{"pageNumber":"386","pageRowStart":"9625","pageSize":"25","recordCount":41081,"records":[{"id":70197767,"text":"70197767 - 2018 - Analysis of mean seismic ground motion and its uncertainty based on the UCERF3 geologic slip rate model with uncertainty for California","interactions":[],"lastModifiedDate":"2018-07-03T10:58:42","indexId":"70197767","displayToPublicDate":"2018-06-20T00:00:00","publicationYear":"2018","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":"Analysis of mean seismic ground motion and its uncertainty based on the UCERF3 geologic slip rate model with uncertainty for California","docAbstract":"The Uniform California Earthquake Rupture Forecast v.3 (UCERF3) model (Field et al., 2014) considers epistemic uncertainty in fault‐slip rate via the inclusion of multiple rate models based on geologic and/or geodetic data. However, these slip rates are commonly clustered about their mean value and do not reflect the broader distribution of possible rates and associated probabilities. Here, we consider both a double‐truncated 2σ Gaussian and a boxcar distribution of slip rates and use a Monte Carlo simulation to sample the entire range of the distribution for California fault‐slip rates. We compute the seismic hazard following the methodology and logic‐tree branch weights applied to the 2014 national seismic hazard model (NSHM) for the western U.S. region (Petersen et al., 2014, 2015). By applying a new approach developed in this study to the probabilistic seismic hazard analysis (PSHA) using precomputed rates of exceedance from each fault as a Green’s function, we reduce the computer time by about 10^5‐fold and apply it to the mean PSHA estimates with 1000 Monte Carlo samples of fault‐slip rates to compare with results calculated using only the mean or preferred slip rates. The difference in the mean probabilistic peak ground motion corresponding to a 2% in 50‐yr probability of exceedance is less than 1% on average over all of California for both the Gaussian and boxcar probability distributions for slip‐rate uncertainty but reaches about 18% in areas near faults compared with that calculated using the mean or preferred slip rates. The average uncertainties in 1σ peak ground‐motion level are 5.5% and 7.3% of the mean with the relative maximum uncertainties of 53% and 63% for the Gaussian and boxcar probability density function (PDF), respectively.","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0220170114","usgsCitation":"Zeng, Y., 2018, Analysis of mean seismic ground motion and its uncertainty based on the UCERF3 geologic slip rate model with uncertainty for California: Seismological Research Letters, v. 89, no. 4, p. 1410-1419, https://doi.org/10.1785/0220170114.","productDescription":"10 p.","startPage":"1410","endPage":"1419","ipdsId":"IP-094845","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":355189,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"89","issue":"4","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2018-04-25","publicationStatus":"PW","scienceBaseUri":"5b46e556e4b060350a15d0f5","contributors":{"authors":[{"text":"Zeng, Yuehua 0000-0003-1161-1264 zeng@usgs.gov","orcid":"https://orcid.org/0000-0003-1161-1264","contributorId":145693,"corporation":false,"usgs":true,"family":"Zeng","given":"Yuehua","email":"zeng@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":738438,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70197818,"text":"70197818 - 2018 - A model ensemble for projecting multi‐decadal coastal cliff retreat during the 21st century","interactions":[],"lastModifiedDate":"2018-08-31T10:53:52","indexId":"70197818","displayToPublicDate":"2018-06-20T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2318,"text":"Journal of Geophysical Research F: Earth Surface","active":true,"publicationSubtype":{"id":10}},"title":"A model ensemble for projecting multi‐decadal coastal cliff retreat during the 21st century","docAbstract":"

Sea cliff retreat rates are expected to accelerate with rising sea levels during the 21st century. Here we develop an approach for a multi‐model ensemble that efficiently projects time‐averaged sea cliff retreat over multi‐decadal time scales and large (>50 km) spatial scales. The ensemble consists of five simple 1‐D models adapted from the literature that relate sea cliff retreat to wave impacts, sea level rise (SLR), historical cliff behavior, and cross‐shore profile geometry. Ensemble predictions are based on Monte Carlo simulations of each individual model, which account for the uncertainty of model parameters. The consensus of the individual models also weights uncertainty, such that uncertainty is greater when predictions from different models do not agree. A calibrated, but unvalidated, ensemble was applied to the 475 km‐long coastline of Southern California (USA), with 4 SLR scenarios of 0.5, 0.93, 1.5, and 2 m by 2100. Results suggest that future retreat rates could increase relative to mean historical rates by more than two‐fold for the higher SLR scenarios, causing an average total land loss of 19 – 41 m by 2100. However, model uncertainty ranges from +/‐ 5 – 15 m, reflecting the inherent difficulties of projecting cliff retreat over multiple decades. To enhance ensemble performance, future work could include weighting each model by its skill in matching observations in different morphological settings

","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2017JF004401","usgsCitation":"Limber, P.W., Barnard, P., Vitousek, S., and Erikson, L.H., 2018, A model ensemble for projecting multi‐decadal coastal cliff retreat during the 21st century: Journal of Geophysical Research F: Earth Surface, v. 123, no. 7, p. 1566-1589, https://doi.org/10.1029/2017JF004401.","productDescription":"24 p.","startPage":"1566","endPage":"1589","ipdsId":"IP-088080","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":468640,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2017jf004401","text":"Publisher Index Page"},{"id":355235,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"123","issue":"7","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-07-20","publicationStatus":"PW","scienceBaseUri":"5b46e555e4b060350a15d0e7","contributors":{"authors":[{"text":"Limber, Patrick W. 0000-0002-8207-3750 plimber@usgs.gov","orcid":"https://orcid.org/0000-0002-8207-3750","contributorId":196794,"corporation":false,"usgs":true,"family":"Limber","given":"Patrick","email":"plimber@usgs.gov","middleInitial":"W.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":738644,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Barnard, Patrick L. 0000-0003-1414-6476 pbarnard@usgs.gov","orcid":"https://orcid.org/0000-0003-1414-6476","contributorId":147147,"corporation":false,"usgs":true,"family":"Barnard","given":"Patrick L.","email":"pbarnard@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":738645,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"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":738646,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Erikson, Li H. 0000-0002-8607-7695 lerikson@usgs.gov","orcid":"https://orcid.org/0000-0002-8607-7695","contributorId":149963,"corporation":false,"usgs":true,"family":"Erikson","given":"Li","email":"lerikson@usgs.gov","middleInitial":"H.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":738647,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70197799,"text":"70197799 - 2018 - Landslides triggered by the 14 November 2016 Mw 7.8 Kaikōura Earthquake, New Zealand","interactions":[],"lastModifiedDate":"2018-07-03T10:57:53","indexId":"70197799","displayToPublicDate":"2018-06-20T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"Landslides triggered by the 14 November 2016 Mw 7.8 Kaikōura Earthquake, New Zealand","docAbstract":"

The 14 November 2016 Mw\">MwMw 7.8 Kaikōura earthquake generated more than 10,000 landslides over a total area of about 10,000  km2\">10,000  km210,000  km2, with the majority concentrated in a smaller area of about 3600  km2\">3600  km23600  km2. The largest landslide triggered by the earthquake had an approximate volume of 20(±2)  M m3\">20(±2)  M m320(±2)  M m3, with a runout distance of about 2.7 km, forming a dam on the Hapuku River. In this article, we present version 1.0 of the landslide inventory we have created for this event. We use the inventory presented in this article to identify and discuss some of the controls on the spatial distribution of landslides triggered by the Kaikōura earthquake. Our main findings are (1) the number of medium to large landslides (source area ≥10,000  m2\">≥10,000  m2≥10,000  m2) triggered by the Kaikōura earthquake is smaller than for similar‐sized landslides triggered by similar magnitude earthquakes in New Zealand; (2) seven of the largest eight landslides (from 5 to 20  M m3\">20  M m320  M m3) occurred on faults that ruptured to the surface during the earthquake; (3) the average landslide density within 200 m of a mapped surface fault rupture is three times that at a distance of 2500 m or more from a mapped surface fault rupture; (4) the “distance to fault” predictor variable, when used as a proxy for ground‐motion intensity, and when combined with slope angle, geology, and elevation variables, has more power in predicting landslide probability than the modeled peak ground acceleration or peak ground velocity; and (5) for the same slope angles, the coastal slopes have landslide point densities that are an order of magnitude greater than those in similar materials on the inland slopes, but their source areas are significantly smaller.

","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120170305","usgsCitation":"Massey, C., Townsend, D., Rathje, E., Allstadt, K.E., Lukovic, B., Kaneko, Y., Bradley, B.A., Wartman, J., Jibson, R.W., Petley, D., Horspool, N., Hamling, I., Carey, J., Cox, S., Davidson, J., Dellow, S., Godt, J.W., Holden, C., Jones, K.D., Kaiser, A.E., Little, M., Lyndsell, B., McColl, S., Morgenstern, R., Rengers, F.K., Rhoades, D., Rosser, B., Strong, D., Singeisen, C., and Villeneuve, M., 2018, Landslides triggered by the 14 November 2016 Mw 7.8 Kaikōura Earthquake, New Zealand: Bulletin of the Seismological Society of America, v. 108, no. 3B, p. 1630-1648, https://doi.org/10.1785/0120170305.","productDescription":"19 p.","startPage":"1630","endPage":"1648","ipdsId":"IP-093006","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":468644,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://eprints.whiterose.ac.uk/128042/1/18_02%20Kaikoura%20paper%20final%20accepted%20version.pdf","text":"External Repository"},{"id":355214,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"New Zealand","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 172.88909912109375,\n -42.807491865911544\n ],\n [\n 174.7430419921875,\n -42.807491865911544\n ],\n [\n 174.7430419921875,\n -41.54764462357735\n ],\n [\n 172.88909912109375,\n -41.54764462357735\n ],\n [\n 172.88909912109375,\n -42.807491865911544\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"108","issue":"3B","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2018-03-27","publicationStatus":"PW","scienceBaseUri":"5b46e555e4b060350a15d0ed","contributors":{"authors":[{"text":"Massey, C.","contributorId":205807,"corporation":false,"usgs":false,"family":"Massey","given":"C.","email":"","affiliations":[{"id":36277,"text":"GNS Science","active":true,"usgs":false}],"preferred":false,"id":738537,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Townsend, D.","contributorId":205808,"corporation":false,"usgs":false,"family":"Townsend","given":"D.","email":"","affiliations":[{"id":36277,"text":"GNS Science","active":true,"usgs":false}],"preferred":false,"id":738538,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rathje, Ellen 0000-0002-4169-7153","orcid":"https://orcid.org/0000-0002-4169-7153","contributorId":197024,"corporation":false,"usgs":false,"family":"Rathje","given":"Ellen","email":"","affiliations":[],"preferred":false,"id":738539,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Allstadt, Kate E. 0000-0003-4977-5248 kallstadt@usgs.gov","orcid":"https://orcid.org/0000-0003-4977-5248","contributorId":167684,"corporation":false,"usgs":true,"family":"Allstadt","given":"Kate","email":"kallstadt@usgs.gov","middleInitial":"E.","affiliations":[{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true},{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":false,"id":738540,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lukovic, B.","contributorId":205809,"corporation":false,"usgs":false,"family":"Lukovic","given":"B.","email":"","affiliations":[{"id":36277,"text":"GNS Science","active":true,"usgs":false}],"preferred":false,"id":738543,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kaneko, Yoshihiro","contributorId":204610,"corporation":false,"usgs":false,"family":"Kaneko","given":"Yoshihiro","email":"","affiliations":[{"id":5111,"text":"GNS Science, New Zealand","active":true,"usgs":false}],"preferred":false,"id":738541,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bradley, Brendon A.","contributorId":202814,"corporation":false,"usgs":false,"family":"Bradley","given":"Brendon","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":738544,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Wartman, J.","contributorId":205810,"corporation":false,"usgs":false,"family":"Wartman","given":"J.","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":738545,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Jibson, Randall W. 0000-0003-3399-0875 jibson@usgs.gov","orcid":"https://orcid.org/0000-0003-3399-0875","contributorId":2985,"corporation":false,"usgs":true,"family":"Jibson","given":"Randall","email":"jibson@usgs.gov","middleInitial":"W.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":738554,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Petley, D. N.","contributorId":205818,"corporation":false,"usgs":false,"family":"Petley","given":"D. N.","affiliations":[{"id":37171,"text":"Universityof Sheffield","active":true,"usgs":false}],"preferred":false,"id":738561,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Horspool, Nick","contributorId":175114,"corporation":false,"usgs":false,"family":"Horspool","given":"Nick","email":"","affiliations":[],"preferred":false,"id":738546,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Hamling, I.","contributorId":205811,"corporation":false,"usgs":false,"family":"Hamling","given":"I.","affiliations":[{"id":36277,"text":"GNS Science","active":true,"usgs":false}],"preferred":false,"id":738547,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Carey, J.","contributorId":205824,"corporation":false,"usgs":false,"family":"Carey","given":"J.","affiliations":[],"preferred":false,"id":738548,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Cox, S.","contributorId":205812,"corporation":false,"usgs":false,"family":"Cox","given":"S.","email":"","affiliations":[{"id":36277,"text":"GNS Science","active":true,"usgs":false}],"preferred":false,"id":738549,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Davidson, John","contributorId":197473,"corporation":false,"usgs":false,"family":"Davidson","given":"John","affiliations":[],"preferred":false,"id":738550,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Dellow, S.","contributorId":205813,"corporation":false,"usgs":false,"family":"Dellow","given":"S.","email":"","affiliations":[{"id":36277,"text":"GNS Science","active":true,"usgs":false}],"preferred":false,"id":738551,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Godt, Jonathan W. 0000-0002-8737-2493 jgodt@usgs.gov","orcid":"https://orcid.org/0000-0002-8737-2493","contributorId":1166,"corporation":false,"usgs":true,"family":"Godt","given":"Jonathan","email":"jgodt@usgs.gov","middleInitial":"W.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":508,"text":"Office of the AD Hazards","active":true,"usgs":true}],"preferred":true,"id":738552,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Holden, Christopher","contributorId":172521,"corporation":false,"usgs":false,"family":"Holden","given":"Christopher","email":"","affiliations":[],"preferred":false,"id":738553,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Jones, Katherine D.","contributorId":169802,"corporation":false,"usgs":false,"family":"Jones","given":"Katherine","email":"","middleInitial":"D.","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":738555,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Kaiser, Anna E.","contributorId":141200,"corporation":false,"usgs":false,"family":"Kaiser","given":"Anna","email":"","middleInitial":"E.","affiliations":[{"id":6956,"text":"GNS Science/Massey University","active":true,"usgs":false}],"preferred":false,"id":738556,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"Little, M.","contributorId":205814,"corporation":false,"usgs":false,"family":"Little","given":"M.","email":"","affiliations":[{"id":36422,"text":"University of Texas","active":true,"usgs":false}],"preferred":false,"id":738557,"contributorType":{"id":1,"text":"Authors"},"rank":21},{"text":"Lyndsell, B.","contributorId":205815,"corporation":false,"usgs":false,"family":"Lyndsell","given":"B.","email":"","affiliations":[{"id":36277,"text":"GNS Science","active":true,"usgs":false}],"preferred":false,"id":738558,"contributorType":{"id":1,"text":"Authors"},"rank":22},{"text":"McColl, S.","contributorId":205816,"corporation":false,"usgs":false,"family":"McColl","given":"S.","email":"","affiliations":[{"id":13571,"text":"Massey University","active":true,"usgs":false}],"preferred":false,"id":738559,"contributorType":{"id":1,"text":"Authors"},"rank":23},{"text":"Morgenstern, R.","contributorId":205817,"corporation":false,"usgs":false,"family":"Morgenstern","given":"R.","email":"","affiliations":[{"id":36277,"text":"GNS Science","active":true,"usgs":false}],"preferred":false,"id":738560,"contributorType":{"id":1,"text":"Authors"},"rank":24},{"text":"Rengers, Francis K. 0000-0002-1825-0943 frengers@usgs.gov","orcid":"https://orcid.org/0000-0002-1825-0943","contributorId":150422,"corporation":false,"usgs":true,"family":"Rengers","given":"Francis","email":"frengers@usgs.gov","middleInitial":"K.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":738562,"contributorType":{"id":1,"text":"Authors"},"rank":25},{"text":"Rhoades, D.","contributorId":205819,"corporation":false,"usgs":false,"family":"Rhoades","given":"D.","email":"","affiliations":[{"id":36277,"text":"GNS Science","active":true,"usgs":false}],"preferred":false,"id":738563,"contributorType":{"id":1,"text":"Authors"},"rank":26},{"text":"Rosser, B.","contributorId":205820,"corporation":false,"usgs":false,"family":"Rosser","given":"B.","email":"","affiliations":[{"id":36277,"text":"GNS Science","active":true,"usgs":false}],"preferred":false,"id":738564,"contributorType":{"id":1,"text":"Authors"},"rank":27},{"text":"Strong, D.","contributorId":131061,"corporation":false,"usgs":false,"family":"Strong","given":"D.","email":"","affiliations":[{"id":7214,"text":"University of California, Davis","active":true,"usgs":false}],"preferred":false,"id":738565,"contributorType":{"id":1,"text":"Authors"},"rank":28},{"text":"Singeisen, C.","contributorId":205821,"corporation":false,"usgs":false,"family":"Singeisen","given":"C.","email":"","affiliations":[{"id":36277,"text":"GNS Science","active":true,"usgs":false}],"preferred":false,"id":738566,"contributorType":{"id":1,"text":"Authors"},"rank":29},{"text":"Villeneuve, M.","contributorId":205822,"corporation":false,"usgs":false,"family":"Villeneuve","given":"M.","email":"","affiliations":[{"id":37172,"text":"University of Canterbury","active":true,"usgs":false}],"preferred":false,"id":738567,"contributorType":{"id":1,"text":"Authors"},"rank":30}]}} ,{"id":70198088,"text":"70198088 - 2018 - Hydrological regime and climate interactively shape riparian vegetation composition along the Colorado River, Grand Canyon","interactions":[],"lastModifiedDate":"2018-11-21T15:35:06","indexId":"70198088","displayToPublicDate":"2018-06-19T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":849,"text":"Applied Vegetation Science","active":true,"publicationSubtype":{"id":10}},"title":"Hydrological regime and climate interactively shape riparian vegetation composition along the Colorado River, Grand Canyon","docAbstract":"

Question

How closely do riparian plant communities track hydrological and climatic variation in space, and how do interactions among hydrological and climatic filters influence success of flow management strategies?

Location

Grand Canyon, Arizona, USA.

Methods

Multi‐year vegetation surveys were conducted across three hydrological zones – active channel, active floodplain and inactive floodplain – within each of 42 sandbars that vary geographically in temperature and precipitation along a 400‐km river segment. Ecological niche models were used to estimate locally optimal conditions of maximum inundation duration, elevation above daily peak flow, mean annual precipitation, and mean maximum and minimum temperature for 16 of the most abundant woody and 58 most abundant herbaceous plant species. These estimates were used to calculate community‐weighted mean (CWM) environmental preferences, which were used to determine how closely vegetation preferences tracked local variation in environmental factors, and to assess interactive responses of species and communities to variation in hydrology and climate.

Results

Communities closely tracked hydrological variation across zones, but less so within zones. Communities tracked variation in minimum temperature more closely than maximum temperature or precipitation. At the species level, woody plants that were more abundant in wetter hydrological conditions were also more abundant in wetter climatic conditions, and vice versa. This relationship was even stronger at the community level, where there were significant negative relationships between CWM preferences of inundation duration and temperature for both woody and herbaceous vegetation.

Conclusions

The climate‐hydrology linkages found in this system suggest that increasing temperatures and drought are likely to reduce the inundation tolerance of riparian vegetation within the Grand Canyon. Increasing the duration of high flow events would likely reduce the abundance of encroaching woody vegetation, but could also reduce the resilience of remaining vegetation to heat waves and drought. The reinforcing effects of climatic and hydrological filters are likely to generally result in greater sensitivity of species composition to environmental change than if those environmental filters acted independently. These results have implications for predicting resource responses to environmental change, as well as prescriptions for direct vegetation management to enhance resilience.

","language":"English","publisher":"Wiley","doi":"10.1111/avsc.12390","usgsCitation":"Butterfield, B.J., Palmquist, E.C., and Ralston, B., 2018, Hydrological regime and climate interactively shape riparian vegetation composition along the Colorado River, Grand Canyon: Applied Vegetation Science, v. 21, no. 4, p. 572-583, https://doi.org/10.1111/avsc.12390.","productDescription":"12 p.","startPage":"572","endPage":"583","ipdsId":"IP-094409","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":437854,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7DN4493","text":"USGS data release","linkHelpText":"Climate, hydrology and riparian vegetation composition data, Grand Canyon, Arizona"},{"id":355671,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Colorado River, Grand Canyon","volume":"21","issue":"4","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-08-19","publicationStatus":"PW","scienceBaseUri":"5b6fc430e4b0f5d57878ea11","contributors":{"authors":[{"text":"Butterfield, Bradley J. 0000-0003-0974-9811","orcid":"https://orcid.org/0000-0003-0974-9811","contributorId":167009,"corporation":false,"usgs":false,"family":"Butterfield","given":"Bradley","email":"","middleInitial":"J.","affiliations":[{"id":24591,"text":"Merriam-Powell Center for Environmental Research and Department of Biological Sciences, Northern Arizona University, Flagstaff, AZ, USA","active":true,"usgs":false}],"preferred":false,"id":739959,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Palmquist, Emily C. 0000-0003-1069-2154 epalmquist@usgs.gov","orcid":"https://orcid.org/0000-0003-1069-2154","contributorId":5669,"corporation":false,"usgs":true,"family":"Palmquist","given":"Emily","email":"epalmquist@usgs.gov","middleInitial":"C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":739960,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ralston, Barbara 0000-0001-9991-8994 bralston@usgs.gov","orcid":"https://orcid.org/0000-0001-9991-8994","contributorId":195797,"corporation":false,"usgs":true,"family":"Ralston","given":"Barbara","email":"bralston@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true},{"id":501,"text":"Office of Science Quality and Integrity","active":true,"usgs":true}],"preferred":true,"id":739961,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70197736,"text":"70197736 - 2018 - Respiratory hazard assessment of combined exposure to complete gasoline exhaust and respirable volcanic ash in a multicellular human lung model at the air-liquid interface","interactions":[],"lastModifiedDate":"2018-06-19T16:41:52","indexId":"70197736","displayToPublicDate":"2018-06-19T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1555,"text":"Environmental Pollution","active":true,"publicationSubtype":{"id":10}},"title":"Respiratory hazard assessment of combined exposure to complete gasoline exhaust and respirable volcanic ash in a multicellular human lung model at the air-liquid interface","docAbstract":"

Communities resident in urban areas located near active volcanoes can experience volcanic ash exposures during, and following, an eruption, in addition to sustained exposures to high concentrations of anthropogenic air pollutants (e.g., vehicle exhaust emissions). Inhalation of anthropogenic pollution is known to cause the onset of, or exacerbate, respiratory and cardiovascular diseases. It is further postulated similar exposure to volcanic ash can also affect such disease states. Understanding of the impact of combined exposure of volcanic ash and anthropogenic pollution to human health, however, remains limited.

The aim of this study was to assess the biological impact of combined exposure to respirable volcanic ash (from Soufrière Hills volcano (SHV), Montserrat and Chaitén volcano (ChV), Chile; representing different magmatic compositions and eruption styles) and freshly-generated complete exhaust from a gasoline vehicle. A multicellular human lung model (an epithelial cell-layer composed of A549 alveolar type II-like cells complemented with human blood monocyte-derived macrophages and dendritic cells cultured at the air-liquid interface) was exposed to diluted exhaust (1:10) continuously for 6 h, followed by immediate exposure to the ash as a dry powder (0.54 ± 0.19 μg/cm2 and 0.39 ± 0.09 μg/cm2 for SHV and ChV ash, respectively). After an 18 h incubation, cells were exposed again for 6 h to diluted exhaust, and a final 18 h incubation (at 37 °C and 5% CO2). Cell cultures were then assessed for cytotoxic, oxidative stress and (pro-)inflammatory responses.

Results indicate that, at all tested (sub-lethal) concentrations, co-exposures with both ash samples induced no significant expression of genes associated with oxidative stress (HMOX1, NQO1) or production of (pro-)inflammatory markers (IL-1β, IL-8, TNF-α) at the gene and protein levels. In summary, considering the employed experimental conditions, combined exposure of volcanic ash and gasoline vehicle exhaust has a limited short-term biological impact to an advanced lung cell in vitro model.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.envpol.2018.01.115","usgsCitation":"Tomasek, I., Horwell, C.J., Bisig, C., Damby, D., Comte, P., Czerwinski, J., Petri-Fink, A., Clift, M., Drasler, B., and Rothen-Rutishauer, B., 2018, Respiratory hazard assessment of combined exposure to complete gasoline exhaust and respirable volcanic ash in a multicellular human lung model at the air-liquid interface: Environmental Pollution, v. 238, p. 977-987, https://doi.org/10.1016/j.envpol.2018.01.115.","productDescription":"12 p.","startPage":"977","endPage":"987","ipdsId":"IP-094236","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":468648,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.envpol.2018.01.115","text":"Publisher Index Page"},{"id":355177,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"238","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b46e559e4b060350a15d103","contributors":{"authors":[{"text":"Tomasek, Ines","contributorId":205741,"corporation":false,"usgs":false,"family":"Tomasek","given":"Ines","email":"","affiliations":[{"id":37158,"text":"Institute of Hazard, Risk & Resilience, Department of Earth Sciences, Durham University, UK","active":true,"usgs":false}],"preferred":false,"id":738328,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Horwell, Claire J.","contributorId":177455,"corporation":false,"usgs":false,"family":"Horwell","given":"Claire","email":"","middleInitial":"J.","affiliations":[{"id":16770,"text":"Dept. Earth Sciences, Durham University, UK","active":true,"usgs":false}],"preferred":false,"id":738329,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bisig, Christoph","contributorId":205742,"corporation":false,"usgs":false,"family":"Bisig","given":"Christoph","email":"","affiliations":[{"id":37159,"text":"Adolphe Merkle Institute, University of Fribourg, Switzerland","active":true,"usgs":false}],"preferred":false,"id":738330,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Damby, David 0000-0002-3238-3961 ddamby@usgs.gov","orcid":"https://orcid.org/0000-0002-3238-3961","contributorId":177453,"corporation":false,"usgs":true,"family":"Damby","given":"David","email":"ddamby@usgs.gov","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":738327,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Comte, Pierre","contributorId":205743,"corporation":false,"usgs":false,"family":"Comte","given":"Pierre","email":"","affiliations":[{"id":37160,"text":"Bern University for Applied Sciences, Nidau, Switzerland","active":true,"usgs":false}],"preferred":false,"id":738331,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Czerwinski, Jan","contributorId":205744,"corporation":false,"usgs":false,"family":"Czerwinski","given":"Jan","email":"","affiliations":[{"id":37160,"text":"Bern University for Applied Sciences, Nidau, Switzerland","active":true,"usgs":false}],"preferred":false,"id":738332,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Petri-Fink, Alke","contributorId":177458,"corporation":false,"usgs":false,"family":"Petri-Fink","given":"Alke","email":"","affiliations":[],"preferred":false,"id":738333,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Clift, Martin J D","contributorId":205745,"corporation":false,"usgs":false,"family":"Clift","given":"Martin J D","affiliations":[{"id":37161,"text":"Swansea University Medical School, Swansea, United Kingdom","active":true,"usgs":false}],"preferred":false,"id":738334,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Drasler, Barbara","contributorId":205746,"corporation":false,"usgs":false,"family":"Drasler","given":"Barbara","email":"","affiliations":[{"id":37159,"text":"Adolphe Merkle Institute, University of Fribourg, Switzerland","active":true,"usgs":false}],"preferred":false,"id":738335,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Rothen-Rutishauer, Barbara","contributorId":205747,"corporation":false,"usgs":false,"family":"Rothen-Rutishauer","given":"Barbara","email":"","affiliations":[{"id":37159,"text":"Adolphe Merkle Institute, University of Fribourg, Switzerland","active":true,"usgs":false}],"preferred":false,"id":738336,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70197754,"text":"70197754 - 2018 - Reverse weathering in marine sediments and the geochemical cycle of potassium in seawater: Insights from the K isotopic composition (41K/39K) of deep-sea pore-fluids","interactions":[],"lastModifiedDate":"2018-08-03T16:12:29","indexId":"70197754","displayToPublicDate":"2018-06-19T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1759,"text":"Geochimica et Cosmochimica Acta","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Reverse weathering in marine sediments and the geochemical cycle of potassium in seawater: Insights from the K isotopic composition (41K/39K) of deep-sea pore-fluids","title":"Reverse weathering in marine sediments and the geochemical cycle of potassium in seawater: Insights from the K isotopic composition (41K/39K) of deep-sea pore-fluids","docAbstract":"

In situ Al-silicate formation, also known as “reverse weathering,” is an important sink of many of the major and minor cations in seawater (e.g. Mg, K, and Li). However, the importance of this sink in global geochemical cycles and isotopic budgets of these elements remains poorly constrained. Here, we report on the potassium isotopic composition (41\">41K/39\">39K) of deep-sea sediment pore-fluids from four (Integrated) Ocean Drilling Program sites (1052, U1378, U1395 and U1403) to characterize potassium isotopic fractionation associated with the formation of authigenic Al-silicate minerals in marine sediments and its role in elevating the 41\">41K/39\">39K of seawater relative to bulk silicate Earth. Isotopic ratios are obtained by high-resolution multi-collector inductively coupled plasma mass spectrometry (MC-ICP-MS) in cold plasma conditions with a long-term external reproducibility of ca. 0.17‰. We find that, although all sites are characterized by pore-fluid K concentrations that decline with increasing depth, their K isotopic profiles vary systematically from site-to-site; at sites characterized by rapid sedimentation rates, pore-fluid profiles of 41\">41K/39\">39K are relatively invariant whereas at sites characterized by slow sedimentation rates, 41\">41K/39\">39K declines with depth by up to 1.8‰. Results from 1-D diffusion-advection-reaction models suggest that these differences may result from a complex interplay between sedimentation rate and fractionation of K isotopes during diffusion, Al-silicate authigenesis, and ion exchange. Model simulations suggest fractionation factors between 0.9980 and 1.0000 for reverse weathering reactions in deep-sea sediments. Although deep-sea sites do not constitute major sinks of K in seawater, some of the processes responsible for K isotopic fractionation at these sites (diffusion and Al-silicate authigenesis) likely play a role in determining the 41\">41K/39\">39K of seawater.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.gca.2018.02.035","usgsCitation":"Santiago Ramos, D.P., Morgan, L.E., Lloyd, N.S., and Higgins, J.A., 2018, Reverse weathering in marine sediments and the geochemical cycle of potassium in seawater: Insights from the K isotopic composition (41K/39K) of deep-sea pore-fluids: Geochimica et Cosmochimica Acta, v. 236, p. 99-120, https://doi.org/10.1016/j.gca.2018.02.035.","productDescription":"22 p.","startPage":"99","endPage":"120","ipdsId":"IP-089179","costCenters":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":355179,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"236","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b46e557e4b060350a15d0ff","contributors":{"authors":[{"text":"Santiago Ramos, Danielle P.","contributorId":199530,"corporation":false,"usgs":false,"family":"Santiago Ramos","given":"Danielle","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":738390,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Morgan, Leah E. 0000-0001-9930-524X lemorgan@usgs.gov","orcid":"https://orcid.org/0000-0001-9930-524X","contributorId":176174,"corporation":false,"usgs":true,"family":"Morgan","given":"Leah","email":"lemorgan@usgs.gov","middleInitial":"E.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":738389,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lloyd, Nicholas S.","contributorId":199532,"corporation":false,"usgs":false,"family":"Lloyd","given":"Nicholas","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":738391,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Higgins, John A.","contributorId":199534,"corporation":false,"usgs":false,"family":"Higgins","given":"John","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":738392,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70200630,"text":"70200630 - 2018 - A method to value nature-related webcam viewing: The value of virtual use with application to brown bear webcam viewing","interactions":[],"lastModifiedDate":"2018-10-26T09:47:55","indexId":"70200630","displayToPublicDate":"2018-06-18T12:37:08","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5771,"text":"Journal of Environmental Economics and Policy","active":true,"publicationSubtype":{"id":10}},"title":"A method to value nature-related webcam viewing: The value of virtual use with application to brown bear webcam viewing","docAbstract":"

There are an estimated 16,000 nature related remote web cameras that provide users around the world with an opportunity to view wildlife. Because there is no monetary price to view the webcams, we utilise variations in the viewers’ opportunity cost of time to estimate consumer surplus. We apply this model to a large sample (n = 2649) of the more than 10 million viewers of Alaska's Katmai National Park and Preserve brown bear webcams. The resulting consumer surplus is around \\$11 per hour of viewing. When applied to the 2.42 million viewer hours, this yields a benefit of \\$27 million annually. Since there are limits on the number of visitors as well as high costs of visiting this remote site, the aggregate webcam viewing value is more than twice the aggregate on-site viewing value. With minimal survey data required to apply this model, we believe it has broad applicability to other nature-related webcams around the world.

","language":"English","publisher":"Taylor and Francis","doi":"10.1080/21606544.2018.1483842","usgsCitation":"Loomis, J.B., Richardson, L., Huber, C., Skibins, J., and Sharp, R., 2018, A method to value nature-related webcam viewing: The value of virtual use with application to brown bear webcam viewing: Journal of Environmental Economics and Policy, v. 7, no. 4, p. 452-462, https://doi.org/10.1080/21606544.2018.1483842.","productDescription":"11 p.","startPage":"452","endPage":"462","ipdsId":"IP-090967","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":358820,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"7","issue":"4","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2018-06-18","publicationStatus":"PW","scienceBaseUri":"5c10a99ae4b034bf6a7e5359","contributors":{"authors":[{"text":"Loomis, John B.","contributorId":197268,"corporation":false,"usgs":false,"family":"Loomis","given":"John","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":749758,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Richardson, Leslie","contributorId":197525,"corporation":false,"usgs":false,"family":"Richardson","given":"Leslie","affiliations":[],"preferred":false,"id":749759,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Huber, Christopher 0000-0001-8446-8134 chuber@usgs.gov","orcid":"https://orcid.org/0000-0001-8446-8134","contributorId":127600,"corporation":false,"usgs":true,"family":"Huber","given":"Christopher","email":"chuber@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":749757,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Skibins, Jeffrey","contributorId":210077,"corporation":false,"usgs":false,"family":"Skibins","given":"Jeffrey","email":"","affiliations":[{"id":12661,"text":"Kansas State University","active":true,"usgs":false}],"preferred":false,"id":749760,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sharp, Ryan","contributorId":168598,"corporation":false,"usgs":false,"family":"Sharp","given":"Ryan","email":"","affiliations":[{"id":12661,"text":"Kansas State University","active":true,"usgs":false}],"preferred":false,"id":749761,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70204848,"text":"70204848 - 2018 - A framework for identifying and characterising coral reef “oases” against a backdrop of degradation","interactions":[],"lastModifiedDate":"2020-09-01T14:08:16.952561","indexId":"70204848","displayToPublicDate":"2018-06-18T08:10:12","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2163,"text":"Journal of Applied Ecology","active":true,"publicationSubtype":{"id":10}},"title":"A framework for identifying and characterising coral reef “oases” against a backdrop of degradation","docAbstract":"
  1. Human activities have led to widespread ecological decline; however, the severity of degradation is spatially heterogeneous due to some locations resisting, escaping, or rebounding from disturbances.
  2. We developed a framework for identifying oases within coral reef regions using long‐term monitoring data. We calculated standardised estimates of coral cover (z‐scores) to distinguish sites that deviated positively from regional means. We also used the coefficient of variation (CV) of coral cover to quantify how oases varied temporally, and to distinguish among types of oases. We estimated “coral calcification capacity” (CCC), a measure of the coral community's ability to produce calcium carbonate structures and tested for an association between this metric and z‐scores of coral cover.
  3. We illustrated our z‐score approach within a modelling framework by extracting z‐scores and CVs from simulated data based on four generalized trajectories of coral cover. We then applied the approach to time‐series data from long‐term reef monitoring programmes in four focal regions in the Pacific (the main Hawaiian Islands and Mo'orea, French Polynesia) and western Atlantic (the Florida Keys and St. John, US Virgin Islands). Among the 123 sites analysed, 38 had positive z‐scores for median coral cover and were categorised as oases.
  4. Synthesis and applications. Our framework provides ecosystem managers with a valuable tool for conservation by identifying “oases” within degraded areas. By evaluating trajectories of change in state (e.g., coral cover) among oases, our approach may help in identifying the mechanisms responsible for spatial variability in ecosystem condition. Increased mechanistic understanding can guide whether management of a particular location should emphasise protection, mitigation or restoration. Analysis of the empirical data suggest that the majority of our coral reef oases originated by either escaping or resisting disturbances, although some sites showed a high capacity for recovery, while others were candidates for restoration. Finally, our measure of reef condition (i.e., median z‐scores of coral cover) correlated positively with coral calcification capacity suggesting that our approach identified oases that are also exceptional for one critical component of ecological function.
","language":"English","publisher":"British Ecological Society","doi":"10.1111/1365-2664.13179","usgsCitation":"Guest, J.R., Edmunds, P.J., Gates, R.D., Kuffner, I.B., Andersson, A.J., Barnes, B.B., Chollett, I., Courtney, T.A., Elahi, R., Gross, K., Lenz, E.A., Mitarai, S., Mumby, P.J., Nelson, H.R., Parker, B.A., Putnam, H.M., Rogers, C.S., and Toth, L., 2018, A framework for identifying and characterising coral reef “oases” against a backdrop of degradation: Journal of Applied Ecology, v. 55, no. 6, p. 2865-2875, https://doi.org/10.1111/1365-2664.13179.","productDescription":"11 p.","startPage":"2865","endPage":"2875","ipdsId":"IP-088135","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true},{"id":29789,"text":"John Wesley Powell Center for Analysis and Synthesis","active":true,"usgs":true}],"links":[{"id":468651,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/1365-2664.13179","text":"Publisher Index Page"},{"id":366671,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"French Polynesia, United States, US Virgin Islands","state":"Florida, Hawaii","otherGeospatial":"Florida Keys","volume":"55","issue":"6","noUsgsAuthors":false,"publicationDate":"2018-06-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Guest, James R.","contributorId":204566,"corporation":false,"usgs":false,"family":"Guest","given":"James","email":"","middleInitial":"R.","affiliations":[{"id":36402,"text":"University of Hawaii","active":true,"usgs":false}],"preferred":false,"id":768732,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Edmunds, Peter J.","contributorId":204567,"corporation":false,"usgs":false,"family":"Edmunds","given":"Peter","email":"","middleInitial":"J.","affiliations":[{"id":36956,"text":"California State University","active":true,"usgs":false}],"preferred":false,"id":768733,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gates, Ruth D.","contributorId":167853,"corporation":false,"usgs":false,"family":"Gates","given":"Ruth","email":"","middleInitial":"D.","affiliations":[{"id":24839,"text":"Hawai'i Institute of Marine Biology, Hawaii","active":true,"usgs":false}],"preferred":false,"id":768734,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kuffner, Ilsa B. 0000-0001-8804-7847 ikuffner@usgs.gov","orcid":"https://orcid.org/0000-0001-8804-7847","contributorId":3105,"corporation":false,"usgs":true,"family":"Kuffner","given":"Ilsa","email":"ikuffner@usgs.gov","middleInitial":"B.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":768735,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Andersson, Andreas J","contributorId":141142,"corporation":false,"usgs":false,"family":"Andersson","given":"Andreas","email":"","middleInitial":"J","affiliations":[{"id":12888,"text":"Scripps Institution of Oceanography, Univ of California","active":true,"usgs":false}],"preferred":false,"id":768736,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Barnes, Brian B.","contributorId":218223,"corporation":false,"usgs":false,"family":"Barnes","given":"Brian","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":768737,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Chollett, Iliana","contributorId":218224,"corporation":false,"usgs":false,"family":"Chollett","given":"Iliana","email":"","affiliations":[],"preferred":false,"id":768738,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Courtney, Travis A.","contributorId":218225,"corporation":false,"usgs":false,"family":"Courtney","given":"Travis","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":768739,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Elahi, Robin","contributorId":218226,"corporation":false,"usgs":false,"family":"Elahi","given":"Robin","email":"","affiliations":[],"preferred":false,"id":768740,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Gross, Kevin","contributorId":71483,"corporation":false,"usgs":true,"family":"Gross","given":"Kevin","email":"","affiliations":[],"preferred":false,"id":768741,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Lenz, Elizabeth A.","contributorId":218227,"corporation":false,"usgs":false,"family":"Lenz","given":"Elizabeth","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":768742,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Mitarai, Satoshi","contributorId":218228,"corporation":false,"usgs":false,"family":"Mitarai","given":"Satoshi","email":"","affiliations":[],"preferred":false,"id":768743,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Mumby, Peter J.","contributorId":175366,"corporation":false,"usgs":false,"family":"Mumby","given":"Peter","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":768744,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Nelson, Hannah R.","contributorId":218229,"corporation":false,"usgs":false,"family":"Nelson","given":"Hannah","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":768745,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Parker, Britt A.","contributorId":218230,"corporation":false,"usgs":false,"family":"Parker","given":"Britt","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":768746,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Putnam, Hollie M.","contributorId":218231,"corporation":false,"usgs":false,"family":"Putnam","given":"Hollie","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":768747,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Rogers, Caroline S. 0000-0001-9056-6961 caroline_rogers@usgs.gov","orcid":"https://orcid.org/0000-0001-9056-6961","contributorId":3126,"corporation":false,"usgs":true,"family":"Rogers","given":"Caroline","email":"caroline_rogers@usgs.gov","middleInitial":"S.","affiliations":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":768748,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Toth, Lauren T. 0000-0002-2568-802X ltoth@usgs.gov","orcid":"https://orcid.org/0000-0002-2568-802X","contributorId":181748,"corporation":false,"usgs":true,"family":"Toth","given":"Lauren","email":"ltoth@usgs.gov","middleInitial":"T.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":768749,"contributorType":{"id":1,"text":"Authors"},"rank":18}]}} ,{"id":70197705,"text":"70197705 - 2018 - Adaptation with climate uncertainty: An examination of agricultural land use in the United States","interactions":[],"lastModifiedDate":"2018-06-19T11:41:57","indexId":"70197705","displayToPublicDate":"2018-06-18T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2599,"text":"Land Use Policy","active":true,"publicationSubtype":{"id":10}},"title":"Adaptation with climate uncertainty: An examination of agricultural land use in the United States","docAbstract":"

This paper examines adaptation responses to climate change through adjustment of agricultural land use. The climate drivers we examine are changes in long-term climate normals (e.g., 10-year moving averages) and changes in inter-annual climate variability. Using US county level data over 1982 to 2012 from Census of Agriculture, we find that impacts of long-term climate normals are as important as that of inter-annual climate variability. Projecting into the future, we find projected climate change will lead to an expansion in crop land share across the northern and interior western United States with decreases in the south. We also find that grazing land share increases in southern regions and Inland Pacific Northwest and declines in the northern areas. However, the extent to which the adaptation potential would be is dependent on the climate model, emission scenario and time horizon under consideration.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.landusepol.2018.05.057","usgsCitation":"Mu, J.E., McCarl, B.A., Sleeter, B.M., Abatzoglou, J.T., and Zhang, H., 2018, Adaptation with climate uncertainty: An examination of agricultural land use in the United States: Land Use Policy, v. 77, p. 392-401, https://doi.org/10.1016/j.landusepol.2018.05.057.","productDescription":"10 p.","startPage":"392","endPage":"401","ipdsId":"IP-076144","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":468652,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.landusepol.2018.05.057","text":"Publisher Index Page"},{"id":355131,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"77","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b46e559e4b060350a15d10b","contributors":{"authors":[{"text":"Mu, Jianhong E.","contributorId":75840,"corporation":false,"usgs":true,"family":"Mu","given":"Jianhong","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":738230,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McCarl, Bruce A.","contributorId":58173,"corporation":false,"usgs":true,"family":"McCarl","given":"Bruce","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":738228,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sleeter, Benjamin M. 0000-0003-2371-9571 bsleeter@usgs.gov","orcid":"https://orcid.org/0000-0003-2371-9571","contributorId":3479,"corporation":false,"usgs":true,"family":"Sleeter","given":"Benjamin","email":"bsleeter@usgs.gov","middleInitial":"M.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true},{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":738226,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Abatzoglou, John T.","contributorId":191729,"corporation":false,"usgs":false,"family":"Abatzoglou","given":"John","email":"","middleInitial":"T.","affiliations":[{"id":33345,"text":" University of Idaho","active":true,"usgs":false}],"preferred":false,"id":738227,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Zhang, Hongliang","contributorId":205709,"corporation":false,"usgs":false,"family":"Zhang","given":"Hongliang","email":"","affiliations":[{"id":37150,"text":"University of Neuchâtel","active":true,"usgs":false}],"preferred":false,"id":738229,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70221454,"text":"70221454 - 2018 - Estimating lag to peak between rainfall and peak streamflow with a mixed-effects model","interactions":[],"lastModifiedDate":"2021-06-16T14:14:34.261411","indexId":"70221454","displayToPublicDate":"2018-06-16T08:52:24","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7168,"text":"Journal of the American Water Resources Association (JAWRA)","active":true,"publicationSubtype":{"id":10}},"title":"Estimating lag to peak between rainfall and peak streamflow with a mixed-effects model","docAbstract":"We test the use of a mixed-effects model for estimating lag to peak for small basins in Maine (drainage areas from 0.8 to 78 km2). Lag to peak is defined as the time between the center of volume of the excess rainfall during a storm event and the resulting peak streamflow. A mixed-effects model allows for multiple observations at sites without violating model assumptions inherent in traditional ordinary least squares models, which assume each observation is independent. The mixed model includes basin drainage area and maximum 15-min rainfall depth for individual storms as explanatory features. Based on a remove-one-site cross-validation analysis, the prediction errors of this model ranged from 42% to +73%. The mixed model substantially outperformed three published models for lag to peak and one published model for centroid lag for estimating lag to peak for small basins in Maine. Lag to peak estimates are a key input to rainfallrunoff models used to design hydraulic infrastructure. The improved accuracy and consistency with model assumptions indicates that mixed models may provide increased data utilization that could enhance models and estimates of lag to peak in other regions.","language":"English","publisher":"American Water Resources Association","doi":"10.1111/1752-1688.12653","usgsCitation":"Lombard, P.J., and Holtschlag, D., 2018, Estimating lag to peak between rainfall and peak streamflow with a mixed-effects model: Journal of the American Water Resources Association (JAWRA), v. 54, no. 4, p. 949-961, https://doi.org/10.1111/1752-1688.12653.","productDescription":"13 p.","startPage":"949","endPage":"961","ipdsId":"IP-089128","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":437859,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7PK0F3D","text":"USGS data release","linkHelpText":"Precipitation and streamflow data for computing lag to peak at selected stations in Maine"},{"id":386535,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Maine","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -69.08203125,\n 47.517200697839414\n ],\n [\n -70.0048828125,\n 46.558860303117164\n ],\n [\n -70.9716796875,\n 45.27488643704891\n ],\n [\n -70.751953125,\n 43.100982876188546\n ],\n [\n -66.8408203125,\n 44.84029065139799\n ],\n [\n -67.3681640625,\n 45.82879925192134\n ],\n [\n -67.9833984375,\n 47.368594345213374\n ],\n [\n -69.08203125,\n 47.517200697839414\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"54","issue":"4","noUsgsAuthors":false,"publicationDate":"2018-04-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Lombard, Pamela J. 0000-0002-0983-1906","orcid":"https://orcid.org/0000-0002-0983-1906","contributorId":205225,"corporation":false,"usgs":true,"family":"Lombard","given":"Pamela","email":"","middleInitial":"J.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":817754,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Holtschlag, David 0000-0001-5185-4928","orcid":"https://orcid.org/0000-0001-5185-4928","contributorId":215360,"corporation":false,"usgs":true,"family":"Holtschlag","given":"David","affiliations":[{"id":382,"text":"Michigan Water Science Center","active":true,"usgs":true}],"preferred":true,"id":817755,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70221449,"text":"70221449 - 2018 - Suspended-sediment concentrations and loads in the lower Mississippi and Atchafalaya rivers decreased by half between 1980 and 2015","interactions":[],"lastModifiedDate":"2021-06-17T10:29:24.325243","indexId":"70221449","displayToPublicDate":"2018-06-16T07:48:30","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2342,"text":"Journal of Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"Suspended-sediment concentrations and loads in the lower Mississippi and Atchafalaya rivers decreased by half between 1980 and 2015","docAbstract":"

The Weighted Regressions on Time, Discharge, and Season (WRTDS) model was used to derive estimates of suspended-sediment concentration (SSC) and suspended-sediment load (SSL), their dependence on discharge, and their trends with confidence intervals, for one site each on the lowermost Mississippi and Atchafalaya Rivers. The WRTDS model reduces uncertainty in SSCs related to variable streamflow conditions. Flow-normalized SSCs in each river were similar, and decreased from about 260 mg/L to 130 mg/L from 1980 through 2015; combined annual SSL in the two rivers decreased from about 200 Megatons per year (MT/y) to about 100 MT/y. Declines in SSC and SSL were more gradual from 2005 through 2015 and show signs of stabilizing. Our estimates of SSL in 2015 differ markedly from several recently published estimates of current and projected future Mississippi River SSLs, which were generally around 200 MT/y. However, these values came mostly from a different site upstream on the Mississippi River. The relationship between SSC and streamflow differed in an important way between the two rivers. SSC increased as streamflow increased for the entire range of observed streamflow in the Atchafalaya River. In the Mississippi River, SSC followed the same pattern during low and moderate streamflow but decreased at the highest streamflow that tended to occur between January and July. Since much of the water flowing in the Atchafalaya originates from the Mississippi River, the difference suggests a within-basin source of suspended sediment for the Atchafalaya River that is absent in the lower Mississippi River. These findings have important implications for the restoration of deltaic wetlands in coastal Louisiana. Accurate estimates of the SSL available in each river are crucial for understanding how effective diversions of river water into adjacent estuaries will be in sustaining these wetlands. Our study demonstrates that there might be far less sediment available than previously reported. Further, the difference in the relationship between SSC and streamflow in the two rivers is highly relevant to the ongoing discussion of coastal restoration strategies because the delta building that is occurring at the mouth of the Atchafalaya River is frequently used as a model of what could be expected with controlled diversions in the lower Mississippi River delta. The differences in the SSC behavior with changes in streamflow between the two rivers needs to be considered when results from the Atchafalaya River system are projected to those of the Mississippi River.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.jhydrol.2018.05.068","usgsCitation":"Mize, S., Murphy, J.C., Diehl, T.H., and Demcheck, D.K., 2018, Suspended-sediment concentrations and loads in the lower Mississippi and Atchafalaya rivers decreased by half between 1980 and 2015: Journal of Hydrology, v. 564, p. 1-11, https://doi.org/10.1016/j.jhydrol.2018.05.068.","productDescription":"11 p.","startPage":"1","endPage":"11","ipdsId":"IP-079997","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":386526,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Louisiana","otherGeospatial":"Lower Mississippi River, Lower Atchafalaya River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -91.60400390625,\n 30.996445897426373\n ],\n [\n -91.5106201171875,\n 31.043521630684204\n ],\n [\n -91.527099609375,\n 31.194007509998823\n ],\n [\n -91.746826171875,\n 31.17050982470345\n ],\n [\n -91.82922363281249,\n 31.123496964067325\n ],\n [\n -91.86767578124999,\n 30.97289931126414\n ],\n [\n -91.8511962890625,\n 30.543338954230222\n ],\n [\n -91.71936035156249,\n 30.140376821599734\n ],\n [\n -91.6094970703125,\n 29.702368038541767\n ],\n [\n -91.4996337890625,\n 29.44916482692468\n ],\n [\n -91.131591796875,\n 29.35345166863502\n ],\n [\n -91.03271484375,\n 29.578234494739206\n ],\n [\n -91.021728515625,\n 29.954934549656144\n ],\n [\n -90.6976318359375,\n 29.835878945929952\n ],\n [\n -90.054931640625,\n 29.702368038541767\n ],\n [\n -89.7967529296875,\n 29.67850809103362\n ],\n [\n -89.84619140625,\n 29.950175057288813\n ],\n [\n -90.3350830078125,\n 30.059585699708215\n ],\n [\n -90.8734130859375,\n 30.183121842195515\n ],\n [\n -91.23596191406249,\n 30.694611546632277\n ],\n [\n -91.60400390625,\n 30.996445897426373\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"564","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Mize, Scott 0000-0001-6751-5568","orcid":"https://orcid.org/0000-0001-6751-5568","contributorId":218508,"corporation":false,"usgs":true,"family":"Mize","given":"Scott","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":817745,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Murphy, Jennifer C. 0000-0002-0881-0919 jmurphy@usgs.gov","orcid":"https://orcid.org/0000-0002-0881-0919","contributorId":167405,"corporation":false,"usgs":true,"family":"Murphy","given":"Jennifer","email":"jmurphy@usgs.gov","middleInitial":"C.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":false,"id":817746,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Diehl, Timothy H. 0000-0001-9691-2212 thdiehl@usgs.gov","orcid":"https://orcid.org/0000-0001-9691-2212","contributorId":546,"corporation":false,"usgs":true,"family":"Diehl","given":"Timothy","email":"thdiehl@usgs.gov","middleInitial":"H.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":581,"text":"Tennessee Water Science Center","active":true,"usgs":true}],"preferred":true,"id":817747,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Demcheck, Dennis K. 0000-0003-2981-078X","orcid":"https://orcid.org/0000-0003-2981-078X","contributorId":210305,"corporation":false,"usgs":true,"family":"Demcheck","given":"Dennis","email":"","middleInitial":"K.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":817748,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70197650,"text":"70197650 - 2018 - Integrating animal movement with habitat suitability for estimating dynamic migratory connectivity","interactions":[],"lastModifiedDate":"2021-08-11T18:52:48.609974","indexId":"70197650","displayToPublicDate":"2018-06-15T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2602,"text":"Landscape Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Integrating animal movement with habitat suitability for estimating dynamic migratory connectivity","docAbstract":"

Context

High-resolution animal movement data are becoming increasingly available, yet having a multitude of empirical trajectories alone does not allow us to easily predict animal movement. To answer ecological and evolutionary questions at a population level, quantitative estimates of a species’ potential to link patches or populations are of importance.

Objectives

We introduce an approach that combines movement-informed simulated trajectories with an environment-informed estimate of the trajectories’ plausibility to derive connectivity. Using the example of bar-headed geese we estimated migratory connectivity at a landscape level throughout the annual cycle in their native range.

Methods

We used tracking data of bar-headed geese to develop a multi-state movement model and to estimate temporally explicit habitat suitability within the species’ range. We simulated migratory movements between range fragments, and calculated a measure we called route viability. The results are compared to expectations derived from published literature.

Results

Simulated migrations matched empirical trajectories in key characteristics such as stopover duration. The viability of the simulated trajectories was similar to that of the empirical trajectories. We found that, overall, the migratory connectivity was higher within the breeding than in wintering areas, corroborating previous findings for this species.

Conclusions

We show how empirical tracking data and environmental information can be fused for meaningful predictions of animal movements throughout the year and even outside the spatial range of the available data. Beyond predicting migratory connectivity, our framework will prove useful for modelling ecological processes facilitated by animal movement, such as seed dispersal or disease ecology.

","language":"English","publisher":"Springer","doi":"10.1007/s10980-018-0637-9","usgsCitation":"van Toor, M.L., Kranstauber, B., Newman, S.H., Prosser, D.J., Takekawa, J., Technitis, G., Weibel, R., Wikelski, M., and Safi, K., 2018, Integrating animal movement with habitat suitability for estimating dynamic migratory connectivity: Landscape Ecology, v. 33, no. 6, p. 879-893, https://doi.org/10.1007/s10980-018-0637-9.","productDescription":"15 p.","startPage":"879","endPage":"893","ipdsId":"IP-084732","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":468656,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10980-018-0637-9","text":"Publisher Index Page"},{"id":355084,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"33","issue":"6","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2018-04-26","publicationStatus":"PW","scienceBaseUri":"5b46e566e4b060350a15d117","contributors":{"authors":[{"text":"van Toor, Marielle L.","contributorId":205670,"corporation":false,"usgs":false,"family":"van Toor","given":"Marielle","email":"","middleInitial":"L.","affiliations":[{"id":37137,"text":"Department of Migration and Immuno-Ecology, Max Planck Institute for Ornithology","active":true,"usgs":false}],"preferred":false,"id":738069,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kranstauber, Bart","contributorId":205671,"corporation":false,"usgs":false,"family":"Kranstauber","given":"Bart","email":"","affiliations":[{"id":37138,"text":"Department of Evolutionary Biology and Environmental Studies, University of Zurich","active":true,"usgs":false}],"preferred":false,"id":738070,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Newman, Scott H.","contributorId":199129,"corporation":false,"usgs":false,"family":"Newman","given":"Scott","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":738071,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Prosser, Diann J. 0000-0002-5251-1799 dprosser@usgs.gov","orcid":"https://orcid.org/0000-0002-5251-1799","contributorId":2389,"corporation":false,"usgs":true,"family":"Prosser","given":"Diann","email":"dprosser@usgs.gov","middleInitial":"J.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":738068,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Takekawa, John Y. 0000-0003-0217-5907","orcid":"https://orcid.org/0000-0003-0217-5907","contributorId":203805,"corporation":false,"usgs":false,"family":"Takekawa","given":"John Y.","affiliations":[{"id":36724,"text":"Audubon California, Richardson Bay Audubon Center and Sanctuary, Tiburon, CA","active":true,"usgs":false}],"preferred":false,"id":738072,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Technitis, Georgios","contributorId":205672,"corporation":false,"usgs":false,"family":"Technitis","given":"Georgios","email":"","affiliations":[{"id":37139,"text":"Department of Geography, University of Zurich","active":true,"usgs":false}],"preferred":false,"id":738073,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Weibel, Robert","contributorId":205673,"corporation":false,"usgs":false,"family":"Weibel","given":"Robert","email":"","affiliations":[{"id":37139,"text":"Department of Geography, University of Zurich","active":true,"usgs":false}],"preferred":false,"id":738074,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Wikelski, Martin","contributorId":205674,"corporation":false,"usgs":false,"family":"Wikelski","given":"Martin","email":"","affiliations":[{"id":37137,"text":"Department of Migration and Immuno-Ecology, Max Planck Institute for Ornithology","active":true,"usgs":false}],"preferred":false,"id":738075,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Safi, Kamran","contributorId":205675,"corporation":false,"usgs":false,"family":"Safi","given":"Kamran","email":"","affiliations":[{"id":37137,"text":"Department of Migration and Immuno-Ecology, Max Planck Institute for Ornithology","active":true,"usgs":false}],"preferred":false,"id":738076,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70198068,"text":"70198068 - 2018 - Reductive dechlorination rates of 4,4′-DDE (1-chloro-4-[2,2-dichloro-1-(4-chlorophenyl)ethenyl]benzene) in sediments of the Palos Verdes Shelf, CA","interactions":[],"lastModifiedDate":"2018-07-13T12:35:26","indexId":"70198068","displayToPublicDate":"2018-06-15T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2662,"text":"Marine Chemistry","active":true,"publicationSubtype":{"id":10}},"title":"Reductive dechlorination rates of 4,4′-DDE (1-chloro-4-[2,2-dichloro-1-(4-chlorophenyl)ethenyl]benzene) in sediments of the Palos Verdes Shelf, CA","docAbstract":"

Wastes from the world's largest manufacturer of DDT (1-chloro-4-[2,2,2-trichloro-1-(4-chlorophenyl)ethyl]benzene) were released into the Los Angeles County municipal sewer system from 1947 to 1971. Following primary treatment, the effluent was discharged through a submarine outfall system whereupon a portion of the DDT and associated degradation products were deposited in sediments of the Palos Verdes Shelf (PVS). Parent DDT is present only in trace amounts in the sediments today, the vast majority having been transformed to DDE (1-chloro-4-[2,2-dichloro-1-(4-chlorophenyl)ethenyl]benzene) shortly following deposition. Previously believed to be inert, DDE is slowly being converted to DDMU (1-chloro-4-[2-chloro-1-(4-chlorophenyl)ethenyl]benzene) and DDMU to DDNU (1-chloro-4-[1-(4-chlorophenyl)ethenyl]benzene) via microbially-mediated reductive dechlorination (RDC). Kinetic and compositional data suggest that this process began sometime in the mid- to late 1970s. Rates of DDE RDC in shelf sediments are spatially variable and have proven difficult to determine accurately. This limits our ability to understand the factors controlling RDC rates and to predict the course of natural recovery. In the present study, concentrations of ten DDT compounds and twelve PCB (polychlorinated biphenyl) congeners were determined in cores collected at two locations on the PVS (stations 3C, 6C, ~7km and ~2km downcurrent from the outfalls, respectively). DDE inventories, normalized to those of non-degrading PCB congeners having similar physico-chemical properties, were modeled to yield first-order RDC rates for the period 1981–2010. Average rates at stations 3C and 6C were 0.044±0.004 and 0.008±0.002yr−1, respectively, with depth-dependent RDC rates at station 3C (1992–2003) ranging from 0.0025 to 0.102yr−1. Comparison of RDC and total loss (i.e., RDC+physical loss) rates suggests that the average per cent loss of DDE due to RDC is ~90% at station 3C (1981–2010) and ~57% at station 6C (1992–2010). Trajectories of adjusted molar inventories of DDE, DDMU, and DDNU were forecast using a first-order multi-step reaction series (M-SRS) model. The results for DDE are consistent with the normalization procedure; RDC rates at stations 3C and 6C were 0.036±0.002yr−1 and 0.010±0.001yr−1, respectively. At station 6C, the DDE to DDMU transformation appears to be the rate limiting step in the reaction sequence, DDE k1→ DDMU k2→ DDNU k3→ unidentified compound(s), whereas at station 3C RDC rates for DDE and DDMU are roughly equivalent. At both locations the transformation rate of DDNU is 7–20 times that of the other steps. Estimated half-lives of DDE at stations 3C and 6C based on the M-SRS model results are ~19 and 72 years, respectively.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.marchem.2017.12.005","usgsCitation":"Eganhouse, R.P., Sherwood, C.R., Pontolillo, J., Edwards, B., and Dickhudt, P., 2018, Reductive dechlorination rates of 4,4′-DDE (1-chloro-4-[2,2-dichloro-1-(4-chlorophenyl)ethenyl]benzene) in sediments of the Palos Verdes Shelf, CA: Marine Chemistry, v. 203, p. 10-21, https://doi.org/10.1016/j.marchem.2017.12.005.","productDescription":"12 p.","startPage":"10","endPage":"21","ipdsId":"IP-088923","costCenters":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":460891,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.marchem.2017.12.005","text":"Publisher Index Page"},{"id":355656,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Palos Verde Shelf","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -118.35111111111111,33.66777777777777 ], [ -118.35111111111111,33.7175 ], [ -118.28444444444445,33.7175 ], [ -118.28444444444445,33.66777777777777 ], [ -118.35111111111111,33.66777777777777 ] ] ] } } ] }","volume":"203","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b6fc431e4b0f5d57878ea15","contributors":{"authors":[{"text":"Eganhouse, Robert P. 0000-0002-2075-5908 eganhous@usgs.gov","orcid":"https://orcid.org/0000-0002-2075-5908","contributorId":206243,"corporation":false,"usgs":true,"family":"Eganhouse","given":"Robert","email":"eganhous@usgs.gov","middleInitial":"P.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":739872,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sherwood, Christopher R. 0000-0001-6135-3553 csherwood@usgs.gov","orcid":"https://orcid.org/0000-0001-6135-3553","contributorId":2866,"corporation":false,"usgs":true,"family":"Sherwood","given":"Christopher","email":"csherwood@usgs.gov","middleInitial":"R.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":739873,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pontolillo, James 0000-0002-1075-1313 jpontoli@usgs.gov","orcid":"https://orcid.org/0000-0002-1075-1313","contributorId":206244,"corporation":false,"usgs":true,"family":"Pontolillo","given":"James","email":"jpontoli@usgs.gov","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":739874,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Edwards, Brian 0000-0002-4655-8208 bedwards@usgs.gov","orcid":"https://orcid.org/0000-0002-4655-8208","contributorId":206245,"corporation":false,"usgs":true,"family":"Edwards","given":"Brian","email":"bedwards@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":739875,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dickhudt, Patrick J. ","contributorId":169593,"corporation":false,"usgs":false,"family":"Dickhudt","given":"Patrick J. ","affiliations":[{"id":25562,"text":"(former) Woods Hole Coastal and Marine Science Center employee","active":true,"usgs":false}],"preferred":false,"id":739876,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70197656,"text":"70197656 - 2018 - Quantifying anthropogenic contributions to century-scale groundwater salinity changes, San Joaquin Valley, California, USA","interactions":[],"lastModifiedDate":"2018-06-18T11:04:24","indexId":"70197656","displayToPublicDate":"2018-06-15T00:00:00","publicationYear":"2018","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":"Quantifying anthropogenic contributions to century-scale groundwater salinity changes, San Joaquin Valley, California, USA","docAbstract":"Total dissolved solids (TDS) concentrations in groundwater tapped for beneficial uses (drinking water, irrigation, freshwater industrial) have increased on average by about 100 mg/L over the last 100 years in the San Joaquin Valley, California (SJV). During this period land use in the SJV changed from natural vegetation and dryland agriculture to dominantly irrigated agriculture with growing urban areas. Century-scale salinity trends were evaluated by comparing TDS concentrations and major ion compositions of groundwater from wells sampled in 1910 (Historic) to data from wells sampled in 1993-2015 (Modern). TDS concentrations in subregions of the SJV, the southern (SSJV), western (WSJV), northeastern (NESJV), and southeastern (SESJV) were calculated using a cell-declustering method. TDS concentrations increased in all regions, with the greatest increases found in the SSJV and SESJV. Evaluation of the Modern data from the NESJV and SESJV found higher TDS concentrations in recently recharged (post-1950) groundwater from shallow (< 50 m) wells surrounded predominantly by agricultural land uses, while premodern (pre-1950) groundwater from deeper wells, and recently recharged groundwater from wells surrounded by mainly urban, natural, and mixed land uses had lower TDS concentrations, approaching the TDS concentrations in the Historic groundwater. For the NESJV and SESJV, inverse geochemical modeling with PHREEQC indicated that weathering of primary silicate minerals accounted for the majority of the increase in TDS concentrations, contributing more than nitrate from fertilizers and sulfate from soil amendments combined. Bicarbonate showed the greatest increase among major ions, resulting from enhanced silicate weathering due to recharge of irrigation water enriched in CO2 during the growing season. The results of this study demonstrate that large anthropogenic changes to the hydrologic regime, like massive development of irrigated agriculture in semi-arid areas like the SJV, can cause large changes in groundwater quality on a regional scale.","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2018.05.333","usgsCitation":"Hansen, J.A., Jurgens, B., and Fram, M.S., 2018, Quantifying anthropogenic contributions to century-scale groundwater salinity changes, San Joaquin Valley, California, USA: Science of the Total Environment, v. 642, p. 125-136, https://doi.org/10.1016/j.scitotenv.2018.05.333.","productDescription":"12 p.","startPage":"125","endPage":"136","ipdsId":"IP-083514","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":460889,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2018.05.333","text":"Publisher Index 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0000-0002-2185-1686","orcid":"https://orcid.org/0000-0002-2185-1686","contributorId":205441,"corporation":false,"usgs":true,"family":"Hansen","given":"Jeffrey","email":"","middleInitial":"A.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":738091,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jurgens, Bryant C. 0000-0002-1572-113X","orcid":"https://orcid.org/0000-0002-1572-113X","contributorId":203409,"corporation":false,"usgs":true,"family":"Jurgens","given":"Bryant","middleInitial":"C.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":738092,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fram, Miranda S. 0000-0002-6337-059X mfram@usgs.gov","orcid":"https://orcid.org/0000-0002-6337-059X","contributorId":1156,"corporation":false,"usgs":true,"family":"Fram","given":"Miranda","email":"mfram@usgs.gov","middleInitial":"S.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":738093,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70200470,"text":"70200470 - 2018 - Harnessing big data to rethink land heterogeneity in Earth system models","interactions":[],"lastModifiedDate":"2018-10-18T14:26:46","indexId":"70200470","displayToPublicDate":"2018-06-14T14:26:38","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1928,"text":"Hydrology and Earth System Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Harnessing big data to rethink land heterogeneity in Earth system models","docAbstract":"

The continual growth in the availability, detail, and wealth of environmental data provides an invaluable asset to improve the characterization of land heterogeneity in Earth system models – a persistent challenge in macroscale models. However, due to the nature of these data (volume and complexity) and computational constraints, these data are underused for global applications. As a proof of concept, this study explores how to effectively and efficiently harness these data in Earth system models over a 1/4° ( ∼ 25km) grid cell in the western foothills of the Sierra Nevada in central California. First, a novel hierarchical multivariate clustering approach (HMC) is introduced that summarizes the high-dimensional environmental data space into hydrologically interconnected representative clusters (i.e., tiles). These tiles and their associated properties are then used to parameterize the sub-grid heterogeneity of the Geophysical Fluid Dynamics Laboratory (GFDL) LM4-HB land model. To assess how this clustering approach impacts the simulated water, energy, and carbon cycles, model experiments are run using a series of different tile configurations assembled using HMC. The results over the test domain show that (1) the observed similarity over the landscape makes it possible to converge on the macroscale response of the fully distributed model with around 300 sub-grid land model tiles; (2) assembling the sub-grid tile configuration from available environmental data can have a large impact on the macroscale states and fluxes of the water, energy, and carbon cycles; for example, the defined subsurface connections between the tiles lead to a dampening of macroscale extremes; (3) connecting the fine-scale grid to the model tiles via HMC enables circumvention of the classic scale discrepancies between the macroscale and field-scale estimates; this has potentially significant implications for the evaluation and application of Earth system models.

","language":"English","publisher":"European Geosciences Union","doi":"10.5194/hess-22-3311-2018","usgsCitation":"Chaney, N.W., Van Huijgevoort, M.H., Shevliakova, E., Malyshev, S., Milly, P.C., Gauthier, P., and Sulman, B.N., 2018, Harnessing big data to rethink land heterogeneity in Earth system models: Hydrology and Earth System Sciences, v. 22, p. 3311-3330, https://doi.org/10.5194/hess-22-3311-2018.","productDescription":"20 p.","startPage":"3311","endPage":"3330","ipdsId":"IP-090830","costCenters":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"links":[{"id":468658,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/hess-22-3311-2018","text":"Publisher Index Page"},{"id":358546,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"22","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2018-06-14","publicationStatus":"PW","scienceBaseUri":"5c10a99ae4b034bf6a7e535d","contributors":{"authors":[{"text":"Chaney, Nathaniel W.","contributorId":169242,"corporation":false,"usgs":false,"family":"Chaney","given":"Nathaniel","email":"","middleInitial":"W.","affiliations":[{"id":25453,"text":"Department of Civil and Environmental Engineering, Princeton University, Princeton, NJ, USA","active":true,"usgs":false}],"preferred":false,"id":749025,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Van Huijgevoort, Marjolein H. J.","contributorId":209888,"corporation":false,"usgs":false,"family":"Van Huijgevoort","given":"Marjolein","email":"","middleInitial":"H. J.","affiliations":[{"id":7108,"text":"Princeton Univ.","active":true,"usgs":false}],"preferred":false,"id":749026,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shevliakova, Elena","contributorId":201589,"corporation":false,"usgs":false,"family":"Shevliakova","given":"Elena","email":"","affiliations":[{"id":36211,"text":"GFDL/NOAA","active":true,"usgs":false}],"preferred":false,"id":749027,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Malyshev, Sergey","contributorId":201588,"corporation":false,"usgs":false,"family":"Malyshev","given":"Sergey","affiliations":[{"id":36211,"text":"GFDL/NOAA","active":true,"usgs":false}],"preferred":false,"id":749028,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Milly, Paul C. D. 0000-0003-4389-3139 cmilly@usgs.gov","orcid":"https://orcid.org/0000-0003-4389-3139","contributorId":176836,"corporation":false,"usgs":true,"family":"Milly","given":"Paul","email":"cmilly@usgs.gov","middleInitial":"C. D.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":false,"id":749024,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Gauthier, Paul P. G.","contributorId":209889,"corporation":false,"usgs":false,"family":"Gauthier","given":"Paul P. G.","affiliations":[{"id":7108,"text":"Princeton Univ.","active":true,"usgs":false}],"preferred":false,"id":749029,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Sulman, Benjamin N. 0000-0002-3265-6691","orcid":"https://orcid.org/0000-0002-3265-6691","contributorId":209890,"corporation":false,"usgs":false,"family":"Sulman","given":"Benjamin","email":"","middleInitial":"N.","affiliations":[{"id":7108,"text":"Princeton Univ.","active":true,"usgs":false}],"preferred":false,"id":749030,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70217156,"text":"70217156 - 2018 - Exposure to human-associated chemical markers of fecal contamination and self-reported illness among swimmers at recreational beaches","interactions":[],"lastModifiedDate":"2021-01-07T13:39:52.424305","indexId":"70217156","displayToPublicDate":"2018-06-14T07:34:54","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1565,"text":"Environmental Science & Technology","onlineIssn":"1520-5851","printIssn":"0013-936X","active":true,"publicationSubtype":{"id":10}},"title":"Exposure to human-associated chemical markers of fecal contamination and self-reported illness among swimmers at recreational beaches","docAbstract":"

Anthropogenic chemicals have been proposed as potential markers of human fecal contamination in recreational water. However, to date, there are no published studies describing their relationships with illness risks. Using a cohort of swimmers at seven U.S. beaches, we examined potential associations between the presence of chemical markers of human fecal pollution and self-reported gastrointestinal (GI) illness, diarrhea, and respiratory illness. Swimmers were surveyed about their beach activities, water exposure, and baseline symptoms on the day of their beach visit, and about any illness experienced 10–12 days later. Risk differences were estimated using model-based standardization and adjusted for the swimmer’s age, beach site, sand contact, rainfall, and water temperature. Sixty-two chemical markers were analyzed from daily water samples at freshwater and marine beaches. Of those, 20 were found consistently. With the possible exception of bisphenol A and cholesterol, no chemicals were consistently associated with increased risks of illness. These two chemicals were suggestively associated with 2% and 1% increased risks of GI illness and diarrhea in both freshwater and marine beaches. Additional research using the more sensitive analytic methods currently available for a wider suite of analytes is needed to support the use of chemical biomarkers to quantify illness risk and identify fecal pollution sources.

","language":"English","publisher":"American Chemical Society","doi":"10.1021/acs.est.8b00639","usgsCitation":"Napier, M.D., Poole, C., Stewart, J.R., Weber, D.J., Glassmeyer, S.T., Kolpin, D.W., Furlong, E., Dufour, A.P., and Wade, T.J., 2018, Exposure to human-associated chemical markers of fecal contamination and self-reported illness among swimmers at recreational beaches: Environmental Science & Technology, v. 52, no. 13, p. 7513-7523, https://doi.org/10.1021/acs.est.8b00639.","productDescription":"11 p.","startPage":"7513","endPage":"7523","ipdsId":"IP-097335","costCenters":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":468659,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://europepmc.org/articles/pmc6192706","text":"External Repository"},{"id":381997,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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Environmental Sciences and Engineering, University of North Carolina-Chapel Hill, Chapel Hill, NC","active":true,"usgs":false}],"preferred":false,"id":807747,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Weber, David J","contributorId":247492,"corporation":false,"usgs":false,"family":"Weber","given":"David","email":"","middleInitial":"J","affiliations":[{"id":49556,"text":"Division of Infectious Diseases, School of Medicine, University of North Carolina Health Care, Chapel Hill, NC","active":true,"usgs":false}],"preferred":false,"id":807748,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Glassmeyer, Susan T.","contributorId":184135,"corporation":false,"usgs":false,"family":"Glassmeyer","given":"Susan","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":807749,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"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":807750,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Furlong, Edward 0000-0002-7305-4603","orcid":"https://orcid.org/0000-0002-7305-4603","contributorId":213730,"corporation":false,"usgs":true,"family":"Furlong","given":"Edward","affiliations":[{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","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}],"preferred":true,"id":807751,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Dufour, Alfred P","contributorId":247494,"corporation":false,"usgs":false,"family":"Dufour","given":"Alfred","email":"","middleInitial":"P","affiliations":[{"id":49559,"text":"U.S. Environmental Protection Agency, Office of Research and Development, National Exposure Research Laboratory, Cincinnati, OH","active":true,"usgs":false}],"preferred":false,"id":807752,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Wade, Timothy J. 0000-0002-7843-0997","orcid":"https://orcid.org/0000-0002-7843-0997","contributorId":247495,"corporation":false,"usgs":false,"family":"Wade","given":"Timothy","email":"","middleInitial":"J.","affiliations":[{"id":49553,"text":"U.S. Environmental Protection Agency, Office of Research and Development, National Health and Environmental Effects Research Laboratory, Research Triangle Park, NC","active":true,"usgs":false}],"preferred":false,"id":807753,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70197626,"text":"70197626 - 2018 - Seagrass impact on sediment exchange between tidal flats and salt Marsh, and the sediment budget of shallow bays","interactions":[],"lastModifiedDate":"2018-07-03T11:04:21","indexId":"70197626","displayToPublicDate":"2018-06-14T00:00:00","publicationYear":"2018","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":"Seagrass impact on sediment exchange between tidal flats and salt Marsh, and the sediment budget of shallow bays","docAbstract":"Seagrasses are marine flowering plants that strongly impact their physical and biological\nsurroundings and are therefore frequently referred to as ecological engineers. The effect of seagrasses on coastal bay resilience and sediment transport dynamics is understudied. Here we use six historical maps of seagrass distribution in Barnegat Bay, USA, to investigate the role of these vegetated surfaces on the sediment storage capacity of shallow bays. Analyses are carried out by means of the Coupled-Ocean-Atmosphere-Wave-Sediment Transport (COAWST) numerical modeling framework. Results show that a decline in the extent of seagrass meadows reduces the sediment mass potentially stored within bay systems. The presence of seagrass reduces shear stress values across the entire bay, including unvegetated areas, and promotes sediment deposition on tidal flats. On the other hand, the presence of seagrasses decreases suspended sediment concentrations, which in turn reduces the delivery of sediment to marsh platforms. Results highlight the relevance of seagrasses for the long-term survival of coastal ecosystems, and the complex dynamics regulating the interaction between subtidal and intertidal landscapes.","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2018GL078056","usgsCitation":"Donatelli, C., Ganju, N.K., Fagherazzi, S., and Leonardi, N., 2018, Seagrass impact on sediment exchange between tidal flats and salt Marsh, and the sediment budget of shallow bays: Geophysical Research Letters, v. 45, no. 10, p. 4933-4943, https://doi.org/10.1029/2018GL078056.","productDescription":"11 p.","startPage":"4933","endPage":"4943","ipdsId":"IP-093431","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":460893,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2018gl078056","text":"Publisher Index Page"},{"id":355044,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Jersey","otherGeospatial":"Barnegat Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -74.25178527832031,\n 39.67759833072648\n ],\n [\n -74.07840728759766,\n 39.67759833072648\n ],\n [\n -74.07840728759766,\n 39.87048617098581\n ],\n [\n -74.25178527832031,\n 39.87048617098581\n ],\n [\n -74.25178527832031,\n 39.67759833072648\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"45","issue":"10","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationDate":"2018-05-20","publicationStatus":"PW","scienceBaseUri":"5b46e567e4b060350a15d11f","contributors":{"authors":[{"text":"Donatelli, Carmine","contributorId":202870,"corporation":false,"usgs":false,"family":"Donatelli","given":"Carmine","affiliations":[{"id":36541,"text":"University of Liverpool, Department of Geography and Planning, 74 Bedford St S.","active":true,"usgs":false}],"preferred":false,"id":737973,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ganju, Neil Kamal 0000-0002-1096-0465 nganju@usgs.gov","orcid":"https://orcid.org/0000-0002-1096-0465","contributorId":192273,"corporation":false,"usgs":true,"family":"Ganju","given":"Neil","email":"nganju@usgs.gov","middleInitial":"Kamal","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":737972,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fagherazzi, Sergio","contributorId":89282,"corporation":false,"usgs":true,"family":"Fagherazzi","given":"Sergio","affiliations":[],"preferred":false,"id":737974,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Leonardi, Nicoletta","contributorId":202868,"corporation":false,"usgs":false,"family":"Leonardi","given":"Nicoletta","email":"","affiliations":[{"id":36541,"text":"University of Liverpool, Department of Geography and Planning, 74 Bedford St S.","active":true,"usgs":false}],"preferred":false,"id":737975,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70197641,"text":"70197641 - 2018 - Dryland photoautotrophic soil surface communities endangered by global change","interactions":[],"lastModifiedDate":"2018-06-15T09:29:38","indexId":"70197641","displayToPublicDate":"2018-06-14T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2845,"text":"Nature Geoscience","active":true,"publicationSubtype":{"id":10}},"title":"Dryland photoautotrophic soil surface communities endangered by global change","docAbstract":"Photoautotrophic surface communities forming biological soil crusts (biocrusts) are crucial for soil stability as well as water, nutrient and trace gas cycling at regional and global scales. Quantitative information on their global coverage and the environmental factors driving their distribution patterns, however, are not readily available. We use observations and environmental modelling to estimate the global distribution of biocrusts and their response to global change using future projected scenarios. We find that biocrusts currently covering approximately 12% of Earth’s terrestrial surface will decrease by about 25–40% within 65 years due to anthropogenically caused climate change and land-use intensification, responding far more drastically than vascular plants. Our results illustrate that current biocrust occurrence is mainly driven by a combination of precipitation, temperature and land management, and future changes are expected to be affected by land-use and climate change in similar proportion. The predicted loss of biocrusts may substantially reduce the microbial contribution to nitrogen cycling and enhance the emissions of soil dust, which affects the functioning of ecosystems as well as human health and should be considered in the modelling, mitigation and management of global change.","language":"English","publisher":"Springer Nature","doi":"10.1038/s41561-018-0072-1","usgsCitation":"Rodriguez-Caballero, E., Belnap, J., Budel, B., Crutzen, P.J., Andreae, M.O., Poschl, U., and Weber, B., 2018, Dryland photoautotrophic soil surface communities endangered by global change: Nature Geoscience, v. 11, p. 185-189, https://doi.org/10.1038/s41561-018-0072-1.","productDescription":"5 p.","startPage":"185","endPage":"189","ipdsId":"IP-078018","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":468661,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://resolver.obvsg.at/urn:nbn:at:at-ubg:3-14404","text":"External Repository"},{"id":355055,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"11","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-02-26","publicationStatus":"PW","scienceBaseUri":"5b46e567e4b060350a15d11d","contributors":{"authors":[{"text":"Rodriguez-Caballero, Emilio 0000-0002-5934-3214","orcid":"https://orcid.org/0000-0002-5934-3214","contributorId":205639,"corporation":false,"usgs":false,"family":"Rodriguez-Caballero","given":"Emilio","email":"","affiliations":[{"id":37132,"text":"Multiphase Chemistry Department, Max Planck Institute for Chemistry, Hahn-Meitner-Weg 1, 55128 Mainz, Germany","active":true,"usgs":false}],"preferred":false,"id":738018,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Belnap, Jayne 0000-0001-7471-2279 jayne_belnap@usgs.gov","orcid":"https://orcid.org/0000-0001-7471-2279","contributorId":1332,"corporation":false,"usgs":true,"family":"Belnap","given":"Jayne","email":"jayne_belnap@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":738017,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Budel, Burkhard","contributorId":172209,"corporation":false,"usgs":false,"family":"Budel","given":"Burkhard","email":"","affiliations":[{"id":26999,"text":"Plant Ecology and Systematics, Institute of Biology, University of Kaiserslautern, Kaiserlautern, Germany","active":true,"usgs":false}],"preferred":false,"id":738019,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Crutzen, Paul J.","contributorId":205640,"corporation":false,"usgs":false,"family":"Crutzen","given":"Paul","email":"","middleInitial":"J.","affiliations":[{"id":37133,"text":"Air Chemistry Department, Max Planck Institute for Chemistry, Hahn-Meitner-Weg 1, 55128 Mainz, Germany","active":true,"usgs":false}],"preferred":false,"id":738020,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Andreae, Meinrat O.","contributorId":205641,"corporation":false,"usgs":false,"family":"Andreae","given":"Meinrat","email":"","middleInitial":"O.","affiliations":[{"id":37134,"text":"Biogeochemistry Department, Max Planck Institute for Chemistry, Hahn-Meitner-Weg 1, 55128 Mainz, Germany","active":true,"usgs":false}],"preferred":false,"id":738021,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Poschl, Ulrich","contributorId":205642,"corporation":false,"usgs":false,"family":"Poschl","given":"Ulrich","email":"","affiliations":[{"id":37132,"text":"Multiphase Chemistry Department, Max Planck Institute for Chemistry, Hahn-Meitner-Weg 1, 55128 Mainz, Germany","active":true,"usgs":false}],"preferred":false,"id":738022,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Weber, Bettina","contributorId":196800,"corporation":false,"usgs":false,"family":"Weber","given":"Bettina","email":"","affiliations":[],"preferred":false,"id":738023,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70197646,"text":"70197646 - 2018 - Rapid crop cover mapping for the conterminous United States","interactions":[],"lastModifiedDate":"2018-06-14T15:57:50","indexId":"70197646","displayToPublicDate":"2018-06-14T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3358,"text":"Scientific Reports","active":true,"publicationSubtype":{"id":10}},"title":"Rapid crop cover mapping for the conterminous United States","docAbstract":"

Timely crop cover maps with sufficient resolution are important components to various environmental planning and research applications. Through the modification and use of a previously developed crop classification model (CCM), which was originally developed to generate historical annual crop cover maps, we hypothesized that such crop cover maps could be generated rapidly during the growing season. Through a process of incrementally removing weekly and monthly independent variables from the CCM and implementing a ‘two model mapping’ approach, we found it viable to generate conterminous United States-wide rapid crop cover maps at a resolution of 250 m for the current year by the month of September. In this approach, we divided the CCM model into one ‘crop type model’ to handle the classification of nine specific crops and a second, binary model to classify the presence or absence of ‘other’ crops. Under the two model mapping approach, the training errors were 0.8% and 1.5% for the crop type and binary model, respectively, while test errors were 5.5% and 6.4%, respectively. With spatial mapping accuracies for annual maps reaching upwards of 70%, this approach demonstrated a strong potential for generating rapid crop cover maps by the 1st of September.

","language":"English","publisher":"Nature","doi":"10.1038/s41598-018-26284-w","usgsCitation":"Dahal, D., Wylie, B.K., and Howard, D., 2018, Rapid crop cover mapping for the conterminous United States: Scientific Reports, v. 8, Article number: 8631; 12 p., https://doi.org/10.1038/s41598-018-26284-w.","productDescription":"Article number: 8631; 12 p.","ipdsId":"IP-089563","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":468660,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41598-018-26284-w","text":"Publisher Index Page"},{"id":355060,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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\"}}]}\n\n\n","volume":"8","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2018-06-05","publicationStatus":"PW","scienceBaseUri":"5b46e567e4b060350a15d11b","contributors":{"authors":[{"text":"Dahal, Devendra 0000-0001-9594-1249 ddahal@usgs.gov","orcid":"https://orcid.org/0000-0001-9594-1249","contributorId":5622,"corporation":false,"usgs":true,"family":"Dahal","given":"Devendra","email":"ddahal@usgs.gov","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":738033,"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":750,"corporation":false,"usgs":true,"family":"Wylie","given":"Bruce","email":"wylie@usgs.gov","middleInitial":"K.","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":738034,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Howard, Daniel 0000-0002-7563-7538","orcid":"https://orcid.org/0000-0002-7563-7538","contributorId":56946,"corporation":false,"usgs":true,"family":"Howard","given":"Daniel","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":false,"id":738035,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70201714,"text":"70201714 - 2018 - Preface to the Focus Section on the Collaboratory for the Study of Earthquake Predictability (CSEP): New results and future directions","interactions":[],"lastModifiedDate":"2019-01-29T10:30:56","indexId":"70201714","displayToPublicDate":"2018-06-13T13:01:51","publicationYear":"2018","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":"Preface to the Focus Section on the Collaboratory for the Study of Earthquake Predictability (CSEP): New results and future directions","docAbstract":"

The Collaboratory for the Study of Earthquake Predictability (CSEP; Jordan, 2006) carries out fully prospective tests of earthquake forecasts, using fixed and standardized statistical tests and authoritative data sets, to assess the predictive skill of forecast models and to make objective comparisons between models. CSEP conducts prospective experiments at four testing centers around the world, at which more than 400 models and model versions are currently under evaluation. These models include a range of methods and scales from long‐term global earthquake forecasts to short‐term regional forecasts used for Operational Earthquake Forecasting (OEF). CSEP has also conducted retrospective tests and developed new testing methods in its quest to answer fundamental scientific questions, improve seismic hazard assessments, and develop new forecast methods for OEF.

","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0220180161","usgsCitation":"Michael, A.J., and Werner, M.J., 2018, Preface to the Focus Section on the Collaboratory for the Study of Earthquake Predictability (CSEP): New results and future directions: Seismological Research Letters, v. 89, no. 4, p. 1226-1228, https://doi.org/10.1785/0220180161.","productDescription":"3 p.","startPage":"1226","endPage":"1228","ipdsId":"IP-098396","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":468662,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://research-information.bris.ac.uk/en/publications/5ef252d7-aa19-4039-bc43-051e520e7e29","text":"External Repository"},{"id":360739,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"89","issue":"4","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-06-13","publicationStatus":"PW","scienceBaseUri":"5c5022c5e4b0708288f7e826","contributors":{"authors":[{"text":"Michael, Andrew J. 0000-0002-2403-5019 michael@usgs.gov","orcid":"https://orcid.org/0000-0002-2403-5019","contributorId":1280,"corporation":false,"usgs":true,"family":"Michael","given":"Andrew","email":"michael@usgs.gov","middleInitial":"J.","affiliations":[{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":754957,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Werner, Maximillian J.","contributorId":211807,"corporation":false,"usgs":false,"family":"Werner","given":"Maximillian","email":"","middleInitial":"J.","affiliations":[{"id":38325,"text":"University of Bristol, UK","active":true,"usgs":false}],"preferred":false,"id":754958,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70216310,"text":"70216310 - 2018 - Divergent effects of land-use, propagule pressure, and climate on woody riparian invasion","interactions":[],"lastModifiedDate":"2020-11-11T15:01:54.712614","indexId":"70216310","displayToPublicDate":"2018-06-13T08:56:52","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1018,"text":"Biological Invasions","active":true,"publicationSubtype":{"id":10}},"title":"Divergent effects of land-use, propagule pressure, and climate on woody riparian invasion","docAbstract":"

Landscape-scale analyses of biological invasion are needed to understand the relative importance of environmental drivers that vary at larger scales, such as climate, propagule pressure, resource availability, and human disturbance. One poorly understood landscape-scale question is, how does human land-use influence riparian plant invasion? To evaluate the relative importance of land-use, climate, propagule pressure, and water availability in riparian invasion, we examined tamarisk (Tamarix ramosissima, T. chinensis, hybrids), Russian olive (Elaeagnus angustifolia), and Siberian elm (Ulmus pumila) occurrence, abundance, and dominance in 238 riparian sites in developed, cultivated, and undeveloped areas of four western USA river basins (281,946 km2). Temperature and propagule pressure from individuals planted nearby largely drove invasive species occurrence, whereas factors likely to affect resource availability (e.g., land-use, precipitation, streamflow intermittency) were more important to abundance and dominance, supporting the argument that species distribution models based on occurrence alone may fail to identify conditions where invasive species have the greatest impact. The role of land-use varied among taxa: urban and suburban land-use increased Siberian elm occurrence, abundance, and dominance, and urban land-use increased Russian olive occurrence, whereas suburban land-use reduced tamarisk dominance. Surprisingly, Siberian elm, which has received scant prior scientific and management attention, occurred as or more frequently than tamarisk and Russian olive (except in undeveloped areas of the Colorado River headwaters) and had higher density and dominance than tamarisk and Russian olive in developed areas. More research is needed to understand the impacts of this largely unrecognized invader on riparian ecosystem services, particularly in urban and suburban areas.


","language":"English","publisher":"Springer","doi":"10.1007/s10530-018-1773-5","usgsCitation":"Perry, L.G., Reynolds, L.V., and Shafroth, P., 2018, Divergent effects of land-use, propagule pressure, and climate on woody riparian invasion: Biological Invasions, v. 20, p. 3271-3295, https://doi.org/10.1007/s10530-018-1773-5.","productDescription":"25 p.","startPage":"3271","endPage":"3295","ipdsId":"IP-097094","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":437863,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7TX3DPF","text":"USGS data release","linkHelpText":"Woody riparian invasive plant presence, stem density, and rank dominance and environmental conditions in 2012 at 238 bridge crossings in the Colorado Headwaters, upper/middle Rio Grande, upper Arkansas, and South Platte River Basins, USA"},{"id":380410,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado, New Mexico","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -104.7216796875,\n 40.88029480552824\n ],\n [\n -104.5458984375,\n 40.81380923056958\n ],\n [\n -109.1162109375,\n 40.74725696280421\n ],\n [\n -109.2919921875,\n 38.58252615935333\n ],\n [\n -109.072265625,\n 36.66841891894786\n ],\n [\n -107.9296875,\n 32.99023555965106\n ],\n [\n -104.853515625,\n 33.76088200086917\n ],\n [\n -103.35937499999999,\n 35.92464453144099\n ],\n [\n -101.90917968749999,\n 38.51378825951165\n ],\n [\n -102.26074218749999,\n 39.50404070558415\n ],\n [\n -104.7216796875,\n 40.88029480552824\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"20","noUsgsAuthors":false,"publicationDate":"2018-06-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Perry, Laura G","contributorId":177873,"corporation":false,"usgs":false,"family":"Perry","given":"Laura","email":"","middleInitial":"G","affiliations":[],"preferred":false,"id":804626,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Reynolds, Lindsay V.","contributorId":141182,"corporation":false,"usgs":false,"family":"Reynolds","given":"Lindsay","email":"","middleInitial":"V.","affiliations":[{"id":6737,"text":"Colorado State University, Department of Ecosystem Science and Sustainability, and Natural Resource Ecology Laboratory","active":true,"usgs":false}],"preferred":false,"id":804627,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shafroth, Patrick B. 0000-0002-6064-871X","orcid":"https://orcid.org/0000-0002-6064-871X","contributorId":225182,"corporation":false,"usgs":true,"family":"Shafroth","given":"Patrick B.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":804628,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70197561,"text":"ofr20181093 - 2018 - Reexamination of the subsurface fault structure in the vicinity of the 1989 moment-magnitude-6.9 Loma Prieta earthquake, central California, using steep-reflection, earthquake, and magnetic data","interactions":[],"lastModifiedDate":"2018-06-14T09:58:01","indexId":"ofr20181093","displayToPublicDate":"2018-06-13T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2018-1093","title":"Reexamination of the subsurface fault structure in the vicinity of the 1989 moment-magnitude-6.9 Loma Prieta earthquake, central California, using steep-reflection, earthquake, and magnetic data","docAbstract":"

We reexamine the geometry of the causative fault structure of the 1989 moment-magnitude-6.9 Loma Prieta earthquake in central California, using seismic-reflection, earthquake-hypocenter, and magnetic data. Our study is prompted by recent interpretations of a two-part dip of the San Andreas Fault (SAF) accompanied by a flower-like structure in the Coachella Valley, in southern California. Initially, the prevailing interpretation of fault geometry in the vicinity of the Loma Prieta earthquake was that the mainshock did not rupture the SAF, but rather a secondary fault within the SAF system, because network locations of aftershocks defined neither a vertical plane nor a fault plane that projected to the surface trace of the SAF. Subsequent waveform cross-correlation and double-difference relocations of Loma Prieta aftershocks appear to have clarified the fault geometry somewhat, with steeply dipping faults in the upper crust possibly connecting to the more moderately southwest-dipping mainshock rupture in the middle crust. Examination of steep-reflection data, extracted from a 1991 seismic-refraction profile through the Loma Prieta area, reveals three robust fault-like features that agree approximately in geometry with the clusters of upper-crustal relocated aftershocks. The subsurface geometry of the San Andreas, Sargent, and Berrocal Faults can be mapped using these features and the aftershock clusters. The San Andreas and Sargent Faults appear to dip northeastward in the uppermost crust and change dip continuously toward the southwest with depth. Previous models of gravity and magnetic data on profiles through the aftershock region also define a steeply dipping SAF, with an initial northeastward dip in the uppermost crust that changes with depth. At a depth 6 to 9 km, upper-crustal faults appear to project into the moderately southwest-dipping, planar mainshock rupture. The change to a planar dipping rupture at 6–9 km is similar to fault geometry seen in the Coachella Valley.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181093","usgsCitation":"Zhang, E., Fuis, G.S., Catchings, R.D., Scheirer, D.S., Goldman, M., and Bauer, K., 2018, Reexamination of the subsurface fault structure in the vicinity of the 1989 moment-magnitude-6.9 Loma Prieta earthquake, central California, using steep-reflection, earthquake, and magnetic data: U.S. Geological Survey Open-File Report 2018–1093, 35 p., https://doi.org/10.3133/ofr20181093.","productDescription":"v; 35 p.","onlineOnly":"Y","ipdsId":"IP-097280","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":355009,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1093/coverthb.jpg"},{"id":355010,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1093/ofr20181093.pdf","text":"Report","size":"8.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1093"}],"country":"United States","state":"California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.92214965820311,\n 36.97128966642495\n ],\n [\n -121.75804138183594,\n 36.97128966642495\n ],\n [\n -121.75804138183594,\n 37.2\n ],\n [\n -121.92214965820311,\n 37.2\n ],\n [\n -121.92214965820311,\n 36.97128966642495\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"

Contact Information, Menlo Park, Calif. 
Office—Earthquake Science Center 
U.S. Geological Survey 
345 Middlefield Road, MS 977 
Menlo Park, CA 94025 
https://earthquake.usgs.gov/

","tableOfContents":"","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"publishedDate":"2018-06-13","noUsgsAuthors":false,"publicationDate":"2018-06-13","publicationStatus":"PW","scienceBaseUri":"5b46e56be4b060350a15d135","contributors":{"authors":[{"text":"Zhang, Edward","contributorId":205530,"corporation":false,"usgs":true,"family":"Zhang","given":"Edward","email":"","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":737673,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fuis, Gary S. 0000-0002-3078-1544","orcid":"https://orcid.org/0000-0002-3078-1544","contributorId":204656,"corporation":false,"usgs":true,"family":"Fuis","given":"Gary","email":"","middleInitial":"S.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":737672,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Catchings, Rufus D. 0000-0002-5191-6102 catching@usgs.gov","orcid":"https://orcid.org/0000-0002-5191-6102","contributorId":1519,"corporation":false,"usgs":true,"family":"Catchings","given":"Rufus","email":"catching@usgs.gov","middleInitial":"D.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true}],"preferred":true,"id":737674,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Scheirer, Daniel S. dscheirer@usgs.gov","contributorId":2325,"corporation":false,"usgs":true,"family":"Scheirer","given":"Daniel S.","email":"dscheirer@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":737675,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Goldman, Mark 0000-0002-0802-829X goldman@usgs.gov","orcid":"https://orcid.org/0000-0002-0802-829X","contributorId":205532,"corporation":false,"usgs":true,"family":"Goldman","given":"Mark","email":"goldman@usgs.gov","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":737676,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bauer, Klaus","contributorId":198443,"corporation":false,"usgs":false,"family":"Bauer","given":"Klaus","email":"","affiliations":[],"preferred":false,"id":737677,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70198113,"text":"70198113 - 2018 - Ensemble smoothed seismicity models for the new Italian Probabilistic Seismic Hazard Map","interactions":[],"lastModifiedDate":"2018-07-17T10:09:09","indexId":"70198113","displayToPublicDate":"2018-06-13T00:00:00","publicationYear":"2018","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":"Ensemble smoothed seismicity models for the new Italian Probabilistic Seismic Hazard Map","docAbstract":"

We develop a long‐term (a few decades or longer) earthquake rate forecast for Italy based on smoothed seismicity for incorporation in the 2017–2018 Italian Probabilistic Seismic Hazard Maps (IPSHM). Because the earthquake rate models from previous IPSHM were computed using source zones that were drawn around seismicity and tectonic provinces, the present model will be the first introduction of the smoothed seismicity method into the IPSHM. Smoothed seismicity models are constructed from both historical CPTI15 (Catalogo Parametrico dei Terremoti Italiani, 1000–2014) and instrumental (1981–2016) earthquake catalogs and use both fixed and adaptive smoothing methods. We compute spatial likelihood values comparing the spatial distribution of observed earthquakes with a suite of trial earthquake rate models to optimize smoothing parameters and catalogs. Then we produce an ensemble model using two different smoothing models (adaptive and fixed) and two earthquake catalogs (historical and instrumental), which are weighted equally through a logic‐tree approach to improve the forecast capability. We also compare our optimized smoothed seismicity models with the best two models of the Italian Collaboratory for the Study of Earthquake Predictability (CSEP) experiment and retrospectively test them with the CSEP methodology. We observed that the ensemble model performs slightly better than the optimized fixed and the adaptive smoothing seismicity models obtained in this study and the best time‐independent model of the CSEP Italian experiment. The preferred ensemble model forecasts an annual rate of 1.47 M&#x2265;5.0\">M≥5.0 earthquakes, with higher rates mainly concentrating along the Apennines chain, eastern Alps, Calabria, and northeast Sicily. Finally, six ensemble models are created from the different smoothing methods using different weights through a logic‐tree approach to estimate the uncertainty associated with the model.

","language":"English","publisher":"SSA","doi":"10.1785/0220180040","usgsCitation":"Akinci, A., Moschetti, M.P., and Taroni, M., 2018, Ensemble smoothed seismicity models for the new Italian Probabilistic Seismic Hazard Map: Seismological Research Letters, v. 89, no. 4, p. 1277-1287, https://doi.org/10.1785/0220180040.","productDescription":"11 p.","startPage":"1277","endPage":"1287","ipdsId":"IP-096395","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":355724,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Italy","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"MultiPolygon\",\"coordinates\":[[[[15.52038,38.23116],[15.16024,37.44405],[15.3099,37.13422],[15.09999,36.61999],[14.33523,36.99663],[13.82673,37.10453],[12.431,37.61295],[12.57094,38.12638],[13.74116,38.03497],[14.76125,38.14387],[15.52038,38.23116]]],[[[9.21001,41.20999],[9.80998,40.50001],[9.66952,39.17738],[9.21482,39.24047],[8.80694,38.90662],[8.4283,39.17185],[8.38825,40.37831],[8.16,40.95001],[8.70999,40.89998],[9.21001,41.20999]]],[[[12.37649,46.76756],[13.80648,46.50931],[13.69811,46.01678],[13.93763,45.59102],[13.14161,45.73669],[12.32858,45.38178],[12.38387,44.88537],[12.26145,44.60048],[12.58924,44.09137],[13.52691,43.58773],[14.02982,42.76101],[15.14257,41.95514],[15.92619,41.96132],[16.1699,41.74029],[15.88935,41.54108],[16.785,41.17961],[17.51917,40.87714],[18.37669,40.35562],[18.48025,40.16887],[18.29339,39.81077],[17.73838,40.27767],[16.8696,40.44223],[16.44874,39.7954],[17.17149,39.4247],[17.05284,38.90287],[16.63509,38.84357],[16.10096,37.9859],[15.68409,37.90885],[15.68796,38.21459],[15.89198,38.75094],[16.10933,38.96455],[15.71881,39.54407],[15.41361,40.04836],[14.9985,40.17295],[14.70327,40.60455],[14.06067,40.78635],[13.62799,41.18829],[12.88808,41.25309],[12.10668,41.70453],[11.19191,42.35543],[10.51195,42.93146],[10.20003,43.92001],[9.70249,44.03628],[8.88895,44.36634],[8.42856,44.23123],[7.85077,43.76715],[7.43518,43.69384],[7.5496,44.1279],[7.00756,44.25477],[6.74996,45.02852],[7.09665,45.3331],[6.80236,45.70858],[6.84359,45.99115],[7.27385,45.77695],[7.75599,45.82449],[8.31663,46.16364],[8.48995,46.00515],[8.96631,46.03693],[9.18288,46.44021],[9.92284,46.3149],[10.36338,46.48357],[10.4427,46.89355],[11.04856,46.75136],[11.16483,46.94158],[12.15309,47.11539],[12.37649,46.76756]]]]},\"properties\":{\"name\":\"Italy\"}}]}","volume":"89","issue":"4","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2018-06-13","publicationStatus":"PW","scienceBaseUri":"5b6fc431e4b0f5d57878ea17","contributors":{"authors":[{"text":"Akinci, Aybige","contributorId":172715,"corporation":false,"usgs":false,"family":"Akinci","given":"Aybige","email":"","affiliations":[{"id":27088,"text":"Istituto Nazionale di Geofisica e Vulcanologia (INGV)","active":true,"usgs":false}],"preferred":false,"id":740075,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Moschetti, Morgan P. 0000-0001-7261-0295 mmoschetti@usgs.gov","orcid":"https://orcid.org/0000-0001-7261-0295","contributorId":1662,"corporation":false,"usgs":true,"family":"Moschetti","given":"Morgan","email":"mmoschetti@usgs.gov","middleInitial":"P.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":740076,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Taroni, Matteo","contributorId":178526,"corporation":false,"usgs":false,"family":"Taroni","given":"Matteo","email":"","affiliations":[],"preferred":false,"id":740077,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70197615,"text":"70197615 - 2018 - Multistate models of bigheaded carps in the Illinois River reveal spatial dynamics of invasive species","interactions":[],"lastModifiedDate":"2018-11-14T09:57:14","indexId":"70197615","displayToPublicDate":"2018-06-13T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1018,"text":"Biological Invasions","active":true,"publicationSubtype":{"id":10}},"title":"Multistate models of bigheaded carps in the Illinois River reveal spatial dynamics of invasive species","docAbstract":"

Knowledge of the spatial distributions and dispersal characteristics of invasive species is necessary for managing the spread of highly mobile species, such as invasive bigheaded carps (Bighead Carp [Hypophthalmichthys nobilis] and Silver Carp [H. molitrix]). Management of invasive bigheaded carps in the Illinois River has focused on using human-made barriers and harvest to limit dispersal towards the Laurentian Great Lakes. Acoustic telemetry data were used to parameterize multistate models to examine the spatial dynamics of bigheaded carps in the Illinois River to (1) evaluate the effects of existing dams on movement, (2) identify how individuals distribute among pools, and (3) gauge the effects of reductions in movement towards the invasion front. Multistate models estimated that movement was generally less likely among upper river pools (Starved Rock, Marseilles, and Dresden Island) than the lower river (La Grange and Peoria) which matched the pattern of gated versus wicket style dams. Simulations using estimated movement probabilities indicated that Bighead Carp accumulate in La Grange Pool while Silver Carp accumulate in Alton Pool. Fewer Bighead Carp reached the upper river compared to Silver Carp during simulations. Reducing upstream movement probabilities (e.g., reduced propagule pressure) by ≥ 75% into any of the upper river pools could reduce upper river abundance with similar results regardless of location. Given bigheaded carp reproduction in the upper Illinois River is presently limited, reduced movement towards the invasion front coupled with removal of individuals reaching these areas could limit potential future dispersal towards the Great Lakes.

","language":"English","publisher":"Springer","doi":"10.1007/s10530-018-1772-6","usgsCitation":"Coulter, A.A., Brey, M.K., Lubejko, M., Kallis, J.L., Coulter, D.P., Glover, D.C., Whitledge, G.W., and Garvey, J.E., 2018, Multistate models of bigheaded carps in the Illinois River reveal spatial dynamics of invasive species: Biological Invasions, v. 20, no. 11, p. 3255-3270, https://doi.org/10.1007/s10530-018-1772-6.","productDescription":"16 p.","startPage":"3255","endPage":"3270","ipdsId":"IP-086127","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":437866,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9RYXNS4","text":"USGS data release","linkHelpText":"Multistate models of bigheaded carps in the Illinois River reveal spatial dynamics of invasive species: Data"},{"id":355022,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Laurentian Great Lakes","volume":"20","issue":"11","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationDate":"2018-06-05","publicationStatus":"PW","scienceBaseUri":"5b46e569e4b060350a15d129","contributors":{"authors":[{"text":"Coulter, Alison A.","contributorId":187652,"corporation":false,"usgs":false,"family":"Coulter","given":"Alison","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":737930,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brey, Marybeth K. 0000-0003-4403-9655 mbrey@usgs.gov","orcid":"https://orcid.org/0000-0003-4403-9655","contributorId":187651,"corporation":false,"usgs":true,"family":"Brey","given":"Marybeth","email":"mbrey@usgs.gov","middleInitial":"K.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":737929,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lubejko, Matthew","contributorId":195897,"corporation":false,"usgs":false,"family":"Lubejko","given":"Matthew","email":"","affiliations":[],"preferred":false,"id":737931,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kallis, Jahn L.","contributorId":205603,"corporation":false,"usgs":false,"family":"Kallis","given":"Jahn","email":"","middleInitial":"L.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":737932,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Coulter, David P.","contributorId":205629,"corporation":false,"usgs":false,"family":"Coulter","given":"David","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":737999,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Glover, David C.","contributorId":178006,"corporation":false,"usgs":false,"family":"Glover","given":"David","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":737933,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Garvey, James E.","contributorId":178007,"corporation":false,"usgs":false,"family":"Garvey","given":"James","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":737935,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Whitledge, Gregory W.","contributorId":205604,"corporation":false,"usgs":false,"family":"Whitledge","given":"Gregory","email":"","middleInitial":"W.","affiliations":[{"id":32417,"text":"Southern Illinois University-Carbondale","active":true,"usgs":false}],"preferred":false,"id":737934,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70222617,"text":"70222617 - 2018 - Broadband ground‐motion simulation of the 2011 Mw 6.2 Christchurch, New Zealand, earthquake","interactions":[],"lastModifiedDate":"2021-08-09T13:10:32.759248","indexId":"70222617","displayToPublicDate":"2018-06-12T08:07:52","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"Broadband ground‐motion simulation of the 2011 Mw 6.2 Christchurch, New Zealand, earthquake","docAbstract":"

This study presents the details and results of hybrid broadband (0–10 Hz) ground‐motion simulations for the 2011 Mw\">MwMw 6.2 Christchurch, New Zealand, earthquake. The simulations utilize a 3D velocity model and a kinematic source model with stochastic realizations of the slip amplitude, rise time, and rake angle. The resulting ground motions capture the salient basin amplification effects that are seen in the observed ground motions in central Christchurch city. Quantitative comparisons of the simulations with both observed recordings and empirical ground‐motion models (GMMs), considering peak ground acceleration, 5% damped pseudospectral acceleration, and 5%–95% significant duration, indicate that the simulations exhibit lower bias than empirical GMMs over the T=1&#x2013;10&#x2009;&#x2009;s\">T=1–10  sT=1–10  s period range, and are comparable at short periods (⁠T&lt;1&#x2009;&#x2009;s\">T<1  sT<1  s⁠). Sensitivity analyses suggest that the effect of stochastic realizations of different slip distributions is relatively small because of the fault dimensions. It is also illustrated that the effect of slip distribution variability is only a small component of the total uncertainty in ground‐motion simulation. As well as the important implications toward ground‐motion simulation validation, the presented simulations provide ground‐motion time series that can be used for forensic structural and geotechnical case histories that are located sufficiently far from strong‐motion station recordings.

","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120170388","usgsCitation":"Razafindrakoto, H.N., Bradley, B.A., and Graves, R., 2018, Broadband ground‐motion simulation of the 2011 Mw 6.2 Christchurch, New Zealand, earthquake: Bulletin of the Seismological Society of America, v. 108, no. 4, p. 2130-2147, https://doi.org/10.1785/0120170388.","productDescription":"18 p.","startPage":"2130","endPage":"2147","ipdsId":"IP-085323","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":387772,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"New Zealand","otherGeospatial":"Christchurch","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 172.02392578125,\n -44.03232064275081\n ],\n [\n 173.2763671875,\n -44.03232064275081\n ],\n [\n 173.2763671875,\n -43.19716728250127\n ],\n [\n 172.02392578125,\n -43.19716728250127\n ],\n [\n 172.02392578125,\n -44.03232064275081\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"108","issue":"4","noUsgsAuthors":false,"publicationDate":"2018-06-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Razafindrakoto, Hoby N. T.","contributorId":174016,"corporation":false,"usgs":false,"family":"Razafindrakoto","given":"Hoby","email":"","middleInitial":"N. T.","affiliations":[{"id":24561,"text":"KAUST","active":true,"usgs":false}],"preferred":false,"id":820776,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bradley, Brendon A.","contributorId":202814,"corporation":false,"usgs":false,"family":"Bradley","given":"Brendon","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":820777,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Graves, Robert 0000-0001-9758-453X rwgraves@usgs.gov","orcid":"https://orcid.org/0000-0001-9758-453X","contributorId":140738,"corporation":false,"usgs":true,"family":"Graves","given":"Robert","email":"rwgraves@usgs.gov","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":820778,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ]}