Florida panthers are endangered pumas that currently persist in reduced patches of habitat in South Florida, USA. We performed mitogenome reference-based assemblies for most parental lines of the admixed Florida panthers that resulted from the introduction of female Texas pumas into South Florida in 1995. With the addition of 2 puma mitogenomes, we characterized 174 single nucleotide polymorphisms (SNPs) across 12 individuals. We defined 5 haplotypes (Pco1–Pco5), one of which (Pco1) had a geographic origin exclusive to Costa Rica and Panama and was possibly introduced into the Everglades National Park, Florida, prior to 1995. Haplotype Pco2 was native to Florida. Haplotypes Pco3 and Pco4 were exclusive to Texas, whereas haplotype Pco5 had an undetermined geographic origin. Phylogenetic inference suggests that haplotypes Pco1–Pco4 diverged ~202000 (95% HPDI = 83000–345000) years ago and that haplotypes Pco2–Pco4 diverged ~61000 (95% HPDI = 9000–127000) years ago. These results are congruent with a south-to-north continental expansion and with a recent North American colonization by pumas. Furthermore, pumas may have migrated from Texas to Florida no earlier than ~44000 (95% HPDI = 2000–98000) years ago. Synonymous mutations presented a greater mean substitution rate than other mitochondrial functional regions: nonsynonymous mutations, tRNAs, rRNAs, and control region. Similarly, all protein-coding genes were under predominant negative selection constraints. We directly and indirectly assessed the presence of potential deleterious SNPs in the ND2 and ND5 genes in Florida panthers prior to and as a consequence of the introduction of Texas pumas. Screenings for such variants are recommended in extant Florida panthers.
","language":"English","publisher":"Oxford","doi":"10.1093/jhered/esx015","usgsCitation":"Ochoa, A., Onorato, D.P., Fitak, R.R., Roelke-Parker, M., and Culver, M., 2017, Evolutionary and functional mitogenomics associated with the genetic restoration of the Florida panther: Journal of Heredity, v. 108, no. 4, p. 449-455, https://doi.org/10.1093/jhered/esx015.","productDescription":"7 p.","startPage":"449","endPage":"455","ipdsId":"IP-084509","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":490049,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/jhered/esx015","text":"Publisher Index Page"},{"id":348597,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"108","issue":"4","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2017-02-16","publicationStatus":"PW","scienceBaseUri":"5a06c8d1e4b09af898c86142","contributors":{"authors":[{"text":"Ochoa, Alexander","contributorId":169994,"corporation":false,"usgs":false,"family":"Ochoa","given":"Alexander","email":"","affiliations":[{"id":17653,"text":"School of Natural Resources & the Environment, The University of Arizona, Tucson","active":true,"usgs":false}],"preferred":false,"id":721648,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Onorato, David P.","contributorId":52704,"corporation":false,"usgs":true,"family":"Onorato","given":"David","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":721649,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fitak, Robert R.","contributorId":169991,"corporation":false,"usgs":false,"family":"Fitak","given":"Robert","email":"","middleInitial":"R.","affiliations":[{"id":12643,"text":"Duke University","active":true,"usgs":false},{"id":32413,"text":"University of Arizona, Tucson, AZ, USA, 85721","active":true,"usgs":false}],"preferred":false,"id":721650,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Roelke-Parker, Melody","contributorId":72715,"corporation":false,"usgs":true,"family":"Roelke-Parker","given":"Melody","affiliations":[],"preferred":false,"id":721651,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Culver, Melanie 0000-0001-5380-3059 mculver@usgs.gov","orcid":"https://orcid.org/0000-0001-5380-3059","contributorId":197693,"corporation":false,"usgs":true,"family":"Culver","given":"Melanie","email":"mculver@usgs.gov","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":719182,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70184967,"text":"70184967 - 2017 - Evaluating simplistic methods to understand current distributions and forecast distribution changes under climate change scenarios: An example with coypu (Myocastor coypus)","interactions":[],"lastModifiedDate":"2017-03-15T12:07:21","indexId":"70184967","displayToPublicDate":"2017-02-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5071,"text":"NeoBiota","active":true,"publicationSubtype":{"id":10}},"title":"Evaluating simplistic methods to understand current distributions and forecast distribution changes under climate change scenarios: An example with coypu (Myocastor coypus)","docAbstract":"Invasive species provide a unique opportunity to evaluate factors controlling biogeographic distributions; we can consider introduction success as an experiment testing suitability of environmental conditions. Predicting potential distributions of spreading species is not easy, and forecasting potential distributions with changing climate is even more difficult. Using the globally invasive coypu (Myocastor coypus [Molina, 1782]), we evaluate and compare the utility of a simplistic ecophysiological based model and a correlative model to predict current and future distribution. The ecophysiological model was based on winter temperature relationships with nutria survival. We developed correlative statistical models using the Software for Assisted Habitat Modeling and biologically relevant climate data with a global extent. We applied the ecophysiological based model to several global circulation model (GCM) predictions for mid-century. We used global coypu introduction data to evaluate these models and to explore a hypothesized physiological limitation, finding general agreement with known coypu distribution locally and globally and support for an upper thermal tolerance threshold. Global circulation model based model results showed variability in coypu predicted distribution among GCMs, but had general agreement of increasing suitable area in the USA. Our methods highlighted the dynamic nature of the edges of the coypu distribution due to climate non-equilibrium, and uncertainty associated with forecasting future distributions. Areas deemed suitable habitat, especially those on the edge of the current known range, could be used for early detection of the spread of coypu populations for management purposes. Combining approaches can be beneficial to predicting potential distributions of invasive species now and in the future and in exploring hypotheses of factors controlling distributions.
","language":"English","publisher":"Pensoft","doi":"10.3897/neobiota.32.8884","usgsCitation":"Jarnevich, C.S., Young, N.E., Sheffels, T.R., Carter, J., Systma, M.D., and Talbert, C., 2017, Evaluating simplistic methods to understand current distributions and forecast distribution changes under climate change scenarios: An example with coypu (Myocastor coypus): NeoBiota, v. 32, p. 107-125, https://doi.org/10.3897/neobiota.32.8884.","productDescription":"19 p.","startPage":"107","endPage":"125","ipdsId":"IP-065118","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":470099,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3897/neobiota.32.8884","text":"Publisher Index Page"},{"id":337613,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"32","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2017-01-04","publicationStatus":"PW","scienceBaseUri":"58ca52cce4b0849ce97c869a","contributors":{"authors":[{"text":"Jarnevich, Catherine S. 0000-0002-9699-2336 jarnevichc@usgs.gov","orcid":"https://orcid.org/0000-0002-9699-2336","contributorId":3424,"corporation":false,"usgs":true,"family":"Jarnevich","given":"Catherine","email":"jarnevichc@usgs.gov","middleInitial":"S.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":683741,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Young, Nicholas E.","contributorId":189060,"corporation":false,"usgs":false,"family":"Young","given":"Nicholas","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":683742,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sheffels, Trevor R.","contributorId":140176,"corporation":false,"usgs":false,"family":"Sheffels","given":"Trevor","email":"","middleInitial":"R.","affiliations":[{"id":6929,"text":"Portland State University","active":true,"usgs":false}],"preferred":false,"id":683743,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Carter, Jacoby 0000-0003-0110-0284 carterj@usgs.gov","orcid":"https://orcid.org/0000-0003-0110-0284","contributorId":2399,"corporation":false,"usgs":true,"family":"Carter","given":"Jacoby","email":"carterj@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":683744,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Systma, Mark D.","contributorId":140177,"corporation":false,"usgs":false,"family":"Systma","given":"Mark","email":"","middleInitial":"D.","affiliations":[{"id":13401,"text":"Portland State University, Portland Oregon","active":true,"usgs":false}],"preferred":false,"id":683745,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Talbert, Colin 0000-0002-9505-1876 talbertc@usgs.gov","orcid":"https://orcid.org/0000-0002-9505-1876","contributorId":181913,"corporation":false,"usgs":true,"family":"Talbert","given":"Colin","email":"talbertc@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":683746,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70182152,"text":"70182152 - 2017 - Identifying movement patterns and spawning areas of Lake Trout in Yellowstone Lake","interactions":[],"lastModifiedDate":"2017-02-20T12:07:16","indexId":"70182152","displayToPublicDate":"2017-02-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3802,"text":"Yellowstone Science","active":true,"publicationSubtype":{"id":10}},"title":"Identifying movement patterns and spawning areas of Lake Trout in Yellowstone Lake","docAbstract":"No abstract available.
","language":"English","publisher":"National Park Service","usgsCitation":"Gresswell, R.E., Heredia, N.A., Romine, J.G., Gutowsky, L.F., Sandstrom, P.T., Parsley, M.J., Bigelow, P.E., Suski, C.D., and Ertel, B.D., 2017, Identifying movement patterns and spawning areas of Lake Trout in Yellowstone Lake: Yellowstone Science, v. 25, no. 1, p. 66-69.","productDescription":"4 p.","startPage":"66","endPage":"69","ipdsId":"IP-075220","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":335839,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":335798,"type":{"id":15,"text":"Index Page"},"url":"https://www.nps.gov/yell/learn/yellowstone-science.htm"}],"volume":"25","issue":"1","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58ac0e2de4b0ce4410e7d5f4","contributors":{"authors":[{"text":"Gresswell, Robert E. 0000-0003-0063-855X bgresswell@usgs.gov","orcid":"https://orcid.org/0000-0003-0063-855X","contributorId":152031,"corporation":false,"usgs":true,"family":"Gresswell","given":"Robert","email":"bgresswell@usgs.gov","middleInitial":"E.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":669807,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Heredia, Nicholas A.","contributorId":181858,"corporation":false,"usgs":false,"family":"Heredia","given":"Nicholas","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":669808,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Romine, Jason G. 0000-0002-6938-1185 jromine@usgs.gov","orcid":"https://orcid.org/0000-0002-6938-1185","contributorId":2823,"corporation":false,"usgs":true,"family":"Romine","given":"Jason","email":"jromine@usgs.gov","middleInitial":"G.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":669809,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gutowsky, Lee F. 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G.","affiliations":[],"preferred":false,"id":669810,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sandstrom, Phillip T.","contributorId":181860,"corporation":false,"usgs":false,"family":"Sandstrom","given":"Phillip","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":669812,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Parsley, Michael J. 0000-0003-0097-6364 mparsley@usgs.gov","orcid":"https://orcid.org/0000-0003-0097-6364","contributorId":2608,"corporation":false,"usgs":true,"family":"Parsley","given":"Michael","email":"mparsley@usgs.gov","middleInitial":"J.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":669811,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bigelow, Patricia E.","contributorId":181861,"corporation":false,"usgs":false,"family":"Bigelow","given":"Patricia","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":669813,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Suski, C. D.","contributorId":181862,"corporation":false,"usgs":false,"family":"Suski","given":"C.","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":669814,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Ertel, Brian D.","contributorId":181863,"corporation":false,"usgs":false,"family":"Ertel","given":"Brian","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":669815,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70187165,"text":"70187165 - 2017 - Tracer-based characterization of hyporheic exchange and benthic biolayers in streams","interactions":[],"lastModifiedDate":"2017-04-25T15:20:57","indexId":"70187165","displayToPublicDate":"2017-02-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Tracer-based characterization of hyporheic exchange and benthic biolayers in streams","docAbstract":"Shallow benthic biolayers at the top of the streambed are believed to be places of enhanced biogeochemical turnover within the hyporheic zone. They can be investigated by reactive stream tracer tests with tracer recordings in the streambed and in the stream channel. Common in-stream measurements of such reactive tracers cannot localize where the processing primarily takes place, whereas isolated vertical depth profiles of solutes within the hyporheic zone are usually not representative of the entire stream. We present results of a tracer test where we injected the conservative tracer bromide together with the reactive tracer resazurin into a third-order stream and combined the recording of in-stream breakthrough curves with multidepth sampling of the hyporheic zone at several locations. The transformation of resazurin was used as an indicator of metabolism, and high-reactivity zones were identified from depth profiles. The results from our subsurface analysis indicate that the potential for tracer transformation (i.e., the reaction rate constant) varied with depth in the hyporheic zone. This highlights the importance of the benthic biolayer, which we found to be on average 2 cm thick in this study, ranging from one third to one half of the full depth of the hyporheic zone. The reach-scale approach integrated the effects of processes along the reach length, isolating hyporheic processes relevant for whole-stream chemistry and estimating effective reaction rates.
","language":"English","publisher":"American Geophysical Union","doi":"10.1002/2016WR019393","usgsCitation":"Knapp, J., Gonzalez-Pinzon, R., Drummond, J.D., Larsen, L., Cirpka, O.A., and Harvey, J.W., 2017, Tracer-based characterization of hyporheic exchange and benthic biolayers in streams: Water Resources Research, v. 53, no. 2, p. 1575-1594, https://doi.org/10.1002/2016WR019393.","productDescription":"20 p.","startPage":"1575","endPage":"1594","ipdsId":"IP-080169","costCenters":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"links":[{"id":470095,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2016wr019393","text":"Publisher Index Page"},{"id":340374,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"53","issue":"2","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2017-02-21","publicationStatus":"PW","scienceBaseUri":"59006062e4b0e85db3a5ddd1","contributors":{"authors":[{"text":"Knapp, Julia L.A.","contributorId":191389,"corporation":false,"usgs":false,"family":"Knapp","given":"Julia L.A.","affiliations":[],"preferred":false,"id":692887,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gonzalez-Pinzon, Ricardo","contributorId":191362,"corporation":false,"usgs":false,"family":"Gonzalez-Pinzon","given":"Ricardo","email":"","affiliations":[],"preferred":false,"id":692888,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Drummond, Jennifer D.","contributorId":191390,"corporation":false,"usgs":false,"family":"Drummond","given":"Jennifer","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":692889,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Larsen, Laurel G.","contributorId":191391,"corporation":false,"usgs":false,"family":"Larsen","given":"Laurel G.","affiliations":[],"preferred":false,"id":692890,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cirpka, Olaf A.","contributorId":191392,"corporation":false,"usgs":false,"family":"Cirpka","given":"Olaf","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":692891,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Harvey, Judson W. 0000-0002-2654-9873 jwharvey@usgs.gov","orcid":"https://orcid.org/0000-0002-2654-9873","contributorId":1796,"corporation":false,"usgs":true,"family":"Harvey","given":"Judson","email":"jwharvey@usgs.gov","middleInitial":"W.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":692886,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70196102,"text":"70196102 - 2017 - A global probabilistic tsunami hazard assessment from earthquake sources","interactions":[],"lastModifiedDate":"2018-03-21T11:38:48","indexId":"70196102","displayToPublicDate":"2017-02-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1791,"text":"Geological Society, London, Special Publications","active":true,"publicationSubtype":{"id":10}},"title":"A global probabilistic tsunami hazard assessment from earthquake sources","docAbstract":"Large tsunamis occur infrequently but have the capacity to cause enormous numbers of casualties, damage to the built environment and critical infrastructure, and economic losses. A sound understanding of tsunami hazard is required to underpin management of these risks, and while tsunami hazard assessments are typically conducted at regional or local scales, globally consistent assessments are required to support international disaster risk reduction efforts, and can serve as a reference for local and regional studies. This study presents a global-scale probabilistic tsunami hazard assessment (PTHA), extending previous global-scale assessments based largely on scenario analysis. Only earthquake sources are considered, as they represent about 80% of the recorded damaging tsunami events. Globally extensive estimates of tsunami run-up height are derived at various exceedance rates, and the associated uncertainties are quantified. Epistemic uncertainties in the exceedance rates of large earthquakes often lead to large uncertainties in tsunami run-up. Deviations between modelled tsunami run-up and event observations are quantified, and found to be larger than suggested in previous studies. Accounting for these deviations in PTHA is important, as it leads to a pronounced increase in predicted tsunami run-up for a given exceedance rate.
","language":"English","publisher":"The Geological Society of London","doi":"10.1144/SP456.5","usgsCitation":"Davies, G., Griffin, J., Lovholt, F., Glimsdal, S., Harbitz, C., Thio, H.K., Lorito, S., Basili, R., Selva, J., Geist, E.L., and Baptista, M.A., 2017, A global probabilistic tsunami hazard assessment from earthquake sources: Geological Society, London, Special Publications, v. 456, p. 219-244, https://doi.org/10.1144/SP456.5.","productDescription":"26 p.","startPage":"219","endPage":"244","ipdsId":"IP-071828","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":352688,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"456","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2017-02-23","publicationStatus":"PW","scienceBaseUri":"5afee8d3e4b0da30c1bfc4b6","contributors":{"authors":[{"text":"Davies, Gareth","contributorId":201783,"corporation":false,"usgs":false,"family":"Davies","given":"Gareth","email":"","affiliations":[{"id":35920,"text":"Geoscience Australia","active":true,"usgs":false}],"preferred":false,"id":731351,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Griffin, Jonathan","contributorId":201786,"corporation":false,"usgs":false,"family":"Griffin","given":"Jonathan","email":"","affiliations":[{"id":35920,"text":"Geoscience Australia","active":true,"usgs":false}],"preferred":false,"id":731352,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lovholt, Finn","contributorId":203385,"corporation":false,"usgs":false,"family":"Lovholt","given":"Finn","email":"","affiliations":[{"id":36607,"text":"NGI","active":true,"usgs":false}],"preferred":false,"id":731353,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Glimsdal, Sylfest","contributorId":203386,"corporation":false,"usgs":false,"family":"Glimsdal","given":"Sylfest","email":"","affiliations":[{"id":36607,"text":"NGI","active":true,"usgs":false}],"preferred":false,"id":731354,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Harbitz, Carl","contributorId":203387,"corporation":false,"usgs":false,"family":"Harbitz","given":"Carl","affiliations":[{"id":36607,"text":"NGI","active":true,"usgs":false}],"preferred":false,"id":731355,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Thio, Hong Kie","contributorId":203388,"corporation":false,"usgs":false,"family":"Thio","given":"Hong","email":"","middleInitial":"Kie","affiliations":[{"id":13386,"text":"AECOM","active":true,"usgs":false}],"preferred":false,"id":731356,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Lorito, Stefano","contributorId":203389,"corporation":false,"usgs":false,"family":"Lorito","given":"Stefano","email":"","affiliations":[{"id":5113,"text":"INGV","active":true,"usgs":false}],"preferred":false,"id":731357,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Basili, Roberto","contributorId":203390,"corporation":false,"usgs":false,"family":"Basili","given":"Roberto","email":"","affiliations":[{"id":5113,"text":"INGV","active":true,"usgs":false}],"preferred":false,"id":731358,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Selva, Jacopo","contributorId":203391,"corporation":false,"usgs":false,"family":"Selva","given":"Jacopo","email":"","affiliations":[{"id":5113,"text":"INGV","active":true,"usgs":false}],"preferred":false,"id":731359,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Geist, Eric L. 0000-0003-0611-1150 egeist@usgs.gov","orcid":"https://orcid.org/0000-0003-0611-1150","contributorId":1956,"corporation":false,"usgs":true,"family":"Geist","given":"Eric","email":"egeist@usgs.gov","middleInitial":"L.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true}],"preferred":true,"id":731350,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Baptista, Maria Ana","contributorId":203392,"corporation":false,"usgs":false,"family":"Baptista","given":"Maria","email":"","middleInitial":"Ana","affiliations":[{"id":36608,"text":"IPMA","active":true,"usgs":false}],"preferred":false,"id":731360,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70189597,"text":"70189597 - 2017 - Four new species of Eimeria (Apicomplexa: Eimeriidae) from Emoia spp. Skinks (Sauria: Scincidae), from Papua New Guinea and the Insular Pacific","interactions":[],"lastModifiedDate":"2017-07-18T12:03:52","indexId":"70189597","displayToPublicDate":"2017-02-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2414,"text":"Journal of Parasitology","active":true,"publicationSubtype":{"id":10}},"title":"Four new species of Eimeria (Apicomplexa: Eimeriidae) from Emoia spp. Skinks (Sauria: Scincidae), from Papua New Guinea and the Insular Pacific","docAbstract":"Between September and November 1991, 54 adult skinks from 15 species were collected by hand or blowpipe from several localities on Rarotonga, Cook Islands, Ovalau Island, Fiji, and Papua New Guinea (PNG), and their feces were examined for coccidians. Species included 5 seaside skinks (Emoia atrocostata), 1 Pacific blue-tailed skink (Emoia caeroleocauda), 2 Fiji slender treeskinks (Emoia concolor), 15 white-bellied copper-striped skinks (Emoia cyanura), 1 Bulolo River forest skink (Emoia guttata), 6 dark-bellied copper-striped skinks (Emoia impar), 5 Papua five-striped skinks (Emoia jakati), 2 Papua slender treeskinks (Emoia kordoana), 3 Papua robust treeskinks (Emoia longicauda), 1 brown-backed forest skink (Emoia loveridgei), 3 Papua black-sided skinks (Emoia pallidiceps), 2 Papua white-spotted skinks (Emoia physicae), 2 Papua yellow-head skinks (Emoia popei), 1 Papua brown forest skink (Emoia submetallica), and 5 Fiji barred treeskinks (Emoia trossula) Species of Eimeria (Ei.) were detected from these Emoia (Em.) spp. and are described here as new. Oocysts of Eimeria iovai n. sp. from Em. pallidiceps from PNG were ellipsoidal with a bilayered wall (L × W) 26.5 × 18.1 μm, with a length/width ratio (L/W) of 1.1. Both micropyle and oocyst residuum were absent, but a fragmented polar granule was present. This eimerian also was found in Em. atrocostata from PNG. Oocysts of Eimeria kirkpatricki n. sp. from Em. atrocostata from PNG were ellipsoidal with a bilayered wall, 18.6 × 13.5 μm, L/W 1.4. A micropyle and oocyst residuum were absent, but a fragmented polar granule was present. This eimerian was also shared by Em. cyanura from the Cook Islands and Fiji, Em. imparfrom the Cook Islands, Em. loveridgei from PNG, Em. pallidicepsfrom PNG, Em. popei from PNG, and Em. submetallica from PNG. Oocysts of Eimeria stevejayuptoni n. sp. from Em. longicaudawere subspheroidal to ellipsoidal with a bilayered wall, 18.7 × 16.6 μm, L/W 1.1. A micropyle and oocyst residuum were absent, but a fragmented polar granule was present. Oocysts of Eimeria emoia n. sp. from Em. longicauda from PNG were cylindroidal with a bilayered wall, 29.2 × 15.7 μm, L/W 1.9. A micropyle and oocyst residuum were absent, but a polar granule was present. These are the first eimerians reported from Emoia spp. and they add to our growing knowledge of the coccidian fauna of scincid lizards of the South Pacific.
","language":"English","publisher":"American Society of Parasitologists","doi":"10.1645/16-67","usgsCitation":"McAllister, C.T., Duszynski, D.W., Austin, C., and Fisher, R.N., 2017, Four new species of Eimeria (Apicomplexa: Eimeriidae) from Emoia spp. Skinks (Sauria: Scincidae), from Papua New Guinea and the Insular Pacific: Journal of Parasitology, v. 103, no. 1, p. 103-110, https://doi.org/10.1645/16-67.","productDescription":"8 p.","startPage":"103","endPage":"110","ipdsId":"IP-078006","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":343987,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Papua New Guinea","otherGeospatial":"Insular Pacific","volume":"103","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"596f1e25e4b0d1f9f0640756","contributors":{"authors":[{"text":"McAllister, Chris T.","contributorId":22704,"corporation":false,"usgs":true,"family":"McAllister","given":"Chris","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":705341,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Duszynski, Donald W.","contributorId":87869,"corporation":false,"usgs":true,"family":"Duszynski","given":"Donald","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":705342,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Austin, Christopher C.","contributorId":8772,"corporation":false,"usgs":true,"family":"Austin","given":"Christopher C.","affiliations":[],"preferred":false,"id":705343,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fisher, Robert N. 0000-0002-2956-3240 rfisher@usgs.gov","orcid":"https://orcid.org/0000-0002-2956-3240","contributorId":1529,"corporation":false,"usgs":true,"family":"Fisher","given":"Robert","email":"rfisher@usgs.gov","middleInitial":"N.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":705344,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70195760,"text":"70195760 - 2017 - Building the vegetation drought response index for Canada (VegDRI-Canada) to monitor agricultural drought: first results","interactions":[],"lastModifiedDate":"2018-02-28T14:03:02","indexId":"70195760","displayToPublicDate":"2017-02-01T00:00:00","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":"Building the vegetation drought response index for Canada (VegDRI-Canada) to monitor agricultural drought: first results","docAbstract":"Drought is a natural climatic phenomenon that occurs throughout the world and impacts many sectors of society. To help decision-makers reduce the impacts of drought, it is important to improve monitoring tools that provide relevant and timely information in support of drought mitigation decisions. Given that drought is a complex natural hazard that manifests in different forms, monitoring can be improved by integrating various types of information (e.g., remote sensing and climate) that is timely and region specific to identify where and when droughts are occurring. The Vegetation Drought Response Index for Canada (VegDRI-Canada) is a recently developed drought monitoring tool for Canada. VegDRI-Canada extends the initial VegDRI concept developed for the conterminous United States to a broader transnational coverage across North America. VegDRI-Canada models are similar to those developed for the United States, integrating satellite observations of vegetation status, climate data, and biophysical information on land use and land cover, soil characteristics, and other environmental factors. Collectively, these different types of data are integrated into the hybrid VegDRI-Canada to isolate the effects of drought on vegetation. Twenty-three weekly VegDRI-Canada models were built for the growing season (April–September) through the weekly analysis of these data using a regression tree-based data mining approach. A 15-year time series of VegDRI-Canada results (s to 2014) was produced using these models and the output was validated by randomly selecting 20% of the historical data, as well as holdout year (15% unseen data) across the growing season that the Pearson’s correlation ranged from 0.6 to 0.77. A case study was also conducted to evaluate the VegDRI-Canada results over the prairie region of Canada for two drought years and one non-drought year for three weekly periods of the growing season (i.e., early-, mid-, and late season). The comparison of the VegDRI-Canada map with the Canadian Drought Monitor (CDM), an independent drought indicator, showed that the VegDRI-Canada maps depicted key spatial drought severity patterns during the two targeted drought years consistent with the CDM. In addition, VegDRI-Canada was compared with canola yields in the Prairie Provinces at the regional scale for a period from 2000 to 2014 to evaluate the indices’ applicability for monitoring drought impacts on crop production. The result showed that VegDRI-Canada values had a relatively higher correlation (i.e., r > 0.5) with canola yield for nonirrigated croplands in the Canadian Prairies region in areas where drought is typically a limiting factor on crop growth, but showed a negative relationship in the southeastern Prairie region, where water availability is less of a limiting factor and in some cases a hindrance to crop growth when waterlogging occurs. These initial results demonstrate VegDRI-Canada’s utility for monitoring drought-related vegetation conditions, particularly in drought prone areas. In general, the results indicated that the VegDRI-Canada models showed sensitivity to known agricultural drought events in Canada over the 15-year period mainly for nonirrigated areas.
","language":"English","publisher":"Taylor & Francis","doi":"10.1080/15481603.2017.1286728","usgsCitation":"Tadesse, T., Champagne, C., Wardlow, B.D., Hadwen, T.A., Brown, J.F., Demisse, G.B., Bayissa, Y.A., and Davidson, A.M., 2017, Building the vegetation drought response index for Canada (VegDRI-Canada) to monitor agricultural drought: first results: GIScience and Remote Sensing, v. 54, no. 2, p. 230-257, https://doi.org/10.1080/15481603.2017.1286728.","productDescription":"28 p.","startPage":"230","endPage":"257","ipdsId":"IP-082660","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":499999,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doaj.org/article/99a8bce08c6143daaa4fc548ecdb117b","text":"External Repository"},{"id":352144,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -138.779296875,\n 41.83682786072714\n ],\n [\n -51.67968749999999,\n 41.83682786072714\n ],\n [\n -51.67968749999999,\n 60\n ],\n [\n -138.779296875,\n 60\n ],\n [\n -138.779296875,\n 41.83682786072714\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"54","issue":"2","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2017-02-08","publicationStatus":"PW","scienceBaseUri":"5afee8d3e4b0da30c1bfc4bc","contributors":{"authors":[{"text":"Tadesse, Tsegaye 0000-0002-4102-1137","orcid":"https://orcid.org/0000-0002-4102-1137","contributorId":147617,"corporation":false,"usgs":false,"family":"Tadesse","given":"Tsegaye","email":"","affiliations":[],"preferred":false,"id":729876,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Champagne, Catherine","contributorId":202836,"corporation":false,"usgs":false,"family":"Champagne","given":"Catherine","email":"","affiliations":[{"id":27920,"text":"Agriculture and Agrifood Canada","active":true,"usgs":false}],"preferred":false,"id":729877,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wardlow, Brian D. 0000-0002-4767-581X","orcid":"https://orcid.org/0000-0002-4767-581X","contributorId":191403,"corporation":false,"usgs":false,"family":"Wardlow","given":"Brian","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":729878,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hadwen, Trevor A.","contributorId":202837,"corporation":false,"usgs":false,"family":"Hadwen","given":"Trevor","email":"","middleInitial":"A.","affiliations":[{"id":27920,"text":"Agriculture and Agrifood Canada","active":true,"usgs":false}],"preferred":false,"id":729879,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Brown, Jesslyn F. 0000-0002-9976-1998 jfbrown@usgs.gov","orcid":"https://orcid.org/0000-0002-9976-1998","contributorId":176609,"corporation":false,"usgs":true,"family":"Brown","given":"Jesslyn","email":"jfbrown@usgs.gov","middleInitial":"F.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":729875,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Demisse, Getachew B.","contributorId":202845,"corporation":false,"usgs":false,"family":"Demisse","given":"Getachew","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":729894,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bayissa, Yared A.","contributorId":202846,"corporation":false,"usgs":false,"family":"Bayissa","given":"Yared","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":729895,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Davidson, Andrew M.","contributorId":202847,"corporation":false,"usgs":false,"family":"Davidson","given":"Andrew","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":729896,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70195840,"text":"70195840 - 2017 - Using diurnal temperature signals to infer vertical groundwater-surface water exchange","interactions":[],"lastModifiedDate":"2018-03-06T11:07:46","indexId":"70195840","displayToPublicDate":"2017-02-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3825,"text":"Groundwater","active":true,"publicationSubtype":{"id":10}},"title":"Using diurnal temperature signals to infer vertical groundwater-surface water exchange","docAbstract":"Heat is a powerful tracer to quantify fluid exchange between surface water and groundwater. Temperature time series can be used to estimate pore water fluid flux, and techniques can be employed to extend these estimates to produce detailed plan-view flux maps. Key advantages of heat tracing include cost-effective sensors and ease of data collection and interpretation, without the need for expensive and time-consuming laboratory analyses or induced tracers. While the collection of temperature data in saturated sediments is relatively straightforward, several factors influence the reliability of flux estimates that are based on time series analysis (diurnal signals) of recorded temperatures. Sensor resolution and deployment are particularly important in obtaining robust flux estimates in upwelling conditions. Also, processing temperature time series data involves a sequence of complex steps, including filtering temperature signals, selection of appropriate thermal parameters, and selection of the optimal analytical solution for modeling. This review provides a synthesis of heat tracing using diurnal temperature oscillations, including details on optimal sensor selection and deployment, data processing, model parameterization, and an overview of computing tools available. Recent advances in diurnal temperature methods also provide the opportunity to determine local saturated thermal diffusivity, which can improve the accuracy of fluid flux modeling and sensor spacing, which is related to streambed scour and deposition. These parameters can also be used to determine the reliability of flux estimates from the use of heat as a tracer.
","language":"English","publisher":"Wiley","doi":"10.1111/gwat.12459","usgsCitation":"Irvine, D.J., Briggs, M.A., Lautz, L.K., Gordon, R.P., McKenzie, J.M., and Cartwright, I., 2017, Using diurnal temperature signals to infer vertical groundwater-surface water exchange: Groundwater, v. 55, no. 1, p. 10-26, https://doi.org/10.1111/gwat.12459.","productDescription":"17 p.","startPage":"10","endPage":"26","ipdsId":"IP-077274","costCenters":[{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true}],"links":[{"id":470089,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/gwat.12459","text":"Publisher Index Page"},{"id":352253,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"55","issue":"1","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2016-10-03","publicationStatus":"PW","scienceBaseUri":"5afee8d3e4b0da30c1bfc4b8","contributors":{"authors":[{"text":"Irvine, Dylan J.","contributorId":190404,"corporation":false,"usgs":false,"family":"Irvine","given":"Dylan","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":730252,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Briggs, Martin A. 0000-0003-3206-4132 mbriggs@usgs.gov","orcid":"https://orcid.org/0000-0003-3206-4132","contributorId":4114,"corporation":false,"usgs":true,"family":"Briggs","given":"Martin","email":"mbriggs@usgs.gov","middleInitial":"A.","affiliations":[{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true},{"id":493,"text":"Office of Ground Water","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":730251,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lautz, Laura K.","contributorId":124523,"corporation":false,"usgs":false,"family":"Lautz","given":"Laura","email":"","middleInitial":"K.","affiliations":[{"id":5082,"text":"Syracuse University","active":true,"usgs":false}],"preferred":false,"id":730253,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gordon, Ryan P.","contributorId":202947,"corporation":false,"usgs":false,"family":"Gordon","given":"Ryan","email":"","middleInitial":"P.","affiliations":[{"id":7257,"text":"Maine Geological Survey","active":true,"usgs":false}],"preferred":false,"id":730254,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McKenzie, Jeffrey M.","contributorId":176299,"corporation":false,"usgs":false,"family":"McKenzie","given":"Jeffrey","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":730255,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Cartwright, Ian","contributorId":190405,"corporation":false,"usgs":false,"family":"Cartwright","given":"Ian","affiliations":[],"preferred":false,"id":730256,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70187249,"text":"70187249 - 2017 - Hard choices in assessing survival past dams — a comparison of single- and paired-release strategies","interactions":[],"lastModifiedDate":"2017-04-28T13:12:55","indexId":"70187249","displayToPublicDate":"2017-02-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1169,"text":"Canadian Journal of Fisheries and Aquatic Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Hard choices in assessing survival past dams — a comparison of single- and paired-release strategies","docAbstract":"Mark–recapture models are widely used to estimate survival of salmon smolts migrating past dams. Paired releases have been used to improve estimate accuracy by removing components of mortality not attributable to the dam. This method is accompanied by reduced precision because (i) sample size is reduced relative to a single, large release; and (ii) variance calculations inflate error. We modeled an idealized system with a single dam to assess trade-offs between accuracy and precision and compared methods using root mean squared error (RMSE). Simulations were run under predefined conditions (dam mortality, background mortality, detection probability, and sample size) to determine scenarios when the paired release was preferable to a single release. We demonstrate that a paired-release design provides a theoretical advantage over a single-release design only at large sample sizes and high probabilities of detection. At release numbers typical of many survival studies, paired release can result in overestimation of dam survival. Failures to meet model assumptions of a paired release may result in further overestimation of dam-related survival. Under most conditions, a single-release strategy was preferable.
","language":"English","publisher":"NRC Research Press","doi":"10.1139/cjfas-2015-0480","usgsCitation":"Zydlewski, J.D., Stich, D.S., and Sigourney, D.B., 2017, Hard choices in assessing survival past dams — a comparison of single- and paired-release strategies: Canadian Journal of Fisheries and Aquatic Sciences, v. 74, no. 2, p. 178-190, https://doi.org/10.1139/cjfas-2015-0480.","productDescription":"13 p.","startPage":"178","endPage":"190","ipdsId":"IP-060342","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":501116,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/1807/73671","text":"External Repository"},{"id":340614,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"74","issue":"2","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"590454a2e4b022cee40dc226","contributors":{"authors":[{"text":"Zydlewski, Joseph D. 0000-0002-2255-2303 jzydlewski@usgs.gov","orcid":"https://orcid.org/0000-0002-2255-2303","contributorId":2004,"corporation":false,"usgs":true,"family":"Zydlewski","given":"Joseph","email":"jzydlewski@usgs.gov","middleInitial":"D.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":false,"id":693107,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stich, Daniel S.","contributorId":139212,"corporation":false,"usgs":false,"family":"Stich","given":"Daniel","email":"","middleInitial":"S.","affiliations":[{"id":12606,"text":"University of Maine, Dept of Plant, Soil, & Envir Sciences","active":true,"usgs":false}],"preferred":false,"id":693486,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sigourney, Douglas B.","contributorId":103068,"corporation":false,"usgs":true,"family":"Sigourney","given":"Douglas","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":693487,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70188375,"text":"70188375 - 2017 - Multi-year microbial source tracking study characterizing fecal contamination in an urban watershed","interactions":[],"lastModifiedDate":"2017-06-07T14:04:58","indexId":"70188375","displayToPublicDate":"2017-02-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3711,"text":"Water Environment Research","active":true,"publicationSubtype":{"id":10}},"title":"Multi-year microbial source tracking study characterizing fecal contamination in an urban watershed","docAbstract":"Microbiological and hydrological data were used to rank tributary stream contributions of bacteria to the Little Blue River in Independence, Missouri. Concentrations, loadings and yields of E. coli and microbial source tracking (MST) markers, were characterized during base flow and storm events in five subbasins within Independence, as well as sources entering and leaving the city through the river. The E. coli water quality threshold was exceeded in 29% of base-flow and 89% of storm-event samples. The total contribution of E. coli and MST markers from tributaries within Independence to the Little Blue River, regardless of streamflow, did not significantly increase the median concentrations leaving the city. Daily loads and yields of E. coli and MST markers were used to rank the subbasins according to their contribution of each constituent to the river. The ranking methodology used in this study may prove useful in prioritizing remediation in the different subbasins.
","language":"English","publisher":"Water Environment Federation","doi":"10.2175/106143016X14798353399412","collaboration":"City of Independence, Missouri Water Pollution Control Station","usgsCitation":"Bushon, R.N., Brady, A.M., Christensen, E.D., and Stelzer, E.A., 2017, Multi-year microbial source tracking study characterizing fecal contamination in an urban watershed: Water Environment Research, v. 89, no. 2, p. 127-143, https://doi.org/10.2175/106143016X14798353399412.","productDescription":"17 p.","startPage":"127","endPage":"143","ipdsId":"IP-069132","costCenters":[{"id":513,"text":"Ohio Water Science Center","active":true,"usgs":true}],"links":[{"id":342249,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Missouri","city":"Independence","otherGeospatial":"Little Blue River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": 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Center","active":true,"usgs":true}],"preferred":true,"id":697453,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stelzer, Erin A. 0000-0001-7645-7603 eastelzer@usgs.gov","orcid":"https://orcid.org/0000-0001-7645-7603","contributorId":1933,"corporation":false,"usgs":true,"family":"Stelzer","given":"Erin","email":"eastelzer@usgs.gov","middleInitial":"A.","affiliations":[{"id":513,"text":"Ohio Water Science Center","active":true,"usgs":true},{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":697454,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70188352,"text":"70188352 - 2017 - Oxygen isotope geochemistry of mafic phenocrysts in primitive mafic lavas from the southernmost Cascade Range, California","interactions":[],"lastModifiedDate":"2018-03-16T11:29:21","indexId":"70188352","displayToPublicDate":"2017-02-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":738,"text":"American Mineralogist","active":true,"publicationSubtype":{"id":10}},"title":"Oxygen isotope geochemistry of mafic phenocrysts in primitive mafic lavas from the southernmost Cascade Range, California","docAbstract":"Previously reported whole-rock δ18O values (5.6–7.8‰) for primitive quaternary mafic lavas from the southernmost Cascades (SMC) are often elevated (up to 1‰) relative to δ18O values expected for mafic magmas in equilibrium with mantle peridotite. Olivine, clinopyroxene, and plagioclase crystals were separated from 29 geochemically well-characterized mafic lavas for δ18O measurements by laser fluorination to assess modification of the mantle sources by ancient and modern subducted components. Oxygen isotope values of olivine phenocrysts in calc-alkaline lavas and contemporaneous high alumina olivine tholeiitic (HAOT) lavas generally exceed depleted mantle olivine values (~4.9–5.3‰). Modern addition of up to 6 wt% slab-derived fluid from Gorda serpentinized peridotite dehydration (~15‰) or chlorite dehydration (~10‰) within the serpentinized peridotite can provide the 18O enrichment detected in olivine phenocrysts (δ18Oolivine = 5.3–6.3‰) in calc-alkaline mafic lavas, and elevate 18O in overlying mantle lithosphere, as well. Specifically, although HAOT δ18Oolivine values (5.5–5.7‰) may reflect partial melting in heterogeneous 18O enriched mantle source domains that developed during multiple subduction events associated with terrane accretion (e.g., <1 wt% of ~15‰ materials), an additional 18O enrichment of up to 2 wt% of 10–15‰ slab-derived hydrous fluids might be accommodated. The calc-alkaline primitive magmas appear to have experienced a continuous range of open system processes, which operate in the mantle and during rapid magma ascent to eruption, and occasionally post quench. Textural relationships and geochemistry of these lava samples are consistent with blends of mafic phenocrysts and degassed melts in varying states of 18O disequilibrium. In lenses of accumulated melt within peridotite near the base of the crust, coexisting olivine and clinopyroxene δ18O values probably are not at isotopic equilibrium because fluids introduced into the system perturbed the δ18Omelt values. A “sudden” melt extraction event interrupts 18O equilibration in phenocrysts and poorly mixed melt(s). Rapid ascent of volatile oversaturated primitive mafic magma through the crust appears to be accompanied by devolatilization and crystallization of anorthite-rich plagioclase with elevated δ18Oplag values. The (Sr/P)N values for the whole rock geochemistry are consistent with a 87Sr/86Sr ~0.7027 slab-derived fluid addition into the infertile peridotite source of magmas, and melt devolatilization is recorded in the mixture of disequilibrium δ18O values for the constituent phases of lavas. Morbidity of the Gorda Plate as it undergoes intense deformation from the spreading ridge to the trench is likely a key factor to developing the carrying capacity of hydrous fluids and mineral phases in the slab subducting into the SMC mantle.
","language":"English","publisher":"Mineralogical Society of America","doi":"10.2138/am-2017-5588","usgsCitation":"Underwood, S.J., and Clynne, M.A., 2017, Oxygen isotope geochemistry of mafic phenocrysts in primitive mafic lavas from the southernmost Cascade Range, California: American Mineralogist, v. 102, no. 2, p. 251-261, https://doi.org/10.2138/am-2017-5588.","productDescription":"11 p.","startPage":"251","endPage":"261","ipdsId":"IP-075965","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":352601,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Cascade Range","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.4920654296875,\n 39.9434364619742\n ],\n [\n -120.794677734375,\n 39.9434364619742\n ],\n [\n -120.794677734375,\n 40.990264773996884\n ],\n [\n -122.4920654296875,\n 40.990264773996884\n ],\n [\n -122.4920654296875,\n 39.9434364619742\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"102","issue":"2","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2017-02-01","publicationStatus":"PW","scienceBaseUri":"5afee8d3e4b0da30c1bfc4be","contributors":{"authors":[{"text":"Underwood, Sandra J.","contributorId":192684,"corporation":false,"usgs":false,"family":"Underwood","given":"Sandra","email":"","middleInitial":"J.","affiliations":[{"id":13628,"text":"Department of Earth Sciences, P.O. Box 173480, Montana State University, Bozeman, MT, USA. 59717.","active":true,"usgs":false}],"preferred":false,"id":697361,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Clynne, Michael A. 0000-0002-4220-2968 mclynne@usgs.gov","orcid":"https://orcid.org/0000-0002-4220-2968","contributorId":2032,"corporation":false,"usgs":true,"family":"Clynne","given":"Michael","email":"mclynne@usgs.gov","middleInitial":"A.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":697360,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70185621,"text":"70185621 - 2017 - Quarterly wildlife mortality report January 2017","interactions":[],"lastModifiedDate":"2023-10-13T14:08:42.205973","indexId":"70185621","displayToPublicDate":"2017-02-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3769,"text":"Wildlife Disease Association Newsletter","active":true,"publicationSubtype":{"id":10}},"title":"Quarterly wildlife mortality report January 2017","docAbstract":"No abstract available.
","language":"English","publisher":"Wildlife Disease Association","usgsCitation":"Richards, B.J., Grear, D.A., Ballmann, A., Dusek, R.J., and Bodenstein, B., 2017, Quarterly wildlife mortality report January 2017: Wildlife Disease Association Newsletter, HTML Document.","productDescription":"HTML Document","ipdsId":"IP-082240","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":338351,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.er.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":338322,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.wildlifedisease.org/PersonifyEbusiness/Resources/Publications/Newsletter/Archive"}],"publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58da2519e4b0543bf7fda7f6","contributors":{"authors":[{"text":"Richards, Bryan J. 0000-0001-9955-2523 brichards@usgs.gov","orcid":"https://orcid.org/0000-0001-9955-2523","contributorId":3533,"corporation":false,"usgs":true,"family":"Richards","given":"Bryan","email":"brichards@usgs.gov","middleInitial":"J.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":686140,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Grear, Daniel A. 0000-0002-5478-1549 dgrear@usgs.gov","orcid":"https://orcid.org/0000-0002-5478-1549","contributorId":189819,"corporation":false,"usgs":true,"family":"Grear","given":"Daniel","email":"dgrear@usgs.gov","middleInitial":"A.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":686141,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ballmann, Anne 0000-0002-0380-056X aballmann@usgs.gov","orcid":"https://orcid.org/0000-0002-0380-056X","contributorId":140319,"corporation":false,"usgs":true,"family":"Ballmann","given":"Anne","email":"aballmann@usgs.gov","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":686142,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dusek, Robert J. 0000-0001-6177-7479 rdusek@usgs.gov","orcid":"https://orcid.org/0000-0001-6177-7479","contributorId":174374,"corporation":false,"usgs":true,"family":"Dusek","given":"Robert","email":"rdusek@usgs.gov","middleInitial":"J.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":686143,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bodenstein, Barbara L. 0000-0001-7946-0103 bbodenstein@usgs.gov","orcid":"https://orcid.org/0000-0001-7946-0103","contributorId":189820,"corporation":false,"usgs":true,"family":"Bodenstein","given":"Barbara","email":"bbodenstein@usgs.gov","middleInitial":"L.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":686144,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70182235,"text":"70182235 - 2017 - Predicting animal home-range structure and transitions using a multistate Ornstein-Uhlenbeck biased random walk","interactions":[],"lastModifiedDate":"2018-03-26T12:17:16","indexId":"70182235","displayToPublicDate":"2017-02-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1465,"text":"Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Predicting animal home-range structure and transitions using a multistate Ornstein-Uhlenbeck biased random walk","docAbstract":"The home‐range concept is central in animal ecology and behavior, and numerous mechanistic models have been developed to understand home range formation and maintenance. These mechanistic models usually assume a single, contiguous home range. Here we describe and implement a simple home‐range model that can accommodate multiple home‐range centers, form complex shapes, allow discontinuities in use patterns, and infer how external and internal variables affect movement and use patterns. The model assumes individuals associate with two or more home‐range centers and move among them with some estimable probability. Movement in and around home‐range centers is governed by a two‐dimensional Ornstein‐Uhlenbeck process, while transitions between centers are modeled as a stochastic state‐switching process. We augmented this base model by introducing environmental and demographic covariates that modify transition probabilities between home‐range centers and can be estimated to provide insight into the movement process. We demonstrate the model using telemetry data from sea otters (Enhydra lutris) in California. The model was fit using a Bayesian Markov Chain Monte Carlo method, which estimated transition probabilities, as well as unique Ornstein‐Uhlenbeck diffusion and centralizing tendency parameters. Estimated parameters could then be used to simulate movement and space use that was virtually indistinguishable from real data. We used Deviance Information Criterion (DIC) scores to assess model fit and determined that both wind and reproductive status were predictive of transitions between home‐range centers. Females were less likely to move between home‐range centers on windy days, less likely to move between centers when tending pups, and much more likely to move between centers just after weaning a pup. These tendencies are predicted by theoretical movement rules but were not previously known and show that our model can extract meaningful behavioral insight from complex movement data.
Morphodynamic equilibrium is a widely adopted yet elusive concept in the field of geomorphology of coasts, rivers and estuaries. Based on the Exner equation, an expression of mass conservation of sediment, we distinguish three types of equilibrium defined as static and dynamic, of which two different types exist. Other expressions such as statistical and quasi-equilibrium which do not strictly satisfy the Exner conditions are also acknowledged for their practical use. The choice of a temporal scale is imperative to analyse the type of equilibrium. We discuss the difference between morphodynamic equilibrium in the “real world” (nature) and the “virtual world” (model). Modelling studies rely on simplifications of the real world and lead to understanding of process interactions. A variety of factors affect the use of virtual-world predictions in the real world (e.g., variability in environmental drivers and variability in the setting) so that the concept of morphodynamic equilibrium should be mathematically unequivocal in the virtual world and interpreted over the appropriate spatial and temporal scale in the real world. We draw examples from estuarine settings which are subject to various governing factors which broadly include hydrodynamics, sedimentology and landscape setting. Following the traditional “tide-wave-river” ternary diagram, we summarize studies to date that explore the “virtual world”, discuss the type of equilibrium reached and how it relates to the real world.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.earscirev.2016.12.002","usgsCitation":"Zhou, Z., Coco, G., Townend, I., Olabarrieta, M., van der Wegen, M., Gong, Z., D’Alpaos, A., Gao, S., Jaffe, B.E., Gelfenbaum, G.R., He, Q., Wang, Y., Lanzoni, S., Wang, Z., Winterwerp, H., and Zhang, C., 2017, Is “morphodynamic equilibrium” an oxymoron?: Earth-Science Reviews, v. 165, p. 257-267, https://doi.org/10.1016/j.earscirev.2016.12.002.","productDescription":"11 p.","startPage":"257","endPage":"267","ipdsId":"IP-080889","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":470085,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://doi.org/10.1016/j.earscirev.2016.12.002>).","text":"External Repository"},{"id":341111,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"165","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59154664e4b01a342e6912e1","contributors":{"authors":[{"text":"Zhou, Zeng","contributorId":191934,"corporation":false,"usgs":false,"family":"Zhou","given":"Zeng","email":"","affiliations":[],"preferred":false,"id":694808,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Coco, Giovanni","contributorId":84978,"corporation":false,"usgs":true,"family":"Coco","given":"Giovanni","affiliations":[],"preferred":false,"id":694809,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Townend, Ian","contributorId":191936,"corporation":false,"usgs":false,"family":"Townend","given":"Ian","affiliations":[],"preferred":false,"id":694810,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Olabarrieta, Maitane 0000-0002-7619-7992 molabarrieta@usgs.gov","orcid":"https://orcid.org/0000-0002-7619-7992","contributorId":81631,"corporation":false,"usgs":true,"family":"Olabarrieta","given":"Maitane","email":"molabarrieta@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":694811,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"van der Wegen, Mick","contributorId":76455,"corporation":false,"usgs":true,"family":"van der Wegen","given":"Mick","affiliations":[],"preferred":false,"id":694812,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Gong, Zheng","contributorId":191939,"corporation":false,"usgs":false,"family":"Gong","given":"Zheng","email":"","affiliations":[],"preferred":false,"id":694813,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"D’Alpaos, Andrea","contributorId":34247,"corporation":false,"usgs":true,"family":"D’Alpaos","given":"Andrea","email":"","affiliations":[],"preferred":false,"id":694814,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Gao, Shu","contributorId":191941,"corporation":false,"usgs":false,"family":"Gao","given":"Shu","email":"","affiliations":[],"preferred":false,"id":694815,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Jaffe, Bruce E. 0000-0002-8816-5920 bjaffe@usgs.gov","orcid":"https://orcid.org/0000-0002-8816-5920","contributorId":2049,"corporation":false,"usgs":true,"family":"Jaffe","given":"Bruce","email":"bjaffe@usgs.gov","middleInitial":"E.","affiliations":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":694816,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Gelfenbaum, Guy R. 0000-0003-1291-6107 ggelfenbaum@usgs.gov","orcid":"https://orcid.org/0000-0003-1291-6107","contributorId":742,"corporation":false,"usgs":true,"family":"Gelfenbaum","given":"Guy","email":"ggelfenbaum@usgs.gov","middleInitial":"R.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true}],"preferred":true,"id":694807,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"He, Qing","contributorId":191942,"corporation":false,"usgs":false,"family":"He","given":"Qing","email":"","affiliations":[],"preferred":false,"id":694817,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Wang, Yaping","contributorId":191943,"corporation":false,"usgs":false,"family":"Wang","given":"Yaping","email":"","affiliations":[],"preferred":false,"id":694818,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Lanzoni, Stefano","contributorId":191944,"corporation":false,"usgs":false,"family":"Lanzoni","given":"Stefano","email":"","affiliations":[],"preferred":false,"id":694819,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Wang, Zhengbing","contributorId":191945,"corporation":false,"usgs":false,"family":"Wang","given":"Zhengbing","email":"","affiliations":[],"preferred":false,"id":694820,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Winterwerp, Han","contributorId":191946,"corporation":false,"usgs":false,"family":"Winterwerp","given":"Han","email":"","affiliations":[],"preferred":false,"id":694821,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Zhang, Changkuan","contributorId":191947,"corporation":false,"usgs":false,"family":"Zhang","given":"Changkuan","email":"","affiliations":[],"preferred":false,"id":694822,"contributorType":{"id":1,"text":"Authors"},"rank":16}]}} ,{"id":70190678,"text":"70190678 - 2017 - Integration of genetic and demographic data to assess population risk in a continuously distributed species","interactions":[],"lastModifiedDate":"2018-03-26T14:33:09","indexId":"70190678","displayToPublicDate":"2017-02-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1324,"text":"Conservation Genetics","active":true,"publicationSubtype":{"id":10}},"title":"Integration of genetic and demographic data to assess population risk in a continuously distributed species","docAbstract":"The identification and demographic assessment of biologically meaningful populations is fundamental to species’ ecology and management. Although genetic tools are used frequently to identify populations, studies often do not incorporate demographic data to understand their respective population trends. We used genetic data to define subpopulations in a continuously distributed species. We assessed demographic independence and variation in population trends across the distribution. Additionally, we identified potential barriers to gene flow among subpopulations. We sampled greater sage-grouse (Centrocercus urophasianus) leks from across their range (≈175,000 Km2) in Wyoming and amplified DNA at 14 microsatellite loci for 1761 samples. Subsequently, we assessed population structure in unrelated individuals (n = 872) by integrating results from multiple Bayesian clustering approaches and used the boundaries to inform our assessment of long-term population trends and lek activity over the period of 1995–2013. We identified four genetic clusters of which two northern ones showed demographic independence from the others. Trends in population size for the northwest subpopulation were statistically different from the other three genetic clusters and the northeast and southwest subpopulations demonstrated a general trend of increasing proportion of inactive leks over time. Population change from 1996 to 2012 suggested population growth in the southern subpopulations and decline, or neutral, change in the northern subpopulations. We suggest that sage-grouse subpopulations in northern Wyoming are at greater risk of extirpation than the southern subpopulations due to smaller census and effective population sizes and higher variability within subpopulations. Our research is an example of incorporating genetic and demographic data and provides guidance on the identification of subpopulations of conservation concern.
","language":"English","publisher":"Springer","doi":"10.1007/s10592-016-0885-7","usgsCitation":"Fedy, B., Row, J.R., and Oyler-McCance, S.J., 2017, Integration of genetic and demographic data to assess population risk in a continuously distributed species: Conservation Genetics, v. 18, no. 1, p. 89-104, https://doi.org/10.1007/s10592-016-0885-7.","productDescription":"16 p.","startPage":"89","endPage":"104","ipdsId":"IP-060878","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":345643,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"18","issue":"1","noUsgsAuthors":false,"publicationDate":"2016-09-22","publicationStatus":"PW","scienceBaseUri":"59b8f220e4b08b1644e0aeeb","contributors":{"authors":[{"text":"Fedy, Bradley C.","contributorId":40536,"corporation":false,"usgs":true,"family":"Fedy","given":"Bradley C.","affiliations":[],"preferred":false,"id":710146,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Row, Jeffery R.","contributorId":178107,"corporation":false,"usgs":false,"family":"Row","given":"Jeffery","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":710147,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Oyler-McCance, Sara J. 0000-0003-1599-8769 sara_oyler-mccance@usgs.gov","orcid":"https://orcid.org/0000-0003-1599-8769","contributorId":1973,"corporation":false,"usgs":true,"family":"Oyler-McCance","given":"Sara","email":"sara_oyler-mccance@usgs.gov","middleInitial":"J.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":710148,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70192944,"text":"70192944 - 2017 - Temporal expansion of annual crop classification layers for the CONUS using the C5 decision tree classifier","interactions":[],"lastModifiedDate":"2017-10-30T15:00:45","indexId":"70192944","displayToPublicDate":"2017-02-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3251,"text":"Remote Sensing Letters","active":true,"publicationSubtype":{"id":10}},"title":"Temporal expansion of annual crop classification layers for the CONUS using the C5 decision tree classifier","docAbstract":"Crop cover maps have become widely used in a range of research applications. Multiple crop cover maps have been developed to suite particular research interests. The National Agricultural Statistics Service (NASS) Cropland Data Layers (CDL) are a series of commonly used crop cover maps for the conterminous United States (CONUS) that span from 2008 to 2013. In this investigation, we sought to contribute to the availability of consistent CONUS crop cover maps by extending temporal coverage of the NASS CDL archive back eight additional years to 2000 by creating annual NASS CDL-like crop cover maps derived from a classification tree model algorithm. We used over 11 million records to train a classification tree algorithm and develop a crop classification model (CCM). The model was used to create crop cover maps for the CONUS for years 2000–2013 at 250 m spatial resolution. The CCM and the maps for years 2008–2013 were assessed for accuracy relative to resampled NASS CDLs. The CCM performed well against a withheld test data set with a model prediction accuracy of over 90%. The assessment of the crop cover maps indicated that the model performed well spatially, placing crop cover pixels within their known domains; however, the model did show a bias towards the ‘Other’ crop cover class, which caused frequent misclassifications of pixels around the periphery of large crop cover patch clusters and of pixels that form small, sparsely dispersed crop cover patches.
","language":"English","publisher":"Taylor & Francis","doi":"10.1080/2150704X.2016.1271469","usgsCitation":"Friesz, A.M., Wylie, B., and Howard, D.M., 2017, Temporal expansion of annual crop classification layers for the CONUS using the C5 decision tree classifier: Remote Sensing Letters, v. 8, no. 4, p. 389-398, https://doi.org/10.1080/2150704X.2016.1271469.","productDescription":"10 p.","startPage":"389","endPage":"398","ipdsId":"IP-075490","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":347729,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"8","issue":"4","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2017-01-03","publicationStatus":"PW","scienceBaseUri":"59f83a38e4b063d5d30980ef","contributors":{"authors":[{"text":"Friesz, Aaron M. 0000-0003-4096-3824 afriesz@usgs.gov","orcid":"https://orcid.org/0000-0003-4096-3824","contributorId":5943,"corporation":false,"usgs":true,"family":"Friesz","given":"Aaron","email":"afriesz@usgs.gov","middleInitial":"M.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":717392,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wylie, Bruce K. 0000-0002-7374-1083 wylie@usgs.gov","orcid":"https://orcid.org/0000-0002-7374-1083","contributorId":197161,"corporation":false,"usgs":true,"family":"Wylie","given":"Bruce K.","email":"wylie@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":717394,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Howard, Daniel M. 0000-0002-7563-7538 danny.howard.ctr@usgs.gov","orcid":"https://orcid.org/0000-0002-7563-7538","contributorId":197063,"corporation":false,"usgs":true,"family":"Howard","given":"Daniel","email":"danny.howard.ctr@usgs.gov","middleInitial":"M.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":717393,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70182798,"text":"70182798 - 2017 - Dynamic strains for earthquake source characterization","interactions":[],"lastModifiedDate":"2017-03-01T14:26:59","indexId":"70182798","displayToPublicDate":"2017-02-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3372,"text":"Seismological Research Letters","onlineIssn":"1938-2057","printIssn":"0895-0695","active":true,"publicationSubtype":{"id":10}},"title":"Dynamic strains for earthquake source characterization","docAbstract":"Strainmeters measure elastodynamic deformation associated with earthquakes over a broad frequency band, with detection characteristics that complement traditional instrumentation, but they are commonly used to study slow transient deformation along active faults and at subduction zones, for example. Here, we analyze dynamic strains at Plate Boundary Observatory (PBO) borehole strainmeters (BSM) associated with 146 local and regional earthquakes from 2004–2014, with magnitudes from M 4.5 to 7.2. We find that peak values in seismic strain can be predicted from a general regression against distance and magnitude, with improvements in accuracy gained by accounting for biases associated with site–station effects and source–path effects, the latter exhibiting the strongest influence on the regression coefficients. To account for the influence of these biases in a general way, we include crustal‐type classifications from the CRUST1.0 global velocity model, which demonstrates that high‐frequency strain data from the PBO BSM network carry information on crustal structure and fault mechanics: earthquakes nucleating offshore on the Blanco fracture zone, for example, generate consistently lower dynamic strains than earthquakes around the Sierra Nevada microplate and in the Salton trough. Finally, we test our dynamic strain prediction equations on the 2011 M 9 Tohoku‐Oki earthquake, specifically continuous strain records derived from triangulation of 137 high‐rate Global Navigation Satellite System Earth Observation Network stations in Japan. Moment magnitudes inferred from these data and the strain model are in agreement when Global Positioning System subnetworks are unaffected by spatial aliasing.","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0220160155","usgsCitation":"Barbour, A., and Crowell, B.W., 2017, Dynamic strains for earthquake source characterization: Seismological Research Letters, v. 88, no. 2A, p. 354-370, https://doi.org/10.1785/0220160155.","productDescription":"17 p. ","startPage":"354","endPage":"370","ipdsId":"IP-076502","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":336775,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":336351,"type":{"id":15,"text":"Index Page"},"url":"https://dx.doi.org/10.1785/0220160155"}],"volume":"88","issue":"2A","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2017-02-01","publicationStatus":"PW","scienceBaseUri":"58b7eba1e4b01ccd5500bad5","contributors":{"authors":[{"text":"Barbour, Andrew J. 0000-0002-6890-2452 abarbour@usgs.gov","orcid":"https://orcid.org/0000-0002-6890-2452","contributorId":140443,"corporation":false,"usgs":true,"family":"Barbour","given":"Andrew J.","email":"abarbour@usgs.gov","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":false,"id":673788,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Crowell, Brendan W.","contributorId":184207,"corporation":false,"usgs":false,"family":"Crowell","given":"Brendan","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":673789,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70182735,"text":"70182735 - 2017 - The importance of quality control in validating concentrationsof contaminants of emerging concern in source and treateddrinking water samples","interactions":[],"lastModifiedDate":"2017-02-28T11:35:18","indexId":"70182735","displayToPublicDate":"2017-02-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"The importance of quality control in validating concentrationsof contaminants of emerging concern in source and treateddrinking water samples","docAbstract":"A national-scale survey of 247 contaminants of emerging concern (CECs), including organic and inorganic chemical\ncompounds, andmicrobial contaminants, was conducted in source and treated drinkingwater samples from\n25 treatment plants across the United States.Multiplemethodswere used to determine these CECs, including six\nanalytical methods tomeasure 174 pharmaceuticals, personal care products, and pesticides. A three-component\nquality assurance/quality control (QA/QC) programwas designed for the subset of 174 CECswhich allowed us to\nassess and compare performances of themethods used. The three components included: 1) a common field QA/\nQC protocol and sample design, 2) individual investigator-developed method-specific QA/QC protocols, and 3) a\nsuite of 46method comparison analytes thatwere determined in two or more analytical methods. Overallmethod\nperformance for the 174 organic chemical CECs was assessed by comparing spiked recoveries in reagent,\nsource, and treated water over a two-year period. In addition to the 247 CECs reported in the larger drinking\nwater study, another 48 pharmaceutical compoundsmeasured did not consistentlymeet predetermined quality\nstandards. Methodologies that did not seem suitable for these analytes are overviewed. The need to exclude\nanalytes based on method performance demonstrates the importance of additional QA/QC protocols.","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2016.02.127","collaboration":"U.S. Environmental Protection Agency","usgsCitation":"Angela L. Batt, Furlong, E.T., Mash, H.E., Glassmeyer, S.T., and Kolpin, D.W., 2017, The importance of quality control in validating concentrationsof contaminants of emerging concern in source and treateddrinking water samples: Science of the Total Environment, v. 579, p. 1618-1628, https://doi.org/10.1016/j.scitotenv.2016.02.127.","productDescription":"11 p. ","startPage":"1618","endPage":"1628","ipdsId":"IP-061364","costCenters":[{"id":5046,"text":"Branch of Analytical Serv (NWQL)","active":true,"usgs":true}],"links":[{"id":470083,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/6145083","text":"Publisher Index Page"},{"id":336331,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":336290,"type":{"id":15,"text":"Index Page"},"url":"https://www.sciencedirect.com/science/article/pii/S0048969716303369"}],"volume":"579","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58b69a3fe4b01ccd54ff3f82","contributors":{"authors":[{"text":"Angela L. Batt","contributorId":184072,"corporation":false,"usgs":false,"family":"Angela L. Batt","affiliations":[],"preferred":false,"id":673494,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Furlong, Edward T. 0000-0002-7305-4603 efurlong@usgs.gov","orcid":"https://orcid.org/0000-0002-7305-4603","contributorId":740,"corporation":false,"usgs":true,"family":"Furlong","given":"Edward","email":"efurlong@usgs.gov","middleInitial":"T.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":5046,"text":"Branch of Analytical Serv (NWQL)","active":true,"usgs":true},{"id":503,"text":"Office of Water Quality","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true}],"preferred":true,"id":673493,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mash, Heath E.","contributorId":184073,"corporation":false,"usgs":false,"family":"Mash","given":"Heath","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":673495,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Glassmeyer, Susan T.","contributorId":184074,"corporation":false,"usgs":false,"family":"Glassmeyer","given":"Susan","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":673496,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kolpin, Dana W. 0000-0002-3529-6505 dwkolpin@usgs.gov","orcid":"https://orcid.org/0000-0002-3529-6505","contributorId":1239,"corporation":false,"usgs":true,"family":"Kolpin","given":"Dana","email":"dwkolpin@usgs.gov","middleInitial":"W.","affiliations":[{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true}],"preferred":true,"id":673497,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70193455,"text":"70193455 - 2017 - Annual changes in seasonal river water temperatures in the eastern and western United States","interactions":[],"lastModifiedDate":"2021-06-04T15:52:04.210872","indexId":"70193455","displayToPublicDate":"2017-02-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3709,"text":"Water","active":true,"publicationSubtype":{"id":10}},"title":"Annual changes in seasonal river water temperatures in the eastern and western United States","docAbstract":"Changes in river water temperatures are anticipated to have direct effects on thermal habitat and fish population vital rates, and therefore, understanding temporal trends in water temperatures may be necessary for predicting changes in thermal habitat and how species might respond to such changes. However, many investigations into trends in water temperatures use regression methods that assume long-term monotonic changes in temperature, when in fact changes are likely to be nonmonotonic. Therefore, our objective was to highlight the need and provide an example of an analytical method to better quantify the short-term, nonmonotonic temporal changes in thermal habitat that are likely necessary to determine the effects of changing thermal conditions on fish populations and communities. To achieve this objective, this study uses Bayesian dynamic linear models (DLMs) to examine seasonal trends in river water temperatures from sites located in the eastern and western United States, regions that have dramatically different riverine habitats and fish communities. We estimated the annual rate of change in water temperature and found little evidence of seasonal changes in water temperatures in the eastern U.S. We found more evidence of warming for river sites located in the western U.S., particularly during the fall and winter seasons. Use of DLMs provided a more detailed view of temporal dynamics in river thermal habitat compared to more traditional methods by quantifying year-to-year changes and associated uncertainty, providing managers with the information needed to adapt decision making to short-term changes in habitat conditions that may be necessary for conserving aquatic resources in the face of a changing climate.
","language":"English","publisher":"MDPI","doi":"10.3390/w9020090","usgsCitation":"Wagner, T., Midway, S.R., Whittier, J.B., DeWeber, J.T., and Paukert, C.P., 2017, Annual changes in seasonal river water temperatures in the eastern and western United States: Water, v. 9, no. 2, 90; 13 p., https://doi.org/10.3390/w9020090.","productDescription":"90; 13 p.","ipdsId":"IP-071167","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":470084,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/w9020090","text":"Publisher Index Page"},{"id":348596,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Upper Colorado River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.6650390625,\n 36.914764288955936\n ],\n [\n -106.58935546875,\n 36.914764288955936\n ],\n [\n -106.58935546875,\n 40.97989806962013\n ],\n [\n -111.6650390625,\n 40.97989806962013\n ],\n [\n -111.6650390625,\n 36.914764288955936\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -80.4638671875,\n 37.33522435930639\n ],\n [\n -74.37744140625,\n 37.33522435930639\n ],\n [\n -74.37744140625,\n 42.391008609205045\n ],\n [\n -80.4638671875,\n 42.391008609205045\n ],\n [\n -80.4638671875,\n 37.33522435930639\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"9","issue":"2","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2017-02-04","publicationStatus":"PW","scienceBaseUri":"5a06c8d1e4b09af898c8614a","contributors":{"authors":[{"text":"Wagner, Tyler 0000-0003-1726-016X twagner@usgs.gov","orcid":"https://orcid.org/0000-0003-1726-016X","contributorId":1050,"corporation":false,"usgs":true,"family":"Wagner","given":"Tyler","email":"twagner@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":719126,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Midway, Stephen R.","contributorId":172159,"corporation":false,"usgs":false,"family":"Midway","given":"Stephen","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":721645,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Whittier, Joanna B.","contributorId":53151,"corporation":false,"usgs":false,"family":"Whittier","given":"Joanna","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":721646,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"DeWeber, Jefferson T.","contributorId":199675,"corporation":false,"usgs":false,"family":"DeWeber","given":"Jefferson","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":721647,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Paukert, Craig P. 0000-0002-9369-8545 cpaukert@usgs.gov","orcid":"https://orcid.org/0000-0002-9369-8545","contributorId":147821,"corporation":false,"usgs":true,"family":"Paukert","given":"Craig","email":"cpaukert@usgs.gov","middleInitial":"P.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true}],"preferred":true,"id":719127,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70193686,"text":"70193686 - 2017 - Generation of 3-D hydrostratigraphic zones from dense airborne electromagnetic data to assess groundwater model prediction error","interactions":[],"lastModifiedDate":"2017-11-02T16:32:12","indexId":"70193686","displayToPublicDate":"2017-02-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Generation of 3-D hydrostratigraphic zones from dense airborne electromagnetic data to assess groundwater model prediction error","docAbstract":"We present a new methodology to combine spatially dense high-resolution airborne electromagnetic (AEM) data and sparse borehole information to construct multiple plausible geological structures using a stochastic approach. The method developed allows for quantification of the performance of groundwater models built from different geological realizations of structure. Multiple structural realizations are generated using geostatistical Monte Carlo simulations that treat sparse borehole lithological observations as hard data and dense geophysically derived structural probabilities as soft data. Each structural model is used to define 3-D hydrostratigraphical zones of a groundwater model, and the hydraulic parameter values of the zones are estimated by using nonlinear regression to fit hydrological data (hydraulic head and river discharge measurements). Use of the methodology is demonstrated for a synthetic domain having structures of categorical deposits consisting of sand, silt, or clay. It is shown that using dense AEM data with the methodology can significantly improve the estimated accuracy of the sediment distribution as compared to when borehole data are used alone. It is also shown that this use of AEM data can improve the predictive capability of a calibrated groundwater model that uses the geological structures as zones. However, such structural models will always contain errors because even with dense AEM data it is not possible to perfectly resolve the structures of a groundwater system. It is shown that when using such erroneous structures in a groundwater model, they can lead to biased parameter estimates and biased model predictions, therefore impairing the model's predictive capability.
","language":"English","publisher":"AGU","doi":"10.1002/2016WR019141","usgsCitation":"Christensen, N.K., Minsley, B.J., and Christensen, S., 2017, Generation of 3-D hydrostratigraphic zones from dense airborne electromagnetic data to assess groundwater model prediction error: Water Resources Research, v. 53, no. 2, p. 1019-1038, https://doi.org/10.1002/2016WR019141.","productDescription":"20 p.","startPage":"1019","endPage":"1038","ipdsId":"IP-081403","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":488731,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://pure.au.dk/portal/en/publications/dcdb9b5e-bf3c-4826-83aa-0fb5cd606845","text":"External Repository"},{"id":348146,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"53","issue":"2","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59fc2ea5e4b0531197b27f85","contributors":{"authors":[{"text":"Christensen, Nikolaj K","contributorId":199736,"corporation":false,"usgs":false,"family":"Christensen","given":"Nikolaj","email":"","middleInitial":"K","affiliations":[{"id":13419,"text":"Aarhus University, Denmark","active":true,"usgs":false}],"preferred":false,"id":719889,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Minsley, Burke J. 0000-0003-1689-1306 bminsley@usgs.gov","orcid":"https://orcid.org/0000-0003-1689-1306","contributorId":697,"corporation":false,"usgs":true,"family":"Minsley","given":"Burke","email":"bminsley@usgs.gov","middleInitial":"J.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":719888,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Christensen, Steen","contributorId":199737,"corporation":false,"usgs":false,"family":"Christensen","given":"Steen","email":"","affiliations":[{"id":13419,"text":"Aarhus University, Denmark","active":true,"usgs":false}],"preferred":false,"id":719890,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70186026,"text":"70186026 - 2017 - Changes in aquatic vegetation and floodplain land cover in the Upper Mississippi and Illinois rivers (1989–2000–2010)","interactions":[],"lastModifiedDate":"2017-03-30T12:02:00","indexId":"70186026","displayToPublicDate":"2017-02-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1552,"text":"Environmental Monitoring and Assessment","onlineIssn":"1573-2959","printIssn":"0167-6369","active":true,"publicationSubtype":{"id":10}},"title":"Changes in aquatic vegetation and floodplain land cover in the Upper Mississippi and Illinois rivers (1989–2000–2010)","docAbstract":"Quantifying changes in the cover of river-floodplain systems can provide important insights into the processes that structure these landscapes as well as the potential consequences to the ecosystem services they provide. We examined net changes in 13 different aquatic and floodplain land cover classes using photo interpreted maps of the navigable portions of the Upper Mississippi River (UMR, above the confluence with the Ohio River) and Illinois River from 1989 to 2000 and from 2000 to 2010. We detected net decreases in vegetated aquatic area in nearly all river reaches from 1989 to 2000. The only river reaches that experienced a subsequent recovery of vegetated aquatic area from 2000 to 2010 were located in the northern portion of the UMR (above navigation pool 14) and two reaches in the Illinois River. Changes on the floodplain were dominated by urban development, which increased in nearly every river reach studied from 1989 to 2000. Agricultural lands declined in most river reaches from 2000 to 2010. The loss of agricultural land cover in the northern UMR was accompanied by increases in forest cover, whereas in the lower UMR and Illinois River, declines in agriculture were accompanied by increases in forest and shallow marsh communities. The changes in aquatic vegetation occupied between 5 and 20% of the total aquatic area and are likely associated with previously reported regional improvements in water clarity, while smaller (1–15% of the total floodplain area) changes in anthropogenic land cover types on the floodplain are likely driven by broad-scale socio-economic conditions.
","language":"English","publisher":"Springer","doi":"10.1007/s10661-017-5774-0","usgsCitation":"De Jager, N.R., and Rohweder, J.J., 2017, Changes in aquatic vegetation and floodplain land cover in the Upper Mississippi and Illinois rivers (1989–2000–2010): Environmental Monitoring and Assessment, v. 189, p. 1-14, https://doi.org/10.1007/s10661-017-5774-0.","productDescription":"Article 77; 14 p.","startPage":"1","endPage":"14","ipdsId":"IP-078207","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":338819,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Illinois River, Upper Mississippi River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -93.31787109374999,\n 36.914764288955936\n ],\n [\n -87.47314453125,\n 36.914764288955936\n ],\n [\n -87.47314453125,\n 44.94924926661153\n ],\n [\n -93.31787109374999,\n 44.94924926661153\n ],\n [\n -93.31787109374999,\n 36.914764288955936\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"189","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2017-01-24","publicationStatus":"PW","scienceBaseUri":"58de194ee4b02ff32c699c9d","contributors":{"authors":[{"text":"De Jager, Nathan R. 0000-0002-6649-4125 ndejager@usgs.gov","orcid":"https://orcid.org/0000-0002-6649-4125","contributorId":3717,"corporation":false,"usgs":true,"family":"De Jager","given":"Nathan","email":"ndejager@usgs.gov","middleInitial":"R.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":687382,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rohweder, Jason J. jrohweder@usgs.gov","contributorId":460,"corporation":false,"usgs":true,"family":"Rohweder","given":"Jason","email":"jrohweder@usgs.gov","middleInitial":"J.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":false,"id":687383,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70182740,"text":"70182740 - 2017 - Comparison of in vitro estrogenic activity and estrogen concentrations insource and treated waters from 25 U.S. drinking water treatment plants","interactions":[],"lastModifiedDate":"2017-02-28T11:28:47","indexId":"70182740","displayToPublicDate":"2017-02-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Comparison of in vitro estrogenic activity and estrogen concentrations insource and treated waters from 25 U.S. drinking water treatment plants","docAbstract":"In vitro bioassays have been successfully used to screen for estrogenic activity in wastewater and surface water,\nhowever, few have been applied to treated drinking water. Here, extracts of source and treated water samples\nwere assayed for estrogenic activity using T47D-KBluc cells and analyzed by liquid chromatography-Fourier transform\nmass spectrometry (LC-FTMS) for natural and synthetic estrogens (including estrone, 17β-estradiol, estriol,\nand ethinyl estradiol). None of the estrogenswere detected above the LC-FTMS quantification limits in treated samples\nand only 5 source waters had quantifiable concentrations of estrone, whereas 3 treated samples and 16 source\nsamples displayed in vitro estrogenicity. Estrone accounted for themajority of estrogenic activity in respective samples,\nhowever the remaining samples that displayed estrogenic activity had no quantitative detections of known estrogenic\ncompounds by chemical analyses. Source water estrogenicity (max, 0.47 ng 17β-estradiol equivalents\n(E2Eq) L−1) was below levels that have been linked to adverse effects in fish and other aquatic organisms. Treated\nwater estrogenicity (max, 0.078 ng E2Eq L−1) was considerably below levels that are expected to be biologically\nrelevant to human consumers. Overall, the advantage of using in vitro techniques in addition to analytical chemical\ndeterminations was displayed by the sensitivity of the T47D-KBluc bioassay, coupled with the ability tomeasure cumulative\neffects of mixtures, specifically when unknown chemicals may be present.","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2016.02.093","collaboration":"U.S. Environmental Protection Agency","usgsCitation":"Conley, J.M., Evans, N., Mash, H., Rosenblum, L., Schenck, K., Glassmeyer, S., Furlong, E.T., Kolpin, D.W., and Wilson, V.S., 2017, Comparison of in vitro estrogenic activity and estrogen concentrations insource and treated waters from 25 U.S. drinking water treatment plants: Science of the Total Environment, v. 579, p. 1610-1617, https://doi.org/10.1016/j.scitotenv.2016.02.093.","productDescription":"8 p. ","startPage":"1610","endPage":"1617","ipdsId":"IP-072842","costCenters":[{"id":5046,"text":"Branch of Analytical Serv (NWQL)","active":true,"usgs":true}],"links":[{"id":336329,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":336298,"type":{"id":15,"text":"Index Page"},"url":"https://www.sciencedirect.com/science/article/pii/S0048969716303035"}],"volume":"579","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58b69a3fe4b01ccd54ff3f80","contributors":{"authors":[{"text":"Conley, Justin M.","contributorId":184086,"corporation":false,"usgs":false,"family":"Conley","given":"Justin","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":673522,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Evans, Nicola","contributorId":184087,"corporation":false,"usgs":false,"family":"Evans","given":"Nicola","email":"","affiliations":[],"preferred":false,"id":673523,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mash, Heath","contributorId":184088,"corporation":false,"usgs":false,"family":"Mash","given":"Heath","affiliations":[],"preferred":false,"id":673524,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rosenblum, Laura","contributorId":184089,"corporation":false,"usgs":false,"family":"Rosenblum","given":"Laura","email":"","affiliations":[],"preferred":false,"id":673525,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Schenck, Kathleen","contributorId":184090,"corporation":false,"usgs":false,"family":"Schenck","given":"Kathleen","affiliations":[],"preferred":false,"id":673526,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Glassmeyer, Susan","contributorId":184091,"corporation":false,"usgs":false,"family":"Glassmeyer","given":"Susan","affiliations":[],"preferred":false,"id":673527,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Furlong, Edward T. 0000-0002-7305-4603 efurlong@usgs.gov","orcid":"https://orcid.org/0000-0002-7305-4603","contributorId":740,"corporation":false,"usgs":true,"family":"Furlong","given":"Edward","email":"efurlong@usgs.gov","middleInitial":"T.","affiliations":[{"id":5046,"text":"Branch of Analytical Serv (NWQL)","active":true,"usgs":true},{"id":503,"text":"Office of Water Quality","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":673521,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Kolpin, Dana W. 0000-0002-3529-6505 dwkolpin@usgs.gov","orcid":"https://orcid.org/0000-0002-3529-6505","contributorId":1239,"corporation":false,"usgs":true,"family":"Kolpin","given":"Dana","email":"dwkolpin@usgs.gov","middleInitial":"W.","affiliations":[{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true}],"preferred":true,"id":673528,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Wilson, Vickie S. 0000-0003-1661-8481","orcid":"https://orcid.org/0000-0003-1661-8481","contributorId":184092,"corporation":false,"usgs":false,"family":"Wilson","given":"Vickie","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":673529,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70179238,"text":"sir20165179 - 2017 - Flood-inundation maps for the St. Joseph River at Elkhart, Indiana","interactions":[],"lastModifiedDate":"2017-02-02T10:11:06","indexId":"sir20165179","displayToPublicDate":"2017-02-01T00:00:00","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":"2016-5179","title":"Flood-inundation maps for the St. Joseph River at Elkhart, Indiana","docAbstract":"Digital flood-inundation maps for a 6.6-mile reach of the St. Joseph River at Elkhart, Indiana, were created by the U.S. Geological Survey (USGS) in cooperation with the Indiana Office of Community and Rural Affairs. The flood-inundation maps, which can be accessed through the USGS Flood Inundation Mapping Science Web site at https://water.usgs.gov/osw/flood_inundation/, depict estimates of the areal extent and depth of flooding corresponding to selected water levels (stages) at the USGS streamgage 04101000, St. Joseph River at Elkhart, Ind. Real-time stages at this streamgage may be obtained on the Internet from the USGS National Water Information System at https://waterdata.usgs.gov/nwis or the National Weather Service (NWS) Advanced Hydrologic Prediction Service at http:/water.weather.gov/ahps/, which also forecasts flood hydrographs at this site (NWS site EKMI3).
Flood profiles were computed for the stream reach by means of a one-dimensional, step-backwater hydraulic modeling software developed by the U.S. Army Corps of Engineers. The hydraulic model was calibrated using the current stage-discharge rating at the USGS streamgage 04101000, St. Joseph River at Elkhart, Ind., and the documented high-water marks from the flood of March 1982. The hydraulic model was then used to compute six water-surface profiles for flood stages at 1-foot (ft) intervals referenced to the streamgage datum ranging from 23.0 ft (the NWS “action stage”) to 28.0 ft, which is the highest stage interval of the current USGS stage-discharge rating curve and 1 ft higher than the NWS “major flood stage.” The simulated water-surface profiles were then combined with a Geographic Information System digital elevation model (derived from light detection and ranging [lidar] data having a 0.49-ft root mean squared error and 4.9-ft horizontal resolution, resampled to a 10-ft grid) to delineate the area flooded at each stage.
The availability of these maps, along with Internet information regarding current stage from the USGS streamgage and forecasted high-flow stages from the NWS, will provide emergency management personnel and residents with information that is critical for flood response activities such as evacuations and road closures, as well as for post-flood recovery efforts.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165179","collaboration":"Prepared in cooperation with the Indiana Office of Community and Rural Affairs","usgsCitation":"Martin, Z.W., 2017, Flood-inundation maps for the St. Joseph River at Elkhart, Indiana: U.S. Geological Survey Scientific Investigations Report 2016–5179, 10 p., https://doi.org/10.3133/sir20165179.","productDescription":"Report: vi, 10 p.; Data Release","numberOfPages":"20","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-079008","costCenters":[{"id":27231,"text":"Indiana-Kentucky Water Science Center","active":true,"usgs":true}],"links":[{"id":333769,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7QZ2836","text":"USGS Data Release","description":"USGS Data Release","linkHelpText":"St. Joseph River at Elkhart, Indiana, Flood-Inundation HEC-RAS Model"},{"id":333734,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5179/coverthb.jpg"},{"id":333735,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5179/sir20165179.pdf","text":"Report","size":"1.35 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016–5179"}],"country":"United States","state":"Indiana","otherGeospatial":"St. Joseph River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -86.04475021362305,\n 41.67355293097283\n ],\n [\n -86.04475021362305,\n 41.69380876113261\n ],\n [\n -85.97402572631836,\n 41.69380876113261\n ],\n [\n -85.97402572631836,\n 41.67355293097283\n ],\n [\n -86.04475021362305,\n 41.67355293097283\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Indiana Water Science Center
U.S. Geological Survey
5957 Lakeside Boulevard,
Indianapolis, IN 46278–1996
Amphibians and reptiles are declining globally. One potential cause of this decline includes impacts resulting from co-occurrence with non-native red imported fire ant, Solenopsis invicta. Although a growing body of anecdotal and observational evidence from laboratory experiments supports this hypothesis, there remains a lack of field scale manipulations testing the effect of fire ants on reptile and amphibian communities. We addressed this gap by measuring reptile and amphibian (“herpetofauna”) community response to successful fire ant reductions over the course of 2 years following hydramethylnon application to five 100–200 ha plots in southeastern coastal South Carolina. By assessing changes in relative abundance and species richness of herpetofauna in response to fire ant reductions, we were able to assess whether some species were particularly vulnerable to fire ant presence, and whether this sensitivity manifested at the community level. We found that herpetofauna abundance and species richness responded positively to fire ant reductions. Our results document that even moderate populations of red imported fire ants decrease both the abundance and diversity of herpetofauna. Given global herpetofauna population declines and continued spread of fire ants, there is urgency to understand the impacts of fire ants beyond anecdotal and singles species studies. Our results provides the first community level investigation addressing these dynamics, by manipulating fire ant abundance to reveal a response in herpetofauna species abundance and richness.
","language":"English","publisher":"Springer","doi":"10.1007/s10530-016-1343-7","usgsCitation":"Allen, C.R., Birge, H.E., Slater, J., and Wiggers, E., 2017, The invasive ant, Solenopsis invicta, reduces herpetofauna richness and abundance: Biological Invasions, v. 19, no. 2, p. 713-722, https://doi.org/10.1007/s10530-016-1343-7.","productDescription":"10 p.","startPage":"713","endPage":"722","ipdsId":"IP-076507","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":347293,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"19","issue":"2","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2016-12-20","publicationStatus":"PW","scienceBaseUri":"59f05123e4b0220bbd9a1da1","contributors":{"authors":[{"text":"Allen, Craig R. 0000-0001-8655-8272 allencr@usgs.gov","orcid":"https://orcid.org/0000-0001-8655-8272","contributorId":1979,"corporation":false,"usgs":true,"family":"Allen","given":"Craig","email":"allencr@usgs.gov","middleInitial":"R.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":714005,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Birge, Hannah E.","contributorId":166737,"corporation":false,"usgs":false,"family":"Birge","given":"Hannah","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":715460,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Slater, J.","contributorId":198243,"corporation":false,"usgs":false,"family":"Slater","given":"J.","email":"","affiliations":[],"preferred":false,"id":715461,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wiggers, E.","contributorId":198244,"corporation":false,"usgs":false,"family":"Wiggers","given":"E.","email":"","affiliations":[],"preferred":false,"id":715462,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70192168,"text":"70192168 - 2017 - Ca isotopic geochemistry of an Antarctic aquatic system","interactions":[],"lastModifiedDate":"2017-11-06T13:21:59","indexId":"70192168","displayToPublicDate":"2017-02-01T00:00:00","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":"Ca isotopic geochemistry of an Antarctic aquatic system","docAbstract":"The McMurdo Dry Valleys, Antarctica, are a polar desert ecosystem. The hydrologic system of the dry valleys is linked to climate with ephemeral streams that flow from glacial melt during the austral summer. Past climate variations have strongly influenced the closed-basin, chemically stratified lakes on the valley floor. Results of previous work point to important roles for both in-stream processes (e.g., mineral weathering, precipitation and dissolution of salts) and in-lake processes (e.g., mixing with paleo-seawater and calcite precipitation) in determining the geochemistry of these lakes. These processes have a significant influence on calcium (Ca) biogeochemistry in this aquatic ecosystem, and thus variations in Ca stable isotope compositions of the waters can aid in validating the importance of these processes. We have analyzed the Ca stable isotope compositions of streams and lakes in the McMurdo Dry Valleys. The results validate the important roles of weathering of aluminosilicate minerals and/or CaCO3 in the hyporheic zone of the streams, and mixing of lake surface water with paleo-seawater and precipitation of Ca-salts during cryo-concentration events to form the deep lake waters. The lakes in the McMurdo Dry Valleys evolved following different geochemical pathways, evidenced by their unique, nonsystematic Ca isotope signatures.
","language":"English","publisher":"AGU Publications","doi":"10.1002/2016GL071169","usgsCitation":"Lyons, W.B., Bullen, T.D., and Welch, K.A., 2017, Ca isotopic geochemistry of an Antarctic aquatic system: Geophysical Research Letters, v. 44, no. 2, p. 882-891, https://doi.org/10.1002/2016GL071169.","productDescription":"10 p.","startPage":"882","endPage":"891","ipdsId":"IP-082104","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"links":[{"id":470087,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2016gl071169","text":"Publisher Index Page"},{"id":348277,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Antarctica, McMurdo Dry Valleys","volume":"44","issue":"2","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2017-01-16","publicationStatus":"PW","scienceBaseUri":"5a07e93ee4b09af898c8cc09","contributors":{"authors":[{"text":"Lyons, W. Berry","contributorId":193456,"corporation":false,"usgs":false,"family":"Lyons","given":"W.","email":"","middleInitial":"Berry","affiliations":[],"preferred":false,"id":714524,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bullen, Thomas D. 0000-0003-2281-1691 tdbullen@usgs.gov","orcid":"https://orcid.org/0000-0003-2281-1691","contributorId":1969,"corporation":false,"usgs":true,"family":"Bullen","given":"Thomas","email":"tdbullen@usgs.gov","middleInitial":"D.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":714523,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Welch, Kathleen A.","contributorId":197891,"corporation":false,"usgs":false,"family":"Welch","given":"Kathleen","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":714525,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ]}