Crayfish are globally diverse and one of the most important taxa in North American streams. Despite their importance, many species are of conservation concern and efforts to improve conditions are limited. Here, we address two major impediments to improving conditions: (a) our lack of knowledge of the interplay among natural landscape and human-induced changes; and (b) a very limited understanding of how species interactions affect overall crayfish distributions.
Ozark Highlands ecoregion, USA.
We used both existing data and field-collected data to examine the relationships between 12 Faxonius species and physicochemical variables at multiple spatial scales. Data were analysed using a generalized linear mixed model. After fitting our environmental variables, we also considered possible relationships between species considered strong competitors and species occurrence.
Our results indicated that elevation, lithology, an interaction between drainage area and anthropogenic disturbance, and the presence of strong competitors were associated with Faxonius occurrences. Faxonius occurrences were associated with assemblage-structuring variables: lithology and elevation. More interestingly, we found several patterns of interactions between drainage area and disturbance. The most common pattern among several species was a decline in occurrence in larger drainages when disturbance was high; however, longpincered crayfish (Faxonius longidigitus) was more likely to occupy large drainages as disturbance increased. Additionally, the presence of species considered strong competitors resulted in lower occurrence probability for many species, including two of the species classified as competitors.
In addition to identifying the relationships between native species and assemblage-structuring variables, we show how the probability of species occurrences relate to interactions between disturbance and natural landscape features. Further, our results suggest competitor presence also plays a role in structuring distributions at the stream segment scale. Our findings emphasize the value of considering both competitor presence and interactions among landscape variables and disturbances in structuring crayfish assemblages.
","language":"English","publisher":"Wiley","doi":"10.1111/ddi.12840","usgsCitation":"Mouser, J., Mollenhauer, R., and Brewer, S.K., 2019, Relationships between landscape constraints and a crayfish assemblage with consideration of competitor presence: Diversity and Distributions, v. 25, no. 1, p. 61-73, https://doi.org/10.1111/ddi.12840.","productDescription":"13 p.","startPage":"61","endPage":"73","ipdsId":"IP-091645","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":468082,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/ddi.12840","text":"Publisher Index Page"},{"id":395040,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arkansas, Missouri","otherGeospatial":"Ozark Highlands ecoregion","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -94.603271484375,\n 34.134541681937364\n ],\n [\n -89.23095703125,\n 34.134541681937364\n ],\n [\n -89.23095703125,\n 38.35888785866677\n ],\n [\n -94.603271484375,\n 38.35888785866677\n ],\n [\n -94.603271484375,\n 34.134541681937364\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"25","issue":"1","noUsgsAuthors":false,"publicationDate":"2018-10-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Mouser, J.B.","contributorId":244447,"corporation":false,"usgs":false,"family":"Mouser","given":"J.B.","affiliations":[{"id":7249,"text":"Oklahoma State University","active":true,"usgs":false}],"preferred":false,"id":832064,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mollenhauer, Robert","contributorId":242899,"corporation":false,"usgs":false,"family":"Mollenhauer","given":"Robert","affiliations":[{"id":7249,"text":"Oklahoma State University","active":true,"usgs":false}],"preferred":false,"id":832065,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brewer, Shannon K. 0000-0002-1537-3921 skbrewer@usgs.gov","orcid":"https://orcid.org/0000-0002-1537-3921","contributorId":2252,"corporation":false,"usgs":true,"family":"Brewer","given":"Shannon","email":"skbrewer@usgs.gov","middleInitial":"K.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":832066,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70204439,"text":"70204439 - 2019 - Estimating forest canopy cover dynamics in Valles Caldera National Preserve, New Mexico, using LiDAR and Landsat data","interactions":[],"lastModifiedDate":"2019-07-23T14:41:00","indexId":"70204439","displayToPublicDate":"2018-10-01T14:38:39","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":836,"text":"Applied Geography","active":true,"publicationSubtype":{"id":10}},"title":"Estimating forest canopy cover dynamics in Valles Caldera National Preserve, New Mexico, using LiDAR and Landsat data","docAbstract":"Increasing tree canopy cover has led to increasing wildfire activity in conifer dominated areas of the southwestern United States. Estimating historical changes in the spatial distribution of tree canopy cover can provide further insights into the dynamics of forest and fuel conditions in these landscapes and help prioritize areas for restoration to mitigate wildfire risks and restore biological functioning. In this study, we explored the relationship between LiDAR derived canopy cover data and Landsat reflectance values, and derived a model to estimate percent canopy cover (PCC) on historical Landsat data from 1987 to 2015 for the Valles Caldera National Preserve (VCNP), located in the southwest Jemez Mountains of New Mexico. We developed a regression model between LiDAR generated canopy cover collected in June 2010 and Landsat Thematic Mapper (TM) reflectance values (bands 1–7 except band 6) and vegetation indices collected for the same date. About 5% (17,000) of the total LiDAR points (329,102) were used as training points and a separate, non-overlapping set of 17,000 points as test points to validate the regression model. A simple linear model with the red band (band 3; R2 = 0.70) was selected as the best model to predict PCC in the rest of the images for 1987–2015. In general, we found a strong consistency between the spatial dynamics of modelled tree canopy cover based on historical Landsat data, wildfire events and forest management practicesthat occurred during the same period. Results showed that about 11% of the study area experienced an increase in PCC for the period of 1987–2015 while 41% of the study area experienced a reduction in PCC during the same time period, mostly in the areas which were affected by stand replacing wildfires in 2011 and 2013. The results indicate an overall increase in medium and high canopy cover classes in specific regions of the study area, which could lead to hazardous wildfires such as those in 2011 and 2013. In the context of ongoing ecological restoration of these montane forests, predicted PCC of contemporary forests could help local managers to identify the areas in the need of immediate restoration efforts by focusing management practices on the areas with closed canopy.
Lesser prairie-chicken (Tympanuchus pallidicinctus) populations have declined since the 1980s. Understanding factors influencing nest-site selection and nest survival are important for conservation and management of lesser prairie-chicken populations. However, >75% of the extant population is in the northern extent of the range where data on breeding season ecology are lacking. We tested factors influencing fine-scale and regional nest-site selection and nest survival across the northern portion of the lesser prairie-chicken range. We trapped and affixed satellite global positioning system and very high frequency transmitters to female lesser prairie-chickens (n = 307) in south-central and western Kansas and eastern Colorado, USA. We located and monitored 257 lesser prairie-chicken nests from 2013 to 2016. We evaluated nest-site selection and nest survival in comparison to vegetation composition and structure. Overall, nest-site selection in relation to vegetation characteristics was similar across our study area. Lesser prairie-chickens selected nest microsites with 75% visual obstruction 2.0–3.5 dm tall and 95.7% of all nests were in habitat with ≥1 dm and ≤4 dm visual obstruction. Nests were located in areas with 6–8% bare ground, on average, avoiding areas with greater percent cover of bare ground. The type of vegetation present was less important than cover of adequate height. Nest survival was maximized when 75% visual obstruction was 2.0–4.0 dm. Nest survival did not vary spatially or among years and generally increased as intensity of drought decreased throughout the study although not significantly. To provide nesting cover considering yearly variation in drought conditions, it is important to maintain residual cover by managing for structural heterogeneity of vegetation. Managing for structural heterogeneity could be accomplished by maintaining or strategically applying practices of the Conservation Reserve Program, using appropriate fire and grazing disturbances in native working grasslands, and establishing site-specific monitoring of vegetation composition and structure.
","language":"English","publisher":"The Wildlife Society","doi":"10.1002/jwmg.21582","usgsCitation":"Lautenbach, J.M., Haukos, D.A., Sullins, D.S., Hagen, C.A., Lautenbach, J.D., Pitman, J.C., Plumb, R.T., Robinson, S.G., and Kraft, J.D., 2019, Factors influencing nesting ecology of lesser prairie-chickens: Journal of Wildlife Management, v. 83, no. 1, p. 205-215, https://doi.org/10.1002/jwmg.21582.","productDescription":"11 p.","startPage":"205","endPage":"215","ipdsId":"IP-098227","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":468085,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"http://hdl.handle.net/10919/99173","text":"Publisher Index Page"},{"id":395681,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado, Kansas","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -104.2822265625,\n 37.020098201368114\n ],\n [\n -98.525390625,\n 37.020098201368114\n ],\n [\n -98.525390625,\n 39.639537564366684\n ],\n [\n -104.2822265625,\n 39.639537564366684\n ],\n [\n -104.2822265625,\n 37.020098201368114\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"83","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Lautenbach, Joseph M.","contributorId":172788,"corporation":false,"usgs":false,"family":"Lautenbach","given":"Joseph","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":834055,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Haukos, David A. 0000-0001-5372-9960 dhaukos@usgs.gov","orcid":"https://orcid.org/0000-0001-5372-9960","contributorId":3664,"corporation":false,"usgs":true,"family":"Haukos","given":"David","email":"dhaukos@usgs.gov","middleInitial":"A.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":834056,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sullins, Daniel S.","contributorId":166689,"corporation":false,"usgs":false,"family":"Sullins","given":"Daniel","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":834057,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hagen, Christian A.","contributorId":177795,"corporation":false,"usgs":false,"family":"Hagen","given":"Christian","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":834058,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lautenbach, Jonathan D.","contributorId":172790,"corporation":false,"usgs":false,"family":"Lautenbach","given":"Jonathan","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":834059,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Pitman, James C.","contributorId":40529,"corporation":false,"usgs":true,"family":"Pitman","given":"James","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":834060,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Plumb, Reid T.","contributorId":172787,"corporation":false,"usgs":false,"family":"Plumb","given":"Reid","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":834061,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Robinson, Samantha G.","contributorId":172786,"corporation":false,"usgs":false,"family":"Robinson","given":"Samantha","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":834062,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Kraft, John D.","contributorId":172789,"corporation":false,"usgs":false,"family":"Kraft","given":"John","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":834063,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70204560,"text":"70204560 - 2019 - Wind River subbasin restoration annual report of USGS activities January 2017 through December 2017","interactions":[],"lastModifiedDate":"2019-08-06T09:38:27","indexId":"70204560","displayToPublicDate":"2018-10-01T08:03:06","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"title":"Wind River subbasin restoration annual report of USGS activities January 2017 through December 2017","docAbstract":"We used Passive Integrated Transponder (PIT)-tagging and a series of instream PIT-tag interrogation systems (PTISs) to investigate life-histories, populations, and efficacy of habitat restoration actions for wild Steelhead Oncorhynchus mykiss in the Wind River subbasin, WA. No hatchery Steelhead have been planted in the Wind River subbasin since 1997, and hatchery adults are estimated to be less than one percent of adults in most years (pers comm. Thomas Buehrens, Washington Department of Fish and Wildlife). Numerous restoration actions have been implemented in the subbasin, including Hemlock Dam removal on Trout Creek in 2009. Data from our study, and companion work by Washington Department of Fish and Wildlife (WDFW), are contributing to Bonneville Power Administration’s (BPA) Research Monitoring and Evaluation (RM&E) Program Strategy of Fish Population Status Monitoring (www.cbfish.org/ProgramStrategy.mvc/ViewProgramStrategySummary/1), specifically the substrategies of: 1) Assessing the Status and Trends of Diversity of Natural Origin Fish Populations and to Uncertainties Research regarding differing life histories of a wild Steelhead population, 2) Assessing the Status and Trend of Adult Natural Origin Fish Populations, and 3) Monitoring and Evaluating the Effectiveness of Tributary Habitat Actions Relative to Environmental, Physical, or Biological Performance Objectives. Our headwaters parr PIT tagging, WDFW parr, smolt, and adult tagging and our instream PTISs are providing data movements and life histories of parr, smolt, and adult Steelhead. During summer 2017, we PIT-tagged age-0 and age-1 Steelhead parr in headwater areas of the Wind River subbasin to characterize population traits and investigate life-history diversity, including growth and pre-smolt downstream movement. Repeat sampling and smolt traps provide opportunities for recapture, and instream PTISs and Columbia River infrastructure provide opportunity for detection of PIT-tagged fish. Throughout the year, we maintained a series of instream PTISs to monitor movement of tagged Steelhead parr, smolts, and adults. This included adding the second array to our upper Wind River PITS, increasing solar capacity and adding improved power cables to some sites. Detections at the instream PTISs have demonstrated trends of age-0 and age-1 parr emigration from natal areas during summer and fall, in addition to the expected movement of parr and smolts in spring. These data are increasing our understanding of varied life histories of juvenile Steelhead; paired with other Steelhead population work in the subbasin we hope to begin to understand factors which may influence parr movements. Long-term monitoring of PIT-tagged fish over multiple years is providing information on contribution of various life-history strategies to smolt production and adult returns. Movements of PIT-tagged adult Steelhead were also recorded at instream PTISs. These data have allowed us to assess adult returns to tributary watersheds within the Wind River subbasin. Determination of adult use of tributary watersheds is providing data to contribute to evaluation of the efficacy of the removal of Hemlock Dam on Trout Creek. Hemlock Dam, located at rkm 2.0 of Trout Creek was removed in summer 2009. The dam had had contributed to hydrologic impairment of Trout Creek and had potential negative effects on Steelhead. The improved upper Wind River PTIS (better site characteristics and grid power) will allow estimates of subbasin adult escapement upstream of that site. Evaluating and planning restoration efforts are of interest to many managers and agencies to ensure efficient use of resources. The evaluation of various life-histories of Lower Columbia River Steelhead within the Wind River subbasin will provide information to better track populations, and to direct habitat restoration and water allocation planning. Increasingly detailed Viable Salmonid Population information, such as that provided by PIT-tagging and instream PTISs networks like those we operate in the Wind River subbasin, will provide data to inform policy and management, as life-history strategies and production bottlenecks are identified and understood.
","language":"English","publisher":"Bonneville Power Administration","collaboration":"Bonneville Power Administration","usgsCitation":"Jezorek, I., 2019, Wind River subbasin restoration annual report of USGS activities January 2017 through December 2017, 53 p.","productDescription":"53 p.","startPage":"1","endPage":"53","ipdsId":"IP-101368","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":366100,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":366091,"type":{"id":11,"text":"Document"},"url":"https://www.cbfish.org/Document.mvc/DocumentViewer/P164011/80611-1.pdf"}],"country":"United States","state":"Washington","otherGeospatial":"Wind River","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -121.963568,45.751448 ], [ -121.963568,45.969903 ], [ -121.787086,45.969903 ], [ -121.787086,45.751448 ], [ -121.963568,45.751448 ] ] ] } } ] }","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Jezorek, Ian 0000-0002-3842-3485","orcid":"https://orcid.org/0000-0002-3842-3485","contributorId":217811,"corporation":false,"usgs":true,"family":"Jezorek","given":"Ian","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":767569,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70199743,"text":"70199743 - 2019 - Groundwater salinity mapping using geophysical log analysis within the Fruitvale and Rosedale Ranch oil fields, Kern County, California, USA","interactions":[],"lastModifiedDate":"2019-03-26T16:18:40","indexId":"70199743","displayToPublicDate":"2018-09-26T15:15:53","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1923,"text":"Hydrogeology Journal","active":true,"publicationSubtype":{"id":10}},"title":"Groundwater salinity mapping using geophysical log analysis within the Fruitvale and Rosedale Ranch oil fields, Kern County, California, USA","docAbstract":"A method is presented for deriving a volume model of groundwater total dissolved solids (TDS) from borehole geophysical and aqueous geochemical measurements. While previous TDS mapping techniques have proved useful in the hydrogeologic setting in which they were developed, they may yield poor results in settings with lithological heterogeneity, complex water chemistry, or limited data. Problems arise because of assumed values for empirical constants in Archie’s Equation, unrealistic porosity and temperature gradients, or bicarbonate-rich groundwater. These issues become critical in complex geologic settings such as the San Joaquin Valley of California, USA. To address this, a method to map TDS in three dimensions is applied to the Fruitvale and Rosedale Ranch oil fields near Bakersfield, California. Borehole resistivity, porosity, and temperature data are used to derive TDS using Archie’s Equation, and are then kriged to interpolate TDS. Archie’s a and m (tortuosity factor and cementation exponent, respectively) are found by comparing model predictions, after kriging, to TDS measurements, and minimizing the differences via mathematical optimization. Contributions of abundant bicarbonate ions to TDS were corrected using an empirical model. This work was motivated by federal and state law requirements to monitor and protect underground sources of drinking water. Modeling shows the legally significant boundary of 10,000 ppm TDS is at ~1,067 m below sea level in Rosedale Ranch, and deepens into Fruitvale to ~1,341 m. Mapping groundwater TDS at this resolution reveals that TDS is primarily controlled by depth, recharge, stratigraphy, and in some places, by faulting and facies changes.
","language":"English","publisher":"Springer","doi":"10.1007/s10040-018-1872-5","usgsCitation":"Stephens, M.J., Shimabukuro, D.H., Gillespie, J., and Chang, W., 2019, Groundwater salinity mapping using geophysical log analysis within the Fruitvale and Rosedale Ranch oil fields, Kern County, California, USA: Hydrogeology Journal, v. 27, no. 2, p. 731-746, https://doi.org/10.1007/s10040-018-1872-5.","productDescription":"16 p.","startPage":"731","endPage":"746","ipdsId":"IP-088343","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":468086,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10040-018-1872-5","text":"Publisher Index Page"},{"id":437630,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7S181PH","text":"USGS data release","linkHelpText":"Geochemical and geophysical data for wells in the Fruitvale and Rosedale Ranch oil and gas fields, Kern County, California, USA"},{"id":357806,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","county":"Kern County","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -119.17,\n 35.34\n ],\n [\n -119.02,\n 35.34\n ],\n [\n -119.02,\n 35.458\n ],\n [\n -119.17,\n 35.458\n ],\n [\n -119.17,\n 35.34\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"27","issue":"2","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2018-09-26","publicationStatus":"PW","scienceBaseUri":"5bc02f8ae4b0fc368eb538a5","contributors":{"authors":[{"text":"Stephens, Michael J. 0000-0001-8995-9928","orcid":"https://orcid.org/0000-0001-8995-9928","contributorId":205895,"corporation":false,"usgs":true,"family":"Stephens","given":"Michael","email":"","middleInitial":"J.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":746426,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Shimabukuro, David H. 0000-0002-6106-5284","orcid":"https://orcid.org/0000-0002-6106-5284","contributorId":208209,"corporation":false,"usgs":false,"family":"Shimabukuro","given":"David","email":"","middleInitial":"H.","affiliations":[{"id":37762,"text":"California State University, Sacramento","active":true,"usgs":false}],"preferred":false,"id":746427,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gillespie, Janice M. 0000-0003-1667-3472","orcid":"https://orcid.org/0000-0003-1667-3472","contributorId":203915,"corporation":false,"usgs":true,"family":"Gillespie","given":"Janice M.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":false,"id":746428,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Chang, Will 0000-0002-0796-0763","orcid":"https://orcid.org/0000-0002-0796-0763","contributorId":208210,"corporation":false,"usgs":false,"family":"Chang","given":"Will","email":"","affiliations":[{"id":37763,"text":"Hypergradient LLC","active":true,"usgs":false}],"preferred":false,"id":746429,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70197860,"text":"70197860 - 2019 - A values-based private landowner typology to improve grassland conservation initiatives","interactions":[],"lastModifiedDate":"2019-03-15T12:45:34","indexId":"70197860","displayToPublicDate":"2018-09-26T12:36:44","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3405,"text":"Society and Natural Resources","active":true,"publicationSubtype":{"id":10}},"title":"A values-based private landowner typology to improve grassland conservation initiatives","docAbstract":"Many conservation initiatives are based on natural science alone, despite an extensive body of literature demonstrating that the incorporation of social science generates more successful and lasting outcomes. The Land Use Value (LUV) scale is an example of a social science tool that grassland conservation practitioners can use to improve their understanding of the land use decisions of private agricultural landowners. Drawing on data from a mail survey, we demonstrated the utility of the LUV scale to segment agricultural producers by four LUV types (Humans First, Nature First, Interconnected, and Disconnected) with significantly different motivations and land use behaviors. This information can be used to evaluate and align grassland conservation practices, policies, and messaging with the LUV types of private agricultural landowners. Tools like the LUV scale are critical to building the social science capacity of conservation professionals and organizations, in order to improve the efficacy of conservation initiatives.
","language":"English","publisher":"Taylor & Francis","doi":"10.1080/08941920.2018.1501526","usgsCitation":"Sweikert, L.A., and Gigliotti, L.M., 2019, A values-based private landowner typology to improve grassland conservation initiatives: Society and Natural Resources, v. 32, no. 2, p. 167-183, https://doi.org/10.1080/08941920.2018.1501526.","productDescription":"17 p.","startPage":"167","endPage":"183","ipdsId":"IP-088877","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":357777,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"32","issue":"2","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2018-09-06","publicationStatus":"PW","scienceBaseUri":"5bc02f8ae4b0fc368eb538a7","contributors":{"authors":[{"text":"Sweikert, Lily A.","contributorId":205889,"corporation":false,"usgs":false,"family":"Sweikert","given":"Lily","email":"","middleInitial":"A.","affiliations":[{"id":5088,"text":"SDSU","active":true,"usgs":false}],"preferred":false,"id":738787,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gigliotti, Larry M. 0000-0002-1693-5113 lgigliotti@usgs.gov","orcid":"https://orcid.org/0000-0002-1693-5113","contributorId":3906,"corporation":false,"usgs":true,"family":"Gigliotti","given":"Larry","email":"lgigliotti@usgs.gov","middleInitial":"M.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":738786,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70199717,"text":"70199717 - 2019 - Carbon storage potential in a recently created brackish marsh in eastern North Carolina, USA","interactions":[],"lastModifiedDate":"2019-01-28T09:20:00","indexId":"70199717","displayToPublicDate":"2018-09-26T12:07:04","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1454,"text":"Ecological Engineering","active":true,"publicationSubtype":{"id":10}},"title":"Carbon storage potential in a recently created brackish marsh in eastern North Carolina, USA","docAbstract":"Carbon (C) sequestration through accumulated plant biomass and storage in soils can potentially make wetland ecosystems net C sinks. Here, we collected GHG flux, plant biomass, and litter decomposition data from three distinct vegetation zones (Spartinaalterniflora, Juncus roemerianus and Spartina patens) on a 7-year-old created brackish marsh in North Carolina, USA, and integrate these data into an overall C mass balance budget. The marsh fixed an average of 1.85 g C m−2 day−1 through plant photosynthesis. About 41–46% of the fixed C remained in plants, while 18.4% of the C was decomposed and released back to the atmosphere as CO2 and CH4, and 8.6–13.2% of the decomposed C was stored as soil C. In all, this created marsh sequestered 28.7–44.7 Mg CO2 year−1 across the 14 ha marsh. Because the brackish marsh emitted only small amounts of CH4 and N2O, the CO2 equivalent emission of the marsh was −0.87 to −0.56 g CO2-eq m−2 day−1, indicating the marsh has a net effect in reducing GHGs to the atmosphere and contributes to cooling. However, resultant CO2 credit (through the increment of soil C) would be worth only $30.76–$47.90 USD per hectare annually, or $431–$671 per year for the project, which, coupled with other enhanced ecosystem services, could provide landowners with some additional economic incentive for future creation projects. Nevertheless, C mass balance determinations and radiative cooling metrics showed promise in demonstrating the potential of a young created brackish marsh to act as a net carbon sink.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecoleng.2018.09.007","usgsCitation":"Shiau, Y., Burchell, M.R., Krauss, K.W., Broome, S.W., and Birgand, F., 2019, Carbon storage potential in a recently created brackish marsh in eastern North Carolina, USA: Ecological Engineering, v. 127, p. 579-588, https://doi.org/10.1016/j.ecoleng.2018.09.007.","productDescription":"10 p.","startPage":"579","endPage":"588","ipdsId":"IP-080504","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":468088,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecoleng.2018.09.007","text":"Publisher Index Page"},{"id":357760,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Carolina","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -76.937255859375,\n 34.56764471968292\n ],\n [\n -76.146240234375,\n 34.56764471968292\n ],\n [\n -76.146240234375,\n 35.0906979730151\n ],\n [\n -76.937255859375,\n 35.0906979730151\n ],\n [\n -76.937255859375,\n 34.56764471968292\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"127","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5bc02f8be4b0fc368eb538af","contributors":{"authors":[{"text":"Shiau, Yo-Jin","contributorId":174552,"corporation":false,"usgs":false,"family":"Shiau","given":"Yo-Jin","email":"","affiliations":[],"preferred":false,"id":746312,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Burchell, Michael R.","contributorId":174553,"corporation":false,"usgs":false,"family":"Burchell","given":"Michael","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":746313,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Krauss, Ken W. 0000-0003-2195-0729 kraussk@usgs.gov","orcid":"https://orcid.org/0000-0003-2195-0729","contributorId":2017,"corporation":false,"usgs":true,"family":"Krauss","given":"Ken","email":"kraussk@usgs.gov","middleInitial":"W.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":true,"id":746311,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Broome, Stephen W.","contributorId":174555,"corporation":false,"usgs":false,"family":"Broome","given":"Stephen","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":746314,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Birgand, Francois","contributorId":208193,"corporation":false,"usgs":false,"family":"Birgand","given":"Francois","email":"","affiliations":[{"id":36764,"text":"Department of Biological and Agricultural Engineering, North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":746315,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70202848,"text":"70202848 - 2019 - The potential for citizen science to produce reliable and useful information in ecology","interactions":[],"lastModifiedDate":"2019-06-18T11:18:53","indexId":"70202848","displayToPublicDate":"2018-09-22T10:11:13","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1321,"text":"Conservation Biology","active":true,"publicationSubtype":{"id":10}},"title":"The potential for citizen science to produce reliable and useful information in ecology","docAbstract":"We examined features of citizen science that influence data quality, inferential power, and usefulness in ecology. As background context for our examination, we considered topics such as ecological sampling (probability based, purposive, opportunistic), linkage between sampling technique and statistical inference(designbased,modelbased),andscientificparadigms(confirmatory,exploratory).Wedistinguished several types of citizen science investigations, from intensive research with rigorous protocols targeting clearly articulated questions to mass-participation internet-based projects with opportunistic data collection lacking samplingdesign,andexaminedoverarchingobjectives,design,analysis,volunteertraining,andperformance. We identified key features that influence data quality: project objectives, design and analysis, and volunteer training and performance. Projects with good designs, trained volunteers, and professional oversight can meet statistical criteria to produce high-quality data with strong inferential power and therefore are well suited for ecological research objectives. Projects with opportunistic data collection, little or no sampling design, and minimal volunteer training are better suited for general objectives related to public education or data exploration because reliable statistical estimation can be difficult or impossible. In some cases, statistically robust analytical methods, external data, or both may increase the inferential power of certain opportunistically collected data. Ecological management, especially by government agencies, frequently requires data suitable for reliable inference. With standardized protocols, state-of-the-art analytical methods, and well-supervised programs, citizen science can make valuable contributions to conservation by increasing the scope of species monitoring efforts. Data quality can be improved by adhering to basic principles of data collection and analysis, designing studies to provide the data quality required, and including suitable statistical expertise, thereby strengthening the science aspect of citizen science and enhancing acceptance by the scientific community and decision makers.","language":"English","publisher":"Wiley","doi":"10.1111/cobi.13223","usgsCitation":"Brown, E., and Williams, B.K., 2019, The potential for citizen science to produce reliable and useful information in ecology: Conservation Biology, v. 33, no. 3, p. 561-569, https://doi.org/10.1111/cobi.13223.","productDescription":"9 p.","startPage":"561","endPage":"569","ipdsId":"IP-078062","costCenters":[{"id":554,"text":"Science and Decisions Center","active":true,"usgs":true}],"links":[{"id":468089,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1111/cobi.13223","text":"External Repository"},{"id":362581,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"33","issue":"3","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2018-11-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Brown, Ellie 0000-0001-7798-830X ebrown@usgs.gov","orcid":"https://orcid.org/0000-0001-7798-830X","contributorId":200491,"corporation":false,"usgs":true,"family":"Brown","given":"Ellie","email":"ebrown@usgs.gov","affiliations":[{"id":554,"text":"Science and Decisions Center","active":true,"usgs":true}],"preferred":false,"id":760254,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Williams, Byron K. 0000-0001-7644-1396","orcid":"https://orcid.org/0000-0001-7644-1396","contributorId":86616,"corporation":false,"usgs":true,"family":"Williams","given":"Byron","email":"","middleInitial":"K.","affiliations":[{"id":554,"text":"Science and Decisions Center","active":true,"usgs":true}],"preferred":false,"id":760255,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70223205,"text":"70223205 - 2019 - Evaluation of a field protocol for internally-tagging fish predators using difficult-to-tag ictalurid catfish as examples","interactions":[],"lastModifiedDate":"2021-08-18T13:02:44.681063","indexId":"70223205","displayToPublicDate":"2018-09-22T07:59:47","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2886,"text":"North American Journal of Fisheries Management","active":true,"publicationSubtype":{"id":10}},"title":"Evaluation of a field protocol for internally-tagging fish predators using difficult-to-tag ictalurid catfish as examples","docAbstract":"Tagging protocols that result in high tag retention will benefit fisheries professionals who use telemetry data. Ictalurid catfish historically have had very poor telemetry tag retention. Here, we use these difficult-to-tag taxa to address two research objectives. First, we evaluated our field-based internal tagging methodology by quantifying six tag retention metrics using data from 48 acoustically-tagged blue catfish (Ictalurus furcatus) released into Milford Reservoir, KS, USA. Second, to better understand the results of this field evaluation, we evaluated tag retention and survival in the hatchery for the closely-related channel catfish (I. punctatus). Field and hatchery studies provided complementary information. Eighty percent of tagged blue catfish were detected at the end of our 5-mo field study (1,139,402 = total detections; 24,243 = average detections per fish). A 13-week hatchery evaluation of our field methodology also had high tag retention (100%). Hatchery treatments that used a lateral-ventral incision had higher tag retention and survival than those treatments that included a mid-ventral incision. Time invested in training, protocol refinement, and field organization were also important. Furthermore, monitoring the surgical history and recovery of individual fish allowed us to correct problems before mortality occurred. Because a need exists for a range of internal tagging methodologies that are effective on an assortment of fish species tagged under a variety of circumstances, our high tag retention methodology may be useful to the expanding research community that studies native and non-native catfish, as well as, other telemetry researchers who seek beneficial refinements to their tagging protocols.
Concentrations of twenty-seven elements, including naturally-occurring water-quality contaminants arsenic, chromium, and uranium, were measured in 217 samples of alluvium and rock from the western Mojave Desert, southern California, using portable (pXRF) and laboratory (LXRF) X-ray fluorescence. Comparison of measurements with NIST-traceable standards was good, although pXRF overestimated iron compared to LXRF. Results suggest pXRF survey data are sufficiently accurate to assess regional geochemical differences in geologic-source terrains. Principal component analysis showed rubidium and potassium were associated with alluvium eroded from felsic terrain, while iron, copper, chromium, and to a lesser extent titanium, manganese, and nickel were associated with alluvium eroded from mafic terrain. Zinc, vanadium, and arsenic were associated with alluvium eroded from hydrothermal terrain. Elemental assemblages associated with different source terrains were traced spatially to identify the source and composition of alluvium composing aquifers pumped for water supply. Changes in geologic source terrain to the Mojave River, associated with movement along the San Andreas Fault over the past one to five million years, reduced the mafic fraction and increased the felsic fraction of alluvium deposited to the regionally important floodplain aquifer along the Mojave River—lowering chromium concentrations in alluvium through geologic time. Comparison of pXRF and sequential extraction data from 40 samples showed arsenic and uranium were more abundant on the surfaces of mineral grains, while chromium and vanadium remained mostly within unweathered mineral grains—suggesting arsenic and uranium may be more readily mobilized into groundwater with changes in pH, redox, or ionic strength than chromium or vanadium.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.gexplo.2018.09.005","usgsCitation":"Groover, K., and Izbicki, J.A., 2019, Selected trace-elements in alluvium and rocks, western Mojave Desert, southern California: Journal of Geochemical Exploration, v. 200, p. 234-248, https://doi.org/10.1016/j.gexplo.2018.09.005.","productDescription":"15 p.","startPage":"234","endPage":"248","ipdsId":"IP-069818","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":468095,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.gexplo.2018.09.005","text":"Publisher Index Page"},{"id":357205,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","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 -117.5,\n 34\n ],\n [\n -116,\n 34\n ],\n [\n -116,\n 35.5\n ],\n [\n -117.5,\n 35.5\n ],\n [\n -117.5,\n 34\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"200","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b98a262e4b0702d0e842e4a","contributors":{"authors":[{"text":"Groover, Krishangi D. 0000-0002-5805-8913","orcid":"https://orcid.org/0000-0002-5805-8913","contributorId":203450,"corporation":false,"usgs":true,"family":"Groover","given":"Krishangi D.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":false,"id":744652,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Izbicki, John A. 0000-0003-0816-4408 jaizbick@usgs.gov","orcid":"https://orcid.org/0000-0003-0816-4408","contributorId":152474,"corporation":false,"usgs":true,"family":"Izbicki","given":"John","email":"jaizbick@usgs.gov","middleInitial":"A.","affiliations":[{"id":493,"text":"Office of Ground Water","active":true,"usgs":true},{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":744653,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70206848,"text":"70206848 - 2019 - Lesser prairie-chicken space use among landscapes in relation to anthropogenic structures","interactions":[],"lastModifiedDate":"2019-11-26T07:15:36","indexId":"70206848","displayToPublicDate":"2018-09-10T07:14:18","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Lesser prairie-chicken space use among landscapes in relation to anthropogenic structures","docAbstract":"The Southern Great Plains has been altered by conversion of native grassland to row‐crop agriculture, which is considered the primary cause of declining lesser prairie‐chicken (Tympanuchus pallidicinctus) populations. However, recent analyses indicate that direct loss of grassland has slowed while lesser prairie‐chicken populations continue to decline, suggesting that remaining grasslands potentially suffer from degradation by various land uses (e.g., increased anthropogenic disturbance). Understanding the spatial ecology of lesser prairie‐chickens relative to anthropogenic structures is important for conservation planning, habitat management, and infrastructure mitigation. We investigated effects of proximity to anthropogenic structures on home range and nest placement (second‐order selection) and within home range space use (third‐order selection) of radio‐marked lesser prairie‐chickens (n = 285) at 2 scales of selection using resource utilization functions and resource selection functions. We collected data from birds marked in the Mixed‐Grass Prairie and Short‐Grass Prairie ecoregions of Kansas, USA, from 15 March 2013 to 14 March 2016. Home range placement did not vary by region or season, and lesser prairie‐chickens placed home ranges farther from powerlines and roads than would be expected at random. As distance increased from 0 to 3 km away from roads and powerlines, the relative probability of home range placement increased 1.66 and 1.54 times, respectively. Distance to powerline was the single most consistent variable negatively affecting nest placement. As the distance from powerline increased from 0 to 3 km, the relative probability of nest placement increased 2.19 times. Distance to oil well did not influence placement of home ranges or nests. When pooled across regions, lesser prairie‐chickens exhibited behavioral avoidance of powerlines, roads, and oil wells within their home range. Lesser prairie‐chickens, on average, used space at greater intensities within their home range farther from wells, powerlines, and roads than available. Across breeding season phases, we found no evidence of increased behavioral avoidance of anthropogenic structures during the nesting or brooding phases compared to the lekking or post‐breeding phases. Within home range space use during the brooding phase was not related to powerlines, wells, or roads. Our results indicate that avoidance of anthropogenic structures may result in functional habitat loss and continued fragmentation of remaining grassland habitat. Reduction or elimination of anthropogenic development in quality lesser prairie‐chicken habitat and concentrating new development in already altered areas that are avoided by lesser prairie‐chickens and no longer considered available habitat may reduce continued habitat degradation throughout the species’ range and aid in population persistence.
The fountain darter Etheostoma fonticola (FOD) is a federally endangered fish listed under the US Endangered Species Act. Here, we identified and characterized a novel aquareovirus isolated from wild fountain darters inhabiting the San Marcos River. This virus was propagated in Chinook salmon embryo (CHSE)-214, rainbow trout gonad-2 and fathead minnow cells at 15°C. The epithelioma papulosum cyprini cell line was refractory at all temperatures evaluated. High throughput sequencing technologies facilitated the complete genome sequencing of this virus utilizing ribosomal RNA-depleted RNA extracted from infected CHSE-214 cells. Conventional PCR primer sets were developed for the detection and confirmation of this virus to assist diagnostic screening methods. Phylogenetic analysis suggests this virus belongs to the Aquareovirus A genus. This research provides requisite initial data critical to support hatchery and refugia biosecurity measures for this endangered species.
","language":"English","publisher":"Inter-Research","doi":"10.3354/dao03261","usgsCitation":"Iwanowicz, L., Iwanowicz, D., Adams, C.R., Lewis, T., Brandt, T., Sanders, L.R., and Cornman, R.S., 2019, Isolation, characterization and molecular identification of a novel aquareovirus that infects the endangered fountain darter, Etheostoma fonticola: Diseases of Aquatic Organisms, v. 130, no. 2, p. 95-108, https://doi.org/10.3354/dao03261.","productDescription":"14 p.","startPage":"95","endPage":"108","ipdsId":"IP-077392","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"links":[{"id":363217,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"130","issue":"2","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Iwanowicz, Luke R. 0000-0002-1197-6178","orcid":"https://orcid.org/0000-0002-1197-6178","contributorId":205661,"corporation":false,"usgs":true,"family":"Iwanowicz","given":"Luke R.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":false,"id":761427,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Iwanowicz, Deborah D. 0000-0002-9613-8594","orcid":"https://orcid.org/0000-0002-9613-8594","contributorId":213902,"corporation":false,"usgs":true,"family":"Iwanowicz","given":"Deborah D.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":false,"id":761428,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Adams, Cynthia R. 0000-0003-4383-530X cradams@usgs.gov","orcid":"https://orcid.org/0000-0003-4383-530X","contributorId":176965,"corporation":false,"usgs":true,"family":"Adams","given":"Cynthia","email":"cradams@usgs.gov","middleInitial":"R.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":761433,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lewis, Teresa","contributorId":215018,"corporation":false,"usgs":false,"family":"Lewis","given":"Teresa","affiliations":[{"id":16956,"text":"US Fish & Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":761429,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Brandt, Tom","contributorId":215019,"corporation":false,"usgs":false,"family":"Brandt","given":"Tom","email":"","affiliations":[{"id":16956,"text":"US Fish & Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":761430,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Sanders, Lakyn R. 0000-0001-5937-7740","orcid":"https://orcid.org/0000-0001-5937-7740","contributorId":202645,"corporation":false,"usgs":true,"family":"Sanders","given":"Lakyn","email":"","middleInitial":"R.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":761432,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Cornman, Robert S. 0000-0001-9511-2192 rcornman@usgs.gov","orcid":"https://orcid.org/0000-0001-9511-2192","contributorId":5356,"corporation":false,"usgs":true,"family":"Cornman","given":"Robert","email":"rcornman@usgs.gov","middleInitial":"S.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":761431,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70203410,"text":"70203410 - 2019 - A global empirical model for near real-time assessment of seismically induced landslides","interactions":[],"lastModifiedDate":"2019-05-14T08:15:34","indexId":"70203410","displayToPublicDate":"2018-09-03T12:40:37","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5739,"text":"Journal of Geophysical Research: Earth Surface","onlineIssn":"2169-9011","active":true,"publicationSubtype":{"id":10}},"title":"A global empirical model for near real-time assessment of seismically induced landslides","docAbstract":"Earthquake-triggered landslides are a significant hazard in seismically active regions, but our ability to assess the hazard they pose in near real-time is limited. In this study, we present a new globally applicable model for seismically induced landslides based on the most comprehensive global dataset available; we use 23 landslide inventories that span a range of earthquake magnitudes and climatic and tectonic settings. We use logistic regression to relate the presence and distribution of earthquake-triggered landslides with spatially distributed estimates of ground shaking, topographic slope, lithology, land-cover type, and a topographic index designed to estimate variability in soil wetness to provide an empirical model of landslide distribution. We tested over 100 combinations of independent predictor variables to find the best-fitting model, using a diverse set of statistical tests. Blind validation tests show the model accurately estimates the distribution of available landslide inventories. The results indicate that the model is reliable and stable, with high “balanced accuracy” (correctly vs. incorrectly classified pixels) for the majority of test events. A cross validation analysis shows high balanced accuracy for a majority of events as well. By combining near-real time estimates of ground shaking with globally available landslide susceptibility data, this model provides a tool to estimate the distribution of co-seismic landslide hazard within minutes of the occurrence of any earthquake worldwide for which a USGS ShakeMap is available.","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2017JF004494","usgsCitation":"Nowicki Jessee, M.A., Hamburger, M., Allstadt, K.E., Wald, D.J., Tanyas, H., Hearne, M., and Thompson, E., 2019, A global empirical model for near real-time assessment of seismically induced landslides: Journal of Geophysical Research: Earth Surface, v. 123, no. 8, p. 1835-1859, https://doi.org/10.1029/2017JF004494.","productDescription":"25 p.","startPage":"1835","endPage":"1859","ipdsId":"IP-098592","costCenters":[{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true},{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":460573,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2017jf004494","text":"Publisher Index Page"},{"id":363731,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"123","issue":"8","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2018-08-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Nowicki Jessee, M. Anna 0000-0001-8076-7647","orcid":"https://orcid.org/0000-0001-8076-7647","contributorId":197022,"corporation":false,"usgs":false,"family":"Nowicki Jessee","given":"M.","email":"","middleInitial":"Anna","affiliations":[],"preferred":false,"id":762617,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hamburger, M.W.","contributorId":20560,"corporation":false,"usgs":true,"family":"Hamburger","given":"M.W.","email":"","affiliations":[],"preferred":false,"id":762618,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Allstadt, Kate E. 0000-0003-4977-5248 kallstadt@usgs.gov","orcid":"https://orcid.org/0000-0003-4977-5248","contributorId":167684,"corporation":false,"usgs":true,"family":"Allstadt","given":"Kate","email":"kallstadt@usgs.gov","middleInitial":"E.","affiliations":[{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true},{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":false,"id":762619,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wald, David J. 0000-0002-1454-4514 wald@usgs.gov","orcid":"https://orcid.org/0000-0002-1454-4514","contributorId":795,"corporation":false,"usgs":true,"family":"Wald","given":"David","email":"wald@usgs.gov","middleInitial":"J.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":762620,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Tanyas, H.","contributorId":215536,"corporation":false,"usgs":false,"family":"Tanyas","given":"H.","affiliations":[],"preferred":false,"id":762621,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hearne, Mike 0000-0002-8225-2396 mhearne@usgs.gov","orcid":"https://orcid.org/0000-0002-8225-2396","contributorId":4659,"corporation":false,"usgs":true,"family":"Hearne","given":"Mike","email":"mhearne@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":762622,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Thompson, E.M.","contributorId":215538,"corporation":false,"usgs":false,"family":"Thompson","given":"E.M.","email":"","affiliations":[],"preferred":false,"id":762623,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70204344,"text":"70204344 - 2019 - Evaluating potential effects of bigheaded carps on fatty acid profiles of multiple trophic levels in large rivers of the Midwest, USA","interactions":[],"lastModifiedDate":"2019-07-18T14:13:17","indexId":"70204344","displayToPublicDate":"2018-09-01T14:05:24","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5453,"text":"Food Webs","active":true,"publicationSubtype":{"id":10}},"title":"Evaluating potential effects of bigheaded carps on fatty acid profiles of multiple trophic levels in large rivers of the Midwest, USA","docAbstract":"Recent work indicates that the establishment of bigheaded carps (Hypophthalmichthys spp.) in the United States has led to a reduction in condition of native planktivores and may detrimentally affect other trophic levels by altering the base of aquatic food webs. We used fatty acids to evaluate potential effects of bigheaded carps on taxa from multiple trophic levels in the Upper Mississippi, Illinois, and St. Croix rivers. Seston fatty acid concentrations were highest in the Illinois River lotic sites and connected backwaters and were positively associated with omega-3 highly unsaturated fatty acids, indicating that these locations had abundant, high-quality basal food resources despite hosting the greatest bigheaded carp densities. Fatty acid profiles of threeridge freshwater mussels tracked the fatty acid values in the seston and were not influenced by bigheaded carp abundances. Hydropsychid caddisflies and bluegill did not differ significantly in total fatty acids or percent lipid among spatial locations, indicating that omnivorous species may be relatively unaffected by bigheaded carps. Gizzard shad, however, exhibited the lowest fatty acid concentrations in the locations with the highest relative bigheaded carp densities, and multivariate models identified bigheaded carp densities as the predictive factor that explained the greatest amount of variability. Zooplankton abundance has been greatly reduced after bigheaded carps establishment in the Illinois River, which may explain the disconnect between the gizzard shad fatty acids and the plentiful, high-quality phytoplankton in that river. Our data provide additional evidence that bigheaded carps are negatively affecting native planktivores such as gizzard shad.","language":"English","publisher":"Elsevier","doi":"10.1016/j.fooweb.2018.e00095","usgsCitation":"Fritts, A.K., Knights, B.C., LaFrancois, T., Vallazza, J.M., Bartsch, L., Bartsch, M.R., Richardson, W.B., Bailey, S., Kreiling, R.M., and Karns, B., 2019, Evaluating potential effects of bigheaded carps on fatty acid profiles of multiple trophic levels in large rivers of the Midwest, USA: Food Webs, v. 16, e00095, https://doi.org/10.1016/j.fooweb.2018.e00095.","productDescription":"e00095","ipdsId":"IP-097779","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":468103,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.fooweb.2018.e00095","text":"Publisher Index 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however, ecological drivers are currently undergoing human-induced alterations, which likely have implications for wildlife. We used the lesser prairie-chicken (Tympanuchus pallidicinctus), an iconic grouse species that exhibits a boom-bust life history strategy, on the Southern High Plains, USA, as a bioindicator of main and interactive effects of severe drought and grazing. This region encompasses the southern and westernmost part of the lesser prairie-chicken range and experienced the worst drought on record in 2011. We surveyed lesser prairie-chicken leks (i.e., communal breeding grounds) across 12 years that represented 7 years before the 2011 drought (\"pre-drought\") and 4 years during and following the 2011 drought (\"post-drought\"). Grazing was annually managed with the objective of achieving ≤50% utilization of above-ground vegetation biomass. We used lek (n = 49) count data and covariates of weather and managed grazing to: 1) estimate long-term lesser prairie-chicken abundance and compare abundance pre-drought and post-drought; 2) examine annually the influence of drought (modified Palmer Drought Index), temperature, the number of days with maximum temperature >75th percentile, and precipitation on long-term lesser prairie-chicken survival and recruitment; and 3) assess and compare the influence of grazing on lesser prairie-chickens pre-drought and post-drought. Lesser prairie-chicken abundance was nearly 7 times greater pre-drought than post-drought, and population declines were attributed to decreased survival and recruitment. The number of days with temperature >75th percentile had the greatest effect, particularly on recruitment. The population exhibited a substantial bust during 2011 and 2012 without a boom to recover in 4 post-drought years. Adaptive grazing positively influenced the population pre-drought, but had no effects post-drought. Results suggest that the severe drought in 2011 may have been beyond the range of environmental conditions to which lesser prairie-chickens, and likely other species, have adapted. Land management practices, such as grazing, should remain adaptive to ensure potential negative influences to all species are avoided. Increasing habitat quantity and quality by reducing habitat loss and fragmentation likely will increase resiliency of the ecosystem and individual species.","language":"English","publisher":"Wiley","doi":"10.1002/ece3.4432","usgsCitation":"Haukos, D.A., Boal, C.W., Fritts1, S.R., B. A. Grisham1, R. D. Cox1, McDaniel4, P., Hagen, C.A., and Greene6, D.U., 2019, Interactive effects of severe drought and grazing on the life history cycle of a bioindicator species on the edge of its range: Ecology and Evolution, v. 8, no. 18, p. 9550-9562, https://doi.org/10.1002/ece3.4432.","productDescription":"13 p.","startPage":"9550","endPage":"9562","ipdsId":"IP-088180","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":460577,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.4432","text":"Publisher Index Page"},{"id":368692,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Southern High Plains","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -104.19433593749999,\n 31.700129553985924\n ],\n [\n -99.5361328125,\n 31.700129553985924\n ],\n [\n -99.5361328125,\n 36.01356058518153\n ],\n [\n -104.19433593749999,\n 36.01356058518153\n ],\n [\n -104.19433593749999,\n 31.700129553985924\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"8","issue":"18","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Haukos, David A. 0000-0001-5372-9960 dhaukos@usgs.gov","orcid":"https://orcid.org/0000-0001-5372-9960","contributorId":3664,"corporation":false,"usgs":true,"family":"Haukos","given":"David","email":"dhaukos@usgs.gov","middleInitial":"A.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":774037,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Boal, Clint W. 0000-0001-6008-8911 cboal@usgs.gov","orcid":"https://orcid.org/0000-0001-6008-8911","contributorId":1909,"corporation":false,"usgs":true,"family":"Boal","given":"Clint","email":"cboal@usgs.gov","middleInitial":"W.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":774038,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fritts1, S. R.","contributorId":220068,"corporation":false,"usgs":false,"family":"Fritts1","given":"S.","email":"","middleInitial":"R.","affiliations":[{"id":37463,"text":"TTU","active":true,"usgs":false}],"preferred":false,"id":774039,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"B. A. Grisham1","contributorId":220069,"corporation":false,"usgs":false,"family":"B. A. Grisham1","affiliations":[{"id":37463,"text":"TTU","active":true,"usgs":false}],"preferred":false,"id":774040,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"R. D. Cox1","contributorId":220070,"corporation":false,"usgs":false,"family":"R. D. Cox1","affiliations":[{"id":37463,"text":"TTU","active":true,"usgs":false}],"preferred":false,"id":774041,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"McDaniel4, P.","contributorId":220071,"corporation":false,"usgs":false,"family":"McDaniel4","given":"P.","email":"","affiliations":[{"id":40129,"text":"chmm","active":true,"usgs":false}],"preferred":false,"id":774042,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hagen, C. A.","contributorId":220072,"corporation":false,"usgs":false,"family":"Hagen","given":"C.","email":"","middleInitial":"A.","affiliations":[{"id":25426,"text":"OSU","active":true,"usgs":false}],"preferred":false,"id":774043,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Greene6, D. U.","contributorId":220073,"corporation":false,"usgs":false,"family":"Greene6","given":"D.","email":"","middleInitial":"U.","affiliations":[{"id":40130,"text":"wc","active":true,"usgs":false}],"preferred":false,"id":774044,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70227934,"text":"70227934 - 2019 - Acoustic telemetry and benthic habitat mapping inform the spatial ecology of Shortnose Sturgeon in the Hudson River, New York, USA","interactions":[],"lastModifiedDate":"2022-02-02T17:50:48.6856","indexId":"70227934","displayToPublicDate":"2018-08-31T11:14:57","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3624,"text":"Transactions of the American Fisheries Society","active":true,"publicationSubtype":{"id":10}},"title":"Acoustic telemetry and benthic habitat mapping inform the spatial ecology of Shortnose Sturgeon in the Hudson River, New York, USA","docAbstract":"A history of overexploitation and industrialization of riverine habitats has impacted the Shortnose Sturgeon Acipenser brevirostrum, leading this species to become one of the earliest listed under the U.S. Endangered Species Act. The present understanding of Shortnose Sturgeon spatial ecology is based on observations from a limited number of Atlantic coastal rivers. To better understand Shortnose Sturgeon in the Hudson River, New York, we used acoustic telemetry to characterize seasonal habitat use and to identify regions of the river where seasonal sturgeon activity occurred. From 2012 to 2016, 101 adult fish were tagged and tracked, and sturgeon detections per unit effort (a metric of fish observation standardized by search effort) were evaluated against benthic habitat variables by using generalized additive regression models. Models indicated strong habitat associations in the spring season defined by gravel-dominated substrates and specific depth ranges, presumably associated with spawning activity. During summer, Shortnose Sturgeon were more dispersed, associating with muddy habitats, whereas in fall/winter, sturgeon congregated in specific regions of the river. These data demonstrate that river use and habitat associations vary seasonally and identify important areas for managing overlap between seasonal habitat use by Shortnose Sturgeon and human activity on the river.
","language":"English","publisher":"American Fisheries Society","doi":"10.1002/tafs.10114","usgsCitation":"Pendleton, R., Standley, C.R., Higgs, A.L., Kenney, G.H., Sullivan, P., Sethi, S., and Harris, B.P., 2019, Acoustic telemetry and benthic habitat mapping inform the spatial ecology of Shortnose Sturgeon in the Hudson River, New York, USA: Transactions of the American Fisheries Society, v. 148, no. 1, p. 35-47, https://doi.org/10.1002/tafs.10114.","productDescription":"13 p.","startPage":"35","endPage":"47","ipdsId":"IP-095043","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":395285,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New York","otherGeospatial":"Hudson River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -74.2071533203125,\n 40.80965166748853\n ],\n [\n -73.47656249999999,\n 40.80965166748853\n ],\n [\n -73.47656249999999,\n 42.75911283724358\n ],\n [\n -74.2071533203125,\n 42.75911283724358\n ],\n [\n -74.2071533203125,\n 40.80965166748853\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"148","issue":"1","noUsgsAuthors":false,"publicationDate":"2018-10-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Pendleton, Richard M.","contributorId":273135,"corporation":false,"usgs":false,"family":"Pendleton","given":"Richard M.","affiliations":[{"id":56428,"text":"New York Department of Conservation","active":true,"usgs":false}],"preferred":false,"id":832604,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Standley, Christopher R.","contributorId":273136,"corporation":false,"usgs":false,"family":"Standley","given":"Christopher","email":"","middleInitial":"R.","affiliations":[{"id":56430,"text":"New York State Department of Transportation","active":true,"usgs":false}],"preferred":false,"id":832605,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Higgs, Amanda L.","contributorId":273137,"corporation":false,"usgs":false,"family":"Higgs","given":"Amanda","email":"","middleInitial":"L.","affiliations":[{"id":56428,"text":"New York Department of Conservation","active":true,"usgs":false}],"preferred":false,"id":832606,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kenney, Gregg H.","contributorId":273138,"corporation":false,"usgs":false,"family":"Kenney","given":"Gregg","email":"","middleInitial":"H.","affiliations":[{"id":56428,"text":"New York Department of Conservation","active":true,"usgs":false}],"preferred":false,"id":832607,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sullivan, Patrick J.","contributorId":273139,"corporation":false,"usgs":false,"family":"Sullivan","given":"Patrick J.","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":832608,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Sethi, Suresh 0000-0002-0053-1827 ssethi@usgs.gov","orcid":"https://orcid.org/0000-0002-0053-1827","contributorId":191424,"corporation":false,"usgs":true,"family":"Sethi","given":"Suresh","email":"ssethi@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":832603,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Harris, Bradley P.","contributorId":273140,"corporation":false,"usgs":false,"family":"Harris","given":"Bradley","email":"","middleInitial":"P.","affiliations":[{"id":12915,"text":"Alaska Pacific University","active":true,"usgs":false}],"preferred":false,"id":832609,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70206328,"text":"70206328 - 2019 - A landscape-level assessment of whitebark pine regeneration in the Rocky Mountains, USA","interactions":[],"lastModifiedDate":"2019-10-30T15:05:11","indexId":"70206328","displayToPublicDate":"2018-08-29T15:02:56","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1688,"text":"Forest Science","active":true,"publicationSubtype":{"id":10}},"title":"A landscape-level assessment of whitebark pine regeneration in the Rocky Mountains, USA","docAbstract":"Whitebark pine (Pinus albicaulis Engelm.) has recently experienced high mortality due to multiple stressors, and future population viability may rely on natural regeneration. We assessed whitebark pine seedling densities throughout the US Rocky Mountains and identified stand, site, and climatic variables related to seedling presence based on data from 1,217 USDA Forest Service Forest Inventory and Analysis plots. Although mean densities were highest in the whitebark pine forest type, 83% of sites with seedlings present occurred in non-whitebark pine forest types, and the highest densities occurred in the lodgepole pine forest type. To identify factors related to whitebark pine seedling presence, we compared the results generated from three statistical models: logistic regression, classification tree, and random forests. All three models identified cover of grouse whortleberry (Vaccinium scoparium Leiberg ex Coville) as an important predictor, two models distinguished live and dead whitebark pine basal area and elevation, and one model recognized seasonal temperature. None of the models identified forest type as an important predictor. Understanding these factors may help managers identify areas where natural regeneration of whitebark pine is likely to occur, including sites in non-whitebark pine forest types.","language":"English","publisher":"Oxford Academic","doi":"10.1093/forsci/fxy029","usgsCitation":"Goeking, S., Izlar, D., and Edwards, T., 2019, A landscape-level assessment of whitebark pine regeneration in the Rocky Mountains, USA: Forest Science, v. 65, no. 1, p. 87-99, https://doi.org/10.1093/forsci/fxy029.","productDescription":"13 p.","startPage":"87","endPage":"99","ipdsId":"IP-088499","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":468104,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/forsci/fxy029","text":"Publisher Index Page"},{"id":368752,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Rocky Mountains","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117.861328125,\n 46.86019101567027\n ],\n [\n -113.466796875,\n 42.4234565179383\n ],\n [\n -111.005859375,\n 40.17887331434696\n ],\n [\n -107.57812499999999,\n 39.977120098439634\n ],\n [\n -108.19335937499999,\n 38.34165619279595\n ],\n [\n -106.787109375,\n 36.10237644873644\n ],\n [\n -103.88671875,\n 37.09023980307208\n ],\n [\n -104.32617187499999,\n 39.027718840211605\n ],\n [\n -105.46875,\n 40.84706035607122\n ],\n [\n -106.69921875,\n 43.389081939117496\n ],\n [\n -110.74218749999999,\n 46.255846818480315\n ],\n [\n -113.02734374999999,\n 47.45780853075031\n ],\n [\n -113.818359375,\n 48.86471476180277\n ],\n [\n -116.19140625,\n 48.80686346108517\n ],\n [\n -117.861328125,\n 46.86019101567027\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"65","issue":"1","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2018-08-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Goeking, Sara","contributorId":220117,"corporation":false,"usgs":false,"family":"Goeking","given":"Sara","email":"","affiliations":[{"id":36493,"text":"USDA Forest Service","active":true,"usgs":false}],"preferred":false,"id":774171,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Izlar, Deborah","contributorId":220118,"corporation":false,"usgs":false,"family":"Izlar","given":"Deborah","email":"","affiliations":[{"id":36493,"text":"USDA Forest Service","active":true,"usgs":false}],"preferred":false,"id":774172,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Edwards, Thomas C. Jr. 0000-0002-0773-0909 tce@usgs.gov","orcid":"https://orcid.org/0000-0002-0773-0909","contributorId":191916,"corporation":false,"usgs":true,"family":"Edwards","given":"Thomas C.","suffix":"Jr.","email":"tce@usgs.gov","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":false,"id":774170,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70204962,"text":"70204962 - 2019 - Characterizing residence patterns of North Atlantic right whales in the southeastern U.S. with a multistate open robust design model","interactions":[],"lastModifiedDate":"2019-08-28T09:20:29","indexId":"70204962","displayToPublicDate":"2018-08-29T08:52:41","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1497,"text":"Endangered Species Research","active":true,"publicationSubtype":{"id":10}},"title":"Characterizing residence patterns of North Atlantic right whales in the southeastern U.S. with a multistate open robust design model","docAbstract":"Effective conservation of endangered North Atlantic right whales (Eubalaena glacialis) requires information about their spatio-temporal distribution. Understanding temporal distribution is particularly important, because a portion of the population migrates between high latitude summer feeding grounds off the northeastern U.S. and Canadian Maritimes coasts and lower latitude calving and wintering grounds off the southeastern U.S. coast (SEUS). Here, we modeled SEUS residence patterns using photo-identification data from coastal South Carolina, Georgia, and Florida from seven winter seasons (2004/2005 – 2010/2011). We used multistate open robust design models to evaluate effects of reproductive status, demographic group, and environmental conditions on SEUS residence. Model estimates accounted for temporal variation and imperfect detection and provided probabilities of entering the SEUS, staying in the SEUS, and being sighted. We also derived estimates for residence time and seasonal abundance. We observed staggered arrival and departure patterns and demographic differences in residence patterns that are characteristic of a differential migration strategy. Calving females arrived earliest and, in most seasons, had mean residence periods more than twice as long as other demographic groups. Conversely, adult males arrived the latest, and had the shortest residence times. Within-season, biweekly detection was positively influenced by survey effort, and seasonal detection rate estimates ranged from 0.83 ± 0.08 for non-calving adult females to 0.98 ± 0.02 for calving females. Results provide insights into right whale behavior, biology, and temporal distribution in the SEUS and can be used to evaluate spatially- and temporally- dynamic management measures.","language":"English","publisher":"Inter-Research","doi":"10.3354/esr00902","usgsCitation":"Krystan, A., Gowan, T., Kendall, W.L., Martin, J., Ortega-Ortiz, J., Jackson, K., Knowlton, A., Naessig, P., Zani, M., Schulte, D., and Taylor, C., 2019, Characterizing residence patterns of North Atlantic right whales in the southeastern U.S. with a multistate open robust design model: Endangered Species Research, v. 36, p. 279-295, https://doi.org/10.3354/esr00902.","productDescription":"17 p.","startPage":"279","endPage":"295","ipdsId":"IP-089091","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":460581,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index 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PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Krystan, A.M.","contributorId":218446,"corporation":false,"usgs":false,"family":"Krystan","given":"A.M.","email":"","affiliations":[{"id":20317,"text":"Florida Fish and Wildlife Research Institute","active":true,"usgs":false}],"preferred":false,"id":769293,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gowan, T.A.","contributorId":218447,"corporation":false,"usgs":false,"family":"Gowan","given":"T.A.","email":"","affiliations":[{"id":20317,"text":"Florida Fish and Wildlife Research Institute","active":true,"usgs":false}],"preferred":false,"id":769294,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kendall, William L. 0000-0003-0084-9891","orcid":"https://orcid.org/0000-0003-0084-9891","contributorId":204844,"corporation":false,"usgs":true,"family":"Kendall","given":"William","email":"","middleInitial":"L.","affiliations":[{"id":200,"text":"Coop Res Unit 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K.B.","contributorId":206454,"corporation":false,"usgs":false,"family":"Jackson","given":"K.B.","email":"","affiliations":[],"preferred":false,"id":769296,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Knowlton, A.R.","contributorId":218449,"corporation":false,"usgs":false,"family":"Knowlton","given":"A.R.","email":"","affiliations":[{"id":37373,"text":"New England Aquarium","active":true,"usgs":false}],"preferred":false,"id":769297,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Naessig, P.","contributorId":218450,"corporation":false,"usgs":false,"family":"Naessig","given":"P.","email":"","affiliations":[{"id":26955,"text":"Sea to Shore Alliance","active":true,"usgs":false}],"preferred":false,"id":769298,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Zani, M.","contributorId":218451,"corporation":false,"usgs":false,"family":"Zani","given":"M.","email":"","affiliations":[{"id":37373,"text":"New England Aquarium","active":true,"usgs":false}],"preferred":false,"id":769299,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Schulte, D.W.","contributorId":218452,"corporation":false,"usgs":false,"family":"Schulte","given":"D.W.","email":"","affiliations":[{"id":26955,"text":"Sea to Shore Alliance","active":true,"usgs":false}],"preferred":false,"id":769300,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Taylor, C.R.","contributorId":218453,"corporation":false,"usgs":false,"family":"Taylor","given":"C.R.","email":"","affiliations":[{"id":26955,"text":"Sea to Shore Alliance","active":true,"usgs":false}],"preferred":false,"id":769301,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70201364,"text":"70201364 - 2019 - A Bayesian approach to predict sub-annual beach change and recovery","interactions":[],"lastModifiedDate":"2019-01-28T08:33:37","indexId":"70201364","displayToPublicDate":"2018-08-27T14:14:37","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1584,"text":"Estuaries and Coasts","active":true,"publicationSubtype":{"id":10}},"title":"A Bayesian approach to predict sub-annual beach change and recovery","docAbstract":"The upper beach, between the astronomical high tide and the dune-toe, supports habitat and recreation along many beaches, making predictions of upper beach change valuable to coastal managers and the public. We developed and tested a Bayesian network (BN) to predict the cross-shore position of an upper beach elevation contour (ZlD) following 1 month to 1-year intervals at Fire Island, New York. We combine hydrodynamic data with series of island-wide topographic data and spatially limited cross-shore profiles. First, we predicted beach configuration of ZlD positions at high spatial resolution (50 m) over intervals spanning 2005–2014. Compared to untrained model predictions, in which all six outcomes are equally likely (prior likelihood = 0.16), our prediction metrics (skill = 0.52; log likelihood ratio = 0.14; accuracy = 0.56) indicate the BN confidently predicts upper beach dynamics. Next, the BN forecasted three intervals of beach recovery following Hurricane Sandy. Results suggest the pre-Sandy training data is sufficiently robust to require only periodic updates to beach slope observations to maintain confidence for forecasts. Finally, we varied input data, using observations collected at a range of temporal (1–12 months) and spatial (50 m to > 1 km) resolutions to evaluate model skill. This experiment shows that data collection techniques with different spatial and temporal frequencies can be used to inform a single modeling framework and can provide insight to BN training requirements. Overall, results indicate that BNs and inputs can be developed for broad coastal change assessment or tailored to a set of predictive requirements, making this methodology applicable to a variety of coastal prediction scenarios.
","language":"English","publisher":"Springer","doi":"10.1007/s12237-018-0444-1","usgsCitation":"Wilson, K., Lentz, E.E., Miselis, J.L., Safak, I., and Brenner, O.T., 2019, A Bayesian approach to predict sub-annual beach change and recovery: Estuaries and Coasts, v. 42, no. 1, p. 112-131, https://doi.org/10.1007/s12237-018-0444-1.","productDescription":"20 p.","startPage":"112","endPage":"131","ipdsId":"IP-088528","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":360174,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"42","issue":"1","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2018-08-27","publicationStatus":"PW","scienceBaseUri":"5c10a953e4b034bf6a7e514b","contributors":{"authors":[{"text":"Wilson, Kathleen 0000-0002-2810-7585 kwilson@usgs.gov","orcid":"https://orcid.org/0000-0002-2810-7585","contributorId":195620,"corporation":false,"usgs":true,"family":"Wilson","given":"Kathleen","email":"kwilson@usgs.gov","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":753813,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lentz, Erika E. 0000-0002-0621-8954 elentz@usgs.gov","orcid":"https://orcid.org/0000-0002-0621-8954","contributorId":173964,"corporation":false,"usgs":true,"family":"Lentz","given":"Erika","email":"elentz@usgs.gov","middleInitial":"E.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":753814,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Miselis, Jennifer L. 0000-0002-4925-3979 jmiselis@usgs.gov","orcid":"https://orcid.org/0000-0002-4925-3979","contributorId":3914,"corporation":false,"usgs":true,"family":"Miselis","given":"Jennifer","email":"jmiselis@usgs.gov","middleInitial":"L.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":753815,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Safak, Ilgar 0000-0001-7675-0770 isafak@usgs.gov","orcid":"https://orcid.org/0000-0001-7675-0770","contributorId":5522,"corporation":false,"usgs":true,"family":"Safak","given":"Ilgar","email":"isafak@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":753816,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Brenner, Owen T. 0000-0002-1588-721X obrenner@usgs.gov","orcid":"https://orcid.org/0000-0002-1588-721X","contributorId":4933,"corporation":false,"usgs":true,"family":"Brenner","given":"Owen","email":"obrenner@usgs.gov","middleInitial":"T.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":753817,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70206990,"text":"70206990 - 2019 - Pressure core analysis of geomechanical and fluid flow properties of seals associated with gas hydrate-bearing reservoirs in the Krishna-Godavari Basin, offshore India","interactions":[],"lastModifiedDate":"2019-12-03T08:31:39","indexId":"70206990","displayToPublicDate":"2018-08-18T08:24:39","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2682,"text":"Marine and Petroleum Geology","active":true,"publicationSubtype":{"id":10}},"title":"Pressure core analysis of geomechanical and fluid flow properties of seals associated with gas hydrate-bearing reservoirs in the Krishna-Godavari Basin, offshore India","docAbstract":"Physical properties of the sediment directly overlying a gas hydrate reservoir provide important controls on the effectiveness of depressurizing that reservoir to extract methane from gas hydrate as an energy resource. The permeability of overlying sediment determines if a gas hydrate reservoir’s upper contact will provide an effective seal that enables efficient reservoir depressurization. Compressibility, stiffness and strength indicate how overlying sediment will deform as the in situ stress changes during production, providing engineering data for well designs. Assessing these properties requires minimally-disturbed sediment. India’s National Gas Hydrates Program Expedition 2 (NGHP-02) provided an opportunity to study these seal sediment properties, reducing disturbance from gas exsolution and bubble growth by collecting a pressure core from the seal sediment just above the primary gas hydrate reservoir at Site NGHP-02-08 in Area C of the Krishna-Godavari Basin. The effective stress chamber (ESC) and the direct shear chamber (DSC) devices in the suite of Pressure Core Characterization Tools (PCCTs) were used to measure permeability, compressibility, stiffness and shear strength at the in situ vertical stress. Geotechnical properties of the predominantly fine-grained seal layer at in situ vertical stress are in typical clay sediment ranges, with low measured permeability (0.02 mD), high compressibility (Cc = 0.26 – 0.33) and low shear strength (404 kPa). Though pressure and temperature were maintained throughout the collection and measurement process to stabilize gas hydrate, the lack of effective stress in the pressure core storage chamber and the chamber pressurization with methane-free water caused core expansion and gas hydrate in a thin coarser-grained layer to dissolve. The PCCTs can reapply in situ stress with incremental loading steps during a consolidation test to account for sediment compaction. Gas hydrate dissolution can be limited by storing cores just above freezing temperatures, and by using solid spacers to reduce the storage chamber’s free volume.","language":"English","publisher":"Elsevier","doi":"10.1016/j.marpetgeo.2018.08.015","usgsCitation":"Jang, J., Dai, S., Yoneda, J., Waite, W., Stern, L.A., Boze, L., Collett, T.S., and Kumar, P., 2019, Pressure core analysis of geomechanical and fluid flow properties of seals associated with gas hydrate-bearing reservoirs in the Krishna-Godavari Basin, offshore India: Marine and Petroleum Geology, v. 108, p. 537-550, https://doi.org/10.1016/j.marpetgeo.2018.08.015.","productDescription":"14 p.","startPage":"537","endPage":"550","ipdsId":"IP-097103","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true},{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":468108,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.osti.gov/biblio/1469805","text":"External Repository"},{"id":369853,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"India","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[77.83745,35.49401],[78.91227,34.32194],[78.81109,33.5062],[79.20889,32.99439],[79.17613,32.48378],[78.45845,32.61816],[78.73889,31.51591],[79.72137,30.88271],[81.11126,30.18348],[80.47672,29.72987],[80.08842,28.79447],[81.0572,28.4161],[81.99999,27.92548],[83.30425,27.36451],[84.67502,27.2349],[85.25178,26.7262],[86.02439,26.63098],[87.22747,26.3979],[88.06024,26.41462],[88.1748,26.81041],[88.04313,27.44582],[88.12044,27.87654],[88.73033,28.08686],[88.81425,27.29932],[88.83564,27.09897],[89.74453,26.7194],[90.37327,26.87572],[91.21751,26.80865],[92.03348,26.83831],[92.10371,27.45261],[91.69666,27.77174],[92.50312,27.89688],[93.41335,28.64063],[94.56599,29.27744],[95.4048,29.03172],[96.11768,29.4528],[96.58659,28.83098],[96.24883,28.41103],[97.32711,28.26158],[97.40256,27.88254],[97.05199,27.69906],[97.134,27.08377],[96.41937,27.26459],[95.12477,26.57357],[95.15515,26.00131],[94.60325,25.1625],[94.55266,24.67524],[94.10674,23.85074],[93.32519,24.07856],[93.28633,23.04366],[93.06029,22.70311],[93.16613,22.27846],[92.67272,22.04124],[92.14603,23.6275],[91.86993,23.62435],[91.70648,22.98526],[91.15896,23.50353],[91.46773,24.07264],[91.91509,24.13041],[92.3762,24.97669],[91.7996,25.14743],[90.87221,25.1326],[89.92069,25.26975],[89.83248,25.96508],[89.35509,26.01441],[88.56305,26.44653],[88.20979,25.76807],[88.93155,25.23869],[88.30637,24.86608],[88.08442,24.50166],[88.69994,24.23371],[88.52977,23.63114],[88.87631,22.87915],[89.03196,22.05571],[88.88877,21.69059],[88.2085,21.70317],[86.9757,21.49556],[87.03317,20.74331],[86.49935,20.15164],[85.06027,19.47858],[83.94101,18.30201],[83.18922,17.67122],[82.19279,17.01664],[82.19124,16.55666],[81.69272,16.31022],[80.792,15.95197],[80.3249,15.89918],[80.02507,15.13641],[80.23327,13.83577],[80.28629,13.00626],[79.86255,12.05622],[79.858,10.35728],[79.34051,10.30885],[78.88535,9.54614],[79.18972,9.21654],[78.27794,8.93305],[77.94117,8.25296],[77.5399,7.96553],[76.59298,8.89928],[76.13006,10.29963],[75.74647,11.30825],[75.3961,11.78125],[74.86482,12.74194],[74.61672,13.99258],[74.44386,14.61722],[73.5342,15.99065],[73.11991,17.92857],[72.82091,19.20823],[72.82448,20.4195],[72.63053,21.35601],[71.17527,20.75744],[70.47046,20.87733],[69.16413,22.0893],[69.64493,22.45077],[69.3496,22.84318],[68.17665,23.69197],[68.8426,24.35913],[71.04324,24.35652],[70.8447,25.2151],[70.28287,25.72223],[70.16893,26.49187],[69.51439,26.94097],[70.6165,27.9892],[71.77767,27.91318],[72.82375,28.96159],[73.45064,29.97641],[74.42138,30.97981],[74.40593,31.69264],[75.25864,32.27111],[74.45156,32.7649],[74.10429,33.44147],[73.74995,34.3177],[74.2402,34.74889],[75.75706,34.50492],[76.87172,34.65354],[77.83745,35.49401]]]},\"properties\":{\"name\":\"India\"}}]}","volume":"108","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Jang, Junbong 0000-0001-5500-7558 jjang@usgs.gov","orcid":"https://orcid.org/0000-0001-5500-7558","contributorId":189400,"corporation":false,"usgs":true,"family":"Jang","given":"Junbong","email":"jjang@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":776532,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dai, Sheng","contributorId":213194,"corporation":false,"usgs":false,"family":"Dai","given":"Sheng","email":"","affiliations":[{"id":38715,"text":"Georgia Institute of Technology, Atlanta, GA","active":true,"usgs":false}],"preferred":false,"id":776533,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Yoneda, J.","contributorId":195813,"corporation":false,"usgs":false,"family":"Yoneda","given":"J.","email":"","affiliations":[],"preferred":false,"id":776534,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Waite, William F. 0000-0002-9436-4109 wwaite@usgs.gov","orcid":"https://orcid.org/0000-0002-9436-4109","contributorId":625,"corporation":false,"usgs":true,"family":"Waite","given":"William F.","email":"wwaite@usgs.gov","affiliations":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":776535,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Stern, Laura A. 0000-0003-3440-5674 lstern@usgs.gov","orcid":"https://orcid.org/0000-0003-3440-5674","contributorId":1197,"corporation":false,"usgs":true,"family":"Stern","given":"Laura","email":"lstern@usgs.gov","middleInitial":"A.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":776536,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Boze, Lee-Gray 0000-0003-1853-7888 lboze@usgs.gov","orcid":"https://orcid.org/0000-0003-1853-7888","contributorId":220996,"corporation":false,"usgs":true,"family":"Boze","given":"Lee-Gray","email":"lboze@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":776537,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Collett, Timothy S. 0000-0002-7598-4708 tcollett@usgs.gov","orcid":"https://orcid.org/0000-0002-7598-4708","contributorId":1698,"corporation":false,"usgs":true,"family":"Collett","given":"Timothy","email":"tcollett@usgs.gov","middleInitial":"S.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":776538,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Kumar, Pushpendra","contributorId":212239,"corporation":false,"usgs":false,"family":"Kumar","given":"Pushpendra","affiliations":[{"id":38465,"text":"Oil and Natural Gas Corp. Panvel, Navi Mumbai, India","active":true,"usgs":false}],"preferred":false,"id":776539,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70203045,"text":"70203045 - 2019 - Tools for managing hydrologic alteration on a regional scale II: Setting targets to protect stream health","interactions":[],"lastModifiedDate":"2019-04-15T11:06:56","indexId":"70203045","displayToPublicDate":"2018-08-15T11:06:40","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1696,"text":"Freshwater Biology","active":true,"publicationSubtype":{"id":10}},"title":"Tools for managing hydrologic alteration on a regional scale II: Setting targets to protect stream health","docAbstract":"Widespread hydrologic alteration creates a need for tools to assess ecological impacts to streams that can be applied across large geographic scales. A regional framework for biologically based flow management can help catchment managers prioritise streams for protection, evaluate impacts of disturbance or interventions and provide a starting point for causal assessment in degraded streams. However, lack of flow data limit the ability to assess hydrologic conditions across a region.\nHydrologic models can address this problem. Regionally calibrated hydrologic models were used to estimate current and reference flows at 572 bioassessment sites in southern and central coastal California. Flow alteration was characterised as the difference in 39 flow metrics calculated from simulations of present‐day and reference flow time‐series, calculated under up to four precipitation conditions.\nBiological condition was assessed with the California Stream Condition Index (CSCI) and its components. Logistic regressions were used to predict the likelihood of high scores (i.e. ≥10th percentile of the CSCI reference calibration data). Statistically significant relationships between increasing severity of hydrologic alteration and decreasing biological condition were used to set thresholds that reflected tolerance for risk of a stakeholder advisory group.\nAn index of hydrologic alteration was created by selecting flow metrics based on their importance for predicting biological response variables in boosted regression tree models. Metrics were selected in the order of decreasing importance, and no more than two metrics per metric class were selected (i.e. duration, frequency, magnitude, timing and variability). Seven metrics were selected: HighDur (duration of high‐flow events), HighNum (# of high‐flow events), NoDisturb (duration between high‐ or low‐flow events), MaxMonthQ (maximum monthly discharge), Q99 (99th percentile of daily streamflow), QmaxIDR (interdecile range of annual maxima) and RBI (Richards–Baker Index).\nApplying the index to data from a probabilistic survey, 34% of stream‐miles in southern California were estimated to be hydrologically altered. One of four management priorities were assigned to each site based on biological condition and hydrologic status: protection (healthy and unaltered, 52% of stream‐miles), monitoring (healthy but altered 4%), evaluation of flow management (unhealthy and altered, 30%) and evaluation of other management (unhealthy but unaltered, 14%).\nRegionally derived biologically based targets for flow alteration allow catchment managers to prioritise activities and conduct screenings for causal assessments across large spatial scales. Furthermore, regional tools pave the way for incorporation of hydrologic management in policies and catchment planning designed to support biological integrity in streams. Development of regional tools should be a priority where hydrologic alteration is pervasive or expected to increase in response to climate change or urbanisation.","language":"English","publisher":"Wiley","doi":"10.1111/fwb.13062","usgsCitation":"Mazor, R.D., May, J.T., Sengupta, A., McCune, K.S., Bledsoe, B.P., and Stein, E.D., 2019, Tools for managing hydrologic alteration on a regional scale II: Setting targets to protect stream health: Freshwater Biology, v. 63, no. 8, p. 786-803, https://doi.org/10.1111/fwb.13062.","productDescription":"18 p.","startPage":"786","endPage":"803","ipdsId":"IP-083790","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":362952,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"63","issue":"8","edition":"Special","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2018-01-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Mazor, Raphael D.","contributorId":173011,"corporation":false,"usgs":false,"family":"Mazor","given":"Raphael","email":"","middleInitial":"D.","affiliations":[{"id":12704,"text":"Southern California Coastal Water Research Project","active":true,"usgs":false}],"preferred":false,"id":760924,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"May, Jason T. 0000-0002-5699-2112 jasonmay@usgs.gov","orcid":"https://orcid.org/0000-0002-5699-2112","contributorId":617,"corporation":false,"usgs":true,"family":"May","given":"Jason","email":"jasonmay@usgs.gov","middleInitial":"T.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":false,"id":760925,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sengupta, Ashmita","contributorId":214836,"corporation":false,"usgs":false,"family":"Sengupta","given":"Ashmita","email":"","affiliations":[{"id":12704,"text":"Southern California Coastal Water Research Project","active":true,"usgs":false}],"preferred":false,"id":760926,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McCune, Kenneth S.","contributorId":214837,"corporation":false,"usgs":false,"family":"McCune","given":"Kenneth","email":"","middleInitial":"S.","affiliations":[{"id":12704,"text":"Southern California Coastal Water Research Project","active":true,"usgs":false}],"preferred":false,"id":760927,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bledsoe, Brian P.","contributorId":140605,"corporation":false,"usgs":false,"family":"Bledsoe","given":"Brian","email":"","middleInitial":"P.","affiliations":[{"id":13538,"text":"Department of Civil and Environmental Engineering, Colorado State University, Fort Collins, Colorado","active":true,"usgs":false}],"preferred":false,"id":760928,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Stein, Eric D.","contributorId":198848,"corporation":false,"usgs":false,"family":"Stein","given":"Eric","email":"","middleInitial":"D.","affiliations":[{"id":12704,"text":"Southern California Coastal Water Research Project","active":true,"usgs":false}],"preferred":false,"id":760929,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70205016,"text":"70205016 - 2019 - Airborne bacteria in Earth’s lower stratosphere resemble taxa detected in the troposphere: results from a new NASA aircraft bioaerosol collector (ABC)","interactions":[],"lastModifiedDate":"2023-11-27T14:47:05.833799","indexId":"70205016","displayToPublicDate":"2018-08-14T10:58:57","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1702,"text":"Frontiers in Microbiology","onlineIssn":"1664-302X","active":true,"publicationSubtype":{"id":10}},"title":"Airborne bacteria in Earth’s lower stratosphere resemble taxa detected in the troposphere: results from a new NASA aircraft bioaerosol collector (ABC)","docAbstract":"Airborne microorganisms in the upper troposphere and lower stratosphere remain elusive due to a lack of reliable sample collection systems. To address this problem, we designed, installed, and flight-validated a novel Aircraft Bioaerosol Collector (ABC) for NASA's C-20A that can make collections for microbiological research investigations up to altitudes of 13.7 km. Herein we report results from the first set of science flights—four consecutive missions flown over the United States (US) from 30 October to 2 November, 2017. To ascertain how the concentration of airborne bacteria changed across the tropopause, we collected air during aircraft Ascent/Descent (0.3 to 11 km), as well as sustained Cruise altitudes in the lower stratosphere (~12 km). Bioaerosols were captured on DNA-treated gelatinous filters inside a cascade air sampler, then analyzed with molecular and culture-based characterization. Several viable bacterial isolates were recovered from flight altitudes, including Bacillus sp., Micrococcus sp., Arthrobacter sp., and Staphylococcus sp. from Cruise samples and Brachybacterium sp. from Ascent/Descent samples. Using 16S V4 sequencing methods for a culture-independent analysis of bacteria, the average number of total OTUs was 305 for Cruise samples and 276 for Ascent/Descent samples. Some taxa were more abundant in the flight samples than the ground samples, including OTUs from families Lachnospiraceae, Ruminococcaceae and Erysipelotrichaceae as well as the following genera: Clostridium, Mogibacterium, Corynebacterium, Bacteroides, Prevotella, Pseudomonas, and Parabacteroides. Surprisingly, our results revealed a homogeneous distribution of bacteria in the atmosphere up to 12 km. The observation could be due to atmospheric conditions producing similar background aerosols across the western US, as suggested by modeled back trajectories and satellite measurements. However, the influence of aircraft-associated bacterial contaminants could not be fully eliminated and that background signal was reported throughout our dataset. Considering the tremendous engineering challenge of collecting biomass at extreme altitudes where contamination from flight hardware remains an ever-present issue, we note the utility of using the stratosphere as a proving ground for planned life detection missions across the solar system.
","language":"English","publisher":"Frontiers Media","doi":"10.3389/fmicb.2018.01752","usgsCitation":"David J. Smith, Ravichandar, J.D., Jain, S., Griffin, D.W., Yu, H., Tan, Q., Thissen, J., Lusby, T., Nicoll, P., Shedler, S., Martinez, P., Osorio, A., Lechniak, J., Choi, S., Sabino, K., Iverson, K., Chan, L., Jaing, C., and McGrath, J., 2019, Airborne bacteria in Earth’s lower stratosphere resemble taxa detected in the troposphere: results from a new NASA aircraft bioaerosol collector (ABC): Frontiers in Microbiology, v. 9, 1752, 20 p., https://doi.org/10.3389/fmicb.2018.01752.","productDescription":"1752, 20 p.","ipdsId":"IP-097097","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":468111,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fmicb.2018.01752","text":"Publisher Index Page"},{"id":367005,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona, California, Colorado, Nevada, Utah","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124.51904296875,\n 32.63937487360669\n ],\n [\n -111.0498046875,\n 32.63937487360669\n ],\n [\n -111.0498046875,\n 41.52502957323801\n ],\n [\n -124.51904296875,\n 41.52502957323801\n ],\n [\n -124.51904296875,\n 32.63937487360669\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"9","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2018-08-14","publicationStatus":"PW","contributors":{"authors":[{"text":"David J. 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2019 - Landscape structure and temporal dynamic effects on Wintering Mallard abundance and distributions in the Mississippi alluvial valley","interactions":[],"lastModifiedDate":"2019-07-26T10:25:40","indexId":"70204440","displayToPublicDate":"2018-08-01T12:54:22","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2602,"text":"Landscape Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Landscape structure and temporal dynamic effects on Wintering Mallard abundance and distributions in the Mississippi alluvial valley","docAbstract":"Context Management of wintering waterfowl in North America requires adaptability because constant landscape and environmental change challenges existing management strategies regarding waterfowl habitat use at large spatial scales. Migratory waterfowl including mallards (Anas platyrhynchos) use the lower Mississippi Alluvial Valley (MAV) for wintering habitat, making this an important area of emphasis for improving wetland conservation strategies, while enhancing the understanding of landscape-use patterns.\nObjectives We used aerial survey data collected in the Arkansas portion of the MAV (ARMAV) to explain the abundance and distribution of mallards in relation to variable landscape conditions.\nMethods We used two-stage, hierarchical spatio-temporal models with a random spatial effect to identify covariates related to changes in mallard abundance and distribution within and among years.\nResults We found distinct spatio-temporal patterns existed for mallard distributions across the ARMAV and these distributions are dependent on the surrounding landscape structure and changing environmental conditions. Models performing best indicated seasonal surface water extent, rice field, wetland and fallow (uncultivated) field abundance positively influenced mallard distribution. Rice fields, surface water and weather were found to influence mallard abundance. Additionally, are results suggest weather and changing surface water affects mallard presence and abundance throughout the winter, because the probability of mallard presence and abundance changed from the northern ARMAV in November to the southern ARMAV in January. \nConclusions Using novel datasets to identify which environmental factors drive changes in regional wildlife distribution and abundance can improve management by providing managers additional information to manage land over landscapes spanning private and public lands. We suggest our analytical approach may be informative in other areas and for other wildlife species.","language":"English","publisher":"Springer","doi":"10.1007/s10980-018-0671-7","usgsCitation":"Herbert, J.A., Chakraborty, A., Naylor, L.W., Beattty, W.S., and Krementz, D.G., 2019, Landscape structure and temporal dynamic effects on Wintering Mallard abundance and distributions in the Mississippi alluvial valley: Landscape Ecology, v. 33, no. 8, p. 1319-1334, https://doi.org/10.1007/s10980-018-0671-7.","productDescription":"16 p.","startPage":"1319","endPage":"1334","ipdsId":"IP-083954","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":365952,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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