{"pageNumber":"439","pageRowStart":"10950","pageSize":"25","recordCount":40797,"records":[{"id":70186667,"text":"70186667 - 2017 - The interaction of climate change and methane hydrates","interactions":[],"lastModifiedDate":"2017-04-19T15:40:55","indexId":"70186667","displayToPublicDate":"2017-04-07T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3283,"text":"Reviews of Geophysics","active":true,"publicationSubtype":{"id":10}},"title":"The interaction of climate change and methane hydrates","docAbstract":"<p><span>Gas hydrate, a frozen, naturally-occurring, and highly-concentrated form of methane, sequesters significant carbon in the global system and is stable only over a range of low-temperature and moderate-pressure conditions. Gas hydrate is widespread in the sediments of marine continental margins and permafrost areas, locations where ocean and atmospheric warming may perturb the hydrate stability field and lead to release of the sequestered methane into the overlying sediments and soils. Methane and methane-derived carbon that escape from sediments and soils and reach the atmosphere could exacerbate greenhouse warming. The synergy between warming climate and gas hydrate dissociation feeds a popular perception that global warming could drive catastrophic methane releases from the contemporary gas hydrate reservoir. Appropriate evaluation of the two sides of the climate-methane hydrate synergy requires assessing direct and indirect observational data related to gas hydrate dissociation phenomena and numerical models that track the interaction of gas hydrates/methane with the ocean and/or atmosphere. Methane hydrate is likely undergoing dissociation now on global upper continental slopes and on continental shelves that ring the Arctic Ocean. Many factors—the depth of the gas hydrates in sediments, strong sediment and water column sinks, and the inability of bubbles emitted at the seafloor to deliver methane to the sea-air interface in most cases—mitigate the impact of gas hydrate dissociation on atmospheric greenhouse gas concentrations though. There is no conclusive proof that hydrate-derived methane is reaching the atmosphere now, but more observational data and improved numerical models will better characterize the climate-hydrate synergy in the future.</span></p>","language":"English","publisher":"AGU","doi":"10.1002/2016RG000534","usgsCitation":"Ruppel, C., and Kessler, J.D., 2017, The interaction of climate change and methane hydrates: Reviews of Geophysics, v. 55, no. 1, p. 126-168, https://doi.org/10.1002/2016RG000534.","productDescription":"43 p.","startPage":"126","endPage":"168","ipdsId":"IP-079102","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":469938,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2016rg000534","text":"Publisher Index Page"},{"id":339403,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"55","issue":"1","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationDate":"2017-02-08","publicationStatus":"PW","scienceBaseUri":"58e8a541e4b09da6799d639f","chorus":{"doi":"10.1002/2016rg000534","url":"http://dx.doi.org/10.1002/2016rg000534","publisher":"Wiley-Blackwell","authors":"Ruppel Carolyn D., Kessler John D.","journalName":"Reviews of Geophysics","publicationDate":"2017","publiclyAccessibleDate":"2/8/2017"},"contributors":{"authors":[{"text":"Ruppel, Carolyn D. 0000-0003-2284-6632 cruppel@usgs.gov","orcid":"https://orcid.org/0000-0003-2284-6632","contributorId":145770,"corporation":false,"usgs":true,"family":"Ruppel","given":"Carolyn D.","email":"cruppel@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":690216,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kessler, John D. 0000-0003-1097-6800","orcid":"https://orcid.org/0000-0003-1097-6800","contributorId":184241,"corporation":false,"usgs":false,"family":"Kessler","given":"John","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":690217,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70186672,"text":"70186672 - 2017 - Observations and 3D hydrodynamics-based modeling of decadal-scale shoreline change along the Outer Banks, North Carolina","interactions":[],"lastModifiedDate":"2017-04-07T09:34:37","indexId":"70186672","displayToPublicDate":"2017-04-07T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1262,"text":"Coastal Engineering","active":true,"publicationSubtype":{"id":10}},"title":"Observations and 3D hydrodynamics-based modeling of decadal-scale shoreline change along the Outer Banks, North Carolina","docAbstract":"<p><span>Long-term decadal-scale shoreline change is an important parameter for quantifying the stability of coastal systems. The decadal-scale coastal change is controlled by processes that occur on short time scales (such as storms) and long-term processes (such as prevailing waves). The ability to predict decadal-scale shoreline change is not well established and the fundamental physical processes controlling this change are not well understood. Here we investigate the processes that create large-scale long-term shoreline change along the Outer Banks of North Carolina, an uninterrupted 60&nbsp;km stretch of coastline, using both observations and a numerical modeling approach. Shoreline positions for a 24-yr period were derived from aerial photographs of the Outer Banks. Analysis of the shoreline position data showed that, although variable, the shoreline eroded an average of 1.5&nbsp;m/yr throughout this period. The modeling approach uses a three-dimensional hydrodynamics-based numerical model coupled to a spectral wave model and simulates the full 24-yr time period on a spatial grid running on a short (second scale) time-step to compute the sediment transport patterns. The observations and the model results show similar magnitudes (O(10</span><sup>5</sup><span>&nbsp;m</span><sup>3</sup><span>/yr)) and patterns of alongshore sediment fluxes. Both the observed and the modeled alongshore sediment transport rates have more rapid changes at the north of our section due to continuously curving coastline, and possible effects of alongshore variations in shelf bathymetry. The southern section with a relatively uniform orientation, on the other hand, has less rapid transport rate changes. Alongshore gradients of the modeled sediment fluxes are translated into shoreline change rates that have agreement in some locations but vary in others. Differences between observations and model results are potentially influenced by geologic framework processes not included in the model. Both the observations and the model results show higher rates of erosion (∼−1&nbsp;m/yr) averaged over the northern half of the section as compared to the southern half where the observed and modeled averaged net shoreline changes are smaller (&lt;0.1&nbsp;m/yr). The model indicates accretion in some shallow embayments, whereas observations indicate erosion in these locations. Further analysis identifies that the magnitude of net alongshore sediment transport is strongly dominated by events associated with high wave energy. However, both big- and small- wave events cause shoreline change of the same order of magnitude because it is the gradients in transport, not the magnitude, that are controlling shoreline change. Results also indicate that alongshore momentum is not a simple balance between wave breaking and bottom stress, but also includes processes of horizontal vortex force, horizontal advection and pressure gradient that contribute to long-term alongshore sediment transport. As a comparison to a more simple approach, an empirical formulation for alongshore sediment transport is used. The empirical estimates capture the effect of the breaking term in the hydrodynamics-based model, however, other processes that are accounted for in the hydrodynamics-based model improve the agreement with the observed alongshore sediment transport.</span></p>","language":"English","publisher":"Elsevier","publisherLocation":"New York, NY","doi":"10.1016/j.coastaleng.2016.11.014","usgsCitation":"Safak, I., List, J.H., Warner, J., and Kumar, N., 2017, Observations and 3D hydrodynamics-based modeling of decadal-scale shoreline change along the Outer Banks, North Carolina: Coastal Engineering, v. 120, p. 78-92, https://doi.org/10.1016/j.coastaleng.2016.11.014.","productDescription":"15 p.","startPage":"78","endPage":"92","ipdsId":"IP-071238","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":469939,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://hdl.handle.net/1912/8747","text":"External Repository"},{"id":339382,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Carolina","otherGeospatial":"Outer Banks","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -76.3,\n              35.13\n            ],\n            [\n              -75.07,\n              35.13\n            ],\n            [\n              -75.07,\n              36.45\n            ],\n            [\n              -76.3,\n              36.45\n            ],\n            [\n              -76.3,\n              35.13\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"120","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58e8a540e4b09da6799d639d","contributors":{"authors":[{"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":690245,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"List, Jeffrey H. 0000-0001-8594-2491 jlist@usgs.gov","orcid":"https://orcid.org/0000-0001-8594-2491","contributorId":174581,"corporation":false,"usgs":true,"family":"List","given":"Jeffrey","email":"jlist@usgs.gov","middleInitial":"H.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":690247,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Warner, John C. 0000-0002-3734-8903 jcwarner@usgs.gov","orcid":"https://orcid.org/0000-0002-3734-8903","contributorId":2681,"corporation":false,"usgs":true,"family":"Warner","given":"John C.","email":"jcwarner@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":690246,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kumar, Nirnimesh","contributorId":190663,"corporation":false,"usgs":false,"family":"Kumar","given":"Nirnimesh","email":"","affiliations":[],"preferred":false,"id":690248,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70186596,"text":"70186596 - 2017 - Counterintuitive roles of experience and weather on migratory performance","interactions":[],"lastModifiedDate":"2017-11-22T16:59:20","indexId":"70186596","displayToPublicDate":"2017-04-06T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3544,"text":"The Auk","onlineIssn":"1938-4254","printIssn":"0004-8038","active":true,"publicationSubtype":{"id":10}},"title":"Counterintuitive roles of experience and weather on migratory performance","docAbstract":"<p><span>Migration allows animals to live in resource-rich but seasonally variable environments. Because of the costs of migration, there is selective pressure to capitalize on variation in weather to optimize migratory performance. To test the degree to which migratory performance (defined as speed of migration) of Golden Eagles (</span><i><i>Aquila chrysaetos</i></i><span>) was determined by age- and season-specific responses to variation in weather, we analyzed 1,863 daily tracks (</span><i>n</i><span> = 83 migrant eagles) and 8,047 hourly tracks (</span><i>n</i><span> = 83) based on 15 min GPS telemetry data from Golden Eagles and 277 hourly tracks based on 30 s data (</span><i>n</i><span> = 37). Spring migrant eagles traveled 139.75 ± 82.19 km day</span><sup>−1</sup><span> (mean ± SE; </span><i>n</i><span> = 57) and 25.59 ± 11.75 km hr</span><sup>−1</sup><span> (</span><i>n</i><span> = 55). Autumn migrant eagles traveled 99.14 ± 59.98 km day</span><sup>−1</sup><span> (</span><i>n</i><span> = 26) and 22.18 ± 9.18 km hr</span><sup>−1</sup><span> (</span><i>n</i><span> = 28). Weather during migration varied by season and by age class. During spring, best-supported daily and hourly models of 15 min data suggested that migratory performance was influenced most strongly by downward solar radiation and that older birds benefited less from flow assistance (tailwinds). During autumn, best-supported daily and hourly models of 15 min data suggested that migratory performance was influenced most strongly by south–north winds and by flow assistance, again less strongly for older birds. In contrast, models for hourly performance based on data collected at 30 s intervals were not well described by a single model, likely reflecting eagles' rapid responses to the many weather conditions they experienced. Although daily speed of travel was similar for all age classes, younger birds traveled at faster hourly speeds than did adults. Our analyses uncovered strong, sometimes counterintuitive, relationships among weather, experience, and migratory flight, and they illustrate the significance of factors other than age in determining migratory performance.</span></p>","language":"English","publisher":"American Ornithological Society","doi":"10.1642/AUK-16-147.1","usgsCitation":"Rus, A.I., Duerr, A.E., Miller, T., Belthoff, J.R., and Katzner, T., 2017, Counterintuitive roles of experience and weather on migratory performance: The Auk, v. 134, no. 3, p. 485-497, https://doi.org/10.1642/AUK-16-147.1.","productDescription":"13 p.","startPage":"485","endPage":"497","ipdsId":"IP-079692","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":469942,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1642/auk-16-147.1","text":"Publisher Index Page"},{"id":339306,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"134","issue":"3","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58e753ebe4b09da6799c0c4b","contributors":{"authors":[{"text":"Rus, Adrian I.","contributorId":190589,"corporation":false,"usgs":false,"family":"Rus","given":"Adrian","email":"","middleInitial":"I.","affiliations":[],"preferred":false,"id":689689,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Duerr, Adam E.","contributorId":102324,"corporation":false,"usgs":true,"family":"Duerr","given":"Adam","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":689690,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Miller, Tricia A.","contributorId":64790,"corporation":false,"usgs":true,"family":"Miller","given":"Tricia A.","affiliations":[],"preferred":false,"id":689691,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Belthoff, James R. 0000-0002-6051-2353","orcid":"https://orcid.org/0000-0002-6051-2353","contributorId":190592,"corporation":false,"usgs":false,"family":"Belthoff","given":"James","email":"","middleInitial":"R.","affiliations":[{"id":16201,"text":"Boise State University","active":true,"usgs":false}],"preferred":false,"id":689692,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Katzner, Todd E. 0000-0003-4503-8435 tkatzner@usgs.gov","orcid":"https://orcid.org/0000-0003-4503-8435","contributorId":5979,"corporation":false,"usgs":true,"family":"Katzner","given":"Todd E.","email":"tkatzner@usgs.gov","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":false,"id":689688,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70186576,"text":"70186576 - 2017 - Observations and a linear model of water level in an interconnected inlet-bay system","interactions":[],"lastModifiedDate":"2017-06-01T10:36:49","indexId":"70186576","displayToPublicDate":"2017-04-05T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2315,"text":"Journal of Geophysical Research C: Oceans","active":true,"publicationSubtype":{"id":10}},"title":"Observations and a linear model of water level in an interconnected inlet-bay system","docAbstract":"<p><span>A system of barrier islands and back-barrier bays occurs along southern Long Island, New York, and in many coastal areas worldwide. Characterizing the bay physical response to water level fluctuations is needed to understand flooding during extreme events and evaluate their relation to geomorphological changes. Offshore sea level is one of the main drivers of water level fluctuations in semienclosed back-barrier bays. We analyzed observed water levels (October 2007 to November 2015) and developed analytical models to better understand bay water level along southern Long Island. An increase (∼0.02 m change in 0.17 m amplitude) in the dominant M</span><sub>2</sub><span> tidal amplitude (containing the largest fraction of the variability) was observed in Great South Bay during mid-2014. The observed changes in both tidal amplitude and bay water level transfer from offshore were related to the dredging of nearby inlets and possibly the changing size of a breach across Fire Island caused by Hurricane Sandy (after December 2012). The bay response was independent of the magnitude of the fluctuations (e.g., storms) at a specific frequency. An analytical model that incorporates bay and inlet dimensions reproduced the observed transfer function in Great South Bay and surrounding areas. The model predicts the transfer function in Moriches and Shinnecock bays where long-term observations were not available. The model is a simplified tool to investigate changes in bay water level and enables the evaluation of future conditions and alternative geomorphological settings.</span></p>","language":"English","publisher":"AGU","doi":"10.1002/2016JC012318","usgsCitation":"Aretxabaleta, A., Ganju, N.K., Butman, B., and Signell, R.P., 2017, Observations and a linear model of water level in an interconnected inlet-bay system: Journal of Geophysical Research C: Oceans, v. 122, no. 4, p. 2760-2780, https://doi.org/10.1002/2016JC012318.","productDescription":"21 p.","startPage":"2760","endPage":"2780","ipdsId":"IP-079414","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":469944,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2016jc012318","text":"Publisher Index Page"},{"id":339265,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"122","issue":"4","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationDate":"2017-04-04","publicationStatus":"PW","scienceBaseUri":"58e6026de4b09da6799ac673","chorus":{"doi":"10.1002/2016jc012318","url":"http://dx.doi.org/10.1002/2016jc012318","publisher":"Wiley-Blackwell","authors":"Aretxabaleta Alfredo L., Ganju Neil K., Butman Bradford, Signell Richard P.","journalName":"Journal of Geophysical Research: Oceans","publicationDate":"4/4/2017","publiclyAccessibleDate":"4/4/2017"},"contributors":{"authors":[{"text":"Aretxabaleta, Alfredo 0000-0002-9914-8018 aaretxabaleta@usgs.gov","orcid":"https://orcid.org/0000-0002-9914-8018","contributorId":140090,"corporation":false,"usgs":true,"family":"Aretxabaleta","given":"Alfredo","email":"aaretxabaleta@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":689633,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ganju, Neil K. 0000-0002-1096-0465 nganju@usgs.gov","orcid":"https://orcid.org/0000-0002-1096-0465","contributorId":174763,"corporation":false,"usgs":true,"family":"Ganju","given":"Neil","email":"nganju@usgs.gov","middleInitial":"K.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":689634,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Butman, Bradford 0000-0002-4174-2073 bbutman@usgs.gov","orcid":"https://orcid.org/0000-0002-4174-2073","contributorId":943,"corporation":false,"usgs":true,"family":"Butman","given":"Bradford","email":"bbutman@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":689635,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Signell, Richard P. 0000-0003-0682-9613 rsignell@usgs.gov","orcid":"https://orcid.org/0000-0003-0682-9613","contributorId":140906,"corporation":false,"usgs":true,"family":"Signell","given":"Richard","email":"rsignell@usgs.gov","middleInitial":"P.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":689636,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70186577,"text":"70186577 - 2017 - Seismic displacement of gently-sloping coastal and marine sediment under multidirectional earthquake loading","interactions":[],"lastModifiedDate":"2017-09-18T15:44:26","indexId":"70186577","displayToPublicDate":"2017-04-05T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1517,"text":"Engineering Geology","active":true,"publicationSubtype":{"id":10}},"title":"Seismic displacement of gently-sloping coastal and marine sediment under multidirectional earthquake loading","docAbstract":"<p><span>Gentle sediment-laden slopes are typical of the onshore coastal zone and offshore continental shelf and slope. Coastal sediment are commonly young weakly consolidated materials that are well stratified, have low strength, and can mobilize shear displacements at low levels of stress. Seismically-driven plastic displacements of these sediment pose a hazard to coastal cities, buried onshore utilities, and offshore infrastructure like harbor protection and outfalls. One-dimensional rigid downslope-directed Newmark sliding block analyses have been used to predict earthquake deformations generally on steeper slopes that are modeled as frictional materials. This study probes the effect of multidirectional earthquake motions on inertial displacements of gently sloping ground of the coastal and offshore condition where soft-compliant soil is expected. Toward that objective, this investigation seeks to understand the effect on Newmark-type displacements of [1] multidirectional earthquake shaking and [2] soil compliance. In order to model multidirectional effects, the earthquake motions are rotated into the local slope strike- and dip-components. On gently sloping ground, including the strike component of motion always results in a larger and more accurate shear stress vector. Strike motions are found to contribute to downslope deformations on any declivity. Compliant response of the soil mass also influences the plastic displacements. The magnitude of seismic displacements can be estimated with a simplified model using only the estimated soil yield-acceleration (</span><i>k</i><sub><i>y</i></sub><span>) and the peak ground velocity (</span><i>V</i><sub><i>max</i></sub><span>) of the earthquake motions. Compliance effects can be effectively mapped using the concept of Plastic Displacement Response Spectra (PDRS).</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.enggeo.2016.12.009","usgsCitation":"Kayen, R.E., 2017, Seismic displacement of gently-sloping coastal and marine sediment under multidirectional earthquake loading: Engineering Geology, v. 227, p. 84-92, https://doi.org/10.1016/j.enggeo.2016.12.009.","productDescription":"9 p.","startPage":"84","endPage":"92","ipdsId":"IP-081076","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":469943,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.enggeo.2016.12.009","text":"Publisher Index Page"},{"id":339263,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"227","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58e6026ce4b09da6799ac671","chorus":{"doi":"10.1016/j.enggeo.2016.12.009","url":"http://dx.doi.org/10.1016/j.enggeo.2016.12.009","publisher":"Elsevier BV","authors":"Kayen Robert","journalName":"Engineering Geology","publicationDate":"12/2016"},"contributors":{"authors":[{"text":"Kayen, Robert E. 0000-0002-0356-072X rkayen@usgs.gov","orcid":"https://orcid.org/0000-0002-0356-072X","contributorId":140764,"corporation":false,"usgs":true,"family":"Kayen","given":"Robert","email":"rkayen@usgs.gov","middleInitial":"E.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":689637,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70186519,"text":"70186519 - 2017 - Acute sensitivity of the vernal pool fairy shrimp, <i>Branchinecta lynchi</i> (Anostraca; Branchinectidae), and surrogate species to 10 chemicals","interactions":[],"lastModifiedDate":"2017-04-05T08:54:31","indexId":"70186519","displayToPublicDate":"2017-04-05T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1571,"text":"Environmental Toxicology and Chemistry","active":true,"publicationSubtype":{"id":10}},"title":"Acute sensitivity of the vernal pool fairy shrimp, <i>Branchinecta lynchi</i> (Anostraca; Branchinectidae), and surrogate species to 10 chemicals","docAbstract":"<p><span>Vernal pool fairy shrimp, </span><i>Branchinecta lynchi</i><span>, (Branchiopoda; Anostraca) and other fairy shrimp species have been listed as threatened or endangered under the US Endangered Species Act. Because few data exist about the sensitivity of </span><i>Branchinecta</i><span> spp. to toxic effects of contaminants, it is difficult to determine whether they are adequately protected by water quality criteria. A series of acute (24-h) lethality/immobilization tests was conducted with 3 species of fairy shrimp (</span><i>B. lynchi, Branchinecta lindahli</i><span>, and </span><i>Thamnocephalus platyurus</i><span>) and 10 chemicals with varying modes of toxic action: ammonia, potassium, chloride, sulfate, chromium(VI), copper, nickel, zinc, alachlor, and metolachlor. The same chemicals were tested in 48-h tests with other branchiopods (the cladocerans </span><i>Daphnia magna</i><span> and </span><i>Ceriodaphnia dubia</i><span>) and an amphipod (</span><i>Hyalella azteca</i><span>), and in 96-h tests with snails (</span><i>Physa gyrina</i><span> and </span><i>Lymnaea stagnalis</i><span>). Median effect concentrations (EC50s) for </span><i>B. lynchi</i><span> were strongly correlated (</span><i>r</i><sup>2 </sup><span>= 0.975) with EC50s for the commercially available fairy shrimp species </span><i>T. platyurus</i><span> for most chemicals tested. Comparison of EC50s for fairy shrimp and EC50s for invertebrate taxa tested concurrently and with other published toxicity data indicated that fairy shrimp were relatively sensitive to potassium and several trace metals compared with other invertebrate taxa, although cladocerans, amphipods, and mussels had similar broad toxicant sensitivity. Interspecies correlation estimation models for predicting toxicity to fairy shrimp from surrogate species indicated that models with cladocerans and freshwater mussels as surrogates produced the best predictions of the sensitivity of fairy shrimp to contaminants. The results of these studies indicate that fairy shrimp are relatively sensitive to a range of toxicants, but Endangered Species Act-listed fairy shrimp of the genus </span><i>Branchinecta</i><span> were not consistently more sensitive than other fairy shrimp taxa. </span><i>Environ Toxicol Chem</i><span> 2017;36:797–806. Published 2016 Wiley Periodicals Inc. on behalf of SETAC. This article is a US government work and, as such, is in the public domain in the United States of America.</span></p>","language":"English","publisher":"Wiley","doi":"10.1002/etc.3723","usgsCitation":"Ivey, C.D., Besser, J.M., Ingersoll, C.G., Wang, N., Rogers, D.C., Raimondo, S., Bauer, C.R., and Hammer, E.J., 2017, Acute sensitivity of the vernal pool fairy shrimp, <i>Branchinecta lynchi</i> (Anostraca; Branchinectidae), and surrogate species to 10 chemicals: Environmental Toxicology and Chemistry, v. 36, no. 3, p. 797-806, https://doi.org/10.1002/etc.3723.","productDescription":"10 p.","startPage":"797","endPage":"806","ipdsId":"IP-079384","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":438382,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F74J0C72","text":"USGS data release","linkHelpText":"Acute sensitivity of the vernal pool fairy shrimp, Branchinecta lynchi (Anostraca; Branchinectidae), and surrogate species to ten chemicals-Data"},{"id":339183,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"36","issue":"3","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2016-12-26","publicationStatus":"PW","scienceBaseUri":"58e6026ee4b09da6799ac679","contributors":{"authors":[{"text":"Ivey, Chris D. 0000-0002-0485-7242 civey@usgs.gov","orcid":"https://orcid.org/0000-0002-0485-7242","contributorId":3308,"corporation":false,"usgs":true,"family":"Ivey","given":"Chris","email":"civey@usgs.gov","middleInitial":"D.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":688563,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Besser, John M. 0000-0002-9464-2244 jbesser@usgs.gov","orcid":"https://orcid.org/0000-0002-9464-2244","contributorId":2073,"corporation":false,"usgs":true,"family":"Besser","given":"John","email":"jbesser@usgs.gov","middleInitial":"M.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":688564,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ingersoll, Christopher G. 0000-0003-4531-5949 cingersoll@usgs.gov","orcid":"https://orcid.org/0000-0003-4531-5949","contributorId":2071,"corporation":false,"usgs":true,"family":"Ingersoll","given":"Christopher","email":"cingersoll@usgs.gov","middleInitial":"G.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":688565,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wang, Ning 0000-0002-2846-3352 nwang@usgs.gov","orcid":"https://orcid.org/0000-0002-2846-3352","contributorId":2818,"corporation":false,"usgs":true,"family":"Wang","given":"Ning","email":"nwang@usgs.gov","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":688566,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rogers, D. Christopher","contributorId":190496,"corporation":false,"usgs":false,"family":"Rogers","given":"D.","email":"","middleInitial":"Christopher","affiliations":[],"preferred":false,"id":688567,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Raimondo, Sandy","contributorId":150748,"corporation":false,"usgs":false,"family":"Raimondo","given":"Sandy","email":"","affiliations":[{"id":18090,"text":"U.S. Environmental Protection Agency, Gulf Ecology Division, Gulf Breeze, FL","active":true,"usgs":false}],"preferred":false,"id":688568,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bauer, Candice R.","contributorId":150724,"corporation":false,"usgs":false,"family":"Bauer","given":"Candice","email":"","middleInitial":"R.","affiliations":[{"id":18077,"text":"U. S. Environmental Protection Agency, Region 5, Water Quality Branch, Chicago, Illinois","active":true,"usgs":false}],"preferred":false,"id":688569,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Hammer, Edward J.","contributorId":150723,"corporation":false,"usgs":false,"family":"Hammer","given":"Edward","email":"","middleInitial":"J.","affiliations":[{"id":18077,"text":"U. S. Environmental Protection Agency, Region 5, Water Quality Branch, Chicago, Illinois","active":true,"usgs":false}],"preferred":false,"id":688570,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70186552,"text":"70186552 - 2017 - Legacy introductions and climatic variation explain spatiotemporal patterns of invasive hybridization in a native trout","interactions":[],"lastModifiedDate":"2017-10-08T11:34:53","indexId":"70186552","displayToPublicDate":"2017-04-05T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1837,"text":"Global Change Biology","active":true,"publicationSubtype":{"id":10}},"title":"Legacy introductions and climatic variation explain spatiotemporal patterns of invasive hybridization in a native trout","docAbstract":"<p>Hybridization between invasive and native species, a significant threat to worldwide biodiversity, is predicted to increase due to climate-induced expansions of invasive species. Long-term research and monitoring are crucial for understanding the ecological and evolutionary processes that modulate the effects of invasive species. Using a large, multi-decade genetics dataset (N = 582 sites, 12,878 individuals) with high-resolution climate predictions and extensive stocking records, we evaluate the spatiotemporal dynamics of hybridization between native cutthroat trout and invasive rainbow trout, the world’s most widely introduced invasive fish, across the northern Rocky Mountains of the United States. Historical effects of stocking and contemporary patterns of climatic variation were strongly related to the spread of hybridization across space and time. The probability of occurrence, extent of, and temporal changes in hybridization increased at sites in close proximity to historical stocking locations with greater rainbow trout propagule pressure, warmer water temperatures, and lower spring precipitation. Although locations with warmer water temperatures were more prone to hybridization, cold sites were not protected from invasion; 58% of hybridized sites had cold mean summer water temperatures (&lt;11<span class=\"st\">°</span>C). Despite cessation of stocking over 40 years ago, hybridization increased over time at half (50%) of the locations with long-term data, the vast majority of which (74%) were initially non-hybridized, emphasizing the chronic, negative impacts of human-mediated hybridization. These results show that effects of climate change on biodiversity must be analyzed in the context of historical human impacts that set ecological and evolutionary trajectories.</p>","language":"English","publisher":"Wiley","doi":"10.1111/gcb.13681","usgsCitation":"Muhlfeld, C.C., Kovach, R.P., Al-Chokhachy, R.K., Amish, S.J., Kershner, J.L., Leary, R., Lowe, W.H., Luikart, G., Matson, P., Schmetterling, D.A., Shepard, B.B., Westley, P.A., Whited, D., Whiteley, A.R., and Allendorf, F.W., 2017, Legacy introductions and climatic variation explain spatiotemporal patterns of invasive hybridization in a native trout: Global Change Biology, v. 23, no. 11, p. 4663-4674, https://doi.org/10.1111/gcb.13681.","productDescription":"12 p.","startPage":"4663","endPage":"4674","ipdsId":"IP-078684","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":469946,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/gcb.13681","text":"Publisher Index Page"},{"id":339275,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","volume":"23","issue":"11","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2017-04-04","publicationStatus":"PW","scienceBaseUri":"58e6026de4b09da6799ac677","contributors":{"authors":[{"text":"Muhlfeld, Clint C. 0000-0002-4599-4059 cmuhlfeld@usgs.gov","orcid":"https://orcid.org/0000-0002-4599-4059","contributorId":924,"corporation":false,"usgs":true,"family":"Muhlfeld","given":"Clint","email":"cmuhlfeld@usgs.gov","middleInitial":"C.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":688708,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kovach, Ryan P. rkovach@usgs.gov","contributorId":5772,"corporation":false,"usgs":true,"family":"Kovach","given":"Ryan","email":"rkovach@usgs.gov","middleInitial":"P.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":false,"id":688709,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Al-Chokhachy, Robert K. 0000-0002-2136-5098 ral-chokhachy@usgs.gov","orcid":"https://orcid.org/0000-0002-2136-5098","contributorId":1674,"corporation":false,"usgs":true,"family":"Al-Chokhachy","given":"Robert","email":"ral-chokhachy@usgs.gov","middleInitial":"K.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":688710,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Amish, Stephen J.","contributorId":104799,"corporation":false,"usgs":false,"family":"Amish","given":"Stephen","email":"","middleInitial":"J.","affiliations":[{"id":5097,"text":"University of Montana, Division of Biological Sciences","active":true,"usgs":false}],"preferred":false,"id":688711,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kershner, Jeffrey L. 0000-0002-7093-9860 jkershner@usgs.gov","orcid":"https://orcid.org/0000-0002-7093-9860","contributorId":310,"corporation":false,"usgs":true,"family":"Kershner","given":"Jeffrey","email":"jkershner@usgs.gov","middleInitial":"L.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":688712,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Leary, Robb F.","contributorId":126726,"corporation":false,"usgs":false,"family":"Leary","given":"Robb F.","affiliations":[{"id":6582,"text":"Montana Fish, Wildlife and Parks, Missoula, Montana 59801, USA","active":true,"usgs":false}],"preferred":false,"id":688713,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Lowe, Winsor H.","contributorId":126722,"corporation":false,"usgs":false,"family":"Lowe","given":"Winsor","email":"","middleInitial":"H.","affiliations":[{"id":6577,"text":"University of Montana, Division of Biological Sciences, Missoula, MT, 59812, USA.","active":true,"usgs":false}],"preferred":false,"id":688721,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Luikart, Gordon","contributorId":97409,"corporation":false,"usgs":false,"family":"Luikart","given":"Gordon","affiliations":[{"id":6580,"text":"University of Montana, Flathead Lake Biological Station, Polson, Montana 59860, USA","active":true,"usgs":false}],"preferred":false,"id":688714,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Matson, Phil","contributorId":190529,"corporation":false,"usgs":false,"family":"Matson","given":"Phil","email":"","affiliations":[],"preferred":false,"id":688715,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Schmetterling, David A.","contributorId":20223,"corporation":false,"usgs":true,"family":"Schmetterling","given":"David","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":689675,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Shepard, Bradley B.","contributorId":145880,"corporation":false,"usgs":false,"family":"Shepard","given":"Bradley","email":"","middleInitial":"B.","affiliations":[{"id":6765,"text":"Montana State University, Department of Land Resources and Environmental Sciences","active":true,"usgs":false}],"preferred":false,"id":688716,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Westley, Peter A. H.","contributorId":190530,"corporation":false,"usgs":false,"family":"Westley","given":"Peter","email":"","middleInitial":"A. H.","affiliations":[],"preferred":false,"id":688717,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Whited, Diane","contributorId":126718,"corporation":false,"usgs":false,"family":"Whited","given":"Diane","affiliations":[{"id":6576,"text":"Flathead Lake Biological Station, University of Montana, Polson, MT 59860, USA","active":true,"usgs":false}],"preferred":false,"id":688718,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Whiteley, Andrew R.","contributorId":150155,"corporation":false,"usgs":false,"family":"Whiteley","given":"Andrew","email":"","middleInitial":"R.","affiliations":[{"id":6932,"text":"University of Massachusetts, Amherst","active":true,"usgs":false}],"preferred":false,"id":688719,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Allendorf, Fred W.","contributorId":124525,"corporation":false,"usgs":false,"family":"Allendorf","given":"Fred","email":"","middleInitial":"W.","affiliations":[{"id":5084,"text":"Division of Biological Sciences, University of Montana, Missoula, MT","active":true,"usgs":false}],"preferred":false,"id":688720,"contributorType":{"id":1,"text":"Authors"},"rank":15}]}}
,{"id":70186586,"text":"70186586 - 2017 - Quantifying habitat benefits of channel reconfigurations on a highly regulated river system, Lower Missouri River, USA","interactions":[],"lastModifiedDate":"2017-04-05T15:45:36","indexId":"70186586","displayToPublicDate":"2017-04-05T00:00:00","publicationYear":"2017","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":"Quantifying habitat benefits of channel reconfigurations on a highly regulated river system, Lower Missouri River, USA","docAbstract":"<p><span>We present a quantitative analysis of habitat availability in a highly regulated lowland river, comparing a restored reach with two reference reaches: an un-restored, channelized reach, and a least-altered reach. We evaluate the effects of channel modifications in terms of distributions of depth and velocity as well as distributions and availability of habitats thought to be supportive of an endangered fish, the pallid sturgeon (</span><i>Scaphirhynchus albus</i><span>). It has been hypothesized that hydraulic conditions that support food production and foraging may limit growth and survival of juvenile pallid sturgeon. To evaluate conditions that support these habitats, we constructed two-dimensional hydrodynamic models for the three study reaches, two located in the Lower Missouri River (channelized and restored reaches) and one in the Yellowstone River (least-altered reach). Comparability among the reaches was improved by scaling by bankfull discharge and bankfull channel area. The analysis shows that construction of side-channel chutes and increased floodplain connectivity increase the availability of foraging habitat, resulting in a system that is more similar to the reference reach on the Yellowstone River. The availability of food-producing habitat is low in all reaches at flows less than bankfull, but the two reaches in the Lower Missouri River – channelized and restored – display a threshold-like response as flows overtop channel banks, reflecting the persistent effects of channelization on hydraulics in the main channel. These high lateral gradients result in punctuated ecological events corresponding to flows in excess of bankfull discharge. This threshold effect in the restored reach remains distinct from that of the least-altered reference reach, where hydraulic changes are less abrupt and overbank flows more gradually inundate the adjacent floodplain. The habitat curves observed in the reference reach on the Yellowstone River may not be attainable within the channelized system on the Missouri River, but the documented hydraulic patterns can be used to inform ongoing channel modifications. Although scaling to bankfull dimensions and discharges provides a basis for comparing the three reaches, implementation of the reference reach concept was complicated by differences in flow-frequency distributions among sites. In particular, habitat availability in the least-altered Yellowstone River reach is affected by increased frequency of low-flow events (less than 0.5 times bankfull flow) and moderately high-flow events (greater than 1.5 times bankfull flow) compared to downstream reaches on the Lower Missouri River.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecoleng.2017.03.004","usgsCitation":"Erwin, S.O., Jacobson, R.B., and Elliott, C.M., 2017, Quantifying habitat benefits of channel reconfigurations on a highly regulated river system, Lower Missouri River, USA: Ecological Engineering, v. 103, no. Part A, p. 59-75, https://doi.org/10.1016/j.ecoleng.2017.03.004.","productDescription":"17 p.","startPage":"59","endPage":"75","ipdsId":"IP-083466","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":461643,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecoleng.2017.03.004","text":"Publisher Index Page"},{"id":438384,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7TB154R","text":"USGS data release","linkHelpText":"Quantifying habitat benefits of channel reconfigurations on a highly regulated river system, Lower Missouri River, USA-Data"},{"id":339261,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Lower Missouri River","volume":"103","issue":"Part A","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58e6026be4b09da6799ac66d","contributors":{"authors":[{"text":"Erwin, Susannah O. 0000-0002-2799-0118 serwin@usgs.gov","orcid":"https://orcid.org/0000-0002-2799-0118","contributorId":5183,"corporation":false,"usgs":true,"family":"Erwin","given":"Susannah","email":"serwin@usgs.gov","middleInitial":"O.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":689657,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jacobson, Robert B. 0000-0002-8368-2064 rjacobson@usgs.gov","orcid":"https://orcid.org/0000-0002-8368-2064","contributorId":1289,"corporation":false,"usgs":true,"family":"Jacobson","given":"Robert","email":"rjacobson@usgs.gov","middleInitial":"B.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":689658,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Elliott, Caroline M. 0000-0002-9190-7462 celliott@usgs.gov","orcid":"https://orcid.org/0000-0002-9190-7462","contributorId":2380,"corporation":false,"usgs":true,"family":"Elliott","given":"Caroline","email":"celliott@usgs.gov","middleInitial":"M.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":689659,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70186557,"text":"70186557 - 2017 - Occurrence of neonicotinoid insecticides in finished drinking water and fate during drinking water treatment","interactions":[],"lastModifiedDate":"2017-05-10T14:12:59","indexId":"70186557","displayToPublicDate":"2017-04-05T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5022,"text":"Environmental Science & Technology Letters","onlineIssn":"2328-8930","active":true,"publicationSubtype":{"id":10}},"title":"Occurrence of neonicotinoid insecticides in finished drinking water and fate during drinking water treatment","docAbstract":"Neonicotinoid insecticides are widespread in surface waters across the agriculturally-intensive Midwestern US. We report for the first time the presence of three neonicotinoids in finished drinking water and demonstrate their general persistence during conventional water treatment. Periodic tap water grab samples were collected at the University of Iowa over seven weeks in 2016 (May-July) after maize/soy planting. Clothianidin, imidacloprid, and thiamethoxam were ubiquitously detected in finished water samples and ranged from 0.24-57.3 ng/L. Samples collected along the University of Iowa treatment train indicate no apparent removal of clothianidin and imidacloprid, with modest thiamethoxam removal (~50%). In contrast, the concentrations of all neonicotinoids were substantially lower in the Iowa City treatment facility finished water using granular activated carbon (GAC) filtration. Batch experiments investigated potential losses. Thiamethoxam losses are due to base-catalyzed hydrolysis at high pH conditions during lime softening.  GAC rapidly and nearly completely removed all three neonicotinoids. Clothianidin is susceptible to reaction with free chlorine and may undergo at least partial transformation during chlorination. Our work provides new insights into the persistence of neonicotinoids and their potential for transformation during water treatment and distribution, while also identifying GAC as an effective management tool to lower neonicotinoid concentrations in finished drinking water.","language":"English","publisher":"ACS Publications","doi":"10.1021/acs.estlett.7b00081","usgsCitation":"Klarich, K.L., Pflug, N.C., DeWald, E.M., Hladik, M., Kolpin, D.W., Cwiertny, D.M., and LeFevre, G.H., 2017, Occurrence of neonicotinoid insecticides in finished drinking water and fate during drinking water treatment: Environmental Science & Technology Letters, v. 4, no. 5, https://doi.org/10.1021/acs.estlett.7b00081.","productDescription":"6 p.","startPage":"173","ipdsId":"IP-082188","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":469945,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1021/acs.estlett.7b00081","text":"Publisher Index Page"},{"id":339270,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"4","issue":"5","edition":"168","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2017-04-05","publicationStatus":"PW","scienceBaseUri":"58e6026de4b09da6799ac675","chorus":{"doi":"10.1021/acs.estlett.7b00081","url":"http://dx.doi.org/10.1021/acs.estlett.7b00081","publisher":"American Chemical Society (ACS)","authors":"Klarich Kathryn L., Pflug Nicholas C., DeWald Eden M., Hladik Michelle L., Kolpin Dana W., Cwiertny David M., LeFevre Gregory H.","journalName":"Environmental Science & Technology Letters","publicationDate":"4/5/2017","auditedOn":"4/8/2017","publiclyAccessibleDate":"4/5/2017"},"contributors":{"authors":[{"text":"Klarich, Kathryn L.","contributorId":190554,"corporation":false,"usgs":false,"family":"Klarich","given":"Kathryn","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":689564,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pflug, Nicholas C.","contributorId":190555,"corporation":false,"usgs":false,"family":"Pflug","given":"Nicholas","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":689565,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"DeWald, Eden M.","contributorId":190556,"corporation":false,"usgs":false,"family":"DeWald","given":"Eden","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":689566,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hladik, Michelle L. 0000-0002-0891-2712 mhladik@usgs.gov","orcid":"https://orcid.org/0000-0002-0891-2712","contributorId":189904,"corporation":false,"usgs":true,"family":"Hladik","given":"Michelle L.","email":"mhladik@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":false,"id":689563,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kolpin, Dana W. 0000-0002-3529-6505 dwkolpin@usgs.gov","orcid":"https://orcid.org/0000-0002-3529-6505","contributorId":1239,"corporation":false,"usgs":true,"family":"Kolpin","given":"Dana","email":"dwkolpin@usgs.gov","middleInitial":"W.","affiliations":[{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true}],"preferred":true,"id":689569,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Cwiertny, David M.","contributorId":190557,"corporation":false,"usgs":false,"family":"Cwiertny","given":"David","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":689567,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"LeFevre, Gergory H.","contributorId":190558,"corporation":false,"usgs":false,"family":"LeFevre","given":"Gergory","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":689568,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70186373,"text":"70186373 - 2017 - Coastal river plumes: Collisions and coalescence","interactions":[],"lastModifiedDate":"2017-04-04T15:00:29","indexId":"70186373","displayToPublicDate":"2017-04-04T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3194,"text":"Progress in Oceanography","active":true,"publicationSubtype":{"id":10}},"title":"Coastal river plumes: Collisions and coalescence","docAbstract":"<div class=\"abstract svAbstract \" data-etype=\"ab\"><p id=\"sp0010\">Plumes of buoyant river water spread in the ocean from river mouths, and these plumes influence water quality, sediment dispersal, primary productivity, and circulation along the world’s coasts. Most investigations of river plumes have focused on large rivers in a coastal region, for which the physical spreading of the plume is assumed to be independent from the influence of other buoyant plumes. Here we provide new understanding of the spreading patterns of multiple plumes interacting along simplified coastal settings by investigating: (i) the relative likelihood of plume-to-plume interactions at different settings using geophysical scaling, (ii) the diversity of plume frontal collision types and the effects of these collisions on spreading patterns of plume waters using a two-dimensional hydrodynamic model, and (iii) the fundamental differences in plume spreading patterns between coasts with single and multiple rivers using a three-dimensional hydrodynamic model. Geophysical scaling suggests that coastal margins with numerous small rivers (watershed areas&nbsp;&lt;&nbsp;10,000&nbsp;km<sup>2</sup>), such as found along most active geologic coastal margins, were much more likely to have river plumes that collide and interact than coastal settings with large rivers (watershed areas&nbsp;&gt;&nbsp;100,000&nbsp;km<sup>2</sup>). When two plume fronts meet, several types of collision attributes were found, including refection, subduction and occlusion. We found that the relative differences in pre-collision plume densities and thicknesses strongly influenced the resulting collision types. The three-dimensional spreading of buoyant plumes was found to be influenced by the presence of additional rivers for all modeled scenarios, including those with and without Coriolis and wind. Combined, these results suggest that plume-to-plume interactions are common phenomena for coastal regions offshore of the world’s smaller rivers and for coastal settings with multiple river mouths in close proximity, and that the spreading and fate of river waters in these settings will be strongly influenced by these interactions. We conclude that new investigations are needed to characterize how plumes interact offshore of river mouths to better understand the transport and fate of terrestrial sources of pollution, nutrients and other materials in the ocean.</p></div>","language":"English","publisher":"Elsevier","doi":"10.1016/j.pocean.2016.11.008","usgsCitation":"Warrick, J.A., and Farnsworth, K.L., 2017, Coastal river plumes: Collisions and coalescence: Progress in Oceanography, v. 151, p. 245-260, https://doi.org/10.1016/j.pocean.2016.11.008.","productDescription":"16 p.","startPage":"245","endPage":"260","ipdsId":"IP-073483","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":339136,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"151","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58e4b0b0e4b09da67999776c","contributors":{"authors":[{"text":"Warrick, Jonathan A. 0000-0002-0205-3814 jwarrick@usgs.gov","orcid":"https://orcid.org/0000-0002-0205-3814","contributorId":167736,"corporation":false,"usgs":true,"family":"Warrick","given":"Jonathan","email":"jwarrick@usgs.gov","middleInitial":"A.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":688387,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Farnsworth, Katherine L 0000-0003-2304-0761","orcid":"https://orcid.org/0000-0003-2304-0761","contributorId":190414,"corporation":false,"usgs":false,"family":"Farnsworth","given":"Katherine","email":"","middleInitial":"L","affiliations":[],"preferred":false,"id":688388,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70186366,"text":"70186366 - 2017 - Fungal and bacterial contributions to nitrogen cycling in cheatgrass-invaded and uninvaded native sagebrush soils of the western USA","interactions":[],"lastModifiedDate":"2017-11-22T17:01:54","indexId":"70186366","displayToPublicDate":"2017-04-04T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3089,"text":"Plant and Soil","active":true,"publicationSubtype":{"id":10}},"title":"Fungal and bacterial contributions to nitrogen cycling in cheatgrass-invaded and uninvaded native sagebrush soils of the western USA","docAbstract":"<div id=\"ASec1\" class=\"AbstractSection\"><p class=\"Heading\"><strong>Aim</strong></p><p id=\"Par1\" class=\"Para\">There is interest in determining how cheatgrass (<i class=\"EmphasisTypeItalic \">Bromus tectorum</i> L.) modifies N cycling in sagebrush (<i class=\"EmphasisTypeItalic \">Artemisia tridentata</i> Nutt.) soils of the western USA.</p></div><div id=\"ASec2\" class=\"AbstractSection\"><p class=\"Heading\"><strong>Methods</strong></p><p id=\"Par2\" class=\"Para\">To gain insight into the roles of fungi and bacteria in N cycling of cheatgrass-invaded and uninvaded sagebrush soils, the fungal protein synthesis inhibitor, cycloheximide (CHX), and the bacteriocidal compound, bronopol (BRO) were combined with a <sup>15</sup>NH<sub>4</sub><sup>+</sup> isotope pool dilution approach.</p></div><div id=\"ASec3\" class=\"AbstractSection\"><p class=\"Heading\"><strong>Results</strong></p><p id=\"Par3\" class=\"Para\">CHX reduced gross N mineralization to the same rate in both sagebrush and cheatgrass soils indicating a role for fungi in N mineralization in both soil types. In cheatgrass soils BRO completely inhibited gross N mineralization, whereas, in sagebrush soils a BRO-resistant gross N mineralization rate was detected that was slower than CHX sensitive gross N mineralization, suggesting that the microbial drivers of gross N mineralization were different in sagebrush and cheatgrass soils. Net N mineralization was stimulated to a higher rate in sagebrush than in cheatgrass soils by CHX, implying that a CHX inhibited N sink was larger in the former than the latter soils. Initial gross NH<sub>4</sub><sup>+</sup> consumption rates were reduced significantly by both CHX and BRO in both soil types, yet, consumption rates recovered significantly between 24 and 48&nbsp;h in CHX-treated sagebrush soils. The recovery of NH<sub>4</sub><sup>+</sup> consumption in sagebrush soils corresponded with an increase in the rate of net nitrification.</p></div><div id=\"ASec4\" class=\"AbstractSection\"><p class=\"Heading\"><strong>Conclusions</strong></p><p id=\"Par4\" class=\"Para\">These results suggest that cheatgrass invasion of sagebrush soils of the northern Great Basin reduces the capacity of the fungal N consumption sink, enhances the capacity of a CHX resistant N sink and alters the contributions of bacteria and fungi to gross N mineralization.</p></div>","language":"English","publisher":"Springer","doi":"10.1007/s11104-017-3209-x","usgsCitation":"DeCrappeo, N., DeLorenze, E.J., Giguere, A.T., Pyke, D.A., and Bottomley, P.J., 2017, Fungal and bacterial contributions to nitrogen cycling in cheatgrass-invaded and uninvaded native sagebrush soils of the western USA: Plant and Soil, v. 416, no. 1-2, p. 271-281, https://doi.org/10.1007/s11104-017-3209-x.","productDescription":"11 p.","startPage":"271","endPage":"281","ipdsId":"IP-079522","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":339140,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","volume":"416","issue":"1-2","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2017-02-27","publicationStatus":"PW","scienceBaseUri":"58e4b0b0e4b09da67999776e","chorus":{"doi":"10.1007/s11104-017-3209-x","url":"http://dx.doi.org/10.1007/s11104-017-3209-x","publisher":"Springer Nature","authors":"DeCrappeo Nicole M., DeLorenze Elizabeth J., Giguere Andrew T., Pyke David A., Bottomley Peter J.","journalName":"Plant and Soil","publicationDate":"2/27/2017","auditedOn":"3/3/2017","publiclyAccessibleDate":"2/27/2017"},"contributors":{"authors":[{"text":"DeCrappeo, Nicole 0000-0002-6928-8853 ndecrappeo@usgs.gov","orcid":"https://orcid.org/0000-0002-6928-8853","contributorId":1939,"corporation":false,"usgs":true,"family":"DeCrappeo","given":"Nicole","email":"ndecrappeo@usgs.gov","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":true,"id":688376,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"DeLorenze, Elizabeth J.","contributorId":190409,"corporation":false,"usgs":false,"family":"DeLorenze","given":"Elizabeth","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":688377,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Giguere, Andrew T","contributorId":190410,"corporation":false,"usgs":false,"family":"Giguere","given":"Andrew","email":"","middleInitial":"T","affiliations":[],"preferred":false,"id":688378,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pyke, David A. 0000-0002-4578-8335 david_a_pyke@usgs.gov","orcid":"https://orcid.org/0000-0002-4578-8335","contributorId":3118,"corporation":false,"usgs":true,"family":"Pyke","given":"David","email":"david_a_pyke@usgs.gov","middleInitial":"A.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":true,"id":688379,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bottomley, Peter J.","contributorId":190411,"corporation":false,"usgs":false,"family":"Bottomley","given":"Peter","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":688380,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70182252,"text":"sir20175006 - 2017 - Water-quality trends in the nation’s rivers and streams, 1972–2012—Data preparation, statistical methods, and trend results","interactions":[],"lastModifiedDate":"2017-11-06T09:53:10","indexId":"sir20175006","displayToPublicDate":"2017-04-04T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2017-5006","title":"Water-quality trends in the nation’s rivers and streams, 1972–2012—Data preparation, statistical methods, and trend results","docAbstract":"<p>Since passage of the Clean Water Act in 1972, Federal, State, and local governments have invested billions of dollars to reduce pollution entering rivers and streams. To understand the return on these investments and to effectively manage and protect the Nation’s water resources in the future, we need to know how and why water quality has been changing over time. As part of the National Water-Quality Assessment Project, of the U.S. Geological Survey’s National Water-Quality Program, data from the U.S. Geological Survey, along with multiple other Federal, State, Tribal, regional, and local agencies, have been used to support the most comprehensive assessment conducted to date of surface-water-quality trends in the United States. This report documents the methods used to determine trends in water quality and ecology because these methods are vital to ensuring the quality of the results. Specific objectives are to document (1) the data compilation and processing steps used to identify river and stream sites throughout the Nation suitable for water-quality, pesticide, and ecology trend analysis, (2) the statistical methods used to determine trends in target parameters, (3) considerations for water-quality, pesticide, and ecology data and streamflow data when modeling trends, (4) sensitivity analyses for selecting data and interpreting trend results with the Weighted Regressions on Time, Discharge, and Season method, and (5) the final trend results at each site. The scope of this study includes trends in water-quality concentrations and loads (nutrient, sediment, major ion, salinity, and carbon), pesticide concentrations and loads, and metrics for aquatic ecology (fish, invertebrates, and algae) for four time periods: (1) 1972–2012, (2) 1982–2012, (3) 1992–2012, and (4) 2002–12. In total, nearly 12,000 trends in concentration, load, and ecology metrics were evaluated in this study; there were 11,893 combinations of sites, parameters, and trend periods. The final trend results are presented with examples of how to interpret the results from each trend model. Interpretation of the trend results, such as causal analysis, is not included.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175006","usgsCitation":"Oelsner, G.P., Sprague, L.A., Murphy, J.C., Zuellig, R.E., Johnson, H.M., Ryberg, K.R., Falcone, J.A., Stets, E.G., Vec-chia, A.V., Riskin, M.L., De Cicco, L.A., Mills, T.J., and Farmer, W.H., 2017, Water-quality trends in the Nation’s rivers and streams, 1972–2012—Data preparation, statistical methods, and trend results (ver. 2.0, October 2017): U.S. Geological Survey Scientific Investigations Report 2017–5006, 136 p., https://doi.org/10.3133/sir20175006.","productDescription":"Report: xv, 136 p.; 8 Appendixes; 5 Data Releases; Project Site; Version History","numberOfPages":"158","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-079324","costCenters":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"links":[{"id":438398,"rank":19,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7TQ5ZS3","text":"USGS data release","linkHelpText":"Water-quality trends and trend component estimates for the Nation's rivers and streams using Weighted Regressions on Time, Discharge, and Season (WRTDS) models and generalized flow normalization, 1972-2012"},{"id":438397,"rank":19,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7D798JN","text":"USGS data release","linkHelpText":"Daily streamflow datasets used to analyze trends in streamflow at sites also analyzed for trends in water quality and ecological condition in the Nation's rivers and streams"},{"id":438396,"rank":19,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7BC3WPC","text":"USGS data release","linkHelpText":"Pesticide concentration and streamflow datasets used to evaluate pesticide trends in the Nations rivers and streams, 1992-2012"},{"id":438395,"rank":19,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7KW5D4H","text":"USGS data release","linkHelpText":"Water-quality and streamflow datasets used in the Weighted Regressions on Time, Discharge, and Season (WRTDS) models to determine trends in the Nations rivers and streams, 1972-2012"},{"id":438394,"rank":19,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7QN64VT","text":"USGS data release","linkHelpText":"Water-quality and streamflow datasets used in Seasonal Kendall trend tests for the Nations rivers and streams, 1972-2012"},{"id":438393,"rank":19,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7G44ND3","text":"USGS data release","linkHelpText":"Ecological community datasets used to evaluate the presence of trends in ecological communities in selected rivers and streams across the United States, 1992-2012"},{"id":348031,"rank":7,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2017/5006/sir20175006_appendix6_ver2.0.pdf","text":"Appendix 6 - ","size":"398 kB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017–5006 Appendix 6","linkHelpText":"Analysis of trends in annual streamflow"},{"id":338789,"rank":6,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2017/5006/sir20175006_appendix5.pdf","text":"Appendix 5 -","size":"6.01 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017–5006 Appendix 5","linkHelpText":"Laboratory performance bias evaluation using percent recovery in U.S. Geological Survey Branch of Quality Systems double-blind reference samples over time"},{"id":348032,"rank":18,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sir/2017/5006/versionHist.txt","text":"Version History","size":"7 kB","linkFileType":{"id":2,"text":"txt"}},{"id":338787,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2017/5006/sir20175006_appendix3.pdf","text":"Appendix 3 -","size":"246 kB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017–5006 Appendix 3","linkHelpText":"Laboratory method and change timeline"},{"id":338788,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2017/5006/sir20175006_appendix4.pdf","text":"Appendix 4 -","size":"5.84 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017–5006 Appendix 4","linkHelpText":"Step-trend analysis of changes in laboratory analysis and sample collection methods"},{"id":338791,"rank":8,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2017/5006/sir20175006_appendix7.xlsx","text":"Appendix 7 - Table 7–1 to Table 7–5","size":"599 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2017–5006 Appendix 7"},{"id":338792,"rank":9,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2017/5006/sir20175006_appendix8.pdf","text":"Appendix 8 -","size":"183 kB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017–5006 Appendix 8","linkHelpText":"Comparison of trends determined using the Seasonal Kendall test and the Weighted Regressions on Time, Discharge, and Season (WRTDS) model"},{"id":338794,"rank":11,"type":{"id":30,"text":"Data Release"},"url":"https://dx.doi.org/10.5066/F7BC3WPC","text":"USGS Data Release","description":"USGS Data Release","linkHelpText":"Pesticide concentration and streamflow datasets used to evaluate pesticide trends in the Nation’s rivers and streams, 1992-2012"},{"id":338793,"rank":10,"type":{"id":30,"text":"Data Release"},"url":"https://dx.doi.org/10.5066/F7KW5D4H","text":"USGS Data Release","description":"USGS Data Release","linkHelpText":"Water-quality and streamflow datasets used in the Weighted Regressions on Time, Discharge, and Season (WRTDS) models to determine trends in the Nation’s rivers and streams, 1972-2012"},{"id":338783,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5006/coverthb2.jpg"},{"id":338785,"rank":2,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2017/5006/sir20175006_appendix1.xlsx","text":"Appendix 1 - Table 1–1 to Table 1–7","size":"976 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2017–5006 Appendix 1"},{"id":338786,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2017/5006/sir20175006_appendix2.xlsx","text":"Appendix 2 - Table 2–1 to Table 2–4","size":"36.9 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2017–5006 Appendix 2"},{"id":338795,"rank":12,"type":{"id":30,"text":"Data Release"},"url":"https://dx.doi.org/10.5066/F7G44ND3","text":"USGS Data Release","description":"USGS Data Release","linkHelpText":"Ecological community datasets used to evaluate the presence of trends in 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States\"}}]}","edition":"Version 1.0: Originally posted April 4, 2017; Version 2.0: November 1, 2017","contact":"<p>Program Coordinator, National Water Quality Program<br>U.S. Geological Survey<br>413 National Center<br>12201 Sunrise Valley Drive<br>Reston, Virginia 20192</p><p><a href=\"https://water.usgs.gov/nawqa/\" data-mce-href=\"https://water.usgs.gov/nawqa/\">https://water.usgs.gov/nawqa/</a></p>","tableOfContents":"<ul><li>Foreword<br></li><li>Abstract<br></li><li>Introduction<br></li><li>Objectives and Scope<br></li><li>Methods</li><li>Trend Results<br></li><li>Summary<br></li><li>Acknowledgements<br></li><li>References<br></li><li>Appendix 1.&nbsp;Streamflow, Water–Quality, and Ecology Sites Included in Trend Analysis<br></li><li>Appendix 2.&nbsp;Variations in Parameter Reporting for Selected Parameters<br></li><li>Appendix 3. Laboratory Method and Change Timeline<br></li><li>Appendix&nbsp;4. Step-Trend Analysis of Changes in Laboratory Analysis and Sample Collection Methods<br></li><li>Appendix&nbsp;5. Laboratory Performance Bias Evaluation Using Percent Recovery in U.S. Geological Survey Branch of Quality Systems Double-Blind Reference Samples over Time<br></li><li>Appendix&nbsp;6. Analysis of Trends in Annual Streamflow<br></li><li>Appendix&nbsp;7. Trend Results<br></li><li>Appendix&nbsp;8. Comparison of Trends Determined Using the Seasonal Kendall Test and the Weighted Regressions on Time, Discharge, and Season Model<br></li></ul>","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"publishedDate":"2017-04-04","revisedDate":"2017-11-01","noUsgsAuthors":false,"publicationDate":"2017-04-04","publicationStatus":"PW","scienceBaseUri":"58e4b0b1e4b09da679997778","contributors":{"authors":[{"text":"Oelsner, Gretchen P. 0000-0001-9329-7357 goelsner@usgs.gov","orcid":"https://orcid.org/0000-0001-9329-7357","contributorId":4440,"corporation":false,"usgs":true,"family":"Oelsner","given":"Gretchen","email":"goelsner@usgs.gov","middleInitial":"P.","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"preferred":true,"id":670229,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sprague, Lori A. 0000-0003-2832-6662 lsprague@usgs.gov","orcid":"https://orcid.org/0000-0003-2832-6662","contributorId":726,"corporation":false,"usgs":true,"family":"Sprague","given":"Lori","email":"lsprague@usgs.gov","middleInitial":"A.","affiliations":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":37277,"text":"WMA - 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,{"id":70186276,"text":"70186276 - 2017 - Density-dependent vulnerability of forest ecosystems to drought","interactions":[],"lastModifiedDate":"2017-11-29T16:41:20","indexId":"70186276","displayToPublicDate":"2017-04-03T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2163,"text":"Journal of Applied Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Density-dependent vulnerability of forest ecosystems to drought","docAbstract":"<p>1. Climate models predict increasing drought intensity and frequency for many regions, which may have negative consequences for tree recruitment, growth and mortality, as well as forest ecosystem services. Furthermore, practical strategies for minimizing vulnerability to drought are limited. Tree population density, a metric of tree abundance in a given area, is a primary driver of competitive intensity among trees, which influences tree growth and mortality. Manipulating tree population density may be a mechanism for moderating drought-induced stress and growth reductions, although the relationship between tree population density and tree drought vulnerability remains poorly quantified, especially across climatic gradients.</p><p>2. In this study, we examined three long-term forest ecosystem experiments in two widely distributed North American pine species, ponderosa pine Pinus ponderosa (Lawson &amp; C. Lawson) and red pine Pinus resinosa (Aiton), to better elucidate the relationship between tree population density, growth and drought. These experiments span a broad latitude and aridity range and include tree population density treatments that have been purposefully maintained for several decades. We investigated how tree population density influenced resistance (growth during drought) and resilience (growth after drought compared to pre-drought growth) of stand-level growth during and after documented drought events.</p><p>3. Our results show that relative tree population density was negatively related to drought resistance and resilience, indicating that trees growing at lower densities were less vulnerable to drought. This result was apparent in all three forest ecosystems, and was consistent across species, stand age and drought intensity.</p><p>4. <i>Synthesis and applications</i>. Our results highlighted that managing pine forest ecosystems at low tree population density represents a promising adaptive strategy for reducing the adverse impacts of drought on forest growth in coming decades. Nonetheless, the broader applicability of our findings to other types of forest ecosystems merits additional investigation.</p>","language":"English","publisher":"Wiley","doi":"10.1111/1365-2664.12847","usgsCitation":"Bottero, A., D’Amato, A.W., Palik, B.J., Bradford, J.B., Fraver, S., Battaglia, M.A., and Asherin, L.A., 2017, Density-dependent vulnerability of forest ecosystems to drought: Journal of Applied Ecology, v. 54, no. 6, p. 1605-1614, https://doi.org/10.1111/1365-2664.12847.","productDescription":"10 p.","startPage":"1605","endPage":"1614","ipdsId":"IP-081481","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":469953,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/1365-2664.12847","text":"Publisher Index Page"},{"id":339078,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"North America","volume":"54","issue":"6","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2017-01-24","publicationStatus":"PW","scienceBaseUri":"58e35f7de4b09da67997eca1","contributors":{"authors":[{"text":"Bottero, Alessandra 0000-0002-0410-2675","orcid":"https://orcid.org/0000-0002-0410-2675","contributorId":190300,"corporation":false,"usgs":false,"family":"Bottero","given":"Alessandra","email":"","affiliations":[],"preferred":false,"id":688108,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"D’Amato, Anthony W.","contributorId":28140,"corporation":false,"usgs":false,"family":"D’Amato","given":"Anthony","email":"","middleInitial":"W.","affiliations":[{"id":13478,"text":"Department of Forest Resources, University of Minnesota, St. Paul, Minnesota (Correspondence to: russellm@umn.edu)","active":true,"usgs":false},{"id":6735,"text":"University of Vermont, Rubenstein School of Environment and Natural Resources","active":true,"usgs":false}],"preferred":false,"id":688109,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Palik, Brian J.","contributorId":190301,"corporation":false,"usgs":false,"family":"Palik","given":"Brian","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":688110,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bradford, John B. 0000-0001-9257-6303 jbradford@usgs.gov","orcid":"https://orcid.org/0000-0001-9257-6303","contributorId":611,"corporation":false,"usgs":true,"family":"Bradford","given":"John","email":"jbradford@usgs.gov","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":688107,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fraver, Shawn","contributorId":91379,"corporation":false,"usgs":false,"family":"Fraver","given":"Shawn","email":"","affiliations":[{"id":7063,"text":"University of Maine","active":true,"usgs":false}],"preferred":false,"id":688111,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Battaglia, Mike A.","contributorId":190302,"corporation":false,"usgs":false,"family":"Battaglia","given":"Mike","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":688112,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Asherin, Lance A.","contributorId":190303,"corporation":false,"usgs":false,"family":"Asherin","given":"Lance","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":688113,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70199835,"text":"70199835 - 2017 - An integrated population model for bird monitoring in North America","interactions":[],"lastModifiedDate":"2018-10-01T14:34:33","indexId":"70199835","displayToPublicDate":"2017-04-01T14:34:23","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1450,"text":"Ecological Applications","active":true,"publicationSubtype":{"id":10}},"title":"An integrated population model for bird monitoring in North America","docAbstract":"<p><span>Integrated population models (IPMs) provide a unified framework for simultaneously analyzing data sets of different types to estimate vital rates, population size, and dynamics; assess contributions of demographic parameters to population changes; and assess population viability. Strengths of an IPM include the ability to estimate latent parameters and improve the precision of parameter estimates. We present a hierarchical IPM that combines two broad‐scale avian monitoring data sets: count data from the North American Breeding Bird Survey (BBS) and capture–recapture data from the Monitoring Avian Productivity and Survivorship (MAPS) program. These data sets are characterized by large numbers of sample sites and observers, factors capable of inducing error in the sampling and observation processes. The IPM integrates the data sets by modeling the population abundance as a first‐order autoregressive function of the previous year's population abundance and vital rates. BBS counts were modeled as a log‐linear function of the annual index of population abundance, observation effects (observer identity and first survey year), and overdispersion. Vital rates modeled included adult apparent survival, estimated from a transient Cormack‐Jolly‐Seber model using MAPS data, and recruitment (surviving hatched birds from the previous season&nbsp;+&nbsp;dispersing adults) estimated as a latent parameter. An assessment of the IPM demonstrated it could recover true parameter values from 200 simulated data sets. The IPM was applied to data sets (1992–2008) of two bird species, Gray Catbird (</span><i>Dumetella carolinensis</i><span>) and Wood Thrush (</span><i>Hylocichla mustelina</i><span>) in the New England/Mid‐Atlantic coastal Bird Conservation Region of the United States. The Gray Catbird population was relatively stable (trend +0.4% per yr), while the Wood Thrush population nearly halved (trend −4.5% per yr) over the 17‐yr study period. IPM estimates of population growth rates, adult survival, and detection and residency probabilities were similar and as precise as estimates from the stand‐alone BBS and CJS models. A benefit of using the IPM was its ability to estimate the latent recruitment parameter. Annual growth rates for both species correlated more with recruitment than survival, and the relationship for Wood Thrush was stronger than for Gray Catbird. The IPM's unified modeling framework facilitates integration of these important data sets.</span></p>","language":"English","publisher":"Ecological Society of America","doi":"10.1002/eap.1493","usgsCitation":"Ahrestani, F.S., Saracco, J.F., Sauer, J.R., Pardieck, K.L., and Royle, J.A., 2017, An integrated population model for bird monitoring in North America: Ecological Applications, v. 27, no. 3, p. 916-924, https://doi.org/10.1002/eap.1493.","productDescription":"9 p.","startPage":"916","endPage":"924","ipdsId":"IP-080990","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":357969,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"27","issue":"3","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2017-03-21","publicationStatus":"PW","scienceBaseUri":"5bc031aae4b0fc368eb53a40","contributors":{"authors":[{"text":"Ahrestani, Farshid S.","contributorId":208349,"corporation":false,"usgs":false,"family":"Ahrestani","given":"Farshid","email":"","middleInitial":"S.","affiliations":[{"id":37785,"text":"The Institute of Bird Populations","active":true,"usgs":false}],"preferred":false,"id":746840,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Saracco, James F.","contributorId":208350,"corporation":false,"usgs":false,"family":"Saracco","given":"James","email":"","middleInitial":"F.","affiliations":[{"id":37785,"text":"The Institute of Bird Populations","active":true,"usgs":false}],"preferred":false,"id":746841,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sauer, John R. 0000-0002-4557-3019 jrsauer@usgs.gov","orcid":"https://orcid.org/0000-0002-4557-3019","contributorId":146917,"corporation":false,"usgs":true,"family":"Sauer","given":"John","email":"jrsauer@usgs.gov","middleInitial":"R.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":746839,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pardieck, Keith L. 0000-0003-2779-4392 kpardieck@usgs.gov","orcid":"https://orcid.org/0000-0003-2779-4392","contributorId":4104,"corporation":false,"usgs":true,"family":"Pardieck","given":"Keith","email":"kpardieck@usgs.gov","middleInitial":"L.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":746842,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Royle, J. Andrew 0000-0003-3135-2167 aroyle@usgs.gov","orcid":"https://orcid.org/0000-0003-3135-2167","contributorId":139626,"corporation":false,"usgs":true,"family":"Royle","given":"J.","email":"aroyle@usgs.gov","middleInitial":"Andrew","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":746843,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70182811,"text":"70182811 - 2017 - Inner-shelf ocean dynamics and seafloor morphologic changes during Hurricane Sandy","interactions":[],"lastModifiedDate":"2018-07-23T12:49:07","indexId":"70182811","displayToPublicDate":"2017-04-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1333,"text":"Continental Shelf Research","active":true,"publicationSubtype":{"id":10}},"title":"Inner-shelf ocean dynamics and seafloor morphologic changes during Hurricane Sandy","docAbstract":"Hurricane Sandy was one of the most destructive hurricanes in US history, making landfall on the New Jersey coast on Oct 30, 2012. Storm impacts included several barrier island breaches, massive coastal erosion, and flooding. While changes to the subaerial landscape are relatively easily observed, storm-induced changes to the adjacent shoreface and inner continental shelf are more difficult to evaluate. These regions provide a framework for the coastal zone, are important for navigation, aggregate resources, marine ecosystems, and coastal evolution. Here we provide unprecedented perspective regarding regional inner continental shelf sediment dynamics based on both observations and numerical modeling over time scales associated with these types of large storm events. Oceanographic conditions and seafloor morphologic changes are evaluated using both a coupled atmospheric-ocean-wave-sediment numerical modeling system and observation analysis from a series of geologic surveys and oceanographic instrument deployments focused on a region offshore of Fire Island, NY. The geologic investigations conducted in 2011 and 2014 revealed lateral movement of sedimentary structures of distances up to 450 m and in water depths up to 30 m, and vertical changes in sediment thickness greater than 1 m in some locations. The modeling investigations utilize a system with grid refinement designed to simulate oceanographic conditions with progressively increasing resolutions for the entire US East Coast (5-km grid), the New York Bight (700-m grid), and offshore of Fire Island, NY (100-m grid), allowing larger scale dynamics to drive smaller scale coastal changes. Model results in the New York Bight identify maximum storm surge of up to 3 m, surface currents on the order of 2 ms-1 along the New Jersey coast, waves up to 8 m in height, and bottom stresses exceeding 10 Pa. Flow down the Hudson Shelf Valley is shown to result in convergent sediment transport and deposition along its axis. Modeled sediment redistribution along Fire Island showed erosion across the crests of inner shelf sand ridges and sedimentation in adjacent troughs, consistent with the geologic observations.","language":"English","publisher":"Elsevier ","doi":"10.1016/j.csr.2017.02.003","usgsCitation":"Warner, J., Schwab, W.C., List, J.H., Safak, I., Liste, M., and Baldwin, W.E., 2017, Inner-shelf ocean dynamics and seafloor morphologic changes during Hurricane Sandy: Continental Shelf Research, v. 138, p. 1-18, https://doi.org/10.1016/j.csr.2017.02.003.","productDescription":"18 p.","startPage":"1","endPage":"18","ipdsId":"IP-072875","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true},{"id":37273,"text":"Advanced Research Computing (ARC)","active":true,"usgs":true}],"links":[{"id":469976,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.csr.2017.02.003","text":"Publisher Index Page"},{"id":336758,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"138","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58e60271e4b09da6799ac67f","chorus":{"doi":"10.1016/j.csr.2017.02.003","url":"http://dx.doi.org/10.1016/j.csr.2017.02.003","publisher":"Elsevier BV","authors":"Warner John C., Schwab William C., List Jeffrey H., Safak Ilgar, Liste Maria, Baldwin Wayne","journalName":"Continental Shelf Research","publicationDate":"4/2017"},"contributors":{"authors":[{"text":"Warner, John C. 0000-0002-3734-8903 jcwarner@usgs.gov","orcid":"https://orcid.org/0000-0002-3734-8903","contributorId":2681,"corporation":false,"usgs":true,"family":"Warner","given":"John C.","email":"jcwarner@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":673847,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schwab, William C. 0000-0001-9274-5154 bschwab@usgs.gov","orcid":"https://orcid.org/0000-0001-9274-5154","contributorId":417,"corporation":false,"usgs":true,"family":"Schwab","given":"William","email":"bschwab@usgs.gov","middleInitial":"C.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":673848,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"List, Jeffrey H. 0000-0001-8594-2491 jlist@usgs.gov","orcid":"https://orcid.org/0000-0001-8594-2491","contributorId":174581,"corporation":false,"usgs":true,"family":"List","given":"Jeffrey","email":"jlist@usgs.gov","middleInitial":"H.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":673849,"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":673850,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Liste, Maria","contributorId":190581,"corporation":false,"usgs":false,"family":"Liste","given":"Maria","email":"","affiliations":[],"preferred":false,"id":673851,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Baldwin, Wayne E. 0000-0001-5886-0917 wbaldwin@usgs.gov","orcid":"https://orcid.org/0000-0001-5886-0917","contributorId":1321,"corporation":false,"usgs":true,"family":"Baldwin","given":"Wayne","email":"wbaldwin@usgs.gov","middleInitial":"E.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":673852,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70192500,"text":"70192500 - 2017 - Seasonal survival of adult female mottled ducks","interactions":[],"lastModifiedDate":"2017-10-26T14:34:00","indexId":"70192500","displayToPublicDate":"2017-04-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Seasonal survival of adult female mottled ducks","docAbstract":"<p><span>The mottled duck (</span><i>Anas fulgivula</i><span>) is a non-migratory duck dependent on coastal habitats to meet all of its life cycle requirements in the Western Gulf Coast (WGC) of Texas and Louisiana, USA. This population of mottled ducks has experienced a moderate decline during the past 2 decades. Adult survival has been identified as an important factor influencing population demography. Previous work based on band-recovery data has provided only annual estimates of survival. We assessed seasonal patterns of female mottled duck survival from 2009 to 2012 using individuals marked with satellite platform transmitter terminals (PTTs). We used temperature and movement sensors within each PTT to indicate potential mortality events. We estimated cumulative weekly survival and ranked factors influential in patterns of mortality using known-fate modeling in Program MARK. Models included 4 predictors: week; hunting and non-hunting periods; biological periods defined as breeding, brooding, molt, and pairing; and mass at time of capture. Models containing hunt periods, during and outside the mottled duck season, comprised essentially 100% of model weights where both legal and illegal harvest had a negative influence on mottled duck survival. Survival rates were low during 2009–2011 (12–38% annual rate of survival), when compared with the long-term banding average of 53% annual survival. During 2011, survival of female mottled ducks was the lowest annual rate (12%) ever documented and coincided with extreme drought. Management actions maximizing the availability of wetlands and associated upland habitats during hunting seasons and drought conditions may increase adult female mottled duck survival.</span></p>","language":"English","publisher":"The Wildlife Society","doi":"10.1002/jwmg.21221","usgsCitation":"Moon, J.A., Haukos, D.A., and Conway, W.C., 2017, Seasonal survival of adult female mottled ducks: Journal of Wildlife Management, v. 81, no. 3, p. 461-469, https://doi.org/10.1002/jwmg.21221.","productDescription":"9 p.","startPage":"461","endPage":"469","ipdsId":"IP-064529","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":461669,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/jwmg.21221","text":"Publisher Index Page"},{"id":347493,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Texas","otherGeospatial":"Chenier Plain Region","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -95.086669921875,\n              29.480252193344267\n            ],\n            [\n              -93.74359130859375,\n              29.480252193344267\n            ],\n            [\n              -93.74359130859375,\n              30.375244781665323\n            ],\n            [\n              -95.086669921875,\n              30.375244781665323\n            ],\n            [\n              -95.086669921875,\n              29.480252193344267\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"81","issue":"3","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationDate":"2017-03-09","publicationStatus":"PW","scienceBaseUri":"5a07e910e4b09af898c8cbf1","contributors":{"authors":[{"text":"Moon, Jena A.","contributorId":171483,"corporation":false,"usgs":false,"family":"Moon","given":"Jena","email":"","middleInitial":"A.","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":716433,"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":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":716081,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Conway, Warren C.","contributorId":51550,"corporation":false,"usgs":true,"family":"Conway","given":"Warren","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":716434,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70193667,"text":"70193667 - 2017 - Estimating occupancy probability of moose using hunter survey data","interactions":[],"lastModifiedDate":"2017-11-06T11:06:34","indexId":"70193667","displayToPublicDate":"2017-04-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Estimating occupancy probability of moose using hunter survey data","docAbstract":"<p><span>Monitoring rare species can be difficult, especially across large spatial extents, making conventional methods of population monitoring costly and logistically challenging. Citizen science has the potential to produce observational data across large areas that can be used to monitor wildlife distributions using occupancy models. We used citizen science (i.e., hunter surveys) to facilitate monitoring of moose (</span><i>Alces alces</i><span>) populations, an especially important endeavor because of their recent apparent declines in the northeastern and upper midwestern regions of the United States. To better understand patterns of occurrence of moose in New York, we used data collected through an annual survey of approximately 11,000 hunters between 2012 and 2014 that recorded detection–non-detection data of moose and other species. We estimated patterns of occurrence of moose in relation to land cover characteristics, climate effects, and interspecific interactions using occupancy models to analyze spatially referenced moose observations. Coniferous and deciduous forest with low prevalence of white-tailed deer (</span><i>Odocoileus virginianus</i><span>) had the highest probability of moose occurrence. This study highlights the potential of data collected using citizen science for understanding the spatial distribution of low-density species across large spatial extents and providing key information regarding where and when future research and management activities should be focused.</span></p>","language":"English","publisher":"Wiley","doi":"10.1002/jwmg.21207","usgsCitation":"Crum, N.J., Fuller, A.K., Sutherland, C.S., Cooch, E.G., and Hurst, J.E., 2017, Estimating occupancy probability of moose using hunter survey data: Journal of Wildlife Management, v. 81, no. 3, p. 521-534, https://doi.org/10.1002/jwmg.21207.","productDescription":"14 p.","startPage":"521","endPage":"534","ipdsId":"IP-074160","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":461649,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/jwmg.21207","text":"Publisher Index Page"},{"id":348253,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New York","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -76.365966796875,\n              42.0125705565935\n            ],\n            [\n              -73.267822265625,\n              42.0125705565935\n            ],\n            [\n              -73.267822265625,\n              45.00753503123719\n            ],\n            [\n              -76.365966796875,\n              45.00753503123719\n            ],\n            [\n              -76.365966796875,\n              42.0125705565935\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"81","issue":"3","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2017-03-28","publicationStatus":"PW","scienceBaseUri":"5a07e90fe4b09af898c8cbe9","contributors":{"authors":[{"text":"Crum, Nathan J.","contributorId":200016,"corporation":false,"usgs":false,"family":"Crum","given":"Nathan","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":720654,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fuller, Angela K. 0000-0002-9247-7468 afuller@usgs.gov","orcid":"https://orcid.org/0000-0002-9247-7468","contributorId":3984,"corporation":false,"usgs":true,"family":"Fuller","given":"Angela","email":"afuller@usgs.gov","middleInitial":"K.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":719841,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sutherland, Christopher S.","contributorId":139375,"corporation":false,"usgs":false,"family":"Sutherland","given":"Christopher","email":"","middleInitial":"S.","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":720655,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cooch, Evan G.","contributorId":100673,"corporation":false,"usgs":true,"family":"Cooch","given":"Evan","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":720656,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hurst, Jeremy E.","contributorId":177504,"corporation":false,"usgs":false,"family":"Hurst","given":"Jeremy","email":"","middleInitial":"E.","affiliations":[{"id":13678,"text":"New York State Department of Environmental Conservation","active":true,"usgs":false}],"preferred":false,"id":720657,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70187329,"text":"70187329 - 2017 - A software tool to assess uncertainty in transient-storage model parameters using Monte Carlo simulations","interactions":[],"lastModifiedDate":"2017-04-28T15:43:43","indexId":"70187329","displayToPublicDate":"2017-04-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1699,"text":"Freshwater Science","active":true,"publicationSubtype":{"id":10}},"title":"A software tool to assess uncertainty in transient-storage model parameters using Monte Carlo simulations","docAbstract":"<p><span>Researchers and practitioners alike often need to understand and characterize how water and solutes move through a stream in terms of the relative importance of in-stream and near-stream storage and transport processes. In-channel and subsurface storage processes are highly variable in space and time and difficult to measure. Storage estimates are commonly obtained using transient-storage models (TSMs) of the experimentally obtained solute-tracer test data. The TSM equations represent key transport and storage processes with a suite of numerical parameters. Parameter values are estimated via inverse modeling, in which parameter values are iteratively changed until model simulations closely match observed solute-tracer data. Several investigators have shown that TSM parameter estimates can be highly uncertain. When this is the case, parameter values cannot be used reliably to interpret stream-reach functioning. However, authors of most TSM studies do not evaluate or report parameter certainty. Here, we present a software tool linked to the One-dimensional Transport with Inflow and Storage (OTIS) model that enables researchers to conduct uncertainty analyses via Monte-Carlo parameter sampling and to visualize uncertainty and sensitivity results. We demonstrate application of our tool to 2 case studies and compare our results to output obtained from more traditional implementation of the OTIS model. We conclude by suggesting best practices for transient-storage modeling and recommend that future applications of TSMs include assessments of parameter certainty to support comparisons and more reliable interpretations of transport processes.</span></p>","language":"English","publisher":"University of Chicago Press","doi":"10.1086/690444","usgsCitation":"Ward, A.S., Kelleher, C.A., Mason, S.J., Wagener, T., McIntyre, N., McGlynn, B.L., Runkel, R.L., and Payn, R.A., 2017, A software tool to assess uncertainty in transient-storage model parameters using Monte Carlo simulations: Freshwater Science, v. 36, no. 1, p. 195-217, https://doi.org/10.1086/690444.","productDescription":"23 p.","startPage":"195","endPage":"217","ipdsId":"IP-074821","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":461661,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://research-information.bris.ac.uk/en/publications/2ec1a71e-046a-4faa-ad85-2f323af51119","text":"External Repository"},{"id":340632,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"36","issue":"1","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"590454a1e4b022cee40dc222","contributors":{"authors":[{"text":"Ward, Adam S.","contributorId":11508,"corporation":false,"usgs":true,"family":"Ward","given":"Adam","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":693393,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kelleher, Christa A.","contributorId":46417,"corporation":false,"usgs":true,"family":"Kelleher","given":"Christa","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":693394,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mason, Seth J. K.","contributorId":191535,"corporation":false,"usgs":false,"family":"Mason","given":"Seth","email":"","middleInitial":"J. K.","affiliations":[],"preferred":false,"id":693395,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wagener, Thorsten","contributorId":176323,"corporation":false,"usgs":false,"family":"Wagener","given":"Thorsten","email":"","affiliations":[],"preferred":false,"id":693396,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McIntyre, Neil","contributorId":191602,"corporation":false,"usgs":false,"family":"McIntyre","given":"Neil","email":"","affiliations":[],"preferred":false,"id":693397,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"McGlynn, Brian L.","contributorId":83012,"corporation":false,"usgs":true,"family":"McGlynn","given":"Brian","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":693398,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Runkel, Robert L. 0000-0003-3220-481X runkel@usgs.gov","orcid":"https://orcid.org/0000-0003-3220-481X","contributorId":685,"corporation":false,"usgs":true,"family":"Runkel","given":"Robert","email":"runkel@usgs.gov","middleInitial":"L.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":693392,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Payn, Robert A.","contributorId":36461,"corporation":false,"usgs":true,"family":"Payn","given":"Robert","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":693399,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70194067,"text":"70194067 - 2017 - Multiple models guide strategies for agricultural nutrient reductions","interactions":[],"lastModifiedDate":"2018-02-06T11:48:12","indexId":"70194067","displayToPublicDate":"2017-04-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1701,"text":"Frontiers in Ecology and the Environment","active":true,"publicationSubtype":{"id":10}},"title":"Multiple models guide strategies for agricultural nutrient reductions","docAbstract":"In response to degraded water quality, federal policy makers in the US and Canada called for a 40% reduction in phosphorus (P) loads to Lake Erie, and state and provincial policy makers in the Great Lakes region set a load-reduction target for the year 2025. Here, we configured five separate SWAT (US Department of Agriculture's Soil and Water Assessment Tool) models to assess load reduction strategies for the agriculturally dominated Maumee River watershed, the largest P source contributing to toxic algal blooms in Lake Erie. Although several potential pathways may achieve the target loads, our results show that any successful pathway will require large-scale implementation of multiple practices. For example, one successful pathway involved targeting 50% of row cropland that has the highest P loss in the watershed with a combination of three practices: subsurface application of P fertilizers, planting cereal rye as a winter cover crop, and installing buffer strips. Achieving these levels of implementation will require local, state/provincial, and federal agencies to collaborate with the private sector to set shared implementation goals and to demand innovation and honest assessments of water quality-related programs, policies, and partnerships.","language":"English","publisher":"Wiley","doi":"10.1002/fee.1472","usgsCitation":"Scavia, D., Kalcic, M., Muenich, R.L., Read, J., Aloysius, N., Bertani, I., Boles, C., Confesor, R., DePinto, J., Gildow, M., Martin, J., Redder, T., Robertson, D.M., Sowa, S.P., Wang, Y., and Yen, H., 2017, Multiple models guide strategies for agricultural nutrient reductions: Frontiers in Ecology and the Environment, v. 15, no. 3, p. 126-132, https://doi.org/10.1002/fee.1472.","productDescription":"7 p.","startPage":"126","endPage":"132","ipdsId":"IP-075287","costCenters":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"links":[{"id":461665,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1002/fee.1472","text":"External Repository"},{"id":348860,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"15","issue":"3","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2017-04-03","publicationStatus":"PW","scienceBaseUri":"5a60fbede4b06e28e9c2379e","contributors":{"authors":[{"text":"Scavia, Donald","contributorId":200340,"corporation":false,"usgs":false,"family":"Scavia","given":"Donald","email":"","affiliations":[{"id":33091,"text":"University of Michigan, Ann Arbor, Michigan","active":true,"usgs":false}],"preferred":false,"id":721980,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kalcic, Margaret","contributorId":169554,"corporation":false,"usgs":false,"family":"Kalcic","given":"Margaret","affiliations":[{"id":33091,"text":"University of Michigan, Ann Arbor, Michigan","active":true,"usgs":false},{"id":16172,"text":"Ohio State University, Columbus, OH","active":true,"usgs":false}],"preferred":false,"id":721981,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Muenich, Rebecca Logsdon","contributorId":169555,"corporation":false,"usgs":false,"family":"Muenich","given":"Rebecca","email":"","middleInitial":"Logsdon","affiliations":[{"id":33091,"text":"University of Michigan, Ann Arbor, Michigan","active":true,"usgs":false}],"preferred":false,"id":721982,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Read, Jennifer","contributorId":140055,"corporation":false,"usgs":false,"family":"Read","given":"Jennifer","email":"","affiliations":[{"id":33091,"text":"University of Michigan, Ann Arbor, Michigan","active":true,"usgs":false}],"preferred":false,"id":721983,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Aloysius, Noel","contributorId":169556,"corporation":false,"usgs":false,"family":"Aloysius","given":"Noel","affiliations":[{"id":16172,"text":"Ohio State University, Columbus, OH","active":true,"usgs":false}],"preferred":false,"id":721984,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bertani, Isabella","contributorId":194574,"corporation":false,"usgs":false,"family":"Bertani","given":"Isabella","email":"","affiliations":[{"id":33091,"text":"University of Michigan, Ann Arbor, Michigan","active":true,"usgs":false}],"preferred":false,"id":721985,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Boles, Chelsie","contributorId":169558,"corporation":false,"usgs":false,"family":"Boles","given":"Chelsie","email":"","affiliations":[{"id":28133,"text":"Limno Tech, Inc., Ann Arbor, Michigan","active":true,"usgs":false}],"preferred":false,"id":721986,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Confesor, Remegio","contributorId":169559,"corporation":false,"usgs":false,"family":"Confesor","given":"Remegio","email":"","affiliations":[{"id":16990,"text":"Heidelberg University","active":true,"usgs":false}],"preferred":false,"id":721987,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"DePinto, Joseph","contributorId":23861,"corporation":false,"usgs":true,"family":"DePinto","given":"Joseph","affiliations":[{"id":28133,"text":"Limno Tech, Inc., Ann Arbor, Michigan","active":true,"usgs":false}],"preferred":false,"id":721988,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Gildow, Marie","contributorId":169560,"corporation":false,"usgs":false,"family":"Gildow","given":"Marie","email":"","affiliations":[{"id":16172,"text":"Ohio State University, Columbus, OH","active":true,"usgs":false}],"preferred":false,"id":721989,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Martin, Jay","contributorId":169561,"corporation":false,"usgs":false,"family":"Martin","given":"Jay","affiliations":[{"id":16172,"text":"Ohio State University, Columbus, OH","active":true,"usgs":false}],"preferred":false,"id":721990,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Redder, Todd","contributorId":169562,"corporation":false,"usgs":false,"family":"Redder","given":"Todd","email":"","affiliations":[{"id":28133,"text":"Limno Tech, Inc., Ann Arbor, Michigan","active":true,"usgs":false}],"preferred":false,"id":721991,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Robertson, Dale M. 0000-0001-6799-0596 dzrobert@usgs.gov","orcid":"https://orcid.org/0000-0001-6799-0596","contributorId":150760,"corporation":false,"usgs":true,"family":"Robertson","given":"Dale","email":"dzrobert@usgs.gov","middleInitial":"M.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":721992,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Sowa, Scott P. 0000-0002-5425-2591 sowasp@missouri.edu","orcid":"https://orcid.org/0000-0002-5425-2591","contributorId":146672,"corporation":false,"usgs":false,"family":"Sowa","given":"Scott","email":"sowasp@missouri.edu","middleInitial":"P.","affiliations":[{"id":7041,"text":"The Nature Conservancy","active":true,"usgs":false}],"preferred":false,"id":721993,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Wang, Yu-Chen","contributorId":169563,"corporation":false,"usgs":false,"family":"Wang","given":"Yu-Chen","email":"","affiliations":[{"id":33091,"text":"University of Michigan, Ann Arbor, Michigan","active":true,"usgs":false}],"preferred":false,"id":721994,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Yen, Haw 0000-0002-5509-8792","orcid":"https://orcid.org/0000-0002-5509-8792","contributorId":169564,"corporation":false,"usgs":false,"family":"Yen","given":"Haw","email":"","affiliations":[{"id":6747,"text":"Texas A&M University","active":true,"usgs":false}],"preferred":false,"id":721996,"contributorType":{"id":1,"text":"Authors"},"rank":16}]}}
,{"id":70193045,"text":"70193045 - 2017 - Spatiotemporal ecology of Apalone spinifera in a large, Great Plains river ecosystem","interactions":[],"lastModifiedDate":"2017-11-06T16:31:52","indexId":"70193045","displayToPublicDate":"2017-04-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1894,"text":"Herpetological Conservation and Biology","onlineIssn":"2151-0733","printIssn":"1931-7603","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Spatiotemporal ecology of <i>Apalone spinifera</i> in a large, Great Plains river ecosystem","title":"Spatiotemporal ecology of Apalone spinifera in a large, Great Plains river ecosystem","docAbstract":"<p>Sparse information exists about the ecology of Spiny Softshell Turtles (Apalone spinifera) in large rivers, at the northwestern extent of their natural range, and in Montana, where they are disjunct from downstream populations and a State Species of Concern. We determined spatiotemporal ecology of 47 female and 12 male turtles from 2009 through 2012 and identified fundamental habitats in the Missouri River in east-central Montana. Movement rates of females were greater than those of males and peaked before nesting. Movement rates of males peaked before overwintering, and movement rates of both sexes were minimal in winter. Home range sizes were not different between sexes, varied among individuals and seasons, and were similar to those reported elsewhere in their northern range. Turtles aggregated and showed interannual fidelity to separate and disparate habitats in different seasons. Turtles often chose fine substrates, tributary confluences, and reaches with islands during summer and mainstem outside bends in the winter. They inhabited shallow, slow water velocity areas from May to September. They inhabited deeper, moderate velocity areas from October to April. We did not observe ice jams and associated riverbed scour at hibernacula, but did observe them elsewhere. Ice jams may be spatially predictable and influence the distribution of riverine turtles during autumn and winter. Preservation of dissimilar habitats used during major portions of the life cycle (lateral habitats, islands, and hibernacula) and natural streamflow patterns, which influenced timing of habitat availability and turtle movement, may facilitate continued existence of Spiny Softshell Turtles in the Missouri River in Montana</p>","language":"English","publisher":"Herpetological Conservation and Biology","usgsCitation":"Tornabene, B., Bramblett, R.G., Zale, A.V., and Leathe, S.A., 2017, Spatiotemporal ecology of Apalone spinifera in a large, Great Plains river ecosystem: Herpetological Conservation and Biology, v. 12, no. 1, p. 252-271.","productDescription":"20 p.","startPage":"252","endPage":"271","ipdsId":"IP-071425","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":348308,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":347693,"type":{"id":15,"text":"Index Page"},"url":"https://www.herpconbio.org/contents_vol12_issue1.html"}],"volume":"12","issue":"1","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a07e90fe4b09af898c8cbeb","contributors":{"authors":[{"text":"Tornabene, Brian J.","contributorId":200041,"corporation":false,"usgs":false,"family":"Tornabene","given":"Brian J.","affiliations":[],"preferred":false,"id":720774,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bramblett, Robert G.","contributorId":169857,"corporation":false,"usgs":false,"family":"Bramblett","given":"Robert","email":"","middleInitial":"G.","affiliations":[{"id":5098,"text":"Department of Ecology, Montana State University","active":true,"usgs":false}],"preferred":false,"id":720775,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Zale, Alexander V. 0000-0003-1703-885X zale@usgs.gov","orcid":"https://orcid.org/0000-0003-1703-885X","contributorId":3010,"corporation":false,"usgs":true,"family":"Zale","given":"Alexander","email":"zale@usgs.gov","middleInitial":"V.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":717743,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Leathe, Stephen A.","contributorId":200042,"corporation":false,"usgs":false,"family":"Leathe","given":"Stephen","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":720776,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70194465,"text":"70194465 - 2017 - Grand challenges in understanding the interplay of climate and land changes","interactions":[],"lastModifiedDate":"2017-11-28T16:30:53","indexId":"70194465","displayToPublicDate":"2017-04-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1421,"text":"Earth Interactions","active":true,"publicationSubtype":{"id":10}},"title":"Grand challenges in understanding the interplay of climate and land changes","docAbstract":"<p><span>Half of Earth’s land surface has been altered by human activities, creating various consequences on the climate and weather systems at local to global scales, which in turn affect a myriad of land surface processes and the adaptation behaviors. This study reviews the status and major knowledge gaps in the interactions of land and atmospheric changes and present 11 grand challenge areas for the scientific research and adaptation community in the coming decade. These land-cover and land-use change (LCLUC)-related areas include 1) impacts on weather and climate, 2) carbon and other biogeochemical cycles, 3) biospheric emissions, 4) the water cycle, 5) agriculture, 6) urbanization, 7) acclimation of biogeochemical processes to climate change, 8) plant migration, 9) land-use projections, 10) model and data uncertainties, and, finally, 11) adaptation strategies. Numerous studies have demonstrated the effects of LCLUC on local to global climate and weather systems, but these putative effects vary greatly in magnitude and even sign across space, time, and scale and thus remain highly uncertain. At the same time, many challenges exist toward improved understanding of the consequences of atmospheric and climate change on land process dynamics and services. Future effort must improve the understanding of the scale-dependent, multifaceted perturbations and feedbacks between land and climate changes in both reality and models. To this end, one critical cross-disciplinary need is to systematically quantify and better understand measurement and model uncertainties. Finally, LCLUC mitigation and adaptation assessments must be strengthened to identify implementation barriers, evaluate and prioritize opportunities, and examine how decision-making processes work in specific contexts.</span></p>","language":"English","publisher":"American Meteorological Society","doi":"10.1175/EI-D-16-0012.1","usgsCitation":"Liu, S., Bond-Lamberty, B., Boysen, L.R., Ford, J.D., Fox, A., Gallo, K., Hatfield, J.L., Henebry, G.M., Huntington, T.G., Liu, Z., Loveland, T.R., Norby, R.J., Sohl, T.L., Steiner, A.L., Yuan, W., Zhang, Z., and Zhao, S., 2017, Grand challenges in understanding the interplay of climate and land changes: Earth Interactions, v. 21, p. 1-43, https://doi.org/10.1175/EI-D-16-0012.1.","productDescription":"Paper No. 2; 43 p.","startPage":"1","endPage":"43","ipdsId":"IP-073337","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":469960,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/11858/00-001M-0000-002D-26BD-F","text":"External Repository"},{"id":349491,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"21","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2017-03-28","publicationStatus":"PW","scienceBaseUri":"5a60fbede4b06e28e9c23799","contributors":{"authors":[{"text":"Liu, Shuguang 0000-0002-6027-3479 sliu@usgs.gov","orcid":"https://orcid.org/0000-0002-6027-3479","contributorId":147403,"corporation":false,"usgs":true,"family":"Liu","given":"Shuguang","email":"sliu@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":723943,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bond-Lamberty, Ben","contributorId":172028,"corporation":false,"usgs":false,"family":"Bond-Lamberty","given":"Ben","email":"","affiliations":[{"id":33852,"text":"Univ of Maryland, College Park, MD","active":true,"usgs":false},{"id":13566,"text":"Joint Global Change Research Institute, Pacific Northwest National Laboratory","active":true,"usgs":false}],"preferred":false,"id":723948,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Boysen, Lena R.","contributorId":200963,"corporation":false,"usgs":false,"family":"Boysen","given":"Lena","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":723949,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ford, James D.","contributorId":200964,"corporation":false,"usgs":false,"family":"Ford","given":"James","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":723950,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fox, Andrew","contributorId":190103,"corporation":false,"usgs":false,"family":"Fox","given":"Andrew","affiliations":[],"preferred":false,"id":723951,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Gallo, Kevin 0000-0001-9162-5011 kgallo@usgs.gov","orcid":"https://orcid.org/0000-0001-9162-5011","contributorId":192334,"corporation":false,"usgs":true,"family":"Gallo","given":"Kevin","email":"kgallo@usgs.gov","affiliations":[],"preferred":true,"id":723952,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hatfield, Jerry L.","contributorId":71082,"corporation":false,"usgs":true,"family":"Hatfield","given":"Jerry","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":723953,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Henebry, Geoffrey M.","contributorId":124528,"corporation":false,"usgs":false,"family":"Henebry","given":"Geoffrey","email":"","middleInitial":"M.","affiliations":[{"id":5087,"text":"Geographic Information Science Center of Excellence (GIScCE), South Dakota State University, Brookings, USA","active":true,"usgs":false}],"preferred":false,"id":723954,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Huntington, Thomas G. 0000-0002-9427-3530 thunting@usgs.gov","orcid":"https://orcid.org/0000-0002-9427-3530","contributorId":1884,"corporation":false,"usgs":true,"family":"Huntington","given":"Thomas","email":"thunting@usgs.gov","middleInitial":"G.","affiliations":[{"id":371,"text":"Maine Water Science Center","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":723944,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Liu, Zhihua","contributorId":105228,"corporation":false,"usgs":true,"family":"Liu","given":"Zhihua","email":"","affiliations":[],"preferred":false,"id":723955,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Loveland, Thomas R. 0000-0003-3114-6646 loveland@usgs.gov","orcid":"https://orcid.org/0000-0003-3114-6646","contributorId":140256,"corporation":false,"usgs":true,"family":"Loveland","given":"Thomas","email":"loveland@usgs.gov","middleInitial":"R.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":723956,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Norby, Richard J. 0000-0002-0238-9828","orcid":"https://orcid.org/0000-0002-0238-9828","contributorId":167836,"corporation":false,"usgs":false,"family":"Norby","given":"Richard","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":723957,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Sohl, Terry L. 0000-0002-9771-4231 sohl@usgs.gov","orcid":"https://orcid.org/0000-0002-9771-4231","contributorId":648,"corporation":false,"usgs":true,"family":"Sohl","given":"Terry","email":"sohl@usgs.gov","middleInitial":"L.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":723958,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Steiner, Allison L.","contributorId":49261,"corporation":false,"usgs":true,"family":"Steiner","given":"Allison","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":723959,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Yuan, Wenping","contributorId":83435,"corporation":false,"usgs":true,"family":"Yuan","given":"Wenping","email":"","affiliations":[],"preferred":false,"id":723960,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Zhang, Zhao","contributorId":200965,"corporation":false,"usgs":false,"family":"Zhang","given":"Zhao","email":"","affiliations":[],"preferred":false,"id":723961,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Zhao, Shuqing","contributorId":9152,"corporation":false,"usgs":true,"family":"Zhao","given":"Shuqing","email":"","affiliations":[],"preferred":false,"id":723962,"contributorType":{"id":1,"text":"Authors"},"rank":17}]}}
,{"id":70190700,"text":"70190700 - 2017 - Inter-nesting movements and habitat-use of adult female Kemp’s ridley turtles in the Gulf of Mexico","interactions":[],"lastModifiedDate":"2017-09-12T15:09:37","indexId":"70190700","displayToPublicDate":"2017-04-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Inter-nesting movements and habitat-use of adult female Kemp’s ridley turtles in the Gulf of Mexico","docAbstract":"<p><span>Species vulnerability is increased when individuals congregate in restricted areas for breeding; yet, breeding habitats are not well defined for many marine species. Identification and quantification of these breeding habitats are essential to effective conservation. Satellite telemetry and switching state-space modeling (SSM) were used to define inter-nesting habitat of endangered Kemp’s ridley turtles (</span><i>Lepidochelys kempii</i><span>) in the Gulf of Mexico. Turtles were outfitted with satellite transmitters after nesting at Padre Island National Seashore, Texas, USA, from 1998 through 2013 (n = 60); Rancho Nuevo, Tamaulipas, Mexico, during 2010 and 2011 (n = 11); and Tecolutla, Veracruz, Mexico, during 2012 and 2013 (n = 11). These sites span the range of nearly all nesting by this species. Inter-nesting habitat lies in a narrow band of nearshore western Gulf of Mexico waters in the USA and Mexico, with mean water depth of 14 to 19 m within a mean distance to shore of 6 to 11 km as estimated by 50% kernel density estimate, α-Hull, and minimum convex polygon methodologies. Turtles tracked during the inter-nesting period moved, on average, 17.5 km/day and a mean total distance of 398 km. Mean home ranges occupied were 725 to 2948 km</span><sup>2</sup><span>. Our results indicate that these nearshore western Gulf waters represent critical inter-nesting habitat for this species, where threats such as shrimp trawling and oil and gas platforms also occur. Up to half of all adult female Kemp’s ridleys occupy this habitat for weeks to months during each nesting season. Because inter-nesting habitat for this species is concentrated in nearshore waters of the western Gulf of Mexico in both Mexico and the USA, international collaboration is needed to protect this essential habitat and the turtles occurring within it.</span></p>","language":"English","publisher":"PLOS ONE","doi":"10.1371/journal.pone.0174248","usgsCitation":"Shaver, D.J., Hart, K.M., Fujisaki, I., Bucklin, D.N., Iverson, A., Rubio, C., Backof, T.F., Burchfield, P.M., Gonzales Diaz Miron, R.D., Dutton, P.H., Frey, A., Peña, J., Gamez, D.G., Martinez, H.J., and Ortiz, J., 2017, Inter-nesting movements and habitat-use of adult female Kemp’s ridley turtles in the Gulf of Mexico: PLoS ONE, v. 12, no. 3, e0174248; 27 p., https://doi.org/10.1371/journal.pone.0174248.","productDescription":"e0174248; 27 p.","ipdsId":"IP-074667","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":469969,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0174248","text":"Publisher Index Page"},{"id":345671,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Mexico, United States","otherGeospatial":"Gulf of Mexico","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -98.3056640625,\n              18.771115062337024\n            ],\n            [\n              -95.29541015625,\n              18.771115062337024\n            ],\n            [\n              -95.29541015625,\n              28.998531814051795\n            ],\n            [\n              -98.3056640625,\n              28.998531814051795\n            ],\n            [\n              -98.3056640625,\n              18.771115062337024\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"12","issue":"3","noUsgsAuthors":false,"publicationDate":"2017-03-20","publicationStatus":"PW","scienceBaseUri":"59b8f21fe4b08b1644e0aee5","contributors":{"authors":[{"text":"Shaver, Donna J.","contributorId":11104,"corporation":false,"usgs":true,"family":"Shaver","given":"Donna","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":710208,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hart, Kristen M. 0000-0002-5257-7974 kristen_hart@usgs.gov","orcid":"https://orcid.org/0000-0002-5257-7974","contributorId":1966,"corporation":false,"usgs":true,"family":"Hart","given":"Kristen","email":"kristen_hart@usgs.gov","middleInitial":"M.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":710209,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fujisaki, Ikuko","contributorId":38359,"corporation":false,"usgs":false,"family":"Fujisaki","given":"Ikuko","affiliations":[],"preferred":false,"id":710210,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bucklin, David N.","contributorId":175273,"corporation":false,"usgs":false,"family":"Bucklin","given":"David","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":710211,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Iverson, Autumn 0000-0002-8353-6745 ariverson@usgs.gov","orcid":"https://orcid.org/0000-0002-8353-6745","contributorId":179150,"corporation":false,"usgs":true,"family":"Iverson","given":"Autumn","email":"ariverson@usgs.gov","affiliations":[],"preferred":true,"id":710212,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Rubio, Cynthia","contributorId":39277,"corporation":false,"usgs":true,"family":"Rubio","given":"Cynthia","email":"","affiliations":[],"preferred":false,"id":710213,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Backof, Thomas F.","contributorId":196388,"corporation":false,"usgs":false,"family":"Backof","given":"Thomas","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":710214,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Burchfield, Patrick M.","contributorId":47676,"corporation":false,"usgs":true,"family":"Burchfield","given":"Patrick","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":710215,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Gonzales Diaz Miron, Raul de Jesus","contributorId":168393,"corporation":false,"usgs":false,"family":"Gonzales Diaz Miron","given":"Raul","email":"","middleInitial":"de Jesus","affiliations":[],"preferred":false,"id":710216,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Dutton, Peter H.","contributorId":98029,"corporation":false,"usgs":true,"family":"Dutton","given":"Peter","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":710217,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Frey, Amy","contributorId":196390,"corporation":false,"usgs":false,"family":"Frey","given":"Amy","email":"","affiliations":[],"preferred":false,"id":710218,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Peña, Jaime","contributorId":34810,"corporation":false,"usgs":true,"family":"Peña","given":"Jaime","affiliations":[],"preferred":false,"id":710219,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Gamez, Daniel Gomez","contributorId":32065,"corporation":false,"usgs":true,"family":"Gamez","given":"Daniel","email":"","middleInitial":"Gomez","affiliations":[],"preferred":false,"id":710220,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Martinez, Hector J.","contributorId":168394,"corporation":false,"usgs":false,"family":"Martinez","given":"Hector","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":710221,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Ortiz, Jaime","contributorId":77447,"corporation":false,"usgs":true,"family":"Ortiz","given":"Jaime","email":"","affiliations":[],"preferred":false,"id":710222,"contributorType":{"id":1,"text":"Authors"},"rank":15}]}}
,{"id":70187205,"text":"70187205 - 2017 - Scale-specific habitat relationships influence patch occupancy: defining neighborhoods to optimize the effectiveness of landscape-scale grassland bird conservation","interactions":[],"lastModifiedDate":"2017-04-26T12:45:06","indexId":"70187205","displayToPublicDate":"2017-04-01T00:00:00","publicationYear":"2017","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":"Scale-specific habitat relationships influence patch occupancy: defining neighborhoods to optimize the effectiveness of landscape-scale grassland bird conservation","docAbstract":"<div id=\"ASec1\" class=\"AbstractSection\"><p class=\"Heading\"><strong>Context</strong></p><p id=\"Par1\" class=\"Para\">Beyond the recognized importance of protecting large areas of contiguous habitat, conservation efforts for many species are complicated by the fact that patch suitability may also be affected by characteristics of the landscape within which the patch is located. Currently, little is known about the spatial scales at which species respond to different aspects of the landscape surrounding an occupied patch.</p></div><div id=\"ASec2\" class=\"AbstractSection\"><p class=\"Heading\"><strong>Objectives</strong></p><p id=\"Par2\" class=\"Para\">Using grassland bird point count data, we describe an approach to evaluating scale-specific effects of landscape composition on patch occupancy.</p></div><div id=\"ASec3\" class=\"AbstractSection\"><p class=\"Heading\"><strong>Methods</strong></p><p id=\"Par3\" class=\"Para\">We used data from 793 point count surveys conducted in idle and grazed grasslands across Wisconsin, USA from 2012 to 2014 to evaluate scale-dependencies in the response of grassland birds to landscape composition. Patch occupancy models were used to evaluate the relationship between occupancy and landscape composition at scales from 100 to 3000&nbsp;m.</p></div><div id=\"ASec4\" class=\"AbstractSection\"><p class=\"Heading\"><strong>Results</strong></p><p id=\"Par4\" class=\"Para\">Bobolink (<i class=\"EmphasisTypeItalic \">Dolichonyx oryzivorus</i>) exhibited a pattern indicating selection for grassland habitats in the surrounding landscape at all spatial scales while selecting against other habitats. Eastern Meadowlark (<i class=\"EmphasisTypeItalic \">Sturnella magna</i>) displayed evidence of scale sensitivity for all habitat types. Grasshopper Sparrow (<i class=\"EmphasisTypeItalic \">Ammodramus savannarum</i>) showed a strong positive response to pasture and idle grass at all scales and negatively to cropland at large scales. Unlike other species, patch occupancy by Henslow’s Sparrow (<i class=\"EmphasisTypeItalic \">A. henslowii</i>) was primarily influenced by patch area.</p></div><div id=\"ASec5\" class=\"AbstractSection\"><p class=\"Heading\"><strong>Conclusions</strong></p><p id=\"Par5\" class=\"Para\">Our results suggest that both working grasslands (pasture) and idle conservation grasslands can play an important role in grassland bird conservation but also highlight the importance of considering species-specific patch and landscape characteristics for effective conservation.</p></div>","language":"English","publisher":"Springer","doi":"10.1007/s10980-016-0462-y","usgsCitation":"Guttery, M., Ribic, C., Sample, D.W., Paulios, A., Trosen, C., Dadisman, J.D., Schneider, D., and Horton, J., 2017, Scale-specific habitat relationships influence patch occupancy: defining neighborhoods to optimize the effectiveness of landscape-scale grassland bird conservation: Landscape Ecology, v. 32, no. 3, p. 515-529, https://doi.org/10.1007/s10980-016-0462-y.","productDescription":"15 p.","startPage":"515","endPage":"529","ipdsId":"IP-071260","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":340457,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"32","issue":"3","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2016-11-08","publicationStatus":"PW","scienceBaseUri":"5901b1b8e4b0c2e071a99b8e","contributors":{"authors":[{"text":"Guttery, Michael","contributorId":191425,"corporation":false,"usgs":false,"family":"Guttery","given":"Michael","email":"","affiliations":[],"preferred":false,"id":693016,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ribic, Christine 0000-0003-2583-1778 caribic@usgs.gov","orcid":"https://orcid.org/0000-0003-2583-1778","contributorId":147952,"corporation":false,"usgs":true,"family":"Ribic","given":"Christine","email":"caribic@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true},{"id":5068,"text":"Midwest Regional Director's Office","active":true,"usgs":true}],"preferred":true,"id":693015,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sample, David W.","contributorId":19484,"corporation":false,"usgs":true,"family":"Sample","given":"David","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":693017,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Paulios, Andy","contributorId":191427,"corporation":false,"usgs":false,"family":"Paulios","given":"Andy","email":"","affiliations":[],"preferred":false,"id":693018,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Trosen, Chris","contributorId":191428,"corporation":false,"usgs":false,"family":"Trosen","given":"Chris","email":"","affiliations":[],"preferred":false,"id":693019,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Dadisman, John D.","contributorId":171934,"corporation":false,"usgs":false,"family":"Dadisman","given":"John","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":693020,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Schneider, Daniel","contributorId":191429,"corporation":false,"usgs":false,"family":"Schneider","given":"Daniel","email":"","affiliations":[],"preferred":false,"id":693021,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Horton, Josephine 0000-0001-8436-4095","orcid":"https://orcid.org/0000-0001-8436-4095","contributorId":191430,"corporation":false,"usgs":false,"family":"Horton","given":"Josephine","affiliations":[],"preferred":false,"id":693022,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70194199,"text":"70194199 - 2017 - Tree mortality across biomes is promoted by drought intensity, lower wood density and higher specific leaf area","interactions":[],"lastModifiedDate":"2018-01-12T15:20:13","indexId":"70194199","displayToPublicDate":"2017-04-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1466,"text":"Ecology Letters","active":true,"publicationSubtype":{"id":10}},"title":"Tree mortality across biomes is promoted by drought intensity, lower wood density and higher specific leaf area","docAbstract":"<p><span>Drought events are increasing globally, and reports of consequent forest mortality are widespread. However, due to a lack of a quantitative global synthesis, it is still not clear whether drought-induced mortality rates differ among global biomes and whether functional traits influence the risk of drought-induced mortality. To address these uncertainties, we performed a global meta-analysis of 58 studies of drought-induced forest mortality. Mortality rates were modelled as a function of drought, temperature, biomes, phylogenetic and functional groups and functional traits. We identified a consistent global-scale response, where mortality increased with drought severity [log mortality (trees trees</span><sup>−1</sup><span>&nbsp;year</span><sup>−1</sup><span>) increased 0.46 (95% CI&nbsp;=&nbsp;0.2–0.7) with one SPEI unit drought intensity]. We found no significant differences in the magnitude of the response depending on forest biomes or between angiosperms and gymnosperms or evergreen and deciduous tree species. Functional traits explained some of the variation in drought responses between species (i.e. increased from 30 to 37% when wood density and specific leaf area were included). Tree species with denser wood and lower specific leaf area showed lower mortality responses. Our results illustrate the value of functional traits for understanding patterns of drought-induced tree mortality and suggest that mortality could become increasingly widespread in the future.</span></p>","language":"English","publisher":"Wiley","doi":"10.1111/ele.12748","usgsCitation":"Greenwood, S., Ruiz-Benito, P., Martínez-Vilalta, J., Lloret, F., Kitzberger, T., Allen, C.D., Fensham, R., Laughlin, D.C., Kattge, J., Bonisch, G., Kraft, N.J., and Jump, A.S., 2017, Tree mortality across biomes is promoted by drought intensity, lower wood density and higher specific leaf area: Ecology Letters, v. 20, no. 4, p. 539-553, https://doi.org/10.1111/ele.12748.","productDescription":"15 p.","startPage":"539","endPage":"553","ipdsId":"IP-080072","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":469957,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/ele.12748","text":"Publisher Index Page"},{"id":349077,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"20","issue":"4","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2017-02-21","publicationStatus":"PW","scienceBaseUri":"5a60fbede4b06e28e9c2379b","contributors":{"authors":[{"text":"Greenwood, Sarah","contributorId":200537,"corporation":false,"usgs":false,"family":"Greenwood","given":"Sarah","email":"","affiliations":[],"preferred":false,"id":722619,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ruiz-Benito, Paloma","contributorId":200538,"corporation":false,"usgs":false,"family":"Ruiz-Benito","given":"Paloma","email":"","affiliations":[],"preferred":false,"id":722620,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Martínez-Vilalta, Jordi","contributorId":182016,"corporation":false,"usgs":false,"family":"Martínez-Vilalta","given":"Jordi","affiliations":[],"preferred":false,"id":722621,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lloret, Francisco","contributorId":181986,"corporation":false,"usgs":false,"family":"Lloret","given":"Francisco","email":"","affiliations":[],"preferred":false,"id":722622,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kitzberger, Thomas","contributorId":181980,"corporation":false,"usgs":false,"family":"Kitzberger","given":"Thomas","email":"","affiliations":[],"preferred":false,"id":722623,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Allen, Craig D. 0000-0002-8777-5989 craig_allen@usgs.gov","orcid":"https://orcid.org/0000-0002-8777-5989","contributorId":2597,"corporation":false,"usgs":true,"family":"Allen","given":"Craig","email":"craig_allen@usgs.gov","middleInitial":"D.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":722618,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Fensham, Rod","contributorId":200542,"corporation":false,"usgs":false,"family":"Fensham","given":"Rod","email":"","affiliations":[],"preferred":false,"id":722624,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Laughlin, Daniel C.","contributorId":200543,"corporation":false,"usgs":false,"family":"Laughlin","given":"Daniel","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":722625,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Kattge, Jens","contributorId":200544,"corporation":false,"usgs":false,"family":"Kattge","given":"Jens","email":"","affiliations":[],"preferred":false,"id":722626,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Bonisch, Gerhard","contributorId":200545,"corporation":false,"usgs":false,"family":"Bonisch","given":"Gerhard","email":"","affiliations":[],"preferred":false,"id":722627,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Kraft, Nathan J. B.","contributorId":190203,"corporation":false,"usgs":false,"family":"Kraft","given":"Nathan","email":"","middleInitial":"J. B.","affiliations":[],"preferred":false,"id":722628,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Jump, Alistair S.","contributorId":200547,"corporation":false,"usgs":false,"family":"Jump","given":"Alistair","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":722629,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}}
,{"id":70187202,"text":"70187202 - 2017 - Mitigating future avian malaria threats to Hawaiian forest birds from climate change","interactions":[],"lastModifiedDate":"2017-04-26T13:12:50","indexId":"70187202","displayToPublicDate":"2017-04-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Mitigating future avian malaria threats to Hawaiian forest birds from climate change","docAbstract":"<p><span>Avian malaria, transmitted by </span><i>Culex quinquefasciatus</i><span> mosquitoes in the Hawaiian Islands, has been a primary contributor to population range limitations, declines, and extinctions for many endemic Hawaiian honeycreepers. Avian malaria is strongly influenced by climate; therefore, predicted future changes are expected to expand transmission into higher elevations and intensify and lengthen existing transmission periods at lower elevations, leading to further population declines and potential extinction of highly susceptible honeycreepers in mid- and high-elevation forests. Based on future climate changes and resulting malaria risk, we evaluated the viability of alternative conservation strategies to preserve endemic Hawaiian birds at mid and high elevations through the 21</span><sup>st</sup><span> century. We linked an epidemiological model with three alternative climatic projections from the Coupled Model Intercomparison Project to predict future malaria risk and bird population dynamics for the coming century. Based on climate change predictions, proposed strategies included mosquito population suppression using modified males, release of genetically modified refractory mosquitoes, competition from other introduced mosquitoes that are not competent vectors, evolved malaria-tolerance in native honeycreepers, feral pig control to reduce mosquito larval habitats, and predator control to improve bird demographics. Transmission rates of malaria are predicted to be higher than currently observed and are likely to have larger impacts in high-elevation forests where current low rates of transmission create a refuge for highly-susceptible birds. As a result, several current and proposed conservation strategies will be insufficient to maintain existing forest bird populations. We concluded that mitigating malaria transmission at high elevations should be a primary conservation goal. Conservation strategies that maintain highly susceptible species like Iiwi (</span><i>Drepanis coccinea</i><span>) will likely benefit other threatened and endangered Hawai’i species, especially in high-elevation forests. Our results showed that mosquito control strategies offer potential long-term benefits to high elevation Hawaiian honeycreepers. However, combined strategies will likely be needed to preserve endemic birds at mid elevations. Given the delay required to research, develop, evaluate, and improve several of these currently untested conservation strategies we suggest that planning should begin expeditiously.</span></p>","language":"English","publisher":"PLOS","doi":"10.1371/journal.pone.0168880","usgsCitation":"Liao, W., Atkinson, C.T., LaPointe, D., and Samuel, M.D., 2017, Mitigating future avian malaria threats to Hawaiian forest birds from climate change: PLoS ONE, v. 12, no. 1, p. 1-25, https://doi.org/10.1371/journal.pone.0168880.","productDescription":"e0168880; 25 p.","startPage":"1","endPage":"25","ipdsId":"IP-075370","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":469962,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0168880","text":"Publisher Index Page"},{"id":340462,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"12","issue":"1","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2017-01-06","publicationStatus":"PW","scienceBaseUri":"5901b1b9e4b0c2e071a99b90","contributors":{"authors":[{"text":"Liao, Wei","contributorId":147740,"corporation":false,"usgs":false,"family":"Liao","given":"Wei","email":"","affiliations":[{"id":13018,"text":"Department of Forest and Wildlife Ecology, University of Wisconsin, Madison","active":true,"usgs":false}],"preferred":false,"id":693050,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Atkinson, Carter T. 0000-0002-4232-5335 catkinson@usgs.gov","orcid":"https://orcid.org/0000-0002-4232-5335","contributorId":1124,"corporation":false,"usgs":true,"family":"Atkinson","given":"Carter","email":"catkinson@usgs.gov","middleInitial":"T.","affiliations":[{"id":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true},{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"preferred":true,"id":693051,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"LaPointe, Dennis dlapointe@usgs.gov","contributorId":2926,"corporation":false,"usgs":true,"family":"LaPointe","given":"Dennis","email":"dlapointe@usgs.gov","affiliations":[{"id":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true}],"preferred":false,"id":693052,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Samuel, Michael D. msamuel@usgs.gov","contributorId":1419,"corporation":false,"usgs":true,"family":"Samuel","given":"Michael","email":"msamuel@usgs.gov","middleInitial":"D.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":693012,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
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