The mission of the Gap Analysis Project (GAP) is to support national and regional assessments of the conservation status of vertebrate species and plant communities. This report explains conterminous United States species richness maps created by the U.S. Geological Survey for four major classes in the phylum Chordata: mammals, birds, reptiles, and amphibians. In this work, we focus on terrestrial vertebrate species and the spatial patterns of richness derived from species’ habitat distribution models. We created species’ habitat distribution models for 1,590 species (282 amphibians, 621 birds, 365 mammals, 322 reptiles) and an additional 129 subspecies (2 amphibians, 28 birds, 94 mammals, 5 reptiles) that occur in the conterminous United States. The 1,590 species level models were spatially combined to create the taxa richness maps at a spatial resolution of 30 meters. Based on those maps we identified the maximum species richness for each of the taxa (43 amphibians, 163 birds, 72 mammals, and 54 reptiles) and show variation in richness across the conterminous United States. Because these habitat models remove unsuitable areas within the range of the species, the patterns of richness presented here are different from the coarse-resolution species’ habitat distribution models commonly presented in the literature. These maps provide a new, more spatially refined richness map. In addition, since these models are logically linked to mapped data layers that constitute habitat suitability, this suite of data can provide an intuitive data system for further exploration of biodiversity and implications for change at ecosystem and landscape scales.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/sir20195034","collaboration":"Prepared in cooperation with North Carolina State University, New Mexico State University, and Boise State University","usgsCitation":"Gergely, K.J., Boykin, K.G., McKerrow, A.J., Rubino, M.J., Tarr, N.M., and Williams, S.G., 2019, Gap Analysis Project (GAP) terrestrial vertebrate species richness maps for the conterminous U.S.: U.S. Geological Survey Scientific Investigations Report 2019–5034, 99 p., https://doi.org/10.3133/sir20195034.","productDescription":"v, 99 p.","numberOfPages":"110","onlineOnly":"Y","ipdsId":"IP-099179","costCenters":[{"id":208,"text":"Core Science Analytics and Synthesis","active":true,"usgs":true},{"id":38315,"text":"GAP Analysis Project","active":true,"usgs":true}],"links":[{"id":364342,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7V122T2","text":"USGS data release","linkHelpText":"U.S. Geological Survey - Gap Analysis Project Species Habitat Maps CONUS_2001"},{"id":364248,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7Q81B3R","text":"USGS data release","linkHelpText":"U.S. Geological Survey - Gap Analysis Project Species Range Maps CONUS_2001"},{"id":364247,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2019/5034/sir20195034.pdf","text":"Report","size":"7.26 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2019–5034"},{"id":364246,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2019/5034/coverthb.jpg"}],"contact":"Director, Core Science Analytics and Synthesis
U.S. Geological Survey
Box 25046, MS-302
Denver, CO 80225-0046
Reef canopies are complex and extremely variable across a range of spatial scales. This variability affects the velocity above as well as within the canopy, and directly impacts the transport of sediment along the bed as well as suspended in the water column. How a canopy affects the transport of sediment is important to understand and predict changes in the position of the adjacent shoreline, particularly as reefs change. In this study, high-resolution seabed complexity models derived from photogrammetry for low roughness and high roughness canopy sites at Moloka’i (Hawai’i) are combined with direct field measurements and three-dimensional numerical modelling to investigate these canopy and sub-canopy impacts on velocity and sediment transport.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Coastal Sediments 2019 Proceedings","largerWorkSubtype":{"id":12,"text":"Conference publication"},"language":"English","publisher":"World Scientific","doi":"10.1142/9789811204487_0083","usgsCitation":"Pomeroy, A., Storlazzi, C.D., Rosenberger, K.J., Hatcher, G., and Warrick, J.A., 2019, Integrating structure from motion, numerical modelling and field measurements to understand carbonate sediment transport in coral reef canopies, in Coastal Sediments 2019 Proceedings, p. 959-969, https://doi.org/10.1142/9789811204487_0083.","productDescription":"11 p.","startPage":"959","endPage":"969","ipdsId":"IP-105554","costCenters":[],"links":[{"id":365999,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"Molokai","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -157.30911254882812,\n 21.01400911571511\n ],\n [\n -156.70623779296875,\n 21.01400911571511\n ],\n [\n -156.70623779296875,\n 21.27657804234913\n ],\n [\n -157.30911254882812,\n 21.27657804234913\n ],\n [\n -157.30911254882812,\n 21.01400911571511\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Pomeroy, Andrew","contributorId":182033,"corporation":false,"usgs":false,"family":"Pomeroy","given":"Andrew","affiliations":[],"preferred":false,"id":767239,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Storlazzi, Curt D. 0000-0001-8057-4490 cstorlazzi@usgs.gov","orcid":"https://orcid.org/0000-0001-8057-4490","contributorId":140584,"corporation":false,"usgs":true,"family":"Storlazzi","given":"Curt","email":"cstorlazzi@usgs.gov","middleInitial":"D.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true}],"preferred":true,"id":767240,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rosenberger, Kurt J. 0000-0002-5185-5776 krosenberger@usgs.gov","orcid":"https://orcid.org/0000-0002-5185-5776","contributorId":140453,"corporation":false,"usgs":true,"family":"Rosenberger","given":"Kurt","email":"krosenberger@usgs.gov","middleInitial":"J.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true}],"preferred":true,"id":767241,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hatcher, Gerry ghatcher@usgs.gov","contributorId":3556,"corporation":false,"usgs":true,"family":"Hatcher","given":"Gerry","email":"ghatcher@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":767242,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Warrick, Jonathan A. 0000-0002-0205-3814 jwarrick@usgs.gov","orcid":"https://orcid.org/0000-0002-0205-3814","contributorId":167736,"corporation":false,"usgs":true,"family":"Warrick","given":"Jonathan","email":"jwarrick@usgs.gov","middleInitial":"A.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":767243,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70203209,"text":"fs20193026 - 2019 - Geological and geophysical data for a three-dimensional view—Inside the San Juan and Silverton Calderas, Southern Rocky Mountains Volcanic Field, Silverton, Colorado","interactions":[],"lastModifiedDate":"2019-06-05T14:01:16","indexId":"fs20193026","displayToPublicDate":"2019-06-04T11:10:00","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2019-3026","title":"Geological and geophysical data for a three-dimensional view—Inside the San Juan and Silverton Calderas, Southern Rocky Mountains Volcanic Field, Silverton, Colorado","docAbstract":"The San Juan-Silverton caldera complex located near Silverton, Colorado, in the Southern Rocky Mountains volcanic field is an ideal natural laboratory for furthering the understanding of shallow-to-deep volcanic-related mineral systems. Recent advances in geophysical data processing and three-dimensional (3D) model construction will help to characterize shallow properties important for understanding surface water and groundwater quality issues and will also improve knowledge of deep geological structures that may have been conduits for hydrothermal fluids that formed mineral deposits. The study has general applications to mineral resource assessments in other areas of the world and to identifying possible groundwater flow paths and associated geochemistry important in abandoned mine lands cleanup.
Silverton, Colorado, is the site of a spectacular succession of igneous rocks that formed beginning about 35 million years ago (Ma). Base metals (copper, lead, and zinc) and precious metals (silver and gold) mined from the late 1870s to 1991 owe their existence to a 25-million-year cycle of igneous activity. The presence of economic, base, and precious metal deposits within a complex geological setting were largely responsible for stimulating studies by the U.S. Geological Survey (USGS) conducted during the early 20th century. The focus of investigations in the late 20th and 21st centuries have broadened in scope to include abandoned mine lands (AML) investigations. The legacy of hard rock mining in headwater catchment areas caused environmental challenges for local communities and downstream water resource users. The Gold King Mine, located a few kilometers north of Silverton, illustrates the potential environmental effects of abandoned mines. On August 5, 2015, during reclamation efforts at the Gold King Mine, a breach of collapsed workings sent approximately 3 million gallons of acidic and metal-rich mine water into the upper Animas River, a tributary to the Colorado River Basin. Mining-related sources of metals and acidity add to geological sources of metals in surface water and groundwater. Weathering processes of altered and mineralized rock have been a source of acid rock drainage that have been ongoing for millennia.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/fs20193026","collaboration":"Prepared in collaboration with U.S. Forest Service, Bureau of Land Management, U.S. Environmental Protection Agency, Colorado Division of Reclamation Mining and Safety, Colorado Department of Public Health and Environment, and Animas River Stakeholders Group","usgsCitation":"Yager, D.B., Anderson, E.D., Rodriguez, B.D., Deszcz-Pan, M., and Smith, B.D., 2019, Geological and geophysical data for a three-dimensional view—Inside the San Juan and Silverton calderas, Southern Rocky Mountains volcanic field, Silverton, Colorado: U.S. Geological Survey Fact Sheet 2019-3026, 4 p., https://doi.org/10.3133/fs20193026.","productDescription":"4 p.","onlineOnly":"N","ipdsId":"IP-103569","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":364304,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2019/3026/coverthb.jpg"},{"id":364305,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2019/3026/fs20193026.pdf","text":"Report","size":"8.83 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2019-3026"}],"country":"United States","state":"Colorado","county":"San Juan County","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-107.5857,37.9702],[-107.5786,37.9667],[-107.5721,37.9636],[-107.5632,37.9573],[-107.5584,37.9524],[-107.5549,37.9493],[-107.5502,37.9475],[-107.5361,37.9445],[-107.5319,37.9414],[-107.5324,37.9378],[-107.5347,37.9337],[-107.5352,37.9291],[-107.5351,37.9237],[-107.532,37.9178],[-107.5278,37.9088],[-107.5247,37.9039],[-107.5212,37.9007],[-107.5211,37.8967],[-107.5279,37.8875],[-107.5324,37.8806],[-107.5329,37.8748],[-107.5317,37.8734],[-107.5305,37.8716],[-107.5204,37.8618],[-107.5179,37.8554],[-107.5184,37.8486],[-107.5176,37.84],[-107.5146,37.8342],[-107.5127,37.8288],[-107.5121,37.8265],[-107.5109,37.8256],[-107.5068,37.8243],[-107.491,37.8236],[-107.4828,37.8223],[-107.4757,37.817],[-107.4705,37.8143],[-107.4669,37.8107],[-107.4627,37.8044],[-107.4578,37.7918],[-107.457,37.785],[-107.4581,37.7791],[-107.4666,37.7668],[-107.4677,37.7645],[-107.4695,37.7645],[-107.4777,37.768],[-107.4812,37.7684],[-107.4829,37.7675],[-107.484,37.7648],[-107.4824,37.7407],[-107.4832,37.6374],[-107.6698,37.6372],[-107.6849,37.6375],[-107.6867,37.6375],[-107.9686,37.6377],[-107.9628,37.6401],[-107.96,37.6415],[-107.9583,37.6429],[-107.9572,37.6456],[-107.9572,37.6479],[-107.9579,37.6524],[-107.9604,37.6592],[-107.9629,37.6646],[-107.966,37.6718],[-107.9685,37.6777],[-107.9698,37.6822],[-107.9699,37.6867],[-107.9688,37.6899],[-107.966,37.6936],[-107.9615,37.6977],[-107.9575,37.7005],[-107.9534,37.7024],[-107.9505,37.7029],[-107.9471,37.7029],[-107.9389,37.7017],[-107.936,37.7017],[-107.9331,37.7027],[-107.9274,37.706],[-107.9239,37.7074],[-107.9181,37.7079],[-107.9135,37.7098],[-107.9094,37.7112],[-107.9049,37.7154],[-107.9014,37.7168],[-107.8968,37.7173],[-107.8904,37.717],[-107.8817,37.7162],[-107.8764,37.7163],[-107.8747,37.7172],[-107.873,37.7213],[-107.8726,37.7259],[-107.8733,37.7317],[-107.8717,37.7368],[-107.8684,37.7431],[-107.8644,37.7477],[-107.8627,37.7509],[-107.8622,37.7537],[-107.8629,37.7559],[-107.8641,37.7582],[-107.8659,37.76],[-107.8677,37.7617],[-107.8683,37.7635],[-107.8672,37.7663],[-107.8615,37.7732],[-107.8592,37.7737],[-107.854,37.7742],[-107.8493,37.7734],[-107.8446,37.7721],[-107.8423,37.7721],[-107.84,37.7726],[-107.8354,37.7767],[-107.8275,37.7859],[-107.8224,37.7915],[-107.8213,37.7928],[-107.8225,37.7955],[-107.8268,37.8063],[-107.8263,37.8082],[-107.8258,37.81],[-107.8085,37.8207],[-107.8056,37.8212],[-107.8004,37.8212],[-107.7975,37.8213],[-107.7952,37.8222],[-107.7935,37.8236],[-107.7918,37.8277],[-107.7885,37.8332],[-107.7868,37.8355],[-107.7845,37.8378],[-107.7812,37.8451],[-107.7762,37.8556],[-107.7756,37.857],[-107.7768,37.8592],[-107.7781,37.8615],[-107.7741,37.8656],[-107.7655,37.8739],[-107.7553,37.8845],[-107.7479,37.8923],[-107.7422,37.8982],[-107.7359,37.9038],[-107.7188,37.8977],[-107.7077,37.8955],[-107.7024,37.892],[-107.6977,37.8912],[-107.6942,37.8917],[-107.6897,37.8967],[-107.6879,37.8976],[-107.6862,37.899],[-107.6839,37.9],[-107.681,37.9],[-107.6682,37.9011],[-107.6595,37.9039],[-107.6514,37.9081],[-107.6422,37.9146],[-107.6394,37.9187],[-107.6389,37.9237],[-107.6404,37.9368],[-107.6405,37.9404],[-107.6407,37.9491],[-107.6385,37.9545],[-107.635,37.9586],[-107.6263,37.9588],[-107.6216,37.9588],[-107.6077,37.9636],[-107.5961,37.9669],[-107.588,37.9688],[-107.5857,37.9702]]]},\"properties\":{\"name\":\"San Juan\",\"state\":\"CO\"}}]}","contact":"Director, Geology, Geophysics, and Geochemistry Science Center
U.S. Geological Survey
Box 25046, MS-964
Denver, CO 80225-0046
Bringing Bayesian Models to Life empowers the reader to extend, enhance, and implement statistical models for ecological and environmental data analysis. We open the black box and show the reader how to connect modern statistical models to computer algorithms. These algorithms allow the user to fit models that answer their scientific questions without needing to rely on automated Bayesian software. We show how to handcraft statistical models that are useful in ecological and environmental science including: linear and generalized linear models, spatial and time series models, occupancy and capture-recapture models, animal movement models, spatio-temporal models, and integrated population-models.
","language":"English","publisher":"Taylor & Francis","doi":"10.1201/9780429243653","usgsCitation":"Hooten, M., and Hefley, T.J., 2019, Bringing Bayesian models to life, 590 p., https://doi.org/10.1201/9780429243653.","productDescription":"590 p.","ipdsId":"IP-103401","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":395444,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationDate":"2019-05-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Hooten, Mevin 0000-0002-1614-723X mhooten@usgs.gov","orcid":"https://orcid.org/0000-0002-1614-723X","contributorId":2958,"corporation":false,"usgs":true,"family":"Hooten","given":"Mevin","email":"mhooten@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":12963,"text":"Colorado Cooperative Fish and Wildlife Research Unit, Fort Collins, CO","active":true,"usgs":false}],"preferred":true,"id":833185,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hefley, Trevor J.","contributorId":147146,"corporation":false,"usgs":false,"family":"Hefley","given":"Trevor","email":"","middleInitial":"J.","affiliations":[{"id":16796,"text":"Dept Fish, Wildlife & Cons Biol, Colorado St Univ, Fort Collins, CO","active":true,"usgs":false}],"preferred":false,"id":833186,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70203794,"text":"70203794 - 2019 - Contemporary human impacts on alpine ecosystems: the direct and indirect effects of human-induced climate change and land use","interactions":[],"lastModifiedDate":"2019-06-13T08:58:02","indexId":"70203794","displayToPublicDate":"2019-06-04T08:57:07","publicationYear":"2019","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Contemporary human impacts on alpine ecosystems: the direct and indirect effects of human-induced climate change and land use","docAbstract":"Alpine ecosystems account for ca. 3 % of terrestrial habitats yet, along with adjacent mountain systems, provide water resources to nearly half of the world’s human population. Approximately 20 % of humans live in or near mountain areas, making it inherently important to understand current impacts on these systems. Here, I review literature regarding current and projected human impacts on alpine ecosystems, including the direct and indirect impacts of human-induced climate change on alpine plant, animal, and soil communities. I also discuss the influence of recreation and tourism, grazing, and other land use changes including the introduction of non-native and invasive species in alpine systems. I conclude with management implications as well as future areas of research needed to better understand changes to these systems.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Reference Module in Earth Systems and Environmental Sciences","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Elsevier","doi":"10.1016/B978-0-12-409548-9.11879-2","usgsCitation":"Winkler, D.E., 2019, Contemporary human impacts on alpine ecosystems: the direct and indirect effects of human-induced climate change and land use, chap. of Reference Module in Earth Systems and Environmental Sciences, https://doi.org/10.1016/B978-0-12-409548-9.11879-2.","ipdsId":"IP-103065","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":364628,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":364616,"type":{"id":15,"text":"Index Page"},"url":"https://www.sciencedirect.com/science/article/pii/B9780124095489118792?via%3Dihub"}],"publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Winkler, Daniel E. 0000-0003-4825-9073","orcid":"https://orcid.org/0000-0003-4825-9073","contributorId":206786,"corporation":false,"usgs":true,"family":"Winkler","given":"Daniel","email":"","middleInitial":"E.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":764150,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70207500,"text":"70207500 - 2019 - A physical model of the high-frequency seismic signal generated by debris flows","interactions":[],"lastModifiedDate":"2019-12-20T16:22:06","indexId":"70207500","displayToPublicDate":"2019-06-03T16:15:07","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1425,"text":"Earth Surface Processes and Landforms","active":true,"publicationSubtype":{"id":10}},"title":"A physical model of the high-frequency seismic signal generated by debris flows","docAbstract":"We propose a physical model for the high‐frequency (>1 Hz) spectral distribution of seismic power generated by debris flows. The modeled debris flow is assumed to have four regions where the impact rate and impulses are controlled by different mechanisms: the flow body, a coarser‐grained snout, a snout lip where particles fall from the snout on the bed, and a dilute front composed of saltating particles. We calculate the seismic power produced by this impact model in two end‐member scenarios, a thin‐flow and thick‐flow limit, which assume that the ratio of grain sizes to flow thicknesses are either near unity or much less than unity. The thin‐flow limit is more appropriate for boulder‐rich flows that are most likely to generate large seismic signals. As a flow passes a seismic station, the rise phase of the seismic amplitude is generated primarily by the snout while the decay phase is generated first by the snout and then the main flow body. The lip and saltating front generate a negligible seismic signal. When ground properties are known, seismic power depends most strongly on both particle diameter and average flow speed cubed, and also depends on length and width of the flow. The effective particle diameter for producing seismic power is substantially higher than the median grain size and close to the 73rd percentile for a realistic grain size distribution. We discuss how the model can be used to estimate effective particle diameter and average flow speed from an integrated measure of seismic power.","language":"English","publisher":"Wiley","doi":"10.1002/esp.4677","usgsCitation":"Farin, M., Tsai, V.C., Lamb, M.P., and Allstadt, K.E., 2019, A physical model of the high-frequency seismic signal generated by debris flows: Earth Surface Processes and Landforms, v. 44, no. 13, p. 2529-2543, https://doi.org/10.1002/esp.4677.","productDescription":"15 p.","startPage":"2529","endPage":"2543","ipdsId":"IP-107456","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":467561,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/esp.4677","text":"Publisher Index Page"},{"id":370589,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"44","issue":"13","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2019-07-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Farin, Maxime 0000-0002-0250-2499","orcid":"https://orcid.org/0000-0002-0250-2499","contributorId":221438,"corporation":false,"usgs":false,"family":"Farin","given":"Maxime","email":"","affiliations":[{"id":7218,"text":"California Institute of Technology","active":true,"usgs":false}],"preferred":false,"id":778239,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tsai, Victor C. 0000-0003-1809-6672","orcid":"https://orcid.org/0000-0003-1809-6672","contributorId":199684,"corporation":false,"usgs":false,"family":"Tsai","given":"Victor","email":"","middleInitial":"C.","affiliations":[{"id":27150,"text":"Seismological Laboratory, California Institute of Technology, Pasadena, CA, USA","active":true,"usgs":false}],"preferred":false,"id":778240,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lamb, Michael P.","contributorId":214027,"corporation":false,"usgs":false,"family":"Lamb","given":"Michael","email":"","middleInitial":"P.","affiliations":[{"id":13711,"text":"Caltech","active":true,"usgs":false}],"preferred":false,"id":778241,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Allstadt, Kate E. 0000-0003-4977-5248","orcid":"https://orcid.org/0000-0003-4977-5248","contributorId":138704,"corporation":false,"usgs":true,"family":"Allstadt","given":"Kate","email":"","middleInitial":"E.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":778242,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70203934,"text":"70203934 - 2019 - Local niche differences predict genotype associations in sister taxa of desert tortoise","interactions":[],"lastModifiedDate":"2019-08-13T15:56:55","indexId":"70203934","displayToPublicDate":"2019-06-03T15:37:57","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1399,"text":"Diversity and Distributions","active":true,"publicationSubtype":{"id":10}},"title":"Local niche differences predict genotype associations in sister taxa of desert tortoise","docAbstract":"Aims
To investigate spatial congruence between ecological niches and genotype in two allopatric species of desert tortoise that are species of conservation concern.
Location
Mojave and Sonoran Desert ecoregions; California, Nevada, Arizona, Utah, USA.
Methods
We compare ecological niches of Gopherus agassizii and Gopherus morafkai using species distribution modelling (SDM) and then calibrate a pooled‐taxa distribution model to explore local differences in species–environment relationships based on the spatial residuals of the pooled‐taxa model. We use multiscale geographically weighted regression (MGWR) applied to those residuals to estimate local species–environment relationships that can vary across the landscape. We identify multivariate clusters in these local species–environment relationships and compare them against models of (a) a geographically based taxonomic designation for two sister species and (b) an environmental ecoregion designation, with respect to their ability to predict a genotype association index for these two species.
Results
We find non‐identical niches for these species, with differences that span physiographic and vegetation niche dimensions. We find evidence for two distinct clusters of local species–environment relationships that when mapped, predict an index of genotype association for the two sister taxa better than did either the geographically based taxonomic designation or an environmental ecoregion designation.
Main conclusions
Exploring local species–environment relationships by coupling SDM and MGWR can benefit studies of biogeography and conservation. We find that niche separation in habitat selection conforms to genotypic differences between sister taxa of tortoise in a recent secondary contact zone. This result may inform decision making by agencies with regulatory or land management authority for the two sister taxa addressed here.
","language":"English","publisher":"John Wiley & Sons Ltd","doi":"10.1111/ddi.12927","usgsCitation":"Inman, R.D., Fotheringham, A.S., Franklin, J., Esque, T., Edwards, T., and Nussear, K., 2019, Local niche differences predict genotype associations in sister taxa of desert tortoise: Diversity and Distributions, v. 25, no. 8, p. 1194-1209, https://doi.org/10.1111/ddi.12927.","productDescription":"16 p.","startPage":"1194","endPage":"1209","ipdsId":"IP-104147","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":467562,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/ddi.12927","text":"Publisher Index Page"},{"id":437431,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P91V2S8C","text":"USGS data release","linkHelpText":"Local ecological niche models, genotype associations and environmental data for desert tortoises."},{"id":364964,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona, California, Nevada, Utah","otherGeospatial":"Mojave Desert, Sonoran Desert","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -119.61914062499999,\n 34.379712580462204\n ],\n [\n -118.564453125,\n 33.797408767572485\n ],\n [\n -117.68554687499999,\n 33.578014746143985\n ],\n [\n -117.158203125,\n 32.62087018318113\n ],\n [\n -114.7412109375,\n 32.731840896865684\n ],\n [\n -114.78515624999999,\n 32.509761735919426\n ],\n [\n -110.830078125,\n 31.316101383495624\n ],\n [\n -109.2919921875,\n 33.100745405144245\n ],\n [\n -112.19238281249999,\n 36.10237644873644\n ],\n [\n -111.7529296875,\n 37.89219554724437\n ],\n [\n -117.24609374999999,\n 37.37015718405753\n ],\n [\n -120.234375,\n 36.4566360115962\n ],\n [\n -119.61914062499999,\n 34.379712580462204\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"25","issue":"8","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2019-06-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Inman, Richard D. 0000-0002-1982-7791 rdinman@usgs.gov","orcid":"https://orcid.org/0000-0002-1982-7791","contributorId":187754,"corporation":false,"usgs":true,"family":"Inman","given":"Richard","email":"rdinman@usgs.gov","middleInitial":"D.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":764835,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fotheringham, A. Stewart","contributorId":216482,"corporation":false,"usgs":false,"family":"Fotheringham","given":"A.","email":"","middleInitial":"Stewart","affiliations":[{"id":6607,"text":"Arizona State University","active":true,"usgs":false}],"preferred":false,"id":764836,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Franklin, Janet","contributorId":197972,"corporation":false,"usgs":false,"family":"Franklin","given":"Janet","email":"","affiliations":[],"preferred":false,"id":764837,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Esque, Todd 0000-0002-4166-6234 tesque@usgs.gov","orcid":"https://orcid.org/0000-0002-4166-6234","contributorId":195896,"corporation":false,"usgs":true,"family":"Esque","given":"Todd","email":"tesque@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":764834,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Edwards, Taylor","contributorId":210006,"corporation":false,"usgs":false,"family":"Edwards","given":"Taylor","email":"","affiliations":[{"id":38044,"text":"University of Arizona Genetics Core, 1657 E. Helen Street, Room 111, University of Arizona, Tucson, AZ 85721","active":true,"usgs":false}],"preferred":false,"id":764838,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Nussear, Kenneth","contributorId":194538,"corporation":false,"usgs":false,"family":"Nussear","given":"Kenneth","affiliations":[{"id":24618,"text":"Department of Geography, University of Nevada, Reno, Reno, NV","active":true,"usgs":false}],"preferred":false,"id":764839,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70228750,"text":"70228750 - 2019 - Long-term trajectories of fractional component change in the Northern Great Basin, USA","interactions":[],"lastModifiedDate":"2022-03-31T14:01:26.798217","indexId":"70228750","displayToPublicDate":"2019-06-03T11:22:39","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Long-term trajectories of fractional component change in the Northern Great Basin, USA","docAbstract":"The need to monitor change in sagebrush steppe is urgent due to the increasing impacts of climate change, shifting fire regimes, and management practices on ecosystem health. Remote sensing provides a cost effective and reliable method for monitoring change through time and attributing changes to drivers. We report an automated method of mapping rangeland fractional component cover over a large portion of the northern Great Basin from 1986 to 2016 using a dense Landsat imagery time-series. Our method improved upon the traditional change vector method by considering the legacy of change at each pixel. We evaluate cover trends stratified by climate bin and assess spatial and temporal relationships with climate variables. Finally, we statistically evaluate the minimum time density needed to accurately characterize temporal patterns and relationships with climate drivers. Over the 30-year period shrub cover declined and bare ground increased. While few pixels had > 10% cover change, a large majority had at least some change. All fractional components had significant spatial relationships with water year precipitation (WYPRCP), maximum temperature (WYTMAX), and minimum temperature (WYTMIN) in all years. Shrub and sagebrush cover in particular respond positively to warming WYTMIN, resulting from the largest increases in WYTMIN being in the coolest and wettest areas, and negatively to warming WYTMAX since the largest increases in WYTMAX are in the warmest and driest areas. The trade-off of lowering temporal density against removing cloud-contaminated years is justified as temporal density appears to have only a modest impact on trends and climate relationships until n ≤ 6, but multi-year gaps are proportionally more influential. Gradual change analysis is likely to be less sensitive to n than abrupt change. These data can be used to answer critical questions regarding the influence of climate change and the suitability of management practices.","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.2762","usgsCitation":"Rigge, M.B., Shi, H., Homer, C., Danielson, P., and Granneman, B.J., 2019, Long-term trajectories of fractional component change in the Northern Great Basin, USA: Ecosphere, v. 10, no. 6, e02762, 24 p., https://doi.org/10.1002/ecs2.2762.","productDescription":"e02762, 24 p.","ipdsId":"IP-102771","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":460369,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.2762","text":"Publisher Index Page"},{"id":396119,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":396132,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9C9O66W","text":"USGS data release","description":"USGS data release","linkHelpText":"Remote Sensing Shrub/Grass National Land Cover Database (NLCD) Back-in-Time (BIT) Products for the Western U.S., 1985 - 2018"}],"country":"United States","state":"California, Idaho, Nevada, Oregon, Utah","otherGeospatial":"Northern Great Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.56347656249999,\n 42.032974332441405\n ],\n [\n -118.16894531249999,\n 35.35321610123823\n ],\n [\n -112.2802734375,\n 34.59704151614417\n ],\n [\n -109.248046875,\n 38.37611542403604\n ],\n [\n -110.0830078125,\n 43.13306116240612\n ],\n [\n -112.8955078125,\n 44.02442151965934\n ],\n [\n -115.6201171875,\n 43.58039085560784\n ],\n [\n -119.35546875000001,\n 44.15068115978094\n ],\n [\n -121.025390625,\n 44.08758502824516\n ],\n [\n -122.56347656249999,\n 42.032974332441405\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"10","issue":"6","noUsgsAuthors":false,"publicationDate":"2019-06-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Rigge, Matthew B. 0000-0003-4471-8009 mrigge@usgs.gov","orcid":"https://orcid.org/0000-0003-4471-8009","contributorId":751,"corporation":false,"usgs":true,"family":"Rigge","given":"Matthew","email":"mrigge@usgs.gov","middleInitial":"B.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":835302,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Shi, Hua 0000-0001-7013-1565 hshi@usgs.gov","orcid":"https://orcid.org/0000-0001-7013-1565","contributorId":646,"corporation":false,"usgs":true,"family":"Shi","given":"Hua","email":"hshi@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":835303,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Homer, Collin 0000-0003-4755-8135","orcid":"https://orcid.org/0000-0003-4755-8135","contributorId":238918,"corporation":false,"usgs":true,"family":"Homer","given":"Collin","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":835304,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Danielson, Patrick 0000-0002-2990-2783 pdanielson@usgs.gov","orcid":"https://orcid.org/0000-0002-2990-2783","contributorId":3551,"corporation":false,"usgs":true,"family":"Danielson","given":"Patrick","email":"pdanielson@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":835305,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Granneman, Brian J. 0000-0002-1910-0955","orcid":"https://orcid.org/0000-0002-1910-0955","contributorId":273180,"corporation":false,"usgs":true,"family":"Granneman","given":"Brian","email":"","middleInitial":"J.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":835306,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70203701,"text":"70203701 - 2019 - An ANCOVA model for porosity and its uncertainty for oil reservoirs based on TORIS dataset","interactions":[],"lastModifiedDate":"2019-06-05T14:24:57","indexId":"70203701","displayToPublicDate":"2019-06-02T14:23:53","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2419,"text":"Journal of Petroleum Science and Engineering","active":true,"publicationSubtype":{"id":10}},"title":"An ANCOVA model for porosity and its uncertainty for oil reservoirs based on TORIS dataset","docAbstract":"Porosity is one of the most important parameters to assess in-place oil or gas in reservoirs, and to evaluate recovery from enhanced production operations. Since it is relatively well-established to determine porosity using different laboratory and field methods, its value is usually determined at many locations across a reservoir as part of the common practice to capture reservoir heterogeneity and the variability in values. This suite of measurements and the distribution of values are most valuable for probabilistic reservoir assessments, and for spatial modeling if the exact data locations are known.
Despite the importance of individual measurements to set the range of values for probabilistic studies, it is not always possible to access these data due to confidentiality. In most cases, commercial or publicly available databases that assessments may rely on usually report only mean values of porosity, like any other reservoir data, or they may not report a value at all. This makes both quantifying the mean value and the uncertainty around it difficult for probabilistic assessments.
In this study, the TORIS (Tertiary Oil Recovery Information System) dataset of the National Petroleum Council and the U.S. Department of Energy was used to model porosity and the uncertainty around predicted values. TORIS is an integrated dataset of production data, reservoir properties, and project databases of crude oil reservoirs in the United States. The model presented in the paper was based on ANCOVA (Analysis of Co-Variance) of data from 1038 reservoirs from the TORIS dataset for porosity prediction, validation and testing for quantitative and qualitative parameters that may be readily available in most cases, and to estimate uncertainty around the mean values. This model also explored association of porosity values to different parameters, and to different depositional systems and diagenetic overprint conditions. Furthermore, an ANN (Artificial Neural Network) model was created to compare the predicted values of both models. Results showed that the ANN model was able to represent more of the variability, however it lacked the insights that might be gained from the ANCOVA model.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.petrol.2019.05.071","usgsCitation":"Karacan, C.O., 2019, An ANCOVA model for porosity and its uncertainty for oil reservoirs based on TORIS dataset: Journal of Petroleum Science and Engineering, 24 p., https://doi.org/10.1016/j.petrol.2019.05.071.","productDescription":"24 p.","ipdsId":"IP-103341","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":364378,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":364371,"type":{"id":15,"text":"Index Page"},"url":"https://www.sciencedirect.com/science/article/pii/S092041051930525X"}],"publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Karacan, C. Ozgen 0000-0002-0947-8241","orcid":"https://orcid.org/0000-0002-0947-8241","contributorId":201991,"corporation":false,"usgs":true,"family":"Karacan","given":"C.","email":"","middleInitial":"Ozgen","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":763708,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70203898,"text":"70203898 - 2019 - Ecological effects of fear: How spatiotemporal heterogeneity in predation risk influences mule deer access to forage in a sky‐island system","interactions":[],"lastModifiedDate":"2019-08-15T12:27:26","indexId":"70203898","displayToPublicDate":"2019-06-02T10:49:14","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Ecological effects of fear: How spatiotemporal heterogeneity in predation risk influences mule deer access to forage in a sky‐island system","docAbstract":"Forage availability and predation risk interact to affect habitat use of ungulates across many biomes. Within sky‐island habitats of the Mojave Desert, increased availability of diverse forage and cover may provide ungulates with unique opportunities to extend nutrient uptake and/or to mitigate predation risk. We addressed whether habitat use and foraging patterns of female mule deer (Odocoileus hemionus) responded to normalized difference vegetation index (NDVI), NDVI rate of change (green‐up), or the occurrence of cougars (Puma concolor). Female mule deer used available green‐up primarily in spring, although growing vegetation was available during other seasons. Mule deer and cougar shared similar habitat all year, and our models indicated cougars had a consistent, negative effect on mule deer access to growing vegetation, particularly in summer when cougar occurrence became concentrated at higher elevations. A seemingly late parturition date coincided with diminishing NDVI during the lactation period. Sky‐island populations, rarely studied, provide the opportunity to determine how mule deer respond to growing foliage along steep elevation and vegetation gradients when trapped with their predators and seasonally limited by aridity. Our findings indicate that fear of predation may restrict access to the forage resources found in sky islands.
","language":"English","publisher":"John Wiley & Sons Ltd","doi":"10.1002/ece3.5291","usgsCitation":"Lowrey, C., Longshore, K., Choate, D.M., Nagol, J.R., Sexton, J.O., and Thompson, D.B., 2019, Ecological effects of fear: How spatiotemporal heterogeneity in predation risk influences mule deer access to forage in a sky‐island system: Ecology and Evolution, v. 9, no. 12, p. 7213-7226, https://doi.org/10.1002/ece3.5291.","productDescription":"14 p.","startPage":"7213","endPage":"7226","ipdsId":"IP-081659","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":467566,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.5291","text":"Publisher Index Page"},{"id":437434,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9CC5E8P","text":"USGS data release","linkHelpText":"Environmental covariates at Mule deer locations within the Desert National Wildlife Refuge, Nevada, 2012-2014"},{"id":364832,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nevada","otherGeospatial":"Desert National Wildlife Refuge","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -115.894775390625,\n 37.19314268101434\n ],\n [\n -115.9002685546875,\n 36.600094165941144\n ],\n [\n -115.6036376953125,\n 36.595684037179055\n ],\n [\n -115.59814453125001,\n 36.569217971443635\n ],\n [\n -115.49652099609375,\n 36.569217971443635\n ],\n [\n -115.48828125000001,\n 36.53391577198655\n ],\n [\n -115.4443359375,\n 36.53612263184686\n ],\n [\n -115.43609619140624,\n 36.507428541837264\n ],\n [\n -115.42236328124999,\n 36.50522086338427\n ],\n [\n -115.42236328124999,\n 36.48755716938576\n ],\n [\n -115.39764404296875,\n 36.511843709862454\n ],\n [\n -115.4608154296875,\n 36.58024660149866\n ],\n [\n -115.3839111328125,\n 36.586863023441836\n ],\n [\n -115.38665771484375,\n 36.681636065615216\n ],\n [\n -115.29602050781249,\n 36.686041276581925\n ],\n [\n -115.3070068359375,\n 37.201893907733826\n ],\n [\n -115.73547363281249,\n 37.204081555898526\n ],\n [\n -115.73547363281249,\n 37.19314268101434\n ],\n [\n -115.894775390625,\n 37.19314268101434\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"9","issue":"12","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2019-06-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Lowrey, Chris 0000-0001-5084-7275","orcid":"https://orcid.org/0000-0001-5084-7275","contributorId":216375,"corporation":false,"usgs":true,"family":"Lowrey","given":"Chris","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":764640,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Longshore, Kathleen 0000-0001-6621-1271","orcid":"https://orcid.org/0000-0001-6621-1271","contributorId":216374,"corporation":false,"usgs":true,"family":"Longshore","given":"Kathleen","email":"","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":764639,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Choate, David M.","contributorId":207778,"corporation":false,"usgs":false,"family":"Choate","given":"David","email":"","middleInitial":"M.","affiliations":[{"id":37455,"text":"University of Nevada","active":true,"usgs":false}],"preferred":false,"id":764641,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Nagol, Jyoteshwar R","contributorId":216376,"corporation":false,"usgs":false,"family":"Nagol","given":"Jyoteshwar","email":"","middleInitial":"R","affiliations":[{"id":7083,"text":"University of Maryland","active":true,"usgs":false}],"preferred":false,"id":764642,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sexton, Joseph O.","contributorId":191918,"corporation":false,"usgs":false,"family":"Sexton","given":"Joseph","email":"","middleInitial":"O.","affiliations":[],"preferred":false,"id":764643,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Thompson, Daniel B.","contributorId":193518,"corporation":false,"usgs":false,"family":"Thompson","given":"Daniel","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":764644,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70204164,"text":"70204164 - 2019 - Migration triggers in a large herbivore: Galapagos giant tortoises navigating resources gradients on volcanoes","interactions":[],"lastModifiedDate":"2019-07-10T09:10:00","indexId":"70204164","displayToPublicDate":"2019-06-01T14:46:10","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1465,"text":"Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Migration triggers in a large herbivore: Galapagos giant tortoises navigating resources gradients on volcanoes","docAbstract":"To understand how migratory behavior evolved and to predict the future of migratory species in the face of global environmental change it is important to quantify intra- and inter-individual variation in migratory behavior. Intra-individual variation includes behavioral response to changing environmental conditions and hence behavioral plasticity in the context of novel conditions. Inter-individual variation determines the degree of variation on which selection can act and the rate of evolutionary response to changes in average and extreme environmental conditions. Here we focus on variation in the partial migratory behavior of Galapagos giant tortoises (Chelonoidis spp.), which exhibit high fidelity to migratory routes over many years. We evaluate the extent and mechanisms by which tortoises adjust migration timing in response to varying annual environmental conditions, integrating movement data within a bioenergetic model of tortoise migration to quantify the fitness consequences of migration timing. We find strong inter-individual variation in the timing of migration, which was not affected by environmental conditions prevailing at the time of migration but rather by marginal expectations estimated from multi-annual averaged conditions, leading to an average annual loss in efficiency of ~15% relative to optimal timing based on year-specific conditions. These results point towards a limited ability of tortoises to adjust the timing of their migrations based on prevailing (and, by extension, future) conditions, suggesting that the adaptability of tortoise migratory behavior to changing conditions is predicated more on past “normal” conditions than responsive to current, changing conditions. Our work offers insights into the level of environmental-tuning in migratory behavior and a general framework for future research across taxa.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecy.2658","usgsCitation":"Bastille-Rousseau, G., Yackulic, C.B., Gibbs, J.P., Friar, J.L., Cabrera, F., and Blake, S., 2019, Migration triggers in a large herbivore: Galapagos giant tortoises navigating resources gradients on volcanoes: Ecology, v. 100, no. 6, e02658; 11 p., https://doi.org/10.1002/ecy.2658.","productDescription":"e02658; 11 p.","ipdsId":"IP-100540","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":365396,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Ecuador","otherGeospatial":"Galapagos Islands","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -91.7578125,\n -0.4833927027896987\n ],\n [\n -91.571044921875,\n -0.9447814006873896\n ],\n [\n -90.582275390625,\n -1.345701455472609\n ],\n [\n -89.5660400390625,\n -1.4720060101903352\n ],\n [\n -89.2034912109375,\n -0.7195855745039547\n ],\n [\n -89.9285888671875,\n 0.4394488164139768\n ],\n [\n -90.8734130859375,\n 0.6591651462894632\n ],\n [\n -91.64794921875,\n 0.10986321392741416\n ],\n [\n -91.7578125,\n -0.4833927027896987\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"100","issue":"6","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2019-04-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Bastille-Rousseau, Guillaume 0000-0001-6799-639X","orcid":"https://orcid.org/0000-0001-6799-639X","contributorId":190877,"corporation":false,"usgs":false,"family":"Bastille-Rousseau","given":"Guillaume","email":"","affiliations":[{"id":40724,"text":"Cooperative Wildlife Research Laboratory and Department of Forestry, Southern Illinois University, 251 Life Science II, Mail Code 6504, Carbondale, Illinois 62901 USA","active":true,"usgs":false}],"preferred":false,"id":765767,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Yackulic, Charles B. 0000-0001-9661-0724 cyackulic@usgs.gov","orcid":"https://orcid.org/0000-0001-9661-0724","contributorId":4662,"corporation":false,"usgs":true,"family":"Yackulic","given":"Charles","email":"cyackulic@usgs.gov","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":765766,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gibbs, James P.","contributorId":102418,"corporation":false,"usgs":false,"family":"Gibbs","given":"James","email":"","middleInitial":"P.","affiliations":[{"id":12623,"text":"State University of New York College of Environmental Science and Forestry","active":true,"usgs":false}],"preferred":false,"id":765768,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Friar, Jacqueline L.","contributorId":216849,"corporation":false,"usgs":false,"family":"Friar","given":"Jacqueline","email":"","middleInitial":"L.","affiliations":[{"id":39531,"text":"Dept of Environmental and Forest Biology, State Univ of New York, College of Environmental Science and Forestry, Syracuse, NY, 13210; Roosevelt Wild Life Station, State Univ of New York, College of Environmental Science and Forestry, Syracuse, NY, 13210","active":true,"usgs":false}],"preferred":false,"id":765769,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cabrera, Freddy","contributorId":174102,"corporation":false,"usgs":false,"family":"Cabrera","given":"Freddy","email":"","affiliations":[],"preferred":false,"id":765770,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Blake, Stephen","contributorId":65339,"corporation":false,"usgs":false,"family":"Blake","given":"Stephen","email":"","affiliations":[{"id":30787,"text":"Saint Louis University","active":true,"usgs":false},{"id":12472,"text":"Max Planck Institute for Ornithology","active":true,"usgs":false}],"preferred":false,"id":765771,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70204255,"text":"70204255 - 2019 - Application of sediment end-member analysis for understanding sediment fluxes, northern Chandeleur Islands, Louisiana","interactions":[],"lastModifiedDate":"2019-07-16T14:41:07","indexId":"70204255","displayToPublicDate":"2019-06-01T14:32:32","publicationYear":"2019","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"title":"Application of sediment end-member analysis for understanding sediment fluxes, northern Chandeleur Islands, Louisiana","docAbstract":"We analyzed grain-size distributions (GSDs) from a time-series of sediment samples to evaluate sediment transport following anthropogenic sand-berm emplacement at the northern Chandeleur Islands, Louisiana. End-member analysis (EMA) was applied to compare the end-member (EM) GSD of a known sediment source to GSDs from surrounding environments and characterize the physical redistribution of source sediment over time. Although we successfully modeled a proxy borrow-source EM using pre-emplacement (2007-2008) datasets, this EM is not easily distinguishable from the modeled emergent-island EM, possibly because the baseline dataset did not provide the necessary sample distribution to distinguish the range of depositional environments. Comparison of post-emplacement (2012) samples from the berm and natural island with the proxy borrow-source EM suggests that this application of EMA can be a valuable tool for understanding sediment redistribution subsequent to restoration efforts, especially if the GSDs of the emplaced and naturally-occurring sediments are dissimilar and adequately sampled.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Coastal Sediments 2019—Proceedings of the 9th International Conference","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"Coastal Sediments 2019 ","conferenceDate":"May 27-31, 2019","conferenceLocation":"Tampa/St. Petersburg, Florida","language":"English","publisher":"World Scientific Co. Pte. Ltd.","doi":"10.1142/9789811204487_0003","usgsCitation":"Bernier, J., Miselis, J.L., Buster, N.A., and Flocks, J.G., 2019, Application of sediment end-member analysis for understanding sediment fluxes, northern Chandeleur Islands, Louisiana, in Coastal Sediments 2019—Proceedings of the 9th International Conference, Tampa/St. Petersburg, Florida, May 27-31, 2019, p. 25-38, https://doi.org/10.1142/9789811204487_0003.","productDescription":"14 p.","startPage":"25","endPage":"38","ipdsId":"IP-105796","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":365627,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Louisiana","otherGeospatial":"Northern Chandeleur Islands","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -89.0277099609375,\n 29.58540020340835\n ],\n [\n -88.77777099609375,\n 29.58540020340835\n ],\n [\n -88.77777099609375,\n 30.063151406016434\n ],\n [\n -89.0277099609375,\n 30.063151406016434\n ],\n [\n -89.0277099609375,\n 29.58540020340835\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Bernier, Julie 0000-0002-9918-5353 jbernier@usgs.gov","orcid":"https://orcid.org/0000-0002-9918-5353","contributorId":3549,"corporation":false,"usgs":true,"family":"Bernier","given":"Julie","email":"jbernier@usgs.gov","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":766198,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Miselis, Jennifer L. 0000-0002-4925-3979 jmiselis@usgs.gov","orcid":"https://orcid.org/0000-0002-4925-3979","contributorId":3914,"corporation":false,"usgs":true,"family":"Miselis","given":"Jennifer","email":"jmiselis@usgs.gov","middleInitial":"L.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":766199,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Buster, Noreen A. 0000-0001-5069-9284 nbuster@usgs.gov","orcid":"https://orcid.org/0000-0001-5069-9284","contributorId":3750,"corporation":false,"usgs":true,"family":"Buster","given":"Noreen","email":"nbuster@usgs.gov","middleInitial":"A.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":766200,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Flocks, James G. 0000-0002-6177-7433 jflocks@usgs.gov","orcid":"https://orcid.org/0000-0002-6177-7433","contributorId":816,"corporation":false,"usgs":true,"family":"Flocks","given":"James","email":"jflocks@usgs.gov","middleInitial":"G.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":766201,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70204585,"text":"70204585 - 2019 - Ground-motion residuals, path effects, and crustal properties: A pilot study in southern California","interactions":[],"lastModifiedDate":"2019-08-07T09:05:26","indexId":"70204585","displayToPublicDate":"2019-06-01T11:55:39","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2314,"text":"Journal of Geophysical Research B: Solid Earth","active":true,"publicationSubtype":{"id":10}},"title":"Ground-motion residuals, path effects, and crustal properties: A pilot study in southern California","docAbstract":"To improve models of ground motion estimation and probabilistic seismic hazard analyses, the engineering seismology field is moving toward developing fully nonergodic ground motion models, models specific for individual source‐to‐site paths. Previous work on this topic has examined systematic variations in ground‐motion along particular paths (from either recorded or simulated earthquake data) and has not included physical properties of the path. We present here a framework to include physical path properties, by seeking correlations between ground motion amplitudes along specific paths and crustal properties, specifically seismic velocity and anelastic attenuation, along that path. Using a large data set of small‐magnitude earthquakes recorded in Southern California, we find a correlation between the gradient of seismic S wave velocity and the path term residual, after accounting for an average geometric spreading and anelastic attenuation, indicating that heterogeneity in crustal velocity primarily controls the path‐specific attenuation. Even in aseismic regions, details of path‐specific ground motion prediction equations can be developed from crustal structure and property data.","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2018JB016796","usgsCitation":"Sahakian, V., Baltay Sundstrom, A.S., Hanks, T.C., Bueler, J., Vernon, F., Kilb, D.L., and Abrahamson, N., 2019, Ground-motion residuals, path effects, and crustal properties: A pilot study in southern California: Journal of Geophysical Research B: Solid Earth, v. 124, no. 6, p. 5738-5753, https://doi.org/10.1029/2018JB016796.","productDescription":"16 p.","startPage":"5738","endPage":"5753","ipdsId":"IP-101300","costCenters":[{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":366300,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.67333984374999,\n 32.45415593941475\n ],\n [\n -114.3017578125,\n 32.45415593941475\n ],\n [\n -114.3017578125,\n 37.23032838760387\n ],\n [\n -122.67333984374999,\n 37.23032838760387\n ],\n [\n -122.67333984374999,\n 32.45415593941475\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"124","issue":"6","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2019-06-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Sahakian, Valerie J.","contributorId":208097,"corporation":false,"usgs":false,"family":"Sahakian","given":"Valerie J.","affiliations":[{"id":6604,"text":"University of Oregon","active":true,"usgs":false}],"preferred":false,"id":767639,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Baltay, Annemarie S. 0000-0002-6514-852X abaltay@usgs.gov","orcid":"https://orcid.org/0000-0002-6514-852X","contributorId":4932,"corporation":false,"usgs":true,"family":"Baltay","given":"Annemarie","email":"abaltay@usgs.gov","middleInitial":"S.","affiliations":[{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":767638,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hanks, Thomas C. 0000-0003-0928-0056 thanks@usgs.gov","orcid":"https://orcid.org/0000-0003-0928-0056","contributorId":3065,"corporation":false,"usgs":true,"family":"Hanks","given":"Thomas","email":"thanks@usgs.gov","middleInitial":"C.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":767640,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bueler, Janine","contributorId":217838,"corporation":false,"usgs":false,"family":"Bueler","given":"Janine","email":"","affiliations":[{"id":27208,"text":"UC San Diego","active":true,"usgs":false}],"preferred":false,"id":767641,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Vernon, Frank","contributorId":217839,"corporation":false,"usgs":false,"family":"Vernon","given":"Frank","affiliations":[{"id":27208,"text":"UC San Diego","active":true,"usgs":false}],"preferred":false,"id":767642,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kilb, Deborah L.","contributorId":216380,"corporation":false,"usgs":false,"family":"Kilb","given":"Deborah","email":"","middleInitial":"L.","affiliations":[{"id":37799,"text":"SCRIPPS","active":true,"usgs":false}],"preferred":false,"id":767643,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Abrahamson, Norm A.","contributorId":217840,"corporation":false,"usgs":false,"family":"Abrahamson","given":"Norm A.","affiliations":[{"id":6609,"text":"UC Berkeley","active":true,"usgs":false}],"preferred":false,"id":767644,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70216096,"text":"70216096 - 2019 - Estimating connectivity of hard clam (Mercenaria mercenaria) and eastern oyster (Crassostrea virginica) larvae in Barnegat Bay","interactions":[],"lastModifiedDate":"2020-11-04T16:44:24.630283","indexId":"70216096","displayToPublicDate":"2019-06-01T10:39:03","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1584,"text":"Estuaries and Coasts","active":true,"publicationSubtype":{"id":10}},"title":"Estimating connectivity of hard clam (Mercenaria mercenaria) and eastern oyster (Crassostrea virginica) larvae in Barnegat Bay","docAbstract":"Hazard analysis at caldera volcanoes is challenging due to the wide range of eruptive and environmental conditions that can plausibly occur during renewed activity. Taupo volcano, New Zealand, is a frequently active and productive rhyolitic caldera volcano that has hosted the world's youngest known supereruption and numerous smaller explosive events. To assess ashfall hazard from future eruptions, we have simulated atmospheric ash dispersal using the Ash3d model. We consider five eruption scenarios spanning magma volumes of 0.1–500 km3 and investigate the main factors governing ash dispersal in modern atmospheric conditions. Our results are examined in the context of regional synoptic weather patterns (Kidson types) that provide a framework for assessing the variability of ashfall distribution in different wind fields. For the smallest eruptions (~0.1‐km3 magma), ashfall thicknesses >1 cm are largely confined to the central North Island, with dispersal controlled by day‐to‐day weather and the dominance of westerly winds. With increasing eruptive volume (1–5‐km3 magma), ashfall thicknesses >1 cm would likely reach major population centers throughout the North Island. Dispersal is less dependent on weather patterns as the formation of a radially expanding umbrella cloud forces ash upwind or crosswind, although strong stratospheric winds significantly restrict umbrella spreading. For large eruptions (50–500‐km3 magma), powerful expansion of the umbrella cloud results in widespread ashfall at damaging thicknesses (>10 cm) across most of the North Island and top of the South Island. Synoptic climatology may prove a useful additional technique for long‐term hazard planning at caldera volcanoes.
Although development and urbanization are typically believed to have negative impacts on carnivoran species, some species can successfully navigate an urban matrix. Sympatric carnivorans compete for limited resources in urban areas, likely with system-specific impacts to their distributions and activity patterns. We used automatically triggered wildlife cameras to assess the local distribution and co-existence of Canis latrans (Coyote), Vulpes vulpes (Red Fox), and Urocyon cinereoargenteus (Gray Fox) across the Pioneer Valley, MA, in relation to different levels of human development. We placed cameras at 79 locations in forested, altered, and urban land-use areas from September to November 2012 and accumulated 1670 trap nights. We determined site characteristics and detection rates for 12 other wildlife species for each camera location to develop a generalized linear model for the local distribution of each focal canid species across the study area. We also compared diel activity patterns among Coyotes, Red Foxes, and Gray Foxes, and calculated coefficients of overlap between each pair. The local distribution of Coyotes was positively associated with the detection rates of their prey and not associated with detection rates of sympatric carnivoran species. Red Foxes and Gray Foxes had negative relationships with the detection rate of Coyotes, and none of the 3 canid species showed a positive correlation with increased levels of urbanization. There was a high degree of temporal overlap in diel activity patterns and limited spatial overlap of our focal species, which suggests that any competition avoidance across our study area occurred at the spatial level. Coyotes fill the role of top predator in the Pioneer Valley, and likely have a negative impact on the local distributions of smaller canids, while their own local distributions seem to be driven by prey availability.
","language":"English","publisher":"Eagle Hill Institute","doi":"10.1656/045.026.0208","usgsCitation":"LeFlore, E.G., Fuller, T.K., Finn, J.T., Organ, J.F., and DeStefano, S., 2019, Wild canid distribution and co-existence in a natural–urban matrix of the Pioneer Valley of Western Massachusetts: Northeastern Naturalist, v. 26, no. 2, p. 325-342, https://doi.org/10.1656/045.026.0208.","productDescription":"18 p.","startPage":"325","endPage":"342","ipdsId":"IP-070732","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":364399,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Massachesetts","county":"Franklin County, Hampshire County","otherGeospatial":"Pioneer Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -72.58255004882812,\n 42.30067461858169\n ],\n [\n -72.38616943359375,\n 42.30067461858169\n ],\n [\n -72.38616943359375,\n 42.50551526821832\n ],\n [\n -72.58255004882812,\n 42.50551526821832\n ],\n [\n -72.58255004882812,\n 42.30067461858169\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"26","issue":"2","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"LeFlore, Eric G.","contributorId":216045,"corporation":false,"usgs":false,"family":"LeFlore","given":"Eric","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":763749,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fuller, Todd K.","contributorId":216046,"corporation":false,"usgs":true,"family":"Fuller","given":"Todd","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":763750,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Finn, John T.","contributorId":43398,"corporation":false,"usgs":false,"family":"Finn","given":"John","email":"","middleInitial":"T.","affiliations":[{"id":16720,"text":"Department of Environmental Conservation, University of Massachusetts, Amherst, MA 01003-9485, USA","active":true,"usgs":false}],"preferred":false,"id":763751,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Organ, John F. 0000-0002-0959-0639 jorgan@usgs.gov","orcid":"https://orcid.org/0000-0002-0959-0639","contributorId":189047,"corporation":false,"usgs":true,"family":"Organ","given":"John","email":"jorgan@usgs.gov","middleInitial":"F.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":763432,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"DeStefano, Stephen 0000-0003-2472-8373 destef@usgs.gov","orcid":"https://orcid.org/0000-0003-2472-8373","contributorId":166706,"corporation":false,"usgs":true,"family":"DeStefano","given":"Stephen","email":"destef@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":false,"id":763433,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70203690,"text":"70203690 - 2019 - Surrogate model development for coastal dune erosion under storm conditions","interactions":[],"lastModifiedDate":"2019-06-21T15:33:04","indexId":"70203690","displayToPublicDate":"2019-05-31T15:27:38","publicationYear":"2019","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Surrogate model development for coastal dune erosion under storm conditions","docAbstract":"Early coastal dune erosion predictions are essential to avoid potential flood consequences but most dune erosion numerical models are computationally expensive, hence their application in Early Warning Systems is limited. Here, based on a combination of optimally sampled synthetic sea storms with a calibrated and validated XBeach model, we develop a surrogate model capable of producing fast and accurate dune erosion predictions under storm conditions when water level and wave forecasts are available. The analysis is performed on Dauphin Island, AL, where we train Multiple Linear Regression Models with oceanographic forcing from the selected sea storms (i.e., XBeach input) and predicted changes in the dune system (i.e., XBeach output). Surrogate model performance is assessed with a rigorous k-fold cross validation. 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(2004) and by Rosenberg and Blancher (2005) and most recently refined by Stanton et al. (2019). The Handbook also provides details about how the estimates were derived, information on limitations and caveats, a guide to using the estimates, and future desired directions for improving the estimates.\n\nThis version of the database is intended as a companion to the Partners in Flight Landbird Conservation Plan: 2016 Revision for Canada and Continental United States (Rosenberg et al. 2016), although estimates for most species included in the database have been updated from those used in the 2016 Plan. Most of the estimates in the database are based on North American Breeding Bird Survey (BBS) data for landbirds from the decade 2006–2015. The information in this 2019 Version of the Handbook, for Version 3.0 of the database, describes all changes that have been made to the database since 2007 (Version 1.0, cf. Blancher et al. 2007)—including the additions documented in the Handbook for Version 2.0 (Blancher et al. 2013)—and therefore serves as a single source document describing the current database.\n\nVersion 3.0 of the database addresses some of the recommendations suggested by Thogmartin et al. (2006) but does not yet fully address other limitations noted by Thogmartin et al. (2006), Blancher et al. (2007), Thogmartin (2010), Matsuoka et al. (2012), and Twedt (2015). By far, the most substantial change to the database comprises the incorporation of quantitative uncertainty bounds around population estimates for most species (see Stanton et al. 2019 for details). PIF Science anticipates that future versions of the database will occur in stages: first, improving elements of the basic PIF approach (e.g., incorporating more recent BBS data, updating Time of Day Adjustments, and refining Pair Adjustments); next, addressing additional concerns inherent in the PIF approach (e.g., replacing average maximum detection distance bins with research-derived species-specific effective detection radii); and later, perhaps replacing the sample-based PIF approach with a spatially-explicit, model-based (pixel-based) approach that more deliberately incorporates habitat and road biases and the proportion of birds available but not detected by current sampling methodology.\n\nThis current Version 3.1 of the Handbook updates citations in the Literature Cited and incorporates relatively minor improvements in text clarity over the previous 3.0 version. The content of the Population Estimates Database itself remains the same except for changes to the global and USA/Canada estimates for Northern Bobwhite and Black Vulture.","language":"English","publisher":"Partners in Flight and Bird Conservancy of the Rockies","usgsCitation":"Will, T., Stanton, J.C., Rosenberg, K.V., Panjabi, A.O., Camfield, A., Shaw, A., Thogmartin, W.E., and Blancher, P.J., 2019, Handbook to the partners in flight population estimates database, version 3.0: Partners in Flight Technical Publication 7, 38 p.","productDescription":"38 p.","ipdsId":"IP-106689","costCenters":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":368039,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":368002,"type":{"id":15,"text":"Index Page"},"url":"https://pif.birdconservancy.org/PopEstimates/"}],"publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Will, Tom","contributorId":149777,"corporation":false,"usgs":false,"family":"Will","given":"Tom","email":"","affiliations":[{"id":17821,"text":"U.S. Fish and Wildlife Service, Division of Migratory Birds","active":true,"usgs":false}],"preferred":false,"id":772445,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stanton, Jessica C. 0000-0002-6225-3703 jcstanton@usgs.gov","orcid":"https://orcid.org/0000-0002-6225-3703","contributorId":5634,"corporation":false,"usgs":true,"family":"Stanton","given":"Jessica","email":"jcstanton@usgs.gov","middleInitial":"C.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":772444,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rosenberg, Kenneth V.","contributorId":171463,"corporation":false,"usgs":false,"family":"Rosenberg","given":"Kenneth","email":"","middleInitial":"V.","affiliations":[{"id":27615,"text":"Cornell Lab of Ornithology, Conservation Science Program","active":true,"usgs":false}],"preferred":false,"id":772446,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Panjabi, Arvind O.","contributorId":169967,"corporation":false,"usgs":false,"family":"Panjabi","given":"Arvind","email":"","middleInitial":"O.","affiliations":[{"id":25644,"text":"Bird Conservancy of the Rockies","active":true,"usgs":false}],"preferred":false,"id":772447,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Camfield, Alaine","contributorId":219517,"corporation":false,"usgs":false,"family":"Camfield","given":"Alaine","email":"","affiliations":[{"id":12590,"text":"Canadian Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":772448,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Shaw, Allison","contributorId":219518,"corporation":false,"usgs":false,"family":"Shaw","given":"Allison","email":"","affiliations":[{"id":25644,"text":"Bird Conservancy of the Rockies","active":true,"usgs":false}],"preferred":false,"id":772449,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Thogmartin, Wayne E. 0000-0002-2384-4279 wthogmartin@usgs.gov","orcid":"https://orcid.org/0000-0002-2384-4279","contributorId":2545,"corporation":false,"usgs":true,"family":"Thogmartin","given":"Wayne","email":"wthogmartin@usgs.gov","middleInitial":"E.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":772450,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Blancher, Peter J.","contributorId":175182,"corporation":false,"usgs":false,"family":"Blancher","given":"Peter","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":772451,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70205618,"text":"70205618 - 2019 - Using a GIS to populate 3D geocellular geologic models","interactions":[],"lastModifiedDate":"2019-09-27T11:25:58","indexId":"70205618","displayToPublicDate":"2019-05-31T11:25:48","publicationYear":"2019","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"title":"Using a GIS to populate 3D geocellular geologic models","docAbstract":"No abstract available
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Geologic Mapping Forum 2019 Abstracts","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"Geologic Mapping Forum","conferenceDate":"April 10-12, 2019","conferenceLocation":"Minneapolis, MN","language":"English","publisher":"Minnesota Geological Survey","usgsCitation":"Sweetkind, D., and Cromwell, G., 2019, Using a GIS to populate 3D geocellular geologic models, in Geologic Mapping Forum 2019 Abstracts, Minneapolis, MN, April 10-12, 2019, p. 86-87.","productDescription":"2 p.","startPage":"86","endPage":"87","ipdsId":"IP-105944","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":367779,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":367772,"type":{"id":15,"text":"Index Page"},"url":"https://hdl.handle.net/11299/202386"}],"publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Sweetkind, Donald S. 0000-0003-0892-4796","orcid":"https://orcid.org/0000-0003-0892-4796","contributorId":210808,"corporation":false,"usgs":true,"family":"Sweetkind","given":"Donald S.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":771884,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cromwell, Geoffrey 0000-0001-8481-405X gcromwell@usgs.gov","orcid":"https://orcid.org/0000-0001-8481-405X","contributorId":5920,"corporation":false,"usgs":true,"family":"Cromwell","given":"Geoffrey","email":"gcromwell@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":771885,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ]}