A landscape-scale perspective on restoration ecology has been advocated, but few studies have informed restoration with landscape metrics or addressed broad-scale threats. Threats such as urban growth may affect restoration effectiveness in a landscape context. Here, we studied longleaf pine savanna in the rapidly urbanizing southeastern United States where a habitat-specialist bird, Bachman's sparrow (Peucaea aestivalis), is closely associated with savanna vegetation structure and frequent fire. Our objectives were to construct a species distribution model for Bachman's sparrow, determine the relationship between fire and urbanization, quantify the urban growth effect (2010–2090), identify potential restoration areas, and determine the interaction between restoration potential and urban growth by 2050. Number of patches, patch size, and isolation metrics were used to evaluate scenarios. The species distribution model was 88% accurate and emphasized multiscale canopy cover characteristics, fire, and percent habitat. Fires were less common <600 m from urban areas, and this fire suppression effect exacerbated urban growth effects. For restoration scenarios, canopy cover reduction by 30% resulted in nearly double the amount of habitat compared to the prescribed fire scenario; canopy cover reduction resulted in larger patch sizes and less patch isolation compared to current conditions. The effect of urban growth on restoration scenarios was unequal. Seventy-four percent of restoration areas from the prescribed fire scenario overlapped with projected urban growth, whereas the canopy cover reduction scenario only overlapped by 9%. We emphasize the benefits of simultaneously considering the effects of urban growth and landscape-scale restoration potential to promote a landscape with greater patch sizes and less isolation.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jenvman.2017.01.005","usgsCitation":"Pickens, B.A., Marcus, J.F., Carpenter, J.P., Anderson, S., Taillie, P.J., and Collazo, J., 2017, The effect of urban growth on landscape-scale restoration for a fire-dependent songbird: Journal of Environmental Management, v. 191, p. 105-115, https://doi.org/10.1016/j.jenvman.2017.01.005.","productDescription":"11 p.","startPage":"105","endPage":"115","ipdsId":"IP-074203","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":469921,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jenvman.2017.01.005","text":"Publisher Index Page"},{"id":352949,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Carolina","volume":"191","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee893e4b0da30c1bfc470","contributors":{"authors":[{"text":"Pickens, Bradley A.","contributorId":140926,"corporation":false,"usgs":false,"family":"Pickens","given":"Bradley","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":732034,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Marcus, Jeffrey F.","contributorId":203645,"corporation":false,"usgs":false,"family":"Marcus","given":"Jeffrey","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":732035,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Carpenter, John P.","contributorId":203646,"corporation":false,"usgs":false,"family":"Carpenter","given":"John","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":732036,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Anderson, Scott","contributorId":56997,"corporation":false,"usgs":true,"family":"Anderson","given":"Scott","affiliations":[],"preferred":false,"id":732037,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Taillie, Paul J.","contributorId":203647,"corporation":false,"usgs":false,"family":"Taillie","given":"Paul","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":732038,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Collazo, Jaime A. 0000-0002-1816-7744 jaime_collazo@usgs.gov","orcid":"https://orcid.org/0000-0002-1816-7744","contributorId":173448,"corporation":false,"usgs":true,"family":"Collazo","given":"Jaime A.","email":"jaime_collazo@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":false,"id":718146,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70189815,"text":"70189815 - 2017 - Disturbance automated reference toolset (DART): Assessing patterns in ecological recovery from energy development on the Colorado Plateau","interactions":[],"lastModifiedDate":"2017-07-26T17:01:43","indexId":"70189815","displayToPublicDate":"2017-04-15T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Disturbance automated reference toolset (DART): Assessing patterns in ecological recovery from energy development on the Colorado Plateau","docAbstract":"A new disturbance automated reference toolset (DART) was developed to monitor human land surface impacts using soil-type and ecological context. DART identifies reference areas with similar soils, topography, and geology; and compares the disturbance condition to the reference area condition using a quantile-based approach based on a satellite vegetation index. DART was able to represent 26–55% of variation of relative differences in bare ground and 26–41% of variation in total foliar cover when comparing sites with nearby ecological reference areas using the Soil Adjusted Total Vegetation Index (SATVI). Assessment of ecological recovery at oil and gas pads on the Colorado Plateau with DART revealed that more than half of well-pads were below the 25th percentile of reference areas. Machine learning trend analysis of poorly recovering well-pads (quantile < 0.23) had out-of-bag error rates between 37 and 40% indicating moderate association with environmental and management variables hypothesized to influence recovery. Well-pads in grasslands (median quantile [MQ] = 13%), blackbrush (Coleogyne ramosissima) shrublands (MQ = 18%), arid canyon complexes (MQ = 18%), warmer areas with more summer-dominated precipitation, and state administered areas (MQ = 12%) had low recovery rates. Results showcase the usefulness of DART for assessing discrete surface land disturbances, and highlight the need for more targeted rehabilitation efforts at oil and gas well-pads in the arid southwest US.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2017.01.034","usgsCitation":"Nauman, T.W., Duniway, M.C., Villarreal, M.L., and Poitras, T.B., 2017, Disturbance automated reference toolset (DART): Assessing patterns in ecological recovery from energy development on the Colorado Plateau: Science of the Total Environment, v. 584-585, p. 476-488, https://doi.org/10.1016/j.scitotenv.2017.01.034.","productDescription":"13 p.","startPage":"476","endPage":"488","ipdsId":"IP-077123","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":469920,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2017.01.034","text":"Publisher Index Page"},{"id":344368,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Colorado Plateau","volume":"584-585","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5979aa55e4b0ec1a488b8c09","contributors":{"authors":[{"text":"Nauman, Travis W. 0000-0001-8004-0608 tnauman@usgs.gov","orcid":"https://orcid.org/0000-0001-8004-0608","contributorId":169241,"corporation":false,"usgs":true,"family":"Nauman","given":"Travis","email":"tnauman@usgs.gov","middleInitial":"W.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":706444,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Duniway, Michael C. 0000-0002-9643-2785 mduniway@usgs.gov","orcid":"https://orcid.org/0000-0002-9643-2785","contributorId":4212,"corporation":false,"usgs":true,"family":"Duniway","given":"Michael","email":"mduniway@usgs.gov","middleInitial":"C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":706445,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Villarreal, Miguel L. 0000-0003-0720-1422 mvillarreal@usgs.gov","orcid":"https://orcid.org/0000-0003-0720-1422","contributorId":1424,"corporation":false,"usgs":true,"family":"Villarreal","given":"Miguel","email":"mvillarreal@usgs.gov","middleInitial":"L.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":706446,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Poitras, Travis B. 0000-0001-8677-1743 tpoitras@usgs.gov","orcid":"https://orcid.org/0000-0001-8677-1743","contributorId":195168,"corporation":false,"usgs":true,"family":"Poitras","given":"Travis","email":"tpoitras@usgs.gov","middleInitial":"B.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":706447,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70186776,"text":"ofr20171026 - 2017 - Potential effects of existing and proposed groundwater withdrawals on water levels and natural groundwater discharge in Snake Valley and surrounding areas, Utah and Nevada","interactions":[],"lastModifiedDate":"2017-04-17T15:35:48","indexId":"ofr20171026","displayToPublicDate":"2017-04-14T00:00:00","publicationYear":"2017","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":"2017-1026","title":"Potential effects of existing and proposed groundwater withdrawals on water levels and natural groundwater discharge in Snake Valley and surrounding areas, Utah and Nevada","docAbstract":"Several U.S. Department of Interior (DOI) agencies are concerned about the cumulative effects of groundwater development on groundwater resources managed by, and other groundwater resources of interest to, these agencies in Snake Valley and surrounding areas. The new water uses that potentially concern the DOI agencies include 12 water-right applications filed in 2005, totaling approximately 8,864 acre-feet per year. To date, only one of these applications has been approved and partially developed. In addition, the DOI agencies are interested in the potential effects of three new water-right applications (UT 18-756, UT 18-758, and UT 18-759) and one water-right change application (UT a40687), which were the subject of a water-right hearing on April 19, 2016.
This report presents a hydrogeologic analysis of areas in and around Snake Valley to assess potential effects of existing and future groundwater development on groundwater resources, specifically groundwater discharge sites, of interest to the DOI agencies. A previously developed steady-state numerical groundwater-flow model was modified to transient conditions with respect to well withdrawals and used to quantify drawdown and capture (withdrawals that result in depletion) of natural discharge from existing and proposed groundwater withdrawals. The original steady-state model simulates and was calibrated to 2009 conditions. To investigate the potential effects of existing and proposed groundwater withdrawals on the groundwater resources of interest to the DOI agencies, 10 withdrawal scenarios were simulated. All scenarios were simulated for periods of 5, 10, 15, 30, 55, and 105 years from the start of 2010; additionally, all scenarios were simulated to a new steady state to determine the ultimate long-term effects of the withdrawals. Capture maps were also constructed as part of this analysis. The simulations used to develop the capture maps test the response of the system, specifically the reduction of natural discharge, to future stresses at a point in the area represented by the model. In this way, these maps can be used as a tool to determine the source of water to, and potential effects at specific areas from, future well withdrawals.
Downward trends in water levels measured in wells indicate that existing groundwater withdrawals in Snake Valley are affecting water levels. The numerical model simulates similar downward trends in water levels; simulated drawdowns in the model, however, are generally less than observed water-level declines. At the groundwater discharge sites of interest to the DOI agencies, simulated drawdowns from existing well withdrawals (projected into the future) range from 0 to about 50 feet. Following the addition of the proposed withdrawals, simulated drawdowns at some sites increase by 25 feet. Simulated drawdown resulting from the proposed withdrawals began in as few as 5 years after 2014 at several of the sites. At the groundwater discharge sites of interest to the DOI agencies, simulated capture of natural discharge resulting from the existing withdrawals ranged from 0 to 87 percent. Following the addition of the proposed withdrawals, simulated capture at several of the sites reached 100 percent, indicating that groundwater discharge at that site would cease. Simulated capture following the addition of the proposed withdrawals increased in as few as 5 years after 2014 at several of the sites.
Director, Utah Water Science Center
U.S. Geological Survey
2329 West Orton Circle
Salt Lake City, UT 84119-2047
801 908-5000
http://ut.water.usgs.gov/
Well-executed evacuations are key to minimizing loss of life from tsunamis, yet they also disrupt communities and business productivity in the process. Most coastal communities implement evacuations based on a previously delineated maximum-inundation zone that integrates zones from multiple tsunami sources. To support consistent evacuation planning that protects lives but attempts to minimize community disruptions, we explore the implications of scenario-based evacuation procedures and use the California (USA) coastline as our case study. We focus on the land in coastal communities that is in maximum-evacuation zones, but is not expected to be flooded by a tsunami generated by a Chilean earthquake scenario. Results suggest that a scenario-based evacuation could greatly reduce the number of residents and employees that would be advised to evacuate for 24–36 h (178,646 and 159,271 fewer individuals, respectively) and these reductions are concentrated primarily in three counties for this scenario. Private evacuation spending is estimated to be greater than public expenditures for operating shelters in the area of potential over-evacuations ($13 million compared to $1 million for a 1.5-day evacuation). Short-term disruption costs for businesses in the area of potential over-evacuation are approximately $122 million for a 1.5-day evacuation, with one-third of this cost associated with manufacturing, suggesting that some disruption costs may be recouped over time with increased short-term production. There are many businesses and organizations in this area that contain individuals with limited mobility or access and functional needs that may have substantial evacuation challenges. This study demonstrates and discusses the difficulties of tsunami-evacuation decision-making for relatively small to moderate events faced by emergency managers, not only in California but in coastal communities throughout the world.
","language":"English","publisher":"Springer","doi":"10.1007/s11069-016-2709-y","usgsCitation":"Wood, N.J., Wilson, R.I., Ratliff, J.L., Peters, J., MacMullan, E., Krebs, T., Shoaf, K., and Miller, K., 2017, Community disruptions and business costs for distant tsunami evacuations using maximum versus scenario-based zones: Natural Hazards, v. 86, no. 2, p. 619-643, https://doi.org/10.1007/s11069-016-2709-y.","productDescription":"25 p.","startPage":"619","endPage":"643","ipdsId":"IP-076947","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":469922,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1007/s11069-016-2709-y","text":"External Repository"},{"id":339725,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"86","issue":"2","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-12-16","publicationStatus":"PW","scienceBaseUri":"58f1e0c8e4b08144348b7de9","contributors":{"authors":[{"text":"Wood, Nathan J. 0000-0002-6060-9729 nwood@usgs.gov","orcid":"https://orcid.org/0000-0002-6060-9729","contributorId":3347,"corporation":false,"usgs":true,"family":"Wood","given":"Nathan","email":"nwood@usgs.gov","middleInitial":"J.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":690972,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wilson, Rick I.","contributorId":56138,"corporation":false,"usgs":false,"family":"Wilson","given":"Rick","email":"","middleInitial":"I.","affiliations":[],"preferred":false,"id":690973,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ratliff, Jamie L. 0000-0002-9967-3314 jratliff@usgs.gov","orcid":"https://orcid.org/0000-0002-9967-3314","contributorId":665,"corporation":false,"usgs":true,"family":"Ratliff","given":"Jamie","email":"jratliff@usgs.gov","middleInitial":"L.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":690974,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Peters, Jeff 0000-0003-4312-0590 jpeters@usgs.gov","orcid":"https://orcid.org/0000-0003-4312-0590","contributorId":4711,"corporation":false,"usgs":true,"family":"Peters","given":"Jeff","email":"jpeters@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":690975,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"MacMullan, Ed","contributorId":190879,"corporation":false,"usgs":false,"family":"MacMullan","given":"Ed","email":"","affiliations":[],"preferred":false,"id":690976,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Krebs, Tessa","contributorId":190880,"corporation":false,"usgs":false,"family":"Krebs","given":"Tessa","email":"","affiliations":[],"preferred":false,"id":690977,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Shoaf, Kimberley","contributorId":190881,"corporation":false,"usgs":false,"family":"Shoaf","given":"Kimberley","email":"","affiliations":[],"preferred":false,"id":690978,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Miller, Kevin","contributorId":178815,"corporation":false,"usgs":false,"family":"Miller","given":"Kevin","affiliations":[],"preferred":false,"id":690979,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70186759,"text":"sir20175024 - 2017 - Developing flood-inundation maps for Johnson Creek, Portland, Oregon","interactions":[],"lastModifiedDate":"2017-04-20T11:18:36","indexId":"sir20175024","displayToPublicDate":"2017-04-14T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2017-5024","title":"Developing flood-inundation maps for Johnson Creek, Portland, Oregon","docAbstract":"Digital flood-inundation maps were created for a 12.9‑mile reach of Johnson Creek by the U.S. Geological Survey (USGS). The flood-inundation maps depict estimates of water depth and areal extent of flooding from the mouth of Johnson Creek to just upstream of Southeast 174th Avenue in Portland, Oregon. Each flood-inundation map is based on a specific water level and associated streamflow at the USGS streamgage, Johnson Creek at Sycamore, Oregon (14211500), which is located near the upstream boundary of the maps. The maps produced by the USGS, and the forecasted flood hydrographs produced by National Weather Service River Forecast Center can be accessed through the USGS Flood Inundation Mapper Web site (http://wimcloud.usgs.gov/apps/FIM/FloodInundationMapper.html).
Water-surface elevations were computed for Johnson Creek using a combined one-dimensional and two‑dimensional unsteady hydraulic flow model. The model was calibrated using data collected from the flood of December 2015 (including the calculated streamflows at two USGS streamgages on Johnson Creek) and validated with data from the flood of January 2009. Results were typically within 0.6 foot (ft) of recorded or measured water-surface elevations from the December 2015 flood, and within 0.8 ft from the January 2009 flood. Output from the hydraulic model was used to create eight flood inundation maps ranging in stage from 9 to 16 ft. Boundary condition hydrographs were identical in shape to those from the December 2015 flood event, but were scaled up or down to produce the amount of streamflow corresponding to a specific water-surface elevation at the Sycamore streamgage (14211500). Sensitivity analyses using other hydrograph shapes, and a version of the model in which the peak flow is maintained for an extended period of time, showed minimal variation, except for overbank areas near the Foster Floodplain Natural Area.
Simulated water-surface profiles were combined with light detection and ranging (lidar) data collected in 2014 to delineate water-surface extents for each of the eight modeled stages. The availability of flood-inundation maps in conjunction with real-time data from the USGS streamgages along Johnson Creek and forecasted hydrographs from the National Weather Service Northwest River Forecast Center will provide residents of the watershed and emergency management personnel with valuable information that may aid in flood response, including potential evacuations, road closures, and mitigation efforts. In addition, these maps may be used for post-flood recovery efforts.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175024","collaboration":"Prepared in cooperation with the City of Portland Bureau of Environmental Services","usgsCitation":"Stonewall, A.J., and Beal, B.A., 2017, Developing flood-Inundation maps for Johnson Creek, Portland, Oregon: U.S. Geological Survey Scientific Investigations Report 2017–5024, 26 p., https://doi.org/10.3133/sir20175024.","productDescription":"v, 26 p.","onlineOnly":"Y","ipdsId":"IP-080503","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":339976,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F75X273G","text":"USGS data release","description":"USGS data release","linkHelpText":"Flood inundation mapping data for Johnson Creek near Sycamore, Oregon"},{"id":339738,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5024/coverthb.jpg"},{"id":339739,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5024/sir20175024.pdf","text":"Report","size":"9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017-5024"}],"country":"United States","state":"Oregon","city":"Portland","otherGeospatial":"Johnson Creek","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.655556,\n 45.506944\n ],\n [\n -122.472222,\n 45.506944\n ],\n [\n -122.472222,\n 45.408333\n ],\n [\n -122.655556,\n 45.408333\n ],\n [\n -122.655556,\n 45.506944\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Oregon Water Science Center
U.S. Geological Survey
2130 SW 5th Avenue
Portland, Oregon 97201
http://or.water.usgs.gov
Clouds are a pervasive and unavoidable issue in satellite-borne optical imagery. Accurate, well-documented, and automated cloud detection algorithms are necessary to effectively leverage large collections of remotely sensed data. The Landsat project is uniquely suited for comparative validation of cloud assessment algorithms because the modular architecture of the Landsat ground system allows for quick evaluation of new code, and because Landsat has the most comprehensive manual truth masks of any current satellite data archive. Currently, the Landsat Level-1 Product Generation System (LPGS) uses separate algorithms for determining clouds, cirrus clouds, and snow and/or ice probability on a per-pixel basis. With more bands onboard the Landsat 8 Operational Land Imager (OLI)/Thermal Infrared Sensor (TIRS) satellite, and a greater number of cloud masking algorithms, the U.S. Geological Survey (USGS) is replacing the current cloud masking workflow with a more robust algorithm that is capable of working across multiple Landsat sensors with minimal modification. Because of the inherent error from stray light and intermittent data availability of TIRS, these algorithms need to operate both with and without thermal data. In this study, we created a workflow to evaluate cloud and cloud shadow masking algorithms using cloud validation masks manually derived from both Landsat 7 Enhanced Thematic Mapper Plus (ETM +) and Landsat 8 OLI/TIRS data. We created a new validation dataset consisting of 96 Landsat 8 scenes, representing different biomes and proportions of cloud cover. We evaluated algorithm performance by overall accuracy, omission error, and commission error for both cloud and cloud shadow. We found that CFMask, C code based on the Function of Mask (Fmask) algorithm, and its confidence bands have the best overall accuracy among the many algorithms tested using our validation data. The Artificial Thermal-Automated Cloud Cover Algorithm (AT-ACCA) is the most accurate nonthermal-based algorithm. We give preference to CFMask for operational cloud and cloud shadow detection, as it is derived from a priori knowledge of physical phenomena and is operable without geographic restriction, making it useful for current and future land imaging missions without having to be retrained in a machine-learning environment.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.rse.2017.03.026","usgsCitation":"Foga, S.C., Scaramuzza, P., Guo, S., Zhu, Z., Dilley, R., Beckmann, T., Schmidt, G.L., Dwyer, J.L., Hughes, M., and Laue, B., 2017, Cloud detection algorithm comparison and validation for operational Landsat data products: Remote Sensing of Environment, v. 194, p. 379-390, https://doi.org/10.1016/j.rse.2017.03.026.","productDescription":"12 p.","startPage":"379","endPage":"390","ipdsId":"IP-076780","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":469926,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.rse.2017.03.026","text":"Publisher Index Page"},{"id":339659,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"194","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58f08e5ee4b06911a29fa842","contributors":{"authors":[{"text":"Foga, Steven Curtis 0000-0003-1835-1987 sfoga@usgs.gov","orcid":"https://orcid.org/0000-0003-1835-1987","contributorId":5703,"corporation":false,"usgs":true,"family":"Foga","given":"Steven","email":"sfoga@usgs.gov","middleInitial":"Curtis","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":690805,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Scaramuzza, Pat 0000-0002-2616-8456 pscar@usgs.gov","orcid":"https://orcid.org/0000-0002-2616-8456","contributorId":3970,"corporation":false,"usgs":true,"family":"Scaramuzza","given":"Pat","email":"pscar@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":690806,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Guo, Song 0000-0001-8823-188X sguo@usgs.gov","orcid":"https://orcid.org/0000-0001-8823-188X","contributorId":5245,"corporation":false,"usgs":true,"family":"Guo","given":"Song","email":"sguo@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":690807,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Zhu, Zhe 0000-0001-8283-6407","orcid":"https://orcid.org/0000-0001-8283-6407","contributorId":190828,"corporation":false,"usgs":false,"family":"Zhu","given":"Zhe","affiliations":[],"preferred":false,"id":690808,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dilley, Ronald 0000-0002-6960-1125 ronald.dilley.ctr@usgs.gov","orcid":"https://orcid.org/0000-0002-6960-1125","contributorId":190829,"corporation":false,"usgs":true,"family":"Dilley","given":"Ronald","email":"ronald.dilley.ctr@usgs.gov","affiliations":[],"preferred":false,"id":690809,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Beckmann, Tim 0000-0002-2557-0638 tim.beckmann.ctr@usgs.gov","orcid":"https://orcid.org/0000-0002-2557-0638","contributorId":190830,"corporation":false,"usgs":true,"family":"Beckmann","given":"Tim","email":"tim.beckmann.ctr@usgs.gov","affiliations":[],"preferred":false,"id":690811,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Schmidt, Gail L. 0000-0002-9684-8158 gschmidt@usgs.gov","orcid":"https://orcid.org/0000-0002-9684-8158","contributorId":3475,"corporation":false,"usgs":true,"family":"Schmidt","given":"Gail","email":"gschmidt@usgs.gov","middleInitial":"L.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":690810,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Dwyer, John L. 0000-0002-8281-0896 dwyer@usgs.gov","orcid":"https://orcid.org/0000-0002-8281-0896","contributorId":3481,"corporation":false,"usgs":true,"family":"Dwyer","given":"John","email":"dwyer@usgs.gov","middleInitial":"L.","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":690812,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Hughes, MJ","contributorId":190831,"corporation":false,"usgs":false,"family":"Hughes","given":"MJ","email":"","affiliations":[],"preferred":false,"id":690813,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Laue, Brady 0000-0002-4559-3618 brady.laue.ctr@usgs.gov","orcid":"https://orcid.org/0000-0002-4559-3618","contributorId":190832,"corporation":false,"usgs":true,"family":"Laue","given":"Brady","email":"brady.laue.ctr@usgs.gov","affiliations":[],"preferred":false,"id":690814,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70186886,"text":"70186886 - 2017 - Integrated species distribution models: combining presence-background data and site-occupancy data with imperfect detection","interactions":[],"lastModifiedDate":"2017-04-13T11:31:34","indexId":"70186886","displayToPublicDate":"2017-04-13T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2717,"text":"Methods in Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Integrated species distribution models: combining presence-background data and site-occupancy data with imperfect detection","docAbstract":"1. The reasons that lead some animals to seasonally migrate, and others to remain in the same area year-round, are poorly understood. Associations between traits, such as body size, and migration provide clues. For example, larger species and individuals are more likely to migrate.
2. One explanation for this size bias in migration is that larger animals are capable of moving faster (movement hypothesis). However, body size is linked to many other biological processes. For instance, the energetic balances of larger animals are generally more sensitive to variation in food density because of body size effects on foraging and metabolism and this sensitivity could drive migratory decisions (forage hypothesis).
3. Identifying the primary selective forces that drive migration ultimately requires quantifying fitness impacts over the full annual migratory cycle. Here, we develop a full annual migratory cycle model from metabolic and foraging theory to compare the importance of the forage and movement hypotheses. We parameterize the model for Galapagos tortoises, which were recently discovered to be size-dependent altitudinal migrants.
4. The model predicts phenomena not included in model development including maximum body sizes, the body size at which individuals begin to migrate, and the seasonal timing of migration and these predictions generally agree with available data. Scenarios strongly support the forage hypothesis over the movement hypothesis. Furthermore, male Galapagos tortoises on Santa Cruz Island would be unable to grow to their enormous sizes without access to both highlands and lowlands.
5. Whereas recent research has focused on links between traits and the migratory phases of the migratory cycle, we find that effects of body size on the non-migratory phases are far more important determinants of the propensity to migrate. Larger animals are more sensitive to changing forage conditions than smaller animals with implications for maintenance of migration and body size in the face of environmental change.
","language":"English","publisher":"Wiley","doi":"10.1111/1365-2656.12679","usgsCitation":"Yackulic, C.B., Blake, S., and Bastille-Rousseau, G., 2017, Benefits of the destinations, not costs of the journeys, shape partial migration patterns: Journal of Animal Ecology, v. 86, no. 4, p. 972-982, https://doi.org/10.1111/1365-2656.12679.","productDescription":"11 p.","startPage":"972","endPage":"982","ipdsId":"IP-065801","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":469927,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/1365-2656.12679","text":"Publisher Index Page"},{"id":438374,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7154F7P","text":"USGS data release","linkHelpText":"Full Annual Cycle Bioenergetics model of migration applied to Galapagos tortoisesData"},{"id":339709,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"86","issue":"4","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2017-05-15","publicationStatus":"PW","scienceBaseUri":"58f08e5ce4b06911a29fa836","contributors":{"authors":[{"text":"Yackulic, Charles B. 0000-0001-9661-0724 cyackulic@usgs.gov","orcid":"https://orcid.org/0000-0001-9661-0724","contributorId":4662,"corporation":false,"usgs":true,"family":"Yackulic","given":"Charles","email":"cyackulic@usgs.gov","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":690957,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Blake, Stephen","contributorId":65339,"corporation":false,"usgs":false,"family":"Blake","given":"Stephen","email":"","affiliations":[{"id":30787,"text":"Saint Louis University","active":true,"usgs":false},{"id":12472,"text":"Max Planck Institute for Ornithology","active":true,"usgs":false}],"preferred":false,"id":690958,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bastille-Rousseau, Guillaume 0000-0001-6799-639X","orcid":"https://orcid.org/0000-0001-6799-639X","contributorId":190877,"corporation":false,"usgs":false,"family":"Bastille-Rousseau","given":"Guillaume","email":"","affiliations":[{"id":40724,"text":"Cooperative Wildlife Research Laboratory and Department of Forestry, Southern Illinois University, 251 Life Science II, Mail Code 6504, Carbondale, Illinois 62901 USA","active":true,"usgs":false}],"preferred":false,"id":690959,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70186890,"text":"70186890 - 2017 - Geomorphic process from topographic form: automating the interpretation of repeat survey data in river valleys","interactions":[],"lastModifiedDate":"2017-09-18T15:43:24","indexId":"70186890","displayToPublicDate":"2017-04-13T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1425,"text":"Earth Surface Processes and Landforms","active":true,"publicationSubtype":{"id":10}},"title":"Geomorphic process from topographic form: automating the interpretation of repeat survey data in river valleys","docAbstract":"The ability to quantify the processes driving geomorphic change in river valley margins is vital to geomorphologists seeking to understand the relative role of transport mechanisms (e.g. fluvial, aeolian, and hillslope processes) in landscape dynamics. High-resolution, repeat topographic data are becoming readily available to geomorphologists. By contrasting digital elevation models derived from repeat surveys, the transport processes driving topographic changes can be inferred, a method termed ‘mechanistic segregation.’ Unfortunately, mechanistic segregation largely relies on subjective and time consuming manual classification, which has implications both for its reproducibility and the practical scale of its application. Here we present a novel computational workflow for the mechanistic segregation of geomorphic transport processes in geospatial datasets. We apply the workflow to seven sites along the Colorado River in the Grand Canyon, where geomorphic transport is driven by a diverse suite of mechanisms. The workflow performs well when compared to field observations, with an overall predictive accuracy of 84% across 113 validation points. The approach most accurately predicts changes due to fluvial processes (100% accuracy) and aeolian processes (96%), with reduced accuracy in predictions of alluvial and colluvial processes (64% and 73%, respectively). Our workflow is designed to be applicable to a diversity of river systems and will likely provide a rapid and objective understanding of the processes driving geomorphic change at the reach and network scales. We anticipate that such an understanding will allow insight into the response of geomorphic transport processes to external forcings, such as shifts in climate, land use, or river regulation, with implications for process-based river management and restoration.
","language":"English","publisher":"Wiley","doi":"10.1002/esp.4143","usgsCitation":"Kasprak, A., Caster, J.J., Bangen, S.G., and Sankey, J.B., 2017, Geomorphic process from topographic form: automating the interpretation of repeat survey data in river valleys: Earth Surface Processes and Landforms, v. 42, no. 12, p. 1872-1883, https://doi.org/10.1002/esp.4143.","productDescription":"12 p.","startPage":"1872","endPage":"1883","ipdsId":"IP-079655","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":438376,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F73776X6","text":"USGS data release","linkHelpText":"Geomorphic Process from Topographic FormData & Models"},{"id":339687,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona, Colorado","otherGeospatial":"Colorado River, Grand Canyon","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -113.8787841796875,\n 35.67068501330236\n ],\n [\n -111.258544921875,\n 35.67068501330236\n ],\n [\n -111.258544921875,\n 37.077093191754436\n ],\n [\n -113.8787841796875,\n 37.077093191754436\n ],\n [\n -113.8787841796875,\n 35.67068501330236\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"42","issue":"12","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2017-04-10","publicationStatus":"PW","scienceBaseUri":"58f08e5de4b06911a29fa83c","contributors":{"authors":[{"text":"Kasprak, Alan 0000-0001-8184-6128 akasprak@usgs.gov","orcid":"https://orcid.org/0000-0001-8184-6128","contributorId":190848,"corporation":false,"usgs":true,"family":"Kasprak","given":"Alan","email":"akasprak@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":690869,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Caster, Joshua J. 0000-0002-2858-1228 jcaster@usgs.gov","orcid":"https://orcid.org/0000-0002-2858-1228","contributorId":131114,"corporation":false,"usgs":true,"family":"Caster","given":"Joshua","email":"jcaster@usgs.gov","middleInitial":"J.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":false,"id":690902,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bangen, Sara G.","contributorId":190858,"corporation":false,"usgs":false,"family":"Bangen","given":"Sara","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":690903,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sankey, Joel B. 0000-0003-3150-4992 jsankey@usgs.gov","orcid":"https://orcid.org/0000-0003-3150-4992","contributorId":3935,"corporation":false,"usgs":true,"family":"Sankey","given":"Joel","email":"jsankey@usgs.gov","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":690904,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70186868,"text":"70186868 - 2017 - Simulation of rapid ecological change in Lake Ontario","interactions":[],"lastModifiedDate":"2017-09-11T12:54:47","indexId":"70186868","displayToPublicDate":"2017-04-12T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2330,"text":"Journal of Great Lakes Research","active":true,"publicationSubtype":{"id":10}},"title":"Simulation of rapid ecological change in Lake Ontario","docAbstract":"Lower trophic level processes are integral to proper functioning of large aquatic ecosystems and have been disturbed in Lake Ontario by various stressors including exotic species. The invasion of benthic habitats by dreissenid mussels has led to systemic changes and native faunal declines. Size-dependent physiological rates, spatial differences and connectivity, competition, and differential population dynamics among invertebrate groups contributed to the change and system complexity. We developed a spatially explicit, individual-based mechanistic model of the benthic ecosystem in Lake Ontario, with coupling to the pelagic system, to examine ecosystem dynamics and effects of dreissenid mussel invasion and native fauna losses. Benthic organisms were represented by functional groups; filter-feeders (i.e., dreissenid mussels), surface deposit-feeders (e.g., native amphipod Diporeia spp.), and deposit-feeders (e.g., oligochaetes and other burrowers). The model was stable, represented ecological structure and function effectively, and reproduced observed effects of the mussel invasion. Two hypotheses for causes of Diporeia loss, competition or disease-like mortality, were tested. Simple competition for food did not explain observed declines in native surface deposit-feeders during the filter-feeder invasion. However, the elevated mortality scenario supports a disease-like cause for loss of the native amphipod, with population changes in various lake areas and altered benthic biomass transfers. Stabilization of mussel populations and possible recovery of the native, surface-deposit feeding amphipod were predicted. Although further research is required on forcing functions, model parameters, and natural conditions, the model provides a valuable tool to help managers understand the benthic system and plan for response to future disruptions.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jglr.2017.03.008","usgsCitation":"McKenna, J., Chalupnicki, M., Dittman, D.E., and Watkins, J.M., 2017, Simulation of rapid ecological change in Lake Ontario: Journal of Great Lakes Research, v. 43, no. 5, p. 871-889, https://doi.org/10.1016/j.jglr.2017.03.008.","productDescription":"19 p.","startPage":"871","endPage":"889","ipdsId":"IP-064471","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":469931,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jglr.2017.03.008","text":"Publisher Index Page"},{"id":339623,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","otherGeospatial":"Lake Ontario","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -79.9530029296875,\n 43.17313537107136\n ],\n [\n -76.0858154296875,\n 43.17313537107136\n ],\n [\n -76.0858154296875,\n 44.27273816279087\n ],\n [\n -79.9530029296875,\n 44.27273816279087\n ],\n [\n -79.9530029296875,\n 43.17313537107136\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"43","issue":"5","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58ef3da7e4b0eed1ab8e3bc6","chorus":{"doi":"10.1016/j.jglr.2017.03.008","url":"http://dx.doi.org/10.1016/j.jglr.2017.03.008","publisher":"Elsevier BV","authors":"McKenna James E., Chalupnicki Marc, Dittman Dawn, Watkins James M.","journalName":"Journal of Great Lakes Research","publicationDate":"4/2017"},"contributors":{"authors":[{"text":"McKenna, James E. Jr. 0000-0002-1428-7597 jemckenna@usgs.gov","orcid":"https://orcid.org/0000-0002-1428-7597","contributorId":190798,"corporation":false,"usgs":true,"family":"McKenna","given":"James E.","suffix":"Jr.","email":"jemckenna@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":690734,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chalupnicki, Marc 0000-0002-3792-9345 mchalupnicki@usgs.gov","orcid":"https://orcid.org/0000-0002-3792-9345","contributorId":173643,"corporation":false,"usgs":true,"family":"Chalupnicki","given":"Marc","email":"mchalupnicki@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":690735,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dittman, Dawn E. 0000-0002-0711-3732 ddittman@usgs.gov","orcid":"https://orcid.org/0000-0002-0711-3732","contributorId":2762,"corporation":false,"usgs":true,"family":"Dittman","given":"Dawn","email":"ddittman@usgs.gov","middleInitial":"E.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":690736,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Watkins, James M.","contributorId":189286,"corporation":false,"usgs":false,"family":"Watkins","given":"James","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":690737,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70185571,"text":"70185571 - 2017 - Geotechnical aspects of the 2016 MW 6.2, MW 6.0, and MW 7.0 Kumamoto earthquakes","interactions":[],"lastModifiedDate":"2017-04-12T14:45:58","indexId":"70185571","displayToPublicDate":"2017-04-12T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":3,"text":"Organization Series"},"title":"Geotechnical aspects of the 2016 MW 6.2, MW 6.0, and MW 7.0 Kumamoto earthquakes","docAbstract":"The 2016 Kumamoto earthquakes are a series of events that began with an earthquake of moment magnitude 6.2 on the Hinagu Fault on April 14, 2016, followed by another foreshock of moment magnitude 6.0 on the Hinagu Fault on April 15, 2016, and a larger moment magnitude 7.0 event on the Futagawa Fault on April 16, 2016 beneath Kumamoto City, Kumamoto Prefecture on Kyushu, Japan. These events are the strongest earthquakes recorded in Kyushu during the modern instrumental era. The earthquakes resulted in substantial damage to infrastructure, buildings, cultural heritage of Kumamoto Castle, roads and highways, slopes, and river embankments due to earthquake-induced landsliding and debris flows. Surface fault rupture produced offset and damage to roads, buildings, river levees, and an agricultural dam. Surprisingly, given the extremely intense earthquake motions, liquefaction occurred only in a few districts of Kumamoto City and in the port areas indicating that the volcanic soils were less susceptible to liquefying than expected given the intensity of earthquake shaking, a significant finding from this event.
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Designed-bioactive anthropogenic contaminants (biocides, pharmaceuticals) comprised 57% of 406 organics detected at least once. The 10 most-frequently detected anthropogenic-organics included eight pesticides (desulfinylfipronil, AMPA, chlorpyrifos, dieldrin, metolachlor, atrazine, CIAT, glyphosate) and two pharmaceuticals (caffeine, metformin) with detection frequencies ranging 66–84% of all sites. Detected contaminant concentrations varied from less than 1 ng L–1 to greater than 10 μg L–1, with 77 and 278 having median detected concentrations greater than 100 ng L–1 and 10 ng L–1, respectively. Cumulative detections and concentrations ranged 4–161 compounds (median 70) and 8.5–102 847 ng L–1, respectively, and correlated significantly with wastewater discharge, watershed development, and toxic release inventory metrics. 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Doing so requires modeling vital rates in the context of species life-history, behavior, and population dynamics theory. In this paper, we explore the details of such an analysis by focusing on the demography of a resident, tree-nesting population of golden eagles (Aquila chrysaetos) in the vicinity of an extensive (142 km2) windfarm in California. During 1994–2000, we tracked the fates of >250 radio-marked individuals of four life-stages and conducted five annual surveys of territory occupancy and reproduction. Collisions with wind turbines accounted for 41% of 88 uncensored fatalities, most of which were subadults and nonbreeding adults (floaters). A consistent overall male preponderance in the population meant that females were the limiting sex in this territorial, monogamous species. Estimates of potential population growth rate and associated variance indicated a stable breeding population, but one for which any further decrease in vital rates would require immigrant floaters to fill territory vacancies. Occupancy surveys 5 and 13 years later (2005 and 2013) showed that the nesting population remained intact, and no upward trend was apparent in the proportion of subadult eagles as pair members, a condition that would have suggested a deficit of adult replacements. However, the number of golden eagle pairs required to support windfarm mortality was large. We estimated that the entire annual reproductive output of 216–255 breeding pairs would have been necessary to support published estimates of 55–65 turbine blade-strike fatalities per year. Although the vital rates forming the basis for these calculations may have changed since the data were collected, our approach should be useful for gaining a clearer understanding of how anthropogenic mortality affects the health of raptor populations, particularly those species with delayed maturity and naturally low reproductive rates.
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This case study considers the prospects for doing so in a more analytically rigorous manner, by quantifying the pollination services for sites being considered for ecological restoration. The specific policy context is the Conservation Reserve Program (CRP), which offers financial and technical assistance to landowners seeking to convert sensitive cropland back to some semblance of the prairie (or, to a lesser extent, forest or wetland) ecosystem that preceded it. Depending on the mix of grasses and wildflowers that are established, CRP enrollments can provide pollinator habitat. Further, depending on their location, they will generate related services, such as biological control of crop pests, recreation, and aesthetics. While offers to enroll in CRP compete based on cost and some anticipated benefits, the eligibility and ranking criteria do not reflect these services to a meaningful degree. Therefore, we develop a conceptual value diagram to identify the sequence of steps and associated models and data necessary to quantify the full range of services, and find that critical data gaps, some of which are artifacts of policy, preclude the application of benefit-relevant indicators (BRIs) or monetization. However, we also find that there is considerable research activity underway to fill these gaps. In addition, a modeling framework has been developed that can estimate field-level effects on services as a function of landscape context. The approach is inherently scalable and not limited in geographic scope, which is essential for a program with a national footprint. The parameters in this framework are sufficiently straightforward that expert judgment could be applied as a stopgap approach until empirically derived estimates are available. While monetization of benefit-relevant indicators of yield changes (crop and honey) and of habitat benefits due to enhanced pollination and pest bio-control services would be relatively straightforward, the merits of proceeding when other services cannot be valued now should be carefully considered.","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"The valuation of ecosystem services from farms and forests","largerWorkSubtype":{"id":9,"text":"Other Report"},"language":"English","publisher":"Council on Food, Agriculture, and Resource Econimics (C-FARE)","doi":"10.22004/ag.econ.260678","usgsCitation":"Iovanna, R., Ando, A.W., Swinton, S., Hellerstein, D., Kagan, J., Mushet, D.M., Otto, C., and Rewa, C.A., 2017, Assessing pollinator habitat services to optimize conservation programs, 28 p., https://doi.org/10.22004/ag.econ.260678.","productDescription":"28 p.","ipdsId":"IP-080737","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":339590,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58ef3da8e4b0eed1ab8e3bce","contributors":{"authors":[{"text":"Iovanna, Richard","contributorId":190711,"corporation":false,"usgs":false,"family":"Iovanna","given":"Richard","email":"","affiliations":[],"preferred":false,"id":690462,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ando, Amy W.","contributorId":189611,"corporation":false,"usgs":false,"family":"Ando","given":"Amy","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":690464,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Swinton, Scott","contributorId":190713,"corporation":false,"usgs":false,"family":"Swinton","given":"Scott","email":"","affiliations":[],"preferred":false,"id":690465,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hellerstein, Daniel","contributorId":190712,"corporation":false,"usgs":false,"family":"Hellerstein","given":"Daniel","email":"","affiliations":[],"preferred":false,"id":690463,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kagan, Jimmy","contributorId":190714,"corporation":false,"usgs":false,"family":"Kagan","given":"Jimmy","email":"","affiliations":[],"preferred":false,"id":690467,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Mushet, David M. 0000-0002-5910-2744 dmushet@usgs.gov","orcid":"https://orcid.org/0000-0002-5910-2744","contributorId":1299,"corporation":false,"usgs":true,"family":"Mushet","given":"David","email":"dmushet@usgs.gov","middleInitial":"M.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":690461,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Otto, Clint 0000-0002-7582-3525 cotto@usgs.gov","orcid":"https://orcid.org/0000-0002-7582-3525","contributorId":5426,"corporation":false,"usgs":true,"family":"Otto","given":"Clint","email":"cotto@usgs.gov","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":690466,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Rewa, Charles A.","contributorId":189190,"corporation":false,"usgs":false,"family":"Rewa","given":"Charles","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":690468,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70185351,"text":"70185351 - 2017 - Facilitating adaptation in montane plants to changing precipitation along an elevation gradient","interactions":[],"lastModifiedDate":"2018-01-04T12:32:26","indexId":"70185351","displayToPublicDate":"2017-04-12T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"seriesTitle":{"id":295,"text":"Technical Report","active":false,"publicationSubtype":{"id":4}},"seriesNumber":"HCSU-080","title":"Facilitating adaptation in montane plants to changing precipitation along an elevation gradient","docAbstract":"Montane plant communities throughout the world have responded to changes in precipitation and temperature regimes by shifting ranges upward in elevation. Continued warmer, drier climate conditions have been documented and are projected to increase in high-elevation areas in Hawai‘i, consistent with climate change effects reported in other environments throughout the world. Organisms that cannot disperse or adapt biologically to projected climate scenarios in situ may decrease in distributional range and abundance over time. Restoration efforts will need\r\nto accommodate future climate change and account for the interactive effects of existing invasive species to ensure long-term persistence. As part of a larger, ongoing restoration effort, we hypothesized that plants from a lower-elevation forest ecotype would have higher rates of survival and growth compared to high-elevation forest conspecifics when grown in common plots along an elevation gradient. We monitored climate conditions at planting sites to identify whether temperature or rainfall influenced survival and growth after 20 weeks. We found that origin significantly affected survival in only one of three native montane species, Dodonaea viscosa. Contrary to our hypothesis, 75.2% of seedlings from high-elevation origin survived in comparison to 58.7% of seedlings from low elevation across the entire elevation gradient. Origin also influenced survival in linearized mixed models that controlled for temperature, precipitation, and elevation in D. viscosa and Chenopodium oahuense. Only C. oahuense seedlings had similar predictors of growth and survival. There were no common patterns of growth or survival between species, indicating that responses to changing precipitation and emperature regimes varied between montane plant species. Results also suggest that locally sourced seed is important to ensure highest survival at restoration sites. Further experimentation on larger spatial and temporal scales is necessary to determine the empirical responses of species and communities to changing climate in the full context of highly degraded Hawaiian ecosystems.","language":"English","publisher":"University of Hawaii Hilo","publisherLocation":"Hilo, HI","usgsCitation":"Hess, S.C., and Leopold, C., 2017, Facilitating adaptation in montane plants to changing precipitation along an elevation gradient: Technical Report HCSU-080, iv, 33 p.","productDescription":"iv, 33 p.","ipdsId":"IP-080120","costCenters":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"links":[{"id":339621,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawai'i","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -155.65155029296875,\n 19.846810534206607\n ],\n [\n -155.65429687499997,\n 19.777042202225964\n ],\n [\n -155.60211181640625,\n 19.735683578629445\n ],\n [\n -155.56365966796875,\n 19.730512997022263\n ],\n [\n -155.5389404296875,\n 19.70724330927441\n ],\n [\n -155.48675537109375,\n 19.694314241825747\n ],\n [\n -155.43182373046875,\n 19.70724330927441\n ],\n [\n -155.37139892578125,\n 19.746024239625427\n ],\n [\n -155.32745361328125,\n 19.81063818250419\n ],\n [\n -155.33294677734375,\n 19.872642883577086\n ],\n [\n -155.36041259765625,\n 19.92945922975802\n ],\n [\n -155.40435791015622,\n 19.944951054874966\n ],\n [\n -155.47576904296875,\n 19.944951054874966\n ],\n [\n -155.54718017578125,\n 19.924294950473808\n ],\n [\n -155.6048583984375,\n 19.882974645034466\n ],\n [\n -155.65155029296875,\n 19.846810534206607\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58ef3daae4b0eed1ab8e3bd8","contributors":{"authors":[{"text":"Hess, Steve C. 0000-0001-6403-9922 shess@usgs.gov","orcid":"https://orcid.org/0000-0001-6403-9922","contributorId":150366,"corporation":false,"usgs":true,"family":"Hess","given":"Steve","email":"shess@usgs.gov","middleInitial":"C.","affiliations":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true},{"id":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true}],"preferred":true,"id":685278,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Leopold, Christina 0000-0003-0499-3196","orcid":"https://orcid.org/0000-0003-0499-3196","contributorId":178961,"corporation":false,"usgs":false,"family":"Leopold","given":"Christina","affiliations":[],"preferred":false,"id":685279,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70184176,"text":"70184176 - 2017 - Final data report for factors controlling DDE dechlorination rates on the Palos Verdes Shelf: A field and laboratory investigation","interactions":[],"lastModifiedDate":"2019-03-06T13:44:23","indexId":"70184176","displayToPublicDate":"2017-04-12T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"title":"Final data report for factors controlling DDE dechlorination rates on the Palos Verdes Shelf: A field and laboratory investigation","docAbstract":"This data report provides a compilation of information developed over the last 6+ years by a\nmulti-disciplinary, multi-institutional research team. The overall goal of this work has been to\nidentify the biological, chemical, and physical factors that control rates of reductive\ndechlorination of DDE and DDMU in sediments of the Palos Verdes Shelf (PVS). More specific\nquestions and objectives are delineated in the Scope of Work (section 12.1., Appendix 1).\nThe study was composed of two parts: 1) field characterization studies, and 2) laboratory\nmicrocosm experiments. The goal of the field characterization studies was to define the\nconditions under which reductive dechlorination of DDE (and DDMU) is occurring in PVS\nsediments. This involved two separate cruises (2009, 2010) during which sediment cores,\nbottom water and other real-time field measurements (e.g., conductivity, temperature, depth of\nthe water column) were acquired. The sediment cores were distributed among research team\nmembers for detailed chemical (R. Eganhouse, B. Orem, M. Reinhard), microbiological (A.\nSpormann), and physical (B. Edwards) analysis as well as for laboratory microcosm experiments\n(M. Reinhard). A team of collaborating USGS scientists generously contributed valuable\ninformation pertaining to geochronology (P. Swarzenski), the character of sedimentary\ngeosorbent phases (P. Hackley), mineralogy (D. Webster), and grain-size characteristics (C.\nSherwood) of PVS sediment samples.\nTogether, this information will serve as framework for a conceptual model of natural degradation\nprocesses in the DDT-contaminated sediments on the PVS. These findings will enable the\nUSEPA to gain a better understanding of the controls on reductive dechlorination and how\ndechlorination rates vary spatially and temporally. This, in turn, should facilitate decision\nmaking concerning the progress of natural attenuation and when monitoring at the site can be\nterminated. Toward that end, a brief Synthesis Report, summarizing and interpreting the\nacquired data, is being prepared and will be released in the coming year.","language":"English","publisher":"U.S. Environmental Protection Agency","usgsCitation":"Eganhouse, R., Pontolillo, J., Orem, W.H., Webster, D.M., Hackley, P.C., Edwards, B.D., Rosenberger, K.J., Dickhudt, P., Sherwood, C.R., Reinhard, M., Qin, S., Dougherty, J., Hopkins, G., Marshall, I., and Spormann, A., 2017, Final data report for factors controlling DDE dechlorination rates on the Palos Verdes Shelf: A field and laboratory investigation, Zip File.","productDescription":"Zip File","ipdsId":"IP-063652","costCenters":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"links":[{"id":339628,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":336716,"type":{"id":15,"text":"Index Page"},"url":"https://cumulis.epa.gov/supercpad/cursites/cscdocument.cfm?id=0900993&doc=Y&colid=36797"}],"country":"United States","otherGeospatial":"Palos Verdes Shelf","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -118.44085693359375,\n 33.773439833797724\n ],\n [\n -118.47381591796875,\n 33.799691173251084\n ],\n [\n -118.5163879394531,\n 33.78827853625996\n ],\n [\n -118.52600097656249,\n 33.76773195605407\n ],\n [\n -118.5150146484375,\n 33.75174787568194\n ],\n [\n -118.50128173828125,\n 33.71291698851023\n ],\n [\n -118.48205566406249,\n 33.678639851675555\n ],\n [\n -118.44223022460938,\n 33.64434904445888\n ],\n [\n -118.4230041503906,\n 33.63062889539564\n ],\n [\n -118.3941650390625,\n 33.618050171974545\n ],\n [\n -118.34747314453125,\n 33.622624465698685\n ],\n [\n -118.31039428710936,\n 33.63634588982396\n ],\n [\n -118.28018188476561,\n 33.67406853374198\n ],\n [\n -118.29666137695311,\n 33.687781758439364\n ],\n [\n -118.32550048828124,\n 33.70377775573253\n ],\n [\n -118.36120605468747,\n 33.72205524868731\n ],\n [\n -118.39691162109375,\n 33.7243396617476\n ],\n [\n -118.41339111328125,\n 33.73119253613475\n ],\n [\n -118.42849731445312,\n 33.75060604160645\n ],\n [\n -118.44085693359375,\n 33.773439833797724\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58ef3dabe4b0eed1ab8e3bdc","contributors":{"authors":[{"text":"Eganhouse, Robert P. eganhous@usgs.gov","contributorId":2031,"corporation":false,"usgs":true,"family":"Eganhouse","given":"Robert P.","email":"eganhous@usgs.gov","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":680343,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pontolillo, James jpontoli@usgs.gov","contributorId":2033,"corporation":false,"usgs":true,"family":"Pontolillo","given":"James","email":"jpontoli@usgs.gov","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":680344,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Orem, William H. 0000-0003-4990-0539 borem@usgs.gov","orcid":"https://orcid.org/0000-0003-4990-0539","contributorId":577,"corporation":false,"usgs":true,"family":"Orem","given":"William","email":"borem@usgs.gov","middleInitial":"H.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":680345,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Webster, Daniel M. webster@usgs.gov","contributorId":3529,"corporation":false,"usgs":true,"family":"Webster","given":"Daniel","email":"webster@usgs.gov","middleInitial":"M.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":680346,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hackley, Paul C. 0000-0002-5957-2551 phackley@usgs.gov","orcid":"https://orcid.org/0000-0002-5957-2551","contributorId":592,"corporation":false,"usgs":true,"family":"Hackley","given":"Paul","email":"phackley@usgs.gov","middleInitial":"C.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true}],"preferred":true,"id":680347,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Edwards, Brian D. bedwards@usgs.gov","contributorId":3161,"corporation":false,"usgs":true,"family":"Edwards","given":"Brian","email":"bedwards@usgs.gov","middleInitial":"D.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":680348,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Rosenberger, Kurt J. 0000-0002-5185-5776 krosenberger@usgs.gov","orcid":"https://orcid.org/0000-0002-5185-5776","contributorId":140453,"corporation":false,"usgs":true,"family":"Rosenberger","given":"Kurt","email":"krosenberger@usgs.gov","middleInitial":"J.","affiliations":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":680349,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Dickhudt, Patrick 0000-0001-8003-7089 pdickhudt@usgs.gov","orcid":"https://orcid.org/0000-0001-8003-7089","contributorId":187402,"corporation":false,"usgs":true,"family":"Dickhudt","given":"Patrick","email":"pdickhudt@usgs.gov","affiliations":[],"preferred":true,"id":680350,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Sherwood, Christopher R. 0000-0001-6135-3553 csherwood@usgs.gov","orcid":"https://orcid.org/0000-0001-6135-3553","contributorId":2866,"corporation":false,"usgs":true,"family":"Sherwood","given":"Christopher","email":"csherwood@usgs.gov","middleInitial":"R.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":680351,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Reinhard, Martin","contributorId":187403,"corporation":false,"usgs":false,"family":"Reinhard","given":"Martin","email":"","affiliations":[],"preferred":false,"id":680352,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Qin, Sujie","contributorId":187404,"corporation":false,"usgs":false,"family":"Qin","given":"Sujie","email":"","affiliations":[],"preferred":false,"id":680353,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Dougherty, Jennifer","contributorId":187405,"corporation":false,"usgs":false,"family":"Dougherty","given":"Jennifer","affiliations":[],"preferred":false,"id":680354,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Hopkins, Gary","contributorId":187406,"corporation":false,"usgs":false,"family":"Hopkins","given":"Gary","affiliations":[],"preferred":false,"id":680355,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Marshall, Ian","contributorId":187407,"corporation":false,"usgs":false,"family":"Marshall","given":"Ian","email":"","affiliations":[],"preferred":false,"id":680356,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Spormann, Alfred","contributorId":187408,"corporation":false,"usgs":false,"family":"Spormann","given":"Alfred","email":"","affiliations":[],"preferred":false,"id":680357,"contributorType":{"id":1,"text":"Authors"},"rank":15}]}} ,{"id":70190047,"text":"70190047 - 2017 - A new model for turbidity current behavior based on integration of flow monitoring and precision coring in a submarine canyon","interactions":[],"lastModifiedDate":"2017-08-07T17:09:12","indexId":"70190047","displayToPublicDate":"2017-04-12T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1796,"text":"Geology","active":true,"publicationSubtype":{"id":10}},"title":"A new model for turbidity current behavior based on integration of flow monitoring and precision coring in a submarine canyon","docAbstract":"Submarine turbidity currents create some of the largest sediment accumulations on Earth, yet there are few direct measurements of these flows. Instead, most of our understanding of turbidity currents results from analyzing their deposits in the sedimentary record. However, the lack of direct flow measurements means that there is considerable debate regarding how to interpret flow properties from ancient deposits. This novel study combines detailed flow monitoring with unusually precisely located cores at different heights, and multiple locations, within the Monterey submarine canyon, offshore California, USA. Dating demonstrates that the cores include the time interval that flows were monitored in the canyon, albeit individual layers cannot be tied to specific flows. There is good correlation between grain sizes collected by traps within the flow and grain sizes measured in cores from similar heights on the canyon walls. Synthesis of flow and deposit data suggests that turbidity currents sourced from the upper reaches of Monterey Canyon comprise three flow phases. Initially, a thin (38–50 m) powerful flow in the upper canyon can transport, tilt, and break the most proximal moorings and deposit chaotic sands and gravel on the canyon floor. The initially thin flow front then thickens and deposits interbedded sands and silty muds on the canyon walls as much as 62 m above the canyon floor. Finally, the flow thickens along its length, thus lofting silty mud and depositing it at greater altitudes than the previous deposits and in excess of 70 m altitude.","language":"English","publisher":"Geological Society of America","doi":"10.1130/G38764.1","usgsCitation":"Symons, W.O., Sumner, E.J., Paull, C.K., Cartigny, M.J., Xu, J., Maier, K., Lorenson, T., and Talling, P.J., 2017, A new model for turbidity current behavior based on integration of flow monitoring and precision coring in a submarine canyon: Geology, v. 45, no. 4, p. 367-370, https://doi.org/10.1130/G38764.1.","productDescription":"4 p.","startPage":"367","endPage":"370","ipdsId":"IP-075966","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":469934,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/g38764.1","text":"Publisher Index Page"},{"id":344623,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"45","issue":"4","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2017-04-01","publicationStatus":"PW","scienceBaseUri":"59897c15e4b09fa1cb0c2c04","contributors":{"authors":[{"text":"Symons, William O.","contributorId":195511,"corporation":false,"usgs":false,"family":"Symons","given":"William","email":"","middleInitial":"O.","affiliations":[],"preferred":false,"id":707308,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sumner, Esther J.","contributorId":195512,"corporation":false,"usgs":false,"family":"Sumner","given":"Esther","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":707309,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Paull, Charles K. 0000-0001-5940-3443","orcid":"https://orcid.org/0000-0001-5940-3443","contributorId":55825,"corporation":false,"usgs":false,"family":"Paull","given":"Charles","email":"","middleInitial":"K.","affiliations":[{"id":7043,"text":"University of North Carolina","active":true,"usgs":false}],"preferred":true,"id":707310,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cartigny, Matthieu J.B.","contributorId":195513,"corporation":false,"usgs":false,"family":"Cartigny","given":"Matthieu","email":"","middleInitial":"J.B.","affiliations":[],"preferred":false,"id":707311,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Xu, Jingping","contributorId":195514,"corporation":false,"usgs":false,"family":"Xu","given":"Jingping","affiliations":[],"preferred":false,"id":707312,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Maier, Katherine L.","contributorId":91411,"corporation":false,"usgs":true,"family":"Maier","given":"Katherine L.","affiliations":[],"preferred":false,"id":707307,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Lorenson, Thomas 0000-0001-7669-2873 tlorenson@usgs.gov","orcid":"https://orcid.org/0000-0001-7669-2873","contributorId":174599,"corporation":false,"usgs":true,"family":"Lorenson","given":"Thomas","email":"tlorenson@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":707313,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Talling, Peter J.","contributorId":195515,"corporation":false,"usgs":false,"family":"Talling","given":"Peter","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":707314,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70186227,"text":"sir20175030 - 2017 - Status and threats analysis for the Florida manatee (Trichechus manatus latirostris), 2016","interactions":[],"lastModifiedDate":"2024-03-04T20:25:12.948526","indexId":"sir20175030","displayToPublicDate":"2017-04-11T15:15:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2017-5030","title":"Status and threats analysis for the Florida manatee (Trichechus manatus latirostris), 2016","docAbstract":"Trichechus manatus (West Indian manatee), especially T. m. latirostris, the Florida subspecies, has been the focus of conservation efforts and extensive research since its listing under the Endangered Species Act of 1973. To determine the status of, and severity of threats to, the Florida manatee, a comprehensive revision and update of the manatee Core Biological Model was completed and used to perform a population viability analysis for the Florida manatee. The probability of the Florida manatee population falling below 500 adults on either the Gulf or East coast within the next 100 years was estimated to be 0.42 percent. This risk of quasi-extinction is low because the estimated adult survival rates are high, the current population size is greater than 2,500 on each coast, and the estimated carrying capacity for manatees is much larger than the current abundance estimates in all four regions of Florida. Three threats contribute in roughly equal measures to the risk of quasi-extinction: watercraft-related mortality, red-tide mortality, and loss of warm-water habitat. Only an increase in watercraft-related mortality has the potential to substantially increase the risk of quasi-extinction at the statewide or coastal level. Expected losses of warm-water habitat are likely to cause a major change in the distribution of the population from the regions where manatees rely heavily on power plant effluents for warmth in winter (Southwest and Atlantic regions) to the regions where manatees primarily use natural springs in winter (Northwest and Upper St. Johns regions). The chances are nearly 50 percent that manatee populations in the Southwest and Atlantic regions will decrease from their 2011 levels by at least 30 percent over the next century.
A large number of scenarios were examined to explore the possible effects of potential emerging threats, and in most of them, the risk of quasi-extinction at the coastal scale within 100 years did not rise above 1 percent. The four exceptions are scenarios in which the rate of watercraft-related mortality increases, carrying capacity is only a fraction of the current estimates, a new chronic source of mortality emerges, or multiple threats emerge in concert. Even in these scenarios, however, the risk of falling below 500 adults on either the East coast or the Gulf coast within 100 years from 2011 is less than 10 percent. High adult survival provides the population with strong resilience to a variety of current and future threats. On the basis of these analyses, we conclude that if these threats continue to be managed effectively, manatees are likely to persist on both coasts of Florida and remain an integral part of the coastal Florida ecosystem through the 21st century. If vigilance in management is reduced, however, the scenarios in which manatees could face risk of decline become more likely.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175030","collaboration":"Prepared in cooperation with the Florida Fish and Wildlife Conservation Commission","usgsCitation":"Runge, M.C., Sanders-Reed, C.A., Langtimm, C.A., Hostetler, J.A., Martin, Julien, Deutsch, C.J., Ward-Geiger, L.I., and Mahon, G.L., 2017, Status and threats analysis for the Florida manatee (Trichechus manatus latirostris), 2016: U.S. Geological Survey Scientific Investigation Report 2017–5030, 40 p., https://doi.org/10.3133/sir20175030.","productDescription":"ix, 40 p.","numberOfPages":"54","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-083198","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":339559,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5030/sir20175030.pdf","text":"Report","size":"2.59 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017-5030"},{"id":339558,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5030/coverthb2.jpg"}],"country":"United States","state":"Florida","contact":"Director, Eastern Ecological Science Center
U.S. Geological Survey
12100 Beech Forest Rd., Ste 4039
Laurel, MD 20708-4039
Electron donor (ED) addition can be very effective in stimulating enhanced reductive bioremediation (ERB) of a wide variety of groundwater contaminants. However, ERB can result in Secondary Water Quality Impacts (SWQIs) including decreased levels of dissolved oxygen (O2), nitrate (NO3- ), and sulfate (SO42- ), and elevated levels of dissolved manganese (Mn2+), dissolved iron (Fe2+), methane (CH4), sulfide (S2- ), organic carbon, and naturally occurring hazardous compounds (e.g., arsenic). Fortunately, this ‘plume’ of impacted groundwater is usually confined within the original contaminant plume and is unlikely to adversely impact potable water supplies. This report summarizes available information on processes controlling the production and natural attenuation of SWQI parameters and can be used as a guide in understanding the magnitude, areal extent, and duration of SWQIs in ERB treatment zones and the natural attenuation of SWQI parameters as the dissolved solutes migrate downgradient with ambient groundwater flow. This information was compiled from a wide variety of sources including a survey and statistical analysis of SWQIs from 47 ERB sites, geochemical model simulations, field studies at sites where organic-rich materials have entered the subsurface (e.g., wastewater, landfill leachate, and hydrocarbon plumes), and basic information on physical, chemical, and biological processes in the subsurface. This information is then integrated to provide a general conceptual model of the major processes controlling SWQI production and attenuation.
","language":"English","publisher":"Strategic Environmental Research and Development Program","usgsCitation":"Borden, R.C., Tillotson, J.M., Ng, G.C., Bekins, B.A., Kent, D.B., and Curtis, G.P., 2017, Extent and persistence of secondary water quality impacts after enhanced reductive bioremediation: Technical Report ER-2131, Report: xi; 54 p.; Appendix A.","productDescription":"Report: xi; 54 p.; Appendix A","ipdsId":"IP-068922","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"links":[{"id":339562,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":339561,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.serdp-estcp.org/Program-Areas/Environmental-Restoration/Contaminated-Groundwater/Emerging-Issues/ER-2131/ER-2131"}],"country":"United States","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58edb945e4b0eed1ab8c6f09","contributors":{"authors":[{"text":"Borden, Robert C.","contributorId":179311,"corporation":false,"usgs":false,"family":"Borden","given":"Robert","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":663283,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tillotson, Jason M.","contributorId":179312,"corporation":false,"usgs":false,"family":"Tillotson","given":"Jason","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":663284,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ng, Gene-Hua Crystal gng@usgs.gov","contributorId":5313,"corporation":false,"usgs":true,"family":"Ng","given":"Gene-Hua","email":"gng@usgs.gov","middleInitial":"Crystal","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":663285,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"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":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true}],"preferred":true,"id":663282,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kent, Douglas B. 0000-0003-3758-8322 dbkent@usgs.gov","orcid":"https://orcid.org/0000-0003-3758-8322","contributorId":1871,"corporation":false,"usgs":true,"family":"Kent","given":"Douglas","email":"dbkent@usgs.gov","middleInitial":"B.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":663286,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Curtis, Gary P. 0000-0003-3975-8882 gpcurtis@usgs.gov","orcid":"https://orcid.org/0000-0003-3975-8882","contributorId":2346,"corporation":false,"usgs":true,"family":"Curtis","given":"Gary","email":"gpcurtis@usgs.gov","middleInitial":"P.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":663287,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70185001,"text":"70185001 - 2017 - Temperature","interactions":[],"lastModifiedDate":"2020-08-20T19:35:31.560536","indexId":"70185001","displayToPublicDate":"2017-04-11T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"6","title":"Temperature","docAbstract":"Stream temperature has direct and indirect effects on stream ecology and is critical in determining both abiotic and biotic system responses across a hierarchy of spatial and temporal scales. Temperature variation is primarily driven by solar radiation, while landscape topography, geology, and stream reach scale ecosystem processes contribute to local variability. Spatiotemporal heterogeneity in freshwater ecosystems influences habitat distributions, physiological functions, and phenology of all aquatic organisms. In this chapter we provide an overview of methods for monitoring stream temperature, characterization of thermal profiles, and modeling approaches to stream temperature prediction. Recent advances in temperature monitoring allow for more comprehensive studies of the underlying processes influencing annual variation of temperatures and how thermal variability may impact aquatic organisms at individual, population, and community based scales. Likewise, the development of spatially explicit predictive models provide a framework for simulating natural and anthropogenic effects on thermal regimes which is integral for sustainable management of freshwater systems.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Methods in stream ecology","language":"English","publisher":"Elsevier","publisherLocation":"San Diego, CA","usgsCitation":"Jones, L.A., Muhlfeld, C.C., and Hauer, F.R., 2017, Temperature, chap. 6 of Methods in stream ecology, v. 1, p. 109-120.","productDescription":"12 p.","startPage":"109","endPage":"120","ipdsId":"IP-080478","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":339560,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":339557,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.elsevier.com/books/methods-in-stream-ecology/hauer/978-0-12-416558-8"}],"volume":"1","edition":"3rd","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58edb945e4b0eed1ab8c6f07","contributors":{"editors":[{"text":"F. Richard Hauer","contributorId":145878,"corporation":false,"usgs":false,"family":"F. Richard Hauer","affiliations":[{"id":6580,"text":"University of Montana, Flathead Lake Biological Station, Polson, Montana 59860, USA","active":true,"usgs":false}],"preferred":false,"id":690625,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Lamberti, G. A.","contributorId":44229,"corporation":false,"usgs":false,"family":"Lamberti","given":"G.","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":690626,"contributorType":{"id":2,"text":"Editors"},"rank":2}],"authors":[{"text":"Jones, Leslie A.","contributorId":145885,"corporation":false,"usgs":false,"family":"Jones","given":"Leslie","email":"","middleInitial":"A.","affiliations":[{"id":16281,"text":"USGS NOROCK Temporary Appt.","active":true,"usgs":false}],"preferred":false,"id":683892,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Muhlfeld, Clint C. 0000-0002-4599-4059 cmuhlfeld@usgs.gov","orcid":"https://orcid.org/0000-0002-4599-4059","contributorId":924,"corporation":false,"usgs":true,"family":"Muhlfeld","given":"Clint","email":"cmuhlfeld@usgs.gov","middleInitial":"C.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":683891,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hauer, F. Richard","contributorId":189116,"corporation":false,"usgs":false,"family":"Hauer","given":"F.","email":"","middleInitial":"Richard","affiliations":[],"preferred":false,"id":683893,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70186797,"text":"70186797 - 2017 - Groundwater flow model for the Little Plover River basin in Wisconsin’s Central Sands","interactions":[],"lastModifiedDate":"2017-04-11T10:40:43","indexId":"70186797","displayToPublicDate":"2017-04-11T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":9,"text":"Other Report"},"seriesTitle":{"id":5368,"text":"Bulletin","active":true,"publicationSubtype":{"id":9}},"seriesNumber":"111","title":"Groundwater flow model for the Little Plover River basin in Wisconsin’s Central Sands","docAbstract":"The Little Plover River is a groundwater-fed stream in the sand plains region of central Wisconsin. In this region, sandy sediment deposited during or soon after the last glaciation forms an important unconfined sand and gravel aquifer. This aquifer supplies water for numerous high-capacity irrigation, municipal, and industrial wells that support a thriving agricultural industry. In recent years the addition of many new wells, combined with observed diminished flows in the Little Plover and other nearby rivers, has raised concerns about the impacts of the wells on groundwater levels and on water levels and flows in nearby lakes, streams, and wetlands. Diverse stakeholder groups, including well operators, Growers, environmentalists, local land owners, and regulatory and government officials have sought a better understanding of the local groundwater-surface water system and have a shared desire to balance the water needs of the he liagricultural, industrial, and urban users with the maintenance and protection of groundwater-dependent natural resources. To help address these issues, the Wisconsin Department of Natural Resources requested that the Wisconsin Geological and Natural History Survey and U.S. Geological Survey cooperatively develop a groundwater flow model that could be used to demonstrate the relationships among groundwater, surface water, and well withdrawals and also be a tool for testing and evaluating alternative water management strategies for the central sands region. Because of an abundance of previous studies, data availability, local interest, and existing regulatory constraints the model focuses on the Little Plover River watershed, but the modeling methodology developed during this study can apply to much of the larger central sands of Wisconsin. The
Little Plover River groundwater flow model simulates three-dimensional groundwater movement in and around the Little Plover River basin under steady-state and transient conditions. This model explicitly includes all high-capacity wells in the model domain and simulates seasonal variations in recharge and well pumping. The model represents the Little Plover River, and other significant streams and drainage ditches in the model domain, as fully connected to the groundwater system, computes stream base flow resulting from groundwater discharge, and routes the flow along the stream channel. A separate soil-water-balance (SWB) model was used to develop groundwater recharge arrays as input for the groundwater flow model. The SWB model uses topography, soils, land use, and climatic data to estimate recharge as deep drainage from the soil zone. The SWB model explicitly includes recharge originating as irrigation water, and computes irrigation using techniques similar to those used by local irrigation operators.
The groundwater flow model uses the U.S. Geological Survey’s MODFLOW modeling code which is freely available, widely accepted, and commonly used by the groundwater community. The groundwater flow model and the SWB model use identical high-resolution numerical grids having model cells 100 feet on a side, with physical properties assigned to each grid cell. This grid allows accurate geographic placement of wells, streams, and other model features. The 3-dimensional grid has three layers; layers 1 and 2 represent the sand and gravel aquifer and layer 3 represents the underlying sandstone. The distribution of material properties in the model (hydraulic conductivity, aquifer thickness, etc.) comes from previous published geologic studies of the region, updated by calibration to recent streamflow and groundwater level data. The SWB model operates on a daily time step. The groundwater flow model was calibrated to monthly stress periods with time steps ranging from 1 to 16 days. More detailed time discretization is possible.
The groundwater model was calibrated to water-level and streamflow data collected during 2013 and 2014 by adjusting model parameters (primarily hydraulic conductivity, storage, and recharge) until the model produced a conditionally optimal fit between field observations and model output, subject to consistency with previously published geologic studies. Calibration was performed under both steady and transient conditions, and used a sophisticated parameter-estimation procedure (PEST) for the calibration process and to identify important model parameters. For the Little Plover River, the two most important parameters are the global recharge multiplier and the hydraulic conductivity of the stream bed. The calibrated model produces water-level and mass-balance results that are consistent with field observations and previous studies of the area.
The completed model is a powerful tool for testing and demonstrating alternative water-management scenarios. Example model applications described in this report include simulating how the cumulative impacts of pumping and land-use change have affected average baseflow in the Little Plover River. Depletion-potential mapping represents a method for predicting which wells and well locations have the greatest impact on nearby surface-water resources.
The completed model is publicly available, along with a companion user’s guide to assist with its operation, at http://wgnhs.org/littleplover- river-groundwater-model.
","language":"English","publisher":"Wisconsin Geological and Natural History Survey","publisherLocation":"Madison, WI","usgsCitation":"Bradbury, K., Fienen, M., Kniffin, M., Jacob Krause, Westenbroek, S.M., Leaf, A.T., and Barlow, P.M., 2017, Groundwater flow model for the Little Plover River basin in Wisconsin’s Central Sands: Bulletin 111, Zip file: Report: x, 82 p., Appendixes 1-8.","productDescription":"Zip file: Report: x, 82 p., Appendixes 1-8","ipdsId":"IP-080836","costCenters":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"links":[{"id":339550,"type":{"id":15,"text":"Index Page"},"url":"https://wgnhs.org/little-plover-river-groundwater-model/"},{"id":339556,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wisconsin","otherGeospatial":"Little Plover River watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": 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Water","active":true,"usgs":true}],"preferred":true,"id":690597,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70186809,"text":"70186809 - 2017 - Is biotic resistance enhanced by natural variation in diversity?","interactions":[],"lastModifiedDate":"2017-10-02T13:00:25","indexId":"70186809","displayToPublicDate":"2017-04-11T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2939,"text":"Oikos","active":true,"publicationSubtype":{"id":10}},"title":"Is biotic resistance enhanced by natural variation in diversity?","docAbstract":"Theories linking diversity to ecosystem function have been challenged by the widespread observation of more exotic species in more diverse native communities. Few studies have addressed the underlying processes by dissecting how biotic resistance to new invaders may be shaped by the same environmental influences that determine diversity and other community properties.
In grasslands with heterogeneous soils, we added invaders and removed competitors to analyze the causes of invasion resistance. Abiotic resistance was measured using invader success in the absence of the resident community. Biotic resistance was measured as the reduction in invader success in the presence of the resident community.
Invaders were most successful where biotic resistance was lowest and abiotic resistance was highest, confirming the dominant role of biotic resistance. Contrary to theory, though, biotic resistance was highest where both species richness and functional diversity were lowest. In the multivariate framework of a structural equation model, biotic resistance was independent of community diversity, and was highest where fertile soils led to high community biomass.
Seed predation slightly augmented biotic resistance without qualitatively changing the results. Soil-related genotypic variation in the invader also did not affect the results.
We conclude that in natural systems, diversity may be correlated with invasibility and yet have little effect on biotic resistance to invasion. More generally, the environmental causes of variation in diversity should be considered when examining the potential functional consequences of diversity.
","language":"English","publisher":"Wiley","doi":"10.1111/oik.04334","usgsCitation":"Grace, J.B., Harrison, S.P., and Cornell, H., 2017, Is biotic resistance enhanced by natural variation in diversity?: Oikos, v. 126, no. 10, p. 1484-1492, https://doi.org/10.1111/oik.04334.","productDescription":"9 p.","startPage":"1484","endPage":"1492","ipdsId":"IP-082516","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":339565,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"126","issue":"10","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2017-05-17","publicationStatus":"PW","scienceBaseUri":"58edb943e4b0eed1ab8c6f01","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":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":690604,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Harrison, Susan P.","contributorId":147735,"corporation":false,"usgs":false,"family":"Harrison","given":"Susan","email":"","middleInitial":"P.","affiliations":[{"id":16917,"text":"Dept. of Env. Sci. and Policy, University of California, Davis","active":true,"usgs":false}],"preferred":false,"id":690605,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cornell, Howard","contributorId":149333,"corporation":false,"usgs":false,"family":"Cornell","given":"Howard","email":"","affiliations":[{"id":7214,"text":"University of California, Davis","active":true,"usgs":false}],"preferred":false,"id":690606,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70180400,"text":"ds1035 - 2017 - USGS Spectral Library Version 7","interactions":[{"subject":{"id":80486,"text":"ds231 - 2007 - USGS Digital Spectral Library splib06a","indexId":"ds231","publicationYear":"2007","noYear":false,"title":"USGS Digital Spectral Library splib06a"},"predicate":"SUPERSEDED_BY","object":{"id":70180400,"text":"ds1035 - 2017 - USGS Spectral Library Version 7","indexId":"ds1035","publicationYear":"2017","noYear":false,"title":"USGS Spectral Library Version 7"},"id":1}],"lastModifiedDate":"2025-01-31T18:24:46.250139","indexId":"ds1035","displayToPublicDate":"2017-04-10T13:15:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"1035","title":"USGS Spectral Library Version 7","docAbstract":"We have assembled a library of spectra measured with laboratory, field, and airborne spectrometers. The instruments used cover wavelengths from the ultraviolet to the far infrared (0.2 to 200 microns [μm]). Laboratory samples of specific minerals, plants, chemical compounds, and manmade materials were measured. In many cases, samples were purified, so that unique spectral features of a material can be related to its chemical structure. These spectro-chemical links are important for interpreting remotely sensed data collected in the field or from an aircraft or spacecraft. This library also contains physically constructed as well as mathematically computed mixtures. Four different spectrometer types were used to measure spectra in the library: (1) Beckman™ 5270 covering the spectral range 0.2 to 3 µm, (2) standard, high resolution (hi-res), and high-resolution Next Generation (hi-resNG) models of Analytical Spectral Devices (ASD) field portable spectrometers covering the range from 0.35 to 2.5 µm, (3) Nicolet™ Fourier Transform Infra-Red (FTIR) interferometer spectrometers covering the range from about 1.12 to 216 µm, and (4) the NASA Airborne Visible/Infra-Red Imaging Spectrometer AVIRIS, covering the range 0.37 to 2.5 µm. Measurements of rocks, soils, and natural mixtures of minerals were made in laboratory and field settings. Spectra of plant components and vegetation plots, comprising many plant types and species with varying backgrounds, are also in this library. Measurements by airborne spectrometers are included for forested vegetation plots, in which the trees are too tall for measurement by a field spectrometer. This report describes the instruments used, the organization of materials into chapters, metadata descriptions of spectra and samples, and possible artifacts in the spectral measurements. To facilitate greater application of the spectra, the library has also been convolved to selected spectrometer and imaging spectrometers sampling and bandpasses, and resampled to selected broadband multispectral sensors. The native file format of the library is the SPECtrum Processing Routines (SPECPR) data format. This report describes how to access freely available software to read the SPECPR format. To facilitate broader access to the library, we produced generic formats of the spectra and metadata in text files. The library is provided on digital media and online at https://speclab.cr.usgs.gov/spectral-lib.html. A long-term archive of these data are stored on the USGS ScienceBase data server (https://dx.doi.org/10.5066/F7RR1WDJ).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds1035","usgsCitation":"Kokaly, R.F., Clark, R.N., Swayze, G.A., Livo, K.E., Hoefen, T.M., Pearson, N.C., Wise, R.A., Benzel, W.M., Lowers, H.A., Driscoll, R.L., and Klein, A.J., 2017, USGS Spectral Library Version 7: U.S. Geological Survey Data Series 1035, 61 p., https://doi.org/10.3133/ds1035.","productDescription":"Report: iv, 61 p.; Dataset; Data Release","numberOfPages":"68","onlineOnly":"Y","ipdsId":"IP-075936","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":336935,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/1035/coverthb.jpg"},{"id":336936,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/1035/ds1035.pdf","text":"Report","size":"4.45 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DS 1035"},{"id":438380,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7RR1WDJ","text":"USGS data release","linkHelpText":"USGS Spectral Library Version 7 Data"}],"contact":"Center Director, USGS Crustal Geophysics and Geochemistry Science Center
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Hyrdokinetic tidal energy is the conversion of tidal current kinetic energy to another more useful form, frequently electricity. As with any other form of renewable energy, resource assessments are essential for the tidal energy project planning and design process. While tidal currents have significant spatial and temporal variability, the predictability of tidal flows makes deterministic modeling a suitable methodology for hydrokinetic tidal energy resource assessments. The scope (theoretical, technical, or practical resource) and scale (turbine, region, or project) of the assessment determine the basic concepts and methodology to be utilized and are described in this chapter. At the turbine scale, the technical resource is frequently quantified as the annual energy production (AEP) computed based on the velocity probability distribution for the specific location as well as the turbine properties. The uncertainty associated with the estimates of the AEP is highly dependent on the accuracy of the tidal constituent amplitudes and phases. Regional resource assessments are frequently used to determine the feasibility of tidal power at the scale of an estuary, using numerical models to predict the spatial distribution of the power density. In addition, simplified models or even analytical analysis can be done to produce an upper bound on the regional theoretical power, although with a high level of uncertainty due to the simplifications and assumptions. Resource assessments at the project scale provide both the theoretical and the technical energy as well as the practical energy accounting for many additional constraints, including social, economic, and environmental restrictions. The International Electrotechnical Commission technical specification for tidal energy resource assessments (IEC 2015) provides the essential guidelines for performing project-scale resource assessments. These guidelines include minimum grid resolution requirements as well as model calibration and validation procedures. In addition, larger projects will need to include the effect of energy extraction on the flow field to produce more accurate estimates of velocity probability distributions for computing the technical resource. An example case study demonstrating a regional feasibility and project-scale resource assessment is presented in this chapter.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Marine renewable energy","largerWorkSubtype":{"id":15,"text":"Monograph"},"publisher":"Springer","doi":"10.1007/978-3-319-53536-4_4","usgsCitation":"Haas, K., Defne, Z., Yang, X., and Bruder, B., 2017, Hydrokinetic tidal energy resource assessments using numerical models, chap. of Marine renewable energy, p. 99-120, https://doi.org/10.1007/978-3-319-53536-4_4.","productDescription":"22 p.","startPage":"99","endPage":"120","ipdsId":"IP-079038","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":413616,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationDate":"2017-04-10","publicationStatus":"PW","contributors":{"editors":[{"text":"Yang, Zhaoqing","contributorId":302797,"corporation":false,"usgs":false,"family":"Yang","given":"Zhaoqing","email":"","affiliations":[],"preferred":false,"id":865470,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Copping, Andrea","contributorId":81806,"corporation":false,"usgs":true,"family":"Copping","given":"Andrea","email":"","affiliations":[],"preferred":false,"id":865471,"contributorType":{"id":2,"text":"Editors"},"rank":2}],"authors":[{"text":"Haas, Kevin","contributorId":23832,"corporation":false,"usgs":true,"family":"Haas","given":"Kevin","affiliations":[],"preferred":false,"id":865466,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Defne, Zafer 0000-0003-4544-4310 zdefne@usgs.gov","orcid":"https://orcid.org/0000-0003-4544-4310","contributorId":5520,"corporation":false,"usgs":true,"family":"Defne","given":"Zafer","email":"zdefne@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":865467,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Yang, Xiufeng","contributorId":302796,"corporation":false,"usgs":false,"family":"Yang","given":"Xiufeng","email":"","affiliations":[],"preferred":false,"id":865468,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bruder, Brittany","contributorId":298808,"corporation":false,"usgs":false,"family":"Bruder","given":"Brittany","email":"","affiliations":[{"id":64689,"text":"Coastal and Hydraulics Laboratory, US Army Engineer Research and Development Center, Kitty Hawk, NC","active":true,"usgs":false}],"preferred":false,"id":865469,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70186750,"text":"70186750 - 2017 - Effects of climate change and anthropogenic modification on a disturbance-dependent species in a large riverine system","interactions":[],"lastModifiedDate":"2017-04-10T08:58:09","indexId":"70186750","displayToPublicDate":"2017-04-10T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Effects of climate change and anthropogenic modification on a disturbance-dependent species in a large riverine system","docAbstract":"Humans have altered nearly every natural disturbance regime on the planet through climate and land-use change, and in many instances, these processes may have interacting effects. For example, projected shifts in temperature and precipitation will likely influence disturbance regimes already affected by anthropogenic fire suppression or river impoundments. Understanding how disturbance-dependent species respond to complex and interacting environmental changes is important for conservation efforts. Using field-based demographic and movement rates, we conducted a metapopulation viability analysis for piping plovers (Charadrius melodus), a threatened disturbance-dependent species, along the Missouri and Platte rivers in the Great Plains of North America. Our aim was to better understand current and projected future metapopulation dynamics given that natural disturbances (flooding or high-flow events) have been greatly reduced by river impoundments and that climate change could further alter the disturbance regime. Although metapopulation abundance has been substantially reduced under the current suppressed disturbance regime (high-flow return interval ~ 20 yr), it could grow if the frequency of high-flow events increases as predicted under likely climate change scenarios. We found that a four-year return interval would maximize metapopulation abundance, and all subpopulations in the metapopulation would act as sources at a return interval of 15 yr or less. Regardless of disturbance frequency, the presence of even a small, stable source subpopulation buffered the metapopulation and sustained a low metapopulation extinction risk. Therefore, climate change could have positive effects in ecosystems where disturbances have been anthropogenically suppressed when climatic shifts move disturbance regimes toward more historical patterns. Furthermore, stable source populations, even if unintentionally maintained through anthropogenic activities, may be critical for the persistence of metapopulations of early-successional species under both suppressed disturbance regimes and disturbance regimes where climate change has further altered disturbance frequency or scope.
","language":"English","publisher":"Ecological Society of America","publisherLocation":"Washington, D.C.","doi":"10.1002/ecs2.1653","usgsCitation":"Zeigler, S.L., Catlin, D.H., Bomberger Brown, M., Fraser, J., Dinan, L.R., Hunt, K.L., Jorgensen, J.G., and Karpanty, S.M., 2017, Effects of climate change and anthropogenic modification on a disturbance-dependent species in a large riverine system: Ecosphere, v. 8, no. 1, e01653: 16 p., https://doi.org/10.1002/ecs2.1653.","productDescription":"e01653: 16 p.","ipdsId":"IP-080891","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":469937,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.1653","text":"Publisher Index Page"},{"id":339493,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Iowa, Nebraska, South Dakota","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -98.45,\n 40.5\n ],\n [\n -96,\n 40.5\n ],\n [\n -96,\n 43.5\n ],\n [\n -98.45,\n 43.5\n ],\n [\n -98.45,\n 40.5\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"8","issue":"1","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationDate":"2017-01-11","publicationStatus":"PW","scienceBaseUri":"58ebadaae4b0b4d95d320093","contributors":{"authors":[{"text":"Zeigler, Sara L. 0000-0002-5472-769X szeigler@usgs.gov","orcid":"https://orcid.org/0000-0002-5472-769X","contributorId":169601,"corporation":false,"usgs":true,"family":"Zeigler","given":"Sara","email":"szeigler@usgs.gov","middleInitial":"L.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":690452,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Catlin, Daniel H.","contributorId":87859,"corporation":false,"usgs":false,"family":"Catlin","given":"Daniel","email":"","middleInitial":"H.","affiliations":[{"id":33131,"text":"Dept of Fish and Wildlife Conservation, Virginia Tech","active":true,"usgs":false}],"preferred":false,"id":690453,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bomberger Brown, M.","contributorId":169602,"corporation":false,"usgs":false,"family":"Bomberger Brown","given":"M.","email":"","affiliations":[{"id":25563,"text":"School of Natural Resources, University of Nebraska, Lincoln, NE 68583","active":true,"usgs":false}],"preferred":false,"id":690454,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fraser, J.D.","contributorId":190706,"corporation":false,"usgs":false,"family":"Fraser","given":"J.D.","email":"","affiliations":[],"preferred":false,"id":690455,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dinan, Lauren R.","contributorId":169605,"corporation":false,"usgs":false,"family":"Dinan","given":"Lauren","email":"","middleInitial":"R.","affiliations":[{"id":25564,"text":"Nongame Bird Program, Nebraska Game and Parks Commission, Lincoln, NE 68503","active":true,"usgs":false}],"preferred":false,"id":690456,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hunt, Kelsi L.","contributorId":169606,"corporation":false,"usgs":false,"family":"Hunt","given":"Kelsi","email":"","middleInitial":"L.","affiliations":[{"id":12780,"text":"Department of Fish and Wildlife Conservation, Virginia Tech, Blacksburg, VA 24061, USA","active":true,"usgs":false}],"preferred":false,"id":690457,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Jorgensen, Joel G.","contributorId":169607,"corporation":false,"usgs":false,"family":"Jorgensen","given":"Joel","email":"","middleInitial":"G.","affiliations":[{"id":25564,"text":"Nongame Bird Program, Nebraska Game and Parks Commission, Lincoln, NE 68503","active":true,"usgs":false}],"preferred":false,"id":690458,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Karpanty, Sarah M.","contributorId":63307,"corporation":false,"usgs":false,"family":"Karpanty","given":"Sarah","email":"","middleInitial":"M.","affiliations":[{"id":33131,"text":"Dept of Fish and Wildlife Conservation, Virginia Tech","active":true,"usgs":false}],"preferred":false,"id":690459,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ]}