The effects of acute environmental stressors on reproduction in wildlife are often difficult to measure because of the labour and disturbance involved in collecting accurate reproductive data. Stress hormones represent a promising option for assessing the effects of environmental perturbations on altricial young; however, it is necessary first to establish how stress levels are affected by environmental conditions during development and whether elevated stress results in reduced survival and recruitment rates. In birds, the stress hormone corticosterone is deposited in feathers during the entire period of feather growth, making it an integrated measure of background stress levels during development. We tested the utility of feather corticosterone levels in 3- to 4-week-old nestling brown pelicans (Pelecanus occidentalis) for predicting survival rates at both the individual and colony levels. We also assessed the relationship of feather corticosterone to nestling body condition and rates of energy delivery to nestlings. Chicks with higher body condition and lower corticosterone levels were more likely to fledge and to be resighted after fledging, whereas those with lower body condition and higher corticosterone levels were less likely to fledge or be resighted after fledging. Feather corticosterone was also associated with intracolony differences in survival between ground and elevated nest sites. Colony-wide, mean feather corticosterone predicted nest productivity, chick survival and post-fledging dispersal more effectively than did body condition, although these relationships were strongest before fledglings dispersed away from the colony. Both reproductive success and nestling corticosterone were strongly related to nutritional conditions, particularly meal delivery rates. We conclude that feather corticosterone is a powerful predictor of reproductive success and could provide a useful metric for rapidly assessing the effects of changes in environmental conditions, provided pre-existing baseline variation is monitored and understood.
","language":"English","publisher":"Oxford Academic","doi":"10.1093/conphys/cow060","usgsCitation":"Lamb, J.S., O’Reilly, K.M., and Jodice, P.G., 2016, Physical condition and stress levels during early development reflect feeding rates and predict pre- and post-fledging survival in a nearshore seabird: Conservation Physiology, v. 4, no. 1, Article cow060; 14 p., https://doi.org/10.1093/conphys/cow060.","productDescription":"Article cow060; 14 p.","ipdsId":"IP-079141","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":471368,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/conphys/cow060","text":"Publisher Index Page"},{"id":347158,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Gulf of Mexico","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -97.3828125,\n 27.352252938063845\n ],\n [\n -82.4853515625,\n 27.352252938063845\n ],\n [\n -82.4853515625,\n 30.90222470517144\n ],\n [\n -97.3828125,\n 30.90222470517144\n ],\n [\n -97.3828125,\n 27.352252938063845\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"4","issue":"1","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2016-12-09","publicationStatus":"PW","scienceBaseUri":"59eeffabe4b0220bbd988fc1","contributors":{"authors":[{"text":"Lamb, Juliet S. 0000-0003-0358-3240","orcid":"https://orcid.org/0000-0003-0358-3240","contributorId":198059,"corporation":false,"usgs":false,"family":"Lamb","given":"Juliet","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":714962,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"O’Reilly, Kathleen M.","contributorId":198060,"corporation":false,"usgs":false,"family":"O’Reilly","given":"Kathleen","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":714963,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jodice, Patrick G.R. 0000-0001-8716-120X pjodice@usgs.gov","orcid":"https://orcid.org/0000-0001-8716-120X","contributorId":1119,"corporation":false,"usgs":true,"family":"Jodice","given":"Patrick","email":"pjodice@usgs.gov","middleInitial":"G.R.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":false,"id":714279,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70191522,"text":"70191522 - 2016 - Estimating abundance: Chapter 27","interactions":[],"lastModifiedDate":"2017-11-30T12:58:43","indexId":"70191522","displayToPublicDate":"2016-01-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Estimating abundance: Chapter 27","docAbstract":"This chapter provides a non-technical overview of ‘closed population capture–recapture’ models, a class of well-established models that are widely applied in ecology, such as removal sampling, covariate models, and distance sampling. These methods are regularly adopted for studies of reptiles, in order to estimate abundance from counts of marked individuals while accounting for imperfect detection. Thus, the chapter describes some classic closed population models for estimating abundance, with considerations for some recent extensions that provide a spatial context for the estimation of abundance, and therefore density. Finally, the chapter suggests some software for use in data analysis, such as the Windows-based program MARK, and provides an example of estimating abundance and density of reptiles using an artificial cover object survey of Slow Worms (Anguis fragilis).
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Reptile ecology and conservation: A handbook of techniques","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Oxford University Press","doi":"10.1093/acprof:oso/9780198726135.003.0027","usgsCitation":"Royle, J., 2016, Estimating abundance: Chapter 27, chap. of Reptile ecology and conservation: A handbook of techniques, p. 388-401, https://doi.org/10.1093/acprof:oso/9780198726135.003.0027.","productDescription":"14 p.","startPage":"388","endPage":"401","ipdsId":"IP-066002","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":349590,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a60fd88e4b06e28e9c24fdf","contributors":{"authors":[{"text":"Royle, J. Andrew 0000-0003-3135-2167 aroyle@usgs.gov","orcid":"https://orcid.org/0000-0003-3135-2167","contributorId":138865,"corporation":false,"usgs":true,"family":"Royle","given":"J. Andrew","email":"aroyle@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":712610,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70187264,"text":"70187264 - 2016 - Predicting invasiveness of species in trade: Climate match, trophic guild and fecundity influence establishment and impact of non-native freshwater fishes","interactions":[],"lastModifiedDate":"2017-04-27T10:40:35","indexId":"70187264","displayToPublicDate":"2016-01-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1399,"text":"Diversity and Distributions","active":true,"publicationSubtype":{"id":10}},"title":"Predicting invasiveness of species in trade: Climate match, trophic guild and fecundity influence establishment and impact of non-native freshwater fishes","docAbstract":"Aim
Impacts of non-native species have motivated development of risk assessment tools for identifying introduced species likely to become invasive. Here, we develop trait-based models for the establishment and impact stages of freshwater fish invasion, and use them to screen non-native species common in international trade. We also determine which species in the aquarium, biological supply, live bait, live food and water garden trades are likely to become invasive. Results are compared to historical patterns of non-native fish establishment to assess the relative importance over time of pathways in causing invasions.
Location
Laurentian Great Lakes region.
Methods
Trait-based classification trees for the establishment and impact stages of invasion were developed from data on freshwater fish species that established or failed to establish in the Great Lakes. Fishes in trade were determined from import data from Canadian and United States regulatory agencies, assigned to specific trades and screened through the developed models.
Results
Climate match between a species’ native range and the Great Lakes region predicted establishment success with 75–81% accuracy. Trophic guild and fecundity predicted potential harmful impacts of established non-native fishes with 75–83% accuracy. Screening outcomes suggest the water garden trade poses the greatest risk of introducing new invasive species, followed by the live food and aquarium trades. Analysis of historical patterns of introduction pathways demonstrates the increasing importance of these trades relative to other pathways. Comparisons among trades reveal that model predictions parallel historical patterns; all fishes previously introduced from the water garden trade have established. The live bait, biological supply, aquarium and live food trades have also contributed established non-native fishes.
Main conclusions
Our models predict invasion risk of potential fish invaders to the Great Lakes region and could help managers prioritize efforts among species and pathways to minimize such risk. Similar approaches could be applied to other taxonomic groups and geographic regions.
","language":"English","publisher":"Wiley","doi":"10.1111/ddi.12391","usgsCitation":"Howeth, J.G., Gantz, C.A., Angermeier, P.L., Frimpong, E.A., Hoff, M.H., Keller, R.P., Mandrak, N.E., Marchetti, M.P., Olden, J., Romagosa, C., and Lodge, D.M., 2016, Predicting invasiveness of species in trade: Climate match, trophic guild and fecundity influence establishment and impact of non-native freshwater fishes: Diversity and Distributions, v. 22, no. 2, p. 148-160, https://doi.org/10.1111/ddi.12391.","productDescription":"13 p.","startPage":"148","endPage":"160","ipdsId":"IP-060340","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":471374,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/ddi.12391","text":"Publisher Index Page"},{"id":340492,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"22","issue":"2","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2015-11-02","publicationStatus":"PW","scienceBaseUri":"59030326e4b0e862d230f727","contributors":{"authors":[{"text":"Howeth, Jennifer G.","contributorId":63319,"corporation":false,"usgs":true,"family":"Howeth","given":"Jennifer","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":693133,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gantz, Crysta A.","contributorId":105647,"corporation":false,"usgs":true,"family":"Gantz","given":"Crysta","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":693134,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"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":693122,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Frimpong, Emmanuel A.","contributorId":79372,"corporation":false,"usgs":true,"family":"Frimpong","given":"Emmanuel","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":693135,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hoff, Michael H.","contributorId":111519,"corporation":false,"usgs":true,"family":"Hoff","given":"Michael","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":693136,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Keller, Reuben P.","contributorId":98637,"corporation":false,"usgs":true,"family":"Keller","given":"Reuben","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":693137,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Mandrak, Nicholas E.","contributorId":177869,"corporation":false,"usgs":false,"family":"Mandrak","given":"Nicholas","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":693138,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Marchetti, Michael P.","contributorId":191469,"corporation":false,"usgs":false,"family":"Marchetti","given":"Michael","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":693139,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Olden, Julian D.","contributorId":66951,"corporation":false,"usgs":true,"family":"Olden","given":"Julian D.","affiliations":[],"preferred":false,"id":693140,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Romagosa, Christina M.","contributorId":39661,"corporation":false,"usgs":true,"family":"Romagosa","given":"Christina M.","affiliations":[],"preferred":false,"id":693141,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Lodge, David M.","contributorId":76622,"corporation":false,"usgs":false,"family":"Lodge","given":"David","email":"","middleInitial":"M.","affiliations":[{"id":16905,"text":"University of Notre Dame, Dept. of Biological Sciences, Notre Dame, IN, 46556, USA","active":true,"usgs":false}],"preferred":false,"id":693142,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70189094,"text":"70189094 - 2016 - A comparison of helicopter-borne electromagnetic systems for hydrogeologic studies","interactions":[],"lastModifiedDate":"2017-06-29T15:02:55","indexId":"70189094","displayToPublicDate":"2016-01-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1806,"text":"Geophysical Prospecting","active":true,"publicationSubtype":{"id":10}},"title":"A comparison of helicopter-borne electromagnetic systems for hydrogeologic studies","docAbstract":"The increased application of airborne electromagnetic surveys to hydrogeological studies is driving a demand for data that can consistently be inverted for accurate subsurface resistivity structure from the near surface to depths of several hundred metres. We present an evaluation of three commercial airborne electromagnetic systems over two test blocks in western Nebraska, USA. The selected test blocks are representative of shallow and deep alluvial aquifer systems with low groundwater salinity and an electrically conductive base of aquifer. The aquifer units show significant lithologic heterogeneity and include both modern and ancient river systems. We compared the various data sets to one another and inverted resistivity models to borehole lithology and to ground geophysical models. We find distinct differences among the airborne electromagnetic systems as regards the spatial resolution of models, the depth of investigation, and the ability to recover near-surface resistivity variations. We further identify systematic biases in some data sets, which we attribute to incomplete or inexact calibration or compensation procedures.
","language":"English","publisher":"Wiley","doi":"10.1111/1365-2478.12262","usgsCitation":"Bedrosian, P.A., Schamper, C., and Auken, E., 2016, A comparison of helicopter-borne electromagnetic systems for hydrogeologic studies: Geophysical Prospecting, v. 64, no. 1, p. 192-215, https://doi.org/10.1111/1365-2478.12262.","productDescription":"24 p.","startPage":"192","endPage":"215","ipdsId":"IP-049361","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":343162,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nebraska","volume":"64","issue":"1","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2015-06-29","publicationStatus":"PW","scienceBaseUri":"595611b7e4b0d1f9f0506768","contributors":{"authors":[{"text":"Bedrosian, Paul A. 0000-0002-6786-1038 pbedrosian@usgs.gov","orcid":"https://orcid.org/0000-0002-6786-1038","contributorId":839,"corporation":false,"usgs":true,"family":"Bedrosian","given":"Paul","email":"pbedrosian@usgs.gov","middleInitial":"A.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":702837,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schamper, Cyril","contributorId":193990,"corporation":false,"usgs":false,"family":"Schamper","given":"Cyril","email":"","affiliations":[],"preferred":false,"id":702838,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Auken, Esben","contributorId":193991,"corporation":false,"usgs":false,"family":"Auken","given":"Esben","email":"","affiliations":[],"preferred":false,"id":702839,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70194448,"text":"70194448 - 2016 - LakeMetabolizer: An R package for estimating lake metabolism from free-water oxygen using diverse statistical models","interactions":[],"lastModifiedDate":"2018-01-24T16:05:13","indexId":"70194448","displayToPublicDate":"2016-01-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1999,"text":"Inland Waters","active":true,"publicationSubtype":{"id":10}},"title":"LakeMetabolizer: An R package for estimating lake metabolism from free-water oxygen using diverse statistical models","docAbstract":"Metabolism is a fundamental process in ecosystems that crosses multiple scales of organization from individual organisms to whole ecosystems. To improve sharing and reuse of published metabolism models, we developed LakeMetabolizer, an R package for estimating lake metabolism from in situ time series of dissolved oxygen, water temperature, and, optionally, additional environmental variables. LakeMetabolizer implements 5 different metabolism models with diverse statistical underpinnings: bookkeeping, ordinary least squares, maximum likelihood, Kalman filter, and Bayesian. Each of these 5 metabolism models can be combined with 1 of 7 models for computing the coefficient of gas exchange across the air–water interface (k). LakeMetabolizer also features a variety of supporting functions that compute conversions and implement calculations commonly applied to raw data prior to estimating metabolism (e.g., oxygen saturation and optical conversion models). These tools have been organized into an R package that contains example data, example use-cases, and function documentation. The release package version is available on the Comprehensive R Archive Network (CRAN), and the full open-source GPL-licensed code is freely available for examination and extension online. With this unified, open-source, and freely available package, we hope to improve access and facilitate the application of metabolism in studies and management of lentic ecosystems.
","language":"English","publisher":"Taylor & Francis","doi":"10.1080/IW-6.4.883","usgsCitation":"Winslow, L., Zwart, J., Batt, R., Dugan, H., Woolway, R., Corman, J., Hanson, P.C., and Read, J.S., 2016, LakeMetabolizer: An R package for estimating lake metabolism from free-water oxygen using diverse statistical models: Inland Waters, v. 6, no. 4, p. 622-636, https://doi.org/10.1080/IW-6.4.883.","productDescription":"15 p.","startPage":"622","endPage":"636","ipdsId":"IP-065534","costCenters":[{"id":160,"text":"Center for Integrated Data Analytics","active":false,"usgs":true}],"links":[{"id":349534,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"6","issue":"4","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2018-01-02","publicationStatus":"PW","scienceBaseUri":"5a60fd87e4b06e28e9c24fa5","contributors":{"authors":[{"text":"Winslow, Luke 0000-0002-8602-5510 lwinslow@usgs.gov","orcid":"https://orcid.org/0000-0002-8602-5510","contributorId":168947,"corporation":false,"usgs":true,"family":"Winslow","given":"Luke","email":"lwinslow@usgs.gov","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":5054,"text":"Office of Water Information","active":true,"usgs":true},{"id":160,"text":"Center for Integrated Data Analytics","active":false,"usgs":true}],"preferred":true,"id":723877,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zwart, Jacob A.","contributorId":173345,"corporation":false,"usgs":false,"family":"Zwart","given":"Jacob A.","affiliations":[{"id":16905,"text":"University of Notre Dame, Dept. of Biological Sciences, Notre Dame, IN, 46556, USA","active":true,"usgs":false}],"preferred":false,"id":723878,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Batt, Ryan D.","contributorId":168948,"corporation":false,"usgs":false,"family":"Batt","given":"Ryan D.","affiliations":[{"id":25393,"text":"Department of Ecology, Evolution, and Natural Resources, Rutgers University, New Brunswick, New Jersey, USA 08901","active":true,"usgs":false}],"preferred":false,"id":723879,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dugan, Hilary","contributorId":150191,"corporation":false,"usgs":false,"family":"Dugan","given":"Hilary","affiliations":[{"id":17938,"text":"Center for Limnology University of Wisconsin, Madison, WI 53706, US","active":true,"usgs":false}],"preferred":false,"id":723880,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Woolway, R. Iestyn","contributorId":150345,"corporation":false,"usgs":false,"family":"Woolway","given":"R. Iestyn","affiliations":[{"id":18007,"text":"Lake Ecosystems Group, Centre for Ecology & Hydrology, Lancaster Environment Centre, Library Avenue, Bailrigg, Lancaster, LA1 4AP, UK.","active":true,"usgs":false}],"preferred":false,"id":723881,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Corman, Jessica","contributorId":194469,"corporation":false,"usgs":false,"family":"Corman","given":"Jessica","affiliations":[],"preferred":false,"id":723882,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hanson, Paul C.","contributorId":35634,"corporation":false,"usgs":false,"family":"Hanson","given":"Paul","email":"","middleInitial":"C.","affiliations":[{"id":12951,"text":"Center for Limnology, University of Wisconsin Madison","active":true,"usgs":false}],"preferred":false,"id":723883,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Read, Jordan S. 0000-0002-3888-6631 jread@usgs.gov","orcid":"https://orcid.org/0000-0002-3888-6631","contributorId":4453,"corporation":false,"usgs":true,"family":"Read","given":"Jordan","email":"jread@usgs.gov","middleInitial":"S.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":160,"text":"Center for Integrated Data Analytics","active":false,"usgs":true},{"id":5054,"text":"Office of Water Information","active":true,"usgs":true}],"preferred":true,"id":723884,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70190332,"text":"70190332 - 2016 - Fire in the Earth System: Bridging data and modeling research","interactions":[],"lastModifiedDate":"2017-08-26T17:20:10","indexId":"70190332","displayToPublicDate":"2016-01-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1112,"text":"Bulletin of the American Meteorological Society","onlineIssn":"1520-0477","printIssn":"0003-0007","active":true,"publicationSubtype":{"id":10}},"title":"Fire in the Earth System: Bridging data and modeling research","docAbstract":"Significant changes in wildfire occurrence, extent, and severity in areas such as western North America and Indonesia in 2015 have made the issue of fire increasingly salient in both the public and scientific spheres. Biomass combustion rapidly transforms land cover, smoke pours into the atmosphere, radiative heat from fires initiates dramatic pyrocumulus clouds, and the repeated ecological and atmospheric effects of fire can even impact regional and global climate. Furthermore, fires have a significant impact on human health, livelihoods, and social and economic systems.
Modeling and databased methods to understand fire have rapidly coevolved over the past decade. Satellite and ground-based data about present-day fire are widely available for applications in research and fire management. Fire modeling has developed in part because of the evolution in vegetation and Earth system modeling efforts, but parameterizations and validation are largely focused on the present day because of the availability of satellite data. Charcoal deposits in sediment cores have emerged as a powerful method to evaluate trends in biomass burning extending back to the Last Glacial Maximum and beyond, and these records provide a context for present-day fire. The Global Charcoal Database version 3 compiled about 700 charcoal records and more than 1,000 records are expected for the future version 4. Together, these advances offer a pathway to explore how the strengths of fire data and fire modeling could address the weaknesses in the overall understanding of human-climate–fire linkages.
A community of researchers studying fire in the Earth system with individual expertise that included paleoecology, paleoclimatology, modern ecology, archaeology, climate, and Earth system modeling, statistics, geography, biogeochemistry, and atmospheric science met at an intensive workshop in Massachusetts to explore new research directions and initiate new collaborations. Research themes, which emerged from the workshop participants via preworkshop surveys, focused on addressing the following questions: What are the climatic, ecological, and human drivers of fire regimes, both past and future? What is the role of humans in shaping historical fire regimes? How does fire ecology affect land cover changes, biodiversity, carbon storage, and human land uses? What are the historical fire trends and their impacts across biomes? Are their impacts local and/or regional? Are the fire trends in the last two decades unprecedented from a historical perspective? The workshop1 aimed to develop testable hypotheses about fire, climate, vegetation, and human interactions by leveraging the confluence of proxy, observational, and model data related to decadal- to millennial-scale fire activity on our planet. New research directions focused on broad interdisciplinary approaches to highlight how knowledge about past fire activity could provide a more complete understanding of the predictive capacity of fire models and inform fire policy in the face of our changing climate.
","largerWorkTitle":"Bulletin of the American Meteorological Society (BAMS)","language":"English","publisher":"American Meteorological Society","doi":"10.1175/BAMS-D-15-00319.1","usgsCitation":"Hantson, S., Kloster, S., Coughlan, M., Daniau, A., Vanniere, B., Bruecher, T., Kehrwald, N.M., and Magi, B.I., 2016, Fire in the Earth System: Bridging data and modeling research: Bulletin of the American Meteorological Society, v. 97, no. 6, p. 1069-1072, https://doi.org/10.1175/BAMS-D-15-00319.1.","productDescription":"4 p.","startPage":"1069","endPage":"1072","ipdsId":"IP-071531","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":471389,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1175/bams-d-15-00319.1","text":"Publisher Index Page"},{"id":345161,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"97","issue":"6","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2016-07-08","publicationStatus":"PW","scienceBaseUri":"59a288c9e4b077f0056692b1","contributors":{"authors":[{"text":"Hantson, Srijn","contributorId":195866,"corporation":false,"usgs":false,"family":"Hantson","given":"Srijn","affiliations":[{"id":34430,"text":"Karlsruhe Institute of Technology, Garmisch-Partenkirchen, Germany","active":true,"usgs":false}],"preferred":false,"id":708480,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kloster, Silvia","contributorId":195867,"corporation":false,"usgs":false,"family":"Kloster","given":"Silvia","email":"","affiliations":[{"id":32387,"text":"Max Planck Institute for Meteorology, Hamburg, Germany","active":true,"usgs":false}],"preferred":false,"id":708481,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Coughlan, Michael","contributorId":168920,"corporation":false,"usgs":false,"family":"Coughlan","given":"Michael","email":"","affiliations":[{"id":25390,"text":"Department of Anthropology, University of Georgia, Athens, Georgia, USA","active":true,"usgs":false}],"preferred":false,"id":708482,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Daniau, Anne-Laure","contributorId":195869,"corporation":false,"usgs":false,"family":"Daniau","given":"Anne-Laure","email":"","affiliations":[{"id":34431,"text":"Université de Bordeaux, Talence, France","active":true,"usgs":false}],"preferred":false,"id":708483,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Vanniere, Boris","contributorId":195870,"corporation":false,"usgs":false,"family":"Vanniere","given":"Boris","affiliations":[{"id":34432,"text":"Université Bourgogne Franche-Comté, Besançon, France","active":true,"usgs":false}],"preferred":false,"id":708484,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bruecher, Tim","contributorId":195871,"corporation":false,"usgs":false,"family":"Bruecher","given":"Tim","email":"","affiliations":[{"id":34427,"text":"GEOMAR, Helmholtz Centre for Ocean Research","active":true,"usgs":false}],"preferred":false,"id":708485,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kehrwald, Natalie M. 0000-0002-9160-2239 nkehrwald@usgs.gov","orcid":"https://orcid.org/0000-0002-9160-2239","contributorId":168918,"corporation":false,"usgs":true,"family":"Kehrwald","given":"Natalie","email":"nkehrwald@usgs.gov","middleInitial":"M.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":708479,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Magi, Brian I.","contributorId":168923,"corporation":false,"usgs":false,"family":"Magi","given":"Brian","email":"","middleInitial":"I.","affiliations":[{"id":25392,"text":"Department of Geography and Earth Science, University of North Carolina at Charlotte, North Carolina, USA","active":true,"usgs":false}],"preferred":false,"id":708486,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70191935,"text":"70191935 - 2016 - San Pedro River Aquifer Binational Report","interactions":[],"lastModifiedDate":"2023-12-20T21:24:11.302348","indexId":"70191935","displayToPublicDate":"2016-01-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":9,"text":"Other Report"},"title":"San Pedro River Aquifer Binational Report","docAbstract":"The United States and Mexico share waters in a number of hydrological basins and aquifers that cross the international boundary. Both countries recognize that, in a region of scarce water resources and expanding populations, a greater scientific understanding of these aquifer systems would be beneficial. In light of this, the Mexican and U.S. Principal Engineers of the International Boundary and Water Commission (IBWC) signed the “Joint Report of the Principal Engineers Regarding the Joint Cooperative Process United States-Mexico for the Transboundary Aquifer Assessment Program\" on August 19, 2009 (IBWC-CILA, 2009). This IBWC “Joint Report” serves as the framework for U.S.-Mexico coordination and dialogue to implement transboundary aquifer studies. The document clarifies several details about the program such as background, roles, responsibilities, funding, relevance of the international water treaties, and the use of information collected or compiled as part of the program. In the document, it was agreed by the parties involved, which included the IBWC, the Mexican National Water Commission (CONAGUA), the U.S. Geological Survey (USGS), and the Universities of Arizona and Sonora, to study two priority binational aquifers, one in the San Pedro River basin and the other in the Santa Cruz River basin.
This report focuses on the Binational San Pedro Basin (BSPB). Reasons for the focus on and interest in this aquifer include the fact that it is shared by the two countries, that the San Pedro River has an elevated ecological value because of the riparian ecosystem that it sustains, and that water resources are needed to sustain the river, existing communities, and continued development. This study describes the aquifer’s characteristics in its binational context; however, most of the scientific work has been undertaken for many years by each country without full knowledge of the conditions on the other side of the border. The general objective of this study is to use new and existing research to define the general hydrologic framework of the Binational San Pedro Aquifer (BSPA), to gather hydrogeological and other relevant data in preparation for future work such as an updated groundwater conceptual model and budget and to establish the basis for a binational numerical model.
The specific objectives are as follows:
The BSPB is one of the most studied basins in the region, and a database of publications has been compiled as part of this project. Previous studies include topics that range from geophysics and hydrogeology to biology and ecosystem services. The economic drivers on each side of the border are quite different. In the Arizona 4 portion of the basin military and tourism dominate while in the Sonoran portion, mining is the most important industry. Water management is also different in the two countries. In Mexico, primary authority for management of water resources devolves from the federal government. In the United States, primary authority rests with the states except in cases of interstate surface waters. Binational waters are not currently jointly managed by the two countries except in cases where treaties have been negotiated such as for the Rio Grande and Colorado Rivers. Thus, there is currently no binational coordination or treaty governing the management of groundwater.
During the 2004–2005 to 2015–2016 hunting seasons, the New Mexico Department of Game and Fish (NMDGF) estimated black bear abundance (Ursus americanus) across the state by coupling density estimates with the distribution of primary habitat generated by Costello et al. (2001). These estimates have been used to set harvest limits. For example, a density of 17 bears/100 km2 for the Sangre de Cristo and Sacramento Mountains and 13.2 bears/100 km2 for the Sandia Mountains were used to set harvest levels. The advancement and widespread acceptance of non-invasive sampling and mark-recapture methods, prompted the NMDGF to collaborate with the New Mexico Cooperative Fish and Wildlife Research Unit and New Mexico State University to update their density estimates for black bear populations in select mountain ranges across the state.
We established 5 study areas in 3 mountain ranges: the northern (NSC; sampled in 2012) and southern Sangre de Cristo Mountains (SSC; sampled in 2013), the Sandia Mountains (Sandias; sampled in 2014), and the northern (NSacs) and southern Sacramento Mountains (SSacs; both sampled in 2014). We collected hair samples from black bears using two concurrent non-invasive sampling methods, hair traps and bear rubs. We used a gender marker and a suite of microsatellite loci to determine the individual identification of hair samples that were suitable for genetic analysis. We used these data to generate mark-recapture encounter histories for each bear and estimated density in a spatially explicit capture-recapture framework (SECR). We constructed a suite of SECR candidate models using sex, elevation, land cover type, and time to model heterogeneity in detection probability and the spatial scale over which detection probability declines. We used Akaike’s Information Criterion corrected for small sample size (AICc) to rank and select the most supported model from which we estimated density.
We set 554 hair traps, 117 bear rubs and collected 4,083 hair samples. We identified 725 (367 M, 358 F) individuals; the sex ratio for each study area was approximately equal. Our density estimates varied within and among mountain ranges with an estimated density of 21.86 bears/100 km2 (95% CI: 17.83 – 26.80) for the NSC, 19.74 bears/100 km2 (95% CI: 13.77 – 28.30) in the SSC, 25.75 bears/100 km2 (95% CI: 13.22 – 50.14) in the Sandias, 21.86 bears/100 km2 (95% CI: 17.83 – 26.80) in the NSacs, and 16.55 bears/100 km2 (95% CI: 11.64 – 23.53) in the SSacs. Overall detection probability for hair traps and bear rubs, combined, was low across all study areas and ranged from 0.00001 to 0.02. We speculate that detection probabilities were affected by failure of some hair samples to produce a complete genotype due to UV degradation of DNA, and our inability to set and check some sampling devices due to wildfires in the SSC. Ultraviolet radiation levels are particularly high in New Mexico compared to other states where NGS methods have been used because New Mexico receives substantial amounts of sunshine, is relatively high in elevation (1,200 m – 4,000 m), and is at a lower latitude. Despite these sampling difficulties, we were able to produce density estimates for New Mexico black bear populations with levels of precision comparable to estimated black bear densities made elsewhere in the U.S.
Our ability to generate reliable black bear density estimates for 3 New Mexico mountain ranges is attributable to our use of a statistically robust study design and analytical method. There are multiple factors that need to be considered when developing future SECR-based density estimation projects. First, the spatial extent of the population of interest and the smallest average home range size must be determined; these will dictate size of the trapping array and spacing necessary between hair traps. The number of technicians needed and access to the study areas will also influence configuration of the trapping array. We believe shorter sampling occasions could be implemented to reduce degradation of DNA due to UV radiation; this might help increase amplification rates and thereby increase both the number of unique individuals identified and the number of recaptures, improving the precision of the density estimates. A pilot study may be useful to determine the length of time hair samples can remain in the field prior to collection. In addition, researchers may consider setting hair traps and bear rubs in more shaded areas (e.g., north facing slopes) to help reduce exposure to UV radiation. To reduce the sampling interval it will be necessary to either hire more field personnel or decrease the number of hair traps per sampling session. Both of these will enhance detection of long-range movement events by individual bears, increase initial capture and recapture rates, and improve precision of the parameter estimates. We recognize that all studies are constrained by limited resources, however, increasing field personnel would also allow a larger study area to be sampled or enable higher trap density.
In conclusion, we estimated the density of black bears in 5 study areas within 3 mountains ranges of New Mexico. Our estimates will aid the NMDGF in setting sustainable harvest limits. Along with estimates of density, information on additional demographic rates (e.g., survival rates and reproduction) and the potential effects that climate change and future land use may have on the demography of black bears may also help inform management of black bears in New Mexico, and may be considered as future areas for research.
","language":"English","publisher":"U.S. Fish and Wildlife Service","usgsCitation":"Gould, M.J., Cain, J.W., Roemer, G.W., and Gould, W., 2016, Estimating black bear density in New Mexico using noninvasive genetic sampling coupled with spatially explicit capture-recapture methods: Cooperator Science Series FWS/CSS-120-2016, ii, 41 p.","productDescription":"ii, 41 p.","numberOfPages":"43","ipdsId":"IP-074771","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":350702,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":350701,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://digitalmedia.fws.gov/cdm/ref/collection/document/id/2132"}],"country":"United States","state":"New Mexico","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a6c4c96e4b06e28e9cabb0a","contributors":{"authors":[{"text":"Gould, Matthew J.","contributorId":201504,"corporation":false,"usgs":false,"family":"Gould","given":"Matthew","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":725970,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cain, James W. III 0000-0003-4743-516X jwcain@usgs.gov","orcid":"https://orcid.org/0000-0003-4743-516X","contributorId":4063,"corporation":false,"usgs":true,"family":"Cain","given":"James","suffix":"III","email":"jwcain@usgs.gov","middleInitial":"W.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":713806,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Roemer, Gary W.","contributorId":95355,"corporation":false,"usgs":true,"family":"Roemer","given":"Gary","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":725971,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gould, William R.","contributorId":63780,"corporation":false,"usgs":true,"family":"Gould","given":"William R.","affiliations":[],"preferred":false,"id":725972,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70192558,"text":"70192558 - 2016 - Discontinuities concentrate mobile predators: Quantifying organism-environment interactions at a seascape scale","interactions":[],"lastModifiedDate":"2017-10-26T15:19:19","indexId":"70192558","displayToPublicDate":"2016-01-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Discontinuities concentrate mobile predators: Quantifying organism-environment interactions at a seascape scale","docAbstract":"Understanding environmental drivers of spatial patterns is an enduring ecological problem that is critical for effective biological conservation. Discontinuities (ecologically meaningful habitat breaks), both naturally occurring (e.g., river confluence, forest edge, drop-off) and anthropogenic (e.g., dams, roads), can influence the distribution of highly mobile organisms that have land- or seascape scale ranges. A geomorphic discontinuity framework, expanded to include ecological patterns, provides a way to incorporate important but irregularly distributed physical features into organism–environment relationships. Here, we test if migratory striped bass (Morone saxatilis) are consistently concentrated by spatial discontinuities and why. We quantified the distribution of 50 acoustically tagged striped bass at 40 sites within Plum Island Estuary, Massachusetts during four-monthly surveys relative to four physical discontinuities (sandbar, confluence, channel network, drop-off), one continuous physical feature (depth variation), and a geographic location variable (region). Despite moving throughout the estuary, striped bass were consistently clustered in the middle geographic region at sites with high sandbar area, close to channel networks, adjacent to complex confluences, with intermediate levels of bottom unevenness, and medium sized drop-offs. In addition, the highest striped bass concentrations occurred at sites with the greatest additive physical heterogeneity (i.e., where multiple discontinuities co-occurred). The need to incorporate irregularly distributed features in organism–environment relationships will increase as high-quality telemetry and GIS data accumulate for mobile organisms. The spatially explicit approach we used to address this challenge can aid both researchers who seek to understand the impact of predators on ecosystems and resource managers who require new approaches for biological conservation.
","language":"English","publisher":"ESA","doi":"10.1002/ecs2.1226","usgsCitation":"Kennedy, C., Mather, M.E., Smith, J.M., Finn, J.T., and Deegan, L.A., 2016, Discontinuities concentrate mobile predators: Quantifying organism-environment interactions at a seascape scale: Ecosphere, v. 7, no. 2, Article e01226; 17 p., https://doi.org/10.1002/ecs2.1226.","productDescription":"Article e01226; 17 p.","ipdsId":"IP-059506","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":471364,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.1226","text":"Publisher Index Page"},{"id":347507,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"7","issue":"2","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationDate":"2016-02-26","publicationStatus":"PW","scienceBaseUri":"5a07ea76e4b09af898c8cc8b","contributors":{"authors":[{"text":"Kennedy, Christina G.","contributorId":145646,"corporation":false,"usgs":false,"family":"Kennedy","given":"Christina G.","affiliations":[{"id":6932,"text":"University of Massachusetts, Amherst","active":true,"usgs":false}],"preferred":false,"id":716465,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mather, Martha E. 0000-0003-3027-0215 mather@usgs.gov","orcid":"https://orcid.org/0000-0003-3027-0215","contributorId":2580,"corporation":false,"usgs":true,"family":"Mather","given":"Martha","email":"mather@usgs.gov","middleInitial":"E.","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":716466,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Smith, Joseph M.","contributorId":106712,"corporation":false,"usgs":false,"family":"Smith","given":"Joseph","email":"","middleInitial":"M.","affiliations":[{"id":17855,"text":"School of Aquatic and Fishery Sciences, University of Washington, Seattle, WA","active":true,"usgs":false},{"id":6932,"text":"University of Massachusetts, Amherst","active":true,"usgs":false}],"preferred":false,"id":716469,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Finn, John T.","contributorId":43398,"corporation":false,"usgs":false,"family":"Finn","given":"John","email":"","middleInitial":"T.","affiliations":[{"id":16720,"text":"Department of Environmental Conservation, University of Massachusetts, Amherst, MA 01003-9485, USA","active":true,"usgs":false}],"preferred":false,"id":716492,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Deegan, Linda A.","contributorId":34094,"corporation":false,"usgs":false,"family":"Deegan","given":"Linda","email":"","middleInitial":"A.","affiliations":[{"id":27818,"text":"The Ecosystems Center, Marine Biological Laboratory. Woods Hole, MA 02543.","active":true,"usgs":false}],"preferred":false,"id":716493,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70191990,"text":"70191990 - 2016 - Evaluation and refinement of Guadalupe Bass conservation strategies to support adaptive management","interactions":[],"lastModifiedDate":"2018-01-25T13:23:19","indexId":"70191990","displayToPublicDate":"2016-01-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":5373,"text":"Cooperator Science Series","active":true,"publicationSubtype":{"id":1}},"seriesNumber":"FWS/CSS-118-2016","title":"Evaluation and refinement of Guadalupe Bass conservation strategies to support adaptive management","docAbstract":"Burbot Lota lota is the sole freshwater representative of the cod-like fishes and supports subsistence, commercial, and recreational fisheries worldwide above approximately 40° N. It is a difficult species to manage effectively due to its preference for deep-water habitats and spawning activity under the ice in winter. Like other gadiform fishes, Burbot use acoustic signaling as part of their mating system, and while the acoustic repertoire of the species has been characterized under artificial conditions (i.e., net pen suspended under ice in a natural lake), there has been no work to determine whether the species is as vocal in natural spawning aggregations. Our objective was to assess the feasibility of collecting and using acoustic data to characterize the spawning activity and locations of Burbot under field conditions. We recorded audio and video of Burbot spawning aggregations through holes drilled into the ice at known spawning grounds at Moyie Lake in British Columbia, Canada. Acoustic recordings (call counts and audiograms) were analyzed using Raven Pro v 1. 4 software. Acoustic behavior was also related to video data to determine how acoustic activity correlated to any observed spawning behavior. In general, wild Burbot spawning in Moyie Lake did not vocalize as frequently as counterparts spawning under artificial conditions. Further, Burbot vocalizations were not recorded in conjunction with spawning activity. While it may be feasible to use passive acoustic monitoring to locate Burbot spawning grounds and identify periods of activity, it does not seem to hold much promise for locating and quantifying spawning activity in real time.
","language":"English","publisher":"U.S. Fish and Wildlife Service","usgsCitation":"Grabowski, T.B., 2016, Evaluation and refinement of Guadalupe Bass conservation strategies to support adaptive management: Cooperator Science Series FWS/CSS-118-2016, ii, 34 p.","productDescription":"ii, 34 p.","numberOfPages":"36","ipdsId":"IP-061759","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":350616,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":350615,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://digitalmedia.fws.gov/cdm/ref/collection/document/id/2126"}],"publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a6afac7e4b06e28e9c9a90c","contributors":{"authors":[{"text":"Grabowski, Timothy B. 0000-0001-9763-8948 tgrabowski@usgs.gov","orcid":"https://orcid.org/0000-0001-9763-8948","contributorId":4178,"corporation":false,"usgs":true,"family":"Grabowski","given":"Timothy","email":"tgrabowski@usgs.gov","middleInitial":"B.","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":713817,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70187721,"text":"70187721 - 2016 - An evaluation of behavior inferences from Bayesian state-space models: A case study with the Pacific walrus","interactions":[],"lastModifiedDate":"2018-06-16T17:49:28","indexId":"70187721","displayToPublicDate":"2016-01-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2671,"text":"Marine Mammal Science","active":true,"publicationSubtype":{"id":10}},"title":"An evaluation of behavior inferences from Bayesian state-space models: A case study with the Pacific walrus","docAbstract":"State-space models offer researchers an objective approach to modeling complex animal location data sets, and state-space model behavior classifications are often assumed to have a link to animal behavior. In this study, we evaluated the behavioral classification accuracy of a Bayesian state-space model in Pacific walruses using Argos satellite tags with sensors to detect animal behavior in real time. We fit a two-state discrete-time continuous-space Bayesian state-space model to data from 306 Pacific walruses tagged in the Chukchi Sea. We matched predicted locations and behaviors from the state-space model (resident, transient behavior) to true animal behavior (foraging, swimming, hauled out) and evaluated classification accuracy with kappa statistics (κ) and root mean square error (RMSE). In addition, we compared biased random bridge utilization distributions generated with resident behavior locations to true foraging behavior locations to evaluate differences in space use patterns. Results indicated that the two-state model fairly classified true animal behavior (0.06 ≤ κ ≤ 0.26, 0.49 ≤ RMSE ≤ 0.59). Kernel overlap metrics indicated utilization distributions generated with resident behavior locations were generally smaller than utilization distributions generated with true foraging behavior locations. Consequently, we encourage researchers to carefully examine parameters and priors associated with behaviors in state-space models, and reconcile these parameters with the study species and its expected behaviors.
","language":"English","publisher":"Wiley","doi":"10.1111/mms.12332","usgsCitation":"Beatty, W.S., Jay, C.V., and Fischbach, A.S., 2016, An evaluation of behavior inferences from Bayesian state-space models: A case study with the Pacific walrus: Marine Mammal Science, v. 32, no. 4, p. 1299-1318, https://doi.org/10.1111/mms.12332.","productDescription":"20 p.","startPage":"1299","endPage":"1318","ipdsId":"IP-069772","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":438647,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F77M060G","text":"USGS data release","linkHelpText":"Walrus Bayesian State-space Model Output from the Bering Sea and Chukchi Sea, 2008-2012"},{"id":341325,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"32","issue":"4","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2016-07-11","publicationStatus":"PW","scienceBaseUri":"591abe36e4b0a7fdb43c8bf5","contributors":{"authors":[{"text":"Beatty, William S. 0000-0003-0013-3113 wbeatty@usgs.gov","orcid":"https://orcid.org/0000-0003-0013-3113","contributorId":173946,"corporation":false,"usgs":true,"family":"Beatty","given":"William","email":"wbeatty@usgs.gov","middleInitial":"S.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":695273,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jay, Chadwick V. 0000-0002-9559-2189 cjay@usgs.gov","orcid":"https://orcid.org/0000-0002-9559-2189","contributorId":192736,"corporation":false,"usgs":true,"family":"Jay","given":"Chadwick","email":"cjay@usgs.gov","middleInitial":"V.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":695274,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fischbach, Anthony S. 0000-0002-6555-865X afischbach@usgs.gov","orcid":"https://orcid.org/0000-0002-6555-865X","contributorId":2865,"corporation":false,"usgs":true,"family":"Fischbach","given":"Anthony","email":"afischbach@usgs.gov","middleInitial":"S.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":695275,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70192004,"text":"70192004 - 2016 - Assessing the feasibility of using acoustic monitoring for Burbot conservation, management, and production","interactions":[],"lastModifiedDate":"2018-01-25T13:20:20","indexId":"70192004","displayToPublicDate":"2016-01-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":5373,"text":"Cooperator Science Series","active":true,"publicationSubtype":{"id":1}},"seriesNumber":" FWS/CSS-118-2016","title":"Assessing the feasibility of using acoustic monitoring for Burbot conservation, management, and production","docAbstract":"Burbot Lota lota is the sole freshwater representative of the cod-like fishes and supports subsistence, commercial, and recreational fisheries worldwide above approximately 40° N. It is a difficult species to manage effectively due to its preference for deep-water habitats and spawning activity under the ice in winter. Like other gadiform fishes, Burbot use acoustic signaling as part of their mating system, and while the acoustic repertoire of the species has been characterized under artificial conditions (i.e., net pen suspended under ice in a natural lake), there has been no work to determine whether the species is as vocal in natural spawning aggregations. Our objective was to assess the feasibility of collecting and using acoustic data to characterize the spawning activity and locations of Burbot under field conditions. We recorded audio and video of Burbot spawning aggregations through holes drilled into the ice at known spawning grounds at Moyie Lake in British Columbia, Canada. Acoustic recordings (call counts and audiograms) were analyzed using Raven Pro v 1. 4 software. Acoustic behavior was also related to video data to determine how acoustic activity correlated to any observed spawning behavior. In general, wild Burbot spawning in Moyie Lake did not vocalize as frequently as counterparts spawning under artificial conditions. Further, Burbot vocalizations were not recorded in conjunction with spawning activity. While it may be feasible to use passive acoustic monitoring to locate Burbot spawning grounds and identify periods of activity, it does not seem to hold much promise for locating and quantifying spawning activity in real time.
","language":"English","publisher":"U.S. Fish and Wildlife Service","doi":"10.13140/RG.2.1.4581.2881","usgsCitation":"Grabowski, T.B., 2016, Assessing the feasibility of using acoustic monitoring for Burbot conservation, management, and production: Cooperator Science Series FWS/CSS-118-2016, ii, 34 p., https://doi.org/10.13140/RG.2.1.4581.2881.","productDescription":"ii, 34 p.","numberOfPages":"36","ipdsId":"IP-072721","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":350614,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":350613,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://digitalmedia.fws.gov/cdm/ref/collection/document/id/2126"}],"publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a6afac6e4b06e28e9c9a901","contributors":{"authors":[{"text":"Grabowski, Timothy B. 0000-0001-9763-8948 tgrabowski@usgs.gov","orcid":"https://orcid.org/0000-0001-9763-8948","contributorId":4178,"corporation":false,"usgs":true,"family":"Grabowski","given":"Timothy","email":"tgrabowski@usgs.gov","middleInitial":"B.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":713831,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70192005,"text":"70192005 - 2016 - Prioritizing landscapes for longleaf pine conservation","interactions":[],"lastModifiedDate":"2018-01-25T13:33:39","indexId":"70192005","displayToPublicDate":"2016-01-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":5373,"text":"Cooperator Science Series","active":true,"publicationSubtype":{"id":1}},"seriesNumber":"FWS/CSS-119-2016","title":"Prioritizing landscapes for longleaf pine conservation","docAbstract":"We developed a spatially explicit model and map, as a decision support tool (DST), to aid conservation agencies creating or maintaining open pine ecosystems. The tool identified areas that are likely to provide the greatest benefit to focal bird populations based on a comprehensive landscape analysis. We used NLCD 2011, SSURGO, and SEGAP data to map the density of desired resources for open pine ecosystems and six focal species of birds and 2 reptiles within the historic range of longleaf pine east of the Mississippi River. Binary rasters were created of sites with desired characteristics such as land form, hydrology, land use and land cover, soils, potential habitat for focal species, and putative source populations of focal species. Each raster was smoothed using a kernel density estimator. Rasters were combined and scaled to map priority locations for the management of each focal species. Species’ rasters were combined and scaled to provide maps of overall priority for birds and for birds and reptiles. The spatial data can be used to identify high priority areas for conservation or to compare areas under consideration for maintenance or creation of open pine ecosystems.
","language":"English","publisher":"U.S. Fish and Wildlife Service","usgsCitation":"Grand, J.B., and Kleiner, K.J., 2016, Prioritizing landscapes for longleaf pine conservation: Cooperator Science Series FWS/CSS-119-2016, ii, 50 p.","productDescription":"ii, 50 p.","numberOfPages":"52","ipdsId":"IP-071312","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":350618,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":350617,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://digitalmedia.fws.gov/cdm/ref/collection/document/id/2131"}],"publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a6afac6e4b06e28e9c9a8ff","contributors":{"authors":[{"text":"Grand, J. Barry 0000-0002-3576-4567 barry_grand@usgs.gov","orcid":"https://orcid.org/0000-0002-3576-4567","contributorId":579,"corporation":false,"usgs":true,"family":"Grand","given":"J.","email":"barry_grand@usgs.gov","middleInitial":"Barry","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":713832,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kleiner, Kevin J.","contributorId":200004,"corporation":false,"usgs":false,"family":"Kleiner","given":"Kevin","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":725822,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70192009,"text":"70192009 - 2016 - Assessing the potential for rainbow trout reproduction in tributaries of the Mountain Fork River below Broken Bow Dam, southeastern Oklahoma","interactions":[],"lastModifiedDate":"2018-01-25T14:52:57","indexId":"70192009","displayToPublicDate":"2016-01-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":5603,"text":"e-Research Paper","active":true,"publicationSubtype":{"id":1}},"seriesNumber":"SRS–58","title":"Assessing the potential for rainbow trout reproduction in tributaries of the Mountain Fork River below Broken Bow Dam, southeastern Oklahoma","docAbstract":"Stocked trout (Salmonidae) in reservoir tailwater systems in the Southern United States have been shown to use tributary streams for spawning and rearing. The lower Mountain Fork of the Little River below Broken Bow Dam is one of two year-round tailwater trout fisheries in Oklahoma, and the only one with evidence of reproduction by stocked rainbow trout (Oncorhynchus mykiss). Whether stocked trout use tributaries in this system for spawning is unknown. Furthermore, an\ninventory of the resident fish communities in these tributaries is lacking. To address these gaps, we surveyed 10 tributaries, from intermittent through third order, for fishes during presumed spawning periods of rainbow trout; we used backpack electrofishing in February and April 2015 and 2016 to determine the composition of the fish assemblages and whether trout were present. Stocked adult trout were found in three tributaries in 2015; wild juvenile rainbow trout were found in Bee Branch in 2015 and in an intermittent tributary of Spillway Creek, just above the “Cold Hole,” in 2016. Fish assemblages were dominated by highland stonerollers (Campostoma spadiceum) in larger, wider systems and by orangebelly darters (Etheostoma radiosum) in smaller, narrower streams. These data fill an information gap in our understanding of small streams in the Ouachita Mountains, and they demonstrate that some streams are suitable for rainbow trout reproduction.","language":"English","publisher":"U.S. Department of Agriculture","usgsCitation":"Long, J.M., Starks, T.A., Farling, T., and Bastarache, R., 2016, Assessing the potential for rainbow trout reproduction in tributaries of the Mountain Fork River below Broken Bow Dam, southeastern Oklahoma: e-Research Paper SRS–58, 11 p.","productDescription":"11 p.","ipdsId":"IP-077629","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":350628,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":350627,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://www.srs.fs.usda.gov/pubs/rp/rp_srs058.pdf"}],"country":"United States","state":"Oklahoma","otherGeospatial":"Mountain Fork River","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a6afac5e4b06e28e9c9a8fa","contributors":{"authors":[{"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":713836,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Starks, Trevor A.","contributorId":145640,"corporation":false,"usgs":false,"family":"Starks","given":"Trevor","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":725831,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Farling, Tyler","contributorId":201482,"corporation":false,"usgs":false,"family":"Farling","given":"Tyler","email":"","affiliations":[],"preferred":false,"id":725832,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bastarache, Robert","contributorId":145764,"corporation":false,"usgs":false,"family":"Bastarache","given":"Robert","email":"","affiliations":[],"preferred":false,"id":725833,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70191228,"text":"70191228 - 2016 - High performance computing to support multiscale representation of hydrography for the conterminous United States","interactions":[],"lastModifiedDate":"2017-10-04T08:41:29","indexId":"70191228","displayToPublicDate":"2016-01-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"High performance computing to support multiscale representation of hydrography for the conterminous United States","docAbstract":"The National Hydrography Dataset (NHD) for the United States furnishes a comprehensive set of vector features representing the surface-waters in the country (U.S. Geological Survey 2000). The high-resolution (HR) layer of the NHD is largely comprised of hydrographic features originally derived from 1:24,000-scale (24K) U.S. Topographic maps. However, in recent years (2009 to present) densified hydrographic feature content, from sources as large as 1:2,400, have been incorporated into some watersheds of the HR NHD within the conterminous United States to better support the needs of various local and state organizations. As such, the HR NHD is a multiresolution dataset with obvious data density variations because of scale changes. In addition, data density variations exist within the HR NHD that are particularly evident in the surface-water flow network (NHD flowlines) because of natural variations of local geographic conditions; and also because of unintentional compilation inconsistencies due to variations in data collection standards and climate conditions over the many years of 24K hydrographic data collection (US Geological Survey 1955).
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"19th ICA Workshop, Automated Generalisation for On-Demand Mapping","largerWorkSubtype":{"id":12,"text":"Conference publication"},"language":"English","publisher":"International Cartographic Association Commission on Generlisation and Multiple Representation","usgsCitation":"Stanislawski, L.V., Liu, Y., Buttenfield, B., Survila, K., Wendel, J., and Okok, A., 2016, High performance computing to support multiscale representation of hydrography for the conterminous United States, in 19th ICA Workshop, Automated Generalisation for On-Demand Mapping, 10 p.","productDescription":"10 p.","ipdsId":"IP-076465","costCenters":[{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"links":[{"id":346350,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":346295,"type":{"id":15,"text":"Index Page"},"url":"https://generalisation.icaci.org/prevevents/95-workshop2016program.html"}],"publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59d4a1abe4b05fe04cc4e10a","contributors":{"authors":[{"text":"Stanislawski, Larry V. 0000-0002-9437-0576 lstan@usgs.gov","orcid":"https://orcid.org/0000-0002-9437-0576","contributorId":3386,"corporation":false,"usgs":true,"family":"Stanislawski","given":"Larry","email":"lstan@usgs.gov","middleInitial":"V.","affiliations":[{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true},{"id":404,"text":"NGTOC Rolla","active":true,"usgs":true}],"preferred":true,"id":711622,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Liu, Yan 0000-0003-2298-4728","orcid":"https://orcid.org/0000-0003-2298-4728","contributorId":196790,"corporation":false,"usgs":false,"family":"Liu","given":"Yan","email":"","affiliations":[],"preferred":false,"id":711623,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Buttenfield, Barbara P.","contributorId":145538,"corporation":false,"usgs":false,"family":"Buttenfield","given":"Barbara P.","affiliations":[{"id":16144,"text":"University of Colorado-Boulder","active":true,"usgs":false}],"preferred":false,"id":711624,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Survila, Kornelijus 0000-0003-4851-6084","orcid":"https://orcid.org/0000-0003-4851-6084","contributorId":196791,"corporation":false,"usgs":false,"family":"Survila","given":"Kornelijus","email":"","affiliations":[],"preferred":false,"id":711625,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wendel, Jeffrey 0000-0003-0294-0250 jwendel@usgs.gov","orcid":"https://orcid.org/0000-0003-0294-0250","contributorId":196792,"corporation":false,"usgs":true,"family":"Wendel","given":"Jeffrey","email":"jwendel@usgs.gov","affiliations":[{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"preferred":true,"id":711626,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Okok, Abdurraouf","contributorId":196793,"corporation":false,"usgs":false,"family":"Okok","given":"Abdurraouf","email":"","affiliations":[],"preferred":false,"id":711627,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70192836,"text":"70192836 - 2016 - Site effects in Port-au-Prince (Haiti) from the analysis of spectral ratio and numerical simulations.","interactions":[],"lastModifiedDate":"2017-10-30T16:11:14","indexId":"70192836","displayToPublicDate":"2016-01-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"Site effects in Port-au-Prince (Haiti) from the analysis of spectral ratio and numerical simulations.","docAbstract":"To provide better insight into seismic ground motion in the Port‐au‐Prince metropolitan area, we investigate site effects at 12 seismological stations by analyzing 78 earthquakes with magnitude smaller than 5 that occurred between 2010 and 2013. Horizontal‐to‐vertical spectral ratio on earthquake recordings and a standard spectral ratio were applied to the seismic data. We also propose a simplified lithostratigraphic map and use available geotechnical and geophysical data to construct representative soil columns in the vicinity of each station that allow us to compute numerical transfer functions using 1D simulations. At most of the studied sites, spectral ratios are characterized by weak‐motion amplification at frequencies above 5 Hz, in good agreement with the numerical transfer functions. A mismatch between the observed amplifications and simulated response at lower frequencies shows that the considered soil columns could be missing a deeper velocity contrast. Furthermore, strong amplification between 2 and 10 Hz linked to local topographic features is found at one station located in the south of the city, and substantial amplification below 5 Hz is detected near the coastline, which we attribute to deep and soft sediments as well as the presence of surface waves. We conclude that for most investigated sites in Port‐au‐Prince, seismic amplifications due to site effects are highly variable but seem not to be important at high frequencies. At some specific locations, however, they could strongly enhance the low‐frequency content of the seismic ground shaking. Although our analysis does not consider nonlinear effects, we thus conclude that, apart from sites close to the coast, sediment‐induced amplification probably had only a minor impact on the level of strong ground motion, and was not the main reason for the high level of damage in Port‐au‐Prince.
","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120150238","usgsCitation":"St. Fleur, S., Bertrand, E., Courboulex, F., Mercier de Lepinay, B., Deschamps, A., Hough, S.E., Cultrera, G., Boisson, D., and Prepetit, C., 2016, Site effects in Port-au-Prince (Haiti) from the analysis of spectral ratio and numerical simulations.: Bulletin of the Seismological Society of America, v. 106, no. 3, p. 1298-1315, https://doi.org/10.1785/0120150238.","productDescription":"18 p.","startPage":"1298","endPage":"1315","ipdsId":"IP-073232","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":347747,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Haiti","city":"Port-au-Prince","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -73,\n 18.127580917219024\n ],\n [\n -72,\n 18.127580917219024\n ],\n [\n -72,\n 18.80751806940863\n ],\n [\n -73,\n 18.80751806940863\n ],\n [\n -73,\n 18.127580917219024\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"106","issue":"3","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-05-24","publicationStatus":"PW","scienceBaseUri":"59f83a3de4b063d5d3098111","contributors":{"authors":[{"text":"St. Fleur, Sadrac","contributorId":198793,"corporation":false,"usgs":false,"family":"St. Fleur","given":"Sadrac","email":"","affiliations":[],"preferred":false,"id":717135,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bertrand, Etienne","contributorId":198794,"corporation":false,"usgs":false,"family":"Bertrand","given":"Etienne","email":"","affiliations":[],"preferred":false,"id":717136,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Courboulex, Francoise","contributorId":198795,"corporation":false,"usgs":false,"family":"Courboulex","given":"Francoise","email":"","affiliations":[],"preferred":false,"id":717137,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mercier de Lepinay, Bernard","contributorId":10322,"corporation":false,"usgs":true,"family":"Mercier de Lepinay","given":"Bernard","email":"","affiliations":[],"preferred":false,"id":717138,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Deschamps, Anne","contributorId":24269,"corporation":false,"usgs":true,"family":"Deschamps","given":"Anne","email":"","affiliations":[],"preferred":false,"id":717139,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hough, Susan E. 0000-0002-5980-2986 hough@usgs.gov","orcid":"https://orcid.org/0000-0002-5980-2986","contributorId":587,"corporation":false,"usgs":true,"family":"Hough","given":"Susan","email":"hough@usgs.gov","middleInitial":"E.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":717134,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Cultrera, Giovanna","contributorId":198798,"corporation":false,"usgs":false,"family":"Cultrera","given":"Giovanna","email":"","affiliations":[],"preferred":false,"id":717140,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Boisson, Dominique","contributorId":198799,"corporation":false,"usgs":false,"family":"Boisson","given":"Dominique","email":"","affiliations":[],"preferred":false,"id":717141,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Prepetit, Claude","contributorId":198800,"corporation":false,"usgs":false,"family":"Prepetit","given":"Claude","email":"","affiliations":[],"preferred":false,"id":717142,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70192861,"text":"70192861 - 2016 - Field and laboratory determination of water-surface elevation and velocity using noncontact measurements","interactions":[],"lastModifiedDate":"2018-02-15T10:56:55","indexId":"70192861","displayToPublicDate":"2016-01-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Field and laboratory determination of water-surface elevation and velocity using noncontact measurements","docAbstract":"Noncontact methods for measuring water-surface elevation and velocity in laboratory flumes and rivers are presented with examples. Water-surface elevations are measured using an array of acoustic transducers in the laboratory and using laser scanning in field situations. Water-surface velocities are based on using particle image velocimetry or other machine vision techniques on infrared video of the water surface. Using spatial and temporal averaging, results from these methods provide information \nthat can be used to develop estimates of discharge for flows over known bathymetry. Making such estimates requires relating water-surface velocities to vertically averaged velocities; the methods here use standard relations. To examine where these relations break down, laboratory data for flows over simple bumps of three amplitudes are evaluated. As anticipated, discharges determined from surface information can have large errors where nonhydrostatic effects are large. In addition to investigating and characterizing this potential error in estimating discharge, a simple method for correction of the issue is presented. With a simple correction based on bed gradient along the flow direction, remotely sensed estimates of discharge appear to be viable.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of the 20th Congress of the Asia Pacific Division of the International Association for Hydro Environment Engineering & Research","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"20th Congress of the Asia Pacific Division of the International Association for Hydro Environment Engineering & Research","conferenceDate":"August 28-31, 2016","conferenceLocation":"Colombo, Sri Lanka","language":"English","publisher":"International Association of Hydraulic Research","usgsCitation":"Nelson, J.M., Kinzel, P.J., Schmeeckle, M.W., McDonald, R.R., and Minear, J., 2016, Field and laboratory determination of water-surface elevation and velocity using noncontact measurements, in Proceedings of the 20th Congress of the Asia Pacific Division of the International Association for Hydro Environment Engineering & Research, Colombo, Sri Lanka, August 28-31, 2016.","ipdsId":"IP-073816","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":351651,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afeea4ce4b0da30c1bfc5e5","contributors":{"authors":[{"text":"Nelson, Jonathan M. 0000-0002-7632-8526 jmn@usgs.gov","orcid":"https://orcid.org/0000-0002-7632-8526","contributorId":2812,"corporation":false,"usgs":true,"family":"Nelson","given":"Jonathan","email":"jmn@usgs.gov","middleInitial":"M.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":717235,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kinzel, Paul J. 0000-0002-6076-9730 pjkinzel@usgs.gov","orcid":"https://orcid.org/0000-0002-6076-9730","contributorId":743,"corporation":false,"usgs":true,"family":"Kinzel","given":"Paul","email":"pjkinzel@usgs.gov","middleInitial":"J.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":717236,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schmeeckle, Mark Walter","contributorId":195264,"corporation":false,"usgs":false,"family":"Schmeeckle","given":"Mark","email":"","middleInitial":"Walter","affiliations":[],"preferred":false,"id":717237,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McDonald, Richard R. 0000-0002-0703-0638 rmcd@usgs.gov","orcid":"https://orcid.org/0000-0002-0703-0638","contributorId":2428,"corporation":false,"usgs":true,"family":"McDonald","given":"Richard","email":"rmcd@usgs.gov","middleInitial":"R.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":717238,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Minear, Justin T.","contributorId":198828,"corporation":false,"usgs":false,"family":"Minear","given":"Justin T.","affiliations":[],"preferred":false,"id":717239,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70185995,"text":"70185995 - 2016 - A review of single-sample-based models and other approaches for radiocarbon dating of dissolved inorganic carbon in groundwater","interactions":[],"lastModifiedDate":"2017-03-30T11:21:50","indexId":"70185995","displayToPublicDate":"2016-01-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1431,"text":"Earth-Science Reviews","active":true,"publicationSubtype":{"id":10}},"title":"A review of single-sample-based models and other approaches for radiocarbon dating of dissolved inorganic carbon in groundwater","docAbstract":"Numerous methods have been proposed to estimate the pre-nuclear-detonation 14C content of dissolved inorganic carbon (DIC) recharged to groundwater that has been corrected/adjusted for geochemical processes in the absence of radioactive decay (14C0) - a quantity that is essential for estimation of radiocarbon age of DIC in groundwater. The models/approaches most commonly used are grouped as follows: (1) single-sample-based models, (2) a statistical approach based on the observed (curved) relationship between 14C and δ13C data for the aquifer, and (3) the geochemical mass-balance approach that constructs adjustment models accounting for all the geochemical reactions known to occur along a groundwater flow path. This review discusses first the geochemical processes behind each of the single-sample-based models, followed by discussions of the statistical approach and the geochemical mass-balance approach. Finally, the applications, advantages and limitations of the three groups of models/approaches are discussed.
The single-sample-based models constitute the prevailing use of 14C data in hydrogeology and hydrological studies. This is in part because the models are applied to an individual water sample to estimate the 14C age, therefore the measurement data are easily available. These models have been shown to provide realistic radiocarbon ages in many studies. However, they usually are limited to simple carbonate aquifers and selection of model may have significant effects on 14C0 often resulting in a wide range of estimates of 14C ages.
Of the single-sample-based models, four are recommended for the estimation of 14C0 of DIC in groundwater: Pearson's model, (Ingerson and Pearson, 1964; Pearson and White, 1967), Han & Plummer's model (Han and Plummer, 2013), the IAEA model (Gonfiantini, 1972; Salem et al., 1980), and Oeschger's model (Geyh, 2000). These four models include all processes considered in single-sample-based models, and can be used in different ranges of 13C values.
In contrast to the single-sample-based models, the extended Gonfiantini & Zuppi model (Gonfiantini and Zuppi, 2003; Han et al., 2014) is a statistical approach. This approach can be used to estimate 14C ages when a curved relationship between the 14C and 13C values of the DIC data is observed. In addition to estimation of groundwater ages, the relationship between 14C and δ13C data can be used to interpret hydrogeological characteristics of the aquifer, e.g. estimating apparent rates of geochemical reactions and revealing the complexity of the geochemical environment, and identify samples that are not affected by the same set of reactions/processes as the rest of the dataset. The investigated water samples may have a wide range of ages, and for waters with very low values of 14C, the model based on statistics may give more reliable age estimates than those obtained from single-sample-based models. In the extended Gonfiantini & Zuppi model, a representative system-wide value of the initial 14C content is derived from the 14C and δ13C data of DIC and can differ from that used in single-sample-based models. Therefore, the extended Gonfiantini & Zuppi model usually avoids the effect of modern water components which might retain ‘bomb’ pulse signatures.
The geochemical mass-balance approach constructs an adjustment model that accounts for all the geochemical reactions known to occur along an aquifer flow path (Plummer et al., 1983; Wigley et al., 1978; Plummer et al., 1994; Plummer and Glynn, 2013), and includes, in addition to DIC, dissolved organic carbon (DOC) and methane (CH4). If sufficient chemical, mineralogical and isotopic data are available, the geochemical mass-balance method can yield the most accurate estimates of the adjusted radiocarbon age. The main limitation of this approach is that complete information is necessary on chemical, mineralogical and isotopic data and these data are often limited.
Failure to recognize the limitations and underlying assumptions on which the various models and approaches are based can result in a wide range of estimates of 14C0 and limit the usefulness of radiocarbon as a dating tool for groundwater. In each of the three generalized approaches (single-sample-based models, statistical approach, and geochemical mass-balance approach), successful application depends on scrutiny of the isotopic (14C and 13C) and chemical data to conceptualize the reactions and processes that affect the 14C content of DIC in aquifers. The recently developed graphical analysis method is shown to aid in determining which approach is most appropriate for the isotopic and chemical data from a groundwater system.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.earscirev.2015.11.004","usgsCitation":"Han, L.F., and Plummer, N., 2016, A review of single-sample-based models and other approaches for radiocarbon dating of dissolved inorganic carbon in groundwater: Earth-Science Reviews, v. 152, p. 119-142, https://doi.org/10.1016/j.earscirev.2015.11.004.","productDescription":"24 p.","startPage":"119","endPage":"142","ipdsId":"IP-068009","costCenters":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"links":[{"id":338803,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"152","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58de194fe4b02ff32c699ca7","contributors":{"authors":[{"text":"Han, L. F","contributorId":190101,"corporation":false,"usgs":false,"family":"Han","given":"L.","email":"","middleInitial":"F","affiliations":[],"preferred":false,"id":687282,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Plummer, Niel 0000-0002-4020-1013 nplummer@usgs.gov","orcid":"https://orcid.org/0000-0002-4020-1013","contributorId":190100,"corporation":false,"usgs":true,"family":"Plummer","given":"Niel","email":"nplummer@usgs.gov","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":687281,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70189206,"text":"70189206 - 2016 - Implications of the methodological choices for hydrologic portrayals of climate change over the contiguous United States: Statistically downscaled forcing data and hydrologic models","interactions":[],"lastModifiedDate":"2017-07-05T16:25:03","indexId":"70189206","displayToPublicDate":"2016-01-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2344,"text":"Journal of Hydrometeorology","active":true,"publicationSubtype":{"id":10}},"title":"Implications of the methodological choices for hydrologic portrayals of climate change over the contiguous United States: Statistically downscaled forcing data and hydrologic models","docAbstract":"Continental-domain assessments of climate change impacts on water resources typically rely on statistically downscaled climate model outputs to force hydrologic models at a finer spatial resolution. This study examines the effects of four statistical downscaling methods [bias-corrected constructed analog (BCCA), bias-corrected spatial disaggregation applied at daily (BCSDd) and monthly scales (BCSDm), and asynchronous regression (AR)] on retrospective hydrologic simulations using three hydrologic models with their default parameters (the Community Land Model, version 4.0; the Variable Infiltration Capacity model, version 4.1.2; and the Precipitation–Runoff Modeling System, version 3.0.4) over the contiguous United States (CONUS). Biases of hydrologic simulations forced by statistically downscaled climate data relative to the simulation with observation-based gridded data are presented. Each statistical downscaling method produces different meteorological portrayals including precipitation amount, wet-day frequency, and the energy input (i.e., shortwave radiation), and their interplay affects estimations of precipitation partitioning between evapotranspiration and runoff, extreme runoff, and hydrologic states (i.e., snow and soil moisture). The analyses show that BCCA underestimates annual precipitation by as much as −250 mm, leading to unreasonable hydrologic portrayals over the CONUS for all models. Although the other three statistical downscaling methods produce a comparable precipitation bias ranging from −10 to 8 mm across the CONUS, BCSDd severely overestimates the wet-day fraction by up to 0.25, leading to different precipitation partitioning compared to the simulations with other downscaled data. Overall, the choice of downscaling method contributes to less spread in runoff estimates (by a factor of 1.5–3) than the choice of hydrologic model with use of the default parameters if BCCA is excluded.
","language":"English","publisher":"American Meteorological Society","doi":"10.1175/JHM-D-14-0187.1","usgsCitation":"Mizukami, N., Clark, M.P., Gutmann, E.D., Mendoza, P.A., Newman, A.J., Nijssen, B., Livneh, B., Hay, L.E., Arnold, J.R., and Brekke, L.D., 2016, Implications of the methodological choices for hydrologic portrayals of climate change over the contiguous United States: Statistically downscaled forcing data and hydrologic models: Journal of Hydrometeorology, v. 17, p. 75-98, https://doi.org/10.1175/JHM-D-14-0187.1.","productDescription":"24 p.","startPage":"75","endPage":"98","ipdsId":"IP-064865","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":471387,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1175/jhm-d-14-0187.1","text":"Publisher Index Page"},{"id":343367,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"17","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2015-12-17","publicationStatus":"PW","scienceBaseUri":"595dfab0e4b0d1f9f056a763","contributors":{"authors":[{"text":"Mizukami, Naoki","contributorId":178120,"corporation":false,"usgs":false,"family":"Mizukami","given":"Naoki","email":"","affiliations":[],"preferred":false,"id":703484,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Clark, Martyn P.","contributorId":194183,"corporation":false,"usgs":false,"family":"Clark","given":"Martyn","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":703485,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gutmann, Ethan D.","contributorId":194227,"corporation":false,"usgs":false,"family":"Gutmann","given":"Ethan","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":703486,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mendoza, Pablo A.","contributorId":194228,"corporation":false,"usgs":false,"family":"Mendoza","given":"Pablo","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":703487,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Newman, Andrew J.","contributorId":194229,"corporation":false,"usgs":false,"family":"Newman","given":"Andrew","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":703488,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Nijssen, Bart","contributorId":178123,"corporation":false,"usgs":false,"family":"Nijssen","given":"Bart","email":"","affiliations":[],"preferred":false,"id":703490,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Livneh, Ben","contributorId":145804,"corporation":false,"usgs":false,"family":"Livneh","given":"Ben","email":"","affiliations":[{"id":12641,"text":"NOAA NMFS","active":true,"usgs":false}],"preferred":false,"id":703491,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Hay, Lauren E. 0000-0003-3763-4595 lhay@usgs.gov","orcid":"https://orcid.org/0000-0003-3763-4595","contributorId":1287,"corporation":false,"usgs":true,"family":"Hay","given":"Lauren","email":"lhay@usgs.gov","middleInitial":"E.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":703502,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Arnold, Jeffrey R.","contributorId":178125,"corporation":false,"usgs":false,"family":"Arnold","given":"Jeffrey","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":703492,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Brekke, Levi D.","contributorId":6776,"corporation":false,"usgs":true,"family":"Brekke","given":"Levi","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":703493,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70187148,"text":"70187148 - 2016 - An evaluation of methods for estimating decadal stream loads","interactions":[],"lastModifiedDate":"2018-03-15T10:26:32","indexId":"70187148","displayToPublicDate":"2016-01-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2342,"text":"Journal of Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"An evaluation of methods for estimating decadal stream loads","docAbstract":"Effective management of water resources requires accurate information on the mass, or load of water-quality constituents transported from upstream watersheds to downstream receiving waters. Despite this need, no single method has been shown to consistently provide accurate load estimates among different water-quality constituents, sampling sites, and sampling regimes. We evaluate the accuracy of several load estimation methods across a broad range of sampling and environmental conditions. This analysis uses random sub-samples drawn from temporally-dense data sets of total nitrogen, total phosphorus, nitrate, and suspended-sediment concentration, and includes measurements of specific conductance which was used as a surrogate for dissolved solids concentration. Methods considered include linear interpolation and ratio estimators, regression-based methods historically employed by the U.S. Geological Survey, and newer flexible techniques including Weighted Regressions on Time, Season, and Discharge (WRTDS) and a generalized non-linear additive model. No single method is identified to have the greatest accuracy across all constituents, sites, and sampling scenarios. Most methods provide accurate estimates of specific conductance (used as a surrogate for total dissolved solids or specific major ions) and total nitrogen – lower accuracy is observed for the estimation of nitrate, total phosphorus and suspended sediment loads. Methods that allow for flexibility in the relation between concentration and flow conditions, specifically Beale’s ratio estimator and WRTDS, exhibit greater estimation accuracy and lower bias. Evaluation of methods across simulated sampling scenarios indicate that (1) high-flow sampling is necessary to produce accurate load estimates, (2) extrapolation of sample data through time or across more extreme flow conditions reduces load estimate accuracy, and (3) WRTDS and methods that use a Kalman filter or smoothing to correct for departures between individual modeled and observed values benefit most from more frequent water-quality sampling.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jhydrol.2016.08.059","usgsCitation":"Lee, C.J., Hirsch, R.M., Schwarz, G., Holtschlag, D.J., Preston, S.D., Crawford, C.G., and Vecchia, A.V., 2016, An evaluation of methods for estimating decadal stream loads: Journal of Hydrology, v. 542, p. 185-203, https://doi.org/10.1016/j.jhydrol.2016.08.059.","productDescription":"19 p.","startPage":"185","endPage":"203","ipdsId":"IP-070870","costCenters":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"links":[{"id":471371,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jhydrol.2016.08.059","text":"Publisher Index Page"},{"id":340405,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"542","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59006063e4b0e85db3a5ddd9","contributors":{"authors":[{"text":"Lee, Casey J. 0000-0002-5753-2038 cjlee@usgs.gov","orcid":"https://orcid.org/0000-0002-5753-2038","contributorId":2627,"corporation":false,"usgs":true,"family":"Lee","given":"Casey","email":"cjlee@usgs.gov","middleInitial":"J.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true},{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true}],"preferred":true,"id":692771,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hirsch, Robert M. 0000-0002-4534-075X rhirsch@usgs.gov","orcid":"https://orcid.org/0000-0002-4534-075X","contributorId":2005,"corporation":false,"usgs":true,"family":"Hirsch","given":"Robert","email":"rhirsch@usgs.gov","middleInitial":"M.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":502,"text":"Office of Surface Water","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"preferred":true,"id":692772,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schwarz, Gregory E. 0000-0002-9239-4566 gschwarz@usgs.gov","orcid":"https://orcid.org/0000-0002-9239-4566","contributorId":543,"corporation":false,"usgs":true,"family":"Schwarz","given":"Gregory E.","email":"gschwarz@usgs.gov","affiliations":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":5067,"text":"Northeast Regional Director's Office","active":true,"usgs":true}],"preferred":false,"id":692773,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Holtschlag, David J. 0000-0001-5185-4928 dholtschlag@usgs.gov","orcid":"https://orcid.org/0000-0001-5185-4928","contributorId":5447,"corporation":false,"usgs":true,"family":"Holtschlag","given":"David","email":"dholtschlag@usgs.gov","middleInitial":"J.","affiliations":[{"id":382,"text":"Michigan Water Science Center","active":true,"usgs":true}],"preferred":true,"id":692774,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Preston, Stephen D. 0000-0003-1515-6692 spreston@usgs.gov","orcid":"https://orcid.org/0000-0003-1515-6692","contributorId":1463,"corporation":false,"usgs":true,"family":"Preston","given":"Stephen","email":"spreston@usgs.gov","middleInitial":"D.","affiliations":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":692775,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Crawford, Charles G. 0000-0003-1653-7841 cgcrawfo@usgs.gov","orcid":"https://orcid.org/0000-0003-1653-7841","contributorId":1064,"corporation":false,"usgs":true,"family":"Crawford","given":"Charles","email":"cgcrawfo@usgs.gov","middleInitial":"G.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"preferred":true,"id":692776,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Vecchia, Aldo V. 0000-0002-2661-4401 avecchia@usgs.gov","orcid":"https://orcid.org/0000-0002-2661-4401","contributorId":1173,"corporation":false,"usgs":true,"family":"Vecchia","given":"Aldo","email":"avecchia@usgs.gov","middleInitial":"V.","affiliations":[{"id":478,"text":"North Dakota Water Science Center","active":true,"usgs":true},{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":692777,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70188069,"text":"70188069 - 2016 - Evaluation of the initial thematic output from a continuous change-detection algorithm for use in automated operational land-change mapping by the U.S. Geological Survey","interactions":[],"lastModifiedDate":"2017-05-30T12:57:22","indexId":"70188069","displayToPublicDate":"2016-01-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3250,"text":"Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Evaluation of the initial thematic output from a continuous change-detection algorithm for use in automated operational land-change mapping by the U.S. Geological Survey","docAbstract":"The U.S. Geological Survey (USGS) has begun the development of operational, 30-m resolution annual thematic land cover data to meet the needs of a variety of land cover data users. The Continuous Change Detection and Classification (CCDC) algorithm is being evaluated as the likely methodology following early trials. Data for training and testing of CCDC thematic maps have been provided by the USGS Land Cover Trends (LC Trends) project, which offers sample-based, manually classified thematic land cover data at 2755 probabilistically located sample blocks across the conterminous United States. These samples represent a high quality, well distributed source of data to train the Random Forest classifier invoked by CCDC. We evaluated the suitability of LC Trends data to train the classifier by assessing the agreement of annual land cover maps output from CCDC with output from the LC Trends project within 14 Landsat path/row locations across the conterminous United States. We used a small subset of circa 2000 data from the LC Trends project to train the classifier, reserving the remaining Trends data from 2000, and incorporating LC Trends data from 1992, to evaluate measures of agreement across time, space, and thematic classes, and to characterize disagreement. Overall agreement ranged from 75% to 98% across the path/rows, and results were largely consistent across time. Land cover types that were well represented in the training data tended to have higher rates of agreement between LC Trends and CCDC outputs. Characteristics of disagreement are being used to improve the use of LC Trends data as a continued source of training information for operational production of annual land cover maps.
","language":"English","publisher":"MDPI","doi":"10.3390/rs8100811","usgsCitation":"Pengra, B., Gallant, A.L., Zhu, Z., and Dahal, D., 2016, Evaluation of the initial thematic output from a continuous change-detection algorithm for use in automated operational land-change mapping by the U.S. Geological Survey: Remote Sensing, v. 8, no. 10, p. 1-33, https://doi.org/10.3390/rs8100811.","productDescription":"Article 811; 33 p.","startPage":"1","endPage":"33","ipdsId":"IP-075088","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":471360,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs8100811","text":"Publisher Index Page"},{"id":341848,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"8","issue":"10","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2016-10-01","publicationStatus":"PW","scienceBaseUri":"592e84bae4b092b266f10d37","contributors":{"authors":[{"text":"Pengra, Bruce 0000-0003-2497-8284 bpengra@usgs.gov","orcid":"https://orcid.org/0000-0003-2497-8284","contributorId":5132,"corporation":false,"usgs":true,"family":"Pengra","given":"Bruce","email":"bpengra@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":696386,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gallant, Alisa L. 0000-0002-3029-6637 gallant@usgs.gov","orcid":"https://orcid.org/0000-0002-3029-6637","contributorId":2940,"corporation":false,"usgs":true,"family":"Gallant","given":"Alisa","email":"gallant@usgs.gov","middleInitial":"L.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":696407,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Zhu, Zhe 0000-0001-8283-6407 zhezhu@usgs.gov","orcid":"https://orcid.org/0000-0001-8283-6407","contributorId":168792,"corporation":false,"usgs":true,"family":"Zhu","given":"Zhe","email":"zhezhu@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":696408,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dahal, Devendra 0000-0001-9594-1249 ddahal@usgs.gov","orcid":"https://orcid.org/0000-0001-9594-1249","contributorId":5622,"corporation":false,"usgs":true,"family":"Dahal","given":"Devendra","email":"ddahal@usgs.gov","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":696409,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70190606,"text":"70190606 - 2016 - Acoustic doppler velocimeter backscatter for quantification of suspended sediment concentration in South San Francisco Bay","interactions":[],"lastModifiedDate":"2017-09-11T10:17:43","indexId":"70190606","displayToPublicDate":"2016-01-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Acoustic doppler velocimeter backscatter for quantification of suspended sediment concentration in South San Francisco Bay","docAbstract":"A data set was acquired on a shallow mudflat in south San Francisco Bay that featured simultaneous, co-located optical and acoustic sensors for subsequent estimation of suspended sediment concentrations (SSC). The optical turbidity sensor output was converted to SSC via an empirical relation derived at a nearby site using bottle sample estimates of SSC. The acoustic data was obtained using an acoustic Doppler velocimeter. Backscatter and noise were combined to develop another empirical relation between the optical estimates of SSC and the relative backscatter from the acoustic velocimeter. The optical and acoustic approaches both reproduced similar general trends in the data and have merit. Some seasonal variation in the dataset was evident, with the two methods differing by greater or lesser amounts depending on which portion of the record was examined. It is hypothesized that this is the result of flocculation, affecting the two signals by different degrees, and that the significance or mechanism of the flocculation has some seasonal variability. In the earlier portion of the record (March), there is a clear difference that appears in the acoustic approach between ebb and flood periods, and this is not evident later in the record (May). The acoustic method has promise but it appears that characteristics of flocs that form and break apart may need to be accounted for to improve the power of the method. This may also be true of the optical method: both methods involve assuming that the sediment characteristics (size, size distribution, and shape) are constant
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Coastal engineering proceedings","largerWorkSubtype":{"id":12,"text":"Conference publication"},"language":"English","publisher":"Coastal Engineering Research Council of COPR Institute of American Society of Civil Engineers (ASCE)","doi":"10.9753/icce.v35.sediment.34","usgsCitation":"Ozturk, M., and Work, P.A., 2016, Acoustic doppler velocimeter backscatter for quantification of suspended sediment concentration in South San Francisco Bay, in Coastal engineering proceedings, v. 35, 12 p., https://doi.org/10.9753/icce.v35.sediment.34.","productDescription":"12 p.","ipdsId":"IP-082707","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":471365,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.9753/icce.v35.sediment.34","text":"Publisher Index Page"},{"id":345609,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"South San Francisco Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.42477416992186,\n 37.408346344484976\n ],\n [\n -121.91390991210938,\n 37.408346344484976\n ],\n [\n -121.91390991210938,\n 37.82280243352756\n ],\n [\n -122.42477416992186,\n 37.82280243352756\n ],\n [\n -122.42477416992186,\n 37.408346344484976\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"35","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2017-06-23","publicationStatus":"PW","scienceBaseUri":"59b77071e4b08b1644ddfb32","contributors":{"authors":[{"text":"Ozturk, Mehmet mozturk@usgs.gov","contributorId":196300,"corporation":false,"usgs":false,"family":"Ozturk","given":"Mehmet","email":"mozturk@usgs.gov","affiliations":[],"preferred":false,"id":709971,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Work, Paul A. 0000-0002-2815-8040 pwork@usgs.gov","orcid":"https://orcid.org/0000-0002-2815-8040","contributorId":168561,"corporation":false,"usgs":true,"family":"Work","given":"Paul","email":"pwork@usgs.gov","middleInitial":"A.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":709970,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70192946,"text":"70192946 - 2016 - The concept of stress in fish","interactions":[],"lastModifiedDate":"2018-01-26T11:17:25","indexId":"70192946","displayToPublicDate":"2016-01-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5606,"text":"Fish Physiology","active":true,"publicationSubtype":{"id":10}},"title":"The concept of stress in fish","docAbstract":"The general physiological response of fish to threatening situations, as with all vertebrates, is referred to as stress. A stress response is initiated almost immediately following the perception of a stressor. Mildly stressful situations can have beneficial or positive effects (eustress), while higher severities induce adaptive responses but also can have maladaptive or negative consequences (distress). The stress response is initiated and controlled by two hormonal systems, those leading to the production of corticosteroids (mainly cortisol) and catecholamines (such as adrenaline and noradrenaline and their precursor dopamine). Together these regulate the secondary stress response factors that alter the distribution of necessary resources such as energy sources and oxygen to vital areas of the body, as well as compromise hydromineral imbalance and the immune system. If fish can resist death due to a stressor, they recover to a similar or somewhat similar homeostatic norm. Long-term consequences of repeated or prolonged exposures to stress are maladaptive by negatively affecting other necessary life functions (growth, development, disease resistance, behavior, and reproduction), in large part because of the energetic cost associated with mounting the stress response (allostatic load).
There is considerable variation in how fish respond to a stressor because of genetic differences among different taxa and also within stocks and species. Variations within the stress response are introduced by the environmental history of the fish, present ambient environmental conditions, and the fish's present physiological condition. Currently, fish physiology has progressed to the point where we can easily recognize when fish are stressed, but we cannot always recognize when fish are unstressed because the lack of clinical signs of stress does not always correspond to fish being unstressed. In other words, we need to be aware of the possibility of false negatives regarding clinical signs of stress. In addition, we cannot use clinical data to precisely or accurately infer severity of a stressor.
","language":"English","publisher":"Elsevier","doi":"10.1016/B978-0-12-802728-8.00001-1","usgsCitation":"Schreck, C.B., and Tort, L., 2016, The concept of stress in fish: Fish Physiology, v. 35, p. 1-34, https://doi.org/10.1016/B978-0-12-802728-8.00001-1.","productDescription":"34 p.","startPage":"1","endPage":"34","ipdsId":"IP-070040","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":350652,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"35","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a6c4c96e4b06e28e9cabb08","contributors":{"authors":[{"text":"Schreck, Carl B. 0000-0001-8347-1139 carl.schreck@usgs.gov","orcid":"https://orcid.org/0000-0001-8347-1139","contributorId":878,"corporation":false,"usgs":true,"family":"Schreck","given":"Carl","email":"carl.schreck@usgs.gov","middleInitial":"B.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":true,"id":717399,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tort, Lluis","contributorId":169142,"corporation":false,"usgs":false,"family":"Tort","given":"Lluis","email":"","affiliations":[],"preferred":false,"id":725890,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70186653,"text":"70186653 - 2016 - Proceedings of the 2015 international summit on fibropapillomatosis: Global status, trends, and population impacts","interactions":[],"lastModifiedDate":"2017-04-25T16:34:06","indexId":"70186653","displayToPublicDate":"2016-01-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"seriesTitle":{"id":269,"text":"NOAA Technical Memorandum","active":false,"publicationSubtype":{"id":4}},"seriesNumber":"NMFS-PIFSC-54","title":"Proceedings of the 2015 international summit on fibropapillomatosis: Global status, trends, and population impacts","docAbstract":"The 2015 International Summit on Fibropapillomatosis (FP) was convened in Honolulu, Hawaii June 11-14, 2015. Scientists from around the world were invited to present results from sea turtle monitoring and research programs as they relate to the global status, trends, and population impacts of FP on green turtles. The participants engaged in discussions that resulted in the following conclusions: 1.Globally, FP has long been present in wild sea turtle populations the earliest mention was in the late 1800s in the Florida Keys. 2.FP primarily affects medium-sized immature turtles in coastal foraging pastures. 3.Expression of FP differs across ocean basins and to some degree within basins. Turtles in the Southeast US, Caribbean, Brazil, and Australia rarely have oral tumors (inside the mouth cavity), whereas they are common and often severe in Hawaii. Internal tumors (on vital organs) occur in the Atlantic and Hawaii, but only rarely in Australia. Liver tumors are common in Florida but not in Hawaii. 4.Recovery from FP through natural processes, when the affliction is not severe, has been documented in wild populations globally. 5.FP causes reduced survivorship, but documented mortality rates in Australia and Hawaii are low. The mortality impact of FP is not currently exceeding population growth rates in some intensively monitored populations (e.g., Florida, Hawaii) as evidenced by increasing nesting trends despite the incidence of FP in immature foraging populations. 6.Pathogens, hosts, and potential disease and environmental cofactors have the capacity to change; while we are having success now, there needs to be continued monitoring to detect changes in the distribution, occurrence, and severity of the disease. 7.While we do not have clear evidence to provide the direct link, globally, the preponderance of sites with a high frequency of FP tumors are areas with some degree of degradation resulting from altered watersheds. Watershed management and responsible coastal development may be the best approach for reducing the spread and prevalence of the disease. 8.Future research efforts should employ a multi-factorial ecological approach (e.g., virology, parasitology, genetics, health, diet, habitat use, water quality, etc.) since there are likely several environmental cofactors involved in the expression of the disease, which is still thought to be caused by a herpesvirus. 9.Minimum FP data collection in new areas should include: individual identification (photo ID, PIT tags, etc.), standard measurements (length and weight), presence/absence of tumors, tumor severity, body condition, oral examination, method of capture, and effort
","conferenceTitle":"2015 International Summit on Fibropapillomatosis","conferenceDate":"June 11-14, 2015","conferenceLocation":"Honolulu, HI","language":"English","publisher":"NOAA","doi":"10.7289/V5/TM-PIFSC-54","usgsCitation":"Hargrove, S.A., Work, T.M., Brunson, S., Foley, A., and Balazs, G.H., 2016, Proceedings of the 2015 international summit on fibropapillomatosis: Global status, trends, and population impacts: NOAA Technical Memorandum NMFS-PIFSC-54, v, 79 p., https://doi.org/10.7289/V5/TM-PIFSC-54.","productDescription":"v, 79 p.","numberOfPages":"87","ipdsId":"IP-077988","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":339356,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58e753ede4b09da6799c0c51","contributors":{"authors":[{"text":"Hargrove, Stacy A.","contributorId":190643,"corporation":false,"usgs":false,"family":"Hargrove","given":"Stacy","email":"","middleInitial":"A.","affiliations":[{"id":16685,"text":"National Oceanic and Atmopheric Administration","active":true,"usgs":false}],"preferred":false,"id":690182,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Work, Thierry M. 0000-0002-4426-9090 thierry_work@usgs.gov","orcid":"https://orcid.org/0000-0002-4426-9090","contributorId":1187,"corporation":false,"usgs":true,"family":"Work","given":"Thierry","email":"thierry_work@usgs.gov","middleInitial":"M.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":690183,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brunson, Shandell","contributorId":190647,"corporation":false,"usgs":false,"family":"Brunson","given":"Shandell","email":"","affiliations":[{"id":7109,"text":"NOAA, National Marine Fisheries Service, Pacific Islands Fisheries Science Center, 1845 Wasp Boulevard, Building 176, Honolulu, HI 96818.","active":true,"usgs":false}],"preferred":false,"id":690184,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Foley, Allen M.","contributorId":80178,"corporation":false,"usgs":true,"family":"Foley","given":"Allen M.","affiliations":[],"preferred":false,"id":690185,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Balazs, George H.","contributorId":127680,"corporation":false,"usgs":false,"family":"Balazs","given":"George","email":"","middleInitial":"H.","affiliations":[{"id":7109,"text":"NOAA, National Marine Fisheries Service, Pacific Islands Fisheries Science Center, 1845 Wasp Boulevard, Building 176, Honolulu, HI 96818.","active":true,"usgs":false}],"preferred":false,"id":690186,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70187207,"text":"70187207 - 2016 - Age, growth and fall diet of channel catfish in Cheat Lake, West Virginia","interactions":[],"lastModifiedDate":"2017-04-26T12:41:20","indexId":"70187207","displayToPublicDate":"2016-01-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2287,"text":"Journal of Fish and Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Age, growth and fall diet of channel catfish in Cheat Lake, West Virginia","docAbstract":"Acidification has historically impaired Cheat Lake's fish community, but recent mitigation efforts within the Cheat River watershed have improved water quality and species richness. Presently, channel catfish Ictalurus punctatus are abundant and attain desirable sizes for anglers. We evaluated the age, growth, and fall diet of the population. We collected a sample of 155 channel catfish from Cheat Lake from 5 August to 4 December 2014, a subset of which we aged (n = 148) using lapillus otoliths. We fit four growth models (von Bertalanffy, logistic, Gompertz, and power) to length-at-age data and compared models using an information theoretic approach. We collected fall diets from 55 fish sampled from 13 October to 4 December 2014. Total lengths of individuals in the sample ranged from 154 to 721 mm and ages ranged from 2 to 19 y. We AICc-selected the von Bertalanffy growth model as the best approximating model, and the power and Gompertz models also had considerable support. Diets were numerically dominated by Diptera larvae, specifically Chironomidae and Chaoboridae, while 39% of stomachs contained terrestrial food items. This study provides baseline data for management of Cheat Lake's channel catfish population. Further, this study fills a knowledge gap in the scientific literature on channel catfish, because few previously published studies have examined the population ecology of channel catfish in the Central Appalachian region.
","language":"English","publisher":"U.S. Fish and Wildlife Service","doi":"10.3996/092015-JFWM-091","usgsCitation":"Hilling, C., Welsh, S.A., and Smith, D.M., 2016, Age, growth and fall diet of channel catfish in Cheat Lake, West Virginia: Journal of Fish and Wildlife Management, v. 7, no. 2, p. 304-314, https://doi.org/10.3996/092015-JFWM-091.","productDescription":"11 p.","startPage":"304","endPage":"314","ipdsId":"IP-074154","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":471372,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3996/092015-jfwm-091","text":"Publisher Index Page"},{"id":340456,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"West Virginia","otherGeospatial":"Cheat Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": 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