterminous United States. Hydrographic network drainage patterns may be extracted from elevation data to guide corrections for existing hydrographic network data. The paper describes three stages in this workflow including data pre-processing, natural channel extraction, and generation of drainage density patterns from extracted channels. The workflow is concurrently implemented by executing procedures on multiple subbasin watersheds within the U.S. National Hydrography Dataset (NHD). Pre-processing defines parameters that are needed for the extraction process. Extraction proceeds in standard fashion: filling sinks, developing flow direction and weighted flow accumulation rasters. Drainage channels with assigned Strahler stream order are extracted within a subbasin and simplified. Drainage density patterns are then estimated with 100-meter resolution and subsequently smoothed with a low-pass filter. The extraction process is found to be of better quality in higher slope terrains. Concurrent processing through the high performance computing environment is shown to facilitate and refine the choice of drainage density extraction parameters and more readily improve extraction procedures than conventional processing.
","conferenceTitle":"27th International Cartographic Conference","conferenceDate":"August 23-28, 2015","conferenceLocation":"Rio de Janeiro, Brazil","language":"English","publisher":"Springer","publisherLocation":"Cham","usgsCitation":"Stanislawski, L.V., Falgout, J.T., and Buttenfield, B., 2015, Automated extraction of natural drainage density patterns for the conterminous United States through high performance computing, 27th International Cartographic Conference, Rio de Janeiro, Brazil, August 23-28, 2015.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-066680","costCenters":[{"id":404,"text":"NGTOC Rolla","active":true,"usgs":true},{"id":37226,"text":"Core Science Analytics, Synthesis, and Libraries","active":true,"usgs":true}],"links":[{"id":311001,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -97.18505859374999,\n 25.97779895546436\n ],\n [\n -97.42675781249999,\n 25.878994400196202\n ],\n [\n -98.2177734375,\n 26.115985925333536\n ],\n [\n -99.0966796875,\n 26.47057302237511\n ],\n [\n -99.580078125,\n 27.625140335093324\n ],\n [\n -100.283203125,\n 28.265682390146477\n ],\n [\n -100.83251953125,\n 29.305561325527698\n ],\n [\n -101.27197265625,\n 29.592565403314087\n ],\n [\n -101.49169921875,\n 29.80251790576445\n ],\n [\n -102.67822265625,\n 29.76437737516313\n ],\n [\n -103.11767578124999,\n 29.036960648558267\n ],\n [\n -104.47998046875,\n 29.611670115197377\n ],\n [\n -104.7216796875,\n 29.973970240516614\n ],\n [\n -104.69970703125,\n 30.20211367909724\n ],\n [\n -104.9853515625,\n 30.675715404167743\n ],\n [\n -106.12792968749999,\n 31.44741029142872\n ],\n [\n -106.45751953125,\n 31.80289258670676\n ],\n [\n -108.21533203125,\n 31.784216884487385\n ],\n [\n -108.204345703125,\n 31.344254455668054\n ],\n [\n -110.98388671874999,\n 31.3348710339506\n ],\n [\n -114.82910156249999,\n 32.52828936482526\n ],\n [\n -114.7412109375,\n 32.731840896865684\n ],\n [\n -117.13623046874999,\n 32.54681317351514\n ],\n [\n -117.3779296875,\n 33.211116472416855\n ],\n [\n -118.23486328125,\n 33.779147331286474\n ],\n [\n -118.564453125,\n 34.043556504127444\n ],\n [\n -118.94897460937499,\n 34.052659421375964\n ],\n [\n -119.2236328125,\n 34.161818161230386\n ],\n [\n -119.66308593749999,\n 34.470335121217495\n ],\n [\n -120.44311523437499,\n 34.45221847282654\n ],\n [\n -120.640869140625,\n 34.56990638085636\n ],\n [\n -120.673828125,\n 35.137879119634185\n ],\n [\n -121.9482421875,\n 36.4566360115962\n ],\n [\n -121.83837890625,\n 36.721273880045004\n ],\n [\n -121.88232421875,\n 36.949891786813296\n ],\n [\n -122.05810546875,\n 36.96744946416931\n ],\n [\n -122.40966796874999,\n 37.23032838760387\n ],\n [\n -122.56347656249999,\n 37.71859032558816\n ],\n [\n -122.67333984374999,\n 37.90953361677018\n ],\n [\n -123.00292968749999,\n 37.996162679728116\n ],\n [\n -123.02490234375,\n 38.238180119798635\n ],\n [\n -123.74999999999999,\n 38.92522904714054\n ],\n [\n -123.85986328124999,\n 39.757879992021756\n ],\n [\n -124.365234375,\n 40.27952566881291\n ],\n [\n -124.4091796875,\n 40.463666324587685\n ],\n [\n -124.18945312500001,\n 41.07935114946899\n ],\n [\n -124.0576171875,\n 41.60722821271717\n ],\n [\n -124.29931640625,\n 42.00032514831621\n ],\n [\n -124.49707031249999,\n 42.827638636242284\n ],\n [\n -124.16748046874999,\n 43.83452678223684\n ],\n [\n -124.03564453125,\n 45.058001435398296\n ],\n [\n -124.03564453125,\n 46.30140615437332\n ],\n [\n -124.25537109375,\n 47.41322033016902\n ],\n [\n -124.62890625,\n 47.91634204016118\n ],\n [\n -124.69482421875,\n 48.4146186174932\n ],\n [\n -123.96972656249999,\n 48.188063481211415\n ],\n [\n -123.134765625,\n 48.17341248658084\n ],\n [\n -122.78320312499999,\n 48.246625590713826\n ],\n [\n -122.81616210937499,\n 48.42920055556841\n ],\n [\n -123.18969726562499,\n 48.50204750525715\n ],\n [\n -123.24462890625,\n 48.69096039092549\n ],\n [\n -122.728271484375,\n 48.77067246880509\n ],\n [\n -122.82714843749999,\n 49.001843917978526\n ],\n [\n -95.174560546875,\n 49.01625665778159\n ],\n [\n -95.152587890625,\n 49.38237278700955\n ],\n [\n -94.81201171875,\n 49.31796095602274\n ],\n [\n -94.669189453125,\n 48.777912755501845\n ],\n [\n -93.834228515625,\n 48.63290858589532\n ],\n [\n -93.8232421875,\n 48.516604348867475\n ],\n [\n -93.44970703125,\n 48.56752037390827\n ],\n [\n -93.33984375,\n 48.66194284607008\n ],\n [\n -92.59277343749999,\n 48.531157010976706\n ],\n [\n -92.08740234375,\n 48.37084770238363\n ],\n [\n -91.4501953125,\n 48.06339653776211\n ],\n [\n -91.07666015625,\n 48.19538740833338\n ],\n [\n -90.8349609375,\n 48.23930899024905\n ],\n [\n -90.791015625,\n 48.10743118848039\n ],\n [\n -89.62646484375,\n 48.019324184801185\n ],\n [\n -89.3463134765625,\n 47.98256841921402\n ],\n [\n -88.3795166015625,\n 48.31973404047173\n ],\n [\n -84.847412109375,\n 46.897739085507\n ],\n [\n -84.55078125,\n 46.464349400461124\n ],\n [\n -84.4134521484375,\n 46.49839225859763\n ],\n [\n -84.19921875,\n 46.53619267489863\n ],\n [\n -84.1058349609375,\n 46.51351558059737\n ],\n [\n -84.122314453125,\n 46.320378031062354\n ],\n [\n -84.00146484374999,\n 46.15700496290803\n ],\n [\n -83.95751953125,\n 46.06560846138691\n ],\n [\n -83.81469726562499,\n 46.11132565729796\n ],\n [\n -83.6334228515625,\n 46.11894150610708\n ],\n [\n -83.42468261718749,\n 46.0007775685566\n ],\n [\n -83.583984375,\n 45.82497145796607\n ],\n [\n -82.518310546875,\n 45.32897866218559\n ],\n [\n -82.12280273437499,\n 43.57243174740972\n ],\n [\n -82.40295410156249,\n 43.000629854450025\n ],\n [\n -82.474365234375,\n 42.79136972365016\n ],\n [\n -82.5732421875,\n 42.5611728553181\n ],\n [\n -82.8533935546875,\n 42.370720143531955\n ],\n [\n -83.07861328125,\n 42.32200108060303\n ],\n [\n -83.12255859375,\n 42.14304156290942\n ],\n [\n -83.14453125,\n 42.04521345501039\n ],\n [\n -83.07861328125,\n 41.86956082699455\n ],\n [\n -82.6776123046875,\n 41.68111756290652\n ],\n [\n -82.3974609375,\n 41.68111756290652\n ],\n [\n -81.243896484375,\n 42.21224516288584\n ],\n [\n -80.09033203125,\n 42.39506551565123\n ],\n [\n -78.9532470703125,\n 42.827638636242284\n ],\n [\n -78.91754150390625,\n 42.95039177450287\n ],\n [\n -79.06585693359375,\n 43.092960677116295\n ],\n [\n -79.06036376953125,\n 43.26120612479979\n ],\n [\n -79.19769287109375,\n 43.45291889355465\n ],\n [\n -78.6895751953125,\n 43.632099415557754\n ],\n [\n -76.7999267578125,\n 43.64005063334694\n ],\n [\n -76.4483642578125,\n 44.11125397357153\n ],\n [\n -75.7781982421875,\n 44.51609322284931\n ],\n [\n -75.30029296875,\n 44.84029065139799\n ],\n [\n -74.827880859375,\n 45.02695045318546\n ],\n [\n -71.510009765625,\n 45.02695045318546\n ],\n [\n -71.3232421875,\n 45.29034662473615\n ],\n [\n -70.653076171875,\n 45.42158812329091\n ],\n [\n -70.68603515625,\n 45.537136680398596\n ],\n [\n -70.301513671875,\n 45.920587344733654\n ],\n [\n -70.2685546875,\n 46.240651955001695\n ],\n [\n -70.059814453125,\n 46.40756396630067\n ],\n [\n -69.993896484375,\n 46.694667307773116\n ],\n [\n -69.246826171875,\n 47.46523622438362\n ],\n [\n -69.01611328125,\n 47.4355191531953\n ],\n [\n -69.0380859375,\n 47.26432008025478\n ],\n [\n -68.93920898437499,\n 47.19717795172789\n ],\n [\n -68.35693359375,\n 47.36115300722623\n ],\n [\n -67.763671875,\n 47.06263847995432\n ],\n [\n -67.78564453125,\n 45.706179285330855\n ],\n [\n -67.423095703125,\n 45.5679096098613\n ],\n [\n -67.423095703125,\n 45.22074260255366\n ],\n [\n -67.17041015625,\n 45.174292524076726\n ],\n [\n -66.961669921875,\n 44.85586880735725\n ],\n [\n -67.24731445312499,\n 44.63739123445585\n ],\n [\n -68.236083984375,\n 44.308126684886126\n ],\n [\n -68.258056640625,\n 44.20583500104184\n ],\n [\n -69.06005859375,\n 44.04811573082351\n ],\n [\n -69.80712890625,\n 43.73935207915473\n ],\n [\n -70.048828125,\n 43.78695837311561\n ],\n [\n -70.2081298828125,\n 43.73538317799622\n ],\n [\n -70.191650390625,\n 43.58039085560786\n ],\n [\n -70.587158203125,\n 43.25320494908846\n ],\n [\n -70.81787109374999,\n 42.89206418807337\n ],\n [\n -70.76568603515625,\n 42.70060440808085\n ],\n [\n -70.68603515625,\n 42.66426107379467\n ],\n [\n -70.63934326171875,\n 42.69051116998241\n ],\n [\n -70.59814453125,\n 42.65416193033991\n ],\n [\n -70.6585693359375,\n 42.589488572714245\n ],\n [\n -70.8782958984375,\n 42.54498667313236\n ],\n [\n -70.83984375,\n 42.508552415528634\n ],\n [\n -70.9771728515625,\n 42.44372793752476\n ],\n [\n -70.97442626953125,\n 42.391008609205045\n ],\n [\n -70.8343505859375,\n 42.26917949243506\n ],\n [\n -70.75469970703125,\n 42.24681856113825\n ],\n [\n -70.64208984375,\n 42.07783959017503\n ],\n [\n -70.5487060546875,\n 41.92680320648791\n ],\n [\n -70.53497314453125,\n 41.820455096140314\n ],\n [\n -70.42785644531249,\n 41.74672584176937\n ],\n [\n -70.21636962890625,\n 41.73852846935917\n ],\n [\n -70.0323486328125,\n 41.781552998900345\n ],\n [\n -70.0103759765625,\n 41.85319643776675\n ],\n [\n -70.0762939453125,\n 41.90432124806034\n ],\n [\n -70.09277343749999,\n 42.02889410108475\n ],\n [\n -70.16143798828125,\n 42.05948945192712\n ],\n [\n -70.1751708984375,\n 42.01869237684385\n ],\n [\n -70.24932861328125,\n 42.06356771883277\n ],\n [\n -70.22186279296875,\n 42.07987816698549\n ],\n [\n -70.13946533203124,\n 42.07580094787543\n ],\n [\n -70.02960205078125,\n 42.02889410108475\n ],\n [\n -69.96917724609375,\n 41.916585116228354\n ],\n [\n -69.93072509765625,\n 41.7856490686444\n ],\n [\n -69.93072509765625,\n 41.6770148220322\n ],\n [\n -69.971923828125,\n 41.61338889474735\n ],\n [\n -69.949951171875,\n 41.253032440653186\n ],\n [\n -70.11199951171875,\n 41.23238023874142\n ],\n [\n -70.279541015625,\n 41.304634388885916\n ],\n [\n -70.44158935546875,\n 41.347948493443546\n ],\n [\n -70.675048828125,\n 41.3500103516271\n ],\n [\n -70.7684326171875,\n 41.31494988250963\n ],\n [\n -70.7958984375,\n 41.29844430929419\n ],\n [\n -71.03759765625,\n 41.49623534616764\n ],\n [\n -71.10076904296875,\n 41.50034959128928\n ],\n [\n -71.180419921875,\n 41.46125371076149\n ],\n [\n -71.3616943359375,\n 41.45507852101139\n ],\n [\n -71.44683837890625,\n 41.43654942411456\n ],\n [\n -71.4935302734375,\n 41.36031866306708\n ],\n [\n -71.531982421875,\n 41.16004614168688\n ],\n [\n -71.97967529296874,\n 41.01928287604565\n ],\n [\n -72.86956787109375,\n 40.724364221722716\n ],\n [\n -73.33099365234375,\n 40.61812224225511\n ],\n [\n -73.75946044921875,\n 40.58267063809529\n ],\n [\n -73.92425537109375,\n 40.543026009954986\n ],\n [\n -73.9874267578125,\n 40.46993497635153\n ],\n [\n -73.96820068359375,\n 40.319325896602095\n ],\n [\n -74.07806396484375,\n 39.928694653732364\n ],\n [\n -74.1357421875,\n 39.631076770083666\n ],\n [\n -74.3994140625,\n 39.364032338047984\n ],\n [\n -74.6356201171875,\n 39.21948715423953\n ],\n [\n -74.8004150390625,\n 38.96795115401593\n ],\n [\n -74.96520996093749,\n 38.929502416386605\n ],\n [\n -75.07507324218749,\n 38.775499003812946\n ],\n [\n -75.0421142578125,\n 38.47939467327645\n ],\n [\n -75.16845703124999,\n 38.004819966413194\n ],\n [\n -75.574951171875,\n 37.65773212628274\n ],\n [\n -75.882568359375,\n 37.16907157713011\n ],\n [\n -75.9814453125,\n 36.88840804313823\n ],\n [\n -75.706787109375,\n 36.16448788632064\n ],\n [\n -75.443115234375,\n 35.7019167328534\n ],\n [\n -75.52001953125,\n 35.22767235493586\n ],\n [\n -76.00341796875,\n 35.10193405724606\n ],\n [\n -76.519775390625,\n 34.6241677899049\n ],\n [\n -76.783447265625,\n 34.66935854524543\n ],\n [\n -77.2119140625,\n 34.58799745550482\n ],\n [\n -77.596435546875,\n 34.37064492478658\n ],\n [\n -77.87109375,\n 34.043556504127444\n ],\n [\n -77.93701171875,\n 33.797408767572485\n ],\n [\n -78.167724609375,\n 33.87041555094183\n ],\n [\n -78.662109375,\n 33.8430453147447\n ],\n [\n -79.013671875,\n 33.568861182555565\n ],\n [\n -79.156494140625,\n 33.32134852669881\n ],\n [\n -79.1455078125,\n 33.201924189778936\n ],\n [\n -79.69482421875,\n 32.7872745269555\n ],\n [\n -80.43090820312499,\n 32.47269502206151\n ],\n [\n -80.44189453125,\n 32.32427558887655\n ],\n [\n -80.83740234375,\n 32.0732655510424\n ],\n [\n -81.265869140625,\n 31.42866311735861\n ],\n [\n -81.419677734375,\n 30.760718908944472\n ],\n [\n -81.34277343749999,\n 29.99300228455108\n ],\n [\n -80.936279296875,\n 29.1233732108192\n ],\n [\n -80.52978515625,\n 28.488005204159457\n ],\n [\n -80.606689453125,\n 28.372068829631633\n ],\n [\n -80.474853515625,\n 27.848790459862073\n ],\n [\n -80.068359375,\n 26.95145308349826\n ],\n [\n -80.079345703125,\n 26.2145910237943\n ],\n [\n -80.167236328125,\n 25.37380917154398\n ],\n [\n -80.79345703125,\n 24.87646991083154\n ],\n [\n -80.9033203125,\n 24.856534339310674\n ],\n [\n -81.177978515625,\n 25.21488107113259\n ],\n [\n -81.2548828125,\n 25.54244147012483\n ],\n [\n -81.551513671875,\n 25.878994400196202\n ],\n [\n -81.67236328125,\n 25.86910939099931\n ],\n [\n -81.89208984375,\n 26.441065564038418\n ],\n [\n -82.11181640625,\n 26.43122806450644\n ],\n [\n -82.298583984375,\n 26.833874515058554\n ],\n [\n -82.63916015625,\n 27.371767300523047\n ],\n [\n -82.869873046875,\n 27.89734922968426\n ],\n [\n -82.72705078125,\n 28.391400375817753\n ],\n [\n -82.7490234375,\n 29.046565622728846\n ],\n [\n -83.023681640625,\n 29.180941290001776\n ],\n [\n -83.8916015625,\n 30.0405664305846\n ],\n [\n -84.3310546875,\n 30.097613277217132\n ],\n [\n -84.320068359375,\n 29.907329376851553\n ],\n [\n -85.05615234375,\n 29.592565403314087\n ],\n [\n -85.36376953125,\n 29.66896252599253\n ],\n [\n -86.02294921875,\n 30.29701788337205\n ],\n [\n -87.03369140625,\n 30.372875188118016\n ],\n [\n -88.17626953125,\n 30.221101852485987\n ],\n [\n -89.27490234375,\n 30.240086360983426\n ],\n [\n -89.31884765624999,\n 29.76437737516313\n ],\n [\n -89.47265625,\n 29.554345125748267\n ],\n [\n -88.9013671875,\n 29.267232865200878\n ],\n [\n -89.27490234375,\n 28.8831596093235\n ],\n [\n -89.69238281249999,\n 29.209713225868185\n ],\n [\n -90.2197265625,\n 29.075375179558346\n ],\n [\n -91.01074218749999,\n 29.0945770775118\n ],\n [\n -91.4501953125,\n 29.34387539941801\n ],\n [\n -92.46093749999999,\n 29.53522956294847\n ],\n [\n -93.44970703125,\n 29.726222319395504\n ],\n [\n -94.52636718749999,\n 29.477861195816843\n ],\n [\n -95.2294921875,\n 29.05616970274342\n ],\n [\n -96.064453125,\n 28.5941685062326\n ],\n [\n -96.767578125,\n 28.16887518006332\n ],\n [\n -97.27294921875,\n 27.68352808378776\n ],\n [\n -97.3388671875,\n 26.980828590472107\n ],\n [\n -97.18505859374999,\n 25.97779895546436\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"563b3a3ae4b0d6133fe75c5d","contributors":{"authors":[{"text":"Stanislawski, Larry V. 0000-0002-9437-0576 lstan@usgs.gov","orcid":"https://orcid.org/0000-0002-9437-0576","contributorId":3386,"corporation":false,"usgs":true,"family":"Stanislawski","given":"Larry","email":"lstan@usgs.gov","middleInitial":"V.","affiliations":[{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true},{"id":404,"text":"NGTOC Rolla","active":true,"usgs":true}],"preferred":true,"id":564554,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Falgout, Jeff T. 0000-0002-7108-477X jfalgout@usgs.gov","orcid":"https://orcid.org/0000-0002-7108-477X","contributorId":4957,"corporation":false,"usgs":true,"family":"Falgout","given":"Jeff","email":"jfalgout@usgs.gov","middleInitial":"T.","affiliations":[{"id":208,"text":"Core Science Analytics and Synthesis","active":true,"usgs":true}],"preferred":true,"id":564555,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Buttenfield, Barbara P.","contributorId":145538,"corporation":false,"usgs":false,"family":"Buttenfield","given":"Barbara P.","affiliations":[{"id":16144,"text":"University of Colorado-Boulder","active":true,"usgs":false}],"preferred":false,"id":564556,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70156264,"text":"fs20153057 - 2015 - Science from genes to landscapes","interactions":[{"subject":{"id":70156264,"text":"fs20153057 - 2015 - Science from genes to landscapes","indexId":"fs20153057","publicationYear":"2015","noYear":false,"title":"Science from genes to landscapes"},"predicate":"SUPERSEDED_BY","object":{"id":70196848,"text":"fs20183030 - 2018 - Ecosystems science: Genes to landscapes","indexId":"fs20183030","publicationYear":"2018","noYear":false,"title":"Ecosystems science: Genes to landscapes"},"id":1}],"supersededBy":{"id":70196848,"text":"fs20183030 - 2018 - Ecosystems science: Genes to landscapes","indexId":"fs20183030","publicationYear":"2018","noYear":false,"title":"Ecosystems science: Genes to landscapes"},"lastModifiedDate":"2018-05-11T14:00:47","indexId":"fs20153057","displayToPublicDate":"2015-08-26T18:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-3057","title":"Science from genes to landscapes","docAbstract":"Wherever flowering plants flourish, pollinating bees, birds, butterflies, bats, and other animals are at work, providing vital and often unnoticed services. Many of these species are in serious decline, a situation if unabated, threatens agricultural production, maintenance of natural plant communities, and other important services. Responding to this urgent challenge, the U.S. Geological Survey (USGS) is part of efforts to provide scientific information to support pollinator conservation, including the implementation of a national pollinator health strategy (http://www.usgs.gov/ecosystems/wildlife/pollinators/.)
\nThis science is but one example of how the Ecosystems Science Mission Area of the USGS conducts science to support sound management and conservation of our Nation’s biological resources. It does this through research, technical assistance, and education conducted by Cooperative Research Units and Science Centers located in nearly every State.
\nThe quality of life and economic strength in America hinges on healthy ecosystems that support living things and natural processes. Ecosystem science better enables society to understand how and why ecosystems change, to predict and forecast future changes, and to guide actions that can prevent damage to, and restore and sustain ecosystems. It is through this knowledge that informed decisions are made about natural resources that can enhance our Nation's economic and environmental well-being.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20153057","usgsCitation":"U.S. Geological Survey, 2015, Science from genes to landscapes: U.S. Geological Survey Fact Sheet 2015-3057, 4 p., https://dx.doi.org/10.3133/fs20153057.","productDescription":"4 p.; HTML Document","numberOfPages":"4","onlineOnly":"N","additionalOnlineFiles":"Y","ipdsId":"IP-068444","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":307557,"rank":1,"type":{"id":2,"text":"Additional Report Piece"},"url":"https://pubs.usgs.gov/fs/2015/3057/","text":"Report HTML","description":"HTML version of FS 2015-3057"},{"id":307558,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2015/3057/pdf/fs20153057.pdf","text":"Report","size":"1.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2015-3057 PDF"},{"id":307559,"rank":3,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2015/3057/images/coverthb.jpg"}],"contact":"Ecosystems Mission Area
http://www.usgs.gov/ecosystems/
http://www.usgs.gov/ask/
1-888-ASK-USGS (1-888-275-8747)
An extensive canal and water management system exists in south Florida to prevent flooding, replenish groundwater, and impede saltwater intrusion. The unconfined Biscayne aquifer, which underlies southeast Florida and provides water for millions of residents, interacts with the canal system. The Biscayne aquifer is composed of a highly transmissive karst limestone; therefore, canal stage and flow may be affected by production well pumping, especially in locations where production wells and canals are in proximity.
\nThe U.S. Geological Survey developed a local-scale, transient, numerical groundwater flow model of a well field in Miami-Dade County to (1) quantify relations between well-field pumping and C-2 Canal (herein referred to as the Snapper Creek Canal) leakage, (2) determine primary controls on canal leakage variability, and (3) summarize results that could simplify characterization of canal/well-field interactions in other locations. In addition to the groundwater model development, stable isotope data from water-quality samples were used to characterize the relations between production well pumping and canal leakage. The results from the groundwater model and the isotope data were used to refine the conceptual flow model of the study area.
\nThe groundwater flow model MODFLOW-NWT was used for simulating groundwater flow and quantifying interactions between pumping from the well field and Snapper Creek Canal leakage. Input data for the groundwater model included precipitation, evapotranspiration, pumping, canal stage, and regional groundwater elevation. The inverse modeling tool UCODE and groundwater data from June 2010 to July 2011 were used to calibrate the model. Parameter sensitivity analyses were performed with UCODE. Model sensitivities to geologic heterogeneity, non-laminar flow, and changes in the regional flow boundary were evaluated. The groundwater model generally fits the calibration criteria well within estimated error ranges for groundwater elevations and canal leakage values. The mean average error for heads simulated with the model was 0.19 meter, and head residuals were generally randomly distributed.
\nThe model simulated groundwater flow under ambient conditions without production well pumping to establish background leakage. Groundwater flow also was simulated with production well pumping to estimate induced leakage from the Snapper Creek Canal that occurs in response to pumping.
\nCanal leakage was quantified as a percentage of total canal leakage. The percentage of leakage during pumping increased non-linearly with pumping rate, indicating a decreasing sensitivity of canal leakage to pumping at relatively large pumping magnitudes. The results for Snapper Creek Canal may serve as an upper limit for well-field interaction with surface-water features in Miami-Dade County, given the proximity (about 50 meters) of the pumping wells in this study to the Snapper Creek Canal.
\nThe isotopic compositions of hydrogen (H) and oxygen (O) in groundwater samples were used to distinguish sources for groundwater within the study area and to assess the extent of natural mixing and pumping-induced mixing with water in the Snapper Creek Canal. Water-level data and water-quality samples were collected from monitoring well clusters, production wells, and the Snapper Creek Canal during discrete sampling events under ambient and pumping conditions. Trends in the isotope data generally follow the regional west-to-east hydraulic gradient across the study area. Data collected within the monitoring-well clusters in closest proximity to the canal indicate that groundwater/surface-water interactions are greatest within the shallow flow zone of the aquifer, especially during pumping conditions. The isotopic composition of samples collected within the study area indicates that the shallow, highly transmissive preferential flow zone receives substantial recharge from the canal. The isotope data from the production wells which are open to the deeper flow zone within the aquifer, indicate only traces of mixing with a 2H- and 18O-enriched source, suggesting little canal admixture with waters of the deeper flow zone.
\nResults from the groundwater model and the stable isotope data analysis indicate the importance of considering geologic heterogeneity when investigating the relations between pumping and canal leakage, not only at this site, but also at other sites with similar heterogeneous geology. The model results were consistently sensitive to the hydrogeologic framework and changes in hydraulic conductivities. The model and the isotope data indicate that the majority of the groundwater/surface-water interactions occurred within the shallow flow zone. A relatively lower-permeability geologic layer occurring between the shallowest and deep preferential flow zones lessens the interactions between the production wells and the canal.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155095","collaboration":"Prepared in cooperation with the Miami-Dade Water and Sewer Department","usgsCitation":"Nemec, Katherine, Antolino, Dominick, Turtora, Michael, and Foster, Adam, 2015, Relations between well-field pumping and induced canal leakage in east-central Miami-Dade County, Florida, 2010–2011: U.S. Geological Survey Scientific Investigations Report 2015–5095, 65 p., https://dx.doi.org/10.3133/sir20155095.","productDescription":"Report: ix, 65 p.; Table","numberOfPages":"80","onlineOnly":"Y","additionalOnlineFiles":"Y","temporalStart":"2010-01-01","temporalEnd":"2011-12-31","ipdsId":"IP-056802","costCenters":[{"id":269,"text":"FLWSC-Ft. Lauderdale","active":true,"usgs":true}],"links":[{"id":307064,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2015/5095/coverthb.jpg"},{"id":307065,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5095/sir20155095.pdf","text":"Report","size":"8.21 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015-5095"},{"id":307066,"rank":3,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2015/5095/sir20155095_table1-6.xlsx","text":"Table 6","size":"69.7 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2015-5095","linkHelpText":"Summary of water-level and water-quality results for visited sites in Miami-Dade county, October 2008 through April 2011."}],"country":"United States","state":"Florida","county":"Miami-Dade County","otherGeospatial":"Snapper Creek","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -80.37700653076172,\n 25.692430237791747\n ],\n [\n -80.37700653076172,\n 25.712074241522732\n ],\n [\n -80.35160064697266,\n 25.712074241522732\n ],\n [\n -80.35160064697266,\n 25.692430237791747\n ],\n [\n -80.37700653076172,\n 25.692430237791747\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, USGS Caribbean-Florida Water Science Center
4446 Pet Lane, Suite 108
Lutz, FL 33559
http://fl.water.usgs.gov
This report presents five storage assessment units (SAUs) that have been identified as potentially suitable for geologic carbon dioxide sequestration within a 35,075-square-mile area that includes the entire onshore and State-water portions of the South Florida Basin. Platform-wide, thick successions of laterally extensive carbonates and evaporites deposited in highly cyclic depositional environments in the South Florida Basin provide several massive, porous carbonate reservoirs that are separated by evaporite seals. For each storage assessment unit identified within the basin, the areal distribution of the reservoir-seal couplet identified as suitable for geologic Carbon dioxide sequestration is presented, along with a description of the geologic characteristics that influence the potential carbon dioxide storage volume and reservoir performance. On a case-by-case basis, strategies for estimating the pore volume existing within structurally and (or) stratigraphically closed traps are also discussed. Geologic information presented in this report has been employed to calculate potential storage capacities for carbon dioxide sequestration in the storage assessment units assessed herein, although complete assessment results are not contained in this report.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Geologic framework for the national assessment of carbon dioxide storage resources (Open-File Report 2012-1024)","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20121024L","usgsCitation":"Roberts-Ashby, T.L., Brennan, S.T., Merrill, M.D., Blondes, M.S., Freeman, P.A., Cahan, S.M., DeVera, C.A., and Lohr, C.D., 2015, Geologic framework for the national assessment of carbon dioxide storage resources—South Florida Basin, chap. L of Warwick, P.D., and Corum, M.D., eds., Geologic framework for the national assessment of carbon dioxide storage resources: U.S. Geological Survey Open-File Report 2012–1024–L, 22 p., https://dx.doi.org/10.3133/ofr20121024L.","productDescription":"Report: vi, 22 p.; Datasets","numberOfPages":"28","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-061691","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true}],"links":[{"id":307480,"rank":3,"type":{"id":28,"text":"Dataset"},"url":"https://pubs.usgs.gov/of/2012/1024/l/downloads/Cell_C5050.zip","text":"Well Density","size":"120 kB","linkFileType":{"id":6,"text":"zip"}},{"id":307479,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2012/1024/l/ofr20121024l.pdf","text":"Report","size":"5.62 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2012-1024-L"},{"id":307473,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2012/1024/l/coverthb.jpg"},{"id":307481,"rank":4,"type":{"id":28,"text":"Dataset"},"url":"https://pubs.usgs.gov/of/2012/1024/l/downloads/SAU_C5050.zip","text":"Storage Assessment Units","size":"1.34 MB","linkFileType":{"id":6,"text":"zip"}}],"country":"United States","state":"Florida","otherGeospatial":"South Florida Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -80.70556640625,\n 28.729130483430154\n ],\n [\n -81.375732421875,\n 28.555576049185973\n ],\n [\n -82.386474609375,\n 28.478348692223165\n ],\n [\n -82.672119140625,\n 28.507315578441784\n ],\n [\n -82.8369140625,\n 28.20760859532738\n ],\n [\n -82.8369140625,\n 27.96044306897833\n ],\n [\n -82.8643798828125,\n 27.824502916144823\n ],\n [\n -82.7764892578125,\n 27.702983735525834\n ],\n [\n -82.6611328125,\n 27.48390806852859\n ],\n [\n -82.562255859375,\n 27.322974947245704\n ],\n [\n -82.4468994140625,\n 27.064017546608703\n ],\n [\n -82.265625,\n 26.632728662035912\n ],\n [\n -82.12280273437499,\n 26.391869671769022\n ],\n [\n -81.93603515625,\n 26.42138972529502\n ],\n [\n -81.82617187499999,\n 25.997549919572112\n ],\n [\n -81.6064453125,\n 25.799891182088334\n ],\n [\n -81.265869140625,\n 25.681137335685307\n ],\n [\n -81.14501953125,\n 25.34402602913433\n ],\n [\n -81.287841796875,\n 25.24469595130604\n ],\n [\n -81.6943359375,\n 24.936257323061316\n ],\n [\n -82.1337890625,\n 24.776759933219164\n ],\n [\n -82.562255859375,\n 24.78673454198888\n ],\n [\n -82.94677734375,\n 24.826624956562167\n ],\n [\n -83.14453125,\n 24.676969798202656\n ],\n [\n -83.07861328125,\n 24.4971463205719\n ],\n [\n -82.825927734375,\n 24.32707654001865\n ],\n [\n -82.177734375,\n 24.37712083961039\n ],\n [\n -81.298828125,\n 24.54712317973075\n ],\n [\n -80.6396484375,\n 24.836595553891183\n ],\n [\n -80.244140625,\n 25.304303764403617\n ],\n [\n -80.068359375,\n 25.730632525531913\n ],\n [\n -80.057373046875,\n 26.322960198925365\n ],\n [\n -80.035400390625,\n 26.88288045572338\n ],\n [\n -80.2001953125,\n 27.35225293806387\n ],\n [\n -80.452880859375,\n 27.877928333679495\n ],\n [\n -80.57373046875,\n 28.275358281817105\n ],\n [\n -80.5078125,\n 28.507315578441784\n ],\n [\n -80.70556640625,\n 28.729130483430154\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"USGS Energy Resources Program,
Health & Environment
12201 Sunrise Valley Drive
National Center, MS 913
Reston, VA 20192
USGS ERP: Geologic CO2 Sequestration
Landslides into valley bottoms can affect longitudinal profiles of rivers, thereby influencing landscape evolution through base-level changes. Large landslides can hinder river incision by temporarily damming rivers, but catastrophic failure of landslide dams may generate large floods that could promote incision. Dam stability therefore strongly modulates the effects of landslide dams and might be expected to vary among geologic settings. Here, we investigate the morphometry, stability, and effects on adjacent channel profiles of 17 former and current landslide dams in eastern Oregon. Data on landslide dam dimensions, former impoundment size, and longitudinal profile form were obtained from digital elevation data constrained by field observations and aerial imagery; while evidence for catastrophic dam breaching was assessed in the field. The dry, primarily extensional terrain of low-gradient volcanic tablelands and basins contrasts with the tectonically active, mountainous landscapes more commonly associated with large landslides. All but one of the eastern Oregon landslide dams are ancient (likely of order 103 to 104 years old), and all but one has been breached. The portions of the Oregon landslide dams blocking channels are small relative to the area of their source landslide complexes (0.4–33.6 km2). The multipronged landslides in eastern Oregon produce marginally smaller volume dams but affect much larger channels and impound more water than do landslide dams in mountainous settings. As a result, at least 14 of the 17 (82%) large landslide dams in our study area appear to have failed cataclysmically, producing large downstream floods now marked by boulder outwash, compared to a 40–70% failure rate for landslide dams in steep mountain environments. Morphometric indices of landslide dam stability calibrated in other environments were applied to the Oregon dams. Threshold values of the Blockage and Dimensionless Blockage Indices calibrated to worldwide data sets successfully separate dam sites in eastern Oregon that failed catastrophically from those that did not. Accumulated sediments upstream of about 50% of the dam sites indicate at least short-term persistence of landslide dams prior to eventual failure. Nevertheless, only three landslide dam remnants and one extant dam significantly elevate the modern river profile. We conclude that eastern Oregon's landslide dams are indeed floodmakers, but we lack clear evidence that they form lasting plugs.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.geomorph.2015.06.040","collaboration":"Prepared in collaboration with Lewis and Clarck College, Portland, OR Central Washington University, USDA Forset Service","usgsCitation":"Safran, E.B., O'Connor, J., Ely, L.L., House, K., Grant, G., Harrity, K., Croall, K., and Jones, E., 2015, Plugs or flood-makers? the unstable landslide dams of eastern Oregon: Geomorphology, v. 248, p. 237-251, https://doi.org/10.1016/j.geomorph.2015.06.040.","productDescription":"15 p.","startPage":"237","endPage":"251","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-061330","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true}],"links":[{"id":471854,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.geomorph.2015.06.040","text":"Publisher Index Page"},{"id":307507,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon","otherGeospatial":"Columbia River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117.20214843749999,\n 44.55916341529184\n ],\n [\n -118.3447265625,\n 46.042735653846506\n ],\n [\n -121.00341796874999,\n 45.72152152227954\n ],\n [\n -121.48681640624999,\n 43.1811470593997\n ],\n [\n -118.58642578124999,\n 43.1811470593997\n ],\n [\n -117.44384765625,\n 41.1290213474951\n ],\n [\n -115.3564453125,\n 41.1455697310095\n ],\n [\n -117.20214843749999,\n 44.55916341529184\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"248","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"55ded526e4b0518e354e07e9","contributors":{"authors":[{"text":"Safran, Elizabeth B.","contributorId":10694,"corporation":false,"usgs":true,"family":"Safran","given":"Elizabeth","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":569719,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"O'Connor, Jim E. 0000-0002-7928-5883 oconnor@usgs.gov","orcid":"https://orcid.org/0000-0002-7928-5883","contributorId":140771,"corporation":false,"usgs":true,"family":"O'Connor","given":"Jim E.","email":"oconnor@usgs.gov","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":false,"id":569718,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ely, Lisa L.","contributorId":19854,"corporation":false,"usgs":true,"family":"Ely","given":"Lisa","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":569720,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"House, Kyle 0000-0002-0019-8075 khouse@usgs.gov","orcid":"https://orcid.org/0000-0002-0019-8075","contributorId":2293,"corporation":false,"usgs":true,"family":"House","given":"Kyle","email":"khouse@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":569721,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Grant, Gordon E.","contributorId":30881,"corporation":false,"usgs":false,"family":"Grant","given":"Gordon E.","affiliations":[{"id":12647,"text":"U.S. Forest Service, Pacific Northwest Research Station","active":true,"usgs":false}],"preferred":false,"id":569722,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Harrity, Kelsey","contributorId":146980,"corporation":false,"usgs":false,"family":"Harrity","given":"Kelsey","email":"","affiliations":[{"id":16764,"text":"Lewis and Clark College, Portland OR","active":true,"usgs":false}],"preferred":false,"id":569723,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Croall, Kelsey","contributorId":146981,"corporation":false,"usgs":false,"family":"Croall","given":"Kelsey","email":"","affiliations":[{"id":16764,"text":"Lewis and Clark College, Portland OR","active":true,"usgs":false}],"preferred":false,"id":569724,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Jones, Emily","contributorId":146982,"corporation":false,"usgs":false,"family":"Jones","given":"Emily","email":"","affiliations":[{"id":16764,"text":"Lewis and Clark College, Portland OR","active":true,"usgs":false}],"preferred":false,"id":569725,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70155119,"text":"sir20155101 - 2015 - Flood-inundation maps for Grand River, Red Cedar River, and Sycamore Creek near Lansing, Michigan","interactions":[],"lastModifiedDate":"2016-02-04T08:54:30","indexId":"sir20155101","displayToPublicDate":"2015-08-26T09:15:00","publicationYear":"2015","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":"2015-5101","title":"Flood-inundation maps for Grand River, Red Cedar River, and Sycamore Creek near Lansing, Michigan","docAbstract":"Digital flood-inundation maps for a total of 19.7 miles of the Grand River, the Red Cedar River, and Sycamore Creek were created by the U.S. Geological Survey (USGS) in cooperation with the City of Lansing, Michigan, and the U.S. Army Corps of Engineers. The flood-inundation maps, which can be accessed through the USGS Flood Inundation Mapping Science Web site at http://water.usgs.gov/osw/flood_inundation/, show estimates of the areal extent and depth of flooding corresponding to selected water levels (stages) at three USGS streamgages: Grand River at Lansing, MI (04113000), Red Cedar River at East Lansing, MI (04112500), and Sycamore Creek at Holt Road near Holt, MI (04112850). Near-real-time stages at these streamgages can be obtained on the Internet from the USGS National Water Information System at http://waterdata.usgs.gov/ or the National Weather Service (NWS) Advanced Hydrologic Prediction Service at http:/water.weather.gov/ahps/, which also forecasts flood hydrographs at all of these sites.
\nEach set of flood profiles was computed by means of a one-dimensional step-backwater model. Each model was calibrated to the current stage-discharge relation at each streamgage and to water levels determined with stage sensors (pressure transducers) temporarily deployed along each stream reach. The hydraulic model was used to compute a set of water-surface profiles for flood stages from nearly Action Stage to above Major Flood stage, as reported by the National Weather Service. The computed water-surface profiles were then used in combination with a Geographic Information System digital elevation model derived from light detection and ranging (lidar) data to delineate the approximate areas flooded at each water level.
\nThese maps, used in conjunction with real-time USGS streamgage data and NWS forecasting, provide critical information to emergency management personnel and the public. This information is used to plan flood response actions, such as evacuations and road closures, as well as aid in postflood recovery efforts.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155101","collaboration":"Prepared in cooperation with the City of Lansing; Michigan, and U.S. Army Corps of Engineers","usgsCitation":"Whitehead, M.T., and Ostheimer, C.J., 2015, Flood-inundation maps for Grand River, Red Cedar River, and Sycamore Creek near Lansing, Michigan (ver. 1.1, February 2016: U.S. Geological Survey Scientific Investigations Report 2015–5101, 19 p.,\nhttps://dx.doi.org/10.3133/sir20155101.","productDescription":"Report: v, 19 p.; Downloads Directory","startPage":"1","endPage":"19","numberOfPages":"29","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-064143","costCenters":[{"id":513,"text":"Ohio Water Science Center","active":true,"usgs":true}],"links":[{"id":316374,"rank":4,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sir/2015/5101/versionHist.txt","size":"1 KB","linkFileType":{"id":2,"text":"txt"},"description":"SIR 2015-5101"},{"id":307510,"rank":3,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sir/2015/5101/downloads/sir20155101_lansing-mi-report-downloads.zip","text":"Downloads Directory","size":"1.15 GB","linkFileType":{"id":6,"text":"zip"},"description":"SIR 2015-5101","linkHelpText":"Grids, Shapefiles, Metadata, and Ancillary Information"},{"id":307357,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5101/sir20155101.pdf","text":"Report","size":"1.20 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015-5101"},{"id":307504,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2015/5101/coverthbr.jpg"}],"country":"United States","state":"Michigan","county":"Eaton County, Ingham County","city":"Lansing","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -84.87556457519531,\n 42.487795634680005\n ],\n [\n -84.87556457519531,\n 42.86589941517495\n ],\n [\n -84.39834594726562,\n 42.86589941517495\n ],\n [\n -84.39834594726562,\n 42.487795634680005\n ],\n [\n -84.87556457519531,\n 42.487795634680005\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Originally posted August 26, 2015; Version 1.1: February 2, 2016","contact":"Director, Michigan-Ohio Water Science Center
U.S. Geological Survey
6480 Doubletree Ave
Columbus, OH 43229–1111
http://oh.water.usgs.gov/
A common challenge in the conservation of broadly distributed, yet imperiled species is understanding which factors facilitate persistence at distributional edges, locations where populations are often vulnerable to extirpation due to changes in climate, land use, or distributions of other species. For Columbia spotted frogs (Rana luteiventris) in the Great Basin (USA), a genetically distinct population segment of conservation concern, we approached this problem by examining (1) landscape-scale habitat availability and distribution, (2) water body-scale habitat associations, and (3) resource management-identified threats to persistence. We found that areas with perennial aquatic habitat and suitable climate are extremely limited in the southern portion of the species’ range. Within these suitable areas, native and non-native predators (trout and American bullfrogs [Lithobates catesbeianus]) are widespread and may further limit habitat availability in upper- and lower-elevation areas, respectively. At the water body scale, spotted frog occupancy was associated with deeper sites containing abundant emergent vegetation and nontrout fish species. Streams with American beaver (Castor canadensis) frequently had these structural characteristics and were significantly more likely to be occupied than ponds, lakes, streams without beaver, or streams with inactive beaver ponds, highlighting the importance of active manipulation of stream environments by beaver. Native and non-native trout reduced the likelihood of spotted frog occupancy, especially where emergent vegetation cover was sparse. Intensive livestock grazing, low aquatic connectivity, and ephemeral hydroperiods were also negatively associated with spotted frog occupancy. We conclude that persistence of this species at the arid end of its range has been largely facilitated by habitat stability (i.e., permanent hydroperiod), connectivity, predator-free refugia, and a commensalistic interaction with an ecosystem engineer. Beaver-induced changes to habitat quality, stability, and connectivity may increase spotted frog population resistance and resilience to seasonal drought, grazing, non-native predators, and climate change, factors which threaten local or regional persistence.
","language":"English","publisher":"Wiley","doi":"10.1002/ece3.1627","usgsCitation":"Arkle, R., and Pilliod, D., 2015, Persistence at distributional edges: Columbia spotted frog habitat in the arid Great Basin, USA: Ecology and Evolution, v. 5, no. 17, p. 3704-3724, https://doi.org/10.1002/ece3.1627.","productDescription":"21 p.","startPage":"3704","endPage":"3724","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-059485","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":471857,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.1627","text":"Publisher Index Page"},{"id":307506,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Idaho, Oregon, Nevada, Utah","otherGeospatial":"Great Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -120.10253906249999,\n 36.98500309285596\n ],\n [\n -120.10253906249999,\n 44.54350521320822\n ],\n [\n -111.9287109375,\n 44.54350521320822\n ],\n [\n -111.9287109375,\n 36.98500309285596\n ],\n [\n -120.10253906249999,\n 36.98500309285596\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"5","issue":"17","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2015-08-18","publicationStatus":"PW","scienceBaseUri":"55ded526e4b0518e354e07e7","chorus":{"doi":"10.1002/ece3.1627","url":"http://dx.doi.org/10.1002/ece3.1627","publisher":"Wiley-Blackwell","authors":"Arkle Robert S., Pilliod David S.","journalName":"Ecology and Evolution","publicationDate":"8/2015","auditedOn":"10/21/2015"},"contributors":{"authors":[{"text":"Arkle, Robert S. 0000-0003-3021-1389 rarkle@usgs.gov","orcid":"https://orcid.org/0000-0003-3021-1389","contributorId":3501,"corporation":false,"usgs":true,"family":"Arkle","given":"Robert S.","email":"rarkle@usgs.gov","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":false,"id":569929,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pilliod, David S. dpilliod@usgs.gov","contributorId":140097,"corporation":false,"usgs":true,"family":"Pilliod","given":"David S.","email":"dpilliod@usgs.gov","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":false,"id":569930,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70155029,"text":"sir20155100 - 2015 - Flood-inundation maps for the Scioto River at La Rue, Ohio","interactions":[],"lastModifiedDate":"2015-08-26T14:51:33","indexId":"sir20155100","displayToPublicDate":"2015-08-26T09:15:00","publicationYear":"2015","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":"2015-5100","title":"Flood-inundation maps for the Scioto River at La Rue, Ohio","docAbstract":"Digital flood-inundation maps for a 3-mile (mi) reach of the Scioto River that extends about 1/2 mi upstream and 1/2 mi downstream of the corporate boundary for La Rue, Ohio, were created by the U.S. Geological Survey (USGS) in cooperation with the Village of La Rue, Marion County Commissioners, Montgomery Township, and Marion County Scioto River Conservancy. The flood-inundation maps show estimates of the areal extent and depth of flooding correspond ing to selected water levels (stages) at the USGS streamgage on the Scioto River at La Rue (station number 03217500). The maps can be accessed through the USGS Flood Inundation Mapping Science Web site at http://water.usgs.gov/osw/flood_ inundation/ . Near-real-time stages at this streamgage can be obtained from the USGS National Water Information System at http://waterdata.usgs.gov/oh/nwis/uv/?site_no=03217500 or the National Weather Service (NWS) Advanced Hydro - logic Prediction Service at http://water.weather.gov/ahps2/ hydrograph.php?wfo=cle&gage=LARO1 , which also forecasts flood hydrographs at this site.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155100","collaboration":"Prepared in cooperation with the Village of La Rue, Marion County Commissioners, Montgomery Township, and Marion County Scioto River Conservancy","usgsCitation":"Whitehead, M.T., 2015, Flood-inundation maps for the Scioto River at La Rue, Ohio: U.S. Geological Survey Scientific Investigations Report 2015–5100,Director, Michigan-Ohio Water Science Center
U.S. Geological Survey
6480 Doubletree Ave
Columbus, OH 43229–1111
http://oh.water.usgs.gov/
Effective management of surface waters requires a robust understanding of spatiotemporal constituent loadings from upstream sources and the uncertainty associated with these estimates. We compared the total dissolved solids loading into the Great Salt Lake (GSL) for water year 2013 with estimates of previously sampled periods in the early 1960s.We also provide updated results on GSL loading, quantitatively bounded by sampling uncertainties, which are useful for current and future management efforts. Our statistical loading results were more accurate than those from simple regression models. Our results indicate that TDS loading to the GSL in water year 2013 was 14.6 million metric tons with uncertainty ranging from 2.8 to 46.3 million metric tons, which varies greatly from previous regression estimates for water year 1964 of 2.7 million metric tons. Results also indicate that locations with increased sampling frequency are correlated with decreasing confidence intervals. Because time is incorporated into the LOADEST models, discrepancies are largely expected to be a function of temporally lagged salt storage delivery to the GSL associated with terrestrial and in-stream processes. By incorporating temporally variable estimates and statistically derived uncertainty of these estimates,we have provided quantifiable variability in the annual estimates of dissolved solids loading into the GSL. Further, our results support the need for increased monitoring of dissolved solids loading into saline lakes like the GSL by demonstrating the uncertainty associated with different levels of sampling frequency.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2015.07.015","collaboration":"Prepared in collaboration with UT DNR, Div of Forestry, Fire, and State Lands","usgsCitation":"Shope, C.L., and Angeroth, C.E., 2015, Calculating salt loads to Great Salt Lake and the associated uncertainties for water year 2013; updating a 48 year old standard: Science of the Total Environment, v. 536, p. 391-405, https://doi.org/10.1016/j.scitotenv.2015.07.015.","productDescription":"15","startPage":"391","endPage":"405","onlineOnly":"N","additionalOnlineFiles":"N","temporalStart":"2012-10-01","temporalEnd":"2013-09-30","ipdsId":"IP-061192","costCenters":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"links":[{"id":471858,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2015.07.015","text":"Publisher Index Page"},{"id":307462,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Utah","otherGeospatial":"Great Salt Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -112.79937744140625,\n 41.73033005046653\n ],\n [\n -113.12072753906249,\n 41.64828831259535\n ],\n [\n -113.11248779296874,\n 41.56203190200195\n ],\n [\n -113.02459716796875,\n 41.37680856570233\n ],\n [\n -113.09326171875,\n 41.333513657873205\n ],\n [\n -113.08227539062499,\n 41.25716209782705\n ],\n [\n -112.884521484375,\n 41.23031465959445\n ],\n [\n -112.82958984375,\n 41.178653972331695\n ],\n [\n -112.85980224609375,\n 41.03171529379288\n ],\n [\n -112.73345947265625,\n 40.932190241465634\n ],\n [\n -112.64556884765624,\n 40.75557964275591\n ],\n [\n -112.55218505859374,\n 40.74517613004631\n ],\n [\n -112.5164794921875,\n 40.90313381465847\n ],\n [\n -112.42584228515625,\n 40.64521960545374\n ],\n [\n -112.34893798828124,\n 40.6410514961004\n ],\n [\n -112.11547851562499,\n 40.79301881008675\n ],\n [\n -112.10723876953124,\n 40.84290487729676\n ],\n [\n -111.884765625,\n 40.93841495689795\n ],\n [\n -111.94244384765625,\n 41.00477542222949\n ],\n [\n -112.08251953125,\n 41.054501963290505\n ],\n [\n -112.22259521484375,\n 41.24890252240322\n ],\n [\n -112.17864990234375,\n 41.31288691435732\n ],\n [\n -112.071533203125,\n 41.335575973123895\n ],\n [\n -112.01934814453125,\n 41.3850519497068\n ],\n [\n -112.06878662109374,\n 41.46537017728069\n ],\n [\n -112.23907470703124,\n 41.411835731001254\n ],\n [\n -112.29400634765624,\n 41.492120839687786\n ],\n [\n -112.445068359375,\n 41.492120839687786\n ],\n [\n -112.40936279296875,\n 41.24683746537623\n ],\n [\n -112.467041015625,\n 41.22205169039092\n ],\n [\n -112.54119873046875,\n 41.457136982923494\n ],\n [\n -112.65655517578125,\n 41.448902743309674\n ],\n [\n -112.763671875,\n 41.55586631766996\n ],\n [\n -112.72247314453124,\n 41.64828831259535\n ],\n [\n -112.79937744140625,\n 41.73033005046653\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"536","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"55dd83a3e4b0518e354dc708","contributors":{"authors":[{"text":"Shope, Christopher L. cshope@usgs.gov","contributorId":5016,"corporation":false,"usgs":true,"family":"Shope","given":"Christopher","email":"cshope@usgs.gov","middleInitial":"L.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":569442,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Angeroth, Cory E. 0000-0002-2915-6418 angeroth@usgs.gov","orcid":"https://orcid.org/0000-0002-2915-6418","contributorId":2105,"corporation":false,"usgs":true,"family":"Angeroth","given":"Cory","email":"angeroth@usgs.gov","middleInitial":"E.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":569443,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70156546,"text":"70156546 - 2015 - Stress-gradient hypothesis explains susceptibility to Bromus tectorum invasion and community stability in North America's semi-arid Artemisia tridentata wyomingensis ecosystems","interactions":[],"lastModifiedDate":"2017-11-22T17:51:13","indexId":"70156546","displayToPublicDate":"2015-08-25T15:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2490,"text":"Journal of Vegetation Science","active":true,"publicationSubtype":{"id":10}},"title":"Stress-gradient hypothesis explains susceptibility to Bromus tectorum invasion and community stability in North America's semi-arid Artemisia tridentata wyomingensis ecosystems","docAbstract":"Questions: (1) What combinations of overlapping water and heat stress and herbivory disturbance gradients are associated with shifts in interactions between Artemisia tridentata subsp. wyomingensis (Artemisia) and herbaceous beneficiary species? (2) Do interactions between Artemisia and beneficiaries shift from competition to facilitation with increasing stress-disturbance where facilitation and competition are most frequent and strongest at the highest and lowest levels, respectively? (3) Do such relationships differ for native and non-native beneficiaries? (4) What are the implications of any observed shifts in interactions between community compositional stability in space and susceptibility to invasion?
\nLocation: North American Artemisia communities.
\nMethods: We tested the stress-gradient hypothesis (SGH) in an observational study consisting of 75 sites located along overlapping water and heat stress and disturbance gradients. We used spatial patterns of association among Artemisia and six native and two non-native beneficiary species; including the invasive annual grass Bromus tectorum, representing a diverse array of life history strategies, to infer whether the net outcome of interactions was facilitation or competition. We assessed implications for community stability by examining shifts in community composition in space and resistance to invasion.
\nResults/Conclusions: Cattle herbivory, a novel disturbance and selective force, was a significant component of two overlapping stress gradients most strongly associated with observed shifts in interactions. Facilitation and competition were strongest and most frequent at the highest and lowest stress levels along both gradients, respectively. Contrasting ecological optima among native and non-native beneficiaries led to strikingly different patterns of interactions. The four native bunchgrasses with the strongest competitive response abilities exhibited the strongest facilitation at their upper limits of stress tolerance, while the two non-natives exhibited the strongest competition at the highest stress levels, which coincided with their maximum abundance. Artemisia facilitation enhanced stability at intermediate stress levels by providing a refuge for native bunchgrasses, which in turn reduced the magnitude of B. tectorum invasion. However, facilitation was a destabilizing force at the highest stress levels when native bunchgrasses became obligate beneficiaries dependent on facilitation for their persistence. B. tectorum dominated these communities, and the next fire may convert them to annual grasslands.
","language":"English","publisher":"Wiley","doi":"10.1111/jvs.12327","usgsCitation":"Reisner, M.D., Doescher, P., and Pyke, D.A., 2015, Stress-gradient hypothesis explains susceptibility to Bromus tectorum invasion and community stability in North America's semi-arid Artemisia tridentata wyomingensis ecosystems: Journal of Vegetation Science, v. 26, no. 6, p. 1212-1224, https://doi.org/10.1111/jvs.12327.","productDescription":"13 p.","startPage":"1212","endPage":"1224","onlineOnly":"N","additionalOnlineFiles":"N","temporalStart":"2008-05-10","temporalEnd":"2009-07-15","ipdsId":"IP-053585","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":307449,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon","otherGeospatial":"Great Basin floristic province","volume":"26","issue":"6","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2015-07-18","publicationStatus":"PW","scienceBaseUri":"55dd83a6e4b0518e354dc71c","contributors":{"authors":[{"text":"Reisner, Michael D.","contributorId":96178,"corporation":false,"usgs":true,"family":"Reisner","given":"Michael","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":569453,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Doescher, Paul S.","contributorId":100306,"corporation":false,"usgs":true,"family":"Doescher","given":"Paul S.","affiliations":[],"preferred":false,"id":569454,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pyke, David A. 0000-0002-4578-8335 david_a_pyke@usgs.gov","orcid":"https://orcid.org/0000-0002-4578-8335","contributorId":3118,"corporation":false,"usgs":true,"family":"Pyke","given":"David","email":"david_a_pyke@usgs.gov","middleInitial":"A.","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":569452,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70156545,"text":"70156545 - 2015 - Genetic signatures of historical dispersal of fish threatened by biological invasions: the case of galaxiids in South America","interactions":[],"lastModifiedDate":"2017-11-29T13:56:24","indexId":"70156545","displayToPublicDate":"2015-08-25T15:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2193,"text":"Journal of Biogeography","active":true,"publicationSubtype":{"id":10}},"title":"Genetic signatures of historical dispersal of fish threatened by biological invasions: the case of galaxiids in South America","docAbstract":"The ecological effects of biological invasions are well documented, but little is known about the effects of invaders on the genetic structure of native species. We examined the phylogeography, genetic variation and population structuring of two galaxiid fishes, Aplochiton zebraand A. taeniatus, threatened by non-native salmonids, and whose conservation is complicated by misidentification and limited knowledge of their genetic diversity.
\nChile and the Falkland Islands.
\nWe combined microsatellite and mitochondrial DNA (16S rDNA and COI) markers to compare genetic diversity, effective population size and gene flow of Aplochiton spp. populations differentially affected by salmonid presence.
\nWe identified two 16S rDNA haplotypes among A. zebra – one dominant in coastal populations and another dominant in inland populations. Populations living on the island of Chiloé displayed a mixture of coastal and inland haplotypes, as well as high microsatellite diversity, as one would expect if the island had been a refugium during the Last Glacial Maximum, or a contact zone among populations. Microsatellite data revealed strong population structuring, indicative of current isolation patterns, and a negative correlation between the genetic diversity of A. zebra and the relative abundance of invasive salmonids.
\nOur study indicates that population structuring of A. zebra reflects the influence of historical patterns of migration, but also the current levels of reduced gene flow among watersheds. Invasive salmonids, known to compete with and prey on native galaxiids, may have had negative impacts on the genetic diversity of Aplochiton spp. The low genetic variation found in some populations, coupled with potential biases in abundance estimates due to species misidentification, highlight the urgent need for more research into the conservation status of the two species of Aplochiton.
\nPrevailing theory suggests that stream temperature warms asymptotically in a downstream direction, beginning at the temperature of the source in the headwaters and leveling off downstream as it converges to match meteorological conditions. However, there have been few empirical examples of longitudinal patterns of temperature in large rivers due to a paucity of data. We constructed longitudinal thermal profiles (temperature versus distance) for 53 rivers in the Pacific Northwest (USA) using an extensive dataset of remotely sensed summertime river temperatures and classified each profile into one of five patterns of downstream warming: asymptotic (increasing then flattening), linear (increasing steadily), uniform (not changing), parabolic (increasing then decreasing), or complex (not fitting other classes). We evaluated (1) how frequently profiles warmed asymptotically downstream as expected, and (2) whether relationships between river temperature and common hydroclimatic variables differed by profile class. We found considerable diversity in profile shape, with 47% of rivers warming asymptotically, and 53% having alternative profile shapes. Water temperature did not warm substantially over the course of the river for coastal parabolic and uniform profiles, and for some linear and complex profiles. Profile classes showed no clear geographical trends. The degree of correlation between river temperature and hydroclimatic variables differed among profile classes, but there was overlap among classes. Water temperature in rivers with asymptotic or parabolic profiles was positively correlated with August air temperature, tributary temperature and velocity, and negatively correlated with elevation, August precipitation, gradient, and distance upstream. Conversely, associations were less apparent in rivers with linear, uniform, or complex profiles. Factors contributing to the unique shape of parabolic profiles differed for coastal and inland rivers, where downstream cooling was influenced locally by climate or cool water inputs, respectively. Potential drivers of shape for complex profiles were specific to each river. These thermal patterns indicate diverse thermal habitats that may promote resilience of aquatic biota to climate change. Without this spatial context, climate change models may incorrectly estimate loss of thermally suitable habitat.
","language":"English","publisher":"Wiley","doi":"10.1002/hyp.10506","usgsCitation":"Fullerton, A.H., Torgersen, C.E., Lawler, J.J., Faux, R.N., Steel, E.A., Beechie, T.J., Ebersole, J.L., and Leibowitz, S.J., 2015, Rethinking the longitudinal stream temperature paradigm: region-wide comparison of thermal infrared imagery reveals unexpected complexity of river temperatures: Hydrological Processes, v. 29, no. 22, p. 4719-4737, https://doi.org/10.1002/hyp.10506.","productDescription":"19 p.","startPage":"4719","endPage":"4737","onlineOnly":"N","additionalOnlineFiles":"N","temporalStart":"1994-07-01","temporalEnd":"2007-08-31","ipdsId":"IP-055750","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":307413,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Idaho, Oregon, Washington","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -116.04858398437499,\n 49.009050809382046\n ],\n [\n -123.321533203125,\n 49.023461463214126\n ],\n [\n -123.211669921875,\n 48.22467264956519\n ],\n [\n -124.771728515625,\n 48.42920055556841\n ],\n [\n -124.71679687499999,\n 47.87214396888731\n ],\n [\n -124.024658203125,\n 45.85941212790755\n ],\n [\n -124.244384765625,\n 43.79488907226601\n ],\n [\n -124.661865234375,\n 42.90011265525328\n ],\n [\n -124.112548828125,\n 41.43449030894922\n ],\n [\n -124.508056640625,\n 40.38839687388361\n ],\n [\n -123.85986328124999,\n 39.740986355883564\n ],\n [\n -123.82690429687499,\n 38.882481197550774\n ],\n [\n -123.035888671875,\n 38.18638677411551\n ],\n [\n -118.78967285156249,\n 38.156156969924915\n ],\n [\n -119.99267578124999,\n 38.993572058209466\n ],\n [\n -119.9981689453125,\n 41.99624282178583\n ],\n [\n -111.0443115234375,\n 42.00848901572399\n ],\n [\n -111.04774475097656,\n 44.47446108518852\n ],\n [\n -116.04858398437499,\n 49.009050809382046\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"29","issue":"22","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2015-06-14","publicationStatus":"PW","scienceBaseUri":"55dd83a5e4b0518e354dc717","contributors":{"authors":[{"text":"Fullerton, Aimee H.","contributorId":146936,"corporation":false,"usgs":false,"family":"Fullerton","given":"Aimee","email":"","middleInitial":"H.","affiliations":[{"id":12641,"text":"NOAA NMFS","active":true,"usgs":false}],"preferred":false,"id":569469,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Torgersen, Christian E. 0000-0001-8325-2737 ctorgersen@usgs.gov","orcid":"https://orcid.org/0000-0001-8325-2737","contributorId":146935,"corporation":false,"usgs":true,"family":"Torgersen","given":"Christian","email":"ctorgersen@usgs.gov","middleInitial":"E.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":true,"id":569468,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lawler, Joshua J.","contributorId":73327,"corporation":false,"usgs":false,"family":"Lawler","given":"Joshua","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":569470,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Faux, Russell N.","contributorId":146937,"corporation":false,"usgs":false,"family":"Faux","given":"Russell","email":"","middleInitial":"N.","affiliations":[{"id":16760,"text":"Watershed Sciences, Inc.","active":true,"usgs":false}],"preferred":false,"id":569471,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Steel, E. Ashley","contributorId":7589,"corporation":false,"usgs":false,"family":"Steel","given":"E.","email":"","middleInitial":"Ashley","affiliations":[],"preferred":false,"id":569472,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Beechie, Timothy J.","contributorId":139468,"corporation":false,"usgs":false,"family":"Beechie","given":"Timothy","email":"","middleInitial":"J.","affiliations":[{"id":6578,"text":"National Marine Fisheries Service, Seattle, WA 98112, USA","active":true,"usgs":false}],"preferred":false,"id":569473,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ebersole, Joseph L.","contributorId":146938,"corporation":false,"usgs":false,"family":"Ebersole","given":"Joseph","email":"","middleInitial":"L.","affiliations":[{"id":12657,"text":"EPA NEIC","active":true,"usgs":false}],"preferred":false,"id":569474,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Leibowitz, Scott J.","contributorId":146939,"corporation":false,"usgs":false,"family":"Leibowitz","given":"Scott","email":"","middleInitial":"J.","affiliations":[{"id":12657,"text":"EPA NEIC","active":true,"usgs":false}],"preferred":false,"id":569475,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70156694,"text":"70156694 - 2015 - Effects of changing climate on aquatic habitat and connectivity for remnant populations of a wide-ranging frog species in an arid landscape","interactions":[],"lastModifiedDate":"2017-11-22T17:49:36","indexId":"70156694","displayToPublicDate":"2015-08-25T12:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Effects of changing climate on aquatic habitat and connectivity for remnant populations of a wide-ranging frog species in an arid landscape","docAbstract":"Amphibian species persisting in isolated streams and wetlands in desert environments can be susceptible to low connectivity, genetic isolation, and climate changes. We evaluated the past (1900–1930), recent (1981–2010), and future (2071–2100) climate suitability of the arid Great Basin (USA) for the Columbia spotted frog (Rana luteiventris) and assessed whether changes in surface water may affect connectivity for remaining populations. We developed a predictive model of current climate suitability and used it to predict the historic and future distribution of suitable climates. We then modeled changes in surface water availability at each time period. Finally, we quantified connectivity among existing populations on the basis of hydrology and correlated it with interpopulation genetic distance. We found that the area of the Great Basin with suitable climate conditions has declined by approximately 49% over the last century and will likely continue to decline under future climate scenarios. Climate conditions at currently occupied locations have been relatively stable over the last century, which may explain persistence at these sites. However, future climates at these currently occupied locations are predicted to become warmer throughout the year and drier during the frog's activity period (May – September). Fall and winter precipitation may increase, but as rain instead of snow. Earlier runoff and lower summer base flows may reduce connectivity between neighboring populations, which is already limited. Many of these changes could have negative effects on remaining populations over the next 50–80 years, but milder winters, longer growing seasons, and wetter falls might positively affect survival and dispersal. Collectively, however, seasonal shifts in temperature, precipitation, and stream flow patterns could reduce habitat suitability and connectivity for frogs and possibly other aquatic species inhabiting streams in this arid region.
","language":"English","publisher":"Blackwell Pub. Ltd.","publisherLocation":"Oxford","doi":"10.1002/ece3.1634","usgsCitation":"Pilliod, D., Arkle, R., Robertson, J.M., Murphy, M., and Funk, W.C., 2015, Effects of changing climate on aquatic habitat and connectivity for remnant populations of a wide-ranging frog species in an arid landscape: Ecology and Evolution, v. 5, no. 18, p. 3979-3994, https://doi.org/10.1002/ece3.1634.","productDescription":"16 p.","startPage":"3979","endPage":"3994","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-059837","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":471861,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.1634","text":"Publisher Index Page"},{"id":307534,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"5","issue":"18","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2015-08-26","publicationStatus":"PW","scienceBaseUri":"55dee32fe4b0518e354e080b","chorus":{"doi":"10.1002/ece3.1634","url":"http://dx.doi.org/10.1002/ece3.1634","publisher":"Wiley-Blackwell","authors":"Pilliod David S., Arkle Robert S., Robertson Jeanne M., Murphy Melanie A., Funk W. Chris","journalName":"Ecology and Evolution","publicationDate":"8/26/2015","auditedOn":"10/2/2015"},"contributors":{"authors":[{"text":"Pilliod, David S. 0000-0003-4207-3518 dpilliod@usgs.gov","orcid":"https://orcid.org/0000-0003-4207-3518","contributorId":147050,"corporation":false,"usgs":true,"family":"Pilliod","given":"David S.","email":"dpilliod@usgs.gov","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":false,"id":570105,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Arkle, Robert S. 0000-0003-3021-1389 rarkle@usgs.gov","orcid":"https://orcid.org/0000-0003-3021-1389","contributorId":147051,"corporation":false,"usgs":true,"family":"Arkle","given":"Robert S.","email":"rarkle@usgs.gov","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":false,"id":570106,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Robertson, Jeanne M.","contributorId":147052,"corporation":false,"usgs":false,"family":"Robertson","given":"Jeanne","email":"","middleInitial":"M.","affiliations":[{"id":16778,"text":"Biology Department, California State University Northbridge","active":true,"usgs":false}],"preferred":false,"id":570107,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Murphy, Melanie","contributorId":88239,"corporation":false,"usgs":true,"family":"Murphy","given":"Melanie","affiliations":[],"preferred":false,"id":570109,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Funk, W. Chris 0000-0002-9254-6718","orcid":"https://orcid.org/0000-0002-9254-6718","contributorId":97589,"corporation":false,"usgs":false,"family":"Funk","given":"W.","email":"","middleInitial":"Chris","affiliations":[{"id":6998,"text":"Department of Biology, Colorado State University","active":true,"usgs":false}],"preferred":false,"id":570108,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70155290,"text":"sir20155099 - 2015 - Flood-inundation maps for the St. Marys River at Decatur, Indiana","interactions":[],"lastModifiedDate":"2015-09-23T09:37:03","indexId":"sir20155099","displayToPublicDate":"2015-08-24T15:15:00","publicationYear":"2015","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":"2015-5099","title":"Flood-inundation maps for the St. Marys River at Decatur, Indiana","docAbstract":"Digital flood-inundation maps for an 8.9-mile reach of the St. Marys River at Decatur, Indiana, were developed by the U.S. Geological Survey (USGS), in cooperation with the Indiana Office of Community and Rural Affairs. The inundation maps, which can be accessed through the USGS Flood Inundation Mapping Science Web site (http://water.usgs.gov/osw/flood_inundation/), depict estimates of the areal extent and depth of flooding corresponding to selected water levels (stages) of the St. Marys River at Decatur (USGS station number 04181500). The maps are useful for estimating near-real-time areas of inundation by referencing concurrent USGS streamgage information at http://waterdata.usgs.gov/. In addition, the streamgage information was provided to the National Weather Service (NWS) for incorporation into their Advanced Hydrologic Prediction Service flood warning system (http:/water.weather.gov/ahps/). NWS-forecasted peak-stage information may be used in conjunction with the maps developed during this study to show predicted areas of flood inundation.
\nDuring this study, flood profiles were computed for the stream reach by means of a one-dimensional, step-backwater model. The model was calibrated by using the stage-discharge relation for the streamgage at St. Marys River at Decatur. The hydraulic model was used to compute 18 water-surface profiles for flood stages varied at 1-foot (ft) intervals and ranging from approximately bankfull (13 ft above gage datum) to greater than the highest recorded water level at the streamgage. To delineate the area of flood inundation for each modeled water level, maps were constructed in a geographic information system by combining the simulated water-surface profiles with a digital-elevation model derived from light detection and ranging (lidar) data. Estimated flood-inundation boundaries along each simulated profile were developed using HEC–GeoRAS software.
\nThe availability of these maps and associated Web mapping tools, along with the current river stage from USGS streamgages and forecasted flood stages from the NWS, provides emergency managers and residents with information that may be critical for flood-emergency planning and flood response activities such as evacuations and road closures, as well as for post-flood recovery efforts.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155099","collaboration":"Prepared in cooperation with the Indiana Office of Community and Rural Affairs","usgsCitation":"Strauch, K.R., 2015, Flood-inundation maps for the St. Marys River at Decatur, Indiana: U.S. Geological Survey Scientific Investigations Report 2015–5099, 8 p., https://dx.doi.org/10.3133/sir20155099.","productDescription":"Report: iv, 8 p.; Metadata; Raw Data","numberOfPages":"16","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-061185","costCenters":[{"id":346,"text":"Indiana Water Science Center","active":true,"usgs":true}],"links":[{"id":308417,"rank":3,"type":{"id":19,"text":"Raw Data"},"url":"https://pubs.usgs.gov/sir/2015/5099/downloads/sir2015-5099_grids.zip","text":"SIR 2015-5099 - All Grid Files","size":"38.4 MB","linkFileType":{"id":6,"text":"zip"},"description":"SIR 2015-5099"},{"id":308418,"rank":4,"type":{"id":19,"text":"Raw Data"},"url":"https://pubs.usgs.gov/sir/2015/5099/downloads/sir2015-5099_shapefiles.zip","text":"SIR 2015-5099 - All Shape Files","size":"1.43 MB","linkFileType":{"id":6,"text":"zip"},"description":"SIR 2015-5099"},{"id":307017,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5099/sir20155099.pdf","text":"Report","size":"1.53 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015-5099"},{"id":307016,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2015/5099/coverthb.jpg"}],"country":"United States","state":"Indiana","county":"Adams","city":"Decatur","otherGeospatial":"St. Mary's River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -84.98268127441406,\n 40.897684312779774\n ],\n [\n -85.01117706298828,\n 40.869131967913475\n ],\n [\n -84.94869232177734,\n 40.82316279497129\n ],\n [\n -84.9074935913086,\n 40.80133575979201\n ],\n [\n -84.89959716796875,\n 40.7958778790764\n ],\n [\n -84.87419128417969,\n 40.817446884558805\n ],\n [\n -84.98268127441406,\n 40.897684312779774\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Indiana Water Science Center
5957 Lakeside Blvd
Indianapolis, IN 46278
http://in.water.usgs.gov/
Daily records of streamflow are essential to understanding hydrologic systems and managing the interactions between human and natural systems. Many watersheds and locations lack streamgages to provide accurate and reliable records of daily streamflow. In such ungaged watersheds, statistical tools and rainfall-runoff models are used to estimate daily streamflow. Previous work compared 19 different techniques for predicting daily streamflow records in the southeastern United States. Here, five of the better-performing methods are compared in a different hydroclimatic region of the United States, in Iowa. The methods fall into three classes: (1) drainage-area ratio methods, (2) nonlinear spatial interpolations using flow duration curves, and (3) mechanistic rainfall-runoff models. The first two classes are each applied with nearest-neighbor and map-correlated index streamgages. Using a threefold validation and robust rank-based evaluation, the methods are assessed for overall goodness of fit of the hydrograph of daily streamflow, the ability to reproduce a daily, no-fail storage-yield curve, and the ability to reproduce key streamflow statistics. As in the Southeast study, a nonlinear spatial interpolation of daily streamflow using flow duration curves is found to be a method with the best predictive accuracy. Comparisons with previous work in Iowa show that the accuracy of mechanistic models with at-site calibration is substantially degraded in the ungaged framework.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155089","collaboration":"Prepared in cooperation with the Department of the Interior WaterSMART Program","usgsCitation":"Farmer, W.H., Knight, R.R., Eash, D.A., Hutchinson, K.J., Linhart, S.M., Christiansen, D.E., Archfield, S.A., Over, T.M., and Kiang, J.E., 2015, Evaluation of statistical and rainfall-runoff models for predicting historical daily streamflow time series in the Des Moines and Iowa River watersheds: U.S. Geological Survey Scientific Investigations Report 2015–5089, 34 p., https://dx.doi.org/10.3133/sir20155089.","productDescription":"vii, 34 p.","numberOfPages":"46","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-064014","costCenters":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"links":[{"id":307083,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5089/sir20155089.pdf","text":"Report","size":"3.29 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015-5089"},{"id":307082,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2015/5089/coverthb.jpg"}],"country":"United States","state":"Iowa, Minnesota","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -96.39404296875,\n 44.59046718130883\n ],\n [\n -96.492919921875,\n 43.74728909225906\n ],\n [\n -96.70166015624999,\n 43.5326204268101\n ],\n [\n -96.778564453125,\n 43.01268088642034\n ],\n [\n -96.416015625,\n 42.3016903282445\n ],\n [\n -96.1962890625,\n 41.80407814427237\n ],\n [\n -96.1083984375,\n 41.28606238749825\n ],\n [\n -95.91064453125,\n 40.65563874006118\n ],\n [\n -95.8447265625,\n 40.57224011776902\n ],\n [\n -95.394287109375,\n 40.56389453066509\n ],\n [\n -94.04296874999999,\n 40.58058466412764\n ],\n [\n -92.79052734375,\n 40.54720023441049\n ],\n [\n -91.483154296875,\n 40.56389453066509\n ],\n [\n -91.16455078125,\n 40.613952441166596\n ],\n [\n -90.911865234375,\n 40.82212357516945\n ],\n [\n -90.791015625,\n 41.1455697310095\n ],\n [\n -90.54931640625,\n 41.36031866306708\n ],\n [\n -90.19775390625,\n 41.599013054830216\n ],\n [\n -89.97802734375,\n 41.95949009892465\n ],\n [\n -90.186767578125,\n 42.25291778330197\n ],\n [\n -90.72509765625,\n 42.771211138625894\n ],\n [\n -90.977783203125,\n 43.068887774169625\n ],\n [\n -91.087646484375,\n 43.35713822211053\n ],\n [\n -91.12060546875,\n 43.61221676817573\n ],\n [\n -91.29638671875,\n 44.01652134387754\n ],\n [\n -91.73583984374999,\n 44.34742225636393\n ],\n [\n -91.97753906249999,\n 44.52001001133986\n ],\n [\n -92.142333984375,\n 44.55916341529184\n ],\n [\n -96.39404296875,\n 44.59046718130883\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Office of Surface Water
U.S. Geological Survey
12201 Sunrise Valley Drive
Reston, VA, 20192
http://water.usgs.gov/osw/
Global sea level is rising and may accelerate with continued fossil fuel consumption from industrial and population growth. In 2012, the U.S. Geological Survey conducted more than 30 training and feedback sessions with Federal, State, and nongovernmental organization (NGO) coastal managers and planners across the northern Gulf of Mexico coast to evaluate user needs, potential benefits, current scientific understanding, and utilization of resource aids and modeling tools focused on sea-level rise. In response to the findings from the sessions, this sea-level rise modeling handbook has been designed as a guide to the science and simulation models for understanding the dynamics and impacts of sea-level rise on coastal ecosystems. The review herein of decision-support tools and predictive models was compiled from the training sessions, from online research, and from publications. The purpose of this guide is to describe and categorize the suite of data, methods, and models and their design, structure, and application for hindcasting and forecasting the potential impacts of sea-level rise in coastal ecosystems. The data and models cover a broad spectrum of disciplines involving different designs and scales of spatial and temporal complexity for predicting environmental change and ecosystem response. These data and models have not heretofore been synthesized, nor have appraisals been made of their utility or limitations. Some models are demonstration tools for non-experts, whereas others require more expert capacity to apply for any given park, refuge, or regional application. A simplified tabular context has been developed to list and contrast a host of decision-support tools and models from the ecological, geological, and hydrological perspectives. Criteria were established to distinguish the source, scale, and quality of information input and geographic datasets; physical and biological constraints and relations; datum characteristics of water and land components; utility options for setting sea-level rise and climate change scenarios; and ease or difficulty of storing, displaying, or interpreting model output. Coastal land managers, engineers, and scientists can benefit from this synthesis of tools and models that have been developed for projecting causes and consequences of sea-level change on the landscape and seascape.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/pp1815","collaboration":"Prepared in cooperation with the Department of the Interior Southeast Climate Science Center","usgsCitation":"Doyle, T.W., Chivoiu, Bogdan, and Enwright, N.M., 2015, Sea-level rise modeling handbook—Resource guide for coastal land managers, engineers, and scientists: U.S. Geological Survey Professional Paper 1815, 76 p.,\nhttps://dx.doi.org/10.3133/pp1815.","productDescription":"ix, 76 p.","numberOfPages":"89","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-045332","costCenters":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"links":[{"id":307080,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/pp/1815/pp1815.pdf","text":"Report","size":"7.47","linkFileType":{"id":1,"text":"pdf"},"description":"PP 1815"},{"id":307079,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/pp/1815/coverthb.jpg"}],"contact":"Director, National Wetlands Research Center
U.S. Geological Survey
700 Cajundome Blvd.
Lafayette, LA 70506
http://www.nwrc.usgs.gov/
In Lake Michigan, diets of planktivorous and benthivorous fishes have varied over the past decades, in part owing to food web changes. To update diet information and compare them to a similar effort in 1994–1995, we analyzed the diets of seven benthivorous and planktivorous fish species collected along two northern Lake Michigan transects that spanned nearshore (18 m), intermediate (46 m), and offshore (91, 110, 128 m) bottom depths during spring, summer, and autumn of 2010. Calanoid copepods (e.g., Limnocalanus macrurus, Leptodiaptomus sicilis, and Senecella calanoides) comprised a majority of the diets in at least one season for all sizes of alewife (Alosa pseudoharengus), bloater (Coregonus hoyi), and rainbow smelt (Osmerus mordax). Similarly, Mysis diluviana was the highest proportion in at least one season for large sizes of alewife, bloater, and rainbow smelt, as well as slimy sculpin (Cottus cognatus) and deepwater sculpin (Myoxocephalus thompsonii). The diets of the remaining two species, ninespine stickleback (Pungitius pungitius) and round goby (Neogobius melanostomus), were dominated by herbivorous cladocerans or dreissenid mussels, respectively. Interspecific diet overlap was minimal at 18 and 46 m. In offshore waters, however, overlap was relatively high, driven by frequent consumption of Mysis. Relative to 1994–1995, 2010 diets revealed increased feeding on calanoid copepods and Mysis, with corresponding declining consumption of Diporeia spp. and herbivorous cladocerans. Relative diet weight was also higher in 1994–1995 than in 2010 for small and large bloater and both sculpin species. We hypothesize that the shifts in diets are reflective of community-level changes in invertebrate prey availability.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jglr.2015.07.011","usgsCitation":"Bunnell, D., Davis, B.M., Chriscinske, M.A., Keeler, K.M., and Mychek-Londer, J., 2015, Diet shifts by planktivorous and benthivorous fishes in northern Lake Michigan in response to ecosystem changes: Journal of Great Lakes Research, v. 41, no. Suppl. 3, p. 161-171, https://doi.org/10.1016/j.jglr.2015.07.011.","productDescription":"11 p.","startPage":"161","endPage":"171","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-058260","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":312207,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":312139,"type":{"id":15,"text":"Index Page"},"url":"https://www.sciencedirect.com/science/article/pii/S0380133015001495"}],"country":"United States","state":"Wisconsin and Michigan","otherGeospatial":"Sturgeon Bay and Frankfort","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -87.40859985351561,\n 44.90841397875737\n ],\n [\n -87.38800048828125,\n 44.89090425391711\n ],\n [\n -87.38456726074219,\n 44.8699828720045\n ],\n [\n -87.38388061523438,\n 44.839316876761046\n ],\n [\n -87.35916137695312,\n 44.825195295107505\n ],\n [\n -87.34268188476562,\n 44.820812031724444\n ],\n [\n -87.32139587402344,\n 44.79937794671695\n ],\n [\n -87.28843688964844,\n 44.80522439622254\n ],\n [\n -87.27470397949219,\n 44.815454257230414\n ],\n [\n -87.264404296875,\n 44.800839614637205\n ],\n [\n -87.26783752441405,\n 44.78134766441459\n ],\n [\n -87.28294372558594,\n 44.76818687659432\n ],\n [\n -87.30697631835936,\n 44.77062428581206\n ],\n [\n -87.31590270996094,\n 44.782809789027425\n ],\n [\n -87.31521606445311,\n 44.794992720781046\n ],\n [\n -87.34336853027344,\n 44.810583121135906\n ],\n [\n -87.35984802246094,\n 44.82032498188776\n ],\n [\n -87.39349365234375,\n 44.8310391278729\n ],\n [\n -87.41065979003906,\n 44.861709529639704\n ],\n [\n -87.43194580078124,\n 44.88068778527483\n ],\n [\n -87.4346923828125,\n 44.887498965976505\n ],\n [\n -87.42027282714844,\n 44.886525989535045\n ],\n [\n -87.42576599121094,\n 44.89041779655458\n ],\n [\n -87.43263244628906,\n 44.89771422497743\n ],\n [\n -87.43125915527344,\n 44.90695503868511\n ],\n [\n -87.41615295410155,\n 44.91181802825403\n ],\n [\n -87.40859985351561,\n 44.90841397875737\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -86.25778198242188,\n 44.66767620116954\n ],\n [\n -86.36489868164062,\n 44.66181582895674\n ],\n [\n -86.34567260742188,\n 44.595356872562256\n ],\n [\n -86.32781982421875,\n 44.569925985528336\n ],\n [\n -86.2481689453125,\n 44.57286088638149\n ],\n [\n -86.22207641601562,\n 44.577752058683366\n ],\n [\n -86.25778198242188,\n 44.66767620116954\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"41","issue":"Suppl. 3","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"566c01d4e4b09cfe53ca5ac4","contributors":{"authors":[{"text":"Bunnell, David B. dbunnell@usgs.gov","contributorId":141167,"corporation":false,"usgs":true,"family":"Bunnell","given":"David B.","email":"dbunnell@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":false,"id":581828,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Davis, Bruce M. bmdavis@usgs.gov","contributorId":4227,"corporation":false,"usgs":true,"family":"Davis","given":"Bruce","email":"bmdavis@usgs.gov","middleInitial":"M.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":581829,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Chriscinske, Margret Ann 0000-0002-9930-0630 mchriscinske@usgs.gov","orcid":"https://orcid.org/0000-0002-9930-0630","contributorId":4416,"corporation":false,"usgs":true,"family":"Chriscinske","given":"Margret","email":"mchriscinske@usgs.gov","middleInitial":"Ann","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":581830,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Keeler, Kevin M.","contributorId":139751,"corporation":false,"usgs":false,"family":"Keeler","given":"Kevin","email":"","middleInitial":"M.","affiliations":[{"id":12902,"text":"MI State UNiversity","active":true,"usgs":false}],"preferred":false,"id":581831,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mychek-Londer, Justin G.","contributorId":64138,"corporation":false,"usgs":true,"family":"Mychek-Londer","given":"Justin G.","affiliations":[],"preferred":false,"id":581832,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70155895,"text":"ds949 - 2015 - Ground-survey and water-quality data for selected wetlands on or near the Lower Brule Indian Reservation in South Dakota, 2012-13","interactions":[],"lastModifiedDate":"2017-10-12T20:02:38","indexId":"ds949","displayToPublicDate":"2015-08-20T10:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"949","title":"Ground-survey and water-quality data for selected wetlands on or near the Lower Brule Indian Reservation in South Dakota, 2012-13","docAbstract":"Numerous lakes, ponds, and wetlands are located within the Lower Brule Indian Reservation. Wetlands are an important resource providing aquatic habitat for plants and animals, and acting as a natural water filtration system. Several of the wetlands on or near the reservation are of particular interest, but information on the physical and biological integrity of these wetlands was needed to provide a base-line reference when planning for future water management needs. A reconnaissance-level study of selected wetlands on and near the Lower Brule Indian Reservation was completed in 2012–13 by the U.S. Geological Survey in cooperation with the Lower Brule Sioux Tribe using ground surveys and water-quality analyses. Ground surveys of six wetland areas (Dorman Slough, Little Bend Wetlands, Miller Pond, Potter Slough, an unnamed slough, and West Brule Community wetlands) were completed to map land, water, vegetation, and man-made features of the selected wetland areas using real-time kinematic global navigation satellite systems equipment. Water samples were collected from four of the selected wetlands. Two separate waterbodies were sampled at one of the wetlands for a total of five sampling locations. Water samples were analyzed for physical properties, selected inorganics, metals, nutrients, and suspended sediment. Concentrations of calcium, sodium, and sulfate were greater at the two wetland sites fed by ground water, compared to the wetland sites fed by surface runoff.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds949","collaboration":"Prepared in cooperation with the Lower Brule Sioux Tribe","usgsCitation":"Neitzert, K.M., and Thompson, R.F., 2015, Ground-survey and water-quality data for selected wetlands on or near the Lower Brule Indian Reservation in South Dakota, 2012–13: U.S. Geological Survey Data Series Report 949, 21 p., https://dx.doi.org/10.3133/ds949.","productDescription":"v, 21 p.; Database","numberOfPages":"32","onlineOnly":"Y","additionalOnlineFiles":"Y","temporalStart":"2012-01-01","temporalEnd":"2013-12-31","ipdsId":"IP-062797","costCenters":[{"id":562,"text":"South Dakota Water Science Center","active":true,"usgs":true},{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"links":[{"id":306899,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/0949/coverthb.jpg"},{"id":306900,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/0949/ds949.pdf","text":"Report","size":"8.26 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DS 949"},{"id":306978,"rank":3,"type":{"id":9,"text":"Database"},"url":"https://water.usgs.gov/GIS/dsdl/ds949_LBWetlands_gdb.zip","text":"Geodatabase","description":"Geodatabase"}],"country":"United States","state":"South Dakota","otherGeospatial":"Lower Brule Indian Reservation","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -100.12252807617188,\n 43.875128129336716\n ],\n [\n -100.12252807617188,\n 44.33956524809713\n ],\n [\n -99.24362182617186,\n 44.33956524809713\n ],\n [\n -99.24362182617186,\n 43.875128129336716\n ],\n [\n -100.12252807617188,\n 43.875128129336716\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, South Dakota Water Science Center
U.S. Geological Survey
1608 Mountain View Road
Rapid City, South Dakota 57702
http://sd.water.usgs.gov/
Digital flood-inundation maps for a 7.7-mile reach of the White River at Petersburg, Indiana, were created by the U.S. Geological Survey (USGS), in cooperation with the Indiana Office of Community and Rural Affairs. The inundation maps, which can be accessed through the USGS Flood Inundation Mapping Science Web site at http://water.usgs.gov/osw/flood_inundation/, depict estimates of the areal extent and depth of flooding corresponding to selected water levels (stages) at the USGS streamgage at White River at Petersburg, Ind. (03374000). Near-real-time stages at this streamgage may be obtained from the USGS National Water Information System at http://waterdata.usgs.gov/ or the National Weather Service (NWS) Advanced Hydrologic Prediction Service at http:/water.weather.gov/ahps/, which also forecasts flood hydrographs at this site (PTRI3).
\nFlood profiles were computed for the White River at Petersburg reach by means of a one-dimensional step-backwater model developed by the U.S. Army Corps of Engineers. The hydraulic model was calibrated by using the most current stage-discharge relations at the White River at Petersburg, Ind., and the White River above Petersburg, Ind. (03373890), gages. The calibrated hydraulic model was then used to compute 18 water-surface profiles for flood stages at approximately 1-foot intervals referenced to the streamgage datum and ranging from bankfull to the highest stage of the current stage-discharge rating curve. The simulated water-surface profiles were then combined with a geographic information system digital elevation model to delineate the area flooded at each water level.
\nThe availability of these maps along with Internet information regarding current stage from the USGS streamgage at White River at Petersburg, Ind., and forecasted stream stages from the NWS provide emergency management personnel and residents with information that is critical for flood response activities such as evacuations and road closures as well as for post-flood recovery efforts.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155107","collaboration":"Prepared in cooperation with the Indiana Office of Community and Rural Affairs","usgsCitation":"Fowler, K.K., 2015, Flood-inundation maps for the White River at Petersburg, Indiana: U.S. Geological Survey Scientific Investigations Report 2015–5107, 11 p., https://dx.doi.org/10.3133/sir20155107.","productDescription":"Report: iv, 11 p.: Metadata: Readme: Spatial Data","numberOfPages":"19","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-063334","costCenters":[{"id":346,"text":"Indiana Water Science Center","active":true,"usgs":true}],"links":[{"id":306743,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2015/5107/coverthb.jpg"},{"id":306746,"rank":4,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/sir/2015/5107/downloads/shapefile/shapefile.zip","text":"Shapefiles","size":"4.51 MB","linkFileType":{"id":6,"text":"zip"},"description":"SIR 2015-5107"},{"id":306744,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5107/sir20155107.pdf","text":"Report","size":"6.82 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015-5107"},{"id":306747,"rank":5,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/sir/2015/5107/downloads/metadata_depth-grids.txt","text":"Metadata Depth Grids","size":"15.4 KB","linkFileType":{"id":2,"text":"txt"},"description":"SIR 2015-5107"},{"id":306745,"rank":3,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/sir/2015/5107/downloads/depth_grids/depth_grids.zip","text":"Depth Grids","size":"88.8 MB","linkFileType":{"id":6,"text":"zip"},"description":"SIR 2015-5107"},{"id":306748,"rank":6,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/sir/2015/5107/downloads/metadata_shapefiles.txt","text":"Metadata Shapefiles","size":"15.9 KB","linkFileType":{"id":2,"text":"txt"},"description":"SIR 2015-5107"},{"id":306809,"rank":7,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/sir/2015/5107/downloads/readme.pdf","text":"Information about the report - readme file","size":"26.3 KB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015-5107"}],"country":"United States","state":"Indiana","city":"Petersburg","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -87.34010696411133,\n 38.50666906026307\n ],\n [\n -87.34010696411133,\n 38.54198948702892\n ],\n [\n -87.22217559814453,\n 38.54198948702892\n ],\n [\n -87.22217559814453,\n 38.50666906026307\n ],\n [\n -87.34010696411133,\n 38.50666906026307\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Indiana Water Science Center
5957 Lakeside Blvd
Indianapolis, IN 46278
http://in.water.usgs.gov/