Pinnipeds are commonly monitored using aerial photographic surveys at land- or ice-based sites, where animals come ashore for resting, pupping, molting, and to avoid predators. Although these counts form the basis for monitoring population change over time, they do not provide information regarding where animals occur in the water, which is often of management and conservation interest. In this study, we developed a hierarchical model that links counts of pinnipeds at terrestrial sites to sightings-at-sea and estimates abundance, spatial distribution, and the proportion of time spent on land (attendance probability). The structure of the model also allows for the inclusion of predictors that may explain variation in ecological and observation processes. We applied the model to Steller sea lions (Eumetopias jubatus) in Glacier Bay, Alaska using counts of sea lions from aerial photographic surveys and opportunistic in-water sightings from vessel surveys. Glacier Bay provided an ideal test and application of the model because data are available on attendance probability based on long-term monitoring. We found that occurrence in the water was positively related to proximity to terrestrial sites, as would be expected for a species that engages in central-place foraging. The proportion of sea lions in attendance at terrestrial sites and overall abundance estimates were consistent with reports from the literature and monitoring programs. The model we describe has benefit and utility for park managers who wish to better understand the overlap between pinnipeds and visitors, and the framework that we present has potential for application across a variety of study systems and taxa.
This map illustrates 119 years of global seismicity in the context of global plate tectonics and the Earth’s physiography. Primarily designed for use by earth scientists, engineers, and educators, this map provides a comprehensive overview of strong (magnitude [M] 5.5 and larger) earthquakes since 1900. The map clearly identifies the locations of the “great” earthquakes (M 8.0 and larger) and the aftershock or rupture area (green fill), if known, of the M 8.3 or larger earthquakes. The circular earthquake symbols are scaled to be proportional to the moment magnitude and therefore to the area of faulting, thus providing a better understanding of the relative sizes and distribution of earthquakes in the magnitude range 5.5 to 9.5. Plotting the known rupture or aftershock areas (which are closely related) of the largest earthquakes also provides a better appreciation of the faulting extent of some of the most famous and damaging instrumentally recorded earthquakes in modern history.
","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3446","usgsCitation":"Hayes, G.P., Smoczyk, G.M., Villaseñor, A.H., Furlong, K.P., and Benz, H.M, 2020, Seismicity of the Earth 1900–2018: U.S. Geological Survey Scientific Investigations Map 3446, scale 1:22,500,000, https://doi.org/10.3133/sim3446. [Supersedes USGS Scientific Investigations Map 3064.]","productDescription":"1 Sheet: 73.25 x 44.75 inches","onlineOnly":"N","ipdsId":"IP-111771","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":371836,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3446/coverthb2.jpg"},{"id":399519,"rank":3,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_109666.htm"},{"id":371837,"rank":2,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3446/sim3446.pdf","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3446"}],"scale":"22500000","contact":"Center Director, Geologic Hazards Science Center
U.S. Geological Survey
Box 25046, Mail Stop 966
Denver, CO 80225
Beaches around the world continuously adjust to daily and seasonal changes in wave and tide conditions, which are themselves changing over longer time-scales. Different approaches to predict multi-year shoreline evolution have been implemented; however, robust and reliable predictions of shoreline evolution are still problematic even in short-term scenarios (shorter than decadal). Here we show results of a modelling competition, where 19 numerical models (a mix of established shoreline models and machine learning techniques) were tested using data collected for Tairua beach, New Zealand with 18 years of daily averaged alongshore shoreline position and beach rotation (orientation) data obtained from a camera system. In general, traditional shoreline models and machine learning techniques were able to reproduce shoreline changes during the calibration period (1999–2014) for normal conditions but some of the model struggled to predict extreme and fast oscillations. During the forecast period (unseen data, 2014–2017), both approaches showed a decrease in models’ capability to predict the shoreline position. This was more evident for some of the machine learning algorithms. A model ensemble performed better than individual models and enables assessment of uncertainties in model architecture. Research-coordinated approaches (e.g., modelling competitions) can fuel advances in predictive capabilities and provide a forum for the discussion about the advantages/disadvantages of available models.
","language":"English","publisher":"Nature","doi":"10.1038/s41598-020-59018-y","usgsCitation":"Jennifer Montaño, Coco, G., Antolinez, J., Beuzen, T., Bryan, K.R., Cagigal, L., Bruno Castelle, Davidson, M., Goldstein, E.B., Ibaceta, R., Déborah Idier, Ludka, B.C., Masoud-Ansari, S., Fernando Mendez, A. Brad Murray, Plant, N.G., Ratlif, K., Robinet, A., Ana Rueda, Nadia Sénéchal, Simmons, J., Splinter, K., Scott Stephens, Townend, I., Vitousek, S., and Vos, K., 2020, Blind testing of shoreline evolution models: Scientific Reports, v. 10, 2137, 10 p., https://doi.org/10.1038/s41598-020-59018-y.","productDescription":"2137, 10 p.","ipdsId":"IP-116455","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":457790,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41598-020-59018-y","text":"Publisher Index Page"},{"id":376470,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"10","noUsgsAuthors":false,"publicationDate":"2020-02-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Jennifer Montaño","contributorId":229413,"corporation":false,"usgs":false,"family":"Jennifer Montaño","affiliations":[{"id":38833,"text":"University of Auckland","active":true,"usgs":false}],"preferred":false,"id":793154,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Coco, Giovanni","contributorId":229414,"corporation":false,"usgs":false,"family":"Coco","given":"Giovanni","email":"","affiliations":[{"id":38833,"text":"University of Auckland","active":true,"usgs":false}],"preferred":false,"id":793155,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Antolinez, Jose","contributorId":229415,"corporation":false,"usgs":false,"family":"Antolinez","given":"Jose","email":"","affiliations":[{"id":41638,"text":"University of Cantabria","active":true,"usgs":false}],"preferred":false,"id":793156,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Beuzen, Tomas 0000-0003-2762-9151","orcid":"https://orcid.org/0000-0003-2762-9151","contributorId":229416,"corporation":false,"usgs":false,"family":"Beuzen","given":"Tomas","email":"","affiliations":[{"id":27304,"text":"University of New South Wales","active":true,"usgs":false}],"preferred":false,"id":793157,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bryan, Karin R.","contributorId":229417,"corporation":false,"usgs":false,"family":"Bryan","given":"Karin","middleInitial":"R.","affiliations":[{"id":12678,"text":"University of Waikato","active":true,"usgs":false}],"preferred":false,"id":793158,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Cagigal, Laura 0000-0001-5384-6382","orcid":"https://orcid.org/0000-0001-5384-6382","contributorId":229418,"corporation":false,"usgs":false,"family":"Cagigal","given":"Laura","email":"","affiliations":[{"id":38833,"text":"University of Auckland","active":true,"usgs":false}],"preferred":false,"id":793159,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bruno Castelle","contributorId":229419,"corporation":false,"usgs":false,"family":"Bruno Castelle","affiliations":[{"id":41639,"text":"University of Bordeaux","active":true,"usgs":false}],"preferred":false,"id":793160,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Davidson, Mark","contributorId":229420,"corporation":false,"usgs":false,"family":"Davidson","given":"Mark","email":"","affiliations":[{"id":7119,"text":"Plymouth University","active":true,"usgs":false}],"preferred":false,"id":793161,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Goldstein, Evan B. 0000-0001-9358-1016","orcid":"https://orcid.org/0000-0001-9358-1016","contributorId":184210,"corporation":false,"usgs":false,"family":"Goldstein","given":"Evan","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":793162,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Ibaceta, Raimundo 0000-0003-2203-7640","orcid":"https://orcid.org/0000-0003-2203-7640","contributorId":229421,"corporation":false,"usgs":false,"family":"Ibaceta","given":"Raimundo","email":"","affiliations":[{"id":27304,"text":"University of New South Wales","active":true,"usgs":false}],"preferred":false,"id":793163,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Déborah Idier","contributorId":229422,"corporation":false,"usgs":false,"family":"Déborah Idier","affiliations":[{"id":41640,"text":"BGRM","active":true,"usgs":false}],"preferred":false,"id":793164,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Ludka, Bonnie C. 0000-0002-3844-2280","orcid":"https://orcid.org/0000-0002-3844-2280","contributorId":229423,"corporation":false,"usgs":false,"family":"Ludka","given":"Bonnie","email":"","middleInitial":"C.","affiliations":[{"id":38264,"text":"Scripps Institution of Oceanography","active":true,"usgs":false}],"preferred":false,"id":793165,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Masoud-Ansari, Sina","contributorId":229424,"corporation":false,"usgs":false,"family":"Masoud-Ansari","given":"Sina","email":"","affiliations":[{"id":38833,"text":"University of Auckland","active":true,"usgs":false}],"preferred":false,"id":793166,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Fernando Mendez","contributorId":229425,"corporation":false,"usgs":false,"family":"Fernando Mendez","affiliations":[{"id":41638,"text":"University of Cantabria","active":true,"usgs":false}],"preferred":false,"id":793167,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"A. 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Brad Murray","affiliations":[{"id":12643,"text":"Duke University","active":true,"usgs":false}],"preferred":false,"id":793168,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Plant, Nathaniel G. 0000-0002-5703-5672 nplant@usgs.gov","orcid":"https://orcid.org/0000-0002-5703-5672","contributorId":3503,"corporation":false,"usgs":true,"family":"Plant","given":"Nathaniel","email":"nplant@usgs.gov","middleInitial":"G.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true},{"id":508,"text":"Office of the AD Hazards","active":true,"usgs":true}],"preferred":true,"id":793169,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Ratlif, Katherine 0000-0003-1410-2756","orcid":"https://orcid.org/0000-0003-1410-2756","contributorId":229427,"corporation":false,"usgs":false,"family":"Ratlif","given":"Katherine","email":"","affiliations":[{"id":12643,"text":"Duke University","active":true,"usgs":false}],"preferred":false,"id":793170,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Robinet, Arthur 0000-0002-2045-892X","orcid":"https://orcid.org/0000-0002-2045-892X","contributorId":229428,"corporation":false,"usgs":false,"family":"Robinet","given":"Arthur","email":"","affiliations":[{"id":41639,"text":"University of Bordeaux","active":true,"usgs":false}],"preferred":false,"id":793171,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Ana Rueda","contributorId":229429,"corporation":false,"usgs":false,"family":"Ana Rueda","affiliations":[{"id":41638,"text":"University of Cantabria","active":true,"usgs":false}],"preferred":false,"id":793172,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Nadia Sénéchal","contributorId":229430,"corporation":false,"usgs":false,"family":"Nadia Sénéchal","affiliations":[{"id":41639,"text":"University of Bordeaux","active":true,"usgs":false}],"preferred":false,"id":793173,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"Simmons, Joshua","contributorId":229431,"corporation":false,"usgs":false,"family":"Simmons","given":"Joshua","email":"","affiliations":[{"id":27304,"text":"University of New South Wales","active":true,"usgs":false}],"preferred":false,"id":793174,"contributorType":{"id":1,"text":"Authors"},"rank":21},{"text":"Splinter, Kristen 0000-0002-0082-8444","orcid":"https://orcid.org/0000-0002-0082-8444","contributorId":229432,"corporation":false,"usgs":false,"family":"Splinter","given":"Kristen","email":"","affiliations":[{"id":27304,"text":"University of New South Wales","active":true,"usgs":false}],"preferred":false,"id":793175,"contributorType":{"id":1,"text":"Authors"},"rank":22},{"text":"Scott Stephens","contributorId":229433,"corporation":false,"usgs":false,"family":"Scott Stephens","affiliations":[{"id":25457,"text":"NIWA","active":true,"usgs":false}],"preferred":false,"id":793176,"contributorType":{"id":1,"text":"Authors"},"rank":23},{"text":"Townend, Ian 0000-0003-2101-3858","orcid":"https://orcid.org/0000-0003-2101-3858","contributorId":229434,"corporation":false,"usgs":false,"family":"Townend","given":"Ian","email":"","affiliations":[{"id":37955,"text":"University of Southampton","active":true,"usgs":false}],"preferred":false,"id":793177,"contributorType":{"id":1,"text":"Authors"},"rank":24},{"text":"Vitousek, Sean 0000-0002-3369-4673 svitousek@usgs.gov","orcid":"https://orcid.org/0000-0002-3369-4673","contributorId":149065,"corporation":false,"usgs":true,"family":"Vitousek","given":"Sean","email":"svitousek@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":793178,"contributorType":{"id":1,"text":"Authors"},"rank":25},{"text":"Vos, Kilian 0000-0002-9518-1582","orcid":"https://orcid.org/0000-0002-9518-1582","contributorId":229435,"corporation":false,"usgs":false,"family":"Vos","given":"Kilian","email":"","affiliations":[{"id":27304,"text":"University of New South Wales","active":true,"usgs":false}],"preferred":false,"id":793179,"contributorType":{"id":1,"text":"Authors"},"rank":26}]}} ,{"id":70211522,"text":"70211522 - 2020 - A random forest approach for bounded outcome variables","interactions":[],"lastModifiedDate":"2020-10-12T17:10:57.648419","indexId":"70211522","displayToPublicDate":"2020-02-07T10:57:19","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2229,"text":"Journal of Computational and Graphical Statistics","active":true,"publicationSubtype":{"id":10}},"title":"A random forest approach for bounded outcome variables","docAbstract":"Random forests have become an established tool for classication and regres-\nsion, in particular in high-dimensional settings and in the presence of non-additive\npredictor-response relationships. For bounded outcome variables restricted to the\nunit interval, however, classical modeling approaches based on mean squared error\nloss may severely suer as they do not account for heteroscedasticity in the data.\nTo address this issue, we propose a random forest approach for relating a beta dis-\ntributed outcome to a set of explanatory variables. Our approach explicitly makes\nuse of the likelihood function of the beta distribution for the selection of splits dur-\ning the tree-building procedure. In each iteration of the tree-building algorithm it\nchooses one explanatory variable in combination with a split point that maximizes\nthe log-likelihood function of the beta distribution with the parameter estimates de-\nrived from the nodes of the currently built tree. Results of several simulation studies\nand an application using data from the U.S.A. National Lakes Assessment Survey\ndemonstrate the properties and usefulness of the method, in particular when com-\npared to random forest approaches based on mean squared error loss and parametric\nregression models.","language":"English","publisher":"Taylor and Francis","doi":"10.1080/10618600.2019.1705310","usgsCitation":"Weinhold, L., Schmid, M., Mitchell, R., Maloney, K.O., Wright, M.N., and Berger, M., 2020, A random forest approach for bounded outcome variables: Journal of Computational and Graphical Statistics, v. 29, no. 3, p. 639-658, https://doi.org/10.1080/10618600.2019.1705310.","productDescription":"20 p.","startPage":"639","endPage":"658","ipdsId":"IP-107449","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"links":[{"id":457792,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/8193767","text":"External Repository"},{"id":376906,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"29","issue":"3","noUsgsAuthors":false,"publicationDate":"2020-02-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Weinhold, Leonie","contributorId":236854,"corporation":false,"usgs":false,"family":"Weinhold","given":"Leonie","email":"","affiliations":[{"id":47552,"text":"University of Bonn, Germany","active":true,"usgs":false}],"preferred":false,"id":794489,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schmid, Matthias","contributorId":236855,"corporation":false,"usgs":false,"family":"Schmid","given":"Matthias","affiliations":[{"id":47552,"text":"University of Bonn, Germany","active":true,"usgs":false}],"preferred":false,"id":794490,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mitchell, Richard M.","contributorId":215406,"corporation":false,"usgs":false,"family":"Mitchell","given":"Richard M.","affiliations":[{"id":39239,"text":"USEPA, Washington D.C.","active":true,"usgs":false}],"preferred":false,"id":794491,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Maloney, Kelly O. 0000-0003-2304-0745 kmaloney@usgs.gov","orcid":"https://orcid.org/0000-0003-2304-0745","contributorId":4636,"corporation":false,"usgs":true,"family":"Maloney","given":"Kelly","email":"kmaloney@usgs.gov","middleInitial":"O.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":794492,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wright, Marvin N.","contributorId":236856,"corporation":false,"usgs":false,"family":"Wright","given":"Marvin","email":"","middleInitial":"N.","affiliations":[{"id":47553,"text":"Leibniz Institute for Prevention Research and Epidemiology, Germany","active":true,"usgs":false}],"preferred":false,"id":794493,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Berger, Moritz","contributorId":236857,"corporation":false,"usgs":false,"family":"Berger","given":"Moritz","email":"","affiliations":[{"id":47552,"text":"University of Bonn, Germany","active":true,"usgs":false}],"preferred":false,"id":794494,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70214480,"text":"70214480 - 2020 - Timing of Cenozoic extension in the southern Stillwater Range and Dixie Valley, Nevada","interactions":[],"lastModifiedDate":"2020-09-28T14:36:21.177826","indexId":"70214480","displayToPublicDate":"2020-02-07T09:31:43","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3524,"text":"Tectonics","active":true,"publicationSubtype":{"id":10}},"title":"Timing of Cenozoic extension in the southern Stillwater Range and Dixie Valley, Nevada","docAbstract":"The Dixie Valley fault bounds the east side of the Stillwater Range in west‐central Nevada and last ruptured in 1954. Offset basalts indicate that slip began more recently than ~14 Ma, and prior work has interpreted the southern segment as an active low‐angle normal fault. Oligocene igneous rocks in the southern Stillwater Range were steeply tilted during large‐magnitude extension prior to ~14 Ma. To refine the timing of early extension and the onset of slip on the Dixie Valley fault, we collected two transects of samples for apatite fission track, apatite and zircon (U‐Th)/He (AHe and ZHe), and apatite 4He/3He thermochronometry. Apatite fission track ages from the Oligocene IXL pluton indicate rapid cooling ~18–14 Ma, and AHe and ZHe ages from the Cretaceous La Plata Canyon pluton indicate rapid cooling ~16–19 Ma. We interpret these data to record cooling during rapid extension. AHe ages from the IXL pluton are ~6–8 Ma and record cooling during slip on the Dixie Valley fault. We modeled these ages and 4He/3He spectra from one sample as the result of cooling during exhumation of a tilted fault block at a constant extension rate. The model predicts slip on the Dixie Valley fault beginning ~8 Ma. Although it does not constrain the initial fault dip, the model illustrates how a low‐angle fault requires a higher extension rate to reproduce cooling ages. Consequently, we prefer a high‐angle southern Dixie Valley fault for strain compatibility with the high‐angle northern segment.
Quantifying human impacts on the nitrogen (N) cycle and investigating natural ecosystem N cycling depend on the magnitude of inputs from natural biological nitrogen fixation (BNF). Here, we present two bottom‐up approaches to quantify tree‐based symbiotic BNF based on forest inventory data across the coterminous United States and SE Alaska. For all major N‐fixing tree genera, we quantify BNF inputs using (1) ecosystem N accretion rates (kg N ha−1 yr−1) scaled with spatial data on tree abundance and (2) percent of N derived from fixation (%Ndfa) scaled with tree N demand (from tree growth rates and stoichiometry). We estimate that trees fix 0.30–0.88 Tg N yr−1 across the study area (1.4–3.4 kg N ha−1 yr−1). Tree‐based N fixation displays distinct spatial variation that is dominated by two genera, Robinia (64% of tree‐associated BNF) and Alnus (24%). The third most important genus, Prosopis, accounted for 5%. Compared to published estimates of other N fluxes, tree‐associated BNF accounted for 0.59 Tg N yr−1, similar to asymbiotic (0.37 Tg N yr−1) and understory symbiotic BNF (0.48 Tg N yr−1), while N deposition contributed 1.68 Tg N yr−1 and rock weathering 0.37 Tg N yr−1. Overall, our results reveal previously uncharacterized spatial patterns in tree BNF that can inform large‐scale N assessments and serve as a model for improving tree‐based BNF estimates worldwide. This updated, lower BNF estimate indicates a greater ratio of anthropogenic to natural N inputs, suggesting an even greater human impact on the N cycle.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2019GB006241","usgsCitation":"Staccone, A., Liao, W., Perakis, S.S., Compton, J., Clark, C., and Menge, D., 2020, A spatially explicit, empirical estimate of tree-based biological nitrogen fixation in forests of the United States: Global Biogeochemical Cycles, v. 34, no. 2, e2019GB006241, 18 p., https://doi.org/10.1029/2019GB006241.","productDescription":"e2019GB006241, 18 p.","ipdsId":"IP-104007","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":457798,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2019gb006241","text":"Publisher Index Page"},{"id":378747,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n 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Wenying","contributorId":241125,"corporation":false,"usgs":false,"family":"Liao","given":"Wenying","email":"","affiliations":[{"id":6644,"text":"Princeton University","active":true,"usgs":false}],"preferred":false,"id":799600,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Perakis, Steven S. 0000-0003-0703-9314 sperakis@usgs.gov","orcid":"https://orcid.org/0000-0003-0703-9314","contributorId":145528,"corporation":false,"usgs":true,"family":"Perakis","given":"Steven","email":"sperakis@usgs.gov","middleInitial":"S.","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":799601,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Compton, Jana","contributorId":145529,"corporation":false,"usgs":false,"family":"Compton","given":"Jana","affiliations":[{"id":6784,"text":"US EPA","active":true,"usgs":false}],"preferred":false,"id":799602,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Clark, Christopher L.","contributorId":168382,"corporation":false,"usgs":false,"family":"Clark","given":"Christopher L.","affiliations":[{"id":25276,"text":"US EPA, National Center for Envirenmental Assessment, DC","active":true,"usgs":false}],"preferred":false,"id":799603,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Menge, Duncan 0000-0003-4736-9844","orcid":"https://orcid.org/0000-0003-4736-9844","contributorId":241126,"corporation":false,"usgs":false,"family":"Menge","given":"Duncan","email":"","affiliations":[{"id":7171,"text":"Columbia University","active":true,"usgs":false}],"preferred":false,"id":799604,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70224284,"text":"70224284 - 2020 - Flea sharing among sympatric rodent hosts: implications for potential plague effects on a threatened sciurid","interactions":[],"lastModifiedDate":"2021-09-20T13:02:13.220326","indexId":"70224284","displayToPublicDate":"2020-02-07T08:00:41","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Flea sharing among sympatric rodent hosts: implications for potential plague effects on a threatened sciurid","docAbstract":"For vector-borne diseases, the abundance and competency of different vector species and their host preferences will impact the transfer of pathogens among hosts. Sylvatic plague is a lethal disease caused by the primarily flea-borne bacterium Yersinia pestis. Sylvatic plague was introduced into the western United States in the early 1900s and impacts many species of rodents. Plague may be suppressing populations of the threatened northern Idaho ground squirrel (Urocitellus brunneus) if a competent flea community is allowing plague to be maintained within the few extant sites that support this rare ground squirrel. We collected fleas from four species of sympatric rodents in central Idaho: northern Idaho ground squirrels, Columbian ground squirrels (Urocitellus columbianus), yellow-pine chipmunks (Tamias amoenus), and deer mice (Peromyscus maniculatus). We evaluated which flea species were present and whether fleas were shared among the rodent community. We documented seven species of fleas among 3356 fleas collected from the four host species of rodents, and all seven species of fleas are known vectors of plague. Three of the seven flea species were detected on all four rodent species, demonstrating potential for spillover of plague (bridge vectors) in the rodent community. We used generalized linear mixed models to evaluate which abiotic and biotic factors influence flea abundance (total number of fleas, regardless of flea species, on each individual host of the four rodent host species). Factors that impacted flea abundance varied among the four host species, but flea abundance: (1) changed over summer depending on host species, (2) was greater on males, and (3) was impacted by summer and winter precipitation depending on host species. Our results suggest this diverse flea community has the capacity to transfer Y. pestis among populations of the four rodents if Y. pestis is present. Furthermore, the disease may be more likely to persist in some locations than others, those that have higher flea abundances, more sympatric hosts, or optimal conditions for fleas, and such high-risk sites can be identified based on their abiotic and biotic factors.
Understanding how land cover and potential competition with invasive species shape patterns of occupancy, extirpation, and colonization of native species across a landscape can help target management for declining native populations. Mourning dove (Zenaida macroura) populations have declined throughout the United States from 1965–2015. The expansion of the Eurasian collared‐dove (Streptopelia decaocto), an introduced species with similar food preferences, may further threaten mourning dove populations. We analyzed data from 2009–2016 from a large‐scale monitoring program in the Western Great Plains of the United States in a 2‐species occupancy model to assess the effects of collared‐doves on mourning dove distributions, while accounting for imperfect detection and variation in land cover across the landscape. Mourning dove occupancy was stable or increasing across our study area, and despite overlap in resource use and co‐occurrence between mourning doves and Eurasian collared‐doves, we found no evidence that collared‐doves are extirpating mourning doves from preferred habitat during the breeding season.
","language":"English","publisher":"The Wildlife Society","doi":"10.1002/jwmg.21835","usgsCitation":"Green, A., Sofaer, H., Otis, D.L., and Van Lanen, N.J., 2020, Co-occurrence and occupancy dynamics of mourning doves and Eurasian collared-doves: Journal of Wildlife Management, v. 84, no. 4, p. 775-785, https://doi.org/10.1002/jwmg.21835.","productDescription":"11 p.","startPage":"775","endPage":"785","ipdsId":"IP-107369","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":437122,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9TYF93I","text":"USGS data release","linkHelpText":"Co-occurrence and Occupancy Dynamics of Mourning Doves and Eurasian Collared-Doves"},{"id":381870,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Texas, Oklahoma, Kansas, Nebraska, South Dakota, North Dakota, Montana, Wyoming, Colorado, New Mexico","otherGeospatial":"Badlands and Prairies and Shortgrass Prairie Bird Conservation Regions","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -101.1181640625,\n 32.95336814579932\n ],\n [\n -101.3818359375,\n 36.63316209558658\n ],\n [\n -101.6455078125,\n 43.068887774169625\n ],\n [\n -100.2392578125,\n 45.182036837015886\n ],\n [\n -100.72265625,\n 47.487513008956554\n ],\n [\n -104.9853515625,\n 48.28319289548349\n ],\n [\n -109.3359375,\n 47.60616304386874\n ],\n [\n -111.8408203125,\n 47.54687159892238\n ],\n [\n -106.171875,\n 42.71473218539458\n ],\n [\n -104.4580078125,\n 37.71859032558816\n ],\n [\n -104.4140625,\n 33.02708758002874\n ],\n [\n -101.1181640625,\n 32.95336814579932\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"84","issue":"4","noUsgsAuthors":false,"publicationDate":"2020-02-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Green, Adam W.","contributorId":246045,"corporation":false,"usgs":false,"family":"Green","given":"Adam W.","affiliations":[{"id":25644,"text":"Bird Conservancy of the Rockies","active":true,"usgs":false}],"preferred":false,"id":807560,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sofaer, Helen 0000-0002-9450-5223","orcid":"https://orcid.org/0000-0002-9450-5223","contributorId":216681,"corporation":false,"usgs":true,"family":"Sofaer","given":"Helen","email":"","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":807561,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Otis, David L","contributorId":246046,"corporation":false,"usgs":false,"family":"Otis","given":"David","email":"","middleInitial":"L","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":807562,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Van Lanen, Nicholas J.","contributorId":246047,"corporation":false,"usgs":false,"family":"Van Lanen","given":"Nicholas","middleInitial":"J.","affiliations":[{"id":25644,"text":"Bird Conservancy of the Rockies","active":true,"usgs":false}],"preferred":false,"id":807563,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70208562,"text":"70208562 - 2020 - Cryptic and extensive hybridization between ancient lineages of American crows","interactions":[],"lastModifiedDate":"2020-03-11T15:51:00","indexId":"70208562","displayToPublicDate":"2020-02-07T06:44:32","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2774,"text":"Molecular Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Cryptic and extensive hybridization between ancient lineages of American crows","docAbstract":"Most species and therefore most hybrid zones have historically been defined using phenotypic characters. However, both speciation and hybridization can occur with negligible morphological differentiation. Recently developed genomic tools provide the means to better understand cryptic speciation and hybridization. The Northwestern Crow (Corvus caurinus) and American Crow (Corvus brachyrhynchos) are continuously distributed sister taxa that lack reliable traditional characters for identification. In this first population genomic study of Northwestern and American crows, we use genomic SNPs (nuDNA) and mtDNA to investigate the degree of genetic differentiation between these crows and the extent to which they may hybridize. Our results indicate that American and Northwestern crows have distinct evolutionary histories, supported by two nuDNA ancestry clusters and two 1.1%‐divergent mtDNA clades dating to the late Pleistocene, when glacial advances may have isolated crow populations in separate refugia. We document extensive hybridization, with geographic overlap of mtDNA clades and admixture of nuDNA across >900 km of western Washington and western British Columbia. This broad hybrid zone consists of late‐generation hybrids and backcrosses, but not recent (e.g., F1) hybrids. Nuclear DNA and mtDNA clines had concordant widths and were both centred in southwestern British Columbia, farther north than previously postulated. Overall, our results suggest a history of reticulate evolution in American and Northwestern crows, perhaps due to recurring neutral expansion(s) from Pleistocene glacial refugia followed by lineage fusion(s). However, we do not rule out a contributing role for more recent potential drivers of hybridization, such as expansion into human‐modified habitats.
","language":"English","publisher":"Wiley","doi":"10.1111/mec.15377","usgsCitation":"Slager, D., Epperly, K., Ha, R., Rohwer, S., Woodall, C.W., Van Hemert, C.R., and Klicka, J., 2020, Cryptic and extensive hybridization between ancient lineages of American crows: Molecular Ecology, v. 29, no. 5, p. 956-969, https://doi.org/10.1111/mec.15377.","productDescription":"14 p.","startPage":"956","endPage":"969","ipdsId":"IP-103862","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":457807,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1101/491654","text":"External Repository"},{"id":372375,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States, Canada","state":"Washington","otherGeospatial":"British Columbia ","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -128.232421875,\n 50.00773901463687\n ],\n [\n -124.1015625,\n 45.583289756006316\n ],\n [\n -118.91601562499999,\n 45.583289756006316\n ],\n [\n -118.91601562499999,\n 55.07836723201515\n ],\n [\n -131.748046875,\n 54.36775852406841\n ],\n [\n -128.232421875,\n 50.00773901463687\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"29","issue":"5","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Slager, David","contributorId":222550,"corporation":false,"usgs":false,"family":"Slager","given":"David","email":"","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":782502,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Epperly, Kevin","contributorId":222551,"corporation":false,"usgs":false,"family":"Epperly","given":"Kevin","email":"","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":782503,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ha, Renee","contributorId":222552,"corporation":false,"usgs":false,"family":"Ha","given":"Renee","email":"","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":782504,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rohwer, Sievert","contributorId":222553,"corporation":false,"usgs":false,"family":"Rohwer","given":"Sievert","email":"","affiliations":[{"id":40561,"text":"Burke Museum of Natural History and Culture","active":true,"usgs":false}],"preferred":false,"id":782505,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Woodall, Christopher W.","contributorId":53696,"corporation":false,"usgs":false,"family":"Woodall","given":"Christopher","email":"","middleInitial":"W.","affiliations":[{"id":7264,"text":"USDA Forest Service, Northern Research Station, Beltsville, MD 20705","active":true,"usgs":false}],"preferred":false,"id":782506,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Van Hemert, Caroline R. 0000-0002-6858-7165 cvanhemert@usgs.gov","orcid":"https://orcid.org/0000-0002-6858-7165","contributorId":3592,"corporation":false,"usgs":true,"family":"Van Hemert","given":"Caroline","email":"cvanhemert@usgs.gov","middleInitial":"R.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":782501,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Klicka, John","contributorId":222554,"corporation":false,"usgs":false,"family":"Klicka","given":"John","email":"","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":782507,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70208693,"text":"70208693 - 2020 - Global physical controls on estuarine habitat distribution during sea levelchange: Consequences for genetic diversification through time","interactions":[],"lastModifiedDate":"2020-02-24T19:00:02","indexId":"70208693","displayToPublicDate":"2020-02-06T18:58:35","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1844,"text":"Global and Planetary Change","active":true,"publicationSubtype":{"id":10}},"title":"Global physical controls on estuarine habitat distribution during sea levelchange: Consequences for genetic diversification through time","docAbstract":"Determining the extrinsic (physical) factors controlling speciation and diversification of species through time is\nof key interest in paleontology and evolutionary biology. The role of sea-level change in shaping species richness\npatterns of marginal marine species has received much attention, but with variable conclusions. Recent work\ncombining genetic data and Geographical Information Systems (GIS)-based habitat modeling yielded a framework\nfor how geomorphology of continental margins mediates genetic connectivity of populations during sealevel\nchange. This approach may ultimately yield insights on how distinct lineages, species, and biodiversity\naccumulate in coastal settings. Here, we expand this GIS work globally to different geomorphic settings to model\nestuarine habitat in a larger geographic framework and test how tectonic setting, oceanographic setting, climate,\nand margin age affect habitat distribution during sea-level change. In addition, independent of estuaries we\nexplore paleobiologic (e.g. Olsson, 1961) and neontolologic effects of sea-level change on evolution, and test the\nrelation between overall shelf area and species richness using data of 1721 fish species. We find 82% global\nreduction of estuarine habitat abundance at lowstand relative to highstand, and find large habitats change in size\nmuch more than small habitats. Consistent with prior work, narrow continental margins have significantly less\nhabitat at highstand and lowstand than wide margins, and narrow margins significantly associate with fore-arc\nsettings, effectively linking tectonic setting to habitat abundance. Surprisingly, narrow margins host greater\nspecies richness, a finding which violates the canonical species-area relation. This finding can be explained if: 1)\nthe physical isolation imposed by narrow margins facilitates the formation of new species over time; 2) the sizestability\nof small habitats, which disproportionately occur on narrow margins, accumulate and retain species\nextirpated in the more variable habitats on wide margins; or 3) the smaller habitats on narrow margins facilitate\ngreater species richness through greater habitat heterogeneity. These results are generally at odds with prior\ninterpretations, but the combination of richness data and population genetic principles offer a different perspective\non these long-studied questions. Finally, we emphasize that the nuance of Pleistocene-Holocene sea\nlevel oscillations should be more explicitly considered in genetic studies.","language":"English","publisher":"Elsevier","doi":"10.1016/j.gloplacha.2020.103128","usgsCitation":"Dolby, G.A., Bedolla, A.M., Bennett, S., and Jacobs, D.K., 2020, Global physical controls on estuarine habitat distribution during sea levelchange: Consequences for genetic diversification through time: Global and Planetary Change, v. 187, 103128, https://doi.org/10.1016/j.gloplacha.2020.103128.","productDescription":"103128","ipdsId":"IP-110919","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":457809,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://escholarship.org/uc/item/3qs0m0qg","text":"External Repository"},{"id":372590,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"187","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Dolby, Greer A. 0000-0002-5923-0690","orcid":"https://orcid.org/0000-0002-5923-0690","contributorId":222726,"corporation":false,"usgs":false,"family":"Dolby","given":"Greer","email":"","middleInitial":"A.","affiliations":[{"id":6607,"text":"Arizona State University","active":true,"usgs":false}],"preferred":false,"id":783031,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bedolla, Arturo M.","contributorId":222727,"corporation":false,"usgs":false,"family":"Bedolla","given":"Arturo","email":"","middleInitial":"M.","affiliations":[{"id":6607,"text":"Arizona State University","active":true,"usgs":false}],"preferred":false,"id":783032,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bennett, S. 0000-0002-9772-4122","orcid":"https://orcid.org/0000-0002-9772-4122","contributorId":29230,"corporation":false,"usgs":true,"family":"Bennett","given":"S.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":false,"id":783030,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jacobs, David K.","contributorId":139394,"corporation":false,"usgs":false,"family":"Jacobs","given":"David","email":"","middleInitial":"K.","affiliations":[{"id":12763,"text":"University of California, Los Angeles","active":true,"usgs":false}],"preferred":false,"id":783033,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70208326,"text":"fs20203005 - 2020 - \"Modified Unified Method\" of carp capture","interactions":[],"lastModifiedDate":"2020-02-07T06:14:37","indexId":"fs20203005","displayToPublicDate":"2020-02-06T15:49:37","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2020-3005","displayTitle":"\"Modified Unified Method\" of Carp Capture","title":"\"Modified Unified Method\" of carp capture","docAbstract":"Populations of Hypophthalmichthys molitrix (silver carp) and Hypophthalmichthys nobilis (bighead carp), (together referred to herein as “bigheaded carp”) have increased exponentially in the greater Mississippi River Basin. Detrimental effects on native fish and economically important fisheries have occurred where these invasive, filter-feeding fish are abundant. The Unified Method, a harvest technique developed in China for bigheaded carp in flood plain lakes, uses herding techniques and a variety of nets to drive bigheaded carp and concentrate them into an area where they can be easily harvested. The U.S. Geological Survey is adapting the Chinese Unified Method concepts to be consistent with North American financial, societal, and environmental conditions. We have modified these techniques and incorporated modern technology to reduce the time and expense of Unified Methods and to allow them to be used in public waters. Thus, the operations in North America are often described as the “Modified Unified Method.” The U.S. Geological Survey is studying and refining the Modified Unified Method to provide stakeholders with efficient, validated, and environmentally friendly methods for carp removal; however, this method is still new to the United States and additional research is needed to further increase the efficiency of Modified Unified Method operations.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20203005","usgsCitation":"Chapman, D.C., 2020, \"Modified Unified Method\" of carp capture: U.S. Geological Survey Fact Sheet 2020–3005, 2 p., https://doi.org/10.3133/fs20203005.","productDescription":"2 p.","numberOfPages":"2","onlineOnly":"N","ipdsId":"IP-115946","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":372124,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2020/3005/coverthb.jpg"},{"id":372125,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2020/3005/fs20203005.pdf","text":"Report","size":"416 kB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2020–5003"}],"contact":"Director, Columbia Environmental Research Center
U.S. Geological Survey
4200 New Haven Road
Columbia, MO 65201
In 2014, groundwater samples from residential and public supply wells in the vicinity of two former U.S. Navy bases at Willow Grove and Warminster, and an active Air National Guard Station at Horsham, Bucks and Montgomery Counties, Pennsylvania, were found to have concentrations of perfluorooctanoic acid (PFOA) and perfluorooctane sulfonate (PFOS), which are per- and polyfluoroalkyl substances (PFAS), above U.S. Environmental Protection Agency (EPA) provisional health advisory (HA) levels for drinking water. Five supply wells near the bases were shut down because of PFAS contamination. In 2016, after EPA established a Lifetime HA for PFAS in drinking water that is lower than the provisional HA in place in 2014, at least 13 additional supply wells near the bases were shut down because of PFAS contamination. At the request of the U.S. Navy, and in consultation with other Federal and State agencies and local stakeholders, the U.S. Geological Survey used historical and recent data on well withdrawals, recharge rates, aquifer properties, groundwater levels, and stream base flow to evaluate regional groundwater-flow paths from identified areas of PFAS groundwater contamination or potential PFAS sources at the bases. Groundwater withdrawals near the bases from public supply and other large wells decreased substantially from the 1990s to 2017, increasing the proportion of groundwater recharge that discharged to local streams. A preliminary groundwater-flow model, calibrated using 1,009 groundwater levels and 17 stream base flow estimates, simulated regional flow paths from the bases and showed that recharge at the bases discharged to withdrawal wells and local streams, generally within a mile or two of the bases. Supply and remediation wells at the bases captured some of the recharge on base areas of possible PFAS contamination, whereas other base recharge was simulated to flow to nearby public supply wells and streams, depending on water use and aquifer recharge conditions between 1999 and 2017. The locations of many residential wells near the bases that were identified by the Navy and Air National Guard as having elevated PFAS concentrations were generally consistent with the simulated flow paths from possible sources at the bases. However, there are some areas of observed PFAS contamination where no flow paths from base sources were simulated. Additionally, no data were available on PFAS concentrations in groundwater in some areas of simulated flow paths from base sources. Data and models used for this study are provided in this report and in digital data releases to support further investigations and model revisions.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191137","collaboration":"Prepared in cooperation with the U.S. Navy","usgsCitation":"Goode, D.J., and Senior, L.A., 2020, Groundwater withdrawals and regional flow paths at and near Willow Grove and Warminster, Pennsylvania—Data compilation and preliminary simulations for conditions in 1999, 2010, 2013, 2016, and 2017: U.S. Geological Survey Open-File Report 2019–1137, 127 p., https://doi.org/10.3133/ofr20191137.","productDescription":"Report: x, 127 p.; 2 Data Releases","numberOfPages":"138","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-113639","costCenters":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"links":[{"id":399427,"rank":5,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_109664.htm"},{"id":371906,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9ZGEI67","text":"USGS data release","linkHelpText":"Groundwater levels, groundwater withdrawals, and point-source discharges to streams in the vicinity of Willow Grove and Warminster, Bucks and Montgomery Counties, Pennsylvania, for selected years during 1999–2017"},{"id":371905,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9K36P5S","text":"USGS data release","linkHelpText":"MODFLOW 6 and MODPATH 7 model data sets used to evaluate groundwater flow in the vicinity of Horsham and Warminster, Bucks and Montgomery Counties, Pennsylvania—Preliminary simulations for conditions in 1999, 2010, 2013, 2016, and 2017"},{"id":372113,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1137/ofr20191137.pdf","text":"Report","size":"21.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019-1137"},{"id":371903,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1137/coverthb.jpg"}],"country":"United States","state":"Pennsylvania","county":"Bucks County, Montgomery County","city":"Warminster, Willow Grove","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -75.3536,\n 40.0678\n ],\n [\n -74.9167,\n 40.0678\n ],\n [\n -74.9167,\n 40.2967\n ],\n [\n -75.3536,\n 40.2967\n ],\n [\n -75.3536,\n 40.0678\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Pennsylvania Water Science Center
U.S. Geological Survey
215 Limekiln Road
New Cumberland, PA 17070
The Gales Creek fault (GCF) is a 60-km-long, northwest-striking dextral fault system (west of Portland, Oregon) that accommodates northward motion and uplift of the Oregon Coast Range. New geologic mapping and geophysical models confirm inferred offsets from earlier geophysical surveys and document ∼12 km of right-lateral offset of a basement high in Eocene Siletz River Volcanics since ca. 35 Ma and ∼8.8 km of right-lateral separation of Miocene Columbia River Basalt at Newberg, Oregon, since 15 Ma (∼0.62 ± 0.12 mm/yr, average long-term rate). Relative uplift of Eocene Coast Range basalt basement west of the fault zone is at least 5 km based on depth to basement under the Tualatin Basin from a recent inversion of gravity data. West of the city of Forest Grove, the fault consists of two subparallel strands ∼7 km apart. The westernmost, Parsons Creek strand, forms a linear valley southward to Henry Hagg Lake, where it continues southward to Newberg as a series of en echelon strands forming both extensional and compressive step-overs. Compressive step-overs in the GCF occur at intersections with ESE-striking sinistral faults crossing the Coast Range, suggesting the GCF is the eastern boundary of an R′ Riedel shear domain that could accommodate up to half of the ∼45° of post–40 Ma clockwise rotation of the Coast Range documented by paleomagnetic studies. Gravity and magnetic anomalies suggest the western strands of the GCF extend southward beneath Newberg into the Northern Willamette Valley, where colinear magnetic anomalies have been correlated with the Mount Angel fault, the proposed source of the 1993 M 5.7 Scotts Mills earthquake. The potential-field data and water-well data also indicate the eastern, Gales Creek strand of the fault may link to the NNW-striking Canby fault through the E-W Beaverton fault to form a 30-km-wide compressive step-over along the south side of the Tualatin Basin. LiDAR data reveal right-lateral stream offsets of as much as 1.5 km, shutter ridges, and other youthful geomorphic features for 60 km along the geophysical and geologic trace of the GCF north of Newberg, Oregon. Paleoseismic trenches document Eocene bedrock thrust over 250 ka surficial deposits along a reverse splay of the fault system near Yamhill, Oregon, and Holocene motion has been recently documented on the GCF along Scoggins Creek and Parsons Creek. The GCF could produce earthquakes in excess of Mw 7, if the entire 60 km segment ruptured in one earthquake. The apparent subsurface links of the GCF to other faults in the Northern Willamette Valley suggest that other faults in the system may also be active.
The 2016–2017 shallow submarine eruption of Bogoslof volcano in Alaska injected plumes of ash and seawater to maximum heights of ~ 12 km. More than 4550 volcanic lightning strokes were detected by the World Wide Lightning Location Network (WWLLN) and Vaisala’s Global Lightning Dataset (GLD360) over 9 months. Lightning assisted monitoring efforts by confirming ash-producing explosions in near-real time, but only 32 out of the 70 explosive events produced detectable lightning. What led to electrical activity within some of the volcanic plumes, but not others? And why did the lightning intensity wax and wane over the lifetime of individual explosions? We address these questions using multiparametric observations from ground-based lightning sensors, satellite imagery, photographs, acoustic signals, and 1D plume modeling. Detailed time-series of monitoring data show that the plumes did not produce detectable lightning until they rose higher than the atmospheric freezing level (approximated by − 20 °C temperatures). For example, on 28 May 2017 (event 40), the delayed onset of lightning coincides with modeled ice formation in upper levels of the plume. Model results suggest that microphysical conditions inside the plume rivaled those of severe thunderstorms, with liquid water contents > 5 g m−3 and vigorous updrafts > 40 m s−1 in the mixed-phase region where liquid water and ice coexist. Based on these findings, we infer that ‘thunderstorm-style’ collisional ice-charging catalyzed the volcanic lightning. However, charge mechanisms likely operated on a continuum, with silicate collisions dominating electrification in the near-vent region, and ice charging taking over in the upper-level plumes. A key implication of this study is that lightning during the Bogoslof eruption provided a reliable indicator of sustained, ash-rich plumes (and associated hazards) above the atmospheric freezing level.
Mule deer (Odocoileus hemionus) survival and population growth in north-central New Mexico, USA, was previously reported to be limited by nutritional constraints due to poor forage conditions in degraded habitats. Management recommendations suggested thinning of pinyon–juniper to improve habitat quality for mule deer. To evaluate the influence of these vegetation treatments, we monitored habitat selection by 48 adult female mule deer from 2011 to 2013 in a population previously reported to be nutritionally limited. Monitoring occurred 1–4 years after completion of treatments that were intended to improve forage conditions, including mechanical reduction of pinyon pine (Pinus edulis) and juniper (Juniperus spp.) density and senescent brush (Quercus gambelii–Cercocarpus montanus) cover. During the summer season, deer selected recently treated areas, but odds ratios decreased with treatment age. However, during winter, deer avoided more recently treated areas and selected thinned areas >4 years old. Deer selected mixed oak (Quercus spp.) and pinyon–juniper savanna vegetation cover types with a moderately open canopy and ponderosa pine (Pinus ponderosa) forests while avoiding grasslands and montane shrublands across all seasons. Deer selected areas closer to water and developed areas, northeast aspects, on gentle slopes, and at lower elevations. Creating a savanna-like cover type may elicit a positive deer response as a result of their strong avoidance of dense, closed canopy pinyon–juniper woodlands. © 2020 The Wildlife Society.
Decarboxylation of carboxylic acids is favored under hydrothermal conditions, and can be influenced by dissolved metals. Here, we use phenylacetic acid as a model compound to study its hydrothermal decarboxylation in the presence of copper(II) salts but no O2. Our results showed a strong oxidizing role of copper in facilitating oxidative decarboxylation.
","language":"English","publisher":"Royal Society of Chemistry","doi":"10.1039/C9CC09825A","usgsCitation":"Fu, X., Jamison, M., Jubb, A., Liao, Y., Aspin, A., Hayes, K., Glein, C.R., and Yang, Z., 2020, Effect of copper salts on hydrothermal oxidative decarboxylation: A study of phenylacetic acid: Chemical Communications (London), v. 56, no. 18, p. 2791-2794, https://doi.org/10.1039/C9CC09825A.","productDescription":"4 p.","startPage":"2791","endPage":"2794","ipdsId":"IP-114238","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":372256,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"56","issue":"18","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Fu, Xuan","contributorId":222396,"corporation":false,"usgs":false,"family":"Fu","given":"Xuan","email":"","affiliations":[],"preferred":false,"id":782072,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jamison, Megan","contributorId":222399,"corporation":false,"usgs":false,"family":"Jamison","given":"Megan","email":"","affiliations":[],"preferred":false,"id":782075,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jubb, Aaron M. 0000-0001-6875-1079","orcid":"https://orcid.org/0000-0001-6875-1079","contributorId":201978,"corporation":false,"usgs":true,"family":"Jubb","given":"Aaron M.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":782071,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Liao, Yiju","contributorId":222398,"corporation":false,"usgs":false,"family":"Liao","given":"Yiju","email":"","affiliations":[],"preferred":false,"id":782074,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Aspin, Alexandria","contributorId":222400,"corporation":false,"usgs":false,"family":"Aspin","given":"Alexandria","email":"","affiliations":[],"preferred":false,"id":782076,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hayes, Kyle","contributorId":222397,"corporation":false,"usgs":false,"family":"Hayes","given":"Kyle","email":"","affiliations":[],"preferred":false,"id":782073,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Glein, Christopher R.","contributorId":222401,"corporation":false,"usgs":false,"family":"Glein","given":"Christopher","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":782077,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Yang, Ziming","contributorId":222402,"corporation":false,"usgs":false,"family":"Yang","given":"Ziming","email":"","affiliations":[],"preferred":false,"id":782078,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70208851,"text":"70208851 - 2020 - Category count models for adaptive management of metapopulations: Case study of an imperiled salamander","interactions":[],"lastModifiedDate":"2020-04-06T23:17:56.775258","indexId":"70208851","displayToPublicDate":"2020-02-05T11:13:58","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5803,"text":"Conservation Science and Practice","active":true,"publicationSubtype":{"id":10}},"title":"Category count models for adaptive management of metapopulations: Case study of an imperiled salamander","docAbstract":"Managing spatially structured populations of imperiled species presents many challenges. Spatial structure can make it difficult to predict population responses to potential recovery activities, and learning through experimentation may not be advised if it could harm threatened populations. Adaptive management provides an appealing framework when experimentation is considered too risky or time consuming; we used such an approach for imperiled flatwoods salamanders at a Florida wildlife refuge. We represented this metapopulation with category count models and used stochastic dynamic programming to identify optimal decision policies that weighed trade‐offs between metapopulation persistence and management costs. We defined possible wetland categories in terms of habitat suitability and occupancy, specified category‐specific management actions, and identified transition probabilities via expert elicitation for two management strategies: “future” status quo (FSQ; frequent growing‐season burns) and extra management actions (EMA; restoration, translocation, head‐starting). We simulated metapopulation dynamics using the resulting optimal management policy and found that under model FSQ, occupancy steadily declined over time, indicating that populations would rapidly become extirpated; with model EMA, occupancy remained stable, suggesting that populations would persist only if additional actions are applied and are effective. This approach can be used to identify optimal solutions while accounting for uncertainty and considering both habitat and population dynamics, and to help managers make conservation decisions for populations at imminent risk of extinction.
","language":"English","publisher":"Society for Conservation Biology","doi":"10.1111/csp2.180","usgsCitation":"O’Donnell, K., Fackler, P.L., Johnson, F.A., Bonneau, M., Martin, J., and Walls, S.C., 2020, Category count models for adaptive management of metapopulations: Case study of an imperiled salamander: Conservation Science and Practice, v. 2, no. 4, e180, 13 p., https://doi.org/10.1111/csp2.180.","productDescription":"e180, 13 p.","ipdsId":"IP-104504","costCenters":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":457832,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/csp2.180","text":"Publisher Index Page"},{"id":437124,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9K3ZA2D","text":"USGS data release","linkHelpText":"Wetland transition probabilities for category count model elicited from experts at 2015 workshop"},{"id":372850,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"St. Marks National Wildlife Refuge","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -84.51919555664062,\n 29.895424526240554\n ],\n [\n -84.26239013671875,\n 29.895424526240554\n ],\n [\n -84.26239013671875,\n 30.139189195422194\n ],\n [\n -84.51919555664062,\n 30.139189195422194\n ],\n [\n -84.51919555664062,\n 29.895424526240554\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"2","issue":"4","noUsgsAuthors":false,"publicationDate":"2020-02-05","publicationStatus":"PW","contributors":{"authors":[{"text":"O’Donnell, Katherine M. 0000-0001-9023-174X kmodonnell@usgs.gov","orcid":"https://orcid.org/0000-0001-9023-174X","contributorId":176897,"corporation":false,"usgs":true,"family":"O’Donnell","given":"Katherine M.","email":"kmodonnell@usgs.gov","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":783661,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fackler, Paul L.","contributorId":17487,"corporation":false,"usgs":true,"family":"Fackler","given":"Paul","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":783662,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Johnson, Fred A. 0000-0002-5854-3695 fjohnson@usgs.gov","orcid":"https://orcid.org/0000-0002-5854-3695","contributorId":2773,"corporation":false,"usgs":true,"family":"Johnson","given":"Fred","email":"fjohnson@usgs.gov","middleInitial":"A.","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":783663,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bonneau, Mathieu","contributorId":150041,"corporation":false,"usgs":false,"family":"Bonneau","given":"Mathieu","email":"","affiliations":[{"id":12557,"text":"University of Florida, FLREC","active":true,"usgs":false}],"preferred":false,"id":783664,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Martin, Julien 0000-0002-7375-129X","orcid":"https://orcid.org/0000-0002-7375-129X","contributorId":213994,"corporation":false,"usgs":true,"family":"Martin","given":"Julien","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":783665,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Walls, Susan C. 0000-0001-7391-9155 swalls@usgs.gov","orcid":"https://orcid.org/0000-0001-7391-9155","contributorId":138952,"corporation":false,"usgs":true,"family":"Walls","given":"Susan","email":"swalls@usgs.gov","middleInitial":"C.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":783666,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70219049,"text":"70219049 - 2020 - Evidence of wildfires and elevated atmospheric oxygen at the Frasnian–Famennian boundary in New York (USA): Implications for the Late Devonian mass extinction","interactions":[],"lastModifiedDate":"2021-03-22T13:26:33.056379","indexId":"70219049","displayToPublicDate":"2020-02-05T08:23:26","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1786,"text":"Geological Society of America Bulletin","active":true,"publicationSubtype":{"id":10}},"title":"Evidence of wildfires and elevated atmospheric oxygen at the Frasnian–Famennian boundary in New York (USA): Implications for the Late Devonian mass extinction","docAbstract":"The Devonian Period experienced significant fluctuations of atmospheric oxygen (O2) levels (∼25–13%), for which the extent and timing are debated. Also characteristic of the Devonian Period, at the Frasnian–Famennian (F–F) boundary, is one of the “big five” mass extinction events of the Phanerozoic. Fossilized charcoal (inertinite) provides a record of wildfire events, which in turn can provide insight into the evolution of terrestrial ecosystems and the atmospheric composition. Here, we report organic petrology, programmed pyrolysis analysis, major and trace element analyses, and initial osmium isotope (Osi) stratigraphy from five sections of Upper Devonian (F–F interval) from western New York, USA. These data are discussed to infer evidence of a wildfire event at the F–F boundary. Based on the evidence for a wildfire at the F–F boundary we also provide an estimate of atmospheric O2 levels of ∼23–25% at this interval, which is in agreement with the models that predict elevated pO2 levels during the Late Devonian. This, coupled with our Os isotope records, support the currently published Osi data that lacks any evidence for an extra-terrestrial impact or volcanic event at the F–F interval, and therefore to act as a trigger for the F–F mass extinction. The elevated O2 level at the F–F interval inferred from this study supports the hypothesis that pCO2 drawdown and associated climate cooling may have acted as a driving mechanism of the F–F mass extinction.
This study is part of the regional stream-quality assessment (RSQA) conducted by the U.S. Geological Survey (USGS) National Water Quality Assessment (NAWQA) project. The purpose of this study is to examine small streams along land-use and stressor gradients at the regional scale and to evaluate the relative importance of instream stressors on diatom, macroinvertebrate, and fish assemblages. In 2015, the RSQA project assessed stream quality in 82 wadeable streams that were selected along an urban land-use gradient in the Pacific Northwest Region (PNW) of the United States. This study evaluates the effects of four major categories of measured instream stressors – flow (i.e. alteration), water quality, habitat, and contaminants (in water and sediment) – on stream biota. We used gradient forest (GF) models to evaluate taxon specific responses to the various stressors for the three biotic assemblages. Results for diatom, invertebrate and fish assemblages showed that several environmental variables including substrate size, dissolved oxygen, and two or more different contaminants were selected in each of the GF models. In general, all three assemblages were negatively associated with any contaminant measures above zero, except the more tolerant taxa in each assemblage, which responded positively to contaminants. Total nitrogen (TN) and total phosphorus (TP) were important in both the diatom and invertebrate GF models but not in the fish models, which were related to temperature and stream flow. TP and TN were the top two variables for diatom GF models and various taxa responded at a range of nutrient concentrations; however, some taxa responded at low concentrations, for example around 0.02 for TP and 0.5 mg/L for TN. In general, the three biotic assemblages responded to multiple stressors following general patterns of known sensitive versus tolerant taxa for each of the biotic groups studied, yet the GF models allow us to explore taxon specific responses. For example, most of the sensitive Ephemeroptera, Plecoptera, Trichoptera invertebrate taxa (EPT) responded negatively when any contaminant increased above zero; yet some taxa such as the tolerant Trichoptera Cheumatopsyche responded positively to contaminants and many of the other stressors. The findings of this study demonstrate the value of using multiple assemblages to monitoring stressor gradients associated with urban stream systems and the importance of evaluating the responses of individual taxa to stressors.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolind.2019.106047","usgsCitation":"Waite, I.R., Pan, Y., and Edwards, P., 2020, Assessment of multi-stressors on compositional turnover of diatom, invertebrate and fish assemblages along an urban gradient in Pacific Northwest streams (USA): Ecological Indicators, v. 112, 106047, 16 p., https://doi.org/10.1016/j.ecolind.2019.106047.","productDescription":"106047, 16 p.","ipdsId":"IP-110362","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":457842,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://pdxscholar.library.pdx.edu/esm_fac/296","text":"Publisher Index Page"},{"id":382783,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington, Oregon","otherGeospatial":"Stream sites in Midwest Washington and Oregon","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.11279296875001,\n 48.86471476180277\n ],\n [\n -123.26660156249999,\n 47.502358951968574\n ],\n [\n -123.28857421875,\n 44.88701247981298\n ],\n [\n -123.37646484374999,\n 43.197167282501276\n ],\n [\n -121.83837890625,\n 43.35713822211053\n ],\n [\n -121.59667968749999,\n 45.19752230305682\n ],\n [\n -121.57470703125,\n 48.03401915864286\n ],\n [\n -121.53076171875,\n 48.980216985374994\n ],\n [\n -123.11279296875001,\n 48.86471476180277\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"112","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Waite, Ian R. 0000-0003-1681-6955 iwaite@usgs.gov","orcid":"https://orcid.org/0000-0003-1681-6955","contributorId":616,"corporation":false,"usgs":true,"family":"Waite","given":"Ian","email":"iwaite@usgs.gov","middleInitial":"R.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":809363,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pan, Yangdong","contributorId":248559,"corporation":false,"usgs":false,"family":"Pan","given":"Yangdong","affiliations":[{"id":6929,"text":"Portland State University","active":true,"usgs":false}],"preferred":false,"id":809364,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Edwards, Patrick","contributorId":248560,"corporation":false,"usgs":false,"family":"Edwards","given":"Patrick","affiliations":[{"id":6929,"text":"Portland State University","active":true,"usgs":false}],"preferred":false,"id":809365,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70209002,"text":"70209002 - 2020 - Diatom enumeration method influences biological assessments of southeastern USA streams","interactions":[],"lastModifiedDate":"2020-03-10T18:52:34","indexId":"70209002","displayToPublicDate":"2020-02-04T18:41:01","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1699,"text":"Freshwater Science","active":true,"publicationSubtype":{"id":10}},"title":"Diatom enumeration method influences biological assessments of southeastern USA streams","docAbstract":"Current fixed-count enumeration methods for benthic diatoms are likely inadequate for most research and monitoring objectives. These methods underestimate taxa richness and may fail to detect losses of species caused by human impacts. Consequently, the full potential of diatoms is not realized in current assessments of biological integrity or species diversity. In this study, we hypothesize that alternative enumeration methods differ in their ability to quantify species composition. Furthermore, we hypothesize that an alternative to the traditional fixed-count method will improve both performance of observed/expected (O/E) indices derived from River Inver- tebrate Prediction and Classification System models and the discrimination of reference-quality and human-modified sites by other standard metrics used in biological assessments. To test these hypotheses, we assessed 1) how well 3 counting methods characterized species richness in a subset of 15 samples of stream benthic diatoms and 2) how counting method affected the performance of O/E indices and metrics by comparing the traditional fixed- count method against the best-performing alternative method. These latter comparisons were based on samples collected from 68 reference-quality streams and 20 streams located along an urban disturbance gradient. We dem- onstrate that traditional fixed counts failed to detect >1⁄2 of species present in most of the 68 reference-quality sites. Instead, timed-presence data produced the O/E index with the best performance and a level of precision similar to published invertebrate O/E indices. Furthermore, the O/E index based on the timed-presence data allowed us to determine which species are most often lost with urbanization. We found that traditional fixed-count and alter- native timed-presence data produce metrics that are nearly equally able to discriminate between reference and dis- turbed sites. This study demonstrates that alternative counting methods improve species detection and require up to ∼30% less effort.","language":"English","publisher":"University of Chicago Press Journals","doi":"10.1086/707725","usgsCitation":"Tyree, M., Carlisle, D.M., and Spaulding, S., 2020, Diatom enumeration method influences biological assessments of southeastern USA streams: Freshwater Science, v. 39, no. 1, p. 183-195, https://doi.org/10.1086/707725.","productDescription":"13 p.","startPage":"183","endPage":"195","ipdsId":"IP-108185","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":457846,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1086/707725","text":"Publisher Index Page"},{"id":373084,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arkansas, Alabama, Georgia, Louisiana, Maryland, Mississippi, Missouri, North Carolina, South Carolina, Virginia, West Virginia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -95.2294921875,\n 29.916852233070173\n ],\n [\n -74.70703125,\n 29.916852233070173\n ],\n [\n -74.70703125,\n 40.3130432088809\n ],\n [\n -95.2294921875,\n 40.3130432088809\n ],\n [\n -95.2294921875,\n 29.916852233070173\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"39","issue":"1","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Tyree, Meredith","contributorId":207506,"corporation":false,"usgs":false,"family":"Tyree","given":"Meredith","email":"","affiliations":[{"id":36621,"text":"University of Colorado","active":true,"usgs":false}],"preferred":false,"id":784479,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Carlisle, Daren M. 0000-0002-7367-348X","orcid":"https://orcid.org/0000-0002-7367-348X","contributorId":223188,"corporation":false,"usgs":true,"family":"Carlisle","given":"Daren","email":"","middleInitial":"M.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":784480,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Spaulding, Sarah A. 0000-0002-9787-7743","orcid":"https://orcid.org/0000-0002-9787-7743","contributorId":223186,"corporation":false,"usgs":true,"family":"Spaulding","given":"Sarah","middleInitial":"A.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":784478,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70208592,"text":"70208592 - 2020 - Preferential elution of ionic solutes in melting snowpacks: Improving process understanding through field observations and modeling in the Rocky Mountains","interactions":[],"lastModifiedDate":"2020-02-20T06:17:15","indexId":"70208592","displayToPublicDate":"2020-02-04T13:48:26","publicationYear":"2020","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":"Preferential elution of ionic solutes in melting snowpacks: Improving process understanding through field observations and modeling in the Rocky Mountains","docAbstract":"The preferential elution of ions from melting snowpacks is a complex problem that has been linked to temporary acidification of water bodies. However, the understanding of these processes in snowpacks around the world, including the polar regions that are experiencing unprecedented warming and melting, remains limited despite being instrumental in supporting climate change adaptation.
In this study, data collected from a snowmelt lysimeter and snowpits at meadow and forest-gap sites in a high elevation watershed in Colorado were combined with the PULSE multi-phase snowpack chemistry model to investigate the controls of meltwater chemistry and preferential elution. The snowdepth at the meadow site was 64% of that at the forest-gap site, and the snowmelt rate was greater there (meadow snowpit) due to higher solar irradiance. Cations such as Ca2+ and NH
The Northern High Plains aquifer underlies about 93,000 square miles of Colorado, Kansas, Nebraska, South Dakota, and Wyoming and is the largest subregion of the nationally important High Plains aquifer. Irrigation, primarily using groundwater, has supported agricultural production since before 1940, resulting in nearly $50 billion in sales in 2012. In 2010, the High Plains aquifer had the largest groundwater withdrawals of any major aquifer system in the United States. Nearly one-half of those withdrawals were from the Northern High Plains aquifer, which has little hydrologic interaction with parts of the aquifer farther south. Land-surface elevation ranges from more than 7,400 feet (ft) near the western edge to less than 1,100 ft near the eastern edge. Major stream primarily flow west to east and include the Big Blue River, Elkhorn River, Loup River, Niobrara River, Republican River and Platte River with its two forks—the North Platte River and South Platte River. Population in the Northern High Plain aquifer area is sparse with only 2 cities having a population greater than 30,000.
Droughts across much of the area from 2001 to 2007, combined with recent (2004–18) legislation, have heightened concerns regarding future groundwater availability and highlighted the need for science-based water-resource management. Groundwater models with the capability to provide forecasts of groundwater availability and related stream base flows from the Northern High Plains aquifer were published recently (2016) and were used to analyze groundwater availability. Stream base flows are generally the dominant component of total streamflow in the Northern High Plains aquifer, and total streamflows or shortages thereof define conjunctive management triggers, at least in Nebraska. Groundwater availability was evaluated through comparison of aquifer-scale water budgets compared for periods before and after major groundwater development and across selected future forecasts. Groundwater-level declines and the forecast amount of groundwater in storage in the aquifer also were examined.
Director, Nebraska Water Science Center
U.S. Geological Survey
5231 South 19th Street
Lincoln, NE 68512