Our current understanding of the relationship between imperiled species and forest management can benefit from global positioning system (GPS) technologies. Fauna of lateseral stage forests have historically been difficult to detect and track in rugged terrain, leading to challenges in movement characterization and conservation. We investigated movement of California Spotted Owls (Strix occidentalis occidentalis) using automated GPS loggers affixed to 15 owls in the northern Sierra Nevada, California. We used >17,000 locations from individual owls to characterize homerange size, movement distances, and roosting and foraging habitat selection at four spatio-temporal scales (landscape, home range, foray, nightly) during the breeding season (April–August). Additionally, we assessed owl use of Protected Activity Centers (PACs), which are designated by the U.S.D.A. Forest Service to protect nesting and roosting habitat. Our results corroborated some previous findings about habitat requirements of California Spotted Owls, while also revealing new nuances in space use and habitat selection. Roosting and foraging owls selected stands with high canopy cover and large trees at multiple spatio-temporal scales, with foraging owls showing strongest selection at the largest (landscape) scale investigated. Although owls selected for PACs while foraging and roosting, PACs protected less than one quarter of foraging space use (volume of use) and fewer than half of observed roosts during the breeding season. Female owl home ranges were double the size of male home ranges, and distances travelled from the nest by females were 1.3 times greater than distances travelled by males, with non-breeding females travelling farthest and visiting up to six PACs during a single breeding season. Foraying behavior of this sort has not been documented previously in California Spotted Owls. Our findings support protection of later seral stage forest attributes for roosting and foraging California Spotted Owls. Given their selection for later seral forest attributes, strongest evidence of foraging habitat selection at the landscape scale, long distances travelled by owls and limited habitat protection afforded by PACs, habitat connectivity across the landscape is likely an important component for owl conservation, and distribution of current protected areas may be inadequate for this wide-ranging species.
The Atastra Creek siliceous hot spring deposit, or sinter, occurs in the Paramount-Bald Peak alteration zone, due north of the Bodie precious metals mining district in the Miocene Bodie Hills volcanic field, California and Nevada, U.S.A. Distinctive features include its geomorphically intact geyser vent mounds, the presence of growth-fault-stepped sinter terraces that developed westward along a NNW trending fault, and atypical Hg, Sb and As concentrations. High-temperature (>75 °C), subaerial, proximal apron sinter occurs in two settings – (1) radiating botryoidal geyserite in vent mounds and (2) bedded geyserite (columnar, nodular, size-sorted geyser eggs) intercalated with mid- to low-temperature (<60 °C), middle to distal apron terrace sinter. The active geyser vent mounds migrated from south to north across the apron terrace through time. A newly recognized, visually striking type of sinter – termed silica infiltrate herein – formed directly beneath the subaerial geyserite deposits. It is characterized by mainly parallel, thin, irregular beds of white silica with narrow borders of dark blue-gray silica, as well as swirly to globular white silica, all chaotically linked together by silica ‘necks’ and ‘bridges’. The silica infiltrate permeates the pre-existing sinter, and is interpreted to represent super-heated fluid injections into the immediately overlying geyser vent mounds and pools. The adjacent sinter sheets preserve fluid-flow directions of warm-water channels that traversed the discharge apron, including microbial streamer fabric and wavy laminated sinter with flattened bubbles. More distal sinter textures are recorded by rimmed terracettes with mammillated and palisade microbial fabrics and rare, warm pool-related stromatolites. However, plants are absent, probably due to the high metalloids, in particular As. Post-depositional events include an inferred hydrothermal eruption breccia and an interpreted drop in the water table accompanied by incursion of steam acid condensate, as evidenced by pervasive hydrothermal alteration of the Atastra Creek deposits. Hence, the well-exposed sedimentary facies distributions, well-preserved geomorphology, and stratigraphic and structural relationships together allow an unusually complete, paleoenvironmental reconstruction of the Atastra Creek paleohydrothermal deposit.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jvolgeores.2018.12.006","usgsCitation":"Campbell, K.A., Guido, D.M., John, D.A., Vikre, P., Rhys, D., and Hamilton, A., 2019, The Miocene Atastra Creek sinter (Bodie Hills volcanic field, California and Nevada): 4D evolution of a geomorphically intact siliceous hot spring deposit: Journal of Volcanology and Geothermal Research, v. 370, p. 65-81, https://doi.org/10.1016/j.jvolgeores.2018.12.006.","productDescription":"17 p.","startPage":"65","endPage":"81","ipdsId":"IP-102174","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":502590,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/11336/104267","text":"External Repository"},{"id":426119,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"370","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Campbell, Kathleen A. 0000-0002-4815-2519","orcid":"https://orcid.org/0000-0002-4815-2519","contributorId":334434,"corporation":false,"usgs":false,"family":"Campbell","given":"Kathleen","email":"","middleInitial":"A.","affiliations":[{"id":38833,"text":"University of Auckland","active":true,"usgs":false}],"preferred":false,"id":895630,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Guido, Diego M. 0000-0003-4696-5644","orcid":"https://orcid.org/0000-0003-4696-5644","contributorId":334435,"corporation":false,"usgs":false,"family":"Guido","given":"Diego","email":"","middleInitial":"M.","affiliations":[{"id":80146,"text":"Universidad Nacional de La Plata, La Plata, Argentina","active":true,"usgs":false}],"preferred":false,"id":895631,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"John, David A. 0000-0001-7977-9106 djohn@usgs.gov","orcid":"https://orcid.org/0000-0001-7977-9106","contributorId":1748,"corporation":false,"usgs":true,"family":"John","given":"David","email":"djohn@usgs.gov","middleInitial":"A.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":895632,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Vikre, Peter 0000-0001-7895-5972","orcid":"https://orcid.org/0000-0001-7895-5972","contributorId":203922,"corporation":false,"usgs":true,"family":"Vikre","given":"Peter","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":895633,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rhys, David","contributorId":334437,"corporation":false,"usgs":false,"family":"Rhys","given":"David","email":"","affiliations":[{"id":12586,"text":"Consultant","active":true,"usgs":false}],"preferred":false,"id":895634,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hamilton, Ayrton","contributorId":334438,"corporation":false,"usgs":false,"family":"Hamilton","given":"Ayrton","email":"","affiliations":[{"id":38833,"text":"University of Auckland","active":true,"usgs":false}],"preferred":false,"id":895635,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70263892,"text":"70263892 - 2019 - An investigation of seismicity induced by hydraulic fracturing in the Sichuan basin of China based on data from a temporary seismic network","interactions":[],"lastModifiedDate":"2025-02-27T15:35:39.361512","indexId":"70263892","displayToPublicDate":"2019-01-15T00:00:00","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"An investigation of seismicity induced by hydraulic fracturing in the Sichuan basin of China based on data from a temporary seismic network","docAbstract":"Hydraulic fracturing has been inferred to trigger the majority of injection‐induced seismicity in the Zhaotong and Changning shale gas field, Sichuan basin of China, in contrast to the Midwestern United States, where massive wastewater disposal has been the dominant triggering mechanism. More than 15,000 earthquakes, with magnitudes ranging up to Mw 4.7, were recorded by a temporary network in the Sichuan basin for three years, with a completeness magnitude of ML 1.1. A catalog of earthquakes relocated with code tomoDD, combined with comprehensive injection data during an eight day period, shows that the earthquakes were highly correlated spatiotemporally with hydraulic fracturing activities mostly from a single well pad. Three ML≥4.0 events occurred during hydraulic fracturing operations from 12 to 19 January 2017, followed by the fourth and largest event, with moment magnitude (Mw) 4.7, on 28 January. The hypocenters of the four largest events were located in dolomite of Cambrian age, between a shale gas reservoir and the top of the crystalline basement rocks. This was found to be similar to 60% of the smaller earthquakes in this cluster, at depths from 2.5 to 4.0 km.
","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120180310","usgsCitation":"Meng, L., McGarr, A.F., Zhou, L., and Zang, Y., 2019, An investigation of seismicity induced by hydraulic fracturing in the Sichuan basin of China based on data from a temporary seismic network: Bulletin of the Seismological Society of America, v. 109, no. 1, p. 348-357, https://doi.org/10.1785/0120180310.","productDescription":"10 p.","startPage":"348","endPage":"357","ipdsId":"IP-101593","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":482559,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"China","otherGeospatial":"Sichuan 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Lingyuan 0000-0001-7267-7625","orcid":"https://orcid.org/0000-0001-7267-7625","contributorId":351561,"corporation":false,"usgs":true,"family":"Meng","given":"Lingyuan","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":928925,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McGarr, Arthur F. 0000-0001-9769-4093 mcgarr@usgs.gov","orcid":"https://orcid.org/0000-0001-9769-4093","contributorId":3178,"corporation":false,"usgs":true,"family":"McGarr","given":"Arthur","email":"mcgarr@usgs.gov","middleInitial":"F.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":928926,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Zhou, Longquan","contributorId":351562,"corporation":false,"usgs":false,"family":"Zhou","given":"Longquan","affiliations":[{"id":84008,"text":"China Earthquake Networks Center","active":true,"usgs":false}],"preferred":false,"id":928927,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Zang, Yang","contributorId":351563,"corporation":false,"usgs":false,"family":"Zang","given":"Yang","affiliations":[{"id":84008,"text":"China Earthquake Networks Center","active":true,"usgs":false}],"preferred":false,"id":928928,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70202670,"text":"70202670 - 2019 - Vertical habitat use of adult Walleye conflicts with expectations from fishery-independent surveys","interactions":[],"lastModifiedDate":"2019-06-18T10:58:04","indexId":"70202670","displayToPublicDate":"2019-01-14T14:16:10","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3624,"text":"Transactions of the American Fisheries Society","active":true,"publicationSubtype":{"id":10}},"title":"Vertical habitat use of adult Walleye conflicts with expectations from fishery-independent surveys","docAbstract":"Stock assessments of Walleyes Sander vitreus in Lake Erie rely on a combination of suspended and bottom overnight gill‐net surveys to provide population and demographic information. However, the assumption that Walleyes undertake diel vertical migrations and become available to the suspended gill nets at night has never been validated. To understand how vertical habitat use affects the availability of Walleyes to fishery‐independent surveys, we compared individual behaviors observed by means of acoustic depth telemetry tags (20 individuals; 2013–2016) with catches in paired suspended and bottom gill‐net sets (273 paired sets; 2013–2016) used by management agencies. In contrast to our expectations and observations in other lakes, the mean depths for Walleyes most often occurred in the lower one‐half to one‐third of the water column, and at lake depths <25 m the fish tended to be close to the bottom. The relationship between fish and lake depth was dependent on year and season. At lake depths >15 m, Walleyes were found at shallower depths during stratified periods (i.e., summer) than during unstratified periods (autumn). They were also found at shallower depths in 2015 and 2016 than in 2013 and 2014. In paired autumn gill‐net surveys, (1) the overall proportion of Walleye catch was nearly equal in suspended and bottom gill nets and (2) the proportion of the catch in suspended gill nets declined with fish length. The pattern of decline was dependent on how deep the suspended net was fished and the year in which the data were collected. These results provide evidence that the suspended gill‐net surveys currently being used to assess Walleye demographics in Lake Erie are biased toward the capture small Walleyes, while bottom nets are biased toward the capture of large ones. Future telemetry investigations will be needed to understand whether these biases reflect differences in the depth of habitat between small and large Walleyes.","language":"English","doi":"10.1002/tafs.10150","usgsCitation":"Ann Marie Gorman, Kraus, R.T., Gutowsky, L., Vandergoot, C., Yingming Zhao, Knight, C., Faust, M., Hayden, T., and Charles Krueger, 2019, Vertical habitat use of adult Walleye conflicts with expectations from fishery-independent surveys: Transactions of the American Fisheries Society, v. 148, no. 3, p. 592-604, https://doi.org/10.1002/tafs.10150.","productDescription":"13 p.","startPage":"592","endPage":"604","ipdsId":"IP-097146","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":467995,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/tafs.10150","text":"Publisher Index Page"},{"id":362144,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Lake Erie","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -84.19921875,\n 41.27780646738183\n ],\n [\n -78.75,\n 41.27780646738183\n ],\n [\n -78.75,\n 43.068887774169625\n ],\n [\n -84.19921875,\n 43.068887774169625\n ],\n [\n -84.19921875,\n 41.27780646738183\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"148","issue":"3","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationDate":"2019-03-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Ann Marie Gorman","contributorId":214228,"corporation":false,"usgs":false,"family":"Ann Marie Gorman","affiliations":[{"id":16232,"text":"Ohio Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":759401,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kraus, Richard T. 0000-0003-4494-1841 rkraus@usgs.gov","orcid":"https://orcid.org/0000-0003-4494-1841","contributorId":2609,"corporation":false,"usgs":true,"family":"Kraus","given":"Richard","email":"rkraus@usgs.gov","middleInitial":"T.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":759400,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gutowsky, Lee","contributorId":214229,"corporation":false,"usgs":false,"family":"Gutowsky","given":"Lee","email":"","affiliations":[{"id":16762,"text":"Ontario Ministry of Natural Resources and Forestry","active":true,"usgs":false}],"preferred":false,"id":759402,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Vandergoot, Christopher 0000-0003-4128-3329 cvandergoot@usgs.gov","orcid":"https://orcid.org/0000-0003-4128-3329","contributorId":178356,"corporation":false,"usgs":true,"family":"Vandergoot","given":"Christopher","email":"cvandergoot@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":759403,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Yingming Zhao","contributorId":140825,"corporation":false,"usgs":false,"family":"Yingming Zhao","affiliations":[{"id":6780,"text":"Ontario Ministry of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":759404,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Knight, Carey","contributorId":214230,"corporation":false,"usgs":false,"family":"Knight","given":"Carey","affiliations":[{"id":16232,"text":"Ohio Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":759405,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Faust, Matt","contributorId":214231,"corporation":false,"usgs":false,"family":"Faust","given":"Matt","email":"","affiliations":[{"id":16232,"text":"Ohio Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":759406,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Hayden, Todd","contributorId":214232,"corporation":false,"usgs":false,"family":"Hayden","given":"Todd","email":"","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":759407,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Charles Krueger","contributorId":203268,"corporation":false,"usgs":false,"family":"Charles Krueger","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":759408,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70205059,"text":"70205059 - 2019 - Pacific sea surface temperature linkages with Tanzania’s multi-season drying trends","interactions":[],"lastModifiedDate":"2019-08-29T09:01:06","indexId":"70205059","displayToPublicDate":"2019-01-14T08:59:34","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5038,"text":"International Journal of Climate Change: Impacts and Responses","seriesDoiName":"10.18848/1835-7156/CGP","printIssn":"1835-7156","active":true,"publicationSubtype":{"id":10}},"title":"Pacific sea surface temperature linkages with Tanzania’s multi-season drying trends","docAbstract":"Droughts in Tanzania pose challenges to agriculture, water resources, and hydropower production, all of which impact livelihoods. Tanzania experienced below average precipitation during 1999-2014 during two important seasons: December to February (DJF) in the south and during March to June (MAMJ) in the northeast. We explore DJF and MAMJ precipitation in the areas with drying trends and examine their relationships with anomalous sea surface temperatures (SST) in the Indo-Pacific and corresponding circulation patterns. It is found that at seasonal time scales, precipitation in DJF and MAMJ trend areas appears inversely related to diabatic forcing in the equatorial Pacific. The dominant influence for droughts in DJF is from eastern Pacific SST while for droughts in MAMJ it is from West Pacific SST. A bivariate regression model with West Pacific and Niño3.4 region SST as predictors is found to recreate multidecadal DJF variability after the 1950s and the extreme drying in MAMJ during the 2000s. The regression model coefficients also indicate differential eastern vs. western Pacific forcing for DJF vs. MAMJ. Thus we suggest that recent La Niña-like conditions, characterized by an enhanced Pacific SST gradient due to cooling in the eastern Pacific and warming in the western Pacific, played a substantial role in Tanzania’s recent multi-season drying trends. SST change scenarios (difference between 2023-2037 and 2000-2014 means) based on CMIP5 projections and observed trends illustrate the uncertainty about future precipitation outcomes and also the potential implications of contrasting linkages to eastern vs. western Pacific SSTs. These scenarios are mainly optimistic for the DJF southern Tanzania trend area, because it appears dominated by Niño3.4 cooling at both seasonal and decadal time scales. Conversely, our scenarios are quite pessimistic for the MAMJ northeastern Tanzania trend area, because we find a dominant negative influence of warming West Pacific SST.","language":"English","publisher":"Wiley","doi":"10.1002/joc.6003","usgsCitation":"Harrison, L., Funk, C., McNally, A., Shukla, S., and Husak, G., 2019, Pacific sea surface temperature linkages with Tanzania’s multi-season drying trends: International Journal of Climate Change: Impacts and Responses, v. 39, no. 6, p. 3057-3075, https://doi.org/10.1002/joc.6003.","productDescription":"19 p.","startPage":"3057","endPage":"3075","ipdsId":"IP-101903","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":467996,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/joc.6003","text":"Publisher Index Page"},{"id":367045,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":367039,"type":{"id":15,"text":"Index Page"},"url":"https://doi.org/10.1002/joc.6003"}],"country":"Tanzania","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[33.90371,-0.95],[34.07262,-1.05982],[37.69869,-3.09699],[37.7669,-3.67712],[39.20222,-4.67677],[38.74054,-5.90895],[38.79977,-6.47566],[39.44,-6.84],[39.47,-7.1],[39.19469,-7.7039],[39.25203,-8.00781],[39.18652,-8.48551],[39.53574,-9.11237],[39.9496,-10.0984],[40.31659,-10.3171],[39.521,-10.89688],[38.42756,-11.2852],[37.82764,-11.26879],[37.47129,-11.56876],[36.77515,-11.59454],[36.51408,-11.72094],[35.3124,-11.43915],[34.55999,-11.52002],[34.28,-10.16],[33.94084,-9.69367],[33.73972,-9.41715],[32.75938,-9.2306],[32.19186,-8.93036],[31.55635,-8.76205],[31.15775,-8.59458],[30.74,-8.34],[30.2,-7.08],[29.62,-6.52],[29.41999,-5.94],[29.51999,-5.41998],[29.34,-4.49998],[29.75351,-4.45239],[30.11632,-4.09012],[30.50554,-3.56858],[30.75224,-3.35931],[30.74301,-3.03431],[30.52766,-2.80762],[30.46967,-2.41383],[30.75831,-2.28725],[30.81613,-1.69891],[30.4191,-1.13466],[30.76986,-1.01455],[31.86617,-1.02736],[33.90371,-0.95]]]},\"properties\":{\"name\":\"United Republic of Tanzania\"}}]}","volume":"39","issue":"6","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2019-02-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Harrison, Laura","contributorId":192382,"corporation":false,"usgs":false,"family":"Harrison","given":"Laura","email":"","affiliations":[],"preferred":false,"id":769796,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Funk, Chris 0000-0002-9254-6718 cfunk@usgs.gov","orcid":"https://orcid.org/0000-0002-9254-6718","contributorId":167070,"corporation":false,"usgs":true,"family":"Funk","given":"Chris","email":"cfunk@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":769795,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McNally, Amy","contributorId":145810,"corporation":false,"usgs":false,"family":"McNally","given":"Amy","email":"","affiliations":[{"id":16236,"text":"UCSB Climate Hazards Group","active":true,"usgs":false}],"preferred":false,"id":769797,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Shukla, Shraddhanand","contributorId":145841,"corporation":false,"usgs":false,"family":"Shukla","given":"Shraddhanand","affiliations":[{"id":16255,"text":"Climate Hazards Group University of California Santa Barbara","active":true,"usgs":false}],"preferred":false,"id":769798,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Husak, Gregory","contributorId":145811,"corporation":false,"usgs":false,"family":"Husak","given":"Gregory","affiliations":[{"id":16236,"text":"UCSB Climate Hazards Group","active":true,"usgs":false}],"preferred":false,"id":769799,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70203154,"text":"70203154 - 2019 - The Laurentian Great Lakes: A case study in ecological disturbance and climate change","interactions":[],"lastModifiedDate":"2019-04-24T09:56:47","indexId":"70203154","displayToPublicDate":"2019-01-13T09:53:20","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1659,"text":"Fisheries Management and Ecology","active":true,"publicationSubtype":{"id":10}},"title":"The Laurentian Great Lakes: A case study in ecological disturbance and climate change","docAbstract":"Climate change effects are already significant, but can also magnify other ecological problems. This can be clearly seen in the Laurentian Great Lakes, which have suffered habitat degradation, fishery overharvest and dramatic alterations by invasive species. Thermal changes are expected to cause extensive loss of suitable fish habitat, and changing precipitation patterns will aggravate the problems with our highly modified lotic and lentic systems. A brief summary of the historic ecological context provided by the Great Lakes case is presented, followed by the descriptions of selected tools that help to understand and evaluate both ecological and climate change problems. Species distribution models and habitat classification combined with climate change predictions can identify the distribution and extent of optimal habitats, and identify which are most vulnerable to climate change. Ecological flow modelling can help to identify when critical flow changes are likely. Mechanistic simulation modelling specifies understanding of how aquatic systems function and can reveal cause and effect relationships. These tools can be used to help managers to protect optimal habitat, resist climate change effects to other habitats and adapt cultural systems to climate‐altered aquatic systems.
Telemetry devices are widely used in avian research, but the degree to which the deployment of such devices affects the survival of study subjects is often not addressed. It is generally assumed that such effects are less pronounced in large-bodied species that conduct relatively short migrations and carry relatively light telemetry devices. We studied Bristle-thighed Curlews Numenius tahitiensis over the period 2012–2017 at a nonbreeding site on the island of Oahu, Hawaii. We used leg-loop harnesses to equip 11 curlews with externally mounted, solar-powered satellite transmitters that constituted ca. 3% of their body mass, and compared the annual survival of these birds to 37 curlews marked only with uniquely engraved leg flags. Despite the species’ large size and the small mass of the transmitters, we documented potential negative effects of externally mounted transmitters on the survival of Bristle-thighed Curlews. We also documented apparent effects of age and sex on the survival of curlews, underscoring the difficulty of disentangling the effects of research techniques on study subjects. Understanding and publicizing the potential effects of research itself on wildlife are crucial steps in the process of refining technical applications and improving the welfare of study animals. We urge researchers to critically assess and report the effects of similar research techniques to minimize deleterious effects in future studies.
","language":"English","publisher":"International Wader Study Group","doi":"10.18194/ws.00145","usgsCitation":"Ruthrauff, D.R., Tibbitts, T.L., and Patil, V.P., 2019, Survival of Bristle-thighed Curlews equipped with externally mounted transmitters: Wader Study, v. 126, no. 2, p. 109-115, https://doi.org/10.18194/ws.00145.","productDescription":"7 p.","startPage":"109","endPage":"115","ipdsId":"IP-104376","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":437606,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9X8J7ST","text":"USGS data release","linkHelpText":"Measurements Used to Determine the Sex of Bristle-thighed Curlews (Numenius tahitiensis)"},{"id":437605,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P93VHNK3","text":"USGS data release","linkHelpText":"Bristle-Thighed Curlew (Numenius tahitiensis) Mark-Resight Encounter History from the James Campbell National Wildlife Refuge and Surrounding Area, Oahu, Hawaii, 2012-2017"},{"id":371181,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":371180,"rank":1,"type":{"id":28,"text":"Dataset"},"url":" https://doi.org/10.5066/P9X8J7ST"}],"volume":"126","issue":"2","noUsgsAuthors":false,"publicationDate":"2019-08-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Ruthrauff, Daniel R. 0000-0003-1355-9156 druthrauff@usgs.gov","orcid":"https://orcid.org/0000-0003-1355-9156","contributorId":4181,"corporation":false,"usgs":true,"family":"Ruthrauff","given":"Daniel","email":"druthrauff@usgs.gov","middleInitial":"R.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":779354,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tibbitts, T. Lee 0000-0002-0290-7592 ltibbitts@usgs.gov","orcid":"https://orcid.org/0000-0002-0290-7592","contributorId":102185,"corporation":false,"usgs":true,"family":"Tibbitts","given":"T.","email":"ltibbitts@usgs.gov","middleInitial":"Lee","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":779355,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Patil, Vijay P. 0000-0002-9357-194X vpatil@usgs.gov","orcid":"https://orcid.org/0000-0002-9357-194X","contributorId":203676,"corporation":false,"usgs":true,"family":"Patil","given":"Vijay","email":"vpatil@usgs.gov","middleInitial":"P.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":false,"id":779356,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70203580,"text":"70203580 - 2019 - Simulating runoff quality with the highway-runoff database and the Stochastic Empirical Loading and Dilution Model","interactions":[],"lastModifiedDate":"2019-05-24T08:14:50","indexId":"70203580","displayToPublicDate":"2019-01-13T07:45:29","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3647,"text":"Transportation Research Record","active":true,"publicationSubtype":{"id":10}},"title":"Simulating runoff quality with the highway-runoff database and the Stochastic Empirical Loading and Dilution Model","docAbstract":"Stormwater practitioners need quantitative information about the quality and volume of highway runoff to assess and mitigate potential adverse effects of runoff on the Nation’s receiving waters. The U.S. Geological Survey developed the Highway Runoff Database (HRDB) in cooperation with the FHWA to provide practice-ready information to meet these information needs on the local or national scale. This paper describes the datasets that are available in version 1.1 of the HRDB and demonstrates how data and statistics from the HRDB can be used with the Stochastic Empirical Loading and Dilution Model (SELDM) to simulate highway runoff. The HRDB includes 249 sites, 6,849 runoff events, and 106,869 event mean concentrations (EMCs) collected during the 1975–2017 period. It includes data from 16 States in the conterminous United States and from Hawaii. The EMCs in the HRDB include measurements for 415 different water-quality constituents. These water-quality measurements include 32,944 trace-metal; 27,496 organic; 15,684 nutrient; 13,016 physical property; 10,307 major inorganic; 6,773 sediment; and 649 other constituent values. There are large variations in the data. For example, EMCs for total suspended solids and total phosphorus range from 0.4 to 5,440 mg/L and 0.004 to 22 mg/L, respectively; geometric means range from 1.58 to 1,379 mg/L and 0.017 to 2.82 mg/L for these constituents, respectively. The example simulations indicate that risks for adverse effects of runoff can vary by orders of magnitude; the HRDB and SELDM facilitate selection of representative statistics from available datasets.
The outbreak and transmission of disease-causing pathogens are contributing to the unprecedented rate of biodiversity decline. Recent advances in genomics have coalesced into powerful tools to monitor, detect, and reconstruct the role of pathogens impacting wildlife populations. Wildlife researchers are thus uniquely positioned to merge ecological and evolutionary studies with genomic technologies to exploit unprecedented ‘Big Data’ tools in disease research; however, many researchers lack the training and expertise required to use these computationally intensive methodologies. To address this disparity, the inaugural ‘Genomics of Disease in Wildlife’ workshop assembled early to mid-career professionals with expertise across scientific disciplines (e.g., genomics, wildlife biology, veterinary sciences, and conservation management) for training in the application of genomic tools to wildlife disease research. A horizon scanning-like exercise, an activity to identify forthcoming trends and challenges, performed by the workshop participants identified and discussed five themes considered to be the most pressing to the application of genomics in wildlife disease research: i) “Improving Communication”, ii) “Methodological and Analytical Advancements”, iii) “Translation into Practice”, iv) “Integrating Landscape Ecology and Genomics”, and v) “Emerging New Questions”. Wide-ranging solutions from the horizon scan were international in scope, itemized both deficiencies and strengths in wildlife genomic initiatives, promoted the use of genomic technologies to unite wildlife and human disease research, and advocated best practices for optimal use of genomic tools in wildlife disease projects. The results offer a glimpse of the potential revolution in human and wildlife disease research possible through multi-disciplinary collaborations at local, regional, and global scales.
","language":"English","publisher":"American Genetic Association","doi":"10.1093/jhered/esz001","usgsCitation":"Fitak, R.R., Antonides, J.D., Baitchman, E.J., Bonaccorso, E., Braun, J., Kubiski, S., Chiu, E., Fagre, A.C., Gagne, R.B., Lee, J.S., Malmberg, J.L., Stenglein, M.D., Dusek, R.J., Forgacs, D., Fountain-Jones, N.M., Gilbertson, M.L., Worsley-Tonks, K.E., Funk, W.C., Trumbo, D.R., Ghersi, B.M., Grimaldi, W., Heisel, S.E., Jardine, C.M., Kamath, P.L., Karmacharya, D., Kozakiewicz, C.P., Kraberger, S., Loisel, D.A., McDonald, C., Miller, S., O’Rourke, D., Ott-Conn, C.N., Páez-Vacas, M., Peel, A.J., Turner, W.C., VanAcker, M.C., VandeWoude, S., and Pecon-Slattery, J., 2019, The expectations and challenges of wildlife disease research in the era of genomics: Forecasting with a horizon scan-like exercise: Journal of Heredity, v. 110, no. 3, p. 261-274, https://doi.org/10.1093/jhered/esz001.","productDescription":"14 p.","startPage":"261","endPage":"274","ipdsId":"IP-098179","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":460521,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/jhered/esz001","text":"Publisher Index Page"},{"id":360891,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"110","issue":"3","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationDate":"2019-01-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Fitak, Robert R.","contributorId":212102,"corporation":false,"usgs":false,"family":"Fitak","given":"Robert","email":"","middleInitial":"R.","affiliations":[{"id":38408,"text":"Department of Biology, Duke University, Durham, North Carolina","active":true,"usgs":false}],"preferred":false,"id":755574,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Antonides, Jennifer D.","contributorId":212103,"corporation":false,"usgs":false,"family":"Antonides","given":"Jennifer","email":"","middleInitial":"D.","affiliations":[{"id":38409,"text":"Department of Forestry & Natural Resources, Purdue University, West Lafayette, IN, USA","active":true,"usgs":false}],"preferred":false,"id":755575,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Baitchman, Eric J.","contributorId":212104,"corporation":false,"usgs":false,"family":"Baitchman","given":"Eric","email":"","middleInitial":"J.","affiliations":[{"id":38410,"text":"Zoo New England Division of Animal Health and Conservation, Boston, MA, USA","active":true,"usgs":false}],"preferred":false,"id":755576,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bonaccorso, Elisa","contributorId":212105,"corporation":false,"usgs":false,"family":"Bonaccorso","given":"Elisa","email":"","affiliations":[{"id":38411,"text":"Instituto BIOSFERA and Colegio de Ciencias Biológicas y Ambientales, Universidad San Francisco de Quito, vía Interoceánica y Diego de Robles, Quito, Ecuador","active":true,"usgs":false}],"preferred":false,"id":755577,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Braun, Josephine","contributorId":212106,"corporation":false,"usgs":false,"family":"Braun","given":"Josephine","email":"","affiliations":[{"id":38412,"text":"Institute for Conservation Research, San Diego Zoo Global, Escondido, CA, USA","active":true,"usgs":false}],"preferred":false,"id":755578,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kubiski, Steven","contributorId":212107,"corporation":false,"usgs":false,"family":"Kubiski","given":"Steven","email":"","affiliations":[{"id":38412,"text":"Institute for Conservation Research, San Diego Zoo Global, Escondido, CA, USA","active":true,"usgs":false}],"preferred":false,"id":755579,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Chiu, 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Rica","interactions":[],"lastModifiedDate":"2019-01-28T14:50:26","indexId":"70201742","displayToPublicDate":"2019-01-11T14:50:19","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5232,"text":"Frontiers in Earth Science","onlineIssn":"2296-6463","active":true,"publicationSubtype":{"id":10}},"title":"Insights into the mechanisms of phreatic eruptions from continuous high frequency volcanic gas monitoring: Rincón de la Vieja volcano, Costa Rica","docAbstract":"Understanding the trigger mechanisms of phreatic eruptions is key to mitigating the effects of these hazardous but poorly forecastable volcanic events. It has recently been established that high-rate volcanic gas observations are potentially very suitable to identifying the source processes driving phreatic eruptions, and to eventually detecting precursory changes prior to individual phreatic blasts. In February-May 2017, we deployed a Multi-GAS instrument to continuously monitor gas concentrations in the crater lake plume of Rincón de la Vieja, a remote and poorly monitored active volcano in Costa Rica, site of frequent phreatic/phreatomagmatic eruptions. Forty-two phreatic/phreatomagmatic eruptions were seismically recorded during our investigated period, 9 of which were also recorded for gas by the Multi-GAS. To the best of our knowledge, these represent the first instrumentally measured gas compositions during individual phreatic/phreatomagmatic explosions at an active volcano. Our results show that during background quiescent degassing the Rincón de la Vieja crater lake plume was characterized by high CO2/SO2 ratios of 64 ± 59 and H2S/SO2 ratios of 0.57 ± 0.20. This composition is interpreted as reflecting hydrothermal (re)processing of magma-sourced gas in the sub-limnic environment. Phreatic blasts were recorded by the Multi-GAS as brief (1–2 min long) pulses of elevated gas mixing ratios (up to ~52 ppmv SO2 and >3,000 ppmv CO2), or more than an order of magnitude higher than during background degassing (~1 ppmv SO2 and ~450 ppmv CO2). During the phreatic eruption(s), the H2S/SO2 ratio was systematically lower (<0.18) than during background degassing, but the CO2/SO2 ratio remained high (and variable), ranging from 37 to 390. These S-poor compositions for the eruptive gas imply extensive processing of the source magmatic gas during pre-eruptive hydrothermal storage, likely by deposition of native S and/or sulfate. Our gas results are thus overall consistent with a mechanism of phreatic eruptions triggered by accumulation of magmatic-hydrothermal gases beneath a hydrothermal seal. We claim that real-time Multi-GAS monitoring is urgently needed at other crater lake-hosting volcanoes (e.g., Ruapehu, Aso), where phreatic eruptions may similarly be preceded by phases of reduced S degassing at the surface.
","language":"English","publisher":"Frontiers Media","doi":"10.3389/feart.2018.00247","usgsCitation":"Battaglia, A., de Moor, J.M., Aiuppa, A., Avard, G., Bakkar, H., Bitetto, M., Mora Fernandez, M.M., Kelly, P.J., Giudice, G., Delle Donne, D., and Villalobos, H., 2019, Insights into the mechanisms of phreatic eruptions from continuous high frequency volcanic gas monitoring: Rincón de la Vieja volcano, Costa Rica: Frontiers in Earth Science, v. 6, p. 1-20, https://doi.org/10.3389/feart.2018.00247.","productDescription":"Article 247; 20 p.","startPage":"1","endPage":"20","ipdsId":"IP-099079","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":467998,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/feart.2018.00247","text":"Publisher Index Page"},{"id":360764,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Costa Rica","otherGeospatial":"Rincón de la Vieja Volcano","volume":"6","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2019-01-11","publicationStatus":"PW","scienceBaseUri":"5c5022c3e4b0708288f7e803","contributors":{"authors":[{"text":"Battaglia, Angelo","contributorId":211890,"corporation":false,"usgs":false,"family":"Battaglia","given":"Angelo","email":"","affiliations":[{"id":38345,"text":"Dipartimento DiSTeM, Università di Palermo, Via Archirafi 36, 90123 Palermo, Italy","active":true,"usgs":false}],"preferred":false,"id":755141,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"de Moor, J. 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M.","contributorId":211893,"corporation":false,"usgs":false,"family":"Mora Fernandez","given":"M.","email":"","middleInitial":"M.","affiliations":[{"id":38347,"text":"Escuela Centroamericana de Geología, Universidad de Costa Rica, San José Costa Rica","active":true,"usgs":false}],"preferred":false,"id":755147,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Kelly, Peter J. 0000-0002-3868-1046 pkelly@usgs.gov","orcid":"https://orcid.org/0000-0002-3868-1046","contributorId":5931,"corporation":false,"usgs":true,"family":"Kelly","given":"Peter","email":"pkelly@usgs.gov","middleInitial":"J.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":755140,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Giudice, Gaetano","contributorId":173682,"corporation":false,"usgs":false,"family":"Giudice","given":"Gaetano","email":"","affiliations":[{"id":27273,"text":"Istituto Nazionale di Geofisica e Vulcanologia, Sezione di Palermo, Italy","active":true,"usgs":false}],"preferred":false,"id":755148,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Delle Donne, Dario","contributorId":211894,"corporation":false,"usgs":false,"family":"Delle Donne","given":"Dario","email":"","affiliations":[{"id":38345,"text":"Dipartimento DiSTeM, Università di Palermo, Via Archirafi 36, 90123 Palermo, Italy","active":true,"usgs":false}],"preferred":false,"id":755149,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Villalobos, Hairo","contributorId":211895,"corporation":false,"usgs":false,"family":"Villalobos","given":"Hairo","email":"","affiliations":[{"id":38348,"text":"Observatorio Vulcanológico y Sismológico de Costa Rica, Universidad Nacional, Heredia, Costa Rica","active":true,"usgs":false}],"preferred":false,"id":755150,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70204959,"text":"70204959 - 2019 - Distribution of modern salt-marsh Foraminifera from the eastern Mississippi Sound, U.S.A.","interactions":[],"lastModifiedDate":"2025-05-14T13:34:40.144004","indexId":"70204959","displayToPublicDate":"2019-01-11T09:02:39","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2294,"text":"Journal of Foraminiferal Research","active":true,"publicationSubtype":{"id":10}},"title":"Distribution of modern salt-marsh Foraminifera from the eastern Mississippi Sound, U.S.A.","docAbstract":"This study documented surface distributions of live and dead foraminiferal assemblages in the low-gradient tidal marshes of the barrier island and estuarine complex of the eastern Mississippi Sound (Grand Bay, Pascagoula River, Fowl River, Dauphin Island). A total of 71,833 specimens representing 38 species were identified from a gradient of different elevation zones across the study area. We identified five live assemblages and nine biofacies for the dead assemblages from estuarine, low marsh, middle marsh, high marsh, and upland transition environments. Although dissolution of calcareous tests was observed in the dead assemblages, characteristic species and abundance patterns dependent on elevation in the intertidal zone were similar between living assemblages and dead biofacies. The assemblages from the eastern Mississippi Sound estuaries were dominated by Ammonia tepida, Cribroelphidium poeyanum, C. excavatum, and Paratrochammina simplissima. The low marshes were dominated by Ammotium salsum, Ammobaculites exiguus, and Miliammina fusca. The dominant species in the middle marshes was Arenoparrella mexicana. The most abundant species in the high marshes was Entzia macrescens. The upland–marsh transition zones were dominated by Trochamminita irregularis and Pseudothurammina limnetis. Canonical correspondence analysis was applied to assess the relationship between a priori defined biofacies and measured environmental data (elevation, grain size, organic matter, and salinity) to test the hypothesis that distribution of foraminiferal assemblages is driven by elevation and hence flooding frequency. Salinity was the second most important explanatory variable of dead assemblages. Riverine freshwater from the Pascagoula River markedly influenced the live and dead assemblages in the Pascagoula River marsh, which was represented by low diversity and densities and dominance by Ammoastuta inepta. The relationship between the measured environmental variables and assemblage distributions can be used in future Mississippi Sound paleo-environmental studies.","language":"English","publisher":"GeoScienceWorld","doi":"10.2113/gsjfr.49.1.29","usgsCitation":"Haller, C., Smith, C., Hallock, P., Hine, A.C., Osterman, L., and McCloskey, T., 2019, Distribution of modern salt-marsh Foraminifera from the eastern Mississippi Sound, U.S.A.: Journal of Foraminiferal Research, v. 49, no. 1, p. 29-47, https://doi.org/10.2113/gsjfr.49.1.29.","productDescription":"19 p.; Data Release","startPage":"29","endPage":"47","ipdsId":"IP-091945","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":437608,"rank":1,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P901T47X","text":"USGS data release","linkHelpText":"Sedimentary data from the lower Pascagoula River, Mississippi, USA"},{"id":366948,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Mississippi","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.4124755859375,\n 30.637912028341123\n ],\n [\n -89.7308349609375,\n 30.477082932837682\n ],\n [\n -89.4891357421875,\n 29.954934549656144\n ],\n [\n -88.0224609375,\n 30.012030680358613\n ],\n [\n -88.4124755859375,\n 30.637912028341123\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"49","issue":"1","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Haller, Christian","contributorId":200685,"corporation":false,"usgs":false,"family":"Haller","given":"Christian","affiliations":[],"preferred":false,"id":769279,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Smith, Christopher G. 0000-0002-8075-4763","orcid":"https://orcid.org/0000-0002-8075-4763","contributorId":218439,"corporation":false,"usgs":true,"family":"Smith","given":"Christopher G.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":769278,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hallock, Pamela 0000-0002-1813-0482","orcid":"https://orcid.org/0000-0002-1813-0482","contributorId":215416,"corporation":false,"usgs":false,"family":"Hallock","given":"Pamela","email":"","affiliations":[{"id":39241,"text":"College of Marine Science, University of South Florida","active":true,"usgs":false}],"preferred":false,"id":769280,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hine, Albert C.","contributorId":218440,"corporation":false,"usgs":false,"family":"Hine","given":"Albert","email":"","middleInitial":"C.","affiliations":[{"id":7163,"text":"University of South Florida","active":true,"usgs":false}],"preferred":false,"id":769281,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Osterman, Lisa 0000-0002-8603-5217 osterman@usgs.gov","orcid":"https://orcid.org/0000-0002-8603-5217","contributorId":218441,"corporation":false,"usgs":true,"family":"Osterman","given":"Lisa","email":"osterman@usgs.gov","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":769282,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"McCloskey, Terrence 0000-0003-3979-3821","orcid":"https://orcid.org/0000-0003-3979-3821","contributorId":218442,"corporation":false,"usgs":true,"family":"McCloskey","given":"Terrence","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":769283,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70201902,"text":"70201902 - 2019 - Patterning emergent marsh vegetation assemblages in coastal Louisiana, USA, with unsupervised artificial neural networks","interactions":[],"lastModifiedDate":"2019-06-13T11:28:05","indexId":"70201902","displayToPublicDate":"2019-01-10T15:08:04","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":849,"text":"Applied Vegetation Science","active":true,"publicationSubtype":{"id":10}},"title":"Patterning emergent marsh vegetation assemblages in coastal Louisiana, USA, with unsupervised artificial neural networks","docAbstract":"Question
Are self‐organizing maps (SOMs) useful for patterning coastal wetland vegetation communities? Do SOMs provide robust alternatives to traditional classification methods, particularly when underlying species response functions are unknown or difficult to approximate, or when a need exists to continuously classify new samples obtained under ongoing long‐term ecosystem monitoring programs as they become available?.
Location
Coastal Louisiana, USA.
Methods
A SOM was trained from in situ observations of 559 vegetation species relative cover data from 2526 samples collected over eight years at 343 locations across coastal Louisiana. Hierarchical cluster analysis was applied to the SOM output to delineate vegetation community types, and indicator species analysis was conducted. Salinity and flood duration were compared across the delineated community types.
Results
The SOM patterned the 2526 training samples into 260 output neurons, which were further clustered into eleven community types. Clear gradients in salinity and flood duration existed among the community types, and geographic zonation of the communities was evident across the landscape. At some locations assemblages were temporally stable; at other locations they varied considerably. Samples not used in training the network were effectively projected onto the SOM and assigned to one of the delineated community types.
Conclusions
The SOM was effective in delineating plant communities in the region that were qualitatively similar to those obtained in previous investigations. Being robust to skewed distributions and the presence of outliers, SOMs provide an alternative to traditional distribution‐based statistical approaches. Their ability to efficiently classify new data into existing community types makes their use an ideal approach to classifying samples obtained from ongoing, long‐term ecological monitoring programs.
The federally threatened northern spotted owl (Strix occidentalis caurina) has been intensively studied across its range, and habitat needs for the species have influenced forest management in northwestern North America for decades. Dense forest canopies are often reported in the scientific literature and agency management plans as an important habitat attribute for spotted owls, though the means of measuring forest canopy and interpreting species requirements vary across studies and more importantly, among management plans. We used light detection and ranging (lidar) measurements of canopy cover, canopy surface heterogeneity, and upper canopy surface connectivity, and an index of the presence of a competitive invasive species, the barred owl (S. varia), in multinomial discrete choice models using a Bayesian framework to evaluate selection of forest cover types by spotted owls in Oregon, USA, 2008–2015. We designated yearly activity centers based on the most biologically significant observation during the nesting season (Mar–Aug), generally centered on the nest tree. Spotted owls selected activity centers with more canopy cover and higher heterogeneity of the canopy surface within 100 m than was available within their territories. The average proportion of canopy cover within 100 m of a spotted owl activity center was 0.79 ± 0.12 (SD; range = 0.34–0.99). The presence of barred owls did not explain variability in selection of spotted owl activity centers, but barred owls might not affect third‐order habitat selection within territories, or our index was too spatially coarse to detect these effects on spotted owl resource selection. We demonstrate that lidar provides researchers and managers with a tool that can accurately measure forest canopies over large areas, and assist in mapping spotted owl habitat.
","language":"English","publisher":"The Wildlife Society","doi":"10.1002/jwmg.21632","usgsCitation":"Sovern, S., Lesmeister, D.B., Dugger, K., Pruett, M., Davis, R.J., and Jenkins, J.M., 2019, Activity center selection by northern spotted owls: Journal of Wildlife Management, v. 83, no. 3, p. 714-727, https://doi.org/10.1002/jwmg.21632.","productDescription":"14 p.","startPage":"714","endPage":"727","ipdsId":"IP-095389","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":468000,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/jwmg.21632","text":"Publisher Index Page"},{"id":379968,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124.288330078125,\n 42.09822241118974\n ],\n [\n -121.70654296874999,\n 42.09822241118974\n ],\n [\n -121.70654296874999,\n 45.166547157856016\n ],\n [\n -124.288330078125,\n 45.166547157856016\n ],\n [\n -124.288330078125,\n 42.09822241118974\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"83","issue":"3","noUsgsAuthors":false,"publicationDate":"2019-01-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Sovern, Stan G.","contributorId":244122,"corporation":false,"usgs":false,"family":"Sovern","given":"Stan G.","affiliations":[{"id":25426,"text":"OSU","active":true,"usgs":false}],"preferred":false,"id":803355,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lesmeister, Damon B. 0000-0003-1102-0122","orcid":"https://orcid.org/0000-0003-1102-0122","contributorId":205006,"corporation":false,"usgs":false,"family":"Lesmeister","given":"Damon","email":"","middleInitial":"B.","affiliations":[{"id":37019,"text":"USDA Forest Service, Pacific Northwest Research Station","active":true,"usgs":false}],"preferred":false,"id":803356,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dugger, Katie M. 0000-0002-4148-246X cdugger@usgs.gov","orcid":"https://orcid.org/0000-0002-4148-246X","contributorId":4399,"corporation":false,"usgs":true,"family":"Dugger","given":"Katie","email":"cdugger@usgs.gov","middleInitial":"M.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":803357,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pruett, M. Shane","contributorId":244123,"corporation":false,"usgs":false,"family":"Pruett","given":"M. Shane","affiliations":[{"id":25426,"text":"OSU","active":true,"usgs":false}],"preferred":false,"id":803358,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Davis, Raymond J.","contributorId":150574,"corporation":false,"usgs":false,"family":"Davis","given":"Raymond","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":803359,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Jenkins, Julianna M.","contributorId":244124,"corporation":false,"usgs":false,"family":"Jenkins","given":"Julianna","email":"","middleInitial":"M.","affiliations":[{"id":36589,"text":"USDA","active":true,"usgs":false}],"preferred":false,"id":803360,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70201739,"text":"70201739 - 2019 - How physics‐based earthquake simulators might help improve earthquake forecasts","interactions":[],"lastModifiedDate":"2019-03-04T11:16:17","indexId":"70201739","displayToPublicDate":"2019-01-09T14:59:27","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3372,"text":"Seismological Research Letters","onlineIssn":"1938-2057","printIssn":"0895-0695","active":true,"publicationSubtype":{"id":10}},"title":"How physics‐based earthquake simulators might help improve earthquake forecasts","docAbstract":"Questions have persisted on the usefulness of physics‐based earthquake simulators with respect to forecasting earthquakes, due mostly to the inevitable assumptions, approximations, and uncertainties. Whether any model is reliable or trustworthy depends entirely on what questions we are asking of it, so the point of this article is to outline a number of currently anticipated and desired inferences, informed largely by recent forecasting efforts in California. This article does not provide an in‐depth review of physics‐based simulators, nor does it render judgment on the usefulness question. The intent, rather, is to provide an explicit list of potential uses, or inferences, to enable more informed discussions among physics‐based modeling experts.
","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0220180299","usgsCitation":"Field, E., 2019, How physics‐based earthquake simulators might help improve earthquake forecasts: Seismological Research Letters, v. 90, no. 2A, p. 467-472, https://doi.org/10.1785/0220180299.","productDescription":"6 p.","startPage":"467","endPage":"472","ipdsId":"IP-103855","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":360766,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"90","issue":"2A","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2019-01-09","publicationStatus":"PW","scienceBaseUri":"5c5022c4e4b0708288f7e807","contributors":{"authors":[{"text":"Field, Edward H. 0000-0001-8172-7882 field@usgs.gov","orcid":"https://orcid.org/0000-0001-8172-7882","contributorId":1165,"corporation":false,"usgs":true,"family":"Field","given":"Edward H.","email":"field@usgs.gov","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":false,"id":755125,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70202833,"text":"70202833 - 2019 - Assessment of operational and structural factors influencing performance of fish collectors in forebays of high-head dams","interactions":[],"lastModifiedDate":"2019-03-28T13:46:18","indexId":"70202833","displayToPublicDate":"2019-01-09T13:31:50","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3624,"text":"Transactions of the American Fisheries Society","active":true,"publicationSubtype":{"id":10}},"title":"Assessment of operational and structural factors influencing performance of fish collectors in forebays of high-head dams","docAbstract":"Providing efficient downstream passage is critical for improving populations of migratory fishes in impounded river systems. High‐head dams, such as those used for water storage or flood‐risk management, pose unique passage challenges requiring unique solutions. Systems to collect fish in dam forebays (“forebay collectors”) for transport to downstream release locations have been used at some high‐head dams in the western United States since the 1950s. Collection efficiency of these facilities has ranged from nearly 0% to 100%, suggesting the need for a better understanding of factors affecting performance in these complex environments if they are to be designed and deployed at new sites. We compiled information on environmental, structural, and performance characteristics of seven existing forebay collectors to quantify factors affecting their performance based on a meta‐analysis using a data set containing 52 separate collection estimates. Covariates included species type (steelhead Oncorhynchus mykiss, Chinook Salmon O. tshawytscha, Coho Salmon O. kisutch, and Sockeye Salmon O. nerka), collector inflow, collector entrance area, relative size of the dam forebay, and whether or not nets were used to enhance collection. We found that inflow, the use of lead nets, the size of the collector entrance area, the relative size of the dam forebay, and the interaction between collector entrance and forebay areas were significant predictors of collection performance. There was also evidence for differences between species. Chinook Salmon exhibited the lowest collection rates among the projects we examined, while steelhead collection rates were highest. These results provide guidance to design more efficient forebay collectors and improve the success of existing systems.","language":"English","publisher":"American Fisheries Society","doi":"10.1002/tafs.10146","usgsCitation":"Kock, T.J., Verretto, N.E., Ackerman, N.K., Perry, R.W., Beeman, J.W., Garello, M.C., and Fielding, S.D., 2019, Assessment of operational and structural factors influencing performance of fish collectors in forebays of high-head dams: Transactions of the American Fisheries Society, v. 148, no. 2, p. 464-479, https://doi.org/10.1002/tafs.10146.","productDescription":"16 p.","startPage":"464","endPage":"479","ipdsId":"IP-101404","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":362509,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon, Washington","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124.01367187499999,\n 43.100982876188546\n ],\n [\n -116.103515625,\n 43.100982876188546\n ],\n [\n -116.103515625,\n 49.15296965617042\n ],\n [\n -124.01367187499999,\n 49.15296965617042\n ],\n [\n -124.01367187499999,\n 43.100982876188546\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"148","issue":"2","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2019-02-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Kock, Tobias J. 0000-0001-8976-0230","orcid":"https://orcid.org/0000-0001-8976-0230","contributorId":214550,"corporation":false,"usgs":true,"family":"Kock","given":"Tobias","middleInitial":"J.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":760184,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Verretto, Nicholas E","contributorId":214551,"corporation":false,"usgs":false,"family":"Verretto","given":"Nicholas","email":"","middleInitial":"E","affiliations":[{"id":39067,"text":"Puget Sound Energy, Bellevue, WA","active":true,"usgs":false}],"preferred":false,"id":760185,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ackerman, Nicklaus K","contributorId":214552,"corporation":false,"usgs":false,"family":"Ackerman","given":"Nicklaus","email":"","middleInitial":"K","affiliations":[{"id":39068,"text":"Portland General Electric, Estacada, OR","active":true,"usgs":false}],"preferred":false,"id":760186,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Perry, Russell W. 0000-0003-4110-8619","orcid":"https://orcid.org/0000-0003-4110-8619","contributorId":214553,"corporation":false,"usgs":true,"family":"Perry","given":"Russell","middleInitial":"W.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":760187,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Beeman, John W","contributorId":214554,"corporation":false,"usgs":false,"family":"Beeman","given":"John","email":"","middleInitial":"W","affiliations":[{"id":39069,"text":"USGS, WFRC, CRRL, Cook, WA","active":true,"usgs":false}],"preferred":false,"id":760188,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Garello, Michael C","contributorId":214555,"corporation":false,"usgs":false,"family":"Garello","given":"Michael","email":"","middleInitial":"C","affiliations":[{"id":39070,"text":"HDR Inc., Gig Harbor, WA","active":true,"usgs":false}],"preferred":false,"id":760189,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Fielding, Scott D","contributorId":214556,"corporation":false,"usgs":false,"family":"Fielding","given":"Scott","email":"","middleInitial":"D","affiliations":[{"id":39071,"text":"U.S. Army Corps of Engineers, Portland, OR","active":true,"usgs":false}],"preferred":false,"id":760190,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70201765,"text":"70201765 - 2019 - Modeling effects of crop production, energy development and conservation-grassland loss on avian habitat","interactions":[],"lastModifiedDate":"2019-01-29T12:37:17","indexId":"70201765","displayToPublicDate":"2019-01-09T12:37:12","publicationYear":"2019","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":"Modeling effects of crop production, energy development and conservation-grassland loss on avian habitat","docAbstract":"Birds are essential components of most ecosystems and provide many services valued by society. However, many populations have undergone striking declines as their habitats have been lost or degraded by human activities. Terrestrial grasslands are vital habitat for birds in the North American Prairie Pothole Region (PPR), but grassland conversion and fragmentation from agriculture and energy-production activities have destroyed or degraded millions of hectares. Conservation grasslands can provide alternate habitat. In the United States, the Conservation Reserve Program (CRP) is the largest program maintaining conservation grasslands on agricultural lands, but conservation grasslands in the PPR have declined by over 1 million ha since the program’s zenith in 2007. We used an ecosystem-services model (InVEST) parameterized for the PPR to quantify grassland-bird habitat remaining in 2014 and to assess the degradation status of the remaining grassland-bird habitat as influenced by crop and energy (i.e., oil, natural gas, and wind) production. We compared our resultant habitat-quality ratings to grassland-bird abundance data from the North American Breeding Bird Survey to confirm that ratings were related to grassland-bird abundance. Of the grassland-bird habitat remaining in 2014, about 19% was degraded by crop production that occurred within 0.1 km of grassland habitats, whereas energy production degraded an additional 16%. We further quantified the changes in availability of grassland-bird habitat under various land-cover scenarios representing incremental losses (10%, 25%, 50%, 75%, and 100%) of CRP grasslands from 2014 levels. Our model identified 1 million ha (9%) of remaining grassland-bird habitat in the PPR that would be lost or degraded if all CRP conservation grasslands were returned to crop production. Grassland regions world-wide face similar challenges in maintaining avian habitat in the face of increasing commodity and energy production to sate the food and energy needs of a growing world population. Identifying ways to model the impacts of the tradeoff between food and energy production and wildlife production is an important step in creating solutions.
","language":"English","publisher":"PLOS","doi":"10.1371/journal.pone.0198382","usgsCitation":"Shaffer, J.A., Roth, C.L., and Mushet, D.M., 2019, Modeling effects of crop production, energy development and conservation-grassland loss on avian habitat: PLoS ONE, v. 14, no. 1, p. 1-17, https://doi.org/10.1371/journal.pone.0198382.","productDescription":"e0198382; 17 p.","startPage":"1","endPage":"17","ipdsId":"IP-089961","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":468001,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0198382","text":"Publisher Index Page"},{"id":437609,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F72J69RM","text":"USGS data release","linkHelpText":"Modeling effects of crop production, energy development and conservation-grassland loss on avian habitat: dataset of BBS data, ND, with habitat rankings"},{"id":360786,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Prairie Pothole Region","volume":"14","issue":"1","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2019-01-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Shaffer, Jill A. 0000-0003-3172-0708 jshaffer@usgs.gov","orcid":"https://orcid.org/0000-0003-3172-0708","contributorId":3184,"corporation":false,"usgs":true,"family":"Shaffer","given":"Jill","email":"jshaffer@usgs.gov","middleInitial":"A.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":755277,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Roth, Cali L. 0000-0001-9077-2765 croth@usgs.gov","orcid":"https://orcid.org/0000-0001-9077-2765","contributorId":174422,"corporation":false,"usgs":true,"family":"Roth","given":"Cali","email":"croth@usgs.gov","middleInitial":"L.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true},{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":755278,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mushet, David M. 0000-0002-5910-2744 dmushet@usgs.gov","orcid":"https://orcid.org/0000-0002-5910-2744","contributorId":1299,"corporation":false,"usgs":true,"family":"Mushet","given":"David","email":"dmushet@usgs.gov","middleInitial":"M.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":755279,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70223857,"text":"70223857 - 2019 - To what extent is drought-induced tree mortality a natural phenomenon?","interactions":[],"lastModifiedDate":"2021-09-10T15:02:02.695241","indexId":"70223857","displayToPublicDate":"2019-01-09T09:36:33","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1839,"text":"Global Ecology and Biogeography","active":true,"publicationSubtype":{"id":10}},"title":"To what extent is drought-induced tree mortality a natural phenomenon?","docAbstract":"Catastrophic forest mortality due to more extreme rainfall deficits and higher temperatures under future climate scenarios has been predicted. The aim of this study is to explore the magnitude of historical drought-induced tree mortality under pre-warming conditions.
North-eastern Australia.
1845–2017.
Trees.
Field survey, historical analysis and climate analysis.
We present evidence of 18%–30% tree mortality from recent droughts across three regions of north-eastern Australia with rainfall deficits less severe than earlier historical droughts. The corrected temperature record represents modest warming at the stations with long records in the vicinity of the study areas. In terms of rainfall deficit the most severe drought on record occurred in the early 20th century, and historical evidence confirms that this drought and earlier droughts before the advent of pastoralism coincided with substantial tree mortality.
Dramatic declines in woody biomass in response to drought historically occurred more than once a century and are a natural phenomenon in semi-arid Australia. The magnitude of drought-induced tree mortality under natural climate fluctuations requires further investigation in other continents. Widespread drought-induced tree mortality is not just a recent global change phenomenon and has been underestimated as a natural ecological process. However, even more severe forest die-off events from more extreme hotter droughts are predicted if Earth’s warming proceeds as currently projected.
","language":"English","publisher":"Wiley","doi":"10.1111/geb.12858","usgsCitation":"Fensham, R., Laffineur, B., and Allen, C.D., 2019, To what extent is drought-induced tree mortality a natural phenomenon?: Global Ecology and Biogeography, v. 287, no. 3801, p. 365-373, https://doi.org/10.1111/geb.12858.","productDescription":"9 p.","startPage":"365","endPage":"373","ipdsId":"IP-080198","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":389057,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Australia","state":"Queensland","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 142.3828125,\n -27.098253906137884\n ],\n [\n 148.359375,\n -27.098253906137884\n ],\n [\n 148.359375,\n -17.518344187852207\n ],\n [\n 142.3828125,\n -17.518344187852207\n ],\n [\n 142.3828125,\n -27.098253906137884\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"287","issue":"3801","noUsgsAuthors":false,"publicationDate":"2019-01-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Fensham, R.","contributorId":68124,"corporation":false,"usgs":true,"family":"Fensham","given":"R.","affiliations":[],"preferred":false,"id":823005,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Laffineur, Boris","contributorId":265580,"corporation":false,"usgs":false,"family":"Laffineur","given":"Boris","email":"","affiliations":[],"preferred":false,"id":823006,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Allen, Craig D. 0000-0002-8777-5989 craig_allen@usgs.gov","orcid":"https://orcid.org/0000-0002-8777-5989","contributorId":2597,"corporation":false,"usgs":true,"family":"Allen","given":"Craig","email":"craig_allen@usgs.gov","middleInitial":"D.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":823007,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70227779,"text":"70227779 - 2019 - A seascape-scale habitat model to support management of fishing impacts on benthic ecosystems","interactions":[],"lastModifiedDate":"2022-01-31T14:52:59.91393","indexId":"70227779","displayToPublicDate":"2019-01-09T08:48:49","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1169,"text":"Canadian Journal of Fisheries and Aquatic Sciences","active":true,"publicationSubtype":{"id":10}},"title":"A seascape-scale habitat model to support management of fishing impacts on benthic ecosystems","docAbstract":"Minimizing fishing impacts on seafloor ecosystems is a growing focus of ocean management; however, few quantitative tools exist to guide seascape-scale habitat management. To meet these needs, we developed a model to assess benthic ecosystem impacts from fishing gear contact. The habitat impacts model is cast in discrete time and can accommodate overlapping fisheries as well as incorporate gear-specific contact dynamics. We implemented the model in the North Pacific using fishing data from 2003 to 2017, estimating that habitat in 3.1% of the 1.2 million km2 study area was disturbed at the end of the simulation period. A marked decline in habitat disturbance was evident since 2010, attributable to a single regulatory gear change that lifted trawl gear components off the seafloor. Running scenarios without these gear modifications showed these policies might have contributed to a 24% reduction in habitat disturbance since their implementation. Ultimately, model outputs provide direct estimates of the spatial and temporal trends of habitat effects from fishing — a key component of regulatory policies for many of the world’s fisheries.
","language":"English","publisher":"Canadian Science Publishing","doi":"10.1139/cjfas-2018-0243","usgsCitation":"Smeltz, T.S., Harris, B., Olson, J., and Sethi, S., 2019, A seascape-scale habitat model to support management of fishing impacts on benthic ecosystems: Canadian Journal of Fisheries and Aquatic Sciences, v. 76, no. 10, p. 1836-1844, https://doi.org/10.1139/cjfas-2018-0243.","productDescription":"9 p.","startPage":"1836","endPage":"1844","ipdsId":"IP-092665","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":468002,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://www.nrcresearchpress.com/doi/abs/10.1139/cjfas-2018-0243","text":"External Repository"},{"id":395132,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"76","issue":"10","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Smeltz, T. Scott","contributorId":272598,"corporation":false,"usgs":false,"family":"Smeltz","given":"T.","email":"","middleInitial":"Scott","affiliations":[{"id":12915,"text":"Alaska Pacific University","active":true,"usgs":false}],"preferred":false,"id":832207,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Harris, Bradley","contributorId":272599,"corporation":false,"usgs":false,"family":"Harris","given":"Bradley","affiliations":[{"id":12915,"text":"Alaska Pacific University","active":true,"usgs":false}],"preferred":false,"id":832208,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Olson, John","contributorId":272600,"corporation":false,"usgs":false,"family":"Olson","given":"John","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":832209,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sethi, Suresh 0000-0002-0053-1827 ssethi@usgs.gov","orcid":"https://orcid.org/0000-0002-0053-1827","contributorId":191424,"corporation":false,"usgs":true,"family":"Sethi","given":"Suresh","email":"ssethi@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":832206,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70215987,"text":"70215987 - 2019 - Improving estimates and forecasts of lake carbon dynamics using data assimilation","interactions":[],"lastModifiedDate":"2020-11-03T14:07:26.459331","indexId":"70215987","displayToPublicDate":"2019-01-09T08:04:29","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2622,"text":"Limnology and Oceanography: Methods","active":true,"publicationSubtype":{"id":10}},"title":"Improving estimates and forecasts of lake carbon dynamics using data assimilation","docAbstract":"Lakes are biogeochemical hotspots on the landscape, contributing significantly to the global carbon cycle despite their small areal coverage. Observations and models of lake carbon pools and fluxes are rarely explicitly combined through data assimilation despite successful use of this technique in other fields. Data assimilation adds value to both observations and models by constraining models with observations of the system and by leveraging knowledge of the system formalized by the model to objectively fill observation gaps. In this article, we highlight the utility of data assimilation in lake carbon cycling research by using the ensemble Kalman filter to combine simple lake carbon models with observations of lake carbon pools and fluxes. We demonstrate that data assimilation helps reduce uncertainty in estimates of lake carbon pools and fluxes and more accurately estimate the true carbon pool size compared to estimates derived from observations alone. Data assimilation techniques should be embraced as valuable tools for lake biogeochemists interested in learning about ecosystem dynamics and forecasting ecosystem states and processes.
Tree mortality is a key driver of forest dynamics and its occurrence is projected to increase in the future due to climate change. Despite recent advances in our understanding of the physiological mechanisms leading to death, we still lack robust indicators of mortality risk that could be applied at the individual tree scale. Here, we build on a previous contribution exploring the differences in growth level between trees that died and survived a given mortality event to assess whether changes in temporal autocorrelation, variance, and synchrony in time-series of annual radial growth data can be used as early warning signals of mortality risk. Taking advantage of a unique global ring-width database of 3065 dead trees and 4389 living trees growing together at 198 sites (belonging to 36 gymnosperm and angiosperm species), we analyzed temporal changes in autocorrelation, variance, and synchrony before tree death (diachronic analysis), and also compared these metrics between trees that died and trees that survived a given mortality event (synchronic analysis). Changes in autocorrelation were a poor indicator of mortality risk. However, we found a gradual increase in inter-annual growth variability and a decrease in growth synchrony in the last ∼20 years before mortality of gymnosperms, irrespective of the cause of mortality. These changes could be associated with drought-induced alterations in carbon economy and allocation patterns. In angiosperms, we did not find any consistent changes in any metric. Such lack of any signal might be explained by the relatively high capacity of angiosperms to recover after a stress-induced growth decline. Our analysis provides a robust method for estimating early-warning signals of tree mortality based on annual growth data. In addition to the frequently reported decrease in growth rates, an increase in inter-annual growth variability and a decrease in growth synchrony may be powerful predictors of gymnosperm mortality risk, but not necessarily so for angiosperms.
","language":"English","publisher":"Frontiers Media","doi":"10.3389/fpls.2018.01964","usgsCitation":"Cailleret, M., Dakos, V., Jansen, S., Robert, E., Aakala, T., Amoroso, M.M., Antos, J., Bigler, C., Bugmann, H., Caccianaga, M., Camarero, J., Cherubini, P., Coyea, M.R., Cufar, K., Das, A., Davi, H., Gea-Izquierdo, G., Gillner, S., Haavik, L.J., Hartmann, H., Heres, A., Hultine, K.R., Janda, P., Kane, J.M., Kharuk, V.I., Kitzberger, T., Klein, T., Levanic, T., Linares, J., Lombardi, F., Makinen, H., Mészáros, I., Metsaranta, J.M., Oberhuber, W., Papadopoulos, A., Petritan, A.M., Rohner, B., Sanguesa-Barreda, G., Smith, J.M., Stan, A.B., Stojanovic, D.B., Suarez, M., Svoboda, M., Trotsiuk, V., Villalba, R., Westwood, A.R., Wyckoff, P.H., and Martínez-Vilalta, J., 2019, Early-warning signals of individual tree mortality based on annual radial growth: Frontiers in Plant Science, v. 9, p. 1-14, https://doi.org/10.3389/fpls.2018.01964.","productDescription":"Article 1964; 14 p.","startPage":"1","endPage":"14","ipdsId":"IP-101375","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":468003,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fpls.2018.01964","text":"Publisher Index Page"},{"id":360792,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"9","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2019-01-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Cailleret, Maxime 0000-0001-6561-1943","orcid":"https://orcid.org/0000-0001-6561-1943","contributorId":181952,"corporation":false,"usgs":false,"family":"Cailleret","given":"Maxime","email":"","affiliations":[],"preferred":false,"id":755204,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dakos, Vasilis","contributorId":198880,"corporation":false,"usgs":false,"family":"Dakos","given":"Vasilis","email":"","affiliations":[],"preferred":false,"id":755205,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jansen, Steven","contributorId":181953,"corporation":false,"usgs":false,"family":"Jansen","given":"Steven","email":"","affiliations":[],"preferred":false,"id":755206,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Robert, Elisabeth M. 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R.","affiliations":[{"id":38352,"text":"Vrije Universiteit Brussel, Royal Museum for Central Africa, Cerdanyola del Valles","active":true,"usgs":false}],"preferred":false,"id":755207,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Aakala, Tuomas","contributorId":181956,"corporation":false,"usgs":false,"family":"Aakala","given":"Tuomas","email":"","affiliations":[],"preferred":false,"id":755208,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Amoroso, Mariano M.","contributorId":211920,"corporation":false,"usgs":false,"family":"Amoroso","given":"Mariano","email":"","middleInitial":"M.","affiliations":[{"id":38353,"text":"Consejo Nacional de Investigaciones Cientificas y Tecnicas","active":true,"usgs":false}],"preferred":false,"id":755209,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Antos, Joe A.","contributorId":211921,"corporation":false,"usgs":false,"family":"Antos","given":"Joe A.","affiliations":[{"id":16829,"text":"University of 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Economic methods for valuing nonmarket public goods include actual behavior-based revealed preference methods, such as the hedonic property method for urban-suburban public goods and travel cost models for outdoor recreation. For valuing proposed public goods for which there is no current behavior, or valuing the existence or passive use values of public goods, economists can rely on stated preference methods. While there is skepticism among some economists for relying on what people say they will pay rather than what their actual behavior suggests they will pay, there is general acceptance of stated preference methods. These stated preference methods include the well-known contingent valuation method and choice experiments (sometimes called conjoint analysis). Lastly, in situations where there is neither time nor money to conduct an original revealed or stated preference study, economists can rely on benefit transfers from existing revealed preference and stated preference studies to provide rough estimates of the values of public goods such as water quality, air quality, wetlands, recreation, and endangered species.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Handbook of Regional Science","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Springer Link","doi":"10.1007/978-3-642-36203-3","isbn":"9783642362033","usgsCitation":"Loomis, J.B., Huber, C., and Richardson, L., 2019, Methods of environmental valuation, chap. of Handbook of Regional Science, 25 p., https://doi.org/10.1007/978-3-642-36203-3.","productDescription":"25 p.","onlineOnly":"Y","ipdsId":"IP-102704","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":365069,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Loomis, John B.","contributorId":197268,"corporation":false,"usgs":false,"family":"Loomis","given":"John","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":757238,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Huber, Christopher 0000-0001-8446-8134 chuber@usgs.gov","orcid":"https://orcid.org/0000-0001-8446-8134","contributorId":127600,"corporation":false,"usgs":true,"family":"Huber","given":"Christopher","email":"chuber@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":757236,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Richardson, Leslie","contributorId":197525,"corporation":false,"usgs":false,"family":"Richardson","given":"Leslie","affiliations":[],"preferred":false,"id":757237,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70205031,"text":"70205031 - 2019 - Short-term effects of ambient air pollution and cardiovascular events in Shiraz, Iran, 2009 to 2015","interactions":[],"lastModifiedDate":"2019-08-29T09:18:55","indexId":"70205031","displayToPublicDate":"2019-01-07T09:14:02","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1564,"text":"Environmental Science and Pollution Research","active":true,"publicationSubtype":{"id":10}},"title":"Short-term effects of ambient air pollution and cardiovascular events in Shiraz, Iran, 2009 to 2015","docAbstract":"Air pollution and dust storms are associated with increased cardiovascular hospital admissions. The aim of this study was to investigate the association between short-term exposure to ambient air pollutants and CVD (cardiovascular disease) events in a long-term observational period. The study included the events of cardiovascular diseases (namely coronary artery disease, ischemic heart disease, myocardial infarction, and pneumo thrombo embolism) within the population of Shiraz, from March 21, 2009 to March 20, 2015. Also, each patient’s demographics were recorded. Main meteorological variables and five ambient pollutants (CO, O3, SO2, NO2, and PM10) were recorded. Statistical analysis was performed using linear regression (GLM) and a generalized additive model (GAM) estimating Poisson distribution and adjusted for the main risk factors and ambient meteorological variables. A mild prevalence (51.5%) of coronary artery disease (CAD) was registered in 6425 events. In GLM analysis, we observed an association among the pollutants with the coronary artery disease hospital admissions which was in the order of CO, NO2, and PM10. The highest association of each pollutant with hospital admission was observed as PM10 at lag 4 (RR = 1.08; 95% CI 1.02, 1.14 and p < 0.05), NO2 at lag 0 (RR = 1.22; 95% CI 1.00, 1.48), and CO at lag 0 (RR = 1.52 95% CI = (1.16, 1.99)). However, on dusty days, there were significantly higher numbers of referrals of cardiovascular patients (mean = 7.54 ± 4.44 and p = 0.002,) than on non-dusty days. According to these data, dust storms and some types of pollutants in the air are responsible for more admissions to hospitals for cardiovascular problems.
","language":"English","publisher":"Springer","doi":"10.1007/s11356-018-3952-4","usgsCitation":"Soleimani, Z., Boloorani, A.D., Khalifeh, R., Griffin, D.W., and Mesdaghinia, A., 2019, Short-term effects of ambient air pollution and cardiovascular events in Shiraz, Iran, 2009 to 2015: Environmental Science and Pollution Research, v. 26, no. 7, p. 6359-6367, https://doi.org/10.1007/s11356-018-3952-4.","productDescription":"9 p.","startPage":"6359","endPage":"6367","ipdsId":"IP-097671","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":367056,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Iran","city":"Shiraz","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 52.397918701171875,\n 29.476067910657175\n ],\n [\n 52.6959228515625,\n 29.476067910657175\n ],\n [\n 52.6959228515625,\n 29.742916942840562\n ],\n [\n 52.397918701171875,\n 29.742916942840562\n ],\n [\n 52.397918701171875,\n 29.476067910657175\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"26","issue":"7","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2019-01-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Soleimani, Zahra","contributorId":218616,"corporation":false,"usgs":false,"family":"Soleimani","given":"Zahra","affiliations":[{"id":39870,"text":"Tehran University","active":true,"usgs":false}],"preferred":false,"id":769646,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Boloorani, Ali Darvishi","contributorId":218617,"corporation":false,"usgs":false,"family":"Boloorani","given":"Ali","email":"","middleInitial":"Darvishi","affiliations":[{"id":39870,"text":"Tehran University","active":true,"usgs":false}],"preferred":false,"id":769647,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Khalifeh, Reza","contributorId":218618,"corporation":false,"usgs":false,"family":"Khalifeh","given":"Reza","affiliations":[{"id":39870,"text":"Tehran University","active":true,"usgs":false}],"preferred":false,"id":769648,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Griffin, Dale W. 0000-0003-1719-5812 dgriffin@usgs.gov","orcid":"https://orcid.org/0000-0003-1719-5812","contributorId":2178,"corporation":false,"usgs":true,"family":"Griffin","given":"Dale","email":"dgriffin@usgs.gov","middleInitial":"W.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":769645,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mesdaghinia, Alireza","contributorId":218619,"corporation":false,"usgs":false,"family":"Mesdaghinia","given":"Alireza","affiliations":[{"id":39870,"text":"Tehran University","active":true,"usgs":false}],"preferred":false,"id":769649,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70206808,"text":"70206808 - 2019 - Deer harvest variation in small and large management units in Pennsylvania","interactions":[],"lastModifiedDate":"2019-11-22T08:52:10","indexId":"70206808","displayToPublicDate":"2019-01-06T08:50:12","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3779,"text":"Wildlife Society Bulletin","onlineIssn":"1938-5463","printIssn":"0091-7648","active":true,"publicationSubtype":{"id":10}},"title":"Deer harvest variation in small and large management units in Pennsylvania","docAbstract":"Large game management units often lead to criticisms from hunters because they assume smaller units possess less variation in wildlife populations and more closely represent their local area. In 2003, Pennsylvania, USA, replaced smaller, socio-political county-based management units with larger wildlife management units (WMUs). We tested the hypothesis that smaller county units possessed less variation in antlered and antlerless white-tailed deer (Odocoileus virginianus) harvest densities among municipalities than did larger WMUs. Spatial variation, as measured by standard deviation and coefficient of variation of deer harvested per km2 was similar for antlered deer (county units 0.44 SD, CV = 0.35; WMUs 0.43 SD, CV = 0.38) and antlerless deer (county units 0.71 SD, CV = 0.44; WMUs 0.84 SD, CV = 0.45). We found no support for the assumption that larger management units resulted in greater spatial variation in deer harvest density.","language":"English","publisher":"Wiley","doi":"10.1002/wsb.939","usgsCitation":"Diefenbach, D.R., and Rosenberry, C.S., 2019, Deer harvest variation in small and large management units in Pennsylvania: Wildlife Society Bulletin, v. 43, no. 1, p. 71-76, https://doi.org/10.1002/wsb.939.","productDescription":"6 p.","startPage":"71","endPage":"76","ipdsId":"IP-088912","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":499836,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doaj.org/article/28d177591ed04cc19ac11dbdb1966e66","text":"External Repository"},{"id":369453,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Pennsylvania 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Arabia) from gravity and aeromagnetic data","interactions":[],"lastModifiedDate":"2019-06-13T13:03:29","indexId":"70203802","displayToPublicDate":"2019-01-05T13:01:58","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3525,"text":"Tectonophysics","active":true,"publicationSubtype":{"id":10}},"title":"Crustal structure of the northern Harrat Rahat volcanic field (Saudi Arabia) from gravity and aeromagnetic data","docAbstract":"New gravity data reveal a prominent negative anomaly along the main vent axis of the northern Harrat Rahat volcanic field in Saudi Arabia. The low continues north of the volcanic field onto exposures of Proterozoic rocks, indicating that the low is caused not only by the volcanic field (and possibly also underlying Cenozoic sediments), but also the underlying Proterozoic basement. An inversion of the gravity field guided by analysis of aeromagnetic data indicates (1) a broad depression of the basement surface that is deeper along the main vent axis in the eastern part of the harrat and in the southwest part of the volcanic field and (2) less dense basement beneath the vent axis. Low densities within the basement most likely arise from lithologic variations in the basement, predating Cenozoic volcanism, although our analysis does not rule out small volumes of partial melt and higher temperatures or extensive fracturing at depth.","language":"English","publisher":"Elsevier","doi":"10.1016/j.tecto.2018.11.005","usgsCitation":"Langenheim, V., Ritzinger, B., Zahran, H.M., Shareef, A., and Al-dahri, M., 2019, Crustal structure of the northern Harrat Rahat volcanic field (Saudi Arabia) from gravity and aeromagnetic data: Tectonophysics, v. 750, p. 9-21, https://doi.org/10.1016/j.tecto.2018.11.005.","productDescription":"13 p.","startPage":"9","endPage":"21","ipdsId":"IP-096731","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":364642,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Saudi Arabia","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[42.77933,16.34789],[42.64957,16.77464],[42.34799,17.07581],[42.27089,17.47472],[41.75438,17.83305],[41.22139,18.6716],[40.93934,19.48649],[40.24765,20.17463],[39.80168,20.33886],[39.1394,21.2919],[39.0237,21.98688],[39.06633,22.57966],[38.49277,23.68845],[38.02386,24.07869],[37.48363,24.28549],[37.15482,24.85848],[37.20949,25.08454],[36.93163,25.60296],[36.6396,25.82623],[36.24914,26.57014],[35.64018,27.37652],[35.13019,28.06335],[34.63234,28.05855],[34.78778,28.60743],[34.83222,28.95748],[34.95604,29.35655],[36.06894,29.19749],[36.50121,29.50525],[36.74053,29.86528],[37.50358,30.00378],[37.66812,30.33867],[37.99885,30.5085],[37.00217,31.50841],[39.00489,32.01022],[39.19547,32.16101],[40.39999,31.88999],[41.88998,31.19001],[44.7095,29.17889],[46.56871,29.09903],[47.45982,29.00252],[47.70885,28.52606],[48.41609,28.552],[48.80759,27.68963],[49.29955,27.46122],[49.47091,27.11],[50.15242,26.68966],[50.21294,26.27703],[50.1133,25.94397],[50.23986,25.60805],[50.52739,25.32781],[50.66056,24.9999],[50.81011,24.75474],[51.11242,24.55633],[51.38961,24.62739],[51.57952,24.2455],[51.61771,24.01422],[52.00073,23.00115],[55.0068,22.49695],[55.20834,22.70833],[55.66666,22],[54.99998,19.99999],[52.00001,19],[49.11667,18.61667],[48.18334,18.16667],[47.46669,17.11668],[47,16.95],[46.74999,17.28334],[46.36666,17.23332],[45.4,17.33334],[45.21665,17.43333],[44.06261,17.41036],[43.79152,17.31998],[43.38079,17.57999],[43.1158,17.08844],[43.21838,16.66689],[42.77933,16.34789]]]},\"properties\":{\"name\":\"Saudi Arabia\"}}]}","volume":"750","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Langenheim, Victoria E. 0000-0003-2170-5213 zulanger@usgs.gov","orcid":"https://orcid.org/0000-0003-2170-5213","contributorId":151042,"corporation":false,"usgs":true,"family":"Langenheim","given":"Victoria E.","email":"zulanger@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":764185,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ritzinger, Brent 0000-0002-5379-1390 britzinger@usgs.gov","orcid":"https://orcid.org/0000-0002-5379-1390","contributorId":216213,"corporation":false,"usgs":true,"family":"Ritzinger","given":"Brent","email":"britzinger@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":764186,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Zahran, Hani M. 0000-0002-0029-3822","orcid":"https://orcid.org/0000-0002-0029-3822","contributorId":203711,"corporation":false,"usgs":false,"family":"Zahran","given":"Hani","email":"","middleInitial":"M.","affiliations":[{"id":36695,"text":"Saudi Geological Survey","active":true,"usgs":false}],"preferred":true,"id":764187,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Shareef, Adel","contributorId":216214,"corporation":false,"usgs":false,"family":"Shareef","given":"Adel","email":"","affiliations":[{"id":36695,"text":"Saudi Geological Survey","active":true,"usgs":false}],"preferred":false,"id":764188,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Al-dahri, Maher","contributorId":216215,"corporation":false,"usgs":false,"family":"Al-dahri","given":"Maher","email":"","affiliations":[{"id":36695,"text":"Saudi Geological Survey","active":true,"usgs":false}],"preferred":false,"id":764189,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70204053,"text":"70204053 - 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However, there is still considerable uncertainty as to which class of assessment models is appropriate to use under different circumstances. A common class of models used when age data are available are statistical catch-at-age assessment (SCAA) models, which track annual cohorts through time. When age data are unavailable, as is often the case in invertebrate fisheries where the lack of a bony structure such as otoliths makes aging difficult, statistical catch-at-size assessment (SCSA) models are more often employed, tracking fish or invertebrates through time by size-classes rather than ages. Do SCAA models actually perform better than SCSA models when age data are available, or is this just an assumption we make in fisheries research and management? We examined this question by evaluating the effectiveness of both SCAA and SCSA models in characterizing cisco, Coregonus artedi, population dynamics in Thunder Bay, Ontario. Both models were fit using an integrated framework with multiple sources of data including hydroacoustic estimates of spawning stock, fishery-dependent and -independent age/length compositions, and harvest data. Our results suggest that for cisco in Thunder Bay, data-limitations related to lack of size-composition data over the size range for which cisco growth is rapid resulted in difficulty estimating relative year-class strength within a SCSA. This led to parameter confounding and ultimately the inability to estimate natural mortality within a SCSA. This hampered the utility of a SCSA model in comparison with a SCAA model when age-composition data were available.
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