An airborne lidar simulator creates a lidar point cloud from a simulated lidar system, flight parameters, and the terrain digital elevation model (DEM). At the basic level, the lidar simulator computes the range from a lidar system to the surface of a terrain using the geomatics lidar equation. The simple computation effectively assumes that the beam divergence is zero. If the beam spot is meaningfully large due to the large beam divergence combined with high sensor altitude, then the beam plane with a finite size interacts with a ground target in a realistic and complex manner. The irradiance distribution of a delta-pulse beam plane is defined based on laser pulse radiative transfer. The airborne lidar simulator in this research simulates the interaction between the delta-pulse and a three-dimensional (3D) object and results in a waveform. The waveform will be convoluted using a system response function. The lidar simulator also computes the total propagated uncertainty (TPU). All sources of the uncertainties associated with the position of the lidar point and the detailed geomatics equations to compute TPU are described. The boresighting error analysis and the 3D accuracy assessment are provided as examples of the application using the simulator
","language":"English","publisher":"MDPI","doi":"10.3390/app9122452","usgsCitation":"Kim, M., 2019, Airborne waveform lidar simulator using the radiative transfer of a laser pulse: Applied Sciences, v. 9, no. 12, 2452; 16 p., https://doi.org/10.3390/app9122452.","productDescription":"2452; 16 p.","ipdsId":"IP-108063","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":460357,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/app9122452","text":"Publisher Index Page"},{"id":364894,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"9","issue":"12","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2019-06-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Kim, Minsu 0000-0003-4472-0926 minsukim@contractor.usgs.gov","orcid":"https://orcid.org/0000-0003-4472-0926","contributorId":216429,"corporation":false,"usgs":true,"family":"Kim","given":"Minsu","email":"minsukim@contractor.usgs.gov","affiliations":[{"id":54490,"text":"KBR, Inc., under contract to USGS","active":true,"usgs":false}],"preferred":true,"id":764745,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70203935,"text":"70203935 - 2019 - Spatially consistent high-resolution land surface temperature mosaics for thermophysical mapping of the Mojave Desert","interactions":[],"lastModifiedDate":"2019-06-24T15:50:40","indexId":"70203935","displayToPublicDate":"2019-06-13T15:47:34","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3380,"text":"Sensors","active":true,"publicationSubtype":{"id":10}},"title":"Spatially consistent high-resolution land surface temperature mosaics for thermophysical mapping of the Mojave Desert","docAbstract":"Daytime and nighttime thermal infrared observations acquired by the ASTER and MODIS instruments onboard the NASA Terra spacecraft have produced a dataset that can be used to map thermophysical properties across large regions, which have implications on surface processes, thermal environments and habitat suitability for desert species. ASTER scenes acquired between 2004 and 2012 are combined using new mosaicking and data-fusion techniques to produce a map of daytime and nighttime land surface temperature with coverage exclusive of the effects of clouds and weather. These data are combined with Landsat 7 visible imagery to generate a consistent map of apparent thermal inertia (ATI), which is related to the presence of exposed bedrock, rocks, fine-grained sediments and water on the surface. The resulting datasets are compared to known geomorphic units and surface types to generate an interpreted mechanical composition map of the entire Mojave Desert at 100 m per pixel that is most sensitive to large clast size distinctions in grain size distribution.","language":"English","publisher":"MDPI","doi":"10.3390/s19122669","usgsCitation":"Nowicki, S.A., Inman, R.D., Esque, T., Nussear, K., and Edwards, C., 2019, Spatially consistent high-resolution land surface temperature mosaics for thermophysical mapping of the Mojave Desert: Sensors, v. 19, no. 12, 2669; 17 p., https://doi.org/10.3390/s19122669.","productDescription":"2669; 17 p.","ipdsId":"IP-093332","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":467532,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/s19122669","text":"Publisher Index Page"},{"id":364965,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"ARizone, California, Nevada, Utah","otherGeospatial":"Mojave Desert","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -119,\n 34\n ],\n [\n -113,\n 34\n ],\n [\n -113,\n 37\n ],\n [\n -119,\n 37\n ],\n [\n -119,\n 34\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"19","issue":"12","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2019-06-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Nowicki, Scott A","contributorId":216483,"corporation":false,"usgs":false,"family":"Nowicki","given":"Scott","email":"","middleInitial":"A","affiliations":[{"id":13339,"text":"University of New Mexico, Albuquerque","active":true,"usgs":false}],"preferred":false,"id":764840,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Inman, Richard D. 0000-0002-1982-7791 rdinman@usgs.gov","orcid":"https://orcid.org/0000-0002-1982-7791","contributorId":187754,"corporation":false,"usgs":true,"family":"Inman","given":"Richard","email":"rdinman@usgs.gov","middleInitial":"D.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":764841,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Esque, Todd 0000-0002-4166-6234 tesque@usgs.gov","orcid":"https://orcid.org/0000-0002-4166-6234","contributorId":195896,"corporation":false,"usgs":true,"family":"Esque","given":"Todd","email":"tesque@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":764842,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Nussear, Kenneth","contributorId":194538,"corporation":false,"usgs":false,"family":"Nussear","given":"Kenneth","affiliations":[{"id":24618,"text":"Department of Geography, University of Nevada, Reno, Reno, NV","active":true,"usgs":false}],"preferred":false,"id":764843,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Edwards, Christopher S.","contributorId":206168,"corporation":false,"usgs":false,"family":"Edwards","given":"Christopher S.","affiliations":[{"id":7202,"text":"NAU","active":true,"usgs":false}],"preferred":false,"id":764844,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70202483,"text":"sir20195011 - 2019 - Hydrologic and hydraulic analyses of selected streams in Richland County, Ohio","interactions":[],"lastModifiedDate":"2019-06-18T08:53:48","indexId":"sir20195011","displayToPublicDate":"2019-06-13T15:11:21","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2019-5011","displayTitle":"Hydrologic and Hydraulic Analyses of Selected Streams in Richland County, Ohio","title":"Hydrologic and hydraulic analyses of selected streams in Richland County, Ohio","docAbstract":"Hydrologic and hydraulic analyses were done for selected reaches of Clear Fork Mohican River and Cedar Fork in Richland County, Ohio. To update and expand a portion of the Federal Emergency Management Agency detailed Flood Insurance Study, the U.S. Geological Survey (USGS) and the Muskingum Watershed Conservancy District initiated a cooperative study. The study comprised an 18.6-mile reach of the Clear Fork Mohican River and a 5.9-mile reach of Cedar Fork.
Historical streamflow data from the streamgage Clear Fork Mohican River at Bellville, Ohio (USGS station number 03131982) and regional regression equations were used to estimate instantaneous peak streamflows for floods with 10-, 4-, 2-, 1-, and 0.2-percent and 1-percent plus annual exceedance probabilities. The 1-percent plus flood elevation is defined by the Federal Emergency Management Agency as a flood elevation derived by using streamflows that include the average predictive error for the regression equation streamflow calculation for the Flood Risk project. This error is then added to the 1-percent annual exceedance probability flood streamflow to calculate the new 1-percent plus streamflow.
The annual exceedance probability streamflows were then used in a Hydrologic Engineering Center-River Analysis System step-backwater model to determine water-surface elevation profiles and flood-inundation boundaries for the 10-, 4-, 2-, 1-, and 0.2-percent and 1-percent plus annual exceedance probability floods and a regulatory floodway along a selected reach of each stream. The Clear Fork Mohican River model was calibrated to 16 flood events by using the current stage-streamflow relation at the streamgage Clear Fork Mohican River at Bellville, Ohio (USGS station number 03131982) and a submersible pressure transducer. Flood-inundation boundaries for the 1- and 0.2-percent annual exceedance probability floods and a regulatory floodway were mapped for each stream.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20195011","collaboration":"Prepared in cooperation with the Muskingum Watershed Conservancy District and Richland County","usgsCitation":"Ostheimer, C.J., 2019, Hydrologic and hydraulic analyses of selected streams in Richland County, Ohio: U.S. Geological Survey Scientific Investigations Report 2019–5011, 18 p., https://doi.org/10.3133/sir20195011.","productDescription":"Report: iv, 18 p., Data Release","numberOfPages":"26","ipdsId":"IP-100978","costCenters":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"links":[{"id":364655,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9NMXM5B","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Geospatial datasets and hydraulic models of the Clear Fork Mohican River and Cedar Fork in Richland County, Ohio"},{"id":364654,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2019/5011/sir20195011.pdf","text":"Report","size":"2.67 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2019–5011"},{"id":364653,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2019/5011/coverthb.jpg"}],"country":"United States","state":"Ohio","county":"Richland county","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -82.66525268554688,\n 40.54850462620186\n ],\n [\n -82.33943939208984,\n 40.54850462620186\n ],\n [\n -82.33943939208984,\n 40.77352187640244\n ],\n [\n -82.66525268554688,\n 40.77352187640244\n ],\n [\n -82.66525268554688,\n 40.54850462620186\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Ohio-Kentucky-Indiana Water Science Center
U.S. Geological Survey
6460 Busch Boulevard Suite 100
Columbus, OH 43229–1737
The current research builds upon a previously published study that demonstrated the combination of Raman spectroscopy coupled with multivariate analysis (MVA) for the prediction of thermal maturity in coal by evaluating the efficacy of this method for the prediction of thermal maturity in shale. MVA techniques eliminate analyst bias in peak-fitting methods by using the full Raman spectrum, and then extricating the important spectral regions for distinguishing samples and building accurate, robust models. Partial least squares (PLS) regression models were developed using Raman spectra and VRo values (0.58–4.59%) for 53 geographically diverse shale chip samples, and 43 shale powder samples. Separate PLS models were built using Raman spectra from shale chips or powders. The calibration sets were validated using approximately one-third of the samples to rigorously assess the predictive accuracy of the models. The root mean standard error of prediction was 0.24 for the shale chip model, and 0.28 for the shale powder model. The coefficients of determination (R2) for the cross-validated data sets were identical (0.90, chips; 0.90, powders), revealing a strong linearity despite the geographic and age diversity of the samples. This study demonstrates the validity of using PLS models for the prediction of shale VRo from Raman spectra. The MVA method described herein presents a Raman alternative to the VRo industry benchmark for assessing thermal maturity in shale that is not imperiled by the shortcomings and subjectivity of peak-fitting methods.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.fuel.2019.05.156","usgsCitation":"Lupoi, J.S., Hackley, P.C., Birsic, E., Fritz, L.P., Solotky, L., Weislogel, A., and Schlaegle, S., 2019, Quantitative evaluation of vitrinite reflectance in shale using Raman spectroscopy and multivariate analysis: Fuel, v. 254, 115573, 9 p., https://doi.org/10.1016/j.fuel.2019.05.156.","productDescription":"115573, 9 p.","ipdsId":"IP-106000","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":467534,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.fuel.2019.05.156","text":"Publisher Index Page"},{"id":384585,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"geometry\": {\n \"type\": 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However, fish navigate the transient waters of intertidal zones, floodplains, intermittent and ephemeral streams, lake margins, seasonally frozen lakes and streams, and anthropogenic aquatic habitats across the globe to access important resources. The selective pressures imposed by water impermanence (i.e., freezing, drying, tidal fluctuations), however, operate similarly across taxa and ecosystems. These similarities are formalized into a conceptual model relating habitat use to surface water phenology. Whereas all necessary life history functions (spawning, foraging, refuge, and dispersal) can be accomplished in temporary habitats, the timing, duration, and predictability of water act as a “life history filter” to which habitats can be used and for what purpose. Habitats wet from minutes to months may all be important—albeit in different ways, for different species. If life history needs co-occur with accessibility, temporary habitats can contribute substantially to individual fitness, overall production and important metapopulation processes. This heuristic is intended to promote research, recognition and conservation of these frequently overlooked habitats that can be disproportionately important relative to their size or brevity of existence. There is a pressing need to quantify how use of temporary aquatic habitats translates to individual fitness benefits, population size and temporal stability, and ecosystem-level consequences. Temporary aquatic habitats are being impacted at an alarming rate by anthropogenic activities altering their existence, phenology, and connectivity. It is timely that scientists, managers and policymakers consider the role these habitats play in global fish production.
","language":"English","publisher":"Wiley","doi":"10.1111/faf.12386","usgsCitation":"Heim, K., Falke, J.A., McMahon, T., Wipfli, M.S., and Calle, L., 2019, A general model of temporary aquatic habitat use: Water phenology as a life history filter: Fish and Fisheries, v. 20, no. 4, p. 802-816, https://doi.org/10.1111/faf.12386.","productDescription":"15 p.","startPage":"802","endPage":"816","ipdsId":"IP-101686","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":388228,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"20","issue":"4","noUsgsAuthors":false,"publicationDate":"2019-06-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Heim, Kurt C.","contributorId":264533,"corporation":false,"usgs":false,"family":"Heim","given":"Kurt C.","affiliations":[{"id":48645,"text":"umt","active":true,"usgs":false}],"preferred":false,"id":821645,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Falke, Jeffrey A. 0000-0002-6670-8250 jfalke@usgs.gov","orcid":"https://orcid.org/0000-0002-6670-8250","contributorId":5195,"corporation":false,"usgs":true,"family":"Falke","given":"Jeffrey","email":"jfalke@usgs.gov","middleInitial":"A.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":821644,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McMahon, Thomas E.","contributorId":264534,"corporation":false,"usgs":false,"family":"McMahon","given":"Thomas E.","affiliations":[{"id":48645,"text":"umt","active":true,"usgs":false}],"preferred":false,"id":821646,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wipfli, Mark S. 0000-0002-4856-6068 mwipfli@usgs.gov","orcid":"https://orcid.org/0000-0002-4856-6068","contributorId":1425,"corporation":false,"usgs":true,"family":"Wipfli","given":"Mark","email":"mwipfli@usgs.gov","middleInitial":"S.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":821643,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Calle, Leonardo","contributorId":264535,"corporation":false,"usgs":false,"family":"Calle","given":"Leonardo","email":"","affiliations":[{"id":48645,"text":"umt","active":true,"usgs":false}],"preferred":false,"id":821647,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70198478,"text":"70198478 - 2019 - Evaluating mechanisms of plant‐mediated effects on herbivore persistence and occupancy across an ecoregion","interactions":[],"lastModifiedDate":"2020-05-27T15:24:46.382467","indexId":"70198478","displayToPublicDate":"2019-06-12T10:18:25","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Evaluating mechanisms of plant‐mediated effects on herbivore persistence and occupancy across an ecoregion","docAbstract":"Contemporary climate change is rapidly creating one of the greatest challenges for management and conservation during the 21st century. Mountain ecosystems, which have a high degree of spatial heterogeneity and contain numerous habitat specialists, have been identified as particularly vulnerable. We used data from multiple years across sites spanning a >40 million ha ecoregion to test hypotheses regarding how community‐level characteristics of vegetation may affect a mammalian generalist herbivore, the American pika (Ochotona princeps ). We examined patterns of pika persistence across sites in the hydrographic Great Basin, and occupancy within a subset of these sites. We used mixed‐effects logistic regression models to compare evidence in support of competing explanations for each pattern within an information–theoretic framework (using Akaike's information criterion). Models reflected four hypothesized classes of mechanisms related to nutritional ecology, ecosystem function, indirect indication of climatic effects, and (synergistic) combinations of these three classes. At the site level, models reflecting synergistic effects received the most support. At the within‐site level, support appeared to be split equally among hypotheses containing predictors related to either nutritional ecology or indirect climate effects. Well‐supported predictors included cover of invasive plant species, cover of more‐xeric plant species, species evenness, and proportion of graminoid species. Our results both (1) identify important aspects of vegetation communities that may influence herbivore distribution in mountainous areas across a large, diverse geographic region, and (2) contribute to an improved understanding of how mountain ecosystems may be affected by ongoing climate change, more broadly.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.2764","usgsCitation":"Wilkening, J.L., Cole, E.J., and Beever, E., 2019, Evaluating mechanisms of plant‐mediated effects on herbivore persistence and occupancy across an ecoregion: Ecosphere, v. 10, no. 6, e02764, 19 p., https://doi.org/10.1002/ecs2.2764.","productDescription":"e02764, 19 p.","ipdsId":"IP-094589","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":467537,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.2764","text":"Publisher Index Page"},{"id":375082,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Idaho, Nevada, Oregon, Utah, Wyoming","otherGeospatial":"Great Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -118.01513671875,\n 36.82687474287728\n ],\n [\n -112.67578124999999,\n 37.70120736474139\n ],\n [\n -112.06054687499999,\n 40.26276066437183\n ],\n [\n -112.32421875,\n 41.983994270935625\n ],\n [\n -113.04931640625,\n 43.18114705939968\n ],\n [\n -113.37890625,\n 43.50075243569041\n ],\n [\n -114.54345703125,\n 42.293564192170095\n ],\n [\n -115.57617187499999,\n 41.705728515237524\n ],\n [\n -116.3232421875,\n 41.49212083968776\n ],\n [\n -117.59765625,\n 41.27780646738183\n ],\n [\n -117.90527343750001,\n 42.08191667830631\n ],\n [\n -118.36669921875,\n 43.6599240747891\n ],\n [\n -119.02587890624999,\n 44.134913443750726\n ],\n [\n -120.25634765624999,\n 43.91372326852401\n ],\n [\n -121.17919921875001,\n 43.56447158721811\n ],\n [\n -121.06933593749999,\n 41.393294288784865\n ],\n [\n -120.7177734375,\n 40.29628651711716\n ],\n [\n -120.38818359375,\n 39.26628442213066\n ],\n [\n -118.01513671875,\n 36.82687474287728\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"10","issue":"6","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2019-06-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Wilkening, Jennifer L. 0000-0001-8748-4578","orcid":"https://orcid.org/0000-0001-8748-4578","contributorId":127685,"corporation":false,"usgs":false,"family":"Wilkening","given":"Jennifer","email":"","middleInitial":"L.","affiliations":[{"id":7111,"text":"U. 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Ecology & Evol.Biol., PhD Student","active":true,"usgs":false}],"preferred":false,"id":741602,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cole, Evan J.","contributorId":206741,"corporation":false,"usgs":false,"family":"Cole","given":"Evan","email":"","middleInitial":"J.","affiliations":[{"id":37388,"text":"Dept. of Environmental Science, University of San Francisco","active":true,"usgs":false}],"preferred":false,"id":741603,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Beever, Erik A. 0000-0002-9369-486X ebeever@usgs.gov","orcid":"https://orcid.org/0000-0002-9369-486X","contributorId":147685,"corporation":false,"usgs":true,"family":"Beever","given":"Erik A.","email":"ebeever@usgs.gov","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true},{"id":5072,"text":"Office of Communication and Publishing","active":true,"usgs":true}],"preferred":true,"id":741601,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70205244,"text":"70205244 - 2019 - Refinement of eDNA as an early monitoring tool at the landscape-level: Study design considerations","interactions":[],"lastModifiedDate":"2019-09-10T10:05:40","indexId":"70205244","displayToPublicDate":"2019-06-12T09:56:33","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1450,"text":"Ecological Applications","active":true,"publicationSubtype":{"id":10}},"title":"Refinement of eDNA as an early monitoring tool at the landscape-level: Study design considerations","docAbstract":"Natural resource managers use data on the spatial range of species to guide management decisions. These data come from survey or monitoring efforts that use a wide variety of tools. Environmental DNA (eDNA) is a surveillance tool that uses genetic markers for detecting species and holds potential as a tool for large-scale monitoring programs. Two challenges of eDNA-based studies are uncertainties created by imperfect capture of eDNA in collection samples (e.g., water field samples) and imperfect detection of eDNA using molecular methods (e.g., quantitative PCR). Occurrence models can be used to address these challenges, thus we use an occurrence model to address two objectives: First, determine how many samples were required to detect species using eDNA; Second, examine when and where to take samples. We collected water samples from three different habitat types in the Upper Mississippi River when both Bighead Carp and Silver Carp were known to be present based on telemetry detections. Each habitat type (backwater, tributary, and impoundment) was sampled during April, May and November. Detections of eDNA for both species varied across sites and months, but were generally low, 0 - 19.3% of samples were positive for eDNA. Overall, we found that eDNA-based sampling holds promise to be a powerful monitoring tool for resource managers, however, limitations of eDNA-based sampling include different biological and ecological characteristics of target species such as seasonal habitat usage patterns as well as aspects of different physical environments that impact the implementation of these methods such as water temperature.","language":"English","publisher":"Wiley","doi":"10.1002/eap.1951","usgsCitation":"Mize, E.L., Erickson, R.A., Merkes, C.M., Berndt, N., Bockrath, K., Credico, J., Grueneis, N., Merry, J., Mosel, K., Tuttle-Lau, M., Von Ruden, K., Amberg, J., Baerwaldt, K., Finney, S., and Monroe, E., 2019, Refinement of eDNA as an early monitoring tool at the landscape-level: Study design considerations: Ecological Applications, v. 29, no. 6, e01951, https://doi.org/10.1002/eap.1951.","productDescription":"e01951","ipdsId":"IP-099527","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences 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Grazing lawns are maintained in quality and quantity by repeated grazing and are a result of a positive feedback since the availability of grazing lawn can increase herbivore populations and increased herbivore populations can result in an increase in grazing lawn extent. We sampled aerial imagery from a long-term dataset (>20 yrs) at an internationally important breeding area for avian herbivores to model changes in grazing lawn abundance over time and identify the possible factors impacting those changes, including numbers of breeding birds, their primary predator, and spring phenology. Our data suggests that avian herbivores and their predators likely exert strong impacts on plant communities and may drive vegetation abundance. Decreases in the number of herbivore nests in our study coincided with an almost complete lack of grazing lawn in the mid-2000s. Any factors dictating the amount of grazing lawn available for avian herbivores could strongly influence breeding success and the maximum size of these populations. Our results demonstrate the importance of studying complex interactions among predators, herbivores and plants, and population moderation by both bottom-up and top-down processes.","language":"English","publisher":"Wiley","doi":"10.1002/ecs2.2767","usgsCitation":"Uher-Koch, B.D., Schmutz, J.A., Wilson, H.M., Anthony, R., Day, T.L., Fondell, T.F., Person, B.T., and Sedinger, J.S., 2019, Ecosystem scale loss of grazing habitat impacted by abundance of dominant herbivores: Ecosphere, v. 10, no. 6, e02767, https://doi.org/10.1002/ecs2.2767.","productDescription":"e02767","ipdsId":"IP-101279","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":467539,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.2767","text":"Publisher Index Page"},{"id":368147,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"10","issue":"6","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2019-06-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Uher-Koch, Brian D. 0000-0002-1885-0260 buher-koch@usgs.gov","orcid":"https://orcid.org/0000-0002-1885-0260","contributorId":5117,"corporation":false,"usgs":true,"family":"Uher-Koch","given":"Brian","email":"buher-koch@usgs.gov","middleInitial":"D.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":772645,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schmutz, Joel A. 0000-0002-6516-0836 jschmutz@usgs.gov","orcid":"https://orcid.org/0000-0002-6516-0836","contributorId":1805,"corporation":false,"usgs":true,"family":"Schmutz","given":"Joel","email":"jschmutz@usgs.gov","middleInitial":"A.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":772646,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wilson, Heather M.","contributorId":37056,"corporation":false,"usgs":false,"family":"Wilson","given":"Heather","email":"","middleInitial":"M.","affiliations":[{"id":13236,"text":"U.S. Fish and Wildlife Service, Migratory Bird Management","active":true,"usgs":false}],"preferred":false,"id":772647,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Anthony, R Michael","contributorId":219603,"corporation":false,"usgs":false,"family":"Anthony","given":"R Michael","affiliations":[{"id":40038,"text":"USGS Alaska Science Center (Retired)","active":true,"usgs":false}],"preferred":false,"id":772648,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Day, Thomas L","contributorId":219604,"corporation":false,"usgs":false,"family":"Day","given":"Thomas","email":"","middleInitial":"L","affiliations":[{"id":12915,"text":"Alaska Pacific University","active":true,"usgs":false}],"preferred":false,"id":772649,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Fondell, Thomas F tfondell@usgs.gov","contributorId":219605,"corporation":false,"usgs":false,"family":"Fondell","given":"Thomas","email":"tfondell@usgs.gov","middleInitial":"F","affiliations":[{"id":40039,"text":"USGS Alaska Science Center (Deceased)","active":true,"usgs":false}],"preferred":false,"id":772650,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Person, Brian T.","contributorId":107457,"corporation":false,"usgs":false,"family":"Person","given":"Brian","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":772651,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Sedinger, James S.","contributorId":213694,"corporation":false,"usgs":false,"family":"Sedinger","given":"James","email":"","middleInitial":"S.","affiliations":[{"id":12742,"text":"University of Nevada Reno","active":true,"usgs":false}],"preferred":false,"id":772652,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70207038,"text":"70207038 - 2019 - Adaptive harvest management for the Svalbard population of pink‐footed geese: 2019 progress summary","interactions":[],"lastModifiedDate":"2019-12-04T15:55:23","indexId":"70207038","displayToPublicDate":"2019-06-11T15:54:36","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"title":"Adaptive harvest management for the Svalbard population of pink‐footed geese: 2019 progress summary","docAbstract":"This report describes an Adaptive Harvest Management (AHM) program designed to maintain the Svalbard population of Pink-footed Geese (Anser brachyrhynchus) near their target level (60,000) by providing sustainable harvests in Norway and Denmark. Specifically, this report provides recent monitoring and assessment results and their implications for the 2019 hunting season.\n\nIn this report we provide results for both the set of nine discrete population models used since 2013 and for a recently developed Integrated Population Model (IPM). Updating model weights (set of nine models) and model parameters (IPM) use the most recent monitoring information available (i.e. through spring 2019). We also compare optimal harvest strategies based on the two modeling approaches. Of growing concern, however, has been the observation that the predictive ability of the original population models has declined over time. Going forward, we suggest that use of the IPM is a superior modeling approach for setting hunting seasons for\nPink-footed Geese.\n\nPopulation sizes in May as estimated by the IPM are in general agreement with counts and capture-markrecapture estimates but are more precise. Estimates of survival from natural causes were relatively constant over time with a mean of 0.93 and estimates of adult kill rate ranged from 0.04 to 0.13. Estimates of countryspecific kill rates suggest that most of the overall increase in kill rate in recent years is attributed to increasing harvest pressure in Denmark. With respect to productivity, the IPM produced estimates of preseason age ratio that were variable over time, but on average suggested that young constituted about 18% of the population just\nprior to the hunting season. Estimates of the preseason age ratio correlated well with the number of days above freezing in May in Svalbard. Our results suggest that population size has stabilized because of declining survival rates that have accompanied an increase in kill rates. Adoption of the IPM this year would result in a harvest quota for the 2019 hunting season of 22,000, based on a May population estimate of 76,500 (95% CI: 66,800 – 86,600) and 8 days above freezing in Svalbard. Using the agreed upon allocation of the total allowable\nharvest, the quotas are 6,600 for Norway and 15,400 for Denmark. Assuming the total quota is met, the IPM predicts a population size in May 2020 of 64,900 (95% CI: 50,300 – 83,700).\n\nWe note that the updated set of original models used since 2013 suggests an allowable harvest of 40,000 in 2019 based on a November 2018 count of 91,900 geese (comprised of 12,900 young and 79,000 adults). We are skeptical of this large quota, however. Using all available demographic data suggests that the November 2018 population size was lower than that indicated by the count and that the winter population experienced more natural mortality than expected. These insights demonstrate the inherent risk of basing a harvest quota\non a single population count, irrespective of other demographic data.","language":"English","publisher":"AEWA European Goose Management International Working Group","collaboration":"Aarhus University, Denmark","usgsCitation":"Johnson, F., Heldbjerg, H., Clausen, K.K., and Madsen, J., 2019, Adaptive harvest management for the Svalbard population of pink‐footed geese: 2019 progress summary, 19 p.","productDescription":"19 p.","ipdsId":"IP-108881","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":369923,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":369893,"type":{"id":11,"text":"Document"},"url":"https://egmp.aewa.info/sites/default/files/meeting_files/documents/AEWA_EGM_IWG_4_7_PFG_AHM%20update.pdf"}],"publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Johnson, Fred 0000-0002-5854-3695","orcid":"https://orcid.org/0000-0002-5854-3695","contributorId":221013,"corporation":false,"usgs":true,"family":"Johnson","given":"Fred","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":776594,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Heldbjerg, Henning","contributorId":174479,"corporation":false,"usgs":false,"family":"Heldbjerg","given":"Henning","email":"","affiliations":[],"preferred":false,"id":776595,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Clausen, Kevin K.","contributorId":174355,"corporation":false,"usgs":false,"family":"Clausen","given":"Kevin","email":"","middleInitial":"K.","affiliations":[{"id":13419,"text":"Aarhus University, Denmark","active":true,"usgs":false}],"preferred":false,"id":776596,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Madsen, Jesper","contributorId":178168,"corporation":false,"usgs":false,"family":"Madsen","given":"Jesper","email":"","affiliations":[],"preferred":false,"id":776597,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70203875,"text":"70203875 - 2019 - Soil characteristics are associated with gradients of big sagebrush canopy structure after disturbance","interactions":[],"lastModifiedDate":"2019-08-15T12:19:43","indexId":"70203875","displayToPublicDate":"2019-06-11T14:21:18","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Soil characteristics are associated with gradients of big sagebrush canopy structure after disturbance","docAbstract":"Reestablishing shrub canopy cover after disturbance in semi-arid ecosystems, such as sagebrush steppe, is essential to provide wildlife habitat and restore ecosystem functioning. While several studies have explored the effects of landscape and climate factors on the success or failure of sagebrush seeding, the influence of soil properties on gradients of shrub canopy structure in successfully seeded areas remains largely unexplored. In this study, we evaluated associations between soil properties and gradients in sagebrush canopy structure in stands that had successfully reestablished after fire and subsequent seeding treatments. Using a dataset collected across the Great Basin, USA, of sagebrush stands that had burned and reestablished\nbetween 1986 and 2013, we tested soil depth and texture, soil surface classification, biological soil crusts plus mean historical precipitation, solar heatload, and fire history as modeling variables to explore gradients in sagebrush canopy structure growth in terms of cover, height, and density. Deeper soils were associated with greater sagebrush canopy structure development in terms of plant density and percent cover, coarser textured soils were associated with greater sagebrush cover and density, and more clayey soils were typically associated with greater height. Biological crust presence was also positively associated with enhanced sagebrush canopy growth, but adding more demographically or morphologically explicit descriptions of biocrust communities did not improve explanatory power. Increasing heatload had a negative effect on sagebrush canopy structure growth, and increased mean annual precipitation was only associated with greater sagebrush height. Given that conservation and restoration of the sagebrush steppe ecosystems has become a priority for land managers, the associations we identify between gradients in post-fire sagebrush canopy structure growth and field-identifiable soil characteristics may improve planning of land treatments for sagebrush restoration and the understanding of semi-arid ecosystem functioning and post-disturbance dynamics.","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.2780","usgsCitation":"Barnard, D., Germino, M., Arkle, R., Bradford, J., Duniway, M., Pilliod, D.S., Pyke, D., Shriver, R., and Welty, J.L., 2019, Soil characteristics are associated with gradients of big sagebrush canopy structure after disturbance: Ecosphere, v. 10, no. 6, e02780, 12 p., https://doi.org/10.1002/ecs2.2780.","productDescription":"e02780, 12 p.","ipdsId":"IP-101399","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":467540,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.2780","text":"Publisher Index Page"},{"id":364792,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"10","issue":"6","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2019-06-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Barnard, David","contributorId":216338,"corporation":false,"usgs":true,"family":"Barnard","given":"David","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":764545,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Germino, Matthew J. 0000-0001-6326-7579 mgermino@usgs.gov","orcid":"https://orcid.org/0000-0001-6326-7579","contributorId":152582,"corporation":false,"usgs":true,"family":"Germino","given":"Matthew J.","email":"mgermino@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":764544,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Arkle, Robert 0000-0003-3021-1389","orcid":"https://orcid.org/0000-0003-3021-1389","contributorId":216339,"corporation":false,"usgs":true,"family":"Arkle","given":"Robert","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":764546,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bradford, John","contributorId":216340,"corporation":false,"usgs":true,"family":"Bradford","given":"John","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":764547,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Duniway, Michael","contributorId":216341,"corporation":false,"usgs":true,"family":"Duniway","given":"Michael","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":764548,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Pilliod, David S. 0000-0003-4207-3518","orcid":"https://orcid.org/0000-0003-4207-3518","contributorId":216342,"corporation":false,"usgs":true,"family":"Pilliod","given":"David","middleInitial":"S.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":764549,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Pyke, David 0000-0002-4578-8335 david_a_pyke@usgs.gov","orcid":"https://orcid.org/0000-0002-4578-8335","contributorId":216343,"corporation":false,"usgs":true,"family":"Pyke","given":"David","email":"david_a_pyke@usgs.gov","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":764550,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Shriver, Robert","contributorId":216344,"corporation":false,"usgs":true,"family":"Shriver","given":"Robert","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":764551,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Welty, Justin L. 0000-0001-7829-7324 jwelty@usgs.gov","orcid":"https://orcid.org/0000-0001-7829-7324","contributorId":216345,"corporation":false,"usgs":true,"family":"Welty","given":"Justin","email":"jwelty@usgs.gov","middleInitial":"L.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":764552,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70203682,"text":"70203682 - 2019 - The roles of flow acceleration and deceleration in sediment suspension in the surf zone","interactions":[],"lastModifiedDate":"2019-06-12T08:41:19","indexId":"70203682","displayToPublicDate":"2019-06-11T12:30:27","publicationYear":"2019","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"The roles of flow acceleration and deceleration in sediment suspension in the surf zone","docAbstract":"Prediction of sediment suspension in the surf zone remains elusive. We explore how suspended sediment concentration at 19 cm above the bed in the mid-surf zone during a storm is influenced by flow acceleration and deceleration. There is a tendency for higher suspended sediment concentrations during onshore flow, with decelerating onshore flows having higher concentrations than steady, accelerating, or reversing flows. The development of models that exploit information on flow acceleration, deceleration, and flow reversal may lead to improved ability to predict suspended sediment transport in the surf zone and resulting geomorphic changes.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Coastal Sediments 2019, Proceedings of the 9th International Conference","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"9th International Conference on Coastal Sediments 2019","conferenceDate":"May 27-31, 2019","conferenceLocation":"Tampa/St. Petersburg, Florida","language":"English","publisher":"World Scientific","doi":"10.1142/9789811204487_0050","usgsCitation":"Jaffe, B.E., and La Selle, S., 2019, The roles of flow acceleration and deceleration in sediment suspension in the surf zone, in Coastal Sediments 2019, Proceedings of the 9th International Conference, Tampa/St. Petersburg, Florida, May 27-31, 2019, p. 565-576, https://doi.org/10.1142/9789811204487_0050.","productDescription":"12 p.","startPage":"565","endPage":"576","ipdsId":"IP-105729","costCenters":[{"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}],"links":[{"id":364594,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2019-05-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Jaffe, Bruce E. 0000-0002-8816-5920 bjaffe@usgs.gov","orcid":"https://orcid.org/0000-0002-8816-5920","contributorId":2049,"corporation":false,"usgs":true,"family":"Jaffe","given":"Bruce","email":"bjaffe@usgs.gov","middleInitial":"E.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true}],"preferred":true,"id":763586,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"La Selle, SeanPaul 0000-0002-4500-7885 slaselle@usgs.gov","orcid":"https://orcid.org/0000-0002-4500-7885","contributorId":181565,"corporation":false,"usgs":true,"family":"La Selle","given":"SeanPaul","email":"slaselle@usgs.gov","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":763587,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70203773,"text":"70203773 - 2019 - Is barotrauma an important factor in the discard mortality of Yellow Perch?","interactions":[],"lastModifiedDate":"2019-06-12T08:46:29","indexId":"70203773","displayToPublicDate":"2019-06-11T09:58:46","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2287,"text":"Journal of Fish and Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Is barotrauma an important factor in the discard mortality of Yellow Perch?","docAbstract":"In physoclistous fishes, barotrauma caused by rapid decompression during capture may be an important source of fishing mortality that is unquantified for some fisheries. We developed a predictive logistic model for barotrauma incidence in Yellow Perch Perca flavescens and applied this model to Ohio's recreational and commercial fisheries in Lake Erie where fisheries managers implicitly consider discard mortality to be negligible in current stock assessment. As expected, capture depth explained most of the variation in incidence, with comparatively small effects of season, sex, and size categories. Measurements of whole body and gonad density provided limited explanation for the categorical effects. Both fisheries spanned a range of depths (7.6 to 16.8 m) that corresponded to a broad range of barotrauma incidence (13 to 74%). Using a recent example, we estimated that additional fishing mortality due to barotrauma in discards was approximately six-fold higher in the commercial than recreational fishery. Overall, this additional mortality was <1% of lake-wide population size estimates. Thus, the assumption that all discarded Yellow Perch survive is unlikely to result in a detectable bias in population estimates. One caveat is that we still do not understand how strong year-classes might influence discard mortality via increased discard rate and barotrauma incidence for small fish.","language":"English","publisher":"US Fish and Wildlife Service","doi":"10.3996/062018-JFWM-056","usgsCitation":"Knight, C., Kraus, R.T., Panos, D., Gorman, A.M., Leonhardt, B., Robinson, J., and Thomas, M.J., 2019, Is barotrauma an important factor in the discard mortality of Yellow Perch?: Journal of Fish and Wildlife Management, v. 10, no. 1, p. 69-78, https://doi.org/10.3996/062018-JFWM-056.","productDescription":"10 p.","startPage":"69","endPage":"78","onlineOnly":"N","ipdsId":"IP-098140","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":467541,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3996/062018-jfwm-056","text":"Publisher Index Page"},{"id":364587,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Lake Erie","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -84,\n 41\n ],\n [\n -78.49731445312499,\n 41\n ],\n [\n -78.49731445312499,\n 43.36512572875844\n ],\n [\n -84,\n 43.36512572875844\n ],\n [\n -84,\n 41\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"10","issue":"1","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationDate":"2018-12-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Knight, Carey","contributorId":216161,"corporation":false,"usgs":false,"family":"Knight","given":"Carey","affiliations":[{"id":16232,"text":"Ohio Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":764065,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kraus, Richard T. 0000-0003-4494-1841 rkraus@usgs.gov","orcid":"https://orcid.org/0000-0003-4494-1841","contributorId":2609,"corporation":false,"usgs":true,"family":"Kraus","given":"Richard","email":"rkraus@usgs.gov","middleInitial":"T.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":764064,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Panos, Demetra","contributorId":216162,"corporation":false,"usgs":false,"family":"Panos","given":"Demetra","email":"","affiliations":[{"id":39374,"text":"University of California Northridge","active":true,"usgs":false}],"preferred":false,"id":764066,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gorman, Ann Marie","contributorId":145525,"corporation":false,"usgs":false,"family":"Gorman","given":"Ann","email":"","middleInitial":"Marie","affiliations":[],"preferred":false,"id":764067,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Leonhardt, Benjamin","contributorId":216163,"corporation":false,"usgs":false,"family":"Leonhardt","given":"Benjamin","affiliations":[{"id":16232,"text":"Ohio Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":764068,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Robinson, Jason","contributorId":216164,"corporation":false,"usgs":false,"family":"Robinson","given":"Jason","affiliations":[{"id":13678,"text":"New York State Department of Environmental Conservation","active":true,"usgs":false}],"preferred":false,"id":764069,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Thomas, Michael J.","contributorId":196240,"corporation":false,"usgs":false,"family":"Thomas","given":"Michael","email":"","middleInitial":"J.","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":764070,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70202729,"text":"ds1104 - 2019 - Regional hydraulic geometry characteristics of stream channels in the Ouachita Mountains of Arkansas","interactions":[],"lastModifiedDate":"2019-06-11T15:50:54","indexId":"ds1104","displayToPublicDate":"2019-06-10T15:40:56","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"1104","displayTitle":"Regional Hydraulic Geometry Characteristics of Stream Channels in the Ouachita Mountains of Arkansas","title":"Regional hydraulic geometry characteristics of stream channels in the Ouachita Mountains of Arkansas","docAbstract":"Many stream channel infrastructure, habitat, and restoration projects are being undertaken on small streams throughout Arkansas by various Federal, State, and local agencies and by private organizations and businesses with limited data on local geomorphology and streamflow relations. Equations are needed that relate drainage area above stable stream reaches and the associated basin characteristics to bankfull streamflow and the associated channel dimensions. These equations, along with streambed material particle information, provide information that can improve stream channel projects. The U.S. Geological Survey and the Arkansas Natural Resources Commission in cooperation with the U.S. Army Corps of Engineers, Little Rock District, undertook a study to develop these equations for streams in the Ouachita Mountains of Arkansas.
Seventeen streamgages operated by the U.S. Geological Survey, located on streams in the Ouachita Mountains, were selected for analysis. Regional hydraulic geometry curves that express the mathematical relation between the bankfull channel dimensions (cross-sectional area, top width, mean depth, and streamflow) and the contributing drainage areas were developed. Streambed material measurements were collected to develop descriptive statistics of the streambed particle-size distributions and percentages of substrate type at each study site. Stream reaches at each study site were classified to the Rosgen level II stream type based on the average of stream channel metrics collected from site cross sections and profiles. Of the 17 selected Ouachita Mountain stream reaches, 6 were classified as B stream types, and 11 were classified as C stream types. The B stream types have infrequently spaced pools; very stable plan forms, profiles, and banks; and narrow, gently sloping valleys, where bank vegetation is a moderate component of stability. The C stream types are meandering, point bar, riffle-pool channels associated with broad valleys having well-defined flood plains and terraces composed of alluvial soils, where bank vegetation is typically a high component of stability.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds1104","collaboration":"Prepared in cooperation with the Arkansas Natural Resources Commission and the U.S. Army Corps of Engineers, Little Rock District","usgsCitation":"Pugh, A.L., and Redman, R.K., 2019, Regional hydraulic geometry characteristics of stream channels in the Ouachita Mountains of Arkansas: U.S. Geological Survey Data Series 1104, 25 p., https://doi.org/10.3133/ds1104.","productDescription":"Report: v, 25 p.; Data Release","numberOfPages":"35","onlineOnly":"Y","ipdsId":"IP-076095","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":364361,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/1104/ds1104.pdf","text":"Report","size":"8.10 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DS 1104"},{"id":364362,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://dx.doi.org/10.5066/F7BC3WNX","text":"USGS data release ","description":"USGS Data Release","linkHelpText":"Regional Hydraulic Geometry Characteristics of Stream Channels in the Ouachita Mountains of Arkansas"},{"id":364360,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/1104/coverthb.jpg"}],"country":"United States","state":"Arkansas","otherGeospatial":"Ouachita Mountains","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -95.350341796875,\n 33.6420625047537\n ],\n [\n -93.306884765625,\n 33.6420625047537\n ],\n [\n -93.306884765625,\n 35.34425514918409\n ],\n [\n -95.350341796875,\n 35.34425514918409\n ],\n [\n -95.350341796875,\n 33.6420625047537\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Lower Mississippi-Gulf Water Science Center
U.S. Geological Survey
640 Grassmere Park, Ste 100
Nashville, TN 37211
Before the 2018 collapse of the summit of Kīlauea volcano, a ca. 200 m in diameter lava lake inside of Halema‘uma‘u crater was embedded in a very active hydrothermal system. In 2015, we carried out an electrical conductivity survey and the data were inverted in 3D. The lack of conductivity contrast precludes distinguishing the lava column from the surrounding hydrothermal zones. Laboratory measurements on samples from the lava lake show that the conductivity of magma is significantly lower than that of hydrothermal zones but the high vesicularity of the upper part of the lava lake may decrease its macroscopic conductivity. Based on the 3D conductivity model, we distinguish at least two types of hydrothermal circulations: 1) one guided by the collapse faults of Halema‘uma‘u crater and by the magmatic column of the lava lake, and 2) another guided by previous caldera faults and fractures related to intrusions. We observe that the location of the faults formed during the 2018 collapse of the summit was greatly influenced by the hydrothermally altered zones.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jvolgeores.2019.06.001","usgsCitation":"Gailler, L., Kauahikaua, J.P., Lenat, J., Revil, A., Gresse, M., Ahmed, A.S., Cluzel, N., Manthilake, G., Gurioli, L., Johnson, T.B., Finizola, A., and Delcher, E., 2019, 3D electrical conductivity imaging of Halema‘uma‘u lava lake (Kīlauea volcano): Journal of Volcanology and Geothermal Research, v. 381, p. 185-192, https://doi.org/10.1016/j.jvolgeores.2019.06.001.","productDescription":"8 p.","startPage":"185","endPage":"192","ipdsId":"IP-094105","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":467543,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jvolgeores.2019.06.001","text":"Publisher Index Page"},{"id":367008,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"Kilauea Volcano","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -155.30402183532715,\n 19.388238642115578\n ],\n [\n -155.23415565490723,\n 19.388238642115578\n ],\n [\n -155.23415565490723,\n 19.433652713875333\n ],\n [\n -155.30402183532715,\n 19.433652713875333\n ],\n [\n -155.30402183532715,\n 19.388238642115578\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"381","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Gailler, Lydie 0000-0002-8132-2428","orcid":"https://orcid.org/0000-0002-8132-2428","contributorId":192584,"corporation":false,"usgs":false,"family":"Gailler","given":"Lydie","email":"","affiliations":[],"preferred":false,"id":769509,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kauahikaua, James P. 0000-0003-3777-503X jimk@usgs.gov","orcid":"https://orcid.org/0000-0003-3777-503X","contributorId":2146,"corporation":false,"usgs":true,"family":"Kauahikaua","given":"James","email":"jimk@usgs.gov","middleInitial":"P.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":769520,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lenat, Jean-Francois 0000-0002-4828-9013","orcid":"https://orcid.org/0000-0002-4828-9013","contributorId":218534,"corporation":false,"usgs":false,"family":"Lenat","given":"Jean-Francois","email":"","affiliations":[{"id":39864,"text":"Laboratoire Magmas et Volcans, Université Blaise Pascal","active":true,"usgs":false}],"preferred":false,"id":769510,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Revil, Andre","contributorId":218535,"corporation":false,"usgs":false,"family":"Revil","given":"Andre","email":"","affiliations":[{"id":39864,"text":"Laboratoire Magmas et Volcans, Université Blaise Pascal","active":true,"usgs":false}],"preferred":false,"id":769511,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gresse, Marceau 0000-0002-3937-3280","orcid":"https://orcid.org/0000-0002-3937-3280","contributorId":218536,"corporation":false,"usgs":false,"family":"Gresse","given":"Marceau","email":"","affiliations":[{"id":39865,"text":"Earthquake Research Institute, University of Tokyo, Tokyo, Japan","active":true,"usgs":false}],"preferred":false,"id":769512,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ahmed, Abdellahi Soueid 0000-0002-4279-0093","orcid":"https://orcid.org/0000-0002-4279-0093","contributorId":218537,"corporation":false,"usgs":false,"family":"Ahmed","given":"Abdellahi","email":"","middleInitial":"Soueid","affiliations":[{"id":39866,"text":"Univ. Grenoble Alpes, Univ. Savoie Mont Blanc, CNRS, IRD, IFSTTAR, ISTerre, 38000 10 Grenoble, France","active":true,"usgs":false}],"preferred":false,"id":769513,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Cluzel, Nicolas 0000-0002-2171-8789","orcid":"https://orcid.org/0000-0002-2171-8789","contributorId":218538,"corporation":false,"usgs":false,"family":"Cluzel","given":"Nicolas","email":"","affiliations":[{"id":39864,"text":"Laboratoire Magmas et Volcans, Université Blaise Pascal","active":true,"usgs":false}],"preferred":false,"id":769514,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Manthilake, Geeth 0000-0001-8161-081X","orcid":"https://orcid.org/0000-0001-8161-081X","contributorId":218539,"corporation":false,"usgs":false,"family":"Manthilake","given":"Geeth","email":"","affiliations":[{"id":39864,"text":"Laboratoire Magmas et Volcans, Université Blaise Pascal","active":true,"usgs":false}],"preferred":false,"id":769515,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Gurioli, Lucia","contributorId":218540,"corporation":false,"usgs":false,"family":"Gurioli","given":"Lucia","email":"","affiliations":[{"id":39864,"text":"Laboratoire Magmas et Volcans, Université Blaise Pascal","active":true,"usgs":false}],"preferred":false,"id":769516,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Johnson, Tim B.","contributorId":127336,"corporation":false,"usgs":false,"family":"Johnson","given":"Tim","email":"","middleInitial":"B.","affiliations":[{"id":6780,"text":"Ontario Ministry of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":769517,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Finizola, Anthony","contributorId":190922,"corporation":false,"usgs":false,"family":"Finizola","given":"Anthony","email":"","affiliations":[],"preferred":false,"id":769518,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Delcher, Eric 0000-0001-6671-7133","orcid":"https://orcid.org/0000-0001-6671-7133","contributorId":218541,"corporation":false,"usgs":false,"family":"Delcher","given":"Eric","email":"","affiliations":[{"id":39867,"text":"Laboratoire GéoSciences Réunion, Université de la Réunion, IPGP, Sorbonne Paris-Cité, 14 CNRS UMR 7154, 15 Avenue René Cassin, CS 92003, 97744 Saint-Denis, La Réunion, France","active":true,"usgs":false}],"preferred":false,"id":769519,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70204764,"text":"70204764 - 2019 - Integrating anthropogenic factors into regional-scale species distribution models — A novel application in the imperiled sagebrush biome","interactions":[],"lastModifiedDate":"2019-10-09T09:38:51","indexId":"70204764","displayToPublicDate":"2019-06-10T10:19:06","publicationYear":"2019","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":"Integrating anthropogenic factors into regional-scale species distribution models — A novel application in the imperiled sagebrush biome","docAbstract":"Species distribution models (SDM) that rely on regional-scale environmental variables will play a key role in forecasting species occurrence in the face of climate change. However, in the Anthropocene, a number of local-scale anthropogenic variables, including wildfire history, land-use change, invasive species, and ecological restoration practices can override regional-scale variables to drive patterns of species distribution. Incorporating these human-induced factors into SDMs remains a major research challenge, in part because spatial variability in these factors occurs at fine scales, rendering prediction over regional extents problematic. Here, we used big sagebrush (Artemisia tridentata Nutt.) as a model species to explore whether including human-induced factors improves the fit of the SDM. We applied a Bayesian hurdle spatial approach using 21,753 data points of field-sampled vegetation obtained from the LANDFIRE program to model sagebrush occurrence and cover by incorporating fire history metrics and restoration treatments from 1980 to 2015 throughout the Great Basin of North America.","language":"English","publisher":"Wiley","doi":"10.1111/gcb.14728","usgsCitation":"Requena-Mullor, J.M., Maguire, K.C., Shinneman, D.J., and Caughlin, T.T., 2019, Integrating anthropogenic factors into regional-scale species distribution models — A novel application in the imperiled sagebrush biome: Global Change Biology, v. 25, no. 11, p. 3844-3858, https://doi.org/10.1111/gcb.14728.","productDescription":"15 p.","startPage":"3844","endPage":"3858","ipdsId":"IP-104486","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":437425,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9NQNH41","text":"USGS data release","linkHelpText":"sagebrush_hurdle_model"},{"id":366563,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":366545,"type":{"id":15,"text":"Index Page"},"url":"https://doi.org/10.1111/gcb.14728"}],"volume":"25","issue":"11","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2019-07-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Requena-Mullor, Juan M.","contributorId":218132,"corporation":false,"usgs":false,"family":"Requena-Mullor","given":"Juan","email":"","middleInitial":"M.","affiliations":[{"id":16201,"text":"Boise State University","active":true,"usgs":false}],"preferred":false,"id":768379,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Maguire, Kaitlin C. 0000-0001-8193-2384","orcid":"https://orcid.org/0000-0001-8193-2384","contributorId":203419,"corporation":false,"usgs":true,"family":"Maguire","given":"Kaitlin","email":"","middleInitial":"C.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":768380,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shinneman, Douglas J. 0000-0002-4909-5181 dshinneman@usgs.gov","orcid":"https://orcid.org/0000-0002-4909-5181","contributorId":147745,"corporation":false,"usgs":true,"family":"Shinneman","given":"Douglas","email":"dshinneman@usgs.gov","middleInitial":"J.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":true,"id":768378,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Caughlin, T. Trevor","contributorId":218133,"corporation":false,"usgs":false,"family":"Caughlin","given":"T.","email":"","middleInitial":"Trevor","affiliations":[{"id":16201,"text":"Boise State University","active":true,"usgs":false}],"preferred":false,"id":768381,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70205857,"text":"70205857 - 2019 - Prevalence and diversity of avian blood parasites in a resident northern passerine","interactions":[],"lastModifiedDate":"2019-10-09T08:08:46","indexId":"70205857","displayToPublicDate":"2019-06-10T08:08:06","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3010,"text":"Parasites & Vectors","printIssn":"1756-3305","active":true,"publicationSubtype":{"id":10}},"title":"Prevalence and diversity of avian blood parasites in a resident northern passerine","docAbstract":"Background: Climate-related changes are expected to influence the prevalence and distribution of vector-borne haemosporidian parasites at northern latitudes, although baseline information about resident birds is still lacking. In this study, we investigated prevalence and genetic diversity of Plasmodium, Haemoproteus, and Leucocytozoon parasites infecting the Northwestern Crow (Corvus caurinus), a non-migratory passerine with unique life-history characteristics. This species occupies both intertidal and forested habitats and is subject to high prevalence of avian keratin disorder (AKD), a disease that causes gross beak deformities. Investigation of avian blood parasites in Northwestern Crows at sites broadly distributed across coastal Alaska provided an opportunity to evaluate specific host factors related to parasite infection status and assess geographic patterns of prevalence.\nResults: We used molecular methods to screen for haemosporidian parasites in Northwestern Crows and estimated genus-specific parasite prevalence with occupancy modeling that accounts for imperfect detection of parasite infection. We observed considerable geographic and annual variation in prevalence of Plasmodium, Haemoproteus, and Leucocytozoon , but these patterns were not correlated with indices of local climatic conditions. Our models also did not provide support for relationships between the probability of parasite infection and body condition or the occurrence of co-infections with other parasite genera or clinical signs of AKD. In our phylogenetic analyses, we identified multiple lineages of each parasite genus, with Leucocytozoon showing greater diversity than Plasmodium or Haemoproteus.\nConclusions: Results from this study expand our knowledge about the prevalence and diversity of avian blood parasites in northern resident birds as well as corvids worldwide. We detected all three genera of avian haemosporidians in Northwestern Crows in Alaska, although only Leucocytozoon occurred at all sites in both years. Given the strong geographic and interannual variation in parasite prevalence and apparent lack of correlation with climatic variables, it appears that there are other key factors responsible for driving transmission dynamics in this region. Thus, caution is warranted when using standard climatic or geographic attributes in a predictive framework. Our phylogenetic results demonstrate lower host specificity for some lineages of Leucocytozoon than is typically reported and provide insights about genetic diversity of local haemosporidian parasites in Alaska.","language":"English","publisher":"Springer","doi":"10.1186/s13071-019-3545-1","usgsCitation":"Van Hemert, C.R., Meixell, B.W., Smith, M.M., and Handel, C.M., 2019, Prevalence and diversity of avian blood parasites in a resident northern passerine: Parasites & Vectors, v. 12, 292, https://doi.org/10.1186/s13071-019-3545-1.","productDescription":"292","ipdsId":"IP-101943","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":467546,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1186/s13071-019-3545-1","text":"Publisher Index Page"},{"id":437426,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9EBB1LG","text":"USGS data release","linkHelpText":"Blood Parasite Infection Data from Northwestern Crows (Corvus caurinus), Alaska, 2007-2008"},{"id":368149,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"12","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2019-06-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Van Hemert, Caroline R. 0000-0002-6858-7165 cvanhemert@usgs.gov","orcid":"https://orcid.org/0000-0002-6858-7165","contributorId":3592,"corporation":false,"usgs":true,"family":"Van Hemert","given":"Caroline","email":"cvanhemert@usgs.gov","middleInitial":"R.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":772640,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Meixell, Brandt W. 0000-0002-6738-0349 bmeixell@usgs.gov","orcid":"https://orcid.org/0000-0002-6738-0349","contributorId":138716,"corporation":false,"usgs":true,"family":"Meixell","given":"Brandt","email":"bmeixell@usgs.gov","middleInitial":"W.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":772641,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Smith, Matthew M. 0000-0002-2259-5135 mmsmith@usgs.gov","orcid":"https://orcid.org/0000-0002-2259-5135","contributorId":5115,"corporation":false,"usgs":true,"family":"Smith","given":"Matthew","email":"mmsmith@usgs.gov","middleInitial":"M.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":772642,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Handel, Colleen M. 0000-0002-0267-7408 cmhandel@usgs.gov","orcid":"https://orcid.org/0000-0002-0267-7408","contributorId":3067,"corporation":false,"usgs":true,"family":"Handel","given":"Colleen","email":"cmhandel@usgs.gov","middleInitial":"M.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":772643,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70206159,"text":"70206159 - 2019 - Modern pollen-assemblages data from small lakes paired with local forest-composition data in northeastern United States","interactions":[],"lastModifiedDate":"2019-10-24T06:55:43","indexId":"70206159","displayToPublicDate":"2019-06-10T06:54:12","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1465,"text":"Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Modern pollen-assemblages data from small lakes paired with local forest-composition data in northeastern United States","docAbstract":"For the past century, pollen analysis has served as a primary tool for inferring past changes in vegetation composition and structure (Birks et al. 2016, Edwards et al. 2017). Pollen-based inferences are supported by empirical studies comparing modern pollen assemblages with modern vegetation composition. In one approach, pollen abundances (usually percentages) for individual taxa are compared directly with quantitative estimates of abundance in surrounding vegetation (Jackson 1994, Davis 2000). This approach has been applied most frequently using spatially extensive but coarse-scale forest inventory data (Webb et al. 1981, Bradshaw and Webb 1985, Prentice & Webb 1986, Prentice et al. 1987, Paciorek & McLachlan 2009, Dawson et al. 2016, Kujawa et al. 2016). In these studies, forest composition cannot usually be estimated accurately within a 1- to 10 km radius of the individual sites owing to limited spatial density of forest inventory data. A few studies have compared vegetation composition within 50-100 m of pollen-sampling sites, but in these cases the pollen is from forest-floor assemblages (Bradshaw 1981, Jackson & Wong 1994, Jackson & Kearsley 1998) or from small forest hollows (Calcote 1995, 1998, Parshall & Calcote 2001). Largely lacking are pollen assemblage data from lake sediments paired with local forest composition, measured within 100 to 1000 m of the lake margins (Jackson 1990). This absence represents a substantial gap in ability to understand and model pollen-vegetation relationships, because lakes are the primary source of fossil-pollen sequences worldwide, and because the leptokurtic nature of pollen dispersal ensures that local vegetation has an important effect on pollen composition in sediments (Jackson 1994, Sugita 1994, 2007a, 2007b, Jackson & Lyford 1999). Here, I present a data set pairing modern pollen assemblages from 33 small lakes in the forested northeastern United States (Fig. 1) with forest composition data measured within 20, 50, 100, 500, and 1000 metres of the lake margins. This data set incorporates most of the sites used in Jackson (1990), adding 16 new sites and delivering the vegetation data by species in absolute units (i.e., total basal area), which allows various weightings and transformations to be applied. The data set should be of value to paleoecologists and forest ecologists in understanding, modeling, and validating the pollen-vegetation relationships that are at the heart of paleoecological inference.","language":"English","publisher":"Wiley","doi":"10.1002/ecy.2784","collaboration":"]","usgsCitation":"Jackson, S., 2019, Modern pollen-assemblages data from small lakes paired with local forest-composition data in northeastern United States: Ecology, v. 100, no. 10, e02784, https://doi.org/10.1002/ecy.2784.","productDescription":"e02784","ipdsId":"IP-104434","costCenters":[{"id":569,"text":"Southwest Climate Science Center","active":true,"usgs":true}],"links":[{"id":467547,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecy.2784","text":"Publisher Index Page"},{"id":368547,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Northeastern United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -81.03515625,\n 42.00032514831621\n ],\n [\n -80.771484375,\n 39.53793974517628\n ],\n [\n -79.1455078125,\n 39.40224434029275\n ],\n [\n -76.3330078125,\n 39.40224434029275\n ],\n [\n -76.4208984375,\n 38.238180119798635\n ],\n [\n -75.234375,\n 37.055177106660814\n ],\n [\n -74.3994140625,\n 38.47939467327645\n ],\n [\n -73.7841796875,\n 38.8225909761771\n ],\n [\n -72.50976562499999,\n 40.48038142908172\n ],\n [\n -71.279296875,\n 40.74725696280421\n ],\n [\n -69.697265625,\n 41.0130657870063\n ],\n [\n -69.2138671875,\n 41.178653972331674\n ],\n [\n -69.873046875,\n 42.74701217318067\n ],\n [\n -68.90625,\n 43.16512263158296\n ],\n [\n -66.8408203125,\n 44.49650533109348\n ],\n [\n -66.884765625,\n 45.460130637921004\n ],\n [\n -67.5439453125,\n 46.558860303117164\n ],\n [\n -67.939453125,\n 47.42808726171425\n ],\n [\n -69.345703125,\n 47.60616304386874\n ],\n [\n -71.8505859375,\n 45.336701909968134\n ],\n [\n -74.92675781249999,\n 45.089035564831036\n ],\n [\n -76.0693359375,\n 44.05601169578525\n ],\n [\n -77.255859375,\n 43.48481212891603\n ],\n [\n -79.27734374999999,\n 43.29320031385282\n ],\n [\n -81.03515625,\n 42.00032514831621\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"100","issue":"10","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2019-08-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Jackson, Stephen","contributorId":219994,"corporation":false,"usgs":true,"family":"Jackson","given":"Stephen","affiliations":[{"id":565,"text":"Southeast Climate Science Center","active":true,"usgs":true}],"preferred":true,"id":773743,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70227957,"text":"70227957 - 2019 - Characterizing urban butterfly populations: The case for purposive point-count surveys","interactions":[],"lastModifiedDate":"2022-02-02T15:35:46.073777","indexId":"70227957","displayToPublicDate":"2019-06-09T09:14:46","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3669,"text":"Urban Ecosystems","active":true,"publicationSubtype":{"id":10}},"title":"Characterizing urban butterfly populations: The case for purposive point-count surveys","docAbstract":"Developing effective butterfly monitoring strategies is key to understanding how butterflies interact with urban environments, and, in turn, to developing local conservation practices. We investigated two urban habitat types (public gardens and restored/reconstructed prairies) and compared three survey methods (Pollard transects, purposive point counts, and random point counts) to determine which was most productive for detecting butterflies and assessing family diversity. We conducted 66 butterfly surveys by using each method (198 total) from May through September in 2015 and 2016 at six sites (three public gardens and three prairie areas) in Ames, Ankeny and Des Moines, Iowa. All survey methods were used on 11 sampling dates at each site. Overall, we observed 2,227 butterflies representing 38 species: 1,076 in public gardens and 1,151 in prairie areas. We used a smaller data set standardized for survey effort, including 1,361 of these sightings, to compare survey methods and habitat types. Although there were no significant differences in number of butterfly sightings between the two habitats, more sightings (798) were documented by using purposive point counts when compared to Pollard transects (297) or random point counts (266) (for both comparisons, p < 0.0001). Occupancy modeling also indicated that purposive point counts were most effective in detecting certain species of butterflies, most notably those within the Pieridae (whites, sulphurs) and Papilionidae (swallowtails). We conclude that public gardens and restored/reconstructed prairies in urban settings can provide important butterfly habitat, and that purposive point-count surveys are most effective for detecting butterflies in these relatively small-scale landscape features.","language":"English","publisher":"Springer","doi":"10.1007/s11252-019-00880-8","usgsCitation":"Lang, B.J., Dixon, P.M., Klaver, R.W., Thompson, J.R., and Widrlechner, M.P., 2019, Characterizing urban butterfly populations: The case for purposive point-count surveys: Urban Ecosystems, v. 22, https://doi.org/10.1007/s11252-019-00880-8.","productDescription":"14 p.","startPage":"1096","ipdsId":"IP-094401","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":467548,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://lib.dr.iastate.edu/nrem_pubs/320","text":"External 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\"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -93.64007949829102,\n 42.038122063141756\n ],\n [\n -93.63484382629395,\n 42.038122063141756\n ],\n [\n -93.63484382629395,\n 42.041755504360836\n ],\n [\n -93.64007949829102,\n 42.041755504360836\n ],\n [\n -93.64007949829102,\n 42.038122063141756\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"22","edition":"1083","noUsgsAuthors":false,"publicationDate":"2019-07-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Lang, Bret J.","contributorId":273237,"corporation":false,"usgs":false,"family":"Lang","given":"Bret","email":"","middleInitial":"J.","affiliations":[{"id":6911,"text":"Iowa State University","active":true,"usgs":false}],"preferred":false,"id":832698,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dixon, Philip M.","contributorId":64086,"corporation":false,"usgs":true,"family":"Dixon","given":"Philip","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":832699,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Klaver, Robert W. 0000-0002-3263-9701 bklaver@usgs.gov","orcid":"https://orcid.org/0000-0002-3263-9701","contributorId":3285,"corporation":false,"usgs":true,"family":"Klaver","given":"Robert","email":"bklaver@usgs.gov","middleInitial":"W.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":832700,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Thompson, Jan R.","contributorId":273239,"corporation":false,"usgs":false,"family":"Thompson","given":"Jan","email":"","middleInitial":"R.","affiliations":[{"id":6911,"text":"Iowa State University","active":true,"usgs":false}],"preferred":false,"id":832701,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Widrlechner, Mark P.","contributorId":273241,"corporation":false,"usgs":false,"family":"Widrlechner","given":"Mark","email":"","middleInitial":"P.","affiliations":[{"id":6911,"text":"Iowa State University","active":true,"usgs":false}],"preferred":false,"id":832702,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70203817,"text":"70203817 - 2019 - Geographic variation in the intensity of warming and phenological mismatch between Arctic shorebirds and invertebrates","interactions":[],"lastModifiedDate":"2019-11-13T13:22:24","indexId":"70203817","displayToPublicDate":"2019-06-08T10:09:42","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1459,"text":"Ecological Monographs","active":true,"publicationSubtype":{"id":10}},"title":"Geographic variation in the intensity of warming and phenological mismatch between Arctic shorebirds and invertebrates","docAbstract":"Responses to climate change can vary across functional groups and trophic levels, leading to a temporal decoupling of trophic interactions or ‘phenological mismatches.’ Despite a growing number of single-species studies that identified phenological mismatches as a nearly universal consequence of climate change, we have a limited understanding of the spatial variation in the intensity of this phenomenon nor what influences this variation. In this study, we tested for geographic patterns in phenological mismatches between six species of shorebirds and their invertebrate prey at ten sites spread across ~13º latitude and ~84º longitude in the Arctic over three years. At each site, we quantified the phenological mismatch between shorebirds and their invertebrate prey at: 1) an individual nest level, as the difference in days between the seasonal peak in food and the peak demand by chicks, and 2) a population level, as the overlapped area under fitted curves for total daily biomass of invertebrates and dates of the peak demand by chicks. We tested whether the intensity of past climatic change observed at each site corresponded with the extent of phenological mismatch and used Structural Equation Modeling to test for causal relationships among: 1) environmental factors, including geographic location and current climatic conditions, 2) the timing of invertebrate emergence and the breeding phenology of shorebirds, and 3) the phenological mismatch between the two trophic levels. The extent of phenological mismatch varied more among different sites than among different species within each site. A greater extent of phenological mismatch at both the individual-nest and population-levels coincided with changes in the timing of snowmelt as well as the potential dissociation of long-term snow phenology from changes in temperature. The timing of snowmelt also affected the shape of the food and demand curves, which determined the extent of phenological mismatch at the population level. Finally, we found larger mismatches at more easterly longitudes, which may be affecting the population dynamics of shorebirds, as two of our study species show regional population declines in only the eastern part of their range. This suggests that phenological mismatches may be resulting in demographic consequences for arctic-nesting birds.","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecm.1383","usgsCitation":"Kwon, E., Weiser, E.L., Lanctot, R.B., Brown, S.C., Gates, H.R., Gilchrist, H.G., Kendall, S.J., David B. Lank, Joseph R. 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