Non-consumptive effects (NCEs) of predators on prey can be as strong as consumptive effects (CEs) and may be driven by numerous mechanisms, including predator characteristics. Previous work has highlighted the importance of predator characteristics in predicting NCEs, but has not addressed how complex life histories of prey could mediate predator NCEs. We conducted a meta-analysis to compare the effects of predator gape limitation (gape limited or not) and hunting mode (active or sit-and-pursue) on the activity, larval period, and size at metamorphosis of larval aquatic amphibians and invertebrates. Larval prey tended to reduce their activity and require more time to reach metamorphosis in the presence of all predator functional groups, but the responses did not differ from zero. Prey metamorphosed at smaller size in response to non-gape-limited, active predators, but counter to expectations, prey metamorphosed larger when confronted by non-gape-limited, sit-and-pursue predators. These results indicate NCEs on larval prey life history can be strongly influenced by predator functional characteristics. More broadly, our results suggest that understanding predator NCEs would benefit from greater consideration of how prey life history attributes mediate population and community-level outcomes.
","language":"English","publisher":"Springer","doi":"10.1007/s00442-014-2996-5","usgsCitation":"Davenport, J., Hossack, B.R., and Lowe, W.H., 2014, Partitioning the non‑consumptive effects of predators on preywith complex life histories: Oecologia, v. 176, no. 1, p. 149-155, https://doi.org/10.1007/s00442-014-2996-5.","productDescription":"7 p.","startPage":"149","endPage":"155","numberOfPages":"7","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-051612","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":295942,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"176","issue":"1","noUsgsAuthors":false,"publicationDate":"2014-06-26","publicationStatus":"PW","scienceBaseUri":"545ded2de4b0ba8303f92b93","contributors":{"authors":[{"text":"Davenport, Jon M.","contributorId":126727,"corporation":false,"usgs":false,"family":"Davenport","given":"Jon M.","affiliations":[{"id":6583,"text":"University of Montana, Division of Biological Sciences, Missoula, MT, USA 59812","active":true,"usgs":false}],"preferred":false,"id":522748,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hossack, Blake R. 0000-0001-7456-9564 blake_hossack@usgs.gov","orcid":"https://orcid.org/0000-0001-7456-9564","contributorId":1177,"corporation":false,"usgs":true,"family":"Hossack","given":"Blake","email":"blake_hossack@usgs.gov","middleInitial":"R.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":522747,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lowe, Winsor H.","contributorId":126722,"corporation":false,"usgs":false,"family":"Lowe","given":"Winsor","email":"","middleInitial":"H.","affiliations":[{"id":6577,"text":"University of Montana, Division of Biological Sciences, Missoula, MT, 59812, USA.","active":true,"usgs":false}],"preferred":false,"id":522749,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70140770,"text":"70140770 - 2014 - Analysis of regional scale risk to whirling disease in populations of Colorado and Rio Grande cutthroat trout using Bayesian belief network model","interactions":[],"lastModifiedDate":"2015-02-11T11:55:06","indexId":"70140770","displayToPublicDate":"2014-09-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3300,"text":"Risk Analysis","active":true,"publicationSubtype":{"id":10}},"title":"Analysis of regional scale risk to whirling disease in populations of Colorado and Rio Grande cutthroat trout using Bayesian belief network model","docAbstract":"Introduction and spread of the parasite Myxobolus cerebralis, the causative agent of whirling disease, has contributed to the collapse of wild trout populations throughout the intermountain west. Of concern is the risk the disease may have on conservation and recovery of native cutthroat trout. We employed a Bayesian belief network to assess probability of whirling disease in Colorado River and Rio Grande cutthroat trout (Oncorhynchus clarkii pleuriticus and Oncorhynchus clarkii virginalis, respectively) within their current ranges in the southwest United States. Available habitat (as defined by gradient and elevation) for intermediate oligochaete worm host, Tubifex tubifex, exerted the greatest influence on the likelihood of infection, yet prevalence of stream barriers also affected the risk outcome. Management areas that had the highest likelihood of infected Colorado River cutthroat trout were in the eastern portion of their range, although the probability of infection was highest for populations in the southern, San Juan subbasin. Rio Grande cutthroat trout had a relatively low likelihood of infection, with populations in the southernmost Pecos management area predicted to be at greatest risk. The Bayesian risk assessment model predicted the likelihood of whirling disease infection from its principal transmission vector, fish movement, and suggested that barriers may be effective in reducing risk of exposure to native trout populations. Data gaps, especially with regard to location of spawning, highlighted the importance in developing monitoring plans that support future risk assessments and adaptive management for subspecies of cutthroat trout.
","language":"English","publisher":"Wiley-Blackwell Publishing, Inc.","doi":"10.1111/risa.12189","usgsCitation":"Kolb Ayre, K., Caldwell, C.A., Stinson, J., and Landis, W.G., 2014, Analysis of regional scale risk to whirling disease in populations of Colorado and Rio Grande cutthroat trout using Bayesian belief network model: Risk Analysis, v. 34, no. 9, p. 1589-1605, https://doi.org/10.1111/risa.12189.","productDescription":"17 p.","startPage":"1589","endPage":"1605","numberOfPages":"17","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-045113","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":297919,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona, Colorado, New Mexico, Utah, Wyoming","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -112.06054687499999,\n 35.08395557927643\n ],\n [\n -112.06054687499999,\n 43.29320031385282\n ],\n [\n -103.86474609375,\n 43.29320031385282\n ],\n [\n -103.86474609375,\n 35.08395557927643\n ],\n [\n -112.06054687499999,\n 35.08395557927643\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"34","issue":"9","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2014-03-24","publicationStatus":"PW","scienceBaseUri":"54dd2b32e4b08de9379b32a6","contributors":{"authors":[{"text":"Kolb Ayre, Kimberley","contributorId":139236,"corporation":false,"usgs":false,"family":"Kolb Ayre","given":"Kimberley","email":"","affiliations":[],"preferred":false,"id":540444,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Caldwell, Colleen A. 0000-0002-4730-4867 ccaldwel@usgs.gov","orcid":"https://orcid.org/0000-0002-4730-4867","contributorId":3050,"corporation":false,"usgs":true,"family":"Caldwell","given":"Colleen","email":"ccaldwel@usgs.gov","middleInitial":"A.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":540395,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stinson, Jonah","contributorId":139237,"corporation":false,"usgs":false,"family":"Stinson","given":"Jonah","email":"","affiliations":[],"preferred":false,"id":540445,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Landis, Wayne G.","contributorId":73518,"corporation":false,"usgs":true,"family":"Landis","given":"Wayne","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":540446,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70133242,"text":"70133242 - 2014 - Age-specific survival of male golden-cheeked warblers on the Fort Hood Military Reservation, Texas","interactions":[],"lastModifiedDate":"2014-11-18T10:01:52","indexId":"70133242","displayToPublicDate":"2014-09-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":947,"text":"Avian Conservation and Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Age-specific survival of male golden-cheeked warblers on the Fort Hood Military Reservation, Texas","docAbstract":"Population models are essential components of large-scale conservation and management plans for the federally endangered Golden-cheeked Warbler (Setophaga chrysoparia; hereafter GCWA). However, existing models are based on vital rate estimates calculated using relatively small data sets that are now more than a decade old. We estimated more current, precise adult and juvenile apparent survival (Φ) probabilities and their associated variances for male GCWAs. In addition to providing estimates for use in population modeling, we tested hypotheses about spatial and temporal variation in Φ. We assessed whether a linear trend in Φ or a change in the overall mean Φ corresponded to an observed increase in GCWA abundance during 1992-2000 and if Φ varied among study plots. To accomplish these objectives, we analyzed long-term GCWA capture-resight data from 1992 through 2011, collected across seven study plots on the Fort Hood Military Reservation using a Cormack-Jolly-Seber model structure within program MARK. We also estimated Φ process and sampling variances using a variance-components approach. Our results did not provide evidence of site-specific variation in adult Φ on the installation. Because of a lack of data, we could not assess whether juvenile Φ varied spatially. We did not detect a strong temporal association between GCWA abundance and Φ. Mean estimates of Φ for adult and juvenile male GCWAs for all years analyzed were 0.47 with a process variance of 0.0120 and a sampling variance of 0.0113 and 0.28 with a process variance of 0.0076 and a sampling variance of 0.0149, respectively. Although juvenile Φ did not differ greatly from previous estimates, our adult Φ estimate suggests previous GCWA population models were overly optimistic with respect to adult survival. These updated Φ probabilities and their associated variances will be incorporated into new population models to assist with GCWA conservation decision making.
","language":"English","publisher":"Resilience Alliance Publications","doi":"10.5751/ACE-00693-090204","usgsCitation":"Duarte, A., Hines, J., Nichols, J., Hatfield, J., and Weckerly, F.W., 2014, Age-specific survival of male golden-cheeked warblers on the Fort Hood Military Reservation, Texas: Avian Conservation and Ecology, v. 9, no. 2, 9 p., https://doi.org/10.5751/ACE-00693-090204.","productDescription":"9 p.","numberOfPages":"9","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-057174","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":472792,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5751/ace-00693-090204","text":"Publisher Index Page"},{"id":296046,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Texas","otherGeospatial":"Fort Hood","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -97.87307739257812,\n 30.99291427996619\n ],\n [\n -97.87307739257812,\n 31.34132223690837\n ],\n [\n -97.47001647949219,\n 31.34132223690837\n ],\n [\n -97.47001647949219,\n 30.99291427996619\n ],\n [\n -97.87307739257812,\n 30.99291427996619\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"9","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5465d62ce4b04d4b7dbd6541","contributors":{"authors":[{"text":"Duarte, Adam","contributorId":28492,"corporation":false,"usgs":false,"family":"Duarte","given":"Adam","affiliations":[{"id":6960,"text":"Department of Biology, Texas State University","active":true,"usgs":false}],"preferred":false,"id":524961,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hines, James E. jhines@usgs.gov","contributorId":3506,"corporation":false,"usgs":true,"family":"Hines","given":"James E.","email":"jhines@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":524960,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nichols, James D. 0000-0002-7631-2890 jnichols@usgs.gov","orcid":"https://orcid.org/0000-0002-7631-2890","contributorId":405,"corporation":false,"usgs":true,"family":"Nichols","given":"James D.","email":"jnichols@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":524962,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hatfield, Jeffrey S. jhatfield@usgs.gov","contributorId":151,"corporation":false,"usgs":true,"family":"Hatfield","given":"Jeffrey S.","email":"jhatfield@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":524963,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Weckerly, Floyd W.","contributorId":10298,"corporation":false,"usgs":false,"family":"Weckerly","given":"Floyd","email":"","middleInitial":"W.","affiliations":[{"id":6960,"text":"Department of Biology, Texas State University","active":true,"usgs":false}],"preferred":false,"id":524964,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70141390,"text":"70141390 - 2014 - Development and characterization of microsatellite markers for the Hawaiian coot, Fulica alai, and Hawaiian gallinule, Gallinula galeata sandvicensis, through next-generation sequencing","interactions":[],"lastModifiedDate":"2015-02-18T14:54:16","indexId":"70141390","displayToPublicDate":"2014-09-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1325,"text":"Conservation Genetics Resources","active":true,"publicationSubtype":{"id":10}},"title":"Development and characterization of microsatellite markers for the Hawaiian coot, Fulica alai, and Hawaiian gallinule, Gallinula galeata sandvicensis, through next-generation sequencing","docAbstract":"We used next generation shotgun sequencing to develop novel microsatellite markers for two endangered waterbirds; the Hawaiian coot (Fulica alai) and Hawaiian gallinule (Gallinula galeata sandvicensis). The 20 loci polymorphic in the Hawaiian coot displayed moderate allelic diversity (average 3.8 alleles/locus) and heterozygosity (average 59.5 %). The 12 loci variable for the Hawaiian gallinule exhibited lower levels of allelic diversity (average 2.4 alleles/locus) and heterozygosity (average 47.5 %). Loci were in linkage equilibrium and only one locus deviated from Hardy–Weinberg equilibrium. These loci are sufficiently variable to assess levels of genetic diversity and will be useful for conservation genetic studies to aid in the management of these endangered waterbirds.
","language":"English","publisher":"Springer Netherlands","doi":"10.1007/s12686-014-0210-z","usgsCitation":"Sonsthagen, S.A., Wilson, R.E., and Underwood, J., 2014, Development and characterization of microsatellite markers for the Hawaiian coot, Fulica alai, and Hawaiian gallinule, Gallinula galeata sandvicensis, through next-generation sequencing: Conservation Genetics Resources, v. 6, no. 3, p. 765-767, https://doi.org/10.1007/s12686-014-0210-z.","productDescription":"3 p.","startPage":"765","endPage":"767","numberOfPages":"3","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-056020","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":298040,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"6","issue":"3","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2014-04-24","publicationStatus":"PW","scienceBaseUri":"54e5c5bce4b02d776a669eb5","contributors":{"authors":[{"text":"Sonsthagen, Sarah A. 0000-0001-6215-5874 ssonsthagen@usgs.gov","orcid":"https://orcid.org/0000-0001-6215-5874","contributorId":3711,"corporation":false,"usgs":true,"family":"Sonsthagen","given":"Sarah","email":"ssonsthagen@usgs.gov","middleInitial":"A.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":540751,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wilson, Robert E. 0000-0003-1800-0183 rewilson@usgs.gov","orcid":"https://orcid.org/0000-0003-1800-0183","contributorId":5718,"corporation":false,"usgs":true,"family":"Wilson","given":"Robert","email":"rewilson@usgs.gov","middleInitial":"E.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":540827,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Underwood, Jared G.","contributorId":139332,"corporation":false,"usgs":false,"family":"Underwood","given":"Jared G.","affiliations":[],"preferred":false,"id":540828,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70137967,"text":"70137967 - 2014 - Cross-scale assessment of potential habitat shifts in a rapidly changing climate","interactions":[],"lastModifiedDate":"2015-01-14T15:42:57","indexId":"70137967","displayToPublicDate":"2014-09-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2100,"text":"Invasive Plant Science and Management","active":true,"publicationSubtype":{"id":10}},"title":"Cross-scale assessment of potential habitat shifts in a rapidly changing climate","docAbstract":"We assessed the ability of climatic, environmental, and anthropogenic variables to predict areas of high-risk for plant invasion and consider the relative importance and contribution of these predictor variables by considering two spatial scales in a region of rapidly changing climate. We created predictive distribution models, using Maxent, for three highly invasive plant species (Canada thistle, white sweetclover, and reed canarygrass) in Alaska at both a regional scale and a local scale. Regional scale models encompassed southern coastal Alaska and were developed from topographic and climatic data at a 2 km (1.2 mi) spatial resolution. Models were applied to future climate (2030). Local scale models were spatially nested within the regional area; these models incorporated physiographic and anthropogenic variables at a 30 m (98.4 ft) resolution. Regional and local models performed well (AUC values > 0.7), with the exception of one species at each spatial scale. Regional models predict an increase in area of suitable habitat for all species by 2030 with a general shift to higher elevation areas; however, the distribution of each species was driven by different climate and topographical variables. In contrast local models indicate that distance to right-of-ways and elevation are associated with habitat suitability for all three species at this spatial level. Combining results from regional models, capturing long-term distribution, and local models, capturing near-term establishment and distribution, offers a new and effective tool for highlighting at-risk areas and provides insight on how variables acting at different scales contribute to suitability predictions. The combinations also provides easy comparison, highlighting agreement between the two scales, where long-term distribution factors predict suitability while near-term do not and vice versa.
","language":"English","publisher":"Weed Science Society of America","doi":"10.1614/IPSM-D-13-00071.1","usgsCitation":"Jarnevich, C.S., Holcombe, T.R., Bell, E., Carlson, M.L., Graziano, G., Lamb, M., Seefeldt, S.S., and Morisette, J.T., 2014, Cross-scale assessment of potential habitat shifts in a rapidly changing climate: Invasive Plant Science and Management, v. 7, no. 3, p. 491-502, https://doi.org/10.1614/IPSM-D-13-00071.1.","productDescription":"12 p.","startPage":"491","endPage":"502","numberOfPages":"12","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-054976","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":297255,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Kenai Peninsula, Prince of Wales Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -152.138671875,\n 59.07444815466584\n ],\n [\n -152.138671875,\n 61.07423085631768\n ],\n [\n -147.744140625,\n 61.07423085631768\n ],\n [\n -147.744140625,\n 59.07444815466584\n ],\n [\n -152.138671875,\n 59.07444815466584\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -133.96728515625,\n 54.64205540129178\n ],\n [\n -133.96728515625,\n 56.37133494106981\n ],\n [\n -131.923828125,\n 56.37133494106981\n ],\n [\n -131.923828125,\n 54.64205540129178\n ],\n [\n -133.96728515625,\n 54.64205540129178\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"7","issue":"3","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2017-01-20","publicationStatus":"PW","scienceBaseUri":"54dd2b6be4b08de9379b3379","contributors":{"authors":[{"text":"Jarnevich, Catherine S. 0000-0002-9699-2336 jarnevichc@usgs.gov","orcid":"https://orcid.org/0000-0002-9699-2336","contributorId":3424,"corporation":false,"usgs":true,"family":"Jarnevich","given":"Catherine","email":"jarnevichc@usgs.gov","middleInitial":"S.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":538341,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Holcombe, Tracy R. holcombet@usgs.gov","contributorId":3694,"corporation":false,"usgs":true,"family":"Holcombe","given":"Tracy","email":"holcombet@usgs.gov","middleInitial":"R.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":538342,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bell, Elizabeth 0000-0002-1587-8241","orcid":"https://orcid.org/0000-0002-1587-8241","contributorId":49736,"corporation":false,"usgs":false,"family":"Bell","given":"Elizabeth","email":"","affiliations":[],"preferred":false,"id":538343,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Carlson, Matthew L.","contributorId":138686,"corporation":false,"usgs":false,"family":"Carlson","given":"Matthew","email":"","middleInitial":"L.","affiliations":[{"id":12492,"text":"UAA Alaska Natural Heritage Program & Biological Sciences Department","active":true,"usgs":false}],"preferred":false,"id":538344,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Graziano, Gino","contributorId":138687,"corporation":false,"usgs":false,"family":"Graziano","given":"Gino","email":"","affiliations":[{"id":12493,"text":"UAF Cooperative Extension Service","active":true,"usgs":false}],"preferred":false,"id":538345,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lamb, Melinda","contributorId":138688,"corporation":false,"usgs":false,"family":"Lamb","given":"Melinda","email":"","affiliations":[{"id":6762,"text":"U.S. Forest Service, La Grande, Oregon","active":true,"usgs":false}],"preferred":false,"id":538346,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Seefeldt, Steven S.","contributorId":138689,"corporation":false,"usgs":false,"family":"Seefeldt","given":"Steven","email":"","middleInitial":"S.","affiliations":[{"id":12493,"text":"UAF Cooperative Extension Service","active":true,"usgs":false}],"preferred":false,"id":538347,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Morisette, Jeffrey T. 0000-0002-0483-0082 morisettej@usgs.gov","orcid":"https://orcid.org/0000-0002-0483-0082","contributorId":307,"corporation":false,"usgs":true,"family":"Morisette","given":"Jeffrey","email":"morisettej@usgs.gov","middleInitial":"T.","affiliations":[{"id":569,"text":"Southwest Climate Science Center","active":true,"usgs":true},{"id":477,"text":"North Central Climate Science Center","active":true,"usgs":true}],"preferred":true,"id":538348,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70148148,"text":"70148148 - 2014 - Evaluation of a regional monitoring program's statistical power to detect temporal trends in forest health indicators","interactions":[],"lastModifiedDate":"2015-05-27T13:20:56","indexId":"70148148","displayToPublicDate":"2014-09-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1547,"text":"Environmental Management","active":true,"publicationSubtype":{"id":10}},"title":"Evaluation of a regional monitoring program's statistical power to detect temporal trends in forest health indicators","docAbstract":"Forests are socioeconomically and ecologically important ecosystems that are exposed to a variety of natural and anthropogenic stressors. As such, monitoring forest condition and detecting temporal changes therein remain critical to sound public and private forestland management. The National Parks Service’s Vital Signs monitoring program collects information on many forest health indicators, including species richness, cover by exotics, browse pressure, and forest regeneration. We applied a mixed-model approach to partition variability in data for 30 forest health indicators collected from several national parks in the eastern United States. We then used the estimated variance components in a simulation model to evaluate trend detection capabilities for each indicator. We investigated the extent to which the following factors affected ability to detect trends: (a) sample design: using simple panel versus connected panel design, (b) effect size: increasing trend magnitude, (c) sample size: varying the number of plots sampled each year, and (d) stratified sampling: post-stratifying plots into vegetation domains. Statistical power varied among indicators; however, indicators that measured the proportion of a total yielded higher power when compared to indicators that measured absolute or average values. In addition, the total variability for an indicator appeared to influence power to detect temporal trends more than how total variance was partitioned among spatial and temporal sources. Based on these analyses and the monitoring objectives of theVital Signs program, the current sampling design is likely overly intensive for detecting a 5 % trend·year−1 for all indicators and is appropriate for detecting a 1 % trend·year−1 in most indicators.
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2014 - Uncertainty in the fate of soil organic carbon: A comparison of three conceptually different soil decomposition models","interactions":[],"lastModifiedDate":"2016-03-24T13:53:34","indexId":"70169225","displayToPublicDate":"2014-09-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2319,"text":"Journal of Geophysical Research G: Biogeosciences","active":true,"publicationSubtype":{"id":10}},"title":"Uncertainty in the fate of soil organic carbon: A comparison of three conceptually different soil decomposition models","docAbstract":"Conventional Q10 soil organic matter decomposition models and more complex microbial models are available for making projections of future soil carbon dynamics. However, it is unclear (1) how well the conceptually different approaches can simulate observed decomposition and (2) to what extent the trajectories of long-term simulations differ when using the different approaches. In this study, we compared three structurally different soil carbon (C) decomposition models (one Q10 and two microbial models of different complexity), each with a one- and two-horizon version. The models were calibrated and validated using 4 years of measurements of heterotrophic soil CO2 efflux from trenched plots in a Dahurian larch (Larix gmelinii Rupr.) plantation. All models reproduced the observed heterotrophic component of soil CO2 efflux, but the trajectories of soil carbon dynamics differed substantially in 100 year simulations with and without warming and increased litterfall input, with microbial models that produced better agreement with observed changes in soil organic C in long-term warming experiments. Our results also suggest that both constant and varying carbon use efficiency are plausible when modeling future decomposition dynamics and that the use of a short-term (e.g., a few years) period of measurement is insufficient to adequately constrain model parameters that represent long-term responses of microbial thermal adaption. These results highlight the need to reframe the representation of decomposition models and to constrain parameters with long-term observations and multiple data streams. We urge caution in interpreting future soil carbon responses derived from existing decomposition models because both conceptual and parameter uncertainties are substantial.
","language":"English","publisher":"Wiley","doi":"10.1002/2014JG002701","usgsCitation":"He, Y., Yang, J., Zhuang, Q., McGuire, A.D., Zhu, Q., Liu, Y., and Teskey, R.O., 2014, Uncertainty in the fate of soil organic carbon: A comparison of three conceptually different soil decomposition models: Journal of Geophysical Research G: Biogeosciences, v. 119, no. 9, p. 1892-1905, https://doi.org/10.1002/2014JG002701.","productDescription":"14 p.","startPage":"1892","endPage":"1905","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-055662","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":319372,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"119","issue":"9","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2014-09-18","publicationStatus":"PW","scienceBaseUri":"56f50fd4e4b0f59b85e1ebfb","contributors":{"authors":[{"text":"He, Yujie","contributorId":32444,"corporation":false,"usgs":true,"family":"He","given":"Yujie","affiliations":[],"preferred":false,"id":623771,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Yang, Jinyan","contributorId":166929,"corporation":false,"usgs":false,"family":"Yang","given":"Jinyan","email":"","affiliations":[],"preferred":false,"id":623772,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Zhuang, Qianlai","contributorId":101975,"corporation":false,"usgs":true,"family":"Zhuang","given":"Qianlai","affiliations":[],"preferred":false,"id":623773,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McGuire, A. David 0000-0003-4646-0750 ffadm@usgs.gov","orcid":"https://orcid.org/0000-0003-4646-0750","contributorId":166708,"corporation":false,"usgs":true,"family":"McGuire","given":"A.","email":"ffadm@usgs.gov","middleInitial":"David","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":false,"id":623362,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Zhu, Qing","contributorId":78664,"corporation":false,"usgs":true,"family":"Zhu","given":"Qing","email":"","affiliations":[],"preferred":false,"id":623774,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Liu, Yaling","contributorId":166930,"corporation":false,"usgs":false,"family":"Liu","given":"Yaling","email":"","affiliations":[],"preferred":false,"id":623775,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Teskey, Robert O.","contributorId":87596,"corporation":false,"usgs":true,"family":"Teskey","given":"Robert","email":"","middleInitial":"O.","affiliations":[],"preferred":false,"id":623776,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70168472,"text":"70168472 - 2014 - Factors related to northern goshawk landscape use in the western Great Lakes region","interactions":[],"lastModifiedDate":"2016-02-16T22:12:27","indexId":"70168472","displayToPublicDate":"2014-09-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2442,"text":"Journal of Raptor Research","active":true,"publicationSubtype":{"id":10}},"title":"Factors related to northern goshawk landscape use in the western Great Lakes region","docAbstract":"Northern Goshawks (Accipiter gentilis) are a species of special conservation concern in the western Great Lakes bioregion and elsewhere in North America, and exhibit landscape-scale spatial use patterns. However, little information exists about Northern Goshawk habitat relations at broad spatial extents, as most existing published information comes from a few locations of relatively small spatial extent and, in some cases, short durations. We used an information-theoretic approach to evaluate competing hypotheses regarding factors (forest canopy cover, successional stage, and heights of the canopy top and base) related to odds of Northern Goshawk landscape use throughout the western Great Lakes bioregion based on an occupancy survey completed in 2008 (Bruggeman et al. 2011). We also combined these data with historical data of Northern Goshawk nest locations in the bioregion from 1979–2006 to evaluate the same competing hypotheses to elucidate long-term trends in use. The odds of Northern Goshawk use in 2008, and from 1979–2008, were positively correlated with average percent canopy cover. In the best-approximating models developed using 1979–2008 data, the odds of landscape use were positively correlated with the percentages of the landscape having canopy heights between 10 m and 25 m, and 25 m and 50 m, and the amount of variability in canopy base height. Also, the odds of landscape use were negatively correlated with the average height at the canopy base. Our results suggest multiple habitat factors were related to Northern Goshawk landscape-scale habitat use, similar to habitat use described at smaller spatial scales in the western Great Lakes bioregion and in western North America and Europe.
","language":"English","publisher":"Raptor Research Foundation","publisherLocation":"Hastings, MN","doi":"10.3356/JRR-13-0058.1","usgsCitation":"Bruggeman, J.E., Andersen, D., and Woodford, J.E., 2014, Factors related to northern goshawk landscape use in the western Great Lakes region: Journal of Raptor Research, v. 48, no. 3, p. 228-239, https://doi.org/10.3356/JRR-13-0058.1.","productDescription":"12 p.","startPage":"228","endPage":"239","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-049904","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":472793,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3356/jrr-13-0058.1","text":"Publisher Index Page"},{"id":318102,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Michigan, Minnesota, Wisconsin","otherGeospatial":"Great Lakes","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -97.294921875,\n 49.009050809382046\n ],\n [\n -95.2294921875,\n 48.980216985374994\n ],\n [\n -95.2294921875,\n 49.468124067331644\n ],\n [\n -94.7021484375,\n 49.35375571830993\n ],\n [\n -94.5703125,\n 48.83579746243093\n ],\n [\n -93.955078125,\n 48.66194284607006\n ],\n [\n -93.55957031249999,\n 48.574789910928864\n ],\n [\n -92.7685546875,\n 48.66194284607006\n ],\n [\n -92.28515625,\n 48.429200555568386\n ],\n [\n -91.7578125,\n 48.19538740833338\n ],\n [\n -91.01074218749999,\n 48.16608541901253\n ],\n [\n -90.615234375,\n 48.16608541901253\n ],\n [\n -89.6484375,\n 48.07807894349862\n ],\n [\n -89.296875,\n 48.04870994288686\n ],\n [\n -88.4619140625,\n 48.22467264956519\n ],\n [\n -87.71484375,\n 48.16608541901253\n ],\n [\n -85.517578125,\n 47.249406957888446\n ],\n [\n -84.5068359375,\n 46.649436163350245\n ],\n [\n -84.24316406249999,\n 46.58906908309182\n ],\n [\n -83.8916015625,\n 46.255846818480336\n ],\n [\n -83.583984375,\n 46.13417004624326\n ],\n [\n -83.4521484375,\n 45.89000815866182\n ],\n [\n -82.705078125,\n 45.521743896993634\n ],\n [\n -82.44140625,\n 44.902577996288876\n ],\n [\n -82.08984375,\n 43.70759350405294\n ],\n [\n -82.3974609375,\n 43.03677585761058\n ],\n [\n -82.705078125,\n 42.61779143282346\n ],\n [\n -83.14453125,\n 42.261049162113856\n ],\n [\n -83.408203125,\n 41.86956082699455\n ],\n [\n -84.55078125,\n 41.77131167976407\n ],\n [\n -85.6494140625,\n 41.902277040963696\n ],\n [\n -86.923828125,\n 42.00032514831621\n ],\n [\n -88.0224609375,\n 42.52069952914966\n ],\n [\n -90.9228515625,\n 43.67581809328341\n ],\n [\n -93.3837890625,\n 44.5278427984555\n ],\n [\n -95.2734375,\n 45.67548217560647\n ],\n [\n -96.6796875,\n 46.28622391806708\n ],\n [\n -97.1630859375,\n 47.754097979680026\n ],\n [\n -97.294921875,\n 49.009050809382046\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"48","issue":"3","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"56c45641e4b0946c65218512","contributors":{"authors":[{"text":"Bruggeman, Jason E.","contributorId":18983,"corporation":false,"usgs":false,"family":"Bruggeman","given":"Jason","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":620462,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Andersen, David E. 0000-0001-9535-3404 dea@usgs.gov","orcid":"https://orcid.org/0000-0001-9535-3404","contributorId":2168,"corporation":false,"usgs":true,"family":"Andersen","given":"David E.","email":"dea@usgs.gov","affiliations":[{"id":34539,"text":"Minnesota Cooperative Fish and Wildlife Research Unit","active":true,"usgs":false},{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":620663,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Woodford, James E.","contributorId":60865,"corporation":false,"usgs":false,"family":"Woodford","given":"James","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":620664,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70154987,"text":"70154987 - 2014 - Circulating fat-soluble vitamin concentrations and nutrient composition of aquatic prey eaten by American oystercatchers (Haematopus palliatus) in the southeastern United States","interactions":[],"lastModifiedDate":"2015-07-22T13:09:28","indexId":"70154987","displayToPublicDate":"2014-09-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2191,"text":"Journal of Avian Medicine and Surgery","active":true,"publicationSubtype":{"id":10}},"title":"Circulating fat-soluble vitamin concentrations and nutrient composition of aquatic prey eaten by American oystercatchers (Haematopus palliatus) in the southeastern United States","docAbstract":"The American oystercatcher (Haematopus palliatus palliatus) is currently listed as a species of high concern by the United States Shorebird Conservation Plan. Because nutritional status directly impacts overall health and reproduction of individuals and populations, adequate management of a wildlife population requires intimate knowledge of a species' diet and nutrient requirements. Fat-soluble vitamin concentrations in blood plasma obtained from American oystercatchers and proximate, vitamin, and mineral composition of various oystercatcher prey species were determined as baseline data to assess nutritional status and nutrient supply. Bird and prey species samples were collected from the Cape Romain region, South Carolina, USA, and the Altamaha River delta islands, Georgia, USA, where breeding populations appear relatively stable in recent years. Vitamin A levels in blood samples were higher than ranges reported as normal for domestic avian species, and vitamin D concentrations were lower than anticipated based on values observed in poultry. Vitamin E levels were within ranges previously reported for avian groups with broadly similar feeding niches such as herons, gulls, and terns (eg, aquatic/estuarine/marine). Prey species (oysters, mussels, clams, blood arks [Anadara ovalis], whelks [Busycon carica], false angel wings [Petricola pholadiformis]) were similar in water content to vertebrate prey, moderate to high in protein, and moderate to low in crude fat. Ash and macronutrient concentrations in prey species were high compared with requirements of carnivores or avian species. Prey items analyzed appear to meet nutritional requirements for oystercatchers, as estimated by extrapolation from domestic carnivores and poultry species; excesses, imbalances, and toxicities—particularly of minerals and fat-soluble vitamins—may warrant further investigation.
","language":"English","publisher":"Association of Avian Veterinarians","doi":"10.1647/2013-033","usgsCitation":"Carlson-Bremer, D., Norton, T., Sanders, F.J., Winn, B., Spinks, M.D., Glatt, B.A., Mazzaro, L., Jodice, P.G., Chen, T.C., and Dierenfeld, E.S., 2014, Circulating fat-soluble vitamin concentrations and nutrient composition of aquatic prey eaten by American oystercatchers (Haematopus palliatus) in the southeastern United States: Journal of Avian Medicine and Surgery, v. 28, no. 3, p. 216-224, https://doi.org/10.1647/2013-033.","productDescription":"9 p.","startPage":"216","endPage":"224","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-033674","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":305895,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Georgia, South Carolina","otherGeospatial":"Cape Romain; Wolfe Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -79.40162658691405,\n 33.008087679871835\n ],\n [\n -79.40162658691405,\n 33.10534697199519\n ],\n [\n -79.288330078125,\n 33.10534697199519\n ],\n [\n -79.288330078125,\n 33.008087679871835\n ],\n [\n -79.40162658691405,\n 33.008087679871835\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -81.33865356445312,\n 31.315514771622293\n ],\n [\n -81.33865356445312,\n 31.371226579385738\n ],\n [\n -81.27204895019531,\n 31.371226579385738\n ],\n [\n -81.27204895019531,\n 31.315514771622293\n ],\n [\n -81.33865356445312,\n 31.315514771622293\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"28","issue":"3","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"55b0beaae4b09a3b01b53081","contributors":{"authors":[{"text":"Carlson-Bremer, Daphne","contributorId":27304,"corporation":false,"usgs":false,"family":"Carlson-Bremer","given":"Daphne","email":"","affiliations":[],"preferred":false,"id":565312,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Norton, Terry M.","contributorId":71020,"corporation":false,"usgs":true,"family":"Norton","given":"Terry M.","affiliations":[],"preferred":false,"id":565313,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sanders, Felicia J.","contributorId":56574,"corporation":false,"usgs":false,"family":"Sanders","given":"Felicia","email":"","middleInitial":"J.","affiliations":[{"id":35670,"text":"South Carolina Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":565314,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Winn, Brad","contributorId":90852,"corporation":false,"usgs":true,"family":"Winn","given":"Brad","email":"","affiliations":[],"preferred":false,"id":565315,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Spinks, Mark D.","contributorId":140933,"corporation":false,"usgs":false,"family":"Spinks","given":"Mark","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":565316,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Glatt, Batsheva A.","contributorId":145791,"corporation":false,"usgs":false,"family":"Glatt","given":"Batsheva","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":565317,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Mazzaro, Lisa","contributorId":145792,"corporation":false,"usgs":false,"family":"Mazzaro","given":"Lisa","email":"","affiliations":[],"preferred":false,"id":565318,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Jodice, Patrick G.R. 0000-0001-8716-120X pjodice@usgs.gov","orcid":"https://orcid.org/0000-0001-8716-120X","contributorId":1119,"corporation":false,"usgs":true,"family":"Jodice","given":"Patrick","email":"pjodice@usgs.gov","middleInitial":"G.R.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":false,"id":564466,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Chen, Tai C.","contributorId":145793,"corporation":false,"usgs":false,"family":"Chen","given":"Tai","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":565319,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Dierenfeld, Ellen S.","contributorId":7677,"corporation":false,"usgs":true,"family":"Dierenfeld","given":"Ellen","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":565320,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70162586,"text":"70162586 - 2014 - Heterogeneous occupancy and density estimates of the pathogenic fungus Batrachochytrium dendrobatidis in waters of North America","interactions":[],"lastModifiedDate":"2018-03-21T15:01:40","indexId":"70162586","displayToPublicDate":"2014-09-01T00:00:00","publicationYear":"2014","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":"Heterogeneous occupancy and density estimates of the pathogenic fungus Batrachochytrium dendrobatidis in waters of North America","docAbstract":"Biodiversity losses are occurring worldwide due to a combination of stressors. For example, by one estimate, 40% of amphibian species are vulnerable to extinction, and disease is one threat to amphibian populations. The emerging infectious disease chytridiomycosis, caused by the aquatic fungus Batrachochytrium dendrobatidis (Bd), is a contributor to amphibian declines worldwide. Bd research has focused on the dynamics of the pathogen in its amphibian hosts, with little emphasis on investigating the dynamics of free-living Bd. Therefore, we investigated patterns of Bd occupancy and density in amphibian habitats using occupancy models, powerful tools for estimating site occupancy and detection probability. Occupancy models have been used to investigate diseases where the focus was on pathogen occurrence in the host. We applied occupancy models to investigate free-living Bd in North American surface waters to determine Bd seasonality, relationships between Bd site occupancy and habitat attributes, and probability of detection from water samples as a function of the number of samples, sample volume, and water quality. We also report on the temporal patterns of Bd density from a 4-year case study of a Bd-positive wetland. We provide evidence that Bd occurs in the environment year-round. Bd exhibited temporal and spatial heterogeneity in density, but did not exhibit seasonality in occupancy. Bd was detected in all months, typically at less than 100 zoospores L−1. The highest density observed was ∼3 million zoospores L−1. We detected Bd in 47% of sites sampled, but estimated that Bd occupied 61% of sites, highlighting the importance of accounting for imperfect detection. When Bd was present, there was a 95% chance of detecting it with four samples of 600 ml of water or five samples of 60 mL. Our findings provide important baseline information to advance the study of Bd disease ecology, and advance our understanding of amphibian exposure to free-living Bd in aquatic habitats over time.
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off Fire Island, New York was mapped in 2011 using interferometric sonar and high-resolution chirp seismic-reflection systems. The area mapped is approximately 50 km long by 8 km wide, extending from Moriches Inlet to Fire Island Inlet in water depths ranging from 8 to 32 m. The morphology of this inner-continental shelf region and modern sediment distribution patterns are determined by erosion of Pleistocene glaciofluvial sediments during the ongoing Holocene marine transgression; much of the shelf is thus an actively forming ravinement surface. Remnants of a Pleistocene outwash lobe define a submerged headland offshore of central Fire Island. East of the submerged headland, relatively older Pleistocene outwash is exposed over much of the inner-continental shelf and covered by asymmetric, sorted bedforms interpreted to indicate erosion and westward transport of reworked sediment. Erosion of the eastern flank of the submerged Pleistocene headland over the last ~ 8000 years yielded an abundance of modern sand that was transported westward and reworked into a field of shoreface-attached ridges offshore of western Fire Island. West of the submerged headland, erosion of Pleistocene outwash continues in troughs between the sand ridges, resulting in modification of the lower shoreface. Comparison of the modern sand ridge morphology with the morphology of the underlying ravinement surface suggests that the sand ridges have moved a minimum of ~ 1000 m westward since formation. Comparison of modern sediment thickness mapped in 1996–1997 and 2011 allows speculation that the nearshore/shoreface sedimentary deposit has gained sediment at the expense of deflation of the sand ridges.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.margeo.2014.06.011","usgsCitation":"Schwab, W.C., Baldwin, W.E., Denny, J.F., Hapke, C.J., Gayes, P.T., List, J.H., and Warner, J., 2014, Modification of the Quaternary stratigraphic framework of the inner-continental shelf by Holocene marine transgression: An example offshore of Fire Island, New York: Marine Geology, v. 355, p. 346-360, https://doi.org/10.1016/j.margeo.2014.06.011.","productDescription":"15 p.","startPage":"346","endPage":"360","ipdsId":"IP-057751","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":472795,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1016/j.margeo.2014.06.011","text":"External Repository"},{"id":328582,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New York","otherGeospatial":"Fire Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -73.3172607421875,\n 40.62333412763721\n ],\n [\n -72.75283813476562,\n 40.76806170936614\n ],\n [\n -72.6690673828125,\n 40.62541876792774\n ],\n [\n -73.24172973632812,\n 40.47202439692057\n ],\n [\n -73.3172607421875,\n 40.62333412763721\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"355","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57d9233ce4b090824ffa1ad1","contributors":{"authors":[{"text":"Schwab, William C. 0000-0001-9274-5154 bschwab@usgs.gov","orcid":"https://orcid.org/0000-0001-9274-5154","contributorId":417,"corporation":false,"usgs":true,"family":"Schwab","given":"William","email":"bschwab@usgs.gov","middleInitial":"C.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":648642,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Baldwin, Wayne E. 0000-0001-5886-0917 wbaldwin@usgs.gov","orcid":"https://orcid.org/0000-0001-5886-0917","contributorId":1321,"corporation":false,"usgs":true,"family":"Baldwin","given":"Wayne","email":"wbaldwin@usgs.gov","middleInitial":"E.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":648643,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Denny, Jane F. 0000-0002-3472-618X jdenny@usgs.gov","orcid":"https://orcid.org/0000-0002-3472-618X","contributorId":418,"corporation":false,"usgs":true,"family":"Denny","given":"Jane","email":"jdenny@usgs.gov","middleInitial":"F.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":648644,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hapke, Cheryl J. 0000-0002-2753-4075 chapke@usgs.gov","orcid":"https://orcid.org/0000-0002-2753-4075","contributorId":2981,"corporation":false,"usgs":true,"family":"Hapke","given":"Cheryl","email":"chapke@usgs.gov","middleInitial":"J.","affiliations":[{"id":6676,"text":"USGS (retired)","active":true,"usgs":false}],"preferred":true,"id":648645,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gayes, Paul T.","contributorId":86466,"corporation":false,"usgs":false,"family":"Gayes","given":"Paul","email":"","middleInitial":"T.","affiliations":[{"id":24750,"text":"Coastal Carolina University","active":true,"usgs":false}],"preferred":false,"id":648646,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"List, Jeffrey H. 0000-0001-8594-2491 jlist@usgs.gov","orcid":"https://orcid.org/0000-0001-8594-2491","contributorId":174581,"corporation":false,"usgs":true,"family":"List","given":"Jeffrey","email":"jlist@usgs.gov","middleInitial":"H.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":648647,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Warner, John C. 0000-0002-3734-8903 jcwarner@usgs.gov","orcid":"https://orcid.org/0000-0002-3734-8903","contributorId":2681,"corporation":false,"usgs":true,"family":"Warner","given":"John C.","email":"jcwarner@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":648648,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70189093,"text":"70189093 - 2014 - Structure and tectonics of the northwestern United States from EarthScope USArray magnetotelluric data","interactions":[],"lastModifiedDate":"2017-06-29T15:06:51","indexId":"70189093","displayToPublicDate":"2014-09-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1427,"text":"Earth and Planetary Science Letters","active":true,"publicationSubtype":{"id":10}},"title":"Structure and tectonics of the northwestern United States from EarthScope USArray magnetotelluric data","docAbstract":"The magnetotelluric component of the EarthScope USArray program has covered over 35% of the continental United States. Resistivity tomography models derived from these data image lithospheric structure and provide constraints on the distribution of fluids and melt within the lithosphere. We present a three-dimensional resistivity model of the northwestern United States which provides new insight into the tectonic assembly of western North America from the Archean to present. Comparison with seismic tomography models reveals regions of correlated and anti-correlated resistivity and velocity that help identify thermal and compositional variations within the lithosphere. Recent (Neogene) tectonic features reflected in the model include the subducting Juan de Fuca–Gorda plate which can be traced beneath the forearc to more than 100 km depth, high lithospheric conductivity along the Snake River Plain, and pronounced lower-crustal and upper-mantle conductivity beneath the Basin and Range. The latter is abruptly terminated to the northwest by the Klamath–Blue Mountains Lineament, which we interpret as an important structure during and since the Mesozoic assembly of the region. This boundary is interpreted to separate hot extended lithosphere from colder, less extended lithosphere. The western edge of Proterozoic North America, as indicated by the Cretaceous initial 87Sr/86Sr = 0.706 contour, is clearly reflected in the resistivity model. We further image an Archean crustal block (“Pend Oreille block”) straddling the Washington/Idaho border, which we speculate separated from the Archean Medicine Hat block in the Proterozoic. Finally, in the modern Cascades forearc, the geometry and internal structure of the Eocene Siletz terrane is reflected in the resistivity model. The apparent eastern edge of the Siletz terrane under the Cascades arc suggests that pre-Tertiary rocks fill the Washington and Oregon back-arc.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.epsl.2013.07.035","usgsCitation":"Bedrosian, P.A., and Feucht, D.W., 2014, Structure and tectonics of the northwestern United States from EarthScope USArray magnetotelluric data: Earth and Planetary Science Letters, v. 402, p. 275-289, https://doi.org/10.1016/j.epsl.2013.07.035.","productDescription":"15 p.","startPage":"275","endPage":"289","ipdsId":"IP-049294","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":343165,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -125.3759765625,\n 35.639441068973944\n ],\n [\n -105,\n 35.639441068973944\n ],\n [\n -105,\n 49.009050809382046\n ],\n [\n -125.3759765625,\n 49.009050809382046\n ],\n [\n -125.3759765625,\n 35.639441068973944\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"402","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"595611c0e4b0d1f9f0506798","contributors":{"authors":[{"text":"Bedrosian, Paul A. 0000-0002-6786-1038 pbedrosian@usgs.gov","orcid":"https://orcid.org/0000-0002-6786-1038","contributorId":839,"corporation":false,"usgs":true,"family":"Bedrosian","given":"Paul","email":"pbedrosian@usgs.gov","middleInitial":"A.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":702835,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Feucht, Daniel W. dfeucht@usgs.gov","contributorId":5022,"corporation":false,"usgs":true,"family":"Feucht","given":"Daniel","email":"dfeucht@usgs.gov","middleInitial":"W.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":702836,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70123000,"text":"sir20145160 - 2014 - 2012 volcanic activity in Alaska: Summary of events and response of the Alaska Volcano Observatory","interactions":[],"lastModifiedDate":"2019-12-16T17:17:34","indexId":"sir20145160","displayToPublicDate":"2014-08-29T16:53:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-5160","title":"2012 volcanic activity in Alaska: Summary of events and response of the Alaska Volcano Observatory","docAbstract":"The Alaska Volcano Observatory (AVO) responded to eruptions, possible eruptions, volcanic unrest, or suspected unrest at 11 volcanic centers in Alaska during 2012. Of the two verified eruptions, one (Cleveland) was clearly magmatic and the other (Kanaga) was most likely a single phreatic explosion. Two other volcanoes had notable seismic swarms that probably were caused by magmatic intrusions (Iliamna and Little Sitkin). For each period of clear volcanic unrest, AVO staff increased monitoring vigilance as needed, reviewed eruptive histories of the volcanoes in question to help evaluate likely outcomes, and shared observations and interpretations with the public. 2012 also was the 100th anniversary of Alaska’s Katmai-Novarupta eruption of 1912, the largest eruption on Earth in the 20th century and one of the most important volcanic eruptions in modern times. AVO marked this occasion with several public events.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145160","collaboration":"The Alaska Volcano Observatory is a cooperative program of the U.S. Geological Survey, University of Alaska Fairbanks Geophysical Institute, and the Alaska Division of Geological and Geophysical Surveys. The Alaska Volcano Observatory is funded by the U.S. Geological Survey Volcano Hazards Program and the State of Alaska","usgsCitation":"Herrick, J.A., Neal, C., Cameron, C., Dixon, J.P., and McGimsey, R.G., 2014, 2012 volcanic activity in Alaska: Summary of events and response of the Alaska Volcano Observatory: U.S. Geological Survey Scientific Investigations Report 2014-5160, vi, 81 p., https://doi.org/10.3133/sir20145160.","productDescription":"vi, 81 p.","numberOfPages":"92","onlineOnly":"Y","ipdsId":"IP-053457","costCenters":[{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":293226,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20145160.jpg"},{"id":293225,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2014/5160/pdf/sir2014-5160.pdf"},{"id":293221,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2014/5160/"}],"country":"United States","state":"Alaska","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"540185afe4b0ae951d95c967","contributors":{"authors":[{"text":"Herrick, Julie A.","contributorId":17151,"corporation":false,"usgs":true,"family":"Herrick","given":"Julie","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":499821,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Neal, Christina A. 0000-0002-7697-7825","orcid":"https://orcid.org/0000-0002-7697-7825","contributorId":82660,"corporation":false,"usgs":true,"family":"Neal","given":"Christina A.","affiliations":[],"preferred":false,"id":499823,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cameron, Cheryl E.","contributorId":37421,"corporation":false,"usgs":true,"family":"Cameron","given":"Cheryl E.","affiliations":[],"preferred":false,"id":499822,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dixon, James P. 0000-0002-8478-9971 jpdixon@usgs.gov","orcid":"https://orcid.org/0000-0002-8478-9971","contributorId":3163,"corporation":false,"usgs":true,"family":"Dixon","given":"James","email":"jpdixon@usgs.gov","middleInitial":"P.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":499820,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McGimsey, Robert G. 0000-0001-5379-7779 mcgimsey@usgs.gov","orcid":"https://orcid.org/0000-0001-5379-7779","contributorId":2352,"corporation":false,"usgs":true,"family":"McGimsey","given":"Robert","email":"mcgimsey@usgs.gov","middleInitial":"G.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":499819,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70118654,"text":"ds875 - 2014 - Geochemical and modal data for igneous rocks associated with epithermal mineral deposits","interactions":[],"lastModifiedDate":"2014-08-29T11:52:06","indexId":"ds875","displayToPublicDate":"2014-08-29T11:49:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"875","title":"Geochemical and modal data for igneous rocks associated with epithermal mineral deposits","docAbstract":"The purposes of this report are to (1) present available geochemical and modal data for igneous rocks associated with epithermal mineral deposits and (2) to make those data widely and readily available for subsequent, more in-depth consideration and interpretation. Epithermal precious and base-metal deposits are commonly associated with subduction-related calc-alkaline to alkaline arc magmatism as well as back-arc continental rift magmatism. These deposits form in association with compositionally diverse extrusive and intrusive igneous rocks. Temperature and depth regimes prevailing during deposit formation are highly variable. The deposits form from hydrothermal fluids that range from acidic to near-neutral pH, and they occur in a variety of structural settings. The disparate temperature, pressure, fluid chemistry, and structural controls have resulted in deposits with wide ranging characteristics. Economic geologists have employed these characteristics to develop classification schemes for epithermal deposits and to constrain the important genetic processes responsible for their formation.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds875","usgsCitation":"du Bray, E.A., 2014, Geochemical and modal data for igneous rocks associated with epithermal mineral deposits: U.S. Geological Survey Data Series 875, Report: iii, 13 p.; Appendix 1, https://doi.org/10.3133/ds875.","productDescription":"Report: iii, 13 p.; Appendix 1","numberOfPages":"20","onlineOnly":"Y","ipdsId":"IP-056326","costCenters":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":293197,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds875.jpg"},{"id":293196,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/ds/875/downloads/EpiMdlDB.xlsx"},{"id":293195,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/875/pdf/ds875.pdf"},{"id":293194,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/875/"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"540185b0e4b0ae951d95c972","contributors":{"authors":[{"text":"du Bray, Edward A. 0000-0002-4383-8394 edubray@usgs.gov","orcid":"https://orcid.org/0000-0002-4383-8394","contributorId":755,"corporation":false,"usgs":true,"family":"du Bray","given":"Edward","email":"edubray@usgs.gov","middleInitial":"A.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":497166,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70122867,"text":"fs20143087 - 2014 - Manganese: it turns iron into steel (and does so much more)","interactions":[],"lastModifiedDate":"2014-08-29T10:27:16","indexId":"fs20143087","displayToPublicDate":"2014-08-29T10:22:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-3087","title":"Manganese: it turns iron into steel (and does so much more)","docAbstract":"Manganese is a common ferrous metal with atomic weight of 25 and the chemical symbol Mn. It constitutes roughly 0.1 percent of the Earth’s crust, making it the 12th most abundant element. Its early uses were limited largely to pigments and oxidants in chemical processes and experiments, but the significance of manganese to human societies exploded with the development of modern steelmaking technology in the 1860s. U.S consumption of manganese is about 500,000 metric tons each year, predominantly by the steel industry. Because manganese is essential and irreplaceable in steelmaking and its global mining industry is dominated by just a few nations, it is considered one of the most critical mineral commodities for the United States.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20143087","collaboration":"USGS Mineral Resources Program","usgsCitation":"Cannon, W.F., 2014, Manganese: it turns iron into steel (and does so much more): U.S. Geological Survey Fact Sheet 2014-3087, 2 p., https://doi.org/10.3133/fs20143087.","productDescription":"2 p.","numberOfPages":"2","onlineOnly":"Y","ipdsId":"IP-045877","costCenters":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":293181,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs20143087.jpg"},{"id":293180,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2014/3087/"},{"id":293179,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2014/3087/pdf/fs2014-3087.pdf"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"540185b3e4b0ae951d95c984","contributors":{"authors":[{"text":"Cannon, William F. 0000-0002-2699-8118 wcannon@usgs.gov","orcid":"https://orcid.org/0000-0002-2699-8118","contributorId":1883,"corporation":false,"usgs":true,"family":"Cannon","given":"William","email":"wcannon@usgs.gov","middleInitial":"F.","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":499693,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70118103,"text":"sir20145142 - 2014 - Hydroclimate of the Spring Mountains and Sheep Range, Clark County, Nevada","interactions":[],"lastModifiedDate":"2014-08-29T10:22:58","indexId":"sir20145142","displayToPublicDate":"2014-08-29T10:15:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-5142","title":"Hydroclimate of the Spring Mountains and Sheep Range, Clark County, Nevada","docAbstract":"Precipitation, potential evapotranspiration, and actual evapotranspiration often are used to characterize the hydroclimate of a region. Quantification of these parameters in mountainous terrains is difficult because limited access often hampers the collection of representative ground data. To fulfill a need to characterize ecological zones in the Spring Mountains and Sheep Range of southern Nevada, spatially and temporally explicit estimates of these hydroclimatic parameters are determined from remote-sensing and model-based methodologies. Parameter-elevation Regressions on Independent Slopes Model (PRISM) precipitation estimates for this area ranges from about 100 millimeters (mm) in the low elevations of the study area (700 meters [m]) to more than 700 mm in the high elevations of the Spring Mountains (> 2,800 m). The PRISM model underestimates precipitation by 7–15 percent based on a comparison with four high‑elevation precipitation gages having more than 20 years of record. Precipitation at 3,000-m elevation is 50 percent greater in the Spring Mountains than in the Sheep Range. The lesser amount of precipitation in the Sheep Range is attributed to partial moisture depletion by the Spring Mountains of eastward-moving, cool-season (October–April) storms. Cool-season storms account for 66–76 percent of annual precipitation. Potential evapotranspiration estimates by the Basin Characterization Model range from about 700 mm in the high elevations of the Spring Mountains to 1,600 mm in the low elevations of the study area. The model realistically simulates lower potential evapotranspiration on northeast-to-northwest facing slopes compared to adjacent southeast-to-southwest facing slopes. Actual evapotranspiration, estimated using a Moderate Resolution Imaging Spectroradiometer based water-balance model, ranges from about 100 to 600 mm. The magnitude and spatial variation of simulated, actual evapotranspiration was validated by comparison to PRISM precipitation. Estimated groundwater recharge, computed as the residual of precipitation depleted by actual evapotranspiration, is within the range of previous estimates. A climatic water deficit dataset and aridity-index-based climate zones are derived from precipitation and evapotranspiration datasets. Climate zones range from arid in the lower elevations of the study area to humid in small pockets on north- to northeast-facing slopes in the high elevations of the Spring Mountains. Correlative analyses between hydroclimatic variables and mean ecosystem elevations indicate that the climatic water deficit is the best predictor of ecosystem distribution (R2 = 0.92). Computed water balances indicate that substantially more recharge is generated in the Spring Mountains than in the Sheep Range. A geospatial database containing compiled and developed hydroclimatic data and other pertinent information accompanies this report.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145142","collaboration":"Prepared in cooperation with the U.S. Forest Service, Bureau of Land Management, and U.S. Fish and Wildlife Service","usgsCitation":"Moreo, M.T., Senay, G.B., Flint, A.L., Damar, N.A., Laczniak, R.J., and Hurja, J., 2014, Hydroclimate of the Spring Mountains and Sheep Range, Clark County, Nevada: U.S. Geological Survey Scientific Investigations Report 2014-5142, Report: 38 p.; 2 Appendices, https://doi.org/10.3133/sir20145142.","productDescription":"Report: 38 p.; 2 Appendices","numberOfPages":"48","ipdsId":"IP-033212","costCenters":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"links":[{"id":293178,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20145142.jpg"},{"id":293176,"type":{"id":3,"text":"Appendix"},"url":"https://water.usgs.gov/lookup/getspatial?sir2014-5142_App1"},{"id":293177,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2014/5142/downloads/sir2014-5142_appendixB.xlsx"},{"id":293175,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2014/5142/pdf/sir2014-5142.pdf"},{"id":293173,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2014/5142/"}],"country":"United States","state":"Nevada","county":"Clark County","otherGeospatial":"Spring Mountains","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -115.81,35.97 ], [ -115.81,36.96 ], [ -114.88,36.96 ], [ -114.88,35.97 ], [ -115.81,35.97 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"540185b2e4b0ae951d95c981","contributors":{"authors":[{"text":"Moreo, Michael T. 0000-0002-9122-6958 mtmoreo@usgs.gov","orcid":"https://orcid.org/0000-0002-9122-6958","contributorId":2363,"corporation":false,"usgs":true,"family":"Moreo","given":"Michael","email":"mtmoreo@usgs.gov","middleInitial":"T.","affiliations":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"preferred":true,"id":496311,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Senay, Gabriel B. 0000-0002-8810-8539 senay@usgs.gov","orcid":"https://orcid.org/0000-0002-8810-8539","contributorId":3114,"corporation":false,"usgs":true,"family":"Senay","given":"Gabriel","email":"senay@usgs.gov","middleInitial":"B.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":496312,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Flint, Alan L. 0000-0002-5118-751X aflint@usgs.gov","orcid":"https://orcid.org/0000-0002-5118-751X","contributorId":1492,"corporation":false,"usgs":true,"family":"Flint","given":"Alan","email":"aflint@usgs.gov","middleInitial":"L.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true},{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":496310,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Damar, Nancy A. 0000-0002-7520-7386 nadamar@usgs.gov","orcid":"https://orcid.org/0000-0002-7520-7386","contributorId":4154,"corporation":false,"usgs":true,"family":"Damar","given":"Nancy","email":"nadamar@usgs.gov","middleInitial":"A.","affiliations":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"preferred":true,"id":496313,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Laczniak, Randell J.","contributorId":90687,"corporation":false,"usgs":true,"family":"Laczniak","given":"Randell","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":496314,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hurja, James","contributorId":91795,"corporation":false,"usgs":true,"family":"Hurja","given":"James","email":"","affiliations":[],"preferred":false,"id":496315,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70123127,"text":"70123127 - 2014 - Laboratory estimation of net trophic transfer efficiencies of PCB congeners to lake trout (Salvelinus namaycush) from its prey","interactions":[],"lastModifiedDate":"2019-03-11T13:52:18","indexId":"70123127","displayToPublicDate":"2014-08-29T08:53:12","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2498,"text":"Journal of Visualized Experiments","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Laboratory estimation of net trophic transfer efficiencies of PCB congeners to lake trout (Salvelinus namaycush) from its prey","title":"Laboratory estimation of net trophic transfer efficiencies of PCB congeners to lake trout (Salvelinus namaycush) from its prey","docAbstract":"A technique for laboratory estimation of net trophic transfer efficiency (γ) of polychlorinated biphenyl (PCB) congeners to piscivorous fish from their prey is described herein. During a 135-day laboratory experiment, we fed bloater (Coregonus hoyi) that had been caught in Lake Michigan to lake trout (Salvelinus namaycush) kept in eight laboratory tanks. Bloater is a natural prey for lake trout. In four of the tanks, a relatively high flow rate was used to ensure relatively high activity by the lake trout, whereas a low flow rate was used in the other four tanks, allowing for low lake trout activity. On a tank-by-tank basis, the amount of food eaten by the lake trout on each day of the experiment was recorded. Each lake trout was weighed at the start and end of the experiment. Four to nine lake trout from each of the eight tanks were sacrificed at the start of the experiment, and all 10 lake trout remaining in each of the tanks were euthanized at the end of the experiment. We determined concentrations of 75 PCB congeners in the lake trout at the start of the experiment, in the lake trout at the end of the experiment, and in bloaters fed to the lake trout during the experiment. Based on these measurements, γ was calculated for each of 75 PCB congeners in each of the eight tanks. Mean γ was calculated for each of the 75 PCB congeners for both active and inactive lake trout. Because the experiment was replicated in eight tanks, the standard error about mean γ could be estimated. Results from this type of experiment are useful in risk assessment models to predict future risk to humans and wildlife eating contaminated fish under various scenarios of environmental contamination.","language":"English","publisher":"MYJoVE Corp","doi":"10.3791/51496","usgsCitation":"Madenjian, C.P., Rediske, R.R., O'Keefe, J., and David, S.R., 2014, Laboratory estimation of net trophic transfer efficiencies of PCB congeners to lake trout (Salvelinus namaycush) from its prey: Journal of Visualized Experiments, v. 90, e51496, https://doi.org/10.3791/51496.","productDescription":"e51496","ipdsId":"IP-052080","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":472805,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.3791/51496","text":"External Repository"},{"id":293246,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":293227,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.3791/51496"}],"volume":"90","noUsgsAuthors":false,"publicationDate":"2014-08-29","publicationStatus":"PW","scienceBaseUri":"5406d9cbe4b044dc0e82896a","contributors":{"authors":[{"text":"Madenjian, Charles P. 0000-0002-0326-164X cmadenjian@usgs.gov","orcid":"https://orcid.org/0000-0002-0326-164X","contributorId":2200,"corporation":false,"usgs":true,"family":"Madenjian","given":"Charles","email":"cmadenjian@usgs.gov","middleInitial":"P.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":499824,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rediske, Richard R.","contributorId":79053,"corporation":false,"usgs":true,"family":"Rediske","given":"Richard","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":499825,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"O'Keefe, James P.","contributorId":99499,"corporation":false,"usgs":true,"family":"O'Keefe","given":"James P.","affiliations":[],"preferred":false,"id":499827,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"David, Solomon R. sdavid@usgs.gov","contributorId":92942,"corporation":false,"usgs":true,"family":"David","given":"Solomon","email":"sdavid@usgs.gov","middleInitial":"R.","affiliations":[],"preferred":false,"id":499826,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70133360,"text":"70133360 - 2014 - Low transient storage and uptake efficiencies in seven agricultural streams: implications for nutrient demand","interactions":[],"lastModifiedDate":"2014-11-14T16:53:14","indexId":"70133360","displayToPublicDate":"2014-08-29T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2262,"text":"Journal of Environmental Quality","active":true,"publicationSubtype":{"id":10}},"title":"Low transient storage and uptake efficiencies in seven agricultural streams: implications for nutrient demand","docAbstract":"We used mass load budgets, transient storage modeling, and nutrient spiraling metrics to characterize nitrate (NO3−), ammonium (NH4+), and inorganic phosphorus (SRP) demand in seven agricultural streams across the United States and to identify in-stream services that may control these conditions. Retention of one or all nutrients was observed in all but one stream, but demand for all nutrients was low relative to the mass in transport. Transient storage metrics (As/A, Fmed200, Tstr, and qs) correlated with NO3− retention but not NH4+ or SRP retention, suggesting in-stream services associated with transient storage and stream water residence time could influence reach-scale NO3− demand. However, because the fraction of median reach-scale travel time due to transient storage (Fmed200) was ≤1.2% across the sites, only a relatively small demand for NO3− could be generated by transient storage. In contrast, net uptake of nutrients from the water column calculated from nutrient spiraling metrics were not significant at any site because uptake lengths calculated from background nutrient concentrations were statistically insignificant and therefore much longer than the study reaches. These results suggest that low transient storage coupled with high surface water NO3− inputs have resulted in uptake efficiencies that are not sufficient to offset groundwater inputs of N. Nutrient retention has been linked to physical and hydrogeologic elements that drive flow through transient storage areas where residence time and biotic contact are maximized; however, our findings indicate that similar mechanisms are unable to generate a significant nutrient demand in these streams relative to the loads.
","language":"English","publisher":"American Society of Agronomy, Crop Science Society of America, Soil Science Society of America","doi":"10.2134/jeq2014.01.0034","usgsCitation":"Sheibley, R.W., Duff, J.H., and Tesoriero, A., 2014, Low transient storage and uptake efficiencies in seven agricultural streams: implications for nutrient demand: Journal of Environmental Quality, v. 43, no. 6, p. 1980-1990, https://doi.org/10.2134/jeq2014.01.0034.","productDescription":"11 p.","startPage":"1980","endPage":"1990","numberOfPages":"11","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-056733","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":296115,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"43","issue":"6","noUsgsAuthors":false,"publicationDate":"2014-11-01","publicationStatus":"PW","scienceBaseUri":"546727bce4b04d4b7dbde879","contributors":{"authors":[{"text":"Sheibley, Rich W. 0000-0003-1627-8536 sheibley@usgs.gov","orcid":"https://orcid.org/0000-0003-1627-8536","contributorId":3044,"corporation":false,"usgs":true,"family":"Sheibley","given":"Rich","email":"sheibley@usgs.gov","middleInitial":"W.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":525004,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Duff, John H. jhduff@usgs.gov","contributorId":961,"corporation":false,"usgs":true,"family":"Duff","given":"John","email":"jhduff@usgs.gov","middleInitial":"H.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":525005,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tesoriero, Anthony J.","contributorId":40207,"corporation":false,"usgs":true,"family":"Tesoriero","given":"Anthony J.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":false,"id":525006,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70173886,"text":"70173886 - 2014 - Post-parturition habitat selection by elk calves and adult female elk in New Mexico","interactions":[],"lastModifiedDate":"2018-02-15T15:14:41","indexId":"70173886","displayToPublicDate":"2014-08-28T14:15:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Post-parturition habitat selection by elk calves and adult female elk in New Mexico","docAbstract":"Neonatal survival and juvenile recruitment are crucial to maintaining viable elk (Cervus elaphus) populations. Neonate survival is known to be influenced by many factors, including bed-site selection. Although neonates select the actual bed-site location, they must do so within the larger calf-rearing area selected by the mother. As calves age, habitat selection should change to meet the changing needs of the growing calf. Our main objectives were to characterize habitat selection at 2 spatial scales and in areas with different predator assemblages in New Mexico. We evaluated bed-site selection by calves and calf-rearing area selection by adult females. We captured 108 elk calves by hand and fitted them with ear tag transmitters in two areas in New Mexico: the Valle Vidal and Blue Range Wolf Recovery Area. In both study areas, we found that concealing cover structure and distance to that cover influenced bed-site selection of young calves (i.e., <2 weeks of age). Older calves (i.e., 3–10 weeks of age) still selected areas in relation to distance to cover, but also preferred areas with higher visibility. At the larger spatial scale of calf-rearing habitat selection by the adult female, concealing cover (e.g., rocks, shrubs, and logs) and other variables important to the hiding calves were still in the most supported models, but selection was also influenced by forage availability and indices of forage quality. Studies that seek to obtain insight into microhabitat selection of ungulate neonates should consider selection by the neonate and selection by the adult female, changes in selection as neonates age, and potential selection differences in areas of differing predation risk. By considering these influences together and at multiple scales, studies can achieve a broader understanding of neonatal ungulate habitat requirements.
","language":"English","publisher":"The Wildlife Society","publisherLocation":"Bethesda, MD","doi":"10.1002/jwmg.776","usgsCitation":"Pitman, J.W., Cain, J.W., Liley, S., Gould, W., Quintana, N.T., and Ballard, W., 2014, Post-parturition habitat selection by elk calves and adult female elk in New Mexico: Journal of Wildlife Management, v. 78, no. 7, p. 1216-1227, https://doi.org/10.1002/jwmg.776.","productDescription":"12 p.","startPage":"1216","endPage":"1227","numberOfPages":"12","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-054883","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":323701,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Mexico","otherGeospatial":"Valle Vidal--Northeast New Mexico; Blue Range Wolf Recovery Area--southwest New Mexico, coincides with Gila National Forest","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -109.05029296875,\n 32.36140331527543\n ],\n [\n -109.05029296875,\n 34.30714385628804\n ],\n [\n -107.545166015625,\n 34.30714385628804\n ],\n [\n -107.545166015625,\n 32.36140331527543\n ],\n [\n -109.05029296875,\n 32.36140331527543\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -105.09521484375,\n 36.527294814546245\n ],\n [\n -105.09521484375,\n 36.97622678464096\n ],\n [\n -104.534912109375,\n 36.97622678464096\n ],\n [\n -104.534912109375,\n 36.527294814546245\n ],\n [\n -105.09521484375,\n 36.527294814546245\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"78","issue":"7","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2014-08-26","publicationStatus":"PW","scienceBaseUri":"57627c37e4b07657d19a6a0d","contributors":{"authors":[{"text":"Pitman, James W.","contributorId":113799,"corporation":false,"usgs":false,"family":"Pitman","given":"James","email":"","middleInitial":"W.","affiliations":[{"id":24672,"text":"New Mexico Department of Game and Fish","active":true,"usgs":false}],"preferred":false,"id":639065,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cain, James W. III 0000-0003-4743-516X jwcain@usgs.gov","orcid":"https://orcid.org/0000-0003-4743-516X","contributorId":4063,"corporation":false,"usgs":true,"family":"Cain","given":"James","suffix":"III","email":"jwcain@usgs.gov","middleInitial":"W.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":639064,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Liley, Stewart","contributorId":171908,"corporation":false,"usgs":false,"family":"Liley","given":"Stewart","affiliations":[],"preferred":false,"id":639066,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gould, William R.","contributorId":63780,"corporation":false,"usgs":true,"family":"Gould","given":"William R.","affiliations":[],"preferred":false,"id":639067,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Quintana, Nichole T.","contributorId":171911,"corporation":false,"usgs":false,"family":"Quintana","given":"Nichole","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":639068,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ballard, Warren","contributorId":80398,"corporation":false,"usgs":true,"family":"Ballard","given":"Warren","affiliations":[],"preferred":false,"id":639069,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70122284,"text":"70122284 - 2014 - A nuclear DNA perspective on delineating evolutionarily significant lineages in polyploids: the case of the endangered shortnose sturgeon (Acipenser brevirostrum)","interactions":[],"lastModifiedDate":"2014-09-23T13:58:35","indexId":"70122284","displayToPublicDate":"2014-08-28T13:57:00","publicationYear":"2014","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":"A nuclear DNA perspective on delineating evolutionarily significant lineages in polyploids: the case of the endangered shortnose sturgeon (Acipenser brevirostrum)","docAbstract":"The shortnose sturgeon, Acipenser brevirostrum, oft considered a phylogenetic relic, is listed as an “endangered species threatened with extinction” in the US and “Vulnerable” on the IUCN Red List. Effective conservation of A. brevirostrum depends on understanding its diversity and evolutionary processes, yet challenges associated with the polyploid nature of its nuclear genome have heretofore limited population genetic analysis to maternally inherited haploid characters. We developed a suite of polysomic microsatellite DNA markers and characterized a sample of 561 shortnose sturgeon collected from major extant populations along the North American Atlantic coast. The 181 alleles observed at 11 loci were scored as binary loci and the data were subjected to multivariate ordination, Bayesian clustering, hierarchical partitioning of variance, and among-population distance metric tests. The methods uncovered moderately high levels of gene diversity suggesting population structuring across and within three metapopulations (Northeast, Mid-Atlantic, and Southeast) that encompass seven demographically discrete and evolutionarily distinct lineages. The predicted groups are consistent with previously described behavioral patterns, especially dispersal and migration, supporting the interpretation that A. brevirostrum exhibit adaptive differences based on watershed. Combined with results of prior genetic (mitochondrial DNA) and behavioral studies, the current work suggests that dispersal is an important factor in maintaining genetic diversity in A. brevirostrum and that the basic unit for conservation management is arguably the local population.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"PLoS ONE","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"PLoS ONE","doi":"10.1371/journal.pone.0102784","usgsCitation":"King, T.L., Henderson, A.P., Kynard, B.E., Kieffer, M.C., Peterson, D.L., Aunins, A.W., and Brown, B.L., 2014, A nuclear DNA perspective on delineating evolutionarily significant lineages in polyploids: the case of the endangered shortnose sturgeon (Acipenser brevirostrum): PLoS ONE, v. 9, no. 8, e102784, https://doi.org/10.1371/journal.pone.0102784.","productDescription":"e102784","numberOfPages":"16","ipdsId":"IP-055543","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"links":[{"id":472806,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0102784","text":"Publisher Index Page"},{"id":294357,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":294356,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1371/journal.pone.0102784"}],"country":"United States","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -83.84,30.5 ], [ -83.84,46.5 ], [ -67.1,46.5 ], [ -67.1,30.5 ], [ -83.84,30.5 ] ] ] } } ] }","volume":"9","issue":"8","noUsgsAuthors":false,"publicationDate":"2014-08-28","publicationStatus":"PW","scienceBaseUri":"5422bb08e4b08312ac7ceec0","contributors":{"authors":[{"text":"King, Tim L. tlking@usgs.gov","contributorId":3520,"corporation":false,"usgs":true,"family":"King","given":"Tim","email":"tlking@usgs.gov","middleInitial":"L.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":499487,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Henderson, Anne P.","contributorId":29290,"corporation":false,"usgs":true,"family":"Henderson","given":"Anne","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":499490,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kynard, Boyd E.","contributorId":53712,"corporation":false,"usgs":true,"family":"Kynard","given":"Boyd","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":499493,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kieffer, Micah C. 0000-0001-9310-018X","orcid":"https://orcid.org/0000-0001-9310-018X","contributorId":40532,"corporation":false,"usgs":true,"family":"Kieffer","given":"Micah","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":499492,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Peterson, Douglas L.","contributorId":38911,"corporation":false,"usgs":true,"family":"Peterson","given":"Douglas","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":499491,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Aunins, Aaron W. 0000-0001-5240-1453 aaunins@usgs.gov","orcid":"https://orcid.org/0000-0001-5240-1453","contributorId":5863,"corporation":false,"usgs":true,"family":"Aunins","given":"Aaron","email":"aaunins@usgs.gov","middleInitial":"W.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":499488,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Brown, Bonnie L.","contributorId":23083,"corporation":false,"usgs":false,"family":"Brown","given":"Bonnie","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":499489,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70122639,"text":"70122639 - 2014 - Re-evaluating the northeastern Minnesota moose decline and the role of wolves","interactions":[],"lastModifiedDate":"2018-01-04T11:32:25","indexId":"70122639","displayToPublicDate":"2014-08-28T11:29:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Re-evaluating the northeastern Minnesota moose decline and the role of wolves","docAbstract":"We re-evaluated findings from Lenarz et al. (2009) that adult moose (Alces alces) survival in northeastern Minnesota was related to high January temperatures and that predation by wolves (Canis lupus) played a minor role. We found significant inverse relationships between annual wolf numbers in part of the moose range and various moose demographics from 2003 to 2013 that suggested a stronger role of wolves than heretofore believed. To re-evaluate the temperature findings, we conducted a simulation study, mimicking the approach taken by Lenarz et al. (2009), to explore the potential for concluding a significant relationship exists between temperature and survival, when no association exists. We found that the high R2s and low probabilities associated with the regression models in Lenarz et al. (2009) should be viewed cautiously in light of the large number of fitted models (m = 45) and few observations (n = 6 for each of 5 response variables).","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Wildlife Management","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"The Wildlife Society","doi":"10.1002/jwmg.775","usgsCitation":"Mech, L.D., and Fieberg, J., 2014, Re-evaluating the northeastern Minnesota moose decline and the role of wolves: Journal of Wildlife Management, v. 78, no. 7, p. 1143-1150, https://doi.org/10.1002/jwmg.775.","productDescription":"8 p.","startPage":"1143","endPage":"1150","ipdsId":"IP-054789","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":293153,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":293053,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1002/jwmg.775"}],"country":"United States","state":"Minnesota","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -92.7018,46.6557 ], [ -92.7018,48.4968 ], [ -89.4918,48.4968 ], [ -89.4918,46.6557 ], [ -92.7018,46.6557 ] ] ] } } ] }","volume":"78","issue":"7","noUsgsAuthors":false,"publicationDate":"2014-08-26","publicationStatus":"PW","scienceBaseUri":"54003435e4b04e908030b54a","contributors":{"authors":[{"text":"Mech, L. David 0000-0003-3944-7769 david_mech@usgs.gov","orcid":"https://orcid.org/0000-0003-3944-7769","contributorId":2518,"corporation":false,"usgs":true,"family":"Mech","given":"L.","email":"david_mech@usgs.gov","middleInitial":"David","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":499519,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fieberg, John","contributorId":44804,"corporation":false,"usgs":false,"family":"Fieberg","given":"John","affiliations":[{"id":7201,"text":"University of Minnesota-St. Paul","active":true,"usgs":false}],"preferred":false,"id":499520,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70122760,"text":"70122760 - 2014 - Irruptive dynamics of introduced caribou on Adak Island, Alaska: an evaluation of Riney-Caughley model predictions","interactions":[],"lastModifiedDate":"2014-08-28T10:55:39","indexId":"70122760","displayToPublicDate":"2014-08-28T10:50:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Irruptive dynamics of introduced caribou on Adak Island, Alaska: an evaluation of Riney-Caughley model predictions","docAbstract":"Large mammalian herbivores introduced to islands without predators are predicted to undergo irruptive population and spatial dynamics, but only a few well-documented case studies support this paradigm. We used the Riney-Caughley model as a framework to test predictions of irruptive population growth and spatial expansion of caribou (Rangifer tarandus granti) introduced to Adak Island in the Aleutian archipelago of Alaska in 1958 and 1959. We utilized a time series of spatially explicit counts conducted on this population intermittently over a 54-year period. Population size increased from 23 released animals to approximately 2900 animals in 2012. Population dynamics were characterized by two distinct periods of irruptive growth separated by a long time period of relative stability, and the catalyst for the initial irruption was more likely related to annual variation in hunting pressure than weather conditions. An unexpected pattern resembling logistic population growth occurred between the peak of the second irruption in 2005 and the next survey conducted seven years later in 2012. Model simulations indicated that an increase in reported harvest alone could not explain the deceleration in population growth, yet high levels of unreported harvest combined with increasing density-dependent feedbacks on fecundity and survival were the most plausible explanation for the observed population trend. No studies of introduced island Rangifer have measured a time series of spatial use to the extent described in this study. Spatial use patterns during the post-calving season strongly supported Riney-Caughley model predictions, whereby high-density core areas expanded outwardly as population size increased. During the calving season, caribou displayed marked site fidelity across the full range of population densities despite availability of other suitable habitats for calving. Finally, dispersal and reproduction on neighboring Kagalaska Island represented a new dispersal front for irruptive dynamics and a new challenge for resource managers. The future demography of caribou on both islands is far from certain, yet sustained and significant hunting pressure should be a vital management tool.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Ecosphere","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Ecological Society of America","publisherLocation":"Washington, D.C.","doi":"10.1890/ES13-00338.1","usgsCitation":"Ricca, M., Van Vuren, D., Weckerly, F.W., Williams, J., and Miles, A.K., 2014, Irruptive dynamics of introduced caribou on Adak Island, Alaska: an evaluation of Riney-Caughley model predictions: Ecosphere, v. 5, no. 8, 24 p., https://doi.org/10.1890/ES13-00338.1.","productDescription":"24 p.","numberOfPages":"24","ipdsId":"IP-052046","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":472807,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1890/es13-00338.1","text":"Publisher Index Page"},{"id":293150,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":293142,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1890/ES13-00338.1"}],"country":"United States","state":"Alaska","otherGeospatial":"Adak Island;Aleutian Archipelago;Kagalaska Island","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -176.992716,51.590596 ], [ -176.992716,52.001917 ], [ -176.250485,52.001917 ], [ -176.250485,51.590596 ], [ -176.992716,51.590596 ] ] ] } } ] }","volume":"5","issue":"8","noUsgsAuthors":false,"publicationDate":"2014-08-11","publicationStatus":"PW","scienceBaseUri":"54003434e4b04e908030b545","contributors":{"authors":[{"text":"Ricca, Mark A.","contributorId":39736,"corporation":false,"usgs":true,"family":"Ricca","given":"Mark A.","affiliations":[],"preferred":false,"id":499685,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Van Vuren, Dirk H.","contributorId":89408,"corporation":false,"usgs":true,"family":"Van Vuren","given":"Dirk H.","affiliations":[],"preferred":false,"id":499687,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Weckerly, Floyd W.","contributorId":10298,"corporation":false,"usgs":false,"family":"Weckerly","given":"Floyd","email":"","middleInitial":"W.","affiliations":[{"id":6960,"text":"Department of Biology, Texas State University","active":true,"usgs":false}],"preferred":false,"id":499684,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Williams, Jeffrey C.","contributorId":41333,"corporation":false,"usgs":false,"family":"Williams","given":"Jeffrey C.","affiliations":[{"id":6987,"text":"U.S. Fish and Wildlife Sevice","active":true,"usgs":false}],"preferred":false,"id":499686,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Miles, A. Keith 0000-0002-3108-808X keith_miles@usgs.gov","orcid":"https://orcid.org/0000-0002-3108-808X","contributorId":196,"corporation":false,"usgs":true,"family":"Miles","given":"A.","email":"keith_miles@usgs.gov","middleInitial":"Keith","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":499683,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70122722,"text":"70122722 - 2014 - Can air temperature be used to project influences of climate change on stream temperature?","interactions":[],"lastModifiedDate":"2017-11-24T17:24:19","indexId":"70122722","displayToPublicDate":"2014-08-28T08:39:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1562,"text":"Environmental Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Can air temperature be used to project influences of climate change on stream temperature?","docAbstract":"Worldwide, lack of data on stream temperature has motivated the use of regression-based statistical models to predict stream temperatures based on more widely available data on air temperatures. Such models have been widely applied to project responses of stream temperatures under climate change, but the performance of these models has not been fully evaluated. To address this knowledge gap, we examined the performance of two widely used linear and nonlinear regression models that predict stream temperatures based on air temperatures. We evaluated model performance and temporal stability of model parameters in a suite of regulated and unregulated streams with 11–44 years of stream temperature data. Although such models may have validity when predicting stream temperatures within the span of time that corresponds to the data used to develop them, model predictions did not transfer well to other time periods. Validation of model predictions of most recent stream temperatures, based on air temperature–stream temperature relationships from previous time periods often showed poor performance when compared with observed stream temperatures. Overall, model predictions were less robust in regulated streams and they frequently failed in detecting the coldest and warmest temperatures within all sites. In many cases, the magnitude of errors in these predictions falls within a range that equals or exceeds the magnitude of future projections of climate-related changes in stream temperatures reported for the region we studied (between 0.5 and 3.0 °C by 2080). The limited ability of regression-based statistical models to accurately project stream temperatures over time likely stems from the fact that underlying processes at play, namely the heat budgets of air and water, are distinctive in each medium and vary among localities and through time.","language":"English","publisher":"IOP Publishing","doi":"10.1088/1748-9326/9/8/084015","usgsCitation":"Arismendi, I., Safeeq, M., Dunham, J., and Johnson, S.L., 2014, Can air temperature be used to project influences of climate change on stream temperature?: Environmental Research Letters, v. 9, no. 8, Article 084015; 12 p., https://doi.org/10.1088/1748-9326/9/8/084015.","productDescription":"Article 084015; 12 p.","numberOfPages":"12","ipdsId":"IP-052781","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":472809,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1088/1748-9326/9/8/084015","text":"Publisher Index Page"},{"id":293143,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"9","issue":"8","noUsgsAuthors":false,"publicationDate":"2014-08-27","publicationStatus":"PW","scienceBaseUri":"5400342fe4b04e908030b534","contributors":{"authors":[{"text":"Arismendi, Ivan","contributorId":70661,"corporation":false,"usgs":true,"family":"Arismendi","given":"Ivan","affiliations":[],"preferred":false,"id":499664,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Safeeq, Mohammad 0000-0003-0529-3925","orcid":"https://orcid.org/0000-0003-0529-3925","contributorId":77814,"corporation":false,"usgs":false,"family":"Safeeq","given":"Mohammad","email":"","affiliations":[{"id":6641,"text":"University of California at Merced","active":true,"usgs":false}],"preferred":false,"id":499665,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dunham, Jason B.","contributorId":64791,"corporation":false,"usgs":true,"family":"Dunham","given":"Jason B.","affiliations":[],"preferred":false,"id":499663,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Johnson, Sherri L.","contributorId":91757,"corporation":false,"usgs":true,"family":"Johnson","given":"Sherri","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":499666,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70110904,"text":"sir20145103 - 2014 - Hydrology and numerical simulation of groundwater movement and heat transport in Snake Valley and surrounding areas, Juab, Miller, and Beaver Counties, Utah, and White Pine and Lincoln Counties, Nevada","interactions":[],"lastModifiedDate":"2017-09-19T16:22:06","indexId":"sir20145103","displayToPublicDate":"2014-08-27T14:32:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-5103","title":"Hydrology and numerical simulation of groundwater movement and heat transport in Snake Valley and surrounding areas, Juab, Miller, and Beaver Counties, Utah, and White Pine and Lincoln Counties, Nevada","docAbstract":"Snake Valley and surrounding areas, along the Utah-Nevada state border, are part of the Great Basin carbonate and alluvial aquifer system. The groundwater system in the study area consists of water in unconsolidated deposits in basins and water in consolidated rock underlying the basins and in the adjacent mountain blocks. Most recharge occurs from precipitation on the mountain blocks and most discharge occurs from the lower altitude basin-fill deposits mainly as evapotranspiration, springflow, and well withdrawals.
The Snake Valley area regional groundwater system was simulated using a three-dimensional model incorporating both groundwater flow and heat transport. The model was constructed with MODFLOW-2000, a version of the U.S. Geological Survey’s groundwater flow model, and MT3DMS, a transport model that simulates advection, dispersion, and chemical reactions of solutes or heat in groundwater systems. Observations of groundwater discharge by evapotranspiration, springflow, mountain stream base flow, and well withdrawals; groundwater-level altitudes; and groundwater temperatures were used to calibrate the model. Parameter values estimated by regression analyses were reasonable and within the range of expected values.
This study represents one of the first regional modeling efforts to include calibration to groundwater temperature data. The inclusion of temperature observations reduced parameter uncertainty, in some cases quite significantly, over using just water-level altitude and discharge observations. Of the 39 parameters used to simulate horizontal hydraulic conductivity, uncertainty on 11 of these parameters was reduced to one order of magnitude or less. Other significant reductions in parameter uncertainty occurred in parameters representing the vertical anisotropy ratio, drain and river conductance, recharge rates, and well withdrawal rates.
The model provides a good representation of the groundwater system. Simulated water-level altitudes range over almost 2,000 meters (m); 98 percent of the simulated values of water-level altitudes in wells are within 30 m of observed water-level altitudes, and 58 percent of them are within 12 m. Nineteen of 20 simulated discharges are within 30 percent of observed discharge. Eighty-one percent of the simulated values of groundwater temperatures in wells are within 2 degrees Celsius (°C) of the observed values, and 55 percent of them are within 0.75 °C. The numerical model represents a more robust quantification of groundwater budget components than previous studies because the model integrates all components of the groundwater budget. The model also incorporates new data including (1) a detailed hydrogeologic framework, and (2) more observations, including several new water-level altitudes throughout the study area, several new measurements of spring discharge within Snake Valley which had not previously been monitored, and groundwater temperature data. Uncertainty in the estimates of subsurface flow are less than those of previous studies because the model balanced recharge and discharge across the entire simulated area, not just in each hydrographic area, and because of the large dataset of observations (water-level altitudes, discharge, and temperatures) used to calibrate the model and the resulting transmissivity distribution.
Groundwater recharge from precipitation and unconsumed irrigation in Snake Valley is 160,000 acre-feet per year (acre-ft/yr), which is within the range of previous estimates. Subsurface inflow from southern Spring Valley to southern Snake Valley is 13,000 acre-ft/yr and is within the range of previous estimates; subsurface inflow from Spring Valley to Snake Valley north of the Snake Range, however, is only 2,200 acre-ft/yr, which is much less than has been previously estimated. Groundwater discharge from groundwater evapotranspiration and springs is 100,000 acre-ft/yr, and discharge to mountain streams is 3,300 acre-ft/yr; these are within the range of previous estimates. Current well withdrawals are 28,000 acre-ft/yr. Subsurface outflow from Snake Valley moves into Pine Valley (2,000 acre-ft/yr), Wah Wah Valley (23 acre-ft/yr), Tule Valley (33,000 acre-ft/yr), Fish Springs Flat (790 acre-ft/yr), and outside of the study area towards Great Salt Lake Desert (8,400 acre-ft/yr); these outflows, totaling about 44,000 acre-ft/yr, are within the range of previous estimates.
The subsurface flow amounts indicate the degree of connectivity between hydrographic areas within the study area. The simulated transmissivity and locations of natural discharge, however, provide a better estimate of the effect of groundwater withdrawals on groundwater resources than does the amount and direction of subsurface flow between hydrographic areas. The distribution of simulated transmissivity throughout the study area includes many areas of high transmissivity within and between hydrographic areas. Increased well withdrawals within these high transmissivity areas will likely affect a large part of the study area, resulting in declining groundwater levels, as well as leading to a decrease in natural discharge to springs and evapotranspiration.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145103","collaboration":"Prepared in cooperation with Juab, Millard, Salt Lake, Tooele, and Utah Counties","usgsCitation":"Masbruch, M.D., Gardner, P.M., and Brooks, L.E., 2014, Hydrology and numerical simulation of groundwater movement and heat transport in Snake Valley and surrounding areas, Juab, Miller, and Beaver Counties, Utah, and White Pine and Lincoln Counties, Nevada: U.S. Geological Survey Scientific Investigations Report 2014-5103, x, 107 p., https://doi.org/10.3133/sir20145103.","productDescription":"x, 107 p.","numberOfPages":"122","onlineOnly":"Y","ipdsId":"IP-042407","costCenters":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"links":[{"id":293136,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20145103.jpg"},{"id":293135,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2014/5103/pdf/sir2014-5103.pdf"},{"id":293134,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2014/5103/"}],"country":"United States","state":"Nevada, Utah","county":"Beaver County, Juab County, Lincoln County, Millard County, White Pine County","otherGeospatial":"Snake Valley","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -115.9,36.98 ], [ -115.9,40.24 ], [ -110.05,40.24 ], [ -110.05,36.98 ], [ -115.9,36.98 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53fee2afe4b01f35f8fd1390","contributors":{"authors":[{"text":"Masbruch, Melissa D. 0000-0001-6568-160X mmasbruch@usgs.gov","orcid":"https://orcid.org/0000-0001-6568-160X","contributorId":1902,"corporation":false,"usgs":true,"family":"Masbruch","given":"Melissa","email":"mmasbruch@usgs.gov","middleInitial":"D.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":494196,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gardner, Philip M. 0000-0003-3005-3587 pgardner@usgs.gov","orcid":"https://orcid.org/0000-0003-3005-3587","contributorId":962,"corporation":false,"usgs":true,"family":"Gardner","given":"Philip","email":"pgardner@usgs.gov","middleInitial":"M.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true},{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"preferred":true,"id":494195,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brooks, Lynette E. 0000-0002-9074-0939 lebrooks@usgs.gov","orcid":"https://orcid.org/0000-0002-9074-0939","contributorId":2718,"corporation":false,"usgs":true,"family":"Brooks","given":"Lynette","email":"lebrooks@usgs.gov","middleInitial":"E.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":494197,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70121945,"text":"ofr20141182 - 2014 - Guidelines for the collection of continuous stream water-temperature data in Alaska","interactions":[],"lastModifiedDate":"2014-08-27T12:23:24","indexId":"ofr20141182","displayToPublicDate":"2014-08-27T11:20:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-1182","title":"Guidelines for the collection of continuous stream water-temperature data in Alaska","docAbstract":"Objectives of stream monitoring programs differ considerably among many of the academic, Federal, state, tribal, and non-profit organizations in the state of Alaska. Broad inclusion of stream-temperature monitoring can provide an opportunity for collaboration in the development of a statewide stream-temperature database. Statewide and regional coordination could reduce overall monitoring cost, while providing better analyses at multiple spatial and temporal scales to improve resource decision-making. Increased adoption of standardized protocols and data-quality standards may allow for validation of historical modeling efforts with better projection calibration. For records of stream water temperature to be generally consistent, unbiased, and reproducible, data must be collected and analyzed according to documented protocols. Collection of water-temperature data requires definition of data-quality objectives, good site selection, proper selection of instrumentation, proper installation of sensors, periodic site visits to maintain sensors and download data, pre- and post-deployment verification against an NIST-certified thermometer, potential data corrections, and proper documentation, review, and approval. A study created to develop a quality-assurance project plan, data-quality objectives, and a database management plan that includes procedures for data archiving and dissemination could provide a means to standardize a statewide stream-temperature database in Alaska. Protocols can be modified depending on desired accuracy or specific needs of data collected. This document is intended to guide users in collecting time series water-temperature data in Alaskan streams and draws extensively on the broader protocols already published by the U.S. Geological Survey.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20141182","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service","usgsCitation":"Toohey, R., Neal, E., and Solin, G.L., 2014, Guidelines for the collection of continuous stream water-temperature data in Alaska: U.S. Geological Survey Open-File Report 2014-1182, iv, 34 p., https://doi.org/10.3133/ofr20141182.","productDescription":"iv, 34 p.","numberOfPages":"37","onlineOnly":"Y","ipdsId":"IP-058762","costCenters":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"links":[{"id":293098,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20141182.PNG"},{"id":293096,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2014/1182/pdf/ofr2014-1182.pdf"},{"id":293094,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2014/1182/"}],"country":"United States","state":"Alaska","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 172.4,51.2 ], [ 172.4,71.4 ], [ -130.0,71.4 ], [ -130.0,51.2 ], [ 172.4,51.2 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53fee2aee4b01f35f8fd138c","contributors":{"authors":[{"text":"Toohey, Ryan C.","contributorId":7201,"corporation":false,"usgs":true,"family":"Toohey","given":"Ryan C.","affiliations":[],"preferred":false,"id":499411,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Neal, Edward G.","contributorId":68775,"corporation":false,"usgs":true,"family":"Neal","given":"Edward G.","affiliations":[],"preferred":false,"id":499412,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Solin, Gary L. glsolin@usgs.gov","contributorId":5675,"corporation":false,"usgs":true,"family":"Solin","given":"Gary","email":"glsolin@usgs.gov","middleInitial":"L.","affiliations":[],"preferred":true,"id":499410,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ]}