Ethiopia experiences significant climate-induced drought and stress on crop and livestock productivity, contributing to widespread food insecurity. Here, we present subseasonal crop water stress analyses that indicate degrading, growing conditions along Ethiopia’s eastern highlands, including productive and populated highland regions. These seasonally shifting areas of increasing water stress stretch from the north to south across eastern Ethiopia, intersecting regions of acute food insecurity and/or high population. Crop model simulations indicate that between 1982 and 2014, parts of eastern Amhara and eastern Oromia experienced increasing water deficits during the critical sowing, flowering, and ripening periods of crop growth. These trends occurred while population in these regions increased by 143% between 2000 and 2015. These areas of enhanced crop water stress in south-central Ethiopia coincide with regions of high population growth and ongoing crop extensification. Conversely, large regions of relatively unpopulated western Ethiopia are becoming wetter. These areas may therefore be good targets for agricultural development.
Freshwater mussels, one of the most imperiled groups of animals in the world, are generally underrepresented in toxicity databases used for the development of ambient water quality criteria and other environmental guidance values. Acute 96-h toxicity tests were conducted to evaluate the sensitivity of 5 species of juvenile mussels from 2 families and 4 tribes to 10 chemicals (ammonia, metals, major ions, and organic compounds) and to screen 10 additional chemicals (mainly organic compounds) with a commonly tested mussel species, fatmucket (Lampsilis siliquoidea). In the multi-species study, median effect concentrations (EC50s) among the 5 species differed by a factor of ≤2 for chloride, potassium, sulfate, and zinc; a factor of ≤5 for ammonia, chromium, copper, and nickel; and factors of 6 and 12 for metolachlor and alachlor, respectively, indicating that mussels representing different families or tribes had similar sensitivity to most of the tested chemicals, regardless of modes of action. There was a strong linear relationship between EC50s for fatmucket and the other 4 mussel species across the 10 chemicals (r2 = 0.97, slope close to 1.0), indicating that fatmucket was similar to other mussel species; thus, this commonly tested species can be a good surrogate for protecting other mussels in acute exposures. The sensitivity of juvenile fatmucket among different populations or cultured from larvae of wild adults and captive-cultured adults was also similar in acute exposures to copper or chloride, indicating captive-cultured adult mussels can reliably be used to reproduce juveniles for toxicity testing. In compiled databases for all freshwater species, 1 or more mussel species were among the 4 most sensitive species for alachlor, ammonia, chloride, potassium, sulfate, copper, nickel, and zinc; therefore, the development of water quality criteria and other environmental guidance values for these chemicals should reflect the sensitivity of mussels. In contrast, the EC50s of fatmucket tested in the single-species study were in the high percentiles (>75th) of species sensitivity distributions for 6 of 7 organic chemicals, indicating mussels might be relatively insensitive to organic chemicals in acute exposures.
","language":"English","publisher":"SETAC Press","doi":"10.1002/etc.3642","usgsCitation":"Wang, N., Ivey, C.D., Ingersoll, C.G., Brumbaugh, W.G., Alvarez, D., Hammer, E.J., Bauer, C.R., Augspurger, T., Raimondo, S., and Barnhart, M., 2017, Acute sensitivity of a broad range of freshwater mussels to chemicals with different modes of toxic action: Environmental Toxicology and Chemistry, v. 36, no. 3, p. 786-796, https://doi.org/10.1002/etc.3642.","productDescription":"11 p.","startPage":"786","endPage":"796","ipdsId":"IP-077267","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":469990,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/8220997","text":"External Repository"},{"id":338421,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"36","issue":"3","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2016-10-04","publicationStatus":"PW","scienceBaseUri":"58da2517e4b0543bf7fda7ec","contributors":{"authors":[{"text":"Wang, Ning 0000-0002-2846-3352 nwang@usgs.gov","orcid":"https://orcid.org/0000-0002-2846-3352","contributorId":2818,"corporation":false,"usgs":true,"family":"Wang","given":"Ning","email":"nwang@usgs.gov","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":686402,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ivey, Chris D. 0000-0002-0485-7242 civey@usgs.gov","orcid":"https://orcid.org/0000-0002-0485-7242","contributorId":3308,"corporation":false,"usgs":true,"family":"Ivey","given":"Chris","email":"civey@usgs.gov","middleInitial":"D.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":686403,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ingersoll, Christopher G. 0000-0003-4531-5949 cingersoll@usgs.gov","orcid":"https://orcid.org/0000-0003-4531-5949","contributorId":2071,"corporation":false,"usgs":true,"family":"Ingersoll","given":"Christopher","email":"cingersoll@usgs.gov","middleInitial":"G.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":686404,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brumbaugh, William G. 0000-0003-0081-375X bbrumbaugh@usgs.gov","orcid":"https://orcid.org/0000-0003-0081-375X","contributorId":493,"corporation":false,"usgs":true,"family":"Brumbaugh","given":"William","email":"bbrumbaugh@usgs.gov","middleInitial":"G.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":686405,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Alvarez, David 0000-0002-6918-2709 dalvarez@usgs.gov","orcid":"https://orcid.org/0000-0002-6918-2709","contributorId":150499,"corporation":false,"usgs":true,"family":"Alvarez","given":"David","email":"dalvarez@usgs.gov","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":686406,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hammer, Edward J.","contributorId":150723,"corporation":false,"usgs":false,"family":"Hammer","given":"Edward","email":"","middleInitial":"J.","affiliations":[{"id":18077,"text":"U. S. Environmental Protection Agency, Region 5, Water Quality Branch, Chicago, Illinois","active":true,"usgs":false}],"preferred":false,"id":686407,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bauer, Candice R.","contributorId":150724,"corporation":false,"usgs":false,"family":"Bauer","given":"Candice","email":"","middleInitial":"R.","affiliations":[{"id":18077,"text":"U. S. Environmental Protection Agency, Region 5, Water Quality Branch, Chicago, Illinois","active":true,"usgs":false}],"preferred":false,"id":686408,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Augspurger, Tom","contributorId":189894,"corporation":false,"usgs":false,"family":"Augspurger","given":"Tom","email":"","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":686409,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Raimondo, Sandy","contributorId":150748,"corporation":false,"usgs":false,"family":"Raimondo","given":"Sandy","email":"","affiliations":[{"id":18090,"text":"U.S. Environmental Protection Agency, Gulf Ecology Division, Gulf Breeze, FL","active":true,"usgs":false}],"preferred":false,"id":686410,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Barnhart, M.Christopher","contributorId":189895,"corporation":false,"usgs":false,"family":"Barnhart","given":"M.Christopher","affiliations":[],"preferred":false,"id":686411,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70185604,"text":"70185604 - 2017 - Modeling nonbreeding distributions of shorebirds and waterfowl in response to climate change","interactions":[],"lastModifiedDate":"2017-03-24T13:34:54","indexId":"70185604","displayToPublicDate":"2017-03-24T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Modeling nonbreeding distributions of shorebirds and waterfowl in response to climate change","docAbstract":"To identify areas on the landscape that may contribute to a robust network of conservation areas, we modeled the probabilities of occurrence of several en route migratory shorebirds and wintering waterfowl in the southern Great Plains of North America, including responses to changing climate. We predominantly used data from the eBird citizen-science project to model probabilities of occurrence relative to land-use patterns, spatial distribution of wetlands, and climate. We projected models to potential future climate conditions using five representative general circulation models of the Coupled Model Intercomparison Project 5 (CMIP5). We used Random Forests to model probabilities of occurrence and compared the time periods 1981–2010 (hindcast) and 2041–2070 (forecast) in “model space.” Projected changes in shorebird probabilities of occurrence varied with species-specific general distribution pattern, migration distance, and spatial extent. Species using the western and northern portion of the study area exhibited the greatest likelihoods of decline, whereas species with more easterly occurrences, mostly long-distance migrants, had the greatest projected increases in probability of occurrence. At an ecoregional extent, differences in probabilities of shorebird occurrence ranged from −0.015 to 0.045 when averaged across climate models, with the largest increases occurring early in migration. Spatial shifts are predicted for several shorebird species. Probabilities of occurrence of wintering Mallards and Northern Pintail are predicted to increase by 0.046 and 0.061, respectively, with northward shifts projected for both species. When incorporated into partner land management decision tools, results at ecoregional extents can be used to identify wetland complexes with the greatest potential to support birds in the nonbreeding season under a wide range of future climate scenarios.
","language":"English","publisher":"Wiley","doi":"10.1002/ece3.2755","usgsCitation":"Reese, G.C., and Skagen, S., 2017, Modeling nonbreeding distributions of shorebirds and waterfowl in response to climate change: Ecology and Evolution, v. 7, no. 5, p. 1497-1513, https://doi.org/10.1002/ece3.2755.","productDescription":"17 p.","startPage":"1497","endPage":"1513","ipdsId":"IP-073714","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":469993,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.2755","text":"Publisher Index Page"},{"id":338301,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Great Plains Landscape Conservation Cooperative","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -106.01806640624999,\n 29.649868677972304\n ],\n [\n -95.47119140625,\n 29.649868677972304\n ],\n [\n -95.47119140625,\n 43.43696596521823\n ],\n [\n -106.01806640624999,\n 43.43696596521823\n ],\n [\n -106.01806640624999,\n 29.649868677972304\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"7","issue":"5","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2017-02-07","publicationStatus":"PW","scienceBaseUri":"58d63031e4b05ec7991310cb","chorus":{"doi":"10.1002/ece3.2755","url":"http://dx.doi.org/10.1002/ece3.2755","publisher":"Wiley-Blackwell","authors":"Reese Gordon C., Skagen Susan K.","journalName":"Ecology and Evolution","publicationDate":"2/7/2017","publiclyAccessibleDate":"2/7/2017"},"contributors":{"authors":[{"text":"Reese, Gordon C. 0000-0002-5191-7770 greese@usgs.gov","orcid":"https://orcid.org/0000-0002-5191-7770","contributorId":189809,"corporation":false,"usgs":true,"family":"Reese","given":"Gordon","email":"greese@usgs.gov","middleInitial":"C.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":686087,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Skagen, Susan K. 0000-0002-6744-1244 skagens@usgs.gov","orcid":"https://orcid.org/0000-0002-6744-1244","contributorId":167829,"corporation":false,"usgs":true,"family":"Skagen","given":"Susan K.","email":"skagens@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":false,"id":686088,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70185565,"text":"70185565 - 2017 - Flood effects provide evidence of an alternate stable state from dam management on the Upper Missouri River","interactions":[],"lastModifiedDate":"2017-07-10T14:57:01","indexId":"70185565","displayToPublicDate":"2017-03-24T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3301,"text":"River Research and Applications","active":true,"publicationSubtype":{"id":10}},"title":"Flood effects provide evidence of an alternate stable state from dam management on the Upper Missouri River","docAbstract":"We examine how historic flooding in 2011 affected the geomorphic adjustments created by dam regulation along the approximately 120 km free flowing reach of the Upper Missouri River bounded upstream by the Garrison Dam (1953) and downstream by Lake Oahe Reservoir (1959) near the City of Bismarck, ND, USA. The largest flood since dam regulation occurred in 2011. Flood releases from the Garrison Dam began in May 2011 and lasted until October, peaking with a flow of more than 4200 m3 s−1. Channel cross-section data and aerial imagery before and after the flood were compared with historic rates of channel change to assess the relative impact of the flood on the river morphology. Results indicate that the 2011 flood maintained trends in island area with the loss of islands in the reach just below the dam and an increase in island area downstream. Channel capacity changes varied along the Garrison Segment as a result of the flood. The thalweg, which has been stable since the mid-1970s, did not migrate. And channel morphology, as defined by a newly developed shoaling metric, which quantifies the degree of channel braiding, indicates significant longitudinal variability in response to the flood. These results show that the 2011 flood exacerbates some geomorphic trends caused by the dam while reversing others. We conclude that the presence of dams has created an alternate geomorphic and related ecological stable state, which does not revert towards pre-dam conditions in response to the flood of record. This suggests that management of sediment transport dynamics as well as flow modification is necessary to restore the Garrison Segment of the Upper Missouri River towards pre-dam conditions and help create or maintain habitat for endangered species. Published 2016. This article is a U.S. Government work and is in the public domain in the USA.
","language":"English","publisher":"Wiley","publisherLocation":"New York, NY","doi":"10.1002/rra.3084","usgsCitation":"Skalak, K., Benthem, A.J., Hupp, C.R., Schenk, E.R., Galloway, J.M., and Nustad, R.A., 2017, Flood effects provide evidence of an alternate stable state from dam management on the Upper Missouri River: River Research and Applications, v. 33, no. 6, p. 889-902, https://doi.org/10.1002/rra.3084.","productDescription":"14 p.","startPage":"889","endPage":"902","ipdsId":"IP-078296","costCenters":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"links":[{"id":338264,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Upper Missouri River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -104.25,\n 44.25\n ],\n [\n -100,\n 44.25\n ],\n [\n -100,\n 48.5\n ],\n [\n -104.25,\n 48.5\n ],\n [\n -104.25,\n 44.25\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"33","issue":"6","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2016-10-07","publicationStatus":"PW","scienceBaseUri":"58d63033e4b05ec7991310d1","contributors":{"authors":[{"text":"Skalak, Katherine 0000-0003-4122-1240 kskalak@usgs.gov","orcid":"https://orcid.org/0000-0003-4122-1240","contributorId":3990,"corporation":false,"usgs":true,"family":"Skalak","given":"Katherine","email":"kskalak@usgs.gov","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":685979,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Benthem, Adam J. 0000-0003-2372-0281 abenthem@usgs.gov","orcid":"https://orcid.org/0000-0003-2372-0281","contributorId":2740,"corporation":false,"usgs":true,"family":"Benthem","given":"Adam","email":"abenthem@usgs.gov","middleInitial":"J.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":685980,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hupp, Cliff R. 0000-0003-1853-9197 crhupp@usgs.gov","orcid":"https://orcid.org/0000-0003-1853-9197","contributorId":2344,"corporation":false,"usgs":true,"family":"Hupp","given":"Cliff","email":"crhupp@usgs.gov","middleInitial":"R.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":685981,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schenk, Edward R. 0000-0001-6886-5754 eschenk@usgs.gov","orcid":"https://orcid.org/0000-0001-6886-5754","contributorId":2183,"corporation":false,"usgs":true,"family":"Schenk","given":"Edward","email":"eschenk@usgs.gov","middleInitial":"R.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":685982,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Galloway, Joel M. 0000-0002-9836-9724 jgallowa@usgs.gov","orcid":"https://orcid.org/0000-0002-9836-9724","contributorId":1562,"corporation":false,"usgs":true,"family":"Galloway","given":"Joel","email":"jgallowa@usgs.gov","middleInitial":"M.","affiliations":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true},{"id":478,"text":"North Dakota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":685983,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Nustad, Rochelle A. 0000-0002-4713-5944 ranustad@usgs.gov","orcid":"https://orcid.org/0000-0002-4713-5944","contributorId":1811,"corporation":false,"usgs":true,"family":"Nustad","given":"Rochelle","email":"ranustad@usgs.gov","middleInitial":"A.","affiliations":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":685984,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70185593,"text":"70185593 - 2017 - Assessment of a strain 19 brucellosis vaccination program in elk","interactions":[],"lastModifiedDate":"2017-03-29T14:55:36","indexId":"70185593","displayToPublicDate":"2017-03-24T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3779,"text":"Wildlife Society Bulletin","onlineIssn":"1938-5463","printIssn":"0091-7648","active":true,"publicationSubtype":{"id":10}},"title":"Assessment of a strain 19 brucellosis vaccination program in elk","docAbstract":"Zoonotic diseases in wildlife present substantial challenges and risks to host populations, susceptible domestic livestock populations, and affected stakeholders. Brucellosis, a disease caused by the bacterium Brucella abortus, is endemic among elk (Cervus canadensis) attending winter feedgrounds and adjacent areas of western Wyoming, USA. To minimize transmission of brucellosis from elk to elk and elk to livestock, managers initiated a B. abortus strain 19 ballistic vaccination program in 1985. We used brucellosis prevalence (1971–2015) and reproductive outcome (2006–2015) data collected from female elk attending feedgrounds to assess efficacy of the strain 19 program while controlling for potentially confounding factors such as site and age. From our generalized linear models, we found that seroprevalence of brucellosis was 1) not lower following inception of vaccination; 2) not inversely associated with proportion of juveniles vaccinated over time; 3) not inversely associated with additional yearlings and adults vaccinated over time; and 4) associated more with feeding end-date than proportion of juveniles vaccinated. Using vaginal implant transmitters in adult females that were seropositive for brucellosis, we found little effect of vaccination coverage at reducing reproductive failures (i.e., abortion or stillbirth). Because we found limited support for efficacy of the strain 19 program, we support research to develop an oral vaccine and suggest that continuing other spatio-temporal management actions will be most effective to minimize transmission of brucellosis and reduce dependency of elk on supplemental winter feeding.
","language":"English","publisher":"The Wildlife Society","publisherLocation":"Washington, D.C.","doi":"10.1002/wsb.734","usgsCitation":"Maichak, E., Scurlock, B.M., Cross, P.C., Rogerson, J., Edwards, W.H., Wise, B., Smith, S.G., and Kreeger, T.J., 2017, Assessment of a strain 19 brucellosis vaccination program in elk: Wildlife Society Bulletin, v. 41, no. 1, p. 70-79, https://doi.org/10.1002/wsb.734.","productDescription":"10 p.","startPage":"70","endPage":"79","ipdsId":"IP-071247","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":499973,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doaj.org/article/5c011601357f4269ab8e87d4a503fb36","text":"External Repository"},{"id":338279,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho, Wyoming","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.0662841796875,\n 42.57937729240967\n ],\n [\n -109.22607421875,\n 42.57937729240967\n ],\n [\n -109.22607421875,\n 43.54257572246922\n ],\n [\n -111.0662841796875,\n 43.54257572246922\n ],\n [\n -111.0662841796875,\n 42.57937729240967\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"41","issue":"1","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2017-03-07","publicationStatus":"PW","scienceBaseUri":"58d63032e4b05ec7991310cd","contributors":{"authors":[{"text":"Maichak, Eric","contributorId":36826,"corporation":false,"usgs":true,"family":"Maichak","given":"Eric","email":"","affiliations":[],"preferred":false,"id":686056,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Scurlock, Brandon M.","contributorId":93788,"corporation":false,"usgs":false,"family":"Scurlock","given":"Brandon","email":"","middleInitial":"M.","affiliations":[{"id":6917,"text":"Wyoming Game and Fish Department, Laramie, USA","active":true,"usgs":false}],"preferred":false,"id":686057,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cross, Paul C. 0000-0001-8045-5213 pcross@usgs.gov","orcid":"https://orcid.org/0000-0001-8045-5213","contributorId":2709,"corporation":false,"usgs":true,"family":"Cross","given":"Paul","email":"pcross@usgs.gov","middleInitial":"C.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":686055,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rogerson, Jared D.","contributorId":106401,"corporation":false,"usgs":true,"family":"Rogerson","given":"Jared D.","affiliations":[],"preferred":false,"id":686058,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Edwards, William H.","contributorId":9144,"corporation":false,"usgs":true,"family":"Edwards","given":"William","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":686059,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wise, Benjamin","contributorId":189800,"corporation":false,"usgs":false,"family":"Wise","given":"Benjamin","affiliations":[],"preferred":false,"id":686065,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Smith, Scott G.","contributorId":189801,"corporation":false,"usgs":false,"family":"Smith","given":"Scott","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":686066,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Kreeger, Terry J.","contributorId":189227,"corporation":false,"usgs":false,"family":"Kreeger","given":"Terry","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":686062,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70184191,"text":"sir20175002 - 2017 - Estimating current and future streamflow characteristics at ungaged sites, central and eastern Montana, with application to evaluating effects of climate change on fish populations","interactions":[],"lastModifiedDate":"2017-03-23T11:48:40","indexId":"sir20175002","displayToPublicDate":"2017-03-23T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2017-5002","title":"Estimating current and future streamflow characteristics at ungaged sites, central and eastern Montana, with application to evaluating effects of climate change on fish populations","docAbstract":"A common statistical procedure for estimating streamflow statistics at ungaged locations is to develop a relational model between streamflow and drainage basin characteristics at gaged locations using least squares regression analysis; however, least squares regression methods are parametric and make constraining assumptions about the data distribution. The random forest regression method provides an alternative nonparametric method for estimating streamflow characteristics at ungaged sites and requires that the data meet fewer statistical conditions than least squares regression methods.
Random forest regression analysis was used to develop predictive models for 89 streamflow characteristics using Precipitation-Runoff Modeling System simulated streamflow data and drainage basin characteristics at 179 sites in central and eastern Montana. The predictive models were developed from streamflow data simulated for current (baseline, water years 1982–99) conditions and three future periods (water years 2021–38, 2046–63, and 2071–88) under three different climate-change scenarios. These predictive models were then used to predict streamflow characteristics for baseline conditions and three future periods at 1,707 fish sampling sites in central and eastern Montana. The average root mean square error for all predictive models was about 50 percent. When streamflow predictions at 23 fish sampling sites were compared to nearby locations with simulated data, the mean relative percent difference was about 43 percent. When predictions were compared to streamflow data recorded at 21 U.S. Geological Survey streamflow-gaging stations outside of the calibration basins, the average mean absolute percent error was about 73 percent.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175002","collaboration":"Prepared in cooperation with the Plains and Prairie Potholes Landscape Conservation Cooperative and the Bureau of Land Management","usgsCitation":"Sando, Roy, and Chase, K.J., 2017, Estimating current and future streamflow characteristics at ungaged sites, central and eastern Montana, with application to evaluating effects of climate change on fish populations: U.S. Geological Survey Scientific Investigations Report 2017–5002, 23 p., https://doi.org/10.3133/sir20175002.","productDescription":"Report: vi, 26 p.; Appendixes 1-1 to 1-18","numberOfPages":"36","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-069581","costCenters":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"links":[{"id":338115,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5002/sir20175002.pdf","text":"Report","size":"14.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017–5002"},{"id":338114,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5002/coverthb.jpg"},{"id":338116,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2017/5002/sir20175002_appendixtables.xlsx","text":"Appendix Tables 1–1 to 1–18","size":"11.9 MB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2017–5002 Appendix Tables 1–1 to 1–18"}],"country":"United States","state":"Montana","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -113.291015625,\n 43.99281450048989\n ],\n [\n -102.23876953125,\n 43.99281450048989\n ],\n [\n -102.23876953125,\n 49.59647007089266\n ],\n [\n -113.291015625,\n 49.59647007089266\n ],\n [\n -113.291015625,\n 43.99281450048989\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Wyoming-Montana Water Science Center
U.S. Geological Survey
3162 Bozeman Ave
Helena, MT 59601
Bathymetric, topographic, and grain-size data were collected in May 2009 along a 33-mi reach of the Colorado River in Grand Canyon National Park, Arizona. The study reach is located from river miles 29 to 62 at the confluence of the Colorado and Little Colorado Rivers. Channel bathymetry was mapped using multibeam and singlebeam echosounders, subaerial topography was mapped using ground-based total-stations, and bed-sediment grain-size data were collected using an underwater digital microscope system. These data were combined to produce digital elevation models, spatially variable estimates of digital elevation model uncertainty, georeferenced grain-size data, and bed-sediment distribution maps. This project is a component of a larger effort to monitor the status and trends of sand storage along the Colorado River in Grand Canyon National Park. This report documents the survey methods and post-processing procedures, digital elevation model production and uncertainty assessment, and procedures for bed-sediment classification, and presents the datasets resulting from this study.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171030","collaboration":"Prepared in cooperation with Northern Arizona University","usgsCitation":"Kaplinski, M., Hazel, J.E., Jr., Grams, P.E., Kohl, Keith, Buscombe, D.D., and Tusso, R.B., 2017, Channel mapping river miles 29–62 of the Colorado River in Grand Canyon National Park, Arizona, May 2009: U.S. Geological Survey Open-File Report 2017–1030, 35 p., https://doi.org/10.3133/ofr20171030.","productDescription":"vi, 35 p.","onlineOnly":"Y","ipdsId":"IP-079813","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":438410,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7930RCG","text":"USGS data release","linkHelpText":"Channel Mapping of the Colorado River in Grand Canyon National Park, Arizona - May 2009, river miles 29 to 62Data"},{"id":338081,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1030/coverthb.jpg"},{"id":338082,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1030/ofr20171030.pdf","text":"Report","size":"2.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1030"},{"id":350633,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://dx.doi.org/10.5066/F7930RCG","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Channel Mapping of the Colorado River in Grand Canyon National Park, Arizona, May 2009, river miles 29 to 62—Data"}],"country":"United States","state":"Arizona","otherGeospatial":"Colorado River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.7,\n 36.541667\n ],\n [\n -112,\n 36.541667\n ],\n [\n -112,\n 36.125\n ],\n [\n -111.7,\n 36.125\n ],\n [\n -111.7,\n 36.541667\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"GCMRC Staff, Southwest Biological Science Center
U.S. Geological Survey
Grand Canyon Monitoring and Research Center
2255 N. Gemini Drive
Flagstaff, Arizona 86001
https://www.gcmrc.gov/
The U.S. Geological Survey (USGS), in cooperation with the Colorado River Basin Salinity Control Forum, studied trends in dissolved-solids loads at selected sites in and near the Uinta Basin, Utah. The Uinta Basin study area includes the Duchesne River Basin and the Middle Green River Basin in Utah from below Flaming Gorge Reservoir to the town of Green River.
Annual dissolved-solids loads for water years (WY) 1989 through 2013 were estimated for 16 gaging stations in the study area using streamflow and water-quality data from the USGS National Water Information System database. Eight gaging stations that monitored catchments with limited or no agricultural land use (natural subbasins) were used to assess loads from natural sources. Four gaging stations that monitored catchments with agricultural land in the Duchesne River Basin were used to assess loads from agricultural sources. Four other gaging stations were included in the dissolved-solids load and trend analysis to help assess the effects of agricultural areas that drain to the Green River in the Uinta Basin, but outside of the Duchesne River Basin.
Estimated mean annual dissolved-solids loads for WY 1989–2013 ranged from 1,520 tons at Lake Fork River above Moon Lake, near Mountain Home, Utah (UT), to 1,760,000 tons at Green River near Green River, UT. The flow-normalized loads at gaging stations upstream of agricultural activities showed no trend or a relatively small change. The largest net change in modeled flow-normalized load was -352,000 tons (a 17.8-percent decrease) at Green River near Green River, UT.
Annual streamflow and modeled dissolved-solids loads at the gaging stations were balanced between upstream and downstream sites to determine how much water and dissolved solids were transported to the Duchesne River and a section of the Green River, and how much was picked up in each drainage area. Mass-balance calculations of WY 1989–2013 mean annual dissolved-solids loads at the studied sites show that Green River near Jensen, UT, accounts for 64 percent of the load in the river at Green River, UT, while the Duchesne River and White River contribute 10 and 13 percent, respectively.
Annual streamflow and modeled dissolved-solids loads at the gaging stations were balanced between upstream and downstream sites to determine how much water and dissolved solids were transported to the Duchesne River and a section of the Green River, and how much was picked up in each drainage area. Mass-balance calculations of WY 1989–2013 mean annual dissolved-solids loads at the studied sites show that Green River near Jensen, UT, accounts for 64 percent of the load in the river at Green River, UT, while the Duchesne River and White River contribute 10 and 13 percent, respectively.
The flow-normalized dissolved-solids loads estimated at Duchesne River near Randlett, UT, and White River near Watson, UT, decreased by 68,000 and 55,300 tons, or 27.8 and 20.8 percent respectively, when comparing 1989 to 2013. The drainage basins for both rivers have undergone salinity-control projects since the early 1980s to reduce the dissolved-solids load entering the Colorado River. Approximately 19 percent of the net change in flow-normalized load at Green River at Green River, UT, is from changes in load modeled at Duchesne River near Randlett, UT, and 16 percent from changes in load modeled at White River near Watson, UT. The net change in flow-normalized load estimated at Green River near Greendale, UT, for WY 1989–2013 accounts for about 45 percent of the net change estimated at Green River at Green River, UT.
Mass-balance calculations of WY 1989–2013 mean annual dissolved-solids loads at the studied sites in the Duchesne River Basin show that 75,400 tons or 44 percent of the load at the Duchesne River near Randlett, UT, gaging station was not accounted for at any of the upstream gages. Most of this unmonitored load is derived from tributary inflow, groundwater discharge, unconsumed irrigation water, and irrigation tail water.
A mass balance of WY 1989–2013 flow-normalized loads estimated at sites in the Duchesne River Basin indicates that the flow-normalized load of unmonitored inflow to the Duchesne River between the Myton and Randlett gaging stations decreased by 38 percent. The total net decrease in flow-normalized load calculated for unmonitored inflow in the drainage basin accounts for 94 percent of the decrease in WY 1989–2013 flow-normalized load modeled at the Duchesne River near Randlett, UT, gaging station. Irrigation improvements in the drainage basin have likely contributed to the decrease in flow-normalized load.
Reductions in dissolved-solids load estimated by the Natural Resources Conservation Service (NRCS) and the Bureau of Reclamation (Reclamation) from on- and off-farm improvements in the Uinta Basin totaled about 135,000 tons in 2013 (81,900 tons from on-farm improvements and 53,300 tons from off-farm improvements). The reduction in dissolved-solids load resulting from on- and off-farm improvements facilitated by the NRCS and Reclamation in the Price River Basin from 1989 to 2013 was estimated to be 64,800 tons.
The amount of sprinkler-irrigated land mapped in the drainage area or subbasin area for a gaging station was used to estimate the reduction in load resulting from the conversion from flood to sprinkler irrigation. Sprinkler-irrigated land mapped in the Uinta Basin totaled 109,630 acres in 2012. Assuming conversion to wheel-line sprinklers, a reduction in dissolved-solids load in the Uinta Basin of 95,800 tons in 2012 was calculated using the sprinkler-irrigation acreage and a pre-salinity-control project dissolved-solids yield of 1.04 tons per acre.
A reduction of 72,800 tons in dissolved-solids load from irrigation improvements was determined from sprinkler-irrigated lands in the Ashley Valley and Jensen, Pelican Lake, and Pleasant Valley areas (mapped in 2012); and in the Price River Basin (mapped in 2011). This decrease in dissolved-solids load is 8,800 tons more than the decrease in unmonitored flow-normalized dissolved-solids load (-64,000 tons) determined for the Green River between the Jensen and Green River gaging stations.
The net WY 1989–2013 change in flow-normalized dissolved-solids load at the Duchesne River near Randlett, UT, and the Green River between the Jensen and Green River, UT, gaging stations determined from mass-balance calculations was compared to reported reductions in dissolved-solids load from on- and off-farm improvements and estimated reductions in load determined from mapped sprinkler-irrigated areas in the Duchesne River Basin and the area draining to the Green River between the Jensen and Green River gaging stations. The combined NRCS and Reclamation estimates of reduction in dissolved-solids load from on- and off-farm improvements in the study area (200,000 tons) is more than the reduction in load estimated using the acreage with sprinkler improvements (136,000 tons) or the mass-balance of flow-normalized load (132,000 tons).
Director, Utah Water Science Center
U.S. Geological Survey
2329 West Orton Circle
Salt Lake City, UT 84119-2047
(801) 908-5000
http://ut.water.usgs.gov/
Decision-analytic models provide forecasts of how systems of interest will respond to management. These models can be parameterized using empirical data, but sometimes require information elicited from experts. When evaluating the effects of disease in species translocation programs, expert judgment is likely to play a role because complete empirical information will rarely be available. We illustrate development of a decision-analytic model built to inform decision-making regarding translocations and other management actions for the boreal toad (Anaxyrus boreas boreas), a species with declines linked to chytridiomycosis caused by Batrachochytrium dendrobatidis (Bd). Using the model, we explored the management implications of major uncertainties in this system, including whether there is a genetic basis for resistance to pathogenic infection by Bd, how translocation can best be implemented, and the effectiveness of efforts to reduce the spread of Bd. Our modeling exercise suggested that while selection for resistance to pathogenic infectionDecision-analytic models provide forecasts of how systems of interest will respond to management. These models can be parameterized using empirical data, but sometimes require information elicited from experts. When evaluating the effects of disease in species translocation programs, expert judgment is likely to play a role because complete empirical information will rarely be available. We illustrate development of a decision-analytic model built to inform decision-making regarding translocations and other management actions for the boreal toad (Anaxyrus boreas boreas), a species with declines linked to chytridiomycosis caused by Batrachochytrium dendrobatidis (Bd). Using the model, we explored the management implications of major uncertainties in this system, including whether there is a genetic basis for resistance to pathogenic infection by Bd, how translocation can best be implemented, and the effectiveness of efforts to reduce the spread of Bd. Our modeling exercise suggested that while selection for resistance to pathogenic infection by Bd could increase numbers of sites occupied by toads, and translocations could increase the rate of toad recovery, efforts to reduce the spread of Bd may have little effect. We emphasize the need to continue developing and parameterizing models necessary to assess management actions for combating chytridiomycosis-associated declines. by Bd could increase numbers of sites occupied by toads, and translocations could increase the rate of toad recovery, efforts to reduce the spread of Bd may have little effect. We emphasize the need to continue developing and parameterizing models necessary to assess management actions for combating chytridiomycosis-associated declines.
","language":"English","publisher":"Springer","publisherLocation":"New York","doi":"10.1007/s10393-016-1117-9","usgsCitation":"Converse, S.J., Bailey, L., Mosher, B.A., Funk, W.C., Gerber, B.D., and Muths, E.L., 2017, A model to inform management actions as a response to chytridiomycosis-associated decline: EcoHealth, v. 14, no. 1, p. 144-155, https://doi.org/10.1007/s10393-016-1117-9.","productDescription":"12 p.","startPage":"144","endPage":"155","ipdsId":"IP-070781","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":337907,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"14","issue":"1","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2016-04-07","publicationStatus":"PW","scienceBaseUri":"58d23b90e4b0236b68f828ec","chorus":{"doi":"10.1007/s10393-016-1117-9","url":"http://dx.doi.org/10.1007/s10393-016-1117-9","publisher":"Springer Nature","authors":"Converse Sarah J., Bailey Larissa L., Mosher Brittany A., Funk W. Chris, Gerber Brian D., Muths Erin","journalName":"EcoHealth","publicationDate":"4/7/2016","auditedOn":"8/1/2016","publiclyAccessibleDate":"4/7/2016"},"contributors":{"authors":[{"text":"Converse, Sarah J. 0000-0002-3719-5441 sconverse@usgs.gov","orcid":"https://orcid.org/0000-0002-3719-5441","contributorId":173772,"corporation":false,"usgs":true,"family":"Converse","given":"Sarah","email":"sconverse@usgs.gov","middleInitial":"J.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":685238,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bailey, Larissa L.","contributorId":93183,"corporation":false,"usgs":true,"family":"Bailey","given":"Larissa L.","affiliations":[],"preferred":false,"id":685239,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mosher, Brittany A.","contributorId":189579,"corporation":false,"usgs":false,"family":"Mosher","given":"Brittany","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":685281,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Funk, W. Chris 0000-0002-9254-6718","orcid":"https://orcid.org/0000-0002-9254-6718","contributorId":97589,"corporation":false,"usgs":false,"family":"Funk","given":"W.","email":"","middleInitial":"Chris","affiliations":[{"id":6998,"text":"Department of Biology, Colorado State University","active":true,"usgs":false}],"preferred":false,"id":685241,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gerber, Brian D.","contributorId":187620,"corporation":false,"usgs":false,"family":"Gerber","given":"Brian","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":685282,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Muths, Erin L. 0000-0002-5498-3132 muthse@usgs.gov","orcid":"https://orcid.org/0000-0002-5498-3132","contributorId":1260,"corporation":false,"usgs":true,"family":"Muths","given":"Erin","email":"muthse@usgs.gov","middleInitial":"L.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":685242,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70185353,"text":"70185353 - 2017 - Changes in community-level riparian plant traits over inundation gradients, Colorado River, Grand Canyon","interactions":[],"lastModifiedDate":"2017-09-05T12:57:05","indexId":"70185353","displayToPublicDate":"2017-03-21T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3750,"text":"Wetlands","onlineIssn":"1943-6246","printIssn":"0277-5212","active":true,"publicationSubtype":{"id":10}},"title":"Changes in community-level riparian plant traits over inundation gradients, Colorado River, Grand Canyon","docAbstract":"Comparisons of community-level functional traits across environmental gradients have potential for identifying links among plant characteristics, adaptations to stress and disturbance, and community assembly. We investigated community-level variation in specific leaf area (SLA), plant mature height, seed mass, stem specific gravity (SSG), relative cover of C4 species, and total plant cover over hydrologic zones and gradients in years 2013 and 2014 in the riparian plant community along the Colorado River in the Grand Canyon. Vegetation cover was lowest in the frequently inundated active channel zone, indicating constraints on plant establishment and production by flood disturbance and anaerobic stress. Changes in trait values over hydrologic zones and inundation gradients indicate that frequently inundated plots exhibit a community-level ruderal strategy with adaptation to submergence (high SLA and low SSG, height, seed mass, C4 relative cover), whereas less frequently inundated plots exhibit adaptation to drought and infrequent flood disturbance (low SLA and high SSG, height, seed mass, C4 relative cover). Variation in traits not associated with inundation suggests niche differentiation and multiple modes of community assembly. The results enhance understanding of future responses of riparian communities of the Grand Canyon to anticipated drying and changes in hydrologic regime.
","language":"English","publisher":"Springer","doi":"10.1007/s13157-017-0895-3","usgsCitation":"McCoy-Sulentic, M., Kolb, T., Merritt, D., Palmquist, E.C., Ralston, B.E., Sarr, D., and Shafroth, P.B., 2017, Changes in community-level riparian plant traits over inundation gradients, Colorado River, Grand Canyon: Wetlands, v. 37, no. 4, p. 635-646, https://doi.org/10.1007/s13157-017-0895-3.","productDescription":"12 p.","startPage":"635","endPage":"646","ipdsId":"IP-080895","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":469998,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s13157-017-0895-3","text":"Publisher Index Page"},{"id":438413,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F73R0R24","text":"USGS data release","linkHelpText":"Community-level riparian plant traits, Colorado River, Grand Canyon, 2013-2015Data"},{"id":337910,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"Grand Canyon","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -113.78814697265625,\n 35.62381451392674\n ],\n [\n -111.60186767578125,\n 35.62381451392674\n ],\n [\n -111.60186767578125,\n 36.84446074079564\n ],\n [\n -113.78814697265625,\n 36.84446074079564\n ],\n [\n -113.78814697265625,\n 35.62381451392674\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"37","issue":"4","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2017-03-17","publicationStatus":"PW","scienceBaseUri":"58d23b8ee4b0236b68f828e6","chorus":{"doi":"10.1007/s13157-017-0895-3","url":"http://dx.doi.org/10.1007/s13157-017-0895-3","publisher":"Springer Nature","authors":"McCoy-Sulentic Miles E., Kolb Thomas E., Merritt David M., Palmquist Emily, Ralston Barbara E., Sarr Daniel A., Shafroth Patrick B.","journalName":"Wetlands","publicationDate":"3/17/2017","auditedOn":"3/20/2017","publiclyAccessibleDate":"3/17/2017"},"contributors":{"authors":[{"text":"McCoy-Sulentic, Miles","contributorId":189593,"corporation":false,"usgs":false,"family":"McCoy-Sulentic","given":"Miles","affiliations":[],"preferred":false,"id":685292,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kolb, Thomas","contributorId":174381,"corporation":false,"usgs":false,"family":"Kolb","given":"Thomas","affiliations":[],"preferred":false,"id":685293,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Merritt, David","contributorId":189308,"corporation":false,"usgs":false,"family":"Merritt","given":"David","affiliations":[],"preferred":false,"id":685294,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Palmquist, Emily C. 0000-0003-1069-2154 epalmquist@usgs.gov","orcid":"https://orcid.org/0000-0003-1069-2154","contributorId":5669,"corporation":false,"usgs":true,"family":"Palmquist","given":"Emily","email":"epalmquist@usgs.gov","middleInitial":"C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":685291,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ralston, Barbara E. 0000-0001-9991-8994 bralston@usgs.gov","orcid":"https://orcid.org/0000-0001-9991-8994","contributorId":606,"corporation":false,"usgs":true,"family":"Ralston","given":"Barbara","email":"bralston@usgs.gov","middleInitial":"E.","affiliations":[{"id":501,"text":"Office of Science Quality and Integrity","active":true,"usgs":true}],"preferred":false,"id":685295,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Sarr, Daniel","contributorId":71148,"corporation":false,"usgs":true,"family":"Sarr","given":"Daniel","affiliations":[],"preferred":false,"id":685301,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Shafroth, Patrick B. 0000-0002-6064-871X shafrothp@usgs.gov","orcid":"https://orcid.org/0000-0002-6064-871X","contributorId":2000,"corporation":false,"usgs":true,"family":"Shafroth","given":"Patrick","email":"shafrothp@usgs.gov","middleInitial":"B.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":685296,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70185288,"text":"70185288 - 2017 - Effects of internal phosphorus loadings and food-web structure on the recovery of a deep lake from eutrophication","interactions":[],"lastModifiedDate":"2017-03-20T08:25:20","indexId":"70185288","displayToPublicDate":"2017-03-20T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2330,"text":"Journal of Great Lakes Research","active":true,"publicationSubtype":{"id":10}},"title":"Effects of internal phosphorus loadings and food-web structure on the recovery of a deep lake from eutrophication","docAbstract":"We used monitoring data from Lake Lugano (Switzerland and Italy) to assess key ecosystem responses to three decades of nutrient management (1983–2014). We investigated whether reductions in external phosphorus loadings (Lext) caused declines in lake phosphorus concentrations (P) and phytoplankton biomass (Chl a), as assumed by the predictive models that underpinned the management plan. Additionally, we examined the hypothesis that deep lakes respond quickly to Lext reductions. During the study period, nutrient management reduced Lext by approximately a half. However, the effects of such reduction on P and Chl a were complex. Far from the scenarios predicted by classic nutrient-management approaches, the responses of P and Chl a did not only reflect changes in Lext, but also variation in internal P loadings (Lint) and food-web structure. In turn, Lint varied depending on basin morphometry and climatic effects, whereas food-web structure varied due to apparently stochastic events of colonization and near-extinction of key species. Our results highlight the complexity of the trajectory of deep-lake ecosystems undergoing nutrient management. From an applied standpoint, they also suggest that [i] the recovery of warm monomictic lakes may be slower than expected due to the development of Lint, and that [ii] classic P and Chl a models based on Lext may be useful in nutrient management programs only if their predictions are used as starting points within adaptive frameworks.
","language":"English","publisher":"International Association for Great Lakes Research","publisherLocation":"Ann Arbor","doi":"10.1016/j.jglr.2017.01.008","usgsCitation":"Lepori, F., and Roberts, J., 2017, Effects of internal phosphorus loadings and food-web structure on the recovery of a deep lake from eutrophication: Journal of Great Lakes Research, v. 43, no. 2, p. 255-264, https://doi.org/10.1016/j.jglr.2017.01.008.","productDescription":"10 p.","startPage":"255","endPage":"264","ipdsId":"IP-076985","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":337833,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Italy, Switzerland","otherGeospatial":"Lake Lugano","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 8.828201293945312,\n 45.8876184503559\n ],\n [\n 9.142684936523436,\n 45.8876184503559\n ],\n [\n 9.142684936523436,\n 46.056079276178885\n ],\n [\n 8.828201293945312,\n 46.056079276178885\n ],\n [\n 8.828201293945312,\n 45.8876184503559\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"43","issue":"2","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58d0ea1ae4b0236b68f67365","contributors":{"authors":[{"text":"Lepori, Fabio","contributorId":166767,"corporation":false,"usgs":false,"family":"Lepori","given":"Fabio","email":"","affiliations":[{"id":24502,"text":"Institute of Earth Sciences, University of Applied Sciences and Arts of Southern Switzerland","active":true,"usgs":false}],"preferred":false,"id":685030,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Roberts, James 0000-0002-4193-610X jroberts@usgs.gov","orcid":"https://orcid.org/0000-0002-4193-610X","contributorId":5453,"corporation":false,"usgs":true,"family":"Roberts","given":"James","email":"jroberts@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":685029,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70185267,"text":"70185267 - 2017 - The vanishing cryovolcanoes of Ceres","interactions":[],"lastModifiedDate":"2017-03-17T11:52:19","indexId":"70185267","displayToPublicDate":"2017-03-17T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"The vanishing cryovolcanoes of Ceres","docAbstract":"Ahuna Mons is a 4 km tall mountain on Ceres interpreted as a geologically young cryovolcanic dome. Other possible cryovolcanic features are more ambiguous, implying that cryovolcanism is only a recent phenomenon or that other cryovolcanic structures have been modified beyond easy identification. We test the hypothesis that Cerean cryovolcanic domes viscously relax, precluding ancient domes from recognition. We use numerical models to predict flow velocities of Ahuna Mons to be 10–500 m/Myr, depending upon assumptions about ice content, rheology, grain size, and thermal parameters. Slower flow rates in this range are sufficiently fast to induce extensive relaxation of cryovolcanic structures over 108–109 years, but gradual enough for Ahuna Mons to remain identifiable today. Positive topographic features, including a tholus underlying Ahuna Mons, may represent relaxed cryovolcanic structures. A composition for Ahuna Mons of >40% ice explains the observed distribution of cryovolcanic structures because viscous relaxation renders old cryovolcanoes unrecognizable.
","language":"English","publisher":"AGU","doi":"10.1002/2016GL072319","usgsCitation":"Sori, M.M., Byrne, S., Bland, M.T., Bramson, A., Ermakov, A., Hamilton, C., Otto, K., Ruesch, O., and Russell, C., 2017, The vanishing cryovolcanoes of Ceres: Geophysical Research Letters, v. 44, no. 3, p. 1243-1250, https://doi.org/10.1002/2016GL072319.","productDescription":"8 p.","startPage":"1243","endPage":"1250","ipdsId":"IP-082312","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":470002,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1002/2016gl072319","text":"External Repository"},{"id":337804,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"44","issue":"3","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2017-02-10","publicationStatus":"PW","scienceBaseUri":"58ccf59ae4b0849ce97f0cd8","contributors":{"authors":[{"text":"Sori, Michael M.","contributorId":173342,"corporation":false,"usgs":false,"family":"Sori","given":"Michael","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":684941,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Byrne, Shane","contributorId":53513,"corporation":false,"usgs":false,"family":"Byrne","given":"Shane","affiliations":[{"id":7042,"text":"University of Arizona","active":true,"usgs":false}],"preferred":false,"id":684942,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bland, Michael T. 0000-0001-5543-1519 mbland@usgs.gov","orcid":"https://orcid.org/0000-0001-5543-1519","contributorId":146287,"corporation":false,"usgs":true,"family":"Bland","given":"Michael","email":"mbland@usgs.gov","middleInitial":"T.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":684940,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bramson, Ali","contributorId":189477,"corporation":false,"usgs":false,"family":"Bramson","given":"Ali","email":"","affiliations":[],"preferred":false,"id":684943,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ermakov, Anton","contributorId":189478,"corporation":false,"usgs":false,"family":"Ermakov","given":"Anton","email":"","affiliations":[],"preferred":false,"id":684944,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hamilton, Christoper","contributorId":189479,"corporation":false,"usgs":false,"family":"Hamilton","given":"Christoper","email":"","affiliations":[],"preferred":false,"id":684945,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Otto, Katharina","contributorId":189480,"corporation":false,"usgs":false,"family":"Otto","given":"Katharina","email":"","affiliations":[],"preferred":false,"id":684946,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Ruesch, Ottaviano","contributorId":177351,"corporation":false,"usgs":false,"family":"Ruesch","given":"Ottaviano","email":"","affiliations":[],"preferred":false,"id":684948,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Russell, Christopher","contributorId":189481,"corporation":false,"usgs":false,"family":"Russell","given":"Christopher","affiliations":[],"preferred":false,"id":684947,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70185258,"text":"70185258 - 2017 - Predicting the impacts of Mississippi River diversions and sea-level rise on spatial patterns of eastern oyster growth rate and production","interactions":[],"lastModifiedDate":"2017-03-17T11:58:47","indexId":"70185258","displayToPublicDate":"2017-03-17T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1458,"text":"Ecological Modelling","active":true,"publicationSubtype":{"id":10}},"title":"Predicting the impacts of Mississippi River diversions and sea-level rise on spatial patterns of eastern oyster growth rate and production","docAbstract":"There remains much debate regarding the perceived tradeoffs of using freshwater and sediment diversions for coastal restoration in terms of balancing the need for wetland restoration versus preserving eastern oyster (Crassostrea virginica) production. Further complicating the issue, climate change-induced sea-level rise (SLR) and land subsidence are also expected to affect estuarine water quality. In this study, we developed a process-based numerical modeling system that couples hydrodynamic, water quality, and oyster population dynamics. We selected Breton Sound Estuary (BSE) (∼2740 km2) in the eastern Mississippi River Deltaic Plain since it is home to several of the largest public oyster seed grounds and private leases for the Gulf coast. The coupled oyster population model was calibrated and validated against field observed oyster growth data. We predicted the responses of oyster population in BSE to small- (142 m3 s−1) and large-scale (7080 m3 s−1) river diversions at the Caernarvon Freshwater Diversion structure planned in the 2012 Coastal Master Plan (Louisiana) under low (0.38 m) and high (1.44 m) relative sea-level rise (RSLR = eustatic SLR + subsidence) compared to a baseline condition (Year 2009). Model results showed that the large-scale diversion had a stronger negative impact on oyster population dynamics via freshening of the entire estuary, resulting in reduced oyster growth rate and production than RSLR. Under the large-scale diversion, areas with optimal oyster growth rates (>15 mg ash-free dry weight (AFDW) oyster−1 wk−1) and production (>500 g AFDW m−2 yr−1) would shift seaward to the southeastern edge of the estuary, turning the estuary into a very low oyster production system. RSLR however played a greater role than the small-scale diversion on the magnitude and spatial pattern of oyster growth rate and production. RSLR would result in an overall estuary-wide decrease in oyster growth rate and production as a consequence of decreased salinities in the middle and lower estuary because rising sea level likely causes increased stage and overbank flow downstream along the lower Mississippi River.
","language":"English","publisher":"International Society for Ecological Modelling","publisherLocation":"Amsterdam","doi":"10.1016/j.ecolmodel.2017.02.028","usgsCitation":"Wang, H., Chen, Q., La Peyre, M., Hu, K., and La Peyre, J.F., 2017, Predicting the impacts of Mississippi River diversions and sea-level rise on spatial patterns of eastern oyster growth rate and production: Ecological Modelling, v. 352, p. 40-53, https://doi.org/10.1016/j.ecolmodel.2017.02.028.","productDescription":"14 p.","startPage":"40","endPage":"53","ipdsId":"IP-079318","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":470003,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecolmodel.2017.02.028","text":"Publisher Index Page"},{"id":337805,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Louisiana","otherGeospatial":"Breton Sound Estuary","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -90.0384521484375,\n 29.262440796698915\n ],\n [\n -89.03594970703125,\n 29.262440796698915\n ],\n [\n -89.03594970703125,\n 29.92637417863576\n ],\n [\n -90.0384521484375,\n 29.92637417863576\n ],\n [\n -90.0384521484375,\n 29.262440796698915\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"352","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58ccf59be4b0849ce97f0cda","contributors":{"authors":[{"text":"Wang, Hongqing 0000-0002-2977-7732 wangh@usgs.gov","orcid":"https://orcid.org/0000-0002-2977-7732","contributorId":140432,"corporation":false,"usgs":true,"family":"Wang","given":"Hongqing","email":"wangh@usgs.gov","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":684909,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chen, Q. 0000-0002-6540-8758","orcid":"https://orcid.org/0000-0002-6540-8758","contributorId":56532,"corporation":false,"usgs":false,"family":"Chen","given":"Q.","affiliations":[{"id":38331,"text":"Northeastern University","active":true,"usgs":false}],"preferred":true,"id":684910,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"La Peyre, Megan 0000-0001-9936-2252 mlapeyre@usgs.gov","orcid":"https://orcid.org/0000-0001-9936-2252","contributorId":79375,"corporation":false,"usgs":true,"family":"La Peyre","given":"Megan","email":"mlapeyre@usgs.gov","affiliations":[{"id":369,"text":"Louisiana Water Science Center","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":684911,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hu, Kelin","contributorId":177218,"corporation":false,"usgs":false,"family":"Hu","given":"Kelin","email":"","affiliations":[],"preferred":false,"id":684912,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"La Peyre, Jerome F.","contributorId":34697,"corporation":false,"usgs":true,"family":"La Peyre","given":"Jerome","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":684913,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70180341,"text":"fs20173002 - 2017 - The U.S. Geological Survey Monthly Water Balance Model Futures Portal","interactions":[],"lastModifiedDate":"2017-03-16T12:27:20","indexId":"fs20173002","displayToPublicDate":"2017-03-16T11:00:00","publicationYear":"2017","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":"2017-3002","title":"The U.S. Geological Survey Monthly Water Balance Model Futures Portal","docAbstract":"Simulations of future climate suggest profiles of temperature and precipitation may differ significantly from those in the past. These changes in climate will likely lead to changes in the hydrologic cycle. As such, natural resource managers are in need of tools that can provide estimates of key components of the hydrologic cycle, uncertainty associated with the estimates, and limitations associated with the climate forcing data used to estimate these components. To help address this need, the U.S. Geological Survey Monthly Water Balance Model Futures Portal (https://my.usgs.gov/mows/) provides a user friendly interface to deliver hydrologic and meteorological variables for monthly historic and potential future climatic conditions across the continental United States.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20173002","collaboration":"Prepared in cooperation with the U.S. Department of the Interior South Central Climate Science Center and the U.S. Environmental Protection Agency","usgsCitation":"Bock, A.R., 2017, The U.S. Geological Survey Monthly Water Balance Model Futures Portal: U.S. Geological Survey Fact Sheet 2017–3002, 6 p., https://doi.org/10.3133/fs20173002.","productDescription":"6 p.","onlineOnly":"Y","ipdsId":"IP-073900","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":336957,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2017/3002/fs20173002.pdf","text":"Report","size":"1.63 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2017-3002"},{"id":336153,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2017/3002/coverthb2.jpg"}],"contact":"Director, USGS Colorado Water Science Center
U.S. Geological Survey
Box 25046, MS 415
Denver, CO 80225-0046
We extend the use of a novel tracing technique to quantify the bioavailability of zinc (Zn) associated with natural particles using snails enriched with a less common Zn stable isotope. Lymnaea stagnalis is a model species that has relatively fast Zn uptake rates from the dissolved phase, enabling their rapid enrichment in 67Zn during the initial phase of labeling. Isotopically enriched snails were subsequently exposed to algae mixed with increasing amounts of metal-rich particles collected from two acid mine drainage impacted rivers. Zinc bioavailability from the natural particles was inferred from calculations of 66Zn assimilation into the snail’s soft tissues. Zinc assimilation efficiency (AE) varied from 28% for the Animas River particles to 45% for the Snake River particles, indicating that particle-bound, or sorbed Zn, was bioavailable from acid mine drainage wastes. The relative binding strength of Zn sorption to the natural particles was inversely related to Zn bioavailability; a finding that would not have been possible without using the reverse labeling approach. Differences in the chemical composition of the particles suggest that their geochemical properties may influence the extent of Zn bioavailability.
","language":"English","publisher":"ACS Publications","doi":"10.1021/acs.est.6b06253","usgsCitation":"Croteau, M.N., Cain, D.J., and Fuller, C.C., 2017, Assessing the dietary bioavailability of metals associated with natural particles: Extending the use of the reverse labeling approach to zinc: Environmental Science & Technology, v. 51, no. 5, p. 2803-2810, https://doi.org/10.1021/acs.est.6b06253.","productDescription":"8 p.","startPage":"2803","endPage":"2810","ipdsId":"IP-081847","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"links":[{"id":337744,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"51","issue":"5","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2017-02-22","publicationStatus":"PW","scienceBaseUri":"58cba419e4b0849ce97dc730","chorus":{"doi":"10.1021/acs.est.6b06253","url":"http://dx.doi.org/10.1021/acs.est.6b06253","publisher":"American Chemical Society (ACS)","authors":"Croteau Marie-Noële, Cain Daniel J., Fuller Christopher C.","journalName":"Environmental Science & Technology","publicationDate":"2/22/2017"},"contributors":{"authors":[{"text":"Croteau, Marie Noele 0000-0003-0346-3580 mcroteau@usgs.gov","orcid":"https://orcid.org/0000-0003-0346-3580","contributorId":895,"corporation":false,"usgs":true,"family":"Croteau","given":"Marie","email":"mcroteau@usgs.gov","middleInitial":"Noele","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":684722,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cain, Daniel J. 0000-0002-3443-0493 djcain@usgs.gov","orcid":"https://orcid.org/0000-0002-3443-0493","contributorId":1784,"corporation":false,"usgs":true,"family":"Cain","given":"Daniel","email":"djcain@usgs.gov","middleInitial":"J.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":684724,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fuller, Christopher C. 0000-0002-2354-8074 ccfuller@usgs.gov","orcid":"https://orcid.org/0000-0002-2354-8074","contributorId":1831,"corporation":false,"usgs":true,"family":"Fuller","given":"Christopher","email":"ccfuller@usgs.gov","middleInitial":"C.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true},{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true}],"preferred":true,"id":684723,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70186183,"text":"70186183 - 2017 - Fallow-land Algorithm based on Neighborhood and TemporalAnomalies (FANTA) to map planted versus fallowed croplands usingMODIS data to assist in drought studies leading to water and foodsecurity assessments","interactions":[],"lastModifiedDate":"2017-03-31T10:42:50","indexId":"70186183","displayToPublicDate":"2017-03-15T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1722,"text":"GIScience and Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Fallow-land Algorithm based on Neighborhood and TemporalAnomalies (FANTA) to map planted versus fallowed croplands usingMODIS data to assist in drought studies leading to water and foodsecurity assessments","docAbstract":"An important metric to monitor for optimizing water use in agricultural areas is the\namount of cropland left fallowed, or unplanted. Fallowed croplands are difficult to\nmodel because they have many expressions; for example, they can be managed and\nremain free of vegetation or be abandoned and become weedy if the climate for that\nseason permits. We used 250 m, 8-day composite Moderate Resolution Imaging\nSpectroradiometer normalized difference vegetation index data to develop an algorithm\nthat can routinely map cropland status (planted or fallowed) with over 75% user’s and\nproducer’s accuracies. The Fallow-land Algorithm based on Neighborhood and\nTemporal Anomalies (FANTA) compares the current greenness of a cultivated pixel to\nits historical greenness and to the greenness of all cultivated pixels within a defined\nspatial neighborhood, and is therefore transportable across space and through time. This\narticle introduces FANTA and applies it to California from 2001 to 2015 as a case study\nfor use in data-poor places and for use in historical modeling. Timely and accurate\nknowledge of the extent of fallowing can provide decision makers with insights and\nknowledge to mitigate the impacts of drought and provide a scientific basis for effective\nmanagement response. This study is part of the WaterSMART (Sustain and Manage\nAmerica’s Resources for Tomorrow) project, an interdisciplinary and collaborative\nresearch effort focused on improving water conservation and optimizing water use.","language":"English","publisher":"Taylor & Francis","doi":"10.1080/15481603.2017.1290913","usgsCitation":"Wallace, C., Thenkabail, P.S., Rodriguez, J.R., and Brown, M.K., 2017, Fallow-land Algorithm based on Neighborhood and TemporalAnomalies (FANTA) to map planted versus fallowed croplands usingMODIS data to assist in drought studies leading to water and foodsecurity assessments: GIScience and Remote Sensing, v. 54, no. 2, p. 258-282, https://doi.org/10.1080/15481603.2017.1290913.","productDescription":"25 p. ","startPage":"258","endPage":"282","ipdsId":"IP-079921","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":470011,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1080/15481603.2017.1290913","text":"Publisher Index Page"},{"id":338940,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":338874,"type":{"id":15,"text":"Index Page"},"url":"https://www.tandfonline.com/doi/full/10.1080/15481603.2017.1290913"}],"country":"United States","state":"California","otherGeospatial":"Central Valley ","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.96997070312499,\n 39.96870074491696\n ],\n [\n -120.003662109375,\n 35.53222622770337\n ],\n [\n -119.54223632812501,\n 34.82282272723702\n ],\n [\n -118.7841796875,\n 34.813803317113155\n ],\n [\n -118.16894531249999,\n 35.17380831799959\n ],\n [\n -119.36645507812499,\n 37.15156050223665\n ],\n [\n -121.387939453125,\n 39.69873414348139\n ],\n [\n -121.92626953124999,\n 40.72228267283148\n ],\n [\n -122.37670898437499,\n 40.88029480552824\n ],\n [\n -123.00292968749999,\n 40.48873742102282\n ],\n [\n -123.01391601562499,\n 40.10328591293439\n ],\n [\n -122.96997070312499,\n 39.96870074491696\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"54","issue":"2","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2017-03-15","publicationStatus":"PW","scienceBaseUri":"58df6abfe4b02ff32c6aea2b","contributors":{"authors":[{"text":"Wallace, Cynthia 0000-0003-0001-8828 cwallace@usgs.gov","orcid":"https://orcid.org/0000-0003-0001-8828","contributorId":149179,"corporation":false,"usgs":true,"family":"Wallace","given":"Cynthia","email":"cwallace@usgs.gov","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":687778,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thenkabail, Prasad S. 0000-0002-2182-8822 pthenkabail@usgs.gov","orcid":"https://orcid.org/0000-0002-2182-8822","contributorId":570,"corporation":false,"usgs":true,"family":"Thenkabail","given":"Prasad","email":"pthenkabail@usgs.gov","middleInitial":"S.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":687779,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rodriguez, Jesus R.","contributorId":190195,"corporation":false,"usgs":false,"family":"Rodriguez","given":"Jesus","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":687781,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brown, Melinda K. 0000-0003-1332-017X","orcid":"https://orcid.org/0000-0003-1332-017X","contributorId":190194,"corporation":false,"usgs":false,"family":"Brown","given":"Melinda","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":687780,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70191302,"text":"70191302 - 2017 - Multi-temporal LiDAR and Landsat quantification of fire-induced changes to forest structure","interactions":[],"lastModifiedDate":"2017-10-03T16:34:40","indexId":"70191302","displayToPublicDate":"2017-03-15T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3254,"text":"Remote Sensing of Environment","printIssn":"0034-4257","active":true,"publicationSubtype":{"id":10}},"title":"Multi-temporal LiDAR and Landsat quantification of fire-induced changes to forest structure","docAbstract":"Measuring post-fire effects at landscape scales is critical to an ecological understanding of wildfire effects. Predominantly this is accomplished with either multi-spectral remote sensing data or through ground-based field sampling plots. While these methods are important, field data is usually limited to opportunistic post-fire observations, and spectral data often lacks validation with specific variables of change. Additional uncertainty remains regarding how best to account for environmental variables influencing fire effects (e.g., weather) for which observational data cannot easily be acquired, and whether pre-fire agents of change such as bark beetle and timber harvest impact model accuracy. This study quantifies wildfire effects by correlating changes in forest structure derived from multi-temporal Light Detection and Ranging (LiDAR) acquisitions to multi-temporal spectral changes captured by the Landsat Thematic Mapper and Operational Land Imager for the 2012 Pole Creek Fire in central Oregon. Spatial regression modeling was assessed as a methodology to account for spatial autocorrelation, and model consistency was quantified across areas impacted by pre-fire mountain pine beetle and timber harvest. The strongest relationship (pseudo-r2 = 0.86, p < 0.0001) was observed between the ratio of shortwave infrared and near infrared reflectance (d74) and LiDAR-derived estimate of canopy cover change. Relationships between percentage of LiDAR returns in forest strata and spectral indices generally increased in strength with strata height. Structural measurements made closer to the ground were not well correlated. The spatial regression approach improved all relationships, demonstrating its utility, but model performance declined across pre-fire agents of change, suggesting that such studies should stratify by pre-fire forest condition. This study establishes that spectral indices such as d74 and dNBR are most sensitive to wildfire-caused structural changes such as reduction in canopy cover and perform best when that structure has not been reduced pre-fire.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.rse.2016.12.022","usgsCitation":"McCarley, T.R., Kolden, C.A., Vaillant, N.M., Hudak, A.T., Smith, A., Wing, B.M., Kellogg, B., and Kreitler, J.R., 2017, Multi-temporal LiDAR and Landsat quantification of fire-induced changes to forest structure: Remote Sensing of Environment, v. 191, p. 419-432, https://doi.org/10.1016/j.rse.2016.12.022.","productDescription":"14 p.","startPage":"419","endPage":"432","ipdsId":"IP-076180","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":470007,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.rse.2016.12.022","text":"Publisher Index Page"},{"id":346371,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon","otherGeospatial":"Pole Creek Fire","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.75,\n 44.0833\n ],\n [\n -121.5,\n 44.0833\n ],\n [\n -121.5,\n 44.25\n ],\n [\n -121.75,\n 44.25\n ],\n [\n -121.75,\n 44.0833\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"191","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59d4a1a9e4b05fe04cc4e0ff","contributors":{"authors":[{"text":"McCarley, T. Ryan","contributorId":196908,"corporation":false,"usgs":false,"family":"McCarley","given":"T.","email":"","middleInitial":"Ryan","affiliations":[],"preferred":false,"id":711897,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kolden, Crystal A.","contributorId":196909,"corporation":false,"usgs":false,"family":"Kolden","given":"Crystal","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":711898,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Vaillant, Nicole M.","contributorId":196237,"corporation":false,"usgs":false,"family":"Vaillant","given":"Nicole","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":711899,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hudak, Andrew T.","contributorId":196022,"corporation":false,"usgs":false,"family":"Hudak","given":"Andrew","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":711900,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Smith, Alistair","contributorId":196910,"corporation":false,"usgs":false,"family":"Smith","given":"Alistair","email":"","affiliations":[],"preferred":false,"id":711901,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wing, Brian M.","contributorId":196911,"corporation":false,"usgs":false,"family":"Wing","given":"Brian","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":711902,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kellogg, Bryce","contributorId":196912,"corporation":false,"usgs":false,"family":"Kellogg","given":"Bryce","email":"","affiliations":[],"preferred":false,"id":711903,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Kreitler, Jason R. 0000-0002-0243-5281 jkreitler@usgs.gov","orcid":"https://orcid.org/0000-0002-0243-5281","contributorId":4050,"corporation":false,"usgs":true,"family":"Kreitler","given":"Jason","email":"jkreitler@usgs.gov","middleInitial":"R.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":711896,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70189771,"text":"70189771 - 2017 - Matching seed to site by climate similarity: techniques to prioritize plant materials development and use in restoration","interactions":[],"lastModifiedDate":"2017-07-25T12:42:20","indexId":"70189771","displayToPublicDate":"2017-03-15T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1450,"text":"Ecological Applications","active":true,"publicationSubtype":{"id":10}},"title":"Matching seed to site by climate similarity: techniques to prioritize plant materials development and use in restoration","docAbstract":"Land management agencies are increasing the use of native plant materials for vegetation treatments to restore ecosystem function and maintain natural ecological integrity. This shift toward the use of natives has highlighted a need to increase the diversity of materials available. A key problem is agreeing on how many, and which, new accessions should be developed. Here we describe new methods that address this problem. Our methods use climate data to calculate a climate similarity index between two points in a defined extent. This index can be used to predict relative performance of available accessions at a target site. In addition, the index can be used in combination with standard cluster analysis algorithms to quantify and maximize climate coverage (mean climate similarity), given a modeled range extent and a specified number of accessions. We demonstrate the utility of this latter feature by applying it to the extents of 11 western North American species with proven or potential use in restoration. First, a species-specific seed transfer map can be readily generated for a species by predicting performance for accessions currently available; this map can be readily updated to accommodate new accessions. Next, the increase in climate coverage achieved by adding successive accessions can be explored, yielding information that managers can use to balance ecological and economic considerations in determining how many accessions to develop. This approach identifies sampling sites, referred to as climate centers, which contribute unique, complementary, climate coverage to accessions on hand, thus providing explicit sampling guidance for both germplasm preservation and research. We examine how these and other features of our approach add to existing methods used to guide plant materials development and use. Finally, we discuss how these new methods provide a framework that could be used to coordinate native plant materials development, evaluation, and use across agencies, regions, and research groups.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/eap.1505","usgsCitation":"Doherty, K., Butterfield, B.J., and Wood, T.E., 2017, Matching seed to site by climate similarity: techniques to prioritize plant materials development and use in restoration: Ecological Applications, v. 27, no. 3, p. 1010-1023, https://doi.org/10.1002/eap.1505.","productDescription":"14 p.","startPage":"1010","endPage":"1023","onlineOnly":"N","ipdsId":"IP-077215","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":344294,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"27","issue":"3","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2017-03-21","publicationStatus":"PW","scienceBaseUri":"597858b5e4b0ec1a488a0910","contributors":{"authors":[{"text":"Doherty, Kyle 0000-0002-3742-7839 kdoherty@usgs.gov","orcid":"https://orcid.org/0000-0002-3742-7839","contributorId":166770,"corporation":false,"usgs":true,"family":"Doherty","given":"Kyle","email":"kdoherty@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":706297,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"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":706298,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wood, Troy E. 0000-0002-1533-5714 twood@usgs.gov","orcid":"https://orcid.org/0000-0002-1533-5714","contributorId":4023,"corporation":false,"usgs":true,"family":"Wood","given":"Troy","email":"twood@usgs.gov","middleInitial":"E.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true},{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":706296,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70185163,"text":"70185163 - 2017 - Assessing the influence of sustainable trail design and maintenance on soil loss","interactions":[],"lastModifiedDate":"2017-03-15T16:04:40","indexId":"70185163","displayToPublicDate":"2017-03-15T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2258,"text":"Journal of Environmental Management","active":true,"publicationSubtype":{"id":10}},"title":"Assessing the influence of sustainable trail design and maintenance on soil loss","docAbstract":"Natural-surfaced trail systems are an important infrastructure component providing a means for accessing remote protected natural area destinations. The condition and usability of trails is a critical concern of land managers charged with providing recreational access while preserving natural conditions, and to visitors seeking high quality recreational opportunities and experiences. While an adequate number of trail management publications provide prescriptive guidance for designing, constructing, and maintaining natural-surfaced trails, surprisingly little research has been directed at providing a scientific basis for this guidance. Results from a review of the literature and three scientific studies are presented to model and clarify the influence of factors that substantially influence trail soil loss and that can be manipulated by trail professionals to sustain high traffic while minimizing soil loss over time. Key factors include trail grade, slope alignment angle, tread drainage features, and the amount of rock in tread substrates. A new Trail Sustainability Rating is developed and offered as a tool for evaluating or improving the sustainability of existing or new trails.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jenvman.2016.11.074","usgsCitation":"Marion, J.L., and Wimpey, J., 2017, Assessing the influence of sustainable trail design and maintenance on soil loss: Journal of Environmental Management, v. 189, p. 46-57, https://doi.org/10.1016/j.jenvman.2016.11.074.","productDescription":"12 p.","startPage":"46","endPage":"57","ipdsId":"IP-077133","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":461697,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jenvman.2016.11.074","text":"Publisher Index Page"},{"id":337667,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"189","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58ca52c6e4b0849ce97c867a","contributors":{"authors":[{"text":"Marion, Jeffrey L. 0000-0003-2226-689X jeff_marion@usgs.gov","orcid":"https://orcid.org/0000-0003-2226-689X","contributorId":3614,"corporation":false,"usgs":true,"family":"Marion","given":"Jeffrey","email":"jeff_marion@usgs.gov","middleInitial":"L.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":684572,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wimpey, Jeremy","contributorId":189354,"corporation":false,"usgs":false,"family":"Wimpey","given":"Jeremy","affiliations":[],"preferred":false,"id":684573,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70185013,"text":"70185013 - 2017 - Using maximum entropy to predict suitable habitat for the endangered dwarf wedgemussel in the Maryland Coastal Plain","interactions":[],"lastModifiedDate":"2017-04-19T16:09:34","indexId":"70185013","displayToPublicDate":"2017-03-14T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":862,"text":"Aquatic Conservation: Marine and Freshwater Ecosystems","active":true,"publicationSubtype":{"id":10}},"title":"Using maximum entropy to predict suitable habitat for the endangered dwarf wedgemussel in the Maryland Coastal Plain","docAbstract":"Although researchers agree that public participation in natural resource decision making is critical to institutional acceptance by stakeholders and the general public, the processes to gain public perceptions of fairness, agency trust, and acceptance of management decisions are not clear. Using results from a mail survey of Minnesota resident anglers, we used structural equation modeling to examine how instrumental versus symbolic motives related to anglers’ perceptions of agency fairness, trustworthiness, and ultimately acceptance of fisheries management decisions. We applied laboratory research on relationships among procedural fairness, trust, and management acceptance, and then tested models incorporating anglers’ perceptions of voice for anglers and nonanglers in management decisions. Results suggested that trust fully mediated the relationship between procedural fairness and management acceptance. Angler perceptions of angler and nonangler voice both related to views of procedural fairness, but angler voice was more strongly related and was also significantly related to acceptance of management decisions.
","language":"English","publisher":"Taylor & Francis","doi":"10.1080/08941920.2016.1238987","usgsCitation":"Schroeder, S., and Fulton, D.C., 2017, Voice, perceived fairness, agency trust, and acceptance of management decisions among Minnesota anglers: Society and Natural Resources, v. 30, no. 5, p. 569-584, https://doi.org/10.1080/08941920.2016.1238987.","productDescription":"16 p.","startPage":"569","endPage":"584","ipdsId":"IP-070493","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":337503,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"30","issue":"5","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2016-10-21","publicationStatus":"PW","scienceBaseUri":"58c90122e4b0849ce97abca2","contributors":{"authors":[{"text":"Schroeder, Susan A.","contributorId":78235,"corporation":false,"usgs":true,"family":"Schroeder","given":"Susan A.","affiliations":[],"preferred":false,"id":684214,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fulton, David C. 0000-0001-5763-7887 dcf@usgs.gov","orcid":"https://orcid.org/0000-0001-5763-7887","contributorId":2208,"corporation":false,"usgs":true,"family":"Fulton","given":"David","email":"dcf@usgs.gov","middleInitial":"C.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":684008,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ]}