El Niño–Southern Oscillation (ENSO) events are accompanied by an anomalous zonal sea surface temperature (SST) gradient over the west Pacific Ocean, defined here as the west Pacific SST gradient (WPG). The WPG is defined as the standardized difference between area-averaged SST over the central Pacific Ocean (Niño-4 region) and west Pacific Ocean (0°–10°N, 130°–150°E). While the direction of the WPG follows ENSO cycles, the magnitude of the gradient varies considerably between individual El Niño and La Niña events. In this study, El Niño and La Niña events are grouped according to the magnitude of the WPG, and tropical SST, circulations, and precipitation are examined for the period 1948–2011. Until the 1980s the WPG showed little trend as the west and central Pacific warmed at similar rates; however, the west Pacific has recently warmed faster than the central Pacific, which has resulted in an increased WPG during La Niña events.
The temporal evolution and distribution of tropical Pacific SST as well as the near-surface tropical Pacific zonal wind, divergence, and vertical velocity are considerably different during ENSO events partitioned according to the strength of the WPG. Modifications to the tropical circulation, resulting in changes to Indo– west Pacific precipitation, are linked to strong and consistent circulation and precipitation modifications throughout the Northern Hemisphere during winter.
","language":"English","publisher":"American Meteorological Society","doi":"10.1175/JCLI-D-12-00344.1","usgsCitation":"Funk, C., and Hoell, A., 2013, The ENSO-related West Pacific Sea surface temperature gradient: Journal of Climate, v. 26, no. 23, p. 9545-9562, https://doi.org/10.1175/JCLI-D-12-00344.1.","productDescription":"18 p.","startPage":"9545","endPage":"9562","ipdsId":"IP-044717","costCenters":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"links":[{"id":473418,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1175/jcli-d-12-00344.1","text":"Publisher Index Page"},{"id":430807,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"26","issue":"23","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Funk, Chris 0000-0002-9254-6718 cfunk@usgs.gov","orcid":"https://orcid.org/0000-0002-9254-6718","contributorId":339957,"corporation":false,"usgs":true,"family":"Funk","given":"Chris","email":"cfunk@usgs.gov","affiliations":[],"preferred":true,"id":905706,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hoell, Andrew 0000-0001-9936-2527","orcid":"https://orcid.org/0000-0001-9936-2527","contributorId":339958,"corporation":false,"usgs":true,"family":"Hoell","given":"Andrew","email":"","affiliations":[{"id":81416,"text":"University of California Santa Barbara,","active":true,"usgs":false},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":905707,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70045121,"text":"70045121 - 2013 - Seismotectonic framework of the 2010 February 27 Mw 8.8 Maule, Chile earthquake sequence","interactions":[],"lastModifiedDate":"2014-01-13T11:55:16","indexId":"70045121","displayToPublicDate":"2013-12-01T10:41:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1803,"text":"Geophysical Journal International","active":true,"publicationSubtype":{"id":10}},"title":"Seismotectonic framework of the 2010 February 27 Mw 8.8 Maule, Chile earthquake sequence","docAbstract":"After the 2010 Mw 8.8 Maule earthquake, an international collaboration involving teams and instruments from Chile, the US, the UK, France and Germany established the International Maule Aftershock Deployment temporary network over the source region of the event to facilitate detailed, open-access studies of the aftershock sequence. Using data from the first 9-months of this deployment, we have analyzed the detailed spatial distribution of over 2500 well-recorded aftershocks. All earthquakes have been relocated using a hypocentral decomposition algorithm to study the details of and uncertainties in both their relative and absolute locations. We have computed regional moment tensor solutions for the largest of these events to produce a catalogue of 465 mechanisms, and have used all of these data to study the spatial distribution of the aftershock sequence with respect to the Chilean megathrust. We refine models of co-seismic slip distribution of the Maule earthquake, and show how small changes in fault geometries assumed in teleseismic finite fault modelling significantly improve fits to regional GPS data, implying that the accuracy of rapid teleseismic fault models can be substantially improved by consideration of existing fault geometry model databases. We interpret all of these data in an integrated seismotectonic framework for the Maule earthquake rupture and its aftershock sequence, and discuss the relationships between co-seismic rupture and aftershock distributions. While the majority of aftershocks are interplate thrust events located away from regions of maximum co-seismic slip, interesting clusters of aftershocks are identified in the lower plate at both ends of the main shock rupture, implying internal deformation of the slab in response to large slip on the plate boundary interface. We also perform Coulomb stress transfer calculations to compare aftershock locations and mechanisms to static stress changes following the Maule rupture. Without the incorporation of uncertainties in earthquake locations, just 55 per cent of aftershock nodal planes align with faults promoted towards failure by co-seismic slip. When epicentral uncertainties are considered (on the order of just ±2–3 km), 90 per cent of aftershocks are consistent with occurring along faults demonstrating positive stress transfer. These results imply large sensitivities of Coulomb stress transfer calculations to uncertainties in both earthquake locations and models of slip distributions, particularly when applied to aftershocks close to a heterogeneous fault rupture; such uncertainties should therefore be considered in similar studies used to argue for or against models of static stress triggering.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Geophysical Journal International","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Royal Astronomical Society","doi":"10.1093/gji/ggt238","usgsCitation":"Hayes, G., Bergman, E., Johnson, K.J., Benz, H.M., Brown, L., and Meltzer, A.S., 2013, Seismotectonic framework of the 2010 February 27 Mw 8.8 Maule, Chile earthquake sequence: Geophysical Journal International, v. 195, no. 2, p. 1034-1051, https://doi.org/10.1093/gji/ggt238.","productDescription":"18 p.","startPage":"1034","endPage":"1051","numberOfPages":"18","ipdsId":"IP-042222","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":280876,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":280875,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1093/gji/ggt238"}],"country":"Chile","city":"Maule","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -78.0,-40.0 ], [ -78.0,-30.0 ], [ -68.0,-30.0 ], [ -68.0,-40.0 ], [ -78.0,-40.0 ] ] ] } } ] }","volume":"195","issue":"2","noUsgsAuthors":false,"publicationDate":"2013-08-23","publicationStatus":"PW","scienceBaseUri":"53cd722ee4b0b29085108220","contributors":{"authors":[{"text":"Hayes, Gavin P. 0000-0003-3323-0112","orcid":"https://orcid.org/0000-0003-3323-0112","contributorId":6157,"corporation":false,"usgs":true,"family":"Hayes","given":"Gavin P.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":476864,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bergman, Eric","contributorId":28160,"corporation":false,"usgs":true,"family":"Bergman","given":"Eric","affiliations":[],"preferred":false,"id":476867,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Johnson, Kendra J.","contributorId":13526,"corporation":false,"usgs":true,"family":"Johnson","given":"Kendra","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":476865,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Benz, Harley M. 0000-0002-6860-2134 benz@usgs.gov","orcid":"https://orcid.org/0000-0002-6860-2134","contributorId":794,"corporation":false,"usgs":true,"family":"Benz","given":"Harley","email":"benz@usgs.gov","middleInitial":"M.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":476863,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Brown, Lucy","contributorId":26618,"corporation":false,"usgs":true,"family":"Brown","given":"Lucy","email":"","affiliations":[],"preferred":false,"id":476866,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Meltzer, Anne S.","contributorId":56719,"corporation":false,"usgs":true,"family":"Meltzer","given":"Anne","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":476868,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70136099,"text":"70136099 - 2013 - Choosing and using climate change scenarios for ecological-impact assessments and conservation decisions","interactions":[],"lastModifiedDate":"2014-12-23T10:23:58","indexId":"70136099","displayToPublicDate":"2013-12-01T10:30:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1321,"text":"Conservation Biology","active":true,"publicationSubtype":{"id":10}},"title":"Choosing and using climate change scenarios for ecological-impact assessments and conservation decisions","docAbstract":"Increased concern over climate change is demonstrated by the many efforts to assess climate effects and develop adaptation strategies. Scientists, resource managers, and decision makers are increasingly expected to use climate information, but they struggle with its uncertainty. With the current proliferation of climate simulations and downscaling methods, scientifically credible strategies for selecting a subset for analysis and decision making are needed. Drawing on a rich literature in climate science and impact assessment and on experience working with natural resource scientists and decision makers, we devised guidelines for choosing climate-change scenarios for ecological impact assessment that recognize irreducible uncertainty in climate projections and address common misconceptions about this uncertainty. This approach involves identifying primary local climate drivers by climate sensitivity of the biological system of interest; determining appropriate sources of information for future changes in those drivers; considering how well processes controlling local climate are spatially resolved; and selecting scenarios based on considering observed emission trends, relative importance of natural climate variability, and risk tolerance and time horizon of the associated decision. The most appropriate scenarios for a particular analysis will not necessarily be the most appropriate for another due to differences in local climate drivers, biophysical linkages to climate, decision characteristics, and how well a model simulates the climate parameters and processes of interest. Given these complexities, we recommend interaction among climate scientists, natural and physical scientists, and decision makers throughout the process of choosing and using climate-change scenarios for ecological impact assessment.
","language":"English","publisher":"Society for Conservation Biology","publisherLocation":"Malden, MA","doi":"10.1111/cobi.12163","collaboration":"University of Washington Climate Impacts Group; National Oceanographic and Atmospheric Administration Earth System Research Laboratory;National Oceanic and Atmospheric Administration, National Marine Fisheries Service, Northwest Fisheries Science Center;School of Marine and Atmospheric Sciences, Stony Brook University","usgsCitation":"Amy K. Snover, Mantua, N.J., Littell, J.S., Alexander, M.A., McClure, M.M., and Janet Nye, 2013, Choosing and using climate change scenarios for ecological-impact assessments and conservation decisions: Conservation Biology, v. 27, no. 6, p. 1147-1157, https://doi.org/10.1111/cobi.12163.","productDescription":"11 p.","startPage":"1147","endPage":"1157","numberOfPages":"11","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-042727","costCenters":[{"id":107,"text":"Alaska Climate Science Center","active":true,"usgs":true}],"links":[{"id":296859,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":296858,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://onlinelibrary.wiley.com/doi/10.1111/cobi.12163/abstract"}],"volume":"27","issue":"6","noUsgsAuthors":false,"publicationDate":"2013-12-02","publicationStatus":"PW","scienceBaseUri":"54dd2b5ae4b08de9379b3330","contributors":{"authors":[{"text":"Amy K. Snover","contributorId":131065,"corporation":false,"usgs":false,"family":"Amy K. Snover","affiliations":[{"id":7220,"text":"Climate Impacts Group, University of Washington, Box 355672, Sea","active":true,"usgs":false}],"preferred":false,"id":537134,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mantua, Nathan J.","contributorId":131069,"corporation":false,"usgs":false,"family":"Mantua","given":"Nathan","email":"","middleInitial":"J.","affiliations":[{"id":7220,"text":"Climate Impacts Group, University of Washington, Box 355672, Sea","active":true,"usgs":false}],"preferred":false,"id":537138,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Littell, Jeremy S. 0000-0002-5302-8280 jlittell@usgs.gov","orcid":"https://orcid.org/0000-0002-5302-8280","contributorId":4428,"corporation":false,"usgs":true,"family":"Littell","given":"Jeremy","email":"jlittell@usgs.gov","middleInitial":"S.","affiliations":[{"id":107,"text":"Alaska Climate Science Center","active":true,"usgs":true},{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true}],"preferred":true,"id":537133,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Alexander, Michael A.","contributorId":131067,"corporation":false,"usgs":false,"family":"Alexander","given":"Michael","email":"","middleInitial":"A.","affiliations":[{"id":7222,"text":"NOAA, Earth System Research Laboratory, R/PSD1, 325 Broadway, Bo","active":true,"usgs":false}],"preferred":false,"id":537136,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McClure, Michelle M.","contributorId":131068,"corporation":false,"usgs":false,"family":"McClure","given":"Michelle","email":"","middleInitial":"M.","affiliations":[{"id":7223,"text":"National Oceanic and Atmospheric Administration, National Marine","active":true,"usgs":false}],"preferred":false,"id":537137,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Janet Nye","contributorId":131066,"corporation":false,"usgs":false,"family":"Janet Nye","affiliations":[{"id":7221,"text":"School of Marine and Atmospheric Sciences, Stony Brook Universit","active":true,"usgs":false}],"preferred":false,"id":537135,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70093255,"text":"70093255 - 2013 - Bird-vegetation associations in thinned and unthinned young Douglas-fir forests 10 years after thinning","interactions":[],"lastModifiedDate":"2014-02-07T10:09:36","indexId":"70093255","displayToPublicDate":"2013-12-01T10:04:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1687,"text":"Forest Ecology and Management","active":true,"publicationSubtype":{"id":10}},"title":"Bird-vegetation associations in thinned and unthinned young Douglas-fir forests 10 years after thinning","docAbstract":"Quantitative associations between animals and vegetation have long been used as a basis for conservation and management, as well as in formulating predictions about the influence of resource management and climate change on populations. A fundamental assumption embedded in the use of such correlations is that they remain relatively consistent over time. However, this assumption of stationarity has been rarely tested – even for forest birds, which are frequently considered to be 'indicator species' in management operations. We investigated the temporal dynamics of bird-vegetation relationships in young Douglas-fir (Pseudotsuga menziesii) forests over more than a decade following initial anthropogenic disturbance (commercial thinning). We modeled bird occurrence or abundance as a function of vegetation characteristics for eight common bird species for each of six breeding seasons following forest thinning. Generally, vegetation relationships were highly inconsistent in magnitude across years, but remained positive or negative within species. For 3 species, relationships that were initially strong dampened over time. For other species, strength of vegetation association was apparently stochastic. These findings indicate that caution should be used when interpreting weak bird-vegetation relationships found in short-term studies and parameterizing predictive models with data collected over the short term.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Forest Ecology and Management","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.foreco.2013.06.052","usgsCitation":"Yegorova, S., Betts, M.G., Hagar, J., and Puettmann, K.J., 2013, Bird-vegetation associations in thinned and unthinned young Douglas-fir forests 10 years after thinning: Forest Ecology and Management, v. 310, p. 1057-1070, https://doi.org/10.1016/j.foreco.2013.06.052.","productDescription":"14 p.","startPage":"1057","endPage":"1070","numberOfPages":"14","ipdsId":"IP-046302","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":282061,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.foreco.2013.06.052"},{"id":282105,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon","otherGeospatial":"Oregon Cascade Mountains;Williamette National Forest","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -122.7449,43.356 ], [ -122.7449,44.9014 ], [ -121.768,44.9014 ], [ -121.768,43.356 ], [ -122.7449,43.356 ] ] ] } } ] }","volume":"310","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53cd4f90e4b0b290850f2c94","contributors":{"authors":[{"text":"Yegorova, Svetlana","contributorId":11505,"corporation":false,"usgs":true,"family":"Yegorova","given":"Svetlana","email":"","affiliations":[],"preferred":false,"id":489993,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Betts, Matthew G.","contributorId":27748,"corporation":false,"usgs":true,"family":"Betts","given":"Matthew","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":489994,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hagar, Joan 0000-0002-3044-6607 joan_hagar@usgs.gov","orcid":"https://orcid.org/0000-0002-3044-6607","contributorId":3369,"corporation":false,"usgs":true,"family":"Hagar","given":"Joan","email":"joan_hagar@usgs.gov","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":true,"id":489992,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Puettmann, Klaus J.","contributorId":36828,"corporation":false,"usgs":true,"family":"Puettmann","given":"Klaus","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":489995,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70132437,"text":"70132437 - 2013 - Roles of patch characteristics, drought frequency, and restoration in long-term trends of a widespread amphibian","interactions":[],"lastModifiedDate":"2020-12-23T14:42:11.34899","indexId":"70132437","displayToPublicDate":"2013-12-01T09:45:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1321,"text":"Conservation Biology","active":true,"publicationSubtype":{"id":10}},"title":"Roles of patch characteristics, drought frequency, and restoration in long-term trends of a widespread amphibian","docAbstract":"Despite the high profile of amphibian declines and the increasing threat of drought and fragmentation to aquatic ecosystems, few studies have examined long-term rates of change for a single species across a large geographic area. We analyzed growth in annual egg-mass counts of the Columbia spotted frog (Rana luteiventris) across the northwestern United States, an area encompassing 3 genetic clades. On the basis of data collected by multiple partners from 98 water bodies between 1991 and 2011, we used state-space and linear-regression models to measure effects of patch characteristics, frequency of summer drought, and wetland restoration on population growth. Abundance increased in the 2 clades with greatest decline history, but declined where populations are considered most secure. Population growth was negatively associated with temporary hydroperiods and landscape modification (measured by the human footprint index), but was similar in modified and natural water bodies. The effect of drought was mediated by the size of the water body: populations in large water bodies maintained positive growth despite drought, whereas drought magnified declines in small water bodies. Rapid growth in restored wetlands in areas of historical population declines provided strong evidence of successful management. Our results highlight the importance of maintaining large areas of habitat and underscore the greater vulnerability of small areas of habitat to environmental stochasticity. Similar long-term growth rates in modified and natural water bodies and rapid, positive responses to restoration suggest pond construction and other forms of management can effectively increase population growth. These tools are likely to become increasingly important to mitigate effects of increased drought expected from global climate change.
","language":"English","publisher":"Society for Conservation Biology","doi":"10.1111/cobi.12119","usgsCitation":"Hossack, B.R., Adams, M.J., Pearl, C.A., Wilson, K.W., Bull, E.L., Lohr, K., Patla, D., Pilliod, D., Jones, J., Wheeler, K., McKay, S., and Corn, P.S., 2013, Roles of patch characteristics, drought frequency, and restoration in long-term trends of a widespread amphibian: Conservation Biology, v. 27, no. 6, p. 1410-1420, https://doi.org/10.1111/cobi.12119.","productDescription":"11 p.","startPage":"1410","endPage":"1420","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-042996","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":381612,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"27","issue":"6","noUsgsAuthors":false,"publicationDate":"2013-08-23","publicationStatus":"PW","scienceBaseUri":"5465d639e4b04d4b7dbd6674","contributors":{"authors":[{"text":"Hossack, Blake R. 0000-0001-7456-9564 blake_hossack@usgs.gov","orcid":"https://orcid.org/0000-0001-7456-9564","contributorId":1177,"corporation":false,"usgs":true,"family":"Hossack","given":"Blake","email":"blake_hossack@usgs.gov","middleInitial":"R.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":522863,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Adams, M. J. 0000-0001-8844-042X mjadams@usgs.gov","orcid":"https://orcid.org/0000-0001-8844-042X","contributorId":3133,"corporation":false,"usgs":false,"family":"Adams","given":"M.","email":"mjadams@usgs.gov","middleInitial":"J.","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":522866,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pearl, Christopher A. 0000-0003-2943-7321 christopher_pearl@usgs.gov","orcid":"https://orcid.org/0000-0003-2943-7321","contributorId":3131,"corporation":false,"usgs":true,"family":"Pearl","given":"Christopher","email":"christopher_pearl@usgs.gov","middleInitial":"A.","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":false,"id":522864,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wilson, Kristine W.","contributorId":127013,"corporation":false,"usgs":false,"family":"Wilson","given":"Kristine","email":"","middleInitial":"W.","affiliations":[{"id":6763,"text":"Utah Division of Wildlife Resources, Salt Lake City, Utah","active":true,"usgs":false}],"preferred":false,"id":807240,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bull, Evelyn L.","contributorId":31104,"corporation":false,"usgs":true,"family":"Bull","given":"Evelyn","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":807241,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lohr, Kristin","contributorId":127012,"corporation":false,"usgs":false,"family":"Lohr","given":"Kristin","affiliations":[{"id":6764,"text":"Idaho Department of Fish and Game, Nampa, Idaho","active":true,"usgs":false}],"preferred":false,"id":807242,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Patla, Debra","contributorId":127009,"corporation":false,"usgs":false,"family":"Patla","given":"Debra","affiliations":[{"id":6761,"text":"Northern Rockies Conservation Cooperative, Jackson, Wyoming","active":true,"usgs":false}],"preferred":false,"id":807243,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Pilliod, David S. 0000-0003-4207-3518 dpilliod@usgs.gov","orcid":"https://orcid.org/0000-0003-4207-3518","contributorId":161,"corporation":false,"usgs":true,"family":"Pilliod","given":"David S.","email":"dpilliod@usgs.gov","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":false,"id":522865,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Jones, Jason","contributorId":127011,"corporation":false,"usgs":false,"family":"Jones","given":"Jason","email":"","affiliations":[{"id":6763,"text":"Utah Division of Wildlife Resources, Salt Lake City, Utah","active":true,"usgs":false}],"preferred":false,"id":807244,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Wheeler, Kevin","contributorId":239996,"corporation":false,"usgs":false,"family":"Wheeler","given":"Kevin","email":"","affiliations":[{"id":36276,"text":"JPL","active":true,"usgs":false}],"preferred":false,"id":807245,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"McKay, Samuel","contributorId":245872,"corporation":false,"usgs":false,"family":"McKay","given":"Samuel","email":"","affiliations":[],"preferred":false,"id":807246,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Corn, P. Stephen 0000-0002-4106-6335 steve_corn@usgs.gov","orcid":"https://orcid.org/0000-0002-4106-6335","contributorId":3227,"corporation":false,"usgs":true,"family":"Corn","given":"P.","email":"steve_corn@usgs.gov","middleInitial":"Stephen","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":522867,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70047753,"text":"70047753 - 2013 - Data-driven modeling of background and mine-related acidity and metals in river basins","interactions":[],"lastModifiedDate":"2017-05-23T13:32:47","indexId":"70047753","displayToPublicDate":"2013-12-01T09:40:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1555,"text":"Environmental Pollution","active":true,"publicationSubtype":{"id":10}},"title":"Data-driven modeling of background and mine-related acidity and metals in river basins","docAbstract":"A novel application of self-organizing map (SOM) and multivariate statistical techniques is used to model the nonlinear interaction among basin mineral-resources, mining activity, and surface-water quality. First, the SOM is trained using sparse measurements from 228 sample sites in the Animas River Basin, Colorado. The model performance is validated by comparing stochastic predictions of basin-alteration assemblages and mining activity at 104 independent sites. The SOM correctly predicts (>98%) the predominant type of basin hydrothermal alteration and presence (or absence) of mining activity. Second, application of the Davies–Bouldin criteria to k-means clustering of SOM neurons identified ten unique environmental groups. Median statistics of these groups define a nonlinear water-quality response along the spatiotemporal hydrothermal alteration-mining gradient. These results reveal that it is possible to differentiate among the continuum between inputs of background and mine-related acidity and metals, and it provides a basis for future research and empirical model development.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.envpol.2013.09.036","usgsCitation":"Friedel, M.J., 2013, Data-driven modeling of background and mine-related acidity and metals in river basins: Environmental Pollution, v. 184, p. 530-539, https://doi.org/10.1016/j.envpol.2013.09.036.","productDescription":"10 p.","startPage":"530","endPage":"539","ipdsId":"IP-038503","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":341590,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"184","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59254a6ee4b0b7ff9fb361b5","contributors":{"authors":[{"text":"Friedel, Michael J","contributorId":119245,"corporation":false,"usgs":true,"family":"Friedel","given":"Michael","email":"","middleInitial":"J","affiliations":[],"preferred":false,"id":518130,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70073896,"text":"70073896 - 2013 - Forest calcium depletion and biotic retention along a soil nitrogen gradient","interactions":[],"lastModifiedDate":"2014-01-24T09:39:03","indexId":"70073896","displayToPublicDate":"2013-12-01T09:33:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1450,"text":"Ecological Applications","active":true,"publicationSubtype":{"id":10}},"title":"Forest calcium depletion and biotic retention along a soil nitrogen gradient","docAbstract":"High nitrogen (N) accumulation in terrestrial ecosystems can shift patterns of nutrient limitation and deficiency beyond N toward other nutrients, most notably phosphorus (P) and base cations (calcium [Ca], magnesium [Mg], and potassium [K]). We examined how naturally high N accumulation from a legacy of symbiotic N fixation shaped P and base cation cycling across a gradient of nine temperate conifer forests in the Oregon Coast Range. We were particularly interested in whether long-term legacies of symbiotic N fixation promoted coupled N and organic P accumulation in soils, and whether biotic demands by non-fixing vegetation could conserve ecosystem base cations as N accumulated. Total soil N (0–100 cm) pools increased nearly threefold across the N gradient, leading to increased nitrate leaching, declines in soil pH from 5.8 to 4.2, 10-fold declines in soil exchangeable Ca, Mg, and K, and increased mobilization of aluminum. These results suggest that long-term N enrichment had acidified soils and depleted much of the readily weatherable base cation pool. Soil organic P increased with both soil N and C across the gradient, but soil inorganic P, biomass P, and P leaching loss did not vary with N, implying that historic symbiotic N fixation promoted soil organic P accumulation and P sufficiency for non-fixers. Even though soil pools of Ca, Mg, and K all declined as soil N increased, only Ca declined in biomass pools, suggesting the emergence of Ca deficiency at high N. Biotic conservation and tight recycling of Ca increased in response to whole-ecosystem Ca depletion, as indicated by preferential accumulation of Ca in biomass and surface soil. Our findings support a hierarchical model of coupled N–Ca cycling under long-term soil N enrichment, whereby ecosystem-level N saturation and nitrate leaching deplete readily available soil Ca, stimulating biotic Ca conservation as overall supply diminishes. We conclude that a legacy of biological N fixation can increase N and P accumulation in soil organic matter to the point that neither nutrient is limiting to subsequent non-fixers, while also resulting in natural N saturation that intensifies base cation depletion and deficiency.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Ecological Applications","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Ecological Society of America","doi":"10.1890/12-2204.1","usgsCitation":"Perakis, S., Sinkhorn, E.R., Catricala, C., Bullen, T.D., Fitzpatrick, J., Hynicka, J.D., and Cromack, K., 2013, Forest calcium depletion and biotic retention along a soil nitrogen gradient: Ecological Applications, v. 23, no. 8, p. 1947-1961, https://doi.org/10.1890/12-2204.1.","productDescription":"15 p.","startPage":"1947","endPage":"1961","numberOfPages":"15","ipdsId":"IP-044899","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":281467,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1890/12-2204.1"},{"id":281468,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon","otherGeospatial":"Oregon Coast Range","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -124.286,43.2258 ], [ -124.286,46.2132 ], [ -122.9839,46.2132 ], [ -122.9839,43.2258 ], [ -124.286,43.2258 ] ] ] } } ] }","volume":"23","issue":"8","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53cd5a20e4b0b290850f9271","contributors":{"authors":[{"text":"Perakis, Steven S. 0000-0003-0703-9314","orcid":"https://orcid.org/0000-0003-0703-9314","contributorId":16797,"corporation":false,"usgs":true,"family":"Perakis","given":"Steven S.","affiliations":[],"preferred":false,"id":489162,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sinkhorn, Emily R.","contributorId":7543,"corporation":false,"usgs":true,"family":"Sinkhorn","given":"Emily","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":489161,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Catricala, Christina ccatricala@usgs.gov","contributorId":5187,"corporation":false,"usgs":true,"family":"Catricala","given":"Christina","email":"ccatricala@usgs.gov","affiliations":[],"preferred":true,"id":489160,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bullen, Thomas D. 0000-0003-2281-1691 tdbullen@usgs.gov","orcid":"https://orcid.org/0000-0003-2281-1691","contributorId":1969,"corporation":false,"usgs":true,"family":"Bullen","given":"Thomas","email":"tdbullen@usgs.gov","middleInitial":"D.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":489159,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fitzpatrick, John A. 0000-0001-6738-7180","orcid":"https://orcid.org/0000-0001-6738-7180","contributorId":101983,"corporation":false,"usgs":true,"family":"Fitzpatrick","given":"John A.","affiliations":[],"preferred":false,"id":489165,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hynicka, Justin D.","contributorId":79797,"corporation":false,"usgs":true,"family":"Hynicka","given":"Justin","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":489164,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Cromack, Kermit Jr.","contributorId":79398,"corporation":false,"usgs":true,"family":"Cromack","given":"Kermit","suffix":"Jr.","email":"","affiliations":[],"preferred":false,"id":489163,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70107102,"text":"70107102 - 2013 - Combined impacts of current and future dust deposition and regional warming on Colorado River Basin snow dynamics and hydrology","interactions":[],"lastModifiedDate":"2016-04-12T16:44:36","indexId":"70107102","displayToPublicDate":"2013-12-01T09:04:00","publicationYear":"2013","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":"Combined impacts of current and future dust deposition and regional warming on Colorado River Basin snow dynamics and hydrology","docAbstract":"The Colorado River provides water to 40 million people in seven western states and two countries and to 5.5 million irrigated acres. The river has long been overallocated. Climate models project runoff losses of 5–20% from the basin by mid-21st century due to human-induced climate change. Recent work has shown that decreased snow albedo from anthropogenic dust loading to the CO mountains shortens the duration of snow cover by several weeks relative to conditions prior to western expansion of the US in the mid-1800s, and advances peak runoff at Lees Ferry, Arizona, by an average of 3 weeks. Increases in evapotranspiration from earlier exposure of soils and germination of plants have been estimated to decrease annual runoff by more than 1.0 billion cubic meters, or ~5% of the annual average. This prior work was based on observed dust loadings during 2005–2008; however, 2009 and 2010 saw unprecedented levels of dust loading on snowpacks in the Upper Colorado River Basin (UCRB), being on the order of 5 times the 2005–2008 loading. Building on our prior work, we developed a new snow albedo decay parameterization based on observations in 2009/10 to mimic the radiative forcing of extreme dust deposition. We convolve low, moderate, and extreme dust/snow albedos with both historic climate forcing and two future climate scenarios via a delta method perturbation of historic records. Compared to moderate dust, extreme dust absorbs 2× to 4× the solar radiation, and shifts peak snowmelt an additional 3 weeks earlier to a total of 6 weeks earlier than pre-disturbance. The extreme dust scenario reduces annual flow volume an additional 1% (6% compared to pre-disturbance), a smaller difference than from low to moderate dust scenarios due to melt season shifting into a season of lower evaporative demand. The sensitivity of flow timing to dust radiative forcing of snow albedo is maintained under future climate scenarios, but the sensitivity of flow volume reductions decreases with increased climate forcing. These results have implications for water management and suggest that dust abatement efforts could be an important component of any climate adaptation strategies in the UCRB.
","language":"English","publisher":"European Geosciences Union","doi":"10.5194/hess-17-4401-2013","usgsCitation":"Deems, J.S., Painter, T.H., Barsugli, J.J., Belnap, J., and Udall, B., 2013, Combined impacts of current and future dust deposition and regional warming on Colorado River Basin snow dynamics and hydrology: Hydrology and Earth System Sciences, v. 17, p. 4401-4413, https://doi.org/10.5194/hess-17-4401-2013.","productDescription":"13 p.","startPage":"4401","endPage":"4413","numberOfPages":"13","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-051183","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":473424,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/hess-17-4401-2013","text":"Publisher Index Page"},{"id":287310,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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S.","contributorId":83032,"corporation":false,"usgs":true,"family":"Deems","given":"Jeffrey","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":493874,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Painter, Thomas H.","contributorId":12378,"corporation":false,"usgs":true,"family":"Painter","given":"Thomas","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":493873,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Barsugli, Joseph J.","contributorId":103587,"corporation":false,"usgs":true,"family":"Barsugli","given":"Joseph","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":493876,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Belnap, Jayne 0000-0001-7471-2279 jayne_belnap@usgs.gov","orcid":"https://orcid.org/0000-0001-7471-2279","contributorId":1332,"corporation":false,"usgs":true,"family":"Belnap","given":"Jayne","email":"jayne_belnap@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":493872,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Udall, Bradley","contributorId":87862,"corporation":false,"usgs":true,"family":"Udall","given":"Bradley","email":"","affiliations":[],"preferred":false,"id":493875,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70104616,"text":"70104616 - 2013 - The significance of ultra-refracted surface gravity waves on sheltered coasts, with application to San Francisco Bay","interactions":[],"lastModifiedDate":"2017-10-30T11:43:47","indexId":"70104616","displayToPublicDate":"2013-12-01T08:19:30","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1587,"text":"Estuarine, Coastal and Shelf Science","active":true,"publicationSubtype":{"id":10}},"title":"The significance of ultra-refracted surface gravity waves on sheltered coasts, with application to San Francisco Bay","docAbstract":"Ocean surface gravity waves propagating over shallow bathymetry undergo spatial modification of propagation direction and energy density, commonly due to refraction and shoaling. If the bathymetric variations are significant the waves can undergo changes in their direction of propagation (relative to deepwater) greater than 90° over relatively short spatial scales. We refer to this phenomenon as ultra-refraction. Ultra-refracted swell waves can have a powerful influence on coastal areas that otherwise appear to be sheltered from ocean waves. Through a numerical modeling investigation it is shown that San Francisco Bay, one of the earth's largest and most protected natural harbors, is vulnerable to ultra-refracted ocean waves, particularly southwest incident swell. The flux of wave energy into San Francisco Bay results from wave transformation due to the bathymetry and orientation of the large ebb tidal delta, and deep, narrow channel through the Golden Gate. For example, ultra-refracted swell waves play a critical role in the intermittent closure of the entrance to Crissy Field Marsh, a small restored tidal wetland located on the sheltered north-facing coast approximately 1.5 km east of the Golden Gate Bridge.","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecss.2013.08.022","usgsCitation":"Hanes, D., and Erikson, L.H., 2013, The significance of ultra-refracted surface gravity waves on sheltered coasts, with application to San Francisco Bay: Estuarine, Coastal and Shelf Science, v. 133, p. 129-136, https://doi.org/10.1016/j.ecss.2013.08.022.","productDescription":"8 p.","startPage":"129","endPage":"136","ipdsId":"IP-050810","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":552,"text":"San Francisco Bay-Delta","active":false,"usgs":true}],"links":[{"id":287249,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Francisco Bay","volume":"133","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5377180ce4b02eab8669efe6","contributors":{"authors":[{"text":"Hanes, D.M.","contributorId":22479,"corporation":false,"usgs":true,"family":"Hanes","given":"D.M.","email":"","affiliations":[],"preferred":false,"id":493757,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Erikson, L. H.","contributorId":21366,"corporation":false,"usgs":true,"family":"Erikson","given":"L.","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":493756,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70145955,"text":"70145955 - 2013 - Petrologic, tectonic, and metallogenic evolution of the southern segment of the ancestral Cascades magmatic arc, California and Nevada","interactions":[],"lastModifiedDate":"2015-04-10T15:41:10","indexId":"70145955","displayToPublicDate":"2013-12-01T04:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1820,"text":"Geosphere","active":true,"publicationSubtype":{"id":10}},"title":"Petrologic, tectonic, and metallogenic evolution of the southern segment of the ancestral Cascades magmatic arc, California and Nevada","docAbstract":"Ongoing arc magmatism along western North America was preceded by ancestral arc magmatism that began ca. 45 Ma and evolved into modern arc volcanism. The southern ancestral arc segment, active from ca. 30 to 3 Ma, adjoins the northern segment in northern California across a proposed subducted slab tear. The east edge of the Walker Lane approximates the east edge of the southern arc whose products, mostly erupted from stratovolcanoes and lava dome complexes arrayed along the crest of the ancestral arc, extend down the west flank of the Sierra Nevada. Southern arc segment rocks include potassic, calc-alkaline intermediate- to silicic-composition lava flows, lava dome complexes, and associated volcaniclastic deposits.
\nNorthern and southern segment rocks are similar to other convergent-margin magmatic arc rocks but are compositionally distinct from each other. Southern segment rocks have lower TiO2, FeO*, CaO, and Na2O contents and higher K2O contents, and exhibit less compositional-temporal variation. Compositional distinctions between the northern and southern segment rocks reflect the composition and thickness of the crust beneath which the associated magma systems were sourced. Northern segment rock compositions are consistent with generation beneath thin, primitive crust, whereas southern segment rocks represent magmas generated and fractionated beneath thicker, more evolved crust.
\nAlthough rocks in the two arc segments have similar metal abundances, they are metallogenically distinct. Small porphyry copper deposits are characteristic of the northern segment whereas significant epithermal precious metal deposits are most commonly associated with the southern segment. These metallogenic differences are also fundamentally linked to the tectonic settings and crustal regimes within which these two arc segments evolved.
","language":"English","publisher":"Geological Society of America","doi":"10.1130/GES00944.1","usgsCitation":"du Bray, E.A., John, D.A., and Cousens, B., 2013, Petrologic, tectonic, and metallogenic evolution of the southern segment of the ancestral Cascades magmatic arc, California and Nevada: Geosphere, v. 10, no. 1, p. 1-39, https://doi.org/10.1130/GES00944.1.","productDescription":"39 p.","startPage":"1","endPage":"39","numberOfPages":"39","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-044845","costCenters":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":473425,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/ges00944.1","text":"Publisher Index Page"},{"id":299593,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Nevada","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124.65087890624999,\n 36.43896124085945\n ],\n [\n -124.65087890624999,\n 42.032974332441405\n ],\n [\n -115.42236328124999,\n 42.032974332441405\n ],\n [\n -115.42236328124999,\n 36.43896124085945\n ],\n [\n -124.65087890624999,\n 36.43896124085945\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"10","issue":"1","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5528f44ee4b026915857cb2b","contributors":{"authors":[{"text":"du Bray, Edward A. 0000-0002-4383-8394 edubray@usgs.gov","orcid":"https://orcid.org/0000-0002-4383-8394","contributorId":755,"corporation":false,"usgs":true,"family":"du Bray","given":"Edward","email":"edubray@usgs.gov","middleInitial":"A.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":544514,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"John, David A. 0000-0001-7977-9106 djohn@usgs.gov","orcid":"https://orcid.org/0000-0001-7977-9106","contributorId":1748,"corporation":false,"usgs":true,"family":"John","given":"David","email":"djohn@usgs.gov","middleInitial":"A.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":544515,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cousens, Brian L.","contributorId":84038,"corporation":false,"usgs":true,"family":"Cousens","given":"Brian L.","affiliations":[],"preferred":false,"id":544516,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70148691,"text":"70148691 - 2013 - Differences in extreme low salinity timing and duration differentially affect eastern oyster (Crassostrea virginica) size class growth and mortality in Breton Sound, LA","interactions":[],"lastModifiedDate":"2015-07-31T11:05:11","indexId":"70148691","displayToPublicDate":"2013-12-01T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1587,"text":"Estuarine, Coastal and Shelf Science","active":true,"publicationSubtype":{"id":10}},"title":"Differences in extreme low salinity timing and duration differentially affect eastern oyster (Crassostrea virginica) size class growth and mortality in Breton Sound, LA","docAbstract":"Understanding how different life history stages are impacted by extreme or stochastic environmental variation is critical for predicting and modeling organism population dynamics. This project examined recruitment, growth, and mortality of seed (25–75 mm) and market (>75 mm) sized oysters along a salinity gradient over two years in Breton Sound, LA. In April 2010, management responses to the Deepwater Horizon oil spill resulted in extreme low salinity (<5) at all sites through August 2010; in 2011, a 100-year Mississippi River flood event resulted in low salinity in late spring. Extended low salinity (<5) during hot summer months (>25 °C) significantly and negatively impacted oyster recruitment, survival and growth in 2010, while low salinity (<5) for a shorter period that did not extend into July (<25 °C) in 2011 had minimal impacts on oyster growth and mortality. In 2011, recruitment was limited, which may be due to a combination of low spring time salinities, high 2010 oyster mortality, minimal 2010 recruitment, cumulative effects from 10 years of declining oyster stock in the area, and poor cultch quality. In both 2010 and 2011, Perkinsus marinusinfection prevalence remained low throughout the year at all sites and almost all infection intensities were light. Oyster plasma osmolality failed to match surrounding low salinity waters in 2010, while oysters appeared to osmoconform throughout 2011 indicating that the high mortality in 2010 may be due to extended valve closing and resulting starvation or asphyxiation in response to the combination of low salinity during high temperatures (>25 °C). With increasing management of our freshwater inputs to estuaries combined with predicted climate changes, how extreme events affect different life history stages is key to understanding variation in population demographics of commercially important species and predicting future populations.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecss.2013.10.001","usgsCitation":"LaPeyre, M.K., Eberline, B.S., Soniat, T.M., and La Peyre, J.F., 2013, Differences in extreme low salinity timing and duration differentially affect eastern oyster (Crassostrea virginica) size class growth and mortality in Breton Sound, LA: Estuarine, Coastal and Shelf Science, v. 135, p. 146-157, https://doi.org/10.1016/j.ecss.2013.10.001.","productDescription":"10 p.","startPage":"146","endPage":"157","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-044031","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":306291,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Louisiana","otherGeospatial":"Breton Sound","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -89.65667724609375,\n 29.16415393327805\n ],\n [\n -89.65667724609375,\n 29.776297851831366\n ],\n [\n -88.868408203125,\n 29.776297851831366\n ],\n [\n -88.868408203125,\n 29.16415393327805\n ],\n [\n -89.65667724609375,\n 29.16415393327805\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"135","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"55bc9c2ae4b033ef52100f1f","contributors":{"authors":[{"text":"LaPeyre, Megan K. 0000-0001-9936-2252 mlapeyre@usgs.gov","orcid":"https://orcid.org/0000-0001-9936-2252","contributorId":585,"corporation":false,"usgs":true,"family":"LaPeyre","given":"Megan","email":"mlapeyre@usgs.gov","middleInitial":"K.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":549058,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Eberline, Benjamin S.","contributorId":141241,"corporation":false,"usgs":false,"family":"Eberline","given":"Benjamin","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":566917,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Soniat, Thomas M.","contributorId":11109,"corporation":false,"usgs":true,"family":"Soniat","given":"Thomas","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":566918,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"La Peyre, Jerome F.","contributorId":34697,"corporation":false,"usgs":true,"family":"La Peyre","given":"Jerome","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":566919,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70156252,"text":"70156252 - 2013 - Protocol for monitoring forest-nesting birds in National Park Service parks","interactions":[],"lastModifiedDate":"2016-09-08T14:38:10","indexId":"70156252","displayToPublicDate":"2013-12-01T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"seriesNumber":"NPS/NCRN/NRR—2014/749","title":"Protocol for monitoring forest-nesting birds in National Park Service parks","docAbstract":"These documents detail the protocol for monitoring forest-nesting birds in National Park Service parks in the National Capital Region Network (NCRN). In the first year of sampling, counts of birds should be made at 384 points on the NCRN spatially randomized grid, developed to sample terrestrial resources. Sampling should begin on or about May 20 and continue into early July; on each day the sampling period begins at sunrise and ends five hours later. Each point should be counted twice, once in the first half of the field season and once in the second half, with visits made by different observers, balancing the within-season coverage of points and their spatial coverage by observers, and allowing observer differences to be tested. Three observers, skilled in identifying birds of the region by sight and sound and with previous experience in conducting timed counts of birds, will be needed for this effort. Observers should be randomly assigned to ‘routes’ consisting of eight points, in close proximity and, ideally, in similar habitat, that can be covered in one morning. Counts are 10 minutes in length, subdivided into four 2.5-min intervals. Within each time interval, new birds (i.e., those not already detected) are recorded as within or beyond 50 m of the point, based on where first detected. Binomial distance methods are used to calculate annual estimates of density for species. The data are also amenable to estimation of abundance and detection probability via the removal method. Generalized linear models can be used to assess between-year changes in density estimates or unadjusted count data. This level of sampling is expected to be sufficient to detect a 50% decline in 10 years for approximately 50 bird species, including 14 of 19 species that are priorities for conservation efforts, if analyses are based on unadjusted count data, and for 30 species (6 priority species) if analyses are based on density estimates. The estimates of required sample sizes are based on the mean number of individuals detected per 10 minutes in available data from surveys in three NCRN parks. Once network-wide data from the first year of sampling are available, this and other aspects of the protocol should be re-assessed, and changes made as desired or necessary before the start of the second field season. Thereafter, changes should not be made to the field methods, and sampling should be conducted annually for at least ten years. NCRN staff should keep apprised of new analytical methods developed for analysis of point-count data.
","language":"English","publisher":"National Park Service","collaboration":"Murray G. Efford","usgsCitation":"Dawson, D.K., and Efford, M.G., 2013, Protocol for monitoring forest-nesting birds in National Park Service parks, xi, 50 p. .","productDescription":"xi, 50 p. ","ipdsId":"IP-066816","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":328408,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":306801,"type":{"id":15,"text":"Index Page"},"url":"https://irma.nps.gov/App/Reference/Profile/2206488/"}],"publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57d28baee4b0571647d0f93f","contributors":{"authors":[{"text":"Dawson, Deanna K. ddawson@usgs.gov","contributorId":1257,"corporation":false,"usgs":true,"family":"Dawson","given":"Deanna","email":"ddawson@usgs.gov","middleInitial":"K.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":568250,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Efford, Murray G.","contributorId":91616,"corporation":false,"usgs":true,"family":"Efford","given":"Murray","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":568251,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70176596,"text":"70176596 - 2013 - Net primary productivity of subalpine meadows in Yosemite National Park in relation to climate variability","interactions":[],"lastModifiedDate":"2017-05-03T13:09:25","indexId":"70176596","displayToPublicDate":"2013-12-01T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3746,"text":"Western North American Naturalist","onlineIssn":"1944-8341","printIssn":"1527-0904","active":true,"publicationSubtype":{"id":10}},"title":"Net primary productivity of subalpine meadows in Yosemite National Park in relation to climate variability","docAbstract":"Subalpine meadows are some of the most ecologically important components of mountain landscapes, and primary productivity is important to the maintenance of meadow functions. Understanding how changes in primary productivity are associated with variability in moisture and temperature will become increasingly important with current and anticipated changes in climate. Our objective was to describe patterns and variability in aboveground live vascular plant biomass in relation to climatic factors. We harvested aboveground biomass at peak growth from four 64-m2 plots each in xeric, mesic, and hydric meadows annually from 1994 to 2000. Data from nearby weather stations provided independent variables of spring snow water content, snow-free date, and thawing degree days for a cumulative index of available energy. We assembled these climatic variables into a set of mixed effects analysis of covariance models to evaluate their relationships with annual aboveground net primary productivity (ANPP), and we used an information theoretic approach to compare the quality of fit among candidate models. ANPP in the xeric meadow was negatively related to snow water content and thawing degree days and in the mesic meadow was negatively related to snow water content. Relationships between ANPP and these 2 covariates in the hydric meadow were not significant. Increasing snow water content may limit ANPP in these meadows if anaerobic conditions delay microbial activity and nutrient availability. Increased thawing degree days may limit ANPP in xeric meadows by prematurely depleting soil moisture. Large within-year variation of ANPP in the hydric meadow limited sensitivity to the climatic variables. These relationships suggest that, under projected warmer and drier conditions, ANPP will increase in mesic meadows but remain unchanged in xeric meadows because declines associated with increased temperatures would offset the increases from decreased snow water content.
","language":"English","publisher":"Monte L. Bean Life Science Museum, Brigham Young University","doi":"10.3398/064.073.0410","usgsCitation":"Moore, P.E., Van Wagtendonk, J.W., Yee, J.L., McClaran, M.P., Cole, D.N., McDougald, N.K., and Brooks, M.L., 2013, Net primary productivity of subalpine meadows in Yosemite National Park in relation to climate variability: Western North American Naturalist, v. 73, no. 4, p. 409-418, https://doi.org/10.3398/064.073.0410.","productDescription":"10 p.","startPage":"409","endPage":"418","ipdsId":"IP-042537","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":488520,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://scholarsarchive.byu.edu/wnan/vol73/iss4/2","text":"External Repository"},{"id":328860,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"73","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57f7f1a9e4b0bc0bec09feea","contributors":{"authors":[{"text":"Moore, Peggy E. 0000-0002-8481-2617 peggy_moore@usgs.gov","orcid":"https://orcid.org/0000-0002-8481-2617","contributorId":3365,"corporation":false,"usgs":true,"family":"Moore","given":"Peggy","email":"peggy_moore@usgs.gov","middleInitial":"E.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":649322,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Van Wagtendonk, Jan W. jan_van_wagtendonk@usgs.gov","contributorId":2648,"corporation":false,"usgs":true,"family":"Van Wagtendonk","given":"Jan","email":"jan_van_wagtendonk@usgs.gov","middleInitial":"W.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":649323,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Yee, Julie L. 0000-0003-1782-157X julie_yee@usgs.gov","orcid":"https://orcid.org/0000-0003-1782-157X","contributorId":3246,"corporation":false,"usgs":true,"family":"Yee","given":"Julie","email":"julie_yee@usgs.gov","middleInitial":"L.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":649324,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McClaran, Mitchel P.","contributorId":15453,"corporation":false,"usgs":true,"family":"McClaran","given":"Mitchel","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":649325,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cole, David N.","contributorId":40086,"corporation":false,"usgs":true,"family":"Cole","given":"David","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":649326,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"McDougald, Neil K.","contributorId":139339,"corporation":false,"usgs":false,"family":"McDougald","given":"Neil","email":"","middleInitial":"K.","affiliations":[{"id":12739,"text":"UC Cooperative Extension, Madera, CA","active":true,"usgs":false}],"preferred":false,"id":649327,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Brooks, Matthew L. 0000-0002-3518-6787 mlbrooks@usgs.gov","orcid":"https://orcid.org/0000-0002-3518-6787","contributorId":393,"corporation":false,"usgs":true,"family":"Brooks","given":"Matthew","email":"mlbrooks@usgs.gov","middleInitial":"L.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":649328,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70191673,"text":"70191673 - 2013 - Data management challenges in species distribution modeling","interactions":[],"lastModifiedDate":"2017-10-17T16:48:59","indexId":"70191673","displayToPublicDate":"2013-12-01T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5516,"text":"Bulletin of the Technical Committee on Data Engineering","active":true,"publicationSubtype":{"id":10}},"title":"Data management challenges in species distribution modeling","docAbstract":"An important component in the fields of ecology and conservation biology is understanding the environmental\nconditions and geographic areas that are suitable for a given species to inhabit. A common tool\nin determining such areas is species distribution modeling which uses computer algorithms to determine\nthe spatial distribution of organisms. Most commonly the correlative relationships between the organism\nand environmental variables are the primary consideration. The data requirements for this type of\nmodeling consist of known presence and possibly absence locations of the species as well as the values\nof environmental or climatic covariates thought to define the species habitat suitability at these locations.\nThese covariate data are generally extracted from remotely sensed imagery, interpolated/gridded\nhistorical climate data, or downscaled climate model output. Traditionally, ecologists and biologists\nhave constructed species distribution models using workflows and data that reside primarily on their\nlocal workstations or networks. This workflow is becoming challenging as scientists increasingly try to\nuse these modeling techniques to inform management decisions under different climate change scenarios.\nThis challenge stems from the fact that remote sensing products, gridded historical climate, and\ndownscaled climate models are not only increasing in spatial and temporal resolution but proliferating\nas well. Any rigorous assessment of uncertainty requires a computationally intensive sensitivity analysis\naccounting for various sources of uncertainty. The scientists fitting these models generally do not have\nthe background in computer science required to take advantage of recent advances in web-service based\ndata acquisition, remote high-powered data processing, or scientific workflow systems. Ecologists in the\nfield of modeling are in need of a tractable platform that abstracts the inherent computational complexity\nrequired to incorporate the burgeoning field of coupled climate and ecological response modeling.\nIn this paper we describe the computational challenges in species distribution modeling and solutions\nusing scientific workflow systems. We focus on the Software for Assisted Species Modeling (SAHM) a\npackage within VisTrails, an open-source scientific workflow system.","language":"English","publisher":"IEEE","usgsCitation":"Talbert, C., Talbert, M., Morisette, J.T., and Koop, D., 2013, Data management challenges in species distribution modeling: Bulletin of the Technical Committee on Data Engineering, v. 36, no. 4, p. 31-40.","productDescription":"10 p.","startPage":"31","endPage":"40","ipdsId":"IP-053026","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":346766,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":346746,"type":{"id":15,"text":"Index Page"},"url":"https://sites.computer.org/debull/A13dec/issue1.htm"}],"volume":"36","issue":"4","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59e71695e4b05fe04cd331ed","contributors":{"authors":[{"text":"Talbert, Colin 0000-0002-9505-1876 talbertc@usgs.gov","orcid":"https://orcid.org/0000-0002-9505-1876","contributorId":181913,"corporation":false,"usgs":true,"family":"Talbert","given":"Colin","email":"talbertc@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":713021,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Talbert, Marian 0000-0003-0588-0265 mtalbert@usgs.gov","orcid":"https://orcid.org/0000-0003-0588-0265","contributorId":196740,"corporation":false,"usgs":true,"family":"Talbert","given":"Marian","email":"mtalbert@usgs.gov","affiliations":[{"id":477,"text":"North Central Climate Science Center","active":true,"usgs":true},{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true}],"preferred":true,"id":713022,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Morisette, Jeffrey T. 0000-0002-0483-0082 morisettej@usgs.gov","orcid":"https://orcid.org/0000-0002-0483-0082","contributorId":307,"corporation":false,"usgs":true,"family":"Morisette","given":"Jeffrey","email":"morisettej@usgs.gov","middleInitial":"T.","affiliations":[{"id":477,"text":"North Central Climate Science Center","active":true,"usgs":true},{"id":569,"text":"Southwest Climate Science Center","active":true,"usgs":true}],"preferred":true,"id":713023,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Koop, David","contributorId":83845,"corporation":false,"usgs":true,"family":"Koop","given":"David","email":"","affiliations":[],"preferred":false,"id":713024,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70191975,"text":"70191975 - 2013 - Developing an outcome-based biodiversity metric in support of the field to market project: Final report","interactions":[],"lastModifiedDate":"2018-12-20T11:55:36","indexId":"70191975","displayToPublicDate":"2013-12-01T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":9,"text":"Other Report"},"seriesTitle":{"id":5602,"text":"Technical Bulletin","active":true,"publicationSubtype":{"id":9}},"seriesNumber":"334","title":"Developing an outcome-based biodiversity metric in support of the field to market project: Final report","docAbstract":"Our objective was to create a metric that would calculate the relative impact of common commercial agricultural practices on terrestrial vertebrate richness. We sought to define impacts in fields (including field borders) of the southeastern region’s commercial production of corn, wheat, soy, and cotton. The metric is intended to serve as an educational tool, allowing producers to see how operational decisions made at the field level impact overall vertebrate species richness and to explore decision impacts to targeted species groups (e.g. game, pest, or beneficial species).
Agricultural landscapes are often mistakenly thought to be unsuitable habitat for most species. However, as demonstrated by results reported here, even large-scale, conventional agricultural producers are potentially important partners in biodiversity conservation. Many vertebrate species do inhabit agricultural landscapes, benefitting from the provision of water, food, or shelter within cultivated fields and their immediate borders (e.g., Holland et al. 2012). In the Southeastern US, of the 613 terrestrial vertebrate species modeled by the Southeast Gap Analysis Program (SEGAP) (http://www.basic.ncsu.edu/segap/index.html), 263 utilize row crop and associated agricultural land cover classes as potential habitat (Box 1). While some species may be sensitive to certain operational practices (e.g., tillage, pest management, or field border management practices), others are generally tolerant, and some may benefit either directly or indirectly. For example, field margins and ditches often serve as semi-natural habitats providing foraging resources and shelter for vertebrates and are shown to positively influence species richness and abundance (Billeter et al. 2007; Herzon & Helenius 2008; Marshall & Moonen 2002; Shore et al. 2005; Weibull et al. 2003; Wuczyńskia et al. 2011). Biodiversity responses are, therefore, complex, as an individual species’ responses to agricultural production practices depends on that animal’s resource specialization, mobility, and life history strategies (Jeanneret et al. 2003a, b; Jennings & Pocock 2009).
The knowledge necessary to define the biodiversity contribution of agricultural lands is specialized, dispersed, and nuanced, and thus not readily accessible. Given access to clearly defined biodiversity tradeoffs between alternative agricultural practices, landowners, land managers and farm operators could collectively enhance the conservation and economic value of agricultural landscapes. Therefore, Field to Market: The Keystone Alliance for Sustainable Agriculture and The Nature Conservancy jointly funded a pilot project to develop a biodiversity metric to integrate into Field to Market’s existing sustainability calculator, The Fieldprint Calculator (http://www. fieldtomarket.org/). Field to Market: The Keystone Alliance for Sustainable Agriculture is an alliance among producers, agribusinesses, food companies, and conservation organizations seeking to create sustainable outcomes for agriculture. The Fieldprint Calculator supports the Keystone Alliance’s vision to achieve safe, accessible, and nutritious food, fiber and fuel in thriving ecosystems to meet the needs of 9 billion people in 2050. In support of this same vision, our project provides proof-of-concept for an outcome-based biodiversity metric for Field to Market to quantify biodiversity impacts of commercial row crop production on terrestrial vertebrate richness.
Little research exists examining the impacts of alternative commercial agricultural practices on overall terrestrial biodiversity (McLaughlin & Mineau 1995). Instead, most studies compare organic versus conventional practices (e.g. Freemark & Kirk 2001; Wickramasinghe et al. 2004), and most studies focus on flora, avian, or invertebrate communities (Jeanneret et al. 2003a; Maes et al. 2008; Pollard & Relton 1970). Therefore, we used an expert-knowledge-based approach to develop a metric that predicts expected impacts to shelter and forage resources, individual species, and overall biodiversity (species richness). This approach is modeled after an ecosystems services concept (WRI 2005), except that we examine services (i.e., resources) provided to vertebrate wildlife rather than service provided to the human population. SEGAP predicts species that are potentially present in an area given landscape-scale habitat availability, configuration, and context (e.g., patch size, proximity to resources, connectivity, potential for disturbance). Based on the prediction of species that may be potentially present, the impacts of management decisions within fields and around their borders can be analyzed based on the impact of those practices to the availability of species’ resources. The final metric provides an index of a producer’s relative impact, but perhaps even more importantly, the underlying database allows producers to explore details such as which species are most impacted or how alternative decisions would impact their score.
","language":"English","publisher":"North Carolina Agricultral Research Service, College of Agriculture and Life Sciences, North Carolina State University","usgsCitation":"Drew, C.A., Alexander-Vaughn, L.B., Collazo, J., McKerrow, A., and Anderson, J., 2013, Developing an outcome-based biodiversity metric in support of the field to market project: Final report: Technical Bulletin 334, 28 p.","productDescription":"28 p.","ipdsId":"IP-046155","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":37226,"text":"Core Science Analytics, Synthesis, and Libraries","active":true,"usgs":true},{"id":38315,"text":"GAP Analysis Project","active":true,"usgs":true}],"links":[{"id":350596,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":350595,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://www.basic.ncsu.edu/eda/downloads/BiodiversityReport_Text.pdf"}],"publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a6afac9e4b06e28e9c9a91e","contributors":{"authors":[{"text":"Drew, C. Ashton","contributorId":140953,"corporation":false,"usgs":false,"family":"Drew","given":"C.","email":"","middleInitial":"Ashton","affiliations":[],"preferred":false,"id":725790,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Alexander-Vaughn, Louise B.","contributorId":199257,"corporation":false,"usgs":false,"family":"Alexander-Vaughn","given":"Louise","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":725791,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Collazo, Jaime A. 0000-0002-1816-7744 jaime_collazo@usgs.gov","orcid":"https://orcid.org/0000-0002-1816-7744","contributorId":173448,"corporation":false,"usgs":true,"family":"Collazo","given":"Jaime A.","email":"jaime_collazo@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":false,"id":713802,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McKerrow, Alexa 0000-0002-8312-2905 amckerrow@usgs.gov","orcid":"https://orcid.org/0000-0002-8312-2905","contributorId":127753,"corporation":false,"usgs":true,"family":"McKerrow","given":"Alexa","email":"amckerrow@usgs.gov","affiliations":[{"id":208,"text":"Core Science Analytics and Synthesis","active":true,"usgs":true}],"preferred":true,"id":725792,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Anderson, John","contributorId":8763,"corporation":false,"usgs":true,"family":"Anderson","given":"John","affiliations":[],"preferred":false,"id":725793,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70189751,"text":"70189751 - 2013 - A scenario study of seismically induced landsliding in Seattle using broadband synthetic seismograms","interactions":[],"lastModifiedDate":"2017-07-24T14:55:11","indexId":"70189751","displayToPublicDate":"2013-12-01T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"A scenario study of seismically induced landsliding in Seattle using broadband synthetic seismograms","docAbstract":"We demonstrate the value of utilizing broadband synthetic seismograms to assess regional seismically induced landslide hazard. Focusing on a case study of an Mw 7.0 Seattle fault earthquake in Seattle, Washington, we computed broadband synthetic seismograms that account for rupture directivity and 3D basin amplification. We then adjusted the computed motions on a fine grid for 1D amplifications based on the site response of typical geologic profiles in Seattle and used these time‐series ground motions to trigger shallow landsliding using the Newmark method. The inclusion of these effects was critical in determining the extent of landsliding triggered. We found that for inertially triggered slope failures modeled by the Newmark method, the ground motions used to simulate landsliding must have broadband frequency content in order to capture the full slope displacement. We applied commonly used simpler methods based on ground‐motion prediction equations for the same scenario and found that they predicted far fewer landslides if only the mean values were used, but far more at the maximum range of the uncertainties, highlighting the danger of using just the mean values for such methods. Our results indicate that landsliding triggered by a large Seattle fault earthquake will be extensive and potentially devastating, causing direct losses and impeding recovery. The high impact of landsliding predicted by this simulation shows that this secondary effect of earthquakes should be studied with as much vigor as other earthquake effects.
","language":"English","publisher":" Seismological Society of America","doi":"10.1785/0120130051","usgsCitation":"Allstadt, K.E., Vidale, J.E., and Frankel, A.D., 2013, A scenario study of seismically induced landsliding in Seattle using broadband synthetic seismograms: Bulletin of the Seismological Society of America, v. 103, no. 6, p. 2971-2992, https://doi.org/10.1785/0120130051.","productDescription":"22 p.","startPage":"2971","endPage":"2992","ipdsId":"IP-046324","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":344268,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","city":"Seattle","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.45,\n 47.5\n ],\n [\n -122.23,\n 47.5\n ],\n [\n -122.23,\n 47.75\n ],\n [\n -122.45,\n 47.75\n ],\n [\n -122.45,\n 47.5\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"103","issue":"6","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2013-10-22","publicationStatus":"PW","scienceBaseUri":"59770755e4b0ec1a48889fc0","contributors":{"authors":[{"text":"Allstadt, Kate E. 0000-0003-4977-5248 kallstadt@usgs.gov","orcid":"https://orcid.org/0000-0003-4977-5248","contributorId":167684,"corporation":false,"usgs":true,"family":"Allstadt","given":"Kate","email":"kallstadt@usgs.gov","middleInitial":"E.","affiliations":[{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true},{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":false,"id":706284,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Vidale, John E.","contributorId":48850,"corporation":false,"usgs":true,"family":"Vidale","given":"John","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":706285,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Frankel, Arthur D. 0000-0001-9119-6106 afrankel@usgs.gov","orcid":"https://orcid.org/0000-0001-9119-6106","contributorId":1363,"corporation":false,"usgs":true,"family":"Frankel","given":"Arthur","email":"afrankel@usgs.gov","middleInitial":"D.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":false,"id":706286,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70187413,"text":"70187413 - 2013 - Using landscape epidemiological models to understand the distribution of chronic wasting disease in the Midwestern USA","interactions":[],"lastModifiedDate":"2017-05-02T13:38:03","indexId":"70187413","displayToPublicDate":"2013-12-01T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2602,"text":"Landscape Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Using landscape epidemiological models to understand the distribution of chronic wasting disease in the Midwestern USA","docAbstract":"Animal movement across the landscape plays a critical role in the ecology of infectious wildlife diseases. Dispersing animals can spread pathogens between infected areas and naïve populations. While tracking free-ranging animals over the geographic scales relevant to landscape-level disease management is challenging, landscape features that influence gene flow among wildlife populations may also influence the contact rates and disease spread between populations. We used spatial diffusion and barriers to white-tailed deer gene flow, identified through landscape genetics, to model the distribution of chronic wasting disease (CWD) in the infected region of southern Wisconsin and northern Illinois, USA. Our generalized linear model showed that risk of CWD infection declined exponentially with distance from current outbreaks, and inclusion of gene flow barriers dramatically improved fit and predictive power of the model. Our results indicate that CWD is spreading across the Midwestern landscape from these two endemic foci, but spread is strongly influenced by highways and rivers that also reduce deer gene flow. We used our model to plot a risk map, providing important information for CWD management by identifying likely routes of disease spread and providing a tool for prioritizing disease monitoring and containment efforts. The current analysis may serve as a framework for modeling future disease risk drawing on genetic information to investigate barriers to spread and extending management and monitoring beyond currently affected regions.
","language":"English","publisher":"Springer","doi":"10.1007/s10980-013-9919-4","usgsCitation":"Robinson, S.J., Samuel, M.D., Rolley, R.E., and Shelton, P., 2013, Using landscape epidemiological models to understand the distribution of chronic wasting disease in the Midwestern USA: Landscape Ecology, v. 28, no. 10, p. 1923-1935, https://doi.org/10.1007/s10980-013-9919-4.","productDescription":"13 p.","startPage":"1923","endPage":"1935","ipdsId":"IP-038493","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":340746,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"28","issue":"10","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2013-08-22","publicationStatus":"PW","scienceBaseUri":"59099ab1e4b0fc4e44915816","contributors":{"authors":[{"text":"Robinson, Stacie J.","contributorId":172022,"corporation":false,"usgs":false,"family":"Robinson","given":"Stacie","email":"","middleInitial":"J.","affiliations":[{"id":12508,"text":"Department of Forest and Wildlife Ecology, University of Wisconsin, 1710 University Ave., Room 285, Madison, WI 53726, USA","active":true,"usgs":false}],"preferred":false,"id":693982,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Samuel, Michael D. msamuel@usgs.gov","contributorId":1419,"corporation":false,"usgs":true,"family":"Samuel","given":"Michael","email":"msamuel@usgs.gov","middleInitial":"D.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":693919,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rolley, Robert E.","contributorId":171376,"corporation":false,"usgs":false,"family":"Rolley","given":"Robert","email":"","middleInitial":"E.","affiliations":[{"id":24833,"text":"Wisconsin DNR, Madison, WI","active":true,"usgs":false}],"preferred":false,"id":693983,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Shelton, Paul","contributorId":171375,"corporation":false,"usgs":false,"family":"Shelton","given":"Paul","email":"","affiliations":[{"id":26879,"text":"Illinois DNR, Springfield, IL","active":true,"usgs":false}],"preferred":false,"id":693984,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70187704,"text":"70187704 - 2013 - An approach for characterizing the distribution of shrubland ecosystem components as continuous fields as part of NLCD","interactions":[],"lastModifiedDate":"2018-03-08T13:04:32","indexId":"70187704","displayToPublicDate":"2013-12-01T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1958,"text":"ISPRS Journal of Photogrammetry and Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"An approach for characterizing the distribution of shrubland ecosystem components as continuous fields as part of NLCD","docAbstract":"Characterizing and quantifying distributions of shrubland ecosystem components is one of the major challenges for monitoring shrubland vegetation cover change across the United States. A new approach has been developed to quantify shrubland components as fractional products within National Land Cover Database (NLCD). This approach uses remote sensing data and regression tree models to estimate the fractional cover of shrubland ecosystem components. The approach consists of three major steps: field data collection, high resolution estimates of shrubland ecosystem components using WorldView-2 imagery, and coarse resolution estimates of these components across larger areas using Landsat imagery. This research seeks to explore this method to quantify shrubland ecosystem components as continuous fields in regions that contain wide-ranging shrubland ecosystems. Fractional cover of four shrubland ecosystem components, including bare ground, herbaceous, litter, and shrub, as well as shrub heights, were delineated in three ecological regions in Arizona, Florida, and Texas. Results show that estimates for most components have relatively small normalized root mean square errors and significant correlations with validation data in both Arizona and Texas. The distribution patterns of shrub height also show relatively high accuracies in these two areas. The fractional cover estimates of shrubland components, except for litter, are not well represented in the Florida site. The research results suggest that this method provides good potential to effectively characterize shrubland ecosystem conditions over perennial shrubland although it is less effective in transitional shrubland. The fractional cover of shrub components as continuous elements could offer valuable information to quantify biomass and help improve thematic land cover classification in arid and semiarid areas.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.isprsjprs.2013.09.009","usgsCitation":"Xian, G.Z., Homer, C.G., Meyer, D., and Granneman, B.J., 2013, An approach for characterizing the distribution of shrubland ecosystem components as continuous fields as part of NLCD: ISPRS Journal of Photogrammetry and Remote Sensing, v. 86, p. 136-149, https://doi.org/10.1016/j.isprsjprs.2013.09.009.","productDescription":"14 p.","startPage":"136","endPage":"149","ipdsId":"IP-046020","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":341311,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona, Florida, Texas","volume":"86","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"591abe39e4b0a7fdb43c8c01","contributors":{"authors":[{"text":"Xian, George Z. 0000-0001-5674-2204 xian@usgs.gov","orcid":"https://orcid.org/0000-0001-5674-2204","contributorId":2263,"corporation":false,"usgs":true,"family":"Xian","given":"George","email":"xian@usgs.gov","middleInitial":"Z.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":695183,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Homer, Collin G. 0000-0003-4755-8135 homer@usgs.gov","orcid":"https://orcid.org/0000-0003-4755-8135","contributorId":2262,"corporation":false,"usgs":true,"family":"Homer","given":"Collin","email":"homer@usgs.gov","middleInitial":"G.","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":695182,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Meyer, Debbie 0000-0002-8841-697X debbie.meyer.ctr@usgs.gov","orcid":"https://orcid.org/0000-0002-8841-697X","contributorId":192028,"corporation":false,"usgs":true,"family":"Meyer","given":"Debbie","email":"debbie.meyer.ctr@usgs.gov","affiliations":[],"preferred":false,"id":695180,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Granneman, Brian J. 0000-0002-1910-0955 grann@usgs.gov","orcid":"https://orcid.org/0000-0002-1910-0955","contributorId":4209,"corporation":false,"usgs":true,"family":"Granneman","given":"Brian","email":"grann@usgs.gov","middleInitial":"J.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":695181,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70188341,"text":"70188341 - 2013 - Next generation of global land cover characterization, mapping, and monitoring","interactions":[],"lastModifiedDate":"2017-06-06T14:38:04","indexId":"70188341","displayToPublicDate":"2013-12-01T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2027,"text":"International Journal of Applied Earth Observation and Geoinformation","active":true,"publicationSubtype":{"id":10}},"title":"Next generation of global land cover characterization, mapping, and monitoring","docAbstract":"Land cover change is increasingly affecting the biophysics, biogeochemistry, and biogeography of the Earth's surface and the atmosphere, with far-reaching consequences to human well-being. However, our scientific understanding of the distribution and dynamics of land cover and land cover change (LCLCC) is limited. Previous global land cover assessments performed using coarse spatial resolution (300 m–1 km) satellite data did not provide enough thematic detail or change information for global change studies and for resource management. High resolution (∼30 m) land cover characterization and monitoring is needed that permits detection of land change at the scale of most human activity and offers the increased flexibility of environmental model parameterization needed for global change studies. However, there are a number of challenges to overcome before producing such data sets including unavailability of consistent global coverage of satellite data, sheer volume of data, unavailability of timely and accurate training and validation data, difficulties in preparing image mosaics, and high performance computing requirements. Integration of remote sensing and information technology is needed for process automation and high-performance computing needs. Recent developments in these areas have created an opportunity for operational high resolution land cover mapping, and monitoring of the world. Here, we report and discuss these advancements and opportunities in producing the next generations of global land cover characterization, mapping, and monitoring at 30-m spatial resolution primarily in the context of United States, Group on Earth Observations Global 30 m land cover initiative (UGLC).
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jag.2013.03.005","usgsCitation":"Giri, C., Pengra, B., Long, J., and Loveland, T.R., 2013, Next generation of global land cover characterization, mapping, and monitoring: International Journal of Applied Earth Observation and Geoinformation, v. 25, p. 30-37, https://doi.org/10.1016/j.jag.2013.03.005.","productDescription":"8 p.","startPage":"30","endPage":"37","ipdsId":"IP-044790","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":342164,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"25","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5937bf2fe4b0f6c2d0d9c789","contributors":{"authors":[{"text":"Giri, Chandra cgiri@usgs.gov","contributorId":189128,"corporation":false,"usgs":true,"family":"Giri","given":"Chandra","email":"cgiri@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":697326,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pengra, Bruce 0000-0003-2497-8284 bpengra@usgs.gov","orcid":"https://orcid.org/0000-0003-2497-8284","contributorId":5132,"corporation":false,"usgs":true,"family":"Pengra","given":"Bruce","email":"bpengra@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":697327,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Long, J.","contributorId":41993,"corporation":false,"usgs":true,"family":"Long","given":"J.","affiliations":[],"preferred":false,"id":697328,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Loveland, Thomas R. 0000-0003-3114-6646 loveland@usgs.gov","orcid":"https://orcid.org/0000-0003-3114-6646","contributorId":140256,"corporation":false,"usgs":true,"family":"Loveland","given":"Thomas","email":"loveland@usgs.gov","middleInitial":"R.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":697329,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70137288,"text":"70137288 - 2013 - Limited denitrification in glacial deposit aquifers having thick unsaturated zones (Long Island, USA)","interactions":[],"lastModifiedDate":"2015-01-07T11:29:32","indexId":"70137288","displayToPublicDate":"2013-12-01T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1923,"text":"Hydrogeology Journal","active":true,"publicationSubtype":{"id":10}},"title":"Limited denitrification in glacial deposit aquifers having thick unsaturated zones (Long Island, USA)","docAbstract":"The goal of this study was to demonstrate how the extent of denitrification, which is indirectly related to dissolved organ carbon and directly related to oxygen concentrations, can also be linked to unsaturated-zone thickness, a mappable aquifer property. Groundwater from public supply and monitoring wells in Northport on Long Island, New York state (USA), were analyzed for denitrification reaction progress using dissolved N2/Ar concentrations by membrane inlet mass spectrometry. This technique allows for discernment of small amounts of excess N2, attributable to denitrification. Results show an average 15 % of total nitrogen in the system was denitrified, significantly lower than model predictions of 35 % denitrification. The minimal denitrification is due to low dissolved organic carbon (29.3–41.1 μmol L−1) and high dissolved oxygen concentrations (58–100 % oxygen saturation) in glacial sediments with minimal solid-phase electron donors to drive denitrification. A mechanism is proposed that combines two known processes for aquifer re-aeration in unconsolidated sands with thick (>10 m) unsaturated zones. First, advective flux provides 50 % freshening of pore space oxygen in the upper 2 m due to barometric pressure changes. Then, oxygen diffusion across the water-table boundary occurs due to high volumetric air content in the unsaturated-zone catchment area.
","language":"English","publisher":"Springer","doi":"10.1007/s10040-013-1038-4","usgsCitation":"Young, C., Kroeger, K.D., and Hanson, G., 2013, Limited denitrification in glacial deposit aquifers having thick unsaturated zones (Long Island, USA): Hydrogeology Journal, v. 21, no. 8, p. 1773-1786, https://doi.org/10.1007/s10040-013-1038-4.","productDescription":"14 p.","startPage":"1773","endPage":"1786","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-053893","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":297030,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Long Island Sound","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -73.8885498046875,\n 40.78054143186031\n ],\n [\n -73.95996093749999,\n 40.979898069620155\n ],\n [\n -71.619873046875,\n 41.52502957323801\n ],\n [\n -71.4111328125,\n 41.16211393939692\n ],\n [\n -73.8885498046875,\n 40.78054143186031\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"21","issue":"8","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationDate":"2013-09-20","publicationStatus":"PW","scienceBaseUri":"54dd2be5e4b08de9379b3554","contributors":{"authors":[{"text":"Young, Caitlin","contributorId":30181,"corporation":false,"usgs":false,"family":"Young","given":"Caitlin","email":"","affiliations":[],"preferred":false,"id":537672,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kroeger, Kevin D. 0000-0002-4272-2349 kkroeger@usgs.gov","orcid":"https://orcid.org/0000-0002-4272-2349","contributorId":1603,"corporation":false,"usgs":true,"family":"Kroeger","given":"Kevin","email":"kkroeger@usgs.gov","middleInitial":"D.","affiliations":[{"id":41100,"text":"Coastal and Marine Hazards and Resources Program","active":true,"usgs":true}],"preferred":true,"id":537671,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hanson, Gilbert","contributorId":65913,"corporation":false,"usgs":true,"family":"Hanson","given":"Gilbert","email":"","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":537673,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70123836,"text":"70123836 - 2013 - Multiple factors affect a population of Agassiz's desert tortoise (Gopherus agassizii) in the Northwestern Mojave Desert","interactions":[],"lastModifiedDate":"2014-09-09T14:30:55","indexId":"70123836","displayToPublicDate":"2013-11-28T14:28:28","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1896,"text":"Herpetological Monographs","active":true,"publicationSubtype":{"id":10}},"title":"Multiple factors affect a population of Agassiz's desert tortoise (Gopherus agassizii) in the Northwestern Mojave Desert","docAbstract":"Numerous factors have contributed to declines in populations of the federally threatened Agassiz's Desert Tortoise (Gopherus agassizii) and continue to limit recovery. In 2010, we surveyed a low-density population on a military test facility in the northwestern Mojave Desert of California, USA, to evaluate population status and identify potential factors contributing to distribution and low densities. Estimated densities of live tortoises ranged spatially from 1.2/km2 to 15.1/km2. Although only one death of a breeding-age tortoise was recorded for the 4-yr period prior to the survey, remains of 16 juvenile and immature tortoises were found, and most showed signs of predation by Common Ravens (Corvus corax) and mammals. Predation may have limited recruitment of young tortoises into the adult size classes. To evaluate the relative importance of different types of impacts to tortoises, we developed predictive models for spatially explicit densities of tortoise sign and live tortoises using topography (i.e., slope), predators (Common Raven, signs of mammalian predators), and anthropogenic impacts (distances from paved road and denuded areas, density of ordnance fragments) as covariates. Models suggest that densities of tortoise sign increased with slope and signs of mammalian predators and decreased with Common Ravens, while also varying based on interaction effects involving these predictors as well as distances from paved roads, denuded areas, and ordnance. Similarly, densities of live tortoises varied by interaction effects among distances to denuded areas and paved roads, density of ordnance fragments, and slope. Thus multiple factors predict the densities and distribution of this population.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Herpetological Monographs","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Herpetologists' League","publisherLocation":"Washington, D.C.","doi":"10.1655/HERPMONOGRAPHS-D-13-00002","usgsCitation":"Berry, K.H., Yee, J.L., Coble, A., Perry, W.M., and Shields, T., 2013, Multiple factors affect a population of Agassiz's desert tortoise (Gopherus agassizii) in the Northwestern Mojave Desert: Herpetological Monographs, v. 27, no. 1, p. 87-109, https://doi.org/10.1655/HERPMONOGRAPHS-D-13-00002.","productDescription":"23 p.","startPage":"87","endPage":"109","numberOfPages":"23","ipdsId":"IP-051403","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":293553,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":293552,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1655/HERPMONOGRAPHS-D-13-00002"}],"country":"United States","state":"California;Nevada","otherGeospatial":"Mojave Desert","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -117.9789,34.1607 ], [ -117.9789,37.5219 ], [ -114.7254,37.5219 ], [ -114.7254,34.1607 ], [ -117.9789,34.1607 ] ] ] } } ] }","volume":"27","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5410146de4b07ab1cd980a50","contributors":{"authors":[{"text":"Berry, Kristin H. 0000-0003-1591-8394 kristin_berry@usgs.gov","orcid":"https://orcid.org/0000-0003-1591-8394","contributorId":437,"corporation":false,"usgs":true,"family":"Berry","given":"Kristin","email":"kristin_berry@usgs.gov","middleInitial":"H.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":500364,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Yee, Julie L. 0000-0003-1782-157X julie_yee@usgs.gov","orcid":"https://orcid.org/0000-0003-1782-157X","contributorId":3246,"corporation":false,"usgs":true,"family":"Yee","given":"Julie","email":"julie_yee@usgs.gov","middleInitial":"L.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":500365,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Coble, Ashley A.","contributorId":30551,"corporation":false,"usgs":true,"family":"Coble","given":"Ashley A.","affiliations":[],"preferred":false,"id":500367,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Perry, William M. 0000-0002-6180-8180 wmperry@usgs.gov","orcid":"https://orcid.org/0000-0002-6180-8180","contributorId":5124,"corporation":false,"usgs":true,"family":"Perry","given":"William","email":"wmperry@usgs.gov","middleInitial":"M.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":500366,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Shields, Timothy A.","contributorId":67424,"corporation":false,"usgs":true,"family":"Shields","given":"Timothy A.","affiliations":[],"preferred":false,"id":500368,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70193157,"text":"70193157 - 2013 - Public lakes, private lakeshore: Modeling protection of native aquatic plants","interactions":[],"lastModifiedDate":"2017-12-05T10:27:39","indexId":"70193157","displayToPublicDate":"2013-11-28T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1547,"text":"Environmental Management","active":true,"publicationSubtype":{"id":10}},"title":"Public lakes, private lakeshore: Modeling protection of native aquatic plants","docAbstract":"Protection of native aquatic plants is an important proenvironmental behavior, because plant loss coupled with nutrient loading can produce changes in lake ecosystems. Removal of aquatic plants by lakeshore property owners is a diffuse behavior that may lead to cumulative impacts on lake ecosystems. This class of behavior is challenging to manage because collective impacts are not obvious to the actors. This paper distinguishes positive and negative beliefs about aquatic plants, in models derived from norm activation theory (Schwartz, Adv Exp Soc Psychol 10:221–279, 1977) and the theory of reasoned action (Fishbein and Ajzen, Belief, attitude, intention, and behavior: an introduction to theory and research, Addison-Wesley, Boston 1975), to examine protection of native aquatic plants by Minnesota lakeshore property owners. We clarify how positive and negative evaluations of native aquatic plants affect protection or removal of these plants. Results are based on a mail survey (n = 3,115). Results suggest that positive evaluations of aquatic plants (i.e., as valuable to lake ecology) may not connect with the global attitudes and behavioral intentions that direct plant protection or removal. Lakeshore property owners’ behavior related to aquatic plants may be driven more by tangible personal benefits derived from accessible, carefully managed lakeshore than intentional action taken to sustain lake ecosystems. The limited connection of positive evaluations of aquatic plants to global attitudes and behavioral intentions may reflect either lack of knowledge of what actions are needed to protect lake health and/or unwillingness to lose perceived benefits derived from lakeshore property.
","language":"English","publisher":"Springer","doi":"10.1007/s00267-013-0054-4","usgsCitation":"Schroeder, S., and Fulton, D.C., 2013, Public lakes, private lakeshore: Modeling protection of native aquatic plants: Environmental Management, v. 52, no. 1, p. 99-112, https://doi.org/10.1007/s00267-013-0054-4.","productDescription":"13 p.","startPage":"99","endPage":"112","ipdsId":"IP-019500","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":349655,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Minnesota","volume":"52","issue":"1","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2013-04-23","publicationStatus":"PW","scienceBaseUri":"5a61029ce4b06e28e9c25472","contributors":{"authors":[{"text":"Schroeder, Susan A.","contributorId":201106,"corporation":false,"usgs":false,"family":"Schroeder","given":"Susan A.","affiliations":[],"preferred":false,"id":724355,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fulton, David C. 0000-0001-5763-7887 dcf@usgs.gov","orcid":"https://orcid.org/0000-0001-5763-7887","contributorId":2208,"corporation":false,"usgs":true,"family":"Fulton","given":"David","email":"dcf@usgs.gov","middleInitial":"C.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":718105,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70048377,"text":"sim3269 - 2013 - Flood-inundation maps for the Elkhart River at Goshen, Indiana","interactions":[],"lastModifiedDate":"2013-11-27T11:05:42","indexId":"sim3269","displayToPublicDate":"2013-11-27T10:43:47","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3269","title":"Flood-inundation maps for the Elkhart River at Goshen, Indiana","docAbstract":"The U.S. Geological Survey (USGS), in cooperation with the Indiana Office of Community and Rural Affairs, created digital flood-inundation maps for an 8.3-mile reach of the Elkhart River at Goshen, Indiana, extending from downstream of the Goshen Dam to downstream from County Road 17. The inundation maps, which can be accessed through the USGS Flood Inundation Mapping Science Web site at http://water.usgs.gov/osw/flood_inundation/, depict estimates of the areal extent and depth of flooding corresponding to nine selected water levels (stages) at the USGS streamgage at Elkhart River at Goshen (station number 04100500). Current conditions for the USGS streamgages in Indiana may be obtained on the Internet at http://waterdata.usgs.gov/. In addition, stream stage data have been provided to the National Weather Service (NWS) for incorporation into their Advanced Hydrologic Prediction Service (AHPS) flood warning system (http://water.weather.gov/ahps/). The NWS forecasts flood hydrographs at many places that are often colocated with USGS streamgages. NWS-forecasted peak-stage information may be used in conjunction with the maps developed in this study to show predicted areas of flood inundation. In this study, flood profiles were computed for the stream reach by means of a one-dimensional step-backwater model. The model was calibrated using the most current stage-discharge relation at the Elkhart River at Goshen streamgage. The hydraulic model was then used to compute nine water-surface profiles for flood stages at 1-foot (ft) intervals referenced to the streamgage datum and ranging from approximately bankfull (5 ft) to greater than the highest recorded water level (13 ft). The simulated water-surface profiles were then combined with a geographic information system (GIS) digital-elevation model (DEM), derived from Light Detection and Ranging (LiDAR) data having a 0.37-ft vertical accuracy and 3.9-ft horizontal resolution in order to delineate the area flooded at each water level. The availability of these maps, along with Internet information regarding current stage from USGS streamgages and forecasted stream stages from the NWS, provide emergency management personnel and residents with information that is critical for flood response activities such as evacuations and road closures as well as for postflood recovery efforts.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3269","collaboration":"Prepared in cooperation with the Indiana Office of Community and Rural Affairs","usgsCitation":"Strauch, K.R., 2013, Flood-inundation maps for the Elkhart River at Goshen, Indiana: U.S. Geological Survey Scientific Investigations Map 3269, Pamphlet: vi, 7 p.; Map sheets JPEG and PDF; Downloads Directory, https://doi.org/10.3133/sim3269.","productDescription":"Pamphlet: vi, 7 p.; Map sheets JPEG and PDF; Downloads Directory","numberOfPages":"18","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-042153","costCenters":[{"id":346,"text":"Indiana Water Science Center","active":true,"usgs":true}],"links":[{"id":279862,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sim3269.jpg"},{"id":279860,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3269/downloads/mapsheets/pdf/"},{"id":279861,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/sim/3269/downloads/"},{"id":279859,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3269/pdf/sim3269-pamphlet.pdf"},{"id":279314,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sim/3269/"}],"projection":"Indiana State Plane Eastern Zone","datum":"North American Datum of 1983","country":"United States","state":"Indiana","otherGeospatial":"Elkhart River","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -85.9,41.5583 ], [ -85.9,41.625 ], [ -85.83,41.625 ], [ -85.83,41.5583 ], [ -85.9,41.5583 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"529716b9e4b08e44bf66fb7d","contributors":{"authors":[{"text":"Strauch, Kellan R. 0000-0002-7218-2099 kstrauch@usgs.gov","orcid":"https://orcid.org/0000-0002-7218-2099","contributorId":1006,"corporation":false,"usgs":true,"family":"Strauch","given":"Kellan","email":"kstrauch@usgs.gov","middleInitial":"R.","affiliations":[{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true}],"preferred":true,"id":484482,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70048541,"text":"70048541 - 2013 - Modeling the effects of fire severity and climate warming on active layer and soil carbon dynamics of black spruce forests across the landscape in interior Alaska","interactions":[],"lastModifiedDate":"2013-11-26T14:23:38","indexId":"70048541","displayToPublicDate":"2013-11-26T11:19:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1562,"text":"Environmental Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Modeling the effects of fire severity and climate warming on active layer and soil carbon dynamics of black spruce forests across the landscape in interior Alaska","docAbstract":"There is a substantial amount of carbon stored in the permafrost soils of boreal forest ecosystems, where it is currently protected from decomposition. The surface organic horizons insulate the deeper soil from variations in atmospheric temperature. The removal of these insulating horizons through consumption by fire increases the vulnerability of permafrost to thaw, and the carbon stored in permafrost to decomposition. In this study we ask how warming and fire regime may influence spatial and temporal changes in active layer and carbon dynamics across a boreal forest landscape in interior Alaska. To address this question, we (1) developed and tested a predictive model of the effect of fire severity on soil organic horizons that depends on landscape-level conditions and (2) used this model to evaluate the long-term consequences of warming and changes in fire regime on active layer and soil carbon dynamics of black spruce forests across interior Alaska. The predictive model of fire severity, designed from the analysis of field observations, reproduces the effect of local topography (landform category, the slope angle and aspect and flow accumulation), weather conditions (drought index, soil moisture) and fire characteristics (day of year and size of the fire) on the reduction of the organic layer caused by fire. The integration of the fire severity model into an ecosystem process-based model allowed us to document the relative importance and interactions among local topography, fire regime and climate warming on active layer and soil carbon dynamics. Lowlands were more resistant to severe fires and climate warming, showing smaller increases in active layer thickness and soil carbon loss compared to drier flat uplands and slopes. In simulations that included the effects of both warming and fire at the regional scale, fire was primarily responsible for a reduction in organic layer thickness of 0.06 m on average by 2100 that led to an increase in active layer thickness of 1.1 m on average by 2100. The combination of warming and fire led to a simulated cumulative loss of 9.6 kgC m−2 on average by 2100. Our analysis suggests that ecosystem carbon storage in boreal forests in interior Alaska is particularly vulnerable, primarily due to the combustion of organic layer thickness in fire and the related increase in active layer thickness that exposes previously protected permafrost soil carbon to decomposition.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Environmental Research Letters","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"IOP Publishing","doi":"10.1088/1748-9326/8/4/045016","usgsCitation":"Genet, H., McGuire, A.D., Barrett, K., Breen, A., Euskirchen, E., Johnstone, J., Kasischke, E., Melvin, A., Bennett, A., Mack, M., Rupp, T., Schuur, A., Turetsky, M., and Yuan, F., 2013, Modeling the effects of fire severity and climate warming on active layer and soil carbon dynamics of black spruce forests across the landscape in interior Alaska: Environmental Research Letters, v. 8, no. 4, 13 p., https://doi.org/10.1088/1748-9326/8/4/045016.","productDescription":"13 p.","numberOfPages":"13","ipdsId":"IP-049470","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":473432,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1088/1748-9326/8/4/045016","text":"Publisher Index Page"},{"id":279848,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":279842,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1088/1748-9326/8/4/045016"}],"country":"United States","state":"Alaska","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -150.64,63.59 ], [ -150.64,67.71 ], [ -141.02,67.71 ], [ -141.02,63.59 ], [ -150.64,63.59 ] ] ] } } ] 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A.E.G.","contributorId":7169,"corporation":false,"usgs":true,"family":"Schuur","given":"A.E.G.","email":"","affiliations":[],"preferred":false,"id":485006,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Turetsky, M.R.","contributorId":107470,"corporation":false,"usgs":true,"family":"Turetsky","given":"M.R.","email":"","affiliations":[],"preferred":false,"id":485018,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Yuan, F.","contributorId":104287,"corporation":false,"usgs":true,"family":"Yuan","given":"F.","email":"","affiliations":[],"preferred":false,"id":485017,"contributorType":{"id":1,"text":"Authors"},"rank":14}]}} ,{"id":70048493,"text":"70048493 - 2013 - Modeling earthquake rate changes in Oklahoma and Arkansas: possible signatures of induced seismicity","interactions":[],"lastModifiedDate":"2014-05-06T09:00:10","indexId":"70048493","displayToPublicDate":"2013-11-26T10:34:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"Modeling earthquake rate changes in Oklahoma and Arkansas: possible signatures of induced seismicity","docAbstract":"The rate of ML≥3 earthquakes in the central and eastern United States increased beginning in 2009, particularly in Oklahoma and central Arkansas, where fluid injection has occurred. We find evidence that suggests these rate increases are man‐made by examining the rate changes in a catalog of ML≥3 earthquakes in Oklahoma, which had a low background seismicity rate before 2009, as well as rate changes in a catalog of ML≥2.2 earthquakes in central Arkansas, which had a history of earthquake swarms prior to the start of injection in 2009. In both cases, stochastic epidemic‐type aftershock sequence models and statistical tests demonstrate that the earthquake rate change is statistically significant, and both the background rate of independent earthquakes and the aftershock productivity must increase in 2009 to explain the observed increase in seismicity. This suggests that a significant change in the underlying triggering process occurred. Both parameters vary, even when comparing natural to potentially induced swarms in Arkansas, which suggests that changes in both the background rate and the aftershock productivity may provide a way to distinguish man‐made from natural earthquake rate changes. In Arkansas we also compare earthquake and injection well locations, finding that earthquakes within 6 km of an active injection well tend to occur closer together than those that occur before, after, or far from active injection. Thus, like a change in productivity, a change in interevent distance distribution may also be an indicator of induced seismicity.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Bulletin of the Seismological Society of America","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120130017","usgsCitation":"Llenos, A.L., and Michael, A.J., 2013, Modeling earthquake rate changes in Oklahoma and Arkansas: possible signatures of induced seismicity: Bulletin of the Seismological Society of America, v. 103, no. 5, p. 2850-2861, https://doi.org/10.1785/0120130017.","productDescription":"12 p.","startPage":"2850","endPage":"2861","numberOfPages":"12","ipdsId":"IP-043592","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":279792,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":279791,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1785/0120130017"}],"country":"United States","state":"Arkansas;Oklahoma","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -102.88,33.03 ], [ -102.88,36.91 ], [ -89.54,36.91 ], [ -89.54,33.03 ], [ -102.88,33.03 ] ] ] } } ] }","volume":"103","issue":"5","noUsgsAuthors":false,"publicationDate":"2013-09-30","publicationStatus":"PW","scienceBaseUri":"5295c2ffe4b0becc369c7ce7","contributors":{"authors":[{"text":"Llenos, Andrea L. 0000-0002-4088-6737 allenos@usgs.gov","orcid":"https://orcid.org/0000-0002-4088-6737","contributorId":4455,"corporation":false,"usgs":true,"family":"Llenos","given":"Andrea","email":"allenos@usgs.gov","middleInitial":"L.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":484833,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Michael, Andrew J. 0000-0002-2403-5019 michael@usgs.gov","orcid":"https://orcid.org/0000-0002-2403-5019","contributorId":1280,"corporation":false,"usgs":true,"family":"Michael","given":"Andrew","email":"michael@usgs.gov","middleInitial":"J.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true}],"preferred":true,"id":484832,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ]}