The United States Geological Survey’s (USGS) Planetary Geologic Map Coordination Group (Flagstaff, Ariz.) surveyed planetary geoscience map makers and users to determine the importance, relevance, and usability of such products to their planetary science research and to current and future needs of the planetary science community. This survey was prepared because the planetary science community lacks a modern assessment of the value invested in geoscience map products and processes (including the diverse scientific and technical personnel who add to and maintain this infrastructure) and a strategy that ensures these efforts appropriately prioritize mapping efforts across all solid surface bodies in the Solar System.
A 30-question survey was conducted through an online questionnaire and was designed to (1) take <10 minutes, (2) instill a sense that responses would be acted upon, and (3) encourage community participation through a user-friendly interface. The survey made a distinction between “standardized” geoscience maps (those published by the USGS that require adherence to specific cartographic standards, conventions, and principles) and “non-standardized” geoscience maps (those published by other venues such as peer-reviewed journals that are not required to, but might, adhere to some cartographic standards, conventions, and principles). The survey was opened on Sunday, March 18, 2017 (to coincide with the annual Lunar and Planetary Science Conference in The Woodlands, Tex.) and was closed on Thursday, May 25, 2017. There was a total of 265 unique responses that were formulated into 17 unique findings that were matched with one or more recommendations to be addressed by the planetary science community.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191012","usgsCitation":"Skinner, J.A. Jr., Huff, A.E., Fortezzo, C.M., Gaither, T., Hare, T.M., Hunter, M.A., Buban, H., 2019, Planetary geologic mapping—program status and future needs: U.S. Geological Survey Open-File Report 2019–1012, 40 p., https://doi.org/10.3133/ofr20191012","productDescription":"vi, 39 p.","numberOfPages":"50","onlineOnly":"Y","ipdsId":"IP-102821","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":361568,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1012/ofr20191012.pdf","text":"Report","size":"1.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019-1012"},{"id":361567,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1012/coverthb.jpg"}],"contact":"Astrogeology Science Center
U.S. Geological Survey
2255 N. Gemini Dr.
Flagstaff, AZ 86001
Black huckleberries (Vaccinium membranaceum) provide a critical food resource to many wildlife species, including apex omnivores such as the grizzly bear (Ursus arctos), and play an important socioeconomic role for many communities in western North America, especially indigenous peoples. Remote sensing imagery offers the potential for accurate landscape-level mapping of huckleberries because the shrub changes colour seasonally. We developed two methods, for local and regional scales, to map a shrub species using leaf seasonal colour change from remote sensing imagery. We assessed accuracy with ground-based vegetation surveys. The high-resolution supervised random forest classification from one-meter resolution National Agricultural Imagery Program (NAIP) imagery achieved an overall accuracy of 75.31% (kappa = 0.26). The approach using multi-temporal 30-meter Landsat imagery similarly had an overall accuracy of 79.19% (kappa = .31). We found underprediction error was related to higher forest cover and a lack of visible colour change on the ground in some plots. Where forest cover was low, both models performed better. In areas with <10% forest cover, the high-resolution classification achieved an accuracy of 80.73% (kappa = 0.48), while the Landsat model had an accuracy of 82.55% (kappa = 0.47). Based on the fine-scale predictions, we found that 94% of huckleberry shrubs identified in our study area of Glacier National Park, Montana, USA are over 100 meters from human recreation trails. This information could be combined with productivity and phenology information to estimate the timing and availability of food resources for wildlife and to provide managers with a tool to identify and manage huckleberries. The development of the multi-temporal Landsat models sets the stage for assessment of impacts of disturbance at regional scales on this ecologically, culturally, and economically important shrub species. Our approach to map huckleberries is straightforward, efficient and accessible to wildlife and environmental managers and researchers in diverse fields.
","language":"English","publisher":"Taylor & Francis","doi":"10.1080/01431161.2019.1580819","usgsCitation":"Shores, C.R., Mikle, N., and Graves, T.A., 2019, Mapping a keystone shrub species, huckleberry (Vaccinium membranaceum), using seasonal colour change in the Rocky Mountains: International Journal of Remote Sensing, v. 40, no. 15, p. 5695-5715, https://doi.org/10.1080/01431161.2019.1580819.","productDescription":"21 p.","startPage":"5695","endPage":"5715","ipdsId":"IP-095407","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":384206,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Montana","otherGeospatial":"Glacier National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -113.961181640625,\n 48.31060120649363\n ],\n [\n -112.939453125,\n 48.242967421301366\n ],\n [\n -113.65631103515625,\n 48.99103162515999\n ],\n [\n -114.81536865234374,\n 49.005447494058096\n ],\n [\n -114.5050048828125,\n 48.545705491847464\n ],\n [\n -114.15618896484375,\n 48.35989909002194\n ],\n [\n -113.961181640625,\n 48.31060120649363\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"40","issue":"15","noUsgsAuthors":false,"publicationDate":"2019-02-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Shores, Carolyn R.","contributorId":254828,"corporation":false,"usgs":false,"family":"Shores","given":"Carolyn","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":811433,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mikle, Nathaniel 0000-0002-6529-8210 nmikle@usgs.gov","orcid":"https://orcid.org/0000-0002-6529-8210","contributorId":177026,"corporation":false,"usgs":true,"family":"Mikle","given":"Nathaniel","email":"nmikle@usgs.gov","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":811434,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Graves, Tabitha A. 0000-0001-5145-2400 tgraves@usgs.gov","orcid":"https://orcid.org/0000-0001-5145-2400","contributorId":5898,"corporation":false,"usgs":true,"family":"Graves","given":"Tabitha","email":"tgraves@usgs.gov","middleInitial":"A.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":811435,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70202376,"text":"70202376 - 2019 - Applying concepts of general resilience to large river ecosystems: A case study from the Upper Mississippi and Illinois rivers","interactions":[],"lastModifiedDate":"2019-02-26T15:01:06","indexId":"70202376","displayToPublicDate":"2019-02-26T15:01:02","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1456,"text":"Ecological Indicators","active":true,"publicationSubtype":{"id":10}},"title":"Applying concepts of general resilience to large river ecosystems: A case study from the Upper Mississippi and Illinois rivers","docAbstract":"Large floodplain-river ecosystems are often highly modified to provide services that society desires, yet these modifications can limit an ecosystem’s ability to adapt to changing conditions. The adaptive capacity of an ecosystem, its general resilience, is a conceptual framework for considering how a system will respond to such changes. We sought to apply aspects of three general resilience principles (diversity and redundancy, connectivity, and controlling variables) to our understanding of floodplain-river ecosystem structure and function. We demonstrate the applicability of this approach in a case study of the Upper Mississippi River System (UMRS). In doing so, we developed ten indicators that highlight important structural and functional aspects of this floodplain-river ecosystem, and likely underlie the capacity of large rivers to cope with environmental change and disturbance. We developed diversity and redundancy indicators for aquatic habitats, patterns of floodplain inundation, and fish communities. Connectivity indicators included metrics of longitudinal and lateral connections. Controlling variable indicators included deviations from historic water surface elevation fluctuations, water clarity, nutrient concentrations, and aquatic invasive species. This set of indicators provides a simple description of the adaptive capacity of four distinct reaches of the UMRS: Upper Impounded, Lower Impounded, Unimpounded Reaches of the Upper Mississippi River and the entire Illinois River. High aquatic habitat diversity and redundancy, fish functional diversity and redundancy, and water clarity, and the scarcity of invasive fish species are all factors that likely contribute to the high general resilience of the Upper Impounded Reach. However, the limited longitudinal connectivity and establishment of a minimum water level for navigation are factors that may inhibit the general resilience of this reach. In the Lower Impounded Reach, there is high within-reach variability for individual indicators such as aquatic habitat diversity, fish functional diversity and redundancy, and longitudinal and lateral connectivity. In the Unimpounded Reach, a high degree of longitudinal connectivity likely enhances its general resilience, but low aquatic habitat diversity, low lateral connectivity, and relatively high number of invasive fish species inhibit general resilience. For the Illinois River Reach, the relatively high fish functional diversity and redundancy likely contributes to its general resilience, whereas high number of invasive fish species, low water clarity, low lateral connectivity, and high range of water levels may inhibit general resilience. Indicators derived from application of concepts of general resilience provide insight into the current coping capacity of the UMRS and identify opportunities for enhancing resilience.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolind.2019.02.002","usgsCitation":"Bouska, K.L., Houser, J.N., De Jager, N.R., Van Appledorn, M., and Rogala, J.T., 2019, Applying concepts of general resilience to large river ecosystems: A case study from the Upper Mississippi and Illinois rivers: Ecological Indicators, v. 101, p. 1094-1110, https://doi.org/10.1016/j.ecolind.2019.02.002.","productDescription":"7 p.","startPage":"1094","endPage":"1110","ipdsId":"IP-099227","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":437559,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9J8BBQ3","text":"USGS data release","linkHelpText":"Percentage of annual days that river stage exceeds 'open river' conditions for lock and dams on the Upper Mississippi River, 1985-2015"},{"id":361559,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Upper Mississippi River System","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -93.31787109374999,\n 36.87962060502676\n ],\n [\n -87.51708984375,\n 36.87962060502676\n ],\n [\n -87.51708984375,\n 45.01141864227728\n ],\n [\n -93.31787109374999,\n 45.01141864227728\n ],\n [\n -93.31787109374999,\n 36.87962060502676\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"101","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Bouska, Kristen L. 0000-0002-4115-2313 kbouska@usgs.gov","orcid":"https://orcid.org/0000-0002-4115-2313","contributorId":178005,"corporation":false,"usgs":true,"family":"Bouska","given":"Kristen","email":"kbouska@usgs.gov","middleInitial":"L.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":758091,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Houser, Jeffrey N. 0000-0003-3295-3132 jhouser@usgs.gov","orcid":"https://orcid.org/0000-0003-3295-3132","contributorId":2769,"corporation":false,"usgs":true,"family":"Houser","given":"Jeffrey","email":"jhouser@usgs.gov","middleInitial":"N.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":758092,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"De Jager, Nathan R. 0000-0002-6649-4125 ndejager@usgs.gov","orcid":"https://orcid.org/0000-0002-6649-4125","contributorId":3717,"corporation":false,"usgs":true,"family":"De Jager","given":"Nathan","email":"ndejager@usgs.gov","middleInitial":"R.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":758093,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Van Appledorn, Molly 0000-0002-8029-0014","orcid":"https://orcid.org/0000-0002-8029-0014","contributorId":205785,"corporation":false,"usgs":true,"family":"Van Appledorn","given":"Molly","email":"","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":758094,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rogala, James T. 0000-0002-1954-4097 jrogala@usgs.gov","orcid":"https://orcid.org/0000-0002-1954-4097","contributorId":2651,"corporation":false,"usgs":true,"family":"Rogala","given":"James","email":"jrogala@usgs.gov","middleInitial":"T.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":758095,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70202387,"text":"70202387 - 2019 - Disease‐structured N‐mixture models: A practical guide to model disease dynamics using count data","interactions":[],"lastModifiedDate":"2019-02-26T14:14:42","indexId":"70202387","displayToPublicDate":"2019-02-26T14:14:38","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Disease‐structured N‐mixture models: A practical guide to model disease dynamics using count data","docAbstract":"Obtaining inferences on disease dynamics (e.g., host population size, pathogen prevalence, transmission rate, host survival probability) typically requires marking and tracking individuals over time. While multistate mark–recapture models can produce high‐quality inference, these techniques are difficult to employ at large spatial and long temporal scales or in small remnant host populations decimated by virulent pathogens, where low recapture rates may preclude the use of mark–recapture techniques. Recently developed N‐mixture models offer a statistical framework for estimating wildlife disease dynamics from count data. N‐mixture models are a type of state‐space model in which observation error is attributed to failing to detect some individuals when they are present (i.e., false negatives). The analysis approach uses repeated surveys of sites over a period of population closure to estimate detection probability. We review the challenges of modeling disease dynamics and describe how N‐mixture models can be used to estimate common metrics, including pathogen prevalence, transmission, and recovery rates while accounting for imperfect host and pathogen detection. We also offer a perspective on future research directions at the intersection of quantitative and disease ecology, including the estimation of false positives in pathogen presence, spatially explicit disease‐structured N‐mixture models, and the integration of other data types with count data to inform disease dynamics. Managers rely on accurate and precise estimates of disease dynamics to develop strategies to mitigate pathogen impacts on host populations. At a time when pathogens pose one of the greatest threats to biodiversity, statistical methods that lead to robust inferences on host populations are critically needed for rapid, rather than incremental, assessments of the impacts of emerging infectious diseases.
","language":"English","publisher":"Wiley","doi":"10.1002/ece3.4849","usgsCitation":"DiRenzo, G.V., Che-Castaldo, C., Saunders, S.P., Campbell Grant, E.H., and Zipkin, E.F., 2019, Disease‐structured N‐mixture models: A practical guide to model disease dynamics using count data: Ecology and Evolution, v. 9, no. 2, p. 899-909, https://doi.org/10.1002/ece3.4849.","productDescription":"11 p.","startPage":"899","endPage":"909","ipdsId":"IP-099044","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":467871,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.4849","text":"Publisher Index Page"},{"id":361552,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"9","issue":"2","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2019-02-05","publicationStatus":"PW","contributors":{"authors":[{"text":"DiRenzo, Graziella V.","contributorId":192177,"corporation":false,"usgs":false,"family":"DiRenzo","given":"Graziella","email":"","middleInitial":"V.","affiliations":[],"preferred":false,"id":758142,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Che-Castaldo, Christian","contributorId":202588,"corporation":false,"usgs":false,"family":"Che-Castaldo","given":"Christian","email":"","affiliations":[{"id":36488,"text":"Stony Brook University","active":true,"usgs":false}],"preferred":false,"id":758143,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Saunders, Sarah P.","contributorId":192752,"corporation":false,"usgs":false,"family":"Saunders","given":"Sarah","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":758144,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Campbell Grant, Evan H. 0000-0003-4401-6496 ehgrant@usgs.gov","orcid":"https://orcid.org/0000-0003-4401-6496","contributorId":150443,"corporation":false,"usgs":true,"family":"Campbell Grant","given":"Evan","email":"ehgrant@usgs.gov","middleInitial":"H.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":758141,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Zipkin, Elise F. 0000-0003-4155-6139","orcid":"https://orcid.org/0000-0003-4155-6139","contributorId":192755,"corporation":false,"usgs":false,"family":"Zipkin","given":"Elise","email":"","middleInitial":"F.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":758145,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70201177,"text":"sir20185145 - 2019 - Catchment-level estimates of nitrogen and phosphorus agricultural use from commercial fertilizer sales for the conterminous United States, 2012","interactions":[],"lastModifiedDate":"2019-02-27T11:51:29","indexId":"sir20185145","displayToPublicDate":"2019-02-26T12:06:29","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2018-5145","displayTitle":"Catchment-Level Estimates of Nitrogen and Phosphorus Agricultural Use from Commercial Fertilizer Sales for the Conterminous United States, 2012","title":"Catchment-level estimates of nitrogen and phosphorus agricultural use from commercial fertilizer sales for the conterminous United States, 2012","docAbstract":"Nutrient inputs from commercial agricultural fertilizer, particularly nitrogen and phosphorus, are important factors contributing to the degradation of surface-water quality and the alteration of aquatic ecosystems. Despite this importance, information about the application of fertilizer to agricultural land is not available in a consistent manner across the United States at a scale useful for regional water-quality assessment. To address this need, an approach is developed to relate commercial fertilizer sales to a set of explanatory variables using spatially referenced modeling methods. Spatially referenced modeling in this study refers to statistically relating fertilizer use, estimated from commercial fertilizer sales data, to spatially referenced data on watershed attributes. Separate models for nitrogen and phosphorus are developed to estimate elemental fertilizer use on agricultural lands for the conterminous United States at the National Hydrography Dataset Plus (NHDPlus) catchment scale for the year 2012. The approach builds on earlier efforts that use Association of American Plant Food Control Officials data on fertilizer sales to provide county-level estimates of nitrogen and phosphorus fertilizer use. The spatially referenced method improves on these efforts by allowing for varying nitrogen to phosphorus ratios at the catchment scale and expanding the set of variables used to allocate county-level sales data to the catchment scale. The models include catchment-level factors that are either primary determinants of fertilizer use, such as the acreage of different crop types, or measures reflecting the intensity of use, such as climate. Explanatory variables available only at the county scale, such as U.S. Department of Agriculture Census of Agriculture estimates of fertilizer expenditures, are included to improve the model predictions of elemental use. The nitrogen and phosphorus models explain more than 90 percent of the variation in elemental use at the state level, and the statistical approach allows for the estimation of uncertainty of predicted use in each catchment. The spatial patterns of model predictions reflect known agricultural cropping practices across the United States that transcend political boundaries, despite the county/state orientation of the fertilizer sales information. The results are expected to be useful for a variety of water-quality assessments that are intended to estimate nitrogen and phosphorus loads to streams.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185145","usgsCitation":"Stewart, J.S., Schwarz, G.E., Brakebill, J.W., and Preston, S.D., 2019, Catchment-level estimates of nitrogen and phosphorus agricultural use from commercial fertilizer sales for the conterminous United States, 2012: U.S. Geological Survey Scientific Investigations Report 2018–5145, 52 p., https://doi.org/10.3133/sir20185145.","productDescription":"Report: x, 52 p.; Data releases","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-092916","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":361425,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5145/sir20185145.pdf","text":"Report","size":"54.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 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U.S. Geological Survey
8505 Research Way
Middleton, Wisconsin 53562
We examined Golden Eagle (Aquila chrysaetos) brood survival in relation to spring temperatures and exposure of nests to afternoon sun in southwestern Idaho from 1970 through 2012. Most (77%) nests classified as shaded in a subset of 96 nests had northwest to east aspects, and most (71%) nests classified as exposed had south to west aspects. We analyzed survival of 1154 Golden Eagle broods in 64 territories. Golden Eagle brood survival at shaded and exposed nests did not differ when the daily maximum temperature was <32.2°C. Survival in exposed nests declined as the number of days with maximum temperature ≥32.2°C increased, but survival in shaded nests did not change. All broods survived from hatching to fledging age in eight exposed nests with artificial shade structures installed over a 6-yr period. During the same period, 7 of 42 broods in nests without shade structures failed to reach fledging age, with two failures (29%) attributed to thermal stress. Use of artificial shade structures in exposed nests may reduce or prevent mortality caused by heat stress, and thus might be a potential tool for mitigation of “take” from anthropogenic structures and activities. Additional experimentation under an adaptive management framework could provide more information about the effectiveness of using shade structures to offset nestling mortality associated with increasing temperatures predicted by climate change models.
","language":"English","publisher":"The Raptor Research Foundation","doi":"10.3356/JRR-17-100","usgsCitation":"Kochert, M.N., Steenhof, K., and Brown, J.L., 2019, Effects of nest exposure and spring temperatures on golden eagle brood survival: An opportunity for mitigation: Journal of Raptor Research, v. 53, no. 1, p. 91-97, https://doi.org/10.3356/JRR-17-100.","productDescription":"7 p.","startPage":"91","endPage":"97","ipdsId":"IP-093510","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":362249,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho","otherGeospatial":" Morley Nelson Snake River Birds of Prey National Conservation Area ","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -116.33148193359375,\n 43.100982876188546\n ],\n [\n -116.01287841796874,\n 43.100982876188546\n ],\n [\n -116.01287841796874,\n 43.27320591705845\n ],\n [\n -116.33148193359375,\n 43.27320591705845\n ],\n [\n -116.33148193359375,\n 43.100982876188546\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"53","issue":"1","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Kochert, Michael N. 0000-0002-4380-3298 mkochert@usgs.gov","orcid":"https://orcid.org/0000-0002-4380-3298","contributorId":3037,"corporation":false,"usgs":true,"family":"Kochert","given":"Michael","email":"mkochert@usgs.gov","middleInitial":"N.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":true,"id":759650,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Steenhof, Karen karen_steenhof@usgs.gov","contributorId":203439,"corporation":false,"usgs":false,"family":"Steenhof","given":"Karen","email":"karen_steenhof@usgs.gov","affiliations":[],"preferred":false,"id":759651,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brown, Jessi L.","contributorId":44817,"corporation":false,"usgs":false,"family":"Brown","given":"Jessi","email":"","middleInitial":"L.","affiliations":[{"id":13184,"text":"Program in Ecology, Evolution and Conservation Biology, University of Nevada","active":true,"usgs":false}],"preferred":false,"id":759652,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70202362,"text":"70202362 - 2019 - Modeling riparian restoration impacts on the hydrologic cycle at the Babacomari Ranch, SE Arizona, USA","interactions":[],"lastModifiedDate":"2019-02-25T13:49:06","indexId":"70202362","displayToPublicDate":"2019-02-25T13:49:03","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3709,"text":"Water","active":true,"publicationSubtype":{"id":10}},"title":"Modeling riparian restoration impacts on the hydrologic cycle at the Babacomari Ranch, SE Arizona, USA","docAbstract":"This paper describes coupling field experiments with surface and groundwater modeling to investigate rangelands of SE Arizona, USA using erosion-control structures to augment shallow and deep aquifer recharge. We collected field data to describe the physical and hydrological properties before and after gabions (caged riprap) were installed in an ephemeral channel. The modular finite-difference flow model is applied to simulate the amount of increase needed to raise groundwater levels. We used the average increase in infiltration measured in the field and projected on site, assuming all infiltration becomes recharge, to estimate how many gabions would be needed to increase recharge in the larger watershed. A watershed model was then applied and calibrated with discharge and 3D terrain measurements, to simulate flow volumes. Findings were coupled to extrapolate simulations and quantify long-term impacts of riparian restoration. Projected scenarios demonstrate how erosion-control structures could impact all components of the annual water budget. Results support the potential of watershed-wide gabion installation to increase total aquifer recharge, with models portraying increased subsurface connectivity and accentuated lateral flow contributions.
","language":"English","publisher":"MDPI","doi":"10.3390/w11020381","usgsCitation":"Norman, L., Callegary, J.B., Lacher, L., Wilson, N., Fandel, C., Forbes, B.T., and Swetnam, T., 2019, Modeling riparian restoration impacts on the hydrologic cycle at the Babacomari Ranch, SE Arizona, USA: Water, v. 11, no. 2, p. 1-20, https://doi.org/10.3390/w11020381.","productDescription":"Article 381; 20 p.","startPage":"1","endPage":"20","ipdsId":"IP-090323","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":467872,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/w11020381","text":"Publisher Index Page"},{"id":361505,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"Babacomari Ranch","volume":"11","issue":"2","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2019-02-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Norman, Laura M. 0000-0002-3696-8406","orcid":"https://orcid.org/0000-0002-3696-8406","contributorId":203300,"corporation":false,"usgs":true,"family":"Norman","given":"Laura M.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":757998,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Callegary, James B. 0000-0003-3604-0517 jcallega@usgs.gov","orcid":"https://orcid.org/0000-0003-3604-0517","contributorId":2171,"corporation":false,"usgs":true,"family":"Callegary","given":"James","email":"jcallega@usgs.gov","middleInitial":"B.","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":757999,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lacher, Laurel","contributorId":213547,"corporation":false,"usgs":false,"family":"Lacher","given":"Laurel","affiliations":[{"id":38785,"text":"Lacher Hydrological Consulting, Tucson, AZ 85719","active":true,"usgs":false}],"preferred":false,"id":758000,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wilson, Natalie R. 0000-0001-5145-1221","orcid":"https://orcid.org/0000-0001-5145-1221","contributorId":202534,"corporation":false,"usgs":true,"family":"Wilson","given":"Natalie R.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":758001,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fandel, Chloé","contributorId":213548,"corporation":false,"usgs":false,"family":"Fandel","given":"Chloé","affiliations":[{"id":38786,"text":"University of Arizona, Hydrology and Water Resources, Tucson, AZ 85719","active":true,"usgs":false}],"preferred":false,"id":758002,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Forbes, Brandon T. 0000-0003-4051-0593 bforbes@usgs.gov","orcid":"https://orcid.org/0000-0003-4051-0593","contributorId":213549,"corporation":false,"usgs":true,"family":"Forbes","given":"Brandon","email":"bforbes@usgs.gov","middleInitial":"T.","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":758003,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Swetnam, Tyson","contributorId":213550,"corporation":false,"usgs":false,"family":"Swetnam","given":"Tyson","email":"","affiliations":[{"id":38787,"text":"University of Arizona , BIO5 Institute, Tucson, AZ 85719","active":true,"usgs":false}],"preferred":false,"id":758004,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70202345,"text":"70202345 - 2019 - Optimizing historic preservation under climate change: Decision support for cultural resource adaptation planning in national parks","interactions":[],"lastModifiedDate":"2019-02-25T13:44:39","indexId":"70202345","displayToPublicDate":"2019-02-25T13:44:34","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2599,"text":"Land Use Policy","active":true,"publicationSubtype":{"id":10}},"title":"Optimizing historic preservation under climate change: Decision support for cultural resource adaptation planning in national parks","docAbstract":"Climate change poses great challenges for cultural resource management, particularly in coastal areas. Cultural resources, such as historic buildings, in coastal areas are vulnerable to climate impacts including inundation, deterioration, and destruction from sea-level rise and storm-related flooding and erosion. However, research that assesses the trade-offs between actions for protecting vulnerable and valuable cultural resources under budgetary constraints is limited. This study focused on developing a decision support model for managing historic buildings at Cape Lookout National Seashore. We designed the Optimal Preservation Decision Support (OptiPres) model to: (a) identify optimal, annual adaptation actions for historic buildings across a 30-year planning horizon, (b) quantify trade-offs between different actions and the timing of adaptation actions under constrained budgets, and (c) estimate the effectiveness of budget allocations on the resource value of historic buildings. Our analysis of the model suggests that: (1) funding allocation thresholds may exist for national parks to maintain the historical significance and use potential of historic buildings under climate change, (2) the quantitative assessment of trade-offs among alternative adaptation actions provides generalizable guidance for decision makers about the dynamics of their managed system, and (3) the OptiPres model can identify cost-efficient approaches to allocate funding to maintain the historical value of buildings vulnerable to the effects of climate change. Therefore, the OptiPres model, while not designed as a prescriptive decision tool, allows managers to understand the consequences of proposed adaptation actions. The OptiPres model can guide park managers to make cost-effective climate adaptation decisions for historic buildings more transparently and robustly.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.landusepol.2019.02.011","usgsCitation":"Xiao, X., Seekamp, E., Post van der Burg, M., Eaton, M.J., Fatoric, S., and McCreary, A., 2019, Optimizing historic preservation under climate change: Decision support for cultural resource adaptation planning in national parks: Land Use Policy, v. 83, p. 379-389, https://doi.org/10.1016/j.landusepol.2019.02.011.","productDescription":"11 p.","startPage":"379","endPage":"389","ipdsId":"IP-102168","costCenters":[{"id":565,"text":"Southeast Climate Science Center","active":true,"usgs":true}],"links":[{"id":467873,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.landusepol.2019.02.011","text":"Publisher Index Page"},{"id":361504,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"83","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Xiao, Xiao","contributorId":212835,"corporation":false,"usgs":false,"family":"Xiao","given":"Xiao","email":"","affiliations":[{"id":13595,"text":"NCSU","active":true,"usgs":false}],"preferred":false,"id":757944,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Seekamp, Erin","contributorId":212832,"corporation":false,"usgs":false,"family":"Seekamp","given":"Erin","email":"","affiliations":[{"id":13595,"text":"NCSU","active":true,"usgs":false}],"preferred":false,"id":757945,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Post van der Burg, Max 0000-0002-3943-4194 maxpostvanderburg@usgs.gov","orcid":"https://orcid.org/0000-0002-3943-4194","contributorId":4947,"corporation":false,"usgs":true,"family":"Post van der Burg","given":"Max","email":"maxpostvanderburg@usgs.gov","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":757946,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Eaton, Mitchell J. 0000-0001-7324-6333","orcid":"https://orcid.org/0000-0001-7324-6333","contributorId":213526,"corporation":false,"usgs":true,"family":"Eaton","given":"Mitchell","middleInitial":"J.","affiliations":[{"id":565,"text":"Southeast Climate Science Center","active":true,"usgs":true}],"preferred":true,"id":757943,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fatoric, Sandra","contributorId":212834,"corporation":false,"usgs":false,"family":"Fatoric","given":"Sandra","email":"","affiliations":[{"id":13595,"text":"NCSU","active":true,"usgs":false}],"preferred":false,"id":757947,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"McCreary, Allie","contributorId":212836,"corporation":false,"usgs":false,"family":"McCreary","given":"Allie","email":"","affiliations":[{"id":13595,"text":"NCSU","active":true,"usgs":false}],"preferred":false,"id":757948,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70202357,"text":"70202357 - 2019 - Modeling δ18O as an early indicator of regime shift arising from salinity stress in coastal vegetation","interactions":[],"lastModifiedDate":"2019-06-18T10:22:04","indexId":"70202357","displayToPublicDate":"2019-02-25T13:41:36","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1923,"text":"Hydrogeology Journal","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Modeling δ18O as an early indicator of regime shift arising from salinity stress in coastal vegetation","title":"Modeling δ18O as an early indicator of regime shift arising from salinity stress in coastal vegetation","docAbstract":"In many important coastal habitats, a combination of increasing soil salinization due to sea level rise, reduced precipitation and storm surges may induce regime shift from salinity-intolerant glycophytic vegetation to salinity-tolerant halophytic species. Early detection of regime shift due to salinity stress in vegetation may facilitate conservation efforts. It has been shown that the 18O value of water in the xylem of trees can be used as a surrogate for salinity in the rooting zone of plants. Coupling measured δ18O values in the tree xylem with simulated δ18O values in trees and salinity in the vadose zone can be used to investigate competitive responses of glycophytic versus halophytic trees. MANTRA-O18 simulations suggest that the impacts of salinization on diminishing the resilience of salinity-intolerant trees can be detected up to 25 years before the glycophytic trees are threatened with regime shift to halophytic species. This early detection provides critical lead time and valuable information and insights useful for planning adaptation strategy to mitigate against the adverse impacts of sea level rise and climate change.
","language":"English","publisher":"Springer","doi":"10.1007/s10040-019-01930-3","usgsCitation":"Teh, S.Y., Koh, H.L., DeAngelis, D.L., Voss, C.I., and da Silveira Lobo Sternberg, L., 2019, Modeling δ18O as an early indicator of regime shift arising from salinity stress in coastal vegetation: Hydrogeology Journal, v. 27, no. 4, p. 1257-1276, https://doi.org/10.1007/s10040-019-01930-3.","productDescription":"10 p.","startPage":"1257","endPage":"1276","ipdsId":"IP-095257","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":361502,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"27","issue":"4","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2019-02-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Teh, Su Yean","contributorId":202650,"corporation":false,"usgs":false,"family":"Teh","given":"Su","email":"","middleInitial":"Yean","affiliations":[{"id":36510,"text":"School of Mathematicla Sciences, Universiti Sains Malaysia","active":true,"usgs":false}],"preferred":false,"id":757975,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Koh, Hock Lye","contributorId":202651,"corporation":false,"usgs":false,"family":"Koh","given":"Hock","email":"","middleInitial":"Lye","affiliations":[{"id":36511,"text":"Sunway University Business School, Jalan Universiti, Malaysia","active":true,"usgs":false}],"preferred":false,"id":757976,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"DeAngelis, Donald L. 0000-0002-1570-4057 don_deangelis@usgs.gov","orcid":"https://orcid.org/0000-0002-1570-4057","contributorId":148065,"corporation":false,"usgs":true,"family":"DeAngelis","given":"Donald","email":"don_deangelis@usgs.gov","middleInitial":"L.","affiliations":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":757974,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Voss, Clifford I. 0000-0001-5923-2752 cvoss@usgs.gov","orcid":"https://orcid.org/0000-0001-5923-2752","contributorId":1559,"corporation":false,"usgs":true,"family":"Voss","given":"Clifford","email":"cvoss@usgs.gov","middleInitial":"I.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":757977,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"da Silveira Lobo Sternberg, Leonel","contributorId":206740,"corporation":false,"usgs":false,"family":"da Silveira Lobo Sternberg","given":"Leonel","email":"","affiliations":[{"id":13532,"text":"Department of Biology, University of Miami","active":true,"usgs":false}],"preferred":false,"id":757978,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70201029,"text":"sir20185159 - 2019 - California’s exposure to volcanic hazards","interactions":[],"lastModifiedDate":"2019-12-10T12:19:03","indexId":"sir20185159","displayToPublicDate":"2019-02-25T05:35:49","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2018-5159","displayTitle":"California’s Exposure to Volcanic Hazards","title":"California’s exposure to volcanic hazards","docAbstract":"The potential for damaging earthquakes, landslides, floods, tsunamis, and wildfires is widely recognized in California. The same cannot be said for volcanic eruptions, despite the fact that they occur in the state about as frequently as the largest earthquakes on the San Andreas Fault. At least ten eruptions have taken place in the past 1,000 years, and future volcanic eruptions are inevitable.
The U.S. Geological Survey’s (USGS) national volcanic threat assessment identifies eight young volcanic areas in California as moderate, high, or very high threat. Of the eight volcanic areas that exist in California, molten rock resides beneath at least seven of these—Medicine Lake volcano, Mount Shasta, Lassen Volcanic Center, Clear Lake volcanic field, the Long Valley volcanic region, Coso volcanic field, and Salton Buttes—and are therefore considered “active” volcanoes producing volcanic earthquakes, toxic gas emissions, hot springs, geothermal systems, and (or) ground movement.
The USGS California Volcano Observatory in Menlo Park, California, monitors these potentially hazardous volcanoes to help communities and government authorities understand, prepare for, and respond to volcanic activity. Although volcanic activity can sometimes be forecast, eruptions, like earthquakes or tsunamis, cannot be prevented. Understanding the hazards and identifying what and who is in harm’s way is the first step in mitigating volcanic risk and building community resilience to volcanic hazards.
This report, which was prepared in collaboration with the California Governor’s Office of Emergency Services and the California Geological Survey, provides a broad perspective on the state’s exposure to volcanic hazards by integrating volcanic hazard information with geospatial data on at-risk populations, infrastructure, and resources. This information is intended to prompt site- and sector-specific vulnerability analyses and preparation of hazard mitigation and response plans.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185159","collaboration":"Prepared in cooperation with the California Governor’s Office of Emergency Services and the California Geological Survey","usgsCitation":"Mangan, M., Ball, J., Wood, N., Jones, J.L., Peters, J., Abdollahian, N., Dinitz, L., Blankenheim, S., Fenton, J., and Pridmore, C., 2019, California’s exposure to volcanic hazards (ver. 1.1, December 2019): U.S. Geological Survey Scientific Investigations Report 2018–5159, 49 p., https://doi.org/10.3133/sir20185159.","productDescription":"Report: vi, 49 p.; 2 Appendixes","numberOfPages":"58","ipdsId":"IP-092973","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":370069,"rank":4,"type":{"id":25,"text":"Version 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\"}}]}","contact":"Volcano Science Center
U.S. Geological Survey
345 Middlefield Road, MS 910
Menlo Park, CA 94025
In 2016, the U.S. Geological Survey, in cooperation with Pikes Peak Regional Water Authority and the Colorado Water Conservation Board, began a study to modernize a Fortran transit-loss accounting program developed by the U.S. Geological Survey to estimate net reusable flows in Fountain and Monument Creeks in El Paso and Pueblo Counties, Colorado. More than 6,000 lines of this FORTRAN77 transit-loss accounting program were revised to comply with the newer Fortran 2003 standard. The upgrade to the newer standard involved making changes in formatting and syntax on each line and, when available, adding new programming constructs that comply with the new standard. These upgrades produced a more readable Fortran program that includes safeguards to prevent accidental mistyping of variables and unintentional changes in named constants during program execution. Program revisions also introduced dynamic array allocation, whole array processing, and handling of input errors to the upgraded transit-loss accounting program.
During the upgrade from FORTRAN77 to the Fortran 2003 standard, revisions were made incrementally to the original transit-loss Fortran program. Because FORTRAN77 is a subset of Fortran 2003, the legacy FORTRAN77 statements and the upgraded Fortran 2003 statements can be compiled within the same program, permitting program revisions to be gradually phased in on a line-by-line basis. This incremental approach helped mitigate risks of introducing logic errors into the Fortran program that could produce incorrect transit-loss estimates.
Verification of the upgraded transit-loss accounting program focused on reproducing archived reusable return flows (RRF) for historical daily runs from January 5, 2015, to October 31, 2018. Because interim files storing daily streambank losses were not historically archived, no record of antecedent streambank storage losses to hydraulically connected alluvial deposits were available to provide initial conditions for each daily run. To overcome the problem of missing historical bank storage and recovery files that contain important information relating to antecedent streambank storage conditions, a 104-day “spin-up” period was required before RRFs calculated by the upgraded program and the original program matched. Estimated daily reusable return flows from archived output generated by the original program and output generated by the upgraded program were compared after this initial “spin-up” period. Daily reusable return flow estimates at delivery nodes and at the bottoms of subreaches from the upgraded Fortran program matched those output by the original program to within 0.01 and 0.0001 cubic feet per second, respectively.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185163","collaboration":"Prepared in cooperation with the Pikes Peak Regional Water Authority and the Colorado Water Conservation Board","usgsCitation":"Colarullo, S.J., and Miller, L.D., 2019, Upgrades to a Fortran program for estimating stream transit losses of reusable water, El Paso and Pueblo Counties, Colorado: U.S. Geological Survey Scientific Investigations Report 2018–5163, 21 p., https://doi.org/10.3133/sir20185163.","productDescription":"Report: vi, 21 p.; 1 Sheet (14 x 26 inches)","numberOfPages":"32","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-101530","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":361220,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5163/sir20185163.pdf","text":"Report","size":"3.95 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018-5163"},{"id":361462,"rank":4,"type":{"id":22,"text":"Related Work"},"url":" https://code.usgs.gov/water/Transit-Loss","text":"Water- Transit Loss","linkHelpText":"- FORTRAN 77 transit-loss accounting program"},{"id":361221,"rank":3,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2018/5163/sir20185163_plate01.pdf","size":"316 KB"},{"id":361219,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5163/coverthb.jpg"}],"country":"United States","state":"Colorado","city":"El Paso, Pueblo","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -105.26687622070312,\n 38.151837403006766\n ],\n [\n -104.3536376953125,\n 38.151837403006766\n ],\n [\n -104.3536376953125,\n 39.102357437817595\n ],\n [\n -105.26687622070312,\n 39.102357437817595\n ],\n [\n -105.26687622070312,\n 38.151837403006766\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Colorado Water Science Center
U.S. Geological Survey
Denver Federal Center, MS-415
Lakewood, CO 80225
The benefits nature provides to people, called ecosystem services, are increasingly recognized and accounted for in assessments of infrastructure development, agricultural management, conservation prioritization, and sustainable sourcing. These assessments are often limited by data, however, a gap with tremendous potential to be filled through Earth observations (EO), which produce a variety of data across spatial and temporal extents and resolutions. Despite widespread recognition of this potential, in practice few ecosystem service studies use EO. Here, we identify challenges and opportunities to using EO in ecosystem service modeling and assessment. Some challenges are technical, related to data awareness, processing, and access. These challenges require systematic investment in model platforms and data management. Other challenges are more conceptual but still systemic; they are byproducts of the structure of existing ecosystem service models and addressing them requires scientific investment in solutions and tools applicable to a wide range of models and approaches. We also highlight new ways in which EO can be leveraged for ecosystem service assessments, identifying promising new areas of research. More widespread use of EO for ecosystem service assessment will only be achieved if all of these types of challenges are addressed. This will require non-traditional funding and partnering opportunities from private and public agencies to promote data exploration, sharing, and archiving. Investing in this integration will be reflected in better and more accurate ecosystem service assessments worldwide.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2019.02.150","usgsCitation":"Ramirez-Reyes, C., Brauman, K.A., Chaplin-Kramer, R., Galford, G.L., Adamo, S.B., Anderson, C.B., Anderson, C., Allington, G.R., Bagstad, K.J., Coe, M.T., Cord, A.F., Dee, L.E., Gould, R.K., Jain, M., Kowal, V.A., Muller-Karger, F.E., Norriss, J., Potapov, P.V., Qui, J., Rieb, J.T., Robinson, B.E., Samberg, L.H., Singh, N., Szeto, S.H., Voigt, B., Watson, K., and Wright, T.M., 2019, Reimagining the potential of Earth observations for ecosystem service assessments: Science of the Total Environment, v. 665, p. 1053-1063, https://doi.org/10.1016/j.scitotenv.2019.02.150.","productDescription":"11 p.","startPage":"1053","endPage":"1063","ipdsId":"IP-103295","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":467876,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2019.02.150","text":"Publisher Index Page"},{"id":361470,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"665","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Ramirez-Reyes, Carlos 0000-0002-7407-071X","orcid":"https://orcid.org/0000-0002-7407-071X","contributorId":213446,"corporation":false,"usgs":false,"family":"Ramirez-Reyes","given":"Carlos","email":"","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":757742,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brauman, Kate A.","contributorId":190423,"corporation":false,"usgs":false,"family":"Brauman","given":"Kate","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":757743,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Chaplin-Kramer, Rebecca 0000-0002-1539-5231","orcid":"https://orcid.org/0000-0002-1539-5231","contributorId":213447,"corporation":false,"usgs":false,"family":"Chaplin-Kramer","given":"Rebecca","email":"","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":757744,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Galford, Gillian L. 0000-0003-2192-7385","orcid":"https://orcid.org/0000-0003-2192-7385","contributorId":213448,"corporation":false,"usgs":false,"family":"Galford","given":"Gillian","email":"","middleInitial":"L.","affiliations":[{"id":13253,"text":"University of Vermont","active":true,"usgs":false}],"preferred":false,"id":757745,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Adamo, Susana B. 0000-0002-9168-7172","orcid":"https://orcid.org/0000-0002-9168-7172","contributorId":213449,"corporation":false,"usgs":false,"family":"Adamo","given":"Susana","email":"","middleInitial":"B.","affiliations":[{"id":7171,"text":"Columbia University","active":true,"usgs":false}],"preferred":false,"id":757746,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Anderson, Christopher B. 0000-0001-7392-4368","orcid":"https://orcid.org/0000-0001-7392-4368","contributorId":213450,"corporation":false,"usgs":false,"family":"Anderson","given":"Christopher","email":"","middleInitial":"B.","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":757747,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Anderson, Clarissa 0000-0001-5970-0253","orcid":"https://orcid.org/0000-0001-5970-0253","contributorId":213451,"corporation":false,"usgs":false,"family":"Anderson","given":"Clarissa","email":"","affiliations":[{"id":34004,"text":"Scripps Institute of Oceanography","active":true,"usgs":false}],"preferred":false,"id":757748,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Allington, Ginger R. 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We used data from 41 park-wide line transect surveys in 2009 and 2014 and multi-season occupancy models with multi-species data to explore trends in species richness and distribution of individual species and factors affecting these trends in Nyungwe National Park (NNP), Rwanda. Mammalian species richness and the distributional range of 5 of the 7 species increased between 2009 and 2014 in NNP. The probability of colonization of a species into a new area in 2014, where it was not present in 2009, was highest in sites with a lower probability of poaching activity, close to tourist trails, and at lower elevations. The probability of colonization with no poaching activity was about 50% but dropped to about 10% with a 100% chance of poaching activity. Duiker species had the largest increase in distribution during the study, while there was a decrease in the distribution of the eastern chimpanzee and blue monkey. Our results suggest that increased patrols should be implemented in areas of the park with low species richness and areas with a low probability of occurrence for species of conservation concern to combat poaching activity and thus increase the probability of a species moving into a new area. Our use of a single multi-season model for multiple species explicitly accounts for imperfect detection and species-specific identities, while allowing for inferences to be made about rarely detected species by sharing covariates with common species. These results can be used to improve conservation planning in NNP for species management and ranger patrol protocols and our modelling framework is broadly applicable to any protected area with presence/absence species field data.","language":"English","publisher":"Wiley","doi":"10.1111/acv.12491","usgsCitation":"Moore, J.F., Hines, J.E., and Masozera, M.K., 2019, Factors affecting species richness and distribution spatially and temporally within a protected area using multi-season occupancy models: Animal Conservation, v. 22, no. 5, p. 503-514, https://doi.org/10.1111/acv.12491.","productDescription":"12 p.","startPage":"503","endPage":"514","ipdsId":"IP-098950","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":368106,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Rwanda","otherGeospatial":"Nyungwe Forest National Park","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[30.4191,-1.13466],[30.81613,-1.69891],[30.75831,-2.28725],[30.4697,-2.41386],[29.93836,-2.34849],[29.63218,-2.91786],[29.02493,-2.83926],[29.11748,-2.29221],[29.25483,-2.21511],[29.29189,-1.62006],[29.57947,-1.34131],[29.82152,-1.44332],[30.4191,-1.13466]]]},\"properties\":{\"name\":\"Rwanda\"}}]}","volume":"22","issue":"5","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2019-02-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Moore, Jennifer F.","contributorId":189122,"corporation":false,"usgs":false,"family":"Moore","given":"Jennifer","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":772590,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hines, James E. 0000-0001-5478-7230 jhines@usgs.gov","orcid":"https://orcid.org/0000-0001-5478-7230","contributorId":146530,"corporation":false,"usgs":true,"family":"Hines","given":"James","email":"jhines@usgs.gov","middleInitial":"E.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":772589,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Masozera, Michel K.","contributorId":201300,"corporation":false,"usgs":false,"family":"Masozera","given":"Michel","email":"","middleInitial":"K.","affiliations":[{"id":35968,"text":"Wildlife Conservation Society, Rwanda Program","active":true,"usgs":false}],"preferred":false,"id":772591,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70202314,"text":"70202314 - 2019 - Assessing lek attendance of male greater sage‐grouse using fine‐resolution GPS data: Implications for population monitoring of lek mating grouse","interactions":[],"lastModifiedDate":"2021-04-16T19:30:05.818684","indexId":"70202314","displayToPublicDate":"2019-02-21T16:56:50","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3103,"text":"Population Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Assessing lek attendance of male greater sage‐grouse using fine‐resolution GPS data: Implications for population monitoring of lek mating grouse","docAbstract":"Counts of males displaying on breeding grounds are the primary management tool used to assess population trends in lekking grouse species. Despite the importance of male lek attendance (i.e., proportion of males on leks available for detection) influencing lek counts, patterns of within season and between season variability in attendance rates are not well understood. We used high‐frequency global positioning system (GPS) telemetry data from male greater sage‐grouse (Centrocercus urophasianus; n = 67) over five lekking seasons (2013–2017) at eight study sites in Nevada to estimate lek attendance rates. Specifically, we recorded daily locations of sage‐grouse in relation to mapped lek boundaries and used generalized additive models to assess temporal variation in attendance rates by age class (subadult vs. adult). Average timing of peak attendance occurred on 16 April but varied from March 16, 2014 to April 21 , 2016. Overall, adult males attended leks at higher rates (0.683 at peak) and earlier in the season (19 March) than subadults (0.421 at peak on April 19). Peak attendance probability was positively related to cumulative winter precipitation. Daily probabilities of lek switching differed between adults (0.019 at peak on March 3) and subadults (0.046 at peak on March 22), and lek switching was negatively related to distance to nearest lek. Our results indicate variable patterns in lek attendance through time, and that lek switching may occur at higher rates than previously thought. We demonstrate the use of generalizable daily attendance curves to date‐correct lek counts and derive estimates of male abundance, although such an approach will likely require the incorporation of information on age structure to produce robust results that are useful for population monitoring.
","language":"English","publisher":"Wiley","doi":"10.1002/1438-390X.1019","usgsCitation":"Wann, G.T., Coates, P.S., Prochazka, B.G., Severson, J.P., Monroe, A., and Aldridge, C., 2019, Assessing lek attendance of male greater sage‐grouse using fine‐resolution GPS data: Implications for population monitoring of lek mating grouse: Population Ecology, v. 61, no. 2, p. 183-197, https://doi.org/10.1002/1438-390X.1019.","productDescription":"15 p.","startPage":"183","endPage":"197","ipdsId":"IP-098337","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":467880,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/1438-390x.1019","text":"Publisher Index Page"},{"id":361440,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nevada","volume":"61","issue":"2","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2019-02-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Wann, Gregory T. 0000-0001-9076-7819 wanng@usgs.gov","orcid":"https://orcid.org/0000-0001-9076-7819","contributorId":3855,"corporation":false,"usgs":true,"family":"Wann","given":"Gregory","email":"wanng@usgs.gov","middleInitial":"T.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":757781,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Coates, Peter S. 0000-0003-2672-9994 pcoates@usgs.gov","orcid":"https://orcid.org/0000-0003-2672-9994","contributorId":3263,"corporation":false,"usgs":true,"family":"Coates","given":"Peter","email":"pcoates@usgs.gov","middleInitial":"S.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":757780,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Prochazka, Brian G. 0000-0001-7270-5550 bprochazka@usgs.gov","orcid":"https://orcid.org/0000-0001-7270-5550","contributorId":174839,"corporation":false,"usgs":true,"family":"Prochazka","given":"Brian","email":"bprochazka@usgs.gov","middleInitial":"G.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":757782,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Severson, John P. 0000-0002-1754-6689","orcid":"https://orcid.org/0000-0002-1754-6689","contributorId":213469,"corporation":false,"usgs":true,"family":"Severson","given":"John","email":"","middleInitial":"P.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":757783,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Monroe, Adrian P. 0000-0003-0934-8225 amonroe@usgs.gov","orcid":"https://orcid.org/0000-0003-0934-8225","contributorId":152209,"corporation":false,"usgs":true,"family":"Monroe","given":"Adrian P.","email":"amonroe@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":757784,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Aldridge, Cameron L. 0000-0003-3926-6941","orcid":"https://orcid.org/0000-0003-3926-6941","contributorId":213471,"corporation":false,"usgs":false,"family":"Aldridge","given":"Cameron L.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":757785,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70202234,"text":"ofr20171064 - 2019 - Evaluation of recommended revisions to Bulletin 17B","interactions":[],"lastModifiedDate":"2019-02-22T10:08:21","indexId":"ofr20171064","displayToPublicDate":"2019-02-21T15:45:00","publicationYear":"2019","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":"2017-1064","displayTitle":"Evaluation of Recommended Revisions to Bulletin 17B","title":"Evaluation of recommended revisions to Bulletin 17B","docAbstract":"For the past 36 years, Bulletin 17B, published by the Interagency Committee on Water Data in 1982, has guided flood-frequency analyses in the United States. During this period, much has been learned about both hydrology and statistical methods. In keeping with the tradition of periodically updating the Bulletin 17B guidelines in light of advances in our understanding and methods, the Hydrologic Frequency Analysis Work Group (HFAWG) was charged by the Subcommittee on Hydrology (SOH) of the Advisory Committee on Water Information (ACWI) to consider possible updates to Bulletin 17B.
The purpose of this report is to consider the statistical performance of possible revisions to Bulletin 17B procedures. Of particular interest are procedures designed to accommodate more general forms of flood information. The concern is how the proposed procedures would affect the precision, accuracy and robustness of flood-frequency estimates. The investigations reported here focus on techniques for the following:
The proposed changes, which mostly involve generalizing Bulletin 17B’s method-of-moments procedures by using the Expected Moments Algorithm (EMA), are relatively modest, at least in the sense that they would not affect the main features of Bulletin 17B. The proposed methods include the following:
The hydrological literature already provides extensive support for the theory behind the proposed changes. The remaining question is practical: How well do the proposed methods perform under typical and realistic conditions and, specifically, with difficult records occasionally encountered in practice? In order to answer these questions, the HFAWG commissioned the work reported here. The following four major sets of results are provided:
Collectively, these studies provide a reasonably comprehensive, valid, and robust assessment of the properties of the Bulletin 17B methods and proposed alternatives. The experiments and analysis indicate that the flood quantile estimators, proposed as a revision of Bulletin 17B, do the following:
Chief, Analysis and Prediction Branch
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Recent information reporting Pink-footed Shearwater Ardenna creatopus mortality from fisheries bycatch throughout its range has encouraged fisheries managers in Chile to evaluate and consider shearwater foraging behaviors to better evaluate risk. In response, we tracked six chickrearing adult Pink-footed Shearwaters from Isla Mocha, off south-central Chile, from 19 to 28 March 2015 using global positioning sensors and time-depth recorders. We recorded seven complete trips averaging 4.2 ± 2.5 d (mean ± SD). Chick-provisioning adults foraged within 334 km (i.e., 175 ± 100 km) of Isla Mocha. Dives (n = 515) occurred throughout the measured foraging range but most frequently occurred within 5–30 km from the mainland coast, in continental shelf waters north of Valdivia. Other regions with diving behavior were within ~20 km of Isla Mocha, and from Lebu to north of Talcahuano. Based on movement behavior analysis, adults spent most of their time at sea “resting/ foraging” (62% ± 6%), with the remainder spent “searching” (16% ± 4%) and “transiting” (20% ± 5%). The proportions of total number of dives associated with these three behaviors were similar. On average, dives were relatively shallow (1.6 ± 1.2 m, maximum depth = 10.1 m) and brief (4.7 ± 4.8 s, maximum duration = 25.7 s). Dives occurred during the day, at night, and at twilight, with most activity occurring at twilight and during the day. Although based on a small sample size, our results may be useful for informing modifications to fishing gear or fisheries policy to reduce the likelihood of bycatch and thus meet Chilean conservation goals for Pink-footed Shearwaters.
","language":"English","publisher":"Pacific Seabird Group","usgsCitation":"Adams, J., Felis, J.J., Czapanskiy, M., Carle, R., and Hodum, P., 2019, Diving behavior of Pink-footed Shearwaters Ardenna creatopus rearing chicks on Isla Mocha, Chile: Marine Ornithology: Journal of Seabird Research and Conservation, v. 47, p. 17-24.","productDescription":"8 p.","startPage":"17","endPage":"24","ipdsId":"IP-092421","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":361421,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":361414,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.marineornithology.org/content/get.cgi?rn=1286"}],"country":"Chile","otherGeospatial":"Isla Mocha","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -74.5,\n -40\n ],\n [\n -73,\n -40\n ],\n [\n -73,\n -38\n ],\n [\n -74.5,\n -38\n ],\n [\n -74.5,\n -40\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"47","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Adams, Josh 0000-0003-3056-925X","orcid":"https://orcid.org/0000-0003-3056-925X","contributorId":213442,"corporation":false,"usgs":true,"family":"Adams","given":"Josh","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":757734,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Felis, Jonathan J. 0000-0002-0608-8950 jfelis@usgs.gov","orcid":"https://orcid.org/0000-0002-0608-8950","contributorId":4825,"corporation":false,"usgs":true,"family":"Felis","given":"Jonathan","email":"jfelis@usgs.gov","middleInitial":"J.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":757735,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Czapanskiy, Max 0000-0002-6302-905X","orcid":"https://orcid.org/0000-0002-6302-905X","contributorId":207793,"corporation":false,"usgs":false,"family":"Czapanskiy","given":"Max","email":"","affiliations":[{"id":37635,"text":"San Fransciso State University","active":true,"usgs":false}],"preferred":false,"id":757736,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Carle, Ryan D.","contributorId":213443,"corporation":false,"usgs":false,"family":"Carle","given":"Ryan D.","affiliations":[{"id":25597,"text":"Oikonos Ecosystem Knowledge","active":true,"usgs":false}],"preferred":false,"id":757737,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hodum, Peter J.","contributorId":213444,"corporation":false,"usgs":false,"family":"Hodum","given":"Peter J.","affiliations":[{"id":25597,"text":"Oikonos Ecosystem Knowledge","active":true,"usgs":false}],"preferred":false,"id":757738,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70202299,"text":"70202299 - 2019 - Geophysical Characterization of the heat source in the Northwest Geysers, California","interactions":[],"lastModifiedDate":"2019-02-21T13:50:42","indexId":"70202299","displayToPublicDate":"2019-02-21T13:50:37","publicationYear":"2019","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Geophysical Characterization of the heat source in the Northwest Geysers, California","docAbstract":"The Geysers, in northern California, is the largest energy producing geothermal field in the world. Looking to expand capacity, the operator Calpine Corporation developed an anomalously hot (~400 °C at 2.5 km depth) part of the field in the northwest Geysers, including testing of an enhanced geothermal systems (EGS). Though the area is anomalously hot, geophysical methods have failed to adequately image any inferred magmatic heat source. Gravity measurements were collected and jointly modeled with existing magnetic data along a two-dimensional profile aligned with an existing geologic cross-section. The key feature of the potential field model is a low-density, low-susceptibility body below the EGS at 5 km depth. Magnetotelluric (MT) measurements were collected around the northwest Geysers and modeled in three-dimensions to characterize subsurface resistivity structure. The resistivity model images an extension of a Quaternary granitic pluton locally known as “the felsite” under the EGS project and a possible zone of partial melt (<10%) below 7 km in the northwestern part of the field.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings, 44th Workshop on Geothermal Reservoir Engineering","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"44th Workshop on Geothermal Reservoir Engineering","conferenceDate":"February 11-13, 2019","conferenceLocation":"Stanford, CA","language":"English","publisher":"Stanford University","usgsCitation":"Peacock, J., Mangan, M.T., Walters, M., Hartline, C., Glen, J.M., Earney, T.E., and Schermerhorn, W.D., 2019, Geophysical Characterization of the heat source in the Northwest Geysers, California, in Proceedings, 44th Workshop on Geothermal Reservoir Engineering, Stanford, CA, February 11-13, 2019, 7 p.","productDescription":"7 p.","ipdsId":"IP-104721","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":361416,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":361392,"type":{"id":11,"text":"Document"},"url":"https://pangea.stanford.edu/ERE/db/GeoConf/papers/SGW/2019/Peacock.pdf"}],"country":"United States","state":"California","otherGeospatial":"Northwest Geysers","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.9,\n 38.75\n ],\n [\n -122.75,\n 38.75\n ],\n [\n -122.75,\n 38.9\n ],\n [\n -122.9,\n 38.9\n ],\n [\n -122.9,\n 38.75\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Peacock, Jared R. 0000-0002-0439-0224","orcid":"https://orcid.org/0000-0002-0439-0224","contributorId":210082,"corporation":false,"usgs":true,"family":"Peacock","given":"Jared R.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":757698,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mangan, Margaret T. 0000-0002-5273-8053 mmangan@usgs.gov","orcid":"https://orcid.org/0000-0002-5273-8053","contributorId":3343,"corporation":false,"usgs":true,"family":"Mangan","given":"Margaret","email":"mmangan@usgs.gov","middleInitial":"T.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true}],"preferred":true,"id":757699,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Walters, Mark 0000-0001-8458-4813","orcid":"https://orcid.org/0000-0001-8458-4813","contributorId":213428,"corporation":false,"usgs":false,"family":"Walters","given":"Mark","email":"","affiliations":[{"id":38755,"text":"Calpine","active":true,"usgs":false}],"preferred":false,"id":757700,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hartline, Craig","contributorId":213429,"corporation":false,"usgs":false,"family":"Hartline","given":"Craig","email":"","affiliations":[{"id":38755,"text":"Calpine","active":true,"usgs":false}],"preferred":false,"id":757701,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Glen, Jonathan M.G. 0000-0002-3502-3355 jglen@usgs.gov","orcid":"https://orcid.org/0000-0002-3502-3355","contributorId":176530,"corporation":false,"usgs":true,"family":"Glen","given":"Jonathan","email":"jglen@usgs.gov","middleInitial":"M.G.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":309,"text":"Geology and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":757702,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Earney, Tait E. 0000-0002-1504-0457","orcid":"https://orcid.org/0000-0002-1504-0457","contributorId":210080,"corporation":false,"usgs":true,"family":"Earney","given":"Tait","email":"","middleInitial":"E.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":757703,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Schermerhorn, William D. 0000-0002-0167-378X","orcid":"https://orcid.org/0000-0002-0167-378X","contributorId":210081,"corporation":false,"usgs":true,"family":"Schermerhorn","given":"William","email":"","middleInitial":"D.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":757704,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70202304,"text":"70202304 - 2019 - Rupture model of the M5.8 Pawnee, Oklahoma earthquake from regional and teleseismic waveforms","interactions":[],"lastModifiedDate":"2019-06-18T10:18:55","indexId":"70202304","displayToPublicDate":"2019-02-21T13:01:29","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Rupture model of the M5.8 Pawnee, Oklahoma earthquake from regional and teleseismic waveforms","docAbstract":"The 2016 M5.8 Pawnee, Oklahoma earthquake is the largest earthquake to have been induced by wastewater disposal. We infer the coseismic slip history from analysis of apparent source time functions and inversion of regional and teleseismic P‐waveforms, using aftershocks as empirical Green's functions. The earthquake nucleated on the shallow part of the fault, initially rupturing towards the surface, followed shortly thereafter by slip deeper on the fault. Deeper slip occurred below the aftershocks and at greater depths than most induced seismicity in the region, suggesting that small‐ to moderate‐sized earthquakes may not occur on deeper parts of faults in Oklahoma because they are further from failure than shallower fault sections. Comparisons with models of pore pressure perturbations further suggest that the earthquake may have initiated within a region of higher pore pressure perturbation but was not confined to this zone. These observations inform source physics and understanding of maximum magnitudes.
","language":"English","publisher":"AGU","doi":"10.1029/2018GL081364","usgsCitation":"Moschetti, M.P., Hartzell, S.H., and Herrmann, R.B., 2019, Rupture model of the M5.8 Pawnee, Oklahoma earthquake from regional and teleseismic waveforms: Geophysical Research Letters, v. 46, no. 5, p. 2494-2502, https://doi.org/10.1029/2018GL081364.","productDescription":"9 p.","startPage":"2494","endPage":"2502","ipdsId":"IP-104842","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":361410,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oklahoma","city":"Pawnee","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -96.82697296142577,\n 36.31388025820415\n ],\n [\n -96.77753448486328,\n 36.31388025820415\n ],\n [\n -96.77753448486328,\n 36.35522760439977\n ],\n [\n -96.82697296142577,\n 36.35522760439977\n ],\n [\n -96.82697296142577,\n 36.31388025820415\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"46","issue":"5","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2019-03-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Moschetti, Morgan P. 0000-0001-7261-0295 mmoschetti@usgs.gov","orcid":"https://orcid.org/0000-0001-7261-0295","contributorId":1662,"corporation":false,"usgs":true,"family":"Moschetti","given":"Morgan","email":"mmoschetti@usgs.gov","middleInitial":"P.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":757716,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hartzell, Stephen H. 0000-0003-0858-9043 shartzell@usgs.gov","orcid":"https://orcid.org/0000-0003-0858-9043","contributorId":2594,"corporation":false,"usgs":true,"family":"Hartzell","given":"Stephen","email":"shartzell@usgs.gov","middleInitial":"H.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":757717,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Herrmann, R. B.","contributorId":213436,"corporation":false,"usgs":false,"family":"Herrmann","given":"R.","email":"","middleInitial":"B.","affiliations":[{"id":37518,"text":"St. Louis University","active":true,"usgs":false}],"preferred":false,"id":757718,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70202301,"text":"70202301 - 2019 - Estimating sand concentrations using ADCP‐based acoustic inversion in a large fluvial system characterized by bi‐modal suspended‐sediment distributions","interactions":[],"lastModifiedDate":"2019-06-18T10:16:40","indexId":"70202301","displayToPublicDate":"2019-02-21T11:11:58","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1425,"text":"Earth Surface Processes and Landforms","active":true,"publicationSubtype":{"id":10}},"title":"Estimating sand concentrations using ADCP‐based acoustic inversion in a large fluvial system characterized by bi‐modal suspended‐sediment distributions","docAbstract":"Quantifying sediment flux within rivers is a challenge for many disciplines due, mainly, to difficulties inherent to traditional sediment sampling methods. These methods are operationally complex, high cost, and high risk. Additionally, the resulting data provide a low spatial and temporal resolution estimate of the total sediment flux, which has impeded advances in the understanding of the hydro‐geomorphic characteristics of rivers. Acoustic technologies have been recognized as a leading tool for increasing the resolution of sediment data by relating their echo intensity level measurements to suspended sediment. Further effort is required to robustly test and develop these techniques across a wide range of conditions found in natural river systems. This article aims to evaluate the application of acoustic inversion techniques using commercially available, down‐looking acoustic Doppler current profilers (ADCPs) in quantifying suspended sediment in a large sand bed river with varying bi‐modal particle size distributions, wash load and suspended‐sand ratios, and water stages. To achieve this objective, suspended sediment was physically sampled along the Paraná River, Argentina, under various hydro‐sedimentological regimes. Two ADCPs emitting different sound frequencies were used to simultaneously profile echo intensity level within the water column. Using the sonar equation, calibrations were determined between suspended‐sand concentrations and acoustic backscatter to solve the inverse problem. The study also analyzed the roles played by each term of the sonar equation, such as ADCP frequency, power supply, instrument constants, and particle size distributions typically found in sand bed rivers, on sediment attenuation and backscatter. Calibrations were successfully developed between corrected backscatter and suspended‐sand concentrations for all sites and ADCP frequencies, resulting in mean suspended‐sand concentration estimates within about 40% of the mean sampled concentrations. Noise values, calculated using the sonar equation and sediment sample characteristics, were fairly constant across evaluations, suggesting that they could be applied to other sand bed rivers.
","language":"English","publisher":"Wiley","doi":"10.1002/esp.4572","usgsCitation":"Szupiany, R.N., Lopez Weibel, C., Guerrero, M., Latosinski, F., Wood, M.S., Dominguez Ruben, L., and Oberg, K., 2019, Estimating sand concentrations using ADCP‐based acoustic inversion in a large fluvial system characterized by bi‐modal suspended‐sediment distributions: Earth Surface Processes and Landforms, v. 44, no. 6, p. 1295-1308, https://doi.org/10.1002/esp.4572.","productDescription":"14 p.","startPage":"1295","endPage":"1308","ipdsId":"IP-100807","costCenters":[{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true}],"links":[{"id":467884,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1002/esp.4572","text":"External Repository"},{"id":361404,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Argentina","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -60.934295654296875,\n -32.11514862261243\n ],\n [\n -60.29296874999999,\n -32.11514862261243\n ],\n [\n -60.29296874999999,\n -31.421631960419596\n ],\n [\n -60.934295654296875,\n -31.421631960419596\n ],\n [\n -60.934295654296875,\n -32.11514862261243\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"44","issue":"6","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2019-01-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Szupiany, Ricardo N.","contributorId":189755,"corporation":false,"usgs":false,"family":"Szupiany","given":"Ricardo","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":757709,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lopez Weibel, Cecilia","contributorId":189756,"corporation":false,"usgs":false,"family":"Lopez Weibel","given":"Cecilia","email":"","affiliations":[],"preferred":false,"id":757710,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Guerrero, Massimo","contributorId":213431,"corporation":false,"usgs":false,"family":"Guerrero","given":"Massimo","email":"","affiliations":[{"id":38756,"text":"University of Bologna, Italy","active":true,"usgs":false}],"preferred":false,"id":757711,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Latosinski, Francisco","contributorId":213432,"corporation":false,"usgs":false,"family":"Latosinski","given":"Francisco","email":"","affiliations":[{"id":38757,"text":"Universidad Nacional del Litoral, Argentina","active":true,"usgs":false}],"preferred":false,"id":757712,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wood, Molly S. 0000-0002-5184-8306 mswood@usgs.gov","orcid":"https://orcid.org/0000-0002-5184-8306","contributorId":788,"corporation":false,"usgs":true,"family":"Wood","given":"Molly","email":"mswood@usgs.gov","middleInitial":"S.","affiliations":[{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true},{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true},{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"preferred":true,"id":757707,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Dominguez Ruben, Lucas","contributorId":213433,"corporation":false,"usgs":false,"family":"Dominguez Ruben","given":"Lucas","affiliations":[{"id":38757,"text":"Universidad Nacional del Litoral, Argentina","active":true,"usgs":false}],"preferred":false,"id":757713,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Oberg, Kevin 0000-0002-7024-3361 kaoberg@usgs.gov","orcid":"https://orcid.org/0000-0002-7024-3361","contributorId":175229,"corporation":false,"usgs":true,"family":"Oberg","given":"Kevin","email":"kaoberg@usgs.gov","affiliations":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true},{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true}],"preferred":true,"id":757708,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70202134,"text":"ofr20191011 - 2019 - Evaluation of Chinook salmon (Oncorhynchus tshawytscha) fry survival at Lookout Point Reservoir, western Oregon, 2017","interactions":[],"lastModifiedDate":"2019-02-21T16:47:19","indexId":"ofr20191011","displayToPublicDate":"2019-02-21T08:44:09","publicationYear":"2019","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":"2019-1011","displayTitle":"Evaluation of Chinook Salmon (Oncorhynchus tshawytscha) Fry Survival in Lookout Point Reservoir, Western Oregon, 2017","title":"Evaluation of Chinook salmon (Oncorhynchus tshawytscha) fry survival at Lookout Point Reservoir, western Oregon, 2017","docAbstract":"A field study was conducted to estimate survival of fry-sized juvenile Chinook salmon (Oncorhynchus tshawytscha) in Lookout Point Reservoir, western Oregon, during 2017. The field study consisted of releasing three groups of genetically marked fish in the reservoir and monthly fish sampling. Fish were released during April 18–19 (43,950 fish), May 30–June 2 (44,145 fish), and on June 28, 2017 (3,920 fish). Reservoir sampling began in May and occurred monthly through October, consisting of 5-day events where juvenile Chinook salmon were collected using various gear types (electrofishing, shoreline traps, gill nets). Data were analyzed using two models: (1) a staggered release-recovery model (SRRM), and (2) a parentage-based tagging (PBT) N-mixture model. The SRRM provided survival estimates from two periods: (1) mid-April to late May (SSRRM1), and (2) late May to late June (SSRRM2). Multiple estimates of survival were possible for each period using different combinations of recovery data from the three groups of fish that were released. Survival estimates for SSRRM1 ranged from 0.470 to 0.520. Estimates for SSRRM2 ranged from 0.968 to 0.969; cumulative survival from mid-April to late June (SSRRM2) was estimated at 0.870. We suspect that issues with the third release group led to biased survival results using the SRRM. The PBT N-mixture model provided survival estimates from six periods: (1) mid-April to mid-May (SNMIX1), (2) mid-May to mid-June (SNMIX2), (3) mid-June to mid-July (SNMIX3), (4) mid-July to mid-August (SNMIX4), (5) mid-August to mid-September (SNMIX5), and (6) mid-September to mid-October (SNMIX6). Survival estimates from the PBT N-mixture model were lowest for SNMIX1 (0.461) and increased monthly to a high of 0.970 for SNMIX6. Cumulative survival from mid-April to mid-July was 0.233 and overall survival from mid-April to mid-October was 0.188. This suggests that most mortality occurred early in the study when juvenile Chinook salmon were small. This could be because these fish were most vulnerable to predation in the reservoir at that time. We determined that mortality of juvenile Chinook salmon was high in the reservoir during this study and similar estimates of parr-to-smolt survival have been observed in other systems. Additional analyses are required, including results from the second year of study (2018), and potentially similar evaluations will need to be made at other locations to determine if reservoir mortality is a limiting survival factor for Chinook salmon in the Middle Fork Willamette River.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191011","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers and Oregon State University","usgsCitation":"Kock, T.J., Perry, R.W., Hansen, G.S., Haner, P.V., Pope, A.C., Plumb, J.M., Cogliati, K.M., and Hansen, A.C., 2019, Evaluation of Chinook salmon (Oncorhynchus tshawytscha) fry survival at Lookout Point Reservoir, western Oregon, 2017: U.S. Geological Survey Open-File Report 2019-1011, 42 p., https://doi.org/10.3133/ofr20191011.","productDescription":"vi, 42 p.","numberOfPages":"52","onlineOnly":"Y","ipdsId":"IP-102234","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":361397,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1011/coverthb.jpg"},{"id":361398,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1011/ofr20191011.pdf","text":"Report","size":"12.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019-1011"}],"country":"United States","state":"Oregon","otherGeospatial":"Lookout Point Reservoir","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.89718627929688,\n 43.91768033000405\n ],\n [\n -122.81410217285155,\n 43.98589821991874\n ],\n [\n -122.64244079589842,\n 43.929055415997134\n ],\n [\n -122.5140380859375,\n 43.82808744469062\n ],\n [\n -122.63626098632812,\n 43.77059798257491\n ],\n [\n -122.75711059570312,\n 43.854830911225235\n ],\n [\n -122.89718627929688,\n 43.91768033000405\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Western Fisheries Research Center
U.S. Geological Survey
6505 NE 65th Street
Seattle, Washington 98115-5016
The Souris River Basin is a 24,000 square-mile basin in the Provinces of Saskatchewan and Manitoba in Canada, and the State of North Dakota in the United States. Above-average snowpack during the winter of 2010–11, along with record-setting rains in May and June of 2011, led to record flooding that caused extensive damage to Minot, North Dakota, and numerous smaller communities in Saskatchewan, Manitoba, and North Dakota. As a result, the International Souris River Board created the Souris River Flood Task Force to evaluate potential reservoir operation changes and flood control measures to manage future floods and droughts. Part of this evaluation involved identifying a need for a stochastic streamflow model to estimate the likelihood of future flooding or drought.
A stochastic natural (unregulated) streamflow simulation model described in a previous report was built upon in this report to include the effects of regulation of four reservoirs (Rafferty, Alameda, and Boundary Reservoirs and Lake Darling) and their operation guidelines. First, a regulated reservoir storage/streamflow routing model was developed and calibrated from when all four reservoirs were in operation until the end of the reconstructed natural streamflow dataset provided by the U.S. Army Corps of Engineers (1992–2011). The regulated reservoir storage/streamflow routing model then was combined with the stochastic natural (unregulated) streamflow model to provide a stochastic regulated streamflow simulation model for the Souris River Basin upstream from Minot, North Dakota.
The stochastic regulated streamflow simulation model was used to estimate regulated flood frequency curves, which are useful for feasibility and design of critical structures such as levees or bridges. Three potential future climatic conditions were considered in this analysis: condition A (wet equilibrium), representing wet (similar to 1970–2017) climatic conditions; condition B (transition), representing transition from wet to dry (similar to 1912–69) climatic conditions; and condition C (dry equilibrium), representing dry climatic conditions. Comparison of the estimated flood frequency curves for regulated flow among the three climatic conditions indicated large differences in flood magnitudes for the more extreme (1-percent or less) annual exceedance probabilities. The estimated 0.2-percent annual exceedance probability flood magnitude for the Souris River upstream from Minot, N. Dak., was 29,300 cubic feet per second for condition A (wet equilibrium), compared to 14,800 cubic feet per second for condition C (dry equilibrium). For comparison, the recorded peak streamflow for 2011 for the Souris River upstream from Minot, N. Dak., was 26,900 cubic feet per second. Although it is not possible to predict how long the current (1970–2017) wet climatic conditions may persist, flood risk for at least the next 25 years, or until about 2040, may be represented best by climatic condition A.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185155","collaboration":"Prepared in cooperation with the North Dakota State Water Commission","usgsCitation":"Kolars, K.A., Vecchia, A.V., and Galloway, J.M., 2019, Stochastic model for simulating Souris River Basin regulated streamflow upstream from Minot, North Dakota: U.S. Geological Survey Scientific Investigations Report 2018–5155, 24 p., https://doi.org/10.3133/sir20185155.","productDescription":"viii, 24 p.","numberOfPages":"36","onlineOnly":"Y","ipdsId":"IP-090130","costCenters":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"links":[{"id":361373,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5155/coverthb.jpg"},{"id":361374,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5155/sir20185155.pdf","text":"Report","size":"1.75 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018–5155"}],"country":"United States","state":"North Dakota","city":"Minot","otherGeospatial":"Souris River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -104.04052734375,\n 48.99824008113872\n ],\n [\n -104.74365234375,\n 49.42884000063522\n ],\n [\n -104.7930908203125,\n 50.004208515595614\n ],\n [\n -103.480224609375,\n 50.52041218671901\n ],\n [\n -102.0245361328125,\n 50.604159488561\n ],\n [\n -101.195068359375,\n 50.25071752130677\n ],\n [\n -100.65673828125,\n 49.745781306155735\n ],\n [\n -99.60891723632812,\n 49.648069803718805\n ],\n [\n -99.18594360351562,\n 49.577773933420914\n ],\n [\n -99.2340087890625,\n 49.39131220507362\n ],\n [\n -99.76547241210936,\n 49.413653634531116\n ],\n [\n -99.4482421875,\n 48.100094697973795\n ],\n [\n -101.502685546875,\n 47.99727386804474\n ],\n [\n -103.568115234375,\n 48.52388120259336\n ],\n [\n -104.04052734375,\n 48.99824008113872\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Dakota Water Science Center
U.S. Geological Survey
821 East Interstate Avenue
Bismarck, ND 58503
The recovery of endangered Lost River suckers (Deltistes luxatus) in Upper Klamath Lake, south-central Oregon, has been impeded because juveniles are not recruiting into adult spawning populations. Adult sucker populations spawn each spring but mortality of age-0 suckers during their first summer is excessively high, and recruitment of juveniles into adult populations does not occur in most years. The last significant year class to join spawning aggregations was hatched in 1991. Capture rates for age-0 Lost River suckers decrease so substantially each summer that it is thought that mortality is nearly 100 percent within the first year of life each year. Causes of mortality are not understood but poor water quality, parasites, disease, predation, and non-native species are suspected to contribute to mortality. Upper Klamath Lake is hypereutrophic and summer water-quality conditions have large diurnal and seasonal fluctuations. Photosynthesis of Aphanizomenon flos-aquae, the most abundant cyanobacterium in Upper Klamath Lake, is responsible for large fluctuations in dissolved-oxygen (DO) concentrations and pH.
We introduced hatchery-raised, passive integrated transponder-tagged juvenile Lost River suckers into large mesocosms located at Fish Banks, Mid North, and Rattlesnake Point in Upper Klamath Lake, Oregon, to assess sucker mortality relative to water-quality conditions. We identified the date of death for each sucker by assessing movement patterns among vertically stratified antennas. We modeled daily mortality using known fate models relative to water-quality conditions measured by sondes. Histopathology was used to understand causes of eminent mortality for moribund suckers.
Fish mortality, growth, health, and movement patterns varied among locations, but it was unclear whether this variation was due to water-quality or other factors. Seasonal mortality was 58.8 percent at Fish Banks, 27.4 percent at Mid North, and 11.5 percent at Rattlesnake Point. Growth over the 109-day study period was lowest at Fish Banks (34.5 ±10.0 millimeters [mm] standard length (SL); 18.6 ±7.7 grams [g]), intermediate at Mid North (57.5 ±13.6 mm SL; 40.1 ±15.4 g), and greatest at Rattlesnake Point (78.4 ±13.0 mm SL; 72.5 ±18.7 g). Our ability to assess causes of juvenile sucker mortality in mesocosms using our modelling approach was limited by low daily mortality. Zero to 3 mortalities occurred per day, except on July 30 at Fish Banks when 7 mortalities occurred. Relative to any other measured and tested water-quality condition, mortality was more likely to occur on days with large fluctuations in oxygen percent saturation. When we assessed the fit of the most parsimonious model, performance was poor, which suggested that other factors were contributing to mortality. Our ability to assess the relationship between seasonal patterns in water quality and fish mortality were limited by the absence of substantial differences in water quality among sites, inconsistency in the depth at which measurements were collected, and no clear pattern in conditions leading up to and during mortality events. Except for DO at Rattlesnake Point and diel temperature variations at Fish Banks, seasonally summarized water-quality factors were similar among sites. The locations of water-quality monitors within the water column likely explain the differences in DO at Rattlesnake Point and temperature variation at Fish Banks. Furthermore, DO concentrations and other water-quality factors occurring during and prior to mortality events were inconsistent.
Microscopic assessments indicated severe gill hyperplasia, fusion of the secondary lamellae, and severe Ichthyobodo sp. infestations on the gills of most moribund suckers. Liver glycogen was usually depleted in suckers with severe Ichthyobodo sp. infestations. Ichthyobodo sp. infestations probably were the immediate cause of death and probably originated from the Klamath Tribes Fish Research Facility, although this parasite also is present in Upper Klamath Lake and severe water-quality conditions may have contributed to morbidity. As suckers in the mesocosms died, they were replaced with suckers from the Fish Research Facility that likely were heavily parasitized with Ichthyobodo sp. Therefore, it is possible that the gradient in mortality rate among sites was owing to site-varying differences in inadvertent increases in introduced parasite loads.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191006","collaboration":"Prepared in cooperation with the Bureau of Reclamation","usgsCitation":"Hereford, D.M., Conway, C.M., Burdick, S.M., Elliott, D.G., Perry, T.M., Dolan-Caret, A., and Harris, A.C., 2019, Assessing causes of mortality for endangered juvenile Lost River suckers (Deltistes luxatus) in mesocosms in Upper Klamath Lake, south-central Oregon, 2016: U.S. Geological Survey Open -File Report 2019-1006, 80 p., https://doi.org/10.3133/ofr20191006.","productDescription":"viii, 80 p.","numberOfPages":"92","onlineOnly":"Y","ipdsId":"IP-098400","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":361283,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1006/ofr20191006.pdf","text":"Report","size":"12.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019-1006"},{"id":361282,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1006/coverthb.jpg"}],"country":"United States","state":"Oregon","otherGeospatial":"Upper Klamath Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.10273742675781,\n 42.22750046697999\n ],\n [\n -121.79374694824219,\n 42.22750046697999\n ],\n [\n -121.79374694824219,\n 42.595554553719204\n ],\n [\n -122.10273742675781,\n 42.595554553719204\n ],\n [\n -122.10273742675781,\n 42.22750046697999\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Western Fisheries Research Center
U.S. Geological Survey
6505 NE 65th Street
Seattle, Washington 98115-5016
The morphodynamics of river-dominated deltas are largely controlled by the supply and retention of sediment within deltaic wetlands and the rate of relative sea-level rise. Yet, sediment budgets for deltas are often poorly constrained. In the Mississippi River Delta, a system rapidly losing land due to natural and anthropogenic causes, restoration efforts seek to build new land through the use of river diversions. At the Davis Pond Freshwater Diversion, a new crevasse splay has emerged since construction was completed in 2002. Here, we use beryllium-7 activity in sediment cores and USGS measurements of discharge and turbidity to calculate seasonal sediment input, deposition, and retention within the vegetated Davis Pond receiving basin. In winter/spring 2015, which included an experimental period of high discharge through the diversion, Davis Pond received 106,800 metric tons of sediment, 44% of which was retained within the basin. During this time, mean flow velocity was 0.21 m s−1 and mean turbidity was 56 formazin nephelometric units (FNU). In summer/fall 2015, the Davis Pond basin received 35,900 metric tons of sediment, 81% of which was retained. Mean flow velocity in summer/fall was 0.10 m s−1 and mean turbidity was 55 FNU. The increase in sediment retention from winter/spring 2015 to summer/fall 2015 may be due in part to the corresponding drop in water flow velocity, which allowed more sediment to settle out of suspension. Although high water discharge increases sediment input and deposition, increased turbulence associated with higher current velocity appears to increase sediment throughput and thereby decrease the sediment trapping efficiency. Sediment retention in Davis Pond is on the high end of the range seen in deltaic wetlands, perhaps due to the enclosed geometry of the receiving basin. Future diversion design and operation should target moderate water discharge and flow velocities in order to jointly maximize sediment deposition and retention and provide optimal conditions for delta growth.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.geomorph.2019.02.008","usgsCitation":"Keogh, M.E., Kolker, A.S., Snedden, G., and Renfro, A.A., 2019, Hydrodynamic controls on sediment retention in an emerging diversion-fed delta: Geomorphology, v. 332, p. 100-111, https://doi.org/10.1016/j.geomorph.2019.02.008.","productDescription":"12 p.","startPage":"100","endPage":"111","ipdsId":"IP-092068","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":467886,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.geomorph.2019.02.008","text":"Publisher Index Page"},{"id":437565,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9V7N49P","text":"USGS data release","linkHelpText":"Mineral content, bulk density, and beryllium-7 activity of wetland soils of the Davis Pond Freshwater Diversion Outfall Area, Louisiana, in 2015"},{"id":361386,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Louisiana","otherGeospatial":"Mississippi River Delta","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -90.36529541015625,\n 29.844217466091493\n ],\n [\n -90.2362060546875,\n 29.844217466091493\n ],\n [\n -90.2362060546875,\n 29.963857983730453\n ],\n [\n -90.36529541015625,\n 29.963857983730453\n ],\n [\n -90.36529541015625,\n 29.844217466091493\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"332","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Keogh, Molly E.","contributorId":213408,"corporation":false,"usgs":false,"family":"Keogh","given":"Molly","email":"","middleInitial":"E.","affiliations":[{"id":13500,"text":"Tulane University","active":true,"usgs":false}],"preferred":false,"id":757660,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kolker, Alexander S.","contributorId":213409,"corporation":false,"usgs":false,"family":"Kolker","given":"Alexander","email":"","middleInitial":"S.","affiliations":[{"id":38749,"text":"Tulane University; Louisiana Universities Marine Consortium","active":true,"usgs":false}],"preferred":false,"id":757661,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Snedden, Gregg A. 0000-0001-7821-3709","orcid":"https://orcid.org/0000-0001-7821-3709","contributorId":212275,"corporation":false,"usgs":true,"family":"Snedden","given":"Gregg","middleInitial":"A.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":757659,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Renfro, Alisha A.","contributorId":213410,"corporation":false,"usgs":false,"family":"Renfro","given":"Alisha","email":"","middleInitial":"A.","affiliations":[{"id":38750,"text":"National Wildlife Federation, Mississippi River Delta Campaign","active":true,"usgs":false}],"preferred":false,"id":757662,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70202282,"text":"70202282 - 2019 - Dynamic N-mixture models with temporal variability in detection probability","interactions":[],"lastModifiedDate":"2019-02-20T10:44:50","indexId":"70202282","displayToPublicDate":"2019-02-20T10:44:45","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1458,"text":"Ecological Modelling","active":true,"publicationSubtype":{"id":10}},"title":"Dynamic N-mixture models with temporal variability in detection probability","docAbstract":"In theory parameters of dynamic N-mixture models can be estimated with multiple years of data without the robust design under the assumption of constant detection probability. However, such an assumption can rarely be met in long-term studies, and the consequences of violating this assumption in the inferences of dynamic N-mixture models have not been assessed. In this study we used simulation studies to evaluate inferences of the original dynamic N-mixture model and two of its spatial extensions in the face of temporal variability in detection probability. We first evaluated the dynamic N-mixture models when detection probability that varied temporally was wrongly treated as a constant. We then evaluated if the robust design was necessary for dynamic N-mixture models to provide valid parameter estimates when detection probability was correctly assumed to vary temporally. Our results showed that, when detection probability that varied temporally was wrongly treated as a constant, biases were introduced in the parameter estimates of dynamic N-mixture models. When detection probability was correctly assumed to vary temporally, the models could provide valid parameter estimates with the robust design. The model could also provide valid parameter estimates when detection probability was a random effect, even without the robust design. Based on our results, we strongly recommended considering temporal variability in detection probability when using dynamic N-mixture models to analyze long-term data and adopting the robust design in long-term surveys. Our work here is not only useful for data analysis but also important for research design, and thus are relevant to a wide range of studies.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolmodel.2018.12.007","usgsCitation":"Zhao, Q., and Royle, J.A., 2019, Dynamic N-mixture models with temporal variability in detection probability: Ecological Modelling, v. 393, p. 20-24, https://doi.org/10.1016/j.ecolmodel.2018.12.007.","productDescription":"5 p.","startPage":"20","endPage":"24","ipdsId":"IP-103124","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":361376,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"393","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Zhao, Qing","contributorId":213406,"corporation":false,"usgs":false,"family":"Zhao","given":"Qing","email":"","affiliations":[{"id":34045,"text":"Department of Fish, Wildlife, and Conservation Biology, Colorado State University, Fort Collins, CO 80523","active":true,"usgs":false}],"preferred":false,"id":757623,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Royle, J. Andrew 0000-0003-3135-2167 aroyle@usgs.gov","orcid":"https://orcid.org/0000-0003-3135-2167","contributorId":139626,"corporation":false,"usgs":true,"family":"Royle","given":"J.","email":"aroyle@usgs.gov","middleInitial":"Andrew","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":757622,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ]}