{"pageNumber":"122","pageRowStart":"3025","pageSize":"25","recordCount":10457,"records":[{"id":70175395,"text":"70175395 - 2016 - Evaluating the effectiveness of wildlife detection and observation technologies at a solar power tower facility","interactions":[],"lastModifiedDate":"2016-08-09T08:42:23","indexId":"70175395","displayToPublicDate":"2016-07-27T09:45:00","publicationYear":"2016","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":"Evaluating the effectiveness of wildlife detection and observation technologies at a solar power tower facility","docAbstract":"

Solar power towers produce electrical energy from sunlight at an industrial scale. Little is known about the effects of this technology on flying animals and few methods exist for automatically detecting or observing wildlife at solar towers and other tall anthropogenic structures. Smoking objects are sometimes observed co-occurring with reflected, concentrated light (“solar flux”) in the airspace around solar towers, but the identity and origins of such objects can be difficult to determine. In this observational pilot study at the world’s largest solar tower facility, we assessed the efficacy of using radar, surveillance video, and insect trapping to detect and observe animals flying near the towers. During site visits in May and September 2014, we monitored the airspace surrounding towers and observed insects, birds, and bats under a variety of environmental and operational conditions. We detected and broadly differentiated animals or objects moving through the airspace generally using radar and near solar towers using several video imaging methods. Video revealed what appeared to be mostly small insects burning in the solar flux. Also, we occasionally detected birds flying in the solar flux but could not accurately identify birds to species or the types of insects and small objects composing the vast majority of smoking targets. Insect trapping on the ground was somewhat effective at sampling smaller insects around the tower, and presence and abundance of insects in the traps generally trended with radar and video observations. Traps did not tend to sample the larger insects we sometimes observed flying in the solar flux or found dead on the ground beneath the towers. Some of the methods we tested (e.g., video surveillance) could be further assessed and potentially used to automatically detect and observe flying animals in the vicinity of solar towers to advance understanding about their effects on wildlife.

","language":"English","publisher":"Public Library of Science","publisherLocation":"San Francisco, CA","doi":"10.1371/journal.pone.0158115","usgsCitation":"Diehl, R.H., Valdez, E.W., Preston, T.M., Wellik, M.J., and Cryan, P.M., 2016, Evaluating the effectiveness of wildlife detection and observation technologies at a solar power tower facility: PLoS ONE, v. 7, no. 11, https://doi.org/10.1371/journal.pone.0158115.","startPage":"e0158115","numberOfPages":"29","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-072111","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":470722,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0158115","text":"Publisher Index Page"},{"id":438582,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7GM85DN","text":"USGS data release","linkHelpText":"Data Recordings from the Ivanpah Solar Electric Generating System (ISEGS) Facility Recorded by the USGS during Spring and Fall 2014"},{"id":326286,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Ivanpah Solar Electric Generating System","volume":"7","issue":"11","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2016-07-27","publicationStatus":"PW","scienceBaseUri":"57aaff0be4b05e859be0f215","contributors":{"authors":[{"text":"Diehl, Robert H. 0000-0001-9141-1734 rhdiehl@usgs.gov","orcid":"https://orcid.org/0000-0001-9141-1734","contributorId":3396,"corporation":false,"usgs":true,"family":"Diehl","given":"Robert","email":"rhdiehl@usgs.gov","middleInitial":"H.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":645040,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Valdez, Ernest W. 0000-0002-7262-3069 ernie@usgs.gov","orcid":"https://orcid.org/0000-0002-7262-3069","contributorId":3600,"corporation":false,"usgs":true,"family":"Valdez","given":"Ernest","email":"ernie@usgs.gov","middleInitial":"W.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":645041,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Preston, Todd M. 0000-0002-8812-9233 tmpreston@usgs.gov","orcid":"https://orcid.org/0000-0002-8812-9233","contributorId":1664,"corporation":false,"usgs":true,"family":"Preston","given":"Todd","email":"tmpreston@usgs.gov","middleInitial":"M.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":645042,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wellik, Mike J. 0000-0002-3123-3988 mwellik@usgs.gov","orcid":"https://orcid.org/0000-0002-3123-3988","contributorId":4587,"corporation":false,"usgs":true,"family":"Wellik","given":"Mike","email":"mwellik@usgs.gov","middleInitial":"J.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":645043,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cryan, Paul M. 0000-0002-2915-8894 cryanp@usgs.gov","orcid":"https://orcid.org/0000-0002-2915-8894","contributorId":147942,"corporation":false,"usgs":true,"family":"Cryan","given":"Paul","email":"cryanp@usgs.gov","middleInitial":"M.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":645044,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70173948,"text":"sir20165090 - 2016 - Comparison of benthos and plankton for selected areas of concern and non-areas of concern in western Lake Michigan Rivers and Harbors in 2012","interactions":[],"lastModifiedDate":"2016-07-28T08:56:28","indexId":"sir20165090","displayToPublicDate":"2016-07-25T15:45:00","publicationYear":"2016","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":"2016-5090","title":"Comparison of benthos and plankton for selected areas of concern and non-areas of concern in western Lake Michigan Rivers and Harbors in 2012","docAbstract":"

Recent data are lacking to assess whether impairments still exist at four of Wisconsin’s largest Lake Michigan harbors that were designated as Areas of Concern (AOCs) in the late 1980s due to sediment contamination and multiple Beneficial Use Impairments (BUIs), such as those affecting benthos (macroinvertebrates) and plankton (zooplankton and phytoplankton) communities. During three seasonal sampling events (“seasons”) in May through August 2012, the U.S. Geological Survey collected sediment benthos and water plankton at the four AOCs as well as six less-degraded non-AOCs along the western Lake Michigan shoreline to assess whether AOC communities were degraded in comparison to non-AOC communities. The four AOCs are the Lower Menominee River, the Lower Green Bay and Fox River, the Sheboygan River, and the Milwaukee Estuary. Due to their size and complexity, multiple locations or “subsites” were sampled within the Lower Green Bay and Fox River AOC (Lower Green Bay, the Fox River near Allouez, and the Fox River near De Pere) and within the Milwaukee Estuary AOC (the Milwaukee River, the Menomonee River, and the Milwaukee Harbor) and single locations were sampled at the other AOCs and non-AOCs. The six non-AOCs are the Escanaba River in Michigan, and the Oconto River, Ahnapee River, Kewaunee River, Manitowoc River, and Root River in Wisconsin. Benthos samples were collected by using Hester-Dendy artificial substrates deployed for 30 days and by using a dredge sampler; zooplankton were collected by net and phytoplankton by whole-water sampler. Except for the Lower Green Bay and Milwaukee Harbor locations, communities at each AOC were compared to all non-AOCs as a group and to paired non-AOCs using taxa relative abundances and metrics, including richness, diversity, and an Index of Biotic Integrity (IBI, for Hester-Dendy samples only). Benthos samples collected during one or more seasons were rated as degraded for at least one metric at all AOCs. In the Milwaukee Estuary, benthos richness was lower in the Milwaukee River subsite spring and summer samples and in the Menomonee River subsite spring sample relative to the paired non-AOCs. Benthos diversity and IBIs at the Menomonee River subsite and IBIs at the Milwaukee River subsite and Sheboygan River were significantly lower than at all non-AOCs as a group across all seasons and therefore were rated as degraded. In addition, IBIs at the Lower Menominee River were significantly lower than those at the paired non-AOCs during all seasons and were therefore rated degraded. Benthos at both Fox River subsites and the Milwaukee River subsite were significantly different from their paired non-AOCs during all three seasons, based on a comparison of the relative abundances of taxa using multivariate testing. Metrics for plankton at AOCs were not significantly lower than those at the paired or group non-AOCs during all seasons; however, zooplankton richness in spring at the Sheboygan River and in fall at the Menomonee River subsite was rated as degraded in comparison to paired non-AOCs. Also, zooplankton richness in fall at the Fox River near Allouez subsite and in spring at the Milwaukee River subsite was rated degraded overall because values were lower than at all non-AOCs as a group and lower than at the paired non-AOCs. Zooplankton diversity in fall at the Fox River near Allouez subsite and the Lower Menominee River was rated degraded in comparison to paired non-AOC comparison sites. Zooplankton communities at the Fox River near Allouez subsite were significantly different from the paired non-AOCs when multivariate comparisons were made without rotifers other than A. priodonta. Overall, benthos and zooplankton BUIs remained at the AOCs in 2012 but no AOCs with a phytoplankton BUI were rated degraded in comparison to non-AOCs. The use of a multiple ecological measures, structural and functional, and multiple statistical analyses, biological metrics and multivariate statistics, provided assessments that defined 2012 status of communities relative to less-impaired non-AOCs in the Great Lakes area.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165090","collaboration":"Prepared in cooperation with the Wisconsin Department of Natural Resources and the U.S. Environmental Protection Agency—Great Lakes National Program Office","usgsCitation":"Scudder Eikenberry, B.C., Bell, A.H., Templar, H.A., and Burns, D.J., 2016, Comparison of benthos and plankton for selected Areas of Concern and non-Areas of Concern in Western Lake Michigan Rivers and Harbors in 2012: U.S. Geological Survey Scientific Investigations Report 2016–5090, 28 p., https://dx.doi.org/10.3133/sir20165090.","productDescription":"vi, 38 p.","startPage":"1","endPage":"28","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-071418","costCenters":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"links":[{"id":325585,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5090/sir20165090.pdf","text":"Report","size":"1.47 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5090"},{"id":325584,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5090/coverthb.jpg"}],"country":"United States","state":"Michigan","otherGeospatial":"Lake Michigan","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -87.4951171875,\n 41.713930073371294\n ],\n [\n -87.703857421875,\n 42.19596877629178\n ],\n [\n -87.73681640625,\n 42.391008609205045\n ],\n [\n -87.747802734375,\n 42.80346172417078\n ],\n [\n -87.81372070312499,\n 43.004647127794435\n ],\n [\n -87.791748046875,\n 43.46089378008257\n ],\n [\n -87.60498046875,\n 43.82660134505384\n ],\n [\n -87.615966796875,\n 44.03232064275084\n ],\n [\n -87.440185546875,\n 44.32384807250689\n ],\n [\n -87.396240234375,\n 44.61393394730626\n ],\n [\n -87.29736328125,\n 44.77793589631623\n ],\n [\n -87.528076171875,\n 44.879228141635274\n ],\n [\n -87.84530639648436,\n 44.621265367781014\n ],\n [\n -87.86453247070312,\n 44.621265367781014\n ],\n [\n -87.91706085205078,\n 44.57848569904532\n ],\n [\n -87.91053771972656,\n 44.56870306646167\n ],\n [\n -87.96066284179688,\n 44.535429806668404\n ],\n [\n -87.99671173095703,\n 44.54497334861026\n ],\n [\n -88.341064453125,\n 44.68427737181225\n ],\n [\n -88.450927734375,\n 44.89479576469787\n ],\n [\n -88.08837890625,\n 44.98811302615805\n ],\n [\n -87.890625,\n 45.10454630976873\n ],\n [\n -87.264404296875,\n 45.259422036351694\n ],\n [\n -87.57202148437499,\n 45.62940492064501\n ],\n [\n -87.066650390625,\n 45.706179285330855\n ],\n [\n -86.9677734375,\n 46.263442671779885\n ],\n [\n -87.4951171875,\n 46.430285240839964\n ],\n [\n -87.9345703125,\n 46.61171462536894\n ],\n [\n -88.3740234375,\n 46.64189395892874\n ],\n [\n -88.70361328125,\n 46.61171462536894\n ],\n [\n -88.604736328125,\n 46.31658418182218\n ],\n [\n -89.18701171875,\n 46.20264638061019\n ],\n [\n -89.154052734375,\n 45.96642454131025\n ],\n [\n -89.09912109375,\n 45.775186183521036\n ],\n [\n -89.02221679687499,\n 45.60635207711834\n ],\n [\n -89.12109375,\n 45.38301927899065\n ],\n [\n -89.176025390625,\n 45.1433047394883\n ],\n [\n -89.20898437499999,\n 44.88701247981298\n ],\n [\n -89.47265625,\n 44.42593442145313\n ],\n [\n -90.054931640625,\n 43.82660134505384\n ],\n [\n -89.527587890625,\n 43.48481212891603\n ],\n [\n -88.846435546875,\n 43.52465500687185\n ],\n [\n -88.494873046875,\n 43.39706523932025\n ],\n [\n -88.39599609375,\n 42.98857645832184\n ],\n [\n -87.4951171875,\n 41.713930073371294\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"

Director, Wisconsin Water Science Center
U.S. Geological Survey
8505 Research Way
Middleton, WI 53562
http://wi.water.usgs.gov

","tableOfContents":"","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"publishedDate":"2016-07-25","noUsgsAuthors":false,"publicationDate":"2016-07-25","publicationStatus":"PW","scienceBaseUri":"57972a20e4b021cadec86f17","contributors":{"authors":[{"text":"Eikenberry, Barbara C. Scudder 0000-0001-8058-1201 beikenberry@usgs.gov","orcid":"https://orcid.org/0000-0001-8058-1201","contributorId":172148,"corporation":false,"usgs":true,"family":"Eikenberry","given":"Barbara C. Scudder","email":"beikenberry@usgs.gov","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":false,"id":639736,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bell, Amanda H. 0000-0002-7199-2145 ahbell@usgs.gov","orcid":"https://orcid.org/0000-0002-7199-2145","contributorId":1752,"corporation":false,"usgs":true,"family":"Bell","given":"Amanda","email":"ahbell@usgs.gov","middleInitial":"H.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":639737,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Olds, Hayley T. 0000-0002-6701-6459 htemplar@usgs.gov","orcid":"https://orcid.org/0000-0002-6701-6459","contributorId":5002,"corporation":false,"usgs":true,"family":"Olds","given":"Hayley T.","email":"htemplar@usgs.gov","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":false,"id":639738,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Burns, Daniel J. 0000-0002-2305-6117 dburns@usgs.gov","orcid":"https://orcid.org/0000-0002-2305-6117","contributorId":5001,"corporation":false,"usgs":true,"family":"Burns","given":"Daniel J.","email":"dburns@usgs.gov","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":639739,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70174963,"text":"70174963 - 2016 - Alternative method of removing otoliths from sturgeon","interactions":[],"lastModifiedDate":"2016-07-25T13:43:55","indexId":"70174963","displayToPublicDate":"2016-07-25T14:45:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2498,"text":"Journal of Visualized Experiments","active":true,"publicationSubtype":{"id":10}},"title":"Alternative method of removing otoliths from sturgeon","docAbstract":"

Extracting the otoliths (ear bones) from fish that have very thick skulls can be difficult and very time consuming. The common practice of making a transverse vertical incision on the top of the skull with a hand or electrical saw may damage the otolith if not performed correctly. Sturgeons (Acipenseridae) are one family in particular that have a very large and thick skull. A new laboratory method entering the brain cavity from the ventral side of the fish to expose the otoliths was easier than other otolith extraction methods found in the literature. Methods reviewed in the literature are designed for the field and are more efficient at processing large quantities of fish quickly. However, this new technique was designed to be more suited for a laboratory setting when time is not pressing and successful extraction from each specimen is critical. The success of finding and removing otoliths using this technique is very high and does not compromise the structure in any manner. This alternative technique is applicable to other similar fish species for extracting the otoliths.

","language":"English","publisher":"JoVE","doi":"10.3791/54316","usgsCitation":"Chalupnicki, M.A., and Dittman, D.E., 2016, Alternative method of removing otoliths from sturgeon: Journal of Visualized Experiments, v. 112, e54316, https://doi.org/10.3791/54316.","productDescription":"e54316","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-070492","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":470728,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/4993311","text":"External Repository"},{"id":325605,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"112","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2016-06-27","publicationStatus":"PW","scienceBaseUri":"57972a20e4b021cadec86f13","contributors":{"authors":[{"text":"Chalupnicki, Marc A. mchalupnicki@usgs.gov","contributorId":3236,"corporation":false,"usgs":true,"family":"Chalupnicki","given":"Marc","email":"mchalupnicki@usgs.gov","middleInitial":"A.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":false,"id":643405,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dittman, Dawn E. 0000-0002-0711-3732 ddittman@usgs.gov","orcid":"https://orcid.org/0000-0002-0711-3732","contributorId":2762,"corporation":false,"usgs":true,"family":"Dittman","given":"Dawn","email":"ddittman@usgs.gov","middleInitial":"E.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":643406,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70174929,"text":"70174929 - 2016 - Fluvial system response to late Pleistocene-Holocene sea-level change on Santa Rosa Island, Channel Islands National Park, California","interactions":[],"lastModifiedDate":"2017-05-04T10:02:01","indexId":"70174929","displayToPublicDate":"2016-07-22T12:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1801,"text":"Geomorphology","active":true,"publicationSubtype":{"id":10}},"title":"Fluvial system response to late Pleistocene-Holocene sea-level change on Santa Rosa Island, Channel Islands National Park, California","docAbstract":"

Santa Rosa Island (SRI) is one of four east-west aligned islands forming the northern Channel Islands chain, and one of the five islands in Channel Islands National Park, California, USA. The island setting provides an unparalleled environment in which to record the response of fluvial systems to major changes of sea level. Many of the larger streams on the island occupy broad valleys that have been filled with alluvium and later incised to form steep- to vertical-walled arroyos, leaving a relict floodplain as much as 12–14 m above the present channel. The period of falling sea level between the end of the last interglacial highstand at ~ 80 ka and the last glacial lowstand at ~ 21 ka was marked by erosion and incision in the uplands and by deposition of alluvial sediment on the exposed marine shelf. Sea level rose relatively rapidly following the last glacial lowstand of − 106 m, triggering a shift from an erosional to a depositional sedimentary regime. Accumulation of sediment occurred first through vertical and lateral accretion in broad, shallow channels on the shelf. Channel avulsion and delta sedimentation produced widespread deposition, creating lobes or wedges of sediment distributed across relatively large areas of the shelf during the latest Pleistocene. Backfilling of valleys onshore (landward of present sea level) appears to have progressed in a more orderly and predictable fashion throughout the Holocene primarily because the streams were confined to their valleys. Vertical aggradation locally reduced stream gradients, causing frequent overbank flooding and lateral channel shift by meandering and/or avulsion. Local channel gradient and morphology, short-term climate variations, and intrinsic controls also affected the timing and magnitudes of these cut, fill, and flood events, and are reflected in the thickness and spacing of the episodic alluvial sequences. Floodplain aggradation within the valleys continued until at least 500 years ago, followed by intensive arroyo cutting that abandoned the relict floodplains, forming alluvial terraces. Sedimentary evidence points to overgrazing and drought, followed by catastrophic flooding, in the mid-nineteenth century as factors that may have accelerated and dramatically enhanced arroyo formation on the island.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.geomorph.2016.05.033","usgsCitation":"Schumann, R.R., Pigati, J., and McGeehin, J.P., 2016, Fluvial system response to late Pleistocene-Holocene sea-level change on Santa Rosa Island, Channel Islands National Park, California: Geomorphology, v. 268, p. 322-340, https://doi.org/10.1016/j.geomorph.2016.05.033.","productDescription":"19 p.","startPage":"322","endPage":"340","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-070182","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":325535,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Channel Islands National Park, Santa Rosa Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -120.26527404785156,\n 33.880677127838844\n ],\n [\n -120.26527404785156,\n 34.04412546508576\n ],\n [\n -119.95765686035155,\n 34.04412546508576\n ],\n [\n -119.95765686035155,\n 33.880677127838844\n ],\n [\n -120.26527404785156,\n 33.880677127838844\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"268","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57933617e4b0eb1ce79e8bb7","contributors":{"authors":[{"text":"Schumann, R. Randall 0000-0001-8158-6960 rschumann@usgs.gov","orcid":"https://orcid.org/0000-0001-8158-6960","contributorId":1569,"corporation":false,"usgs":true,"family":"Schumann","given":"R.","email":"rschumann@usgs.gov","middleInitial":"Randall","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":643188,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pigati, Jeffery S. jpigati@usgs.gov","contributorId":140289,"corporation":false,"usgs":true,"family":"Pigati","given":"Jeffery S.","email":"jpigati@usgs.gov","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":false,"id":643189,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McGeehin, John P. mcgeehin@usgs.gov","contributorId":140956,"corporation":false,"usgs":true,"family":"McGeehin","given":"John","email":"mcgeehin@usgs.gov","middleInitial":"P.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":false,"id":643190,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70174856,"text":"70174856 - 2016 - Setting priorities for private land conservation in fire-prone landscapes: Are fire risk reduction and biodiversity conservation competing or compatible objectives?","interactions":[],"lastModifiedDate":"2016-08-04T15:13:58","indexId":"70174856","displayToPublicDate":"2016-07-20T05:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1468,"text":"Ecology and Society","active":true,"publicationSubtype":{"id":10}},"title":"Setting priorities for private land conservation in fire-prone landscapes: Are fire risk reduction and biodiversity conservation competing or compatible objectives?","docAbstract":"

Although wildfire plays an important role in maintaining biodiversity in many ecosystems, fire management to protect human assets is often carried out by different agencies than those tasked for conserving biodiversity. In fact, fire risk reduction and biodiversity conservation are often viewed as competing objectives. Here we explored the role of management through private land conservation and asked whether we could identify private land acquisition strategies that fulfill the mutual objectives of biodiversity conservation and fire risk reduction, or whether the maximization of one objective comes at a detriment to the other. Using a fixed budget and number of homes slated for development, we simulated 20 years of housing growth under alternative conservation selection strategies, and then projected the mean risk of fires destroying structures and the area and configuration of important habitat types in San Diego County, California, USA. We found clear differences in both fire risk projections and biodiversity impacts based on the way conservation lands are prioritized for selection, but these differences were split between two distinct groupings. If no conservation lands were purchased, or if purchases were prioritized based on cost or likelihood of development, both the projected fire risk and biodiversity impacts were much higher than if conservation lands were purchased in areas with high fire hazard or high species richness. Thus, conserving land focused on either of the two objectives resulted in nearly equivalent mutual benefits for both. These benefits not only resulted from preventing development in sensitive areas, but they were also due to the different housing patterns and arrangements that occurred as development was displaced from those areas. Although biodiversity conflicts may still arise using other fire management strategies, this study shows that mutual objectives can be attained through land-use planning in this region. These results likely generalize to any place where high species richness overlaps with hazardous wildland vegetation.

","language":"English","publisher":"The Resilience Alliance","doi":"10.5751/ES-08410-210302","usgsCitation":"Syphard, A.D., Butsic, V., Bar-Massada, A., Keeley, J.E., Tracey, J.A., and Fisher, R.N., 2016, Setting priorities for private land conservation in fire-prone landscapes: Are fire risk reduction and biodiversity conservation competing or compatible objectives?: Ecology and Society, v. 21, no. 3, Article 2; 11 p, https://doi.org/10.5751/ES-08410-210302.","productDescription":"Article 2; 11 p","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-071415","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":470739,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5751/es-08410-210302","text":"Publisher Index Page"},{"id":325459,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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rfisher@usgs.gov","orcid":"https://orcid.org/0000-0002-2956-3240","contributorId":1529,"corporation":false,"usgs":true,"family":"Fisher","given":"Robert","email":"rfisher@usgs.gov","middleInitial":"N.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":642835,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70178793,"text":"70178793 - 2016 - Hierarchical animal movement models for population-level inference","interactions":[],"lastModifiedDate":"2016-12-07T17:59:02","indexId":"70178793","displayToPublicDate":"2016-07-19T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5233,"text":"Environmetrics ","active":true,"publicationSubtype":{"id":10}},"title":"Hierarchical animal movement models for population-level inference","docAbstract":"

New methods for modeling animal movement based on telemetry data are developed regularly. With advances in telemetry capabilities, animal movement models are becoming increasingly sophisticated. Despite a need for population-level inference, animal movement models are still predominantly developed for individual-level inference. Most efforts to upscale the inference to the population level are either post hoc or complicated enough that only the developer can implement the model. Hierarchical Bayesian models provide an ideal platform for the development of population-level animal movement models but can be challenging to fit due to computational limitations or extensive tuning required. We propose a two-stage procedure for fitting hierarchical animal movement models to telemetry data. The two-stage approach is statistically rigorous and allows one to fit individual-level movement models separately, then resample them using a secondary MCMC algorithm. The primary advantages of the two-stage approach are that the first stage is easily parallelizable and the second stage is completely unsupervised, allowing for an automated fitting procedure in many cases. We demonstrate the two-stage procedure with two applications of animal movement models. The first application involves a spatial point process approach to modeling telemetry data, and the second involves a more complicated continuous-time discrete-space animal movement model. We fit these models to simulated data and real telemetry data arising from a population of monitored Canada lynx in Colorado, USA.

","language":"English","publisher":"Wiley-Blackwell ","doi":"10.1002/env.2402","usgsCitation":"Hooten, M., Buderman, F.E., Brost, B.M., Hanks, E., and Ivans, J.S., 2016, Hierarchical animal movement models for population-level inference: Environmetrics , v. 27, no. 6, p. 322-333, https://doi.org/10.1002/env.2402.","productDescription":"12 p.","startPage":"322","endPage":"333","ipdsId":"IP-076019","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":470741,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://arxiv.org/abs/1606.09585","text":"External Repository"},{"id":331665,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"27","issue":"6","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2016-07-19","publicationStatus":"PW","scienceBaseUri":"58492df2e4b06d80b7b093a4","contributors":{"authors":[{"text":"Hooten, Mevin 0000-0002-1614-723X mhooten@usgs.gov","orcid":"https://orcid.org/0000-0002-1614-723X","contributorId":2958,"corporation":false,"usgs":true,"family":"Hooten","given":"Mevin","email":"mhooten@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":12963,"text":"Colorado Cooperative Fish and Wildlife Research Unit, Fort Collins, CO","active":true,"usgs":false}],"preferred":true,"id":655144,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Buderman, Frances E.","contributorId":171634,"corporation":false,"usgs":false,"family":"Buderman","given":"Frances","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":655198,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brost, Brian M.","contributorId":171484,"corporation":false,"usgs":false,"family":"Brost","given":"Brian","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":655199,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hanks, Ephraim M.","contributorId":104630,"corporation":false,"usgs":true,"family":"Hanks","given":"Ephraim M.","affiliations":[],"preferred":false,"id":655200,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ivans, Jacob S.","contributorId":177286,"corporation":false,"usgs":false,"family":"Ivans","given":"Jacob","email":"","middleInitial":"S.","affiliations":[{"id":16861,"text":"Colorado Parks and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":655201,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70170068,"text":"sir20165042 - 2016 - Effects of aquifer storage and recovery activities on water quality in the Little Arkansas River and Equus Beds Aquifer, south-central Kansas, 2011–14","interactions":[],"lastModifiedDate":"2017-05-02T07:42:28","indexId":"sir20165042","displayToPublicDate":"2016-07-18T00:00:00","publicationYear":"2016","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":"2016-5042","title":"Effects of aquifer storage and recovery activities on water quality in the Little Arkansas River and Equus Beds Aquifer, south-central Kansas, 2011–14","docAbstract":"

The Equus Beds aquifer in south-central Kansas is aprimary water source for the city of Wichita. The Equus Beds aquifer storage and recovery (ASR) project was developed to help the city of Wichita meet increasing current (2016) and future water demands. The Equus Beds ASR project pumps water out of the Little Arkansas River during above-base flow conditions, treats it using drinking-water quality standards as a guideline, and recharges it into the Equus Beds aquifer for later use. Phase II of the Equus Beds ASR project currently (2016) includes a river intake facility and a surface-water treatment facility with a 30 million gallon per day capacity. Water diverted from the Little Arkansas River is delivered to an adjacent presedimentation basin for solids removal. Subsequently, waste from the surface-water treatment facility and the presedimentation basin is returned to the Little Arkansas River through a residuals return line. The U.S. Geological Survey, in cooperation with the city of Wichita, developed and implemented a hydrobiological monitoring program as part of the ASR project to characterize and quantify the effects of aquifer storage and recovery activities on the Little Arkansas River and Equus Beds aquifer water quality.

Data were collected from 2 surface-water sites (one upstream and one downstream from the residuals return line), 1 residuals return line site, and 2 groundwater well sites (each having a shallow and deep part): the Little Arkansas River upstream from the ASR facility near Sedgwick, Kansas (upstream surface-water site 375350097262800), about 0.03 mile (mi) upstream from the residuals return line site; the Little Arkansas River near Sedgwick, Kans. (downstream surface-water site 07144100), about 1.68 mi downstream from the residuals return line site; discharge from the Little Arkansas River ASR facility near Sedgwick, Kansas (residuals return line site 375348097262800); 25S 01 W 07BCCC01 SMW–S11 near CW36 (MW–7 shallow groundwater well site 375327097285401); 25S01 W 07BCCC02 DMW–S10 near CW36 (MW–7 deep groundwater well site 375327097285402); 25S 01W 07BCCA01 SMW–S13 near CW36 (MW–8 shallow groundwater well site 375332097284801); and 25S 01W 07BCCA02 DMW–S14 near CW36 (MW–8 deep groundwater well site 375332097284802). The U.S. Geological Survey, in cooperation with the city of Wichita, assessed the effects of the ASR Phase II facility residuals return line discharges on stream quality of the Little Arkansas River by measuring continuous physicochemical properties and collecting discrete water-quality and sediment samples for about 2 years pre- (January 2011 through April 2013) and post-ASR (May 2013 through December 2014) Phase II facility operation upstream and downstream from the ASR Phase II facility. Additionally, habitat variables were quantified and macroinvertebrate and fish communities were sampled upstream and downstream from the ASR Phase II facility during the study period. To assess the effects of aquifer recharge on Equus Beds groundwater quality, continuous physicochemical properties were measured and discrete water-quality samples were collected before and during the onset of Phase II aquifer recharge in two (shallow and deep) groundwater wells.

Little Arkansas River streamflow was about 10 times larger after the facility began operating because of greater rainfall. Residuals return line release volumes were a very minimal proportion (0.06 percent) of downstream streamflow volume during the months the ASR facility was operating. Upstream and downstream continuously measured water temperature and dissolved oxygen median differences were smaller post-ASR than pre-ASR. Turbidity generally was smaller at the downstream site throughout the study period and decreased at both sites after the ASR Phase II facility began discharging despite a median residuals return line turbidity that was about an order of magnitude larger than the median turbidity at the downstream site. Upstream and downstream continuously measured turbidity median differences were larger post-ASR than pre-ASR. Median post-ASR continuously measured nitrite plus nitrate and continuously computed total suspended solids and suspended-sediment concentrations were smaller than pre-ASR likely because of higher streamflows and dilution; whereas, median continuously computed dissolved and total organic carbon concentrations were larger likely because of higher streamflows and runoff conditions.

None of the discretely measured water-quality constituents (dissolved and suspended solids, primary ions, suspended sediment, nutrients, carbon, trace elements, viral and bacterial indicators, and pesticides) in surface water were significantly different between the upstream and downstream sites after the ASR Phase II facility began discharging; however, pre-ASR calcium, sodium, hardness, manganese, and arsenate concentrations were significantly larger at the upstream site, which indicates that some water-quality conditions at the upstream and downstream sites were more similar post-ASR. Most of the primary constituents that make up dissolved solids decreased at both sites after the ASR Phase II facility began operation. Discretely collected total suspended solids concentrations were similar between the upstream and downstream sites before the facility began operating but were about 27 percent smaller at the downstream site after the facility began operating, despite the total suspended solids concentrations in the residuals return line being 15 times larger than the downstream site.

Overall habitat scores were indicative of suboptimal conditions upstream and downstream from the ASR Phase II facility throughout the study period. Substrate fouling and sediment deposition mean scores indicated marginal conditions at the upstream and downstream sites during the study period, demonstrating that sediment deposition was evident pre- and post-ASR and no substantial changes in these habitat characteristics were noted after the ASR Phase II facility began discharging. Macroinvertebrate community composition (evaluated using functional feeding, behavioral, and tolerance metrics) generally was similar between sites during the study period. Fewer macroinvertebrate metrics were significant between the upstream and downstream sites post-ASR (6) than pre-ASR (14), which suggests that macroinvertebate communities were more similar after the ASR facility began discharging. Upstream-downstream comparisons in macroinvertebrate aquatic-life-support metrics had no significant differences for the post-ASR time period and neither site was fully supporting for any of the Kansas Department of Health and Environment aquatic-life-support metrics (Macroinvertebrate Biotic Index; Kansas Biotic Index with tolerances for nutrients and oxygen-demanding substances; Ephemeroptera, Plecoptera, and Trichoptera [EPT] richness; and percentage of EPT species). Overall, using macroinvertebrate aquatic life-support criteria from the Kansas Department of Health and Environment, upstream and downstream sites were classified as partially supporting before and after the onset of ASR facility operations. Fish community trophic status and tolerance groups generally were similar among sites during the study period. Fish community Little Arkansas River Basin Index of Biotic Integrity scores at the upstream and downstream sites were indicative of fair-to-good conditions before the facility began operating and decreased to fair conditions after the facility began operating.

Groundwater physicochemical changes concurrent with the beginning of recharge operations at the Sedgwick basin were more pronounced in shallow groundwater. No constituent concentrations in the pre-recharge period in comparison to the post-recharge period increased to concentrations exceeding drinking water regulations; however, nitrate decreased significantly from a pre-recharge exceedance of the U.S. Environmental Protection Agency maximum contaminant level to a post recharge nonexceedance. Shallow groundwater chemical concentrations or rates of detection increased after artificial recharge began for the ions potassium, chloride, and fluoride; phosphorus and organic carbon species; trace elements barium, manganese, nickel, arsenate, arsenic, and boron; agricultural pesticides atrazine, metolachlor, metribuzin, and simazine; organic disinfection byproducts bromodichloromethane and trichloromethane; and gross beta levels. Additionally, water temperature, and pH were larger after recharge began; and total solids and slime-forming bacteria concentrations and densities were smaller. Total solids, nitrate, and selenium significantly decreased; and potassium, chloride, nickel, arsenic, fluoride, phosphorus and carbon species, and gross beta levels significantly increased in shallow groundwater after artificial recharge. Results of biological activity reaction tests indicated that water quality microbiology was different before and after artificial recharge began; at times, these differences may lead to changes in dominant bacterial populations that, in turn, may lead to formation and expansion in populations that may cause bioplugging and other unwanted effects. Calcite, iron (II) hydroxide, hydroxyapatite, and similar minerals, had shifts in saturation indices that generally were from undersaturation toward equilibrium and, in some cases, toward oversaturation. These shifts toward neutral saturation indices might suggest reduced weathering of the minerals present in the Equus Beds aquifer. Chemical weathering in the shallow parts of the aquifer may be accelerated because of the increased water temperatures and the system is more vulnerable to clogged pores and mineral dissolution as the equilibrium state is affected by recharge and withdrawal. When oversaturation is indicated for iron minerals, plugging of aquifer materials may happen.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165042","collaboration":"Prepared in cooperation with the City of Wichita, Kansas","usgsCitation":"Stone, M.L., Garrett, J.D., Poulton, B.C., and Ziegler, A.C., 2016, Effects of aquifer storage and recovery activities on water quality in the Little Arkansas River and Equus Beds aquifer, south-central Kansas, 2011–14: U.S. Geological Survey Scientific Investigations Report 2016–5024, 88 p., https://dx.doi.org/10.3133/sir20165042.","productDescription":"Report: xii, 88 p.; Appendix Files","numberOfPages":"104","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-068666","costCenters":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"links":[{"id":325362,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5042/sir20165042.pdf","text":"Report","size":"5.59 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016–5024"},{"id":325361,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5042/coverthb.jpg"},{"id":325363,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2016/5042/sir20165042_appendixtables.xlsx","text":"Appendix Files","size":"199 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2016–5024 Appendix Files"}],"country":"United States","state":"Kansas","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -97.70416259765625,\n 38.10106333042556\n ],\n [\n -97.57232666015625,\n 38.09998264736481\n ],\n [\n -97.57781982421875,\n 38.08160859009049\n ],\n [\n -97.55035400390625,\n 38.0545795282119\n ],\n [\n -97.525634765625,\n 38.019967758742766\n ],\n [\n -97.48580932617188,\n 38.01239425385966\n ],\n [\n -97.43499755859374,\n 37.94203148678865\n ],\n [\n -97.42813110351562,\n 37.90845010709064\n ],\n [\n -97.36221313476562,\n 37.814123701604466\n ],\n [\n -97.46520996093749,\n 37.814123701604466\n ],\n [\n -97.47894287109375,\n 37.82280243352756\n ],\n [\n -97.50640869140625,\n 37.820632846207864\n ],\n [\n -97.52838134765624,\n 37.83473402375478\n ],\n [\n -97.57095336914062,\n 37.85859141570558\n ],\n [\n -97.61764526367188,\n 37.87702138607635\n ],\n [\n -97.67120361328125,\n 37.88677656291023\n ],\n [\n -97.70278930664062,\n 37.898697801966094\n ],\n [\n -97.70416259765625,\n 38.10106333042556\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"

Director, Kansas Water Science Center
U.S. Geological Survey
4821 Quail Crest Place Lawrence, KS 66049

\n

http://ks.water.usgs.gov

","tableOfContents":"","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2016-07-18","noUsgsAuthors":false,"publicationDate":"2016-07-18","publicationStatus":"PW","scienceBaseUri":"578defa1e4b0f1bea0e03bc5","contributors":{"authors":[{"text":"Stone, Mandy L. 0000-0002-6711-1536 mstone@usgs.gov","orcid":"https://orcid.org/0000-0002-6711-1536","contributorId":4409,"corporation":false,"usgs":true,"family":"Stone","given":"Mandy","email":"mstone@usgs.gov","middleInitial":"L.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":true,"id":642671,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Garrett, Jessica D. 0000-0002-4466-3709 jgarrett@usgs.gov","orcid":"https://orcid.org/0000-0002-4466-3709","contributorId":4229,"corporation":false,"usgs":true,"family":"Garrett","given":"Jessica","email":"jgarrett@usgs.gov","middleInitial":"D.","affiliations":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true},{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true}],"preferred":true,"id":642672,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Poulton, Barry C. 0000-0002-7219-4911 bpoulton@usgs.gov","orcid":"https://orcid.org/0000-0002-7219-4911","contributorId":2421,"corporation":false,"usgs":true,"family":"Poulton","given":"Barry","email":"bpoulton@usgs.gov","middleInitial":"C.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":642673,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ziegler, Andrew C. aziegler@usgs.gov","contributorId":433,"corporation":false,"usgs":true,"family":"Ziegler","given":"Andrew C.","email":"aziegler@usgs.gov","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":false,"id":642674,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70191919,"text":"70191919 - 2016 - State-and-transition simulation models: a framework for forecasting landscape change","interactions":[],"lastModifiedDate":"2017-10-18T16:55:06","indexId":"70191919","displayToPublicDate":"2016-07-16T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2717,"text":"Methods in Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"State-and-transition simulation models: a framework for forecasting landscape change","docAbstract":"

Summary

  1. A wide range of spatially explicit simulation models have been developed to forecast landscape dynamics, including models for projecting changes in both vegetation and land use. While these models have generally been developed as separate applications, each with a separate purpose and audience, they share many common features.
  2. We present a general framework, called a state-and-transition simulation model (STSM), which captures a number of these common features, accompanied by a software product, called ST-Sim, to build and run such models. The STSM method divides a landscape into a set of discrete spatial units and simulates the discrete state of each cell forward as a discrete-time-inhomogeneous stochastic process. The method differs from a spatially interacting Markov chain in several important ways, including the ability to add discrete counters such as age and time-since-transition as state variables, to specify one-step transition rates as either probabilities or target areas, and to represent multiple types of transitions between pairs of states.
  3. We demonstrate the STSM method using a model of land-use/land-cover (LULC) change for the state of Hawai'i, USA. Processes represented in this example include expansion/contraction of agricultural lands, urbanization, wildfire, shrub encroachment into grassland and harvest of tree plantations; the model also projects shifts in moisture zones due to climate change. Key model output includes projections of the future spatial and temporal distribution of LULC classes and moisture zones across the landscape over the next 50 years.
  4. State-and-transition simulation models can be applied to a wide range of landscapes, including questions of both land-use change and vegetation dynamics. Because the method is inherently stochastic, it is well suited for characterizing uncertainty in model projections. When combined with the ST-Sim software, STSMs offer a simple yet powerful means for developing a wide range of models of landscape dynamics.
","language":"English","publisher":"Wiley","doi":"10.1111/2041-210X.12597","usgsCitation":"Daniel, C., Frid, L., Sleeter, B.M., and Fortin, M., 2016, State-and-transition simulation models: a framework for forecasting landscape change: Methods in Ecology and Evolution, v. 7, no. 11, p. 1413-1423, https://doi.org/10.1111/2041-210X.12597.","productDescription":"11 p.","startPage":"1413","endPage":"1423","ipdsId":"IP-071108","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":470746,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/2041-210x.12597","text":"Publisher Index Page"},{"id":346924,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"7","issue":"11","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-07-16","publicationStatus":"PW","scienceBaseUri":"59e86839e4b05fe04cd4d218","contributors":{"authors":[{"text":"Daniel, Colin","contributorId":197531,"corporation":false,"usgs":false,"family":"Daniel","given":"Colin","affiliations":[],"preferred":false,"id":713685,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Frid, Leonardo","contributorId":196604,"corporation":false,"usgs":false,"family":"Frid","given":"Leonardo","email":"","affiliations":[],"preferred":false,"id":713686,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sleeter, Benjamin M. 0000-0003-2371-9571 bsleeter@usgs.gov","orcid":"https://orcid.org/0000-0003-2371-9571","contributorId":3479,"corporation":false,"usgs":true,"family":"Sleeter","given":"Benjamin","email":"bsleeter@usgs.gov","middleInitial":"M.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true},{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":713684,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fortin, Marie-Josee","contributorId":197532,"corporation":false,"usgs":false,"family":"Fortin","given":"Marie-Josee","email":"","affiliations":[],"preferred":false,"id":713687,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70174672,"text":"70174672 - 2016 - Assessing the influence of watershed characteristics on chlorophyll a in waterbodies at global and regional scales","interactions":[],"lastModifiedDate":"2018-01-02T20:44:35","indexId":"70174672","displayToPublicDate":"2016-07-14T11:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1999,"text":"Inland Waters","active":true,"publicationSubtype":{"id":10}},"title":"Assessing the influence of watershed characteristics on chlorophyll a in waterbodies at global and regional scales","docAbstract":"

Prediction of primary production of lentic water bodies (i.e., lakes and reservoirs) is valuable to researchers and resource managers alike, but is very rarely done at the global scale. With the development of remote sensing technologies, it is now feasible to gather large amounts of data across the world, including understudied and remote regions. To determine which factors were most important in explaining the variation of chlorophyll a (Chl-a), an indicator of primary production in water bodies, at global and regional scales, we first developed a geospatial database of 227 water bodies and watersheds with corresponding Chl-a, nutrient, hydrogeomorphic, and climate data. Then we used a generalized additive modeling approach and developed model selection criteria to select models that most parsimoniously related Chl-a to predictor variables for all 227 water bodies and for 51 lakes in the Laurentian Great Lakes region in the data set. Our best global model contained two hydrogeomorphic variables (water body surface area and the ratio of watershed to water body surface area) and a climate variable (average temperature in the warmest model selection criteria to select models that most parsimoniously related Chl-a to predictor variables quarter) and explained ~ 30% of variation in Chl-a. Our regional model contained one hydrogeomorphic variable (flow accumulation) and the same climate variable, but explained substantially more variation (58%). Our results indicate that a regional approach to watershed modeling may be more informative to predicting Chl-a, and that nearly a third of global variability in Chl-a may be explained using hydrogeomorphic and climate variables.

","language":"English","publisher":"International Society of Limnology","doi":"10.1080/IW-6.3.964","usgsCitation":"Woelmer, W., Kao, Y., Bunnell, D., Deines, A.M., Bennion, D., Rogers, M.W., Brooks, C., Sayers, M.J., Banach, D.M., Grimm, A.G., and Shuchman, R.A., 2016, Assessing the influence of watershed characteristics on chlorophyll a in waterbodies at global and regional scales: Inland Waters, v. 6, no. 3, p. 379-392, https://doi.org/10.1080/IW-6.3.964.","productDescription":"14 p.","startPage":"379","endPage":"392","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-071310","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":325241,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"6","issue":"3","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2018-01-02","publicationStatus":"PW","scienceBaseUri":"5788a99ae4b0d27deb3813c2","contributors":{"authors":[{"text":"Woelmer, Whitney 0000-0001-5147-3877 wwoelmer@usgs.gov","orcid":"https://orcid.org/0000-0001-5147-3877","contributorId":150485,"corporation":false,"usgs":true,"family":"Woelmer","given":"Whitney","email":"wwoelmer@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":642453,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kao, Yu-Chun","contributorId":35626,"corporation":false,"usgs":false,"family":"Kao","given":"Yu-Chun","affiliations":[{"id":6649,"text":"University of Michigan, School of Natural Resources and Environment","active":true,"usgs":false}],"preferred":false,"id":642454,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bunnell, David B. 0000-0003-3521-7747 dbunnell@usgs.gov","orcid":"https://orcid.org/0000-0003-3521-7747","contributorId":169859,"corporation":false,"usgs":true,"family":"Bunnell","given":"David B.","email":"dbunnell@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":false,"id":642452,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Deines, Andrew M.","contributorId":166920,"corporation":false,"usgs":false,"family":"Deines","given":"Andrew","email":"","middleInitial":"M.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":642455,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bennion, David 0000-0003-4927-4195 dbennion@usgs.gov","orcid":"https://orcid.org/0000-0003-4927-4195","contributorId":149533,"corporation":false,"usgs":true,"family":"Bennion","given":"David","email":"dbennion@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":642456,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Rogers, Mark W. 0000-0001-7205-5623 mwrogers@usgs.gov","orcid":"https://orcid.org/0000-0001-7205-5623","contributorId":4590,"corporation":false,"usgs":true,"family":"Rogers","given":"Mark","email":"mwrogers@usgs.gov","middleInitial":"W.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":642457,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Brooks, Colin N.","contributorId":103961,"corporation":false,"usgs":true,"family":"Brooks","given":"Colin N.","affiliations":[],"preferred":false,"id":642458,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Sayers, Michael J.","contributorId":172893,"corporation":false,"usgs":false,"family":"Sayers","given":"Michael","email":"","middleInitial":"J.","affiliations":[{"id":27113,"text":"Michigan Tech University","active":true,"usgs":false}],"preferred":false,"id":642459,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Banach, David M.","contributorId":172894,"corporation":false,"usgs":false,"family":"Banach","given":"David","email":"","middleInitial":"M.","affiliations":[{"id":27113,"text":"Michigan Tech University","active":true,"usgs":false}],"preferred":false,"id":642460,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Grimm, Amanda G.","contributorId":150482,"corporation":false,"usgs":false,"family":"Grimm","given":"Amanda","email":"","middleInitial":"G.","affiliations":[{"id":16203,"text":"Michigan Technological university","active":true,"usgs":false}],"preferred":false,"id":642461,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Shuchman, Robert A.","contributorId":150483,"corporation":false,"usgs":false,"family":"Shuchman","given":"Robert","email":"","middleInitial":"A.","affiliations":[{"id":16203,"text":"Michigan Technological university","active":true,"usgs":false}],"preferred":false,"id":642462,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70174993,"text":"70174993 - 2016 - Post-project geomorphic assessment of a large process-based river restoration project","interactions":[],"lastModifiedDate":"2016-07-27T12:01:10","indexId":"70174993","displayToPublicDate":"2016-07-11T14:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1801,"text":"Geomorphology","active":true,"publicationSubtype":{"id":10}},"title":"Post-project geomorphic assessment of a large process-based river restoration project","docAbstract":"

This study describes channel changes following completion of the Provo River Restoration Project (PRRP), the largest stream restoration project in Utah and one of the largest projects in the United States in which a gravel-bed river was fully reconstructed. We summarize project objectives and the design process, and we analyze monitoring data collected during the first 7 years after project completion. Post-project channel adjustment during the study period included two phases: (i) an initial phase of rapid, but small-scale, adjustment during the first years after stream flow was introduced to the newly constructed channel and (ii) a subsequent period of more gradual topographic adjustment and channel migration. Analysis of aerial imagery and ground-survey data demonstrate that the channel has been more dynamic in the downstream 4 km where a local source contributes a significant annual supply of bed material. Here, the channel migrates and exhibits channel adjustments that are more consistent with project objectives. The upstream 12 km of the PRRP are sediment starved, the channel has been laterally stable, and this condition may not be consistent with large-scale project objectives.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.geomorph.2016.07.018","usgsCitation":"Erwin, S.O., Schmidt, J.C., and Allred, T.M., 2016, Post-project geomorphic assessment of a large process-based river restoration project: Geomorphology, v. 270, p. 145-158, https://doi.org/10.1016/j.geomorph.2016.07.018.","productDescription":"13 p.","startPage":"145","endPage":"158","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-059645","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":325699,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Utah","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.34300231933592,\n 40.61343119773193\n ],\n [\n -111.39038085937499,\n 40.614994915836924\n ],\n [\n -111.39244079589844,\n 40.64261456761013\n ],\n [\n -111.41853332519531,\n 40.670222795307346\n ],\n [\n -111.44256591796875,\n 40.65303410892721\n ],\n [\n -111.45423889160156,\n 40.62646106367355\n ],\n [\n -111.45561218261719,\n 40.59257812608644\n ],\n [\n -111.4892578125,\n 40.488215202002614\n ],\n [\n -111.53800964355467,\n 40.415064437473674\n ],\n [\n -111.533203125,\n 40.387873874881834\n ],\n [\n -111.48994445800781,\n 40.3805514624311\n ],\n [\n -111.46591186523438,\n 40.39937891475059\n ],\n [\n -111.43775939941406,\n 40.45373976275493\n ],\n [\n -111.4398193359375,\n 40.49709237269567\n ],\n [\n -111.4398193359375,\n 40.51797520038851\n ],\n [\n -111.43089294433594,\n 40.54772199417569\n ],\n [\n -111.41372680664061,\n 40.57276168240752\n ],\n [\n -111.40205383300781,\n 40.58579947707732\n ],\n [\n -111.37596130371094,\n 40.58997103470642\n ],\n [\n -111.34300231933592,\n 40.58840673108871\n ],\n [\n -111.31484985351562,\n 40.589449604232975\n ],\n [\n -111.31278991699219,\n 40.6113461833302\n ],\n [\n -111.34300231933592,\n 40.61343119773193\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"270","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5799db68e4b0589fa1c7ea07","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":643524,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schmidt, John C. 0000-0002-2988-3869 jcschmidt@usgs.gov","orcid":"https://orcid.org/0000-0002-2988-3869","contributorId":1983,"corporation":false,"usgs":true,"family":"Schmidt","given":"John","email":"jcschmidt@usgs.gov","middleInitial":"C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":643525,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Allred, Tyler M.","contributorId":173170,"corporation":false,"usgs":false,"family":"Allred","given":"Tyler","email":"","middleInitial":"M.","affiliations":[{"id":27172,"text":"Allred Restoration, Inc., Tremonton, UT","active":true,"usgs":false}],"preferred":false,"id":643526,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70174869,"text":"70174869 - 2016 - High spatio-temporal resolution observations of crater-lake temperatures at Kawah Ijen volcano, East Java, Indonesia","interactions":[],"lastModifiedDate":"2016-08-04T15:11:34","indexId":"70174869","displayToPublicDate":"2016-07-08T14:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1109,"text":"Bulletin of Volcanology","active":true,"publicationSubtype":{"id":10}},"title":"High spatio-temporal resolution observations of crater-lake temperatures at Kawah Ijen volcano, East Java, Indonesia","docAbstract":"

The crater lake of Kawah Ijen volcano, East Java, Indonesia, has displayed large and rapid changes in temperature at point locations during periods of unrest, but measurement techniques employed to-date have not resolved how the lake’s thermal regime has evolved over both space and time. We applied a novel approach for mapping and monitoring variations in crater-lake apparent surface (“skin”) temperatures at high spatial (~32 cm) and temporal (every two minutes) resolution at Kawah Ijen on 18 September 2014. We used a ground-based FLIR T650sc camera with digital and thermal infrared (TIR) sensors from the crater rim to collect (1) a set of visible imagery around the crater during the daytime and (2) a time series of co-located visible and TIR imagery at one location from pre-dawn to daytime. We processed daytime visible imagery with the Structure-from-Motion photogrammetric method to create a digital elevation model onto which the time series of TIR imagery was orthorectified and georeferenced. Lake apparent skin temperatures typically ranged from ~21 to 33oC. At two locations, apparent skin temperatures were ~ 4 and 7 oC less than in-situ lake temperature measurements at 1.5 and 5 m depth, respectively. These differences, as well as the large spatio-temporal variations observed in skin temperatures, were likely largely associated with atmospheric effects such as evaporative cooling of the lake surface and infrared absorption by water vapor and SO2. Calculations based on orthorectified TIR imagery thus yielded underestimates of volcanic heat fluxes into the lake, whereas volcanic heat fluxes estimated based on in-situ temperature measurements (68 to 111 MW) were likely more representative of Kawah Ijen in a quiescent state. The ground-based imaging technique should provide a valuable tool to continuously monitor crater-lake temperatures and contribute insight into the spatio-temporal evolution of these temperatures associated with volcanic activity.

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Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-07-08","publicationStatus":"PW","scienceBaseUri":"5790a181e4b030378fb47431","contributors":{"authors":[{"text":"Lewicki, Jennifer L. 0000-0003-1994-9104 jlewicki@usgs.gov","orcid":"https://orcid.org/0000-0003-1994-9104","contributorId":5071,"corporation":false,"usgs":true,"family":"Lewicki","given":"Jennifer","email":"jlewicki@usgs.gov","middleInitial":"L.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":642918,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Corentin Caudron","contributorId":172993,"corporation":false,"usgs":false,"family":"Corentin Caudron","affiliations":[{"id":27136,"text":"University of Cambridge","active":true,"usgs":false}],"preferred":false,"id":642919,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"van Hinsberg, Vincent","contributorId":172994,"corporation":false,"usgs":false,"family":"van Hinsberg","given":"Vincent","email":"","affiliations":[{"id":6646,"text":"McGill University","active":true,"usgs":false}],"preferred":false,"id":642920,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hilley, George","contributorId":147793,"corporation":false,"usgs":false,"family":"Hilley","given":"George","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":642921,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70175124,"text":"70175124 - 2016 - Geologic context of recurring slope lineae in Melas and Coprates Chasmata, Mars","interactions":[],"lastModifiedDate":"2018-11-01T14:48:59","indexId":"70175124","displayToPublicDate":"2016-07-07T14:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2317,"text":"Journal of Geophysical Research E: Planets","active":true,"publicationSubtype":{"id":10}},"title":"Geologic context of recurring slope lineae in Melas and Coprates Chasmata, Mars","docAbstract":"

One of the major Mars discoveries of recent years is the existence of recurring slope lineae (RSL), which suggests that liquid water occurs on or near the surface of Mars today. These dark and narrow features emerge from steep, rocky exposures and incrementally grow, fade, and reform on a seasonal basis and are detected in images from the High Resolution Imaging Science Experiment camera. RSL are known to occur at scattered midlatitude and equatorial sites with little spatial connection to one another. One major exception is the steep, low-albedo slopes of Melas and Coprates Chasmata, in Valles Marineris where RSL are detected among diverse geologic surfaces (e.g., bedrock and talus) and landforms (e.g., inselbergs and landslides). New images show topographic changes including sediment deposition on active RSL slopes. Midwall locations in Coprates and Melas appear to have more areally extensively abundant RSL and related fans as compared with other RSL sites found on Mars. Water budget estimates for regional RSL are on the order of 105 to 106 m3 of fluid, for depths of 10 to 100mm, and suggest that a significant amount of near-surface watermight be present. Many RSL are concentrated near local topographic highs, such as ridge crests or peaks, which is challenging to explain via groundwater or ice without a recharge mechanism. Collectively, results provide additional support for the notion that significant amounts of near-surface water can be found on Mars today and suggest that a widespread mechanism, possibly related to the atmosphere, is recharging RSL sources.

","language":"English","publisher":"American Geophysical Union","doi":"10.1002/2015JE004991","usgsCitation":"Chojnacki, M., McEwen, A., Dundas, C.M., Ojha, L., Urso, A., and Sutton, S., 2016, Geologic context of recurring slope lineae in Melas and Coprates Chasmata, Mars: Journal of Geophysical Research E: Planets, v. 121, p. 1-28, https://doi.org/10.1002/2015JE004991.","productDescription":"28 p.","startPage":"1","endPage":"28","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-071262","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":325844,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"121","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-07-07","publicationStatus":"PW","scienceBaseUri":"579c7e2be4b0589fa1ca11db","contributors":{"authors":[{"text":"Chojnacki, Matthew","contributorId":96576,"corporation":false,"usgs":true,"family":"Chojnacki","given":"Matthew","affiliations":[],"preferred":false,"id":644022,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McEwen, Alfred","contributorId":59723,"corporation":false,"usgs":true,"family":"McEwen","given":"Alfred","affiliations":[],"preferred":false,"id":644023,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dundas, Colin M. 0000-0003-2343-7224 cdundas@usgs.gov","orcid":"https://orcid.org/0000-0003-2343-7224","contributorId":2937,"corporation":false,"usgs":true,"family":"Dundas","given":"Colin","email":"cdundas@usgs.gov","middleInitial":"M.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":644021,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ojha, Lujendra","contributorId":64933,"corporation":false,"usgs":true,"family":"Ojha","given":"Lujendra","affiliations":[],"preferred":false,"id":644024,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Urso, Anna","contributorId":173270,"corporation":false,"usgs":false,"family":"Urso","given":"Anna","email":"","affiliations":[{"id":27205,"text":"U. Arizona","active":true,"usgs":false}],"preferred":false,"id":644025,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Sutton, Sarah","contributorId":173271,"corporation":false,"usgs":false,"family":"Sutton","given":"Sarah","affiliations":[{"id":27205,"text":"U. Arizona","active":true,"usgs":false}],"preferred":false,"id":644026,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70174288,"text":"70174288 - 2016 - Density-dependent home-range size revealed by spatially explicit capture–recapture","interactions":[],"lastModifiedDate":"2016-07-12T19:11:20","indexId":"70174288","displayToPublicDate":"2016-07-07T12:45:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1445,"text":"Ecography","active":true,"publicationSubtype":{"id":10}},"title":"Density-dependent home-range size revealed by spatially explicit capture–recapture","docAbstract":"

The size of animal home ranges often varies inversely with population density among populations of a species. This fact has implications for population monitoring using spatially explicit capture–recapture (SECR) models, in which both the scale of home-range movements σ and population density D usually appear as parameters, and both may vary among populations. It will often be appropriate to model a structural relationship between population-specific values of these parameters, rather than to assume independence. We suggest re-parameterizing the SECR model using kp = σp √Dp, where kp relates to the degree of overlap between home ranges and the subscript p distinguishes populations. We observe that kp is often nearly constant for populations spanning a range of densities. This justifies fitting a model in which the separate kp are replaced by the single parameter k and σp is a density-dependent derived parameter. Continuous density-dependent spatial variation in σ may also be modelled, using a scaled non-Euclidean distance between detectors and the locations of animals. We illustrate these methods with data from automatic photography of tigers (Panthera tigris) across India, in which the variation is among populations, from mist-netting of ovenbirds (Seiurus aurocapilla) in Maryland, USA, in which the variation is within a single population over time, and from live-trapping of brushtail possums (Trichosurus vulpecula) in New Zealand, modelling spatial variation within one population. Possible applications and limitations of the methods are discussed. A model in which kp is constant, while density varies, provides a parsimonious null model for SECR. The parameter k of the null model is a concise summary of the empirical relationship between home-range size and density that is useful in comparative studies. We expect deviations from this model, particularly the dependence of kp on covariates, to be biologically interesting.

","language":"English","publisher":"Blackwell Publishers","publisherLocation":"Oxford","doi":"10.1111/ecog.01511","usgsCitation":"Efford, M., Dawson, D.K., Jhala, Y., and Qureshi, Q., 2016, Density-dependent home-range size revealed by spatially explicit capture–recapture: Ecography, v. 39, no. 7, p. 676-688, https://doi.org/10.1111/ecog.01511.","productDescription":"13 p.","startPage":"676","endPage":"688","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-065283","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":324803,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"39","issue":"7","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2015-09-07","publicationStatus":"PW","scienceBaseUri":"577f6f1ae4b0ef4d2f45d42c","contributors":{"authors":[{"text":"Efford, M.G.","contributorId":13352,"corporation":false,"usgs":true,"family":"Efford","given":"M.G.","affiliations":[],"preferred":false,"id":641693,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dawson, Deanna K. ddawson@usgs.gov","contributorId":1257,"corporation":false,"usgs":true,"family":"Dawson","given":"Deanna","email":"ddawson@usgs.gov","middleInitial":"K.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":641690,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jhala, Y.V.","contributorId":96889,"corporation":false,"usgs":true,"family":"Jhala","given":"Y.V.","email":"","affiliations":[],"preferred":false,"id":641694,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Qureshi, Q.","contributorId":172713,"corporation":false,"usgs":false,"family":"Qureshi","given":"Q.","email":"","affiliations":[],"preferred":false,"id":641695,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70169855,"text":"70169855 - 2016 - A framework for assessing the feasibility of native fish conservation translocations: Applications to threatened bull trout","interactions":[],"lastModifiedDate":"2016-08-02T09:11:26","indexId":"70169855","displayToPublicDate":"2016-07-07T10:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2886,"text":"North American Journal of Fisheries Management","active":true,"publicationSubtype":{"id":10}},"title":"A framework for assessing the feasibility of native fish conservation translocations: Applications to threatened bull trout","docAbstract":"
There is an urgent need to consider more aggressive and direct interventions for the conservation of freshwater fishes that are threatened by invasive species, habitat loss, and climate change. Conservation introduction (moving a species outside its indigenous range to other areas where conditions are predicted to be more suitable) is one type of translocation strategy that fisheries managers can use to establish new conservation populations in areas of refugia. To date, however, there are few examples of successful conservation-based introductions. Many attempts fail to establish new populations—in part because environmental factors that might influence success are inadequately evaluated before the translocation is implemented. We developed a framework to assess the feasibility of rescuing threatened fish populations through translocation into historically unoccupied stream and lake habitats. The suitability of potential introduction sites was evaluated based on four major components: the recipient habitat, recipient community, donor population, and future threats. Specific questions were then developed to evaluate each major component. The final assessment was based on a scoring system that addressed each question by using criteria developed from characteristics representative of highly suitable habitats and populations. This framework was used to evaluate the proposed within-drainage translocation of three Bull Trout Salvelinus confluentus populations in Glacier National Park, Montana. Our results indicated that within-drainage translocation is a feasible strategy for conserving locally adapted populations of Bull Trout through the creation of new areas of refugia in Glacier National Park. The framework provides a flexible platform that can help managers make informed decisions for moving threatened fishes into new areas of refugia for conservation and recovery programs.
","language":"English","publisher":"American Fisheries Society","publisherLocation":"Lawrence, KS","doi":"10.1080/02755947.2016.1146177","usgsCitation":"Galloway, B.T., Muhlfeld, C.C., Guy, C.S., Downs, C.C., and Fredenberg, W.A., 2016, A framework for assessing the feasibility of native fish conservation translocations: Applications to threatened bull trout: North American Journal of Fisheries Management, v. 36, no. 4, p. 754-768, https://doi.org/10.1080/02755947.2016.1146177.","startPage":"754","endPage":"768","numberOfPages":"15","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-067117","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":470763,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://scholarworks.montana.edu/xmlui/handle/1/12673","text":"External Repository"},{"id":325894,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"36","issue":"4","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2016-07-07","publicationStatus":"PW","scienceBaseUri":"57a1c42ce4b006cb45552be4","contributors":{"authors":[{"text":"Galloway, Benjamin T.","contributorId":168290,"corporation":false,"usgs":false,"family":"Galloway","given":"Benjamin","email":"","middleInitial":"T.","affiliations":[{"id":5120,"text":"Montana State University, Department of Mathematical Sciences, Bozeman, MT 59717","active":true,"usgs":false}],"preferred":false,"id":625347,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"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":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":625346,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Guy, Christopher S. 0000-0002-9936-4781 cguy@usgs.gov","orcid":"https://orcid.org/0000-0002-9936-4781","contributorId":2876,"corporation":false,"usgs":true,"family":"Guy","given":"Christopher","email":"cguy@usgs.gov","middleInitial":"S.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":5062,"text":"Office of the Chief Scientist for Ecosystems","active":true,"usgs":true}],"preferred":true,"id":625348,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Downs, Christopher C.","contributorId":105067,"corporation":false,"usgs":true,"family":"Downs","given":"Christopher","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":625349,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fredenberg, Wade A.","contributorId":78860,"corporation":false,"usgs":true,"family":"Fredenberg","given":"Wade","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":625351,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70179390,"text":"70179390 - 2016 - Detection, prevalence, and transmission of avian hematozoa in waterfowl at the Arctic/sub-Arctic interface: co-infections, viral interactions, and sources of variation.","interactions":[],"lastModifiedDate":"2016-12-30T10:37:46","indexId":"70179390","displayToPublicDate":"2016-07-07T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3010,"text":"Parasites & Vectors","printIssn":"1756-3305","active":true,"publicationSubtype":{"id":10}},"title":"Detection, prevalence, and transmission of avian hematozoa in waterfowl at the Arctic/sub-Arctic interface: co-infections, viral interactions, and sources of variation.","docAbstract":"Background: The epidemiology of avian hematozoa at high latitudes is still not well understood, particularly in sub-Arctic and Arctic habitats, where information is limited regarding seasonality and range of transmission, co-infection dynamics with parasitic and viral agents, and possible fitness consequences of infection. Such information is important as climate warming may lead to northward expansion of hematozoa with unknown consequences to northern-breeding avian taxa, particularly populations that may be previously unexposed to blood parasites.\nMethods: We used molecular methods to screen blood samples and cloacal/oropharyngeal swabs collected from 1347 ducks of five species during May-August 2010, in interior Alaska, for the presence of hematozoa, Influenza A Virus (IAV), and IAV antibodies. Using models to account for imperfect detection of parasites, we estimated seasonal variation in prevalence of three parasite genera (Haemoproteus, Plasmodium, Leucocytozoon) and investigated how co-infection with parasites and viruses were related to the probability of infection.\n\nResults: We detected parasites from each hematozoan genus in adult and juvenile ducks of all species sampled. Seasonal patterns in detection and prevalence varied by parasite genus and species, age, and sex of duck hosts. The probabilities of infection for Haemoproteus and Leucocytozoon parasites were strongly positively correlated, but hematozoa infection was not correlated with IAV infection or serostatus. The probability of Haemoproteus infection was negatively related to body condition in juvenile ducks; relationships between Leucocytozoon infection and body condition varied among host species.\n\nConclusions: We present prevalence estimates for Haemoproteus, Leucocytozoon, and Plasmodium infections in waterfowl at the interface of the sub-Arctic and Arctic and provide evidence for local transmission of all three parasite genera. Variation in prevalence and molecular detection of hematozoa parasites in wild ducks is influenced by seasonal timing and a number of host traits. A positive correlation in co-infection of Leucocytozoon and Haemoproteus suggests that infection probability by parasites in one or both genera is enhanced by infection with the other, or that encounter rates of hosts and genus-specific vectors are correlated. Using size-adjusted mass as an index of host condition, we did not find evidence for strong deleterious consequences of hematozoa infection in wild ducks.","language":"English","publisher":"BioMed Central","doi":"10.1186/s13071-016-1666-3","usgsCitation":"Meixell, B.W., Arnold, T.W., Lindberg, M.S., Smith, M.M., Ramey, A.M., and Runstadler, J.A., 2016, Detection, prevalence, and transmission of avian hematozoa in waterfowl at the Arctic/sub-Arctic interface: co-infections, viral interactions, and sources of variation.: Parasites & Vectors, v. 9, no. 390, 18 p., https://doi.org/10.1186/s13071-016-1666-3.","productDescription":"18 p.","ipdsId":"IP-074072","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":470767,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1186/s13071-016-1666-3","text":"Publisher Index Page"},{"id":438594,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7QJ7FD2","text":"USGS data release","linkHelpText":"Morphology and Disease Information from Waterfowl, Interior Alaska, 2010"},{"id":332677,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":332668,"type":{"id":15,"text":"Index Page"},"url":"https://dx.doi.org/ 10.1186/s13071-016-1666-3"}],"volume":"9","issue":"390","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2016-07-07","publicationStatus":"PW","scienceBaseUri":"586781f8e4b0cd2dabe7c719","chorus":{"doi":"10.1186/s13071-016-1666-3","url":"http://dx.doi.org/10.1186/s13071-016-1666-3","publisher":"Springer Nature","authors":"Meixell Brandt W., Arnold Todd W., Lindberg Mark S., Smith Matthew M., Runstadler Jonathan A., Ramey Andrew M.","journalName":"Parasites & Vectors","publicationDate":"7/7/2016"},"contributors":{"authors":[{"text":"Meixell, Brandt W. 0000-0002-6738-0349 bmeixell@usgs.gov","orcid":"https://orcid.org/0000-0002-6738-0349","contributorId":138716,"corporation":false,"usgs":true,"family":"Meixell","given":"Brandt","email":"bmeixell@usgs.gov","middleInitial":"W.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":657031,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Arnold, Todd W.","contributorId":36058,"corporation":false,"usgs":false,"family":"Arnold","given":"Todd","email":"","middleInitial":"W.","affiliations":[{"id":12644,"text":"University of Minnesota, St. Paul","active":true,"usgs":false}],"preferred":false,"id":657046,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lindberg, Mark S.","contributorId":63292,"corporation":false,"usgs":false,"family":"Lindberg","given":"Mark","email":"","middleInitial":"S.","affiliations":[{"id":7211,"text":"University of Alaska, Fairbanks","active":true,"usgs":false}],"preferred":false,"id":657047,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Smith, Matthew M. 0000-0002-2259-5135 mmsmith@usgs.gov","orcid":"https://orcid.org/0000-0002-2259-5135","contributorId":5115,"corporation":false,"usgs":true,"family":"Smith","given":"Matthew","email":"mmsmith@usgs.gov","middleInitial":"M.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":657032,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ramey, Andrew M. 0000-0002-3601-8400 aramey@usgs.gov","orcid":"https://orcid.org/0000-0002-3601-8400","contributorId":1872,"corporation":false,"usgs":true,"family":"Ramey","given":"Andrew","email":"aramey@usgs.gov","middleInitial":"M.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":657033,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Runstadler, Jonathan A.","contributorId":24706,"corporation":false,"usgs":false,"family":"Runstadler","given":"Jonathan","email":"","middleInitial":"A.","affiliations":[{"id":12444,"text":"Massachusetts Institute of Technology","active":true,"usgs":false}],"preferred":false,"id":657048,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70175341,"text":"70175341 - 2016 - Experimental whole-lake increase of dissolved organic carbon concentration produces unexpected increase in crustacean zooplankton density","interactions":[],"lastModifiedDate":"2016-08-05T12:23:58","indexId":"70175341","displayToPublicDate":"2016-07-04T14:30:00","publicationYear":"2016","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":"Experimental whole-lake increase of dissolved organic carbon concentration produces unexpected increase in crustacean zooplankton density","docAbstract":"

The observed pattern of lake browning, or increased terrestrial dissolved organic carbon (DOC) concentration, across the northern hemisphere has amplified the importance of understanding how consumer productivity varies with DOC concentration. Results from comparative studies suggest these increased DOC concentrations may reduce crustacean zooplankton productivity due to reductions in resource quality and volume of suitable habitat. Although these spatial comparisons provide an expectation for the response of zooplankton productivity as DOC concentration increases, we still have an incomplete understanding of how zooplankton respond to temporal increases in DOC concentration within a single system. As such, we used a whole-lake manipulation, in which DOC concentration was increased from 8 to 11 mg L−1 in one basin of a manipulated lake, to test the hypothesis that crustacean zooplankton production should subsequently decrease. In contrast to the spatially derived expectation of sharp DOC-mediated decline, we observed a small increase in zooplankton densities in response to our experimental increase in DOC concentration of the treatment basin. This was due to significant increases in gross primary production and resource quality (lower seston carbon-to-phosphorus ratio; C:P). These results demonstrate that temporal changes in lake characteristics due to increased DOC may impact zooplankton in ways that differ from those observed in spatial surveys. We also identified significant interannual variability across our study region, which highlights potential difficulty in detecting temporal responses of organism abundances to gradual environmental change (e.g., browning).

","language":"English","publisher":"Wiley","doi":"10.1111/gcb.13260","collaboration":"Notre Dame University, McGill University","usgsCitation":"Kelly, P., Craig, N., Solomon, C.T., Weidel, B., Zwart, J., and Jones, S., 2016, Experimental whole-lake increase of dissolved organic carbon concentration produces unexpected increase in crustacean zooplankton density: Global Change Biology, v. 22, no. 8, p. 2766-2775, https://doi.org/10.1111/gcb.13260.","productDescription":"9 p.","startPage":"2766","endPage":"2775","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-068467","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":326132,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Michigan","otherGeospatial":"Long Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -83.43360900878906,\n 45.1907479300741\n ],\n [\n -83.44528198242188,\n 45.19195769867925\n ],\n [\n -83.44837188720702,\n 45.203812070185016\n ],\n [\n -83.45146179199219,\n 45.20889175910327\n ],\n [\n -83.46519470214844,\n 45.21542212118822\n ],\n [\n -83.47206115722656,\n 45.231623854757395\n ],\n [\n -83.49128723144531,\n 45.23911861682938\n ],\n [\n -83.51943969726562,\n 45.2398438639272\n ],\n [\n -83.5458755493164,\n 45.24105258851866\n ],\n [\n -83.5565185546875,\n 45.23452517023689\n ],\n [\n -83.55411529541016,\n 45.21832426364806\n ],\n [\n -83.52733612060547,\n 45.21808242410029\n ],\n [\n -83.5125732421875,\n 45.21977527933444\n ],\n [\n -83.50776672363281,\n 45.21711505562335\n ],\n [\n -83.4957504272461,\n 45.20840799874946\n ],\n [\n -83.48613739013672,\n 45.196796515952244\n ],\n [\n -83.47927093505858,\n 45.18687649773411\n ],\n [\n -83.45970153808594,\n 45.17453454979928\n ],\n [\n -83.44253540039062,\n 45.16170576909783\n ],\n [\n -83.42536926269531,\n 45.16025327223976\n ],\n [\n -83.41850280761719,\n 45.16775744075824\n ],\n [\n -83.4133529663086,\n 45.17453454979928\n ],\n [\n -83.4136962890625,\n 45.18711846996982\n ],\n [\n -83.43360900878906,\n 45.1907479300741\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"22","issue":"8","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2016-04-06","publicationStatus":"PW","scienceBaseUri":"57a5b8bbe4b0ebae89b788a6","contributors":{"authors":[{"text":"Kelly, Patrick T.","contributorId":69059,"corporation":false,"usgs":true,"family":"Kelly","given":"Patrick T.","affiliations":[],"preferred":false,"id":644780,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Craig, Nicola","contributorId":150803,"corporation":false,"usgs":false,"family":"Craig","given":"Nicola","email":"","affiliations":[{"id":6646,"text":"McGill University","active":true,"usgs":false}],"preferred":false,"id":644781,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Solomon, Christopher T.","contributorId":34014,"corporation":false,"usgs":false,"family":"Solomon","given":"Christopher","email":"","middleInitial":"T.","affiliations":[{"id":6646,"text":"McGill University","active":true,"usgs":false}],"preferred":false,"id":644782,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Weidel, Brian 0000-0001-6095-2773 bweidel@usgs.gov","orcid":"https://orcid.org/0000-0001-6095-2773","contributorId":2485,"corporation":false,"usgs":true,"family":"Weidel","given":"Brian","email":"bweidel@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":644779,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Zwart, Jacob A.","contributorId":173345,"corporation":false,"usgs":false,"family":"Zwart","given":"Jacob A.","affiliations":[{"id":16905,"text":"University of Notre Dame, Dept. of Biological Sciences, Notre Dame, IN, 46556, USA","active":true,"usgs":false}],"preferred":false,"id":644783,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Jones, Stuart E.","contributorId":22222,"corporation":false,"usgs":false,"family":"Jones","given":"Stuart E.","affiliations":[{"id":6966,"text":"Department of Biological Sciences, University of Notre Dame","active":true,"usgs":false}],"preferred":false,"id":644784,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70171019,"text":"70171019 - 2016 - Anadromous salmonids in the Delta: New science 2006–2016","interactions":[],"lastModifiedDate":"2018-09-25T11:05:20","indexId":"70171019","displayToPublicDate":"2016-07-01T11:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3331,"text":"San Francisco Estuary and Watershed Science","active":true,"publicationSubtype":{"id":10}},"title":"Anadromous salmonids in the Delta: New science 2006–2016","docAbstract":"
\n
\n
\n
\n

As juvenile salmon enter the Sacramento–SanJoaquin River Delta (“the Delta”) they disperse among its complex channel network where they are subject to channel-specific processes that affect their rate of migration, vulnerability to predation, feeding success, growth rates, and ultimately, survival. In the decades before 2006, tools available to quantify growth, dispersal, and survival of juvenile salmon in this complex channel network were limited.Fortunately, thanks to technological advances such as acoustic telemetry and chemical and structural otolith analysis, much has been learned over the past decade about the role of the Delta in the life cycle of juvenile salmon. Here, we review new science between 2006and 2016 that sheds light on how different life stages and runs of juvenile salmon grow, move, and survive in the complex channel network of the Delta. One of the most important advances during the past decade has been the widespread adoption of acoustic telemetry techniques. Use of telemetry has shed light on how survival varies among alternative migration routes and the proportion of fish that use each migration route. Chemical and structural analysis of otoliths has provided insights about when juveniles left their natal river and provided evidence of extended rearing in the brackish or saltwater regions of the Delta. New advancements in genetics now allow individuals captured by trawls to be assigned to specific runs. Detailed information about movement and survival in the Delta has spurred development of agent-based models of juvenile salmon that are coupled to hydrodynamic models. Although much has been learned, knowledge gaps remain about how very small juvenile salmon (fry and parr) use the Delta. Understanding how all life stages of juvenile salmon grow, rear, and survive in the Delta is critical for devising management strategies that support a diversity of life history strategies.

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","language":"English","publisher":"San Francisco Bay-Delta Science Consortium","publisherLocation":"Sacramento, CA","doi":"10.15447/sfews.2016v14iss2art7","usgsCitation":"Perry, R.W., Buchanan, R.A., Brandes, P., Burau, J.R., and Israel, J., 2016, Anadromous salmonids in the Delta: New science 2006–2016: San Francisco Estuary and Watershed Science, v. 14, no. 2, Article 7; 28 p., https://doi.org/10.15447/sfews.2016v14iss2art7.","productDescription":"Article 7; 28 p.","numberOfPages":"28","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-075447","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":552,"text":"San Francisco Bay-Delta","active":false,"usgs":true},{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":470773,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.15447/sfews.2016v14iss2art7","text":"Publisher Index Page"},{"id":325895,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Francisco Bay Delta","volume":"14","issue":"2","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2016-07-22","publicationStatus":"PW","scienceBaseUri":"57a1c42de4b006cb45552bf0","contributors":{"authors":[{"text":"Perry, Russell W. 0000-0003-4110-8619 rperry@usgs.gov","orcid":"https://orcid.org/0000-0003-4110-8619","contributorId":2820,"corporation":false,"usgs":true,"family":"Perry","given":"Russell","email":"rperry@usgs.gov","middleInitial":"W.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":629559,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Buchanan, Rebecca A.","contributorId":117624,"corporation":false,"usgs":true,"family":"Buchanan","given":"Rebecca","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":629560,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brandes, Patricia L.","contributorId":25834,"corporation":false,"usgs":true,"family":"Brandes","given":"Patricia L.","affiliations":[],"preferred":false,"id":629561,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Burau, Jon R. 0000-0002-5196-5035 jrburau@usgs.gov","orcid":"https://orcid.org/0000-0002-5196-5035","contributorId":1500,"corporation":false,"usgs":true,"family":"Burau","given":"Jon","email":"jrburau@usgs.gov","middleInitial":"R.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":629562,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Israel, Joshua A","contributorId":169428,"corporation":false,"usgs":false,"family":"Israel","given":"Joshua A","affiliations":[{"id":25508,"text":"Bureau of Reclamation, Bay-Delta Office, 801 I St., Suite 140, Sacramento, CA","active":true,"usgs":false}],"preferred":false,"id":629563,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70187246,"text":"70187246 - 2016 - Ungulate browsers promote herbaceous layer diversity in logged temperate forests","interactions":[],"lastModifiedDate":"2017-04-28T13:19:54","indexId":"70187246","displayToPublicDate":"2016-07-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Ungulate browsers promote herbaceous layer diversity in logged temperate forests","docAbstract":"

Ungulates are leading drivers of plant communities worldwide, with impacts linked to animal density, disturbance and vegetation structure, and site productivity. Many ecosystems have more than one ungulate species; however, few studies have specifically examined the combined effects of two or more species on plant communities. We examined the extent to which two ungulate browsers (moose [Alces americanus]) and white-tailed deer [Odocoileus virginianus]) have additive (compounding) or compensatory (opposing) effects on herbaceous layer composition and diversity, 5–6 years after timber harvest in Massachusetts, USA. We established three combinations of ungulates using two types of fenced exclosures – none (full exclosure), deer (partial exclosure), and deer + moose (control) in six replicated blocks. Species composition diverged among browser treatments, and changes were generally additive. Plant assemblages characteristic of closed canopy forests were less abundant and assemblages characteristic of open/disturbed habitats were more abundant in deer + moose plots compared with ungulate excluded areas. Browsing by deer + moose resulted in greater herbaceous species richness at the plot scale (169 m2) and greater woody species richness at the subplot scale (1 m2) than ungulate exclusion and deer alone. Browsing by deer + moose resulted in strong changes to the composition, structure, and diversity of forest herbaceous layers, relative to areas free of ungulates and areas browed by white-tailed deer alone. Our results provide evidence that moderate browsing in forest openings can promote both herbaceous and woody plant diversity. These results are consistent with the classic grazing-species richness curve, but have rarely been documented in forests.

","language":"English","publisher":"Wiley","doi":"10.1002/ece3.2223","usgsCitation":"Faison, E.K., DeStefano, S., Foster, D., Motzkin, G., and Rapp, J., 2016, Ungulate browsers promote herbaceous layer diversity in logged temperate forests: Ecology and Evolution, v. 6, no. 13, p. 4591-4602, https://doi.org/10.1002/ece3.2223.","productDescription":"12 p.","startPage":"4591","endPage":"4602","ipdsId":"IP-069428","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":470795,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.2223","text":"Publisher Index Page"},{"id":340616,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"6","issue":"13","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2016-06-12","publicationStatus":"PW","scienceBaseUri":"590454a4e4b022cee40dc23a","contributors":{"authors":[{"text":"Faison, Edward K.","contributorId":191559,"corporation":false,"usgs":false,"family":"Faison","given":"Edward","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":693489,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"DeStefano, Stephen 0000-0003-2472-8373 destef@usgs.gov","orcid":"https://orcid.org/0000-0003-2472-8373","contributorId":166706,"corporation":false,"usgs":true,"family":"DeStefano","given":"Stephen","email":"destef@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":false,"id":693104,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Foster, David R.","contributorId":149881,"corporation":false,"usgs":false,"family":"Foster","given":"David R.","affiliations":[{"id":16810,"text":"Harvard Univ.","active":true,"usgs":false}],"preferred":false,"id":693490,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Motzkin, Glenn","contributorId":191567,"corporation":false,"usgs":false,"family":"Motzkin","given":"Glenn","email":"","affiliations":[],"preferred":false,"id":693491,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rapp, Josh","contributorId":79757,"corporation":false,"usgs":true,"family":"Rapp","given":"Josh","email":"","affiliations":[],"preferred":false,"id":693492,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70191680,"text":"70191680 - 2016 - Effects of seasonal weather on breeding phenology and reproductive success of alpine ptarmigan in Colorado","interactions":[],"lastModifiedDate":"2017-10-17T16:20:32","indexId":"70191680","displayToPublicDate":"2016-07-01T00:00:00","publicationYear":"2016","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":"Effects of seasonal weather on breeding phenology and reproductive success of alpine ptarmigan in Colorado","docAbstract":"

Animal populations occurring at high elevations are often assumed to be in peril of extinctions or local extirpations due to elevational-dispersal limitations and thermoregulatory constraints as habitats change and warm. However, long-term monitoring of high-elevation populations is uncommon relative to those occurring at lower elevations, and evidence supporting this assumption is limited. We analyzed 45 years of reproductive data for two Colorado populations of white-tailed ptarmigan (Lagopus leucura), an alpine-endemic species with restricted distribution in western North America. Seasonal temperatures measured by the number of growing degree days warmed significantly at our study sites for pre-nesting, nesting, and brood-rearing seasonal periods (mean advance of 8 growing degree days per decade), and both populations advanced their reproductive phenology over the study period based on median hatch dates (median advance of 3.7 and 1.9 days per decade for the northern and southern sites, respectively). Reproductive performance measured by the number of chicks per hen declined significantly at one study site but not the other, and differences between sites may have been due to habitat degradation at one study area. Annual variability in chicks per hen was large at both sites but only weakly related to seasonal weather. An index of precipitation and temperature during the brood-rearing period was the best predictor for reproductive success with warm and dry conditions relating positively to number of chicks per hen. Our results provide evidence for two alpine ptarmigan populations that are remarkably invariant to fluctuations in seasonal weather with respect to reproductive success as measured by number of chicks per hen in the breeding population. These results are surprising given the general perception of alpine animal populations as being highly sensitive to warming temperatures.

","language":"English","publisher":"PLOS","doi":"10.1371/journal.pone.0158913","usgsCitation":"Wann, G.T., Aldridge, C.L., and Braun, C.E., 2016, Effects of seasonal weather on breeding phenology and reproductive success of alpine ptarmigan in Colorado: PLoS ONE, v. 11, no. 7, p. 1-16, https://doi.org/10.1371/journal.pone.0158913.","productDescription":"e0158913; 16 p.","startPage":"1","endPage":"16","ipdsId":"IP-066508","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":470799,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0158913","text":"Publisher Index Page"},{"id":346754,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","volume":"11","issue":"7","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2016-07-15","publicationStatus":"PW","scienceBaseUri":"59e71693e4b05fe04cd331b6","contributors":{"authors":[{"text":"Wann, Gregory T. 0000-0001-9076-7819 wanng@usgs.gov","orcid":"https://orcid.org/0000-0001-9076-7819","contributorId":3855,"corporation":false,"usgs":true,"family":"Wann","given":"Gregory","email":"wanng@usgs.gov","middleInitial":"T.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":713046,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Aldridge, Cameron L. 0000-0003-3926-6941 aldridgec@usgs.gov","orcid":"https://orcid.org/0000-0003-3926-6941","contributorId":191773,"corporation":false,"usgs":true,"family":"Aldridge","given":"Cameron","email":"aldridgec@usgs.gov","middleInitial":"L.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":false,"id":713047,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Braun, Clait E.","contributorId":59368,"corporation":false,"usgs":true,"family":"Braun","given":"Clait","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":713048,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70192682,"text":"70192682 - 2016 - Age, sex and social influences on adult survival in the cooperatively breeding Karoo Scrub-robin","interactions":[],"lastModifiedDate":"2017-11-08T14:48:54","indexId":"70192682","displayToPublicDate":"2016-07-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1494,"text":"Emu","active":true,"publicationSubtype":{"id":10}},"title":"Age, sex and social influences on adult survival in the cooperatively breeding Karoo Scrub-robin","docAbstract":"

Among cooperatively breeding species, helpers are hypothesised to increase the survival of breeders by reducing breeder workload in offspring care and increased group vigilance against predators. Furthermore, parental nepotism or other benefits of group living may provide a survival benefit to young that delay dispersal to help. We tested these hypotheses in the Karoo Scrub-robin (Cercotrichas coryphaeus), a long-lived, and facultative cooperatively breeding species in which male helpers make substantial contributions to the care of young. We found that annual breeder survival in the presence of helpers did not differ detectably from breeders without helpers or breeders that lost helpers. Furthermore, helpers did not gain a survival benefit from deferred breeding; apparent survival did not differ detectably between male helpers and male breeders followed from one year old. These results are consistent with other studies suggesting a lack of adult survival benefits among species where breeders do not substantially reduce workloads when helpers are present. They are also consistent with the hypothesis that males that delay dispersal make the ‘best of a bad job’ by helping on their natal territory to gain indirect fitness benefits when they are unable to obtain a territory vacancy nearby.

","language":"English","publisher":"CSIRO Publishing","doi":"10.1071/MU15076","usgsCitation":"Lloyd, P., Martin, T.E., Taylor, A., Braae, A., and Altwegg, R., 2016, Age, sex and social influences on adult survival in the cooperatively breeding Karoo Scrub-robin: Emu, v. 116, no. 4, p. 394-401, https://doi.org/10.1071/MU15076.","productDescription":"8 p.","startPage":"394","endPage":"401","ipdsId":"IP-067108","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":348481,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"116","issue":"4","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2017-02-17","publicationStatus":"PW","scienceBaseUri":"5a0425c1e4b0dc0b45b453f7","contributors":{"authors":[{"text":"Lloyd, Penn","contributorId":200179,"corporation":false,"usgs":false,"family":"Lloyd","given":"Penn","email":"","affiliations":[],"preferred":false,"id":721321,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Martin, Thomas E. 0000-0002-4028-4867 tmartin@usgs.gov","orcid":"https://orcid.org/0000-0002-4028-4867","contributorId":1208,"corporation":false,"usgs":true,"family":"Martin","given":"Thomas","email":"tmartin@usgs.gov","middleInitial":"E.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":716711,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Taylor, Andrew","contributorId":200183,"corporation":false,"usgs":false,"family":"Taylor","given":"Andrew","affiliations":[],"preferred":false,"id":721322,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Braae, Anne","contributorId":200184,"corporation":false,"usgs":false,"family":"Braae","given":"Anne","email":"","affiliations":[],"preferred":false,"id":721323,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Altwegg, Res","contributorId":171528,"corporation":false,"usgs":false,"family":"Altwegg","given":"Res","email":"","affiliations":[],"preferred":false,"id":721324,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70155923,"text":"70155923 - 2016 - Examination of the Reelfoot Rift Petroleum System, south-central United States, and the elements that remain for potential exploration and development","interactions":[],"lastModifiedDate":"2016-07-08T12:23:56","indexId":"70155923","displayToPublicDate":"2016-07-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5128,"text":"GCSSEPM Foundation Perkins-Rosen Research Conference Proceedings","active":true,"publicationSubtype":{"id":10}},"title":"Examination of the Reelfoot Rift Petroleum System, south-central United States, and the elements that remain for potential exploration and development","docAbstract":"

The Reelfoot rift is one segment of a late Proterozoic(?) to early Paleozoic intracontinental rift complex in the south-central United States. The rift complex is situated beneath Mesozoic to Cenozoic strata of the Mississippi embayment of southeastern Missouri, northeastern Arkansas, and western Tennessee and Kentucky. The rift portion of the stratigraphic section consists primarily of synrift Cambrian and Ordovician strata, capped by a postrift sag succession of Late Ordovician to Cenozoic age. Potential synrift source rocks have been identified in the Cambrian Elvins Shale. Thermal maturity of Paleozoic strata within the rift ranges from the oil window to the dry gas window. Petroleum generation in Elvins source rocks likely occurred during the middle to late Paleozoic. Upper Cretaceous sedimentary rocks unconformably overlie various Paleozoic units and define the likely upper boundary of the petroleum system.

\n

No production has been established in the Reel-foot rift. However, at least nine of 22 exploratory wells have reported petroleum shows, mainly gas shows with some asphalt or solid hydrocarbon residue. Regional seismic profiling shows the presence of two large inversion structures (Blytheville arch and Pascola arch). The Blytheville arch is marked by a core of structurally thickened Elvins Shale, whereas the Pascola arch reflects the structural uplift of a portion of the entire rift basin. Structural uplift and faulting within the Reelfoot rift since the late Paleozoic appear to have disrupted older conventional hydrocarbon traps and likely spilled any potential conventional petroleum accumulations. The remaining potential resources within the Reelfoot rift are likely shale gas accumulations within the Elvins Shale; however, reservoir continuity and porosity as well as pervasive faulting appear to be significant future challenges for explorers and drillers.

","language":"English","publisher":"GCSSEPM Foundation","doi":"10.5724/gcs.15.34.0345","usgsCitation":"Coleman, J.L., and Pratt, T.L., 2016, Examination of the Reelfoot Rift Petroleum System, south-central United States, and the elements that remain for potential exploration and development: GCSSEPM Foundation Perkins-Rosen Research Conference Proceedings, v. 34, p. 345-371, https://doi.org/10.5724/gcs.15.34.0345.","productDescription":"27 p.","startPage":"345","endPage":"371","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-067310","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":324921,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"34","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2015-12-01","publicationStatus":"PW","scienceBaseUri":"5780ceb6e4b0811616822324","contributors":{"authors":[{"text":"Coleman, James L. jlcoleman@usgs.gov","contributorId":141060,"corporation":false,"usgs":true,"family":"Coleman","given":"James","email":"jlcoleman@usgs.gov","middleInitial":"L.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":566897,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pratt, Thomas L. 0000-0003-3131-3141 tpratt@usgs.gov","orcid":"https://orcid.org/0000-0003-3131-3141","contributorId":3279,"corporation":false,"usgs":true,"family":"Pratt","given":"Thomas","email":"tpratt@usgs.gov","middleInitial":"L.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":566898,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70155922,"text":"70155922 - 2016 - Geology and hydrocarbon potential of the Hartford-Deerfield Basin, Connecticut and Massachusetts","interactions":[],"lastModifiedDate":"2016-07-08T12:05:38","indexId":"70155922","displayToPublicDate":"2016-07-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5128,"text":"GCSSEPM Foundation Perkins-Rosen Research Conference Proceedings","active":true,"publicationSubtype":{"id":10}},"title":"Geology and hydrocarbon potential of the Hartford-Deerfield Basin, Connecticut and Massachusetts","docAbstract":"

The Hartford-Deerfield basin, a Late Triassic to Early Jurassic rift basin located in central Connecticut and Massachusetts, is the northernmost basin of the onshore Mesozoic rift basins in the eastern United States. The presence of asphaltic petroleum in outcrops indicates that at least one active petroleum system has existed within the basin. However, to-date oil and gas wells have not been drilled in the basin to test any type of petroleum trap. There are good to excellent quality source rocks (up to 3.8% present day total organic carbon) within the Jurassic East Berlin and Portland formations. While these source rock intervals are fairly extensive and at peak oil to peak gas stages of maturity, individual source rock beds are relatively thin (typically less than 1 m) based solely on outcrop observations. Potential reservoir rocks within the Hartford-Deerfield basin are arkosic conglomerates, pebbly sandstones, and finer grained sandstones, shales, siltstones, and fractured igneous rocks of the Triassic New Haven and Jurassic East Berlin and Portland formations (and possibly other units). Sandstone porosity data from 75 samples range from less than 1% to 21%, with a mean of 5%. Permeability is equally low, except around joints, fractures, and faults. Seals are likely to be unfractured intra-formational shales and tight igneous bodies. Maturation, generation, and expulsion likely occurred during the late synrift period (Early Jurassic) accentuated by an increase in local geothermal gradient, igneous intrusions, and hydrothermal fluid circulation. Migration pathways were likely along syn- and postrift faults and fracture zones. Petroleum resources, if present, are probably unconventional (continuous) accumulations as conventionally accumulated petroleum is likely not present in significant volumes.

","language":"English","publisher":"GCSSEPM Foundation","doi":"10.5724/gcs.15.34.0195","usgsCitation":"Coleman, J.L., 2016, Geology and hydrocarbon potential of the Hartford-Deerfield Basin, Connecticut and Massachusetts: GCSSEPM Foundation Perkins-Rosen Research Conference Proceedings, v. 34, p. 195-214, https://doi.org/10.5724/gcs.15.34.0195.","productDescription":"20 p.","startPage":"195","endPage":"214","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-067309","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":324918,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Connecticut, Massachusetts","otherGeospatial":"Hartford-Deerfield Basin","volume":"34","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2015-12-01","publicationStatus":"PW","scienceBaseUri":"5780ceb7e4b0811616822350","contributors":{"authors":[{"text":"Coleman, James L. jlcoleman@usgs.gov","contributorId":141060,"corporation":false,"usgs":true,"family":"Coleman","given":"James","email":"jlcoleman@usgs.gov","middleInitial":"L.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":566896,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70179387,"text":"70179387 - 2016 - A point mutation in the polymerase protein PB2 allows a reassortant H9N2 influenza isolate of wild-bird origin to replicate in human cells.","interactions":[],"lastModifiedDate":"2016-12-30T10:49:18","indexId":"70179387","displayToPublicDate":"2016-07-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1988,"text":"Infection, Genetics and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"A point mutation in the polymerase protein PB2 allows a reassortant H9N2 influenza isolate of wild-bird origin to replicate in human cells.","docAbstract":"H9N2 influenza A viruses are on the list of potentially pandemic subtypes. Therefore, it is important to understand how genomic reassortment and genetic polymorphisms affect phenotypes of H9N2 viruses circulating in the wild bird reservoir. A comparative genetic analysis of North American H9N2 isolates of wild bird origin identified a naturally occurring reassortant virus containing gene segments derived from both North American and Eurasian lineage ancestors. The PB2 segment of this virus encodes 10 amino acid changes that distinguish it from other H9 strains circulating in North America. G590S, one of the 10 amino acid substitutions observed, was present in ~ 12% of H9 viruses worldwide. This mutation combined with R591 has been reported as a marker of pathogenicity for human pandemic 2009 H1N1 viruses. Screening by polymerase reporter assay of all the natural polymorphisms at these two positions identified G590/K591 and S590/K591 as the most active, with the highest polymerase activity recorded for the SK polymorphism. Rescued viruses containing these two polymorphic combinations replicated more efficiently in MDCK cells and they were the only ones tested that were capable of establishing productive infection in NHBE cells. A global analysis of all PB2 sequences identified the K591 signature in six viral HA/NA subtypes isolated from several hosts in seven geographic locations. Interestingly, introducing the K591 mutation into the PB2 of a human-adapted H3N2 virus did not affect its polymerase activity. Our findings demonstrate that a single point mutation in the PB2 of a low pathogenic H9N2 isolate could have a significant effect on viral phenotype and increase its propensity to infect mammals. However, this effect is not universal, warranting caution in interpreting point mutations without considering protein sequence context.","language":"English","publisher":"Elsevier ","doi":"10.1016/j.meegid.2016.04.011","usgsCitation":"Hussein, I.T., Ma, E.J., Meixell, B.W., Hill, N., Lindberg, M.S., Albrecht, R.A., Bahl, J., and Runstadler, J.A., 2016, A point mutation in the polymerase protein PB2 allows a reassortant H9N2 influenza isolate of wild-bird origin to replicate in human cells.: Infection, Genetics and Evolution, v. 41, p. 279-288, https://doi.org/10.1016/j.meegid.2016.04.011.","productDescription":"10 p.","startPage":"279","endPage":"288","ipdsId":"IP-071158","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":470788,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://hdl.handle.net/1721.1/133904","text":"External Repository"},{"id":332680,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"41","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"586781f8e4b0cd2dabe7c71b","contributors":{"authors":[{"text":"Hussein, Islam T.M.","contributorId":177787,"corporation":false,"usgs":false,"family":"Hussein","given":"Islam","email":"","middleInitial":"T.M.","affiliations":[],"preferred":false,"id":657049,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ma, Eric J.","contributorId":177788,"corporation":false,"usgs":false,"family":"Ma","given":"Eric","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":657050,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Meixell, Brandt W. 0000-0002-6738-0349 bmeixell@usgs.gov","orcid":"https://orcid.org/0000-0002-6738-0349","contributorId":138716,"corporation":false,"usgs":true,"family":"Meixell","given":"Brandt","email":"bmeixell@usgs.gov","middleInitial":"W.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":657020,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hill, Nichola J.","contributorId":30342,"corporation":false,"usgs":true,"family":"Hill","given":"Nichola J.","affiliations":[],"preferred":false,"id":657051,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lindberg, Mark S.","contributorId":63292,"corporation":false,"usgs":false,"family":"Lindberg","given":"Mark","email":"","middleInitial":"S.","affiliations":[{"id":7211,"text":"University of Alaska, Fairbanks","active":true,"usgs":false}],"preferred":false,"id":657052,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Albrecht, Randy A.","contributorId":177789,"corporation":false,"usgs":false,"family":"Albrecht","given":"Randy","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":657053,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bahl, Justin","contributorId":171803,"corporation":false,"usgs":false,"family":"Bahl","given":"Justin","affiliations":[{"id":26950,"text":"University of Texas School of Public Health, 1200 Pressler Street, Houston, TX 77030, USA","active":true,"usgs":false}],"preferred":false,"id":657054,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Runstadler, Jonathan A.","contributorId":24706,"corporation":false,"usgs":false,"family":"Runstadler","given":"Jonathan","email":"","middleInitial":"A.","affiliations":[{"id":12444,"text":"Massachusetts Institute of Technology","active":true,"usgs":false}],"preferred":false,"id":657055,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70187758,"text":"70187758 - 2016 - Preface: Impacts of extreme climate events and disturbances on carbon dynamics","interactions":[],"lastModifiedDate":"2017-05-17T10:54:46","indexId":"70187758","displayToPublicDate":"2016-07-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1011,"text":"Biogeosciences","active":true,"publicationSubtype":{"id":10}},"title":"Preface: Impacts of extreme climate events and disturbances on carbon dynamics","docAbstract":"

The impacts of extreme climate events and disturbances (ECE&D) on the carbon cycle have received growing attention in recent years. This special issue showcases a collection of recent advances in understanding the impacts of ECE&D on carbon cycling. Notable advances include quantifying how harvesting activities impact forest structure, carbon pool dynamics, and recovery processes; observed drastic increases of the concentrations of dissolved organic carbon and dissolved methane in thermokarst lakes in western Siberia during a summer warming event; disentangling the roles of herbivores and fire on forest carbon dioxide flux; direct and indirect impacts of fire on the global carbon balance; and improved atmospheric inversion of regional carbon sources and sinks by incorporating disturbances. Combined, studies herein indicate several major research needs. First, disturbances and extreme events can interact with one another, and it is important to understand their overall impacts and also disentangle their effects on the carbon cycle. Second, current ecosystem models are not skillful enough to correctly simulate the underlying processes and impacts of ECE&D (e.g., tree mortality and carbon consequences). Third, benchmark data characterizing the timing, location, type, and magnitude of disturbances must be systematically created to improve our ability to quantify carbon dynamics over large areas. Finally, improving the representation of ECE&D in regional climate/earth system models and accounting for the resulting feedbacks to climate are essential for understanding the interactions between climate and ecosystem dynamics.

","language":"English","publisher":"European Geosciences Union","doi":"10.5194/bg-13-3665-2016","usgsCitation":"Xiao, J., Liu, S., and Stoy, P., 2016, Preface: Impacts of extreme climate events and disturbances on carbon dynamics: Biogeosciences, v. 13, p. 3665-3675, https://doi.org/10.5194/bg-13-3665-2016.","productDescription":"11 p.","startPage":"3665","endPage":"3675","ipdsId":"IP-069417","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":470800,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/bg-13-3665-2016","text":"Publisher Index Page"},{"id":341425,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"13","noUsgsAuthors":false,"publicationDate":"2016-06-22","publicationStatus":"PW","scienceBaseUri":"593e25bce4b0764e6c61b73b","contributors":{"authors":[{"text":"Xiao, Jingfeng","contributorId":66998,"corporation":false,"usgs":true,"family":"Xiao","given":"Jingfeng","email":"","affiliations":[],"preferred":false,"id":695505,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"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":695506,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stoy, Paul C.","contributorId":60860,"corporation":false,"usgs":true,"family":"Stoy","given":"Paul C.","affiliations":[],"preferred":false,"id":695507,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70182781,"text":"70182781 - 2016 - The statistical power to detect cross-scale interactions at macroscales","interactions":[],"lastModifiedDate":"2017-03-01T12:46:23","indexId":"70182781","displayToPublicDate":"2016-07-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"The statistical power to detect cross-scale interactions at macroscales","docAbstract":"

Macroscale studies of ecological phenomena are increasingly common because stressors such as climate and land-use change operate at large spatial and temporal scales. Cross-scale interactions (CSIs), where ecological processes operating at one spatial or temporal scale interact with processes operating at another scale, have been documented in a variety of ecosystems and contribute to complex system dynamics. However, studies investigating CSIs are often dependent on compiling multiple data sets from different sources to create multithematic, multiscaled data sets, which results in structurally complex, and sometimes incomplete data sets. The statistical power to detect CSIs needs to be evaluated because of their importance and the challenge of quantifying CSIs using data sets with complex structures and missing observations. We studied this problem using a spatially hierarchical model that measures CSIs between regional agriculture and its effects on the relationship between lake nutrients and lake productivity. We used an existing large multithematic, multiscaled database, LAke multiscaled GeOSpatial, and temporal database (LAGOS), to parameterize the power analysis simulations. We found that the power to detect CSIs was more strongly related to the number of regions in the study rather than the number of lakes nested within each region. CSI power analyses will not only help ecologists design large-scale studies aimed at detecting CSIs, but will also focus attention on CSI effect sizes and the degree to which they are ecologically relevant and detectable with large data sets.

","language":"English","publisher":"Wiley","doi":"10.1002/ecs2.1417","usgsCitation":"Wagner, T., Fergus, C.E., Stow, C., Cheruvelil, K.S., and Soranno, P.A., 2016, The statistical power to detect cross-scale interactions at macroscales: Ecosphere, v. 7, no. 7, HTML document , https://doi.org/10.1002/ecs2.1417.","productDescription":"HTML document ","ipdsId":"IP-071692","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":470783,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.1417","text":"Publisher Index Page"},{"id":336753,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"7","issue":"7","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2016-07-28","publicationStatus":"PW","scienceBaseUri":"58b7eba8e4b01ccd5500bb1b","contributors":{"authors":[{"text":"Wagner, Tyler 0000-0003-1726-016X twagner@usgs.gov","orcid":"https://orcid.org/0000-0003-1726-016X","contributorId":1050,"corporation":false,"usgs":true,"family":"Wagner","given":"Tyler","email":"twagner@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":673735,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fergus, C. Emi","contributorId":150608,"corporation":false,"usgs":false,"family":"Fergus","given":"C.","email":"","middleInitial":"Emi","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":680427,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stow, Craig A.","contributorId":49733,"corporation":false,"usgs":true,"family":"Stow","given":"Craig A.","affiliations":[],"preferred":false,"id":680428,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cheruvelil, Kendra S.","contributorId":172029,"corporation":false,"usgs":false,"family":"Cheruvelil","given":"Kendra","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":680429,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Soranno, Patricia A.","contributorId":172104,"corporation":false,"usgs":false,"family":"Soranno","given":"Patricia","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":680430,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ]}