In 1972, the USA and Canada agreed to restore the chemical, physical, and biological integrity of the Great Lakes ecosystem under the first Great Lakes Water Quality Agreement. In subsequent amendments, part of the St. Lawrence River at Massena, New York and segments of three tributaries, were designated as an Area of Concern (AOC) due to the effects of polychlorinated biphenyls (PCBs), lead and copper contamination, and habitat degradation and resulting impairment to several beneficial uses. Because sediments have been largely remediated, the present study was initiated to evaluate the current status of the benthic macroinvertebrate (benthos) beneficial use impairment (BUI). Benthic macroinvertebrate communities and sediment toxicity tests using Chironomus dilutus were used to test the hypotheses that community condition and sediment toxicity at AOC sites were not significantly different from those of adjacent reference sites. Grain size was found to be the main driver of community composition and macroinvertebrate assemblages, and bioassessment metrics did not differ significantly between AOC and reference sites of the same sediment class. Median growth of C. dilutus and its survival in three of the four river systems did not differ significantly in sediments from AOC and reference sites. Comparable macroinvertebrate assemblages and general lack of toxicity across most AOC and reference sites suggest that the quality of sediments should not significantly impair benthic macroinvertebrate communities in most sites in the St. Lawrence River AOC.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jglr.2016.05.001","usgsCitation":"Duffy, B.T., Baldigo, B.P., Smith, A., George, S.D., and David, A.M., 2016, Assessing condition of macroinvertebrate communities and sediment toxicity in the St. Lawrence River at Massena Area-of-Concern: Journal of Great Lakes Research, v. 42, no. 4, p. 910-919, https://doi.org/10.1016/j.jglr.2016.05.001.","productDescription":"10 p.","startPage":"910","endPage":"919","ipdsId":"IP-052396","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":470562,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jglr.2016.05.001","text":"Publisher Index Page"},{"id":328753,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New York","city":"Messena","otherGeospatial":"St. Lawrence River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -75.05859375,\n 44.8996597828752\n ],\n [\n -75.05859375,\n 45.06770141120143\n ],\n [\n -74.55047607421875,\n 45.06770141120143\n ],\n [\n -74.55047607421875,\n 44.8996597828752\n ],\n [\n -75.05859375,\n 44.8996597828752\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"42","issue":"4","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57f7c63de4b0bc0bec09c882","chorus":{"doi":"10.1016/j.jglr.2016.05.001","url":"http://dx.doi.org/10.1016/j.jglr.2016.05.001","publisher":"Elsevier BV","authors":"Duffy Brian T., Baldigo Barry P., Smith Alexander J., George Scott D., David Anthony M.","journalName":"Journal of Great Lakes Research","publicationDate":"8/2016"},"contributors":{"authors":[{"text":"Duffy, Brian T.","contributorId":6352,"corporation":false,"usgs":true,"family":"Duffy","given":"Brian","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":649064,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Baldigo, Barry P. 0000-0002-9862-9119 bbaldigo@usgs.gov","orcid":"https://orcid.org/0000-0002-9862-9119","contributorId":1234,"corporation":false,"usgs":true,"family":"Baldigo","given":"Barry","email":"bbaldigo@usgs.gov","middleInitial":"P.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":649065,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Smith, Alexander J.","contributorId":140345,"corporation":false,"usgs":false,"family":"Smith","given":"Alexander J.","affiliations":[{"id":13464,"text":"Environmental Analyst, NY State Dept of Environmental Conservation","active":true,"usgs":false}],"preferred":false,"id":649066,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"George, Scott D. 0000-0002-8197-1866 sgeorge@usgs.gov","orcid":"https://orcid.org/0000-0002-8197-1866","contributorId":3014,"corporation":false,"usgs":true,"family":"George","given":"Scott","email":"sgeorge@usgs.gov","middleInitial":"D.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":649067,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"David, Anthony M.","contributorId":36032,"corporation":false,"usgs":true,"family":"David","given":"Anthony","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":649068,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70175981,"text":"ds1016 - 2016 - Toxicity of bed sediments from the Niagara River Area of Concern and tributaries, New York, to Chironomus dilutus and Hyalella azteca, 2014-15","interactions":[],"lastModifiedDate":"2016-09-20T09:44:30","indexId":"ds1016","displayToPublicDate":"2016-09-20T10:00:00","publicationYear":"2016","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":"1016","title":"Toxicity of bed sediments from the Niagara River Area of Concern and tributaries, New York, to Chironomus dilutus and Hyalella azteca, 2014-15","docAbstract":"The Niagara River was designated as an Area of Concern in 1987 on both the United States and Canadian sides of the international boundary line because past industrial discharges and hazardous waste sites had caused extensive degradation of aquatic habitats. The degradation of the “benthos”, or the benthic macroinvertebrate community, was identified as one of seven beneficial use impairments caused by contaminated bed sediments. The U.S. Geological Survey and the New York State Department of Environmental Conservation, in cooperation with the U.S. Environmental Protection Agency, conducted a study in 2014 and 2015 to gather more extensive data on (a) the toxicity of bed sediments and (b) the status of macroinvertebrate communities on the main stem and tributaries of the Niagara River. This report addresses the first component of that study (toxicity of bed sediments), and summarizes results from laboratory toxicity tests that compare the survival and growth of two macroinvertebrate species between bed sediments from study sites and laboratory controls. Sediment toxicity was negligible at most sites, however poor performance of one or both test species in bed sediments from several tributary sites suggests that the quality of sediments may be adversely affecting benthic macroinvertebrate communities in some tributaries to the Niagara River.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds1016","collaboration":"Prepared in cooperation with the U.S. Environmental Protection Agency and the New York State Department of Environmental Conservation","usgsCitation":"George, S.D., Baldigo, B.P., and Duffy, B.T., 2016, Toxicity of bed sediments from the Niagara River Area of Concern and tributaries, New York, to Chironomus dilutus and Hyalella azteca, 2014–15: U.S. Geological Survey Data Series 1016, 8 p., https://dx.doi.org/10.3133/ds1016.","productDescription":"Report: iv, 8 p.; Data Release","numberOfPages":"16","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-074812","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":438546,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7FB5129","text":"USGS data release","linkHelpText":"Data from 10-day sediment toxicity tests of bed sediments from the Niagara River Area of Concern and tributaries, New York, with Chironomus dilutus and Hyalella azteca, 201415"},{"id":328719,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://dx.doi.org/10.5066/F7FB5129","text":"USGS data release ","description":"USGS data release ","linkHelpText":"Data from 10-day sediment toxicity tests of bed sediments from the Niagara River Area of Concern and tributaries, New York, with Chironomus dilutus and Hyalella azteca, 2014-15 "},{"id":328717,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/1016/coverthb.jpg"},{"id":328718,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/1016/ds1016.pdf","text":"Report","size":"1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DS 1016"}],"country":"United States","state":"New York","otherGeospatial":"Niagara River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -79.22927856445312,\n 42.8054768278603\n ],\n [\n -79.22927856445312,\n 43.29320031385282\n ],\n [\n -78.72665405273438,\n 43.29320031385282\n ],\n [\n -78.72665405273438,\n 42.8054768278603\n ],\n [\n -79.22927856445312,\n 42.8054768278603\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New York Water Science Center
U.S. Geological Survey
425 Jordan Road
Troy, NY 12180-8349
(518) 285-5602
Or visit our Website at:
http://ny.water.usgs.gov
An investigation into the magnitude and frequency of floods in Washington State computed the annual exceedance probability (AEP) statistics for 648 U.S. Geological Survey unregulated streamgages in and near the borders of Washington using the recorded annual peak flows through water year 2014. This is an updated report from a previous report published in 1998 that used annual peak flows through the water year 1996. New in this report, a regional skew coefficient was developed for the Pacific Northwest region that includes areas in Oregon, Washington, Idaho and western Montana within the Columbia River drainage basin south of the United States-Canada border, the coastal areas of Oregon and western Washington, and watersheds draining into Puget Sound, Washington. The skew coefficient is an important term in the Log Pearson Type III equation used to define the distribution of the log-transformed annual peaks. The Expected Moments Algorithm was used to fit historical and censored peak-flow data to the log Pearson Type III distribution. A Multiple Grubb-Beck test was employed to censor low outliers of annual peak flows to improve on the frequency distribution. This investigation also includes a section on observed trends in annual peak flows that showed significant trends (p-value < 0.05) in 21 of 83 long-term sites, but with small magnitude Kendall tau values suggesting a limited monotonic trend in the time series of annual peaks. Most of the sites with a significant trend in western Washington were positive and all the sites with significant trends (three sites) in eastern Washington were negative.
Multivariate regression analysis with measured basin characteristics and the AEP statistics at long-term, unregulated, and un-urbanized (defined as drainage basins with less than 5 percent impervious land cover for this investigation) streamgages within Washington and some in Idaho and Oregon that are near the Washington border was used to develop equations to estimate AEP statistics at ungaged basins. Washington was divided into four regions to improve the accuracy of the regression equations; a set of equations for eight selected AEPs and for each region were constructed. Selected AEP statistics included the annual peak flows that equaled or exceeded 50, 20, 10, 4, 2, 1, 0.5 and 0.2 percent of the time equivalent to peak flows for peaks with a 2-, 5-, 10-, 25-, 50-, 100-, 200-, and 500-year recurrence intervals, respectively. Annual precipitation and drainage area were the significant basin characteristics in the regression equations for all four regression regions in Washington and forest cover was significant for the two regression regions in eastern Washington. Average standard error of prediction for the regional regression equations ranged from 70.19 to 125.72 percent for Regression Regions 1 and 2 on the eastern side of the Cascade Mountains and from 43.22 to 58.04 percent for Regression Regions 3 and 4 on the western side of the Cascade Mountains. The pseudo coefficient of determination (where a value of 100 signifies a perfect regression model) ranged from 68.39 to 90.68 for Regression Regions 1 and 2, and 92.35 to 95.44 for Regions 3 and 4.
The calculated AEP statistics for the streamgages and the regional regression equations are expected to be incorporated into StreamStats after the publication of this report. StreamStats is the interactive Web-based map tool created by the U.S. Geological Survey to allow the user to choose a streamgage and obtain published statistics or choose ungaged locations where the program automatically applies the regional regression equations and computes the estimates of the AEP statistics.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165118","collaboration":"Prepared in cooperation with the Washington State Department of Transportation and the Washington State Department of Ecology","usgsCitation":"Mastin, M.C., Konrad, C.P., Veilleux, A.G., and Tecca, A.E., 2016, Magnitude, frequency, and trends of floods at gaged and ungaged sites in Washington, based on data through water year 2014 (ver 1.2, November 2017): U.S. Geological Survey Scientific Investigations Report 2016–5118, 70 p., https://dx.doi.org/10.3133/sir20165118.","productDescription":"Report: vi, 69 p.; 3 Tables","numberOfPages":"80","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-075256","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":329272,"rank":7,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sir/2016/5118/versionHist.txt","size":"3 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\"}}]}","edition":"Version 1.0: Originally post September 20, 2016; Version 1.1: October 4, 2016; Version 1.2: November 2017","contact":"Director, Washington Water Science Center
U.S. Geological Survey
934 Broadway, Suite 300
Tacoma, Washington 98402
Wetlands in central North Dakota were revisited after 50 years to assess changes following extreme drought and a prolonged wet period. We compared data collected during 1961–1966 to current (2013–2014) wetland conditions. We revisited 80 wetlands in 2013 and 2014 across three study areas and measured wetland area, ponded-water depth, and specific conductance. Wetlands at the three study areas responded to prolonged wet conditions in one of three ways. Wetlands at Crystal Springs became larger, and had deeper ponds of lower specific conductance in 2013–14 compared to the 1960s. Wetlands at Cottonwood were larger with deeper ponds of slightly higher specific conductance in 2013–2014. Wetlands at Mt. Moriah had only subtle changes in size, pond depth, and specific conductance between periods. Prolonged wet conditions led to merging of most wetlands (defined as the outer edge of wet-meadow vegetation) at Crystal Springs and a few wetlands at Cottonwood. Low topographic relief at Crystal Springs and Cottonwood contributed to storage of excess water in wetlands with associated responses to prolonged wet conditions. In contrast, higher topographic relief and natural outlets into two intermittent streams at Mt. Moriah resulted in wetlands being less impacted by prolonged wet conditions.
","language":"English","publisher":"Springer","doi":"10.1007/s13157-016-0818-8","usgsCitation":"Cressey, R.L., Austin, J.E., and Stafford, J.D., 2016, Three responses of wetland conditions to climatic extremes in the Prairie Pothole Region: Wetlands, v. 36, no. s2, p. 357-370, https://doi.org/10.1007/s13157-016-0818-8.","productDescription":"14 p.","startPage":"357","endPage":"370","ipdsId":"IP-076277","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":328731,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Dakota","county":"Stutsman County","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-99.2669,47.3268],[-98.8466,47.327],[-98.8392,47.327],[-98.8232,47.3272],[-98.8152,47.3271],[-98.4991,47.327],[-98.467,47.3266],[-98.4677,47.2402],[-98.4685,46.9788],[-98.4412,46.9789],[-98.4396,46.6296],[-98.7894,46.6294],[-99.0379,46.6309],[-99.1616,46.6317],[-99.4122,46.6316],[-99.4498,46.6319],[-99.4477,46.8044],[-99.4476,46.9788],[-99.4821,46.9795],[-99.4824,47.0089],[-99.4822,47.0162],[-99.4821,47.0249],[-99.4826,47.0396],[-99.4827,47.1558],[-99.4801,47.3267],[-99.2669,47.3268]]]},\"properties\":{\"name\":\"Stutsman\",\"state\":\"ND\"}}]}","volume":"36","issue":"s2","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2016-09-10","publicationStatus":"PW","scienceBaseUri":"57f7c63de4b0bc0bec09c890","contributors":{"authors":[{"text":"Cressey, Ryann L.","contributorId":174689,"corporation":false,"usgs":false,"family":"Cressey","given":"Ryann","email":"","middleInitial":"L.","affiliations":[{"id":27498,"text":"SDCFWRU, USGS, Ducks Unlimited, Bismark","active":true,"usgs":false}],"preferred":false,"id":648986,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Austin, Jane E. 0000-0001-8775-2210 jaustin@usgs.gov","orcid":"https://orcid.org/0000-0001-8775-2210","contributorId":146411,"corporation":false,"usgs":true,"family":"Austin","given":"Jane","email":"jaustin@usgs.gov","middleInitial":"E.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":648985,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stafford, Joshua D. jstafford@usgs.gov","contributorId":4267,"corporation":false,"usgs":true,"family":"Stafford","given":"Joshua","email":"jstafford@usgs.gov","middleInitial":"D.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":648987,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70174983,"text":"sir20165108 - 2016 - Flood-inundation map library for the Licking River and South Fork Licking River near Falmouth, Kentucky","interactions":[],"lastModifiedDate":"2016-09-19T13:57:31","indexId":"sir20165108","displayToPublicDate":"2016-09-19T10:45:00","publicationYear":"2016","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":"2016-5108","title":"Flood-inundation map library for the Licking River and South Fork Licking River near Falmouth, Kentucky","docAbstract":"Digital flood inundation maps for a 17-mile reach of Licking River and 4-mile reach of South Fork Licking River near Falmouth, Kentucky, were created by the U.S. Geological Survey (USGS) in cooperation with Pendleton County and the U.S. Army Corps of Engineers–Louisville District. The inundation maps, which can be accessed through the USGS Flood Inundation Mapping Science Web site at http://wim.usgs.gov/FIMI/FloodInundationMapper.html, depict estimates of the areal extent and depth of flooding corresponding to selected water levels (stages) at the USGS streamgage on the Licking River at Catawba, Ky., (station 03253500) and the USGS streamgage on the South Fork Licking River at Hayes, Ky., (station 03253000). Current conditions (2015) for the USGS streamgages may be obtained online at the USGS National Water Information System site (http://waterdata.usgs.gov/nwis). In addition, the streamgage information has been provided to the National Weather Service (NWS) for incorporation into their Advanced Hydrologic Prediction Service (AHPS) flood warning system (http:/water.weather.gov/ahps/). The flood hydrograph forecasts provided by the NWS are usually collocated with USGS streamgages. The forecasted peak-stage information, also available on the NWS Web site, may be used in conjunction with the maps developed in this study to show predicted areas of flood inundation.
In this study, flood profiles were computed for the Licking River reach and South Fork Licking River reach by using a one-dimensional step-backwater model. The hydraulic model was calibrated by using the most current (2015) stage-discharge relations for the Licking River at Catawba, Ky., and the South Fork Licking River at Hayes, Ky., USGS streamgages. The calibrated model was then used to calculate 60 water-surface profiles for a sequence of flood stages, at 2-foot intervals, referenced to the streamgage datum and ranging from an elevation near bankfull to the elevation associated with a major flood that occurred in the region in 1997. To delineate the flooded area at each interval flood stage, the simulated water-surface profiles were combined with a digital elevation model of the study area by using geographic information system software.
The availability of these flood inundation maps for Falmouth, Ky., along with online information regarding current stages from the USGS streamgages and forecasted stages from the NWS, provides emergency management personnel and local residents with information that is critical for flood response activities such as evacuations, road closures, and post-flood recovery efforts.
Director, USGS Indiana-Kentucky Water Science Center
9818 Bluegrass Parkway
Louisville, KY 40299
A statewide study was led to develop regression equations for estimating three selected spring and three selected fall low-flow frequency statistics for ungaged stream sites in Iowa. The estimation equations developed for the six low-flow frequency statistics include spring (April through June) 1-, 7-, and 30-day mean low flows for a recurrence interval of 10 years and fall (October through December) 1-, 7-, and 30-day mean low flows for a recurrence interval of 10 years. Estimates of the three selected spring statistics are provided for 241 U.S. Geological Survey continuous-record streamgages, and estimates of the three selected fall statistics are provided for 238 of these streamgages, using data through June 2014. Because only 9 years of fall streamflow record were available, three streamgages included in the development of the spring regression equations were not included in the development of the fall regression equations. Because of regulation, diversion, or urbanization, 30 of the 241 streamgages were not included in the development of the regression equations. The study area includes Iowa and adjacent areas within 50 miles of the Iowa border. Because trend analyses indicated statistically significant positive trends when considering the period of record for most of the streamgages, the longest, most recent period of record without a significant trend was determined for each streamgage for use in the study. Geographic information system software was used to measure 63 selected basin characteristics for each of the 211streamgages used to develop the regional regression equations. The study area was divided into three low-flow regions that were defined in a previous study for the development of regional regression equations.
Because several streamgages included in the development of regional regression equations have estimates of zero flow calculated from observed streamflow for selected spring and fall low-flow frequency statistics, the final equations for the three low-flow regions were developed using two types of regression analyses—left-censored and generalized-least-squares regression analyses. A total of 211 streamgages were included in the development of nine spring regression equations—three equations for each of the three low-flow regions. A total of 208 streamgages were included in the development of nine fall regression equations—three equations for each of the three low-flow regions. A censoring threshold was used to develop 15 left-censored regression equations to estimate the three fall low-flow frequency statistics for each of the three low-flow regions and to estimate the three spring low-flow frequency statistics for the southern and northwest regions. For the northeast region, generalized-least-squares regression was used to develop three equations to estimate the three spring low-flow frequency statistics. For the northeast region, average standard errors of prediction range from 32.4 to 48.4 percent for the spring equations and average standard errors of estimate range from 56.4 to 73.8 percent for the fall equations. For the northwest region, average standard errors of estimate range from 58.9 to 62.1 percent for the spring equations and from 83.2 to 109.4 percent for the fall equations. For the southern region, average standard errors of estimate range from 43.2 to 64.0 percent for the spring equations and from 78.1 to 78.7 percent for the fall equations.
The regression equations are applicable only to stream sites in Iowa with low flows not substantially affected by regulation, diversion, or urbanization and with basin characteristics within the range of those used to develop the equations. The regression equations will be implemented within the U.S. Geological Survey StreamStats Web-based geographic information system application. StreamStats allows users to click on any ungaged stream site and compute estimates of the six selected spring and fall low-flow statistics; in addition, 90-percent prediction intervals and the measured basin characteristics for the ungaged site are provided. StreamStats also allows users to click on any Iowa streamgage to obtain computed estimates for the six selected spring and fall low-flow statistics.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165111","collaboration":"Prepared in cooperation with the Iowa Department of Natural Resources","usgsCitation":"Eash, D.A., Barnes, K.K., and O’Shea, P.S., 2016, Methods for estimating selected spring and fall low-flow frequency statistics for ungaged stream sites in Iowa, based on data through June 2014 (ver. 1.1, October 2016): U.S. Geological Survey Scientific Investigations Report 2016–5111, 32 p., https://dx.doi.org/10.3133/sir20165111.","productDescription":"Report: vi, 32 p.; Appendix Table 1–1","numberOfPages":"42","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-070749","costCenters":[{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true}],"links":[{"id":328721,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5111/sir20165111.pdf","text":"Report","size":"2.56 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016–5111"},{"id":328722,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2016/5111/sir20165111_appendix_table1-1.xlsx","text":"Appendix Table 1–1","size":"91.9 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2016–5111 Appendix Table 1–1"},{"id":329298,"rank":4,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sir/2016/5111/versionHist.txt","text":"Version History","size":"1 kB","linkFileType":{"id":2,"text":"txt"},"description":"SIR 2016–5111 Version History"},{"id":328720,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5111/coverthb.jpg"}],"country":"United States","state":"Iowa","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -97.218017578125,\n 39.86758762451019\n ],\n [\n -97.218017578125,\n 44.06390660801779\n ],\n [\n -89.461669921875,\n 44.06390660801779\n ],\n [\n -89.461669921875,\n 39.86758762451019\n ],\n [\n -97.218017578125,\n 39.86758762451019\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Version 1.0: Originally posted September 19, 2016; Version 1.1: October 5, 2016","contact":"Director, Iowa Water Science Center
U.S. Geological Survey
P.O. Box 1230
Iowa City, IA 52244
A growing number of ungulate populations are living within or near the wildland–urban interface. When resources at the interface are of greater quality than that of adjacent natural habitat, wildlife can be attracted to these developed areas. Little is known about how use of the wildland–urban interface by wildlife may affect vital rates. Under natural conditions, recruitment by desert bighorn sheep (Ovis canadensis nelsoni) correlates with variation in the timing and amount of rainfall that initiates and enhances growth of annual plant species. However, for populations that forage in developed areas, this relationship may become decoupled. In the River Mountains of Nevada, USA, desert bighorn sheep have been feeding in a municipal park at the wildland–urban interface since its establishment in 1985. Approximately one-third of the population now uses the park during summer months when nutritional content of natural forage is low. We hypothesized that use of this municipal area, with its abundant vegetation and water resources, may have decoupled the previous relationship between precipitation and lamb recruitment. We assessed variables known to affect lamb recruitment before (1971–1986) and after (1987–2006) establishment of the park using linear regression models. Our top candidate model for the pre-park period indicated that total November precipitation was the greatest driver of lamb recruitment in this population. After park establishment, this relationship became decoupled because lamb recruitment was no longer driven by weather variables. These results raise questions about the effects of decoupling drivers of population growth and maintaining natural populations near urban areas.
","language":"English","publisher":"Wildlife Society","publisherLocation":"Washington, D.C.","doi":"10.1002/wsb.679","usgsCitation":"Longshore, K.M., Lowrey, C.E., and Cummings, P., 2016, Foraging at the wildland–urban interface decouples weather as a driver of recruitment for desert bighorn sheep: Wildlife Society Bulletin, v. 40, no. 3, p. 494-499, https://doi.org/10.1002/wsb.679.","productDescription":"6 p.","startPage":"494","endPage":"499","ipdsId":"IP-072045","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":500052,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doaj.org/article/4ab750e0d2274a96a5325257b601991a","text":"External Repository"},{"id":328690,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nevada","otherGeospatial":"Lake Mead National Recreation Area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -114.97707366943358,\n 35.97272720799364\n ],\n [\n -114.97707366943358,\n 36.0410487010891\n ],\n [\n -114.8339080810547,\n 36.0410487010891\n ],\n [\n -114.8339080810547,\n 35.97272720799364\n ],\n [\n -114.97707366943358,\n 35.97272720799364\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"40","issue":"3","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2016-08-12","publicationStatus":"PW","scienceBaseUri":"57ed48b1e4b090825011d4d5","contributors":{"authors":[{"text":"Longshore, Kathleen M. 0000-0001-6621-1271 longshore@usgs.gov","orcid":"https://orcid.org/0000-0001-6621-1271","contributorId":2677,"corporation":false,"usgs":true,"family":"Longshore","given":"Kathleen","email":"longshore@usgs.gov","middleInitial":"M.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":648874,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lowrey, Chris E. 0000-0001-5084-7275 clowrey@usgs.gov","orcid":"https://orcid.org/0000-0001-5084-7275","contributorId":3225,"corporation":false,"usgs":true,"family":"Lowrey","given":"Chris","email":"clowrey@usgs.gov","middleInitial":"E.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":648875,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cummings, Patrick","contributorId":174650,"corporation":false,"usgs":false,"family":"Cummings","given":"Patrick","email":"","affiliations":[{"id":27489,"text":"Nevada Department of Wildlife","active":true,"usgs":false}],"preferred":false,"id":648876,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70176471,"text":"70176471 - 2016 - Pockmark asymmetry and seafloor currents in the Santos Basin offshore Brazil","interactions":[],"lastModifiedDate":"2017-11-18T09:58:42","indexId":"70176471","displayToPublicDate":"2016-09-16T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1742,"text":"Geo-Marine Letters","active":true,"publicationSubtype":{"id":10}},"title":"Pockmark asymmetry and seafloor currents in the Santos Basin offshore Brazil","docAbstract":"Pockmarks form by gas/fluid expulsion into the ocean and are preserved under conditions of negligible sedimentation. Ideally, they are circular at the seafloor and symmetrical in profile. Elliptical pockmarks are more enigmatic. They are associated with seafloor currents while asymmetry is connected to sedimentation patterns. This study examines these associations through morphological analysis of new multibeam data collected across the Santos continental slope offshore Brazil in 2011 (353–865 mbsl). Of 984 pockmarks, 78% are both elliptical and asymmetric. Geometric criteria divide the pockmarks into three depth ranges that correlate with a transition between two currents: the Brazil Current transfers Tropical Water and South Atlantic Central Water southwestwards while the Intermediate Western Boundary Current transfers Antarctic Intermediate Water northeastwards. It is suggested that the velocity of seafloor currents and their persistence dictate pockmark ellipticity, orientation and profile asymmetry. Fast currents (>20 cm/s) are capable of maintaining pockmark flank steepness close to the angle of repose. These morphological expressions present direct evidence for an edge effect of the South Atlantic Subtropical Gyre and, in general, provide a correlation between pockmark geometry and seafloor currents that can be applied at other locations worldwide.
","language":"English","publisher":"Springer-Verlag","doi":"10.1007/s00367-016-0468-0","usgsCitation":"Schattner, U., Lazar, M., Souza, L.A., ten Brink, U., and Mahiques, M.M., 2016, Pockmark asymmetry and seafloor currents in the Santos Basin offshore Brazil: Geo-Marine Letters, v. 36, no. 6, p. 457-464, https://doi.org/10.1007/s00367-016-0468-0.","productDescription":"8 p.","startPage":"457","endPage":"464","ipdsId":"IP-079073","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":489106,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://dx.doi.org/10.1007/s00367-016-0468-0","text":"External Repository"},{"id":328692,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Brazil","otherGeospatial":"Santos Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -49.3,\n -22.5\n ],\n [\n -49.3,\n -30\n ],\n [\n -41.6,\n -30\n ],\n [\n -41.6,\n -22.5\n ],\n [\n -49.3,\n -22.5\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"36","issue":"6","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationDate":"2016-09-14","publicationStatus":"PW","scienceBaseUri":"57f7c63fe4b0bc0bec09c8a9","contributors":{"authors":[{"text":"Schattner, U. 0000-0002-4453-4552","orcid":"https://orcid.org/0000-0002-4453-4552","contributorId":174637,"corporation":false,"usgs":false,"family":"Schattner","given":"U.","affiliations":[{"id":27488,"text":"Dr. Mosses Straus Dept of Marine Geosciences, Leon H. Charney School of Marine Sciences, University of Haifa","active":true,"usgs":false}],"preferred":false,"id":648891,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lazar, M.","contributorId":174652,"corporation":false,"usgs":false,"family":"Lazar","given":"M.","email":"","affiliations":[],"preferred":false,"id":648892,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Souza, L. A. P.","contributorId":174653,"corporation":false,"usgs":false,"family":"Souza","given":"L.","email":"","middleInitial":"A. P.","affiliations":[],"preferred":false,"id":648893,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"ten Brink, Uri S. 0000-0001-6858-3001 utenbrink@usgs.gov","orcid":"https://orcid.org/0000-0001-6858-3001","contributorId":127560,"corporation":false,"usgs":true,"family":"ten Brink","given":"Uri S.","email":"utenbrink@usgs.gov","affiliations":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":648894,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mahiques, M. M.","contributorId":174654,"corporation":false,"usgs":false,"family":"Mahiques","given":"M.","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":648895,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70176475,"text":"70176475 - 2016 - Inter-population differences in salinity tolerance and osmoregulation of juvenile wild and hatchery-born Sacramento splittail","interactions":[],"lastModifiedDate":"2016-09-16T14:59:12","indexId":"70176475","displayToPublicDate":"2016-09-16T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3919,"text":"Conservation Physiology","onlineIssn":"2051-1434","active":true,"publicationSubtype":{"id":10}},"title":"Inter-population differences in salinity tolerance and osmoregulation of juvenile wild and hatchery-born Sacramento splittail","docAbstract":"The Sacramento splittail (Pogonichthys macrolepidotus) is a minnow endemic to the highly modified San Francisco Estuary of California, USA and its associated rivers and tributaries. This species is composed of two genetically distinct populations, which, according to field observations and otolith strontium signatures, show largely allopatric distribution patterns as recently hatched juveniles. Juvenile Central Valley splittail are found primarily in the nearly fresh waters of the Sacramento and San Joaquin rivers and their tributaries, whereas San Pablo juveniles are found in the typically higher-salinity waters (i.e. up to 10‰) of the Napa and Petaluma Rivers. As the large salinity differences between young-of-year habitats may indicate population-specific differences in salinity tolerance, we hypothesized that juvenile San Pablo and Central Valley splittail populations differ in their response to salinity. In hatchery-born and wild-caught juvenile San Pablo splittail, we found upper salinity tolerances, where mortalities occurred within 336 h of exposure to 16‰ or higher, which was higher than the upper salinity tolerance of 14‰ for wild-caught juvenile Central Valley splittail. This, in conjunction with slower recovery of plasma osmolality, but not ion levels, muscle moisture or gill Na+,K+-ATPase activity, in Central Valley relative to San Pablo splittail during osmoregulatory disturbance provides some support for our hypothesis of inter-population variation in salinity tolerance and osmoregulation. The modestly improved salinity tolerance of San Pablo splittail is consistent with its use of higher-salinity habitats. Although confirmation of the putative adaptive difference through further studies is recommended, this may highlight the need for population-specific management considerations.
","language":"English","publisher":"Society for Experimental Biology","publisherLocation":"Oxford","doi":"10.1093/conphys/cov063","usgsCitation":"Verhille, C.E., Dabruzzi, T.F., Cocherell, D.E., Mahardja, B., Feyrer, F.V., Foin, T.C., Baerwald, M.R., and Fangue, N.A., 2016, Inter-population differences in salinity tolerance and osmoregulation of juvenile wild and hatchery-born Sacramento splittail: Conservation Physiology, v. 4, no. 1, 12 p., https://doi.org/10.1093/conphys/cov063.","productDescription":"12 p.","ipdsId":"IP-078718","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":462079,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/conphys/cov063","text":"Publisher Index Page"},{"id":328689,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Francisco Estuary","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.7008056640625,\n 37.212831514455964\n ],\n [\n -122.7008056640625,\n 39.80853604144591\n ],\n [\n -120.49255371093749,\n 39.80853604144591\n ],\n [\n -120.49255371093749,\n 37.212831514455964\n ],\n [\n -122.7008056640625,\n 37.212831514455964\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"4","issue":"1","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2016-02-16","publicationStatus":"PW","scienceBaseUri":"57f7c63fe4b0bc0bec09c8a3","contributors":{"authors":[{"text":"Verhille, Christine E.","contributorId":174642,"corporation":false,"usgs":false,"family":"Verhille","given":"Christine","email":"","middleInitial":"E.","affiliations":[{"id":13461,"text":"U.C. Davis","active":true,"usgs":false}],"preferred":false,"id":648877,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dabruzzi, Theresa F.","contributorId":174643,"corporation":false,"usgs":false,"family":"Dabruzzi","given":"Theresa","email":"","middleInitial":"F.","affiliations":[{"id":13461,"text":"U.C. Davis","active":true,"usgs":false}],"preferred":false,"id":648878,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cocherell, Dennis E.","contributorId":174644,"corporation":false,"usgs":false,"family":"Cocherell","given":"Dennis","email":"","middleInitial":"E.","affiliations":[{"id":13461,"text":"U.C. Davis","active":true,"usgs":false}],"preferred":false,"id":648879,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mahardja, Brian","contributorId":174645,"corporation":false,"usgs":false,"family":"Mahardja","given":"Brian","email":"","affiliations":[{"id":13461,"text":"U.C. Davis","active":true,"usgs":false}],"preferred":false,"id":648880,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Feyrer, Frederick V. 0000-0003-1253-2349 ffeyrer@usgs.gov","orcid":"https://orcid.org/0000-0003-1253-2349","contributorId":5901,"corporation":false,"usgs":true,"family":"Feyrer","given":"Frederick","email":"ffeyrer@usgs.gov","middleInitial":"V.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":false,"id":648881,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Foin, Theodore C.","contributorId":174646,"corporation":false,"usgs":false,"family":"Foin","given":"Theodore","email":"","middleInitial":"C.","affiliations":[{"id":13461,"text":"U.C. Davis","active":true,"usgs":false}],"preferred":false,"id":648882,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Baerwald, Melinda R.","contributorId":171890,"corporation":false,"usgs":false,"family":"Baerwald","given":"Melinda","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":648868,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Fangue, Nann A.","contributorId":152479,"corporation":false,"usgs":false,"family":"Fangue","given":"Nann","email":"","middleInitial":"A.","affiliations":[{"id":7214,"text":"University of California, Davis","active":true,"usgs":false}],"preferred":false,"id":648883,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70178661,"text":"70178661 - 2016 - Comparison of methods for quantifying surface sublimation over seasonally snow-covered terrain","interactions":[],"lastModifiedDate":"2017-04-27T10:03:31","indexId":"70178661","displayToPublicDate":"2016-09-15T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1924,"text":"Hydrological Processes","active":true,"publicationSubtype":{"id":10}},"title":"Comparison of methods for quantifying surface sublimation over seasonally snow-covered terrain","docAbstract":"Snow sublimation can be an important component of the snow-cover mass balance, and there is considerable interest in quantifying the role of this process within the water and energy balance of snow-covered regions. In recent years, robust eddy covariance (EC) instrumentation has been used to quantify snow sublimation over snow-covered surfaces in complex mountainous terrain. However, EC can be challenging for monitoring turbulent fluxes in snow-covered environments because of intensive data, power, and fetch requirements, and alternative methods of estimating snow sublimation are often relied upon. To evaluate the relative merits of methods for quantifying surface sublimation, fluxes calculated by the EC, Bowen ratio–energy balance (BR), bulk aerodynamic flux (BF), and aerodynamic profile (AP) methods and their associated uncertainty were compared at two forested openings in the Colorado Rocky Mountains. Biases between methods are evaluated over a range of environmental conditions, and limitations of each method are discussed. Mean surface sublimation rates from both sites ranged from 0.33 to 0.36 mm day−1, 0.14 to 0.37 mm day−1, 0.10 to 0.17 mm day−1, and 0.03 to 0.10 mm day−1 for the EC, BR, BF and AP methods, respectively. The EC and/or BF methods are concluded to be superior for estimating surface sublimation in snow-covered forested openings. The surface sublimation rates quantified in this study are generally smaller in magnitude compared with previously published studies in this region and help to refine sublimation estimates for forested openings in the Colorado Rocky Mountains.
","language":"English","publisher":"Wiley","doi":"10.1002/hyp.10864","usgsCitation":"Sexstone, G.A., Clow, D.W., Stannard, D.I., and Fassnacht, S.R., 2016, Comparison of methods for quantifying surface sublimation over seasonally snow-covered terrain: Hydrological Processes, v. 30, no. 19, p. 3373-3389, https://doi.org/10.1002/hyp.10864.","productDescription":"17 p.","startPage":"3373","endPage":"3389","ipdsId":"IP-071074","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":331427,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"30","issue":"19","noUsgsAuthors":false,"publicationDate":"2016-06-06","publicationStatus":"PW","scienceBaseUri":"584144e0e4b04fc80e5073a8","contributors":{"authors":[{"text":"Sexstone, Graham A. 0000-0001-8913-0546 sexstone@usgs.gov","orcid":"https://orcid.org/0000-0001-8913-0546","contributorId":5159,"corporation":false,"usgs":true,"family":"Sexstone","given":"Graham","email":"sexstone@usgs.gov","middleInitial":"A.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":654741,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Clow, David W. 0000-0001-6183-4824 dwclow@usgs.gov","orcid":"https://orcid.org/0000-0001-6183-4824","contributorId":1671,"corporation":false,"usgs":true,"family":"Clow","given":"David","email":"dwclow@usgs.gov","middleInitial":"W.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":654742,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stannard, David I. distanna@usgs.gov","contributorId":562,"corporation":false,"usgs":true,"family":"Stannard","given":"David","email":"distanna@usgs.gov","middleInitial":"I.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":false,"id":654743,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fassnacht, Steven R.","contributorId":177135,"corporation":false,"usgs":false,"family":"Fassnacht","given":"Steven","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":654744,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70176453,"text":"70176453 - 2016 - Prerequisites for understanding climate-change impacts on northern prairie wetlands","interactions":[],"lastModifiedDate":"2017-01-03T16:13:01","indexId":"70176453","displayToPublicDate":"2016-09-14T17:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3750,"text":"Wetlands","onlineIssn":"1943-6246","printIssn":"0277-5212","active":true,"publicationSubtype":{"id":10}},"title":"Prerequisites for understanding climate-change impacts on northern prairie wetlands","docAbstract":"The Prairie Pothole Region (PPR) contains ecosystems that are typified by an extensive matrix of grasslands and depressional wetlands, which provide numerous ecosystem services. Over the past 150 years the PPR has experienced numerous landscape modifications resulting in agricultural conversion of 75–99 % of native prairie uplands and drainage of 50–90 % of wetlands. There is concern over how and where conservation dollars should be spent within the PPR to protect and restore wetland basins to support waterbird populations that will be robust to a changing climate. However, while hydrological impacts of landscape modifications appear substantial, they are still poorly understood. Previous modeling efforts addressing impacts of climate change on PPR wetlands have yet to fully incorporate interacting or potentially overshadowing impacts of landscape modification. We outlined several information needs for building more informative models to predict climate change effects on PPR wetlands. We reviewed how landscape modification influences wetland hydrology and present a conceptual model to describe how modified wetlands might respond to climate variability. We note that current climate projections do not incorporate cyclical variability in climate between wet and dry periods even though such dynamics have shaped the hydrology and ecology of PPR wetlands. We conclude that there are at least three prerequisite steps to making meaningful predictions about effects of climate change on PPR wetlands. Those evident to us are: 1) an understanding of how physical and watershed characteristics of wetland basins of similar hydroperiods vary across temperature and moisture gradients; 2) a mechanistic understanding of how wetlands respond to climate across a gradient of anthropogenic modifications; and 3) improved climate projections for the PPR that can meaningfully represent potential changes in climate variability including intensity and duration of wet and dry periods. Once these issues are addressed, we contend that modeling efforts will better inform and quantify ecosystem services provided by wetlands to meet needs of waterbird conservation and broader societal interests such as flood control and water quality.","language":"English","publisher":"Springer","doi":"10.1007/s13157-016-0811-2","usgsCitation":"Anteau, M.J., Wiltermuth, M.T., Post van der Burg, M., and Pearse, A.T., 2016, Prerequisites for understanding climate-change impacts on northern prairie wetlands: Wetlands, v. 36, no. s2, p. 299-307, https://doi.org/10.1007/s13157-016-0811-2.","productDescription":"9 p.","startPage":"299","endPage":"307","ipdsId":"IP-073902","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":328661,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"36","issue":"s2","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2016-09-08","publicationStatus":"PW","scienceBaseUri":"57da66a5e4b090824ffb164c","chorus":{"doi":"10.1007/s13157-016-0811-2","url":"http://dx.doi.org/10.1007/s13157-016-0811-2","publisher":"Springer Nature","authors":"Anteau Michael J., Wiltermuth Mark T., van der Burg Max Post, Pearse Aaron T.","journalName":"Wetlands","publicationDate":"9/8/2016","auditedOn":"2/15/2017","publiclyAccessibleDate":"9/8/2016"},"contributors":{"authors":[{"text":"Anteau, Michael J. 0000-0002-5173-5870 manteau@usgs.gov","orcid":"https://orcid.org/0000-0002-5173-5870","contributorId":3427,"corporation":false,"usgs":true,"family":"Anteau","given":"Michael","email":"manteau@usgs.gov","middleInitial":"J.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":648803,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wiltermuth, Mark T. 0000-0002-8871-2816 mwiltermuth@usgs.gov","orcid":"https://orcid.org/0000-0002-8871-2816","contributorId":708,"corporation":false,"usgs":true,"family":"Wiltermuth","given":"Mark","email":"mwiltermuth@usgs.gov","middleInitial":"T.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true},{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":648804,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Post van der Burg, Max 0000-0002-3943-4194 maxpostvanderburg@usgs.gov","orcid":"https://orcid.org/0000-0002-3943-4194","contributorId":4947,"corporation":false,"usgs":true,"family":"Post van der Burg","given":"Max","email":"maxpostvanderburg@usgs.gov","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":648805,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pearse, Aaron T. 0000-0002-6137-1556 apearse@usgs.gov","orcid":"https://orcid.org/0000-0002-6137-1556","contributorId":1772,"corporation":false,"usgs":true,"family":"Pearse","given":"Aaron","email":"apearse@usgs.gov","middleInitial":"T.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":648806,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70176456,"text":"70176456 - 2016 - Vegetative response to water availability on the San Carlos Apache Reservation","interactions":[],"lastModifiedDate":"2016-09-14T16:02:53","indexId":"70176456","displayToPublicDate":"2016-09-14T17:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1687,"text":"Forest Ecology and Management","active":true,"publicationSubtype":{"id":10}},"title":"Vegetative response to water availability on the San Carlos Apache Reservation","docAbstract":"On the San Carlos Apache Reservation in east-central Arizona, U.S.A., vegetation types such as ponderosa pine forests, pinyon-juniper woodlands, and grasslands have significant ecological, cultural, and economic value for the Tribe. This value extends beyond the tribal lands and across the Western United States. Vegetation across the Southwestern United States is susceptible to drought conditions and fluctuating water availability. Remotely sensed vegetation indices can be used to measure and monitor spatial and temporal vegetative response to fluctuating water availability conditions. We used the Moderate Resolution Imaging Spectroradiometer (MODIS)-derived Modified Soil Adjusted Vegetation Index II (MSAVI2) to measure the condition of three dominant vegetation types (ponderosa pine forest, woodland, and grassland) in response to two fluctuating environmental variables: precipitation and the Standardized Precipitation Evapotranspiration Index (SPEI). The study period covered 2002 through 2014 and focused on a region within the San Carlos Apache Reservation. We determined that grassland and woodland had a similar moderate to strong, year-round, positive relationship with precipitation as well as with summer SPEI. This suggests that these vegetation types respond negatively to drought conditions and are more susceptible to initial precipitation deficits. Ponderosa pine forest had a comparatively weaker relationship with monthly precipitation and summer SPEI, indicating that it is more buffered against short-term drought conditions. This research highlights the response of multiple, dominant vegetation types to seasonal and inter-annual water availability. This research demonstrates that multi-temporal remote sensing imagery can be an effective tool for the large scale detection of vegetation response to adverse impacts from climate change and support potential management practices such as increased monitoring and management of drought-affected areas. Different vegetation types displayed various responses to water availability, further highlighting the need for individual management plans for forest and woodland, especially considering the projected drier conditions in the Southwest U.S. and other arid or semi-arid regions around the world.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.foreco.2016.07.012","usgsCitation":"Petrakis, R., Wu, Z., McVay, J., Middleton, B.R., Dye, D.G., and Vogel, J.M., 2016, Vegetative response to water availability on the San Carlos Apache Reservation: Forest Ecology and Management, v. 378, p. 14-23, https://doi.org/10.1016/j.foreco.2016.07.012.","productDescription":"10 p.","startPage":"14","endPage":"23","ipdsId":"IP-076045","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":462081,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.foreco.2016.07.012","text":"Publisher Index Page"},{"id":328660,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"San Carlos Apache Reservation","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -110.30,\n 33\n ],\n [\n -110.30,\n 34.0\n ],\n [\n -109.30,\n 34.0\n ],\n [\n -109.30,\n 33\n ],\n [\n -110.30,\n 33\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"378","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57da66a6e4b090824ffb164e","contributors":{"authors":[{"text":"Petrakis, Roy E. 0000-0001-8932-077X rpetrakis@usgs.gov","orcid":"https://orcid.org/0000-0001-8932-077X","contributorId":174623,"corporation":false,"usgs":true,"family":"Petrakis","given":"Roy","email":"rpetrakis@usgs.gov","middleInitial":"E.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":648813,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wu, Zhuoting 0000-0001-7393-1832 zwu@usgs.gov","orcid":"https://orcid.org/0000-0001-7393-1832","contributorId":4953,"corporation":false,"usgs":true,"family":"Wu","given":"Zhuoting","email":"zwu@usgs.gov","affiliations":[{"id":498,"text":"Office of Land Remote Sensing (Geography)","active":true,"usgs":true},{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":648812,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McVay, Jason jcmcvay@usgs.gov","contributorId":140042,"corporation":false,"usgs":true,"family":"McVay","given":"Jason","email":"jcmcvay@usgs.gov","affiliations":[{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true}],"preferred":true,"id":648842,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Middleton, Barry R. 0000-0001-8924-4121 bmiddleton@usgs.gov","orcid":"https://orcid.org/0000-0001-8924-4121","contributorId":3947,"corporation":false,"usgs":true,"family":"Middleton","given":"Barry","email":"bmiddleton@usgs.gov","middleInitial":"R.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":648843,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dye, Dennis G. 0000-0002-7100-272X ddye@usgs.gov","orcid":"https://orcid.org/0000-0002-7100-272X","contributorId":4233,"corporation":false,"usgs":true,"family":"Dye","given":"Dennis","email":"ddye@usgs.gov","middleInitial":"G.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":648844,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Vogel, John M. 0000-0002-8226-1188 jvogel@usgs.gov","orcid":"https://orcid.org/0000-0002-8226-1188","contributorId":3167,"corporation":false,"usgs":true,"family":"Vogel","given":"John","email":"jvogel@usgs.gov","middleInitial":"M.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":648845,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70176461,"text":"70176461 - 2016 - Potential of environmental DNA to evaluate Northern pike (Esox lucius) eradication efforts: An experimental test and case study","interactions":[],"lastModifiedDate":"2016-09-14T15:58:02","indexId":"70176461","displayToPublicDate":"2016-09-14T16:50:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Potential of environmental DNA to evaluate Northern pike (Esox lucius) eradication efforts: An experimental test and case study","docAbstract":"Determining the success of invasive species eradication efforts is challenging because populations at very low abundance are difficult to detect. Environmental DNA (eDNA) sampling has recently emerged as a powerful tool for detecting rare aquatic animals; however, detectable fragments of DNA can persist over time despite absence of the targeted taxa and can therefore complicate eDNA sampling after an eradication event. This complication is a large concern for fish eradication efforts in lakes since killed fish can sink to the bottom and slowly decay. DNA released from these carcasses may remain detectable for long periods. Here, we evaluated the efficacy of eDNA sampling to detect invasive Northern pike (Esox lucius) following piscicide eradication efforts in southcentral Alaskan lakes. We used field observations and experiments to test the sensitivity of our Northern pike eDNA assay and to evaluate the persistence of detectable DNA emitted from Northern pike carcasses. We then used eDNA sampling and traditional sampling (i.e., gillnets) to test for presence of Northern pike in four lakes subjected to a piscicide-treatment designed to eradicate this species. We found that our assay could detect an abundant, free-roaming population of Northern pike and could also detect low-densities of Northern pike held in cages. For these caged Northern pike, probability of detection decreased with distance from the cage. We then stocked three lakes with Northern pike carcasses and collected eDNA samples 7, 35 and 70 days post-stocking. We detected DNA at 7 and 35 days, but not at 70 days. Finally, we collected eDNA samples ~ 230 days after four lakes were subjected to piscicide-treatments and detected Northern pike DNA in 3 of 179 samples, with a single detection at each of three lakes, though we did not catch any Northern pike in gillnets. Taken together, we found that eDNA can help to inform eradication efforts if used in conjunction with multiple lines of inquiry and sampling is delayed long enough to allow full degradation of DNA in the water.
","language":"English","publisher":"PLOS","doi":"10.1371/journal.pone.0162277","usgsCitation":"Dunker, K.J., Sepulveda, A.J., Massengill, R.L., Olsen, J.B., Russ, O.L., Wenburg, J.K., and Antonovich, A., 2016, Potential of environmental DNA to evaluate Northern pike (Esox lucius) eradication efforts: An experimental test and case study: PLoS ONE, v. 11, no. 9, e0162277; 21 p., https://doi.org/10.1371/journal.pone.0162277.","productDescription":"e0162277; 21 p.","ipdsId":"IP-074321","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":470569,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0162277","text":"Publisher Index Page"},{"id":328659,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"11","issue":"9","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2016-09-14","publicationStatus":"PW","scienceBaseUri":"57da66a5e4b090824ffb164a","contributors":{"authors":[{"text":"Dunker, Kristine J.","contributorId":38864,"corporation":false,"usgs":false,"family":"Dunker","given":"Kristine","email":"","middleInitial":"J.","affiliations":[{"id":6770,"text":"Alaska Department of Fish & Game, Division of Commercial Fish, Soldotna, AK 99669","active":true,"usgs":false}],"preferred":false,"id":648828,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sepulveda, Adam J. 0000-0001-7621-7028 asepulveda@usgs.gov","orcid":"https://orcid.org/0000-0001-7621-7028","contributorId":150628,"corporation":false,"usgs":true,"family":"Sepulveda","given":"Adam","email":"asepulveda@usgs.gov","middleInitial":"J.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":648827,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Massengill, Robert L.","contributorId":174630,"corporation":false,"usgs":false,"family":"Massengill","given":"Robert","email":"","middleInitial":"L.","affiliations":[{"id":7058,"text":"Alaska Department of Fish and Game","active":true,"usgs":false}],"preferred":false,"id":648829,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Olsen, Jeffrey B.","contributorId":174632,"corporation":false,"usgs":false,"family":"Olsen","given":"Jeffrey","email":"","middleInitial":"B.","affiliations":[{"id":5128,"text":"U.S. Fish and Wildlife Service, University of Montana, Missoula, MT 59812","active":true,"usgs":false}],"preferred":false,"id":648831,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Russ, Ora L.","contributorId":174633,"corporation":false,"usgs":false,"family":"Russ","given":"Ora","email":"","middleInitial":"L.","affiliations":[{"id":5128,"text":"U.S. Fish and Wildlife Service, University of Montana, Missoula, MT 59812","active":true,"usgs":false}],"preferred":false,"id":648832,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wenburg, John K.","contributorId":174634,"corporation":false,"usgs":false,"family":"Wenburg","given":"John","email":"","middleInitial":"K.","affiliations":[{"id":5128,"text":"U.S. Fish and Wildlife Service, University of Montana, Missoula, MT 59812","active":true,"usgs":false}],"preferred":false,"id":648833,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Antonovich, Anton","contributorId":174631,"corporation":false,"usgs":false,"family":"Antonovich","given":"Anton","email":"","affiliations":[{"id":7058,"text":"Alaska Department of Fish and Game","active":true,"usgs":false}],"preferred":false,"id":648830,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70176435,"text":"70176435 - 2016 - An evaluation of rapid methods for monitoring vegetation characteristics of wetland bird habitat","interactions":[],"lastModifiedDate":"2016-09-14T11:51:56","indexId":"70176435","displayToPublicDate":"2016-09-14T12:50:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3751,"text":"Wetlands Ecology and Management","active":true,"publicationSubtype":{"id":10}},"title":"An evaluation of rapid methods for monitoring vegetation characteristics of wetland bird habitat","docAbstract":"Wetland managers benefit from monitoring data of sufficient precision and accuracy to assess wildlife habitat conditions and to evaluate and learn from past management decisions. For large-scale monitoring programs focused on waterbirds (waterfowl, wading birds, secretive marsh birds, and shorebirds), precision and accuracy of habitat measurements must be balanced with fiscal and logistic constraints. We evaluated a set of protocols for rapid, visual estimates of key waterbird habitat characteristics made from the wetland perimeter against estimates from (1) plots sampled within wetlands, and (2) cover maps made from aerial photographs. Estimated percent cover of annuals and perennials using a perimeter-based protocol fell within 10 percent of plot-based estimates, and percent cover estimates for seven vegetation height classes were within 20 % of plot-based estimates. Perimeter-based estimates of total emergent vegetation cover did not differ significantly from cover map estimates. Post-hoc analyses revealed evidence for observer effects in estimates of annual and perennial covers and vegetation height. Median time required to complete perimeter-based methods was less than 7 percent of the time needed for intensive plot-based methods. Our results show that rapid, perimeter-based assessments, which increase sample size and efficiency, provide vegetation estimates comparable to more intensive methods.
","language":"English","publisher":"Springer","doi":"10.1007/s11273-015-9476-5","usgsCitation":"Tavernia, B.G., Lyons, J., Loges, B.W., Wilson, A., Collazo, J., and Runge, M.C., 2016, An evaluation of rapid methods for monitoring vegetation characteristics of wetland bird habitat: Wetlands Ecology and Management, v. 24, no. 5, p. 495-505, https://doi.org/10.1007/s11273-015-9476-5.","productDescription":"11 p.","startPage":"495","endPage":"505","ipdsId":"IP-067154","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":328639,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"24","issue":"5","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2015-12-17","publicationStatus":"PW","scienceBaseUri":"57da669ee4b090824ffb1642","contributors":{"authors":[{"text":"Tavernia, Brian G. btavernia@usgs.gov","contributorId":174618,"corporation":false,"usgs":false,"family":"Tavernia","given":"Brian","email":"btavernia@usgs.gov","middleInitial":"G.","affiliations":[{"id":7041,"text":"The Nature Conservancy","active":true,"usgs":false}],"preferred":false,"id":648752,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lyons, James E.","contributorId":35461,"corporation":false,"usgs":true,"family":"Lyons","given":"James E.","affiliations":[],"preferred":false,"id":648753,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Loges, Brian W.","contributorId":146554,"corporation":false,"usgs":false,"family":"Loges","given":"Brian","email":"","middleInitial":"W.","affiliations":[{"id":6678,"text":"U.S. Fish and Wildlife Service, Alaska Maritime National Wildlife Refuge","active":true,"usgs":false}],"preferred":false,"id":648793,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wilson, Andrew","contributorId":174620,"corporation":false,"usgs":false,"family":"Wilson","given":"Andrew","affiliations":[],"preferred":false,"id":648794,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Collazo, Jaime A. 0000-0002-1816-7744 jaime_collazo@usgs.gov","orcid":"https://orcid.org/0000-0002-1816-7744","contributorId":173448,"corporation":false,"usgs":true,"family":"Collazo","given":"Jaime A.","email":"jaime_collazo@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":false,"id":648754,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Runge, Michael C. 0000-0002-8081-536X mrunge@usgs.gov","orcid":"https://orcid.org/0000-0002-8081-536X","contributorId":3358,"corporation":false,"usgs":true,"family":"Runge","given":"Michael","email":"mrunge@usgs.gov","middleInitial":"C.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":648751,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70176418,"text":"ofr20161158 - 2016 - Behavior and movements of adult spring Chinook salmon (Oncorhynchus tshawytscha) in the Chehalis River Basin, southwestern Washington, 2015","interactions":[],"lastModifiedDate":"2016-09-15T08:29:31","indexId":"ofr20161158","displayToPublicDate":"2016-09-14T00:00:00","publicationYear":"2016","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":"2016-1158","title":"Behavior and movements of adult spring Chinook salmon (Oncorhynchus tshawytscha) in the Chehalis River Basin, southwestern Washington, 2015","docAbstract":"Recent interest in flood control and restoration strategies in the Chehalis River Basin has increased the need to understand the current status and ecology of spring Chinook salmon. Based on the extended period between freshwater entry and spawn timing, spring Chinook salmon have the longest exposure of all adult Chinook salmon life histories to the low-flow and high water temperature conditions that typically occur during summer. About 100 adult spring Chinook salmon were found dead in the Chehalis River in July and August 2009. Adult Chinook salmon are known to hold in cool-water refugia during warm summer months, but the extent to which spring Chinook salmon might use thermal refugia in the Chehalis River is unknown. The movements and temperature exposures of adult spring Chinook salmon following their return to the Chehalis River were investigated using radiotelemetry and transmitters equipped with temperature sensors, combined with water temperature monitoring throughout the basin. A total of 23 spring Chinook salmon were radio-tagged between April and early July 2015; 11 were captured and released in the main-stem Chehalis River, and 12 were captured and released in the South Fork Newaukum River. Tagged fish were monitored with a combination of fixed-site monitoring locations and regular mobile tracking, from freshwater entry through the spawning period.
Water temperature and flow conditions in the main-stem Chehalis River during 2015 were atypical compared to historical averages. Mean monthly water temperatures between March and July 2015 were higher than any decade since 1960 and mean daily flows were 30–70 percent of the flows in previous years. Overall, 96 percent of the tagged fish were detected, with a mean of 62 d in the detection history of tagged fish. Of the 11 fish released in the main-stem Chehalis River, six fish (55 percent) moved upstream, either shortly after release (2–7 d, 50 percent), or following a short delay (12–18 d, 50 percent). One fish released in the main-stem Chehalis River remained near the release location for 64 d before moving upstream.
The final fates for the seven fish that moved upstream in the main-stem Chehalis River included two fish with unknown fates, two fish with a fate of pre-spawn mortality, and three fish that were assigned a fate of spawner. Four (36 percent) of the radio-tagged Chinook salmon released in the main-stem Chehalis River showed limited movement from their release sites, and were assigned fates of unknown (one fish), pre-spawn mortality (one fish), and spit/mortality (2 fish). The 12 spring Chinook salmon released in the South Fork Newaukum River remained in the South Fork Newaukum River throughout the study period. Five (42 percent) of these fish were actively moving through the spawning period and were assigned a fate of spawner. Seven (58 percent) of these fish were detected for a period following release, but their detection histories ended prior to the spawning period. The fates assigned to these seven fish included two fish with spit/mortality fates and five fish with fates of pre-spawn mortality. Tagged fish in both the Chehalis River and the South Fork Newaukum River showed limited movements during the peak water temperatures in July and August, and were not frequently detected at sites where water temperatures were greater than 21 °C. Pre-spawn mortality due to predation or harvest may be an important factor in the Chehalis River Basin as it was the assigned fate for 27 percent of the fish released in the main-stem Chehalis River and 42 percent of the fish released in the South Fork Newaukum River.
This study represents a substantial contribution to the understanding of spring Chinook salmon in the Chehalis River Basin. The water temperatures and flow conditions during the 2015 study period were not typical of the historical conditions in the basin and the numbers of tagged fish monitored was relatively low, so results should be interpreted with those cautions in mind.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161158","collaboration":"Prepared in cooperation with the Washington Department of Fish and Wildlife","usgsCitation":"Liedtke, T.L., Zimmerman, M.S., Tomka, R.G., Holt, Curt, and Jennings, Lyle, 2016, Behavior and movements of adult spring Chinook salmon (Oncorhynchus tshawytscha) in the Chehalis River Basin, southwestern Washington, 2015: U.S. Geological Survey Open-File Report 2016-1158, 57 p., https://dx.doi.org/10.3133/ofr20161158.","productDescription":"vi, 57 p.","numberOfPages":"67","onlineOnly":"Y","ipdsId":"IP-076409","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":328667,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1158/ofr20161158.pdf","text":"Report","size":"4.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1158"},{"id":328666,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1158/coverthb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Chehalis River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.837890625,\n 46.38293856752681\n ],\n [\n -123.837890625,\n 46.965259400349275\n ],\n [\n -122.52227783203125,\n 46.965259400349275\n ],\n [\n -122.52227783203125,\n 46.38293856752681\n ],\n [\n -123.837890625,\n 46.38293856752681\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Western Fisheries Research Center
U.S. Geological Survey
6505 NE 65th Street
Seattle, Washington 98115
http://wfrc.usgs.gov/
The acquisition and transfer of water rights to wetland areas of Lahontan Valley, Nevada, has caused concern over the potential effects on shallow aquifer water levels. In 1992, water levels in Lahontan Valley were measured to construct a water-table map of the shallow aquifer prior to the effects of water-right transfers mandated by the Fallon Paiute-Shoshone Tribal Settlement Act of 1990 (Public Law 101-618, 104 Stat. 3289). From 1992 to 2012, approximately 11,810 water-righted acres, or 34,356 acre-feet of water, were acquired and transferred to wetland areas of Lahontan Valley. This report documents changes in water levels measured during the period of water-right transfers and presents an evaluation of five groundwater-flow model scenarios that simulated water-level changes in Lahontan Valley in response to water-right transfers and a reduction in irrigation season length by 50 percent.
Water levels measured in 98 wells from 2012 to 2013 were used to construct a water-table map. Water levels in 73 of the 98 wells were compared with water levels measured in 1992 and used to construct a water-level change map. Water-level changes in the 73 wells ranged from -16.2 to 4.1 feet over the 20-year period. Rises in water levels in Lahontan Valley may correspond to annual changes in available irrigation water, increased canal flows after the exceptionally dry and shortened irrigation season of 1992, and the increased conveyance of water rights transferred to Stillwater National Wildlife Refuge. Water-level declines generally occurred near the boundary of irrigated areas and may be associated with groundwater pumping, water-right transfers, and inactive surface-water storage reservoirs. The largest water-level declines were in the area near Carson Lake.
Groundwater-level response to water-right transfers was evaluated by comparing simulated and observed water-level changes for periods representing water-right transfers and a shortened irrigation season in areas near Fallon and Stillwater, Nevada. In the Stillwater modeled area, water rights associated with nearly 50 percent of the irrigated land were transferred from 1992 to 1998, represented by the model scenario reduction in groundwater recharge by 50 percent. The scenario resulted in a simulated average decline of 0.6 foot; average observed water-level change for the modeled area was estimated to be 0.0 foot, or no change. In the Fallon modeled area, transfers of water rights associated with 180 acres of land occurred from 1994 to 2008. The transfer is most similar to the scenario for removal of 320 acres of irrigated land. The model scenario resulted in simulated water-level declines of 0.1; water levels measured from 1994 to 2012 indicate no significant trends in water levels, or approximately zero change in water levels, for the Fallon modeled area.
The model scenarios included the simulation of a irrigation season shortened by 50 percent, which was determined to have occurred in the 1992 irrigation season in both modeled areas. The shortening of the irrigation season in the Fallon modeled area resulted in simulated water-level declines of 1.1 feet; observed declines were estimated to be 1.3 feet. The Stillwater model simulations resulted in a simulated decline of 1.4 feet, and observed water levels declined an estimated 2.3 feet for the area. The estimated difference between simulated and observed water levels are 0.2 and 0.9 foot for the Fallon and Stillwater modeled areas, respectively. Observed water-level changes were generally within one standard deviation of changes from model simulations, based on the selected periods of comparison. Simulated and observed water-level changes agree well, generally within 1 foot; however, the model scenarios were only approximately similar to the observed conditions, and periods of comparison were generally shorter for the observed periods and included additional cumulative effects of water-right transfers. Climate variability was not considered in the model scenarios.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165045","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service","usgsCitation":"Smith, D.W., Buto, S.G., and Welborn, T.L., 2016, Groundwater-level change and evaluation of simulated water levels for irrigated areas in Lahontan Valley, Churchill County, west-central Nevada, 1992‒2012: U.S. Geological Survey Scientific Investigations Report 2016-5045, 23 p., https://dx.doi.org/10.3133/sir20165045.","productDescription":"Report: vi, 23 p.; 1 Plate: 30.00 x 26.00 inches; 3 Appendixes; 2 Data Releases","numberOfPages":"34","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-049203","costCenters":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"links":[{"id":438548,"rank":8,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7222RWF","text":"USGS data release","linkHelpText":"Go to View Manage Groundwater-level and groundwater-level change contours for the Lahontan Valley shallow aquifer near Fallon, Nevada, 2012"},{"id":328562,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2016/5045/sir20165045_appendix2.xlsx","text":"Appendix 2","size":"11 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2016-5045 Appendix 2"},{"id":328558,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5045/coverthb.jpg"},{"id":328559,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5045/sir20165045.pdf","text":"Report","size":"4.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5045"},{"id":328560,"rank":3,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2016/5045/sir20165045_plate01.pdf","text":"Plate 1","size":"1.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5045 Plate 1","linkHelpText":"Water-level Contours of Lahontan Valley"},{"id":328561,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2016/5045/sir20165045_appendix1.xlsx","text":"Appendix 1","size":"28 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2016-5045 Appendix 1"},{"id":328563,"rank":6,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2016/5045/sir20165045_appendix3.pdf","text":"Appendix 3","size":"608 KB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5045 Appendix 3"},{"id":328564,"rank":7,"type":{"id":30,"text":"Data Release"},"url":"https://dx.doi.org/10.5066/F7222RWF","text":"GIS Datasets","description":"SIR 2016-5045 GIS data","linkHelpText":"Groundwater-level and groundwater-level change contours for the Lahontan Valley shallow aquifer near Fallon, Nevada, 2012"}],"country":"United States","state":"Nevada","county":"Churchill County","otherGeospatial":"Lahontan Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -119.25,\n 39\n ],\n [\n -119.25,\n 39.75\n ],\n [\n -118.40,\n 39.75\n ],\n [\n -118.40,\n 39\n ],\n [\n -119.25,\n 39\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Nevada Water Science Center
U.S. Geological Survey
2730 N. Deer Run Rd.
Carson City, NV 89701
http://nevada.usgs.gov/
Streamflow and water temperature in the Middle Fork Willamette River (MFWR), western Oregon, have been regulated and altered since the construction of Lookout Point, Dexter, and Hills Creek Dams in 1954 and 1961, respectively. Each year, summer releases from the dams typically are cooler than pre-dam conditions, with the reverse (warmer than pre-dam conditions) occurring in autumn. This pattern has been detrimental to habitat of endangered Upper Willamette River (UWR) Chinook salmon (Oncorhynchus tshawytscha) and UWR winter steelhead (O. mykiss) throughout multiple life stages. In this study, scenarios testing different dam-operation strategies and hypothetical dam-outlet structures were simulated using CE-QUAL-W2 hydrodynamic/temperature models of the MFWR system from Hills Creek Lake (HCR) to Lookout Point (LOP) and Dexter (DEX) Lakes to explore and understand the efficacy of potential flow and temperature mitigation options.
Model scenarios were run in constructed wet, normal, and dry hydrologic calendar years, and designed to minimize the effects of Hills Creek and Lookout Point Dams on river temperature by prioritizing warmer lake surface releases in May–August and cooler, deep releases in September–December. Operational scenarios consisted of a range of modified release rate rules, relaxation of power-generation constraints, variations in the timing of refill and drawdown, and maintenance of different summer maximum lake levels at HCR and LOP. Structural scenarios included various combinations of hypothetical floating outlets near the lake surface and hypothetical new outlets at depth. Scenario results were compared to scenarios using existing operational rules that give temperature management some priority (Base), scenarios using pre-2012 operational rules that prioritized power generation over temperature management (NoBlend), and estimated temperatures from a without-dams condition (WoDams).
Results of the tested model scenarios led to the following conclusions:
Director, Oregon Water Science Center
U.S. Geological Survey
2130 SW 5th Avenue
Portland, Oregon 97201
http://or.water.usgs.gov
The U.S. Geological Survey (USGS), in cooperation with the Colorado Department of Transportation, developed regional-regression equations for estimating the 50-, 20-, 10-, 4-, 2-, 1-, 0.5-, 0.2-percent annual exceedance-probability discharge (AEPD) for natural streamflow in eastern Colorado. A total of 188 streamgages, consisting of 6,536 years of record and a mean of approximately 35 years of record per streamgage, were used to develop the peak-streamflow regional-regression equations. The estimated AEPDs for each streamgage were computed using the USGS software program PeakFQ. The AEPDs were determined using systematic data through water year 2013. Based on previous studies conducted in Colorado and neighboring States and on the availability of data, 72 characteristics (57 basin and 15 climatic characteristics) were evaluated as candidate explanatory variables in the regression analysis. Paleoflood and non-exceedance bound ages were established based on reconnaissance-level methods. Multiple lines of evidence were used at each streamgage to arrive at a conclusion (age estimate) to add a higher degree of certainty to reconnaissance-level estimates. Paleoflood or nonexceedance bound evidence was documented at 41 streamgages, and 3 streamgages had previously collected paleoflood data.To determine the peak discharge of a paleoflood or non-exceedanc bound, two different hydraulic models were used.
The mean standard error of prediction (SEP) for all 8 AEPDs was reduced approximately 25 percent compared to the previous flood-frequency study. For paleoflood data to be effective in reducing the SEP in eastern Colorado, a larger ratio than 44 of 188 (23 percent) streamgages would need paleoflood data and that paleoflood data would need to increase the record length by more than 25 years for the 1-percent AEPD. The greatest reduction in SEP for the peak-streamflow regional-regression equations was observed when additional new basin characteristics were included in the peak-streamflow regional-regression equations and when eastern Colorado was divided into two separate hydrologic regions. To make further reductions in the uncertainties of the peak-streamflow regional-regression equations in the Foothills and Plains hydrologic regions, additional streamgages or crest-stage gages are needed to collect peak-streamflow data on natural streams in eastern Colorado.
Generalized-Least Squares regression was used to compute the final peak-streamflow regional-regression equations for peak-streamflow. Dividing eastern Colorado into two new individual regions at –104° longitude resulted in peak-streamflow regional-regression equations with the smallest SEP. The new hydrologic region located between –104° longitude and the Kansas-Nebraska State line will be designated the Plains hydrologic region and the hydrologic region comprising the rest of eastern Colorado located west of the –104° longitude and east of the Rocky Mountains and below 7,500 feet in the South Platte River Basin and below 9,000 feet in the Arkansas River Basin will be designated the Foothills hydrologic region.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165099","collaboration":"Prepared in cooperation with the Colorado Department of Transportation","usgsCitation":"Kohn, M.S., Stevens, M.R., Harden, T.M., Godaire, J.E., Klinger, R.E., and Mommandi, Amanullah, 2016, Paleoflood investigations to improve peak-streamflow regional-regression equations for natural streamflow in eastern Colorado, 2015: U.S. Geological Survey Scientific Investigations Report 2016–5099, 58 p., https://dx.doi.org/10.3133/sir20165099.","productDescription":"Report: ix, 57 p.; 3 Appendixes","onlineOnly":"Y","ipdsId":"IP-064605","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":328604,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2016/5099/sir20165099_Appendix6.zip","text":"Appendix 6","size":"10.6 MB","linkFileType":{"id":6,"text":"zip"},"description":"SIR 2016-5099 Appendix 6"},{"id":328603,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2016/5099/sir20165099_Appendix5.zip","text":"Appendix 5","size":"540 kB","linkFileType":{"id":6,"text":"zip"},"description":"SIR 2016-5099 Appendix 5"},{"id":328602,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2016/5099/sir20165099_Appendix4.zip","text":"Appendix 4","size":"15.4 MB","linkFileType":{"id":6,"text":"zip"},"description":"SIR 2016-5099 Appendix 4"},{"id":328354,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5099/sir20165099.pdf","text":"Report","size":"127 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5099"},{"id":328353,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5099/coverthb.jpg"}],"country":"United States","state":"Colorado","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -110.5,\n 42\n ],\n [\n -110.5,\n 36\n ],\n [\n -100.5,\n 36\n ],\n [\n -100.5,\n 42\n ],\n [\n -110.5,\n 42\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, USGS Colorado Water Science Center
Box 25046, Mail Stop 415
Denver, CO 80225
In the past decade, difficulties encountered in reproducing the results of a cancer study at Duke University resulted in a scandal and an investigation which concluded that tools used for data management, analysis, and modeling were inappropriate for the documentation of the study, let alone the reproduction of the results. New protocols were developed which require that data analysis and modeling be carried out with scripts that can be used to reproduce the results and are a record of all decisions and interpretations made during an analysis or a modeling effort. In the hydrological sciences, we face similar challenges and need to develop similar standards for transparency and repeatability of results. A promising route is to start making use of open-source languages (such as R and Python) to write scripts and to use collaborative coding environments (such as Git) to share our codes for inspection and use by the hydrological community. An important side-benefit to adopting such protocols is consistency and efficiency among collaborators.
","language":"English","publisher":"EGU","doi":"10.5194/hess-20-3739-2016","usgsCitation":"Fienen, M., and Bakker, M., 2016, HESS Opinions: Repeatable research: what hydrologistscan learn from the Duke cancer research scandal: Hydrology and Earth System Sciences, v. 20, p. 3739-3743, https://doi.org/10.5194/hess-20-3739-2016.","productDescription":"5 p.","startPage":"3739","endPage":"3743","ipdsId":"IP-075419","costCenters":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"links":[{"id":462083,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/hess-20-3739-2016","text":"Publisher Index Page"},{"id":328593,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"20","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2016-09-12","publicationStatus":"PW","scienceBaseUri":"57d91527e4b090824ff9fa36","contributors":{"authors":[{"text":"Fienen, Michael 0000-0002-7756-4651 mnfienen@usgs.gov","orcid":"https://orcid.org/0000-0002-7756-4651","contributorId":174604,"corporation":false,"usgs":true,"family":"Fienen","given":"Michael","email":"mnfienen@usgs.gov","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":false,"id":648709,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bakker, Mark","contributorId":56137,"corporation":false,"usgs":true,"family":"Bakker","given":"Mark","email":"","affiliations":[],"preferred":false,"id":648710,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70176414,"text":"70176414 - 2016 - Intertidal salt marshes as an important source of inorganic carbon to the coastal ocean","interactions":[],"lastModifiedDate":"2016-09-13T09:44:52","indexId":"70176414","displayToPublicDate":"2016-09-13T10:40:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2620,"text":"Limnology and Oceanography","active":true,"publicationSubtype":{"id":10}},"title":"Intertidal salt marshes as an important source of inorganic carbon to the coastal ocean","docAbstract":"Dynamic tidal export of dissolved inorganic carbon (DIC) to the coastal ocean from highly productive intertidal marshes and its effects on seawater carbonate chemistry are thoroughly evaluated. The study uses a comprehensive approach by combining tidal water sampling of CO2parameters across seasons, continuous in situ measurements of biogeochemically-relevant parameters and water fluxes, with high-resolution modeling in an intertidal salt marsh of the U.S. northeast region. Salt marshes can acidify and alkalize tidal water by injecting CO2 (DIC) and total alkalinity (TA). DIC and TA generation may also be decoupled due to differential effects of marsh aerobic and anaerobic respiration on DIC and TA. As marsh DIC is added to tidal water, the buffering capacity first decreases to a minimum and then increases quickly. Large additions of marsh DIC can result in higher buffering capacity in ebbing tide than incoming tide. Alkalization of tidal water, which mostly occurs in the summer due to anaerobic respiration, can further modify buffering capacity. Marsh exports of DIC and alkalinity may have complex implications for the future, more acidified ocean. Marsh DIC export exhibits high variability over tidal and seasonal cycles, which is modulated by both marsh DIC generation and by water fluxes. The marsh DIC export of 414 g C m−2 yr−1, based on high-resolution measurements and modeling, is more than twice the previous estimates. It is a major term in the marsh carbon budget and translates to one of the largest carbon fluxes along the U.S. East Coast.
","language":"English","publisher":"ASLO","doi":"10.1002/lno.10347","usgsCitation":"Wang, Z., Kroeger, K.D., Ganju, N., Gonneea Eagle, M., and Chu, S.N., 2016, Intertidal salt marshes as an important source of inorganic carbon to the coastal ocean: Limnology and Oceanography, v. 61, no. 5, p. 1916-1931, https://doi.org/10.1002/lno.10347.","productDescription":"16 p.","startPage":"1916","endPage":"1931","ipdsId":"IP-073972","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":470570,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/lno.10347","text":"Publisher Index Page"},{"id":328589,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Massachusetts","otherGeospatial":"Sage Lot Pond, Waquoit Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -70.5188798904419,\n 41.54953955986466\n ],\n [\n -70.5188798904419,\n 41.55718297621677\n ],\n [\n -70.50287246704102,\n 41.55718297621677\n ],\n [\n -70.50287246704102,\n 41.54953955986466\n ],\n [\n -70.5188798904419,\n 41.54953955986466\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"61","issue":"5","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationDate":"2016-07-18","publicationStatus":"PW","scienceBaseUri":"57d91527e4b090824ff9fa38","chorus":{"doi":"10.1002/lno.10347","url":"http://dx.doi.org/10.1002/lno.10347","publisher":"Wiley-Blackwell","authors":"Wang Zhaohui Aleck, Kroeger Kevin D., Ganju Neil K., Gonneea Meagan Eagle, Chu Sophie N.","journalName":"Limnology and Oceanography","publicationDate":"7/18/2016"},"contributors":{"authors":[{"text":"Wang, Zhaohui Aleck","contributorId":174589,"corporation":false,"usgs":false,"family":"Wang","given":"Zhaohui Aleck","affiliations":[{"id":13627,"text":"Woods Hole Oceanographic Institution, Woods Hole, MA","active":true,"usgs":false}],"preferred":false,"id":648666,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kroeger, Kevin D. 0000-0002-4272-2349 kkroeger@usgs.gov","orcid":"https://orcid.org/0000-0002-4272-2349","contributorId":1603,"corporation":false,"usgs":true,"family":"Kroeger","given":"Kevin","email":"kkroeger@usgs.gov","middleInitial":"D.","affiliations":[{"id":41100,"text":"Coastal and Marine Hazards and Resources Program","active":true,"usgs":true}],"preferred":true,"id":648665,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ganju, Neil K. 0000-0002-1096-0465 nganju@usgs.gov","orcid":"https://orcid.org/0000-0002-1096-0465","contributorId":140088,"corporation":false,"usgs":true,"family":"Ganju","given":"Neil K.","email":"nganju@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":648667,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gonneea Eagle, Meagan 0000-0001-5072-2755 mgonneea@usgs.gov","orcid":"https://orcid.org/0000-0001-5072-2755","contributorId":174590,"corporation":false,"usgs":true,"family":"Gonneea Eagle","given":"Meagan","email":"mgonneea@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":648668,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Chu, Sophie N.","contributorId":174603,"corporation":false,"usgs":false,"family":"Chu","given":"Sophie","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":648669,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70175951,"text":"ofr20161140 - 2016 - Examination of flood characteristics at selected streamgages in the Meramec River Basin, eastern Missouri, December 2015–January 2016","interactions":[],"lastModifiedDate":"2016-09-14T10:32:53","indexId":"ofr20161140","displayToPublicDate":"2016-09-13T00:00:00","publicationYear":"2016","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":"2016-1140","title":"Examination of flood characteristics at selected streamgages in the Meramec River Basin, eastern Missouri, December 2015–January 2016","docAbstract":"Heavy rainfall resulted in major flooding in the Meramec River Basin in eastern Missouri during late December 2015 through early January 2016. Cumulative rainfall from December 14 to 29, 2015, ranged from 7.6 to 12.3 inches at selected precipitation stations in the basin with flooding driven by the heaviest precipitation (3.9–9.7 inches) between December 27 and 29, 2015. Financial losses from flooding included damage to homes and other structures, damage to roads, and debris removal. Eight of 11 counties in the basin were declared a Federal Disaster Area.
The U.S. Geological Survey (USGS), in cooperation with the U.S. Army Corps of Engineers and St. Louis Metropolitan Sewer District, operates multiple streamgages along the Meramec River and its primary tributaries including the Bourbeuse River and Big River. The period of record for streamflow at streamgages in the basin included in this report ranges from 24 to 102 years. Instrumentation in a streamgage shelter automatically makes observations of stage using a variety of methods (submersible pressure transducer, non-submersible pressure transducer, or non-contact radar). These observations are recorded autonomously at a predetermined programmed frequency (typically either 15 or 30 minutes) dependent on drainage-area size and concomitant flashiness of the stream. Although stage data are important, streamflow data are equally or more important for streamflow forecasting, water-quality constituent loads computation, flood-frequency analysis, and flood mitigation planning. Streamflows are computed from recorded stage data using an empirically determined relation between stage and streamflow termed a “rating.” Development and verification of the rating requires periodic onsite discrete measurements of streamflow throughout time and over the range of stages to define local hydraulic conditions.
The purpose of this report is to examine characteristics of flooding that occurred in the Meramec River Basin in December 2015–January 2016 including peak stages, peak streamflows, and the flood-frequency statistics associated with the peak flows. A comparison between the December 2015–January 2016 flood and a similar flood in December 1982 in the Meramec River Basin also is included.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161140","usgsCitation":"Holmes, R.R., Jr., Koenig, T.A., Rydlund, P.H., and Heimann, D.C., 2016, Examination of flood characteristics at selected streamgages in the Meramec River Basin, Eastern Missouri, December 2015–January 2016: U.S. Geological Survey Open-File Report 2016–1140, 7 p., https://dx.doi.org/10.3133/ofr20161140.","productDescription":"Report: 7 p., Tables: 1-3","numberOfPages":"8","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-077164","costCenters":[{"id":396,"text":"Missouri Water Science Center","active":true,"usgs":true}],"links":[{"id":328622,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1140/ofr20161140.pdf","text":"Report","size":"1.34 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016–1140"},{"id":328621,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1140/coverthb.jpg"},{"id":328623,"rank":3,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/of/2016/1140/ofr20161140_tables1-3.xlsx","text":"Tables 1–3","size":"333 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"OFR 2016–1140 Tables"}],"country":"United States","state":"Missouri","otherGeospatial":"Meramec River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -91.900634765625,\n 37.3002752813443\n ],\n [\n -91.900634765625,\n 38.18638677411551\n ],\n [\n -90.2911376953125,\n 38.18638677411551\n ],\n [\n -90.2911376953125,\n 37.3002752813443\n ],\n [\n -91.900634765625,\n 37.3002752813443\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Chief, Office of Surface Water
U.S. Geological Survey
415 National Center
12201 Sunrise Valley Drive
Reston, VA 20192
Sediment budgets of the Lower Missouri River were developed in a study led by the U.S. Geological Survey in cooperation with the U.S. Army Corps of Engineers. The scope of the study included the development of a long-term (post-impoundment, 1968–2014) average annual sediment budget and selected annual, monthly, and daily sediment budgets for a reach and period that adequate data were available. Included in the analyses were 31 main-stem and tributary stations of the Lower Missouri River and two Mississippi River stations—the Mississippi River below Grafton, Illinois, and the Mississippi River at St. Louis, Missouri.
Long-term average annual suspended-sediment loads of Missouri River main-stem stations ranged from 0.33 million tons at the Missouri River at Yankton, South Dakota, station to 71.2 million tons at Missouri River at Hermann, Mo., station. Gaged tributary gains accounted for 9–36 percent of the local reach budgets and cumulative gaged tributary contributions accounted for 84 percent of the long-term average suspended-sediment load of the Missouri River at Hermann, Mo., station. Although the sediment budgets for seven defined main-stem reaches generally were incomplete—missing bedload, reach storage, and ungaged tributary contributions—the budget residuals (net result of sediment inputs and outputs) for six of the seven reaches ranged from -7.0 to 1.7 million tons, or from -9.2 to 4.0 percent of the reach output suspended-sediment load, and were within the 10 percent reported measurement error of annual suspended-sediment loads for large rivers. The remaining reach, downstream from Gavin’s Point Dam, extended from Yankton, S. Dak., to Sioux City, Iowa, and had a budget residual of -9.8 million tons, which was -88 percent of the suspended-sediment load at Sioux City.
The Lower Missouri River reach from Omaha, Nebraska, to Nebraska City, Nebr., had periods of concurrent sediment data for each primary budget component with which to analyze and determine a suspended-sediment budget for selected annual, monthly, and daily time increments. The temporal changes in the cumulative annual budget residuals were poorly correlated with the comparatively steady 1968–2011 annual stage trends at the Missouri River at Nebraska City, Nebr., station. An accurate total sediment budget is developed by having concurrent data available for all primary suspended and bedload components for a reach of interest throughout a period. Such a complete budget, with concurrent record for suspended-sediment load and bedload components, is unavailable for any reach and period in the Lower Missouri River. The primary data gaps are in bedload data, and also in suspended-sediment gains and losses including ungaged tributary inputs and sediment storage. Bedload data gaps in the Missouri River Basin are much more prevalent than suspended-sediment data gaps, and the first step in the development of reach bedload budgets is the establishment of a standardized bedload monitoring program at main-stem stations.
The temporal changes in flow-adjusted suspended-sediment concentrations analyzed at main-stem Missouri River stations indicated an overall downward change in concentrations between 1968 and 2014. Temporary declines in flow-adjusted suspended-sediment concentrations during and following large floods were evident but generally returned to near pre-flood values within about 6 months.
Data uncertainties associated with the development of a sediment budget include uncertainties associated with the collection of suspended-sediment and bedload data and the computation of suspended-sediment loads. These uncertainties vary depending on the frequency of data collection, the variability of conditions being represented by the discrete samples, and the statistical approach to suspended-sediment load computations. The coefficients of variation of suspended-sediment loads of Missouri River tributary stations for 1968–2014 were greater, 75.0 percent, than the main-stem stations, 47.1 percent. The lower coefficient of variation at main-stem stations compared to tributaries, primarily is the result of the lower variability in streamflow and sediment discharge identified at main-stem stations. To obtain similar accuracy between suspended-sediment loads at main-stem and tributary stations, a longer period of record is required of the tributary stations. During 1968–2014, however, the Missouri River main-stem station record was much more complete (87 percent) than the tributary station record (28 percent).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165097","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers","usgsCitation":"Heimann, D.C., 2016, Generalized sediment budgets of the Lower Missouri River, 1968–2014: U.S. Geological Survey Scientific Investigations Report 2016–5097, 51 p., https://dx.doi.org/10.3133/sir20165097.","productDescription":"Report: vii, 51 p.; Tables 1-9","numberOfPages":"64","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-073678","costCenters":[{"id":396,"text":"Missouri Water Science Center","active":true,"usgs":true}],"links":[{"id":328577,"rank":12,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2016/5097/sir20165097_tables.zip","text":"Tables 1–9","size":"8.88 MB","linkFileType":{"id":6,"text":"zip"},"description":"SIR 2016–5097 Tables 1–9"},{"id":328568,"rank":3,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2016/5097/sir20165097_table_1.xlsx","text":"Table 1","size":"599 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2016–5097 Table 1"},{"id":328569,"rank":4,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2016/5097/sir20165097_table_2.xlsx","text":"Table 2","size":"6.15 MB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2016–5097 Table 2"},{"id":328570,"rank":5,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2016/5097/sir20165097_table_3.xlsx","text":"Table 3","size":"9.11 MB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2016–5097 Table 3"},{"id":328565,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5097/coverthb.jpg"},{"id":328566,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5097/sir20165097.pdf","text":"Report","size":"5.29 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016–5097"},{"id":328574,"rank":9,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2016/5097/sir20165097_table_7.xlsx","text":"Table 7","size":"496 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2016–5097 Table 7"},{"id":328571,"rank":6,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2016/5097/sir20165097_table_4.xlsx","text":"Table 4","size":"496 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2016–5097 Table 4"},{"id":328575,"rank":10,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2016/5097/sir20165097_table_8.xlsx","text":"Table 8","size":"46.4 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2016–5097 Table 8"},{"id":328572,"rank":7,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2016/5097/sir20165097_table_5.xlsx","text":"Table 5","size":"499 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2016–5097 Table 5"},{"id":328573,"rank":8,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2016/5097/sir20165097_table_6.xlsx","text":"Table 6","size":"493 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2016–5097 Table 6"},{"id":328576,"rank":11,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2016/5097/sir20165097_table_9.xlsx","text":"Table 9","size":"586 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2016–5097 Table 9"}],"country":"United States","otherGeospatial":"Missouri River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -90.120849609375,\n 38.81617117607388\n ],\n [\n -91.318359375,\n 38.89103282648846\n ],\n [\n -92.933349609375,\n 40.59727063442027\n ],\n [\n -95.361328125,\n 43.51668853502909\n ],\n [\n -97.72338867187499,\n 45.91294412737392\n ],\n [\n -99.54711914062499,\n 47.57652571374621\n ],\n [\n -104.0185546875,\n 48.99463598353408\n ],\n [\n -105.029296875,\n 49.468124067331644\n ],\n [\n -113.203125,\n 49.56797785892715\n ],\n [\n -112.587890625,\n 44.98034238084973\n ],\n [\n -107.09472656249999,\n 40.9964840143779\n ],\n [\n -102.06298828125,\n 38.35888785866677\n ],\n [\n -94.59228515625,\n 37.10776507118514\n ],\n [\n -91.64794921875,\n 37.142803443716836\n ],\n [\n -90.9173583984375,\n 38.36750215395045\n ],\n [\n -90.120849609375,\n 38.81617117607388\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Missouri Water Science Center
U.S. Geological Survey
1400 Independence Road
Rolla, MO 65401
Relative-gravity data and absolute-gravity data were collected at 68 stations in the Sierra Vista Subwatershed, Upper San Pedro Basin, Arizona, in May–June 2015 for the purpose of estimating aquifer-storage change. Similar data from 2014 and a description of the survey network were published in U.S. Geological Survey Open-File Report 2015–1086. Data collection and network adjustment results are presented in this report, which is accompanied by a supporting Web Data Release (http://dx.doi.org/10.5066/F7SQ8XHX). Station positions are presented from a Global Positioning System campaign to determine station elevation.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161155","collaboration":"Prepared in cooperation with The Nature Conservancy","usgsCitation":"Kennedy, J.R., 2016, Gravity change from 2014 to 2015, Sierra Vista Subwatershed, Upper San Pedro Basin, Arizona: U.S. Geological Survey Open-File Report 2016–1155, 15 p., https://dx.doi.org/10.3133/ofr20161155.","productDescription":"Report: v, 15 p.; Datasets","numberOfPages":"20","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-074089","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"links":[{"id":328551,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1155/coverthb.jpg"},{"id":328553,"rank":5,"type":{"id":28,"text":"Dataset"},"url":"https://pubs.usgs.gov/of/2016/1155/ofr20161155_SanPedroGravity2014-2015_AbsoluteGravity.txt","text":"Absolute gravity","size":"237 bytes","linkFileType":{"id":2,"text":"txt"},"description":"OFR 2016-1155 Absolute gravity"},{"id":328552,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1155/ofr20161155.pdf","text":"Report","size":"1.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1155"},{"id":328554,"rank":3,"type":{"id":28,"text":"Dataset"},"url":"https://pubs.usgs.gov/of/2016/1155/ofr20161155_SanPedroGravity2014-2015_AdjustedGravity.csv","text":"Adjusted gravity","size":"5 KB","linkFileType":{"id":7,"text":"csv"},"description":"OFR 2016-1155 Adjusted gravity"},{"id":328756,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://dx.doi.org/10.5066/F7SQ8XHX","text":"GIS Data","description":"OFR 2016-1155 GIS Data"},{"id":328555,"rank":4,"type":{"id":28,"text":"Dataset"},"url":"https://pubs.usgs.gov/of/2016/1155/ofr20161155_SanPedroGravity2014-2015_RelativeGravity.txt","text":"Relative gravity","size":"12 KB","linkFileType":{"id":2,"text":"txt"},"description":"OFR 2016-1155 Relative gravity"}],"country":"United States","state":"Arizona","otherGeospatial":"Upper San Pedro Basin, Sierra Vista Subwatershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -110.33912658691406,\n 31.439794704219466\n ],\n [\n -110.33912658691406,\n 31.633506308954388\n ],\n [\n -110.09880065917969,\n 31.633506308954388\n ],\n [\n -110.09880065917969,\n 31.439794704219466\n ],\n [\n -110.33912658691406,\n 31.439794704219466\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Arizona Water Science Center
U.S. Geological Survey
520 N. Park Avenue
Tucson, AZ 85719
http://az.water.usgs.gov
The work explained in this report was conducted to assess geomorphic adjustment of the lower White River, Arkansas, to hydrologic modifications and establish forest age and community structure within selected communities within the floodplain. Also, the HEC–GeoRAS model was evaluated for predicting flood depth and duration within the floodplain. Hydrologic modeling using HEC–GeoRAS is a common way to model flooding in a floodplain. A parameterized model exists for the White River, Arkansas, based on observed flows at gauges, but its ability to reproduce current and future hydrological conditions throughout the floodplain has not been quantified. The objectives of this work are to—
\nThis study provides baseline information on the current geomorphic and hydrologic conditions of the river and can assist in the interpretation of forest responses to past hydrologic and geomorphic processes. Understanding the implications for floodplain forests of geomorphic adjustment in the Lower Mississippi Alluvial Valley is key to managing the region’s valuable resources for a sustainable future.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161113","usgsCitation":"King, S.L., Keim, R.F., Hupp, C.R., Edwards, B.L., Kroschel, W.A., Johnson, E.L., and Cochran, J.W., 2016, Altered hydrologic and geomorphic processes and bottomland hardwood plant communities of the lower White River Basin: U.S. Geological Survey Open-File Report 2016–1113, 32 p., https://dx.doi.org/10.3133/ofr20161113. ","productDescription":"v, 33 p.","numberOfPages":"39","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-073365","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":328275,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1113/ofr20161113.pdf","text":"Report","size":"1.44 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1113"},{"id":328274,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1113/coverthb.jpg"}],"country":"United States","state":"Arkansas","otherGeospatial":"Lower White River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -91.461181640625,\n 34.01851844336969\n ],\n [\n -91.461181640625,\n 34.856636719051735\n ],\n [\n -90.9613037109375,\n 34.856636719051735\n ],\n [\n -90.9613037109375,\n 34.01851844336969\n ],\n [\n -91.461181640625,\n 34.01851844336969\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Louisiana Water Science Center
U.S. Geological Survey
3535 South Sherwood Forest Blvd.
Suite 120
Baton Rouge, LA 70816
http://la.water.usgs.gov/
Temperate lakes may contain both coolwater fish species such as walleye (Sander vitreus) and warmwater fish species such as largemouth bass (Micropterus salmoides). Recent declining walleye and increasing largemouth bass populations have raised questions regarding the future trajectories and management actions for these species. We developed a thermodynamic model of water temperatures driven by downscaled climate data and lake-specific characteristics to estimate daily water temperature profiles for 2148 lakes in Wisconsin, US, under contemporary (1989–2014) and future (2040–2064 and 2065–2089) conditions. We correlated contemporary walleye recruitment and largemouth bass relative abundance to modeled water temperature, lake morphometry, and lake productivity, and projected lake-specific changes in each species under future climate conditions. Walleye recruitment success was negatively related and largemouth bass abundance was positively related to water temperature degree days. Both species exhibited a threshold response at the same degree day value, albeit in opposite directions. Degree days were predicted to increase in the future, although the magnitude of increase varied among lakes, time periods, and global circulation models (GCMs). Under future conditions, we predicted a loss of walleye recruitment in 33–75% of lakes where recruitment is currently supported and a 27–60% increase in the number of lakes suitable for high largemouth bass abundance. The percentage of lakes capable of supporting abundant largemouth bass but failed walleye recruitment was predicted to increase from 58% in contemporary conditions to 86% by mid-century and to 91% of lakes by late century, based on median projections across GCMs. Conversely, the percentage of lakes with successful walleye recruitment and low largemouth bass abundance was predicted to decline from 9% of lakes in contemporary conditions to only 1% of lakes in both future periods. Importantly, we identify up to 85 resilient lakes predicted to continue to support natural walleye recruitment. Management resources could target preserving these resilient walleye populations.
","language":"English","publisher":"Wiley","doi":"10.1111/gcb.13462","usgsCitation":"Hansen, G., Read, J.S., Hansen, J.F., and Winslow, L., 2016, Projected shifts in fish species dominance in Wisconsin lakes under climate change: Global Change Biology, v. 23, no. 4, p. 1463-1476, https://doi.org/10.1111/gcb.13462.","productDescription":"14 p.","startPage":"1463","endPage":"1476","ipdsId":"IP-073795","costCenters":[{"id":160,"text":"Center for Integrated Data Analytics","active":false,"usgs":true}],"links":[{"id":470572,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/gcb.13462","text":"Publisher Index Page"},{"id":438550,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7X0655K","text":"USGS data release","linkHelpText":"Projected shifts in fish species dominance in Wisconsin lakes under climate 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