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The U.S. Geological Survey, in cooperation with Gwinnett County Department of Water Resources, established a Long-Term Trend Monitoring (LTTM) program in 1996. The LTTM program is a comprehensive, long-term, water-quantity and water-quality monitoring program designed to document and analyze the hydrologic and water-quality conditions of selected watersheds of Gwinnett County, Georgia. Water-quality monitoring initially began in six watersheds and was expanded to another six watersheds in 2001.

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As part of the LTTM program, streamflow, precipitation, water temperature, specific conductance, and turbidity were measured continuously at the 12 watershed monitoring stations for water years 2004–09. In addition, discrete water-quality samples were collected seasonally from May through October (summer) and November through April (winter), including one base-flow and three stormflow event composite samples, during the study period. Samples were analyzed for nutrients (nitrogen and phosphorus), total organic carbon, trace elements (total lead and total zinc), total dissolved solids, and total suspended sediment (total suspended solids and suspended-sediment concentrations). The sampling scheme was designed to identify variations in water quality both hydrologically and seasonally.

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The 12 watersheds were characterized for basin slope, population density, land use for 2009, and the percentage of impervious area from 2000 to 2009. Precipitation in water years 2004–09 was about 18 percent below average, and the county experienced exceptional drought conditions and below average runoff in water years 2007 and 2008. Watershed water yields, the percentage of precipitation that results in runoff, typically are lower in low precipitation years and are higher for watersheds with the highest percentages of impervious areas.

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A comparison of base-flow and stormflow water-quality samples indicates that turbidity and concentrations of total ammonia plus organic nitrogen, total nitrogen, total phosphorus, total organic carbon, total lead, total zinc, total suspended solids, and suspended-sediment concentrations increased with increasing discharge at all watersheds. Specific conductance, however, decreased during stormflow at all watersheds, and total dissolved solids concentrations decreased during stormflow at a few of the watersheds. Total suspended solids and suspended-sediment concentrations typically were two orders of magnitude higher in stormflow samples, turbidities were about 1.5 orders of magnitude higher, total phosphorus and total zinc were about one order of magnitude higher, and total ammonia plus organic nitrogen, total nitrogen, total organic carbon, and total lead were about twofold higher than in base-flow samples.

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Seasonal patterns and long-term trends in flow-adjusted water-quality concentrations were identified for five representative constituents—total nitrogen, total phosphorus, total zinc, total dissolved solids, and total suspended solids. Seasonal patterns for all five constituents were fairly similar, with higher concentrations in the summer and lower concentrations in the winter. Significant linear long-term trends in stormflow composite concentrations were identified for 36 of the 60 constituent-watershed combinations (5 constituents multiplied by 12 watersheds) for the period of record through water year 2011. Significant trends typically were decreasing for total nitrogen, total phosphorus, total suspended solids, and total zinc and increasing for total dissolved solids. Total dissolved solids and total suspended solids trends had the largest magnitude changes per year.

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Stream water loads were estimated for 10 water-quality constituents. These estimates represent the cumulative effects of watershed characteristics, hydrologic processes, biogeochemical processes, climatic variability, and human influences on watershed water quality. Yields, in load per unit area, were used to compare loads from watersheds with different sizes. A load estimation approach developed for the Gwinnett County LTTM program that incorporates storm-event composited samples was used with some minor modifications. This approach employs the commonly used regression-model method. Concentrations were modeled as a function of discharge, time, season, and turbidity to improve model predictions and reduce errors in load estimates. Total suspended solids annual loads have been identified in Gwinnett County’s Watershed Protection Plan for target performance criterion.

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The amount of annual runoff is the primary factor in determining the amount of annual constituent loads. Below average runoff during water years 2004–09, especially during water years 2006–08, resulted in corresponding below average loads. Variations in constituent yields between watersheds appeared to be related to various watershed characteristics. Suspended sediment (total suspended solids and suspended-sediment concentrations) along with constituents transported predominately in solid phase (total phosphorus, total organic carbon, total lead, and total zinc) and total dissolved solids typically had higher yields from watersheds that had high percentages of impervious areas or high basin slope. High total nitrogen yields were also associated with watersheds with high percentages of impervious areas. Low total nitrogen, total suspended solids, total lead, and total zinc yields appear to be associated with watersheds that have a low percentage of high-density development. Total suspended solids yields were lower in drought years, water years 2007–08, from the combined effects of less runoff and the result of fewer, lower magnitude storms, which likely resulted in less surface erosion and lower stream sediment transport.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145141","isbn":"9781411338159","collaboration":"Prepared in cooperation with Gwinnett County Department of Water Resources","usgsCitation":"Joiner, J.K., Aulenbach, B.T., and Landers, M.N., 2014, Watershed characteristics and water-quality trends and loads in 12 watersheds in Gwinnett County, Georgia: U.S. Geological Survey Scientific Investigations Report 2014-5141, viii, 79 p., https://doi.org/10.3133/sir20145141.","productDescription":"viii, 79 p.","numberOfPages":"92","onlineOnly":"N","ipdsId":"IP-057246","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":291595,"type":{"id":15,"text":"Index 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John K. 0000-0001-9702-4911 jkjoiner@usgs.gov","orcid":"https://orcid.org/0000-0001-9702-4911","contributorId":3056,"corporation":false,"usgs":true,"family":"Joiner","given":"John","email":"jkjoiner@usgs.gov","middleInitial":"K.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":496070,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Aulenbach, Brent T. 0000-0003-2863-1288 btaulenb@usgs.gov","orcid":"https://orcid.org/0000-0003-2863-1288","contributorId":3057,"corporation":false,"usgs":true,"family":"Aulenbach","given":"Brent","email":"btaulenb@usgs.gov","middleInitial":"T.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":316,"text":"Georgia Water Science Center","active":true,"usgs":true}],"preferred":true,"id":496071,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Landers, Mark N. 0000-0002-3014-0480 landers@usgs.gov","orcid":"https://orcid.org/0000-0002-3014-0480","contributorId":1103,"corporation":false,"usgs":true,"family":"Landers","given":"Mark","email":"landers@usgs.gov","middleInitial":"N.","affiliations":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"preferred":true,"id":496069,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70119003,"text":"70119003 - 2014 - Mapping and monitoring Mount Graham red squirrel habitat with Lidar and Landsat imagery","interactions":[],"lastModifiedDate":"2016-04-26T10:02:52","indexId":"70119003","displayToPublicDate":"2014-08-04T09:27:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1458,"text":"Ecological Modelling","active":true,"publicationSubtype":{"id":10}},"title":"Mapping and monitoring Mount Graham red squirrel habitat with Lidar and Landsat imagery","docAbstract":"

The Mount Graham red squirrel (Tamiasciurus hudsonicus grahamensis) is an endemic subspecies located in the Pinaleño Mountains of southeast Arizona. Living in a conifer forest on a sky-island surrounded by desert, the Mount Graham red squirrel is one of the rarest mammals in North America. Over the last two decades, drought, insect infestations, and fire destroyed much of its habitat. A federal recovery team is working on a plan to recover the squirrel and detailed information is necessary on its habitat requirements and population dynamics. Toward that goal I developed and compared three probabilistic models of Mount Graham red squirrel habitat with a geographic information system and logistic regression. Each model contained the same topographic variables (slope, aspect, elevation), but the Landsat model contained a greenness variable (Normalized Difference Vegetation Index) extracted from Landsat, the Lidar model contained three forest-inventory variables extracted from lidar, while the Hybrid model contained Landsat and lidar variables. The Hybrid model produced the best habitat classification accuracy, followed by the Landsat and Lidar models, respectively. Landsat-derived forest greenness was the best predictor of habitat, followed by topographic (elevation, slope, aspect) and lidar (tree height, canopy bulk density, and live basal area) variables, respectively. The Landsat model's probabilities were significantly correlated with all 12 lidar variables, indicating its utility for habitat mapping. While the Hybrid model produced the best classification results, only the Landsat model was suitable for creating a habitat time series or habitat–population function between 1986 and 2013. The techniques I highlight should prove valuable in the development of Landsat- or lidar-based habitat models range wide.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolmodel.2014.07.004","usgsCitation":"Hatten, J.R., 2014, Mapping and monitoring Mount Graham red squirrel habitat with Lidar and Landsat imagery: Ecological Modelling, v. 289, p. 106-123, https://doi.org/10.1016/j.ecolmodel.2014.07.004.","productDescription":"18 p.","startPage":"106","endPage":"123","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-053195","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":291561,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":291556,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.ecolmodel.2014.07.004"}],"country":"United States","state":"Arizona","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -109.859696,32.631505 ], [ -109.859696,32.650297 ], [ -109.827681,32.650297 ], [ -109.827681,32.631505 ], [ -109.859696,32.631505 ] ] ] } } ] }","volume":"289","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53e09030e4b0beb42bdc040c","contributors":{"authors":[{"text":"Hatten, James R. 0000-0003-4676-8093 jhatten@usgs.gov","orcid":"https://orcid.org/0000-0003-4676-8093","contributorId":3431,"corporation":false,"usgs":true,"family":"Hatten","given":"James","email":"jhatten@usgs.gov","middleInitial":"R.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":497568,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70118992,"text":"70118992 - 2014 - Geostatistical estimation of signal-to-noise ratios for spectral vegetation indices","interactions":[],"lastModifiedDate":"2014-08-04T09:26:36","indexId":"70118992","displayToPublicDate":"2014-08-04T09:03:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1958,"text":"ISPRS Journal of Photogrammetry and Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Geostatistical estimation of signal-to-noise ratios for spectral vegetation indices","docAbstract":"In the past 40 years, many spectral vegetation indices have been developed to quantify vegetation biophysical parameters. An ideal vegetation index should contain the maximum level of signal related to specific biophysical characteristics and the minimum level of noise such as background soil influences and atmospheric effects. However, accurate quantification of signal and noise in a vegetation index remains a challenge, because it requires a large number of field measurements or laboratory experiments. In this study, we applied a geostatistical method to estimate signal-to-noise ratio (S/N) for spectral vegetation indices. Based on the sample semivariogram of vegetation index images, we used the standardized noise to quantify the noise component of vegetation indices. In a case study in the grasslands and shrublands of the western United States, we demonstrated the geostatistical method for evaluating S/N for a series of soil-adjusted vegetation indices derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor. The soil-adjusted vegetation indices were found to have higher S/N values than the traditional normalized difference vegetation index (NDVI) and simple ratio (SR) in the sparsely vegetated areas. This study shows that the proposed geostatistical analysis can constitute an efficient technique for estimating signal and noise components in vegetation indices.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"ISPRS Journal of Photogrammetry and Remote Sensing","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.isprsjprs.2014.06.013","usgsCitation":"Ji, L., Zhang, L., Rover, J.R., Wylie, B.K., and Chen, X., 2014, Geostatistical estimation of signal-to-noise ratios for spectral vegetation indices: ISPRS Journal of Photogrammetry and Remote Sensing, v. 96, p. 20-27, https://doi.org/10.1016/j.isprsjprs.2014.06.013.","productDescription":"8 p.","startPage":"20","endPage":"27","ipdsId":"IP-033481","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":291559,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":291558,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.isprsjprs.2014.06.013"}],"volume":"96","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53e09030e4b0beb42bdc040a","contributors":{"authors":[{"text":"Ji, Lei 0000-0002-6133-1036 lji@usgs.gov","orcid":"https://orcid.org/0000-0002-6133-1036","contributorId":2832,"corporation":false,"usgs":true,"family":"Ji","given":"Lei","email":"lji@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":497564,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zhang, Li","contributorId":98139,"corporation":false,"usgs":true,"family":"Zhang","given":"Li","affiliations":[],"preferred":false,"id":497567,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rover, Jennifer R. 0000-0002-3437-4030 jrover@usgs.gov","orcid":"https://orcid.org/0000-0002-3437-4030","contributorId":2941,"corporation":false,"usgs":true,"family":"Rover","given":"Jennifer","email":"jrover@usgs.gov","middleInitial":"R.","affiliations":[],"preferred":false,"id":497565,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"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":497563,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Chen, Xuexia","contributorId":14213,"corporation":false,"usgs":true,"family":"Chen","given":"Xuexia","affiliations":[],"preferred":false,"id":497566,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70114991,"text":"70114991 - 2014 - What caused terrestrial dust loading and climate downturns between A.D. 533 and 540?","interactions":[],"lastModifiedDate":"2017-06-30T13:43:27","indexId":"70114991","displayToPublicDate":"2014-08-01T16:11:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1727,"text":"GSA Special Papers","active":true,"publicationSubtype":{"id":10}},"title":"What caused terrestrial dust loading and climate downturns between A.D. 533 and 540?","docAbstract":"Sn-rich particles, Ni-rich particles, and cosmic spherules are found together at four discrete stratigraphic levels within the 362-360 m depth interval of the Greenland Ice Sheet Project 2 (GISP2) ice core (72.6°N, 38.5°W, elevation: 3203 m). Using a previously derived calendar-year time scale, these particles span a time of increased dust loading of Earth's atmosphere between A.D. 533 and 540. The Sn-rich and Ni-rich particles contain an average of 10–11 wt% C. Their high C contents coupled with local enrichments in the volatile elements I, Zn, Cu, and Xe suggest a cometary source for the dust. The late spring timing of extraterrestrial input best matches the Eta Aquarid meteor shower associated with comet 1P/Halley. An increased flux of cometary dust might explain a modest climate downturn in A.D. 533. Both cometary dust and volcanic sulfate probably contributed to the profound global dimming during A.D. 536 and 537 but may be insufficient sources of fine aerosols. We found tropical marine microfossils and aerosol-sized CaCO3 particles at the end A.D. 535–start A.D. 536 level that we attribute to a low-latitude explosion in the ocean. This additional source of dust is probably needed to explain the solar dimming during A.D. 536 and 537. Although there has been no extinction documented at A.D. 536, our results are relevant because mass extinctions may also have multiple drivers. Detailed examinations of fine particles at and near extinction horizons can help to determine the relative contributions of cosmic and volcanic drivers to mass extinctions.","language":"English","publisher":"Geological Society of America","doi":"10.1130/2014.2505(23)","usgsCitation":"Abbott, D.H., Breger, D., Biscaye, P.E., Barron, J.A., Juhl, R.A., and McCafferty, P., 2014, What caused terrestrial dust loading and climate downturns between A.D. 533 and 540?: GSA Special Papers, v. 505, p. 421-437, https://doi.org/10.1130/2014.2505(23).","productDescription":"17 p.","startPage":"421","endPage":"437","numberOfPages":"17","ipdsId":"IP-030122","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":472829,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.7916/d81v5dcr","text":"External Repository"},{"id":294949,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":289248,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1130/2014.2505(23)"}],"volume":"505","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"542fbab6e4b092f17df61e55","contributors":{"authors":[{"text":"Abbott, Dallas H.","contributorId":23870,"corporation":false,"usgs":true,"family":"Abbott","given":"Dallas","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":495463,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Breger, Dee","contributorId":80213,"corporation":false,"usgs":true,"family":"Breger","given":"Dee","email":"","affiliations":[],"preferred":false,"id":495466,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Biscaye, Pierre E.","contributorId":65784,"corporation":false,"usgs":true,"family":"Biscaye","given":"Pierre","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":495465,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Barron, John A. 0000-0002-9309-1145 jbarron@usgs.gov","orcid":"https://orcid.org/0000-0002-9309-1145","contributorId":2222,"corporation":false,"usgs":true,"family":"Barron","given":"John","email":"jbarron@usgs.gov","middleInitial":"A.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":495461,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Juhl, Robert A.","contributorId":8403,"corporation":false,"usgs":true,"family":"Juhl","given":"Robert","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":495462,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"McCafferty, Patrick","contributorId":43292,"corporation":false,"usgs":true,"family":"McCafferty","given":"Patrick","email":"","affiliations":[],"preferred":false,"id":495464,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70094717,"text":"70094717 - 2014 - Implementation of NGA-West2 ground motion models in the 2014 U.S. National Seismic Hazard Maps","interactions":[],"lastModifiedDate":"2014-10-02T16:00:31","indexId":"70094717","displayToPublicDate":"2014-08-01T15:57:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1436,"text":"Earthquake Spectra","active":true,"publicationSubtype":{"id":10}},"title":"Implementation of NGA-West2 ground motion models in the 2014 U.S. National Seismic Hazard Maps","docAbstract":"The U.S. National Seismic Hazard Maps (NSHMs) have been an important component of seismic design regulations in the United States for the past several decades. These maps present earthquake ground shaking intensities at specified probabilities of being exceeded over a 50-year time period. The previous version of the NSHMs was developed in 2008; during 2012 and 2013, scientists at the U.S. Geological Survey have been updating the maps based on their assessment of the “best available science,” resulting in the 2014 NSHMs. The update includes modifications to the seismic source models and the ground motion models (GMMs) for sites across the conterminous United States. This paper focuses on updates in the Western United States (WUS) due to the use of new GMMs for shallow crustal earthquakes in active tectonic regions developed by the Next Generation Attenuation (NGA-West2) project. Individual GMMs, their weighted combination, and their impact on the hazard maps relative to 2008 are discussed. In general, the combined effects of lower medians and increased standard deviations in the new GMMs have caused only small changes, within 5–20%, in the probabilistic ground motions for most sites across the WUS compared to the 2008 NSHMs.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Earthquake Spectra","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Earthquake Engineering Research Institute","doi":"10.1193/062913EQS177M","usgsCitation":"Rezaeian, S., Petersen, M.D., Moschetti, M.P., Powers, P., Harmsen, S., and Frankel, A.D., 2014, Implementation of NGA-West2 ground motion models in the 2014 U.S. National Seismic Hazard Maps: Earthquake Spectra, v. 30, no. 3, p. 1319-1333, https://doi.org/10.1193/062913EQS177M.","productDescription":"15 p.","startPage":"1319","endPage":"1333","numberOfPages":"15","ipdsId":"IP-054744","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":294886,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":294885,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1193/062913EQS177M"}],"volume":"30","issue":"3","noUsgsAuthors":false,"publicationDate":"2014-08-01","publicationStatus":"PW","scienceBaseUri":"542e6964e4b092f17df5a8b2","contributors":{"authors":[{"text":"Rezaeian, Sanaz 0000-0001-7589-7893 srezaeian@usgs.gov","orcid":"https://orcid.org/0000-0001-7589-7893","contributorId":4395,"corporation":false,"usgs":true,"family":"Rezaeian","given":"Sanaz","email":"srezaeian@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":490832,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Petersen, Mark D. 0000-0001-8542-3990 mpetersen@usgs.gov","orcid":"https://orcid.org/0000-0001-8542-3990","contributorId":1163,"corporation":false,"usgs":true,"family":"Petersen","given":"Mark","email":"mpetersen@usgs.gov","middleInitial":"D.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":490828,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"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":490830,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Powers, Peter","contributorId":92596,"corporation":false,"usgs":true,"family":"Powers","given":"Peter","affiliations":[],"preferred":false,"id":490833,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Harmsen, Stephen C. harmsen@usgs.gov","contributorId":1795,"corporation":false,"usgs":true,"family":"Harmsen","given":"Stephen C.","email":"harmsen@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":false,"id":490831,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Frankel, Arthur D. 0000-0001-9119-6106 afrankel@usgs.gov","orcid":"https://orcid.org/0000-0001-9119-6106","contributorId":1363,"corporation":false,"usgs":true,"family":"Frankel","given":"Arthur","email":"afrankel@usgs.gov","middleInitial":"D.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":false,"id":490829,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70125279,"text":"70125279 - 2014 - Guidelines for use of fishes in research","interactions":[],"lastModifiedDate":"2020-01-06T14:10:25","indexId":"70125279","displayToPublicDate":"2014-08-01T15:52:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":3,"text":"Organization Series"},"title":"Guidelines for use of fishes in research","docAbstract":"

The 2004 and 2014 Guidelines were developed to provide a structure that advances appropriate \nattention toward valid experimental designs and procedures with aquatic animals while ensuring \nhumane treatment of the experimental subjects. At a practical level, the Guidelines are intended \nto provide general recommendations on field and laboratory endeavors, such as sampling, \nholding, and handling fishes; to offer information on administrative matters, including \nregulations and permits; and to address typical ethical concerns, such as perceptions of pain or \ndiscomfort experienced by experimental subjects. These Guidelines must be recognized as \nguidelines. They are not intended to provide detailed instructions but rather to alert investigators \nto a broad array of topics and concerns to consider prior to initiating study. At a comprehensive \nlevel, the principles upon which these Guidelines are based are broadly applicable, and many of \nthe described practices and approaches can be adapted to situations involving other aquatic \nanimal species and conditions.

\n
\n

Understanding the differences between fishes and other vertebrates, especially mammals, is \ncritically important to conducting scientifically sound research with fishes. Disparities in life \nhistories and mortality rates in fishes versus other vertebrates are critical in designing sustainable \nsampling levels in fish populations. The UFR Committee points out that (1) compared to \nmammalian populations, adult populations of many fish species persist despite very high natural \nmortality rates in juvenile stages by virtue of the fact that most species lay thousands or tens of \nthousands of eggs; (2) because of these mortality patterns, research on fishes, especially field \nresearch or research on early life stages, can involve, and often requires, much larger numbers of \nresearch subjects than does research on mammals; and (3) the animal handling and husbandry \nrequirements for fishes are fundamentally different from those for mammals and other \nvertebrates, in general. Policies, regulations, and recommendations developed for research on \nmammals, birds, reptiles, or even amphibians are frequently inappropriate for research with \nfishes. The Guidelines also address some of the ethical concerns that motivate guidelines used \nfor research with other vertebrates, while being mindful of the unique physiology and general \nnature of fishes.

\n
\n

The Guidelines were developed for general use by investigators within the United States; \ntherefore, the roles, responsibilities, and informational needs of Institutional Animal Care and \nUse Committees (IACUCs) were given specific attention. All United States institutions that use \nvertebrate animals for research, teaching, research training, and biological testing are required to \ncreate an IACUC to oversee and evaluate all aspects of the institution’s animal care and use \nprogram. Investigators from other nations who read this document may disregard specific \nreferences to U.S. state and federal laws and regulations, as their institutional infrastructure and \nprocesses may differ from those of an internal committee such as IACUCs. The principles described herein, however, are applicable to research on fishes regardless of geographic location. \nInvestigators in other nations may benefit by modifying any of the specific provisions pertaining \nto the United States, thereby adopting guidelines consistent with the laws and regulations of their \nown government. The UFR Committee urges that the Guidelines be endorsed and adopted \n(adapted, where necessary) by those state and federal authorities with regulatory responsibilities \nfor fishes, offices with federal oversight (e.g., National Institutes of Health, Office of Laboratory \nAnimal Welfare; http://grants.nih.gov/grants/olaw/olaw.htm) as well as by universities and other \ninstitutions and authorities using fishes and aquatic animals within their research and teaching \nprograms.

","language":"English","publisher":"American Fisheries Society","publisherLocation":"Bethesda, MD","usgsCitation":"Jenkins, J., Bart, H., Bowker, J.D., Bowser, P., MacMillan, J., Nickum, J., Rose, J.D., Sorenson, P.W., Whitledge, G., Rachlin, J., Warkentine, B., and Bart, H.L., 2014, Guidelines for use of fishes in research, xiv, 90 p.","productDescription":"xiv, 90 p.","numberOfPages":"104","ipdsId":"IP-043958","costCenters":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"links":[{"id":294005,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":293865,"type":{"id":15,"text":"Index Page"},"url":"https://fisheries.org/policy-media/science-guidelines/guidelines-for-the-use-of-fishes-in-research/"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5419513be4b091c7ffc8e6eb","contributors":{"authors":[{"text":"Jenkins, J. A. 0000-0002-5087-0894","orcid":"https://orcid.org/0000-0002-5087-0894","contributorId":115368,"corporation":false,"usgs":true,"family":"Jenkins","given":"J. A.","affiliations":[],"preferred":false,"id":501108,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bart, H.L. Jr.","contributorId":42679,"corporation":false,"usgs":true,"family":"Bart","given":"H.L.","suffix":"Jr.","email":"","affiliations":[],"preferred":false,"id":778965,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bowker, James D.","contributorId":51240,"corporation":false,"usgs":true,"family":"Bowker","given":"James","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":778966,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bowser, P.R.","contributorId":17935,"corporation":false,"usgs":true,"family":"Bowser","given":"P.R.","email":"","affiliations":[],"preferred":false,"id":778967,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"MacMillan, J.R.","contributorId":181511,"corporation":false,"usgs":false,"family":"MacMillan","given":"J.R.","email":"","affiliations":[],"preferred":false,"id":778968,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Nickum, J.G.","contributorId":58227,"corporation":false,"usgs":true,"family":"Nickum","given":"J.G.","email":"","affiliations":[],"preferred":false,"id":778969,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Rose, J. D.","contributorId":221596,"corporation":false,"usgs":false,"family":"Rose","given":"J.","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":778970,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Sorenson, P. W.","contributorId":221595,"corporation":false,"usgs":false,"family":"Sorenson","given":"P.","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":778971,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Whitledge, G.W.","contributorId":33465,"corporation":false,"usgs":true,"family":"Whitledge","given":"G.W.","email":"","affiliations":[],"preferred":false,"id":778972,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Rachlin, J.W.","contributorId":86725,"corporation":false,"usgs":true,"family":"Rachlin","given":"J.W.","email":"","affiliations":[],"preferred":false,"id":778973,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Warkentine, B.E.","contributorId":86298,"corporation":false,"usgs":true,"family":"Warkentine","given":"B.E.","affiliations":[],"preferred":false,"id":778974,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Bart, H. L.","contributorId":221597,"corporation":false,"usgs":false,"family":"Bart","given":"H.","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":778975,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70116314,"text":"70116314 - 2014 - Stream sediment sources in midwest agricultural basins with land retirement along channel","interactions":[],"lastModifiedDate":"2014-10-03T15:27:35","indexId":"70116314","displayToPublicDate":"2014-08-01T15:23:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2262,"text":"Journal of Environmental Quality","active":true,"publicationSubtype":{"id":10}},"title":"Stream sediment sources in midwest agricultural basins with land retirement along channel","docAbstract":"Documenting the effects of agricultural land retirement on stream-sediment sources is critical to identifying management practices that improve water quality and aquatic habitat. Particularly difficult to quantify are the effects from conservation easements that commonly are discontinuous along channelized streams and ditches throughout the agricultural midwestern United States. Our hypotheses were that sediment from cropland, retired land, stream banks, and roads would be discernible using isotopic and elemental concentrations and that source contributions would vary with land retirement distribution along tributaries of West Fork Beaver Creek in Minnesota. Channel-bed and suspended sediment were sampled at nine locations and compared with local source samples by using linear discriminant analysis and a four-source mixing model that evaluated seven tracers: In, P, total C, Be, Tl, Th, and Ti. The proportion of sediment sources differed significantly between suspended and channel-bed sediment. Retired land contributed to channel-bed sediment but was not discernible as a source of suspended sediment, suggesting that retired-land material was not mobilized during high-flow conditions. Stream banks were a large contributor to suspended sediment; however, the percentage of stream-bank sediment in the channel bed was lower in basins with more continuous retired land along the riparian corridor. Cropland sediments had the highest P concentrations; basins with the highest cropland-sediment contributions also had the highest P concentrations. Along stream reaches with retired land, there was a lower proportion of cropland material in suspended sediment relative to sites that had almost no land retirement, indicating less movement of nutrients and sediment from cropland to the channel as a result of land retirement.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Environmental Quality","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"American Society of Agronomy","doi":"10.2134/jeq2013.12.0521","usgsCitation":"Williamson, T., Christensen, V.G., Richardson, W.B., Frey, J.W., Gellis, A., Kieta, K., and Fitzpatrick, F.A., 2014, Stream sediment sources in midwest agricultural basins with land retirement along channel: Journal of Environmental Quality, v. 43, no. 5, p. 1624-1634, https://doi.org/10.2134/jeq2013.12.0521.","productDescription":"11 p.","startPage":"1624","endPage":"1634","numberOfPages":"11","ipdsId":"IP-051267","costCenters":[{"id":354,"text":"Kentucky Water Science Center","active":true,"usgs":true}],"links":[{"id":472830,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.2134/jeq2013.12.0521","text":"Publisher Index Page"},{"id":294941,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":294940,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.2134/jeq2013.12.0521"}],"country":"United States","state":"Minnesota","otherGeospatial":"West Fork Beaver Creek","volume":"43","issue":"5","noUsgsAuthors":false,"publicationDate":"2014-09-01","publicationStatus":"PW","scienceBaseUri":"542fbaaee4b092f17df61e00","contributors":{"authors":[{"text":"Williamson, Tanja N. tnwillia@usgs.gov","contributorId":452,"corporation":false,"usgs":true,"family":"Williamson","given":"Tanja N.","email":"tnwillia@usgs.gov","affiliations":[{"id":354,"text":"Kentucky Water Science Center","active":true,"usgs":true}],"preferred":false,"id":495751,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Christensen, Victoria G. 0000-0003-4166-7461 vglenn@usgs.gov","orcid":"https://orcid.org/0000-0003-4166-7461","contributorId":2354,"corporation":false,"usgs":true,"family":"Christensen","given":"Victoria","email":"vglenn@usgs.gov","middleInitial":"G.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":495755,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Richardson, William B. 0000-0002-7471-4394 wrichardson@usgs.gov","orcid":"https://orcid.org/0000-0002-7471-4394","contributorId":3277,"corporation":false,"usgs":true,"family":"Richardson","given":"William","email":"wrichardson@usgs.gov","middleInitial":"B.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":495756,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Frey, Jeffrey W. 0000-0002-3453-5009 jwfrey@usgs.gov","orcid":"https://orcid.org/0000-0002-3453-5009","contributorId":487,"corporation":false,"usgs":true,"family":"Frey","given":"Jeffrey","email":"jwfrey@usgs.gov","middleInitial":"W.","affiliations":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true},{"id":346,"text":"Indiana Water Science Center","active":true,"usgs":true},{"id":27231,"text":"Indiana-Kentucky Water Science Center","active":true,"usgs":true}],"preferred":true,"id":495752,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gellis, Allen C. 0000-0002-3449-2889 agellis@usgs.gov","orcid":"https://orcid.org/0000-0002-3449-2889","contributorId":1709,"corporation":false,"usgs":true,"family":"Gellis","given":"Allen C.","email":"agellis@usgs.gov","affiliations":[{"id":375,"text":"Maryland, Delaware, and the District of Columbia Water Science Center","active":false,"usgs":true}],"preferred":false,"id":495754,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kieta, K. A.","contributorId":47314,"corporation":false,"usgs":true,"family":"Kieta","given":"K. A.","affiliations":[],"preferred":false,"id":495757,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Fitzpatrick, Faith A. fafitzpa@usgs.gov","contributorId":1182,"corporation":false,"usgs":true,"family":"Fitzpatrick","given":"Faith","email":"fafitzpa@usgs.gov","middleInitial":"A.","affiliations":[{"id":476,"text":"North Carolina Water Science Center","active":true,"usgs":true}],"preferred":false,"id":495753,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70108033,"text":"70108033 - 2014 - Path durations for use in the stochastic‐method simulation of ground motions","interactions":[],"lastModifiedDate":"2014-10-10T16:46:29","indexId":"70108033","displayToPublicDate":"2014-08-01T15:13:00","publicationYear":"2014","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":"Path durations for use in the stochastic‐method simulation of ground motions","docAbstract":"The stochastic method of ground‐motion simulation assumes that the energy in a target spectrum is spread over a duration DT. DT is generally decomposed into the duration due to source effects (DS) and to path effects (DP). For the most commonly used source, seismological theory directly relates DS to the source corner frequency, accounting for the magnitude scaling of DT. In contrast, DP is related to propagation effects that are more difficult to represent by analytic equations based on the physics of the process. We are primarily motivated to revisit DT because the function currently employed by many implementations of the stochastic method for active tectonic regions underpredicts observed durations, leading to an overprediction of ground motions for a given target spectrum. Further, there is some inconsistency in the literature regarding which empirical duration corresponds to DT. Thus, we begin by clarifying the relationship between empirical durations and DT as used in the first author’s implementation of the stochastic method, and then we develop a new DP relationship. The new DP function gives significantly longer durations than in the previous DP function, but the relative contribution of DP to DT still diminishes with increasing magnitude. Thus, this correction is more important for small events or subfaults of larger events modeled with the stochastic finite‐fault method.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Bulletin of the Seismological Society of America","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120140058","usgsCitation":"Boore, D.M., and Thompson, E., 2014, Path durations for use in the stochastic‐method simulation of ground motions: Bulletin of the Seismological Society of America, v. 104, no. 5, p. 2541-2552, https://doi.org/10.1785/0120140058.","productDescription":"12 p.","startPage":"2541","endPage":"2552","numberOfPages":"12","ipdsId":"IP-054703","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":294917,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":294916,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1785/0120140058"}],"volume":"104","issue":"5","noUsgsAuthors":false,"publicationDate":"2014-08-12","publicationStatus":"PW","scienceBaseUri":"542fbaa5e4b092f17df61d65","contributors":{"authors":[{"text":"Boore, David M. boore@usgs.gov","contributorId":2509,"corporation":false,"usgs":true,"family":"Boore","given":"David","email":"boore@usgs.gov","middleInitial":"M.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":false,"id":493952,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thompson, Eric M.","contributorId":48501,"corporation":false,"usgs":true,"family":"Thompson","given":"Eric M.","affiliations":[],"preferred":false,"id":493953,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70127920,"text":"70127920 - 2014 - Relaxed selection causes microevolution of seawater osmoregulation and gene expression in landlocked Alewives","interactions":[],"lastModifiedDate":"2014-10-02T15:20:15","indexId":"70127920","displayToPublicDate":"2014-08-01T15:05:24","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2932,"text":"Oecologia","active":true,"publicationSubtype":{"id":10}},"title":"Relaxed selection causes microevolution of seawater osmoregulation and gene expression in landlocked Alewives","docAbstract":"Ecological transitions from marine to freshwater environments have been important in the creation of diversity among fishes. Evolutionary changes associated with these transitions likely involve modifications of osmoregulatory function. In particular, relaxed selection on hypo-osmoregulation should strongly affect animals that transition into novel freshwater environments. We used populations of the Alewife (Alosa pseudoharengus) to study evolutionary shifts in hypo-osmoregulatory capacity and ion regulation associated with freshwater transitions. Alewives are ancestrally anadromous, but multiple populations in Connecticut have been independently restricted to freshwater lakes; these landlocked populations complete their entire life cycle in freshwater. Juvenile landlocked and anadromous Alewives were exposed to three salinities (1, 20 and 30 ppt) in small enclosures within the lake. We detected strong differentiation between life history forms: landlocked Alewives exhibited reduced seawater tolerance and hypo-osmoregulatory performance compared to anadromous Alewives. Furthermore, gill Na+/K+-ATPase activity and transcription of genes for seawater osmoregulation (NKCC—Na+/K+/2Cl− cotransporter and CFTR—cystic fibrosis transmembrane conductance regulator) exhibited reduced responsiveness to seawater challenge. Our study demonstrates that adaptations of marine-derived species to completely freshwater life cycles involve partial loss of seawater osmoregulatory performance mediated through changes to ion regulation in the gill.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Oecologia","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Springer","doi":"10.1007/s00442-014-2961-3","usgsCitation":"Velotta, J.P., McCormick, S., O’Neill, R.J., and Schultz, E., 2014, Relaxed selection causes microevolution of seawater osmoregulation and gene expression in landlocked Alewives: Oecologia, v. 175, no. 4, p. 1081-1092, https://doi.org/10.1007/s00442-014-2961-3.","productDescription":"12 p.","startPage":"1081","endPage":"1092","numberOfPages":"12","ipdsId":"IP-051427","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"links":[{"id":294880,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":294879,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1007/s00442-014-2961-3"}],"country":"United States","state":"Connecticut","volume":"175","issue":"4","noUsgsAuthors":false,"publicationDate":"2014-05-24","publicationStatus":"PW","scienceBaseUri":"542e697ce4b092f17df5aa00","contributors":{"authors":[{"text":"Velotta, Jonathan P.","contributorId":86281,"corporation":false,"usgs":true,"family":"Velotta","given":"Jonathan","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":502687,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McCormick, Stephen D. 0000-0003-0621-6200","orcid":"https://orcid.org/0000-0003-0621-6200","contributorId":84678,"corporation":false,"usgs":true,"family":"McCormick","given":"Stephen D.","affiliations":[],"preferred":false,"id":502686,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"O’Neill, Rachel J.","contributorId":78668,"corporation":false,"usgs":true,"family":"O’Neill","given":"Rachel","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":502685,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schultz, Eric T.","contributorId":77071,"corporation":false,"usgs":true,"family":"Schultz","given":"Eric T.","affiliations":[],"preferred":false,"id":502684,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70099640,"text":"70099640 - 2014 - Pulverization provides a mechanism for the nucleation of earthquakes at low stress on strong faults","interactions":[],"lastModifiedDate":"2017-06-30T13:44:23","indexId":"70099640","displayToPublicDate":"2014-08-01T13:32:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5232,"text":"Frontiers in Earth Science","onlineIssn":"2296-6463","active":true,"publicationSubtype":{"id":10}},"title":"Pulverization provides a mechanism for the nucleation of earthquakes at low stress on strong faults","docAbstract":"

An earthquake occurs when rock that has been deformed under stress rebounds elastically along a fault plane (Gilbert, 1884; Reid, 1911), radiating seismic waves through the surrounding earth. Rupture along the entire fault surface does not spontaneously occur at the same time, however. Rather the rupture starts in one tiny area, the rupture nucleation zone, and spreads sequentially along the fault. Like a row of dominoes, one bit of rebounding fault triggers the next. This triggering is understood to occur because of the large dynamic stresses at the tip of an active seismic rupture. The importance of these crack tip stresses is a central question in earthquake physics. The crack tip stresses are minimally important, for example, in the time predictable earthquake model (Shimazaki and Nakata, 1980), which holds that prior to rupture stresses are comparable to fault strength in many locations on the future rupture plane, with bits of variation. The stress/strength ratio is highest at some point, which is where the earthquake nucleates. This model does not require any special conditions or processes at the nucleation site; the whole fault is essentially ready for rupture at the same time. The fault tip stresses ensure that the rupture occurs as a single rapid earthquake, but the fact that fault tip stresses are high is not particularly relevant since the stress at most points does not need to be raised by much. Under this model it should technically be possible to forecast earthquakes based on the stress-renewaql concept, or estimates of when the fault as a whole will reach the critical stress level, a practice used in official hazard mapping (Field, 2008). This model also indicates that physical precursors may be present and detectable, since stresses are unusually high over a significant area before a large earthquake.

","language":"English","publisher":"Frontiers Media","doi":"10.3389/feart.2014.00020","usgsCitation":"Felzer, K., 2014, Pulverization provides a mechanism for the nucleation of earthquakes at low stress on strong faults: Frontiers in Earth Science, v. 2, Article 20; 4 p., https://doi.org/10.3389/feart.2014.00020.","productDescription":"Article 20; 4 p.","numberOfPages":"4","ipdsId":"IP-051871","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":472831,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/feart.2014.00020","text":"Publisher Index Page"},{"id":294921,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":294920,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.3389/feart.2014.00020"}],"volume":"2","noUsgsAuthors":false,"publicationDate":"2014-08-19","publicationStatus":"PW","scienceBaseUri":"542fbaa7e4b092f17df61d8c","contributors":{"authors":[{"text":"Felzer, Karen R.","contributorId":87471,"corporation":false,"usgs":true,"family":"Felzer","given":"Karen R.","affiliations":[],"preferred":false,"id":491995,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70132440,"text":"70132440 - 2014 - Performance and effects of land cover type on synthetic surface reflectance data and NDVI estimates for assessment and monitoring of semi-arid rangeland","interactions":[],"lastModifiedDate":"2020-12-31T16:51:48.214552","indexId":"70132440","displayToPublicDate":"2014-08-01T11:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2027,"text":"International Journal of Applied Earth Observation and Geoinformation","active":true,"publicationSubtype":{"id":10}},"title":"Performance and effects of land cover type on synthetic surface reflectance data and NDVI estimates for assessment and monitoring of semi-arid rangeland","docAbstract":"

Federal land management agencies provide stewardship over much of the rangelands in the arid andsemi-arid western United States, but they often lack data of the proper spatiotemporal resolution andextent needed to assess range conditions and monitor trends. Recent advances in the blending of com-plementary, remotely sensed data could provide public lands managers with the needed information.We applied the Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM) to five Landsat TMand concurrent Terra MODIS scenes, and used pixel-based regression and difference image analyses toevaluate the quality of synthetic reflectance and NDVI products associated with semi-arid rangeland. Pre-dicted red reflectance data consistently demonstrated higher accuracy, less bias, and stronger correlationwith observed data than did analogous near-infrared (NIR) data. The accuracy of both bands tended todecline as the lag between base and prediction dates increased; however, mean absolute errors (MAE)were typically ≤10%. The quality of area-wide NDVI estimates was less consistent than either spectra lband, although the MAE of estimates predicted using early season base pairs were ≤10% throughout the growing season. Correlation between known and predicted NDVI values and agreement with the 1:1regression line tended to decline as the prediction lag increased. Further analyses of NDVI predictions,based on a 22 June base pair and stratified by land cover/land use (LCLU), revealed accurate estimates through the growing season; however, inter-class performance varied. This work demonstrates the successful application of the STARFM algorithm to semi-arid rangeland; however, we encourage evaluation of STARFM’s performance on a per product basis, stratified by LCLU, with attention given to the influence of base pair selection and the impact of the time lag.

","language":"English","publisher":"Elsevier, Inc.","publisherLocation":"Amsterdam, Holland","doi":"10.1016/j.jag.2014.01.008","usgsCitation":"Olexa, E.M., and Lawrence, R.L., 2014, Performance and effects of land cover type on synthetic surface reflectance data and NDVI estimates for assessment and monitoring of semi-arid rangeland: International Journal of Applied Earth Observation and Geoinformation, v. 30, p. 30-41, https://doi.org/10.1016/j.jag.2014.01.008.","productDescription":"12 p.","startPage":"30","endPage":"41","numberOfPages":"12","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-050870","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":296058,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho, Utah, Wyoming","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -112.87353515625,\n 41.4509614012039\n ],\n [\n -110.379638671875,\n 40.455307212131494\n ],\n [\n -109.302978515625,\n 42.439674178149424\n ],\n [\n -111.90673828125,\n 43.5326204268101\n ],\n [\n -112.87353515625,\n 41.4509614012039\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"30","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5465d635e4b04d4b7dbd662b","contributors":{"authors":[{"text":"Olexa, Edward M. 0000-0002-2000-6798 eolexa@usgs.gov","orcid":"https://orcid.org/0000-0002-2000-6798","contributorId":4448,"corporation":false,"usgs":true,"family":"Olexa","given":"Edward","email":"eolexa@usgs.gov","middleInitial":"M.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":522880,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lawrence, Rick L","contributorId":127018,"corporation":false,"usgs":false,"family":"Lawrence","given":"Rick","email":"","middleInitial":"L","affiliations":[{"id":6765,"text":"Montana State University, Department of Land Resources and Environmental Sciences","active":true,"usgs":false}],"preferred":false,"id":522881,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70120476,"text":"70120476 - 2014 - Continuous estimation of baseflow in snowmelt-dominated streams and rivers in the Upper Colorado River Basin: A chemical hydrograph separation approach","interactions":[],"lastModifiedDate":"2017-01-03T14:56:27","indexId":"70120476","displayToPublicDate":"2014-08-01T10:45:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Continuous estimation of baseflow in snowmelt-dominated streams and rivers in the Upper Colorado River Basin: A chemical hydrograph separation approach","docAbstract":"

Effective science-based management of water resources in large basins requires a qualitative understanding of hydrologic conditions and quantitative measures of the various components of the water budget, including difficult to measure components such as baseflow discharge to streams. Using widely available discharge and continuously collected specific conductance (SC) data, we adapted and applied a long established chemical hydrograph separation approach to quantify daily and representative annual baseflow discharge at fourteen streams and rivers at large spatial (> 1,000 km2 watersheds) and temporal (up to 37 years) scales in the Upper Colorado River Basin. On average, annual baseflow was 21-58% of annual stream discharge, 13-45% of discharge during snowmelt, and 40-86% of discharge during low-flow conditions. Results suggest that reservoirs may act to store baseflow discharged to the stream during snowmelt and release that baseflow during low-flow conditions, and that irrigation return flows may contribute to increases in fall baseflow in heavily irrigated watersheds. The chemical hydrograph separation approach, and associated conceptual model defined here provide a basis for the identification of land use, management, and climate effects on baseflow.

","language":"English","publisher":"American Geophysical Union","publisherLocation":"Washington, D.C.","doi":"10.1002/2013WR014939","usgsCitation":"Miller, M.P., Susong, D.D., Shope, C.L., Heilweil, V.M., and Stolp, B.J., 2014, Continuous estimation of baseflow in snowmelt-dominated streams and rivers in the Upper Colorado River Basin: A chemical hydrograph separation approach: Water Resources Research, v. 50, no. 8, p. 6986-6999, https://doi.org/10.1002/2013WR014939.","productDescription":"14 p.","startPage":"6986","endPage":"6999","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-052142","costCenters":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"links":[{"id":472837,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2013wr014939","text":"Publisher Index Page"},{"id":292271,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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ddsusong@usgs.gov","contributorId":1040,"corporation":false,"usgs":true,"family":"Susong","given":"David","email":"ddsusong@usgs.gov","middleInitial":"D.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":498273,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shope, Christopher L. cshope@usgs.gov","contributorId":5016,"corporation":false,"usgs":true,"family":"Shope","given":"Christopher","email":"cshope@usgs.gov","middleInitial":"L.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":498275,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Heilweil, Victor M. heilweil@usgs.gov","contributorId":837,"corporation":false,"usgs":true,"family":"Heilweil","given":"Victor","email":"heilweil@usgs.gov","middleInitial":"M.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":498271,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Stolp, Bernard J. 0000-0003-3803-1497 bjstolp@usgs.gov","orcid":"https://orcid.org/0000-0003-3803-1497","contributorId":963,"corporation":false,"usgs":true,"family":"Stolp","given":"Bernard","email":"bjstolp@usgs.gov","middleInitial":"J.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":498272,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70129258,"text":"70129258 - 2014 - Analytical solutions for benchmarking cold regions subsurface water flow and energy transport models: one-dimensional soil thaw with conduction and advection","interactions":[],"lastModifiedDate":"2014-10-21T09:58:21","indexId":"70129258","displayToPublicDate":"2014-08-01T09:57:38","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":664,"text":"Advances in Water Resources","active":true,"publicationSubtype":{"id":10}},"title":"Analytical solutions for benchmarking cold regions subsurface water flow and energy transport models: one-dimensional soil thaw with conduction and advection","docAbstract":"Numerous cold regions water flow and energy transport models have emerged in recent years. Dissimilarities often exist in their mathematical formulations and/or numerical solution techniques, but few analytical solutions exist for benchmarking flow and energy transport models that include pore water phase change. This paper presents a detailed derivation of the Lunardini solution, an approximate analytical solution for predicting soil thawing subject to conduction, advection, and phase change. Fifteen thawing scenarios are examined by considering differences in porosity, surface temperature, Darcy velocity, and initial temperature. The accuracy of the Lunardini solution is shown to be proportional to the Stefan number. The analytical solution results obtained for soil thawing scenarios with water flow and advection are compared to those obtained from the finite element model SUTRA. Three problems, two involving the Lunardini solution and one involving the classic Neumann solution, are recommended as standard benchmarks for future model development and testing.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Advances in Water Resources","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier Science Ltd.","publisherLocation":"England","doi":"10.1016/j.advwatres.2014.05.005","usgsCitation":"Kurylyk, B.L., McKenzie, J.M., MacQuarrie, K., and Voss, C.I., 2014, Analytical solutions for benchmarking cold regions subsurface water flow and energy transport models: one-dimensional soil thaw with conduction and advection: Advances in Water Resources, v. 70, p. 172-184, https://doi.org/10.1016/j.advwatres.2014.05.005.","productDescription":"13 p.","startPage":"172","endPage":"184","numberOfPages":"13","ipdsId":"IP-056692","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"links":[{"id":295518,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":295517,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.advwatres.2014.05.005"},{"id":295493,"type":{"id":15,"text":"Index Page"},"url":"https://www.sciencedirect.com/science/article/pii/S0309170814000992"}],"volume":"70","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"544775a3e4b0f888a81b82f2","contributors":{"authors":[{"text":"Kurylyk, Barret L.","contributorId":78262,"corporation":false,"usgs":true,"family":"Kurylyk","given":"Barret","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":503584,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McKenzie, Jeffrey M","contributorId":36476,"corporation":false,"usgs":true,"family":"McKenzie","given":"Jeffrey","email":"","middleInitial":"M","affiliations":[],"preferred":false,"id":503583,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"MacQuarrie, Kerry T. B.","contributorId":85525,"corporation":false,"usgs":true,"family":"MacQuarrie","given":"Kerry T. B.","affiliations":[],"preferred":false,"id":503585,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Voss, Clifford I. 0000-0001-5923-2752 cvoss@usgs.gov","orcid":"https://orcid.org/0000-0001-5923-2752","contributorId":1559,"corporation":false,"usgs":true,"family":"Voss","given":"Clifford","email":"cvoss@usgs.gov","middleInitial":"I.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":503582,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70129219,"text":"70129219 - 2014 - A mass balance approach to investigating geochemical controls on secondary water quality impacts at a crude oil spill site near Bemidji, MN","interactions":[],"lastModifiedDate":"2018-09-14T16:48:05","indexId":"70129219","displayToPublicDate":"2014-08-01T09:52:17","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2233,"text":"Journal of Contaminant Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"A mass balance approach to investigating geochemical controls on secondary water quality impacts at a crude oil spill site near Bemidji, MN","docAbstract":"

Secondary water quality impacts can result from a broad range of coupled reactions triggered by primary groundwater contaminants. Data from a crude-oil spill research site near Bemidji, MN provide an ideal test case for investigating the complex interactions controlling secondary impacts, including depleted dissolved oxygen and elevated organic carbon, inorganic carbon, CH4, Mn, Fe, and other dissolved ions. To better understand these secondary impacts, this study began with an extensive data compilation of various data types, comprising aqueous, sediment, gas, and oil phases, covering a 260 m cross-sectional domain over 30 years. Mass balance calculations are used to quantify pathways that control secondary components, by using the data to constrain the sources and sinks for the important redox processes. The results show that oil constituents other than BTEX (benzene, toluene, ethylbenzene, o-, m- and p-xylenes), including n-alkanes and other aromatic compounds, play significant roles in plume evolution and secondary water quality impacts. The analysis underscores previous results on the importance of non-aqueous phases. Over 99.9% of the Fe2+ plume is attenuated by immobilization on sediments as Fe(II) and 85–95% of the carbon biodegradation products are outgassed. Gaps identified in carbon and Fe mass balances and in pH buffering mechanisms are used to formulate a new conceptual model. This new model includes direct out-gassing of CH4 and CO2 from organic carbon biodegradation, dissolution of directly produced CO2, and sorption with H+ exchange to improve pH buffering. The identification of these mechanisms extends understanding of natural attenuation of potential secondary impacts at enhanced reductive dechlorination sites, particularly for reduced Fe plumes, produced CH4, and pH perturbations.

","language":"English","publisher":"Elsevier Science","publisherLocation":"Amsterdam","doi":"10.1016/j.jconhyd.2014.04.006","usgsCitation":"Ng, G., Bekins, B.A., Cozzarelli, I.M., Baedecker, M., Bennett, P.C., and Amos, R.T., 2014, A mass balance approach to investigating geochemical controls on secondary water quality impacts at a crude oil spill site near Bemidji, MN: Journal of Contaminant Hydrology, v. 164, p. 1-15, https://doi.org/10.1016/j.jconhyd.2014.04.006.","productDescription":"15 p.","startPage":"1","endPage":"15","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-053326","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":472841,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jconhyd.2014.04.006","text":"Publisher Index Page"},{"id":295516,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":295484,"rank":1,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.jconhyd.2014.04.006"}],"country":"United States","state":"Minnesota","city":"Bemidji","volume":"164","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5447759ae4b0f888a81b82e8","chorus":{"doi":"10.1016/j.jconhyd.2014.04.006","url":"http://dx.doi.org/10.1016/j.jconhyd.2014.04.006","publisher":"Elsevier BV","authors":"Ng G.-H. Crystal, Bekins Barbara A., Cozzarelli Isabelle M., Baedecker Mary Jo, Bennett Philip C., Amos Richard T.","journalName":"Journal of Contaminant Hydrology","publicationDate":"8/2014","auditedOn":"7/24/2015","publiclyAccessibleDate":"5/24/2014"},"contributors":{"authors":[{"text":"Ng, Gene-Hua Crystal","contributorId":7212,"corporation":false,"usgs":true,"family":"Ng","given":"Gene-Hua Crystal","affiliations":[],"preferred":false,"id":503556,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bekins, Barbara A. 0000-0002-1411-6018 babekins@usgs.gov","orcid":"https://orcid.org/0000-0002-1411-6018","contributorId":1348,"corporation":false,"usgs":true,"family":"Bekins","given":"Barbara","email":"babekins@usgs.gov","middleInitial":"A.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":503554,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cozzarelli, Isabelle M. 0000-0002-5123-1007 icozzare@usgs.gov","orcid":"https://orcid.org/0000-0002-5123-1007","contributorId":1693,"corporation":false,"usgs":true,"family":"Cozzarelli","given":"Isabelle","email":"icozzare@usgs.gov","middleInitial":"M.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"preferred":true,"id":503555,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Baedecker, Mary Jo","contributorId":68671,"corporation":false,"usgs":true,"family":"Baedecker","given":"Mary Jo","affiliations":[],"preferred":false,"id":503558,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bennett, Philip C.","contributorId":30567,"corporation":false,"usgs":true,"family":"Bennett","given":"Philip","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":503557,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Amos, Richard T.","contributorId":69081,"corporation":false,"usgs":true,"family":"Amos","given":"Richard","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":503559,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70129548,"text":"70129548 - 2014 - Major element and oxygen isotope geochemistry of vapour-phase garnet from the Topopah Spring Tuff at Yucca Mountain, Nevada, USA","interactions":[],"lastModifiedDate":"2016-05-05T12:40:44","indexId":"70129548","displayToPublicDate":"2014-08-01T09:41:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2748,"text":"Mineralogical Magazine","active":true,"publicationSubtype":{"id":10}},"title":"Major element and oxygen isotope geochemistry of vapour-phase garnet from the Topopah Spring Tuff at Yucca Mountain, Nevada, USA","docAbstract":"

Twenty vapour-phase garnets were studied in two samples of the Topopah Spring Tuff of the Paintbrush Group from Yucca Mountain, in southern Nevada. The Miocene-age Topopah Spring Tuff is a 350 m thick, devitrified, moderately to densely welded ash-flow tuff that is zoned compositionally from high-silica rhyolite to latite. During cooling of the tuff, escaping vapour produced lithophysae (former gas cavities) lined with an assemblage of tridymite (commonly inverted to cristobalite or quartz), sanidine and locally, hematite and/or garnet. Vapour-phase topaz and economic deposits associated commonly with topaz-bearing rhyolites (characteristically enriched in F) were not found in the Topopah Spring Tuff at Yucca Mountain. Based on their occurrence only in lithophysae, the garnets are not primary igneous phenocrysts, but rather crystals that grew from a F-poor magma-derived vapour trapped during and after emplacement of the tuff. The garnets are euhedral, vitreous, reddish brown, trapezohedral, as large as 2 mm in diameter and fractured. The garnets also contain inclusions of tridymite. Electron microprobe analyses of the garnets reveal that they are almandine-spessartine (48.0 and 47.9 mol.%, respectively), have an average composition of (Fe1.46Mn1.45Mg0.03Ca0.10)(Al1.93Ti0.02)Si3.01O12 and are comparatively homogeneous in Fe and Mn concentrations from core to rim. Composited garnets from each sample site have δ18O values of 7.2 and 7.4‰. The associated quartz (after tridymite) has δ18O values of 17.4 and 17.6‰, values indicative of reaction with later, low-temperature water. Unaltered tridymite from higher in the stratigraphic section has a δ18O of 11.1‰ which, when coupled with the garnet δ18O values in a quartz-garnet fractionation equation, indicates isotopic equilibration (vapour-phase crystallization) at temperatures of ~600°C. This high-temperature mineralization, formed during cooling of the tuffs, is distinct from the later and commonly recognized low-temperature stage (generally 50–70°C) of calcite, quartz and opal secondary mineralization, formed from downward-percolating meteoric water, that locally coats fracture footwalls and lithophysal floors.

","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Mineralogical Magazine","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"The Mineralogical Society of Great Britain and Ireland","doi":"10.1180/minmag.2014.078.4.14","usgsCitation":"Moscati, R.J., and Johnson, C.A., 2014, Major element and oxygen isotope geochemistry of vapour-phase garnet from the Topopah Spring Tuff at Yucca Mountain, Nevada, USA: Mineralogical Magazine, v. 78, no. 4, p. 1029-1041, https://doi.org/10.1180/minmag.2014.078.4.14.","productDescription":"13 p.","startPage":"1029","endPage":"1041","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-052493","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":295710,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":295658,"rank":1,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1180/minmag.2014.078.4.14"}],"country":"United States","state":"Nevada","otherGeospatial":"Yucca Mountain","volume":"78","issue":"4","noUsgsAuthors":false,"publicationDate":"2018-07-05","publicationStatus":"PW","scienceBaseUri":"544b6a2ae4b03653c63fb1d8","contributors":{"authors":[{"text":"Moscati, Richard J. 0000-0002-0818-4401 rmoscati@usgs.gov","orcid":"https://orcid.org/0000-0002-0818-4401","contributorId":2462,"corporation":false,"usgs":true,"family":"Moscati","given":"Richard","email":"rmoscati@usgs.gov","middleInitial":"J.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":503808,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Johnson, Craig A. 0000-0002-1334-2996 cjohnso@usgs.gov","orcid":"https://orcid.org/0000-0002-1334-2996","contributorId":909,"corporation":false,"usgs":true,"family":"Johnson","given":"Craig","email":"cjohnso@usgs.gov","middleInitial":"A.","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":503807,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70120181,"text":"70120181 - 2014 - Time-averaged discharge rate of subaerial lava at Kīlauea Volcano, Hawai‘i, measured from TanDEM-X interferometry: Implications for magma supply and storage during 2011-2013","interactions":[],"lastModifiedDate":"2019-03-13T15:06:08","indexId":"70120181","displayToPublicDate":"2014-08-01T08:51:24","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2314,"text":"Journal of Geophysical Research B: Solid Earth","active":true,"publicationSubtype":{"id":10}},"title":"Time-averaged discharge rate of subaerial lava at Kīlauea Volcano, Hawai‘i, measured from TanDEM-X interferometry: Implications for magma supply and storage during 2011-2013","docAbstract":"

Differencing digital elevation models (DEMs) derived from TerraSAR add-on for Digital Elevation Measurements (TanDEM-X) synthetic aperture radar imagery provides a measurement of elevation change over time. On the East Rift Zone (EZR) of Kīlauea Volcano, Hawai‘i, the effusion of lava causes changes in topography. When these elevation changes are summed over the area of an active lava flow, it is possible to quantify the volume of lava emplaced at the surface during the time spanned by the TanDEM-X data—a parameter that can be difficult to measure across the entirety of an ~100 km2 lava flow field using ground-based techniques or optical remote sensing data. Based on the differences between multiple TanDEM-X-derived DEMs collected days to weeks apart, the mean dense-rock equivalent time-averaged discharge rate of lava at Kīlauea between mid-2011 and mid-2013 was approximately 2 m3/s, which is about half the long-term average rate over the course of Kīlauea's 1983–present ERZ eruption. This result implies that there was an increase in the proportion of lava stored versus erupted, a decrease in the rate of magma supply to the volcano, or some combination of both during this time period. In addition to constraining the time-averaged discharge rate of lava and the rates of magma supply and storage, topographic change maps derived from space-based TanDEM-X data provide insights into the four-dimensional evolution of Kīlauea's ERZ lava flow field. TanDEM-X data are a valuable complement to other space-, air-, and ground-based observations of eruptive activity at Kīlauea and offer great promise at locations around the world for aiding with monitoring not just volcanic eruptions but any hazardous activity that results in surface change, including landslides, floods, earthquakes, and other natural and anthropogenic processes.

","language":"English","publisher":"American Geophysical Union","publisherLocation":"Richmond, VA","doi":"10.1002/2014JB011132","usgsCitation":"Poland, M., 2014, Time-averaged discharge rate of subaerial lava at Kīlauea Volcano, Hawai‘i, measured from TanDEM-X interferometry: Implications for magma supply and storage during 2011-2013: Journal of Geophysical Research B: Solid Earth, v. 119, no. 7, p. 5464-5481, https://doi.org/10.1002/2014JB011132.","productDescription":"18 p.","startPage":"5464","endPage":"5481","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-055642","costCenters":[{"id":336,"text":"Hawaiian Volcano Observatory","active":false,"usgs":true},{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":292052,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawai'i","otherGeospatial":"Kilauea Volcano","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -155.303007,19.410477 ], [ -155.303007,19.431523 ], [ -155.270993,19.431523 ], [ -155.270993,19.410477 ], [ -155.303007,19.410477 ] ] ] } } ] }","volume":"119","issue":"7","noUsgsAuthors":false,"publicationDate":"2014-07-29","publicationStatus":"PW","scienceBaseUri":"53ec7bd4e4b02bf5a76740c0","contributors":{"authors":[{"text":"Poland, Michael P. 0000-0001-5240-6123 mpoland@usgs.gov","orcid":"https://orcid.org/0000-0001-5240-6123","contributorId":635,"corporation":false,"usgs":true,"family":"Poland","given":"Michael P.","email":"mpoland@usgs.gov","affiliations":[{"id":336,"text":"Hawaiian Volcano Observatory","active":false,"usgs":true}],"preferred":false,"id":497965,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70118652,"text":"70118652 - 2014 - Emplacement and erosive effects of the south Kasei Valles lava on Mars","interactions":[],"lastModifiedDate":"2018-11-08T16:14:33","indexId":"70118652","displayToPublicDate":"2014-08-01T08:43:21","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2499,"text":"Journal of Volcanology and Geothermal Research","active":true,"publicationSubtype":{"id":10}},"title":"Emplacement and erosive effects of the south Kasei Valles lava on Mars","docAbstract":"Although it has generally been accepted that the Martian outflow channels were carved by floods of water, observations of large channels on Venus and Mercury demonstrate that lava flows can cause substantial erosion. Recent observations of large lava flows within outflow channels on Mars have revived discussion of the hypothesis that the Martian channels are also produced by lava. An excellent example is found in south Kasei Valles (SKV), where the most recent major event was emplacement of a large lava flow. Calculations using high-resolution Digital Terrain Models (DTMs) demonstrate that this flow was locally turbulent, similar to a previously described flood lava flow in Athabasca Valles. The modeled peak local flux of approximately 106 m3 s−1 was approximately an order of magnitude lower than that in Athabasca, which may be due to distance from the vent. Fluxes close to 107 m3 s−1 are estimated in some reaches but these values are probably records of local surges caused by a dam-breach event within the flow. The SKV lava was locally erosive and likely caused significant (kilometer-scale) headwall retreat at several cataracts with tens to hundreds of meters of relief. However, in other places the net effect of the flow was unambiguously aggradational, and these are more representative of most of the flow. The larger outflow channels have lengths of thousands of kilometers and incision of a kilometer or more. Therefore, lava flows comparable to the SKV flow did not carve the major Martian outflow channels, although the SKV flow was among the largest and highest-flux lava flows known in the Solar System.","language":"English","publisher":"Elsevier","doi":"10.1016/j.jvolgeores.2014.06.005","usgsCitation":"Dundas, C.M., and Keszthelyi, L., 2014, Emplacement and erosive effects of the south Kasei Valles lava on Mars: Journal of Volcanology and Geothermal Research, v. 282, p. 92-102, https://doi.org/10.1016/j.jvolgeores.2014.06.005.","productDescription":"11 p.","startPage":"92","endPage":"102","numberOfPages":"11","ipdsId":"IP-053692","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":291369,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Kasei Valley, Mars","volume":"282","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53dc9baee4b076157862d961","contributors":{"authors":[{"text":"Dundas, Colin M. 0000-0003-2343-7224 cdundas@usgs.gov","orcid":"https://orcid.org/0000-0003-2343-7224","contributorId":2937,"corporation":false,"usgs":true,"family":"Dundas","given":"Colin","email":"cdundas@usgs.gov","middleInitial":"M.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":497164,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Keszthelyi, Laszlo P. 0000-0003-1879-4331 laz@usgs.gov","orcid":"https://orcid.org/0000-0003-1879-4331","contributorId":52802,"corporation":false,"usgs":true,"family":"Keszthelyi","given":"Laszlo P.","email":"laz@usgs.gov","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":497165,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70118564,"text":"ofr20141165 - 2014 - A hierarchical integrated population model for greater sage-grouse (Centrocercus urophasianus) in the Bi-State Distinct Population Segment, California and Nevada","interactions":[],"lastModifiedDate":"2014-08-01T09:36:09","indexId":"ofr20141165","displayToPublicDate":"2014-08-01T08:36:00","publicationYear":"2014","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":"2014-1165","title":"A hierarchical integrated population model for greater sage-grouse (Centrocercus urophasianus) in the Bi-State Distinct Population Segment, California and Nevada","docAbstract":"

Greater sage-grouse (Centrocercus urophasianus, hereafter referred to as “sage-grouse”) are endemic to sagebrush (Artemisia spp.) ecosystems throughout Western North America. Populations of sage-grouse have declined in distribution and abundance across the range of the species (Schroeder and others, 2004; Knick and Connelly, 2011), largely as a result of human disruption of sagebrush communities (Knick and Connelly, 2011). The Bi-State Distinct Population Segment (DPS) represents sage-grouse populations that are geographically isolated and genetically distinct (Benedict and others, 2003; Oyler-McCance and others, 2005) and that are present at the extreme southwestern distribution of the sage-grouse range (Schroeder and others, 2004), straddling the border of California and Nevada. Subpopulations of sage-grouse in the DPS may be at increased risk of extirpation because of a substantial loss of sagebrush habitat and lack of connectivity (Oyler-McCance and others, 2005). Sage-grouse in the Bi-State DPS represent small, localized breeding populations distributed across 18,325 km2.

\n
\n

The U.S. Fish and Wildlife Service currently (2014) is evaluating the Bi-State DPS as threatened or endangered under the Endangered Species Act of 1973, independent of other sage-grouse populations. This DPS was designated as a higher priority for listing than sage-grouse in other parts of the species’ range (U.S. Department of the Interior, 2010). Range-wide population analyses for sage-grouse have included portions of the Bi-State DPS (Sage and Columbian Sharp-tailed Grouse Technical Committee 2008; Garton and others, 2011). Although these analyses are informative, the underlying data only represent a portion of the DPS and are comprised of lek count observations only. A thorough examination of population dynamics and persistence that includes multiple subpopulations and represents the majority of the DPS is largely lacking. Furthermore, fundamental information on population growth rate (i.e., finite rate of change, λ) and specific demographic parameters that explain sources of variation in λ within different subpopulations would be valuable for making conservation and management decisions for this DPS.

\n
\n

During 2003–12, agencies and universities collaborated to conduct extensive monitoring of sage-grouse populations within the Bi-State DPS. Data regarding lek attendance, movement, and survival of sage-grouse across multiple life stages were documented. Specifically, sage-grouse from nearly all subpopulations were marked and tracked across multiple seasons using radio-telemetry techniques. A hierarchical integrated population modeling (IPM) approach was used to derive demographic parameters for the Bi-State DPS using the large amount of data collected over a 10-year period. This modeling approach allows integration of multiple data sources to inform population growth rates and population vital rates for the Bi-State DPS overall, as well as for individual subpopulations. These models are more informative than other models because they integrate inputs of demographic data (for example, survival and fecundity rates) and survey data (for example, lek observations). The findings here will help characterize population growth rates within the Bi-State DPS.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20141165","collaboration":"Prepared in cooperation with the Bureau of Land Management, Nevada Department of Wildlife, and U.S. Fish and Wildlife Service","usgsCitation":"Coates, P.S., Halstead, B., Blomberg, E.J., Brussee, B., Howe, K., Wiechman, L., Tebbenkamp, J., Reese, K.P., Gardner, S., and Casazza, M.L., 2014, A hierarchical integrated population model for greater sage-grouse (Centrocercus urophasianus) in the Bi-State Distinct Population Segment, California and Nevada: U.S. Geological Survey Open-File Report 2014-1165, iv, 34 p., https://doi.org/10.3133/ofr20141165.","productDescription":"iv, 34 p.","numberOfPages":"42","onlineOnly":"Y","ipdsId":"IP-057936","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":291511,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20141165.jpg"},{"id":291500,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2014/1165/"},{"id":291504,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2014/1165/pdf/ofr2014-1165.pdf"}],"country":"United States","state":"California;Nevada","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -124.41,32.39 ], [ -124.41,42.01 ], [ -113.96,42.01 ], [ -113.96,32.39 ], [ -124.41,32.39 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53dc9baee4b076157862d957","contributors":{"authors":[{"text":"Coates, Peter S. 0000-0003-2672-9994 pcoates@usgs.gov","orcid":"https://orcid.org/0000-0003-2672-9994","contributorId":3263,"corporation":false,"usgs":true,"family":"Coates","given":"Peter","email":"pcoates@usgs.gov","middleInitial":"S.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":497039,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Halstead, Brian J. 0000-0002-5535-6528 bhalstead@usgs.gov","orcid":"https://orcid.org/0000-0002-5535-6528","contributorId":3051,"corporation":false,"usgs":true,"family":"Halstead","given":"Brian J.","email":"bhalstead@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":497038,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Blomberg, Erik J.","contributorId":17543,"corporation":false,"usgs":false,"family":"Blomberg","given":"Erik","email":"","middleInitial":"J.","affiliations":[{"id":7063,"text":"University of Maine","active":true,"usgs":false}],"preferred":false,"id":497040,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brussee, Brianne","contributorId":62152,"corporation":false,"usgs":true,"family":"Brussee","given":"Brianne","affiliations":[],"preferred":false,"id":497043,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Howe, Kristy B.","contributorId":59354,"corporation":false,"usgs":true,"family":"Howe","given":"Kristy B.","affiliations":[],"preferred":false,"id":497042,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wiechman, Lief","contributorId":108039,"corporation":false,"usgs":true,"family":"Wiechman","given":"Lief","affiliations":[],"preferred":false,"id":497046,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Tebbenkamp, Joel","contributorId":25089,"corporation":false,"usgs":true,"family":"Tebbenkamp","given":"Joel","email":"","affiliations":[],"preferred":false,"id":497041,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Reese, Kerry P.","contributorId":70254,"corporation":false,"usgs":true,"family":"Reese","given":"Kerry","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":497044,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Gardner, Scott C.","contributorId":80206,"corporation":false,"usgs":true,"family":"Gardner","given":"Scott C.","affiliations":[],"preferred":false,"id":497045,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Casazza, Michael L. 0000-0002-5636-735X mike_casazza@usgs.gov","orcid":"https://orcid.org/0000-0002-5636-735X","contributorId":2091,"corporation":false,"usgs":true,"family":"Casazza","given":"Michael","email":"mike_casazza@usgs.gov","middleInitial":"L.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":497037,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70118141,"text":"ofr20141163 - 2014 - Spatially explicit modeling of greater sage-grouse (Centrocercus urophasianus) habitat in Nevada and northeastern California: a decision-support tool for management","interactions":[],"lastModifiedDate":"2014-08-01T08:43:10","indexId":"ofr20141163","displayToPublicDate":"2014-08-01T08:22:00","publicationYear":"2014","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":"2014-1163","title":"Spatially explicit modeling of greater sage-grouse (Centrocercus urophasianus) habitat in Nevada and northeastern California: a decision-support tool for management","docAbstract":"Greater sage-grouse (Centrocercus urophasianus, hereafter referred to as “sage-grouse”) populations are declining throughout the sagebrush (Artemisia spp.) ecosystem, including millions of acres of potential habitat across the West. Habitat maps derived from empirical data are needed given impending listing decisions that will affect both sage-grouse population dynamics and human land-use restrictions. This report presents the process for developing spatially explicit maps describing relative habitat suitability for sage-grouse in Nevada and northeastern California. Maps depicting habitat suitability indices (HSI) values were generated based on model-averaged resource selection functions informed by more than 31,000 independent telemetry locations from more than 1,500 radio-marked sage-grouse across 12 project areas in Nevada and northeastern California collected during a 15-year period (1998–2013). Modeled habitat covariates included land cover composition, water resources, habitat configuration, elevation, and topography, each at multiple spatial scales that were relevant to empirically observed sage-grouse movement patterns. We then present an example of how the HSI can be delineated into categories. Specifically, we demonstrate that the deviation from the mean can be used to classify habitat suitability into three categories of habitat quality (high, moderate, and low) and one non-habitat category. The classification resulted in an agreement of 93–97 percent for habitat versus non-habitat across a suite of independent validation datasets. Lastly, we provide an example of how space use models can be integrated with habitat models to help inform conservation planning. In this example, we combined probabilistic breeding density with a non-linear probability of occurrence relative to distance to nearest lek (traditional breeding ground) using count data to calculate a composite space use index (SUI). The SUI was then classified into two categories of use (high and low-to-no) and intersected with the HSI categories to create potential management prioritization scenarios based oninformation about sage-grouse occupancy coupled with habitat suitability. This provided an example of a conservation planning application that uses the intersection of the spatially-explicit HSI and empirically-based SUI to identify potential spatially explicit strategies for sage-grouse management. Importantly, the reported categories for the HSI and SUI can be reclassified relatively easily to employ alternative conservation thresholds that may be identified through decision-making processes with stake-holders, managers, and biologists. Moreover, the HSI/SUI interface map can be updated readily as new data become available.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20141163","collaboration":"Prepared in cooperation with the State of Nevada Sagebrush Ecosystem Program, Bureau of Land Management, Nevada Department of Wildlife, and California Department of Fish and Wildlife","usgsCitation":"Coates, P.S., Casazza, M.L., Brussee, B.E., Ricca, M., Gustafson, K., Overton, C.T., Sanchez-Chopitea, E., Kroger, T., Mauch, K., Niell, L., Howe, K., Gardner, S., Espinosa, S., and Delehanty, D.J., 2014, Spatially explicit modeling of greater sage-grouse (Centrocercus urophasianus) habitat in Nevada and northeastern California: a decision-support tool for management: U.S. Geological Survey Open-File Report 2014-1163, vi, 83 p., https://doi.org/10.3133/ofr20141163.","productDescription":"vi, 83 p.","numberOfPages":"93","onlineOnly":"Y","ipdsId":"IP-058087","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":438749,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P99E64Y4","text":"USGS data release","linkHelpText":"Spatially Explicit Modeling of Annual and Seasonal Habitat for Greater Sage-Grouse (Centrocercus urophasianus) in Northeastern California"},{"id":291503,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20141163.jpg"},{"id":291499,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2014/1163/"},{"id":291502,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2014/1163/pdf/ofr2014-1163.pdf"}],"country":"United States","state":"California;Nevada","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -122.0,35.0 ], [ -122.0,42.0 ], [ -114.04,42.0 ], [ -114.04,35.0 ], [ -122.0,35.0 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53dc9bafe4b076157862d968","contributors":{"authors":[{"text":"Coates, Peter S. 0000-0003-2672-9994 pcoates@usgs.gov","orcid":"https://orcid.org/0000-0003-2672-9994","contributorId":3263,"corporation":false,"usgs":true,"family":"Coates","given":"Peter","email":"pcoates@usgs.gov","middleInitial":"S.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":496455,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Casazza, Michael L. 0000-0002-5636-735X mike_casazza@usgs.gov","orcid":"https://orcid.org/0000-0002-5636-735X","contributorId":2091,"corporation":false,"usgs":true,"family":"Casazza","given":"Michael","email":"mike_casazza@usgs.gov","middleInitial":"L.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":496453,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brussee, Brianne E. 0000-0002-2452-7101 bbrussee@usgs.gov","orcid":"https://orcid.org/0000-0002-2452-7101","contributorId":4249,"corporation":false,"usgs":true,"family":"Brussee","given":"Brianne","email":"bbrussee@usgs.gov","middleInitial":"E.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":496456,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ricca, Mark A.","contributorId":39736,"corporation":false,"usgs":true,"family":"Ricca","given":"Mark A.","affiliations":[],"preferred":false,"id":496461,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gustafson, K. Benjamin","contributorId":53710,"corporation":false,"usgs":true,"family":"Gustafson","given":"K. Benjamin","affiliations":[],"preferred":false,"id":496462,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Overton, Cory T. 0000-0002-5060-7447 coverton@usgs.gov","orcid":"https://orcid.org/0000-0002-5060-7447","contributorId":3262,"corporation":false,"usgs":true,"family":"Overton","given":"Cory","email":"coverton@usgs.gov","middleInitial":"T.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":496454,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Sanchez-Chopitea, Erika","contributorId":23462,"corporation":false,"usgs":true,"family":"Sanchez-Chopitea","given":"Erika","affiliations":[],"preferred":false,"id":496458,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Kroger, Travis","contributorId":38483,"corporation":false,"usgs":true,"family":"Kroger","given":"Travis","affiliations":[],"preferred":false,"id":496460,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Mauch, Kimberly","contributorId":91796,"corporation":false,"usgs":true,"family":"Mauch","given":"Kimberly","affiliations":[],"preferred":false,"id":496466,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Niell, Lara","contributorId":30557,"corporation":false,"usgs":true,"family":"Niell","given":"Lara","affiliations":[],"preferred":false,"id":496459,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Howe, Kristy","contributorId":79815,"corporation":false,"usgs":true,"family":"Howe","given":"Kristy","affiliations":[],"preferred":false,"id":496463,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Gardner, Scott","contributorId":82627,"corporation":false,"usgs":true,"family":"Gardner","given":"Scott","affiliations":[],"preferred":false,"id":496465,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Espinosa, Shawn","contributorId":20253,"corporation":false,"usgs":true,"family":"Espinosa","given":"Shawn","affiliations":[],"preferred":false,"id":496457,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Delehanty, David J.","contributorId":80811,"corporation":false,"usgs":true,"family":"Delehanty","given":"David","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":496464,"contributorType":{"id":1,"text":"Authors"},"rank":14}]}} ,{"id":70135874,"text":"70135874 - 2014 - Causal networks clarify productivity-richness interrelations, bivariate plots do not","interactions":[],"lastModifiedDate":"2014-12-18T11:33:46","indexId":"70135874","displayToPublicDate":"2014-08-01T01:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1711,"text":"Functional Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Causal networks clarify productivity-richness interrelations, bivariate plots do not","docAbstract":"
    \n
  1. Perhaps no other pair of variables in ecology has generated as much discussion as species richness and ecosystem productivity, as illustrated by the reactions by Pierce (2013) and others to Adler et al.'s (2011) report that empirical patterns are weak and inconsistent. Adler et al. (2011) argued we need to move beyond a focus on simplistic bivariate relationships and test mechanistic, multivariate causal hypotheses. We feel the continuing debate over productivity–richness relationships (PRRs) provides a focused context for illustrating the fundamental difficulties of using bivariate relationships to gain scientific understanding.
    2. \n
  2. Pierce (2013) disputes Adler et al.'s (2011) conclusion that bivariate productivity–richness relationships (PRRs) are ‘weak and variable’. He argues, instead, that relationships in the Adler et al. data are actually strong and, further, that failure to adhere to the humped-back model (HBM; sensu Grime 1979) threatens scientists' ability to advise conservationists. Here, we show that Pierce's reanalyses are invalid, that statistically significant boundary relations in the Adler et al. data are difficult to detect when proper methods are used and that his advice neither advances scientific understanding nor provides the quantitative forecasts actually needed by decision makers.
    3. \n
  3. We begin by examining Grimes' HBM through the lens of causal networks. We first translate the ideas contained in the HBM into a causal diagram, which shows explicitly how multiple processes are hypothesized to control biomass production and richness and their interrelationship. We then evaluate the causal diagram using structural equation modelling and example data from a published study of meadows in Finland. Formal analysis rejects the literal translation of the HBM and reveals additional processes at work. This exercise shows how the practice of abstracting systems as causal networks (i) clarifies possible hypotheses, (ii) permits explicit testing and (iii) provides more powerful and useful predictions.
    4. \n
  4. Building on the Finnish meadow example, we contrast the utility of bivariate plots compared with structural equation models for investigating underlying processes. Simulations illustrate the fallibility of bivariate analysis as a means of supporting one theory over another, while models based on causal networks can quantify the sensitivity of diversity patterns to both management and natural constraints.
    5. \n
  5. A key piece of Pierce's critique of Adler et al.'s conclusions relies on upper boundary regression which he claims to reveal strong relationships between production and richness in Adler et al.'s original data. We demonstrate that this technique shows strong associations in purely random data and is invalid for Adler et al.'s data because it depends on a uniform data distribution. We instead perform quantile regression on both the site-level summaries of the data and the plot-level data (using mixed-model quantile regression). Using a variety of nonlinear curve-fitting approaches, we were unable to detect a significant humped-shape boundary in the Adler et al. data. We reiterate that the bivariate productivity–richness relationships in Adler et al.'s data are weak and variable.
    6. \n
  6. We urge ecologists to consider productivity–richness relationships through the lens of causal networks to advance our understanding beyond bivariate analysis. Further, we emphasize that models based on a causal network conceptualization can also provide more meaningful guidance for conservation management than can a bivariate perspective. Measuring only two variables does not permit the evaluation of complex ideas nor resolve debates about underlying mechanisms.
    7. \n
","language":"English","publisher":"Wiley-Blackwell Publishing Ltd.","doi":"10.1111/1365-2435.12269","usgsCitation":"Grace, J.B., Adler, P.B., Harpole, W.S., Borer, E.T., and Seabloom, E.W., 2014, Causal networks clarify productivity-richness interrelations, bivariate plots do not: Functional Ecology, v. 28, no. 4, p. 787-798, https://doi.org/10.1111/1365-2435.12269.","productDescription":"12 p.","startPage":"787","endPage":"798","numberOfPages":"12","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-052277","costCenters":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"links":[{"id":472842,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/1365-2435.12269","text":"Publisher Index Page"},{"id":296792,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"28","issue":"4","noUsgsAuthors":false,"publicationDate":"2014-03-24","publicationStatus":"PW","scienceBaseUri":"54dd2b4ee4b08de9379b3309","contributors":{"authors":[{"text":"Grace, James B. 0000-0001-6374-4726 gracej@usgs.gov","orcid":"https://orcid.org/0000-0001-6374-4726","contributorId":884,"corporation":false,"usgs":true,"family":"Grace","given":"James","email":"gracej@usgs.gov","middleInitial":"B.","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":536955,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Adler, Peter B.","contributorId":64789,"corporation":false,"usgs":false,"family":"Adler","given":"Peter","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":536956,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Harpole, W. Stanley","contributorId":131024,"corporation":false,"usgs":false,"family":"Harpole","given":"W.","email":"","middleInitial":"Stanley","affiliations":[{"id":6911,"text":"Iowa State University","active":true,"usgs":false}],"preferred":false,"id":536957,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Borer, Elizabeth T.","contributorId":45049,"corporation":false,"usgs":false,"family":"Borer","given":"Elizabeth","email":"","middleInitial":"T.","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":536958,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Seabloom, Eric W.","contributorId":60762,"corporation":false,"usgs":false,"family":"Seabloom","given":"Eric","email":"","middleInitial":"W.","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":536959,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70147408,"text":"70147408 - 2014 - NGA-West2 Research Project","interactions":[],"lastModifiedDate":"2015-05-01T13:28:47","indexId":"70147408","displayToPublicDate":"2014-08-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1436,"text":"Earthquake Spectra","active":true,"publicationSubtype":{"id":10}},"title":"NGA-West2 Research Project","docAbstract":"

The NGA-West2 project is a large multidisciplinary, multi-year research program on the Next Generation Attenuation (NGA) models for shallow crustal earthquakes in active tectonic regions. The research project has been coordinated by the Pacific Earthquake Engineering Research Center (PEER), with extensive technical interactions among many individuals and organizations. NGA-West2 addresses several key issues in ground-motion seismic hazard, including updating the NGA database for a magnitude range of 3.0–7.9; updating NGA ground-motion prediction equations (GMPEs) for the “average” horizontal component; scaling response spectra for damping values other than 5%; quantifying the effects of directivity and directionality for horizontal ground motion; resolving discrepancies between the NGA and the National Earthquake Hazards Reduction Program (NEHRP) site amplification factors; analysis of epistemic uncertainty for NGA GMPEs; and developing GMPEs for vertical ground motion. This paper presents an overview of the NGA-West2 research program and its subprojects.

","language":"English","publisher":"Earthquake Engineering Research Institute","doi":"10.1193/072113EQS209M","usgsCitation":"Bozorgnia, Y., Abrahamson, N., Al Atik, L., Ancheta, T.D., Atkinson, G.M., Baker, J., Baltay Sundstrom, A.S., Boore, D.M., Campbell, K.W., Chiou, B.S., Darragh, R.B., Day, S., Donahue, J., Graves, R.W., Gregor, N., Hanks, T.C., Idriss, I.M., Kamai, R., Kishida, T., Kottke, A., Mahin, S.A., Rezaeian, S., Rowshandel, B., Seyhan, E., Shahi, S., Shantz, T., Silva, W., Spudich, P.A., Stewart, J.P., Watson-Lamprey, J., Wooddell, K., and Youngs, R., 2014, NGA-West2 Research Project: Earthquake Spectra, v. 30, no. 3, p. 973-987, https://doi.org/10.1193/072113EQS209M.","productDescription":"15 p.","startPage":"973","endPage":"987","numberOfPages":"15","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-051126","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":300028,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"30","issue":"3","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2014-08-01","publicationStatus":"PW","scienceBaseUri":"5544a3b3e4b0a658d79478c7","contributors":{"authors":[{"text":"Bozorgnia, Yousef","contributorId":40101,"corporation":false,"usgs":false,"family":"Bozorgnia","given":"Yousef","affiliations":[{"id":6643,"text":"University of California - 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We evaluated several potential drivers of primary production by benthic algae (periphyton) in north-temperate lakes. We used continuous dissolved oxygen measurements from in situ benthic chambers to quantify primary production by periphyton at multiple depths across 11 lakes encompassing a broad range of dissolved organic carbon (DOC) and total phosphorous (TP) concentrations. Light-use efficiency (primary production per unit incident light) was inversely related to average light availability (% of surface light) in 7 of the 11 study lakes, indicating that benthic algal assemblages exhibit photoadaptation, likely through physiological or compositional changes. DOC alone explained 86% of the variability in log-transformed whole-lake benthic production rates. TP was not an important driver of benthic production via its effects on nutrient and light availability. This result is contrary to studies in other systems, but may be common in relatively pristine north-temperate lakes. Our simple empirical model may allow for the prediction of whole-lake benthic primary production from easily obtained measurements of DOC concentration.

","language":"English","publisher":"Association for the Sciences of Limnology and Oceanography","doi":"10.4319/lo.2014.59.6.2112","usgsCitation":"Godwin, S.C., Jones, S., Weidel, B., and Solomon, C.T., 2014, Dissolved organic carbon concentration controls benthic primary production: results from in situ chambers in north-temperate lakes: Limnology and Oceanography, v. 59, no. 6, p. 2112-2120, https://doi.org/10.4319/lo.2014.59.6.2112.","productDescription":"9 p.","startPage":"2112","endPage":"2120","numberOfPages":"9","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-056921","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":488302,"rank":2,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://figshare.com/articles/journal_contribution/Dissolved_organic_carbon_concentration_controls_benthic_primary_production_Results_from_in_situ_chambers_in_north-temperate_lakes/24826899","text":"External Repository"},{"id":296074,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"59","issue":"6","noUsgsAuthors":false,"publicationDate":"2014-10-12","publicationStatus":"PW","scienceBaseUri":"5465d631e4b04d4b7dbd65ba","contributors":{"authors":[{"text":"Godwin, Sean C.","contributorId":127430,"corporation":false,"usgs":false,"family":"Godwin","given":"Sean","email":"","middleInitial":"C.","affiliations":[{"id":6646,"text":"McGill University","active":true,"usgs":false}],"preferred":false,"id":525128,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jones, Stuart E.","contributorId":22222,"corporation":false,"usgs":false,"family":"Jones","given":"Stuart E.","affiliations":[{"id":6966,"text":"Department of Biological Sciences, University of Notre Dame","active":true,"usgs":false}],"preferred":false,"id":525129,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Weidel, Brian 0000-0001-6095-2773 bweidel@usgs.gov","orcid":"https://orcid.org/0000-0001-6095-2773","contributorId":2485,"corporation":false,"usgs":true,"family":"Weidel","given":"Brian","email":"bweidel@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":525127,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Solomon, Christopher T.","contributorId":34014,"corporation":false,"usgs":false,"family":"Solomon","given":"Christopher","email":"","middleInitial":"T.","affiliations":[{"id":6646,"text":"McGill University","active":true,"usgs":false}],"preferred":false,"id":525130,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70171520,"text":"70171520 - 2014 - Long-term trends in alkalinity in large rivers of the conterminous US in relation to acidification, agriculture, and hydrologic modification","interactions":[],"lastModifiedDate":"2016-06-03T16:36:25","indexId":"70171520","displayToPublicDate":"2014-08-01T00:00:00","publicationYear":"2014","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":"Long-term trends in alkalinity in large rivers of the conterminous US in relation to acidification, agriculture, and hydrologic modification","docAbstract":"

Alkalinity increases in large rivers of the conterminous US are well known, but less is understood about the processes leading to these trends as compared with headwater systems more intensively examined in conjunction with acid deposition studies. Nevertheless, large rivers are important conduits of inorganic carbon and other solutes to coastal areas and may have substantial influence on coastal calcium carbonate saturation dynamics. We examined long-term (mid-20th to early 21st century) trends in alkalinity and other weathering products in 23 rivers of the conterminous US. We used a rigorous flow-weighting technique which allowed greater focus on solute trends occurring independently of changes in flow. Increasing alkalinity concentrations and yield were widespread, occurring at 14 and 13 stations, respectively. Analysis of trends in other weathering products suggested that the causes of alkalinity trends were diverse, but at many stations alkalinity increases coincided with decreasing nitrate + sulfate and decreasing cation:alkalinity ratios, which is consistent with recovery from acidification. A positive correlation between the Sen–Thiel slopes of alkalinity increases and agricultural lime usage indicated that agricultural lime contributed to increasing solute concentration in some areas. However, several stations including the Altamaha, Upper Mississippi, and San Joaquin Rivers exhibited solute trends, such as increasing cation:alkalinity ratios and increasing nitrate + sulfate, more consistent with increasing acidity, emphasizing that multiple processes affect alkalinity trends in large rivers. This study was unique in its examination of alkalinity trends in large rivers covering a wide range of climate and land use types, but more detailed analyses will help to better elucidate temporal changes to river solutes and especially the effects they may have on coastal calcium carbonate saturation state.

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Estuarine eutrophication has led to numerous ecological changes, including loss of seagrass beds. One potential cause of these losses is a reduction in light availability due to increased attenuation by phytoplankton. Future sea level rise will also tend to reduce light penetration and modify seagrass habitat. In the present study, we integrate a spectral irradiance model into a biogeochemical model coupled to the Regional Ocean Model System (ROMS). It is linked to a bio-optical seagrass model to assess potential seagrass habitat in a eutrophic estuary under future nitrate loading and sea-level rise scenarios. The model was applied to West Falmouth Harbor, a shallow estuary located on Cape Cod (Massachusetts) where nitrate from groundwater has led to eutrophication and seagrass loss in landward portions of the estuary. Measurements of chlorophyll, turbidity, light attenuation, and seagrass coverage were used to assess the model accuracy. Mean chlorophyll based on uncalibrated in-situ fluorometry varied from 28 μg L−1 at the landward-most site to 6.5 μg L−1 at the seaward site, while light attenuation ranged from 0.86 to 0.45 m-1. The model reproduced the spatial variability in chlorophyll and light attenuation with RMS errors of 3.72 μg L−1 and 0.07 m-1 respectively. Scenarios of future nitrate reduction and sea-level rise suggest an improvement in light climate in the landward basin with a 75% reduction in nitrate loading. This coupled model may be useful to assess habitat availability changes due to eutrophication and sediment resuspension and fully considers spatial variability on the tidal timescale.

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