Freshwater mussels are ecologically and economically important members of many aquatic ecosystems, but are globally among the most imperiled taxa. Propagation techniques for mussels have been developed and used to boost declining and restore extirpated populations. Here we use a cohort of propagated mussels to estimate the intrinsic variability in size and growth rate of Lampsilis siliquoidea (a commonly propagated species). Understanding the magnitude and pattern of variation in data is critical to determining whether effects observed in nature or experimental treatments are likely to be important. The coefficient of variation (CV) of L. siliquoidea soft tissues (6.0%) was less than the CV of linear shell dimensions (25.1-66.9%). Size-weight relationships were best when mussel width (the maximum left-right dimension with both valves appressed) was used as a predictor, but 95% credible intervals on these predictions for soft tissues were ~145 mg wide (about 50% of the mean soft tissue mass). Mussels in this study were treated identically, raised from a single cohort and yet variation in soft tissue mass at a particular size class (as determined by shell dimensions) was still high. High variability in mussel size is often acknowledged, but seldom discussed in the context of mussel conservation. High variability will influence the survival of stocked juvenile cohorts, may affect the ability to experimentally detect sublethal stressors and may lead to incongruities between the effects that mussels have on structure (via hard shells) and biogeochemical cycles (via soft tissue metabolism). Given their imperiled status and longevity, there is often reluctance to destructively sample unionid mussel soft tissues even in metabolic studies (e.g., studies of nutrient cycling). High intrinsic variability suggests that using shell dimensions (particularly shell length) as a response variable in studies of sublethal stressors or metabolic processes will make confident identifications of smaller effect sizes difficult.
","language":"English","publisher":"Public Library of Science","doi":"10.1371/journal.pone.0112252","usgsCitation":"Larson, J.H., Eckert, N., and Bartsch, M., 2014, Intrinsic variability in shell and soft tissue growth of the freshwater mussel Lampsilis siliquoidea: PLoS ONE, v. 9, no. 11, e112252; 7 p., https://doi.org/10.1371/journal.pone.0112252.","productDescription":"e112252; 7 p.","numberOfPages":"7","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-058170","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":472632,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0112252","text":"Publisher Index Page"},{"id":296369,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"9","issue":"11","noUsgsAuthors":false,"publicationDate":"2014-11-20","publicationStatus":"PW","scienceBaseUri":"547ee2c7e4b09357f05f8a57","contributors":{"authors":[{"text":"Larson, James H. 0000-0002-6414-9758 jhlarson@usgs.gov","orcid":"https://orcid.org/0000-0002-6414-9758","contributorId":4250,"corporation":false,"usgs":true,"family":"Larson","given":"James","email":"jhlarson@usgs.gov","middleInitial":"H.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":525795,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Eckert, Nathan L.","contributorId":127593,"corporation":false,"usgs":false,"family":"Eckert","given":"Nathan L.","affiliations":[{"id":7071,"text":"U.S. Fish and Wildlife Service, Genoa National Fish Hatchery","active":true,"usgs":false}],"preferred":false,"id":525796,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bartsch, Michelle 0000-0002-9571-5564 mbartsch@usgs.gov","orcid":"https://orcid.org/0000-0002-9571-5564","contributorId":3165,"corporation":false,"usgs":true,"family":"Bartsch","given":"Michelle","email":"mbartsch@usgs.gov","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":525797,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70125641,"text":"70125641 - 2014 - Persistence of DNA in carcasses, slime and avian feces may affect interpretation of environmental DNA data","interactions":[],"lastModifiedDate":"2014-11-20T10:09:13","indexId":"70125641","displayToPublicDate":"2014-11-20T10:15:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Persistence of DNA in carcasses, slime and avian feces may affect interpretation of environmental DNA data","docAbstract":"The prevention of non-indigenous aquatic invasive species spreading into new areas is a goal of many resource managers. New techniques have been developed to survey for species that are difficult to capture with conventional gears that involve the detection of their DNA in water samples (eDNA). This technique is currently used to track the invasion of bigheaded carps (silver carp and bighead carp; Hypophthalmichthys molitrix and H. nobilis) in the Chicago Area Waterway System and Upper Mississippi River. In both systems DNA has been detected from silver carp without the capture of a live fish, which has led to some uncertainty about the source of the DNA. The potential contribution to eDNA by vectors and fomites has not been explored. Because barges move from areas with a high abundance of bigheaded carps to areas monitored for the potential presence of silver carp, we used juvenile silver carp to simulate the barge transport of dead bigheaded carp carcasses, slime residue, and predator feces to determine the potential of these sources to supply DNA to uninhabited waters where it could be detected and misinterpreted as indicative of the presence of live bigheaded carp. Our results indicate that all three vectors are feasible sources of detectable eDNA for at least one month after their deposition. This suggests that current monitoring programs must consider alternative vectors of DNA in the environment and consider alternative strategies to minimize the detection of DNA not directly released from live bigheaded carps.
","language":"English","publisher":"Public Library of Science","doi":"10.1371/journal.pone.0113346","usgsCitation":"Merkes, C., McCalla, S., Jensen, N.R., Gaikowski, M.P., and Amberg, J., 2014, Persistence of DNA in carcasses, slime and avian feces may affect interpretation of environmental DNA data: PLoS ONE, v. 9, no. 11, e113346; 7 p., https://doi.org/10.1371/journal.pone.0113346.","productDescription":"e113346; 7 p.","numberOfPages":"7","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-058016","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":472633,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0113346","text":"Publisher Index Page"},{"id":296222,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"9","issue":"11","noUsgsAuthors":false,"publicationDate":"2014-11-17","publicationStatus":"PW","scienceBaseUri":"546f10f5e4b057be23d4a799","contributors":{"authors":[{"text":"Merkes, Christopher M. cmerkes@usgs.gov","contributorId":5620,"corporation":false,"usgs":true,"family":"Merkes","given":"Christopher M.","email":"cmerkes@usgs.gov","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":false,"id":519522,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McCalla, S. Grace smccalla@usgs.gov","contributorId":4897,"corporation":false,"usgs":true,"family":"McCalla","given":"S. Grace","email":"smccalla@usgs.gov","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":false,"id":519521,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jensen, Nathan R. njensen@usgs.gov","contributorId":3911,"corporation":false,"usgs":true,"family":"Jensen","given":"Nathan","email":"njensen@usgs.gov","middleInitial":"R.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":false,"id":519520,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gaikowski, Mark P. 0000-0002-6507-9341 mgaikowski@usgs.gov","orcid":"https://orcid.org/0000-0002-6507-9341","contributorId":796,"corporation":false,"usgs":true,"family":"Gaikowski","given":"Mark","email":"mgaikowski@usgs.gov","middleInitial":"P.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":false,"id":519518,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Amberg, Jon J. jamberg@usgs.gov","contributorId":797,"corporation":false,"usgs":true,"family":"Amberg","given":"Jon J.","email":"jamberg@usgs.gov","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":false,"id":519519,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70138054,"text":"70138054 - 2014 - Mapping current and potential distribution of non-native Prosopis juliflora in the Afar region of Ethiopia","interactions":[],"lastModifiedDate":"2015-01-15T08:40:14","indexId":"70138054","displayToPublicDate":"2014-11-13T08:45:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Mapping current and potential distribution of non-native Prosopis juliflora in the Afar region of Ethiopia","docAbstract":"We used correlative models with species occurrence points, Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation indices, and topo-climatic predictors to map the current distribution and potential habitat of invasive Prosopis juliflora in Afar, Ethiopia. Time-series of MODIS Enhanced Vegetation Indices (EVI) and Normalized Difference Vegetation Indices (NDVI) with 250 m2 spatial resolution were selected as remote sensing predictors for mapping distributions, while WorldClim bioclimatic products and generated topographic variables from the Shuttle Radar Topography Mission product (SRTM) were used to predict potential infestations. We ran Maxent models using non-correlated variables and the 143 species-occurrence points. Maxent generated probability surfaces were converted into binary maps using the 10-percentile logistic threshold values. Performances of models were evaluated using area under the receiver-operating characteristic (ROC) curve (AUC). Our results indicate that the extent of P. juliflora invasion is approximately 3,605 km2 in the Afar region (AUC = 0.94), while the potential habitat for future infestations is 5,024 km2 (AUC = 0.95). Our analyses demonstrate that time-series of MODIS vegetation indices and species occurrence points can be used with Maxent modeling software to map the current distribution of P. juliflora, while topo-climatic variables are good predictors of potential habitat in Ethiopia. Our results can quantify current and future infestations, and inform management and policy decisions for containing P. juliflora. Our methods can also be replicated for managing invasive species in other East African countries.
","language":"English","publisher":"Public Library of Science","publisherLocation":"San Francisco, CA","doi":"10.1371/journal.pone.0112854","usgsCitation":"Wakie, T., Evangelista, P.H., Jarnevich, C.S., and Laituri, M., 2014, Mapping current and potential distribution of non-native Prosopis juliflora in the Afar region of Ethiopia: PLoS ONE, v. 9, no. 11, p. 1-9, https://doi.org/10.1371/journal.pone.0112854.","productDescription":"9 p.","startPage":"1","endPage":"9","numberOfPages":"9","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-052121","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":472640,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0112854","text":"Publisher Index Page"},{"id":297264,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":297259,"type":{"id":15,"text":"Index Page"},"url":"https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0112854"}],"country":"Ethiopia","volume":"9","issue":"11","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2014-11-13","publicationStatus":"PW","scienceBaseUri":"54dd2bede4b08de9379b357a","contributors":{"authors":[{"text":"Wakie, Tewodros","contributorId":138730,"corporation":false,"usgs":false,"family":"Wakie","given":"Tewodros","email":"","affiliations":[{"id":6737,"text":"Colorado State University, Department of Ecosystem Science and Sustainability, and Natural Resource Ecology Laboratory","active":true,"usgs":false}],"preferred":false,"id":538518,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Evangelista, Paul H.","contributorId":14747,"corporation":false,"usgs":true,"family":"Evangelista","given":"Paul","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":538519,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jarnevich, Catherine S. 0000-0002-9699-2336 jarnevichc@usgs.gov","orcid":"https://orcid.org/0000-0002-9699-2336","contributorId":3424,"corporation":false,"usgs":true,"family":"Jarnevich","given":"Catherine","email":"jarnevichc@usgs.gov","middleInitial":"S.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":538517,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Laituri, Melinda","contributorId":138731,"corporation":false,"usgs":false,"family":"Laituri","given":"Melinda","affiliations":[{"id":6737,"text":"Colorado State University, Department of Ecosystem Science and Sustainability, and Natural Resource Ecology Laboratory","active":true,"usgs":false}],"preferred":false,"id":538520,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70129713,"text":"70129713 - 2014 - Vulnerability of breeding waterbirds to climate change in the Prairie Pothole Region, U.S.A.","interactions":[],"lastModifiedDate":"2014-11-13T10:27:18","indexId":"70129713","displayToPublicDate":"2014-11-12T04:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Vulnerability of breeding waterbirds to climate change in the Prairie Pothole Region, U.S.A.","docAbstract":"The Prairie Pothole Region (PPR) of the north-central U.S. and south-central Canada contains millions of small prairie wetlands that provide critical habitat to many migrating and breeding waterbirds. Due to their small size and the relatively dry climate of the region, these wetlands are considered at high risk for negative climate change effects as temperatures increase. To estimate the potential impacts of climate change on breeding waterbirds, we predicted current and future distributions of species common in the PPR using species distribution models (SDMs). We created regional-scale SDMs for the U.S. PPR using Breeding Bird Survey occurrence records for 1971–2011 and wetland, upland, and climate variables. For each species, we predicted current distribution based on climate records for 1981–2000 and projected future distributions to climate scenarios for 2040–2049. Species were projected to, on average, lose almost half their current habitat (-46%). However, individual species projections varied widely, from +8% (Upland Sandpiper) to -100% (Wilson's Snipe). Variable importance ranks indicated that land cover (wetland and upland) variables were generally more important than climate variables in predicting species distributions. However, climate variables were relatively more important during a drought period. Projected distributions of species responses to climate change contracted within current areas of distribution rather than shifting. Given the large variation in species-level impacts, we suggest that climate change mitigation efforts focus on species projected to be the most vulnerable by enacting targeted wetland management, easement acquisition, and restoration efforts.
","language":"English","publisher":"Public Library of Science","doi":"10.1371/journal.pone.0096747","usgsCitation":"Steen, V., Skagen, S.K., and Noon, B.R., 2014, Vulnerability of breeding waterbirds to climate change in the Prairie Pothole Region, U.S.A.: PLoS ONE, v. 9, no. 6, e96747; 14 p., https://doi.org/10.1371/journal.pone.0096747.","productDescription":"e96747; 14 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-053462","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":472641,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0096747","text":"Publisher Index Page"},{"id":296019,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":295754,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0096747"}],"country":"United States","state":"Minnesota, North Dakota, South Dakota","otherGeospatial":"Prairie Pothole Region","volume":"9","issue":"6","noUsgsAuthors":false,"publicationDate":"2014-06-13","publicationStatus":"PW","scienceBaseUri":"546476a1e4b0ba83040c936d","contributors":{"authors":[{"text":"Steen, Valerie vsteen@usgs.gov","contributorId":5598,"corporation":false,"usgs":true,"family":"Steen","given":"Valerie","email":"vsteen@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":519912,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Skagen, Susan K. 0000-0002-6744-1244 skagens@usgs.gov","orcid":"https://orcid.org/0000-0002-6744-1244","contributorId":2009,"corporation":false,"usgs":true,"family":"Skagen","given":"Susan","email":"skagens@usgs.gov","middleInitial":"K.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":false,"id":519911,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Noon, Barry R.","contributorId":119751,"corporation":false,"usgs":true,"family":"Noon","given":"Barry","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":519913,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70129723,"text":"70129723 - 2014 - Deformation from the 1989 Loma Prieta earthquake near the southwest margin of the Santa Clara Valley, California","interactions":[],"lastModifiedDate":"2020-12-03T12:50:06.352931","indexId":"70129723","displayToPublicDate":"2014-11-12T03:30:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1820,"text":"Geosphere","active":true,"publicationSubtype":{"id":10}},"title":"Deformation from the 1989 Loma Prieta earthquake near the southwest margin of the Santa Clara Valley, California","docAbstract":"Damage to pavement and near-surface utility pipes, caused by the 17 October 1989, Loma Prieta earthquake, provides evidence for ground deformation in a 663 km2 area near the southwest margin of the Santa Clara Valley, California (USA). A total of 1427 damage sites, collected from more than 30 sources, are concentrated in four zones, three of which lie near previously mapped faults. In one of these zones, the channel lining of Los Gatos Creek, a 2-km-long concrete strip trending perpendicular to regional geologic structure, was broken by thrusts that were concentrated in two belts, each several tens of meters wide, separated by more than 300 m of relatively undeformed concrete.
\nTo gain additional measurement of any permanent ground deformation that accompanied this damage, we compiled and conducted post-earthquake surveys along two 5-km lines of horizontal control and a 15-km level line. Measurements of horizontal distortion indicate approximately 0.1 m shortening in a NE-SW direction across the valley margin, similar to the amount measured in the channel lining. Evaluation of precise leveling by the National Geodetic Survey showed a downwarp, with an amplitude of >0.1 m over a span of >12 km, that resembled regional geodetic models of coseismic deformation. Although the leveling indicates broad, regional warping, abrupt discontinuities characteristic of faulting characterize both the broad-scale distribution of damage and the local deformation of the channel lining. Reverse movement largely along preexisting faults and probably enhanced significantly by warping combined with enhanced ground shaking, produced the documented coseismic ground deformation.
","language":"English","publisher":"Geological Society of America","doi":"10.1130/GES01095.1","usgsCitation":"Schmidt, K.M., Ellen, S.D., and Peterson, D.M., 2014, Deformation from the 1989 Loma Prieta earthquake near the southwest margin of the Santa Clara Valley, California: Geosphere, v. 10, no. 6, p. 1177-1202, https://doi.org/10.1130/GES01095.1.","productDescription":"26 p.","startPage":"1177","endPage":"1202","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-057868","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":472642,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/ges01095.1","text":"Publisher Index Page"},{"id":380932,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Santa Clara Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.26684570312499,\n 35.639441068973944\n ],\n [\n -119.81689453125,\n 35.639441068973944\n ],\n [\n -119.81689453125,\n 37.23032838760387\n ],\n [\n -122.26684570312499,\n 37.23032838760387\n ],\n [\n -122.26684570312499,\n 35.639441068973944\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"10","issue":"6","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"546476a0e4b0ba83040c9355","contributors":{"authors":[{"text":"Schmidt, Kevin M. 0000-0003-2365-8035 kschmidt@usgs.gov","orcid":"https://orcid.org/0000-0003-2365-8035","contributorId":1985,"corporation":false,"usgs":true,"family":"Schmidt","given":"Kevin","email":"kschmidt@usgs.gov","middleInitial":"M.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":519916,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ellen, Stephen D.","contributorId":107300,"corporation":false,"usgs":true,"family":"Ellen","given":"Stephen","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":519917,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Peterson, David M.","contributorId":11644,"corporation":false,"usgs":true,"family":"Peterson","given":"David","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":519918,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70133045,"text":"70133045 - 2014 - The relative impacts of climate and land-use change on conterminous United States bird species from 2001 to 2075","interactions":[],"lastModifiedDate":"2017-01-23T15:21:04","indexId":"70133045","displayToPublicDate":"2014-11-12T03:15:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"The relative impacts of climate and land-use change on conterminous United States bird species from 2001 to 2075","docAbstract":"Species distribution models often use climate data to assess contemporary and/or future ranges for animal or plant species. Land use and land cover (LULC) data are important predictor variables for determining species range, yet are rarely used when modeling future distributions. In this study, maximum entropy modeling was used to construct species distribution maps for 50 North American bird species to determine relative contributions of climate and LULC for contemporary (2001) and future (2075) time periods. Species presence data were used as a dependent variable, while climate, LULC, and topographic data were used as predictor variables. Results varied by species, but in general, measures of model fit for 2001 indicated significantly poorer fit when either climate or LULC data were excluded from model simulations. Climate covariates provided a higher contribution to 2001 model results than did LULC variables, although both categories of variables strongly contributed. The area deemed to be \"suitable\" for 2001 species presence was strongly affected by the choice of model covariates, with significantly larger ranges predicted when LULC was excluded as a covariate. Changes in species ranges for 2075 indicate much larger overall range changes due to projected climate change than due to projected LULC change. However, the choice of study area impacted results for both current and projected model applications, with truncation of actual species ranges resulting in lower model fit scores and increased difficulty in interpreting covariate impacts on species range. Results indicate species-specific response to climate and LULC variables; however, both climate and LULC variables clearly are important for modeling both contemporary and potential future species ranges.
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at 27 locations near Boston, Massachusetts, including 2 strong-motion stations","interactions":[],"lastModifiedDate":"2014-11-13T09:45:51","indexId":"ofr20141232","displayToPublicDate":"2014-11-11T09:15:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-1232","title":"Surface wave site characterization at 27 locations near Boston, Massachusetts, including 2 strong-motion stations","docAbstract":"The geotechnical properties of the soils in and around Boston, Massachusetts, have been extensively studied. This is partly due to the importance of the Boston Blue Clay and the extent of landfill in the Boston area. Although New England is not a region that is typically associated with seismic hazards, there have been several historical earthquakes that have caused significant ground shaking (for example, see Street and Lacroix, 1979; Ebel, 1996; Ebel, 2006). The possibility of strong ground shaking, along with heightened vulnerability from unreinforced masonry buildings, motivates further investigation of seismic hazards throughout New England. Important studies that are pertinent to seismic hazards in New England include source-parameter studies (Somerville and others, 1987; Boore and others, 2010), wave-propagation studies (Frankel, 1991; Viegas and others, 2010), empirical ground-motion prediction equations (GMPE) for computing ground-motion intensity (Tavakoli and Pezeshk, 2005; Atkinson and Boore, 2006), site-response studies (Hayles and others, 2001; Ebel and Kim, 2006), and liquefaction studies (Brankman and Baise, 2008). The shear-wave velocity (VS) profiles collected for this report are pertinent to the GMPE, site response, and liquefaction aspects of seismic hazards in the greater Boston area. Besides the application of these data for the Boston region, the data may be applicable throughout New England, through correlations with geologic units (similar to Ebel and Kim, 2006) or correlations with topographic slope (Wald and Allen, 2007), because few VS measurements are available in stable tectonic regions.
Ebel and Hart (2001) used felt earthquake reports to infer amplification patterns throughout the greater Boston region and noted spatial correspondence with the dominant period and amplification factors obtained from ambient noise (horizontal-to-vertical ratios) by Kummer (1998). Britton (2003) compiled geotechnical borings in the area and produced a microzonation map based on generalized velocity profiles, where the amplifications were computed using Shake (Schnable and others, 1972), along with an assumed input ground motion. The velocities were constrained by only a few local measurements associated with the Central Artery/Tunnel project. The additional VS measurements presented in this report provide a number of benefits. First, these measurements provide improved spatial coverage. Second, the larger sample size provides better constraints on the mean and variance of the VS distribution for each layer, which may be paired with a three-dimensional (3D) model of the stratigraphy to generate one-dimensional (1D) profiles for use in a standard site-response analysis (for example, Britton, 2003). Third, the velocity profiles may also be used, along with a 3D model of the stratigraphy, as input into a 3D simulation of the ground motion to investigate the effects of basin-generated surface waves and the potential focusing of seismic waves.
This report begins with a short review of the geology of the study area and the field methods that we used to estimate the velocity profiles. The raw data, processed data, and the interpreted VS profiles are given in appendix 1. Photographs and descriptions of the sites are provided in appendix 2.
Over the next century, one of the largest contributions to sea level rise will come from ice sheets and glaciers calving ice into the ocean1. Factors controlling the rapid and nonlinear variations in calving fluxes are poorly understood, and therefore difficult to include in prognostic climate-forced land-ice models. Here we analyse globally distributed calving data sets from Svalbard, Alaska (USA), Greenland and Antarctica in combination with simulations from a first-principles, particle-based numerical calving model to investigate the size and inter-event time of calving events. We find that calving events triggered by the brittle fracture of glacier ice are governed by the same power-law distributions as avalanches in the canonical Abelian sandpile model2. This similarity suggests that calving termini behave as self-organized critical systems that readily flip between states of sub-critical advance and super-critical retreat in response to changes in climate and geometric conditions. Observations of sudden ice-shelf collapse and tidewater glacier retreat in response to gradual warming of their environment3 are consistent with a system fluctuating around its critical point in response to changing external forcing. We propose that self-organized criticality provides a yet unexplored framework for investigations into calving and projections of sea level rise.
","language":"English","publisher":"Nature","doi":"10.1038/ngeo2290","usgsCitation":"Astrom, J., Vallot, D., Schafer, M., Welty, E., O’Neel, S., Bartholomaus, T., Liu, Y., Riikila, T., Zwinger, T., Timonen, J., and Moore, J.N., 2014, Termini of calving glaciers as self-organized critical systems: Nature Geoscience, v. 7, p. 874-878, https://doi.org/10.1038/ngeo2290.","productDescription":"5 p.","startPage":"874","endPage":"878","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-058378","costCenters":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"links":[{"id":296131,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"7","noUsgsAuthors":false,"publicationDate":"2014-11-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Astrom, J.","contributorId":127397,"corporation":false,"usgs":false,"family":"Astrom","given":"J.","email":"","affiliations":[{"id":6937,"text":"CSC – IT Centre for Science, P.O. Box 405, 02101, Espoo, Finland","active":true,"usgs":false}],"preferred":false,"id":525016,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Vallot, D.","contributorId":127398,"corporation":false,"usgs":false,"family":"Vallot","given":"D.","email":"","affiliations":[{"id":6938,"text":"Department of Earth Science, Uppsala University, Villavägen 16, Uppsala, 75236, Sweden","active":true,"usgs":false}],"preferred":false,"id":525017,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schafer, M.","contributorId":127399,"corporation":false,"usgs":false,"family":"Schafer","given":"M.","email":"","affiliations":[{"id":6939,"text":"Arctic Centre, University of Lapland, PL122, 96100 Rovaniemi, Finland","active":true,"usgs":false}],"preferred":false,"id":525018,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Welty, E.","contributorId":56464,"corporation":false,"usgs":true,"family":"Welty","given":"E.","email":"","affiliations":[],"preferred":false,"id":525019,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"O’Neel, Shad 0000-0002-9185-0144 soneel@usgs.gov","orcid":"https://orcid.org/0000-0002-9185-0144","contributorId":166740,"corporation":false,"usgs":true,"family":"O’Neel","given":"Shad","email":"soneel@usgs.gov","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true},{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true},{"id":107,"text":"Alaska Climate Science Center","active":true,"usgs":true}],"preferred":true,"id":525015,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bartholomaus, T.C.","contributorId":94569,"corporation":false,"usgs":true,"family":"Bartholomaus","given":"T.C.","affiliations":[],"preferred":false,"id":525020,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Liu, Y.","contributorId":127400,"corporation":false,"usgs":false,"family":"Liu","given":"Y.","email":"","affiliations":[{"id":6940,"text":"State Key Laboratory of Earth Surface Processes and Resource Ecology, College of Global Change and Earth System Science, Beijing Normal University, Beijing, China","active":true,"usgs":false}],"preferred":false,"id":525021,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Riikila, T.","contributorId":127401,"corporation":false,"usgs":false,"family":"Riikila","given":"T.","email":"","affiliations":[{"id":6941,"text":"Department of Physics and Nanoscience Center, University of Jyväskylä, P.O. Box 35, 40014, Jyväskylä, Finland","active":true,"usgs":false}],"preferred":false,"id":525022,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Zwinger, T.","contributorId":82612,"corporation":false,"usgs":true,"family":"Zwinger","given":"T.","email":"","affiliations":[],"preferred":false,"id":525024,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Timonen, J.","contributorId":248787,"corporation":false,"usgs":false,"family":"Timonen","given":"J.","email":"","affiliations":[],"preferred":false,"id":809840,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Moore, Johnnie N.","contributorId":13668,"corporation":false,"usgs":true,"family":"Moore","given":"Johnnie","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":525023,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70131483,"text":"70131483 - 2014 - On the downscaling of actual evapotranspiration maps based on combination of MODIS and landsat-based actual evapotranspiration estimates","interactions":[],"lastModifiedDate":"2017-01-18T11:27:04","indexId":"70131483","displayToPublicDate":"2014-11-07T17:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3250,"text":"Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"On the downscaling of actual evapotranspiration maps based on combination of MODIS and landsat-based actual evapotranspiration estimates","docAbstract":"Downscaling is one of the important ways of utilizing the combined benefits of the high temporal resolution of Moderate Resolution Imaging Spectroradiometer (MODIS) images and fine spatial resolution of Landsat images. We have evaluated the output regression with intercept method and developed the Linear with Zero Intercept (LinZI) method for downscaling MODIS-based monthly actual evapotranspiration (AET) maps to the Landsat-scale monthly AET maps for the Colorado River Basin for 2010. We used the 8-day MODIS land surface temperature product (MOD11A2) and 328 cloud-free Landsat images for computing AET maps and downscaling. The regression with intercept method does have limitations in downscaling if the slope and intercept are computed over a large area. A good agreement was obtained between downscaled monthly AET using the LinZI method and the eddy covariance measurements from seven flux sites within the Colorado River Basin. The mean bias ranged from −16 mm (underestimation) to 22 mm (overestimation) per month, and the coefficient of determination varied from 0.52 to 0.88. Some discrepancies between measured and downscaled monthly AET at two flux sites were found to be due to the prevailing flux footprint. A reasonable comparison was also obtained between downscaled monthly AET using LinZI method and the gridded FLUXNET dataset. The downscaled monthly AET nicely captured the temporal variation in sampled land cover classes. The proposed LinZI method can be used at finer temporal resolution (such as 8 days) with further evaluation. The proposed downscaling method will be very useful in advancing the application of remotely sensed images in water resources planning and management.
","language":"English","publisher":"MDPI","doi":"10.3390/rs61110483","usgsCitation":"Singh, R.K., Senay, G.B., Velpuri, N.M., Bohms, S., and Verdin, J.P., 2014, On the downscaling of actual evapotranspiration maps based on combination of MODIS and landsat-based actual evapotranspiration estimates: Remote Sensing, v. 6, no. 11, p. 10483-10509, https://doi.org/10.3390/rs61110483.","productDescription":"27 p.","startPage":"10483","endPage":"10509","numberOfPages":"27","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-057248","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":472650,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs61110483","text":"Publisher Index Page"},{"id":295950,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":295953,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://www.mdpi.com/2072-4292/6/11/10483"}],"volume":"6","issue":"11","noUsgsAuthors":false,"publicationDate":"2014-10-30","publicationStatus":"PW","scienceBaseUri":"545ddf17e4b0ba8303f8b625","contributors":{"authors":[{"text":"Singh, Ramesh K. 0000-0002-8164-3483 rsingh@usgs.gov","orcid":"https://orcid.org/0000-0002-8164-3483","contributorId":3895,"corporation":false,"usgs":true,"family":"Singh","given":"Ramesh","email":"rsingh@usgs.gov","middleInitial":"K.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":521245,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Senay, Gabriel B. 0000-0002-8810-8539 senay@usgs.gov","orcid":"https://orcid.org/0000-0002-8810-8539","contributorId":3114,"corporation":false,"usgs":true,"family":"Senay","given":"Gabriel","email":"senay@usgs.gov","middleInitial":"B.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":521246,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Velpuri, Naga Manohar 0000-0002-6370-1926 nvelpuri@usgs.gov","orcid":"https://orcid.org/0000-0002-6370-1926","contributorId":4441,"corporation":false,"usgs":true,"family":"Velpuri","given":"Naga","email":"nvelpuri@usgs.gov","middleInitial":"Manohar","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":521247,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bohms, Stefanie 0000-0002-2979-4655 sbohms@usgs.gov","orcid":"https://orcid.org/0000-0002-2979-4655","contributorId":3148,"corporation":false,"usgs":true,"family":"Bohms","given":"Stefanie","email":"sbohms@usgs.gov","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":521248,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Verdin, James P. 0000-0003-0238-9657 verdin@usgs.gov","orcid":"https://orcid.org/0000-0003-0238-9657","contributorId":720,"corporation":false,"usgs":true,"family":"Verdin","given":"James","email":"verdin@usgs.gov","middleInitial":"P.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":521249,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70074082,"text":"sir20105090P - 2014 - Porphyry copper assessment of East and Southeast Asia: Philippines, Taiwan (Republic of China), Republic of Korea (South Korea), and Japan","interactions":[{"subject":{"id":70074082,"text":"sir20105090P - 2014 - Porphyry copper assessment of East and Southeast Asia: Philippines, Taiwan (Republic of China), Republic of Korea (South Korea), and Japan","indexId":"sir20105090P","publicationYear":"2014","noYear":false,"chapter":"P","title":"Porphyry copper assessment of East and Southeast Asia: Philippines, Taiwan (Republic of China), Republic of Korea (South Korea), and Japan"},"predicate":"IS_PART_OF","object":{"id":70040436,"text":"sir20105090 - 2010 - Global mineral resource assessment","indexId":"sir20105090","publicationYear":"2010","noYear":false,"title":"Global mineral resource assessment"},"id":1}],"isPartOf":{"id":70040436,"text":"sir20105090 - 2010 - Global mineral resource assessment","indexId":"sir20105090","publicationYear":"2010","noYear":false,"title":"Global mineral resource assessment"},"lastModifiedDate":"2020-07-01T19:22:00.184549","indexId":"sir20105090P","displayToPublicDate":"2014-11-04T14:30:00","publicationYear":"2014","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":"2010-5090","chapter":"P","title":"Porphyry copper assessment of East and Southeast Asia: Philippines, Taiwan (Republic of China), Republic of Korea (South Korea), and Japan","docAbstract":"The U.S. Geological Survey collaborated with member countries of the Coordinating Committee for Geoscience Programmes in East and Southeast Asia (CCOP) on an assessment of the porphyry copper resources of East and Southeast Asia as part of a global mineral resource assessment. The assessment covers the Philippines in Southeast Asia, and the Republic of Korea (South Korea), Taiwan (Province of China), and Japan in East Asia. The Philippines host world class porphyry copper deposits, such as the Tampakan and Atlas deposits. No porphyry copper deposits have been discovered in the Republic of Korea (South Korea), Taiwan (Province of China), or Japan.
\nThirteen geographic areas were delineated as tracts that are permissive for porphyry copper deposits in the assessed area. Individual tracts range from about 3,000 to 100,000 square kilometers in area. Permissive tracts are delineated on the basis of mapped distributions of igneous rocks of specific age ranges that define subduction-related magmatic arcs or magmatic belts that might contain porphyry copper deposits. Most of these magmatic arcs are subduction related, although some porphyry deposits and prospects are present in back-arc or poorly understood tectonic settings. Maps at various scales were used in the compilation; however, the final tract boundaries are intended for use at a scale of 1:1,000,000.
\nNumbers of undiscovered deposits were estimated at different levels of confidence for 10 permissive tracts in the Philippines including one area that extends to eastern Taiwan (Republic of China); permissive tracts in South Korea and Japan are discussed qualitatively. Estimates of numbers of undiscovered deposits were combined with grade and tonnage models using Monte Carlo simulation to estimate amounts of undiscovered resources. Grades and tonnages of known porphyry copper deposits in the study area were compared with global grade and tonnage models to determine the appropriate model for simulation of undiscovered resources. Most of the known deposits are best described as copper-gold subtypes of porphyry copper deposits. For some permissive tracts, a general porphyry copper-gold-molybdenum model was used.
\nThirty-eight porphyry copper deposits are known in the Philippines; the mean number of undiscovered deposits was estimated to be 28. Mean (arithmetic) resources that could be associated with the undiscovered deposits are 90 million metric tons of copper and 5,800 metric tons of gold, as well as byproduct molybdenum and silver. Additional resources that could be discovered in extensions to known deposits were not evaluated. Assessment results, presented in tables and graphs, indicate expected amounts of total contained metal and mineralized rock in undiscovered deposits at different quantile levels, as well as the arithmetic mean for each tract.
\nThe Philippines have a long history of porphyry exploration cycles and mine development, interrupted at times by political and social unrest, environmental concerns, and natural disasters. Changes in mining laws within the region and the recent high price of gold on the world market have prompted renewed interest in porphyry copper deposits in the region. South Korea and Japan have been thoroughly explored for many types of mineral deposits. Available data suggest that the permissive rocks in South Korea typically are too deeply eroded to preserve porphyry copper deposits. Porphyry copper systems may be present in Japan, but are likely to lie at depths greater than the 1 kilometer from the surface protocol adopted for this study.
\nDescriptions of the geologic basis for delineating each tract, the data used, the geologic criteria and rationale for the assessment, and results of the assessment are included in appendixes along with the description of a geographic information system (GIS) that includes tract boundaries, known porphyry copper deposits and significant prospects, and assessment results.
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jhammars@usgs.gov","orcid":"https://orcid.org/0000-0003-2742-3460","contributorId":1226,"corporation":false,"usgs":true,"family":"Hammarstrom","given":"Jane","email":"jhammars@usgs.gov","middleInitial":"M.","affiliations":[{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true},{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":523284,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bookstrom, Arthur A. 0000-0003-1336-3364 abookstrom@usgs.gov","orcid":"https://orcid.org/0000-0003-1336-3364","contributorId":1542,"corporation":false,"usgs":true,"family":"Bookstrom","given":"Arthur","email":"abookstrom@usgs.gov","middleInitial":"A.","affiliations":[{"id":5056,"text":"Office of the AD Energy and Minerals, and Environmental Health","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":523285,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Demarr, Michael W.","contributorId":127350,"corporation":false,"usgs":false,"family":"Demarr","given":"Michael","email":"","middleInitial":"W.","affiliations":[{"id":6785,"text":"USGS Contractor, Minerals & Environmental Resources Sci Ctr","active":true,"usgs":false}],"preferred":false,"id":523286,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dicken, Connie L. cdicken@usgs.gov","contributorId":4714,"corporation":false,"usgs":true,"family":"Dicken","given":"Connie L.","email":"cdicken@usgs.gov","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":false,"id":523287,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ludington, Stephen slud@usgs.gov","contributorId":3093,"corporation":false,"usgs":true,"family":"Ludington","given":"Stephen","email":"slud@usgs.gov","affiliations":[{"id":662,"text":"Western Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":false,"id":523288,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Robinson, Gilpin R. Jr. grobinso@usgs.gov","contributorId":3083,"corporation":false,"usgs":true,"family":"Robinson","given":"Gilpin","suffix":"Jr.","email":"grobinso@usgs.gov","middleInitial":"R.","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":false,"id":523289,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Zientek, Michael L. 0000-0002-8522-9626 mzientek@usgs.gov","orcid":"https://orcid.org/0000-0002-8522-9626","contributorId":2420,"corporation":false,"usgs":true,"family":"Zientek","given":"Michael","email":"mzientek@usgs.gov","middleInitial":"L.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":523290,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70131501,"text":"70131501 - 2014 - Whitebark pine, population density, and home-range size of grizzly bears in the greater Yellowstone ecosystem","interactions":[],"lastModifiedDate":"2018-03-17T17:13:33","indexId":"70131501","displayToPublicDate":"2014-11-04T13:15:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Whitebark pine, population density, and home-range size of grizzly bears in the greater Yellowstone ecosystem","docAbstract":"Changes in life history traits of species can be an important indicator of potential factors influencing populations. For grizzly bears (Ursus arctos) in the Greater Yellowstone Ecosystem (GYE), recent decline of whitebark pine (WBP; Pinus albicaulis), an important fall food resource, has been paired with a slowing of population growth following two decades of robust population increase. These observations have raised questions whether resource decline or density-dependent processes may be associated with changes in population growth. Distinguishing these effects based on changes in demographic rates can be difficult. However, unlike the parallel demographic responses expected from both decreasing food availability and increasing population density, we hypothesized opposing behavioral responses of grizzly bears with regard to changes in home-range size. We used the dynamic changes in food resources and population density of grizzly bears as a natural experiment to examine hypotheses regarding these potentially competing influences on grizzly bear home-range size. We found that home-range size did not increase during the period of whitebark pine decline and was not related to proportion of whitebark pine in home ranges. However, female home-range size was negatively associated with an index of population density. Our data indicate that home-range size of grizzly bears in the GYE is not associated with availability of WBP, and, for female grizzly bears, increasing population density may constrain home-range size.
","language":"English","publisher":"Public Library of Science","doi":"10.1371/journal.pone.0088160","collaboration":"US Fish and Wildlife Service","usgsCitation":"Bjornlie, D., van Manen, F.T., Ebinger, M.R., Haroldson, M.A., Thompson, D.J., and Costello, C., 2014, Whitebark pine, population density, and home-range size of grizzly bears in the greater Yellowstone ecosystem: PLoS ONE, v. 9, no. 2, p. 1-7, https://doi.org/10.1371/journal.pone.0088160.","productDescription":"Article e88160; 7 p.","startPage":"1","endPage":"7","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-053114","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":472652,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0088160","text":"Publisher Index Page"},{"id":295865,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho, Montana, Wyoming","otherGeospatial":"Yellowstone National Park","volume":"9","issue":"2","noUsgsAuthors":false,"publicationDate":"2014-02-10","publicationStatus":"PW","scienceBaseUri":"5459eaa5e4b009f8aec97040","contributors":{"authors":[{"text":"Bjornlie, Daniel D.","contributorId":145512,"corporation":false,"usgs":false,"family":"Bjornlie","given":"Daniel D.","affiliations":[{"id":16140,"text":"Wyoming Game & Fish Department, Large Carnivore Section, Lander, Wyoming 82520, USA","active":true,"usgs":false}],"preferred":false,"id":521328,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"van Manen, Frank T. 0000-0001-5340-8489 fvanmanen@usgs.gov","orcid":"https://orcid.org/0000-0001-5340-8489","contributorId":2267,"corporation":false,"usgs":true,"family":"van Manen","given":"Frank","email":"fvanmanen@usgs.gov","middleInitial":"T.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":521327,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ebinger, Michael R. mebinger@usgs.gov","contributorId":5771,"corporation":false,"usgs":true,"family":"Ebinger","given":"Michael","email":"mebinger@usgs.gov","middleInitial":"R.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":521329,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Haroldson, Mark A. 0000-0002-7457-7676 mharoldson@usgs.gov","orcid":"https://orcid.org/0000-0002-7457-7676","contributorId":1773,"corporation":false,"usgs":true,"family":"Haroldson","given":"Mark","email":"mharoldson@usgs.gov","middleInitial":"A.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":521330,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Thompson, Daniel J.","contributorId":149795,"corporation":false,"usgs":false,"family":"Thompson","given":"Daniel","email":"","middleInitial":"J.","affiliations":[{"id":5116,"text":"Large Carnivore Section, Wyoming Game & Fish Department, 260 Buena Vista, Lander, WY 82520, USA","active":true,"usgs":false}],"preferred":false,"id":521331,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Costello, Cecily M.","contributorId":145510,"corporation":false,"usgs":false,"family":"Costello","given":"Cecily M.","affiliations":[{"id":5117,"text":"University of Montana, College of Forestry and Conservation, University Hall, Room 309, Missoula, MT 59812, USA","active":true,"usgs":false}],"preferred":false,"id":521332,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70131492,"text":"70131492 - 2014 - Limitations to estimating bacterial cross-speciestransmission using genetic and genomic markers: Inferences from simulation modeling","interactions":[],"lastModifiedDate":"2020-12-29T12:52:06.935036","indexId":"70131492","displayToPublicDate":"2014-11-04T11:30:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1601,"text":"Evolutionary Applications","active":true,"publicationSubtype":{"id":10}},"title":"Limitations to estimating bacterial cross-speciestransmission using genetic and genomic markers: Inferences from simulation modeling","docAbstract":"Cross‐species transmission (CST) of bacterial pathogens has major implications for human health, livestock, and wildlife management because it determines whether control actions in one species may have subsequent effects on other potential host species. The study of bacterial transmission has benefitted from methods measuring two types of genetic variation: variable number of tandem repeats (VNTRs) and single nucleotide polymorphisms (SNPs). However, it is unclear whether these data can distinguish between different epidemiological scenarios. We used a simulation model with two host species and known transmission rates (within and between species) to evaluate the utility of these markers for inferring CST. We found that CST estimates are biased for a wide range of parameters when based on VNTRs and a most parsimonious reconstructed phylogeny. However, estimations of CST rates lower than 5% can be achieved with relatively low bias using as low as 250 SNPs. CST estimates are sensitive to several parameters, including the number of mutations accumulated since introduction, stochasticity, the genetic difference of strains introduced, and the sampling effort. Our results suggest that, even with whole‐genome sequences, unbiased estimates of CST will be difficult when sampling is limited, mutation rates are low, or for pathogens that were recently introduced.
Hydro-ecological stream classification-the process of grouping streams by similar hydrologic responses and, by extension, similar aquatic habitat-has been widely accepted and is considered by some to be one of the first steps towards developing ecological flow targets. A new classification of 1543 streamgauges in the contiguous USA is presented by use of a novel and parsimonious approach to understand similarity in ecological streamflow response. This novel classification approach uses seven fundamental daily streamflow statistics (FDSS) rather than winnowing down an uncorrelated subset from 200 or more ecologically relevant streamflow statistics (ERSS) commonly used in hydro-ecological classification studies. The results of this investigation demonstrate that the distributions of 33 tested ERSS are consistently different among the classification groups derived from the seven FDSS. It is further shown that classification based solely on the 33 ERSS generally does a poorer job in grouping similar streamgauges than the classification based on the seven FDSS. This new classification approach has the additional advantages of overcoming some of the subjectivity associated with the selection of the classification variables and provides a set of robust continental-scale classes of US streamgauges. Published 2013. This article is a U.S. Government work and is in the public domain in the USA.
","language":"English","publisher":"John Wiley & Sons","publisherLocation":"Chichester, West Sussex, UK","doi":"10.1002/rra.2710","collaboration":"USGS National Water Census","usgsCitation":"Archfield, S.A., Kennen, J., Carlisle, D.M., and Wolock, D.M., 2014, An objective and parsimonious approach for classifying natural flow regimes at a continental scale: River Research and Applications, v. 30, no. 9, p. 1166-1183, https://doi.org/10.1002/rra.2710.","productDescription":"18 p.","startPage":"1166","endPage":"1183","numberOfPages":"18","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-050605","costCenters":[{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true}],"links":[{"id":297295,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":297285,"type":{"id":15,"text":"Index Page"},"url":"https://onlinelibrary.wiley.com/doi/10.1002/rra.2710/full"}],"volume":"30","issue":"9","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationDate":"2013-09-30","publicationStatus":"PW","scienceBaseUri":"54dd2b30e4b08de9379b329e","contributors":{"authors":[{"text":"Archfield, Stacey A. 0000-0002-9011-3871 sarch@usgs.gov","orcid":"https://orcid.org/0000-0002-9011-3871","contributorId":1874,"corporation":false,"usgs":true,"family":"Archfield","given":"Stacey","email":"sarch@usgs.gov","middleInitial":"A.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"preferred":true,"id":538563,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kennen, Jonathan G. 0000-0002-5426-4445 jgkennen@usgs.gov","orcid":"https://orcid.org/0000-0002-5426-4445","contributorId":574,"corporation":false,"usgs":true,"family":"Kennen","given":"Jonathan G.","email":"jgkennen@usgs.gov","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":538564,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Carlisle, Daren M. 0000-0002-7367-348X dcarlisle@usgs.gov","orcid":"https://orcid.org/0000-0002-7367-348X","contributorId":513,"corporation":false,"usgs":true,"family":"Carlisle","given":"Daren","email":"dcarlisle@usgs.gov","middleInitial":"M.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":503,"text":"Office of Water Quality","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true}],"preferred":true,"id":538565,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wolock, David M. 0000-0002-6209-938X dwolock@usgs.gov","orcid":"https://orcid.org/0000-0002-6209-938X","contributorId":540,"corporation":false,"usgs":true,"family":"Wolock","given":"David","email":"dwolock@usgs.gov","middleInitial":"M.","affiliations":[{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true},{"id":503,"text":"Office of Water Quality","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"preferred":true,"id":538566,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70157371,"text":"70157371 - 2014 - Using mark-recapture distance sampling methods on line transect surveys","interactions":[],"lastModifiedDate":"2017-11-24T17:47:57","indexId":"70157371","displayToPublicDate":"2014-11-01T12:15:00","publicationYear":"2014","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":"Using mark-recapture distance sampling methods on line transect surveys","docAbstract":"Multi-channel seismic reflection data, well logs, and recovered sediment cores have been used in this study to characterize the geologic controls on the occurrence of gas hydrate in the Shenhu area of the South China Sea. The concept of the \"gas hydrate petroleum system\" has allowed for the systematic analysis of the impact of gas source, geologic controls on gas migration, and the role of the host sediment in the formation and stability of gas hydrates as encountered during the 2007 Guangzhou Marine Geological Survey Gas Hydrate Expedition (GMGS-1) in the Shenhu area. Analysis of seismic and bathymetric data identified seventeen sub-linear, near-parallel submarine canyons in this area. These canyons, formed in the Miocene, migrated in a northeasterly direction, and resulted in the burial and abandonment of canyons partially filled by coarse-grained sediments. Downhole wireline log (DWL) data were acquired from eight drill sites and sediment coring was conducted at five of these sites, which revealed the presence of suitable reservoirs for the occurrence of concentrated gas hydrate accumulations. Gas hydrate-bearing sediment layers were identified from well log and core data at three sites mainly within silt and silt clay sediments. Gas hydrate was also discovered in a sand reservoir at one site as inferred from the analysis of the DWL data. Seismic anomalies attributed to the presence of gas below the base of gas hydrate stability zone, provided direct evidence for the migration of gas into the overlying gas hydrate-bearing sedimentary sections. Geochemical analyses of gas samples collected from cores confirmed that the occurrence of gas hydrate in the Shenhu area is controlled by the presence thermogenic methane gas that has migrated into the gas hydrate stability zone from a more deeply buried source.
","language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam","doi":"10.1016/j.margeo.2014.09.040","usgsCitation":"Wang, X., Lee, M.W., Collett, T.S., Yang, S., Guo, Y., and Wu, S., 2014, Geological controls on the occurrence of gas hydrate from core, downhole log, and seismic data in the Shenhu area, South China Sea: Marine Geology, v. 357, p. 272-292, https://doi.org/10.1016/j.margeo.2014.09.040.","productDescription":"21 p.","startPage":"272","endPage":"292","numberOfPages":"21","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-055596","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":296523,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"China","otherGeospatial":"Shenhu area, South China Sea","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 115.1,\n 19.8333\n ],\n [\n 115.2833,\n 19.8333\n ],\n [\n 115.2833,\n 19.9333\n ],\n [\n 115.1,\n 19.9333\n ],\n [\n 115.1,\n 19.8333\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"357","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54882b51e4b02acb4f0c8c35","contributors":{"authors":[{"text":"Lee, Myung W. mlee@usgs.gov","contributorId":779,"corporation":false,"usgs":true,"family":"Lee","given":"Myung","email":"mlee@usgs.gov","middleInitial":"W.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":526662,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wang, Xiujuan","contributorId":127764,"corporation":false,"usgs":false,"family":"Wang","given":"Xiujuan","email":"","affiliations":[{"id":7142,"text":"Institute of Oceanology, Chinese Academy of Sciences","active":true,"usgs":false}],"preferred":false,"id":526660,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Collett, Timothy S. 0000-0002-7598-4708 tcollett@usgs.gov","orcid":"https://orcid.org/0000-0002-7598-4708","contributorId":1698,"corporation":false,"usgs":true,"family":"Collett","given":"Timothy","email":"tcollett@usgs.gov","middleInitial":"S.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":526659,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Yang, Shengxiong","contributorId":74306,"corporation":false,"usgs":true,"family":"Yang","given":"Shengxiong","affiliations":[],"preferred":false,"id":526663,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Guo, Yiqun","contributorId":68659,"corporation":false,"usgs":false,"family":"Guo","given":"Yiqun","affiliations":[{"id":34423,"text":"Guangzhou Marine Geological Survey, Guangzhou, China","active":true,"usgs":false}],"preferred":false,"id":526664,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wu, Shiguo","contributorId":11126,"corporation":false,"usgs":true,"family":"Wu","given":"Shiguo","affiliations":[],"preferred":false,"id":526665,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70147344,"text":"70147344 - 2014 - Analysis of projected water availability with current basin management plan, Pajaro Valley, California","interactions":[],"lastModifiedDate":"2015-04-30T10:49:52","indexId":"70147344","displayToPublicDate":"2014-11-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3823,"text":"Journal of Hydrology: Regional Studies","active":true,"publicationSubtype":{"id":10}},"title":"Analysis of projected water availability with current basin management plan, Pajaro Valley, California","docAbstract":"The projection and analysis of the Pajaro Valley Hydrologic Model (PVHM) 34 years into the future using MODFLOW with the Farm Process (MF-FMP) facilitates assessment of potential future water availability. The projection is facilitated by the integrated hydrologic model, MF-FMP that fully couples the simulation of the use and movement of water from precipitation, streamflow, runoff, groundwater flow, and consumption by natural and agricultural vegetation throughout the hydrologic system at all times. MF-FMP allows for more complete analysis of conjunctive-use water-resource systems than previously possible with MODFLOW by combining relevant aspects of the landscape with the groundwater and surface-water components. This analysis is accomplished using distributed cell-by-cell supply-constrained and demand-driven components across the landscape within “water-balance subregions” (WBS) comprised of one or more model cells that can represent a single farm, a group of farms, watersheds, or other hydrologic or geopolitical entities. Analysis of conjunctive use would be difficult without embedding the fully coupled supply-and-demand into a fully coupled simulation, and are difficult to estimate a priori.
\nThe analysis of projected supply and demand for the Pajaro Valley indicate that the current water supply facilities constructed to provide alternative local sources of supplemental water to replace coastal groundwater pumpage, but may not completely eliminate additional overdraft. The simulation of the coastal distribution system (CDS) replicates: 20 miles of conveyance pipeline, managed aquifer recharge and recovery (MARR) system that captures local runoff, and recycled-water treatment facility (RWF) from urban wastewater, along with the use of other blend water supplies, provide partial relief and substitution for coastal pumpage (aka in-lieu recharge). The effects of these Basin Management Plan (BMP) projects were analyzed subject to historical climate variations and assumptions of 2009 urban water demand and land use. Water supplied directly from precipitation, and indirectly from reuse, captured local runoff, and groundwater is necessary but inadequate to satisfy agricultural demand without coastal and regional storage depletion that facilitates seawater intrusion. These facilities reduce potential seawater intrusion by about 45% with groundwater levels in the four regions served by the CDS projected to recover to levels a few feet above sea level. The projected recoveries are not high enough to prevent additional seawater intrusion during dry-year periods or in the deeper aquifers where pumpage is greater. While these facilities could reduce coastal pumpage by about 55% of the historical 2000–2009 pumpage for these regions, and some of the water is delivered in excess of demand, other coastal regions continue to create demands on coastal pumpage that will need to be replaced to reduce seawater intrusion. In addition, inland urban and agricultural demands continue to sustain water levels below sea level causing regional landward gradients that also drive seawater intrusion. Seawater intrusion is reduced by about 45% but it supplies about 55% of the recovery of groundwater levels in the coastal regions served by the CDS. If economically feasible, water from summer agricultural runoff and tile-drain returnflows could be another potential local source of water that, if captured and reused, could offset the imbalance between supply and demand as well as reducing discharge of agricultural runoff into the National Marine Sanctuary of Monterey Bay. A BMP update (2012) identifies projects and programs that will fund a conservation program and will provide additional, alternative water sources to reduce or replace coastal and inland pumpage, and to replenish the aquifers with managed aquifer recharge in an inland portion of the Pajaro Valley.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jhydrol.2014.07.005","usgsCitation":"Hanson, R.T., Lockwood, B., and Schmid, W., 2014, Analysis of projected water availability with current basin management plan, Pajaro Valley, California: Journal of Hydrology: Regional Studies, v. 519, no. A, p. 131-147, https://doi.org/10.1016/j.jhydrol.2014.07.005.","productDescription":"17 p.","startPage":"131","endPage":"147","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-041544","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":299982,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Pajaro Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.84112548828125,\n 36.797739040981085\n ],\n [\n -121.84112548828125,\n 36.89005557519409\n ],\n [\n -121.70654296874999,\n 36.89005557519409\n ],\n [\n -121.70654296874999,\n 36.797739040981085\n ],\n [\n -121.84112548828125,\n 36.797739040981085\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"519","issue":"A","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"55435229e4b0a658d794149f","contributors":{"authors":[{"text":"Hanson, Randall T. 0000-0002-9819-7141 rthanson@usgs.gov","orcid":"https://orcid.org/0000-0002-9819-7141","contributorId":801,"corporation":false,"usgs":true,"family":"Hanson","given":"Randall","email":"rthanson@usgs.gov","middleInitial":"T.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":545830,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lockwood, Brian","contributorId":80202,"corporation":false,"usgs":true,"family":"Lockwood","given":"Brian","email":"","affiliations":[],"preferred":false,"id":545831,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schmid, Wolfgang","contributorId":84020,"corporation":false,"usgs":false,"family":"Schmid","given":"Wolfgang","affiliations":[{"id":13040,"text":"Department of Hydrology and Water Resources, University of Arizona","active":true,"usgs":false}],"preferred":false,"id":545832,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70155223,"text":"70155223 - 2014 - Costs and benefits of group living with disease: a case study of pneumonia in bighorn lambs (Ovis canadensis)","interactions":[],"lastModifiedDate":"2015-08-19T10:10:42","indexId":"70155223","displayToPublicDate":"2014-11-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3173,"text":"Proceedings of the Royal Society B","active":true,"publicationSubtype":{"id":10}},"title":"Costs and benefits of group living with disease: a case study of pneumonia in bighorn lambs (Ovis canadensis)","docAbstract":"Group living facilitates pathogen transmission among social hosts, yet temporally stable host social organizations can actually limit transmission of some pathogens. When there are few between-subpopulation contacts for the duration of a disease event, transmission becomes localized to subpopulations. The number of per capita infectious contacts approaches the subpopulation size as pathogen infectiousness increases. Here, we illustrate that this is the case during epidemics of highly infectious pneumonia in bighorn lambs (Ovis canadensis). We classified individually marked bighorn ewes into disjoint seasonal subpopulations, and decomposed the variance in lamb survival to weaning into components associated with individual ewes, subpopulations, populations and years. During epidemics, lamb survival varied substantially more between ewe-subpopulations than across populations or years, suggesting localized pathogen transmission. This pattern of lamb survival was not observed during years when disease was absent. Additionally, group sizes in ewe-subpopulations were independent of population size, but the number of ewe-subpopulations increased with population size. Consequently, although one might reasonably assume that force of infection for this highly communicable disease scales with population size, in fact, host social behaviour modulates transmission such that disease is frequency-dependent within populations, and some groups remain protected during epidemic events.
","language":"English","publisher":"Royal Society","publisherLocation":"London","doi":"10.1098/rspb.2014.2331","usgsCitation":"Manlove, K.R., Cassirer, E.F., Cross, P.C., Plowright, R., and Hudson, P., 2014, Costs and benefits of group living with disease: a case study of pneumonia in bighorn lambs (Ovis canadensis): Proceedings of the Royal Society B, v. 281, no. 1797, art20142331, https://doi.org/10.1098/rspb.2014.2331.","productDescription":"art20142331","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-058080","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":472851,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1098/rspb.2014.2331","text":"Publisher Index Page"},{"id":306916,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"281","issue":"1797","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2014-12-22","publicationStatus":"PW","scienceBaseUri":"55d5a8ade4b0518e3546a4b5","contributors":{"authors":[{"text":"Manlove, Kezia R.","contributorId":74651,"corporation":false,"usgs":true,"family":"Manlove","given":"Kezia","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":565166,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cassirer, E. Frances","contributorId":23404,"corporation":false,"usgs":true,"family":"Cassirer","given":"E.","email":"","middleInitial":"Frances","affiliations":[],"preferred":false,"id":565167,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cross, Paul C. 0000-0001-8045-5213 pcross@usgs.gov","orcid":"https://orcid.org/0000-0001-8045-5213","contributorId":2709,"corporation":false,"usgs":true,"family":"Cross","given":"Paul","email":"pcross@usgs.gov","middleInitial":"C.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":565165,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Plowright, Raina K.","contributorId":23038,"corporation":false,"usgs":true,"family":"Plowright","given":"Raina K.","affiliations":[],"preferred":false,"id":565168,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hudson, Peter J.","contributorId":85056,"corporation":false,"usgs":true,"family":"Hudson","given":"Peter J.","affiliations":[],"preferred":false,"id":565169,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70139387,"text":"70139387 - 2014 - A legacy of divergent fishery management regimes and the resilience of rainbow and cutthroat trout populations in Lake Crescent, Olympic National Park, Washington","interactions":[],"lastModifiedDate":"2016-12-19T11:50:01","indexId":"70139387","displayToPublicDate":"2014-11-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2900,"text":"Northwest Science","onlineIssn":"2161-9859","printIssn":"0029-344X","active":true,"publicationSubtype":{"id":10}},"title":"A legacy of divergent fishery management regimes and the resilience of rainbow and cutthroat trout populations in Lake Crescent, Olympic National Park, Washington","docAbstract":"As a means to increase visitation, early fisheries management in the National Park Service (NPS) promoted sport harvest and hatchery supplementation. Today, NPS management objectives focus on the preservation of native fish. We summarized management regimes of Olympic National Park's Lake Crescent, which included decades of liberal sport harvest and hatchery releases of 14.3 million salmonids. Notably, nonnative species failed to persist in the lake. Complementary analyses of annual redd counts (1989–2012) and genetics data delineated three sympatric trout (one rainbow; two cutthroat) populations that exhibited distinct spatial and temporal spawning patterns, variable emergence timings, and genetic distinctiveness. Allacustrine rainbow trout spawned in the lake outlet from January to May. Cutthroat trout spawned in the major inlet tributary (Barnes Creek) from February to June and in the outlet river (Lyre) from September to March, an unusual timing for coastal cutthroat trout. Redd counts for each species were initially low (rainbow = mean 89; range 37–159; cutthroat = mean 93; range 18–180), and significantly increased for rainbow trout (mean 306; range 254–352) after implementation of catch-and-release regulations. Rainbow and cutthroat trout reached maximum sizes of 10.4 kg and 5.4 kg, respectively, and are among the largest throughout their native ranges. Morphometric analyses revealed interspecific differences but no intraspecific differences between the two cutthroat populations. Genetic analyses identified three distinct populations and low levels (9–17%) of interspecific hybridization. Lake Crescent rainbow trout were genetically divergent from 24 nearby Oncorhynchus mykiss populations, and represented a unique evolutionary legacy worthy of protection. The indigenous and geographically isolated Lake Crescent trout populations were resilient to overharvest and potential interactions with introduced fish species.
","language":"English","publisher":"Northwest Scientific Association","publisherLocation":"Cheney, WA","doi":"10.3955/046.088.0404","usgsCitation":"Brenkman, S.J., Duda, J., Kennedy, P.R., and Baker, B.M., 2014, A legacy of divergent fishery management regimes and the resilience of rainbow and cutthroat trout populations in Lake Crescent, Olympic National Park, Washington: Northwest Science, v. 88, no. 4, p. 280-304, https://doi.org/10.3955/046.088.0404.","productDescription":"25 p.","startPage":"280","endPage":"304","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-046220","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":297595,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Lake Crescent, Olympic National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.93264770507812,\n 48.00646264573117\n ],\n [\n -123.93264770507812,\n 48.167917284047974\n ],\n [\n -123.43963623046874,\n 48.167917284047974\n ],\n [\n -123.43963623046874,\n 48.00646264573117\n ],\n [\n -123.93264770507812,\n 48.00646264573117\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"88","issue":"4","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54dd2b1ae4b08de9379b3244","contributors":{"authors":[{"text":"Brenkman, Samuel J.","contributorId":138941,"corporation":false,"usgs":false,"family":"Brenkman","given":"Samuel","email":"","middleInitial":"J.","affiliations":[{"id":12587,"text":"Olympic National Park, Port Angeles, WA","active":true,"usgs":false}],"preferred":false,"id":539378,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Duda, Jeffrey J. 0000-0001-7431-8634 jduda@usgs.gov","orcid":"https://orcid.org/0000-0001-7431-8634","contributorId":3323,"corporation":false,"usgs":true,"family":"Duda","given":"Jeffrey J.","email":"jduda@usgs.gov","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":false,"id":539376,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kennedy, Philip R.","contributorId":63703,"corporation":false,"usgs":false,"family":"Kennedy","given":"Philip","email":"","middleInitial":"R.","affiliations":[{"id":12587,"text":"Olympic National Park, Port Angeles, WA","active":true,"usgs":false}],"preferred":false,"id":539379,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Baker, Bruce M. bakerb@usgs.gov","contributorId":138951,"corporation":false,"usgs":false,"family":"Baker","given":"Bruce","email":"bakerb@usgs.gov","middleInitial":"M.","affiliations":[{"id":12438,"text":"Washington Department of Fish and Wildlife","active":true,"usgs":false}],"preferred":false,"id":539428,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70136277,"text":"70136277 - 2014 - Does lake size matter? Combining morphology and process modeling to examine the contribution of lake classes to population-scale processes","interactions":[],"lastModifiedDate":"2015-08-19T09:14:55","indexId":"70136277","displayToPublicDate":"2014-11-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1999,"text":"Inland Waters","active":true,"publicationSubtype":{"id":10}},"title":"Does lake size matter? Combining morphology and process modeling to examine the contribution of lake classes to population-scale processes","docAbstract":"With lake abundances in the thousands to millions, creating an intuitive understanding of the distribution of morphology and processes in lakes is challenging. To improve researchers’ understanding of large-scale lake processes, we developed a parsimonious mathematical model based on the Pareto distribution to describe the distribution of lake morphology (area, perimeter and volume). While debate continues over which mathematical representation best fits any one distribution of lake morphometric characteristics, we recognize the need for a simple, flexible model to advance understanding of how the interaction between morphometry and function dictates scaling across large populations of lakes. These models make clear the relative contribution of lakes to the total amount of lake surface area, volume, and perimeter. They also highlight the critical thresholds at which total perimeter, area and volume would be evenly distributed across lake size-classes have Pareto slopes of 0.63, 1 and 1.12, respectively. These models of morphology can be used in combination with models of process to create overarching “lake population” level models of process. To illustrate this potential, we combine the model of surface area distribution with a model of carbon mass accumulation rate. We found that even if smaller lakes contribute relatively less to total surface area than larger lakes, the increasing carbon accumulation rate with decreasing lake size is strong enough to bias the distribution of carbon mass accumulation towards smaller lakes. This analytical framework provides a relatively simple approach to upscaling morphology and process that is easily generalizable to other ecosystem processes.
","language":"English","publisher":"Freshwater Biological Association","doi":"10.5268/IW-5.1.740","usgsCitation":"Winslow, L.A., Read, J.S., Hanson, P.C., and Stanley, E.H., 2014, Does lake size matter? Combining morphology and process modeling to examine the contribution of lake classes to population-scale processes: Inland Waters, v. 5, p. 7-14, https://doi.org/10.5268/IW-5.1.740.","productDescription":"8 p.","startPage":"7","endPage":"14","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-051175","costCenters":[{"id":160,"text":"Center for Integrated Data Analytics","active":false,"usgs":true}],"links":[{"id":306908,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"5","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"55d5a8aee4b0518e3546a4bb","contributors":{"authors":[{"text":"Winslow, Luke A. 0000-0002-8602-5510 lwinslow@usgs.gov","orcid":"https://orcid.org/0000-0002-8602-5510","contributorId":5919,"corporation":false,"usgs":true,"family":"Winslow","given":"Luke","email":"lwinslow@usgs.gov","middleInitial":"A.","affiliations":[],"preferred":false,"id":537277,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Read, Jordan S. 0000-0002-3888-6631 jread@usgs.gov","orcid":"https://orcid.org/0000-0002-3888-6631","contributorId":4453,"corporation":false,"usgs":true,"family":"Read","given":"Jordan","email":"jread@usgs.gov","middleInitial":"S.","affiliations":[{"id":160,"text":"Center for Integrated Data Analytics","active":false,"usgs":true},{"id":5054,"text":"Office of Water Information","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":537276,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hanson, Paul C.","contributorId":35634,"corporation":false,"usgs":false,"family":"Hanson","given":"Paul","email":"","middleInitial":"C.","affiliations":[{"id":12951,"text":"Center for Limnology, University of Wisconsin Madison","active":true,"usgs":false}],"preferred":false,"id":537278,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stanley, Emily H.","contributorId":55725,"corporation":false,"usgs":false,"family":"Stanley","given":"Emily","email":"","middleInitial":"H.","affiliations":[{"id":12951,"text":"Center for Limnology, University of Wisconsin Madison","active":true,"usgs":false}],"preferred":false,"id":537279,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70155250,"text":"70155250 - 2014 - A seasonal agricultural drought forecast system for food-insecure regions of East Africa","interactions":[],"lastModifiedDate":"2017-01-18T11:29:02","indexId":"70155250","displayToPublicDate":"2014-11-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1928,"text":"Hydrology and Earth System Sciences","active":true,"publicationSubtype":{"id":10}},"title":"A seasonal agricultural drought forecast system for food-insecure regions of East Africa","docAbstract":" The increasing food and water demands of East Africa's growing population are stressing the region's inconsistent water resources and rain-fed agriculture. More accurate seasonal agricultural drought forecasts for this region can inform better water and agricultural management decisions, support optimal allocation of the region's water resources, and mitigate socio-economic losses incurred by droughts and floods. Here we describe the development and implementation of a seasonal agricultural drought forecast system for East Africa (EA) that provides decision support for the Famine Early Warning Systems Network's science team. We evaluate this forecast system for a region of equatorial EA (2° S to 8° N, and 36° to 46° E) for the March-April-May growing season. This domain encompasses one of the most food insecure, climatically variable and socio-economically vulnerable regions in EA, and potentially the world: this region has experienced famine as recently as 2011.
To assess the agricultural outlook for the upcoming season our forecast system simulates soil moisture (SM) scenarios using the Variable Infiltration Capacity (VIC) hydrologic model forced with climate scenarios for the upcoming season. First, to show that the VIC model is appropriate for this application we forced the model with high quality atmospheric observations and found that the resulting SM values were consistent with the Food and Agriculture Organization's (FAO's) Water Requirement Satisfaction Index (WRSI), an index used by FEWS NET to estimate crop yields. Next we tested our forecasting system with hindcast runs (1993–2012). We found that initializing SM forecasts with start-of-season (5 March) SM conditions resulted in useful SM forecast skill (> 0.5 correlation) at 1-month, and in some cases at 3 month lead times. Similarly, when the forecast was initialized with mid-season (i.e. 5 April) SM conditions the skill until the end-of-season improved. This shows that early-season rainfall is critical for end-of-season outcomes. Finally we show that, in terms of forecasting spatial patterns of SM anomalies, the skill of this agricultural drought forecast system is generally greater (> 0.8 correlation) during drought years. This means that this system might be particularity useful for identifying the events that present the greatest risk to the region.
Sources of seismic hazard in the Puget Sound region of northwestern Washington include deep earthquakes associated with the Cascadia subduction zone, and shallow earthquakes associated with some of the numerous crustal (upper-plate) faults that crisscross the region. Our paleoseismic investigations on one of the more prominent crustal faults, the Darrington–Devils Mountain fault zone, included trenching of fault scarps developed on latest Pleistocene glacial sediments and analysis of cores from an adjacent wetland near Lake Creek, 14 km southeast of Mount Vernon, Washington. Trench excavations revealed evidence of a single earthquake, radiocarbon dated to ca. 2 ka, but extensive burrowing and root mixing of sediments within 50–100 cm of the ground surface may have destroyed evidence of other earthquakes. Cores in a small wetland adjacent to our trench site provided stratigraphic evidence (formation of a laterally extensive, prograding wedge of hillslope colluvium) of an earthquake ca. 2 ka, which we interpret to be the same earthquake documented in the trenches. A similar colluvial wedge lower in the wetland section provides possible evidence for a second earthquake dated to ca. 8 ka. Three-dimensional trenching techniques revealed evidence for 2.2 ± 1.1 m of right-lateral offset of a glacial outwash channel margin, and 45–70 cm of north-side-up vertical separation across the fault zone. These offsets indicate a net slip vector of 2.3 ± 1.1 m, plunging 14° west on a 286°-striking, 90°-dipping fault plane. The dominant right-lateral sense of slip is supported by the presence of numerous Riedel R shears preserved in two of our trenches, and probable right-lateral offset of a distinctive bedrock fault zone in a third trench. Holocene north-side-up, right-lateral oblique slip is opposite the south-side-up, left-lateral oblique sense of slip inferred from geologic mapping of Eocene and older rocks along the fault zone. The cause of this slip reversal is unknown but may be related to clockwise rotation of the Darrington–Devils Mountain fault zone into a position more favorable to right-lateral slip in the modern N-S compressional stress field.
","language":"English","publisher":"Geological Society of America","doi":"10.1130/GES01067.1","usgsCitation":"Personius, S.F., Briggs, R.W., Nelson, A.R., Schermer, E.R., Maharrey, J.Z., Sherrod, B.L., Spaulding, S.A., and Bradley, L., 2014, Holocene earthquakes and right-lateral slip on the left-lateral Darrington-Devils Mountain fault zone, northern Puget Sound, Washington: Geosphere, v. 10, no. 6, p. 1482-1500, https://doi.org/10.1130/GES01067.1.","productDescription":"19 p.","startPage":"1482","endPage":"1500","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-059226","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":472667,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/ges01067.1","text":"Publisher Index Page"},{"id":297530,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Puget Sound","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.46435546875,\n 48.93693495409401\n ],\n [\n -122.10205078125,\n 48.90805939965008\n ],\n [\n -122.14599609375001,\n 47.27922900257082\n ],\n [\n -123.02490234375,\n 47.2195681123155\n ],\n [\n -123.46435546875,\n 48.93693495409401\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"10","issue":"6","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54dd2bc6e4b08de9379b34c0","contributors":{"authors":[{"text":"Personius, Stephen F. personius@usgs.gov","contributorId":1214,"corporation":false,"usgs":true,"family":"Personius","given":"Stephen","email":"personius@usgs.gov","middleInitial":"F.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":false,"id":519229,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Briggs, Richard W. 0000-0001-8108-0046 rbriggs@usgs.gov","orcid":"https://orcid.org/0000-0001-8108-0046","contributorId":4136,"corporation":false,"usgs":true,"family":"Briggs","given":"Richard","email":"rbriggs@usgs.gov","middleInitial":"W.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":519231,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nelson, Alan R. 0000-0001-7117-7098 anelson@usgs.gov","orcid":"https://orcid.org/0000-0001-7117-7098","contributorId":812,"corporation":false,"usgs":true,"family":"Nelson","given":"Alan","email":"anelson@usgs.gov","middleInitial":"R.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":519226,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schermer, Elizabeth R","contributorId":115146,"corporation":false,"usgs":true,"family":"Schermer","given":"Elizabeth","email":"","middleInitial":"R","affiliations":[],"preferred":false,"id":519232,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Maharrey, J. Zebulon","contributorId":116234,"corporation":false,"usgs":true,"family":"Maharrey","given":"J.","email":"","middleInitial":"Zebulon","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":false,"id":519233,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Sherrod, Brian L. 0000-0002-4492-8631 bsherrod@usgs.gov","orcid":"https://orcid.org/0000-0002-4492-8631","contributorId":2834,"corporation":false,"usgs":true,"family":"Sherrod","given":"Brian","email":"bsherrod@usgs.gov","middleInitial":"L.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":519230,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Spaulding, Sarah A. 0000-0002-9787-7743 sspaulding@usgs.gov","orcid":"https://orcid.org/0000-0002-9787-7743","contributorId":1157,"corporation":false,"usgs":true,"family":"Spaulding","given":"Sarah","email":"sspaulding@usgs.gov","middleInitial":"A.","affiliations":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"preferred":true,"id":519228,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Bradley, Lee-Ann bradley@usgs.gov","contributorId":1141,"corporation":false,"usgs":true,"family":"Bradley","given":"Lee-Ann","email":"bradley@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":false,"id":519227,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70178372,"text":"70178372 - 2014 - Transcriptomic analysis of the mussel Elliptio complanata identifies candidate stress-response genes and an abundance of novel or noncoding transcripts","interactions":[],"lastModifiedDate":"2017-07-24T10:35:24","indexId":"70178372","displayToPublicDate":"2014-11-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Transcriptomic analysis of the mussel Elliptio complanata identifies candidate stress-response genes and an abundance of novel or noncoding transcripts","docAbstract":"Mussels are useful indicator species of environmental stress and degradation, and the global decline in freshwater mussel diversity and abundance is of conservation concern. Elliptio complanata is a common freshwater mussel of eastern North America that can serve both as an indicator and as an experimental model for understanding mussel physiology and genetics. To support genetic components of these research goals, we assembled transcriptome contigs from Illumina paired-end reads. Despite efforts to collapse similar contigs, the final assembly was in excess of 136,000 contigs with an N50 of 982 bp. Even so, comparisons to the CEGMA database of conserved eukaryotic genes indicated that ∼20% of genes remain unrepresented. However, numerous candidate stress-response genes were present, and we identified lineage-specific patterns of diversification among molluscs for cytochrome P450 detoxification genes and two saccharide-modifying enzymes: 1,3 beta-galactosyltransferase and fucosyltransferase. Less than a quarter of contigs had protein-level similarity based on modest BLAST and Hmmer3 statistical thresholds. These results add comparative genomic resources for molluscs and suggest a wealth of novel proteins and noncoding transcripts.
","language":"English","publisher":"PLOS","doi":"10.1371/journal.pone.0112420","usgsCitation":"Cornman, R.S., Robertson, L.S., Galbraith, H.S., and Blakeslee, C.J., 2014, Transcriptomic analysis of the mussel Elliptio complanata identifies candidate stress-response genes and an abundance of novel or noncoding transcripts: PLoS ONE, v. 9, no. 11, e112420; 10 p., https://doi.org/10.1371/journal.pone.0112420.","productDescription":"e112420; 10 p.","ipdsId":"IP-060559","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":472676,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0112420","text":"Publisher Index Page"},{"id":330996,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"9","issue":"11","noUsgsAuthors":false,"publicationDate":"2014-11-06","publicationStatus":"PW","scienceBaseUri":"582c2ce6e4b0c253be072c0c","contributors":{"authors":[{"text":"Cornman, Robert S. 0000-0001-9511-2192 rcornman@usgs.gov","orcid":"https://orcid.org/0000-0001-9511-2192","contributorId":5356,"corporation":false,"usgs":true,"family":"Cornman","given":"Robert","email":"rcornman@usgs.gov","middleInitial":"S.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":653795,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Robertson, Laura S. lrobertson@usgs.gov","contributorId":2288,"corporation":false,"usgs":true,"family":"Robertson","given":"Laura","email":"lrobertson@usgs.gov","middleInitial":"S.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":false,"id":653796,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Galbraith, Heather S. 0000-0003-3704-3517 hgalbraith@usgs.gov","orcid":"https://orcid.org/0000-0003-3704-3517","contributorId":4519,"corporation":false,"usgs":true,"family":"Galbraith","given":"Heather","email":"hgalbraith@usgs.gov","middleInitial":"S.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":653797,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Blakeslee, Carrie J. 0000-0002-0801-5325 cblakeslee@usgs.gov","orcid":"https://orcid.org/0000-0002-0801-5325","contributorId":5462,"corporation":false,"usgs":true,"family":"Blakeslee","given":"Carrie","email":"cblakeslee@usgs.gov","middleInitial":"J.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":653798,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70136365,"text":"70136365 - 2014 - Effects of distributed and centralized stormwater best management practices and land cover on urban stream hydrology at the catchment scale","interactions":[],"lastModifiedDate":"2014-12-30T14:59:09","indexId":"70136365","displayToPublicDate":"2014-11-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2342,"text":"Journal of Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"Effects of distributed and centralized stormwater best management practices and land cover on urban stream hydrology at the catchment scale","docAbstract":"Urban stormwater runoff remains an important issue that causes local and regional-scale water quantity and quality issues. Stormwater best management practices (BMPs) have been widely used to mitigate runoff issues, traditionally in a centralized manner; however, problems associated with urban hydrology have remained. An emerging trend is implementation of BMPs in a distributed manner (multi-BMP treatment trains located on the landscape and integrated with urban design), but little catchment-scale performance of these systems have been reported to date. Here, stream hydrologic data (March, 2011–September, 2012) are evaluated in four catchments located in the Chesapeake Bay watershed: one utilizing distributed stormwater BMPs, two utilizing centralized stormwater BMPs, and a forested catchment serving as a reference. Among urban catchments with similar land cover, geology and BMP design standards (i.e. 100-year event), but contrasting placement of stormwater BMPs, distributed BMPs resulted in: significantly greater estimated baseflow, a higher minimum precipitation threshold for stream response and maximum discharge increases, better maximum discharge control for small precipitation events, and reduced runoff volume during an extreme (1000-year) precipitation event compared to centralized BMPs. For all catchments, greater forest land cover and less impervious cover appeared to be more important drivers than stormwater BMP spatial pattern, and caused lower total, stormflow, and baseflow runoff volume; lower maximum discharge during typical precipitation events; and lower runoff volume during an extreme precipitation event. Analysis of hydrologic field data in this study suggests that both the spatial distribution of stormwater BMPs and land cover are important for management of urban stormwater runoff. In particular, catchment-wide application of distributed BMPs improved stream hydrology compared to centralized BMPs, but not enough to fully replicate forested catchment stream hydrology. Integrated planning of stormwater management, protected riparian buffers and forest land cover with suburban development in the distributed-BMP catchment enabled multi-purpose use of land that provided esthetic value and green-space, community gathering points, and wildlife habitat in addition to hydrologic stormwater treatment.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jhydrol.2014.07.007","usgsCitation":"Loperfido, J.V., Noe, G., Jarnagin, S.T., and Hogan, D.M., 2014, Effects of distributed and centralized stormwater best management practices and land cover on urban stream hydrology at the catchment scale: Journal of Hydrology, v. 519, no. Part C, p. 2584-2595, https://doi.org/10.1016/j.jhydrol.2014.07.007.","productDescription":"12 p.","startPage":"2584","endPage":"2595","numberOfPages":"12","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-038949","costCenters":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"links":[{"id":296947,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"519","issue":"Part C","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54dd2b89e4b08de9379b33e6","contributors":{"authors":[{"text":"Loperfido, John V. jloperfido@usgs.gov","contributorId":4324,"corporation":false,"usgs":true,"family":"Loperfido","given":"John","email":"jloperfido@usgs.gov","middleInitial":"V.","affiliations":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"preferred":false,"id":537442,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Noe, Gregory B. 0000-0002-6661-2646 gnoe@usgs.gov","orcid":"https://orcid.org/0000-0002-6661-2646","contributorId":2332,"corporation":false,"usgs":true,"family":"Noe","given":"Gregory","email":"gnoe@usgs.gov","middleInitial":"B.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":false,"id":537441,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jarnagin, S. Taylor","contributorId":131134,"corporation":false,"usgs":false,"family":"Jarnagin","given":"S.","email":"","middleInitial":"Taylor","affiliations":[{"id":7258,"text":"Landscape Ecology Branch, U.S. Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":537443,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hogan, Dianna M. 0000-0003-1492-4514 dhogan@usgs.gov","orcid":"https://orcid.org/0000-0003-1492-4514","contributorId":2299,"corporation":false,"usgs":true,"family":"Hogan","given":"Dianna","email":"dhogan@usgs.gov","middleInitial":"M.","affiliations":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"preferred":false,"id":537440,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70122361,"text":"sir20145166 - 2014 - Groundwater-flow and land-subsidence model of Antelope Valley, California","interactions":[],"lastModifiedDate":"2014-10-31T15:21:38","indexId":"sir20145166","displayToPublicDate":"2014-10-31T14:00:00","publicationYear":"2014","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":"2014-5166","title":"Groundwater-flow and land-subsidence model of Antelope Valley, California","docAbstract":"Antelope Valley, California, is a topographically closed basin in the western part of the Mojave Desert, about 50 miles northeast of Los Angeles. The Antelope Valley groundwater basin is about 940 square miles and is separated from the northern part of Antelope Valley by faults and low-lying hills. Prior to 1972, groundwater provided more than 90 percent of the total water supply in the valley; since 1972, it has provided between 50 and 90 percent. Most groundwater pumping in the valley occurs in the Antelope Valley groundwater basin, which includes the rapidly growing cities of Lancaster and Palmdale. Groundwater-level declines of more than 270 feet in some parts of the groundwater basin have resulted in an increase in pumping lifts, reduced well efficiency, and land subsidence of more than 6 feet in some areas. Future urban growth and limits on the supply of imported water may increase reliance on groundwater.
\n\n
In 2011, the Los Angeles County Superior Court of California ruled that the Antelope Valley groundwater basin is in overdraft—groundwater extractions are in excess of the Court-defined safe yield of the groundwater basin. The Court determined that the safe yield of the adjudicated area of the basin was 110,000 acre-feet per year (acre-ft/yr). Natural recharge is an important component of total groundwater recharge in Antelope Valley; however, the exact quantity and distribution of natural recharge, primarily in the form of mountain-front recharge, is uncertain, with total estimates ranging from 30,000 to 160,000 acre-ft/yr. Technical experts, retained by parties to the adjudication, used 60,000 acre-ft/yr to estimate the sustainable yield of the basin, and this value was used in this study. In order to better understand the uncertainty associated with natural recharge and to provide a tool to aid in groundwater management, a numerical model of groundwater flow and land subsidence in the Antelope Valley groundwater basin was developed using old and new geohydrologic information.
\n\n
The groundwater-flow system consists of three aquifers: the upper, middle, and lower aquifers. The three aquifers, which were identified on the basis of the hydrologic properties, age, and depth of the unconsolidated deposits, consist of gravel, sand, silt, and clay alluvial deposits and clay and silty clay lacustrine deposits. Prior to groundwater development in the valley, recharge was primarily the infiltration of runoff from the surrounding mountains. Groundwater flowed from the recharge areas to discharge areas around the playas where it discharged from the aquifer system as either evapotranspiration or from springs. Partial barriers to horizontal groundwater flow, such as faults, have been identified in the groundwater basin. Water-level declines owing to groundwater development have eliminated the natural sources of discharge, and pumping for agricultural and urban uses have become the primary source of discharge from the groundwater system. Infiltration of return flow from agricultural irrigation has become an important source of recharge to the aquifer system.
\n\n
The groundwater-flow model of the basin was discretized horizontally into a grid of 130 rows and 118 columns of square cells 1 kilometer (0.621 mile) on a side, and vertically into four layers representing the upper (two layers), middle (one layer), and lower (one layer) aquifers. Faults that were thought to act as horizontal-flow barriers were simulated in the model. The model was calibrated to simulate steady-state conditions, represented by 1915 water levels and transient-state conditions during 1915–95, by using water-level and subsidence data. Initial estimates of the aquifer-system properties and stresses were obtained from a previously published numerical model of the Antelope Valley groundwater basin; estimates also were obtained from recently collected hydrologic data and from results of simulations of groundwater-flow and land-subsidence models of the Edwards Air Force Base area. Some of these initial estimates were modified during model calibration. Groundwater pumpage for agriculture was estimated on the basis of irrigated crop acreage and crop consumptive-use data. Pumpage for public supply, which is metered, was compiled and entered into a database used for this study. Estimated annual agricultural pumpage peaked at 395,000 acre-feet (acre-ft) in 1951 and then declined because of declining agricultural production. Recharge from irrigation return flows was assumed to be 30 percent of agricultural pumpage; delays associated with return flow moving through the unsaturated zone were also simulated. The annual quantity of mountain-front recharge initially was based on estimates from previous studies. The model was calibrated using the PEST software suite; prior information from the area was incorporated through the use of Tikhonov regularization. During model calibration, the estimated mountain-front recharge was reduced from the previous estimate of 30,300 acre-ft/yr to 29,150 acre-ft/yr.
\n\n
Results of the simulations using the calibrated model indicate that simulated groundwater pumpage exceeded recharge in most years, resulting in an estimated cumulative depletion in groundwater storage of 8,700,000 acre-ft during the transient-simulation period (1915–2005). About 15,000,000 acre-ft of cumulative groundwater pumpage was simulated during the transient-simulation period (1915–2005), reaching a maximum rate of about 400,000 acre-ft/yr in 1951. Groundwater pumpage resulted in simulated hydraulic heads declining by more than 150 feet (ft) compared to 1915 conditions in agricultural areas. The decline in hydraulic head in the groundwater basin is the result of this depletion of groundwater storage. In turn, the simulated decline in hydraulic head in the groundwater basin has resulted in the decrease in natural discharge from the basin and has caused compaction of aquitards, resulting in land subsidence. The areal distribution of total simulated land subsidence for 2005, after about 90 years of groundwater development, indicates that land subsidence occurred throughout almost the entire Lancaster subbasin, with a maximum of about 9.4 ft in the central and eastern parts of the subbasin.
\n\n
An important objective of this study was to systematically address the uncertainty in estimates of natural recharge and related aquifer parameters by using the groundwater-flow and land-subsidence model with observational data and expert knowledge. After the model was calibrated to the observations and a reasonable parameter set obtained, the parameter null space—parameter values that do not appreciably affect the model calibration but may have importance for prediction—was identified. The effect of parameter uncertainty on the estimation of mountain-front recharge was addressed using the Null-Space Monte Carlo method. The Pareto trade-off method of visualizing uncertainty was also used to portray the reasonableness of larger natural-recharge rates. Results indicate that the total mountain-front recharge likely ranges between 28,000 and 44,000 acre-ft/yr, which is appreciably less than published estimates of 60,000 acre-ft/yr. Additionally, expected errors associated with agricultural pumpage estimates used in this study were found to have relatively little effect on the estimates of mountain-front recharge, reflecting the difficulty in increasing recharge through manipulation of other components of the water budget.
\n\n
The calibrated model was used to simulate the response of the aquifer to potential future pumping scenarios: (1) no change in the distribution of pumpage, or status quo; (2) redistribution of pumpage; and (3) artificial recharge. All three of these scenarios specify a total pumpage throughout the Antelope Valley of 110,000 acre-ft/yr according to the safe yield value ruled by the Los Angeles County Superior Court of California. This reduction in groundwater pumpage is assumed uniform throughout the basin, based on a 10-percent reduction of the total pumpage in 2005 to achieve the 110,000 acre-ft/yr level. The calibrated Antelope Valley groundwater-flow and land-subsidence model was used to simulate the hydrologic effects of the three groundwater-management scenarios during a 50-year period by using the reduced, temporally constant, pumpage distribution.
\n\n
Results from the first scenario indicated that the total drawdown observed since predevelopment would continue, with values exceeding 325 ft near Palmdale; consequently, land subsidence would also continue, with additional subsidence (since 2005) exceeding 3 ft in the central part of the Lancaster subbasin. The second scenario evaluated redistributing pumpage from areas in the Lancaster subbasin where simulated hydraulic-head declines were the greatest to areas where declines were smallest. Neither a formal optimization algorithm nor water-rights allocations were considered when redistributing the pumpage. Results indicated that hydraulic heads near Palmdale, where the pumpage was reduced, would recover by about 200 ft compared to 2005 conditions, with only 30 ft of additional drawdown in the northwestern part of the Lancaster subbasin, where the pumpage was increased. The magnitude of the simulated additional land subsidence decreased slightly compared to the first, status quo, scenario but land subsidence continued to be simulated throughout most of the northern part of the Lancaster subbasin. The third scenario consisted of two artificial-recharge simulations along the Upper Amargosa Creek channel and at a site located north of Antelope Buttes. Results indicate that applying artificial recharge at these sites would yield continued drawdowns and associated land subsidence. However, the magnitudes of drawdown and subsidence would be smaller than those simulated in the status quo scenario, indicating that artificial-recharge operations in the Antelope Valley could be expected to reduce the magnitude and extent of continued water-level declines and associated land subsidence.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145166","collaboration":"Prepared in cooperation with the Los Angeles County Department of Public Works, Antelope Valley-East Kern Water Agency, Palmdale Water District, and Edwards Air Force Base","usgsCitation":"Siade, A.J., Nishikawa, T., Rewis, D.L., Martin, P., and Phillips, S.P., 2014, Groundwater-flow and land-subsidence model of Antelope Valley, California: U.S. Geological Survey Scientific Investigations Report 2014-5166, Report: xiv, 138 p.; 5 Appendix Tables, https://doi.org/10.3133/sir20145166.","productDescription":"Report: xiv, 138 p.; 5 Appendix Tables","numberOfPages":"154","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-023623","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":295810,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20145166.jpg"},{"id":295798,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2014/5166/pdf/sir2014-5166.pdf","size":"13.5 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":295799,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2014/5166/downloads/sir2014-5166_appendix_2_table_1.xlsx","text":"Appendix 2 Table 1","size":"1.5 MB","linkFileType":{"id":3,"text":"xlsx"}},{"id":295800,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2014/5166/downloads/sir2014-5166_appendix_3_table_1_and_2.xlsx","text":"Appendix 3 Tables 1 and 2","size":"259 kB","linkFileType":{"id":3,"text":"xlsx"}},{"id":295801,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2014/5166/downloads/sir2014-5166_appendix_4_table_1.xlsx","text":"Appendix 4 Table 1","size":"222 kB","linkFileType":{"id":3,"text":"xlsx"}},{"id":295802,"rank":6,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2014/5166/downloads/sir2014-5166_appendix_7_table_1.xlsx","text":"Appendix 7 Table 1","size":"238 kB","linkFileType":{"id":3,"text":"xlsx"}},{"id":295803,"rank":7,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2014/5166/downloads/sir2014-5166_appendixtables.xlsx","text":"Appendix Tables","size":"1.3 MB","linkFileType":{"id":3,"text":"xlsx"}},{"id":295777,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2014/5166/"}],"country":"United States","state":"California","otherGeospatial":"Antelope Valley","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5454968ee4b0dc7793747c72","contributors":{"authors":[{"text":"Siade, Adam J. asiade@usgs.gov","contributorId":1533,"corporation":false,"usgs":true,"family":"Siade","given":"Adam","email":"asiade@usgs.gov","middleInitial":"J.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":522821,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nishikawa, Tracy 0000-0002-7348-3838 tnish@usgs.gov","orcid":"https://orcid.org/0000-0002-7348-3838","contributorId":1515,"corporation":false,"usgs":true,"family":"Nishikawa","given":"Tracy","email":"tnish@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":522824,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rewis, Diane L. dlrewis@usgs.gov","contributorId":1511,"corporation":false,"usgs":true,"family":"Rewis","given":"Diane","email":"dlrewis@usgs.gov","middleInitial":"L.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":522822,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Martin, Peter pmmartin@usgs.gov","contributorId":799,"corporation":false,"usgs":true,"family":"Martin","given":"Peter","email":"pmmartin@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":522823,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Phillips, Steven P. 0000-0002-5107-868X sphillip@usgs.gov","orcid":"https://orcid.org/0000-0002-5107-868X","contributorId":1506,"corporation":false,"usgs":true,"family":"Phillips","given":"Steven","email":"sphillip@usgs.gov","middleInitial":"P.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":522879,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70141779,"text":"70141779 - 2014 - Influence of fuels, weather and the built environment on the exposure of property to wildfire","interactions":[],"lastModifiedDate":"2015-02-20T16:17:06","indexId":"70141779","displayToPublicDate":"2014-10-31T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Influence of fuels, weather and the built environment on the exposure of property to wildfire","docAbstract":"Wildfires can pose a significant risk to people and property. Billions of dollars are spent investing in fire management actions in an attempt to reduce the risk of loss. One of the key areas where money is spent is through fuel treatment – either fuel reduction (prescribed fire) or fuel removal (fuel breaks). Individual treatments can influence fire size and the maximum distance travelled from the ignition and presumably risk, but few studies have examined the landscape level effectiveness of these treatments. Here we use a Bayesian Network model to examine the relative influence of the built and natural environment, weather, fuel and fuel treatments in determining the risk posed from wildfire to the wildland-urban interface. Fire size and distance travelled was influenced most strongly by weather, with exposure to fires most sensitive to changes in the built environment and fire parameters. Natural environment variables and fuel load all had minor influences on fire size, distance travelled and exposure of assets. These results suggest that management of fuels provided minimal reductions in risk to assets and adequate planning of the changes in the built environment to cope with the expansion of human populations is going to be vital for managing risk from fire under future climates.
","language":"English","publisher":"PLOS One","doi":"10.1371/journal.pone.0111414","usgsCitation":"Penman, T.D., Collins, L.S., Syphard, A.D., Keeley, J.E., and Bradstock, R.A., 2014, Influence of fuels, weather and the built environment on the exposure of property to wildfire: PLoS ONE, v. 9, no. 10, e111414; 9 p., https://doi.org/10.1371/journal.pone.0111414.","productDescription":"e111414; 9 p.","numberOfPages":"9","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-056457","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":472678,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0111414","text":"Publisher Index Page"},{"id":298077,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"9","issue":"10","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2014-10-31","publicationStatus":"PW","scienceBaseUri":"54e868bee4b02d776a67c5c9","contributors":{"authors":[{"text":"Penman, Trent D.","contributorId":139403,"corporation":false,"usgs":false,"family":"Penman","given":"Trent","email":"","middleInitial":"D.","affiliations":[{"id":12769,"text":"Centre for Environmental Rist Management of Bushfires, U of Wollongong, Australia","active":true,"usgs":false}],"preferred":false,"id":541089,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Collins, Luke S.","contributorId":76108,"corporation":false,"usgs":false,"family":"Collins","given":"Luke","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":541090,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Syphard, Alexandra D.","contributorId":8977,"corporation":false,"usgs":false,"family":"Syphard","given":"Alexandra","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":541091,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Keeley, Jon E. 0000-0002-4564-6521 jon_keeley@usgs.gov","orcid":"https://orcid.org/0000-0002-4564-6521","contributorId":1268,"corporation":false,"usgs":true,"family":"Keeley","given":"Jon","email":"jon_keeley@usgs.gov","middleInitial":"E.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":541092,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bradstock, Ross A.","contributorId":42826,"corporation":false,"usgs":false,"family":"Bradstock","given":"Ross","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":541093,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ]}