Shallow cores collected in the 1980s on the Chukchi Shelf of western Arctic Alaska sampled pre-Cenozoic strata whose presence, age, and character are poorly known across the region. Five cores from the Herald Arch foreland contain Cenomanian to Coniacian strata, as documented by biostratigraphy, geochronology, and thermochronology. Shallow seismic reflection data collected during the 1970s and 1980s show that these Upper Cretaceous strata are truncated near the seafloor by subtle angular unconformities, including the Paleogene mid-Brookian unconformity in one core and the Pliocene-Pleistocene unconformity in four cores. Sedimentary structures and lithofacies suggest that Upper Cretaceous strata were deposited in a low accommodation setting that ranged from low-lying coastal plain (nonmarine) to muddy, shallow-marine environments near shore. These observations, together with sparse evidence from the adjacent western North Slope, suggest that Upper Cretaceous strata likely were deposited across all of Arctic Alaska.
A sixth core from the Herald Arch contains lower Toarcian marine strata, indicated by biostratigraphy, truncated by a Neogene or younger unconformity. These Lower Jurassic strata evidently were deposited south of the arch, buried structurally to high levels of thermal maturity during the Early Cretaceous, and uplifted on the Herald thrust-fault system during the mid to Late Cretaceous. These interpretations are based on regional stratigraphy and apatite fission-track data reported in a complementary report and are corroborated by the presence of recycled palynomorphs of Early Jurassic age and high thermal maturity found in Upper Cretaceous strata in two of the foreland cores. This dataset provides evidence that uplift and exhumation of the Herald thrust belt provided sediment to the foreland during the Late Cretaceous.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Studies by the U.S. Geological Survey in Alaska, vol. 15 (Professional Paper 1814)","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/pp1814C","usgsCitation":"Houseknecht, D.W., Craddock, W.H., and Lease, R.O., 2016, Upper Cretaceous and Lower Jurassic strata in shallow cores on the Chukchi Shelf, Arctic Alaska, in Dumoulin, J.A., ed., Studies by the U.S. Geological Survey in Alaska, vol. 15: U.S. Geological Survey Professional Paper 1814–C, 37 p., https://dx.doi.org/10.3133/pp1814C.","productDescription":"Report: v, 37 p.; 10 Figures","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-068732","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":317938,"rank":2,"type":{"id":29,"text":"Figure"},"url":"https://pubs.usgs.gov/pp/1814/c/pp1814C_fig4.pdf","text":"Figure 4 - High Resolution","size":"170 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Figure 4","linkHelpText":"Graphic section and composite photograph of U.S. Geological Survey vibracore C62, Chukchi Shelf, Alaska"},{"id":317937,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/pp/1814/c/pp1814C.pdf","text":"Report","size":"3.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"PP 1814-C PDF"},{"id":317939,"rank":3,"type":{"id":29,"text":"Figure"},"url":"https://pubs.usgs.gov/pp/1814/c/pp1814C_fig6.pdf","text":"Figure 6 - High Resolution","size":"170 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Figure 6","linkHelpText":"Graphic section and composite photograph of U.S. Geological Survey vibracore C67, Chukchi Shelf, Alaska"},{"id":317943,"rank":7,"type":{"id":29,"text":"Figure"},"url":"https://pubs.usgs.gov/pp/1814/c/pp1814C_fig16A.pdf","text":"Figure 16A - High Resolution","size":"468 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Figure 16A","linkHelpText":"Composite photographs of U.S. Geological Survey rotary core C3, Chukchi Shelf, Alaska"},{"id":317940,"rank":4,"type":{"id":29,"text":"Figure"},"url":"https://pubs.usgs.gov/pp/1814/c/pp1814C_fig8.pdf","text":"Figure 8 - High Resolution","size":"390 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Figure 8","linkHelpText":"Graphic section and composite photograph of U.S. Geological Survey vibracore C65, Chukchi Shelf, Alaska"},{"id":317941,"rank":5,"type":{"id":29,"text":"Figure"},"url":"https://pubs.usgs.gov/pp/1814/c/pp1814C_fig11.pdf","text":"Figure 11 - High Resolution","size":"431 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Figure 11","linkHelpText":"Graphic section and composite photograph of U.S. Geological Survey vibracore C53, Chukchi Shelf, Alaska"},{"id":317942,"rank":6,"type":{"id":29,"text":"Figure"},"url":"https://pubs.usgs.gov/pp/1814/c/pp1814C_fig13.pdf","text":"Figure 13 - High Resolution","size":"23 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Figure 13","linkHelpText":"Composite photograph of U.S. Geological Survey cores from the Chukchi Shelf, Alaska, showing examples of damage induced by rotary coring"},{"id":317944,"rank":8,"type":{"id":29,"text":"Figure"},"url":"https://pubs.usgs.gov/pp/1814/c/pp1814C_fig16B.pdf","text":"Figure 16B - High Resolution","size":"456 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Figure 16B","linkHelpText":"Composite photographs of U.S. Geological Survey rotary core C3, Chukchi Shelf, Alaska"},{"id":317945,"rank":9,"type":{"id":29,"text":"Figure"},"url":"https://pubs.usgs.gov/pp/1814/c/pp1814C_fig16C.pdf","text":"Figure 16C - High Resolution","size":"476 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Figure 16C","linkHelpText":"Composite photographs of U.S. Geological Survey rotary core C3, Chukchi Shelf, Alaska"},{"id":317946,"rank":10,"type":{"id":29,"text":"Figure"},"url":"https://pubs.usgs.gov/pp/1814/c/pp1814C_fig16D.pdf","text":"Figure 16D - High Resolution","size":"486 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Figure 16D","linkHelpText":"Composite photographs of U.S. Geological Survey rotary core C3, Chukchi Shelf, Alaska"},{"id":317947,"rank":11,"type":{"id":29,"text":"Figure"},"url":"https://pubs.usgs.gov/pp/1814/c/pp1814C_fig20.pdf","text":"Figure 20 - High Resolution","size":"342 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Figure 20","linkHelpText":"Photographs of U.S. Geological Survey rotary core C7, Chukchi Shelf, Alaska"},{"id":317948,"rank":12,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/pp/1814/c/coverthb.jpg"}],"country":"Russia, United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -149.326171875,\n 64.05297838071347\n ],\n [\n -147.7880859375,\n 73.41588526207096\n ],\n [\n -152.9736328125,\n 73.94679115710252\n ],\n [\n -159.03808593749997,\n 74.3192352189468\n ],\n [\n -166.11328125,\n 74.35482803013984\n ],\n [\n -173.32031249999997,\n 74.28356347036141\n ],\n [\n -180.0439453125,\n 73.86150600047368\n ],\n [\n -184.3505859375,\n 73.41588526207096\n ],\n [\n -187.8662109375,\n 72.97118902284586\n ],\n [\n -185.361328125,\n 69.7333343903359\n ],\n [\n -182.1533203125,\n 66.8265202749748\n ],\n [\n -180.3955078125,\n 64.99793920061401\n ],\n [\n -178.59375,\n 63.48976680530999\n ],\n [\n -170.90332031249997,\n 64.03374392176401\n ],\n [\n -165.9814453125,\n 64.07219957867284\n ],\n [\n -161.279296875,\n 64.30182213914463\n ],\n [\n -154.6435546875,\n 64.24459476798192\n ],\n [\n -149.326171875,\n 64.05297838071347\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Alaska Science Center staff
U.S. Geological Survey
4210 University Dr.
Anchorage, AK 99508
Alaska Mineral Resources
Alaska Science Center
A lack of nutritious food during the first year of life is a hypothesized factor that may limit survival of endangered pallid sturgeonScaphirhynchus albus in the lower Missouri River (LMOR). Unfortunately, information for age-0 pallid sturgeon diets remains limited, but diet analyses for age-0 Scaphirhynchus spp. (sturgeon hereafter) have occurred. Little information, however, exists on age-0 sturgeon diets in the LMOR; thus, our primary objective was to document age-0 sturgeon diets in this system. We examined guts contents from 30 individuals, which were genetically identified as shovelnose sturgeon Scaphirhynchus platorynchus, and three stomachs were empty. The remaining age-0 shovelnose sturgeon consumed chironomid larvae almost exclusively (>98% of prey items consumed). Our results were similar to studies conducted in other systems, and it appears unlikely that a lack of nutritious food was a major factor affecting the individuals captured during this study. This effort provides important information to help guide ongoing adaptive management efforts in the LMOR.
","language":"English","publisher":"Wiley Online","doi":"10.1002/rra.3003","usgsCitation":"Gosch, N., Miller, M., Gemeinhardt, T., Starks, T.A., Civiello, A.P., Long, J.M., and Bonneau, J., 2016, Age-0 Shovelnose Sturgeon prey consumption in the Lower Missouri River: River Research and Applications, v. 32, no. 8, p. 1819-1823, https://doi.org/10.1002/rra.3003.","productDescription":"5 p.","startPage":"1819","endPage":"1823","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-064837","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":471242,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/rra.3003","text":"Publisher Index Page"},{"id":323261,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Missouri","otherGeospatial":"Missouri River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -94.72412109375,\n 38.35888785866677\n ],\n [\n -90.263671875,\n 38.35888785866677\n ],\n [\n -90.263671875,\n 39.470125122358176\n ],\n [\n -94.72412109375,\n 39.470125122358176\n ],\n [\n -94.72412109375,\n 38.35888785866677\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"32","issue":"8","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationDate":"2016-02-12","publicationStatus":"PW","scienceBaseUri":"575941b8e4b04f417c25678d","contributors":{"authors":[{"text":"Gosch, N.J.C.","contributorId":66513,"corporation":false,"usgs":true,"family":"Gosch","given":"N.J.C.","email":"","affiliations":[],"preferred":false,"id":637854,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Miller, M.L.","contributorId":244627,"corporation":false,"usgs":false,"family":"Miller","given":"M.L.","email":"","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":637855,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gemeinhardt, T. R.","contributorId":171492,"corporation":false,"usgs":false,"family":"Gemeinhardt","given":"T. R.","affiliations":[],"preferred":false,"id":637856,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Starks, Trevor A.","contributorId":145640,"corporation":false,"usgs":false,"family":"Starks","given":"Trevor","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":637857,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Civiello, A. P.","contributorId":171493,"corporation":false,"usgs":false,"family":"Civiello","given":"A.","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":637858,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Long, James M. 0000-0002-8658-9949 jmlong@usgs.gov","orcid":"https://orcid.org/0000-0002-8658-9949","contributorId":3453,"corporation":false,"usgs":true,"family":"Long","given":"James","email":"jmlong@usgs.gov","middleInitial":"M.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":637752,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bonneau, J. L.","contributorId":171494,"corporation":false,"usgs":false,"family":"Bonneau","given":"J. L.","affiliations":[],"preferred":false,"id":637859,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70161873,"text":"sir20165001 - 2016 - Modified method for estimating petroleum source-rock potential using wireline logs, with application to the Kingak Shale, Alaska North Slope","interactions":[],"lastModifiedDate":"2016-02-15T11:17:38","indexId":"sir20165001","displayToPublicDate":"2016-02-11T14:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2016-5001","title":"Modified method for estimating petroleum source-rock potential using wireline logs, with application to the Kingak Shale, Alaska North Slope","docAbstract":"In 2012, the U.S. Geological Survey completed an assessment of undiscovered, technically recoverable oil and gas resources in three source rocks of the Alaska North Slope, including the lower part of the Jurassic to Lower Cretaceous Kingak Shale. In order to identify organic shale potential in the absence of a robust geochemical dataset from the lower Kingak Shale, we introduce two quantitative parameters, $\\Delta DT_\\bar{x}$ and $\\Delta DT_z$, estimated from wireline logs from exploration wells and based in part on the commonly used delta-log resistivity ($\\Delta \\text{ }log\\text{ }R$) technique. Calculation of $\\Delta DT_\\bar{x}$ and $\\Delta DT_z$ is intended to produce objective parameters that may be proportional to the quality and volume, respectively, of potential source rocks penetrated by a well and can be used as mapping parameters to convey the spatial distribution of source-rock potential. Both the $\\Delta DT_\\bar{x}$ and $\\Delta DT_z$ mapping parameters show increased source-rock potential from north to south across the North Slope, with the largest values at the toe of clinoforms in the lower Kingak Shale. Because thermal maturity is not considered in the calculation of $\\Delta DT_\\bar{x}$ or $\\Delta DT_z$, total organic carbon values for individual wells cannot be calculated on the basis of $\\Delta DT_\\bar{x}$ or $\\Delta DT_z$ alone. Therefore, the $\\Delta DT_\\bar{x}$ and $\\Delta DT_z$ mapping parameters should be viewed as first-step reconnaissance tools for identifying source-rock potential.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165001","usgsCitation":"Rouse, W.A., and Houseknecht, D.W., 2016, Modified method for estimating petroleum source-rock potential using wireline logs, with application to the Kingak Shale, Alaska North Slope: U.S. Geological Survey Scientific Investigations Report 2016–5001, 40 p., https://dx.doi.org/10.3133/sir20165001.","productDescription":"v, 40 p.","numberOfPages":"50","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-061129","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":316733,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5001/coverthb.jpg"},{"id":316734,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5001/sir20165001.pdf","text":"Report","size":"5.46 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5001"}],"country":"United States","state":"Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -166.81640625,\n 66.51326044311188\n ],\n [\n -166.81640625,\n 71.35706654962706\n ],\n [\n -140.80078125,\n 71.35706654962706\n ],\n [\n -140.80078125,\n 66.51326044311188\n ],\n [\n -166.81640625,\n 66.51326044311188\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Energy Resources Program
U.S. Geological Survey
12201 Sunrise Valley Drive
National Center, MS 913
Reston, VA 20192
703–648–6470
http://energy.usgs.gov/
The model presented in this report is a spreadsheet-based model using Visual Basic for Applications within Microsoft Excel (http://dx.doi.org/10.5066/F7057D0Z) prepared in cooperation with the U.S. Army Corps of Engineers and U.S. Fish and Wildlife Service. It uses the same model structure and, initially, parameters as used by Wildhaber and others (2015) for pallid sturgeon. The difference between the model structure used for this report and that used by Wildhaber and others (2015) is that variance is not partitioned. For the model of this report, all variance is applied at the iteration and time-step levels of the model. Wildhaber and others (2015) partition variance into parameter variance (uncertainty about the value of a parameter itself) applied at the iteration level and temporal variance (uncertainty caused by random environmental fluctuations with time) applied at the time-step level. They included implicit individual variance (uncertainty caused by differences between individuals) within the time-step level.
The interface developed for the model of this report is designed to allow the user the flexibility to change population model structure and parameter values and uncertainty separately for every component of the model. This flexibility makes the modeling tool potentially applicable to any fish species; however, the flexibility inherent in this modeling tool makes it possible for the user to obtain spurious outputs. The value and reliability of the model outputs are only as good as the model inputs. Using this modeling tool with improper or inaccurate parameter values, or for species for which the structure of the model is inappropriate, could lead to untenable management decisions. By facilitating fish population modeling, this modeling tool allows the user to evaluate a range of management options and implications. The goal of this modeling tool is to be a user-friendly modeling tool for developing fish population models useful to natural resource managers to inform their decision-making processes; however, as with all population models, caution is needed, and a full understanding of the limitations of a model and the veracity of user-supplied parameters should always be considered when using such model output in the management of any species.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161009","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers and U.S. Fish and Wildlife Service","usgsCitation":"Moran, E.H., Wildhaber, M.L., Green, N.S., and Albers, J.L., 2016, Visual basic, Excel-based fish population modeling tool—The pallid sturgeon example: U.S. Geological Survey Open-File Report 2016–1009, 20 p., https://dx.doi.org/10.3133/ofr20161009.","productDescription":"vi, 20 p.","numberOfPages":"29","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-066994","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":316871,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1009/coverthb.jpg"},{"id":316872,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1009/ofr20161009.pdf","text":"Report","size":"17.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1009"},{"id":316917,"rank":3,"type":{"id":4,"text":"Application Site"},"url":"https://dx.doi.org/10.5066/F7057D0Z","text":"http://dx.doi.org/10.5066/F7057D0Z","description":"Microsoft Visual Basic for Applications"}],"contact":"Director, Columbia Environmental Research Center
U.S. Geological Survey
4200 New Haven Road
Columbia, MO 65201-8709
The cold and clear water conditions present below many large dams create ideal conditions for the development of economically important salmonid fisheries. Many of these tailwater fisheries have experienced declines in the abundance and condition of large trout species, yet the causes of these declines remain uncertain. Here, we develop, assess, and apply a drift-foraging bioenergetics model to identify the factors limiting rainbow trout (Oncorhynchus mykiss) growth in a large tailwater. We explored the relative importance of temperature, prey quantity, and prey size by constructing scenarios where these variables, both singly and in combination, were altered. Predicted growth matched empirical mass-at-age estimates, particularly for younger ages, demonstrating that the model accurately describes how current temperature and prey conditions interact to determine rainbow trout growth. Modeling scenarios that artificially inflated prey size and abundance demonstrate that rainbow trout growth is limited by the scarcity of large prey items and overall prey availability. For example, shifting 10% of the prey biomass to the 13 mm (large) length class, without increasing overall prey biomass, increased lifetime maximum mass of rainbow trout by 88%. Additionally, warmer temperatures resulted in lower predicted growth at current and lower levels of prey availability; however, growth was similar across all temperatures at higher levels of prey availability. Climate change will likely alter flow and temperature regimes in large rivers with corresponding changes to invertebrate prey resources used by fish. Broader application of drift-foraging bioenergetics models to build a mechanistic understanding of how changes to habitat conditions and prey resources affect growth of salmonids will benefit management of tailwater fisheries.
","language":"English","publisher":"NRC Research Press","doi":"10.1139/cjfas-2015-0268","usgsCitation":"Dodrill, M.J., Yackulic, C.B., Kennedy, T.A., and Haye, J.W., 2016, Prey size and availability limits maximum size of rainbow trout in a large tailwater: insights from a drift-foraging bioenergetics model: Canadian Journal of Fisheries and Aquatic Sciences, v. 73, no. 5, p. 759-772, https://doi.org/10.1139/cjfas-2015-0268.","productDescription":"14 p.","startPage":"759","endPage":"772","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-065511","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":317928,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"Lees Ferry, Colorado River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.62452697753906,\n 36.82632511529419\n ],\n [\n -111.62452697753906,\n 36.86204269508728\n ],\n [\n -111.5939712524414,\n 36.86204269508728\n ],\n [\n -111.5939712524414,\n 36.82632511529419\n ],\n [\n -111.62452697753906,\n 36.82632511529419\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"73","issue":"5","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"56bdb0b1e4b06458514aeeae","contributors":{"authors":[{"text":"Dodrill, Michael J. 0000-0002-7038-7170 mdodrill@usgs.gov","orcid":"https://orcid.org/0000-0002-7038-7170","contributorId":5468,"corporation":false,"usgs":true,"family":"Dodrill","given":"Michael","email":"mdodrill@usgs.gov","middleInitial":"J.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":619783,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Yackulic, Charles B. 0000-0001-9661-0724 cyackulic@usgs.gov","orcid":"https://orcid.org/0000-0001-9661-0724","contributorId":4662,"corporation":false,"usgs":true,"family":"Yackulic","given":"Charles","email":"cyackulic@usgs.gov","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":619784,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kennedy, Theodore A. tkennedy@usgs.gov","contributorId":166704,"corporation":false,"usgs":true,"family":"Kennedy","given":"Theodore","email":"tkennedy@usgs.gov","middleInitial":"A.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":false,"id":619785,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Haye, John W","contributorId":166705,"corporation":false,"usgs":false,"family":"Haye","given":"John","email":"","middleInitial":"W","affiliations":[{"id":24493,"text":"Cawthron Institute, Nelson, New Zealand","active":true,"usgs":false}],"preferred":false,"id":619786,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70168375,"text":"70168375 - 2016 - Identification of lake trout Salvelinus namaycush spawning habitat in northern Lake Huron using high-resolution satellite imagery","interactions":[],"lastModifiedDate":"2016-02-11T09:14:43","indexId":"70168375","displayToPublicDate":"2016-02-11T10:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2330,"text":"Journal of Great Lakes Research","active":true,"publicationSubtype":{"id":10}},"title":"Identification of lake trout Salvelinus namaycush spawning habitat in northern Lake Huron using high-resolution satellite imagery","docAbstract":"The availability and quality of spawning habitat may limit lake trout recovery in the Great Lakes, but little is known about the location and characteristics of current spawning habitats. Current methods used to identify lake trout spawning locations are time- and labor-intensive and spatially limited. Due to the observation that some lake trout spawning sites are relatively clean of overlaying algae compared to areas not used for spawning, we suspected that spawning sites could be identified using satellite imagery. Satellite imagery collected just before and after the spawning season in 2013 was used to assess whether lake trout spawning habitat could be identified based on its spectral characteristics. Results indicated that Pléiades high-resolution multispectral satellite imagery can be successfully used to estimate algal coverage of substrates and temporal changes in algal coverage, and that models developed from processed imagery can be used to identify potential lake trout spawning sites based on comparison of sites where lake trout eggs were and were not observed after spawning. Satellite imagery is a potential new tool for identifying lake trout spawning habitat at large scales in shallow nearshore areas of the Great Lakes.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jglr.2015.11.011","usgsCitation":"Grimm, A.G., Brooks, C., Binder, T., Riley, S.C., Farha, S., Shuchman, R.A., and Krueger, C., 2016, Identification of lake trout Salvelinus namaycush spawning habitat in northern Lake Huron using high-resolution satellite imagery: Journal of Great Lakes Research, v. 42, no. 1, p. 127-135, https://doi.org/10.1016/j.jglr.2015.11.011.","productDescription":"9 p.","startPage":"127","endPage":"135","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-069823","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":317927,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Lake Huron","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -84.2486572265625,\n 45.805828539928356\n ],\n [\n -84.2486572265625,\n 46.31658418182218\n ],\n [\n -83.2379150390625,\n 46.31658418182218\n ],\n [\n -83.2379150390625,\n 45.805828539928356\n ],\n [\n -84.2486572265625,\n 45.805828539928356\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"42","issue":"1","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"56bdb0ace4b06458514aeeaa","contributors":{"authors":[{"text":"Grimm, Amanda G.","contributorId":150482,"corporation":false,"usgs":false,"family":"Grimm","given":"Amanda","email":"","middleInitial":"G.","affiliations":[{"id":16203,"text":"Michigan Technological university","active":true,"usgs":false}],"preferred":false,"id":619829,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brooks, Colin N.","contributorId":103961,"corporation":false,"usgs":true,"family":"Brooks","given":"Colin N.","affiliations":[],"preferred":false,"id":619830,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Binder, Thomas R.","contributorId":21093,"corporation":false,"usgs":true,"family":"Binder","given":"Thomas R.","affiliations":[],"preferred":false,"id":619831,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Riley, Stephen C. 0000-0002-8968-8416 sriley@usgs.gov","orcid":"https://orcid.org/0000-0002-8968-8416","contributorId":2661,"corporation":false,"usgs":true,"family":"Riley","given":"Stephen","email":"sriley@usgs.gov","middleInitial":"C.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":false,"id":619828,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Farha, Steven A. 0000-0001-9953-6996 sfarha@usgs.gov","orcid":"https://orcid.org/0000-0001-9953-6996","contributorId":5170,"corporation":false,"usgs":true,"family":"Farha","given":"Steven","email":"sfarha@usgs.gov","middleInitial":"A.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":619832,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Shuchman, Robert A.","contributorId":150483,"corporation":false,"usgs":false,"family":"Shuchman","given":"Robert","email":"","middleInitial":"A.","affiliations":[{"id":16203,"text":"Michigan Technological university","active":true,"usgs":false}],"preferred":false,"id":619833,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Krueger, Charles C.","contributorId":73131,"corporation":false,"usgs":true,"family":"Krueger","given":"Charles C.","affiliations":[],"preferred":false,"id":619834,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70170450,"text":"70170450 - 2016 - Contrasting evolutionary histories of MHC class I and class II loci in grouse—Effects of selection and gene conversion","interactions":[],"lastModifiedDate":"2016-04-20T15:55:05","indexId":"70170450","displayToPublicDate":"2016-02-10T17:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1890,"text":"Heredity","active":true,"publicationSubtype":{"id":10}},"title":"Contrasting evolutionary histories of MHC class I and class II loci in grouse—Effects of selection and gene conversion","docAbstract":"Genes of the major histocompatibility complex (MHC) encode receptor molecules that are responsible for recognition of intracellular and extracellular pathogens (class I and class II genes, respectively) in vertebrates. Given the different roles of class I and II MHC genes, one might expect the strength of selection to differ between these two classes. Different selective pressures may also promote different rates of gene conversion at each class. Despite these predictions, surprisingly few studies have looked at differences between class I and II genes in terms of both selection and gene conversion. Here, we investigated the molecular evolution of MHC class I and II genes in five closely related species of prairie grouse (Centrocercus and Tympanuchus) that possess one class I and two class II loci. We found striking differences in the strength of balancing selection acting on MHC class I versus class II genes. More than half of the putative antigen-binding sites (ABS) of class II were under positive or episodic diversifying selection, compared with only 10% at class I. We also found that gene conversion had a stronger role in shaping the evolution of MHC class II than class I. Overall, the combination of strong positive (balancing) selection and frequent gene conversion has maintained higher diversity of MHC class II than class I in prairie grouse. This is one of the first studies clearly demonstrating that macroevolutionary mechanisms can act differently on genes involved in the immune response against intracellular and extracellular pathogens.
","language":"English","publisher":"Genetical Society","publisherLocation":"London","doi":"10.1038/hdy.2016.6","collaboration":"University of Lodz, University of Wisconsin, University of North Texas","usgsCitation":"Minias, P., Bateson, Z.W., Whittingham, L.A., Johnson, J., Oyler-McCance, S.J., and Dunn, P.O., 2016, Contrasting evolutionary histories of MHC class I and class II loci in grouse—Effects of selection and gene conversion: Heredity, v. 116, p. 466-476, https://doi.org/10.1038/hdy.2016.6.","productDescription":"11 p.","startPage":"466","endPage":"476","numberOfPages":"11","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-066342","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":471243,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/hdy.2016.6","text":"Publisher Index Page"},{"id":320330,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"116","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2016-02-10","publicationStatus":"PW","scienceBaseUri":"5718a839e4b0ef3b7caba500","contributors":{"authors":[{"text":"Minias, Piotr","contributorId":168775,"corporation":false,"usgs":false,"family":"Minias","given":"Piotr","email":"","affiliations":[{"id":25360,"text":"University of Lodz","active":true,"usgs":false}],"preferred":false,"id":627241,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bateson, Zachary W.","contributorId":168776,"corporation":false,"usgs":false,"family":"Bateson","given":"Zachary","email":"","middleInitial":"W.","affiliations":[{"id":7200,"text":"University of Wisconsin-Milwaukee","active":true,"usgs":false}],"preferred":false,"id":627242,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Whittingham, Linda A.","contributorId":168777,"corporation":false,"usgs":false,"family":"Whittingham","given":"Linda","email":"","middleInitial":"A.","affiliations":[{"id":7200,"text":"University of Wisconsin-Milwaukee","active":true,"usgs":false}],"preferred":false,"id":627243,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Johnson, Jeff A.","contributorId":107208,"corporation":false,"usgs":true,"family":"Johnson","given":"Jeff A.","affiliations":[],"preferred":false,"id":627244,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Oyler-McCance, Sara J. 0000-0003-1599-8769 sara_oyler-mccance@usgs.gov","orcid":"https://orcid.org/0000-0003-1599-8769","contributorId":1973,"corporation":false,"usgs":true,"family":"Oyler-McCance","given":"Sara","email":"sara_oyler-mccance@usgs.gov","middleInitial":"J.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":627240,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Dunn, Peter O.","contributorId":168778,"corporation":false,"usgs":false,"family":"Dunn","given":"Peter","email":"","middleInitial":"O.","affiliations":[{"id":7200,"text":"University of Wisconsin-Milwaukee","active":true,"usgs":false}],"preferred":false,"id":627245,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70168342,"text":"70168342 - 2016 - Wide-area estimates of evapotranspiration by red gum (Eucalyptus camaldulensis) and associated vegetation in the Murray-Darling River Basin, Australia","interactions":[],"lastModifiedDate":"2016-04-21T10:59:08","indexId":"70168342","displayToPublicDate":"2016-02-10T13:45:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1924,"text":"Hydrological Processes","active":true,"publicationSubtype":{"id":10}},"title":"Wide-area estimates of evapotranspiration by red gum (Eucalyptus camaldulensis) and associated vegetation in the Murray-Darling River Basin, Australia","docAbstract":"Floodplain red gum forests (Eucalyptus camaldulensis plus associated grasses, reeds and sedges) are sites of high biodiversity in otherwise arid regions of southeastern Australia. They depend on periodic floods from rivers, but dams and diversions have reduced flood frequencies and volumes, leading to deterioration of trees and associated biota. There is a need to determine their water requirements so environmental flows can be administered to maintain or restore the forests. Their water requirements include the frequency and extent of overbank flooding, which recharges the floodplain soils with water, as well as the actual amount of water consumed in evapotranspiration (ET). We estimated the flooding requirements and ET for a 38 134 ha area of red gum forest fed by the Murrumbidgee River in Yanga National Park, New South Wales. ET was estimated by three methods: sap flux sensors placed in individual trees; a remote sensing method based on the Enhanced Vegetation Index from MODIS satellite imagery and a water balance method based on differences between river flows into and out of the forest. The methods gave comparable estimates yet covered different spatial and temporal scales. We estimated flood frequency and volume requirements by comparing Normalized Difference Vegetation Index values from Landsat images with flood history from 1995 to 2014, which included both wet periods and dry periods. ET during wet years is about 50% of potential ET but is much less in dry years because of the trees' ability to control stomatal conductance. Based on our analyses plus other studies, red gum trees at this location require environmental flows of 2000 GL yr−1 every other year, with peak flows of 20 000 ML d−1, to produce flooding sufficient to keep them in good condition. However, only about 120–200 GL yr−1 of river water is consumed in ET, with the remainder flowing out of the forest where it enters the Murray River system.
","language":"English","publisher":"Wiley","doi":"10.1002/hyp.10734","usgsCitation":"Nagler, P.L., Doody, T.M., Glenn, E.P., Jarchow, C.J., Barreto-Munoz, A., and Didan, K., 2016, Wide-area estimates of evapotranspiration by red gum (Eucalyptus camaldulensis) and associated vegetation in the Murray-Darling River Basin, Australia: Hydrological Processes, v. 30, no. 9, p. 1376-1387, https://doi.org/10.1002/hyp.10734.","productDescription":"12 p.","startPage":"1376","endPage":"1387","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-064981","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":317918,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Australia","otherGeospatial":"Murray-Darling River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 143.4814453125,\n -34.73032697882121\n ],\n [\n 143.4814453125,\n -34.31394984163212\n ],\n [\n 144.35623168945312,\n -34.31394984163212\n ],\n [\n 144.35623168945312,\n -34.73032697882121\n ],\n [\n 143.4814453125,\n -34.73032697882121\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"30","issue":"9","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2015-11-29","publicationStatus":"PW","scienceBaseUri":"56bc5f35e4b08d617f660028","contributors":{"authors":[{"text":"Nagler, Pamela L. 0000-0003-0674-103X pnagler@usgs.gov","orcid":"https://orcid.org/0000-0003-0674-103X","contributorId":1398,"corporation":false,"usgs":true,"family":"Nagler","given":"Pamela","email":"pnagler@usgs.gov","middleInitial":"L.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":619773,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Doody, Tanya M.","contributorId":138691,"corporation":false,"usgs":false,"family":"Doody","given":"Tanya","email":"","middleInitial":"M.","affiliations":[{"id":12494,"text":"CSIRO Land and Water, Australia","active":true,"usgs":false}],"preferred":false,"id":619774,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Glenn, Edward P.","contributorId":19289,"corporation":false,"usgs":true,"family":"Glenn","given":"Edward","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":619775,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jarchow, Christopher J. 0000-0002-0424-4104 cjarchow@usgs.gov","orcid":"https://orcid.org/0000-0002-0424-4104","contributorId":5813,"corporation":false,"usgs":true,"family":"Jarchow","given":"Christopher","email":"cjarchow@usgs.gov","middleInitial":"J.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":false,"id":619776,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Barreto-Munoz, Armando","contributorId":131000,"corporation":false,"usgs":false,"family":"Barreto-Munoz","given":"Armando","email":"","affiliations":[{"id":7204,"text":"University of Arizona, Electrical and Computer Engineering","active":true,"usgs":false}],"preferred":false,"id":619777,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Didan, Kamel","contributorId":130999,"corporation":false,"usgs":false,"family":"Didan","given":"Kamel","email":"","affiliations":[{"id":7204,"text":"University of Arizona, Electrical and Computer Engineering","active":true,"usgs":false}],"preferred":false,"id":619778,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70168327,"text":"70168327 - 2016 - Effects of permafrost aggradation on peat properties as determined from a pan-Arctic synthesis of plant macrofossils","interactions":[],"lastModifiedDate":"2020-03-26T12:55:24","indexId":"70168327","displayToPublicDate":"2016-02-10T12:45:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2320,"text":"Journal of Geophysical Research: Biogeosciences","active":true,"publicationSubtype":{"id":10}},"title":"Effects of permafrost aggradation on peat properties as determined from a pan-Arctic synthesis of plant macrofossils","docAbstract":"Permafrost dynamics play an important role in high-latitude peatland carbon balance and are key to understanding the future response of soil carbon stocks. Permafrost aggradation can control the magnitude of the carbon feedback in peatlands through effects on peat properties. We compiled peatland plant macrofossil records for the northern permafrost zone (515 cores from 280 sites) and classified samples by vegetation type and environmental class (fen, bog, tundra and boreal permafrost, and thawed permafrost). We examined differences in peat properties (bulk density, carbon (C), nitrogen (N) and organic matter content, and C/N ratio) and C accumulation rates among vegetation types and environmental classes. Consequences of permafrost aggradation differed between boreal and tundra biomes, including differences in vegetation composition, C/N ratios, and N content. The vegetation composition of tundra permafrost peatlands was similar to permafrost-free fens, while boreal permafrost peatlands more closely resembled permafrost-free bogs. Nitrogen content in boreal permafrost and thawed permafrost peatlands was significantly lower than in permafrost-free bogs despite similar vegetation types (0.9% versus 1.5% N). Median long-term C accumulation rates were higher in fens (23 g C m−2 yr−1) than in permafrost-free bogs (18 g C m−2 yr−1) and were lowest in boreal permafrost peatlands (14 g C m−2 yr−1). The plant macrofossil record demonstrated transitions from fens to bogs to permafrost peatlands, bogs to fens, permafrost aggradation within fens, and permafrost thaw and reaggradation. Using data synthesis, we have identified predominant peatland successional pathways, changes in vegetation type, peat properties, and C accumulation rates associated with permafrost aggradation.
","language":"English","publisher":"AGU Publications","doi":"10.1002/2015JG003061","usgsCitation":"Treat, C.C., Jones, M.C., Camill, P., Gallego-Sala, A., Garneau, M., Harden, J.W., Hugelius, G., Klein, E., Kokfelt, U., Kuhry, P., Loisel, J., Mathijssen, J., O'Donnell, J., Oksanen, P., Ronkainen, T., Sannel, A.B., Talbot, J.J., Tarnocal, C., and Valiranta, M., 2016, Effects of permafrost aggradation on peat properties as determined from a pan-Arctic synthesis of plant macrofossils: Journal of Geophysical Research: Biogeosciences, v. 121, no. 1, p. 78-94, https://doi.org/10.1002/2015JG003061.","productDescription":"17 p.","startPage":"78","endPage":"94","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-068874","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":471245,"rank":0,"type":{"id":40,"text":"Open Access Publisher 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B. K.","contributorId":38450,"corporation":false,"usgs":false,"family":"Sannel","given":"A.","email":"","middleInitial":"B. K.","affiliations":[],"preferred":false,"id":619696,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Talbot, J. J.","contributorId":21045,"corporation":false,"usgs":false,"family":"Talbot","given":"J.","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":619697,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Tarnocal, C.M.","contributorId":166677,"corporation":false,"usgs":false,"family":"Tarnocal","given":"C.M.","email":"","affiliations":[{"id":24491,"text":"Agriculture and Agri-Food Canada","active":true,"usgs":false}],"preferred":false,"id":619698,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Valiranta, M.","contributorId":166678,"corporation":false,"usgs":false,"family":"Valiranta","given":"M.","affiliations":[{"id":18162,"text":"University of Helsinki","active":true,"usgs":false}],"preferred":false,"id":619699,"contributorType":{"id":1,"text":"Authors"},"rank":19}]}} ,{"id":70168332,"text":"70168332 - 2016 - Extensive dispersal of Roanoke logperch (Percina rex) inferred from genetic marker data","interactions":[],"lastModifiedDate":"2016-02-10T11:06:44","indexId":"70168332","displayToPublicDate":"2016-02-10T12:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1471,"text":"Ecology of Freshwater Fish","active":true,"publicationSubtype":{"id":10}},"title":"Extensive dispersal of Roanoke logperch (Percina rex) inferred from genetic marker data","docAbstract":"The dispersal ecology of most stream fishes is poorly characterised, complicating conservation efforts for these species. We used microsatellite DNA marker data to characterise dispersal patterns and effective population size (Ne) for a population of Roanoke logperchPercina rex, an endangered darter (Percidae). Juveniles and candidate parents were sampled for 2 years at sites throughout the Roanoke River watershed. Dispersal was inferred via genetic assignment tests (ATs), pedigree reconstruction (PR) and estimation of lifetime dispersal distance under a genetic isolation-by-distance model. Estimates of Ne varied from 105 to 1218 individuals, depending on the estimation method. Based on PR, polygamy was frequent in parents of both sexes, with individuals spawning with an average of 2.4 mates. The sample contained 61 half-sibling pairs, but only one parent–offspring pair and no full-sib pairs, which limited our ability to discriminate natal dispersal of juveniles from breeding dispersal of their parents between spawning events. Nonetheless, all methods indicated extensive dispersal. The AT indicated unrestricted dispersal among sites ≤15 km apart, while siblings inferred by the PR were captured an average of 14 km and up to 55 km apart. Model-based estimates of median lifetime dispersal distance (6–24 km, depending on assumptions) bracketed AT and PR estimates, indicating that widely dispersed individuals do, on average, contribute to gene flow. Extensive dispersal of P. rex suggests that darters and other small benthic stream fishes may be unexpectedly mobile. Monitoring and management activities for such populations should encompass entire watersheds to fully capture population dynamics.
","language":"English","publisher":"John Wiley & Sons","doi":"10.1111/eff.12177","usgsCitation":"Roberts, J.H., Angermeier, P.L., and Hallerman, E.M., 2016, Extensive dispersal of Roanoke logperch (Percina rex) inferred from genetic marker data: Ecology of Freshwater Fish, v. 25, no. 1, p. 1-16, https://doi.org/10.1111/eff.12177.","productDescription":"16 p.","startPage":"1","endPage":"16","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-037298","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":317905,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"25","issue":"1","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2014-08-25","publicationStatus":"PW","scienceBaseUri":"56bc5f30e4b08d617f660010","contributors":{"authors":[{"text":"Roberts, James H.","contributorId":83811,"corporation":false,"usgs":true,"family":"Roberts","given":"James","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":619737,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Angermeier, Paul L. 0000-0003-2864-170X biota@usgs.gov","orcid":"https://orcid.org/0000-0003-2864-170X","contributorId":166679,"corporation":false,"usgs":true,"family":"Angermeier","given":"Paul","email":"biota@usgs.gov","middleInitial":"L.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":619704,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hallerman, Eric M.","contributorId":40501,"corporation":false,"usgs":true,"family":"Hallerman","given":"Eric","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":619738,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70168333,"text":"70168333 - 2016 - American woodcock migratory connectivity as indicated by hydrogen isotopes","interactions":[],"lastModifiedDate":"2016-03-31T13:08:09","indexId":"70168333","displayToPublicDate":"2016-02-10T11:45:00","publicationYear":"2016","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":"American woodcock migratory connectivity as indicated by hydrogen isotopes","docAbstract":"To identify factors contributing to the long-term decline of American woodcock, a holistic understanding of range-wide population connectivity throughout the annual cycle is needed. We used band recovery data and isotopic composition of primary (P1) and secondary (S13) feathers to estimate population sources and connectivity among natal, early fall, and winter ranges of hunter-harvested juvenile American woodcock. We used P1 feathers from known-origin pre-fledged woodcock (n = 43) to create a hydrogenδ2Hf isoscape by regressing δ2Hf against expected growing-season precipitation (δ2Hp). Modeled δ2Hp values explained 79% of the variance in P1 δ2Hf values, indicating good model fit for estimating woodcock natal origins. However, a poor relationship (r2 = 0.23) between known-origin, S13 δ2Hf values, and expected δ2Hp values precluded assignment of early fall origins. We applied the δ2Hfisoscape to assign natal origins using P1 feathers from 494 hunter-harvested juvenile woodcock in the United States and Canada during 2010–2011 and 2011–2012 hunting seasons. Overall, 64% of all woodcock origins were assigned to the northernmost (>44°N) portion of both the Central and Eastern Management Regions. In the Eastern Region, assignments were more uniformly distributed along the Atlantic coast, whereas in the Central Region, most woodcock were assigned to origins within and north of the Great Lakes region. We compared our origin assignments to spatial coverage of the annual American woodcock Singing Ground Survey (SGS) and evaluated whether the survey effectively encompasses the entire breeding range. When we removed the inadequately surveyed Softwood shield Bird Conservation Region (BCR) from the northern portion of the SGS area, only 48% of juvenile woodcock originated in areas currently surveyed by the SGS. Of the individuals assigned to the northernmost portions of the breeding range, several were harvested in the southern extent of the wintering range. Based upon this latitudinal winter stratification, we examined whether woodcock employed a leapfrog migration strategy. Using δ2Hf values and band-recovery data, we found some support for this migration strategy hypothesis but not as a singular explanation. The large harvest derivation of individuals from the northernmost portions of the breeding range, and the difference in breeding distributions within each Management Region should be considered in future range-wide conservation and harvest management planning for American woodcock.
","language":"English","publisher":"Wildlife Society","doi":"10.1002/jwmg.1035","usgsCitation":"Sullins, D.S., Conway, W.C., Haukos, D.A., Hobson, K., Wassenaar, L.I., Comer, C.E., and Hung, I., 2016, American woodcock migratory connectivity as indicated by hydrogen isotopes: Journal of Wildlife Management, v. 80, no. 3, p. 510-526, https://doi.org/10.1002/jwmg.1035.","productDescription":"17 p.","startPage":"510","endPage":"526","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-064387","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":317903,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"80","issue":"3","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationDate":"2016-01-12","publicationStatus":"PW","scienceBaseUri":"56bc5f29e4b08d617f65ffd5","contributors":{"authors":[{"text":"Sullins, Daniel S.","contributorId":166689,"corporation":false,"usgs":false,"family":"Sullins","given":"Daniel","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":619731,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Conway, Warren C.","contributorId":51550,"corporation":false,"usgs":true,"family":"Conway","given":"Warren","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":619732,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Haukos, David A. 0000-0001-5372-9960 dhaukos@usgs.gov","orcid":"https://orcid.org/0000-0001-5372-9960","contributorId":3664,"corporation":false,"usgs":true,"family":"Haukos","given":"David","email":"dhaukos@usgs.gov","middleInitial":"A.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":619705,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hobson, Keith A.","contributorId":47306,"corporation":false,"usgs":true,"family":"Hobson","given":"Keith A.","affiliations":[],"preferred":false,"id":619733,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wassenaar, Leonard I","contributorId":150277,"corporation":false,"usgs":false,"family":"Wassenaar","given":"Leonard","email":"","middleInitial":"I","affiliations":[{"id":17954,"text":"International Atomic Energy Agency, Vienna, Austria","active":true,"usgs":false}],"preferred":false,"id":619734,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Comer, Christopher E.","contributorId":166690,"corporation":false,"usgs":false,"family":"Comer","given":"Christopher","email":"","middleInitial":"E.","affiliations":[{"id":32360,"text":"Stephen F. Austin State University, Nacogdoches, TX","active":true,"usgs":false}],"preferred":false,"id":619735,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hung, I-Kuai","contributorId":166691,"corporation":false,"usgs":false,"family":"Hung","given":"I-Kuai","email":"","affiliations":[],"preferred":false,"id":619736,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70168326,"text":"70168326 - 2016 - The global Landsat archive: Status, consolidation, and direction","interactions":[],"lastModifiedDate":"2017-01-17T19:17:44","indexId":"70168326","displayToPublicDate":"2016-02-10T11:45:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3254,"text":"Remote Sensing of Environment","printIssn":"0034-4257","active":true,"publicationSubtype":{"id":10}},"title":"The global Landsat archive: Status, consolidation, and direction","docAbstract":"New and previously unimaginable Landsat applications have been fostered by a policy change in 2008 that made analysis-ready Landsat data free and open access. Since 1972, Landsat has been collecting images of the Earth, with the early years of the program constrained by onboard satellite and ground systems, as well as limitations across the range of required computing, networking, and storage capabilities. Rather than robust on-satellite storage for transmission via high bandwidth downlink to a centralized storage and distribution facility as with Landsat-8, a network of receiving stations, one operated by the U.S. government, the other operated by a community of International Cooperators (ICs), were utilized. ICs paid a fee for the right to receive and distribute Landsat data and over time, more Landsat data was held outside the archive of the United State Geological Survey (USGS) than was held inside, much of it unique. Recognizing the critical value of these data, the USGS began a Landsat Global Archive Consolidation (LGAC) initiative in 2010 to bring these data into a single, universally accessible, centralized global archive, housed at the Earth Resources Observation and Science (EROS) Center in Sioux Falls, South Dakota. The primary LGAC goals are to inventory the data held by ICs, acquire the data, and ingest and apply standard ground station processing to generate an L1T analysis-ready product. As of January 1, 2015 there were 5,532,454 images in the USGS archive. LGAC has contributed approximately 3.2 million of those images, more than doubling the original USGS archive holdings. Moreover, an additional 2.3 million images have been identified to date through the LGAC initiative and are in the process of being added to the archive. The impact of LGAC is significant and, in terms of images in the collection, analogous to that of having had twoadditional Landsat-5 missions. As a result of LGAC, there are regions of the globe that now have markedly improved Landsat data coverage, resulting in an enhanced capacity for mapping, monitoring change, and capturing historic conditions. Although future missions can be planned and implemented, the past cannot be revisited, underscoring the value and enhanced significance of historical Landsat data and the LGAC initiative. The aim of this paper is to report the current status of the global USGS Landsat archive, document the existing and anticipated contributions of LGAC to the archive, and characterize the current acquisitions of Landsat-7 and Landsat-8. Landsat-8 is adding data to the archive at an unprecedented rate as nearly all terrestrial images are now collected. We also offer key lessons learned so far from the LGAC initiative, plus insights regarding other critical elements of the Landsat program looking forward, such as acquisition, continuity, temporal revisit, and the importance of continuing to operationalize the Landsat program.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.rse.2015.11.032","usgsCitation":"Wulder, M.A., White, J.C., Loveland, T., Woodcock, C., Belward, A., Cohen, W.B., Fosnight, E.A., Shaw, J., Masek, J.G., and Roy, D.P., 2016, The global Landsat archive: Status, consolidation, and direction: Remote Sensing of Environment, v. 185, p. 271-283, https://doi.org/10.1016/j.rse.2015.11.032.","productDescription":"13 p.","startPage":"271","endPage":"283","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-071343","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":471246,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.rse.2015.11.032","text":"Publisher Index Page"},{"id":317904,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"185","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"56bc5f35e4b08d617f660026","contributors":{"authors":[{"text":"Wulder, Michael A.","contributorId":103584,"corporation":false,"usgs":true,"family":"Wulder","given":"Michael","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":619672,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"White, Joanne C.","contributorId":63362,"corporation":false,"usgs":true,"family":"White","given":"Joanne","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":619673,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Loveland, Thomas 0000-0003-3114-6646 loveland@usgs.gov","orcid":"https://orcid.org/0000-0003-3114-6646","contributorId":140611,"corporation":false,"usgs":true,"family":"Loveland","given":"Thomas","email":"loveland@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":619671,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Woodcock, Curtis","contributorId":166666,"corporation":false,"usgs":false,"family":"Woodcock","given":"Curtis","affiliations":[{"id":13570,"text":"Boston University","active":true,"usgs":false}],"preferred":false,"id":619674,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Belward, Alan","contributorId":166667,"corporation":false,"usgs":false,"family":"Belward","given":"Alan","affiliations":[{"id":18032,"text":"European Commission, Joint Research Centere, Institute for Environment and Sustainability, Ispra Varese, Italy","active":true,"usgs":false}],"preferred":false,"id":619675,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Cohen, Warren B.","contributorId":100093,"corporation":false,"usgs":true,"family":"Cohen","given":"Warren","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":619676,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Fosnight, Eugene A. 0000-0002-8557-3697 fosnight@usgs.gov","orcid":"https://orcid.org/0000-0002-8557-3697","contributorId":2961,"corporation":false,"usgs":true,"family":"Fosnight","given":"Eugene","email":"fosnight@usgs.gov","middleInitial":"A.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":619677,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Shaw, Jerad 0000-0002-8319-2778 jshaw@usgs.gov","orcid":"https://orcid.org/0000-0002-8319-2778","contributorId":3564,"corporation":false,"usgs":true,"family":"Shaw","given":"Jerad","email":"jshaw@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":619678,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Masek, Jeffery G.","contributorId":87438,"corporation":false,"usgs":true,"family":"Masek","given":"Jeffery","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":619679,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Roy, David P.","contributorId":71083,"corporation":false,"usgs":true,"family":"Roy","given":"David","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":619680,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70168337,"text":"70168337 - 2016 - An empirical assessment of which inland floods can be managed","interactions":[],"lastModifiedDate":"2016-02-10T10:24:37","indexId":"70168337","displayToPublicDate":"2016-02-10T11:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2258,"text":"Journal of Environmental Management","active":true,"publicationSubtype":{"id":10}},"title":"An empirical assessment of which inland floods can be managed","docAbstract":"Riverine flooding is a significant global issue. Although it is well documented that the influence of landscape structure on floods decreases as flood size increases, studies that define a threshold flood-return period, above which landscape features such as topography, land cover and impoundments can curtail floods, are lacking. Further, the relative influences of natural versus built features on floods is poorly understood. Assumptions about the types of floods that can be managed have considerable implications for the cost-effectiveness of decisions to invest in transforming land cover (e.g., reforestation) and in constructing structures (e.g., storm-water ponds) to control floods. This study defines parameters of floods for which changes in landscape structure can have an impact. We compare nine flood-return periods across 31 watersheds with widely varying topography and land cover in the southeastern United States, using long-term hydrologic records (≥20 years). We also assess the effects of built flow-regulating features (best management practices and artificial water bodies) on selected flood metrics across urban watersheds. We show that landscape features affect magnitude and duration of only those floods with return periods ≤10 years, which suggests that larger floods cannot be managed effectively by manipulating landscape structure. Overall, urban watersheds exhibited larger (270 m3/s) but quicker (0.41 days) floods than non-urban watersheds (50 m3/s and 1.5 days). However, urban watersheds with more flow-regulating features had lower flood magnitudes (154 m3/s), but similar flood durations (0.55 days), compared to urban watersheds with fewer flow-regulating features (360 m3/s and 0.23 days). Our analysis provides insight into the magnitude, duration and count of floods that can be curtailed by landscape structure and its management. Our findings are relevant to other areas with similar climate, topography, and land use, and can help ensure that investments in flood management are made wisely after considering the limitations of landscape features to regulate floods.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jenvman.2015.10.044","usgsCitation":"Mogollon, B., Frimpong, E.A., Hoegh, A.B., and Angermeier, P.L., 2016, An empirical assessment of which inland floods can be managed: Journal of Environmental Management, v. 167, p. 38-48, https://doi.org/10.1016/j.jenvman.2015.10.044.","productDescription":"11 p.","startPage":"38","endPage":"48","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-060039","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":471247,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jenvman.2015.10.044","text":"Publisher Index Page"},{"id":317898,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"167","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"56bc5f2ce4b08d617f65ffe0","chorus":{"doi":"10.1016/j.jenvman.2015.10.044","url":"http://dx.doi.org/10.1016/j.jenvman.2015.10.044","publisher":"Elsevier BV","authors":"Mogollón Beatriz, Frimpong Emmanuel A., Hoegh Andrew B., Angermeier Paul L.","journalName":"Journal of Environmental Management","publicationDate":"2/2016"},"contributors":{"authors":[{"text":"Mogollon, Beatriz","contributorId":166682,"corporation":false,"usgs":false,"family":"Mogollon","given":"Beatriz","email":"","affiliations":[{"id":35590,"text":"USAID/USFS","active":true,"usgs":false}],"preferred":false,"id":619719,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Frimpong, Emmanuel A.","contributorId":79372,"corporation":false,"usgs":true,"family":"Frimpong","given":"Emmanuel","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":619720,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hoegh, Andrew B.","contributorId":166684,"corporation":false,"usgs":false,"family":"Hoegh","given":"Andrew","email":"","middleInitial":"B.","affiliations":[{"id":12694,"text":"Virginia Tech","active":true,"usgs":false}],"preferred":false,"id":619721,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Angermeier, Paul L. 0000-0003-2864-170X biota@usgs.gov","orcid":"https://orcid.org/0000-0003-2864-170X","contributorId":166679,"corporation":false,"usgs":true,"family":"Angermeier","given":"Paul","email":"biota@usgs.gov","middleInitial":"L.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":619709,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70215608,"text":"70215608 - 2016 - Techniques for monitoring Brachyramphus murrelets: A comparison of radar, autonomous acoustic recording and audio‐visual surveys","interactions":[],"lastModifiedDate":"2020-10-26T16:20:18.20685","indexId":"70215608","displayToPublicDate":"2016-02-10T11:14:35","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3779,"text":"Wildlife Society Bulletin","onlineIssn":"1938-5463","printIssn":"0091-7648","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Techniques for monitoring Brachyramphus murrelets: A comparison of radar, autonomous acoustic recording and audio‐visual surveys","title":"Techniques for monitoring Brachyramphus murrelets: A comparison of radar, autonomous acoustic recording and audio‐visual surveys","docAbstract":"Conditions in Alaska, USA, pose a challenge for monitoring populations of Brachyramphus murrelets using standard survey methods, because of strong winds, 2 sympatric species, short nights, and variable nesting habitat. We tested 3 methods for monitoring Brachyramphus murrelets breeding in the Kodiak Archipelago, Alaska, in 2010–2012. In addition to standard audio‐visual and radar methods, we tested—for the first time with murrelets in Alaska—the application of autonomous acoustic recorders for monitoring vocal activity. We completed 74 radar, 124 audio‐visual, and 134 autonomous acoustic surveys, focused on presunrise activity peaks; this yielded 26,375 murrelet detections. Marbled (B. marmoratus) and Kittlitz's murrelets (B. brevirostris) could not be distinguished using combinations of radar and acoustic recordings; therefore, at‐sea surveys will be required to determine localized species proportions. Of the 3 methods, radar sampled the largest area and detected silently flying murrelets, providing the most reliable data on local populations; however, radar identification of murrelets was unreliable in winds exceeding 18 km/hr. Audio‐visual surveys were useful for species identification and to document behaviors associated with local nesting, whereas autonomous acoustic recorders allowed season‐long monitoring of murrelet vocal activity. Within potential forest‐nesting habitat of marbled murrelets, all 3 methods gave similar measures of presunrise murrelet activity, but only radar reliably sampled murrelets commuting between nest and ocean. Because of their low cost and flexible programming, automated sound recorders offer an affordable way to sample vocal activity prior to more intensive or expensive radar and audio‐visual surveys. We recommend that population monitoring and habitat studies of Brachyramphus murrelets in Alaska include combinations of all 3 methods.
","language":"English","publisher":"Wiley","doi":"10.1002/wsb.623","usgsCitation":"Cragg, J., Burger, A.E., and Piatt, J.F., 2016, Techniques for monitoring Brachyramphus murrelets: A comparison of radar, autonomous acoustic recording and audio‐visual surveys: Wildlife Society Bulletin, https://doi.org/10.1002/wsb.623.","ipdsId":"IP-057687","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":471248,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doaj.org/article/c6a0cd7970714963a885294974c8bc3d","text":"External Repository"},{"id":379764,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":379737,"type":{"id":15,"text":"Index Page"},"url":"https://wildlife.onlinelibrary.wiley.com/doi/full/10.1002/wsb.623"}],"country":"United States","state":"Alaska","otherGeospatial":"Kodiak Archipelago","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -154.720458984375,\n 56.30434864830831\n ],\n [\n -153.8250732421875,\n 56.52616947342749\n ],\n [\n -152.20458984375,\n 57.35616414789182\n ],\n [\n -151.69372558593747,\n 58.24594583464163\n ],\n [\n -152.38037109375,\n 58.69121321309073\n ],\n [\n -152.9296875,\n 58.54819451046483\n ],\n [\n -153.8360595703125,\n 57.94692981959113\n ],\n [\n -154.85778808593747,\n 57.41537824180043\n ],\n [\n -154.8797607421875,\n 56.41390137600676\n ],\n [\n -154.720458984375,\n 56.30434864830831\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationDate":"2016-02-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Cragg, J.L.","contributorId":243996,"corporation":false,"usgs":false,"family":"Cragg","given":"J.L.","affiliations":[{"id":41163,"text":"Department of Biology, University of Victoria","active":true,"usgs":false}],"preferred":false,"id":802956,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Burger, Alan E.","contributorId":179916,"corporation":false,"usgs":false,"family":"Burger","given":"Alan","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":802957,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Piatt, John F. 0000-0002-4417-5748 jpiatt@usgs.gov","orcid":"https://orcid.org/0000-0002-4417-5748","contributorId":3025,"corporation":false,"usgs":true,"family":"Piatt","given":"John","email":"jpiatt@usgs.gov","middleInitial":"F.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":802958,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70168339,"text":"70168339 - 2016 - The first description of oarfish Regalecus glesne (Regalecus russellii Cuvier 1816) ageing structures","interactions":[],"lastModifiedDate":"2016-02-10T10:00:22","indexId":"70168339","displayToPublicDate":"2016-02-10T11:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2166,"text":"Journal of Applied Ichthyology","active":true,"publicationSubtype":{"id":10}},"title":"The first description of oarfish Regalecus glesne (Regalecus russellii Cuvier 1816) ageing structures","docAbstract":"Flood regulation is a widely valued and studied service provided by watersheds. Flood regulation benefits people directly by decreasing the socio-economic costs of flooding and indirectly by its positive impacts on cultural (e.g., fishing) and provisioning (e.g., water supply) ecosystem services. Like other regulating ecosystem services (e.g., pollination, water purification), flood regulation is often enhanced or replaced by technology, but the relative efficacy of natural versus technological features in controlling floods has scarcely been examined. In an effort to assess flood regulation capacity for selected urban watersheds in the southeastern United States, we: (1) used long-term flood records to assess relative influence of technological and biophysical indicators on flood magnitude and duration, (2) compared the widely used runoff curve number (RCN) approach for assessing the biophysical capacity to regulate floods to an alternative approach that acknowledges land cover and soil properties separately, and (3) mapped technological and biophysical flood regulation capacities based on indicator importance-values derived for flood magnitude and duration. We found that watersheds with high biophysical (via the alternative approach) and technological capacities lengthened the duration and lowered the peak of floods. We found the RCN approach yielded results opposite that expected, possibly because it confounds soil and land cover processes, particularly in urban landscapes, while our alternative approach coherently separates these processes. Mapping biophysical (via the alternative approach) and technological capacities revealed great differences among watersheds. Our study improves on previous mapping of flood regulation by (1) incorporating technological capacity, (2) providing high spatial resolution (i.e., 10-m pixel) maps of watershed capacities, and (3) deriving importance-values for selected landscape indicators. By accounting for technology that enhances or replaces natural flood regulation, our approach enables watershed managers to make more informed choices in their flood-control investments.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolind.2015.09.049","usgsCitation":"Mogollon, B., Villamagna, A., Frimpong, E.A., and Angermeier, P.L., 2016, Mapping technological and biophysical capacities of watersheds to regulate floods: Ecological Indicators, v. 61, no. 2, p. 483-499, https://doi.org/10.1016/j.ecolind.2015.09.049.","productDescription":"17 p.","startPage":"483","endPage":"499","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-060338","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":471250,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecolind.2015.09.049","text":"Publisher Index Page"},{"id":317897,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"61","issue":"2","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"56bc5f35e4b08d617f660020","contributors":{"authors":[{"text":"Mogollon, Beatriz","contributorId":166682,"corporation":false,"usgs":false,"family":"Mogollon","given":"Beatriz","email":"","affiliations":[{"id":35590,"text":"USAID/USFS","active":true,"usgs":false}],"preferred":false,"id":619716,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Villamagna, Amy M.","contributorId":166683,"corporation":false,"usgs":false,"family":"Villamagna","given":"Amy M.","affiliations":[{"id":35056,"text":"Plymouth State University","active":true,"usgs":false}],"preferred":false,"id":619717,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Frimpong, Emmanuel A.","contributorId":79372,"corporation":false,"usgs":true,"family":"Frimpong","given":"Emmanuel","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":619718,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Angermeier, Paul L. 0000-0003-2864-170X biota@usgs.gov","orcid":"https://orcid.org/0000-0003-2864-170X","contributorId":166679,"corporation":false,"usgs":true,"family":"Angermeier","given":"Paul","email":"biota@usgs.gov","middleInitial":"L.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":619710,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70168340,"text":"70168340 - 2016 - An index of floodplain surface complexity","interactions":[],"lastModifiedDate":"2016-02-10T09:52:47","indexId":"70168340","displayToPublicDate":"2016-02-10T10:45:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1928,"text":"Hydrology and Earth System Sciences","active":true,"publicationSubtype":{"id":10}},"title":"An index of floodplain surface complexity","docAbstract":"Floodplain surface topography is an important component of floodplain ecosystems. It is the primary physical template upon which ecosystem processes are acted out, and complexity in this template can contribute to the high biodiversity and productivity of floodplain ecosystems. There has been a limited appreciation of floodplain surface complexity because of the traditional focus on temporal variability in floodplains as well as limitations to quantifying spatial complexity. An index of floodplain surface complexity (FSC) is developed in this paper and applied to eight floodplains from different geographic settings. The index is based on two key indicators of complexity, variability in surface geometry (VSG) and the spatial organisation of surface conditions (SPO), and was determined at three sampling scales. FSC, VSG, and SPO varied between the eight floodplains and these differences depended upon sampling scale. Relationships between these measures of spatial complexity and seven geomorphological and hydrological drivers were investigated. There was a significant decline in all complexity measures with increasing floodplain width, which was explained by either a power, logarithmic, or exponential function. There was an initial rapid decline in surface complexity as floodplain width increased from 1.5 to 5 km, followed by little change in floodplains wider than 10 km. VSG also increased significantly with increasing sediment yield. No significant relationships were determined between any of the four hydrological variables and floodplain surface complexity.
","language":"English","publisher":"Copernicus Publications","doi":"10.5194/hess-20-431-2016","usgsCitation":"Scown, M.W., Thoms, M.C., and De Jager, N.R., 2016, An index of floodplain surface complexity: Hydrology and Earth System Sciences, v. 20, p. 431-441, https://doi.org/10.5194/hess-20-431-2016.","productDescription":"11 p.","startPage":"431","endPage":"441","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-064127","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":471251,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/hess-20-431-2016","text":"Publisher Index Page"},{"id":317895,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"20","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2016-01-26","publicationStatus":"PW","scienceBaseUri":"56bc5f2de4b08d617f65ffe8","contributors":{"authors":[{"text":"Scown, Murray W.","contributorId":145709,"corporation":false,"usgs":false,"family":"Scown","given":"Murray","email":"","middleInitial":"W.","affiliations":[{"id":24492,"text":"Riverine Landscapes Research Laboratory, University of New England, Armidale, Australia","active":true,"usgs":false}],"preferred":false,"id":619713,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thoms, Martin C. 0000-0002-8074-0476","orcid":"https://orcid.org/0000-0002-8074-0476","contributorId":145710,"corporation":false,"usgs":false,"family":"Thoms","given":"Martin","email":"","middleInitial":"C.","affiliations":[{"id":16205,"text":"Riverine Landscapes Research Laboratory, University of New England, NSW, Australia","active":true,"usgs":false}],"preferred":false,"id":619714,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"De Jager, Nathan R. 0000-0002-6649-4125 ndejager@usgs.gov","orcid":"https://orcid.org/0000-0002-6649-4125","contributorId":3717,"corporation":false,"usgs":true,"family":"De Jager","given":"Nathan","email":"ndejager@usgs.gov","middleInitial":"R.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":619712,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70173988,"text":"70173988 - 2016 - Regional monitoring programs in the United States: Synthesis of four case studies from Pacific, Atlantic, and Gulf Coasts","interactions":[],"lastModifiedDate":"2017-10-30T11:23:43","indexId":"70173988","displayToPublicDate":"2016-02-10T09:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5094,"text":"Regional Studies in Marine Science","onlineIssn":"2352-4855","active":true,"publicationSubtype":{"id":10}},"title":"Regional monitoring programs in the United States: Synthesis of four case studies from Pacific, Atlantic, and Gulf Coasts","docAbstract":"Water quality monitoring is a cornerstone of environmental protection and ambient monitoring provides managers with the critical data they need to take informed action. Unlike site-specific monitoring that is at the heart of regulatory permit compliance, regional monitoring can provide an integrated, holistic view of the environment, allowing managers to obtain a more complete picture of natural variability and cumulative impacts, and more effectively prioritize management actions. By reviewing four long-standing regional monitoring programs that cover portions of all three coasts in the United States – Chesapeake Bay, Tampa Bay, Southern California Bight, and San Francisco Bay – important insights can be gleaned about the benefits that regional monitoring provides to managers. These insights include the underlying reasons that make regional monitoring programs successful, the challenges to maintain relevance and viability in the face of ever-changing technology, competing demands and shifting management priorities. The lessons learned can help other managers achieve similar successes as they seek to establish and reinvigorate their own monitoring programs.
","language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam, Netherlands","doi":"10.1016/j.rsma.2015.11.007","usgsCitation":"Tango, P.J., Schiff, K., Trowbridge, P., Sherwood, E., and Batiuk, R., 2016, Regional monitoring programs in the United States: Synthesis of four case studies from Pacific, Atlantic, and Gulf Coasts: Regional Studies in Marine Science, v. 4, p. A1-A7, https://doi.org/10.1016/j.rsma.2015.11.007.","productDescription":"7 p.","startPage":"A1","endPage":"A7","numberOfPages":"7","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-066996","costCenters":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true},{"id":552,"text":"San Francisco Bay-Delta","active":false,"usgs":true}],"links":[{"id":324173,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Delaware, Florida, Maryland, New Jersey, Pennsylvania, Virginia, West Virginia,","city":"San Francisco, Tampa","otherGeospatial":"Chesapeake Bay, San Francisco Bay, Southern California Bight, Tampa Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.07159423828125,\n 37.155938651244625\n ],\n [\n -123.07159423828125,\n 38.34596449365382\n ],\n [\n -121.24237060546876,\n 38.34596449365382\n ],\n [\n -121.24237060546876,\n 37.155938651244625\n ],\n [\n -123.07159423828125,\n 37.155938651244625\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -120.50903320312501,\n 34.488447837809304\n ],\n [\n -118.02612304687499,\n 34.511083202999714\n ],\n [\n -116.68579101562499,\n 32.699488680852674\n ],\n [\n -119.4049072265625,\n 32.602361666817515\n ],\n [\n -120.377197265625,\n 33.48185394054361\n ],\n [\n -120.50903320312501,\n 34.488447837809304\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -82.95501708984375,\n 27.38396203008555\n ],\n [\n -82.95501708984375,\n 28.214869548073377\n ],\n [\n -82.265625,\n 28.214869548073377\n ],\n [\n -82.265625,\n 27.38396203008555\n ],\n [\n -82.95501708984375,\n 27.38396203008555\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -77.87109375,\n 36.55377524336086\n ],\n [\n -77.87109375,\n 39.95185892663005\n ],\n [\n -74.102783203125,\n 39.95185892663005\n ],\n [\n -74.102783203125,\n 36.55377524336086\n ],\n [\n -77.87109375,\n 36.55377524336086\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"4","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"576a6548e4b07657d1a11e67","contributors":{"authors":[{"text":"Tango, Peter J. pjtango@usgs.gov","contributorId":4088,"corporation":false,"usgs":true,"family":"Tango","given":"Peter","email":"pjtango@usgs.gov","middleInitial":"J.","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":true,"id":640166,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schiff, K.","contributorId":172254,"corporation":false,"usgs":false,"family":"Schiff","given":"K.","email":"","affiliations":[{"id":12704,"text":"Southern California Coastal Water Research Project","active":true,"usgs":false}],"preferred":false,"id":640167,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Trowbridge, P.R.","contributorId":11035,"corporation":false,"usgs":true,"family":"Trowbridge","given":"P.R.","email":"","affiliations":[],"preferred":false,"id":640168,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sherwood, E.T.","contributorId":172255,"corporation":false,"usgs":false,"family":"Sherwood","given":"E.T.","email":"","affiliations":[{"id":27015,"text":"Tampa Bay Estuary Program","active":true,"usgs":false}],"preferred":false,"id":640169,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Batiuk, R.A.","contributorId":16550,"corporation":false,"usgs":true,"family":"Batiuk","given":"R.A.","email":"","affiliations":[],"preferred":false,"id":640170,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70168926,"text":"70168926 - 2016 - Asthenosphere–lithosphere interactions in Western Saudi Arabia: Inferences from 3He/4He in xenoliths and lava flows from Harrat Hutaymah","interactions":[],"lastModifiedDate":"2016-03-08T16:02:15","indexId":"70168926","displayToPublicDate":"2016-02-10T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2588,"text":"LITHOS","active":true,"publicationSubtype":{"id":10}},"title":"Asthenosphere–lithosphere interactions in Western Saudi Arabia: Inferences from 3He/4He in xenoliths and lava flows from Harrat Hutaymah","docAbstract":"Extensive volcanic fields on the western Arabian Plate have erupted intermittently over the last 30 Ma following emplacement of the Afar flood basalts in Ethiopia. In an effort to better understand the origin of this volcanism in western Saudi Arabia, we analyzed3He/4He, and He, CO2 and trace element concentrations in minerals separated from xenoliths and lava flows from Harrat Hutaymah, supplemented with reconnaissance He isotope data from several other volcanic fields (Harrat Al Birk, Harrat Al Kishb and Harrat Ithnayn). Harrat Hutaymah is young (< 850 ka) and the northeasternmost of the volcanic fields. There is a remarkable homogeneity of 3He/4He trapped within most xenoliths, with a weighted mean of 7.54 ± 0.03 RA (2σ, n = 20). This homogeneity occurs over at least eight different xenolith types (including spinel lherzolite, amphibole clinopyroxenite, olivine websterite, clinopyroxenite and garnet websterite), and encompasses ten different volcanic centers within an area of ~ 2500 km2. The homogeneity is caused by volatile equilibration between the xenoliths and fluids derived from their host magma, as fluid inclusions are annealed during the infiltration of vapor-saturated magmas along crystalline grain boundaries. The notable exceptions are the anhydrous spinel lherzolites, which have a lower weighted mean 3He/4He of 6.8 ± 0.3 RA (2σ, n = 2), contain lower concentrations of trapped He, and have a distinctly depleted light rare earth element signature. 3He/4He values of ~ 6.8 RA are also commonly found in spinel lherzolites from harrats Ithnayn, Al Birk, and from Zabargad Island in the Red Sea. Olivine from non-xenolith-bearing lava flows at Hutaymah spans the He isotope range of the xenoliths. The lower 3He/4He in the anhydrous spinel lherzolites appears to be tied to remnant Proterozoic lithosphere prior to metasomatic fluid overprinting.
\nElevated 3He/4He in the western harrats has been observed only at Rahat (up to 11.8 RA; Murcia et al., 2013), a volcanic field situated above thinned lithosphere beneath the Makkah-Medinah-Nafud volcanic lineament. Previous work established that spinel lherzolites at Hutaymah are sourced near the lithosphere-asthenosphere boundary (LAB), while other xenolith types there are derived from shallower depths within the lithosphere itself (Thornber, 1992). Helium isotopes are consistent with melts originating near the LAB beneath many of the Arabian harrats, and any magma derived from the Afar mantle plume currently appears to be of minor importance.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.lithos.2016.01.031","usgsCitation":"Konrad, K., Graham, D.W., Thornber, C., Duncan, R.A., Kent, A., and Al-Amri, A., 2016, Asthenosphere–lithosphere interactions in Western Saudi Arabia: Inferences from 3He/4He in xenoliths and lava flows from Harrat Hutaymah: LITHOS, v. 248-251, p. 339-352, https://doi.org/10.1016/j.lithos.2016.01.031.","productDescription":"14 p.","startPage":"339","endPage":"352","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-070268","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":471252,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.lithos.2016.01.031","text":"Publisher Index Page"},{"id":318695,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Saudi Arabia, Yemen","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 34.62890625,\n 28.14950321154457\n ],\n [\n 39.63867187499999,\n 30.29701788337205\n ],\n [\n 48.9990234375,\n 14.179186142354181\n ],\n [\n 43.59375,\n 12.46876014482322\n ],\n [\n 34.62890625,\n 28.14950321154457\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"248-251","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"56e005c1e4b015c306fd0ef3","contributors":{"authors":[{"text":"Konrad, Kevin","contributorId":167397,"corporation":false,"usgs":false,"family":"Konrad","given":"Kevin","email":"","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":622137,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Graham, David W.","contributorId":167398,"corporation":false,"usgs":false,"family":"Graham","given":"David","email":"","middleInitial":"W.","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":622138,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Thornber, Carl 0000-0002-6382-4408 cthornber@usgs.gov","orcid":"https://orcid.org/0000-0002-6382-4408","contributorId":167396,"corporation":false,"usgs":true,"family":"Thornber","given":"Carl","email":"cthornber@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":622136,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Duncan, Robert A.","contributorId":167399,"corporation":false,"usgs":false,"family":"Duncan","given":"Robert","email":"","middleInitial":"A.","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":622139,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kent, Adam J. 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R.","affiliations":[],"preferred":false,"id":622140,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Al-Amri, Abdulla","contributorId":167400,"corporation":false,"usgs":false,"family":"Al-Amri","given":"Abdulla","affiliations":[{"id":24707,"text":"King Saud University, Riyahd, KSA","active":true,"usgs":false}],"preferred":false,"id":622141,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70173439,"text":"70173439 - 2016 - Antemortem detection of chronic wasting disease prions in nasal brush collections and rectal biopsies from white-tailed deer by real time quaking-induced conversion","interactions":[],"lastModifiedDate":"2016-06-14T15:20:19","indexId":"70173439","displayToPublicDate":"2016-02-10T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2218,"text":"Journal of Clinical Microbiology","active":true,"publicationSubtype":{"id":10}},"title":"Antemortem detection of chronic wasting disease prions in nasal brush collections and rectal biopsies from white-tailed deer by real time quaking-induced conversion","docAbstract":"Chronic wasting disease (CWD), a transmissible spongiform encephalopathy of cervids, was first documented nearly 50 years ago in Colorado and Wyoming and has since spread to cervids in 23 states, two Canadian provinces, and the Republic of Korea. The expansion of this disease makes the development of sensitive diagnostic assays and antemortem sampling techniques crucial for the mitigation of its spread; this is especially true in cases of relocation/reintroduction of farmed or free-ranging deer and elk or surveillance studies of private or protected herds, where depopulation is contraindicated. This study sought to evaluate the sensitivity of the real-time quaking-induced conversion (RT-QuIC) assay by using recto-anal mucosa-associated lymphoid tissue (RAMALT) biopsy specimens and nasal brush samples collected antemortem from farmed white-tailed deer (n = 409). Antemortem findings were then compared to results from ante- and postmortem samples (RAMALT, brainstem, and medial retropharyngeal lymph nodes) evaluated by using the current gold standard in vitro assay, immunohistochemistry (IHC) analysis. We hypothesized that the sensitivity of RT-QuIC would be comparable to IHC analysis in antemortem tissues and would correlate with both the genotype and the stage of clinical disease. Our results showed that RAMALT testing by RT-QuIC assay had the highest sensitivity (69.8%) compared to that of postmortem testing, with a specificity of >93.9%. These data suggest that RT-QuIC, like IHC analysis, is an effective assay for detection of PrPCWD in rectal biopsy specimens and other antemortem samples and, with further research to identify more sensitive tissues, bodily fluids, or experimental conditions, has potential for large-scale and rapid automated testing for CWD diagnosis.
","language":"English","publisher":"American Society for Microbiology","doi":"10.1128/JCM.02699-15","usgsCitation":"Haley, N.J., Siepker, C., Walter, W.D., Thomsen, B.V., Greenlee, J.J., Lehmkuhl, A.D., and Richt, J.A., 2016, Antemortem detection of chronic wasting disease prions in nasal brush collections and rectal biopsies from white-tailed deer by real time quaking-induced conversion: Journal of Clinical Microbiology, v. 54, no. 4, p. 1108-1116, https://doi.org/10.1128/JCM.02699-15.","productDescription":"9 p.","startPage":"1108","endPage":"1116","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-069676","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":471254,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1128/jcm.02699-15","text":"Publisher Index Page"},{"id":323603,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"54","issue":"4","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57612aade4b04f417c2ce46a","contributors":{"authors":[{"text":"Haley, Nicholas J.","contributorId":171814,"corporation":false,"usgs":false,"family":"Haley","given":"Nicholas","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":638772,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Siepker, Chris","contributorId":171815,"corporation":false,"usgs":true,"family":"Siepker","given":"Chris","email":"","affiliations":[],"preferred":false,"id":638773,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Walter, W. David 0000-0003-3068-1073 wwalter@usgs.gov","orcid":"https://orcid.org/0000-0003-3068-1073","contributorId":5083,"corporation":false,"usgs":true,"family":"Walter","given":"W.","email":"wwalter@usgs.gov","middleInitial":"David","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":637133,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Thomsen, Bruce V.","contributorId":171816,"corporation":false,"usgs":false,"family":"Thomsen","given":"Bruce","email":"","middleInitial":"V.","affiliations":[],"preferred":false,"id":638774,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Greenlee, Justin J.","contributorId":171817,"corporation":false,"usgs":false,"family":"Greenlee","given":"Justin","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":638775,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lehmkuhl, Aaron D.","contributorId":171818,"corporation":false,"usgs":false,"family":"Lehmkuhl","given":"Aaron","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":638776,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Richt, Jurgen a.","contributorId":171819,"corporation":false,"usgs":false,"family":"Richt","given":"Jurgen","email":"","middleInitial":"a.","affiliations":[],"preferred":false,"id":638777,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70173600,"text":"70173600 - 2016 - Predicting the risk of toxic blooms of golden alga from cell abundance and environmental covariates","interactions":[],"lastModifiedDate":"2016-06-10T14:59:45","indexId":"70173600","displayToPublicDate":"2016-02-09T09:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2622,"text":"Limnology and Oceanography: Methods","active":true,"publicationSubtype":{"id":10}},"title":"Predicting the risk of toxic blooms of golden alga from cell abundance and environmental covariates","docAbstract":"Golden alga (Prymnesium parvum) is a toxic haptophyte that has caused considerable ecological damage to marine and inland aquatic ecosystems worldwide. Studies focused primarily on laboratory cultures have indicated that toxicity is poorly correlated with the abundance of golden alga cells. This relationship, however, has not been rigorously evaluated in the field where environmental conditions are much different. The ability to predict toxicity using readily measured environmental variables and golden alga abundance would allow managers rapid assessments of ichthyotoxicity potential without laboratory bioassay confirmation, which requires additional resources to accomplish. To assess the potential utility of these relationships, several a priori models relating lethal levels of golden alga ichthyotoxicity to golden alga abundance and environmental covariates were constructed. Model parameters were estimated using archived data from four river basins in Texas and New Mexico (Colorado, Brazos, Red, Pecos). Model predictive ability was quantified using cross-validation, sensitivity, and specificity, and the relative ranking of environmental covariate models was determined by Akaike Information Criterion values and Akaike weights. Overall, abundance was a generally good predictor of ichthyotoxicity as cross validation of golden alga abundance-only models ranged from ∼ 80% to ∼ 90% (leave-one-out cross-validation). Environmental covariates improved predictions, especially the ability to predict lethally toxic events (i.e., increased sensitivity), and top-ranked environmental covariate models differed among the four basins. These associations may be useful for monitoring as well as understanding the abiotic factors that influence toxicity during blooms.
","language":"English","publisher":"Wiley","doi":"10.1002/lom3.10048","usgsCitation":"Patino, R., VanLandeghem, M.M., and Denny, S., 2016, Predicting the risk of toxic blooms of golden alga from cell abundance and environmental covariates: Limnology and Oceanography: Methods, v. 13, no. 10, p. 568-586, https://doi.org/10.1002/lom3.10048.","productDescription":"18 p.","startPage":"568","endPage":"586","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-053132","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":471255,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/lom3.10048","text":"Publisher Index Page"},{"id":323461,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Mexico, Texas","otherGeospatial":"Colorado River Basin, Brazos River Basin, Red River Basin, Pecos River 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Shawn","contributorId":145738,"corporation":false,"usgs":false,"family":"Denny","given":"Shawn","email":"","affiliations":[],"preferred":false,"id":638471,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70164477,"text":"70164477 - 2016 - Spatial and temporal variation in microcystins occurrence in wadeable streams in the southeastern USA","interactions":[],"lastModifiedDate":"2018-08-07T12:32:00","indexId":"70164477","displayToPublicDate":"2016-02-08T09:45:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1571,"text":"Environmental Toxicology and Chemistry","active":true,"publicationSubtype":{"id":10}},"title":"Spatial and temporal variation in microcystins occurrence in wadeable streams in the southeastern USA","docAbstract":"Despite historical observations of potential microcystin-producing cyanobacteria (including Leptolyngbya,Phormidium, Pseudoanabaena, and Anabaena species) in 74% of headwater streams in Alabama, Georgia, South Carolina, and North Carolina (USA) from 1993 to 2011, fluvial cyanotoxin occurrence has not been systematically assessed in the southeastern United States. To begin to address this data gap, a spatial reconnaissance of fluvial microcystin concentrations was conducted in 75 wadeable streams in the Piedmont region (southeastern USA) during June 2014. Microcystins were detected using enzyme-linked immunosorbent assay (limit = 0.10 µg/L) in 39% of the streams with mean, median, and maximum detected concentrations of 0.29 µg/L, 0.11 µg/L, and 3.2 µg/L, respectively. Significant (α = 0.05) correlations were observed between June 2014 microcystin concentrations and stream flow, total nitrogen to total phosphorus ratio, and water temperature; but each of these factors explained 38% or less of the variability in fluvial microcystins across the region. Temporal microcystin variability was assessed monthly through October 2014 in 5 of the streams where microcystins were observed in June and in 1 reference location; microcystins were repeatedly detected in all but the reference stream. Although microcystin concentrations in the present study did not exceed World Health Organization recreational guidance thresholds, their widespread occurrence demonstrates the need for further investigation of possible in-stream environmental health effects as well as potential impacts on downstream lakes and reservoirs. Environ Toxicol Chem 2016;9999:1–7. Published 2016 Wiley Periodicals Inc. on behalf of SETAC. This article is a US Government work and, as such, is in the public domain in the United States of America.
","language":"English","publisher":"Wiley, Inc.","doi":"10.1002/etc.3391","usgsCitation":"Loftin, K.A., Clark, J.M., Journey, C.A., Kolpin, D.W., Van Metre, P., and Bradley, P.M., 2016, Spatial and temporal variation in microcystins occurrence in wadeable streams in the southeastern USA: Environmental Toxicology and Chemistry, v. 35, no. 9, p. 2281-2287, https://doi.org/10.1002/etc.3391.","productDescription":"7 p.","startPage":"2281","endPage":"2287","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-069266","costCenters":[{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":438637,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7VQ30RM","text":"USGS data release","linkHelpText":"Periphyton (1993-2011) and Water Quality (2014) Data for ET&C Article Entitled Spatial and Temporal Variation in Microcystins Occurrence in 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cjourney@usgs.gov","orcid":"https://orcid.org/0000-0002-2284-5851","contributorId":2617,"corporation":false,"usgs":true,"family":"Journey","given":"Celeste","email":"cjourney@usgs.gov","middleInitial":"A.","affiliations":[{"id":559,"text":"South Carolina Water Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":false,"id":597541,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kolpin, Dana W. 0000-0002-3529-6505 dwkolpin@usgs.gov","orcid":"https://orcid.org/0000-0002-3529-6505","contributorId":1239,"corporation":false,"usgs":true,"family":"Kolpin","given":"Dana","email":"dwkolpin@usgs.gov","middleInitial":"W.","affiliations":[{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true}],"preferred":true,"id":597542,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Van Metre, Peter C. pcvanmet@usgs.gov","contributorId":486,"corporation":false,"usgs":true,"family":"Van Metre","given":"Peter C.","email":"pcvanmet@usgs.gov","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":false,"id":597543,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bradley, Paul M. 0000-0001-7522-8606 pbradley@usgs.gov","orcid":"https://orcid.org/0000-0001-7522-8606","contributorId":361,"corporation":false,"usgs":true,"family":"Bradley","given":"Paul","email":"pbradley@usgs.gov","middleInitial":"M.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":597538,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70164478,"text":"70164478 - 2016 - Aerobic biodegradation potential of endocrine disrupting chemicals in surface-water sediment at Rocky Mountains National Park, USA","interactions":[],"lastModifiedDate":"2018-08-09T12:08:22","indexId":"70164478","displayToPublicDate":"2016-02-08T09:45:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1529,"text":"Environmental Chemistry","active":true,"publicationSubtype":{"id":10}},"title":"Aerobic biodegradation potential of endocrine disrupting chemicals in surface-water sediment at Rocky Mountains National Park, USA","docAbstract":"Endocrine disrupting chemicals (EDC) in surface water and bed sediment threaten the structure and function of aquatic ecosystems. In natural, remote, and protected surface-water environments where contaminant releases are sporadic, contaminant biodegradation is a fundamental driver of exposure concentration, timing, duration, and, thus, EDC ecological risk. Anthropogenic contaminants, including known and suspected EDC, were detected in surface water and sediment collected from 2 streams and 2 lakes in Rocky Mountains National Park (ROMO). The potential for aerobic EDC biodegradation was assessed in collected sediments using 6 14C-radiolabeled model compounds. Aerobic microbial mineralization of natural (estrone and 17β-estradiol) and synthetic (17α-ethinylestradiol) estrogen was significant at all sites. ROMO bed sediment microbial communities also effectively degraded the xenoestrogens, bisphenol-A and 4-nonylphenol. The same sediment samples exhibited little potential for aerobic biodegradation of triclocarban, however, illustrating the need to assess a wider range of contaminant compounds. The current results support recent concerns over the widespread environmental occurrence of carbanalide antibacterials, like triclocarban and triclosan, and suggest that backcountry use of products containing these compounds should be discouraged.
","language":"English","publisher":"Wiley, Inc.","doi":"10.1002/etc.3266","usgsCitation":"Bradley, P.M., Battaglin, W.A., Iwanowicz, L., Clark, J.M., and Journey, C.A., 2016, Aerobic biodegradation potential of endocrine disrupting chemicals in surface-water sediment at Rocky Mountains National Park, USA: Environmental Chemistry, v. 35, no. 5, p. 1087-1096, https://doi.org/10.1002/etc.3266.","productDescription":"10 p.","startPage":"1087","endPage":"1096","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-067297","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":316641,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Rocky Mountain National Park","volume":"35","issue":"5","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationDate":"2015-11-20","publicationStatus":"PW","scienceBaseUri":"56b9bc28e4b08d617f63a7df","chorus":{"doi":"10.1002/etc.3266","url":"http://dx.doi.org/10.1002/etc.3266","publisher":"Wiley-Blackwell","authors":"Bradley Paul M., Battaglin William A., Iwanowicz Luke R., Clark Jimmy M., Journey Celeste A.","journalName":"Environmental Toxicology and Chemistry","publicationDate":"3/15/2016","auditedOn":"4/19/2016"},"contributors":{"authors":[{"text":"Bradley, Paul M. 0000-0001-7522-8606 pbradley@usgs.gov","orcid":"https://orcid.org/0000-0001-7522-8606","contributorId":361,"corporation":false,"usgs":true,"family":"Bradley","given":"Paul","email":"pbradley@usgs.gov","middleInitial":"M.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":597544,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Battaglin, William A. 0000-0001-7287-7096 wbattagl@usgs.gov","orcid":"https://orcid.org/0000-0001-7287-7096","contributorId":1527,"corporation":false,"usgs":true,"family":"Battaglin","given":"William","email":"wbattagl@usgs.gov","middleInitial":"A.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":597545,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Iwanowicz, Luke R. 0000-0002-1197-6178 liwanowicz@usgs.gov","orcid":"https://orcid.org/0000-0002-1197-6178","contributorId":150383,"corporation":false,"usgs":true,"family":"Iwanowicz","given":"Luke R. ","email":"liwanowicz@usgs.gov","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":false,"id":597546,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Clark, Jimmy M. 0000-0002-3138-5738 jmclark@usgs.gov","orcid":"https://orcid.org/0000-0002-3138-5738","contributorId":4773,"corporation":false,"usgs":true,"family":"Clark","given":"Jimmy","email":"jmclark@usgs.gov","middleInitial":"M.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":559,"text":"South Carolina Water Science Center","active":true,"usgs":true}],"preferred":true,"id":597547,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Journey, Celeste A. 0000-0002-2284-5851 cjourney@usgs.gov","orcid":"https://orcid.org/0000-0002-2284-5851","contributorId":2617,"corporation":false,"usgs":true,"family":"Journey","given":"Celeste","email":"cjourney@usgs.gov","middleInitial":"A.","affiliations":[{"id":559,"text":"South Carolina Water Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":false,"id":597548,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70169886,"text":"70169886 - 2016 - Chaparral","interactions":[],"lastModifiedDate":"2016-04-06T15:31:06","indexId":"70169886","displayToPublicDate":"2016-02-08T09:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Chaparral","docAbstract":"One of the most dynamic California ecosystems is chaparral. Dominated by evergreen, sclerophyllous shrubs and small trees, chaparral is the most extensive vegetation type in the state (Figure 1). The nearly impenetrable tangle of stiff branches of this unusual vegetation inhibits exploration, and as a consequence the public know little about its natural history and unique characteristics. This under-valued ecosystem is recognized instead by the threat of its extensive, high-intensity canopy-burning wildfires that characterize the dry summer and fall seasons of the state. Because urban areas frequently share borders or intermix with chaparral, societal interests often conflict with conservation of this ecosystem, and understanding its history and dynamics are a key to appreciating its importance.
In this chapter we emphasize the principal structure and dynamics of this important ecosystem. The long summer rainless period has strong impacts on all organisms and, importantly, the droughts influence the fire regime that characterizes chaparral. An ecosystem currently characterized by a specific drought and wildfire regime can expect significant impacts from climate change. Because of its dominance at lower elevations, chaparral also is frequently found at or near the boundaries of urban developments and metropolitan centers. Attempts to suppress fire also affect chaparral dynamics in the long absence of fire. The conflicts between the impacts of chaparral wildfire and human life and structures has been an aspect of California’s history since the beginning, but as development encroaches ever more into chaparral regions, the conflicts have increased. Consequently, understanding this vegetation is important not only because of its significance in understanding ecological evolution and the ecological services provided by chaparral, but also because of its direct impacts on human settlements.
Diamondback terrapins (Malaclemys terrapin) are currently in decline across much of their historical range, and demographic data on a regional scale are needed to identify where their populations are at greatest risk. Because terrapins residing in salt marshes are difficult to capture, we designed a cylindrical bait trap (CBT) that could be deployed in shallow tidal waters. From 2003 to 2006, trials were conducted with CBTs in the Chesapeake Bay, Maryland (USA) to determine terrapin sex, size, and age distribution within 3 salt marsh interior habitats—open bays, tidal guts, and broken marshes—using 15 traps/habitat. Analyses based on 791 total captures with CBTs indicate that smaller terrapins, (i.e., adult male and subadult) were more prevalent within the transecting tidal guts and broken marshes, whereas the adult females were more evenly distributed among habitats, including open bays. Subadult females made up the largest percent of catch in the CBTs deployed within the 3 marsh interior habitats. During a 12-day trial in which we compared capture performance of CBTs and modified fyke nets along open shorelines during the nesting season, fyke nets outperformed CBTs by accounting for 95.2% of the 604 terrapin captures. Although the long drift leads of the fyke nets proved more effective for intercepting along-shore travel of adult female terrapins during the nesting season, CBTs provided a more effective means of live-trapping terrapins within the shallow interior marshes.
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