Climate, sea level rise, and urbanization are undergoing unprecedented levels of combined change and are expected to have large effects on natural resources—particularly along the Gulf of Mexico coastline (Gulf Coast). Management decisions to address these effects (i.e., adaptation) require an understanding of the relative vulnerability of various resources to these stressors. To meet this need, the four Landscape Conservation Cooperatives along the Gulf partnered with the Gulf of Mexico Alliance to conduct this Gulf Coast Vulnerability Assessment (GCVA). Vulnerability in this context incorporates the aspects of exposure and sensitivity to threats, coupled with the adaptive capacity to mitigate those threats. Potential impact and adaptive capacity reflect natural history features of target species and ecosystems. The GCVA used an expert opinion approach to qualitatively assess the vulnerability of four ecosystems: mangrove, oyster reef, tidal emergent marsh, and barrier islands, and a suite of wildlife species that depend on them. More than 50 individuals participated in the completion of the GCVA, facilitated via Ecosystem and Species Expert Teams. Of the species assessed, Kemp’s ridley sea turtle was identified as the most vulnerable species across the Gulf Coast. Experts identified the main threats as loss of nesting habitat to sea level rise, erosion, and urbanization. Kemp’s ridley also had an overall low adaptive capacity score due to their low genetic diversity, and higher nest site fidelity as compared to other assessed species. Tidal emergent marsh was the most vulnerable ecosystem, due in part to sea level rise and erosion. In general, avian species were more vulnerable than fish because of nesting habitat loss to sea level rise, erosion, and potential increases in storm surge. Assessors commonly indicated a lack of information regarding impacts due to projected changes in the disturbance regime, biotic interactions, and synergistic effects in both the species and habitat assessments. Many of the assessors who focused on species also identified data gaps regarding genetic information, phenotypic plasticity, life history, and species responses to past climate change and sea level rise. Regardless of information gaps, the results from the GCVA can be used to inform Gulf-wide adaptation plans. Given the scale of climatic impacts, coordinated efforts to address Gulf-wide threats to species and ecosystems will enhance the effectiveness of management actions and also have the potential to maximize the efficacy of limited funding.
","language":"English","publisher":"Gulf Coast Prairie Landscape Conservation Cooperative","collaboration":"Amanda Watson; Joshua Reece; Cynthia Kallio Edwards; Laura Geselbracht; Mark Woodrey; Megan LaPeyre; P. Soupy Daylander","usgsCitation":"Watson, A., Reece, J.S., Tirpak, B., Edwards, C.K., Geselbracht, L., Woodrey, M., LaPeyre, M.K., and Dalyander, P., 2015, The Gulf Coast Vulnerability Assessment: Mangrove, Tidal Emergent Marsh, Barrier Islands, and Oyster Reef.","startPage":"1-132","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-067311","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":325345,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":311396,"type":{"id":15,"text":"Index Page"},"url":"https://gulfcoastprairielcc.org/science/science-projects/gulf-coast-vulnerability-assessment/"}],"publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"578cac34e4b0c1aacabb4a7d","contributors":{"authors":[{"text":"Watson, Amanda","contributorId":149887,"corporation":false,"usgs":false,"family":"Watson","given":"Amanda","email":"","affiliations":[{"id":17848,"text":"Mississippi State University","active":true,"usgs":false}],"preferred":false,"id":579920,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Reece, Joshua S.","contributorId":84654,"corporation":false,"usgs":true,"family":"Reece","given":"Joshua","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":579921,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tirpak, Blair 0000-0002-2679-8378 btirpak@usgs.gov","orcid":"https://orcid.org/0000-0002-2679-8378","contributorId":149886,"corporation":false,"usgs":true,"family":"Tirpak","given":"Blair","email":"btirpak@usgs.gov","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":579919,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Edwards, Cynthia Kallio","contributorId":149888,"corporation":false,"usgs":false,"family":"Edwards","given":"Cynthia","email":"","middleInitial":"Kallio","affiliations":[{"id":17849,"text":"Wildlife Management Institute","active":true,"usgs":false}],"preferred":false,"id":579922,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Geselbracht, Laura","contributorId":149889,"corporation":false,"usgs":false,"family":"Geselbracht","given":"Laura","email":"","affiliations":[{"id":7041,"text":"The Nature Conservancy","active":true,"usgs":false}],"preferred":false,"id":579923,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Woodrey, Mark","contributorId":149890,"corporation":false,"usgs":false,"family":"Woodrey","given":"Mark","affiliations":[{"id":17848,"text":"Mississippi State University","active":true,"usgs":false}],"preferred":false,"id":579924,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"LaPeyre, Megan K. 0000-0001-9936-2252 mlapeyre@usgs.gov","orcid":"https://orcid.org/0000-0001-9936-2252","contributorId":585,"corporation":false,"usgs":true,"family":"LaPeyre","given":"Megan","email":"mlapeyre@usgs.gov","middleInitial":"K.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":579925,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Dalyander, P. Soupy 0000-0001-9583-0872 sdalyander@usgs.gov","orcid":"https://orcid.org/0000-0001-9583-0872","contributorId":149892,"corporation":false,"usgs":true,"family":"Dalyander","given":"P. Soupy","email":"sdalyander@usgs.gov","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":579926,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70173769,"text":"70173769 - 2015 - Range-wide wetland associations of the King Rail: A multi-scale approach","interactions":[],"lastModifiedDate":"2016-06-09T13:17:28","indexId":"70173769","displayToPublicDate":"2016-06-09T14:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3750,"text":"Wetlands","onlineIssn":"1943-6246","printIssn":"0277-5212","active":true,"publicationSubtype":{"id":10}},"title":"Range-wide wetland associations of the King Rail: A multi-scale approach","docAbstract":"King Rail populations have declined and identifying wetland features that influence King Rail occupancy can help prevent further population declines. We integrated continent-wide marsh bird survey data with spatial wetland data from the National Wetland Inventory (NWI) to examine wetland features that influenced King Rail occupancy throughout the species’ range. We analyzed wetland data at 7 spatial scales to examine the scale(s) at which 68 wetland features were most strongly related to King Rail occupancy. Occupancy was most strongly associated with estuarine features and brackish and tidal saltwater regimes. King Rail occupancy was positively associated with emergent and scrub-shrub wetlands and negatively associated with forested wetlands. The best spatial scale for assessing King Rail occupancy differed among wetland features; we could not identify one spatial scale (among all wetland features) that best explained variation in occupancy. Future research on King Rail habitat that includes multiple spatial scales is more likely to identify the suite of features that influence occupancy. Our results indicate that NWI data may be useful for predicting occupancy based on broad habitat features across the King Rail’s range, which may help inform management decisions for this and other wetland-dependent birds.
","language":"English","publisher":"Springer","doi":"10.1007/s13157-015-0648-0","usgsCitation":"Glisson, W.J., Conway, C.J., Nadeau, C.P., Borgmann, K.L., and Laxson, T.A., 2015, Range-wide wetland associations of the King Rail: A multi-scale approach: Wetlands, v. 35, no. 3, p. 557-587, https://doi.org/10.1007/s13157-015-0648-0.","productDescription":"11 p.","startPage":"557","endPage":"587","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-061708","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":323377,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"35","issue":"3","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2015-03-18","publicationStatus":"PW","scienceBaseUri":"575a8523e4b04f417c27108f","contributors":{"authors":[{"text":"Glisson, Wesley J.","contributorId":171646,"corporation":false,"usgs":false,"family":"Glisson","given":"Wesley","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":638202,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Conway, Courtney J. 0000-0003-0492-2953 cconway@usgs.gov","orcid":"https://orcid.org/0000-0003-0492-2953","contributorId":2951,"corporation":false,"usgs":true,"family":"Conway","given":"Courtney","email":"cconway@usgs.gov","middleInitial":"J.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":638146,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nadeau, Christopher P.","contributorId":105956,"corporation":false,"usgs":true,"family":"Nadeau","given":"Christopher","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":638203,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Borgmann, Kathi L.","contributorId":171647,"corporation":false,"usgs":false,"family":"Borgmann","given":"Kathi","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":638204,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Laxson, Thomas A.","contributorId":171648,"corporation":false,"usgs":false,"family":"Laxson","given":"Thomas","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":638205,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70159315,"text":"70159315 - 2015 - Final project memorandum: sea-level rise modeling handbook: resource guide for resource managers, engineers, and scientists","interactions":[],"lastModifiedDate":"2016-07-11T15:43:49","indexId":"70159315","displayToPublicDate":"2016-06-06T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":18,"text":"Abstract or summary"},"title":"Final project memorandum: sea-level rise modeling handbook: resource guide for resource managers, engineers, and scientists","docAbstract":"Coastal wetlands of the Southeastern United States are undergoing retreat and migration from increasing tidal inundation and saltwater intrusion attributed to climate variability and sea-level rise. Much of the literature describing potential sea-level rise projections and modeling predictions are found in peer-reviewed academic journals or government technical reports largely suited to reading by other Ph.D. scientists who are more familiar or engaged in the climate change debate. Various sea-level rise and coastal wetland models have been developed and applied of different designs and scales of spatial and temporal complexity for predicting habitat and environmental change that have not heretofore been synthesized to aid natural resource managers of their utility and limitations. Training sessions were conducted with Federal land managers with U.S. Fish and Wildlife Service, National Park Service, and NOAA National Estuarine Research Reserves as well as state partners and nongovernmental organizations across the northern Gulf Coast from Florida to Texas to educate and to evaluate user needs and understanding of concepts, data, and modeling tools for projecting sea-level rise and its impact on coastal habitats and wildlife. As a result, this handbook was constructed from these training and feedback sessions with coastal managers and biologists of published decision-support tools and simulation models for sea-level rise and climate change assessments. A simplified tabular context was developed listing the various kinds of decision-support tools and ecological models along with criteria to distinguish the source, scale, and quality of information input and geographic data sets, physical and biological constraints and relationships, datum characteristics of water and land elevation components, utility options for setting sea-level rise and climate change scenarios, and ease or difficulty of storing, displaying, or interpreting model output. The handbook is designed to be a primer to understanding sea-level rise and a practical synthesis of the current state of knowledge and modeling tools as a resource guide for DOl land management needs and facilitating Landscape Conservation Cooperative (LCC) research and conservation initiatives.
","language":"English","collaboration":"Southeast Climate Science Center","usgsCitation":"Doyle, T.W., 2015, Final project memorandum: sea-level rise modeling handbook: resource guide for resource managers, engineers, and scientists.","productDescription":"8 p.","startPage":"8","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-065874","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":310250,"type":{"id":15,"text":"Index Page"},"url":"https://www.sciencebase.gov/catalog/item/560c29c2e4b058f706e540f9","text":"Final Memo for A Handbook for Resource Managers to Understand and Utilize Sea-Level Rise and Coastal Wetland Models for Ecosystem Management under Future Conditions","size":"120.61 KB","linkFileType":{"id":1,"text":"pdf"},"description":"Final Memo for A Handbook for Resource Managers to Understand and Utilize Sea-Level Rise and Coastal Wetland Models for Ecosystem Management under Future Conditions"},{"id":322358,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5756909de4b023b96ec20aa0","contributors":{"authors":[{"text":"Doyle, Thomas W. 0000-0001-5754-0671 doylet@usgs.gov","orcid":"https://orcid.org/0000-0001-5754-0671","contributorId":703,"corporation":false,"usgs":true,"family":"Doyle","given":"Thomas","email":"doylet@usgs.gov","middleInitial":"W.","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":true,"id":577988,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70155806,"text":"70155806 - 2015 - Applications of genetic data to improve management and conservation of river fishes and their habitats","interactions":[],"lastModifiedDate":"2016-05-18T07:30:00","indexId":"70155806","displayToPublicDate":"2016-04-13T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1657,"text":"Fisheries","onlineIssn":"1548-8446","printIssn":"0363-2415","active":true,"publicationSubtype":{"id":10}},"title":"Applications of genetic data to improve management and conservation of river fishes and their habitats","docAbstract":"Digital flood-inundation maps for a 2.6-mile reach of the Schoharie Creek at Prattsville, New York, were created by the U.S. Geological Survey (USGS) in cooperation with the New York State Department of Environmental Conservation. The flood-inundation maps, which can be accessed through the USGS Flood Inundation Mapping Science Web site at http://water.usgs.gov/osw/flood_inundation/, depict estimates of the areal extent and depth of flooding corresponding to selected water levels (stages) at the USGS streamgage at Schoharie Creek at Prattsville (station number 01350000). Near-real-time stages at this streamgage may be obtained online from the USGS National Water Information System (http://waterdata.usgs.gov/) or the National Weather Service Advanced Hydrologic Prediction Service (http://water.weather.gov/ahps/), which also forecasts flood hydrographs at this site. National Weather Service-forecasted peak-stage information may be used in conjunction with the maps developed in this study to show predicted areas and depths of flood inundation.
\nFlood profiles were computed for the stream reach by means of a one-dimensional step-backwater model. The model was calibrated by using the stage-discharge relation (rating 82.0) at the Schoharie Creek at Prattsville streamgage (station 01350000) and high-water marks from the flood of August 28, 2011. The hydraulic model was then used to compute 17 water-surface profiles for flood stages at 1-foot intervals referenced to the streamgage datum and ranging from bankfull to greater than the highest recorded water level at the streamgage. The simulated water-surface profiles were then combined with a geographic information system digital elevation model, derived from light detection and ranging (lidar) data having a 0.61-foot vertical root-mean squared error and 6.6-foot horizontal resolution, in order to delineate the area flooded at each water level.
\nThese flood-inundation maps, along with near-real-time stage data from USGS streamgages and forecasted stage data from the National Weather Service, can provide emergency management personnel and residents with information that is critical for flood response activities such as evacuations and road closures as well as for postflood recovery efforts.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155190","collaboration":"Prepared in cooperation with the New York State Department of Environmental Conservation","usgsCitation":"Nystrom, E.A., 2016, Flood-inundation maps for the Schoharie Creek at Prattsville, New York, 2014: U.S. Geological Survey Scientific Investigations Report 2015–5190, 12 p., 17 sheets, https://dx.doi.org/10.3133/sir20155190.","productDescription":"Report: vii, 15 p.; 17 Sheets: 17.00 x 22.00 inches or smaller; Application Sites; Metadata","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-067775","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":316401,"rank":12,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sir/2015/5190/downloads/sir20155190_sheet10-prattsville-stage18.pdf","text":"Sheet10—stage of 18.0 feet","size":"6.11 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U.S. Geological Survey
425 Jordan Road
Troy, NY 12180-8349
Information requests:
(518) 285-5602
Or visit our Web site at:
http://ny.water.usgs.gov
The bison (Bison bison) of the Yellowstone ecosystem, USA, exemplify the difficulty of conserving large mammals that migrate across the boundaries of conservation areas. Bison are infected with brucellosis (Brucella abortus) and their seasonal movements can expose livestock to infection. Yellowstone National Park has embarked on a program of adaptive management of bison, which requires a model that assimilates data to support management decisions. We constructed a Bayesian state-space model to reveal the influence of brucellosis on the Yellowstone bison population. A frequency-dependent model of brucellosis transmission was superior to a density-dependent model in predicting out-of-sample observations of horizontal transmission probability. A mixture model including both transmission mechanisms converged on frequency dependence. Conditional on the frequency-dependent model, brucellosis median transmission rate was 1.87 yr−1. The median of the posterior distribution of the basic reproductive ratio (R0) was 1.75. Seroprevalence of adult females varied around 60% over two decades, but only 9.6 of 100 adult females were infectious. Brucellosis depressed recruitment; estimated population growth rate λ averaged 1.07 for an infected population and 1.11 for a healthy population. We used five-year forecasting to evaluate the ability of different actions to meet management goals relative to no action. Annually removing 200 seropositive female bison increased by 30-fold the probability of reducing seroprevalence below 40% and increased by a factor of 120 the probability of achieving a 50% reduction in transmission probability relative to no action. Annually vaccinating 200 seronegative animals increased the likelihood of a 50% reduction in transmission probability by fivefold over no action. However, including uncertainty in the ability to implement management by representing stochastic variation in the number of accessible bison dramatically reduced the probability of achieving goals using interventions relative to no action. Because the width of the posterior predictive distributions of future population states expands rapidly with increases in the forecast horizon, managers must accept high levels of uncertainty. These findings emphasize the necessity of iterative, adaptive management with relatively short-term commitment to action and frequent reevaluation in response to new data and model forecasts. We believe our approach has broad applications.
","language":"English","publisher":"Ecological Society of America","doi":"10.1890/14-1413.1","usgsCitation":"Hobbs, N., Geremia, C., Treanor, J., Wallen, R., White, P., Hooten, M., and Rhyan, J.C., 2015, State-space modeling to support management of brucellosis in the Yellowstone bison population: Ecological Monographs, v. 85, no. 4, p. 525-556, https://doi.org/10.1890/14-1413.1.","productDescription":"32 p.","startPage":"525","endPage":"556","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-053288","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":318110,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wyoming","otherGeospatial":"Yellowstone National Park","volume":"85","issue":"4","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"56c599ace4b0946c6521edfc","contributors":{"authors":[{"text":"Hobbs, N. Thompson","contributorId":35031,"corporation":false,"usgs":true,"family":"Hobbs","given":"N. Thompson","affiliations":[],"preferred":false,"id":620718,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Geremia, Chris","contributorId":167003,"corporation":false,"usgs":false,"family":"Geremia","given":"Chris","email":"","affiliations":[],"preferred":false,"id":620719,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Treanor, John","contributorId":92063,"corporation":false,"usgs":true,"family":"Treanor","given":"John","affiliations":[],"preferred":false,"id":620720,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wallen, Rick","contributorId":14202,"corporation":false,"usgs":true,"family":"Wallen","given":"Rick","affiliations":[],"preferred":false,"id":620721,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"White, P.J.","contributorId":91436,"corporation":false,"usgs":true,"family":"White","given":"P.J.","affiliations":[],"preferred":false,"id":620722,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hooten, Mevin 0000-0002-1614-723X mhooten@usgs.gov","orcid":"https://orcid.org/0000-0002-1614-723X","contributorId":2958,"corporation":false,"usgs":true,"family":"Hooten","given":"Mevin","email":"mhooten@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":12963,"text":"Colorado Cooperative Fish and Wildlife Research Unit, Fort Collins, CO","active":true,"usgs":false}],"preferred":true,"id":619788,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Rhyan, Jack C.","contributorId":11185,"corporation":false,"usgs":true,"family":"Rhyan","given":"Jack","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":620723,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70168365,"text":"70168365 - 2015 - Population trends and survival of nesting green sea turtles Chelonia mydas on Aves Island, Venezuela","interactions":[],"lastModifiedDate":"2022-11-02T15:06:23.594321","indexId":"70168365","displayToPublicDate":"2016-02-16T11:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1497,"text":"Endangered Species Research","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Population trends and survival of nesting green sea turtles Chelonia mydas on Aves Island, Venezuela","title":"Population trends and survival of nesting green sea turtles Chelonia mydas on Aves Island, Venezuela","docAbstract":"Long-term demographic data are valuable for assessing the effect of anthropogenic impacts on endangered species and evaluating recovery programs. Using a 2-state open robust design model, we analyzed mark-recapture data from green turtles Chelonia mydas sighted between 1979 and 2009 on Aves Island, Venezuela, a rookery heavily impacted by human activities before it was declared a wildlife refuge in 1972. Based on the encounter histories of 7689 nesting females, we estimated the abundance, annual survival, and remigration intervals for this population. Female survival varied from 0.14-0.91, with a mean of 0.79, which is low compared to survival of other populations from the Caribbean (mean = 0.84) and Australia (mean = 0.95), even though we partially corrected for tag loss, which is known to negatively bias survival estimates. This supports prior suggestions that Caribbean populations in general, and the Aves Island population in particular, may be more strongly impacted than populations elsewhere. It is likely that nesters from this rookery are extracted while foraging in remote feeding grounds where hunting still occurs. Despite its relatively low survival, the nesting population at Aves Island increased during the past 30 years from approx. 500 to >1000 nesting females in 2009. Thus, this population, like others in the Caribbean and the Atlantic, seems to be slowly recovering following protective management. Although these findings support the importance of long-term conservation programs aimed at protecting nesting grounds, they also highlight the need to extend management actions to foraging grounds where human activities may still impact green turtle populations.
","language":"English","publisher":"Inter-Research Science Publisher","doi":"10.3354/esr00695","usgsCitation":"Garcia-Cruz, M.A., Lampo, M., Penaloza, C.L., Kendall, W., Sole, G., and Rodriguez-Clark, K.M., 2015, Population trends and survival of nesting green sea turtles Chelonia mydas on Aves Island, Venezuela: Endangered Species Research, v. 29, no. 2, p. 103-116, https://doi.org/10.3354/esr00695.","productDescription":"14 p.","startPage":"103","endPage":"116","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-061027","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":471500,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3354/esr00695","text":"Publisher Index Page"},{"id":318059,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Venezuela","otherGeospatial":"Aves Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -63.38424114450454,\n 15.41986000335801\n ],\n [\n -63.38424114450454,\n 15.383063099888886\n ],\n [\n -63.33335107339563,\n 15.383063099888886\n ],\n [\n -63.33335107339563,\n 15.41986000335801\n ],\n [\n -63.38424114450454,\n 15.41986000335801\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"29","issue":"2","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"56c44831e4b0946c6521170b","contributors":{"authors":[{"text":"Garcia-Cruz, Marco A.","contributorId":166909,"corporation":false,"usgs":false,"family":"Garcia-Cruz","given":"Marco","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":620325,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lampo, Margarita","contributorId":166910,"corporation":false,"usgs":false,"family":"Lampo","given":"Margarita","email":"","affiliations":[],"preferred":false,"id":620326,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Penaloza, Claudia L.","contributorId":166911,"corporation":false,"usgs":false,"family":"Penaloza","given":"Claudia","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":620327,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kendall, William L. 0000-0003-0084-9891 wkendall@usgs.gov","orcid":"https://orcid.org/0000-0003-0084-9891","contributorId":166709,"corporation":false,"usgs":true,"family":"Kendall","given":"William L.","email":"wkendall@usgs.gov","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":false,"id":619805,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sole, Genaro","contributorId":166912,"corporation":false,"usgs":false,"family":"Sole","given":"Genaro","email":"","affiliations":[],"preferred":false,"id":620328,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Rodriguez-Clark, Kathryn M.","contributorId":166913,"corporation":false,"usgs":false,"family":"Rodriguez-Clark","given":"Kathryn","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":620329,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70168364,"text":"70168364 - 2015 - Evaluation of a waistband for attaching external radiotransmitters to anurans","interactions":[],"lastModifiedDate":"2016-02-16T09:18:56","indexId":"70168364","displayToPublicDate":"2016-02-16T10:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3779,"text":"Wildlife Society Bulletin","onlineIssn":"1938-5463","printIssn":"0091-7648","active":true,"publicationSubtype":{"id":10}},"title":"Evaluation of a waistband for attaching external radiotransmitters to anurans","docAbstract":"Radiotelemetry provides fine-scale temporal and spatial information about an individual's movements and habitat use; however, its use for monitoring amphibians has been restricted by transmitter mass and lack of suitable attachment techniques. We describe a novel waistband for attaching external radiotransmitters to anurans and evaluate the percentages of resulting abrasions, lacerations, and shed transmitters. We used radiotelemetry to monitor movements and habitat use of wood frogs (Lithobates sylvaticus) in 2006 and 2011–2013 in Maine, USA; American toads (Anaxyrus americanus) in 2012 in North Carolina, USA; and, wood frogs, southern leopard frogs (L. sphenocephalus), and green frogs (L. clamitans) in 2012 in South Carolina, USA. We monitored 172 anurans for 1–365 days (56.4 ± 59.4) in a single year and 1–691 days (60.5 ± 94.1) across years. Our waistband resulted in an injury percentage comparable to 7 alternative anuran waistband attachment techniques; however, 12.5% fewer anurans shed their waistband when attached with our technique. Waistband retention facilitates longer monitoring periods and, thus, provides a greater quantity of data per radiotagged individual.
","language":"English","publisher":"Wildlife Society","doi":"10.1002/wsb.554","usgsCitation":"Groff, L.A., Pitt, A.L., Baldwin, R.F., Calhoun, A.J., and Loftin, C., 2015, Evaluation of a waistband for attaching external radiotransmitters to anurans: Wildlife Society Bulletin, v. 39, no. 3, p. 610-615, https://doi.org/10.1002/wsb.554.","productDescription":"6 p.","startPage":"610","endPage":"615","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-059664","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":500030,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doaj.org/article/2de99f8197794b30b5eb6bbf1c431a2c","text":"External Repository"},{"id":318039,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"39","issue":"3","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2015-07-21","publicationStatus":"PW","scienceBaseUri":"56c4482be4b0946c652116dc","chorus":{"doi":"10.1002/wsb.554","url":"http://dx.doi.org/10.1002/wsb.554","publisher":"Wiley-Blackwell","authors":"Groff Luke A., Pitt Amber L., Baldwin Robert F., Calhoun Aram J. K., Loftin Cynthia S.","journalName":"Wildlife Society Bulletin","publicationDate":"7/2015","auditedOn":"10/1/2015"},"contributors":{"authors":[{"text":"Groff, Luke A.","contributorId":95735,"corporation":false,"usgs":true,"family":"Groff","given":"Luke","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":620305,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pitt, Amber L.","contributorId":166900,"corporation":false,"usgs":false,"family":"Pitt","given":"Amber","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":620306,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Baldwin, Robert F.","contributorId":96415,"corporation":false,"usgs":true,"family":"Baldwin","given":"Robert","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":620307,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Calhoun, Aram J.K.","contributorId":93829,"corporation":false,"usgs":false,"family":"Calhoun","given":"Aram","email":"","middleInitial":"J.K.","affiliations":[{"id":7063,"text":"University of Maine","active":true,"usgs":false}],"preferred":false,"id":620308,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Loftin, Cyndy 0000-0001-9104-3724 cyndy_loftin@usgs.gov","orcid":"https://orcid.org/0000-0001-9104-3724","contributorId":146427,"corporation":false,"usgs":true,"family":"Loftin","given":"Cyndy","email":"cyndy_loftin@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":619804,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70173494,"text":"70173494 - 2015 - Distribution, abundance, and habitat associations of a large bivalve (Panopea generosa) in a eutrophic, fjord estuary","interactions":[],"lastModifiedDate":"2016-06-17T12:01:14","indexId":"70173494","displayToPublicDate":"2016-02-15T09:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2455,"text":"Journal of Shellfish Research","active":true,"publicationSubtype":{"id":10}},"title":"Distribution, abundance, and habitat associations of a large bivalve (Panopea generosa) in a eutrophic, fjord estuary","docAbstract":"Marine bivalves are important ecosystem constituents and frequently support valuable fisheries. In many nearshore areas, human disturbance—including declining habitat and water quality—can affect the distribution and abundance of bivalve populations, and complicate ecosystem and fishery management assessments. Infaunal bivalves, in particular, are frequently cryptic and difficult to detect; thus, assessing potential impacts on their populations requires suitable, scalable methods for estimating abundance and distribution. In this study, population size of a common benthic bivalve (the geoduck Panopea generosa) is estimated with a Bayesian habitat-based model fit to scuba and tethered camera data in Hood Canal, a fjord basin in Washington state. Densities declined more than two orders of magnitude along a north—south gradient, concomitant with patterns of deepwater dissolved oxygen, and intensity and duration of seasonal hypoxia. Across the basin, geoducks were most abundant in loose, unconsolidated, sand substrate. The current study demonstrates the utility of using scuba, tethered video, and habitat models to estimate the abundance and distribution of a large infaunal bivalve at a regional (385-km2) scale.
","language":"English","publisher":"National Shellfisheries Association","doi":"10.2983/035.034.0117","usgsCitation":"Mcdonald, P.S., Essington, T.E., Davis, J.P., Galloway, A.W., Stevick, B.C., Jensen, G.C., VanBlaricom, G.R., and Armstrong, D., 2015, Distribution, abundance, and habitat associations of a large bivalve (Panopea generosa) in a eutrophic, fjord estuary: Journal of Shellfish Research, v. 34, no. 1, p. 137-145, https://doi.org/10.2983/035.034.0117.","productDescription":"8 p.","startPage":"137","endPage":"145","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-063458","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":323886,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Hood Canal","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.84362792968749,\n 47.44480754169439\n ],\n [\n -122.838134765625,\n 47.428087261714275\n ],\n [\n -122.93426513671875,\n 47.37696459572701\n ],\n [\n -123.02627563476562,\n 47.349989032003215\n ],\n [\n -123.07159423828125,\n 47.344406158662096\n ],\n [\n -123.101806640625,\n 47.352780247239586\n ],\n [\n -123.10867309570311,\n 47.333238640473475\n ],\n [\n -123.14163208007811,\n 47.336961408985005\n ],\n [\n -123.167724609375,\n 47.352780247239586\n ],\n [\n -123.15948486328126,\n 47.38998234483188\n ],\n [\n -123.12240600585938,\n 47.4596655525415\n ],\n [\n -123.06335449218749,\n 47.53111102290634\n ],\n [\n -123.00155639648436,\n 47.61264397257417\n ],\n [\n -122.96585083007812,\n 47.640410285382224\n ],\n [\n -122.93014526367188,\n 47.65891296651944\n ],\n [\n -122.89993286132812,\n 47.706065135695745\n ],\n [\n -122.88894653320311,\n 47.743017409121826\n ],\n [\n -122.87933349609376,\n 47.81684332352077\n ],\n [\n -122.87109375,\n 47.82975208084834\n ],\n [\n -122.81204223632811,\n 47.86293128876346\n ],\n [\n -122.78045654296874,\n 47.83528342275264\n ],\n [\n -122.7777099609375,\n 47.81684332352077\n ],\n [\n -122.80929565429688,\n 47.70514099299205\n ],\n [\n -122.78320312499999,\n 47.68850362252604\n ],\n [\n -122.7777099609375,\n 47.75502125407674\n ],\n [\n -122.75161743164061,\n 47.79470655664555\n ],\n [\n -122.73239135742188,\n 47.82237604116143\n ],\n [\n -122.69119262695311,\n 47.850952356425296\n ],\n [\n -122.68981933593749,\n 47.869380336792005\n ],\n [\n -122.60879516601561,\n 47.8527954492302\n ],\n [\n -122.67608642578126,\n 47.79562911029222\n ],\n [\n -122.71728515624999,\n 47.74486433470359\n ],\n [\n -122.73788452148436,\n 47.71715357016648\n ],\n [\n -122.74200439453125,\n 47.68203210030427\n ],\n [\n -122.75161743164061,\n 47.66168780332917\n ],\n [\n -122.84225463867186,\n 47.635783590864854\n ],\n [\n -122.838134765625,\n 47.65058757118734\n ],\n [\n -122.85873413085936,\n 47.64318610543658\n ],\n [\n -122.91366577148438,\n 47.613569753973955\n ],\n [\n -122.93701171874999,\n 47.581157652951454\n ],\n [\n -122.95486450195311,\n 47.57930492644292\n ],\n [\n -122.96585083007812,\n 47.57467282332527\n ],\n [\n -122.991943359375,\n 47.53945544742392\n ],\n [\n -123.02490234375,\n 47.49864785970502\n ],\n [\n -123.06060791015624,\n 47.45037978769006\n ],\n [\n -123.10455322265625,\n 47.40299687942135\n ],\n [\n -123.09494018554686,\n 47.38440370312246\n ],\n [\n -123.04412841796875,\n 47.37603463349758\n ],\n [\n -123.00292968749999,\n 47.386263315961884\n ],\n [\n -122.97134399414061,\n 47.409502941311075\n ],\n [\n -122.85873413085936,\n 47.44294999517949\n ],\n [\n -122.84362792968749,\n 47.44480754169439\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"34","issue":"1","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57651f32e4b07657d19c788d","contributors":{"authors":[{"text":"Mcdonald, P. Sean","contributorId":171699,"corporation":false,"usgs":false,"family":"Mcdonald","given":"P.","email":"","middleInitial":"Sean","affiliations":[],"preferred":false,"id":639537,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Essington, Timothy E.","contributorId":95826,"corporation":false,"usgs":false,"family":"Essington","given":"Timothy","email":"","middleInitial":"E.","affiliations":[{"id":13190,"text":"School of Aquatic and Fishery Sciences, University of Washington","active":true,"usgs":false}],"preferred":false,"id":639538,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Davis, Jonathan P.","contributorId":172078,"corporation":false,"usgs":false,"family":"Davis","given":"Jonathan","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":639539,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Galloway, Aaron W.E.","contributorId":172072,"corporation":false,"usgs":false,"family":"Galloway","given":"Aaron","email":"","middleInitial":"W.E.","affiliations":[],"preferred":false,"id":639540,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Stevick, Bethany C.","contributorId":172079,"corporation":false,"usgs":false,"family":"Stevick","given":"Bethany","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":639541,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Jensen, Gregory C.","contributorId":172080,"corporation":false,"usgs":false,"family":"Jensen","given":"Gregory","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":639542,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"VanBlaricom, Glenn R. glennvb@usgs.gov","contributorId":3540,"corporation":false,"usgs":true,"family":"VanBlaricom","given":"Glenn","email":"glennvb@usgs.gov","middleInitial":"R.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":false,"id":637196,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Armstrong, David A.","contributorId":172081,"corporation":false,"usgs":false,"family":"Armstrong","given":"David A.","affiliations":[],"preferred":false,"id":639543,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70168425,"text":"70168425 - 2015 - Past and future warming of a deep European lake (Lake Lugano): What are the climatic drivers?","interactions":[],"lastModifiedDate":"2016-02-12T13:11:25","indexId":"70168425","displayToPublicDate":"2016-02-12T14:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2330,"text":"Journal of Great Lakes Research","active":true,"publicationSubtype":{"id":10}},"title":"Past and future warming of a deep European lake (Lake Lugano): What are the climatic drivers?","docAbstract":"We used four decades (1972–2013) of temperature data from Lake Lugano, Switzerland and Italy, to address the hypotheses that: [i] the lake has been warming; [ii] part of the warming reflects global trends and is independent from climatic oscillations and [iii] the lake will continue to warm until the end of the 21st century. During the time spanned by our data, the surface waters of the lake (0–5 m) warmed at rates of 0.2–0.9 °C per decade, depending on season. The temperature of the deep waters (50-m bottom) displayed a rising trend in a meromictic basin of the lake and a sawtooth pattern in the other basin, which is holomictic. Long-term variation in surfacewater temperature correlated to global warming and multidecadal variation in two climatic oscillations, the Atlantic Multidecadal Oscillation (AMO) and the East Atlantic Pattern (EA).However, we did not detect an influence of the EA on the lake's temperature (as separate from the effect of global warming). Moreover, the effect of the AMO, estimated to a maximum of +1 °C, was not sufficient to explain the observed temperature increase (+2–3 °C in summer). Based on regional climate projections, we predicted that the lake will continue to warm at least until the end of the 21st century. Our results strongly suggest that the warming of Lake Lugano is tied to globalclimate change. To sustain current ecosystem conditions in Lake Lugano, we suggest that manage- ment plans that curtail eutrophication and (or) mitigation of global warming be pursued.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jglr.2015.08.004","usgsCitation":"Lepori, F., and Roberts, J., 2015, Past and future warming of a deep European lake (Lake Lugano): What are the climatic drivers?: Journal of Great Lakes Research, v. 41, no. 4, p. 973-981, https://doi.org/10.1016/j.jglr.2015.08.004.","productDescription":"9 p.","startPage":"973","endPage":"981","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-062114","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":317993,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Italy, Switzerland","otherGeospatial":"Lake Lugano","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 9.128265380859375,\n 46.02462129598765\n ],\n [\n 9.093246459960938,\n 46.003162403888766\n ],\n [\n 9.043121337890625,\n 46.01079318614809\n ],\n [\n 8.979263305664062,\n 45.98217232489232\n ],\n [\n 8.9703369140625,\n 45.94303320745295\n ],\n [\n 8.98681640625,\n 45.91294412737392\n ],\n [\n 8.977890014648438,\n 45.90099949265736\n ],\n [\n 8.968276977539062,\n 45.90386643939614\n ],\n [\n 8.966217041015625,\n 45.92536382097966\n ],\n [\n 8.949050903320312,\n 45.933482886823676\n ],\n [\n 8.90167236328125,\n 45.9000438108451\n ],\n [\n 8.892059326171875,\n 45.90338862522072\n ],\n [\n 8.883819580078125,\n 45.933960441921585\n ],\n [\n 8.887252807617188,\n 45.952581883190994\n ],\n [\n 8.854293823242188,\n 45.96212891405598\n ],\n [\n 8.86390686035156,\n 45.97549199391509\n ],\n [\n 8.881072998046875,\n 45.96976535445165\n ],\n [\n 8.89068603515625,\n 45.994099482736694\n ],\n [\n 8.916091918945312,\n 45.99553056897413\n ],\n [\n 8.902359008789062,\n 45.97024259702345\n ],\n [\n 8.90716552734375,\n 45.952104488469985\n ],\n [\n 8.90167236328125,\n 45.9353930825417\n ],\n [\n 8.913345336914062,\n 45.924408558629004\n ],\n [\n 8.942184448242188,\n 45.95783295371863\n ],\n [\n 8.951797485351562,\n 45.9874205909687\n ],\n [\n 8.944931030273438,\n 45.9950535443403\n ],\n [\n 8.953170776367188,\n 46.00602407059352\n ],\n [\n 8.977890014648438,\n 46.003162403888766\n ],\n [\n 9.043807983398438,\n 46.02795859751178\n ],\n [\n 9.08843994140625,\n 46.026528350100904\n ],\n [\n 9.1131591796875,\n 46.03987588680908\n ],\n [\n 9.128265380859375,\n 46.02462129598765\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"41","issue":"4","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"56bf022ee4b06458514b3105","contributors":{"authors":[{"text":"Lepori, Fabio","contributorId":166767,"corporation":false,"usgs":false,"family":"Lepori","given":"Fabio","email":"","affiliations":[{"id":24502,"text":"Institute of Earth Sciences, University of Applied Sciences and Arts of Southern Switzerland","active":true,"usgs":false}],"preferred":false,"id":620051,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Roberts, James 0000-0002-4193-610X jroberts@usgs.gov","orcid":"https://orcid.org/0000-0002-4193-610X","contributorId":5453,"corporation":false,"usgs":true,"family":"Roberts","given":"James","email":"jroberts@usgs.gov","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":620050,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70168370,"text":"70168370 - 2015 - Influence of habitat and intrinsic characteristics on survival of neonatal pronghorn","interactions":[],"lastModifiedDate":"2016-02-15T12:37:52","indexId":"70168370","displayToPublicDate":"2016-02-10T16:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Influence of habitat and intrinsic characteristics on survival of neonatal pronghorn","docAbstract":"Increased understanding of the influence of habitat (e.g., composition, patch size) and intrinsic (e.g., age, birth mass) factors on survival of neonatal pronghorn (Antilocapra americana) is a prerequisite to successful management programs, particularly as they relate to population dynamics and the role of population models in adaptive species management. Nevertheless, few studies have presented empirical data quantifying the influence of habitat variables on survival of neonatal pronghorn. During 2002–2005, we captured and radiocollared 116 neonates across two sites in western South Dakota. We documented 31 deaths during our study, of which coyote (Canis latrans) predation (n = 15) was the leading cause of mortality. We used known fate analysis in Program MARK to investigate the influence of intrinsic and habitat variables on neonatal survival. We generated a priori models that we grouped into habitat and intrinsic effects. The highest-ranking model indicated that neonate mortality was best explained by site, percent grassland, and open water habitat; 90-day survival (0.80; 90% CI = 0.71–0.88) declined 23% when grassland and water increased from 80.1 to 92.3% and 0.36 to 0.40%, respectively, across 50% natal home ranges. Further, our results indicated that grassland patch size and shrub density were important predictors of neonate survival; neonate survival declined 17% when shrub density declined from 5.0 to 2.5 patches per 100 ha. Excluding the site covariates, intrinsic factors (i.e., sex, age, birth mass, year, parturition date) were not important predictors of survival of neonatal pronghorns. Further, neonatal survival may depend on available land cover and interspersion of habitats. We have demonstrated that maintaining minimum and maximum thresholds for habitat factors (e.g., percentages of grassland and open water patches, density of shrub patches) throughout natal home ranges will in turn, ensure relatively high (>0.50) neonatal survival rates, especially as they relate to coyote predation. Thus, landscape level variables (particularly percentages of open water, grassland habitats, and shrub density) should be incorporated into the development or implementation of pronghorn management plans across sagebrush steppe communities of the western Dakotas, and potentially elsewhere within the geographic range of pronghorn.
","language":"English","publisher":"PLOS","doi":"10.1371/journal.pone.0144026","usgsCitation":"Jacques, C.N., Jenks, J., Grovenburg, T.W., and Klaver, R.W., 2015, Influence of habitat and intrinsic characteristics on survival of neonatal pronghorn: PLoS ONE, v. 10, no. 12, e0144026; 17 p., https://doi.org/10.1371/journal.pone.0144026.","productDescription":"e0144026; 17 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-067993","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":471501,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0144026","text":"Publisher Index Page"},{"id":317924,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"South Dakota","county":"Fall River County, Harding County","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -104.029541015625,\n 45.205263456162385\n ],\n [\n -104.029541015625,\n 45.94351068030587\n ],\n [\n -102.89794921875,\n 45.94351068030587\n ],\n [\n -102.89794921875,\n 45.205263456162385\n ],\n [\n -104.029541015625,\n 45.205263456162385\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -104.04052734375,\n 43.00866413845207\n ],\n [\n -104.04052734375,\n 43.49676775343911\n ],\n [\n -102.9473876953125,\n 43.49676775343911\n ],\n [\n -102.9473876953125,\n 43.00866413845207\n ],\n [\n -104.04052734375,\n 43.00866413845207\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"10","issue":"12","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2015-12-02","publicationStatus":"PW","scienceBaseUri":"56bc5f34e4b08d617f66001d","contributors":{"authors":[{"text":"Jacques, Christopher N.","contributorId":15521,"corporation":false,"usgs":true,"family":"Jacques","given":"Christopher","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":619813,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jenks, Jonathan A.","contributorId":51591,"corporation":false,"usgs":true,"family":"Jenks","given":"Jonathan A.","affiliations":[],"preferred":false,"id":619814,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Grovenburg, Troy W.","contributorId":57712,"corporation":false,"usgs":true,"family":"Grovenburg","given":"Troy","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":619815,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Klaver, Robert W. 0000-0002-3263-9701 bklaver@usgs.gov","orcid":"https://orcid.org/0000-0002-3263-9701","contributorId":3285,"corporation":false,"usgs":true,"family":"Klaver","given":"Robert","email":"bklaver@usgs.gov","middleInitial":"W.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":619812,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70162649,"text":"70162649 - 2015 - Crocodylus acutus (American Crocodile). Long distance juvenile movement","interactions":[],"lastModifiedDate":"2016-07-11T15:41:31","indexId":"70162649","displayToPublicDate":"2016-02-01T16:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1898,"text":"Herpetological Review","active":true,"publicationSubtype":{"id":10}},"title":"Crocodylus acutus (American Crocodile). Long distance juvenile movement","docAbstract":"Crocodylus acutus (American Crocodile) is the most widely distributed New World crocodilian species with its range extending from Peru in the south to the southern tip of peninsular Florida in the north. Crocodylus acutus occupies primarily coastal brackish water habitat, however it also occurs in freshwater to hypersaline habitats (Thorbjarnarson 2010. In Crocodiles. Status Survey and Conservation Action Plan. [Third Edition], American Crocodile Crocodylus acutus, pp. 46–53 S.C. Manolis and C. Stevenson. Crocodile Specialist Group, Darwin). There is limited literature on long distance movements of juvenile crocodilians worldwide and no literature on juvenile crocodiles in Florida. However, adult C. acutus in Florida have been documented to make seasonal movements of 5–15 km from preferred foraging habitat to nesting beaches (Mazzotti 1983. The Ecology of Crocodylus acutus in Florida. PhD Dissertation. The Pennsylvania State University, University Park, Pennsylvania. 161pp), and one adult was documented making a 35 km trip from her nest site to preferred foraging habitat (Cherkiss et. al. 2006. Herpetol. Rev. 38:72–73). Rodda (1984. Herpetologica 40:444–451) reported on juvenile C. acutus movement in Gatun Lake, Panama, and found that juveniles stayed within 1 km of their nest site for the first month. Movements of juvenile Crocodylus porosus (Saltwater Crocodile) in a river system in Northern Australia showed a maximum movement of 38.9 km from a known nest site, with the majority of the crocodiles staying within 15.6 km downstream to 6.8 km upstream (Webb and Messel 1978. Aust. Wildlife Res. 5:263–283). Juvenile movement of Crocodylus niloticus (Nile Crocodile) in Lake Ngezi, Zimbabwe showed crocodiles restricted their movements from 1.0 km up to 4.5 km through the wet and dry seasons (Hutton 1989. Am. Zool. 29:1033–1049). Long distance movements of alligators were recorded for sizes ranging from 28 cm to 361 cm in a coastal refuge in Louisiana, where the distance traveled ranged from 0.3 km to 90.2 km. The data showed that the smaller alligators moved greater distance than larger ones (Lance et al. 2011. Southeast Nat. 10:389–398). An ongoing 30 year mark and recapture study for Crocodylus acutus in Florida allowed us to look at long distance movement (>30 km) of juveniles (30km). Initial and most recent captures as a juvenile were used to analyze distances moved (Fig. 1). These distances were measured linearly between capture locations. Maximum linear distances of 76.3 km and 69.6 km were recorded for animals 4838 and 6662. All crocodiles moved from nesting habitat through potentially optimal nursery habitat prior to reaching their recapture locations. These juvenile long distance movements could be due to larger crocodiles facilitating their dispersal from the nest location (Lance et al. 2011. op. cit.). These data (Table 1.) support that there is exchange of individuals among the nesting colonies and our ongoing efforts to monitor this threatened species allow us to make observations of how juvenile crocodiles are moving throughout the landscape in an ecosystem currently undergoing restoration.
","language":"English","publisher":"Society for the Study of Amphibians and Reptiles","usgsCitation":"Crespo, R., Beauchamp, J.S., Mazzotti, F., and Cherkiss, M.S., 2015, Crocodylus acutus (American Crocodile). Long distance juvenile movement: Herpetological Review, v. 46, no. 4, p. 623-624.","productDescription":"2 p.","startPage":"623","endPage":"624","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-060401","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":316426,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"46","issue":"4","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"56b081a8e4b010e2af2a1158","contributors":{"authors":[{"text":"Crespo, Rafael","contributorId":152647,"corporation":false,"usgs":false,"family":"Crespo","given":"Rafael","email":"","affiliations":[{"id":12557,"text":"University of Florida, FLREC","active":true,"usgs":false}],"preferred":false,"id":590044,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Beauchamp, Jeffrey S.","contributorId":138880,"corporation":false,"usgs":false,"family":"Beauchamp","given":"Jeffrey","email":"","middleInitial":"S.","affiliations":[{"id":12559,"text":"University of Florida, FLEC","active":true,"usgs":false}],"preferred":false,"id":590045,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mazzotti, Frank","contributorId":32609,"corporation":false,"usgs":true,"family":"Mazzotti","given":"Frank","affiliations":[],"preferred":false,"id":590046,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cherkiss, Michael S. 0000-0002-7802-6791 mcherkiss@usgs.gov","orcid":"https://orcid.org/0000-0002-7802-6791","contributorId":4571,"corporation":false,"usgs":true,"family":"Cherkiss","given":"Michael","email":"mcherkiss@usgs.gov","middleInitial":"S.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":590043,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70159980,"text":"ofr20151226 - 2015 - Science information to support Missouri River Scaphirhynchus albus (pallid sturgeon) effects analysis","interactions":[],"lastModifiedDate":"2017-03-03T09:08:04","indexId":"ofr20151226","displayToPublicDate":"2016-01-26T10:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-1226","title":"Science information to support Missouri River Scaphirhynchus albus (pallid sturgeon) effects analysis","docAbstract":"The Missouri River Pallid Sturgeon Effects Analysis (EA) was commissioned by the U.S. Army Corps of Engineers to develop a foundation of understanding of how pallid sturgeon (Scaphirhynchus albus) population dynamics are linked to management actions in the Missouri River. The EA consists of several steps: (1) development of comprehensive, conceptual ecological models illustrating pallid sturgeon population dynamics and links to management actions and other drivers; (2) compilation and assessment of available scientific literature, databases, and models; (3) development of predictive, quantitative models to explore the system dynamics and population responses to management actions; and (4) analysis and assessment of effects of system operations and actions on species’ habitats and populations. This report addresses the second objective, compilation and assessment of relevant information.
\nScientific information on pallid sturgeon and its environment has grown substantially during the last decade. Presently available (2015) information indicates that stocked sturgeon are surviving and growing, and that wild and hatchery sturgeon are spawning in the wild. However, natural recruitment to age-1 and older has not been detected since systematic sampling began in 2005. Population models indicate the sensitivity of population growth to certain demographic variables, in particular early-life stage survival and perhaps adult fecundity. This report documents the existing population models for the pallid sturgeon, and the substantial quantities of information developed through the Pallid Sturgeon Population Assessment Program (PSPAP), the Habitat Assessment and Monitoring Program (HAMP), the Comprehensive Sturgeon Research Project (CSRP), range-wide genetics databases, and related research studies. The reference database compiled for the EA consists of over 190 peer-reviewed documents specifically related to pallid sturgeon and over 12,000 references on the Missouri River system and related species.
\nNotwithstanding the large quantity of information available, the EA faces challenges in synthesizing the information into useful, quantitative models. In particular, critical demographic parameters for population models remain uncertain and the functional relationships between the two main categories of physical management action—changes in flow regime and reengineering channel form—and pallid sturgeon survival responses are obscure. In addition, there is an overarching uncertainty about how physical management actions interact with propagation management actions in view of evolving understanding of genetic structuring of the pallid sturgeon population. Synthesis efforts are also challenged by the fragmentation of information sources among projects and agencies; one objective of this report is to facilitate future assessments by providing documentation of what information is available and where.
\n","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151226","collaboration":"Prepared in cooperation with the Missouri River Recovery Program","usgsCitation":"Jacobson, R.B., Parsley, M.J., Annis, M.L., Colvin, M.E., Welker, T.L., and James, D.A.,\n2015, Science information to support Missouri River Scaphirhynchus albus (pallid sturgeon)\neffects analysis: U.S. Geological Survey Open-File Report 2015–1226, 78 p.,\nhttps://dx.doi.org/10.3133/ofr20151226.","productDescription":"vii, 78 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-059606","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":314737,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2015/1226/coverthb.jpg"},{"id":314738,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1226/ofr20151226.pdf","text":"Report","size":"5.71 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2015-1226"}],"country":"United States","state":"Iowa, Kansas, Missouri, Montana, Nebraska, North Dakota, South Dakota","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -94.6142578125,\n 37.28279464911045\n ],\n [\n -91.82373046875,\n 37.52715361723378\n ],\n [\n -90.06591796875,\n 38.8225909761771\n ],\n [\n -96.50390625,\n 43.96119063892024\n ],\n [\n -100.26123046875,\n 48.37084770238363\n ],\n [\n -104.04052734375,\n 48.99463598353408\n ],\n [\n -112.8076171875,\n 49.023461463214126\n ],\n [\n -112.60986328125,\n 45.089035564831036\n ],\n [\n -106.74316406249999,\n 40.979898069620155\n ],\n [\n -102.06298828125,\n 38.993572058209466\n ],\n [\n -94.6142578125,\n 37.28279464911045\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"
Director, USGS Columbia Environmental Research Center
4200 New Haven Road
Columbia, MO 65201
Knowledge of climatic variability at small spatial extents (< 50 km) is needed to assess vulnerabilities of biological reserves to climate change. We used empirical and modeled weather station data to test if climate change has increased the synchrony of surface air temperatures among 50 sites within the Greater Yellowstone Area (GYA) of the interior western United States. This important biological reserve is the largest protected area in the Lower 48 states and provides critical habitat for some of the world’s most iconic wildlife. We focused our analyses on temporal shifts and shape changes in the annual distributions of seasonal minimum and maximum air temperatures among valley-bottom and higher elevation sites from 1948–2012. We documented consistent patterns of warming since 1948 at all 50 sites, with the most pronounced changes occurring during the Winter and Summer when minimum and maximum temperature distributions increased. These shifts indicate more hot temperatures and less cold temperatures would be expected across the GYA. Though the shifting statistical distributions indicate warming, little change in the shape of the temperature distributions across sites since 1948 suggest the GYA has maintained a diverse portfolio of temperatures within a year. Spatial heterogeneity in temperatures is likely maintained by the GYA’s physiographic complexity and its large size, which encompasses multiple climate zones that respond differently to synoptic drivers. Having a diverse portfolio of temperatures may help biological reserves spread the extinction risk posed by climate change.
","language":"English","publisher":"PLOS","doi":"10.1371/journal.pone.0145060","usgsCitation":"Sepulveda, A.J., Tercek, M.T., Al-Chokhachy, R.K., Ray, A., Thoma, D.P., Hossack, B.R., Pederson, G.T., Rodman, A., and Olliff, T., 2015, The shifting climate portfolio of the Greater Yellowstone Area: PLoS ONE, v. 10, no. 12, e0145060; 16 p., https://doi.org/10.1371/journal.pone.0145060.","productDescription":"e0145060; 16 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-065298","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":471506,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0145060","text":"Publisher Index Page"},{"id":314536,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Montana, Wyoming","otherGeospatial":"Yellowstone National Park","geographicExtents":"{\n 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Science Center","active":true,"usgs":true}],"preferred":true,"id":589007,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tercek, Mike T","contributorId":152351,"corporation":false,"usgs":false,"family":"Tercek","given":"Mike","email":"","middleInitial":"T","affiliations":[{"id":18906,"text":"Walking Shadow Ecology, Gardiner, MT, 59030, USA","active":true,"usgs":false}],"preferred":false,"id":589008,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Al-Chokhachy, Robert K. 0000-0002-2136-5098 ral-chokhachy@usgs.gov","orcid":"https://orcid.org/0000-0002-2136-5098","contributorId":1674,"corporation":false,"usgs":true,"family":"Al-Chokhachy","given":"Robert","email":"ral-chokhachy@usgs.gov","middleInitial":"K.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":589009,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ray, Andrew","contributorId":101972,"corporation":false,"usgs":true,"family":"Ray","given":"Andrew","affiliations":[],"preferred":false,"id":589010,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Thoma, David P.","contributorId":45975,"corporation":false,"usgs":true,"family":"Thoma","given":"David","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":589011,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hossack, Blake R. 0000-0001-7456-9564 blake_hossack@usgs.gov","orcid":"https://orcid.org/0000-0001-7456-9564","contributorId":1177,"corporation":false,"usgs":true,"family":"Hossack","given":"Blake","email":"blake_hossack@usgs.gov","middleInitial":"R.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":589012,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Pederson, Gregory T. 0000-0002-6014-1425 gpederson@usgs.gov","orcid":"https://orcid.org/0000-0002-6014-1425","contributorId":3106,"corporation":false,"usgs":true,"family":"Pederson","given":"Gregory","email":"gpederson@usgs.gov","middleInitial":"T.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":589013,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Rodman, Ann","contributorId":150932,"corporation":false,"usgs":false,"family":"Rodman","given":"Ann","affiliations":[{"id":6924,"text":"National Park Service, Upper Columbia Basin Network","active":true,"usgs":false}],"preferred":false,"id":589014,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Olliff, Tom","contributorId":152352,"corporation":false,"usgs":false,"family":"Olliff","given":"Tom","email":"","affiliations":[{"id":18907,"text":"National Park Service, Intermountain Region Landscape Conservation and Climate Change Division, 2327 University Way, Suite 2, Bozeman, MT 59715, USA","active":true,"usgs":false}],"preferred":false,"id":589015,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70162214,"text":"70162214 - 2015 - Invaded invaders: Infection of invasive Brown Treesnakes on Guam by an exotic larval cestode with a life cycle comprised of non-native hosts","interactions":[],"lastModifiedDate":"2016-01-19T08:28:57","indexId":"70162214","displayToPublicDate":"2016-01-19T09:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Invaded invaders: Infection of invasive Brown Treesnakes on Guam by an exotic larval cestode with a life cycle comprised of non-native hosts","docAbstract":"Multiple host introductions to the same non-native environment have the potential to complete life cycles of parasites incidentally transported with them. Our goal was to identify a recently detected parasitic flatworm in the invasive Brown Treesnake (Boiga irregularis) on the remote Pacific island of Guam. We considered possible factors influencing parasite transmission, and tested for correlations between infection status and potential indicators of host fitness. We used genetic data from the parasite and information about the native ranges of other possible non-native hosts to hypothesize how it arrived on Guam and how its life cycle may be currently supported.
\nWe identified the parasite by comparing larval morphology and mtDNA sequences with other Pseudophyllid tapeworms. We assessed probability of infection in individual snakes using logistic regression and examined different factors influencing presence of parasites in hosts.
\nWe identified the parasite as the pseudophyllid cestode Spirometra erinaceieuropaei, with all sampled worms from multiple snakes sharing a single mtDNA haplotype. Infection appears to be limited to the only freshwater watershed on the island, where infection prevalence was high (77.5%). Larger snakes had a higher probability of being infected, consistent with the chronic nature of such infections. While infection status was positively correlated with body condition, infected snakes tended to have lower intra-peritoneal fat body mass, potentially indicating a negative effect on energy stores.
\nWe discovered that B. irregularis inhabiting a small area of forested habitat in a freshwater watershed on Guam are often infected by a novel parasite of Asian origin. While further work is needed, this species of Spirometra, itself a non-native species, likely depends on a suite of recently introduced hosts from different parts of the world to complete the life cycle. This baseline study provides little evidence of any effects on host fitness, but additional data are needed to more thoroughly explore the consequences of infection in this invasive snake population.
","language":"English","publisher":"Public Library of Science","doi":"10.1371/journal.pone.0143718","usgsCitation":"Holldorf, E., Siers, S.R., Richmond, J.Q., Klug, P.E., and Reed, R., 2015, Invaded invaders: Infection of invasive Brown Treesnakes on Guam by an exotic larval cestode with a life cycle comprised of non-native hosts: PLoS ONE, v. 10, no. 12, e0143718: 16 p., https://doi.org/10.1371/journal.pone.0143718.","productDescription":"e0143718: 16 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-063527","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":471509,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0143718","text":"Publisher Index Page"},{"id":314453,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Guam","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 144.60411071777344,\n 13.233261466546951\n ],\n [\n 144.60411071777344,\n 13.655328309840225\n ],\n [\n 144.97283935546872,\n 13.655328309840225\n ],\n [\n 144.97283935546872,\n 13.233261466546951\n ],\n [\n 144.60411071777344,\n 13.233261466546951\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"10","issue":"12","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2015-12-23","publicationStatus":"PW","scienceBaseUri":"569f5e32e4b0961cf27fd169","contributors":{"authors":[{"text":"Holldorf, Elden T","contributorId":152311,"corporation":false,"usgs":false,"family":"Holldorf","given":"Elden T","affiliations":[{"id":12728,"text":"Cherokee Services Group","active":true,"usgs":false}],"preferred":false,"id":588885,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Siers, Shane R.","contributorId":152305,"corporation":false,"usgs":false,"family":"Siers","given":"Shane","email":"","middleInitial":"R.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":588886,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Richmond, Jonathan Q. 0000-0001-9398-4894 jrichmond@usgs.gov","orcid":"https://orcid.org/0000-0001-9398-4894","contributorId":5400,"corporation":false,"usgs":true,"family":"Richmond","given":"Jonathan","email":"jrichmond@usgs.gov","middleInitial":"Q.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":588887,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Klug, Page E. pklug@usgs.gov","contributorId":5545,"corporation":false,"usgs":true,"family":"Klug","given":"Page","email":"pklug@usgs.gov","middleInitial":"E.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":588888,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Reed, Robert 0000-0001-8349-6168 reedr@usgs.gov","orcid":"https://orcid.org/0000-0001-8349-6168","contributorId":152301,"corporation":false,"usgs":true,"family":"Reed","given":"Robert","email":"reedr@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":588884,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70162213,"text":"70162213 - 2015 - Caveats for correlative species distribution modeling","interactions":[],"lastModifiedDate":"2016-01-19T08:31:38","indexId":"70162213","displayToPublicDate":"2016-01-19T09:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1457,"text":"Ecological Informatics","active":true,"publicationSubtype":{"id":10}},"title":"Caveats for correlative species distribution modeling","docAbstract":"Correlative species distribution models are becoming commonplace in the scientific literature and public outreach products, displaying locations, abundance, or suitable environmental conditions for harmful invasive species, threatened and endangered species, or species of special concern. Accurate species distribution models are useful for efficient and adaptive management and conservation, research, and ecological forecasting. Yet, these models are often presented without fully examining or explaining the caveats for their proper use and interpretation and are often implemented without understanding the limitations and assumptions of the model being used. We describe common pitfalls, assumptions, and caveats of correlative species distribution models to help novice users and end users better interpret these models. Four primary caveats corresponding to different phases of the modeling process, each with supporting documentation and examples, include: (1) all sampling data are incomplete and potentially biased; (2) predictor variables must capture distribution constraints; (3) no single model works best for all species, in all areas, at all spatial scales, and over time; and (4) the results of species distribution models should be treated like a hypothesis to be tested and validated with additional sampling and modeling in an iterative process.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecoinf.2015.06.007","usgsCitation":"Jarnevich, C.S., Stohlgren, T.J., Kumar, S., Morisette, J.T., and Holcombe, T.R., 2015, Caveats for correlative species distribution modeling: Ecological Informatics, v. 29, no. 1, p. 6-15, https://doi.org/10.1016/j.ecoinf.2015.06.007.","productDescription":"10 p.","startPage":"6","endPage":"15","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-066207","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":314454,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"29","issue":"1","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"569f5e30e4b0961cf27fd165","contributors":{"authors":[{"text":"Jarnevich, Catherine S. 0000-0002-9699-2336 jarnevichc@usgs.gov","orcid":"https://orcid.org/0000-0002-9699-2336","contributorId":3424,"corporation":false,"usgs":true,"family":"Jarnevich","given":"Catherine","email":"jarnevichc@usgs.gov","middleInitial":"S.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":588879,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stohlgren, Thomas J. 0000-0001-9696-4450 stohlgrent@usgs.gov","orcid":"https://orcid.org/0000-0001-9696-4450","contributorId":2902,"corporation":false,"usgs":true,"family":"Stohlgren","given":"Thomas","email":"stohlgrent@usgs.gov","middleInitial":"J.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":588880,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kumar, Sunil","contributorId":84992,"corporation":false,"usgs":true,"family":"Kumar","given":"Sunil","affiliations":[],"preferred":false,"id":588881,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Morisette, Jeffrey T. 0000-0002-0483-0082 morisettej@usgs.gov","orcid":"https://orcid.org/0000-0002-0483-0082","contributorId":307,"corporation":false,"usgs":true,"family":"Morisette","given":"Jeffrey","email":"morisettej@usgs.gov","middleInitial":"T.","affiliations":[{"id":569,"text":"Southwest Climate Science Center","active":true,"usgs":true},{"id":477,"text":"North Central Climate Science Center","active":true,"usgs":true}],"preferred":true,"id":588882,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Holcombe, Tracy R. holcombet@usgs.gov","contributorId":3694,"corporation":false,"usgs":true,"family":"Holcombe","given":"Tracy","email":"holcombet@usgs.gov","middleInitial":"R.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":588883,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70161998,"text":"70161998 - 2015 - Efficient wetland surface water detection and monitoring via Landsat: Comparison with in situ data from the Everglades Depth Estimation Network","interactions":[],"lastModifiedDate":"2019-12-12T10:54:01","indexId":"70161998","displayToPublicDate":"2016-01-11T16:00:00","publicationYear":"2015","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":"Efficient wetland surface water detection and monitoring via Landsat: Comparison with in situ data from the Everglades Depth Estimation Network","docAbstract":"The U.S. Geological Survey is developing new Landsat science products. One, named Dynamic Surface Water Extent (DSWE), is focused on the representation of ground surface inundation as detected in cloud-/shadow-/snow-free pixels for scenes collected over the U.S. and its territories. Characterization of DSWE uncertainty to facilitate its appropriate use in science and resource management is a primary objective. A unique evaluation dataset developed from data made publicly available through the Everglades Depth Estimation Network (EDEN) was used to evaluate one candidate DSWE algorithm that is relatively simple, requires no scene-based calibration data, and is intended to detect inundation in the presence of marshland vegetation. A conceptual model of expected algorithm performance in vegetated wetland environments was postulated, tested and revised. Agreement scores were calculated at the level of scenes and vegetation communities, vegetation index classes, water depths, and individual EDEN gage sites for a variety of temporal aggregations. Landsat Archive cloud cover attribution errors were documented. Cloud cover had some effect on model performance. Error rates increased with vegetation cover. Relatively low error rates for locations of little/no vegetation were unexpectedly dominated by omission errors due to variable substrates and mixed pixel effects. Examined discrepancies between satellite and in situ modeled inundation demonstrated the utility of such comparisons for EDEN database improvement. Importantly, there seems no trend or bias in candidate algorithm performance as a function of time or general hydrologic conditions, an important finding for long-term monitoring. The developed database and knowledge gained from this analysis will be used for improved evaluation of candidate DSWE algorithms as well as other measurements made on Everglades surface inundation, surface water heights and vegetation using radar, lidar and hyperspectral instruments. Although no other sites have such an extensive in situ network or long-term records, the broader applicability of this and other candidate DSWE algorithms is being evaluated in other wetlands using this work as a guide. Continued interaction among DSWE producers and potential users will help determine whether the measured accuracies are adequate for practical utility in resource management.
","language":"English","publisher":"MDPI","doi":"10.3390/rs70912503","usgsCitation":"Jones, J., 2015, Efficient wetland surface water detection and monitoring via Landsat: Comparison with in situ data from the Everglades Depth Estimation Network: Remote Sensing, v. 9, no. 7, p. 12503-12538, https://doi.org/10.3390/rs70912503.","productDescription":"36 p.","startPage":"12503","endPage":"12538","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-066317","costCenters":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"links":[{"id":471512,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs70912503","text":"Publisher Index Page"},{"id":314188,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Everglades National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -81.331787109375,\n 24.831610355586918\n ],\n [\n -80.31280517578125,\n 24.831610355586918\n ],\n [\n -80.31280517578125,\n 26.561506704037942\n ],\n [\n -81.331787109375,\n 26.561506704037942\n ],\n [\n -81.331787109375,\n 24.831610355586918\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"9","issue":"7","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2015-09-23","publicationStatus":"PW","scienceBaseUri":"5694d22de4b039675d005dc0","contributors":{"authors":[{"text":"Jones, John W. 0000-0001-6117-3691 jwjones@usgs.gov","orcid":"https://orcid.org/0000-0001-6117-3691","contributorId":2220,"corporation":false,"usgs":true,"family":"Jones","given":"John","email":"jwjones@usgs.gov","middleInitial":"W.","affiliations":[{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true},{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":588290,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70159276,"text":"70159276 - 2015 - Accuracy assessment/validation methodology and results of 2010–11 land-cover/land-use data for Pools 13, 26, La Grange, and Open River South, Upper Mississippi River System","interactions":[],"lastModifiedDate":"2017-05-04T10:53:38","indexId":"70159276","displayToPublicDate":"2016-01-11T10:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":5000,"text":"Long Term Resource Monitoring Technical Report","active":true,"publicationSubtype":{"id":1}},"seriesNumber":"2015-T001","title":"Accuracy assessment/validation methodology and results of 2010–11 land-cover/land-use data for Pools 13, 26, La Grange, and Open River South, Upper Mississippi River System","docAbstract":"The U.S. Geological Survey (USGS)-Upper Midwest Environmental Sciences Center (UMESC) was responsible for development of several land cover/land use (LCU) systemic datasets of the Upper Mississippi River System (UMRS). These efforts (1989 and 2000) were funded by the U.S. Army Corps of Engineers’ Upper Mississippi River Restoration Program (UMRR) Long Term Resource Monitoring (LTRM) element. Development of systemic datasets includes the acquisition, processing, and serving of high-resolution aerial photography and land cover/land use spatial datasets (http://www.umesc.usgs.gov/data_library/land_cover_use/land_cover_use_data.html). In 2008, the UMRR reached a collaborative agreement with the U.S. Fish and Wildlife Service-Region 3 to collect high-resolution digital imagery of the entire UMRS floodplain during 2010–11 for LTRM. The UMESC helped acquire, process, and serve this imagery, as well as produce and serve the 2010–11 LCU systemic dataset of the UMRS floodplain. Digital imagery for Pools 13, 26, La Grange, and Open River South was collected using an Applanix DSS 439 digital sensor system with a 40 millimeter lens and Color Infrared (CIR) filter. The imagery was collected at a resolution of 20 centimeters/pixel (8 inches/pixel) for Pool 13 and 40 centimeters/pixel (16 inches/pixel) for Pools 26, Open River South, and La Grange. All imagery was projected to Universal Transverse Mercator (UTM) Zone 15, North American Datum of 1983 (NAD 83). The General Wetland Vegetation Classification (GWVC) system used for mapping is hierarchical, and its 31 classes can be collapsed into broader categories using either a 15- or 7-class level.
\nWhile the 1989 and 2000 LCU systemic datasets have not gone through a traditional thematic accuracy assessment (AA) in the past, nor have they undergone a validation analysis, the end products are of high quality. For each systemic dataset produced (1989, 2000, 2010–11), extensive field reconnaissance is performed before photointerpretation. The intent of this field reconnaissance is to learn, test, and verify image signatures as they relate to vegetation types. Questionable areas on the imagery are visited, and the plants or land features observed in the area are recorded for reference. This procedure verifies vegetation signatures on the imagery with those on the ground. In addition, once the photointerpretation is complete, the final LCU dataset undergoes extensive quality assurance/quality control to ensure the imagery is mapped correctly.
\nSince the 2000 LCU systemic dataset was developed, there has been a growing interest in completing thematic AAs for the LTRM LCU spatial datasets. The objective of an AA is to measure the probability that a particular location has been assigned its correct vegetation class. An AA estimates thematic (map class) errors in the data, giving users information needed to determine data suitability for a particular application. At the same time, data producers are able to learn more about the nature of errors in the data. Thus, the two attributes of an AA are “producers’ accuracy,” which is the probability that an AA point has been mapped correctly (also referred to as an error of omission); and “users’ accuracy,” which is the probability that the map actually represents what was found on the ground (also referred to as error of commission). Producers’ and users’ accuracies can be obtained from the same set of data by using different analyses.
\nAccuracy assessment is an extensive effort that requires seasonal field personnel and equipment, data entry, analyses, and post processing—tasks that are costly and time consuming. The geospatial team at the UMESC has suggested a validation process for understanding the accuracy of the spatial datasets, which will be tested on at least some areas of the UMRS. Validation is not a true verification of map-class type in the field; however, it can provide the user of the map with useful information that is similar to a field AA.
\nSimilar to an AA, validation involves generating random points based on the total area for each map class. However, instead of collecting field data, two or three individuals not involved with the photo-interpretative mapping separately review each of the points onscreen and record a best-fit vegetation type(s) for each site. Once the individual analyses are complete, results are joined together and a comparative analysis is performed. The objective of this initial analysis is to identify areas where the validation results were in agreement (matches) and areas where validation results were in disagreement (mismatches). The two or three individuals then perform an analysis, looking at each mismatched site, and agree upon a final validation class. (If two vegetation types at a specific site appear to be equally prevalent, the validation team is permitted to assign the site two best-fit vegetation types.) Following the validation team’s comparative analysis of vegetation assignments, the data are entered into a database and compared to the mappers’ vegetation assignments. Agreements and disagreements between the map and validation classes are identified, and a contingency table is produced. This document presents the AA processes/results for Pools 13 and La Grange, as well as the validation process/results for Pools 13 and 26 and Open River South.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","usgsCitation":"Jakusz, J., Dieck, J., Langrehr, H., Ruhser, J., and Lubinski, S., 2015, Accuracy assessment/validation methodology and results of 2010–11 land-cover/land-use data for Pools 13, 26, La Grange, and Open River South, Upper Mississippi River System: Long Term Resource Monitoring Technical Report 2015-T001, vi, 46 p.","productDescription":"vi, 46 p.","numberOfPages":"56","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-061221","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":310113,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/mis/ltrmp2015-t001/coverthb.jpg"},{"id":310199,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/mis/ltrmp2015-t001/ltrm2015t001.pdf","text":"Report","size":"1.28 MB","linkFileType":{"id":1,"text":"pdf"},"description":"LTRMP TR2015-T001"}],"country":"United States","state":"Iowa, Illinois, Minnesota, Missouri, Wisconsin","otherGeospatial":"Upper Mississippi River System","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"MultiPolygon\",\"coordinates\":[[[[-87.800477,42.49192],[-87.812461,42.232278],[-87.524844,41.691635],[-87.531646,39.347888],[-87.640435,39.166727],[-87.496537,38.778571],[-87.975511,38.232742],[-88.158207,37.664542],[-88.078046,37.532029],[-88.450127,37.411717],[-88.490068,37.067874],[-89.058036,37.188767],[-89.171881,37.068184],[-89.202607,36.601576],[-89.343753,36.630991],[-89.429311,36.481875],[-89.55264,36.577178],[-89.527029,36.341679],[-89.703511,36.243412],[-89.615128,36.113816],[-89.733095,36.000608],[-90.368718,35.995812],[-90.075934,36.281485],[-90.157136,36.484317],[-94.617919,36.499414],[-94.605734,39.122204],[-95.082714,39.516712],[-94.876344,39.806894],[-95.382957,40.027112],[-95.870481,40.71248],[-95.929889,41.415155],[-96.096186,41.547192],[-96.077543,41.777824],[-96.628741,42.757532],[-96.448134,43.104452],[-96.598396,43.495074],[-96.453049,43.500415],[-96.452948,45.268925],[-96.835451,45.586129],[-96.587093,45.816445],[-96.559271,46.058272],[-96.789572,46.639079],[-96.851293,47.589264],[-97.139497,48.153108],[-97.108655,48.691484],[-97.238387,48.982631],[-95.153711,48.998903],[-95.153314,49.384358],[-94.974286,49.367738],[-94.555835,48.716207],[-93.741843,48.517347],[-92.984963,48.623731],[-92.634931,48.542873],[-92.698824,48.494892],[-92.341207,48.23248],[-92.066269,48.359602],[-91.542512,48.053268],[-90.88548,48.245784],[-90.703702,48.096009],[-89.489226,48.014528],[-90.735927,47.624343],[-92.058888,46.809938],[-92.025789,46.710839],[-91.781928,46.697604],[-90.880358,46.957661],[-90.78804,46.844886],[-90.920813,46.637432],[-90.327548,46.550262],[-89.929158,46.29975],[-88.141001,45.930608],[-88.13364,45.823128],[-87.831442,45.714938],[-87.887828,45.358122],[-87.647454,45.345232],[-87.72796,45.207956],[-87.59188,45.094689],[-87.983065,44.72073],[-87.970702,44.530292],[-87.021088,45.296541],[-87.73063,43.893862],[-87.910172,43.236634],[-87.800477,42.49192]]],[[[-86.880572,45.331467],[-86.956192,45.351179],[-86.82177,45.427602],[-86.880572,45.331467]]]]},\"properties\":{\"name\":\"Iowa\",\"nation\":\"USA \"}}]}","contact":"Upper Midwest Environmental Science Center
2630 Fanta Reed Road
La Crosse, WI 54603
http://www.umesc.usgs.gov/
http://www.umesc.usgs.gov/ltrmp.html
Historical data for nine selected streamgages in southwest and south-central Kansas were used in an assessment of streamflow characteristics and trends. This information is required by the U.S. Fish and Wildlife Service and the Kansas Department of Wildlife, Parks and Tourism to assist with the effective management of Etheostoma cragini (Arkansas darter) habitats and populations in the State. Changing streamflow conditions, such as a reduction or elimination of streamflow, may adversely affect the Arkansas darter. Priority basins for the Arkansas darter represented by the selected streamgages include the Cimarron River, Rattlesnake Creek, the North Fork Ninnescah River, the South Fork Ninnescah River, the Medicine Lodge River, and the Chikaskia River.
\nStreamflow conditions were assessed using annual streamflow characteristics computed for the period of record for each of the selected streamgages. Specific streamflow characteristics computed were mean discharge, mean base flow, 90th-percentile flow, 10th-percentile flow, minimum 7-day mean flow, minimum 28-day mean flow, number of days of flow less than 1 cubic foot per second, and number of zero-flow days.
\nTwo of the priority basins had statistically significant decreases in annual mean discharge during the period of record. In the Cimarron River Basin, there was a pronounced multidecadal decrease in the magnitude and variability of annual mean discharge. Concurrently, the percentage of the annual mean discharge that was contributed by base flow increased. In the Rattlesnake Creek Basin, there was a pre-1985 decrease in annual mean discharge. Typically, in these two basins, significant decreases were indicated for mean base flow, 90th-percentile flow, 10th-percentile flow, minimum 7-day mean flow, and minimum 28-day mean flow. No significant trend in annual mean discharge was indicated for the North Fork Ninnescah, South Fork Ninnescah, Medicine Lodge, and Chikaskia River Basins. For the Medicine Lodge and Chikaskia River Basins as well as the downstream part of the South Fork Ninnescah River Basin, a significant increase in mean base flow and 10th-percentile flow was indicated. Also, for the latter two basins, a significant increase was indicated for minimum 7-day mean flow.
\nFactors investigated to explain long-term trends in annual mean discharge, or lack thereof, included precipitation and groundwater withdrawals. Annual precipitation in the study area varied substantially from 1951 to 2013 with no pronounced long-term trend. Thus, a precipitation-related explanation for the significant decrease in annual mean discharge in the Cimarron River and Rattlesnake Creek Basins was not supported. Because the most pronounced decreases in annual mean discharge were in the basin with the largest groundwater-level declines (that is, the Cimarron River Basin), both in terms of magnitude and areal extent, it is likely that groundwater withdrawals were a primary, if not dominant, causative factor.
\nThe occurrence of extremely low-flow (less than 1 cubic foot per second) and zero-flow days varied by basin and year. Typically, such days occurred in the summer and autumn for all basins.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155167","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service and the Kansas Department of Wildlife, Parks and Tourism","usgsCitation":"Juracek, K.E., 2015, Streamflow characteristics and trends at selected streamgages in southwest and south-central Kansas: U.S. Geological Survey Scientific Investigations Report 2015–5167, 20 p., https://dx.doi.org/10.3133/sir20155167.","productDescription":"vi, 20 p.","numberOfPages":"30","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-065381","costCenters":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"links":[{"id":312557,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5167/sir20155167.pdf","text":"Report","size":"3.05 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015-5167"},{"id":312556,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2015/5167/coverthb.jpg"}],"country":"United States","state":"Kansas","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -102.0465087890625,\n 37.00255267215955\n ],\n [\n -102.0465087890625,\n 38.69408504756833\n ],\n [\n -96.9488525390625,\n 38.69408504756833\n ],\n [\n -96.9488525390625,\n 37.00255267215955\n ],\n [\n -102.0465087890625,\n 37.00255267215955\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Kansas Water Science Center
U.S. Geological Survey
4821 Quail Crest Place
Lawrence, KS 66049
http://ks.water.usgs.gov
The main component of this publication is a geologic map database prepared using geographic information system (GIS) applications. The geodatabase of geologic points, lines, and polygons was produced as a compilation from five adjoining map sections originally published as printed maps in 1987 (see references in metadata). Four of the sections (U.S. Geological Survey Miscellaneous Field Studies Maps MF–1957, MF–1958, MF–1959, MF–1960) were created by scanning and geo-referencing stable base map material consisting of mylar positives. The final section (MF–1956) was compiled by hand tracing an enlargement of the available printed paper base map onto mylar using a #00 rapidograph pen, the mylar positive was then digitally scanned and geo-referenced. This method was chosen because the original basemap materials (mylar positives) for the MF–1956 section were unavailable at the time of this publication. Due to the condition of the available MF–1956 map section used as the base (which had previously been folded) the accuracy within the boundary of the MF–1956 section is presumed to be degraded in certain areas. The locations of the degraded areas and the degree of degradation within these areas is unclear. Final compilation of the database was completed using the ArcScan toolset, and the Editor toolset in ESRI ArcMap 10.1. Polygon topology was created from the lines and labels were added to the resultant geological polygons, lines, and points. Joseph A. Bard and David W. Ramsey updated and corrected the geodatabase, created the metadata and web presence, and provided the GIS-expertise to bring the geodatabase and metadata to completion. Included are links to files to view or print the original map sheets and the accompanying pamphlets.
\nThe orignial geologic maps were prepared under the Geothermal Research Program of the U.S. Geological Survey as a basis for interpreting the history of magmatic activity in the volcanic field. The San Francisco field, which is largely Pleistocene in age, is in northern Arizona, just north of the broad transition zone between the Colorado Plateau and the Basin and Range province. It is one of several dominantly basaltic volcanic fields of the late Cenozoic age situated near the margin of the Colorado Plateau. The volcanic field contains rocks ranging in composition from basalt to rhyolite—the products of eruption through Precambrian basement rocks and approximately a kilometer of overlying, nearly horizontal, Paleozoic and Mesozoic sedimentary rocks. About 500 km3 of erupted rocks cover about 5,000 km2 of predominantly Permian and locally preserved Triassic sedimentary rocks that form the erosionally stripped surface of the Colorado Plateau in Northern Arizona.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds961","usgsCitation":"Bard, J.A., Ramsey, D.W., Wolfe, E.W., Ulrich, G.E., Newhall, C.G., Moore, R.B., Bailey, N.G., and Holm, R.F., 2015, Database compilation for the geologic map of the San Francisco volcanic field, north-central Arizona: U.S. Geological Survey Data Series 961, https://dx.doi.org/10.3133/ds961","productDescription":"Database; Metadata; Read Me","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-053386","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":313858,"rank":8,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/mf1956","text":"Miscellaneous Field Studies Map 1956","linkHelpText":"Geologic map of the SP Mountain part of the San Francisco Volcanic Field, north-central Arizona"},{"id":313859,"rank":9,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/mf1957","text":"Miscellaneous Field Studies Map 1957","linkHelpText":"Geologic map of the northwest part of the San Francisco Volcanic Field, north-central Arizona"},{"id":313860,"rank":10,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/mf1958","text":"Miscellaneous Field Studies Map 1958","linkHelpText":"Geologic map of the southwest part of the San Francisco volcanic field, north-central Arizona"},{"id":313857,"rank":7,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/ds/0961/ds961_metadata_san_francisco_volcanic_field.txt","text":"San Francisco volcanic field"},{"id":314062,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":313851,"rank":1,"type":{"id":9,"text":"Database"},"url":"https://pubs.usgs.gov/ds/0961/ds961_database.zip","text":"Database","size":"162 MB","linkFileType":{"id":6,"text":"zip"}},{"id":313852,"rank":2,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/ds/0961/readme.txt"},{"id":313853,"rank":3,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/ds/0961/ds961_metadata_geolines.txt","text":"Geolines"},{"id":313854,"rank":4,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/ds/0961/ds961_metadata_geounits.txt","text":"Geounits"},{"id":313855,"rank":5,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/ds/0961/ds961_metadata_map_extents.txt","text":"Map extents"},{"id":313856,"rank":6,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/ds/0961/ds961_metadata_sample_points.txt","text":"Sample points"},{"id":313861,"rank":11,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/mf1959","text":"Miscellaneous Field Studies Map 1959","linkHelpText":"Geologic map of the central part of the San Francisco Volcanic Field, north-central Arizona"},{"id":313862,"rank":12,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/mf1960","text":"Miscellaneous Field Studies Map 1960","linkHelpText":"Geologic map of the east part of the San Francisco Volcanic Field, north-central Arizona"},{"id":399132,"rank":14,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_103857.htm"}],"country":"United States","state":"Arizona","otherGeospatial":"San Francisco volcanic field","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -112.4161,\n 35.0761\n ],\n [\n -111.1189,\n 35.0761\n ],\n [\n -111.1189,\n 35.8411\n ],\n [\n -112.4161,\n 35.8411\n ],\n [\n -112.4161,\n 35.0761\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Volcano Hazards Program
U.S. Geological Survey
12201 Sunrise Valley Drive, MS 904
Reston, VA 20192
http://volcanoes.usgs.gov/
An understanding of historic and current water quality is needed to manage and improve aquatic communities within the Blackwater River watershed, WV. The Blackwater River, which historically offered an excellent Salvelinus fontinalis (Brook Trout) fishery, has been affected by logging, coal mining, use of off-road vehicles, and land development. Using information-theoretic methods, we examined trends in water quality at 12 sites in the watershed for the 14 years of 1980–1993. Except for Beaver Creek, downward trends in acidity and upward trends in alkalinity, conductivity, and hardness were consistent with decreases in hydrogen ion concentration. Water-quality trends for Beaver Creek were inconsistent with the other sites and reflect ongoing coal-mining influences. Dissolved oxygen trended downward, possibly due to natural conditions, but remained above thresholds that would be detrimental to aquatic life. Water quality changed only slightly within the watershed from 1980–1993, possibly reflecting few changes in development and land uses during this time. These data serve as a baseline for future water-quality studies and may help to inform management planning.
","language":"English","publisher":"Eagle Hill Institute","doi":"10.1656/058.014.sp711","usgsCitation":"Smith, J., Welsh, S., Anderson, J.T., and Fortney, R.H., 2015, Water quality trends in the Blackwater River watershed, West Virginia: Southeastern Naturalist, v. 14, no. sp7, p. 103-111, https://doi.org/10.1656/058.014.sp711.","productDescription":"9 p.","startPage":"103","endPage":"111","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-053509","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":313997,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"West Virginia","otherGeospatial":"Blackwater River Watershed","volume":"14","issue":"sp7","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"568f8c3ce4b0e7a44bc5ec9c","contributors":{"authors":[{"text":"Smith, Jessica","contributorId":152104,"corporation":false,"usgs":false,"family":"Smith","given":"Jessica","email":"","affiliations":[{"id":16210,"text":"Division of Forestry and Natural Resources, West Virginia University","active":true,"usgs":false}],"preferred":false,"id":587949,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Welsh, Stuart A. 0000-0003-0362-054X swelsh@usgs.gov","orcid":"https://orcid.org/0000-0003-0362-054X","contributorId":152088,"corporation":false,"usgs":true,"family":"Welsh","given":"Stuart A.","email":"swelsh@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":false,"id":587831,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Anderson, James T.","contributorId":28071,"corporation":false,"usgs":false,"family":"Anderson","given":"James","email":"","middleInitial":"T.","affiliations":[{"id":12432,"text":"West Virginia University","active":true,"usgs":false}],"preferred":false,"id":587950,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fortney, Ronald H.","contributorId":37576,"corporation":false,"usgs":false,"family":"Fortney","given":"Ronald","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":587951,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70159573,"text":"pp1821 - 2015 - Flooding in the Northeastern United States, 2011","interactions":[],"lastModifiedDate":"2016-01-06T08:48:31","indexId":"pp1821","displayToPublicDate":"2016-01-05T16:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":331,"text":"Professional Paper","code":"PP","onlineIssn":"2330-7102","printIssn":"1044-9612","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1821","title":"Flooding in the Northeastern United States, 2011","docAbstract":"Flooding in the Northeastern United States during 2011 was widespread and record setting. This report summarizes peak streamflows that were recorded by the U.S. Geological Survey (USGS) during separate flooding events in February, March, April, May, July, August, and September. The flooding of late April, which combined snowmelt and heavy rain and the floods associated with the tropical storms of late August and September, were the most severe and widespread. Precipitation totals from March to May for Pennsylvania, New York, and Vermont were documented as being the highest totals in 117 years of record. In late August, the heavy rains associated with Hurricane Irene produced widespread flooding in many parts of the Northeastern United States, which resulted in damage estimates in excess of $7 billion and approximately 45 deaths. In September, Tropical Storm Lee produced 6–12 inches of rain in parts of the Northeastern United States adding to the growing total of record peak streamflows set in 2011.
\nThe annual exceedance probability (AEP) for 327 streamgages in the Northeastern United States were computed using annual peak streamflow data through 2011 and are included in this report. The 2011 peak streamflow for 129 of those streamgages was estimated to have an AEP of less than or equal to 1 percent. Almost 100 of these peak streamflows were a result of the flooding associated with Hurricane Irene in late August 2011. More extreme than the 1-percent AEP, is the 0.2-percent AEP. The USGS recorded peak streamflows at 31 streamgages that equaled or exceeded the estimated 0.2-percent AEP during 2011. Collectively, the USGS recorded peak streamflows having estimated AEPs of less than 1 percent in Connecticut, Delaware, Maine, Maryland, Massachusetts, Ohio, Pennsylvania, New Hampshire, New Jersey, New York, and Vermont and new period-of-record peak streamflows were recorded at more than 180 streamgages resulting from the floods of 2011.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/pp1821","usgsCitation":"Suro, T.P., Roland, M.A., and Kiah, R.G., 2015, Flooding in the Northeastern United States, 2011: U.S. Geological Survey Professional Paper 1821, 32 p., https://dx.doi.org/10.3133/pp1821.","productDescription":"Report: v, 32 p.; 2 Tables","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-062473","costCenters":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"links":[{"id":313165,"rank":4,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/pp/1821/downloads/pp1821_table2.xlsx","text":"Table 2","size":"80.4 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"Table 2"},{"id":313163,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/pp/1821/pp1821.pdf","text":"Report","size":"16.0 MB","description":"Professional Paper 1821"},{"id":313162,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/pp/1821/coverthb.jpg"},{"id":313164,"rank":3,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/pp/1821/downloads/pp1821_table1.xlsx","text":"Table 1","size":"152 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"Table 1"}],"country":"United States","state":"Connecticut, Delaware, Maine, Maryland, Massachusetts, Ohio, Pennsylvania, New Hampshire, New Jersey, New York, Vermont","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -73.3447265625,\n 45.336701909968106\n ],\n [\n -72.2900390625,\n 45.398449976304086\n ],\n [\n -70.751953125,\n 46.07323062540838\n ],\n [\n -70.1806640625,\n 46.255846818480336\n ],\n [\n -69.6533203125,\n 45.706179285330855\n ],\n [\n -68.8623046875,\n 44.15068115978091\n ],\n [\n -70.224609375,\n 43.03677585761058\n ],\n [\n -70.400390625,\n 42.45588764197166\n ],\n [\n -69.5654296875,\n 42.06560675405716\n ],\n [\n -69.78515625,\n 41.3108238809182\n ],\n [\n -70.400390625,\n 40.91351257612758\n ],\n [\n -71.1474609375,\n 40.88029480552824\n ],\n [\n -72.333984375,\n 40.54720023441049\n ],\n [\n -73.6962890625,\n 40.111688665595956\n ],\n [\n -74.2236328125,\n 39.436192999314095\n ],\n [\n -74.8828125,\n 38.71980474264239\n ],\n [\n -75.05859375,\n 37.85750715625203\n ],\n [\n -75.41015624999999,\n 37.405073750176946\n ],\n [\n -75.849609375,\n 36.914764288955936\n ],\n [\n -76.728515625,\n 36.77409249464195\n ],\n [\n -78.1787109375,\n 36.949891786813296\n ],\n [\n -78.75,\n 37.75334401310656\n ],\n [\n -79.4970703125,\n 38.61687046392973\n ],\n [\n -80.244140625,\n 38.993572058209466\n ],\n [\n -81.2109375,\n 38.993572058209466\n ],\n [\n -81.298828125,\n 38.41055825094609\n ],\n [\n -82.30957031249999,\n 38.47939467327645\n ],\n [\n -83.1884765625,\n 38.71980474264239\n ],\n [\n -83.8037109375,\n 38.47939467327645\n ],\n [\n -84.638671875,\n 38.788345355085625\n ],\n [\n -85.5615234375,\n 38.685509760012\n ],\n [\n -86.044921875,\n 39.36827914916014\n ],\n [\n -85.7373046875,\n 40.48038142908172\n ],\n [\n -85.20996093749999,\n 40.91351257612758\n ],\n [\n -85.341796875,\n 42.00032514831621\n ],\n [\n -84.5068359375,\n 42.293564192170095\n ],\n [\n -83.8037109375,\n 42.35854391749705\n ],\n [\n -83.14453125,\n 42.16340342422401\n ],\n [\n -83.14453125,\n 41.73852846935917\n ],\n [\n -82.30957031249999,\n 41.57436130598913\n ],\n [\n -81.2548828125,\n 41.934976500546604\n ],\n [\n -80.15625,\n 42.391008609205045\n ],\n [\n -79.6728515625,\n 42.71473218539458\n ],\n [\n -79.62890625,\n 43.229195113965005\n ],\n [\n -78.8818359375,\n 43.61221676817573\n ],\n [\n -78.22265625,\n 43.61221676817573\n ],\n [\n -77.783203125,\n 43.929549935614595\n ],\n [\n -77.607421875,\n 44.308126684886126\n ],\n [\n -76.7724609375,\n 44.49650533109348\n ],\n [\n -75.498046875,\n 44.84029065139799\n ],\n [\n -74.8388671875,\n 45.182036837015886\n ],\n [\n -73.3447265625,\n 45.336701909968106\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Chief, Office of Surface Water
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This map and associated digital databases are the result of compilation and interpretation of published and unpublished 1:250,000-scale and limited 1:500,000- to 1:63,360-scale maps. Covering the entire state of Alaska, it reflects more than a century of work by a host of geologists and almost two decades of compilation work. There are two versions of the map: a detailed digital version, and a simplified, “generalized” map for print. The map units described in the accompanying pamphlet reflect those of the detailed digital map. At the end of each unit description, the generalized map unit for that unit is listed.
\nCompilation of this map began in September 1996, using available 1:250,000-scale data to compile and release a regional map of central Alaska (Wilson and others, 1998). An ongoing iterative process was used to describe and correlate individual geologic units to produce the units for this statewide map and its interim products—a series of regional geologic map compilations—which were released as the process continued (in the references cited in the pamphlet that are shown with an *). As additional geologic data were acquired, previously released data, correlations, and interpretations were updated as needed. Compilation of this map was complex, because the original source maps were made by different generations of geologists, mapping with very different ideas. Several of the older maps were completed before the concepts of accreted (suspect) terranes or even plate tectonics existed. On the other hand, some of the more recent maps were so governed by terrane analysis that conventional stratigraphic nomenclature was not used or is obscured. We adopted a traditional stratigraphic approach and avoided use of the sometimes controversial and commonly inconsistently defined or applied terrane terminology.
\nOur decision to adopt a traditional approach is evident in a map that emphasizes the age and lithology of map units, rather than differences among fault-bounded packages of rocks. We did our best to resolve conflicting interpretations and map data from the regional compilations and from the individual source maps in areas where regional compilations had not been produced. We made every effort to preserve the original geologic map information, incorporating, where available, new data, but we were careful to not overinterpret the geologic data. Yet even our willingness to make interpretations and revisions did not enable us in some areas to resolve mapping conflicts or to reconcile different mapping styles. Therefore, there are several areas on the map where map units are separated by “quadrangle boundary faults.” More data and fieldwork may allow resolution of these conflicts.
\nThis Alaska compilation is unique in that it is integrated with a rich database of information provided in the spatial datasets and standalone attribute databases. Within the spatial files every line and polygon is attributed to its original source; the references to these sources are contained in related tables, as well as in stand-alone tables. Additional attributes include typical lithology, geologic setting, and age range for the map units. Also included are tables of radiometric ages.
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Science Center staff
U.S. Geological Survey
4210 University Dr.
Anchorage, AK 99508
Alaska Mineral Resources
Alaska Science Center
Environmental tracers provide information on groundwater age, recharge conditions, and flow processes which can be helpful for evaluating groundwater sustainability and vulnerability. Dissolved noble gas data have proven particularly useful in mountainous terrain because they can be used to determine recharge elevation. However, tracer-derived recharge elevations have not been utilized as calibration targets for numerical groundwater flow models. Herein, we constrain and calibrate a regional groundwater flow model with noble-gas-derived recharge elevations for the first time. Tritium and noble gas tracer results improved the site conceptual model by identifying a previously uncertain contribution of mountain block recharge from the Coast Mountains to an alluvial coastal aquifer in humid southwestern British Columbia. The revised conceptual model was integrated into a three-dimensional numerical groundwater flow model and calibrated to hydraulic head data in addition to recharge elevations estimated from noble gas recharge temperatures. Recharge elevations proved to be imperative for constraining hydraulic conductivity, recharge location, and bedrock geometry, and thus minimizing model nonuniqueness. Results indicate that 45% of recharge to the aquifer is mountain block recharge. A similar match between measured and modeled heads was achieved in a second numerical model that excludes the mountain block (no mountain block recharge), demonstrating that hydraulic head data alone are incapable of quantifying mountain block recharge. This result has significant implications for understanding and managing source water protection in recharge areas, potential effects of climate change, the overall water budget, and ultimately ensuring groundwater sustainability.
","language":"English","publisher":"American Geophysical Union","doi":"10.1002/2015WR017274","usgsCitation":"Doyle, J.M., Gleeson, T., Manning, A.H., and Mayer, K.U., 2015, Using noble gas tracers to constrain a groundwater flow model with recharge elevations: A novel approach for mountainous terrain: Water Resources Research, v. 51, no. 10, p. 8094-8113, https://doi.org/10.1002/2015WR017274.","productDescription":"20 p.","startPage":"8094","endPage":"8113","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-065559","costCenters":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":471513,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2015wr017274","text":"Publisher Index Page"},{"id":313328,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"51","issue":"10","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2015-10-12","publicationStatus":"PW","scienceBaseUri":"568ce932e4b0e7a44bc0f115","contributors":{"authors":[{"text":"Doyle, Jessica M.","contributorId":151068,"corporation":false,"usgs":false,"family":"Doyle","given":"Jessica","email":"","middleInitial":"M.","affiliations":[{"id":18175,"text":"Waterline Resources Inc., Nanaimo, British Columbia, Canada","active":true,"usgs":false}],"preferred":false,"id":584241,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gleeson, Tom","contributorId":81041,"corporation":false,"usgs":true,"family":"Gleeson","given":"Tom","email":"","affiliations":[],"preferred":false,"id":584242,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Manning, Andrew H. 0000-0002-6404-1237 amanning@usgs.gov","orcid":"https://orcid.org/0000-0002-6404-1237","contributorId":1305,"corporation":false,"usgs":true,"family":"Manning","given":"Andrew","email":"amanning@usgs.gov","middleInitial":"H.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":584240,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mayer, K. Ulrich","contributorId":151069,"corporation":false,"usgs":false,"family":"Mayer","given":"K.","email":"","middleInitial":"Ulrich","affiliations":[{"id":18176,"text":"Department of Earth and Ocean Science, University of British Columbia, Vancouver, British Columbia, Canada","active":true,"usgs":false}],"preferred":false,"id":584243,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ]}