{"pageNumber":"443","pageRowStart":"11050","pageSize":"25","recordCount":40797,"records":[{"id":70185708,"text":"70185708 - 2017 - Divergent surface and total soil moisture projections under global warming","interactions":[],"lastModifiedDate":"2017-03-28T10:02:43","indexId":"70185708","displayToPublicDate":"2017-03-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Divergent surface and total soil moisture projections under global warming","docAbstract":"

Land aridity has been projected to increase with global warming. Such projections are mostly based on off-line aridity and drought metrics applied to climate model outputs but also are supported by climate-model projections of decreased surface soil moisture. Here we comprehensively analyze soil moisture projections from the Coupled Model Intercomparison Project phase 5, including surface, total, and layer-by-layer soil moisture. We identify a robust vertical gradient of projected mean soil moisture changes, with more negative changes near the surface. Some regions of the northern middle to high latitudes exhibit negative annual surface changes but positive total changes. We interpret this behavior in the context of seasonal changes in the surface water budget. This vertical pattern implies that the extensive drying predicted by off-line drought metrics, while consistent with the projected decline in surface soil moisture, will tend to overestimate (negatively) changes in total soil water availability.

","language":"English","publisher":"American Geophysical Union","doi":"10.1002/2016GL071921","usgsCitation":"Berg, A., Sheffield, J., and Milly, P., 2017, Divergent surface and total soil moisture projections under global warming: Geophysical Research Letters, v. 44, no. 1, p. 236-244, https://doi.org/10.1002/2016GL071921.","productDescription":"9 p.","startPage":"236","endPage":"244","ipdsId":"IP-082638","costCenters":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"links":[{"id":470051,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2016gl071921","text":"Publisher Index Page"},{"id":338440,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"44","issue":"1","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2017-01-13","publicationStatus":"PW","scienceBaseUri":"58db7631e4b0ee37af29e49e","contributors":{"authors":[{"text":"Berg, Alexis","contributorId":187496,"corporation":false,"usgs":false,"family":"Berg","given":"Alexis","email":"","affiliations":[],"preferred":false,"id":686481,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sheffield, Justin","contributorId":189922,"corporation":false,"usgs":false,"family":"Sheffield","given":"Justin","email":"","affiliations":[],"preferred":false,"id":686482,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Milly, Paul C.D. 0000-0003-4389-3139 cmilly@usgs.gov","orcid":"https://orcid.org/0000-0003-4389-3139","contributorId":2119,"corporation":false,"usgs":true,"family":"Milly","given":"Paul C.D.","email":"cmilly@usgs.gov","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":false,"id":686480,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70189627,"text":"70189627 - 2017 - Broadband seismic noise attenuation versus depth at the Albuquerque Seismological Laboratory","interactions":[],"lastModifiedDate":"2018-03-29T11:32:05","indexId":"70189627","displayToPublicDate":"2017-03-01T00:00:00","publicationYear":"2017","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":"Broadband seismic noise attenuation versus depth at the Albuquerque Seismological Laboratory","docAbstract":"

Seismic noise induced by atmospheric processes such as wind and pressure changes can be a major contributor to the background noise observed in many seismograph stations, especially those installed at or near the surface. Cultural noise such as vehicle traffic or nearby buildings with air handling equipment also contributes to seismic background noise. Such noise sources fundamentally limit our ability to resolve earthquake‐generated signals. Many previous seismic noise versus depth studies focused separately on either high‐frequency (&gt;1&#x2009;&#x2009;Hz\">>1  Hz) or low‐frequency (&lt;0.05&#x2009;&#x2009;Hz\"><0.05  Hz) bands. In this study, we use modern high‐quality broadband (BB) and very broadband (VBB) seismometers installed at depths ranging from 1.5 to 188 m at the Albuquerque Seismological Laboratory to evaluate noise attenuation as a function of depth over a broad range of frequencies (0.002–50 Hz). Many modern seismometer deployments use BB or VBB seismometers installed at various depths, depending on the application. These depths range from one‐half meter or less in aftershock study deployments, to one or two meters in the Incorporated Research Institutions for Seismology Transportable Array (TA), to a few meters (shallow surface vaults) up to 100 m or more (boreholes) in the permanent observatories of the Global Seismographic Network (GSN). It is important for managers and planners of these and similar arrays and networks of seismograph stations to understand the attenuation of surface‐generated noise versus depth so that they can achieve desired performance goals within their budgets as well as their frequency band of focus. The results of this study will assist in decisions regarding BB and VBB seismometer installation depths. In general, we find that greater installation depths are better and seismometer emplacement in hard rock is better than in soil. Attenuation for any given depth varies with frequency. More specifically, we find that the dependence of depth will be application dependent based on the frequency band and sensitive axes of interest. For quick deployments (like aftershock studies), 1 m may be deep enough to produce good data, especially when the focus is on vertical data where temperature stability fundamentally limits the low‐frequency noise levels and little low‐frequency data will be used. For temporary (medium‐term) deployments (e.g., TA) where low cost can be very important, 2–3 m should be sufficient, but such shallow installations will limit the ability to resolve low‐frequency signals, especially on horizontal components. Of course, one should try for maximum burial depth within the budget when there is interest in using the data for low‐frequency applications. For long‐term deployments like the permanent observatories of the GSN and similar networks, 100–200 m depth in hard rock is desirable to achieve lowest noise, although 30–60 m may be acceptable.

","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120160187","usgsCitation":"Hutt, C.R., Ringler, A.T., and Gee, L., 2017, Broadband seismic noise attenuation versus depth at the Albuquerque Seismological Laboratory: Bulletin of the Seismological Society of America, v. 107, no. 3, p. 1402-1412, https://doi.org/10.1785/0120160187.","productDescription":"11 p.","startPage":"1402","endPage":"1412","ipdsId":"IP-082061","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":352932,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"107","issue":"3","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2017-03-21","publicationStatus":"PW","scienceBaseUri":"5afee8c4e4b0da30c1bfc4a4","contributors":{"authors":[{"text":"Hutt, Charles R. 0000-0001-9033-9195 bhutt@usgs.gov","orcid":"https://orcid.org/0000-0001-9033-9195","contributorId":1622,"corporation":false,"usgs":true,"family":"Hutt","given":"Charles","email":"bhutt@usgs.gov","middleInitial":"R.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":705487,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ringler, Adam T. 0000-0002-9839-4188 aringler@usgs.gov","orcid":"https://orcid.org/0000-0002-9839-4188","contributorId":145576,"corporation":false,"usgs":true,"family":"Ringler","given":"Adam","email":"aringler@usgs.gov","middleInitial":"T.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":705488,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gee, Lind 0000-0003-2883-9847 lgee@usgs.gov","orcid":"https://orcid.org/0000-0003-2883-9847","contributorId":193064,"corporation":false,"usgs":true,"family":"Gee","given":"Lind","email":"lgee@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":705489,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70193265,"text":"70193265 - 2017 - Integrating multiple data sources in species distribution modeling: A framework for data fusion","interactions":[],"lastModifiedDate":"2018-12-20T12:52:54","indexId":"70193265","displayToPublicDate":"2017-03-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1465,"text":"Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Integrating multiple data sources in species distribution modeling: A framework for data fusion","docAbstract":"

The last decade has seen a dramatic increase in the use of species distribution models (SDMs) to characterize patterns of species’ occurrence and abundance. Efforts to parameterize SDMs often create a tension between the quality and quantity of data available to fit models. Estimation methods that integrate both standardized and non-standardized data types offer a potential solution to the tradeoff between data quality and quantity. Recently several authors have developed approaches for jointly modeling two sources of data (one of high quality and one of lesser quality). We extend their work by allowing for explicit spatial autocorrelation in occurrence and detection error using a Multivariate Conditional Autoregressive (MVCAR) model and develop three models that share information in a less direct manner resulting in more robust performance when the auxiliary data is of lesser quality. We describe these three new approaches (“Shared,” “Correlation,” “Covariates”) for combining data sources and show their use in a case study of the Brown-headed Nuthatch in the Southeastern U.S. and through simulations. All three of the approaches which used the second data source improved out-of-sample predictions relative to a single data source (“Single”). When information in the second data source is of high quality, the Shared model performs the best, but the Correlation and Covariates model also perform well. When the information quality in the second data source is of lesser quality, the Correlation and Covariates model performed better suggesting they are robust alternatives when little is known about auxiliary data collected opportunistically or through citizen scientists. Methods that allow for both data types to be used will maximize the useful information available for estimating species distributions.

","language":"English","publisher":"Wiley","doi":"10.1002/ecy.1710","usgsCitation":"Pacifici, K., Reich, B.J., Miller, D.A., Gardner, B., Stauffer, G.E., Singh, S., McKerrow, A., and Collazo, J., 2017, Integrating multiple data sources in species distribution modeling: A framework for data fusion: Ecology, v. 98, no. 3, p. 840-850, https://doi.org/10.1002/ecy.1710.","productDescription":"11 p.","startPage":"840","endPage":"850","ipdsId":"IP-073421","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":208,"text":"Core Science Analytics and Synthesis","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":470049,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecy.1710","text":"Publisher Index Page"},{"id":348018,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"98","issue":"3","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59fadd24e4b0531197b13cad","contributors":{"authors":[{"text":"Pacifici, Krishna","contributorId":26564,"corporation":false,"usgs":false,"family":"Pacifici","given":"Krishna","email":"","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":719048,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Reich, Brian J.","contributorId":150871,"corporation":false,"usgs":false,"family":"Reich","given":"Brian","email":"","middleInitial":"J.","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":719049,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Miller, David A.W. davidmiller@usgs.gov","contributorId":4043,"corporation":false,"usgs":true,"family":"Miller","given":"David","email":"davidmiller@usgs.gov","middleInitial":"A.W.","affiliations":[{"id":7260,"text":"Pennsylvania State University","active":true,"usgs":false},{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":719050,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gardner, Beth","contributorId":91612,"corporation":false,"usgs":false,"family":"Gardner","given":"Beth","affiliations":[{"id":13553,"text":"University of Washington-Seattle","active":true,"usgs":false}],"preferred":false,"id":719051,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Stauffer, Glenn E.","contributorId":171536,"corporation":false,"usgs":false,"family":"Stauffer","given":"Glenn","email":"","middleInitial":"E.","affiliations":[{"id":7260,"text":"Pennsylvania State University","active":true,"usgs":false}],"preferred":false,"id":719052,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Singh, Susheela","contributorId":11646,"corporation":false,"usgs":false,"family":"Singh","given":"Susheela","email":"","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":719061,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"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":719062,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"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":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":false,"id":719063,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70188344,"text":"70188344 - 2017 - Toppling analysis of the Echo Cliffs precariously balanced rock","interactions":[],"lastModifiedDate":"2022-11-02T14:00:48.646049","indexId":"70188344","displayToPublicDate":"2017-03-01T00:00:00","publicationYear":"2017","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":"Toppling analysis of the Echo Cliffs precariously balanced rock","docAbstract":"

Toppling analysis of a precariously balanced rock (PBR) can provide insight into the nature of ground motion that has not occurred at that location in the past and, by extension, can constrain peak ground motions for use in engineering design. Earlier approaches have targeted 2D models of the rock or modeled the rock–pedestal contact using spring‐damper assemblies that require recalibration for each rock. Here, a method to model PBRs in 3D is presented through a case study of the Echo Cliffs PBR. The 3D model is created from a point cloud of the rock, the pedestal, and their interface, obtained using terrestrial laser scanning. The dynamic response of the model under earthquake excitation is simulated using a rigid‐body dynamics algorithm. The veracity of this approach is demonstrated through comparisons against data from shake‐table experiments. Fragility maps for toppling probability of the Echo Cliffs PBR as a function of various ground‐motion parameters, rock–pedestal interface friction coefficient, and excitation direction are presented. These fragility maps indicate that the toppling probability of this rock is low (less than 0.2) for peak ground acceleration (PGA) and peak ground velocity (PGV) lower than 3  m/s2 and 0.75  m/s, respectively, suggesting that the ground‐motion intensities at this location from earthquakes on nearby faults have most probably not exceeded the above‐mentioned PGA and PGV during the age of the PBR. Additionally, the fragility maps generated from this methodology can also be directly coupled with existing probabilistic frameworks to obtain direct constraints on unexceeded ground motion at a PBR’s location.

","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120160169","usgsCitation":"Veeraraghavan, S., Hudnut, K.W., and Krishnan, S., 2017, Toppling analysis of the Echo Cliffs precariously balanced rock: Bulletin of the Seismological Society of America, v. 107, no. 1, p. 72-84, https://doi.org/10.1785/0120160169.","productDescription":"13 p.","startPage":"72","endPage":"84","ipdsId":"IP-078915","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":470046,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://resolver.caltech.edu/CaltechAUTHORS:20161213-141035303","text":"External Repository"},{"id":342189,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Echo Cliffs precariously balanced rock","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -118.92706014090601,\n 34.12673669928829\n ],\n [\n -118.92706014090601,\n 34.12580082827124\n ],\n [\n -118.92597045637072,\n 34.12580082827124\n ],\n [\n -118.92597045637072,\n 34.12673669928829\n ],\n [\n -118.92706014090601,\n 34.12673669928829\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"107","issue":"1","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-12-13","publicationStatus":"PW","scienceBaseUri":"5937bf2de4b0f6c2d0d9c75b","contributors":{"authors":[{"text":"Veeraraghavan, Swetha","contributorId":192670,"corporation":false,"usgs":false,"family":"Veeraraghavan","given":"Swetha","email":"","affiliations":[],"preferred":false,"id":697334,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hudnut, Kenneth W. 0000-0002-3168-4797 hudnut@usgs.gov","orcid":"https://orcid.org/0000-0002-3168-4797","contributorId":2550,"corporation":false,"usgs":true,"family":"Hudnut","given":"Kenneth","email":"hudnut@usgs.gov","middleInitial":"W.","affiliations":[{"id":508,"text":"Office of the AD Hazards","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":697333,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Krishnan, Swaminathan","contributorId":192671,"corporation":false,"usgs":false,"family":"Krishnan","given":"Swaminathan","email":"","affiliations":[],"preferred":false,"id":697335,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70195838,"text":"70195838 - 2017 - Rapid carbon loss and slow recovery following permafrost thaw in boreal peatlands","interactions":[],"lastModifiedDate":"2018-03-06T11:16:30","indexId":"70195838","displayToPublicDate":"2017-03-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1837,"text":"Global Change Biology","active":true,"publicationSubtype":{"id":10}},"title":"Rapid carbon loss and slow recovery following permafrost thaw in boreal peatlands","docAbstract":"

Permafrost peatlands store one-third of the total carbon (C) in the atmosphere and are increasingly vulnerable to thaw as high-latitude temperatures warm. Large uncertainties remain about C dynamics following permafrost thaw in boreal peatlands. We used a chronosequence approach to measure C stocks in forested permafrost plateaus (forest) and thawed permafrost bogs, ranging in thaw age from young (<10 years) to old (>100 years) from two interior Alaska chronosequences. Permafrost originally aggraded simultaneously with peat accumulation (syngenetic permafrost) at both sites. We found that upon thaw, C loss of the forest peat C is equivalent to ~30% of the initial forest C stock and is directly proportional to the prethaw C stocks. Our model results indicate that permafrost thaw turned these peatlands into net C sources to the atmosphere for a decade following thaw, after which post-thaw bog peat accumulation returned sites to net C sinks. It can take multiple centuries to millennia for a site to recover its prethaw C stocks; the amount of time needed for them to regain their prethaw C stocks is governed by the amount of C that accumulated prior to thaw. Consequently, these findings show that older peatlands will take longer to recover prethaw C stocks, whereas younger peatlands will exceed prethaw stocks in a matter of centuries. We conclude that the loss of sporadic and discontinuous permafrost by 2100 could result in a loss of up to 24 Pg of deep C from permafrost peatlands.

","language":"English","publisher":"Wiley","doi":"10.1111/gcb.13403","usgsCitation":"Jones, M.C., Harden, J.W., O’Donnell, J.A., Manies, K.L., Jorgenson, M., Treat, C.C., and Ewing, S., 2017, Rapid carbon loss and slow recovery following permafrost thaw in boreal peatlands: Global Change Biology, v. 23, no. 3, p. 1109-1127, https://doi.org/10.1111/gcb.13403.","productDescription":"19 p.","startPage":"1109","endPage":"1127","ipdsId":"IP-075945","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":352258,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"23","issue":"3","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2016-10-15","publicationStatus":"PW","scienceBaseUri":"5afee8b9e4b0da30c1bfc496","contributors":{"authors":[{"text":"Jones, Miriam C. 0000-0002-6650-7619 miriamjones@usgs.gov","orcid":"https://orcid.org/0000-0002-6650-7619","contributorId":4056,"corporation":false,"usgs":true,"family":"Jones","given":"Miriam","email":"miriamjones@usgs.gov","middleInitial":"C.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":730234,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Harden, Jennifer W. 0000-0002-6570-8259 jharden@usgs.gov","orcid":"https://orcid.org/0000-0002-6570-8259","contributorId":1971,"corporation":false,"usgs":true,"family":"Harden","given":"Jennifer","email":"jharden@usgs.gov","middleInitial":"W.","affiliations":[{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":730235,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"O’Donnell, Jonathan A. 0000-0001-7031-9808","orcid":"https://orcid.org/0000-0001-7031-9808","contributorId":191423,"corporation":false,"usgs":false,"family":"O’Donnell","given":"Jonathan","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":730236,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Manies, Kristen L. 0000-0003-4941-9657 kmanies@usgs.gov","orcid":"https://orcid.org/0000-0003-4941-9657","contributorId":2136,"corporation":false,"usgs":true,"family":"Manies","given":"Kristen","email":"kmanies@usgs.gov","middleInitial":"L.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":730237,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jorgenson, M. Torre","contributorId":202940,"corporation":false,"usgs":false,"family":"Jorgenson","given":"M. Torre","affiliations":[{"id":36554,"text":"Ecoscience","active":true,"usgs":false}],"preferred":false,"id":730238,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Treat, Claire C.","contributorId":150798,"corporation":false,"usgs":false,"family":"Treat","given":"Claire","email":"","middleInitial":"C.","affiliations":[{"id":18105,"text":"University of New Hampshire, Durham","active":true,"usgs":false}],"preferred":false,"id":730239,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ewing, Stephanie","contributorId":202941,"corporation":false,"usgs":false,"family":"Ewing","given":"Stephanie","affiliations":[{"id":36555,"text":"Montana State University","active":true,"usgs":false}],"preferred":false,"id":730240,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70192085,"text":"70192085 - 2017 - South Polar Skua breeding populations in the Ross Sea assessed from demonstrated relationship with Adélie Penguin numbers","interactions":[],"lastModifiedDate":"2017-10-19T15:26:47","indexId":"70192085","displayToPublicDate":"2017-03-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3093,"text":"Polar Biology","active":true,"publicationSubtype":{"id":10}},"title":"South Polar Skua breeding populations in the Ross Sea assessed from demonstrated relationship with Adélie Penguin numbers","docAbstract":"

In the Ross Sea region, most South Polar Skuas (Stercorarius maccormicki) nest near Adélie Penguin (Pygoscelis adeliae) colonies, preying and scavenging on fish, penguins, and other carrion. To derive a relationship to predict skua numbers from better-quantified penguin numbers, we used distance sampling to estimate breeding skua numbers within 1000 m of 5 penguin nesting locations (Cape Crozier, Cape Royds, and 3 Cape Bird locations) on Ross Island in 3 consecutive years. Estimated numbers of skua breeding pairs were highest at Cape Crozier (270,000 penguin pairs; 1099 and 1347 skua pairs in 2 respective years) and lowest at Cape Royds (3000 penguin pairs; 45 skua pairs). The log–log linear relationship (R2 = 0.98) between pairs of skuas and penguins was highly significant, and most historical estimates of skua and penguin numbers in the Ross Sea were within 95 % prediction intervals of the regression. Applying our regression model to current Adélie Penguin colony sizes at 23 western Ross Sea locations predicted that 4635 pairs of skuas now breed within 1000 m of penguin colonies in the Ross Island metapopulation (including Beaufort Island) and northern Victoria Land. We estimate, using published skua estimates for elsewhere in Antarctica, that the Ross Sea South Polar Skua population comprises ~50 % of the world total, although this may be an overestimate because of incomplete data elsewhere. To improve predictions and enable measurement of future skua population change, we recommend additional South Polar Skua surveys using consistent distance-sampling methods at penguin colonies of a range of sizes.

","language":"English","publisher":"Springer","doi":"10.1007/s00300-016-1980-4","usgsCitation":"Wilson, D.J., Lyver, P.O., Greene, T.C., Whitehead, A.L., Dugger, K., Karl, B.J., Barringer, J.R., McGarry, R., Pollard, A.M., and Ainley, D.G., 2017, South Polar Skua breeding populations in the Ross Sea assessed from demonstrated relationship with Adélie Penguin numbers: Polar Biology, v. 40, no. 3, p. 577-592, https://doi.org/10.1007/s00300-016-1980-4.","productDescription":"16 p.","startPage":"577","endPage":"592","ipdsId":"IP-067093","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":346998,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":" Ross Island","volume":"40","issue":"3","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2016-06-08","publicationStatus":"PW","scienceBaseUri":"59e9b995e4b05fe04cd65ca2","contributors":{"authors":[{"text":"Wilson, Deborah J.","contributorId":197733,"corporation":false,"usgs":false,"family":"Wilson","given":"Deborah","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":714161,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lyver, Phil O’B.","contributorId":197706,"corporation":false,"usgs":false,"family":"Lyver","given":"Phil","email":"","middleInitial":"O’B.","affiliations":[],"preferred":false,"id":714162,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Greene, Terry C.","contributorId":197734,"corporation":false,"usgs":false,"family":"Greene","given":"Terry","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":714163,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Whitehead, Amy L.","contributorId":197735,"corporation":false,"usgs":false,"family":"Whitehead","given":"Amy","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":714164,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dugger, Katie M. 0000-0002-4148-246X cdugger@usgs.gov","orcid":"https://orcid.org/0000-0002-4148-246X","contributorId":4399,"corporation":false,"usgs":true,"family":"Dugger","given":"Katie","email":"cdugger@usgs.gov","middleInitial":"M.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":714109,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Karl, Brian J.","contributorId":197736,"corporation":false,"usgs":false,"family":"Karl","given":"Brian","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":714165,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Barringer, James R. F.","contributorId":197737,"corporation":false,"usgs":false,"family":"Barringer","given":"James","email":"","middleInitial":"R. F.","affiliations":[],"preferred":false,"id":714166,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"McGarry, Roger","contributorId":197738,"corporation":false,"usgs":false,"family":"McGarry","given":"Roger","email":"","affiliations":[],"preferred":false,"id":714167,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Pollard, Annie M.","contributorId":197739,"corporation":false,"usgs":false,"family":"Pollard","given":"Annie","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":714168,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Ainley, David G.","contributorId":32039,"corporation":false,"usgs":false,"family":"Ainley","given":"David","email":"","middleInitial":"G.","affiliations":[{"id":34154,"text":"Point Reyes Bird Observatory, Stinson Beach, CA","active":true,"usgs":false}],"preferred":false,"id":714169,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70193303,"text":"70193303 - 2017 - Evidence for early life in Earth’s oldest hydrothermal vent precipitates","interactions":[],"lastModifiedDate":"2017-11-01T13:58:14","indexId":"70193303","displayToPublicDate":"2017-03-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2840,"text":"Nature","active":true,"publicationSubtype":{"id":10}},"title":"Evidence for early life in Earth’s oldest hydrothermal vent precipitates","docAbstract":"

Although it is not known when or where life on Earth began, some of the earliest habitable environments may have been submarine-hydrothermal vents. Here we describe putative fossilized microorganisms that are at least 3,770 million and possibly 4,280 million years old in ferruginous sedimentary rocks, interpreted as seafloor-hydrothermal vent-related precipitates, from the Nuvvuagittuq belt in Quebec, Canada. These structures occur as micrometre-scale haematite tubes and filaments with morphologies and mineral assemblages similar to those of filamentous microorganisms from modern hydrothermal vent precipitates and analogous microfossils in younger rocks. The Nuvvuagittuq rocks contain isotopically light carbon in carbonate and carbonaceous material, which occurs as graphitic inclusions in diagenetic carbonate rosettes, apatite blades intergrown among carbonate rosettes and magnetite–haematite granules, and is associated with carbonate in direct contact with the putative microfossils. Collectively, these observations are consistent with an oxidized biomass and provide evidence for biological activity in submarine-hydrothermal environments more than 3,770 million years ago.

","language":"English","publisher":"Nature Publishing Group","doi":"10.1038/nature21377","usgsCitation":"Dodd, M.S., Papineau, D., Grenne, T., Slack, J.F., Rittner, M., Pirajno, F., O’Neil, J., and Little, C., 2017, Evidence for early life in Earth’s oldest hydrothermal vent precipitates: Nature, v. 543, p. 60-64, https://doi.org/10.1038/nature21377.","productDescription":"5 p.","startPage":"60","endPage":"64","ipdsId":"IP-077463","costCenters":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":348022,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada","state":"Quebec","otherGeospatial":"Nuvvuagittuq belt","volume":"543","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2017-03-02","publicationStatus":"PW","scienceBaseUri":"59fadd23e4b0531197b13ca4","contributors":{"authors":[{"text":"Dodd, Matthew S.","contributorId":199305,"corporation":false,"usgs":false,"family":"Dodd","given":"Matthew","email":"","middleInitial":"S.","affiliations":[{"id":35507,"text":"London Centre for Nanotechnology; Department of Earth Sciences, University College London","active":true,"usgs":false}],"preferred":false,"id":718602,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Papineau, Dominic","contributorId":199310,"corporation":false,"usgs":false,"family":"Papineau","given":"Dominic","email":"","affiliations":[{"id":35507,"text":"London Centre for Nanotechnology; Department of Earth Sciences, University College London","active":true,"usgs":false}],"preferred":false,"id":718603,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Grenne, Tor","contributorId":7460,"corporation":false,"usgs":false,"family":"Grenne","given":"Tor","email":"","affiliations":[{"id":35509,"text":"Geological Survey of Norway","active":true,"usgs":false}],"preferred":false,"id":718604,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Slack, John F. 0000-0001-6600-3130 jfslack@usgs.gov","orcid":"https://orcid.org/0000-0001-6600-3130","contributorId":1032,"corporation":false,"usgs":true,"family":"Slack","given":"John","email":"jfslack@usgs.gov","middleInitial":"F.","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":718601,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rittner, Martin","contributorId":199306,"corporation":false,"usgs":false,"family":"Rittner","given":"Martin","email":"","affiliations":[{"id":35508,"text":"Department of Earth Sciences, University College London","active":true,"usgs":false}],"preferred":false,"id":718606,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Pirajno, Franco","contributorId":199308,"corporation":false,"usgs":false,"family":"Pirajno","given":"Franco","email":"","affiliations":[{"id":35510,"text":"Centre for Exploration Targeting, The University of Western Australia","active":true,"usgs":false}],"preferred":false,"id":719092,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"O’Neil, Jonathan","contributorId":69333,"corporation":false,"usgs":false,"family":"O’Neil","given":"Jonathan","email":"","affiliations":[{"id":35511,"text":"Department of Earth and Environmental Sciences, University of Ottawa","active":true,"usgs":false}],"preferred":false,"id":719116,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Little, Crispin T.S.","contributorId":199307,"corporation":false,"usgs":false,"family":"Little","given":"Crispin T.S.","affiliations":[{"id":35453,"text":"University of Leeds, UK","active":true,"usgs":false}],"preferred":false,"id":719117,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70192616,"text":"70192616 - 2017 - The basis function approach for modeling autocorrelation in ecological data","interactions":[],"lastModifiedDate":"2017-11-10T11:17:00","indexId":"70192616","displayToPublicDate":"2017-03-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1465,"text":"Ecology","active":true,"publicationSubtype":{"id":10}},"title":"The basis function approach for modeling autocorrelation in ecological data","docAbstract":"

Analyzing ecological data often requires modeling the autocorrelation created by spatial and temporal processes. Many seemingly disparate statistical methods used to account for autocorrelation can be expressed as regression models that include basis functions. Basis functions also enable ecologists to modify a wide range of existing ecological models in order to account for autocorrelation, which can improve inference and predictive accuracy. Furthermore, understanding the properties of basis functions is essential for evaluating the fit of spatial or time-series models, detecting a hidden form of collinearity, and analyzing large data sets. We present important concepts and properties related to basis functions and illustrate several tools and techniques ecologists can use when modeling autocorrelation in ecological data.

","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecy.1674","usgsCitation":"Hefley, T.J., Broms, K.M., Brost, B.M., Buderman, F.E., Kay, S.L., Scharf, H., Tipton, J., Williams, P.J., and Hooten, M., 2017, The basis function approach for modeling autocorrelation in ecological data: Ecology, v. 98, no. 3, p. 632-646, https://doi.org/10.1002/ecy.1674.","productDescription":"15 p.","startPage":"632","endPage":"646","ipdsId":"IP-070118","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":470033,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://arxiv.org/abs/1606.05658","text":"External Repository"},{"id":348572,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"98","issue":"3","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a06c8cfe4b09af898c86138","contributors":{"authors":[{"text":"Hefley, Trevor J.","contributorId":147146,"corporation":false,"usgs":false,"family":"Hefley","given":"Trevor","email":"","middleInitial":"J.","affiliations":[{"id":16796,"text":"Dept Fish, Wildlife & Cons Biol, Colorado St Univ, Fort Collins, CO","active":true,"usgs":false}],"preferred":false,"id":721574,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Broms, Kristin M.","contributorId":171524,"corporation":false,"usgs":false,"family":"Broms","given":"Kristin","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":721575,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brost, Brian M.","contributorId":171484,"corporation":false,"usgs":false,"family":"Brost","given":"Brian","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":721576,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Buderman, Frances E.","contributorId":171634,"corporation":false,"usgs":false,"family":"Buderman","given":"Frances","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":721577,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kay, Shannon L.","contributorId":193049,"corporation":false,"usgs":false,"family":"Kay","given":"Shannon","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":721578,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Scharf, Henry","contributorId":200238,"corporation":false,"usgs":false,"family":"Scharf","given":"Henry","affiliations":[],"preferred":false,"id":721579,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Tipton, John","contributorId":166999,"corporation":false,"usgs":false,"family":"Tipton","given":"John","affiliations":[],"preferred":false,"id":721580,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Williams, Perry J.","contributorId":169058,"corporation":false,"usgs":false,"family":"Williams","given":"Perry","email":"","middleInitial":"J.","affiliations":[{"id":25400,"text":"U.S. Fish and Wildlife Service, Big Oaks National Wildlife Refuge","active":true,"usgs":false}],"preferred":false,"id":721581,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Hooten, Mevin 0000-0002-1614-723X mhooten@usgs.gov","orcid":"https://orcid.org/0000-0002-1614-723X","contributorId":2958,"corporation":false,"usgs":true,"family":"Hooten","given":"Mevin","email":"mhooten@usgs.gov","affiliations":[{"id":12963,"text":"Colorado Cooperative Fish and Wildlife Research Unit, Fort Collins, CO","active":true,"usgs":false},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":716562,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70195175,"text":"70195175 - 2017 - In-well time-of-travel approach to evaluate optimal purge duration during low-flow sampling of monitoring wells","interactions":[],"lastModifiedDate":"2018-02-07T13:18:25","indexId":"70195175","displayToPublicDate":"2017-03-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1534,"text":"Environmental Earth Sciences","active":true,"publicationSubtype":{"id":10}},"title":"In-well time-of-travel approach to evaluate optimal purge duration during low-flow sampling of monitoring wells","docAbstract":"

A common assumption with groundwater sampling is that low (<0.5 L/min) pumping rates during well purging and sampling captures primarily lateral flow from the formation through the well-screened interval at a depth coincident with the pump intake. However, if the intake is adjacent to a low hydraulic conductivity part of the screened formation, this scenario will induce vertical groundwater flow to the pump intake from parts of the screened interval with high hydraulic conductivity. Because less formation water will initially be captured during pumping, a substantial volume of water already in the well (preexisting screen water or screen storage) will be captured during this initial time until inflow from the high hydraulic conductivity part of the screened formation can travel vertically in the well to the pump intake. Therefore, the length of the time needed for adequate purging prior to sample collection (called optimal purge duration) is controlled by the in-well, vertical travel times. A preliminary, simple analytical model was used to provide information on the relation between purge duration and capture of formation water for different gross levels of heterogeneity (contrast between low and high hydraulic conductivity layers). The model was then used to compare these time–volume relations to purge data (pumping rates and drawdown) collected at several representative monitoring wells from multiple sites. Results showed that computation of time-dependent capture of formation water (as opposed to capture of preexisting screen water), which were based on vertical travel times in the well, compares favorably with the time required to achieve field parameter stabilization. If field parameter stabilization is an indicator of arrival time of formation water, which has been postulated, then in-well, vertical flow may be an important factor at wells where low-flow sampling is the sample method of choice.

","language":"English","publisher":"Springer","doi":"10.1007/s12665-017-6561-5","usgsCitation":"Harte, P.T., 2017, In-well time-of-travel approach to evaluate optimal purge duration during low-flow sampling of monitoring wells: Environmental Earth Sciences, v. 76, p. 1-13, https://doi.org/10.1007/s12665-017-6561-5.","productDescription":"Article 251; 13 p.","startPage":"1","endPage":"13","ipdsId":"IP-071519","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":351267,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"76","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationDate":"2017-03-21","publicationStatus":"PW","scienceBaseUri":"5a7c1e7ce4b00f54eb229355","contributors":{"authors":[{"text":"Harte, Philip T. 0000-0002-7718-1204 ptharte@usgs.gov","orcid":"https://orcid.org/0000-0002-7718-1204","contributorId":1008,"corporation":false,"usgs":true,"family":"Harte","given":"Philip","email":"ptharte@usgs.gov","middleInitial":"T.","affiliations":[{"id":405,"text":"NH/VT office of New England Water Science Center","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":727304,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70187613,"text":"70187613 - 2017 - Solving for source parameters using nested array data: A case study from the Canterbury, New Zealand earthquake sequence","interactions":[],"lastModifiedDate":"2019-12-17T09:32:50","indexId":"70187613","displayToPublicDate":"2017-03-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3208,"text":"Pure and Applied Geophysics","active":true,"publicationSubtype":{"id":10}},"title":"Solving for source parameters using nested array data: A case study from the Canterbury, New Zealand earthquake sequence","docAbstract":"

The seismic spectrum can be constructed by assuming a Brune spectral model and estimating the parameters of seismic moment (M0), corner frequency (fc), and high-frequency site attenuation (κ). Using seismic data collected during the 2010–2011 Canterbury, New Zealand, earthquake sequence, we apply the non-linear least-squares Gauss–Newton method, a deterministic downhill optimization technique, to simultaneously determine the M0, fc, and κ for each event-station pair. We fit the Brune spectral acceleration model to Fourier-transformed S-wave records following application of path and site corrections to the data. For each event, we solve for a single M0 and fc, while any remaining residual kappa, &#x03BA;r\">κrκr, is allowed to differ per station record to reflect varying high-frequency falloff due to path and site attenuation. We use a parametric forward modeling method, calculating initial M0 and fc values from the local GNS New Zealand catalog Mw, GNS magnitudes and measuring an initial &#x03BA;r\">κrκr using an automated high-frequency linear regression method. Final solutions for M0, fc, and &#x03BA;r\">κrκr are iteratively computed through minimization of the residual function, and the Brune model stress drop is then calculated from the final, best-fit fc. We perform the spectral fitting routine on nested array seismic data that include the permanent GeoNet accelerometer network as well as a dense network of nearly 200 Quake Catcher Network (QCN) MEMs accelerometers, analyzing over 180 aftershocks Mw,GNS ≥ 3.5 that occurred from 9 September 2010 to 31 July 2011. QCN stations were hosted by public volunteers and served to fill spatial gaps between existing GeoNet stations. Moment magnitudes determined using the spectral fitting procedure (Mw,SF) range from 3.5 to 5.7 and agree well with Mw,GNS, with a median difference of 0.09 and 0.17 for GeoNet and QCN records, respectively, and 0.11 when data from both networks are combined. The majority of events are calculated to have stress drops between 1.7 and 13 MPa (20th and 80th percentile, correspondingly) for the combined networks. The overall median stress drop for the combined networks is 3.2 MPa, which is similar to median stress drops previously reported for the Canterbury sequence. We do not observe a correlation between stress drop and depth for this region, nor a relationship between stress drop and magnitude over the catalog considered. Lateral spatial patterns in stress drop, such as a cluster of aftershocks near the eastern extent of the Greendale fault with higher stress drops and lower stress drops for aftershocks of the 2011 Mw,GNS 6.2 Christchurch mainshock, are found to be in agreement with previous reports. As stress drop is arguably a method-dependent calculation and subject to high spatial variability, our results using the parametric Gauss–Newton algorithm strengthen conclusions that the Canterbury sequence has stress drops that are more similar to those found in intraplate regions, with overall higher stress drops that are typically observed in tectonically active areas.

","language":"English","publisher":"Springer","doi":"10.1007/s00024-016-1445-2","usgsCitation":"Neighbors, C., Cochran, E.S., Ryan, K., and Kaiser, A.E., 2017, Solving for source parameters using nested array data: A case study from the Canterbury, New Zealand earthquake sequence: Pure and Applied Geophysics, v. 174, no. 3, p. 875-893, https://doi.org/10.1007/s00024-016-1445-2.","productDescription":"19 p.","startPage":"875","endPage":"893","ipdsId":"IP-070144","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":341100,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"New Zealand","city":"Christchurch","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 172.24365234374997,\n -44.087585028245165\n ],\n [\n 173.29833984375,\n -44.087585028245165\n ],\n [\n 173.29833984375,\n -43.052833917627936\n ],\n [\n 172.24365234374997,\n -43.052833917627936\n ],\n [\n 172.24365234374997,\n -44.087585028245165\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"174","issue":"3","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-12-26","publicationStatus":"PW","scienceBaseUri":"59154657e4b01a342e6912df","contributors":{"authors":[{"text":"Neighbors, Corrie","contributorId":127529,"corporation":false,"usgs":false,"family":"Neighbors","given":"Corrie","affiliations":[{"id":7004,"text":"Department of Earth Sciences, University of California, Riverside","active":true,"usgs":false}],"preferred":false,"id":694761,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cochran, Elizabeth S. 0000-0003-2485-4484 ecochran@usgs.gov","orcid":"https://orcid.org/0000-0003-2485-4484","contributorId":2025,"corporation":false,"usgs":true,"family":"Cochran","given":"Elizabeth","email":"ecochran@usgs.gov","middleInitial":"S.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":694760,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ryan, Kenneth 0000-0003-3933-3163 kryan@usgs.gov","orcid":"https://orcid.org/0000-0003-3933-3163","contributorId":191921,"corporation":false,"usgs":true,"family":"Ryan","given":"Kenneth","email":"kryan@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":694762,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kaiser, Anna E.","contributorId":141200,"corporation":false,"usgs":false,"family":"Kaiser","given":"Anna","email":"","middleInitial":"E.","affiliations":[{"id":6956,"text":"GNS Science/Massey University","active":true,"usgs":false}],"preferred":false,"id":694763,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70192856,"text":"70192856 - 2017 - LANDFIRE 2015 Remap – Utilization of Remotely Sensed Data to Classify Existing Vegetation Type and Structure to Support Strategic Planning and Tactical Response","interactions":[],"lastModifiedDate":"2017-10-30T15:08:59","indexId":"70192856","displayToPublicDate":"2017-03-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1440,"text":"Earthzine","active":true,"publicationSubtype":{"id":10}},"title":"LANDFIRE 2015 Remap – Utilization of Remotely Sensed Data to Classify Existing Vegetation Type and Structure to Support Strategic Planning and Tactical Response","docAbstract":"

The LANDFIRE Program produces national scale vegetation, fuels, fire regimes, and landscape disturbance data for the entire U.S. These data products have been used to model the potential impacts of fire on the landscape [1], the wildfire risks associated with land and resource management [2, 3], and those near population centers and accompanying Wildland Urban Interface zones [4], as well as many other applications. The initial LANDFIRE National Existing Vegetation Type (EVT) and vegetation structure layers, including vegetation percent cover and height, were mapped circa 2001 and released in 2009 [5]. Each EVT is representative of the dominant plant community within a given area. The EVT layer has since been updated by identifying areas of landscape change and modifying the vegetation types utilizing a series of rules that consider the disturbance type, severity of disturbance, and time since disturbance [6, 7]. Non-disturbed areas were adjusted for vegetation growth and succession. LANDFIRE vegetation structure layers also have been updated by using data modeling techniques [see 6 for a full description]. The subsequent updated versions of LANDFIRE include LANDFIRE 2008, 2010, 2012, and LANDFIRE 2014 is being incrementally released, with all data being released in early 2017. Additionally, a comprehensive remap of the baseline data, LANDFIRE 2015 Remap, is being prototyped, and production is tentatively planned to begin in early 2017 to provide a more current baseline for future updates.

","language":"English","publisher":"IEEE","usgsCitation":"Picotte, J.J., Long, J., Peterson, B., and Nelson, K., 2017, LANDFIRE 2015 Remap – Utilization of Remotely Sensed Data to Classify Existing Vegetation Type and Structure to Support Strategic Planning and Tactical Response: Earthzine, v. March 2017, HTML Document.","productDescription":"HTML Document","ipdsId":"IP-078297","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":347731,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":347605,"type":{"id":15,"text":"Index Page"},"url":"https://earthzine.org/2017/03/20/landfire-2015-remap-utilization-of-remotely-sensed-data-to-classify-existing-vegetation-type-and-structure-to-support-strategic-planning-and-tactical-response/"}],"volume":"March 2017","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59f83a38e4b063d5d30980ec","contributors":{"authors":[{"text":"Picotte, Joshua J. 0000-0002-4021-4623 jpicotte@usgs.gov","orcid":"https://orcid.org/0000-0002-4021-4623","contributorId":4626,"corporation":false,"usgs":true,"family":"Picotte","given":"Joshua","email":"jpicotte@usgs.gov","middleInitial":"J.","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":717219,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Long, Jordan 0000-0002-4814-464X jlong@usgs.gov","orcid":"https://orcid.org/0000-0002-4814-464X","contributorId":3609,"corporation":false,"usgs":true,"family":"Long","given":"Jordan","email":"jlong@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":717221,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Peterson, Birgit 0000-0002-4356-1540 bpeterson@usgs.gov","orcid":"https://orcid.org/0000-0002-4356-1540","contributorId":192353,"corporation":false,"usgs":true,"family":"Peterson","given":"Birgit","email":"bpeterson@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":717220,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Nelson, Kurtis 0000-0003-4911-4511 knelson@usgs.gov","orcid":"https://orcid.org/0000-0003-4911-4511","contributorId":3602,"corporation":false,"usgs":true,"family":"Nelson","given":"Kurtis","email":"knelson@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":717222,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70192069,"text":"70192069 - 2017 - When perception reflects reality: Non-native grass invasion alters small mammal risk landscapes and survival","interactions":[],"lastModifiedDate":"2017-10-19T13:52:07","indexId":"70192069","displayToPublicDate":"2017-03-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"When perception reflects reality: Non-native grass invasion alters small mammal risk landscapes and survival","docAbstract":"

Modification of habitat structure due to invasive plants can alter the risk landscape for wildlife by, for example, changing the quality or availability of refuge habitat. Whether perceived risk corresponds with actual fitness outcomes, however, remains an important open question. We simultaneously measured how habitat changes due to a common invasive grass (cheatgrass, Bromus tectorum) affected the perceived risk, habitat selection, and apparent survival of a small mammal, enabling us to assess how well perceived risk influenced important behaviors and reflected actual risk. We measured perceived risk by nocturnal rodents using a giving-up density foraging experiment with paired shrub (safe) and open (risky) foraging trays in cheatgrass and native habitats. We also evaluated microhabitat selection across a cheatgrass gradient as an additional assay of perceived risk and behavioral responses for deer mice (Peromyscus maniculatus) at two spatial scales of habitat availability. Finally, we used mark-recapture analysis to quantify deer mouse apparent survival across a cheatgrass gradient while accounting for detection probability and other habitat features. In the foraging experiment, shrubs were more important as protective cover in cheatgrass-dominated habitats, suggesting that cheatgrass increased perceived predation risk. Additionally, deer mice avoided cheatgrass and selected shrubs, and marginally avoided native grass, at two spatial scales. Deer mouse apparent survival varied with a cheatgrass–shrub interaction, corresponding with our foraging experiment results, and providing a rare example of a native plant mediating the effects of an invasive plant on wildlife. By synthesizing the results of three individual lines of evidence (foraging behavior, habitat selection, and apparent survival), we provide a rare example of linkage between behavioral responses of animals indicative of perceived predation risk and actual fitness outcomes. Moreover, our results suggest that exotic grass invasions can influence wildlife populations by altering risk landscapes and survival.

","language":"English","publisher":"Wiley","doi":"10.1002/ece3.2785","usgsCitation":"Ceradnini, J.P., and Chalfoun, A.D., 2017, When perception reflects reality: Non-native grass invasion alters small mammal risk landscapes and survival: Ecology and Evolution, v. 7, no. 6, p. 1823-1835, https://doi.org/10.1002/ece3.2785.","productDescription":"13 p.","startPage":"1823","endPage":"1835","ipdsId":"IP-073821","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":470034,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.2785","text":"Publisher Index Page"},{"id":346981,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wyoming","otherGeospatial":"Thunder Basin National Grassland","volume":"7","issue":"6","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2017-02-15","publicationStatus":"PW","scienceBaseUri":"59e9b996e4b05fe04cd65ca7","contributors":{"authors":[{"text":"Ceradnini, Joseph P.","contributorId":197675,"corporation":false,"usgs":false,"family":"Ceradnini","given":"Joseph","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":714060,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chalfoun, Anna D. 0000-0002-0219-6006 achalfoun@usgs.gov","orcid":"https://orcid.org/0000-0002-0219-6006","contributorId":197589,"corporation":false,"usgs":true,"family":"Chalfoun","given":"Anna","email":"achalfoun@usgs.gov","middleInitial":"D.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":714059,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70190053,"text":"70190053 - 2017 - Unusual geologic evidence of coeval seismic shaking and tsunamis shows variability in earthquake size and recurrence in the area of the giant 1960 Chile earthquake","interactions":[],"lastModifiedDate":"2017-08-08T10:52:14","indexId":"70190053","displayToPublicDate":"2017-03-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2667,"text":"Marine Geology","active":true,"publicationSubtype":{"id":10}},"title":"Unusual geologic evidence of coeval seismic shaking and tsunamis shows variability in earthquake size and recurrence in the area of the giant 1960 Chile earthquake","docAbstract":"

An uncommon coastal sedimentary record combines evidence for seismic shaking and coincident tsunami inundation since AD 1000 in the region of the largest earthquake recorded instrumentally: the giant 1960 southern Chile earthquake (Mw 9.5). The record reveals significant variability in the size and recurrence of megathrust earthquakes and ensuing tsunamis along this part of the Nazca-South American plate boundary. A 500-m long coastal outcrop on Isla Chiloé, midway along the 1960 rupture, provides continuous exposure of soil horizons buried locally by debris-flow diamicts and extensively by tsunami sand sheets. The diamicts flattened plants that yield geologically precise ages to correlate with well-dated evidence elsewhere. The 1960 event was preceded by three earthquakes that probably resembled it in their effects, in AD 898 - 1128, 1300 - 1398 and 1575, and by five relatively smaller intervening earthquakes. Earthquakes and tsunamis recurred exceptionally often between AD 1300 and 1575. Their average recurrence interval of 85 years only slightly exceeds the time already elapsed since 1960. This inference is of serious concern because no earthquake has been anticipated in the region so soon after the 1960 event, and current plate locking suggests that some segments of the boundary are already capable of producing large earthquakes. This long-term earthquake and tsunami history of one of the world's most seismically active subduction zones provides an example of variable rupture mode, in which earthquake size and recurrence interval vary from one earthquake to the next.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.margeo.2016.12.007","usgsCitation":"Cisternas, M., Garrett, E., Wesson, R.L., Dura, T., and Ely, L.L., 2017, Unusual geologic evidence of coeval seismic shaking and tsunamis shows variability in earthquake size and recurrence in the area of the giant 1960 Chile earthquake: Marine Geology, v. 385, no. 1 March 2017, p. 101-113, https://doi.org/10.1016/j.margeo.2016.12.007.","productDescription":"13 p.","startPage":"101","endPage":"113","ipdsId":"IP-083320","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":470047,"rank":2,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://durham-repository.worktribe.com/file/1364141/1/Accepted%20Journal%20Article","text":"External Repository"},{"id":344645,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://ars.els-cdn.com/content/image/1-s2.0-S0025322716X00138-cov150h.gif"}],"geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -74.619140625,\n -43.46089378008257\n ],\n [\n -73.19091796875,\n -43.46089378008257\n ],\n [\n -73.19091796875,\n -41.73033005046652\n ],\n [\n -74.619140625,\n -41.73033005046652\n ],\n [\n -74.619140625,\n -43.46089378008257\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"385","issue":"1 March 2017","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"598acddce4b09fa1cb0e13db","contributors":{"authors":[{"text":"Cisternas, M.","contributorId":193403,"corporation":false,"usgs":false,"family":"Cisternas","given":"M.","email":"","affiliations":[],"preferred":false,"id":707338,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Garrett, E","contributorId":195524,"corporation":false,"usgs":false,"family":"Garrett","given":"E","email":"","affiliations":[],"preferred":false,"id":707339,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wesson, Robert L. 0000-0003-2702-0012 rwesson@usgs.gov","orcid":"https://orcid.org/0000-0003-2702-0012","contributorId":850,"corporation":false,"usgs":true,"family":"Wesson","given":"Robert","email":"rwesson@usgs.gov","middleInitial":"L.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":707340,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dura, T.","contributorId":193399,"corporation":false,"usgs":false,"family":"Dura","given":"T.","affiliations":[],"preferred":false,"id":707341,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ely, L. L","contributorId":193400,"corporation":false,"usgs":false,"family":"Ely","given":"L.","email":"","middleInitial":"L","affiliations":[],"preferred":false,"id":707342,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70184186,"text":"70184186 - 2017 - Mercury exposure may influence fluctuating asymmetry in waterbirds","interactions":[],"lastModifiedDate":"2017-11-22T17:04:33","indexId":"70184186","displayToPublicDate":"2017-03-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1571,"text":"Environmental Toxicology and Chemistry","active":true,"publicationSubtype":{"id":10}},"title":"Mercury exposure may influence fluctuating asymmetry in waterbirds","docAbstract":"

Variation in avian bilateral symmetry can be an indicator of developmental instability in response to a variety of stressors, including environmental contaminants. The authors used composite measures of fluctuating asymmetry to examine the influence of mercury concentrations in 2 tissues on fluctuating asymmetry within 4 waterbird species. Fluctuating asymmetry increased with mercury concentrations in whole blood and breast feathers of Forster's terns (Sterna forsteri), a species with elevated mercury concentrations. Specifically, fluctuating asymmetry in rectrix feather 1 was the most strongly correlated structural variable of those tested (wing chord, tarsus, primary feather 10, rectrix feather 6) with mercury concentrations in Forster's terns. However, for American avocets (Recurvirostra americana), black-necked stilts (Himantopus mexicanus), and Caspian terns (Hydroprogne caspia), the authors found no relationship between fluctuating asymmetry and either whole-blood or breast feather mercury concentrations, even though these species had moderate to elevated mercury exposure. The results indicate that mercury contamination may act as an environmental stressor during development and feather growth and contribute to fluctuating asymmetry of some species of highly contaminated waterbirds.

","language":"English","publisher":"Wiley","doi":"10.1002/etc.3688","usgsCitation":"Herring, G., Eagles-Smith, C.A., and Ackerman, J., 2017, Mercury exposure may influence fluctuating asymmetry in waterbirds: Environmental Toxicology and Chemistry, v. 36, no. 6, p. 1599-1605, https://doi.org/10.1002/etc.3688.","productDescription":"7 p.","startPage":"1599","endPage":"1605","ipdsId":"IP-067136","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":438432,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7KW5D5Z","text":"USGS data release","linkHelpText":"Fluctuating asymmetry in waterbirds in relation to mercury exposure"},{"id":336770,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"36","issue":"6","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2016-11-16","publicationStatus":"PW","scienceBaseUri":"58b7eb9ee4b01ccd5500bacd","contributors":{"authors":[{"text":"Herring, Garth 0000-0003-1106-4731 gherring@usgs.gov","orcid":"https://orcid.org/0000-0003-1106-4731","contributorId":4403,"corporation":false,"usgs":true,"family":"Herring","given":"Garth","email":"gherring@usgs.gov","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}],"preferred":true,"id":680424,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Eagles-Smith, Collin A. 0000-0003-1329-5285 ceagles-smith@usgs.gov","orcid":"https://orcid.org/0000-0003-1329-5285","contributorId":505,"corporation":false,"usgs":true,"family":"Eagles-Smith","given":"Collin","email":"ceagles-smith@usgs.gov","middleInitial":"A.","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":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":680423,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ackerman, Joshua T. 0000-0002-3074-8322 jackerman@usgs.gov","orcid":"https://orcid.org/0000-0002-3074-8322","contributorId":147078,"corporation":false,"usgs":true,"family":"Ackerman","given":"Joshua T.","email":"jackerman@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":680425,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70187194,"text":"70187194 - 2017 - Estimating regional-scale permeability–depth relations in a fractured-rock terrain using groundwater-flow model calibration","interactions":[],"lastModifiedDate":"2018-03-29T11:08:46","indexId":"70187194","displayToPublicDate":"2017-03-01T00:00:00","publicationYear":"2017","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":"Estimating regional-scale permeability–depth relations in a fractured-rock terrain using groundwater-flow model calibration","docAbstract":"

The trend of decreasing permeability with depth was estimated in the fractured-rock terrain of the upper Potomac River basin in the eastern USA using model calibration on 200 water-level observations in wells and 12 base-flow observations in subwatersheds. Results indicate that permeability at the 1–10 km scale (for groundwater flowpaths) decreases by several orders of magnitude within the top 100 m of land surface. This depth range represents the transition from the weathered, fractured regolith into unweathered bedrock. This rate of decline is substantially greater than has been observed by previous investigators that have plotted in situ wellbore measurements versus depth. The difference is that regional water levels give information on kilometer-scale connectivity of the regolith and adjacent fracture networks, whereas in situ measurements give information on near-hole fractures and fracture networks. The approach taken was to calibrate model layer-to-layer ratios of hydraulic conductivity (LLKs) for each major rock type. Most rock types gave optimal LLK values of 40–60, where each layer was twice a thick as the one overlying it. Previous estimates of permeability with depth from deeper data showed less of a decline at <300 m than the regional modeling results. There was less certainty in the modeling results deeper than 200 m and for certain rock types where fewer water-level observations were available. The results have implications for improved understanding of watershed-scale groundwater flow and transport, such as for the timing of the migration of pollutants from the water table to streams.

","language":"English","publisher":"Springer","doi":"10.1007/s10040-016-1483-y","usgsCitation":"Sanford, W.E., 2017, Estimating regional-scale permeability–depth relations in a fractured-rock terrain using groundwater-flow model calibration: Hydrogeology Journal, v. 25, no. 2, p. 405-419, https://doi.org/10.1007/s10040-016-1483-y.","productDescription":"15 p.","startPage":"405","endPage":"419","ipdsId":"IP-076752","costCenters":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"links":[{"id":352927,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"25","issue":"2","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2016-11-11","publicationStatus":"PW","scienceBaseUri":"5afee8c4e4b0da30c1bfc4a6","contributors":{"authors":[{"text":"Sanford, Ward E. 0000-0002-6624-0280 wsanford@usgs.gov","orcid":"https://orcid.org/0000-0002-6624-0280","contributorId":2268,"corporation":false,"usgs":true,"family":"Sanford","given":"Ward","email":"wsanford@usgs.gov","middleInitial":"E.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":692987,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70185623,"text":"70185623 - 2017 - Land-use change and managed aquifer recharge effects on the hydrogeochemistry of two contrasting atoll island aquifers, Roi-Namur Island, Republic of the Marshall Islands","interactions":[],"lastModifiedDate":"2019-12-17T08:18:10","indexId":"70185623","displayToPublicDate":"2017-03-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":835,"text":"Applied Geochemistry","active":true,"publicationSubtype":{"id":10}},"title":"Land-use change and managed aquifer recharge effects on the hydrogeochemistry of two contrasting atoll island aquifers, Roi-Namur Island, Republic of the Marshall Islands","docAbstract":"Freshwater resources on low-lying atoll islands are highly vulnerable to climate change and sea-level rise. In addition to rainwater catchment, groundwater in the freshwater lens is a critically important water resource on many atoll islands, especially during drought. Although many atolls have high annual rainfall rates, dense natural vegetation and high evapotranspiration rates can limit recharge to the freshwater lens. Here we evaluate the effects of land-use/land-cover change and managed aquifer recharge on the hydrogeochemistry and supply of groundwater on Roi-Namur Island, Republic of the Marshall Islands. Roi-Namur is an artificially conjoined island that has similar hydrogeology on the Roi and Namur lobes, but has contrasting land-use/land-cover and managed aquifer recharge only on Roi. Vegetation removal and managed aquifer recharge operations have resulted in an estimated 8.6 x 105 m3 of potable groundwater in the freshwater lens on Roi, compared to only 1.6 x 104 m3 on Namur. We use groundwater samples from a suite of 33 vertically nested monitoring wells, statistical testing, and geochemical modeling using PHREEQC to show that the differences in land-use/land-cover and managed aquifer recharge on Roi and Namur have a statistically significant effect on several groundwater-quality parameters and the controlling geochemical processes. Results also indicate a seven-fold reduction in the dissolution of carbonate rock in the freshwater lens and overlying vadose zone of Roi compared to Namur. Mixing of seawater and the freshwater lens is a more dominant hydrogeochemical process on Roi because of the greater recharge and flushing of the aquifer with freshwater as compared to Namur. In contrast, equilibrium processes and dissolution-precipitation non-equilibrium reactions are more dominant on Namur because of the longer residence times relative to the rate of geochemical reactions. Findings from Roi-Namur Island support selective land-use/land-cover change and managed aquifer recharge as a promising management approach for communities on other low-lying atoll islands to increase the resilience of their groundwater supplies and help them adapt to future climate change related stresses.","language":"English","publisher":"Elsevier","doi":"10.1016/j.apgeochem.2017.03.006","usgsCitation":"Hejazian, M., Gurdak, J., Swarzenski, P.W., Odigie, K., and Storlazzi, C.D., 2017, Land-use change and managed aquifer recharge effects on the hydrogeochemistry of two contrasting atoll island aquifers, Roi-Namur Island, Republic of the Marshall Islands: Applied Geochemistry, v. 80, p. 58-71, https://doi.org/10.1016/j.apgeochem.2017.03.006.","productDescription":"14 p. ","startPage":"58","endPage":"71","ipdsId":"IP-077856","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":470040,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.apgeochem.2017.03.006","text":"Publisher Index Page"},{"id":338342,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Republic of the Marshall Islands","otherGeospatial":"Roi-Namur","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 165.9158706665039,\n 10.008748597487081\n ],\n [\n 166.036376953125,\n 10.008748597487081\n ],\n [\n 166.036376953125,\n 10.18518740926906\n ],\n [\n 165.9158706665039,\n 10.18518740926906\n ],\n [\n 165.9158706665039,\n 10.008748597487081\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"80","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58d63035e4b05ec7991310d7","chorus":{"doi":"10.1016/j.apgeochem.2017.03.006","url":"http://dx.doi.org/10.1016/j.apgeochem.2017.03.006","publisher":"Elsevier BV","authors":"Hejazian Mehrdad, Gurdak Jason J., Swarzenski Peter, Odigie Kingsley O., Storlazzi Curt D.","journalName":"Applied Geochemistry","publicationDate":"5/2017"},"contributors":{"authors":[{"text":"Hejazian, Mehrdad","contributorId":189821,"corporation":false,"usgs":false,"family":"Hejazian","given":"Mehrdad","email":"","affiliations":[],"preferred":false,"id":686147,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gurdak, Jason J.","contributorId":189822,"corporation":false,"usgs":false,"family":"Gurdak","given":"Jason J.","affiliations":[],"preferred":false,"id":686148,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Swarzenski, Peter W. 0000-0003-0116-0578","orcid":"https://orcid.org/0000-0003-0116-0578","contributorId":189823,"corporation":false,"usgs":false,"family":"Swarzenski","given":"Peter","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":686149,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Odigie, Kingsley","contributorId":172016,"corporation":false,"usgs":false,"family":"Odigie","given":"Kingsley","affiliations":[{"id":17620,"text":"UCSC","active":true,"usgs":false}],"preferred":false,"id":686150,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Storlazzi, Curt D. 0000-0001-8057-4490 cstorlazzi@usgs.gov","orcid":"https://orcid.org/0000-0001-8057-4490","contributorId":140584,"corporation":false,"usgs":true,"family":"Storlazzi","given":"Curt","email":"cstorlazzi@usgs.gov","middleInitial":"D.","affiliations":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":686146,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70185038,"text":"70185038 - 2017 - Autumn olive (Elaeagnus umbellata) presence and proliferation on former surface coal mines in Eastern USA","interactions":[],"lastModifiedDate":"2017-03-13T16:53:20","indexId":"70185038","displayToPublicDate":"2017-03-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1018,"text":"Biological Invasions","active":true,"publicationSubtype":{"id":10}},"title":"Autumn olive (Elaeagnus umbellata) presence and proliferation on former surface coal mines in Eastern USA","docAbstract":"

Invasive plants threaten native plant communities. Surface coal mines in the Appalachian Mountains are among the most disturbed landscapes in North America, but information about land cover characteristics of Appalachian mined lands is lacking. The invasive shrub autumn olive (Elaeagnus umbellata) occurs on these sites and interferes with ecosystem recovery by outcompeting native trees, thus inhibiting re-establishment of the native woody-plant community. We analyzed Landsat 8 satellite imagery to describe autumn olive’s distribution on post-mined lands in southwestern Virginia within the Appalachian coalfield. Eight images from April 2013 through January 2015 served as input data. Calibration and validation data obtained from high-resolution aerial imagery were used to develop a land cover classification model that identified areas where autumn olive was a primary component of land cover. Results indicate that autumn olive cover was sufficiently dense to enable detection on approximately 12.6 % of post-mined lands within the study area. The classified map had user’s and producer’s accuracies of 85.3 and 78.6 %, respectively, for the autumn olive coverage class. Overall accuracy was assessed in reference to an independent validation dataset at 96.8 %. Autumn olive was detected more frequently on mines disturbed prior to 2003, the last year of known plantings, than on lands disturbed by more recent mining. These results indicate that autumn olive growing on reclaimed coal mines in Virginia and elsewhere in eastern USA can be mapped using Landsat 8 Operational Land Imager imagery; and that autumn olive occurrence is a significant landscape vegetation feature on former surface coal mines in the southwestern Virginia segment of the Appalachian coalfield.

","language":"English","publisher":"Springer","doi":"10.1007/s10530-016-1271-6","usgsCitation":"Oliphant, A., Wynne, R., Zipper, C.E., Ford, W., Donovan, P.F., and Li, J., 2017, Autumn olive (Elaeagnus umbellata) presence and proliferation on former surface coal mines in Eastern USA: Biological Invasions, v. 19, no. 1, p. 179-195, https://doi.org/10.1007/s10530-016-1271-6.","productDescription":"17 p.","startPage":"179","endPage":"195","ipdsId":"IP-072884","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":337475,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"19","issue":"1","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2016-09-12","publicationStatus":"PW","scienceBaseUri":"58c7af98e4b0849ce9795e6a","contributors":{"authors":[{"text":"Oliphant, Adam J.","contributorId":189232,"corporation":false,"usgs":false,"family":"Oliphant","given":"Adam J.","affiliations":[],"preferred":false,"id":684165,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wynne, R.H.","contributorId":147844,"corporation":false,"usgs":false,"family":"Wynne","given":"R.H.","email":"","affiliations":[],"preferred":false,"id":684166,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Zipper, Carl E.","contributorId":43683,"corporation":false,"usgs":true,"family":"Zipper","given":"Carl","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":684167,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ford, W. Mark 0000-0002-9611-594X wford@usgs.gov","orcid":"https://orcid.org/0000-0002-9611-594X","contributorId":172499,"corporation":false,"usgs":true,"family":"Ford","given":"W. Mark","email":"wford@usgs.gov","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":false,"id":684033,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Donovan, P. F.","contributorId":189233,"corporation":false,"usgs":false,"family":"Donovan","given":"P.","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":684168,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Li, Jing","contributorId":9166,"corporation":false,"usgs":true,"family":"Li","given":"Jing","email":"","affiliations":[],"preferred":false,"id":684169,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70191921,"text":"70191921 - 2017 - San Francisco Bay living shorelines: Restoring Eelgrass and Olympia Oysters for habitat and shore protection","interactions":[],"lastModifiedDate":"2020-08-21T13:20:58.481643","indexId":"70191921","displayToPublicDate":"2017-03-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"17","title":"San Francisco Bay living shorelines: Restoring Eelgrass and Olympia Oysters for habitat and shore protection","docAbstract":"

Living shorelines projects utilize a suite of sediment stabilization and habitat restoration techniques to maintain or build the shoreline, while creating habitat for a variety of species, including invertebrates, fish, and birds (see National Oceanic and Atmospheric Administration [NOAA] 2015 for an overview). The term “living shorelines” denotes provision of living space and support for estuarine and coastal organisms through the strategic placement of native vegetation and natural materials. This green coastal infrastructure can serve as an alternative to bulkheads and other engineering solutions that provide little to no habitat in comparison (Arkema et al. 2013; Gittman et al. 2014; Scyphers et al. 2011). In the United States, the living shorelines approach has been implemented primarily on the East and Gulf Coasts, where it has been shown to enhance habitat values and increase connectivity between wetlands, mudflats, and subtidal lands, while reducing shoreline erosion during storms and even hurricanes (Currin et al. 2015; Gittman et al. 2014, 2015).

","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Living shorelines: The science and management of nature-based coastal protection","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"CRC Press","isbn":"9781498740029","usgsCitation":"Boyer, K.E., Zabin, C., De La Cruz, S., Grosholz, E., Orr, M., Lowe, J., Latta, M., Miller, J., Kiriakopolos, S., Pinnell, C., Kunz, D., Moderan, J., Stockmann, K., Ayala, G., Abbott, R., and Obernolte, R., 2017, San Francisco Bay living shorelines: Restoring Eelgrass and Olympia Oysters for habitat and shore protection, chap. 17 of Living shorelines: The science and management of nature-based coastal protection, p. 333-362.","productDescription":"30 p.","startPage":"333","endPage":"362","ipdsId":"IP-080822","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":351822,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":346922,"type":{"id":15,"text":"Index Page"},"url":"https://www.crcpress.com/Living-Shorelines-The-Science-and-Management-of-Nature-Based-Coastal-Protection/Bilkovic-Mitchell-Peyre-Toft/p/book/9781498740029"}],"country":"United States","state":"California","otherGeospatial":"San Francisco Bay area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.3544921875,\n 37.046408899699564\n ],\n [\n -121.33300781249999,\n 37.046408899699564\n ],\n [\n -121.33300781249999,\n 38.37611542403604\n ],\n [\n -123.3544921875,\n 38.37611542403604\n ],\n [\n -123.3544921875,\n 37.046408899699564\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee8c4e4b0da30c1bfc4a0","contributors":{"authors":[{"text":"Boyer, Katharyn E.","contributorId":177069,"corporation":false,"usgs":false,"family":"Boyer","given":"Katharyn","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":713695,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zabin, Chela","contributorId":197536,"corporation":false,"usgs":false,"family":"Zabin","given":"Chela","email":"","affiliations":[],"preferred":false,"id":713696,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"De La Cruz, Susan sdelacruz@usgs.gov","contributorId":131159,"corporation":false,"usgs":true,"family":"De La Cruz","given":"Susan","email":"sdelacruz@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":713694,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Grosholz, Edwin D.","contributorId":171563,"corporation":false,"usgs":false,"family":"Grosholz","given":"Edwin D.","affiliations":[],"preferred":false,"id":713697,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Orr, Michelle","contributorId":197537,"corporation":false,"usgs":false,"family":"Orr","given":"Michelle","email":"","affiliations":[],"preferred":false,"id":713698,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lowe, Jeremy","contributorId":197538,"corporation":false,"usgs":false,"family":"Lowe","given":"Jeremy","email":"","affiliations":[],"preferred":false,"id":713699,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Latta, Marilyn","contributorId":167186,"corporation":false,"usgs":false,"family":"Latta","given":"Marilyn","email":"","affiliations":[{"id":24636,"text":"California State Coastal Conservancy","active":true,"usgs":false}],"preferred":false,"id":713700,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Miller, Jen","contributorId":202607,"corporation":false,"usgs":false,"family":"Miller","given":"Jen","email":"","affiliations":[],"preferred":false,"id":713701,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Kiriakopolos, Stephanie","contributorId":197540,"corporation":false,"usgs":false,"family":"Kiriakopolos","given":"Stephanie","email":"","affiliations":[],"preferred":false,"id":713702,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Pinnell, Cassie","contributorId":197541,"corporation":false,"usgs":false,"family":"Pinnell","given":"Cassie","email":"","affiliations":[],"preferred":false,"id":713703,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Kunz, Damien","contributorId":197542,"corporation":false,"usgs":false,"family":"Kunz","given":"Damien","email":"","affiliations":[],"preferred":false,"id":713704,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Moderan, Julien","contributorId":197543,"corporation":false,"usgs":false,"family":"Moderan","given":"Julien","email":"","affiliations":[],"preferred":false,"id":713705,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Stockmann, Kevin","contributorId":197544,"corporation":false,"usgs":false,"family":"Stockmann","given":"Kevin","affiliations":[],"preferred":false,"id":713706,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Ayala, Geana","contributorId":197545,"corporation":false,"usgs":false,"family":"Ayala","given":"Geana","email":"","affiliations":[],"preferred":false,"id":713707,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Abbott, Robert","contributorId":197546,"corporation":false,"usgs":false,"family":"Abbott","given":"Robert","email":"","affiliations":[],"preferred":false,"id":713708,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Obernolte, Rena","contributorId":197547,"corporation":false,"usgs":false,"family":"Obernolte","given":"Rena","email":"","affiliations":[],"preferred":false,"id":713709,"contributorType":{"id":1,"text":"Authors"},"rank":16}]}} ,{"id":70186150,"text":"70186150 - 2017 - Managing native predators: Evidence from a partial removal of raccoons (Procyon lotor) on the Outer Banks of North Carolina, USA","interactions":[],"lastModifiedDate":"2017-03-30T11:10:56","indexId":"70186150","displayToPublicDate":"2017-03-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3731,"text":"Waterbirds","onlineIssn":"19385390","printIssn":"15244695","active":true,"publicationSubtype":{"id":10}},"title":"Managing native predators: Evidence from a partial removal of raccoons (Procyon lotor) on the Outer Banks of North Carolina, USA","docAbstract":"

Raccoons (Procyon lotor) are important predators of ground-nesting species in coastal systems. They have been identified as a primary cause of nest failure for the American Oystercatcher (Haematopus palliatus) throughout its range. Concerns over the long-term effects of raccoon predation and increased nest success following a hurricane inspired a mark-resight study of the raccoon population on a barrier island off North Carolina, USA. Approximately half of the raccoons were experimentally removed in 2008. Nests (n = 700) were monitored on two adjacent barrier islands during 2004–2013. Daily nest survival estimates were highest for 2004 (0.974 ± 0.005) and lowest for 2007 and 2008 (0.925 ± 0.009 and 0.925 ± 0.010, respectively). The only model in our candidate set that received any support included island and time of season, along with a diminishing effect of the hurricane and a constant, 5-year effect of the raccoon removal. For both hurricane and raccoon removal, however, the support for island-specific effects was weak (β = -0.204 ± 0.116 and 0.146 ± 0.349, respectively). We conclude that either the raccoon reduction was inadequate, or factors other than predation cause more variation in nest success than previously recognized. A multi-faceted approach to management aimed at reducing nest losses to storm overwash, predation, and human disturbance is likely to yield the largest population level benefits.

","language":"English","publisher":"The Waterbird Society","doi":"10.1675/063.040.sp103","usgsCitation":"Stocking, J.J., Simons, T.R., Parsons, A.W., and O’Connell, A.F., 2017, Managing native predators: Evidence from a partial removal of raccoons (Procyon lotor) on the Outer Banks of North Carolina, USA: Waterbirds, v. 40, no. sp1, p. 10-18, https://doi.org/10.1675/063.040.sp103.","productDescription":"9 p.","startPage":"10","endPage":"18","ipdsId":"IP-071197","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":338798,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Carolina","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -76.7449951171875,\n 34.56764471968292\n ],\n [\n -75.91552734375,\n 34.56764471968292\n ],\n [\n -75.91552734375,\n 35.1356330179272\n ],\n [\n -76.7449951171875,\n 35.1356330179272\n ],\n [\n -76.7449951171875,\n 34.56764471968292\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"40","issue":"sp1","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58de194de4b02ff32c699c91","contributors":{"authors":[{"text":"Stocking, Jessica J.","contributorId":68626,"corporation":false,"usgs":true,"family":"Stocking","given":"Jessica","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":687692,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Simons, Theodore R. 0000-0002-1884-6229 tsimons@usgs.gov","orcid":"https://orcid.org/0000-0002-1884-6229","contributorId":2623,"corporation":false,"usgs":true,"family":"Simons","given":"Theodore","email":"tsimons@usgs.gov","middleInitial":"R.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":687675,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Parsons, Arielle W.","contributorId":91383,"corporation":false,"usgs":true,"family":"Parsons","given":"Arielle","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":687693,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"O’Connell, Allan F. 0000-0001-7032-7023 aoconnell@usgs.gov","orcid":"https://orcid.org/0000-0001-7032-7023","contributorId":471,"corporation":false,"usgs":true,"family":"O’Connell","given":"Allan","email":"aoconnell@usgs.gov","middleInitial":"F.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":687676,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70184974,"text":"70184974 - 2017 - Northern bobwhite breeding season ecology on a reclaimed surface mine","interactions":[],"lastModifiedDate":"2017-03-15T11:31:24","indexId":"70184974","displayToPublicDate":"2017-03-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Northern bobwhite breeding season ecology on a reclaimed surface mine","docAbstract":"

Surface coal mining and subsequent reclamation of surface mines have converted large forest areas into early successional vegetative communities in the eastern United States. This reclamation can provide a novel opportunity to conserve northern bobwhite (Colinus virginianus). We evaluated the influence of habitat management activities on nest survival, nest-site selection, and brood resource selection on managed and unmanaged units of a reclaimed surface mine, Peabody Wildlife Management Area (Peabody), in west-central Kentucky, USA, from 2010 to 2013. We compared resource selection, using discrete-choice analysis, and nest survival, using the nest survival model in Program MARK, between managed and unmanaged units of Peabody at 2 spatial scales: the composition and configuration of vegetation types (i.e., macrohabitat) and vegetation characteristics at nest sites and brood locations (i.e., microhabitat). On managed sites, we also investigated resource selection relative to a number of different treatments (e.g., herbicide, disking, prescribed fire). We found no evidence that nest-site selection was influenced by macrohabitat variables, but bobwhite selected nest sites in areas with greater litter depth than was available at random sites. On managed units, bobwhite were more likely to nest where herbicide was applied to reduce sericea lespedeza (Lespedeza cuneata) compared with areas untreated with herbicide. Daily nest survival was not influenced by habitat characteristics or by habitat management but was influenced by nest age and the interaction of nest initiation date and nest age. Daily nest survival was greater for older nests occurring early in the breeding season (0.99, SE < 0.01) but was lower for older nests occurring later in the season (0.08, SE = 0.13). Brood resource selection was not influenced by macrohabitat or microhabitat variables we measured, but broods on managed units selected areas treated with herbicide to control sericea lespedeza and were located closer to firebreaks and disked native-warm season grass stands than would be expected at random. Our results suggest the vegetation at Peabody was sufficient without manipulation to support nesting and brood-rearing northern bobwhite at a low level, but habitat management practices improved vegetation for nesting and brood-rearing resource selection. Reproductive rates (e.g., nest survival and re-nesting rates) at Peabody were lower than reported in other studies, which may be related to nutritional deficiencies caused by the abundance of sericea lespedeza. On reclaimed mine lands dominated by sericea lespedeza, we suggest continuing practices such as disking and herbicide application that are targeted at reducing sericea lespedeza to improve the vegetation for nesting and brood-rearing bobwhite.

","language":"English","publisher":"The WIldlife Society","doi":"10.1002/jwmg.21182","usgsCitation":"Brooke, J.M., Tanner, E.P., Peters, D.C., Tanner, A.M., Harper, C.A., Keyser, P.D., Clark, J.D., and Morgan, J.J., 2017, Northern bobwhite breeding season ecology on a reclaimed surface mine: Journal of Wildlife Management, v. 81, no. 1, p. 73-85, https://doi.org/10.1002/jwmg.21182.","productDescription":"13 p.","startPage":"73","endPage":"85","ipdsId":"IP-068704","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":337605,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Kentucky","otherGeospatial":"Peabody Wildlife Management 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PSC"},"noUsgsAuthors":false,"publicationDate":"2016-10-06","publicationStatus":"PW","scienceBaseUri":"58ca52cbe4b0849ce97c8696","contributors":{"authors":[{"text":"Brooke, Jarred M.","contributorId":146940,"corporation":false,"usgs":false,"family":"Brooke","given":"Jarred","email":"","middleInitial":"M.","affiliations":[{"id":12716,"text":"University of Tennessee","active":true,"usgs":false}],"preferred":false,"id":683783,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tanner, Evan P.","contributorId":146943,"corporation":false,"usgs":false,"family":"Tanner","given":"Evan","email":"","middleInitial":"P.","affiliations":[{"id":12716,"text":"University of Tennessee","active":true,"usgs":false}],"preferred":false,"id":683784,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Peters, David C.","contributorId":146941,"corporation":false,"usgs":false,"family":"Peters","given":"David","email":"","middleInitial":"C.","affiliations":[{"id":12716,"text":"University of Tennessee","active":true,"usgs":false}],"preferred":false,"id":683782,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Tanner, Ashley M.","contributorId":177321,"corporation":false,"usgs":false,"family":"Tanner","given":"Ashley","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":683786,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Harper, Craig A.","contributorId":146944,"corporation":false,"usgs":false,"family":"Harper","given":"Craig","email":"","middleInitial":"A.","affiliations":[{"id":12716,"text":"University of Tennessee","active":true,"usgs":false}],"preferred":false,"id":683787,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Keyser, Patrick D.","contributorId":146945,"corporation":false,"usgs":false,"family":"Keyser","given":"Patrick","email":"","middleInitial":"D.","affiliations":[{"id":12716,"text":"University of Tennessee","active":true,"usgs":false}],"preferred":false,"id":683785,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Clark, Joseph D. 0000-0002-8547-8112 jclark1@usgs.gov","orcid":"https://orcid.org/0000-0002-8547-8112","contributorId":2265,"corporation":false,"usgs":true,"family":"Clark","given":"Joseph","email":"jclark1@usgs.gov","middleInitial":"D.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":683781,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Morgan, John J.","contributorId":146946,"corporation":false,"usgs":false,"family":"Morgan","given":"John","email":"","middleInitial":"J.","affiliations":[{"id":13409,"text":"Kentucky Department of Fish & Wildlife Resources","active":true,"usgs":false}],"preferred":false,"id":684457,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70188371,"text":"70188371 - 2017 - Subsurface volatile content of martian double-layer ejecta (DLE) craters","interactions":[],"lastModifiedDate":"2018-11-01T14:44:37","indexId":"70188371","displayToPublicDate":"2017-03-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1963,"text":"Icarus","active":true,"publicationSubtype":{"id":10}},"title":"Subsurface volatile content of martian double-layer ejecta (DLE) craters","docAbstract":"

Excess ice is widespread throughout the martian mid-latitudes, particularly in Arcadia Planitia, where double-layer ejecta (DLE) craters also tend to be abundant. In this region, we observe the presence of thermokarstically-expanded secondary craters that likely form from impacts that destabilize a subsurface layer of excess ice, which subsequently sublimates. The presence of these expanded craters shows that excess ice is still preserved within the adjacent terrain. Here, we focus on a 15-km DLE crater that contains abundant superposed expanded craters in order to study the distribution of subsurface volatiles both at the time when the secondary craters formed and, by extension, remaining today. To do this, we measure the size distribution of the superposed expanded craters and use topographic data to calculate crater volumes as a proxy for the volumes of ice lost to sublimation during the expansion process. The inner ejecta layer contains craters that appear to have undergone more expansion, suggesting that excess ice was most abundant in that region. However, both of the ejecta layers had more expanded craters than the surrounding terrain. We extrapolate that the total volume of ice remaining within the entire ejecta deposit is as much as 74 km3 or more. The variation in ice content between the ejecta layers could be the result of (1) volatile preservation from the formation of the DLE crater, (2) post-impact deposition in the form of ice lenses; or (3) preferential accumulation or preservation of subsequent snowfall. We have ruled out (2) as the primary mode for ice deposition in this location based on inconsistencies with our observations, though it may operate in concert with other processes. Although none of the existing DLE formation hypotheses are completely consistent with our observations, which may merit a new or modified mechanism, we can conclude that DLE craters contain a significant quantity of excess ice today.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.icarus.2016.11.031","usgsCitation":"Viola, D., McEwen, A.S., Dundas, C.M., and Byrne, S., 2017, Subsurface volatile content of martian double-layer ejecta (DLE) craters: Icarus, v. 284, p. 325-343, https://doi.org/10.1016/j.icarus.2016.11.031.","productDescription":"19 p.","startPage":"325","endPage":"343","ipdsId":"IP-077824","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":342216,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Mars","volume":"284","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"593910abe4b0764e6c5e8850","contributors":{"authors":[{"text":"Viola, Donna","contributorId":127526,"corporation":false,"usgs":false,"family":"Viola","given":"Donna","email":"","affiliations":[{"id":7042,"text":"University of Arizona","active":true,"usgs":false}],"preferred":false,"id":697430,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McEwen, Alfred S.","contributorId":61657,"corporation":false,"usgs":false,"family":"McEwen","given":"Alfred","email":"","middleInitial":"S.","affiliations":[{"id":7042,"text":"University of Arizona","active":true,"usgs":false}],"preferred":false,"id":697431,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dundas, Colin M. 0000-0003-2343-7224 cdundas@usgs.gov","orcid":"https://orcid.org/0000-0003-2343-7224","contributorId":2937,"corporation":false,"usgs":true,"family":"Dundas","given":"Colin","email":"cdundas@usgs.gov","middleInitial":"M.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":697429,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Byrne, Shane","contributorId":192609,"corporation":false,"usgs":false,"family":"Byrne","given":"Shane","email":"","affiliations":[],"preferred":false,"id":697432,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70193547,"text":"70193547 - 2017 - Reply to: Terry, J. and Goff, J. comment on “Late Cenozoic sea level and the rise of modern rimmed atolls” by Toomey et al. (2016), Palaeogeography, Palaeoclimatology, Palaeoecology 4 51: 73–83.","interactions":[],"lastModifiedDate":"2017-11-06T12:23:06","indexId":"70193547","displayToPublicDate":"2017-03-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2996,"text":"Palaeogeography, Palaeoclimatology, Palaeoecology","printIssn":"0031-0182","active":true,"publicationSubtype":{"id":10}},"title":"Reply to: Terry, J. and Goff, J. comment on “Late Cenozoic sea level and the rise of modern rimmed atolls” by Toomey et al. (2016), Palaeogeography, Palaeoclimatology, Palaeoecology 4 51: 73–83.","docAbstract":"

We appreciate Terry and Goff's thoughtful comment in response to our proposed atoll development model. Flank collapse of reef-built slopes likely does affect plan-form atoll morphology in some locations and potentially poses a tsunami hazard to low-lying Pacific islands (Terry and Goff, 2013). However, given the often rapid rates of lagoon infill (> 1 mm/yr; Montaggioni, 2005), such failure events would likely need to be frequent and widespread in order to leave a morphologic imprint on modern western Pacific atoll lagoon depths. Few atoll flank collapse features have been dated but many of the arcuate bight-like structures (ABLS) identified could be inherited from scars incised into the initial volcanic edifice (e.g. Terry and Goff, 2013 and refs. therein) — submarine mass wasting has been extensively documented on young hotspot islands (e.g. Hawaiian Islands: Moore et al., 1989; Reunion: Oehler et al., 2008). Atolls in the Marshall Islands, where our main study site Enewetak Atoll is located, are likely ~ 50–100 million years old (Larson et al., 1995) and dating of adjacent deep-water turbidite aprons in the Nauru Basin (DSDP Site 462; Schlanger and Silva, 1986) suggests that large atoll flank collapse events have been relatively infrequent there since the mid-Miocene (< 11 Ma). In our simple, 1D atoll development model (Toomey et al., 2016a), we included the minimum set of processes (vertical accretion, dissolution, and lagoonal infilling) required to accurately simulate Enewetak's ‘recent’ depositional history (8.5–0 Ma) and explain basic differences in lagoon depth among western Pacific atolls.

We agree future development of a model incorporating the wider range of processes impacting connectivity between reef-bound lagoons and the ocean (e.g. Ouillon et al., 2004; Toomey et al., 2016b), including stochastic mass wasting events, will be essential for exploring the plan-form and 3D shapes of atolls. To our knowledge, no quantitative model of long-term atoll development has explicitly linked lagoon restriction/sedimentation to episodic flank collapse events (e.g. Montaggioni et al., 2015; Paterson et al., 2006; Quinn, 1991; Warrlich et al., 2002). Testing Terry and Goff's proposed conceptual model for how rim failure processes affect atoll morphology in a numerical context will require deep drilling along arcuate bight-like structures, as well as adjacent, unaffected, rim and lagoon areas, in order quantify how often failures occur and how quickly the rim/lagoon is rebuilt afterwards. The model we present here provides a general framework capable of integrating atoll flank collapse processes once they are sufficiently constrained by such observational datasets.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.palaeo.2016.11.028","usgsCitation":"Toomey, M., Ashton, A., Raymo, M.E., and Perron, J.T., 2017, Reply to: Terry, J. and Goff, J. comment on “Late Cenozoic sea level and the rise of modern rimmed atolls” by Toomey et al. (2016), Palaeogeography, Palaeoclimatology, Palaeoecology 4 51: 73–83.: Palaeogeography, Palaeoclimatology, Palaeoecology, v. 469, p. 159-160, https://doi.org/10.1016/j.palaeo.2016.11.028.","productDescription":"2 p.","startPage":"159","endPage":"160","ipdsId":"IP-080565","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":470037,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1016/j.palaeo.2016.11.028","text":"External Repository"},{"id":348264,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"469","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a07e929e4b09af898c8cc01","contributors":{"authors":[{"text":"Toomey, Michael 0000-0003-0167-9273 mtoomey@usgs.gov","orcid":"https://orcid.org/0000-0003-0167-9273","contributorId":184097,"corporation":false,"usgs":true,"family":"Toomey","given":"Michael","email":"mtoomey@usgs.gov","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":719324,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ashton, Andrew","contributorId":184098,"corporation":false,"usgs":false,"family":"Ashton","given":"Andrew","affiliations":[],"preferred":false,"id":719325,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Raymo, Maureen E.","contributorId":184099,"corporation":false,"usgs":false,"family":"Raymo","given":"Maureen","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":719326,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Perron, J. Taylor","contributorId":184100,"corporation":false,"usgs":false,"family":"Perron","given":"J.","email":"","middleInitial":"Taylor","affiliations":[],"preferred":false,"id":719327,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70185031,"text":"70185031 - 2017 - Relations of alpine plant communities across environmental gradients: Multilevel versus multiscale analyses","interactions":[],"lastModifiedDate":"2017-03-14T12:20:25","indexId":"70185031","displayToPublicDate":"2017-03-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":797,"text":"Annals of the Association of American Geographers","active":true,"publicationSubtype":{"id":10}},"title":" Relations of alpine plant communities across environmental gradients: Multilevel versus multiscale analyses","docAbstract":"

Alpine plant communities vary, and their environmental covariates could influence their response to climate change. A single multilevel model of how alpine plant community composition is determined by hierarchical relations is compared to a separate examination of those relations at different scales. Nonmetric multidimensional scaling of species cover for plots in four regions across the Rocky Mountains created dependent variables. Climate variables are derived for the four regions from interpolated data. Plot environmental variables are measured directly and the presence of thirty-seven site characteristics is recorded and used to create additional independent variables. Multilevel and best subsets regressions are used to determine the strength of the hypothesized relations. The ordinations indicate structure in the assembly of plant communities. The multilevel analyses, although revealing significant relations, provide little explanation; of the site variables, those related to site microclimate are most important. In multiscale analyses (whole and separate regions), different variables are better explanations within the different regions. This result indicates weak environmental niche control of community composition. The weak relations of the structure in the patterns of species association to the environment indicates that either alpine vegetation represents a case of the neutral theory of biogeography being a valid explanation or that it represents disequilibrium conditions. The implications of neutral theory and disequilibrium explanations are similar: Response to climate change will be difficult to quantify above equilibrium background turnover.

","language":"English","publisher":"Taylor & Francis","doi":"10.1080/24694452.2016.1218267","usgsCitation":"Malanson, G.P., Zimmerman, D.L., Kinney, M., and Fagre, D.B., 2017, Relations of alpine plant communities across environmental gradients: Multilevel versus multiscale analyses: Annals of the Association of American Geographers, v. 107, no. 1, p. 41-53, https://doi.org/10.1080/24694452.2016.1218267.","productDescription":"13 p.","startPage":"41","endPage":"53","ipdsId":"IP-071596","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":337500,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"107","issue":"1","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2016-09-28","publicationStatus":"PW","scienceBaseUri":"58c90123e4b0849ce97abcba","contributors":{"authors":[{"text":"Malanson, George P.","contributorId":189162,"corporation":false,"usgs":false,"family":"Malanson","given":"George","email":"","middleInitial":"P.","affiliations":[{"id":6768,"text":"University of Iowa","active":true,"usgs":false}],"preferred":false,"id":684012,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zimmerman, Dale L.","contributorId":166811,"corporation":false,"usgs":false,"family":"Zimmerman","given":"Dale","email":"","middleInitial":"L.","affiliations":[{"id":6768,"text":"University of Iowa","active":true,"usgs":false}],"preferred":false,"id":684010,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kinney, Mitch","contributorId":189163,"corporation":false,"usgs":false,"family":"Kinney","given":"Mitch","email":"","affiliations":[],"preferred":false,"id":684013,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fagre, Daniel B. 0000-0001-8552-9461 dan_fagre@usgs.gov","orcid":"https://orcid.org/0000-0001-8552-9461","contributorId":2036,"corporation":false,"usgs":true,"family":"Fagre","given":"Daniel","email":"dan_fagre@usgs.gov","middleInitial":"B.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":684011,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70193625,"text":"70193625 - 2017 - Intraspecific functional diversity of common species enhances community stability","interactions":[],"lastModifiedDate":"2017-11-06T11:09:57","indexId":"70193625","displayToPublicDate":"2017-03-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Intraspecific functional diversity of common species enhances community stability","docAbstract":"

Common species are fundamental to the structure and function of their communities and may enhance community stability through intraspecific functional diversity (iFD). We measured among-habitat and within-habitat iFD (i.e., among- and within-plant community types) of two common small mammal species using stable isotopes and functional trait dendrograms, determined whether iFD was related to short-term population stability and small mammal community stability, and tested whether spatially explicit trait filters helped explain observed patterns of iFD. Southern red-backed voles (Myodes gapperi) had greater iFD than deer mice (Peromyscus maniculatus), both among habitats, and within the plant community in which they were most abundant (their “primary habitat”). Peromyscus maniculatus populations across habitats differed significantly between years and declined 78% in deciduous forests, their primary habitat, as did the overall deciduous forest small mammal community. Myodes gapperi populations were stable across habitats and within coniferous forest, their primary habitat, as was the coniferous forest small mammal community. Generalized linear models representing internal trait filters (e.g., competition), which increase within-habitat type iFD, best explained variation in M. gapperidiet, while models representing internal filters and external filters (e.g., climate), which suppress within-habitat iFD, best explained P. maniculatus diet. This supports the finding that M. gapperi had higher iFD than P. maniculatus and is consistent with the theory that internal trait filters are associated with higher iFD than external filters. Common species with high iFD can impart a stabilizing influence on their communities, information that can be important for conserving biodiversity under environmental change.

","language":"English","publisher":"Wiley","doi":"10.1002/ece3.2721","usgsCitation":"Wood, C.M., McKinney, S.T., and Loftin, C., 2017, Intraspecific functional diversity of common species enhances community stability: Ecology and Evolution, v. 7, no. 5, p. 1553-1560, https://doi.org/10.1002/ece3.2721.","productDescription":"8 p.","startPage":"1553","endPage":"1560","ipdsId":"IP-074150","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":470041,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.2721","text":"Publisher Index Page"},{"id":348254,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"7","issue":"5","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2017-02-08","publicationStatus":"PW","scienceBaseUri":"5a07e928e4b09af898c8cbff","contributors":{"authors":[{"text":"Wood, Connor M.","contributorId":167785,"corporation":false,"usgs":false,"family":"Wood","given":"Connor","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":720658,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McKinney, Shawn T. smckinney@usgs.gov","contributorId":5175,"corporation":false,"usgs":true,"family":"McKinney","given":"Shawn","email":"smckinney@usgs.gov","middleInitial":"T.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":720659,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Loftin, Cynthia S. 0000-0001-9104-3724 cyndy_loftin@usgs.gov","orcid":"https://orcid.org/0000-0001-9104-3724","contributorId":2167,"corporation":false,"usgs":true,"family":"Loftin","given":"Cynthia S.","email":"cyndy_loftin@usgs.gov","affiliations":[],"preferred":true,"id":719663,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70186330,"text":"70186330 - 2017 - Surface geophysical methods for characterising frozen ground in transitional permafrost landscapes","interactions":[],"lastModifiedDate":"2018-01-13T15:10:14","indexId":"70186330","displayToPublicDate":"2017-03-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3032,"text":"Permafrost and Periglacial Processes","active":true,"publicationSubtype":{"id":10}},"title":"Surface geophysical methods for characterising frozen ground in transitional permafrost landscapes","docAbstract":"

The distribution of shallow frozen ground is paramount to research in cold regions, and is subject to temporal and spatial changes influenced by climate, landscape disturbance and ecosystem succession. Remote sensing from airborne and satellite platforms is increasing our understanding of landscape-scale permafrost distribution, but typically lacks the resolution to characterise finer-scale processes and phenomena, which are better captured by integrated surface geophysical methods. Here, we demonstrate the use of electrical resistivity imaging (ERI), electromagnetic induction (EMI), ground penetrating radar (GPR) and infrared imaging over multiple summer field seasons around the highly dynamic Twelvemile Lake, Yukon Flats, central Alaska, USA. Twelvemile Lake has generally receded in the past 30 yr, allowing permafrost aggradation in the receded margins, resulting in a mosaic of transient frozen ground adjacent to thick, older permafrost outside the original lakebed. ERI and EMI best evaluated the thickness of shallow, thin permafrost aggradation, which was not clear from frost probing or GPR surveys. GPR most precisely estimated the depth of the active layer, which forward electrical resistivity modelling indicated to be a difficult target for electrical methods, but could be more tractable in time-lapse mode. Infrared imaging of freshly dug soil pit walls captured active-layer thermal gradients at unprecedented resolution, which may be useful in calibrating emerging numerical models. GPR and EMI were able to cover landscape scales (several kilometres) efficiently, and new analysis software showcased here yields calibrated EMI data that reveal the complicated distribution of shallow permafrost in a transitional landscape.

","language":"English","publisher":"Wiley","doi":"10.1002/ppp.1893","usgsCitation":"Briggs, M.A., Campbell, S., Nolan, J., Walvoord, M.A., Ntarlagiannis, D., Day-Lewis, F.D., and Lane, J.W., 2017, Surface geophysical methods for characterising frozen ground in transitional permafrost landscapes: Permafrost and Periglacial Processes, v. 28, no. 1, p. 52-65, https://doi.org/10.1002/ppp.1893.","productDescription":"14 p.","startPage":"52","endPage":"65","ipdsId":"IP-069599","costCenters":[{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true}],"links":[{"id":438431,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9UST855","text":"USGS data release","linkHelpText":"Surface geophysical data for characterizing shallow, discontinuous frozen ground near Fort Yukon, Alaska"},{"id":339120,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -145.5,\n 66.45\n ],\n [\n -145.25,\n 66.45\n ],\n [\n -145.25,\n 66.6\n ],\n [\n -145.5,\n 66.6\n ],\n [\n -145.5,\n 66.45\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"28","issue":"1","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2016-05-24","publicationStatus":"PW","scienceBaseUri":"58e4b0b1e4b09da67999777a","contributors":{"authors":[{"text":"Briggs, Martin A. 0000-0003-3206-4132 mbriggs@usgs.gov","orcid":"https://orcid.org/0000-0003-3206-4132","contributorId":4114,"corporation":false,"usgs":true,"family":"Briggs","given":"Martin","email":"mbriggs@usgs.gov","middleInitial":"A.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true},{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true},{"id":493,"text":"Office of Ground Water","active":true,"usgs":true}],"preferred":true,"id":688344,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Campbell, Seth","contributorId":190402,"corporation":false,"usgs":false,"family":"Campbell","given":"Seth","affiliations":[],"preferred":false,"id":688345,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nolan, Jay","contributorId":190403,"corporation":false,"usgs":false,"family":"Nolan","given":"Jay","email":"","affiliations":[],"preferred":false,"id":688346,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Walvoord, Michelle Ann 0000-0003-4269-8366 walvoord@usgs.gov","orcid":"https://orcid.org/0000-0003-4269-8366","contributorId":147211,"corporation":false,"usgs":true,"family":"Walvoord","given":"Michelle","email":"walvoord@usgs.gov","middleInitial":"Ann","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":688347,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ntarlagiannis, Dimitrios","contributorId":150729,"corporation":false,"usgs":false,"family":"Ntarlagiannis","given":"Dimitrios","affiliations":[{"id":12727,"text":"Rutgers University","active":true,"usgs":false}],"preferred":false,"id":688348,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Day-Lewis, Frederick D. 0000-0003-3526-886X daylewis@usgs.gov","orcid":"https://orcid.org/0000-0003-3526-886X","contributorId":1672,"corporation":false,"usgs":true,"family":"Day-Lewis","given":"Frederick","email":"daylewis@usgs.gov","middleInitial":"D.","affiliations":[{"id":493,"text":"Office of Ground Water","active":true,"usgs":true},{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":688349,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Lane, John W. Jr. 0000-0002-3558-243X jwlane@usgs.gov","orcid":"https://orcid.org/0000-0002-3558-243X","contributorId":189168,"corporation":false,"usgs":true,"family":"Lane","given":"John","suffix":"Jr.","email":"jwlane@usgs.gov","middleInitial":"W.","affiliations":[{"id":493,"text":"Office of Ground Water","active":true,"usgs":true},{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true}],"preferred":false,"id":688350,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ]}