We assess erosion and flooding risk in the northern Gulf of Mexico by identifying interdependencies among oceanographic drivers and probabilistically modeling the resulting potential for coastal change. Wave and water level observations are used to determine relationships between six hydrodynamic parameters that influence total water level and therefore erosion and flooding, through consideration of a wide range of univariate distribution functions and multivariate elliptical copulas. Using these relationships, we explore how different our interpretation of the present-day erosion/flooding risk could be if we had seen more or fewer extreme realizations of individual and combinations of parameters in the past by simulating 10,000 physically and statistically consistent sea-storm time series. We find that seasonal total water levels associated with the 100 year return period could be up to 3 m higher in summer and 0.6 m higher in winter relative to our best estimate based on the observational records. Impact hours of collision and overwash—where total water levels exceed the dune toe or dune crest elevations—could be on average 70% (collision) and 100% (overwash) larger than inferred from the observations. Our model accounts for non-stationarity in a straightforward, non-parametric way that can be applied (with little adjustments) to many other coastlines. The probabilistic model presented here, which accounts for observational uncertainty, can be applied to other coastlines where short record lengths limit the ability to identify the full range of possible wave and water level conditions that coastal mangers and planners must consider to develop sustainable management strategies.
","language":"English","publisher":"AGU Publications","doi":"10.1002/2015JC011482","usgsCitation":"Plant, N.G., Wahl, T., and Long, J.W., 2016, Probabilistic assessment of erosion and flooding risk in the northern Gulf of Mexico: Journal of Geophysical Research C: Oceans, v. 121, no. 5, p. 3029-3043, https://doi.org/10.1002/2015JC011482.","productDescription":"15 p.","startPage":"3029","endPage":"3043","ipdsId":"IP-070871","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":470631,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://eprints.soton.ac.uk/393754/2/pdf","text":"External Repository"},{"id":328093,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"121","issue":"5","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationDate":"2016-05-13","publicationStatus":"PW","scienceBaseUri":"57c7f1abe4b0f2f0cebf11ad","contributors":{"authors":[{"text":"Plant, Nathaniel G. 0000-0002-5703-5672 nplant@usgs.gov","orcid":"https://orcid.org/0000-0002-5703-5672","contributorId":3503,"corporation":false,"usgs":true,"family":"Plant","given":"Nathaniel","email":"nplant@usgs.gov","middleInitial":"G.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true},{"id":508,"text":"Office of the AD Hazards","active":true,"usgs":true}],"preferred":true,"id":647454,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wahl, Thomas","contributorId":141017,"corporation":false,"usgs":false,"family":"Wahl","given":"Thomas","email":"","affiliations":[{"id":13653,"text":"University South Florida","active":true,"usgs":false}],"preferred":false,"id":647455,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Long, Joseph W. 0000-0003-2912-1992 jwlong@usgs.gov","orcid":"https://orcid.org/0000-0003-2912-1992","contributorId":3303,"corporation":false,"usgs":true,"family":"Long","given":"Joseph","email":"jwlong@usgs.gov","middleInitial":"W.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":647456,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70176157,"text":"70176157 - 2016 - Model calibration criteria for estimating ecological flow characteristics","interactions":[],"lastModifiedDate":"2018-04-02T15:27:59","indexId":"70176157","displayToPublicDate":"2016-08-31T10:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Model calibration criteria for estimating ecological flow characteristics","docAbstract":"Quantification of streamflow characteristics in ungauged catchments remains a challenge. Hydrological modeling is often used to derive flow time series and to calculate streamflow characteristics for subsequent applications that may differ from those envisioned by the modelers. While the estimation of model parameters for ungauged catchments is a challenging research task in itself, it is important to evaluate whether simulated time series preserve critical aspects of the streamflow hydrograph. To address this question, seven calibration objective functions were evaluated for their ability to preserve ecologically relevant streamflow characteristics of the average annual hydrograph using a runoff model, HBV-light, at 27 catchments in the southeastern United States. Calibration trials were repeated 100 times to reduce parameter uncertainty effects on the results, and 12 ecological flow characteristics were computed for comparison. Our results showed that the most suitable calibration strategy varied according to streamflow characteristic. Combined objective functions generally gave the best results, though a clear underprediction bias was observed. The occurrence of low prediction errors for certain combinations of objective function and flow characteristic suggests that (1) incorporating multiple ecological flow characteristics into a single objective function would increase model accuracy, potentially benefitting decision-making processes; and (2) there may be a need to have different objective functions available to address specific applications of the predicted time series.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Hydro-ecological modeling","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"MDPI","isbn":"978-3-03842-212-9","usgsCitation":"Vis, M., Knight, R., Poole, S., Wolfe, W.J., and Seibert, J., 2016, Model calibration criteria for estimating ecological flow characteristics, chap. of Hydro-ecological modeling, p. 256-281.","productDescription":"26 p.","startPage":"256","endPage":"281","ipdsId":"IP-079269","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":29789,"text":"John Wesley Powell Center for Analysis and Synthesis","active":true,"usgs":true}],"links":[{"id":328094,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":328058,"type":{"id":15,"text":"Index Page"},"url":"https://www.mdpi.com/books/pdfview/book/215"}],"publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57c7f1aae4b0f2f0cebf11ab","contributors":{"editors":[{"text":"Breuer, Lutz","contributorId":174162,"corporation":false,"usgs":false,"family":"Breuer","given":"Lutz","email":"","affiliations":[],"preferred":false,"id":647594,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Kraft, Philipp","contributorId":174163,"corporation":false,"usgs":false,"family":"Kraft","given":"Philipp","email":"","affiliations":[],"preferred":false,"id":647595,"contributorType":{"id":2,"text":"Editors"},"rank":2}],"authors":[{"text":"Vis, Marc","contributorId":174146,"corporation":false,"usgs":false,"family":"Vis","given":"Marc","email":"","affiliations":[{"id":27368,"text":"University of Zurich","active":true,"usgs":false}],"preferred":false,"id":647510,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Knight, Rodney 0000-0001-9588-0167 rrknight@usgs.gov","orcid":"https://orcid.org/0000-0001-9588-0167","contributorId":152422,"corporation":false,"usgs":true,"family":"Knight","given":"Rodney","email":"rrknight@usgs.gov","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":581,"text":"Tennessee Water Science Center","active":true,"usgs":true}],"preferred":true,"id":647509,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Poole, Sandra","contributorId":174147,"corporation":false,"usgs":false,"family":"Poole","given":"Sandra","email":"","affiliations":[{"id":27368,"text":"University of Zurich","active":true,"usgs":false}],"preferred":false,"id":647511,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wolfe, William J. wjwolfe@usgs.gov","contributorId":174054,"corporation":false,"usgs":true,"family":"Wolfe","given":"William","email":"wjwolfe@usgs.gov","middleInitial":"J.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":false,"id":647512,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Seibert, Jan","contributorId":176322,"corporation":false,"usgs":false,"family":"Seibert","given":"Jan","email":"","affiliations":[],"preferred":false,"id":647513,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70175747,"text":"70175747 - 2016 - Methods for exploring uncertainty in groundwater management predictions","interactions":[],"lastModifiedDate":"2016-09-01T13:13:07","indexId":"70175747","displayToPublicDate":"2016-08-31T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Methods for exploring uncertainty in groundwater management predictions","docAbstract":"Models of groundwater systems help to integrate knowledge about the natural and human system covering different spatial and temporal scales, often from multiple disciplines, in order to address a range of issues of concern to various stakeholders. A model is simply a tool to express what we think we know. Uncertainty, due to lack of knowledge or natural variability, means that there are always alternative models that may need to be considered. This chapter provides an overview of uncertainty in models and in the definition of a problem to model, highlights approaches to communicating and using predictions of uncertain outcomes and summarises commonly used methods to explore uncertainty in groundwater management predictions. It is intended to raise awareness of how alternative models and hence uncertainty can be explored in order to facilitate the integration of these techniques with groundwater management.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Integrated groundwater management","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Springer","doi":"10.1007/978-3-319-23576-9_28","isbn":"978-3-319-23575-2","usgsCitation":"Guillaume, J.H., Hunt, R.J., Comunian, A., Fu, B., and Blakers, R.S., 2016, Methods for exploring uncertainty in groundwater management predictions, chap. of Integrated groundwater management, p. 711-737, https://doi.org/10.1007/978-3-319-23576-9_28.","productDescription":"27 p.","startPage":"711","endPage":"737","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-057337","costCenters":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"links":[{"id":488538,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/978-3-319-23576-9_28","text":"Publisher Index Page"},{"id":328111,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57c7f1a9e4b0f2f0cebf11a9","contributors":{"editors":[{"text":"Jakeman, Anthony J. 0000-0001-5282-2215","orcid":"https://orcid.org/0000-0001-5282-2215","contributorId":173848,"corporation":false,"usgs":false,"family":"Jakeman","given":"Anthony","email":"","middleInitial":"J.","affiliations":[{"id":17939,"text":"The Australian National University","active":true,"usgs":false}],"preferred":false,"id":647604,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Barreteau, Olivier","contributorId":173849,"corporation":false,"usgs":false,"family":"Barreteau","given":"Olivier","email":"","affiliations":[{"id":27301,"text":"IRSTEA - UMR G-EAU (France)","active":true,"usgs":false}],"preferred":false,"id":647605,"contributorType":{"id":2,"text":"Editors"},"rank":2},{"text":"Hunt, Randall J. 0000-0001-6465-9304 rjhunt@usgs.gov","orcid":"https://orcid.org/0000-0001-6465-9304","contributorId":1129,"corporation":false,"usgs":true,"family":"Hunt","given":"Randall","email":"rjhunt@usgs.gov","middleInitial":"J.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":647606,"contributorType":{"id":2,"text":"Editors"},"rank":3},{"text":"Rinaudo, Jean-Daniel","contributorId":173850,"corporation":false,"usgs":false,"family":"Rinaudo","given":"Jean-Daniel","email":"","affiliations":[{"id":27302,"text":"BRGM (France)","active":true,"usgs":false}],"preferred":false,"id":647607,"contributorType":{"id":2,"text":"Editors"},"rank":4},{"text":"Ross, Andrew","contributorId":173851,"corporation":false,"usgs":false,"family":"Ross","given":"Andrew","email":"","affiliations":[{"id":13328,"text":"UNESCO-IHE","active":true,"usgs":false}],"preferred":false,"id":647608,"contributorType":{"id":2,"text":"Editors"},"rank":5}],"authors":[{"text":"Guillaume, Joseph H. A.","contributorId":173856,"corporation":false,"usgs":false,"family":"Guillaume","given":"Joseph","email":"","middleInitial":"H. A.","affiliations":[{"id":6718,"text":"Aalto University, Finland","active":true,"usgs":false}],"preferred":false,"id":646295,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hunt, Randall J. 0000-0001-6465-9304 rjhunt@usgs.gov","orcid":"https://orcid.org/0000-0001-6465-9304","contributorId":1129,"corporation":false,"usgs":true,"family":"Hunt","given":"Randall","email":"rjhunt@usgs.gov","middleInitial":"J.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":646294,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Comunian, Alessandro","contributorId":173857,"corporation":false,"usgs":false,"family":"Comunian","given":"Alessandro","email":"","affiliations":[{"id":27304,"text":"University of New South Wales","active":true,"usgs":false}],"preferred":false,"id":646296,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fu, Baihua 0000-0003-2494-0518","orcid":"https://orcid.org/0000-0003-2494-0518","contributorId":174165,"corporation":false,"usgs":false,"family":"Fu","given":"Baihua","email":"","affiliations":[],"preferred":false,"id":647603,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Blakers, Rachel S","contributorId":173858,"corporation":false,"usgs":false,"family":"Blakers","given":"Rachel","email":"","middleInitial":"S","affiliations":[{"id":27305,"text":"Australia National University","active":true,"usgs":false}],"preferred":false,"id":646297,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70176162,"text":"70176162 - 2016 - Temperature is better than precipitation as a predictor of plant community assembly across a dryland region","interactions":[],"lastModifiedDate":"2016-09-16T16:21:53","indexId":"70176162","displayToPublicDate":"2016-08-31T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2490,"text":"Journal of Vegetation Science","active":true,"publicationSubtype":{"id":10}},"title":"Temperature is better than precipitation as a predictor of plant community assembly across a dryland region","docAbstract":"How closely do plant communities track climate? Research suggests that plant species converge toward similar environmental tolerances relative to the environments that they experience. Whether these patterns apply to severe environments or scale up to plant community-level patterns of relative climatic tolerances is poorly understood. Using estimates of species' climatic tolerances acquired from occurrence records, we determined the contributions of individual species' climatic niche breadths and environmental filtering to the relationships between community-average climatic tolerances and the local climates experienced by those communities.
Southwestern United States drylands.
Interspecific variation in niche breadth was assessed as a function of species' climatic optima (median climatic niche value). The relationships between climatic optima and tolerances were used as null expectations for the relationship between abundance-weighted mean climatic tolerances of communities and the local climate of that community. Deviations from this null expectation indicate that species with greater or lesser climatic tolerances are favoured relative to co-occurring species. The intensity of environmental filtering was estimated by comparing the range of climatic tolerances within each community to a null distribution generated from a random assembly algorithm.
The temperature niches of species were consistently symmetrical and of similar breadths, regardless of their temperature optima. In contrast, precipitation niches were skewed toward wetter conditions, and niche breadth increased with increasing precipitation optima. At the community level, relationships with climate were much stronger for temperature than for precipitation. Furthermore, cold and heat were stronger assembly filters than drought or precipitation, with the intensity of environmental filtering increasing at both ends of climatic gradients. Community-average climatic tolerances did deviate significantly from null expectations, indicating that species with higher or lower relative climatic tolerances were favoured under certain conditions.
Despite strong water limitation of plant performance in dryland ecosystems, communities tracked variation in temperature much more closely, intimating strong responses to anticipated temperature increases. Furthermore, abundance distributions were biased toward species with higher or lower relative climatic tolerances under different climatic conditions, but predictably so, indicating the need for assembly models that include processes other than simple environmental filtering.
","language":"English","publisher":"International Association for Vegetation Science","publisherLocation":"Uppsala, Sweden","doi":"10.1111/jvs.12440","usgsCitation":"Butterfield, B.J., and Munson, S.M., 2016, Temperature is better than precipitation as a predictor of plant community assembly across a dryland region: Journal of Vegetation Science, v. 27, no. 5, p. 938-947, https://doi.org/10.1111/jvs.12440.","productDescription":"10 p.","startPage":"938","endPage":"947","ipdsId":"IP-060796","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":328089,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","volume":"27","issue":"5","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-08-04","publicationStatus":"PW","scienceBaseUri":"57c7f1afe4b0f2f0cebf11b7","contributors":{"authors":[{"text":"Butterfield, Bradley J. 0000-0003-0974-9811","orcid":"https://orcid.org/0000-0003-0974-9811","contributorId":167009,"corporation":false,"usgs":false,"family":"Butterfield","given":"Bradley","email":"","middleInitial":"J.","affiliations":[{"id":24591,"text":"Merriam-Powell Center for Environmental Research and Department of Biological Sciences, Northern Arizona University, Flagstaff, AZ, USA","active":true,"usgs":false}],"preferred":false,"id":647521,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Munson, Seth M. 0000-0002-2736-6374 smunson@usgs.gov","orcid":"https://orcid.org/0000-0002-2736-6374","contributorId":1334,"corporation":false,"usgs":true,"family":"Munson","given":"Seth","email":"smunson@usgs.gov","middleInitial":"M.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true},{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true}],"preferred":true,"id":647520,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70176185,"text":"70176185 - 2016 - Approaches to stream solute load estimation for solutes with varying dynamics from five diverse small watershed","interactions":[],"lastModifiedDate":"2016-08-31T14:46:03","indexId":"70176185","displayToPublicDate":"2016-08-31T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Approaches to stream solute load estimation for solutes with varying dynamics from five diverse small watershed","docAbstract":"Estimating streamwater solute loads is a central objective of many water-quality monitoring and research studies, as loads are used to compare with atmospheric inputs, to infer biogeochemical processes, and to assess whether water quality is improving or degrading. In this study, we evaluate loads and associated errors to determine the best load estimation technique among three methods (a period-weighted approach, the regression-model method, and the composite method) based on a solute's concentration dynamics and sampling frequency. We evaluated a broad range of varying concentration dynamics with stream flow and season using four dissolved solutes (sulfate, silica, nitrate, and dissolved organic carbon) at five diverse small watersheds (Sleepers River Research Watershed, VT; Hubbard Brook Experimental Forest, NH; Biscuit Brook Watershed, NY; Panola Mountain Research Watershed, GA; and Río Mameyes Watershed, PR) with fairly high-frequency sampling during a 10- to 11-yr period. Data sets with three different sampling frequencies were derived from the full data set at each site (weekly plus storm/snowmelt events, weekly, and monthly) and errors in loads were assessed for the study period, annually, and monthly. For solutes that had a moderate to strong concentration–discharge relation, the composite method performed best, unless the autocorrelation of the model residuals was <0.2, in which case the regression-model method was most appropriate. For solutes that had a nonexistent or weak concentration–discharge relation (modelR2 < about 0.3), the period-weighted approach was most appropriate. The lowest errors in loads were achieved for solutes with the strongest concentration–discharge relations. Sample and regression model diagnostics could be used to approximate overall accuracies and annual precisions. For the period-weighed approach, errors were lower when the variance in concentrations was lower, the degree of autocorrelation in the concentrations was higher, and sampling frequency was higher. The period-weighted approach was most sensitive to sampling frequency. For the regression-model and composite methods, errors were lower when the variance in model residuals was lower. For the composite method, errors were lower when the autocorrelation in the residuals was higher. Guidelines to determine the best load estimation method based on solute concentration–discharge dynamics and diagnostics are presented, and should be applicable to other studies.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.1298","usgsCitation":"Aulenbach, B.T., Burns, D.A., Shanley, J.B., Yanai, R.D., Bae, K., Wild, A., Yang, Y., and Yi, D., 2016, Approaches to stream solute load estimation for solutes with varying dynamics from five diverse small watershed: Ecosphere, v. 7, no. 6, e01298; 22 p., https://doi.org/10.1002/ecs2.1298.","productDescription":"e01298; 22 p.","ipdsId":"IP-065579","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":470632,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.1298","text":"Publisher Index Page"},{"id":328145,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"7","issue":"6","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationDate":"2016-06-17","publicationStatus":"PW","scienceBaseUri":"57c7f1a3e4b0f2f0cebf119f","contributors":{"authors":[{"text":"Aulenbach, Brent T. 0000-0003-2863-1288 btaulenb@usgs.gov","orcid":"https://orcid.org/0000-0003-2863-1288","contributorId":3057,"corporation":false,"usgs":true,"family":"Aulenbach","given":"Brent","email":"btaulenb@usgs.gov","middleInitial":"T.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":316,"text":"Georgia Water Science Center","active":true,"usgs":true}],"preferred":true,"id":647649,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Burns, Douglas A. 0000-0001-6516-2869 daburns@usgs.gov","orcid":"https://orcid.org/0000-0001-6516-2869","contributorId":1237,"corporation":false,"usgs":true,"family":"Burns","given":"Douglas","email":"daburns@usgs.gov","middleInitial":"A.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":647650,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shanley, James B. 0000-0002-4234-3437 jshanley@usgs.gov","orcid":"https://orcid.org/0000-0002-4234-3437","contributorId":1953,"corporation":false,"usgs":true,"family":"Shanley","given":"James","email":"jshanley@usgs.gov","middleInitial":"B.","affiliations":[{"id":405,"text":"NH/VT office of New England Water Science Center","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":647651,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Yanai, Ruth D.","contributorId":59720,"corporation":false,"usgs":true,"family":"Yanai","given":"Ruth","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":647652,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bae, Kikang","contributorId":174183,"corporation":false,"usgs":false,"family":"Bae","given":"Kikang","email":"","affiliations":[{"id":27381,"text":"State University of New York, College of Environmental Science and Forestry, Syracuse, NY","active":true,"usgs":false}],"preferred":false,"id":647653,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wild, Adam","contributorId":174184,"corporation":false,"usgs":false,"family":"Wild","given":"Adam","email":"","affiliations":[{"id":27381,"text":"State University of New York, College of Environmental Science and Forestry, Syracuse, NY","active":true,"usgs":false}],"preferred":false,"id":647654,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Yang, Yang","contributorId":174185,"corporation":false,"usgs":false,"family":"Yang","given":"Yang","email":"","affiliations":[{"id":27381,"text":"State University of New York, College of Environmental Science and Forestry, Syracuse, NY","active":true,"usgs":false}],"preferred":false,"id":647655,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Yi, Dong","contributorId":174186,"corporation":false,"usgs":false,"family":"Yi","given":"Dong","email":"","affiliations":[{"id":27381,"text":"State University of New York, College of Environmental Science and Forestry, Syracuse, NY","active":true,"usgs":false}],"preferred":false,"id":647656,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70176280,"text":"70176280 - 2016 - Summer-autumn habitat use of yearling rainbow trout in two streams in the Lake Ontario watershed","interactions":[],"lastModifiedDate":"2016-09-07T12:42:34","indexId":"70176280","displayToPublicDate":"2016-08-31T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2948,"text":"Open Fish Science Journal","active":true,"publicationSubtype":{"id":10}},"title":"Summer-autumn habitat use of yearling rainbow trout in two streams in the Lake Ontario watershed","docAbstract":"Understanding the habitat requirements of salmonids in streams is an important component of fisheries management. We examined the summer and autumn habitat use of yearling Rainbow Trout Oncorhynchus mykiss in relation to available habitat in two streams in the Lake Ontario watershed. Little interstream variation in trout habitat use was observed; the variation that did occur was largely due to differences between streams in available habitat in the autumn. In both streams, yearling Rainbow Trout utilized pool habitat and during periods of high stream discharge were associated with larger substrate that may provide a velocity barrier. These findings may assist resource managers in their efforts to protect and restore habitat for migratory Rainbow Trout in the Lake Ontario watershed.
","language":"English","publisher":"Bentham Science Publishers","doi":"10.2174/1874401X01609010045","usgsCitation":"Johnson, J.H., McKenna, J., and Chalupnicki, M., 2016, Summer-autumn habitat use of yearling rainbow trout in two streams in the Lake Ontario watershed: Open Fish Science Journal, v. 9, p. 45-50, https://doi.org/10.2174/1874401X01609010045.","productDescription":"6 p.","startPage":"45","endPage":"50","ipdsId":"IP-075868","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":470634,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.2174/1874401x01609010045","text":"Publisher Index Page"},{"id":328311,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New York","otherGeospatial":"Grout Brook, Orwell Brook","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -76.29592895507812,\n 42.71296638907414\n ],\n [\n -76.29592895507812,\n 42.80295793799244\n ],\n [\n -76.23310089111328,\n 42.80295793799244\n ],\n [\n -76.23310089111328,\n 42.71296638907414\n ],\n [\n -76.29592895507812,\n 42.71296638907414\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -76.02573394775389,\n 43.5107129908437\n ],\n [\n -76.02573394775389,\n 43.611471040985286\n ],\n [\n -75.970458984375,\n 43.611471040985286\n ],\n [\n -75.970458984375,\n 43.5107129908437\n ],\n [\n -76.02573394775389,\n 43.5107129908437\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"9","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57d13a40e4b0571647cf8e11","contributors":{"authors":[{"text":"Johnson, James H. 0000-0002-5619-3871 jhjohnson@usgs.gov","orcid":"https://orcid.org/0000-0002-5619-3871","contributorId":389,"corporation":false,"usgs":true,"family":"Johnson","given":"James","email":"jhjohnson@usgs.gov","middleInitial":"H.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":648187,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McKenna, James E. Jr. 0000-0002-1428-7597 jemckenna@usgs.gov","orcid":"https://orcid.org/0000-0002-1428-7597","contributorId":627,"corporation":false,"usgs":true,"family":"McKenna","given":"James E.","suffix":"Jr.","email":"jemckenna@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":false,"id":648188,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Chalupnicki, Marc 0000-0002-3792-9345 mchalupnicki@usgs.gov","orcid":"https://orcid.org/0000-0002-3792-9345","contributorId":173643,"corporation":false,"usgs":true,"family":"Chalupnicki","given":"Marc","email":"mchalupnicki@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":648189,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70175054,"text":"fs20163055 - 2016 - Streamflow of 2015—Water year national summary","interactions":[],"lastModifiedDate":"2016-09-12T09:41:28","indexId":"fs20163055","displayToPublicDate":"2016-08-30T11:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2016-3055","title":"Streamflow of 2015—Water year national summary","docAbstract":"The maps and graphs in this summary describe national streamflow conditions for water year 2015 (October 1, 2014, to September 30, 2015) in the context of the 86-year period 1930–2015, unless otherwise noted. The illustrations are based on observed data from the U.S. Geological Survey’s (USGS) National Streamflow Information Program http://water.usgs.gov/nsip). The period 1930–2015 was used because prior to 1930, the number of streamgages was too small to provide representative data for computing statistics for most regions of the country.
In the summary, reference is made to the term “runoff,” which is the depth to which a river basin, State, or other geographic area would be covered with water if all the streamflow within the area during a specified time period was uniformly distributed upon it. Runoff quantifies the magnitude of water flowing through the Nation's rivers and streams in measurement units that can be compared from one area to another.
Each of the maps and graphs can be expanded to a larger view by clicking on the image. In all of the graphics, a rank of 1 indicates the highest flow of all years analyzed. Rankings of streamflow are grouped into much-below normal, below normal, normal, above normal, and much-above normal, based on percentiles of flow (greater than 90 percent, 76–90 percent, 25–75 percent, 10–24 percent, and less than 10 percent, respectively) (http://waterwatch.usgs.gov/?id=ww_current). Some data used to produce maps and graphs are provisional and subject to change.
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U.S. Geological Survey
415 National Center
Reston, VA 20192
http://water.usgs.gov/osw/
The prevalence and histopathology of neoplastic lesions were assessed in white suckerCatostomus commersonii captured at two Lake Michigan Areas of Concern (AOCs), the Sheboygan River and Milwaukee Estuary. Findings were compared to those observed at two non-AOC sites, the Root and Kewaunee rivers. At each site, approximately 200 adult suckers were collected during their spawning migration. Raised skin lesions were observed at all sites and included discrete white spots, mucoid plaques on the body surface and fins and large papillomatous lesions on lips and body. Microscopically, hyperplasia, papilloma and squamous cell carcinoma were documented. Liver neoplasms were also observed at all sites and included both hepatocellular and biliary tumours. Based on land use, the Kewaunee River was the site least impacted by human activities previously associated with fish tumours and had significantly fewer liver neoplasms when compared to the other sites. The proportion of white suckers with liver tumours followed the same patterns as the proportion of urban land use in the watershed: the Milwaukee Estuary had the highest prevalence, followed by the Root, Sheboygan and Kewaunee rivers. The overall skin neoplasm (papilloma and carcinoma) prevalence did not follow the same pattern, although the percentage of white suckers with squamous cell carcinoma exhibited a similar relationship to land use. Testicular tumours (seminoma) were observed at both AOC sites but not at the non-AOC sites. Both skin and liver tumours were significantly and positively associated with age but not sex.
","language":"English","publisher":"Wiley","doi":"10.1111/jfd.12520","usgsCitation":"Blazer, V., Walsh, H., Braham, R., Hahn, C.M., Mazik, P., and McIntyre, P., 2016, Tumours in white suckers from Lake Michigan tributaries: Pathology and prevalence: Journal of Fish Diseases, v. 40, no. 3, p. 377-393, https://doi.org/10.1111/jfd.12520.","productDescription":"17 p.","startPage":"377","endPage":"393","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-073605","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":34983,"text":"Contaminant Biology Program","active":true,"usgs":true}],"links":[{"id":470636,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/jfd.12520","text":"Publisher Index Page"},{"id":327986,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"40","issue":"3","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2016-08-24","publicationStatus":"PW","scienceBaseUri":"57c54ea1e4b0f2f0cebc9874","chorus":{"doi":"10.1111/jfd.12520","url":"http://dx.doi.org/10.1111/jfd.12520","publisher":"Wiley-Blackwell","authors":"Blazer V S, Walsh H L, Braham R P, Hahn C M, Mazik P, McIntyre P B","journalName":"Journal of Fish Diseases","publicationDate":"8/24/2016","publiclyAccessibleDate":"8/24/2016"},"contributors":{"authors":[{"text":"Blazer, Vicki S. 0000-0001-6647-9614 vblazer@usgs.gov","orcid":"https://orcid.org/0000-0001-6647-9614","contributorId":150384,"corporation":false,"usgs":true,"family":"Blazer","given":"Vicki S.","email":"vblazer@usgs.gov","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":638506,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Walsh, H.L. 0000-0001-6392-4604 hwalsh@usgs.gov","orcid":"https://orcid.org/0000-0001-6392-4604","contributorId":15927,"corporation":false,"usgs":true,"family":"Walsh","given":"H.L.","email":"hwalsh@usgs.gov","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":false,"id":647275,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Braham, R.P.","contributorId":65378,"corporation":false,"usgs":true,"family":"Braham","given":"R.P.","email":"","affiliations":[],"preferred":false,"id":647276,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hahn, C. 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Sediment oxygen demand (SOD) rates in Kansas streams are not well understood. During 2014 and 2015, the U.S. Geological Survey, in cooperation with the Kansas Department of Health and Environment, measured SOD at eight stream sites in eastern Kansas to quantify SOD rates and variability with respect to season, land use, and bottom-sediment characteristics. Sediment oxygen demand rates (SODT) ranged from 0.01 to 3.15 grams per square meter per day at the ambient temperature of the measurements. The summer mean SOD rate was 3.0-times larger than the late fall mean rate, likely because of increased biological activity at warm water temperatures. Given the substantial amount of variability in SOD rates possible within sites, heterogeneity of substrate type is an important consideration when designing SOD studies and interpreting the results. Sediment oxygen demand in eastern Kansas streams was correlated with land use and streambed-sediment characteristics, though the strength of relations varied seasonally. The small number of study sites precluded a more detailed analysis. The effect of basin land use and streambed sediment characteristics on SOD is currently (2016) not well understood, and there may be many contributing factors including basin influences on water quality that affect biogeochemical cycles and the biological communities supported by the stream.
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\"}}]}","contact":"Director, Kansas Water Science Center
U.S. Geological Survey
4821 Quail Crest Place
Lawrence, KS 66049
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California’s vast reservoir system, fed by annual snow-and rainfall, plays an important part in providing water to the State’s human and wildlife population. There are almost 1,300 reservoirs throughout the State, but only approximately 200 of them are considered storage reservoirs, and many of the larger ones are critical components of the Federal Central Valley Project and California State Water Project. Storage reservoirs, such as the ones shown in figure 1, capture winter precipitation for use in California’s dry summer months. In addition to engineered reservoir storage, California also depends on water “stored” in the statewide snowpack, which slowly melts during the course of the summer, to augment the State’s water supply.
Director, California Water Science Center
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, CA 95819
http://ca.water.usgs.gov
The Saline Valley Conservancy District (SVCD) operates wells that supply water to most of the water users in Saline and Gallatin Counties, Illinois. The SVCD wells draw water from a shallow sand and gravel aquifer located in close proximity to an abandoned underground coal mine, several abandoned oil wells, and at least one operational oil well. The aquifer that yields water to the SVCD wells overlies the New Albany Shale, which may be subjected to shale-gas exploration by use of hydraulic fracturing. The SVCD has sought technical assistance from the U.S. Geological Survey to characterize baseline water quality at the SVCD well field so that future changes in water quality (if any) and the cause of those changes (including mine leachate and hydraulic fracturing) can be identified.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds1009","collaboration":"Prepared in cooperation with the Saline Valley Conservancy District","usgsCitation":"Gorczynska, Magdalena, and Kay, R.T., 2016, Groundwater quality at the Saline Valley Conservancy District well field, Gallatin County, Illinois: U.S. Geological Survey Data Series 1009, 13 p., https://dx.doi.org/10.3133/ds1009.","productDescription":"iv, 13 p.","numberOfPages":"22","onlineOnly":"Y","ipdsId":"IP-068668","costCenters":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"links":[{"id":327989,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/1009/coverthb.jpg"},{"id":327990,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/1009/ds1009.pdf","text":"Report","size":"300 kB","linkFileType":{"id":1,"text":"pdf"},"description":"DS 1009"}],"country":"United States","state":"Illinois","county":"Gallatin County","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-88.0897,37.8995],[-88.0882,37.8966],[-88.0864,37.8931],[-88.0841,37.8904],[-88.0831,37.8892],[-88.0818,37.8876],[-88.079,37.884],[-88.0767,37.8803],[-88.0739,37.8766],[-88.0721,37.8735],[-88.0689,37.8691],[-88.0666,37.8652],[-88.0625,37.8598],[-88.0558,37.8557],[-88.0499,37.8531],[-88.0411,37.8495],[-88.0329,37.8469],[-88.0304,37.8457],[-88.0278,37.8444],[-88.0251,37.8417],[-88.024,37.8389],[-88.0239,37.8363],[-88.0239,37.8357],[-88.0252,37.8317],[-88.0262,37.8306],[-88.0267,37.8302],[-88.0276,37.8296],[-88.0293,37.829],[-88.0326,37.8276],[-88.0331,37.8274],[-88.0377,37.8265],[-88.0418,37.826],[-88.0474,37.8265],[-88.0503,37.8271],[-88.0523,37.8276],[-88.0588,37.8303],[-88.0652,37.8325],[-88.0677,37.8334],[-88.0723,37.8349],[-88.0758,37.8355],[-88.0793,37.835],[-88.0822,37.8336],[-88.0833,37.8318],[-88.0838,37.829],[-88.0837,37.8261],[-88.0836,37.8251],[-88.0821,37.8211],[-88.0819,37.8205],[-88.0794,37.8155],[-88.0772,37.8118],[-88.0763,37.8106],[-88.0711,37.8077],[-88.0659,37.8059],[-88.0612,37.8053],[-88.0566,37.8062],[-88.053,37.8075],[-88.0501,37.8093],[-88.049,37.8097],[-88.0466,37.8106],[-88.0421,37.8117],[-88.0413,37.8118],[-88.0367,37.8119],[-88.0351,37.8116],[-88.0333,37.8111],[-88.031,37.8098],[-88.03,37.8086],[-88.0292,37.8072],[-88.0281,37.804],[-88.0277,37.8023],[-88.027,37.799],[-88.03,37.795],[-88.0309,37.7919],[-88.0316,37.7881],[-88.0326,37.7829],[-88.0331,37.7805],[-88.0352,37.7698],[-88.0408,37.7619],[-88.0417,37.7606],[-88.0531,37.7445],[-88.0644,37.7365],[-88.0836,37.728],[-88.0854,37.7271],[-88.0953,37.7227],[-88.1036,37.7183],[-88.1182,37.7105],[-88.1317,37.6979],[-88.1478,37.6776],[-88.1528,37.67],[-88.1541,37.6672],[-88.1552,37.6645],[-88.1565,37.6591],[-88.1566,37.6564],[-88.1566,37.6541],[-88.1567,37.6484],[-88.1534,37.638],[-88.1527,37.6358],[-88.1425,37.6132],[-88.1414,37.6106],[-88.1371,37.5961],[-88.1335,37.5836],[-88.1301,37.579],[-88.1233,37.5717],[-88.1354,37.5773],[-88.1481,37.5765],[-88.1528,37.5775],[-88.1568,37.5789],[-88.1647,37.5912],[-88.167,37.5935],[-88.1699,37.5958],[-88.1907,37.6024],[-88.2075,37.6025],[-88.2604,37.6031],[-88.3719,37.6028],[-88.3718,37.6894],[-88.3721,37.7039],[-88.3739,37.7783],[-88.3732,37.8648],[-88.3742,37.9097],[-88.3311,37.9102],[-88.3071,37.9123],[-88.2634,37.9118],[-88.2482,37.9121],[-88.2295,37.9128],[-88.2126,37.9117],[-88.1362,37.9127],[-88.1349,37.9173],[-88.1193,37.9089],[-88.11,37.9056],[-88.106,37.902],[-88.1026,37.8979],[-88.0998,37.8933],[-88.0975,37.8919],[-88.0951,37.8923],[-88.0897,37.8995]]]},\"properties\":{\"name\":\"Gallatin\",\"state\":\"IL\"}}]}","contact":"Director, Illinois Water Science Center
U.S. Geological Survey
405 N Goodwin
Urbana, Illinois 61801
Dam removal and other fish barrier removal projects in western North America are assumed to boost freshwater productivity via the transport of marine-derived nutrients from recolonizing Pacific salmon (Oncorhynchus spp.). In anticipation of the removal of two hydroelectric dams on the Elwha River in Washington State, we tested this hypothesis with a salmon carcass addition experiment. Our study was designed to examine how background nutrient dynamics and benthic food webs vary seasonally, and how these features respond to salmon subsidies. We conducted our experiment in six side channels of the Elwha River, each with a spatially paired reference and treatment reach. Each reach was sampled on multiple occasions from October 2007 to August 2008, before and after carcass placement. We evaluated nutrient limitation status; measured water chemistry, periphyton, benthic invertebrates, and juvenile rainbow trout (O. mykiss) response; and traced salmon-derived nutrient uptake using stable isotopes. Outside of winter, algal accrual was limited by both nitrogen and phosphorous and remained so even in the presence of salmon carcasses. One month after salmon addition, dissolved inorganic nitrogen levels doubled in treatment reaches. Two months after addition, benthic algal accrual was significantly elevated. We detected no changes in invertebrate or fish metrics, with the exception of 15N enrichment. Natural seasonal variability was greater than salmon effects for the majority of our response metrics. Yet seasonality and synchronicity of nutrient supply and demand are often overlooked in nutrient enhancement studies. Timing and magnitude of salmon-derived nitrogen utilization suggest that uptake of dissolved nutrients was favored over direct consumption of carcasses. The highest proportion of salmon-derived nitrogen was incorporated by herbivores (18–30%) and peaked 1–2 months after carcass addition. Peak nitrogen enrichment in predators (11–16%) occurred 2–3 months after addition. All taxa returned to background δ15N levels by 7 months. Since this study was conducted, both dams on the Elwha River were removed over 2011–2014 to open over 90% of the basin to anadromous fishes. We anticipate that as the full portfolio of salmon species expands through the basin, nutrient supply and demand will come into better balance.
","language":"English","publisher":"Ecological Society of America","publisherLocation":"Washington, D.C.","doi":"10.1002/ecs2.1422","usgsCitation":"Morley, S., Coe, H., Duda, J., Dunphy, L., McHenry, M., Beckman, B., Elofson, M., Sampson, E.M., and Ward, L., 2016, Seasonal variation exceeds effects of salmon carcass additions on benthic food webs in the Elwha River: Ecosphere, v. 7, no. 8, https://doi.org/10.1002/ecs2.1422.","productDescription":"19 p.","startPage":"article e01422","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-065535","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":470640,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.1422","text":"Publisher Index Page"},{"id":327875,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"7","issue":"8","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2016-08-18","publicationStatus":"PW","scienceBaseUri":"57c15a21e4b0f2f0ceb8baa3","contributors":{"authors":[{"text":"Morley, S.A.","contributorId":49619,"corporation":false,"usgs":true,"family":"Morley","given":"S.A.","email":"","affiliations":[],"preferred":false,"id":647116,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Coe, H.J.","contributorId":174061,"corporation":false,"usgs":false,"family":"Coe","given":"H.J.","email":"","affiliations":[{"id":27351,"text":"Ocean Associates, Seattle, WA","active":true,"usgs":false}],"preferred":false,"id":647118,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Duda, J.J. 0000-0001-7431-8634","orcid":"https://orcid.org/0000-0001-7431-8634","contributorId":105073,"corporation":false,"usgs":true,"family":"Duda","given":"J.J.","affiliations":[],"preferred":false,"id":647115,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dunphy, L.S.","contributorId":174060,"corporation":false,"usgs":false,"family":"Dunphy","given":"L.S.","email":"","affiliations":[{"id":27350,"text":"School of Aquatic and Fishery Sciences, UW, Seattle, WA","active":true,"usgs":false}],"preferred":false,"id":647117,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McHenry, M.L.","contributorId":29476,"corporation":false,"usgs":true,"family":"McHenry","given":"M.L.","email":"","affiliations":[],"preferred":false,"id":647119,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Beckman, B.R.","contributorId":51941,"corporation":false,"usgs":true,"family":"Beckman","given":"B.R.","email":"","affiliations":[],"preferred":false,"id":647120,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Elofson, M.","contributorId":174064,"corporation":false,"usgs":false,"family":"Elofson","given":"M.","affiliations":[{"id":27352,"text":"Natural Resources Dept., Lower Elwha Klallam Tribe, Port Angeles, WA","active":true,"usgs":false}],"preferred":false,"id":647121,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Sampson, E. M.","contributorId":174139,"corporation":false,"usgs":false,"family":"Sampson","given":"E.","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":647122,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Ward, L.","contributorId":30934,"corporation":false,"usgs":true,"family":"Ward","given":"L.","affiliations":[],"preferred":false,"id":647123,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70175900,"text":"ofr20161139 - 2016 - Water-surface elevation and discharge measurement data for the Red River of the North and its tributaries near Fargo, North Dakota, water years 2014–15","interactions":[],"lastModifiedDate":"2017-10-12T19:55:27","indexId":"ofr20161139","displayToPublicDate":"2016-08-25T00:00:00","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":"2016-1139","title":"Water-surface elevation and discharge measurement data for the Red River of the North and its tributaries near Fargo, North Dakota, water years 2014–15","docAbstract":"The U.S. Geological Survey, in cooperation with the Fargo Diversion Board of Authority, collected water-surface elevations during a range of discharges needed for calibration of hydrologic and hydraulic models for specific reaches of interest in water years 2014–15. These water-surface elevation and discharge measurement data were collected for design planning of diversion structures on the Red River of the North and Wild Rice River and the aqueduct/diversion structures on the Sheyenne and Maple Rivers. The Red River of the North and Sheyenne River reaches were surveyed six times, and discharges ranged from 276 to 6,540 cubic feet per second and from 166 to 2,040 cubic feet per second, respectively. The Wild Rice River reach also was surveyed six times during 2014 and 2015, and discharges ranged from 13 to 1,550 cubic feet per second. The Maple River reach was surveyed four times, and discharges ranged from 16.4 to 633 cubic feet per second. Water-surface elevation differences from upstream to downstream in the reaches ranged from 0.33 feet in the Red River of the North reach to 9.4 feet in the Maple River reach.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161139","collaboration":"Prepared in cooperation with the Fargo Diversion Board of Authority","usgsCitation":"Damschen, W.C., and Galloway, J.M., 2016, Water-surface elevation and discharge measurement data for the Red River of the North and its tributaries near Fargo, North Dakota, water years 2014–15: U.S. Geological Survey Open-File Report 2016–1139, 16 p., https://dx.doi.org/10.3133/ofr20161139.","productDescription":"iv, 16 p.","numberOfPages":"24","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-074364","costCenters":[{"id":478,"text":"North Dakota Water Science Center","active":true,"usgs":true},{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"links":[{"id":327822,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1139/coverthb.jpg"},{"id":327823,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1139/ofr20161139.pdf","text":"Report","size":"1.74 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016–1139"}],"country":"United States","state":"North Dakota","city":"Fargo","otherGeospatial":"Maple River, Red River of the North, Sheyenne River, Wild Rice River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -97,\n 46.6667\n ],\n [\n -97,\n 47.10378387099161\n ],\n [\n -96.6667,\n 47.10378387099161\n ],\n [\n -96.6667,\n 46.6667\n ],\n [\n -97,\n 46.6667\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, North Dakota Water Science Center
U.S. Geological Survey
821 E Interstate Ave
Bismarck, ND 58503
Large floodplain rivers have internal structures shaped by directions and rates of water movement. In a previous study, we showed that spatial variation in local current velocities and degrees of hydrological exchange creates a patch-work mosaic of nitrogen and phosphorus concentrations and ratios in the Upper Mississippi River. Here, we used long-term fish and limnological data sets to test the hypothesis that fish communities differ between the previously identified patches defined by high or low nitrogen to phosphorus ratios (TN:TP) and to determine the extent to which select limnological covariates might explain those differences. Species considered as habitat generalists were common in both patch types but were at least 2 times as abundant in low TN:TP patches. Dominance by these species resulted in lower diversity in low TN:TP patches, whereas an increased relative abundance of a number of rheophilic (flow-dependent) species resulted in higher diversity and a more even species distribution in high TN:TP patches. Of the limnological variables considered, the strongest predictor of fish species assemblage and diversity was water flow velocity, indicating that spatial patterns in water-mediated connectivity may act as the main driver of both local nutrient concentrations and fish community composition in these reaches. The coupling among hydrology, biogeochemistry, and biodiversity in these river reaches suggests that landscape-scale restoration projects that manipulate hydrogeomorphic patterns may also modify the spatial mosaic of nutrients and fish communities. Published 2016. This article is a U.S. Government work and is in the public domain in the USA.
","language":"English","publisher":"Wiley","doi":"10.1002/rra.3026","usgsCitation":"De Jager, N.R., and Houser, J.N., 2016, Patchiness in a large floodplain river: Associations among hydrology, nutrients, and fish communities: River Research and Applications, v. 32, no. 9, p. 1915-1926, https://doi.org/10.1002/rra.3026.","productDescription":"12 p.","startPage":"1915","endPage":"1926","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-062928","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":327828,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"32","issue":"9","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2016-03-31","publicationStatus":"PW","scienceBaseUri":"57c6a086e4b0f2f0cebdb037","contributors":{"authors":[{"text":"De Jager, Nathan R. 0000-0002-6649-4125 ndejager@usgs.gov","orcid":"https://orcid.org/0000-0002-6649-4125","contributorId":3717,"corporation":false,"usgs":true,"family":"De Jager","given":"Nathan","email":"ndejager@usgs.gov","middleInitial":"R.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":647011,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Houser, Jeffrey N. 0000-0003-3295-3132 jhouser@usgs.gov","orcid":"https://orcid.org/0000-0003-3295-3132","contributorId":2769,"corporation":false,"usgs":true,"family":"Houser","given":"Jeffrey","email":"jhouser@usgs.gov","middleInitial":"N.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":647012,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70176067,"text":"70176067 - 2016 - Reservoirs and water management influence fish mercury concentrations in the western United States and Canada","interactions":[],"lastModifiedDate":"2018-08-07T12:25:42","indexId":"70176067","displayToPublicDate":"2016-08-24T16:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Reservoirs and water management influence fish mercury concentrations in the western United States and Canada","docAbstract":"Anthropogenic manipulation of aquatic habitats can profoundly alter mercury (Hg) cycling and bioaccumulation. The impoundment of fluvial systems is among the most common habitat manipulations and is known to increase fish Hg concentrations immediately following impoundment. However, it is not well understood how Hg concentrations differ between reservoirs and lakes at large spatial and temporal scales or how reservoir management influences fish Hg concentrations. This study evaluated total Hg (THg) concentrations in 64,386 fish from 883 reservoirs and 1387 lakes, across the western United States and Canada, to assess differences between reservoirs and lakes, as well as the influence of reservoir management on fish THg concentrations. Fish THg concentrations were 1.4-fold higher in reservoirs (0.13 ± 0.011 μg/g wet weight ± standard error) than lakes (0.09 ± 0.006), though this difference varied among ecoregions. Fish THg concentrations were 1.5- to 2.6-fold higher in reservoirs than lakes of the North American Deserts, Northern Forests, and Mediterranean California ecoregions, but did not differ between reservoirs and lakes in four other ecoregions. Fish THg concentrations peaked in three-year-old reservoirs then rapidly declined in 4–12 year old reservoirs. Water management was particularly important in influencing fish THg concentrations, which were up to 11-times higher in reservoirs with minimum water storage occurring in May, June, or July compared to reservoirs with minimum storage occurring in other months. Between-year changes in maximum water storage strongly influenced fish THg concentrations, but within-year fluctuations in water levels did not influence fish THg concentrations. Specifically, fish THg concentrations increased up to 3.2-fold over the range of between-year changes in maximum water storage in all ecoregions except Mediterranean California. These data highlight the role of reservoir creation and management in influencing fish THg concentrations and suggest that water management may provide an effective means of mitigating Hg bioaccumulation in some reservoirs.
","language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam","doi":"10.1016/j.scitotenv.2016.03.050","usgsCitation":"Willacker, J.J., Eagles-Smith, C.A., Lutz, M.A., Tate, M., Lepak, J.M., and Ackerman, J., 2016, Reservoirs and water management influence fish mercury concentrations in the western United States and Canada: Science of the Total Environment, v. 568, p. 739-748, https://doi.org/10.1016/j.scitotenv.2016.03.050.","productDescription":"10 p.","startPage":"739","endPage":"748","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-070755","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":29789,"text":"John Wesley Powell Center for Analysis and Synthesis","active":true,"usgs":true},{"id":34983,"text":"Contaminant Biology Program","active":true,"usgs":true}],"links":[{"id":470641,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2016.03.050","text":"Publisher Index Page"},{"id":327818,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","volume":"568","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57c6a089e4b0f2f0cebdb047","chorus":{"doi":"10.1016/j.scitotenv.2016.03.050","url":"http://dx.doi.org/10.1016/j.scitotenv.2016.03.050","publisher":"Elsevier BV","authors":"Willacker James J., Eagles-Smith Collin A., Lutz Michelle A., Tate Michael T., Lepak Jesse M., Ackerman Joshua T.","journalName":"Science of The Total Environment","publicationDate":"10/2016"},"contributors":{"authors":[{"text":"Willacker, James J. jwillacker@usgs.gov","contributorId":5614,"corporation":false,"usgs":true,"family":"Willacker","given":"James","email":"jwillacker@usgs.gov","middleInitial":"J.","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":true,"id":646984,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Eagles-Smith, Collin A. 0000-0003-1329-5285 ceagles-smith@usgs.gov","orcid":"https://orcid.org/0000-0003-1329-5285","contributorId":505,"corporation":false,"usgs":true,"family":"Eagles-Smith","given":"Collin","email":"ceagles-smith@usgs.gov","middleInitial":"A.","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":646983,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lutz, Michelle A. malutz@usgs.gov","contributorId":131020,"corporation":false,"usgs":true,"family":"Lutz","given":"Michelle","email":"malutz@usgs.gov","middleInitial":"A.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":false,"id":646985,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Tate, Michael T. 0000-0003-1525-1219 mttate@usgs.gov","orcid":"https://orcid.org/0000-0003-1525-1219","contributorId":3144,"corporation":false,"usgs":true,"family":"Tate","given":"Michael T.","email":"mttate@usgs.gov","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":646986,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lepak, Jesse M.","contributorId":172156,"corporation":false,"usgs":false,"family":"Lepak","given":"Jesse","email":"","middleInitial":"M.","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":646988,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ackerman, Joshua T. 0000-0002-3074-8322 jackerman@usgs.gov","orcid":"https://orcid.org/0000-0002-3074-8322","contributorId":147078,"corporation":false,"usgs":true,"family":"Ackerman","given":"Joshua T.","email":"jackerman@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":646987,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70176068,"text":"70176068 - 2016 - Evaluation of a method for quantifying eugenol concentrations in the fillet tissue from freshwater fish species","interactions":[],"lastModifiedDate":"2016-08-24T15:01:37","indexId":"70176068","displayToPublicDate":"2016-08-24T10:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2143,"text":"Journal of AOAC International","active":true,"publicationSubtype":{"id":10}},"title":"Evaluation of a method for quantifying eugenol concentrations in the fillet tissue from freshwater fish species","docAbstract":"AQUI-S 20E® (active ingredient, eugenol; AQUI-S New Zealand Ltd, Lower Hutt, New Zealand) is being pursued for approval as an immediate-release sedative in the United States. A validated method to quantify the primary residue (the marker residue) in fillet tissue from AQUI-S 20E–exposed fish was needed. A method was evaluated for determining concentrations of the AQUI-S 20E marker residue, eugenol, in freshwater fish fillet tissue. Method accuracies from fillet tissue fortified at nominal concentrations of 0.15, 1, and 60 μg/g from six fish species ranged from 88–102%. Within-day and between-day method precisions (% CV) from the fortified tissue were ≤8.4% CV. There were no coextracted compounds from the control fillet tissue of seven fish species that interfered with eugenol analyses. Six compounds used as aquaculture drugs did not interfere with eugenol analyses. The lower limit of quantitation (LLOQ) was 0.012 μg/g. The method was robust, i.e., in most cases, minor changes to the method did not impact method performance. Eugenol was stable in acetonitrile–water (3 + 7, v/v) for at least 14 days, in fillet tissue extracts for 4 days, and in fillet tissue stored at ~ −80°C for at least 84 days.
","language":"English","publisher":"Association of Official Agricultural Chemists (AOAC)","publisherLocation":"Arlington, VA","doi":"10.5740/jaoacint.15-0161","usgsCitation":"Meinertz, J.R., Schreier, T.M., Porcher, S.T., and Smerud, J.R., 2016, Evaluation of a method for quantifying eugenol concentrations in the fillet tissue from freshwater fish species: Journal of AOAC International, v. 99, no. 2, p. 558-564, https://doi.org/10.5740/jaoacint.15-0161.","startPage":"558","endPage":"564","numberOfPages":"7","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-059729","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":327815,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"99","issue":"2","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2019-11-27","publicationStatus":"PW","scienceBaseUri":"57c6a035e4b0f2f0cebdafe2","contributors":{"authors":[{"text":"Meinertz, Jeffery R. 0000-0002-8855-2648 jmeinertz@usgs.gov","orcid":"https://orcid.org/0000-0002-8855-2648","contributorId":2495,"corporation":false,"usgs":true,"family":"Meinertz","given":"Jeffery","email":"jmeinertz@usgs.gov","middleInitial":"R.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":646989,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schreier, Theresa M. 0000-0001-7722-6292 tschreier@usgs.gov","orcid":"https://orcid.org/0000-0001-7722-6292","contributorId":3344,"corporation":false,"usgs":true,"family":"Schreier","given":"Theresa","email":"tschreier@usgs.gov","middleInitial":"M.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":646990,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Porcher, Scott T. sporcher@usgs.gov","contributorId":5030,"corporation":false,"usgs":true,"family":"Porcher","given":"Scott","email":"sporcher@usgs.gov","middleInitial":"T.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":646991,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Smerud, Justin R. 0000-0003-4385-7437 jrsmerud@usgs.gov","orcid":"https://orcid.org/0000-0003-4385-7437","contributorId":5031,"corporation":false,"usgs":true,"family":"Smerud","given":"Justin","email":"jrsmerud@usgs.gov","middleInitial":"R.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":646992,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70189894,"text":"70189894 - 2016 - NHDPlusHR: A national geospatial framework for surface-water information","interactions":[],"lastModifiedDate":"2017-08-06T16:51:06","indexId":"70189894","displayToPublicDate":"2016-08-24T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2126,"text":"JAWRA","active":true,"publicationSubtype":{"id":10}},"title":"NHDPlusHR: A national geospatial framework for surface-water information","docAbstract":"The U.S. Geological Survey is developing a new geospatial hydrographic framework for the United States, called the National Hydrography Dataset Plus High Resolution (NHDPlusHR), that integrates a diversity of the best-available information, robustly supports ongoing dataset improvements, enables hydrographic generalization to derive alternate representations of the network while maintaining feature identity, and supports modern scientific computing and Internet accessibility needs. This framework is based on the High Resolution National Hydrography Dataset, the Watershed Boundaries Dataset, and elevation from the 3-D Elevation Program, and will provide an authoritative, high precision, and attribute-rich geospatial framework for surface-water information for the United States. Using this common geospatial framework will provide a consistent basis for indexing water information in the United States, eliminate redundancy, and harmonize access to, and exchange of water information.
","language":"English","publisher":"American Water Resources Association","doi":"10.1111/1752-1688.12429","usgsCitation":"Viger, R.J., Rea, A.H., Simley, J.D., and Hanson, K.M., 2016, NHDPlusHR: A national geospatial framework for surface-water information: JAWRA, v. 52, no. 4, p. 901-905, https://doi.org/10.1111/1752-1688.12429.","productDescription":"5 p.","startPage":"901","endPage":"905","ipdsId":"IP-074030","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":344609,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"52","issue":"4","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2016-05-20","publicationStatus":"PW","scienceBaseUri":"59882a95e4b05ba66e9ffdda","contributors":{"authors":[{"text":"Viger, Roland J. 0000-0003-2520-714X rviger@usgs.gov","orcid":"https://orcid.org/0000-0003-2520-714X","contributorId":168799,"corporation":false,"usgs":true,"family":"Viger","given":"Roland","email":"rviger@usgs.gov","middleInitial":"J.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":706641,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rea, Alan H. ahrea@usgs.gov","contributorId":1813,"corporation":false,"usgs":true,"family":"Rea","given":"Alan","email":"ahrea@usgs.gov","middleInitial":"H.","affiliations":[{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"preferred":true,"id":706642,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Simley, Jeffrey D. jdsimley@usgs.gov","contributorId":4582,"corporation":false,"usgs":true,"family":"Simley","given":"Jeffrey","email":"jdsimley@usgs.gov","middleInitial":"D.","affiliations":[{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"preferred":true,"id":706643,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hanson, Karen M. khanson@usgs.gov","contributorId":936,"corporation":false,"usgs":true,"family":"Hanson","given":"Karen","email":"khanson@usgs.gov","middleInitial":"M.","affiliations":[{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"preferred":true,"id":706644,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70182790,"text":"70182790 - 2016 - StreamThermal: A software package for calculating thermal metrics from stream temperature data","interactions":[],"lastModifiedDate":"2018-02-28T14:34:01","indexId":"70182790","displayToPublicDate":"2016-08-24T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1657,"text":"Fisheries","onlineIssn":"1548-8446","printIssn":"0363-2415","active":true,"publicationSubtype":{"id":10}},"title":"StreamThermal: A software package for calculating thermal metrics from stream temperature data","docAbstract":"Improving quality and better availability of continuous stream temperature data allows natural resource managers, particularly in fisheries, to understand associations between different characteristics of stream thermal regimes and stream fishes. However, there is no convenient tool to efficiently characterize multiple metrics reflecting stream thermal regimes with the increasing amount of data. This article describes a software program packaged as a library in R to facilitate this process. With this freely-available package, users will be able to quickly summarize metrics that describe five categories of stream thermal regimes: magnitude, variability, frequency, timing, and rate of change. The installation and usage instruction of this package, the definition of calculated thermal metrics, as well as the output format from the package are described, along with an application showing the utility for multiple metrics. We believe this package can be widely utilized by interested stakeholders and greatly assist more studies in fisheries.","language":"English, French, Spanish","publisher":"Taylor & Francis","doi":"10.1080/03632415.2016.1210517","collaboration":"Yin-Phan Tsang; Dana Infante (Michigan State University)\nLizhu Wang (International Joint Commission)\nDarren Thornbrugh (US EPA)","usgsCitation":"Tsang, Y., Infante, D.M., Stewart, J.S., Wang, L., Tingly, R., Thornbrugh, D., Cooper, A., and Wesley, D., 2016, StreamThermal: A software package for calculating thermal metrics from stream temperature data: Fisheries, v. 41, no. 9, p. 548-554, https://doi.org/10.1080/03632415.2016.1210517.","productDescription":"7 p.","startPage":"548","endPage":"554","ipdsId":"IP-064619","costCenters":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"links":[{"id":336746,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"41","issue":"9","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2016-08-24","publicationStatus":"PW","scienceBaseUri":"58b7eba7e4b01ccd5500bb0f","contributors":{"authors":[{"text":"Tsang, Yin-Phan","contributorId":177342,"corporation":false,"usgs":false,"family":"Tsang","given":"Yin-Phan","email":"","affiliations":[],"preferred":false,"id":673753,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Infante, Dana M. 0000-0003-1385-1587","orcid":"https://orcid.org/0000-0003-1385-1587","contributorId":150821,"corporation":false,"usgs":false,"family":"Infante","given":"Dana","email":"","middleInitial":"M.","affiliations":[{"id":18112,"text":"Dept. of Fisheries and Wildlife,","active":true,"usgs":false}],"preferred":false,"id":673754,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stewart, Jana S. 0000-0002-8121-1373 jsstewar@usgs.gov","orcid":"https://orcid.org/0000-0002-8121-1373","contributorId":539,"corporation":false,"usgs":true,"family":"Stewart","given":"Jana","email":"jsstewar@usgs.gov","middleInitial":"S.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":673752,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wang, Lizhu","contributorId":184191,"corporation":false,"usgs":false,"family":"Wang","given":"Lizhu","email":"","affiliations":[{"id":6983,"text":"Michigan DNR","active":true,"usgs":false}],"preferred":false,"id":673755,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Tingly, Ralph","contributorId":184192,"corporation":false,"usgs":false,"family":"Tingly","given":"Ralph","email":"","affiliations":[],"preferred":false,"id":673756,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Thornbrugh, Darren","contributorId":184193,"corporation":false,"usgs":false,"family":"Thornbrugh","given":"Darren","email":"","affiliations":[],"preferred":false,"id":673757,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Cooper, Arthur","contributorId":184194,"corporation":false,"usgs":false,"family":"Cooper","given":"Arthur","affiliations":[],"preferred":false,"id":673758,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Wesley, Daniel","contributorId":184195,"corporation":false,"usgs":false,"family":"Wesley","given":"Daniel","email":"","affiliations":[],"preferred":false,"id":673759,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70175465,"text":"sim3364 - 2016 - Sedimentation survey of Lago Lucchetti, Yauco, Puerto Rico, September 2013–May 2014","interactions":[],"lastModifiedDate":"2016-09-12T09:58:34","indexId":"sim3364","displayToPublicDate":"2016-08-23T17:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3364","title":"Sedimentation survey of Lago Lucchetti, Yauco, Puerto Rico, September 2013–May 2014","docAbstract":"The U.S. Geological Survey conducted a sedimentation survey of Lago Lucchetti, Yauco, Puerto Rico, in 2013–14 in cooperation with the Puerto Rico Aqueduct and Sewer Authority. The survey updated a previous survey, conducted in 2000, and provided accurate information regarding reservoir storage capacity and sedimentation rate using bathymetric techniques and a global positioning system coupled with a depth sounder device. The results of the 2013–14 survey indicated a total storage capacity for Lago Lucchetti of 10.21 million cubic meters and a long-term sedimentation rate loss of 0.16 million cubic meters per year based on the original capacity in 1952. Sediment accumulation was about 10.14 million cubic meters over the life of the reservoir, which represents a storage decrease of about 50 percent of the original capacity in 1952. On the basis of a comparison between the 2013–14 and 2000 surveys, the useful life for Lago Lucchetti is projected to end in 2076.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3364","collaboration":"Prepared in cooperation with the Puerto Rico Aqueduct and Sewer Authority","usgsCitation":"Gómez-Fragoso, Julieta, 2016, Sedimentation survey of Lago Lucchetti, Yauco, Puerto Rico, September 2013–May 2014: U.S. Geological Survey Scientific Investigations Map 3364, 1 sheet, https://dx.doi.org/10.3133/sim3364.","productDescription":"Report: 29 x 32 inches; Data release","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-069514","costCenters":[{"id":156,"text":"Caribbean Water Science Center","active":true,"usgs":true}],"links":[{"id":438559,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7V122WZ","text":"USGS data release","linkHelpText":"Spatial Data for the Sedimentation Survey of Lago Lucchetti, Yauco, Puerto Rico, September 2013-May 2014"},{"id":327268,"rank":3,"type":{"id":30,"text":"Data 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18.104413341539487\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Caribbean-Florida Water Science Center
U.S. Geological Survey
4446 Pet Lane, Suite 108
Lutz, FL 33559
https://www.usgs.gov/water/caribbeanflorida/
A groundwater/surface-water model was constructed and calibrated for the Black Earth Creek watershed in south-central Wisconsin. The model was then run to simulate scenarios representing common societal concerns in the basin, focusing on maintaining a cold-water resource in an urbanizing fringe near its upper stream reaches and minimizing downstream flooding. Although groundwater and surface water are considered a single resource, many hydrologic models simplistically simulate feedback loops between the groundwater system and other hydrologic processes. These feedbacks include timing and rates of evapotranspiration, surface runoff, soil-zone flow, and interactions with the groundwater system; however, computer models can now routinely and iteratively couple the surface-water and groundwater systems—albeit with longer model run times. In this study, preliminary calibrations of uncoupled transient surface-water and steady-state groundwater models were used to form the starting point for final calibration of one transient computer simulation that iteratively couples groundwater and surface water. The computer code GSFLOW (Groundwater/Surface-water FLOW) was used to simulate the coupled hydrologic system; a surface-water model represented hydrologic processes in the atmosphere, at land surface, and within the soil zone, and a groundwater-flow model represented the unsaturated zone, saturated zone, and streams. The coupled GSFLOW model was run on a daily time step during water years 1985–2007. Early simulation times (1985–2000) were used for spin-up to make the simulation results less sensitive to initial conditions specified; the spin-up period was not included in the model calibration. Model calibration used observed heads, streamflows, solar radiation, and snowpack measurements from 2000 to 2007 for history matching. Calibration was performed by using the PEST parameter estimation software suite.
\nSimulated streamflows from the calibrated GSFLOW model and other basin characteristics were used as input to the one-dimensional SNTEMP (Stream-Network TEMPerature) model. SNTEMP was used to simulate daily stream temperature in selected stream reaches in the watershed. The temperature model was calibrated to high-resolution stream temperature time-series data measured in 2005. The calibrated GSFLOW and SNTEMP models were then used to simulate effects of potential climate change for the years 2010 through 2100. An ensemble of climate models and emission scenarios was evaluated. Downscaled climate drivers for the simulation period showed increases in maximum and minimum air temperature. Scenarios of future precipitation, however, did not show a monotonic trend like temperature. Uncertainty in the climate drivers increased with time for both temperature and precipitation.
\nForecasts of potential climate change scenarios showed growing season length increasing by weeks, and both potential and actual evapotranspiration rates increasing appreciably, in response to increasing air temperature. Simulated actual evapotranspiration rates increased less than simulated potential evapotranspiration rates as a result of water limitation in the root zone during the summer high-evapotranspiration period. The hydrologic-system response to climate change was characterized by a reduction in the importance of the snowmelt pulse and an increase in the importance of fall and winter groundwater recharge. The less dynamic hydrologic regime is likely to result in drier soil conditions, with relatively less drying expected in groundwater-fed systems. Groundwater discharge in the current upper cold-water reaches of Black Earth Creek is expected to decrease; flooding in downstream reaches may appreciably increase. The magnitude of changes in forecasted flow and associated groundwater/surface-water interaction is dependent on the General Circulation Model and emission scenario chosen.
\nPotential future changes in air temperature drivers were consistently upward regardless of General Circulation Model and emission scenario selected; thus, simulated stream temperatures are forecast to increase appreciably with future climate. However, the amount of temperature increase was variable. Such uncertainty is reflected in temperature model results, along with uncertainty in the groundwater/surface-water interaction itself. The estimated increase in annual average temperature ranged from approximately 3 to 6 degrees Celsius by 2100 in the upper reaches of Black Earth Creek and 2 to 4 degrees Celsius in reaches farther downstream. As with all forecasts that rely on projections of an unknowable future, the results are best considered to approximate potential outcomes of climate change given the underlying uncertainty.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165091","collaboration":"Prepared in cooperation with the Wisconsin Department of Natural Resources, Village of Cross Plains, Village of Black Earth, Town of Black Earth, Town of Vermont, Village of Mazomanie, and City of Middleton","usgsCitation":"Hunt, R.J., Westenbroek, S.M., Walker, J.F., Selbig, W.R., Regan, R.S., Leaf, A.T., and Saad, D.A., 2016, Simulation of climate change effects on streamflow, groundwater, and stream temperature using GSFLOW and SNTEMP in the Black Earth Creek Watershed, Wisconsin: U.S. Geological Survey Scientific Investigations Report 2016–5091, 117 p., https://dx.doi.org/10.3133/sir20165091.","productDescription":"Report: x, 49 p.; Appendixes: 1–6","startPage":"1","endPage":"117","numberOfPages":"132","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-072633","costCenters":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"links":[{"id":327327,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5091/coverthb.jpg"},{"id":327328,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5091/sir20165091.pdf","text":"Report","size":"8.79 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016–5091"}],"country":"United States","state":"Wisconsin","otherGeospatial":"Black Earth Creek Watershed","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -89.73333333333333,43.06666666666667 ], [ -89.73333333333333,43.18333333333333 ], [ -89.55,43.18333333333333 ], [ -89.55,43.06666666666667 ], [ -89.73333333333333,43.06666666666667 ] ] ] } } ] }","contact":"Director, Wisconsin Water Science Center
U.S. Geological Survey
8505 Research Way
Middleton, Wisconsin 53562
Invasive species such as Asian carps have the potential to travel in the egg, larval, or fry stages from the Des Plaines River (DPR) to the Chicago Sanitary and Ship Canal (CSSC) by way of the network of secondary-permeability features in the dolomite aquifer between these water bodies. Such movement would circumvent the electric fish barrier on the canal and allow Asian carps to travel unimpeded into Lake Michigan. This potential pathway for the spread of Asian carps and other invasive species was evaluated by the U.S. Geological Survey.
The bed of the DPR appears to be in at least partial contact with the exposed bedrock in most of the area from about 1 mile west of Kingery Highway to Romeo Road (the study area). Areas of exposed bedrock are the most likely places for Asian carps to enter the groundwater system from the DPR. Water levels in the DPR typically are about 7–16 feet higher than those in the CSSC in most of the study area. This difference in water level provides the driving force for the potential spread of Asian carps from the DPR to the CSSC by way of groundwater.
Groundwater flow (and potentially invasive-species movement) is through an interconnected network of permeable vertical and horizontal fractures within the Silurian dolomite bedrock. At least some of the fractures are associated with paleo-karst features. Several investigative techniques identified horizontal permeable fractures at about 546–552 feet above the North American Vertical Datum of 1988 within about 55 feet of the CSSC in the focus area between Lemont Road and Interstate 355. The elevation of the bottom of the CSSC in this area is about 551 feet, indicating that a direct conduit for flow of groundwater to the CSSC may be present. Wells further away from the CSSC in this area do not intercept fractures, so the fracture network may not be continuous between the DPR and the CSSC. These data are consistent with field observations of the secondary-permeability network along the CSSC walls, which indicate that the secondary-permeability features are completely filled with Pennsylvanian sediments within a few feet of the canal wall.
Water-level data indicate the potential for flow from the DPR into the Silurian aquifer in the focus area, then from the aquifer to the CSSC. Water-level data also indicate that the fractures within the aquifer in the focus area are hydraulically well connected to the CSSC but not to the DPR, indicating that flow from the DPR to the groundwater system may not be substantial or rapid.
Water-quality data in the CSSC and the DPR show similar values and trends and are affected by diel and longer term variations in climate and precipitation. However, the values and trends in water quality in the groundwater system tended to be substantially different from those in the DPR and the CSSC, indicating that the DPR and the CSSC do not appreciably recharge the groundwater system. Water-quality and flow data do indicate that groundwater discharges to the CSSC in part of the focus area. The absence of substantial hydraulic interaction between the groundwater and the DPR is supported by the absence of detectable concentrations of the dye tracer added to the DPR in groundwater in the focus area, which indicates that water from the DPR requires more than 2 weeks to move into the monitored parts of the groundwater system under approximately typical hydraulic conditions. The totality of the data indicates that there is minimal potential for the inter-basin spread of Asian carps by way of the groundwater pathway between Romeo Road and Stickney, Illinois.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165095","collaboration":"Prepared in cooperation with the U.S. Environmental Protection Agency as part of the Great Lakes Restoration Initiative ","usgsCitation":"Kay, R.T., Mills, P.C., and Jackson, P.R., 2016, Geology, hydrology, water quality, and potential for interbasin invasive-species spread by way of the groundwater pathway near Lemont, Illinois: U.S. Geological Survey Scientific Investigations Report 2016–5095, 91 p., https://dx.doi.org/10.3133/sir20165095.","productDescription":"ix, 91 p.","numberOfPages":"106","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-036386","costCenters":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"links":[{"id":438562,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7HH6H55","text":"USGS data release","linkHelpText":"Spatial distribution of Rhodamine WT dye concentration measured in the Des Plaines River and the Chicago Sanitary and Ship Canal, Chicago, IL in November 2011"},{"id":438561,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7S180KR","text":"USGS data release","linkHelpText":"Acoustic Doppler current profiler velocity data collected in the Chicago Sanitary and Ship Canal in 2010 and 2011 in support of the interbasin transport study for invasive Asian carp"},{"id":438560,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7N877WG","text":"USGS data release","linkHelpText":"Water-quality distribution in the Chicago Sanitary and Ship Canal, USGS towed multiparameter sonde, Daily tow data files (Feb. 25-27, 2010 and March 2-3, 2010)"},{"id":327111,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5095/sir20165095.pdf","text":"Report","size":"13.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5095"},{"id":327110,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5095/coverthb.jpg"}],"country":"United States","state":"Illinois","city":"Lemont","otherGeospatial":"Des Plaines River, Chicago Sanitary and Ship Canal, Illinois Canal and Michigan Canal","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -87.53082275390625,\n 41.43860847395724\n ],\n [\n -88.37677001953125,\n 41.46125371076149\n ],\n [\n -88.37127685546875,\n 42.3179394544685\n ],\n [\n -87.84393310546875,\n 42.309815415686664\n ],\n [\n -87.64068603515625,\n 42.05948945192712\n ],\n [\n -87.53082275390625,\n 41.75287318430239\n ],\n [\n -87.53082275390625,\n 41.43860847395724\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Illinois Water Science Center
U.S. Geological Survey
405 N Goodwin
Urbana, IL 61801
Or visit our Web site at:
http://il.water.usgs.gov
Warming climates are rapidly transforming lake ecosystems worldwide, but the breadth of changes in tropical lakes is poorly documented. Sustainable management of freshwater fisheries and biodiversity requires accounting for historical and ongoing stressors such as climate change and harvest intensity. This is problematic in tropical Africa, where records of ecosystem change are limited and local populations rely heavily on lakes for nutrition. Here, using a ∼1,500-y paleoecological record, we show that declines in fishery species and endemic molluscs began well before commercial fishing in Lake Tanganyika, Africa’s deepest and oldest lake. Paleoclimate and instrumental records demonstrate sustained warming in this lake during the last ∼150 y, which affects biota by strengthening and shallowing stratification of the water column. Reductions in lake mixing have depressed algal production and shrunk the oxygenated benthic habitat by 38% in our study areas, yielding fish and mollusc declines. Late-20th century fish fossil abundances at two of three sites were lower than at any other time in the last millennium and fell in concert with reduced diatom abundance and warming water. A negative correlation between lake temperature and fish and mollusc fossils over the last ∼500 y indicates that climate warming and intensifying stratification have almost certainly reduced potential fishery production, helping to explain ongoing declines in fish catches. Long-term declines of both benthic and pelagic species underscore the urgency of strategic efforts to sustain Lake Tanganyika’s extraordinary biodiversity and ecosystem services.
","language":"English","publisher":"National Academy of Sciences","doi":"10.1073/pnas.1603237113","usgsCitation":"Cohen, A.S., Gergurich, E.L., Kraemer, B.M., McGlue, M., McIntyre, P.B., Russell, J.M., Simmons, J.D., and Swarzenski, P.W., 2016, Climate warming reduces fish production and benthic habitat in Lake Tanganyika, one of the most biodiverse freshwater ecosystems: Proceedings of the National Academy of Sciences, v. 113, no. 34, p. 9563-9568, https://doi.org/10.1073/pnas.1603237113.","productDescription":"6 p.","startPage":"9563","endPage":"9568","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-075949","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":470647,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1073/pnas.1603237113","text":"External 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USA","active":true,"usgs":false}],"preferred":false,"id":649161,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Simmons, Jack D.","contributorId":174741,"corporation":false,"usgs":false,"family":"Simmons","given":"Jack","email":"","middleInitial":"D.","affiliations":[{"id":27505,"text":"Department of Geosciences, University of Arizona, Tucson, AZ 85721 USA","active":true,"usgs":false}],"preferred":false,"id":649162,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Swarzenski, Peter W. 0000-0003-0116-0578 pswarzen@usgs.gov","orcid":"https://orcid.org/0000-0003-0116-0578","contributorId":1070,"corporation":false,"usgs":true,"family":"Swarzenski","given":"Peter","email":"pswarzen@usgs.gov","middleInitial":"W.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":649155,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70175949,"text":"70175949 - 2016 - Antigenic characterization of H3 subtypes of avian influenza A viruses from North America","interactions":[],"lastModifiedDate":"2016-08-22T15:52:31","indexId":"70175949","displayToPublicDate":"2016-08-22T16:45:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":948,"text":"Avian Diseases","active":true,"publicationSubtype":{"id":10}},"title":"Antigenic characterization of H3 subtypes of avian influenza A viruses from North America","docAbstract":"Besides humans, H3 subtypes of influenza A viruses (IAVs) can infect various animal hosts, including avian, swine, equine, canine, and sea mammal species. These H3 viruses are both antigenically and genetically diverse. Here, we characterized the antigenic diversity of contemporary H3 avian IAVs recovered from migratory birds in North America. Hemagglutination inhibition (HI) assays were performed on 37 H3 isolates of avian IAVs recovered from 2007 to 2011 using generated reference chicken sera. These isolates were recovered from samples taken in the Atlantic, Mississippi, Central, and Pacific waterfowl migration flyways. Antisera to all the tested H3 isolates cross-reacted with each other and, to a lesser extent, with those to H3 canine and H3 equine IAVs. Antigenic cartography showed that the largest antigenic distance among the 37 avian IAVs is about four units, and each unit corresponds to a 2 log 2 difference in the HI titer. However, none of the tested H3 IAVs cross-reacted with ferret sera derived from contemporary swine and human IAVs. Our results showed that the H3 avian IAVs we tested lacked significant antigenic diversity, and these viruses were antigenically different from those circulating in swine and human populations. This suggests that H3 avian IAVs in North American waterfowl are antigenically relatively stable.
","language":"English","publisher":"American Association of Avian Pathologists","doi":"10.1637/11086-041015-RegR","usgsCitation":"Bailey, E., Long, L., Zhao, N., Hall, J.S., Baroch, J.A., Nolting, J., Senter, L., Cunningham, F.L., Pharr, G.T., Hanson, L., Slemons, R., DeLiberto, T.J., and Wan, X., 2016, Antigenic characterization of H3 subtypes of avian influenza A viruses from North America: Avian Diseases, v. 60, no. 1s, p. 346-353, https://doi.org/10.1637/11086-041015-RegR.","productDescription":"8 p.","startPage":"346","endPage":"353","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-071562","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":470648,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/4911812","text":"External 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J.","contributorId":145606,"corporation":false,"usgs":false,"family":"DeLiberto","given":"Thomas","email":"","middleInitial":"J.","affiliations":[{"id":16167,"text":"7United States Department of Agriculture, Animal and Plant Health Inspection Service, Wildlife Services, National Wildlife Disease Program, 4101 LaPorte Ave., Fort Collins, CO, United States of America.","active":true,"usgs":false}],"preferred":false,"id":646670,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Wan, Xiu-Feng","contributorId":173959,"corporation":false,"usgs":false,"family":"Wan","given":"Xiu-Feng","email":"","affiliations":[{"id":17848,"text":"Mississippi State University","active":true,"usgs":false}],"preferred":false,"id":646671,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}} ,{"id":70175924,"text":"70175924 - 2016 - Transport of atrazine versus bromide and δO18 in sand","interactions":[],"lastModifiedDate":"2018-02-13T10:26:52","indexId":"70175924","displayToPublicDate":"2016-08-22T09:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3728,"text":"Water, Air, & Soil Pollution","onlineIssn":"1573-2932","printIssn":"0049-6979","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Transport of atrazine versus bromide and δO18 in sand","title":"Transport of atrazine versus bromide and δO18 in sand","docAbstract":"The objective of this research was to determine the process of atrazine transport compared to bromide and δO18 transport in sands near Denver. Three 1.5 × 2 × 1.5-m plots were installed and allowed to equilibrate for 2 years before research initiation and were instrumented with 1.5 × 2-m zero-tension pan lysimeters installed at 1.5-m depths. Additionally, each plot was instrumented with suction lysimeters, tensiometers, time domain reflectometry (TDR) moisture probes, and thermocouples (to measure soil temperature) at 15-cm depth increments. All plots were enclosed with a raised frame (of 8-cm height) to prevent surface runoff. During the 2-year period before research began, all suction and pan lysimeters were purged monthly and were sampled for fluids immediately prior to atrazine and KBr application to obtain background concentrations. Atrazine illustrated little movement until after a significant rainfall event, which peaked concentrations at depths of about 90 to 135 cm. Both Br− and δO18 moved rapidly through the soil, probably owing to soil porosity and anion exclusion for Br−. Concentrations of atrazine exceeding 5.0 μL−1 were observed with depth (90 to 150 cm) after several months. It appears that significant rainfall events were a key factor in the movement of atrazine in the sand, which allowed the chemicals to move to greater depths and thus avoid generally found biodegradation processes.
","language":"English","publisher":"Kluwer Academic Publishers","doi":"10.1007/s11270-016-2983-z","usgsCitation":"Tindall, J.A., and Friedel, M.J., 2016, Transport of atrazine versus bromide and δO18 in sand: Water, Air, & Soil Pollution, v. 227, p. 1-11, https://doi.org/10.1007/s11270-016-2983-z.","productDescription":"Article 294; 11 p.","startPage":"1","endPage":"11","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-076528","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":327128,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"227","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2016-08-02","publicationStatus":"PW","scienceBaseUri":"57bc141be4b03fd6b7dd6a73","contributors":{"authors":[{"text":"Tindall, James A. 0000-0002-0940-1586 jtindall@usgs.gov","orcid":"https://orcid.org/0000-0002-0940-1586","contributorId":2529,"corporation":false,"usgs":true,"family":"Tindall","given":"James","email":"jtindall@usgs.gov","middleInitial":"A.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":646555,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Friedel, Michael J. 0000-0002-5060-3999 mfriedel@usgs.gov","orcid":"https://orcid.org/0000-0002-5060-3999","contributorId":595,"corporation":false,"usgs":true,"family":"Friedel","given":"Michael","email":"mfriedel@usgs.gov","middleInitial":"J.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":646556,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70169908,"text":"70169908 - 2016 - Spatial differences in hydrologic characteristics and water chemistry of a temperate coastal plain peatland: The Great Dismal Swamp, USA","interactions":[],"lastModifiedDate":"2019-12-14T06:26:41","indexId":"70169908","displayToPublicDate":"2016-08-19T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Spatial differences in hydrologic characteristics and water chemistry of a temperate coastal plain peatland: The Great Dismal Swamp, USA","docAbstract":"Spatial differences in hydrologic processes and geochemistry across forested peatlands control the response of the wetland-community species and resiliency to natural and anthropogenic disturbances. Knowing these controls is essential to effectively managing peatlands as resilient wetland habitats. The Great Dismal Swamp is a 45,325 hectare peatland in the Atlantic Coastal Plain of Virginia and North Carolina, USA, managed by the U.S. Fish and Wildlife Service. The existing forest-species distribution is a product of timber harvesting, hydrologic alteration by canal and road construction, and wildfires. Since 2009, studies of hydrologic and geochemical controls have expanded knowledge of groundwater flow paths, water chemistry, response to precipitation events, and characteristics of the peat. Dominant hydrologic and geochemical controls include (1) the gradual slope in land surface, (2) vertical differences in the hydraulic characteristics of the peat, (3) the proximity of lateral groundwater and small stream inflows from uplands, (4) the presence of an extensive canal and road network, and (5) small, adjustable-height dams on the canals. Although upland sources provide some surface water and lateral groundwater inflow to western parts of the swamp, direct groundwater recharge by precipitation is the major source of water throughout the swamp and the only source in many areas. Additionally, the proximity and type of upland water sources affect water levels and nutrient concentrations in canal water and groundwater. Where streams are a dominant upland source, variations in groundwater levels and nutrient concentrations are greater than where recharge by precipitation is the primary water source. Where upland groundwater is a dominant source, water levels are more stable. Because the species distribution of forest communities in the Swamp is strongly influenced by these controls, swamp managers are beginning to incorporate this knowledge into forest, water, and fire management plans.